From 3e9080e07d02cae3a86866b1ec1d46dc13c3943a Mon Sep 17 00:00:00 2001 From: Giuseppe Musicco Date: Sat, 30 Sep 2023 09:24:58 +0200 Subject: [PATCH] Matchday #7 --- .../1_scraping_fbref-checkpoint.ipynb | 2622 ++++---- ..._players_dataset_creation-checkpoint.ipynb | 2082 +++---- ...er_match_dataset_creation-checkpoint.ipynb | 2702 ++++----- ...ng_match_probable_players-checkpoint.ipynb | 851 +-- ...k_training_and_prediction-checkpoint.ipynb | 5288 +++++++++-------- .../7_lineup_simulation-checkpoint.ipynb | 663 +-- 1_scraping_fbref.ipynb | 2622 ++++---- 3_players_dataset_creation.ipynb | 2082 +++---- 4_player_match_dataset_creation.ipynb | 2702 ++++----- 5_scraping_match_probable_players.ipynb | 851 +-- ...ural_network_training_and_prediction.ipynb | 5288 +++++++++-------- 7_lineup_simulation.ipynb | 485 +- ...ntacalcio_Stagione_2023_24_Giornata_5.xlsx | Bin 0 -> 58748 bytes ...ntacalcio_Stagione_2023_24_Giornata_6.xlsx | Bin 0 -> 59214 bytes fbref_data/keepers_players.csv | 57 +- fbref_data/outfield_players.csv | 887 +-- fbref_data/teams.csv | 40 +- fbref_data/teams_vs.csv | 40 +- mid_outputs/database_entries.xlsx | Bin 583729 -> 932266 bytes mid_outputs/database_entries_gk.xlsx | Bin 43469 -> 64489 bytes mid_outputs/match_probable_players.xlsx | Bin 15443 -> 15295 bytes mid_outputs/players_stats.xlsx | Bin 282595 -> 296710 bytes mid_outputs/players_stats_rwk.xlsx | Bin 491720 -> 494696 bytes mid_outputs/players_votes.xlsx | Bin 55799 -> 79315 bytes mid_outputs/team_data.xlsx | Bin 34659 -> 35434 bytes outputs/pred_avg_seriea.xlsx | Bin 1430644 -> 1453936 bytes outputs/pred_matchday_7.xlsx | Bin 0 -> 740383 bytes saves/modelb.data-00000-of-00001 | Bin 34665 -> 34665 bytes saves/modelb.index | Bin 2799 -> 2799 bytes saves/modelb_gk.data-00000-of-00001 | Bin 37878 -> 37878 bytes saves/modelb_gk.index | Bin 3573 -> 3573 bytes tmp/playermatchdata.xlsx | Bin 15979 -> 16091 bytes 32 files changed, 14764 insertions(+), 14498 deletions(-) create mode 100644 fantacalcio/voti/Voti_Fantacalcio_Stagione_2023_24_Giornata_5.xlsx create mode 100644 fantacalcio/voti/Voti_Fantacalcio_Stagione_2023_24_Giornata_6.xlsx create mode 100644 outputs/pred_matchday_7.xlsx diff --git a/.ipynb_checkpoints/1_scraping_fbref-checkpoint.ipynb b/.ipynb_checkpoints/1_scraping_fbref-checkpoint.ipynb index 7b85157..fc3f97c 100644 --- a/.ipynb_checkpoints/1_scraping_fbref-checkpoint.ipynb +++ b/.ipynb_checkpoints/1_scraping_fbref-checkpoint.ipynb @@ -287,119 +287,119 @@ " it ITA\n", " DF\n", " Inter\n", - " 35-223\n", + " 35-232\n", " 1988\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", + " 3.0\n", + " 3.0\n", + " 270.0\n", " 0.0\n", " ...\n", - " 2.0\n", - " 1.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 4.0\n", " 3.0\n", + " 4.0\n", " 0.0\n", - " 100.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 15.0\n", + " 10.0\n", + " 2.0\n", + " 83.3\n", " \n", " \n", " 1\n", + " Yacine Adli\n", + " fr FRA\n", + " MF\n", + " Milan\n", + " 23-063\n", + " 2000\n", + " 1.0\n", + " 1.0\n", + " 57.0\n", + " 0.0\n", + " ...\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 5.0\n", + " 0.0\n", + " 1.0\n", + " 0.0\n", + " \n", + " \n", + " 2\n", " Michel Aebischer\n", " ch SUI\n", " MF\n", " Bologna\n", - " 26-258\n", + " 26-267\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 347.0\n", + " 6.0\n", + " 6.0\n", + " 527.0\n", " 0.0\n", " ...\n", - " 7.0\n", - " 5.0\n", + " 10.0\n", + " 6.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 23.0\n", - " 2.0\n", - " 3.0\n", + " 29.0\n", + " 4.0\n", + " 6.0\n", " 40.0\n", " \n", " \n", - " 2\n", - " Luis Alberto\n", - " es ESP\n", - " MF\n", - " Lazio\n", - " 30-358\n", - " 1992\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 2.0\n", - " ...\n", - " 3.0\n", - " 5.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 24.0\n", - " 2.0\n", - " 4.0\n", - " 33.3\n", - " \n", - " \n", " 3\n", - " Pontus Almqvist\n", - " se SWE\n", - " FW\n", - " Lecce\n", - " 24-073\n", - " 1999\n", - " 4.0\n", - " 4.0\n", - " 347.0\n", + " Jean-Daniel Akpa-Akpro\n", + " ci CIV\n", + " MF\n", + " Monza\n", + " 30-354\n", + " 1992\n", " 1.0\n", + " 0.0\n", + " 7.0\n", + " 0.0\n", " ...\n", - " 3.0\n", - " 8.0\n", - " 1.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 15.0\n", - " 0.0\n", - " 3.0\n", " 0.0\n", " \n", " \n", " 4\n", - " Lorenzo Amatucci\n", - " it ITA\n", + " Luis Alberto\n", + " es ESP\n", " MF\n", - " Fiorentina\n", - " 19-228\n", - " 2004\n", - " 1.0\n", - " 0.0\n", - " 16.0\n", - " 0.0\n", + " Lazio\n", + " 31-002\n", + " 1992\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 2.0\n", " ...\n", - " 1.0\n", + " 6.0\n", + " 8.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", + " 36.0\n", + " 3.0\n", + " 5.0\n", + " 37.5\n", " \n", " \n", " ...\n", @@ -426,60 +426,60 @@ " ...\n", " \n", " \n", - " 424\n", + " 453\n", " Joshua Zirkzee\n", " nl NED\n", " FW\n", " Bologna\n", - " 22-122\n", + " 22-131\n", " 2001\n", - " 4.0\n", - " 4.0\n", - " 356.0\n", + " 6.0\n", + " 6.0\n", + " 520.0\n", " 1.0\n", " ...\n", - " 3.0\n", + " 5.0\n", " 1.0\n", - " 1.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 11.0\n", - " 9.0\n", " 2.0\n", - " 81.8\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 15.0\n", + " 12.0\n", + " 3.0\n", + " 80.0\n", " \n", " \n", - " 425\n", + " 454\n", " Zito\n", " ao ANG\n", " FW\n", " Cagliari\n", - " 21-196\n", + " 21-205\n", " 2002\n", - " 4.0\n", - " 3.0\n", - " 297.0\n", - " 1.0\n", - " ...\n", - " 3.0\n", - " 8.0\n", - " 5.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", " 6.0\n", - " 1.0\n", " 5.0\n", - " 16.7\n", + " 477.0\n", + " 2.0\n", + " ...\n", + " 5.0\n", + " 12.0\n", + " 6.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 9.0\n", + " 2.0\n", + " 7.0\n", + " 22.2\n", " \n", " \n", - " 426\n", + " 455\n", " Nadir Zortea\n", " it ITA\n", " DF\n", " Atalanta\n", - " 24-094\n", + " 24-103\n", " 1999\n", " 3.0\n", " 0.0\n", @@ -498,16 +498,16 @@ " 0.0\n", " \n", " \n", - " 427\n", + " 456\n", " Milan Đurić\n", " ba BIH\n", " FW,MF\n", " Hellas Verona\n", - " 33-122\n", + " 33-131\n", " 1990\n", - " 4.0\n", + " 5.0\n", " 1.0\n", - " 152.0\n", + " 154.0\n", " 0.0\n", " ...\n", " 7.0\n", @@ -517,21 +517,21 @@ " 0.0\n", " 0.0\n", " 4.0\n", - " 21.0\n", - " 14.0\n", - " 60.0\n", + " 23.0\n", + " 15.0\n", + " 60.5\n", " \n", " \n", - " 428\n", + " 457\n", " Mateusz Łęgowski\n", " pl POL\n", " MF\n", " Salernitana\n", - " 20-235\n", + " 20-244\n", " 2003\n", - " 4.0\n", + " 5.0\n", " 2.0\n", - " 161.0\n", + " 167.0\n", " 0.0\n", " ...\n", " 3.0\n", @@ -540,70 +540,70 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 14.0\n", + " 16.0\n", " 4.0\n", " 5.0\n", " 44.4\n", " \n", " \n", "\n", - "

429 rows × 115 columns

\n", + "

458 rows × 115 columns

\n", "" ], "text/plain": [ - " player nationality position team age birth_year \\\n", - "0 Francesco Acerbi it ITA DF Inter 35-223 1988 \n", - "1 Michel Aebischer ch SUI MF Bologna 26-258 1997 \n", - "2 Luis Alberto es ESP MF Lazio 30-358 1992 \n", - "3 Pontus Almqvist se SWE FW Lecce 24-073 1999 \n", - "4 Lorenzo Amatucci it ITA MF Fiorentina 19-228 2004 \n", - ".. ... ... ... ... ... ... \n", - "424 Joshua Zirkzee nl NED FW Bologna 22-122 2001 \n", - "425 Zito ao ANG FW Cagliari 21-196 2002 \n", - "426 Nadir Zortea it ITA DF Atalanta 24-094 1999 \n", - "427 Milan Đurić ba BIH FW,MF Hellas Verona 33-122 1990 \n", - "428 Mateusz Łęgowski pl POL MF Salernitana 20-235 2003 \n", + " player nationality position team age \\\n", + "0 Francesco Acerbi it ITA DF Inter 35-232 \n", + "1 Yacine Adli fr FRA MF Milan 23-063 \n", + "2 Michel Aebischer ch SUI MF Bologna 26-267 \n", + "3 Jean-Daniel Akpa-Akpro ci CIV MF Monza 30-354 \n", + "4 Luis Alberto es ESP MF Lazio 31-002 \n", + ".. ... ... ... ... ... \n", + "453 Joshua Zirkzee nl NED FW Bologna 22-131 \n", + "454 Zito ao ANG FW Cagliari 21-205 \n", + "455 Nadir Zortea it ITA DF Atalanta 24-103 \n", + "456 Milan Đurić ba BIH FW,MF Hellas Verona 33-131 \n", + "457 Mateusz Łęgowski pl POL MF Salernitana 20-244 \n", "\n", - " games games_starts minutes goals ... fouls fouled offsides \\\n", - "0 1.0 1.0 90.0 0.0 ... 2.0 1.0 0.0 \n", - "1 4.0 4.0 347.0 0.0 ... 7.0 5.0 0.0 \n", - "2 4.0 4.0 360.0 2.0 ... 3.0 5.0 0.0 \n", - "3 4.0 4.0 347.0 1.0 ... 3.0 8.0 1.0 \n", - "4 1.0 0.0 16.0 0.0 ... 1.0 0.0 0.0 \n", - ".. ... ... ... ... ... ... ... ... \n", - "424 4.0 4.0 356.0 1.0 ... 3.0 1.0 1.0 \n", - "425 4.0 3.0 297.0 1.0 ... 3.0 8.0 5.0 \n", - "426 3.0 0.0 96.0 1.0 ... 3.0 0.0 0.0 \n", - "427 4.0 1.0 152.0 0.0 ... 7.0 1.0 2.0 \n", - "428 4.0 2.0 161.0 0.0 ... 3.0 3.0 0.0 \n", + " birth_year games games_starts minutes goals ... fouls fouled \\\n", + "0 1988 3.0 3.0 270.0 0.0 ... 3.0 4.0 \n", + "1 2000 1.0 1.0 57.0 0.0 ... 0.0 0.0 \n", + "2 1997 6.0 6.0 527.0 0.0 ... 10.0 6.0 \n", + "3 1992 1.0 0.0 7.0 0.0 ... 0.0 0.0 \n", + "4 1992 6.0 6.0 540.0 2.0 ... 6.0 8.0 \n", + ".. ... ... ... ... ... ... ... ... \n", + "453 2001 6.0 6.0 520.0 1.0 ... 5.0 1.0 \n", + "454 2002 6.0 5.0 477.0 2.0 ... 5.0 12.0 \n", + "455 1999 3.0 0.0 96.0 1.0 ... 3.0 0.0 \n", + "456 1990 5.0 1.0 154.0 0.0 ... 7.0 1.0 \n", + "457 2003 5.0 2.0 167.0 0.0 ... 3.0 3.0 \n", "\n", - " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 4.0 3.0 \n", - "1 0.0 0.0 0.0 23.0 2.0 \n", - "2 0.0 0.0 0.0 24.0 2.0 \n", - "3 1.0 0.0 0.0 15.0 0.0 \n", - "4 0.0 0.0 0.0 1.0 0.0 \n", - ".. ... ... ... ... ... \n", - "424 0.0 0.0 0.0 11.0 9.0 \n", - "425 0.0 0.0 0.0 6.0 1.0 \n", - "426 0.0 0.0 0.0 4.0 0.0 \n", - "427 0.0 0.0 0.0 4.0 21.0 \n", - "428 0.0 0.0 0.0 14.0 4.0 \n", + " offsides pens_won pens_conceded own_goals ball_recoveries \\\n", + "0 0.0 0.0 0.0 0.0 15.0 \n", + "1 0.0 0.0 0.0 0.0 5.0 \n", + "2 0.0 0.0 0.0 0.0 29.0 \n", + "3 0.0 0.0 0.0 0.0 1.0 \n", + "4 0.0 0.0 0.0 0.0 36.0 \n", + ".. ... ... ... ... ... \n", + "453 2.0 0.0 0.0 0.0 15.0 \n", + "454 6.0 0.0 0.0 0.0 9.0 \n", + "455 0.0 0.0 0.0 0.0 4.0 \n", + "456 2.0 0.0 0.0 0.0 4.0 \n", + "457 0.0 0.0 0.0 0.0 16.0 \n", "\n", - " aerials_lost aerials_won_pct \n", - "0 0.0 100.0 \n", - "1 3.0 40.0 \n", - "2 4.0 33.3 \n", - "3 3.0 0.0 \n", - "4 1.0 0.0 \n", - ".. ... ... \n", - "424 2.0 81.8 \n", - "425 5.0 16.7 \n", - "426 1.0 0.0 \n", - "427 14.0 60.0 \n", - "428 5.0 44.4 \n", + " aerials_won aerials_lost aerials_won_pct \n", + "0 10.0 2.0 83.3 \n", + "1 0.0 1.0 0.0 \n", + "2 4.0 6.0 40.0 \n", + "3 0.0 0.0 0.0 \n", + "4 3.0 5.0 37.5 \n", + ".. ... ... ... \n", + "453 12.0 3.0 80.0 \n", + "454 2.0 7.0 22.2 \n", + "455 0.0 1.0 0.0 \n", + "456 23.0 15.0 60.5 \n", + "457 4.0 5.0 44.4 \n", "\n", - "[429 rows x 115 columns]" + "[458 rows x 115 columns]" ] }, "execution_count": 3, @@ -676,23 +676,23 @@ " al ALB\n", " GK\n", " Empoli\n", - " 34-195\n", + " 34-204\n", " 1989\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 9.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 10.0\n", " ...\n", - " 27.5\n", - " 9.0\n", - " 22.2\n", - " 27.0\n", - " 23.0\n", - " 1.0\n", - " 4.3\n", + " 32.1\n", + " 24.0\n", + " 58.3\n", + " 44.0\n", + " 50.0\n", " 2.0\n", - " 1.00\n", - " 15.7\n", + " 4.0\n", + " 3.0\n", + " 0.75\n", + " 12.7\n", " \n", " \n", " 1\n", @@ -700,7 +700,7 @@ " it ITA\n", " GK\n", " Empoli\n", - " 22-027\n", + " 22-036\n", " 2001\n", " 1.0\n", " 1.0\n", @@ -724,23 +724,23 @@ " it ITA\n", " GK\n", " Atalanta\n", - " 23-082\n", + " 23-091\n", " 2000\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", " 3.0\n", " ...\n", - " 36.8\n", - " 6.0\n", - " 83.3\n", - " 69.2\n", - " 13.0\n", - " 1.0\n", - " 7.7\n", + " 38.2\n", + " 15.0\n", + " 80.0\n", + " 60.7\n", + " 30.0\n", + " 3.0\n", + " 10.0\n", " 0.0\n", " 0.00\n", - " 14.5\n", + " 11.2\n", " \n", " \n", " 3\n", @@ -748,7 +748,7 @@ " it ITA\n", " GK\n", " Frosinone\n", - " 24-260\n", + " 24-269\n", " 1999\n", " 1.0\n", " 1.0\n", @@ -772,7 +772,7 @@ " dk DEN\n", " GK\n", " Fiorentina\n", - " 24-183\n", + " 24-192\n", " 1999\n", " 2.0\n", " 2.0\n", @@ -796,23 +796,23 @@ " it ITA\n", " GK\n", " Sassuolo\n", - " 36-237\n", + " 36-246\n", " 1987\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", - " 5.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 6.0\n", " ...\n", - " 37.1\n", - " 34.0\n", - " 26.5\n", - " 28.1\n", - " 46.0\n", - " 2.0\n", - " 4.3\n", + " 39.4\n", + " 42.0\n", + " 26.2\n", + " 28.3\n", + " 73.0\n", + " 4.0\n", + " 5.5\n", " 3.0\n", - " 1.00\n", - " 14.5\n", + " 0.75\n", + " 13.1\n", " \n", " \n", " 6\n", @@ -820,22 +820,22 @@ " it ITA\n", " GK\n", " Sassuolo\n", - " 29-085\n", + " 29-094\n", " 1994\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", - " 4.0\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", + " 6.0\n", " ...\n", - " 37.1\n", - " 9.0\n", - " 33.3\n", - " 34.6\n", - " 9.0\n", + " 41.2\n", + " 19.0\n", + " 26.3\n", + " 29.4\n", + " 26.0\n", " 0.0\n", " 0.0\n", " 7.0\n", - " 7.00\n", + " 3.50\n", " 28.9\n", " \n", " \n", @@ -844,23 +844,23 @@ " it ITA\n", " GK\n", " Monza\n", - " 26-056\n", + " 26-065\n", " 1997\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", " 5.0\n", + " 5.0\n", + " 450.0\n", + " 6.0\n", " ...\n", - " 28.7\n", - " 22.0\n", - " 40.9\n", - " 40.3\n", - " 45.0\n", + " 30.4\n", + " 34.0\n", + " 52.9\n", + " 47.5\n", + " 73.0\n", " 2.0\n", - " 4.4\n", + " 2.7\n", " 2.0\n", - " 0.67\n", - " 11.7\n", + " 0.40\n", + " 10.5\n", " \n", " \n", " 8\n", @@ -868,23 +868,23 @@ " it ITA\n", " GK\n", " Lecce\n", - " 28-162\n", + " 28-171\n", " 1995\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 5.0\n", " ...\n", - " 31.0\n", - " 42.0\n", - " 52.4\n", - " 38.7\n", - " 54.0\n", - " 2.0\n", - " 3.7\n", - " 2.0\n", + " 30.9\n", + " 55.0\n", + " 47.3\n", + " 36.3\n", + " 80.0\n", + " 3.0\n", + " 3.8\n", + " 3.0\n", " 0.50\n", - " 10.3\n", + " 9.6\n", " \n", " \n", " 9\n", @@ -892,7 +892,7 @@ " fr FRA\n", " GK\n", " Milan\n", - " 28-080\n", + " 28-089\n", " 1995\n", " 4.0\n", " 4.0\n", @@ -916,23 +916,23 @@ " es ESP\n", " GK\n", " Genoa\n", - " 25-117\n", + " 25-126\n", " 1998\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 7.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 9.0\n", " ...\n", - " 39.7\n", - " 22.0\n", - " 95.5\n", - " 62.5\n", - " 75.0\n", - " 8.0\n", - " 10.7\n", + " 39.1\n", + " 37.0\n", + " 94.6\n", + " 62.1\n", + " 113.0\n", + " 12.0\n", + " 10.6\n", " 2.0\n", - " 0.50\n", - " 9.3\n", + " 0.33\n", + " 8.5\n", " \n", " \n", " 11\n", @@ -940,23 +940,23 @@ " it ITA\n", " GK\n", " Napoli\n", - " 26-183\n", + " 26-192\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 5.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 6.0\n", " ...\n", - " 24.7\n", - " 11.0\n", + " 24.1\n", + " 21.0\n", " 0.0\n", - " 20.4\n", - " 27.0\n", + " 20.5\n", + " 53.0\n", " 1.0\n", - " 3.7\n", - " 7.0\n", - " 1.75\n", - " 18.2\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", " \n", " \n", " 12\n", @@ -964,23 +964,23 @@ " rs SRB\n", " GK\n", " Torino\n", - " 26-213\n", + " 26-222\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 7.0\n", " ...\n", - " 38.1\n", - " 36.0\n", - " 75.0\n", - " 61.3\n", - " 33.0\n", - " 3.0\n", - " 9.1\n", - " 5.0\n", - " 1.25\n", - " 15.8\n", + " 35.6\n", + " 50.0\n", + " 80.0\n", + " 62.9\n", + " 47.0\n", + " 4.0\n", + " 8.5\n", + " 9.0\n", + " 1.50\n", + " 17.5\n", " \n", " \n", " 13\n", @@ -988,23 +988,23 @@ " it ITA\n", " GK\n", " Hellas Verona\n", - " 27-213\n", + " 27-222\n", " 1996\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 6.0\n", " ...\n", - " 42.9\n", - " 35.0\n", - " 88.6\n", - " 62.7\n", - " 54.0\n", + " 45.2\n", + " 50.0\n", + " 84.0\n", + " 61.5\n", + " 72.0\n", " 1.0\n", - " 1.9\n", - " 8.0\n", + " 1.4\n", + " 12.0\n", " 2.00\n", - " 19.4\n", + " 20.0\n", " \n", " \n", " 14\n", @@ -1012,23 +1012,23 @@ " ar ARG\n", " GK\n", " Atalanta\n", - " 29-138\n", + " 29-147\n", " 1994\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", " 2.0\n", " ...\n", - " 29.3\n", - " 18.0\n", - " 55.6\n", - " 46.1\n", + " 29.0\n", " 28.0\n", - " 2.0\n", - " 7.1\n", - " 8.0\n", - " 2.67\n", - " 22.0\n", + " 64.3\n", + " 48.9\n", + " 43.0\n", + " 4.0\n", + " 9.3\n", + " 12.0\n", + " 3.00\n", + " 19.9\n", " \n", " \n", " 15\n", @@ -1036,23 +1036,23 @@ " mx MEX\n", " GK\n", " Salernitana\n", - " 38-070\n", + " 38-079\n", " 1985\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 8.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 10.0\n", " ...\n", - " 35.9\n", - " 35.0\n", - " 54.3\n", - " 43.6\n", - " 63.0\n", + " 35.6\n", + " 47.0\n", + " 46.8\n", + " 39.9\n", + " 88.0\n", " 4.0\n", - " 6.3\n", - " 1.0\n", - " 0.25\n", - " 7.8\n", + " 4.5\n", + " 3.0\n", + " 0.50\n", + " 13.5\n", " \n", " \n", " 16\n", @@ -1060,23 +1060,23 @@ " pt POR\n", " GK\n", " Roma\n", - " 35-218\n", + " 35-227\n", " 1988\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", " 6.0\n", + " 6.0\n", + " 540.0\n", + " 11.0\n", " ...\n", - " 29.3\n", - " 17.0\n", - " 11.8\n", - " 22.1\n", - " 34.0\n", - " 2.0\n", - " 5.9\n", + " 27.5\n", + " 31.0\n", + " 19.4\n", + " 24.2\n", + " 62.0\n", " 2.0\n", + " 3.2\n", + " 3.0\n", " 0.50\n", - " 12.2\n", + " 13.7\n", " \n", " \n", " 17\n", @@ -1084,7 +1084,7 @@ " it ITA\n", " GK\n", " Juventus\n", - " 30-315\n", + " 30-324\n", " 1992\n", " 2.0\n", " 2.0\n", @@ -1108,7 +1108,7 @@ " it ITA\n", " GK\n", " Empoli\n", - " 26-031\n", + " 26-040\n", " 1997\n", " 1.0\n", " 1.0\n", @@ -1132,23 +1132,23 @@ " it ITA\n", " GK\n", " Lazio\n", - " 29-188\n", + " 29-197\n", " 1994\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 7.0\n", - " ...\n", - " 26.4\n", - " 15.0\n", - " 20.0\n", - " 27.9\n", - " 48.0\n", - " 2.0\n", - " 4.2\n", " 6.0\n", - " 1.50\n", - " 15.7\n", + " 6.0\n", + " 540.0\n", + " 8.0\n", + " ...\n", + " 28.8\n", + " 29.0\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", " \n", " \n", " 20\n", @@ -1156,23 +1156,23 @@ " rs SRB\n", " GK\n", " Cagliari\n", - " 27-118\n", + " 27-127\n", " 1996\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 9.0\n", " ...\n", - " 37.8\n", - " 40.0\n", - " 65.0\n", - " 50.0\n", - " 62.0\n", + " 38.5\n", + " 57.0\n", + " 54.4\n", + " 45.1\n", + " 87.0\n", + " 5.0\n", + " 5.7\n", " 4.0\n", - " 6.5\n", - " 3.0\n", - " 0.75\n", - " 12.5\n", + " 0.67\n", + " 11.9\n", " \n", " \n", " 21\n", @@ -1180,23 +1180,23 @@ " it ITA\n", " GK\n", " Udinese\n", - " 32-203\n", + " 32-212\n", " 1991\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 10.0\n", " ...\n", - " 29.7\n", - " 32.0\n", - " 31.3\n", - " 35.4\n", - " 49.0\n", - " 0.0\n", - " 0.0\n", + " 30.2\n", + " 45.0\n", + " 26.7\n", + " 32.8\n", + " 69.0\n", + " 1.0\n", + " 1.4\n", " 3.0\n", - " 0.75\n", - " 14.0\n", + " 0.50\n", + " 13.6\n", " \n", " \n", " 22\n", @@ -1204,23 +1204,23 @@ " pl POL\n", " GK\n", " Bologna\n", - " 32-139\n", + " 32-148\n", " 1991\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", " 4.0\n", " ...\n", - " 32.1\n", - " 22.0\n", - " 31.8\n", - " 34.2\n", - " 57.0\n", + " 31.1\n", + " 34.0\n", + " 29.4\n", + " 33.6\n", + " 89.0\n", + " 3.0\n", + " 3.4\n", " 2.0\n", - " 3.5\n", - " 2.0\n", - " 0.50\n", - " 11.5\n", + " 0.33\n", + " 10.3\n", " \n", " \n", " 23\n", @@ -1228,23 +1228,23 @@ " ch SUI\n", " GK\n", " Inter\n", - " 34-278\n", + " 34-287\n", " 1988\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 1.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 3.0\n", " ...\n", - " 30.8\n", - " 29.0\n", - " 20.7\n", - " 28.3\n", - " 41.0\n", + " 29.7\n", + " 39.0\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", " 2.0\n", - " 4.9\n", - " 0.0\n", - " 0.00\n", - " 6.5\n", + " 0.33\n", + " 9.6\n", " \n", " \n", " 24\n", @@ -1252,7 +1252,7 @@ " it ITA\n", " GK\n", " Monza\n", - " 21-171\n", + " 21-180\n", " 2002\n", " 1.0\n", " 1.0\n", @@ -1272,263 +1272,293 @@ " \n", " \n", " 25\n", + " Marco Sportiello\n", + " it ITA\n", + " GK\n", + " Milan\n", + " 31-143\n", + " 1992\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", + " 1.0\n", + " ...\n", + " 28.0\n", + " 2.0\n", + " 0.0\n", + " 28.5\n", + " 28.0\n", + " 2.0\n", + " 7.1\n", + " 2.0\n", + " 1.00\n", + " 13.2\n", + " \n", + " \n", + " 26\n", " Wojciech Szczęsny\n", " pl POL\n", " GK\n", " Juventus\n", - " 33-156\n", + " 33-165\n", " 1990\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 1.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 5.0\n", " ...\n", - " 33.1\n", - " 6.0\n", - " 66.7\n", - " 52.0\n", - " 33.0\n", + " 33.2\n", + " 16.0\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", " 1.0\n", - " 3.0\n", - " 0.0\n", - " 0.00\n", - " 9.6\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", " \n", " \n", - " 26\n", + " 27\n", " Pietro Terracciano\n", " it ITA\n", " GK\n", " Fiorentina\n", - " 33-197\n", + " 33-206\n", " 1990\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 3.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 4.0\n", " ...\n", - " 33.1\n", - " 9.0\n", - " 11.1\n", - " 25.0\n", - " 16.0\n", + " 34.7\n", + " 22.0\n", + " 45.5\n", + " 38.3\n", + " 44.0\n", + " 3.0\n", + " 6.8\n", " 1.0\n", - " 6.3\n", - " 1.0\n", - " 0.50\n", - " 13.7\n", + " 0.25\n", + " 10.2\n", " \n", " \n", - " 27\n", + " 28\n", " Stefano Turati\n", " it ITA\n", " GK\n", " Frosinone\n", - " 22-016\n", + " 22-025\n", " 2001\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", " 5.0\n", + " 5.0\n", + " 450.0\n", + " 7.0\n", " ...\n", - " 26.0\n", - " 13.0\n", - " 53.8\n", - " 41.7\n", - " 33.0\n", + " 26.9\n", + " 16.0\n", + " 56.3\n", + " 43.5\n", + " 67.0\n", " 2.0\n", - " 6.1\n", " 3.0\n", - " 1.00\n", - " 16.3\n", + " 3.0\n", + " 0.60\n", + " 13.4\n", " \n", " \n", "\n", - "

28 rows × 47 columns

\n", + "

29 rows × 47 columns

\n", "" ], "text/plain": [ " player nationality position team age \\\n", - "0 Etrit Berisha al ALB GK Empoli 34-195 \n", - "1 Elia Caprile it ITA GK Empoli 22-027 \n", - "2 Marco Carnesecchi it ITA GK Atalanta 23-082 \n", - "3 Michele Cerofolini it ITA GK Frosinone 24-260 \n", - "4 Oliver Christensen dk DEN GK Fiorentina 24-183 \n", - "5 Andrea Consigli it ITA GK Sassuolo 36-237 \n", - "6 Alessio Cragno it ITA GK Sassuolo 29-085 \n", - "7 Michele Di Gregorio it ITA GK Monza 26-056 \n", - "8 Wladimiro Falcone it ITA GK Lecce 28-162 \n", - "9 Mike Maignan fr FRA GK Milan 28-080 \n", - "10 Josep Martinez es ESP GK Genoa 25-117 \n", - "11 Alex Meret it ITA GK Napoli 26-183 \n", - "12 Vanja Milinković-Savić rs SRB GK Torino 26-213 \n", - "13 Lorenzo Montipò it ITA GK Hellas Verona 27-213 \n", - "14 Juan Musso ar ARG GK Atalanta 29-138 \n", - "15 Guillermo Ochoa mx MEX GK Salernitana 38-070 \n", - "16 Rui Patrício pt POR GK Roma 35-218 \n", - "17 Mattia Perin it ITA GK Juventus 30-315 \n", - "18 Samuele Perisan it ITA GK Empoli 26-031 \n", - "19 Ivan Provedel it ITA GK Lazio 29-188 \n", - "20 Boris Radunović rs SRB GK Cagliari 27-118 \n", - "21 Marco Silvestri it ITA GK Udinese 32-203 \n", - "22 Łukasz Skorupski pl POL GK Bologna 32-139 \n", - "23 Yann Sommer ch SUI GK Inter 34-278 \n", - "24 Alessandro Sorrentino it ITA GK Monza 21-171 \n", - "25 Wojciech Szczęsny pl POL GK Juventus 33-156 \n", - "26 Pietro Terracciano it ITA GK Fiorentina 33-197 \n", - "27 Stefano Turati it ITA GK Frosinone 22-016 \n", + "0 Etrit Berisha al ALB GK Empoli 34-204 \n", + "1 Elia Caprile it ITA GK Empoli 22-036 \n", + "2 Marco Carnesecchi it ITA GK Atalanta 23-091 \n", + "3 Michele Cerofolini it ITA GK Frosinone 24-269 \n", + "4 Oliver Christensen dk DEN GK Fiorentina 24-192 \n", + "5 Andrea Consigli it ITA GK Sassuolo 36-246 \n", + "6 Alessio Cragno it ITA GK Sassuolo 29-094 \n", + "7 Michele Di Gregorio it ITA GK Monza 26-065 \n", + "8 Wladimiro Falcone it ITA GK Lecce 28-171 \n", + "9 Mike Maignan fr FRA GK Milan 28-089 \n", + "10 Josep Martinez es ESP GK Genoa 25-126 \n", + "11 Alex Meret it ITA GK Napoli 26-192 \n", + "12 Vanja Milinković-Savić rs SRB GK Torino 26-222 \n", + "13 Lorenzo Montipò it ITA GK Hellas Verona 27-222 \n", + "14 Juan Musso ar ARG GK Atalanta 29-147 \n", + "15 Guillermo Ochoa mx MEX GK Salernitana 38-079 \n", + "16 Rui Patrício pt POR GK Roma 35-227 \n", + "17 Mattia Perin it ITA GK Juventus 30-324 \n", + "18 Samuele Perisan it ITA GK Empoli 26-040 \n", + "19 Ivan Provedel it ITA GK Lazio 29-197 \n", + "20 Boris Radunović rs SRB GK Cagliari 27-127 \n", + "21 Marco Silvestri it ITA GK Udinese 32-212 \n", + "22 Łukasz Skorupski pl POL GK Bologna 32-148 \n", + "23 Yann Sommer ch SUI GK Inter 34-287 \n", + "24 Alessandro Sorrentino it ITA GK Monza 21-180 \n", + "25 Marco Sportiello it ITA GK Milan 31-143 \n", + "26 Wojciech Szczęsny pl POL GK Juventus 33-165 \n", + "27 Pietro Terracciano it ITA GK Fiorentina 33-206 \n", + "28 Stefano Turati it ITA GK Frosinone 22-025 \n", "\n", " birth_year gk_games gk_games_starts gk_minutes gk_goals_against ... \\\n", - "0 1989 2.0 2.0 180.0 9.0 ... \n", + "0 1989 4.0 4.0 360.0 10.0 ... \n", "1 2001 1.0 1.0 90.0 1.0 ... \n", - "2 2000 1.0 1.0 90.0 3.0 ... \n", + "2 2000 2.0 2.0 180.0 3.0 ... \n", "3 1999 1.0 1.0 90.0 1.0 ... \n", "4 1999 2.0 2.0 180.0 6.0 ... \n", - "5 1987 3.0 3.0 270.0 5.0 ... \n", - "6 1994 1.0 1.0 90.0 4.0 ... \n", - "7 1997 3.0 3.0 270.0 5.0 ... \n", - "8 1995 4.0 4.0 360.0 4.0 ... \n", + "5 1987 4.0 4.0 360.0 6.0 ... \n", + "6 1994 2.0 2.0 180.0 6.0 ... \n", + "7 1997 5.0 5.0 450.0 6.0 ... \n", + "8 1995 6.0 6.0 540.0 5.0 ... \n", "9 1995 4.0 4.0 360.0 7.0 ... \n", - "10 1998 4.0 4.0 360.0 7.0 ... \n", - "11 1997 4.0 4.0 360.0 5.0 ... \n", - "12 1997 4.0 4.0 360.0 4.0 ... \n", - "13 1996 4.0 4.0 360.0 4.0 ... \n", - "14 1994 3.0 3.0 270.0 2.0 ... \n", - "15 1985 4.0 4.0 360.0 8.0 ... \n", - "16 1988 4.0 4.0 360.0 6.0 ... \n", + "10 1998 6.0 6.0 540.0 9.0 ... \n", + "11 1997 6.0 6.0 540.0 6.0 ... \n", + "12 1997 6.0 6.0 540.0 7.0 ... \n", + "13 1996 6.0 6.0 540.0 6.0 ... \n", + "14 1994 4.0 4.0 360.0 2.0 ... \n", + "15 1985 6.0 6.0 540.0 10.0 ... \n", + "16 1988 6.0 6.0 540.0 11.0 ... \n", "17 1992 2.0 2.0 180.0 1.0 ... \n", "18 1997 1.0 1.0 90.0 2.0 ... \n", - "19 1994 4.0 4.0 360.0 7.0 ... \n", - "20 1996 4.0 4.0 360.0 4.0 ... \n", - "21 1991 4.0 4.0 360.0 4.0 ... \n", - "22 1991 4.0 4.0 360.0 4.0 ... \n", - "23 1988 4.0 4.0 360.0 1.0 ... \n", + "19 1994 6.0 6.0 540.0 8.0 ... \n", + "20 1996 6.0 6.0 540.0 9.0 ... \n", + "21 1991 6.0 6.0 540.0 10.0 ... \n", + "22 1991 6.0 6.0 540.0 4.0 ... \n", + "23 1988 6.0 6.0 540.0 3.0 ... \n", "24 2002 1.0 1.0 90.0 1.0 ... \n", - "25 1990 2.0 2.0 180.0 1.0 ... \n", - "26 1990 2.0 2.0 180.0 3.0 ... \n", - "27 2001 3.0 3.0 270.0 5.0 ... \n", + "25 1992 2.0 2.0 180.0 1.0 ... \n", + "26 1990 4.0 4.0 360.0 5.0 ... \n", + "27 1990 4.0 4.0 360.0 4.0 ... \n", + "28 2001 5.0 5.0 450.0 7.0 ... \n", "\n", " gk_passes_length_avg gk_goal_kicks gk_pct_goal_kicks_launched \\\n", - "0 27.5 9.0 22.2 \n", + "0 32.1 24.0 58.3 \n", "1 42.6 4.0 50.0 \n", - "2 36.8 6.0 83.3 \n", + "2 38.2 15.0 80.0 \n", "3 38.3 5.0 60.0 \n", "4 33.2 8.0 62.5 \n", - "5 37.1 34.0 26.5 \n", - "6 37.1 9.0 33.3 \n", - "7 28.7 22.0 40.9 \n", - "8 31.0 42.0 52.4 \n", + "5 39.4 42.0 26.2 \n", + "6 41.2 19.0 26.3 \n", + "7 30.4 34.0 52.9 \n", + "8 30.9 55.0 47.3 \n", "9 29.2 23.0 60.9 \n", - "10 39.7 22.0 95.5 \n", - "11 24.7 11.0 0.0 \n", - "12 38.1 36.0 75.0 \n", - "13 42.9 35.0 88.6 \n", - "14 29.3 18.0 55.6 \n", - "15 35.9 35.0 54.3 \n", - "16 29.3 17.0 11.8 \n", + "10 39.1 37.0 94.6 \n", + "11 24.1 21.0 0.0 \n", + "12 35.6 50.0 80.0 \n", + "13 45.2 50.0 84.0 \n", + "14 29.0 28.0 64.3 \n", + "15 35.6 47.0 46.8 \n", + "16 27.5 31.0 19.4 \n", "17 29.1 11.0 9.1 \n", "18 26.3 12.0 16.7 \n", - "19 26.4 15.0 20.0 \n", - "20 37.8 40.0 65.0 \n", - "21 29.7 32.0 31.3 \n", - "22 32.1 22.0 31.8 \n", - "23 30.8 29.0 20.7 \n", + "19 28.8 29.0 27.6 \n", + "20 38.5 57.0 54.4 \n", + "21 30.2 45.0 26.7 \n", + "22 31.1 34.0 29.4 \n", + "23 29.7 39.0 20.5 \n", "24 21.0 2.0 0.0 \n", - "25 33.1 6.0 66.7 \n", - "26 33.1 9.0 11.1 \n", - "27 26.0 13.0 53.8 \n", + "25 28.0 2.0 0.0 \n", + "26 33.2 16.0 50.0 \n", + "27 34.7 22.0 45.5 \n", + "28 26.9 16.0 56.3 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 27.0 23.0 1.0 \n", + "0 44.0 50.0 2.0 \n", "1 50.3 10.0 2.0 \n", - "2 69.2 13.0 1.0 \n", + "2 60.7 30.0 3.0 \n", "3 45.8 18.0 0.0 \n", "4 49.4 15.0 0.0 \n", - "5 28.1 46.0 2.0 \n", - "6 34.6 9.0 0.0 \n", - "7 40.3 45.0 2.0 \n", - "8 38.7 54.0 2.0 \n", + "5 28.3 73.0 4.0 \n", + "6 29.4 26.0 0.0 \n", + "7 47.5 73.0 2.0 \n", + "8 36.3 80.0 3.0 \n", "9 47.0 52.0 12.0 \n", - "10 62.5 75.0 8.0 \n", - "11 20.4 27.0 1.0 \n", - "12 61.3 33.0 3.0 \n", - "13 62.7 54.0 1.0 \n", - "14 46.1 28.0 2.0 \n", - "15 43.6 63.0 4.0 \n", - "16 22.1 34.0 2.0 \n", + "10 62.1 113.0 12.0 \n", + "11 20.5 53.0 1.0 \n", + "12 62.9 47.0 4.0 \n", + "13 61.5 72.0 1.0 \n", + "14 48.9 43.0 4.0 \n", + "15 39.9 88.0 4.0 \n", + "16 24.2 62.0 2.0 \n", "17 18.9 26.0 2.0 \n", "18 29.6 18.0 0.0 \n", - "19 27.9 48.0 2.0 \n", - "20 50.0 62.0 4.0 \n", - "21 35.4 49.0 0.0 \n", - "22 34.2 57.0 2.0 \n", - "23 28.3 41.0 2.0 \n", + "19 32.3 63.0 3.0 \n", + "20 45.1 87.0 5.0 \n", + "21 32.8 69.0 1.0 \n", + "22 33.6 89.0 3.0 \n", + "23 27.3 59.0 5.0 \n", "24 23.0 8.0 1.0 \n", - "25 52.0 33.0 1.0 \n", - "26 25.0 16.0 1.0 \n", - "27 41.7 33.0 2.0 \n", + "25 28.5 28.0 2.0 \n", + "26 45.8 59.0 1.0 \n", + "27 38.3 44.0 3.0 \n", + "28 43.5 67.0 2.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.3 2.0 \n", + "0 4.0 3.0 \n", "1 20.0 2.0 \n", - "2 7.7 0.0 \n", + "2 10.0 0.0 \n", "3 0.0 0.0 \n", "4 0.0 3.0 \n", - "5 4.3 3.0 \n", + "5 5.5 3.0 \n", "6 0.0 7.0 \n", - "7 4.4 2.0 \n", - "8 3.7 2.0 \n", + "7 2.7 2.0 \n", + "8 3.8 3.0 \n", "9 23.1 3.0 \n", - "10 10.7 2.0 \n", - "11 3.7 7.0 \n", - "12 9.1 5.0 \n", - "13 1.9 8.0 \n", - "14 7.1 8.0 \n", - "15 6.3 1.0 \n", - "16 5.9 2.0 \n", + "10 10.6 2.0 \n", + "11 1.9 8.0 \n", + "12 8.5 9.0 \n", + "13 1.4 12.0 \n", + "14 9.3 12.0 \n", + "15 4.5 3.0 \n", + "16 3.2 3.0 \n", "17 7.7 2.0 \n", "18 0.0 1.0 \n", - "19 4.2 6.0 \n", - "20 6.5 3.0 \n", - "21 0.0 3.0 \n", - "22 3.5 2.0 \n", - "23 4.9 0.0 \n", + "19 4.8 7.0 \n", + "20 5.7 4.0 \n", + "21 1.4 3.0 \n", + "22 3.4 2.0 \n", + "23 8.5 2.0 \n", "24 12.5 0.0 \n", - "25 3.0 0.0 \n", - "26 6.3 1.0 \n", - "27 6.1 3.0 \n", + "25 7.1 2.0 \n", + "26 1.7 1.0 \n", + "27 6.8 1.0 \n", + "28 3.0 3.0 \n", "\n", " gk_def_actions_outside_pen_area_per90 gk_avg_distance_def_actions \n", - "0 1.00 15.7 \n", + "0 0.75 12.7 \n", "1 2.00 12.4 \n", - "2 0.00 14.5 \n", + "2 0.00 11.2 \n", "3 0.00 0.0 \n", "4 1.50 22.0 \n", - "5 1.00 14.5 \n", - "6 7.00 28.9 \n", - "7 0.67 11.7 \n", - "8 0.50 10.3 \n", + "5 0.75 13.1 \n", + "6 3.50 28.9 \n", + "7 0.40 10.5 \n", + "8 0.50 9.6 \n", "9 0.75 9.8 \n", - "10 0.50 9.3 \n", - "11 1.75 18.2 \n", - "12 1.25 15.8 \n", - "13 2.00 19.4 \n", - "14 2.67 22.0 \n", - "15 0.25 7.8 \n", - "16 0.50 12.2 \n", + "10 0.33 8.5 \n", + "11 1.33 17.2 \n", + "12 1.50 17.5 \n", + "13 2.00 20.0 \n", + "14 3.00 19.9 \n", + "15 0.50 13.5 \n", + "16 0.50 13.7 \n", "17 1.00 15.0 \n", "18 1.00 21.0 \n", - "19 1.50 15.7 \n", - "20 0.75 12.5 \n", - "21 0.75 14.0 \n", - "22 0.50 11.5 \n", - "23 0.00 6.5 \n", + "19 1.17 16.0 \n", + "20 0.67 11.9 \n", + "21 0.50 13.6 \n", + "22 0.33 10.3 \n", + "23 0.33 9.6 \n", "24 0.00 9.0 \n", - "25 0.00 9.6 \n", - "26 0.50 13.7 \n", - "27 1.00 16.3 \n", + "25 1.00 13.2 \n", + "26 0.25 8.5 \n", + "27 0.25 10.2 \n", + "28 0.60 13.4 \n", "\n", - "[28 rows x 47 columns]" + "[29 rows x 47 columns]" ] }, "execution_count": 4, @@ -1598,482 +1628,482 @@ " \n", " 0\n", " Atalanta\n", - " 23.0\n", - " 49.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 8.0\n", + " 24.0\n", + " 50.5\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 48.0\n", - " 34.0\n", - " 9.0\n", + " 79.0\n", + " 55.0\n", + " 17.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 232.0\n", - " 60.0\n", - " 65.0\n", - " 48.0\n", + " 362.0\n", + " 109.0\n", + " 97.0\n", + " 52.9\n", " \n", " \n", " 1\n", " Bologna\n", - " 22.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 54.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 3.0\n", " 2.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 42.0\n", - " 41.0\n", - " 4.0\n", + " 73.0\n", + " 61.0\n", + " 8.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", - " 0.0\n", - " 205.0\n", - " 46.0\n", - " 34.0\n", - " 57.5\n", + " 288.0\n", + " 73.0\n", + " 47.0\n", + " 60.8\n", " \n", " \n", " 2\n", " Cagliari\n", - " 21.0\n", - " 37.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 22.0\n", + " 38.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 46.0\n", - " 35.0\n", - " 7.0\n", + " 70.0\n", + " 47.0\n", + " 8.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 241.0\n", - " 51.0\n", - " 60.0\n", - " 45.9\n", + " 349.0\n", + " 71.0\n", + " 92.0\n", + " 43.6\n", " \n", " \n", " 3\n", " Empoli\n", - " 27.0\n", - " 47.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 0.0\n", - " 0.0\n", + " 28.0\n", + " 45.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 1.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 59.0\n", - " 7.0\n", + " 76.0\n", + " 83.0\n", + " 12.0\n", " 0.0\n", " 2.0\n", " 1.0\n", - " 176.0\n", - " 39.0\n", - " 54.0\n", - " 41.9\n", + " 281.0\n", + " 60.0\n", + " 82.0\n", + " 42.3\n", " \n", " \n", " 4\n", " Fiorentina\n", - " 22.0\n", - " 61.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 57.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 9.0\n", - " 7.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 49.0\n", - " 52.0\n", - " 4.0\n", + " 71.0\n", + " 70.0\n", + " 10.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 196.0\n", - " 53.0\n", - " 56.0\n", - " 48.6\n", + " 315.0\n", + " 75.0\n", + " 96.0\n", + " 43.9\n", " \n", " \n", " 5\n", " Frosinone\n", - " 23.0\n", - " 48.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", - " 4.0\n", + " 24.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 5.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 43.0\n", - " 49.0\n", - " 11.0\n", + " 61.0\n", + " 69.0\n", + " 16.0\n", " 2.0\n", " 0.0\n", " 0.0\n", - " 202.0\n", - " 52.0\n", - " 53.0\n", - " 49.5\n", + " 294.0\n", + " 80.0\n", + " 79.0\n", + " 50.3\n", " \n", " \n", " 6\n", " Genoa\n", - " 19.0\n", - " 33.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", + " 22.0\n", + " 34.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 7.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 51.0\n", - " 35.0\n", + " 68.0\n", + " 57.0\n", " 5.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 177.0\n", - " 60.0\n", - " 46.0\n", - " 56.6\n", + " 265.0\n", + " 83.0\n", + " 66.0\n", + " 55.7\n", " \n", " \n", " 7\n", " Hellas Verona\n", - " 21.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 22.0\n", + " 45.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 66.0\n", - " 46.0\n", - " 12.0\n", + " 87.0\n", + " 78.0\n", + " 14.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 207.0\n", - " 82.0\n", - " 71.0\n", - " 53.6\n", + " 339.0\n", + " 117.0\n", + " 116.0\n", + " 50.2\n", " \n", " \n", " 8\n", " Inter\n", - " 19.0\n", - " 48.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 13.0\n", - " 11.0\n", + " 22.0\n", + " 53.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 15.0\n", + " 12.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 47.0\n", - " 45.0\n", - " 5.0\n", + " 68.0\n", + " 67.0\n", + " 9.0\n", " 2.0\n", " 0.0\n", " 0.0\n", - " 187.0\n", - " 44.0\n", - " 30.0\n", - " 59.5\n", + " 278.0\n", + " 77.0\n", + " 46.0\n", + " 62.6\n", " \n", " \n", " 9\n", " Juventus\n", - " 21.0\n", - " 48.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 22.0\n", + " 50.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", " 9.0\n", - " 7.0\n", " 1.0\n", " 2.0\n", " ...\n", - " 51.0\n", - " 48.0\n", - " 10.0\n", + " 73.0\n", + " 75.0\n", + " 12.0\n", " 1.0\n", " 0.0\n", - " 0.0\n", - " 181.0\n", - " 38.0\n", - " 26.0\n", - " 59.4\n", + " 1.0\n", + " 280.0\n", + " 67.0\n", + " 41.0\n", + " 62.0\n", " \n", " \n", " 10\n", " Lazio\n", " 20.0\n", - " 56.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 4.0\n", - " 0.0\n", - " 0.0\n", + " 54.0\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.0\n", + " 6.0\n", + " 1.0\n", + " 1.0\n", " ...\n", - " 47.0\n", - " 46.0\n", - " 4.0\n", + " 72.0\n", + " 64.0\n", + " 7.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 188.0\n", - " 30.0\n", - " 51.0\n", - " 37.0\n", + " 284.0\n", + " 53.0\n", + " 66.0\n", + " 44.5\n", " \n", " \n", " 11\n", " Lecce\n", - " 19.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", - " 5.0\n", + " 22.0\n", + " 46.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 6.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 55.0\n", - " 62.0\n", - " 3.0\n", + " 82.0\n", + " 86.0\n", + " 5.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 191.0\n", - " 54.0\n", - " 43.0\n", - " 55.7\n", + " 286.0\n", + " 73.0\n", + " 67.0\n", + " 52.1\n", " \n", " \n", " 12\n", " Milan\n", - " 19.0\n", - " 55.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 23.0\n", + " 56.8\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 13.0\n", + " 8.0\n", " 3.0\n", " 3.0\n", " ...\n", - " 45.0\n", - " 53.0\n", - " 6.0\n", + " 63.0\n", + " 77.0\n", + " 8.0\n", " 2.0\n", " 1.0\n", " 0.0\n", - " 169.0\n", - " 33.0\n", - " 42.0\n", - " 44.0\n", + " 287.0\n", + " 61.0\n", + " 65.0\n", + " 48.4\n", " \n", " \n", " 13\n", " Monza\n", - " 22.0\n", - " 56.8\n", + " 23.0\n", + " 54.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 53.0\n", - " 35.0\n", - " 5.0\n", + " 69.0\n", + " 61.0\n", + " 9.0\n", " 0.0\n", - " 1.0\n", + " 2.0\n", " 0.0\n", - " 175.0\n", - " 37.0\n", - " 45.0\n", - " 45.1\n", + " 257.0\n", + " 56.0\n", + " 74.0\n", + " 43.1\n", " \n", " \n", " 14\n", " Napoli\n", - " 19.0\n", - " 61.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 5.0\n", - " 1.0\n", + " 20.0\n", + " 60.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 7.0\n", " 2.0\n", + " 4.0\n", " ...\n", - " 42.0\n", - " 39.0\n", - " 14.0\n", - " 1.0\n", + " 65.0\n", + " 64.0\n", + " 16.0\n", + " 2.0\n", " 1.0\n", " 0.0\n", - " 208.0\n", - " 47.0\n", - " 35.0\n", - " 57.3\n", + " 301.0\n", + " 56.0\n", + " 52.0\n", + " 51.9\n", " \n", " \n", " 15\n", " Roma\n", " 23.0\n", - " 57.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 10.0\n", - " 8.0\n", + " 59.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 9.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 53.0\n", - " 45.0\n", - " 7.0\n", + " 70.0\n", + " 57.0\n", + " 9.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 196.0\n", - " 76.0\n", - " 54.0\n", - " 58.5\n", + " 286.0\n", + " 104.0\n", + " 83.0\n", + " 55.6\n", " \n", " \n", " 16\n", " Salernitana\n", - " 21.0\n", - " 51.5\n", + " 22.0\n", + " 52.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 48.0\n", - " 62.0\n", - " 5.0\n", + " 73.0\n", + " 90.0\n", + " 10.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 183.0\n", - " 54.0\n", - " 86.0\n", - " 38.6\n", + " 298.0\n", + " 82.0\n", + " 120.0\n", + " 40.6\n", " \n", " \n", " 17\n", " Sassuolo\n", - " 24.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 4.0\n", + " 25.0\n", + " 42.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 36.0\n", - " 41.0\n", - " 3.0\n", + " 57.0\n", + " 58.0\n", + " 7.0\n", " 1.0\n", " 3.0\n", - " 0.0\n", - " 171.0\n", - " 37.0\n", - " 50.0\n", - " 42.5\n", + " 1.0\n", + " 265.0\n", + " 55.0\n", + " 85.0\n", + " 39.3\n", " \n", " \n", " 18\n", " Torino\n", - " 22.0\n", - " 51.3\n", + " 23.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 53.0\n", - " 43.0\n", - " 10.0\n", + " 71.0\n", + " 60.0\n", + " 11.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 193.0\n", - " 59.0\n", - " 63.0\n", - " 48.4\n", + " 301.0\n", + " 82.0\n", + " 93.0\n", + " 46.9\n", " \n", " \n", " 19\n", " Udinese\n", - " 22.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 24.0\n", + " 46.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 56.0\n", - " 42.0\n", - " 5.0\n", + " 79.0\n", + " 63.0\n", + " 6.0\n", " 0.0\n", - " 1.0\n", + " 2.0\n", " 0.0\n", - " 203.0\n", - " 64.0\n", - " 52.0\n", - " 55.2\n", + " 309.0\n", + " 101.0\n", + " 68.0\n", + " 59.8\n", " \n", " \n", "\n", @@ -2082,92 +2112,92 @@ ], "text/plain": [ " team players_used possession games games_starts minutes \\\n", - "0 Atalanta 23.0 49.5 4.0 44.0 360.0 \n", - "1 Bologna 22.0 56.5 4.0 44.0 360.0 \n", - "2 Cagliari 21.0 37.8 4.0 44.0 360.0 \n", - "3 Empoli 27.0 47.8 4.0 44.0 360.0 \n", - "4 Fiorentina 22.0 61.0 4.0 44.0 360.0 \n", - "5 Frosinone 23.0 48.3 4.0 44.0 360.0 \n", - "6 Genoa 19.0 33.3 4.0 44.0 360.0 \n", - "7 Hellas Verona 21.0 43.5 4.0 44.0 360.0 \n", - "8 Inter 19.0 48.8 4.0 44.0 360.0 \n", - "9 Juventus 21.0 48.8 4.0 44.0 360.0 \n", - "10 Lazio 20.0 56.0 4.0 44.0 360.0 \n", - "11 Lecce 19.0 43.5 4.0 44.0 360.0 \n", - "12 Milan 19.0 55.3 4.0 44.0 360.0 \n", - "13 Monza 22.0 56.8 4.0 44.0 360.0 \n", - "14 Napoli 19.0 61.8 4.0 44.0 360.0 \n", - "15 Roma 23.0 57.0 4.0 44.0 360.0 \n", - "16 Salernitana 21.0 51.5 4.0 44.0 360.0 \n", - "17 Sassuolo 24.0 43.5 4.0 44.0 360.0 \n", - "18 Torino 22.0 51.3 4.0 44.0 360.0 \n", - "19 Udinese 22.0 48.5 4.0 44.0 360.0 \n", + "0 Atalanta 24.0 50.5 6.0 66.0 540.0 \n", + "1 Bologna 23.0 54.7 6.0 66.0 540.0 \n", + "2 Cagliari 22.0 38.2 6.0 66.0 540.0 \n", + "3 Empoli 28.0 45.3 6.0 66.0 540.0 \n", + "4 Fiorentina 24.0 57.2 6.0 66.0 540.0 \n", + "5 Frosinone 24.0 49.2 6.0 66.0 540.0 \n", + "6 Genoa 22.0 34.3 6.0 66.0 540.0 \n", + "7 Hellas Verona 22.0 45.2 6.0 66.0 540.0 \n", + "8 Inter 22.0 53.2 6.0 66.0 540.0 \n", + "9 Juventus 22.0 50.3 6.0 66.0 540.0 \n", + "10 Lazio 20.0 54.0 6.0 66.0 540.0 \n", + "11 Lecce 22.0 46.7 6.0 66.0 540.0 \n", + "12 Milan 23.0 56.8 6.0 66.0 540.0 \n", + "13 Monza 23.0 54.2 6.0 66.0 540.0 \n", + "14 Napoli 20.0 60.7 6.0 66.0 540.0 \n", + "15 Roma 23.0 59.7 6.0 66.0 540.0 \n", + "16 Salernitana 22.0 52.3 6.0 66.0 540.0 \n", + "17 Sassuolo 25.0 42.3 6.0 66.0 540.0 \n", + "18 Torino 23.0 49.2 6.0 66.0 540.0 \n", + "19 Udinese 24.0 46.2 6.0 66.0 540.0 \n", "\n", " goals assists pens_made pens_att ... fouls fouled offsides \\\n", - "0 8.0 8.0 0.0 0.0 ... 48.0 34.0 9.0 \n", - "1 3.0 2.0 0.0 1.0 ... 42.0 41.0 4.0 \n", - "2 1.0 1.0 0.0 0.0 ... 46.0 35.0 7.0 \n", - "3 0.0 0.0 0.0 0.0 ... 43.0 59.0 7.0 \n", - "4 9.0 7.0 0.0 0.0 ... 49.0 52.0 4.0 \n", - "5 7.0 4.0 2.0 2.0 ... 43.0 49.0 11.0 \n", - "6 4.0 3.0 0.0 0.0 ... 51.0 35.0 5.0 \n", - "7 4.0 2.0 0.0 0.0 ... 66.0 46.0 12.0 \n", - "8 13.0 11.0 2.0 2.0 ... 47.0 45.0 5.0 \n", - "9 9.0 7.0 1.0 2.0 ... 51.0 48.0 10.0 \n", - "10 4.0 4.0 0.0 0.0 ... 47.0 46.0 4.0 \n", - "11 7.0 5.0 2.0 2.0 ... 55.0 62.0 3.0 \n", - "12 9.0 6.0 3.0 3.0 ... 45.0 53.0 6.0 \n", - "13 3.0 3.0 0.0 0.0 ... 53.0 35.0 5.0 \n", - "14 8.0 5.0 1.0 2.0 ... 42.0 39.0 14.0 \n", - "15 10.0 8.0 1.0 1.0 ... 53.0 45.0 7.0 \n", - "16 3.0 3.0 0.0 0.0 ... 48.0 62.0 5.0 \n", - "17 5.0 4.0 1.0 1.0 ... 36.0 41.0 3.0 \n", - "18 5.0 3.0 0.0 0.0 ... 53.0 43.0 10.0 \n", - "19 1.0 1.0 0.0 0.0 ... 56.0 42.0 5.0 \n", + "0 11.0 11.0 0.0 0.0 ... 79.0 55.0 17.0 \n", + "1 3.0 2.0 0.0 1.0 ... 73.0 61.0 8.0 \n", + "2 2.0 2.0 0.0 0.0 ... 70.0 47.0 8.0 \n", + "3 1.0 1.0 0.0 0.0 ... 76.0 83.0 12.0 \n", + "4 12.0 9.0 0.0 0.0 ... 71.0 70.0 10.0 \n", + "5 9.0 5.0 2.0 2.0 ... 61.0 69.0 16.0 \n", + "6 8.0 7.0 0.0 0.0 ... 68.0 57.0 5.0 \n", + "7 4.0 2.0 0.0 0.0 ... 87.0 78.0 14.0 \n", + "8 15.0 12.0 2.0 2.0 ... 68.0 67.0 9.0 \n", + "9 11.0 9.0 1.0 2.0 ... 73.0 75.0 12.0 \n", + "10 7.0 6.0 1.0 1.0 ... 72.0 64.0 7.0 \n", + "11 8.0 6.0 2.0 2.0 ... 82.0 86.0 5.0 \n", + "12 13.0 8.0 3.0 3.0 ... 63.0 77.0 8.0 \n", + "13 4.0 3.0 0.0 0.0 ... 69.0 61.0 9.0 \n", + "14 12.0 7.0 2.0 4.0 ... 65.0 64.0 16.0 \n", + "15 12.0 9.0 1.0 1.0 ... 70.0 57.0 9.0 \n", + "16 4.0 3.0 0.0 0.0 ... 73.0 90.0 10.0 \n", + "17 10.0 7.0 1.0 1.0 ... 57.0 58.0 7.0 \n", + "18 6.0 4.0 0.0 0.0 ... 71.0 60.0 11.0 \n", + "19 2.0 2.0 0.0 0.0 ... 79.0 63.0 6.0 \n", "\n", " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 232.0 60.0 \n", - "1 0.0 0.0 0.0 205.0 46.0 \n", - "2 0.0 1.0 0.0 241.0 51.0 \n", - "3 0.0 2.0 1.0 176.0 39.0 \n", - "4 0.0 1.0 0.0 196.0 53.0 \n", - "5 2.0 0.0 0.0 202.0 52.0 \n", - "6 0.0 0.0 0.0 177.0 60.0 \n", - "7 0.0 1.0 0.0 207.0 82.0 \n", - "8 2.0 0.0 0.0 187.0 44.0 \n", - "9 1.0 0.0 0.0 181.0 38.0 \n", - "10 0.0 0.0 0.0 188.0 30.0 \n", - "11 1.0 0.0 0.0 191.0 54.0 \n", - "12 2.0 1.0 0.0 169.0 33.0 \n", - "13 0.0 1.0 0.0 175.0 37.0 \n", - "14 1.0 1.0 0.0 208.0 47.0 \n", - "15 0.0 1.0 0.0 196.0 76.0 \n", - "16 0.0 1.0 0.0 183.0 54.0 \n", - "17 1.0 3.0 0.0 171.0 37.0 \n", - "18 0.0 2.0 0.0 193.0 59.0 \n", - "19 0.0 1.0 0.0 203.0 64.0 \n", + "0 0.0 0.0 0.0 362.0 109.0 \n", + "1 0.0 1.0 0.0 288.0 73.0 \n", + "2 0.0 1.0 0.0 349.0 71.0 \n", + "3 0.0 2.0 1.0 281.0 60.0 \n", + "4 0.0 1.0 0.0 315.0 75.0 \n", + "5 2.0 0.0 0.0 294.0 80.0 \n", + "6 0.0 0.0 0.0 265.0 83.0 \n", + "7 0.0 1.0 0.0 339.0 117.0 \n", + "8 2.0 0.0 0.0 278.0 77.0 \n", + "9 1.0 0.0 1.0 280.0 67.0 \n", + "10 1.0 0.0 0.0 284.0 53.0 \n", + "11 1.0 0.0 0.0 286.0 73.0 \n", + "12 2.0 1.0 0.0 287.0 61.0 \n", + "13 0.0 2.0 0.0 257.0 56.0 \n", + "14 2.0 1.0 0.0 301.0 56.0 \n", + "15 0.0 1.0 0.0 286.0 104.0 \n", + "16 0.0 1.0 0.0 298.0 82.0 \n", + "17 1.0 3.0 1.0 265.0 55.0 \n", + "18 0.0 2.0 0.0 301.0 82.0 \n", + "19 0.0 2.0 0.0 309.0 101.0 \n", "\n", " aerials_lost aerials_won_pct \n", - "0 65.0 48.0 \n", - "1 34.0 57.5 \n", - "2 60.0 45.9 \n", - "3 54.0 41.9 \n", - "4 56.0 48.6 \n", - "5 53.0 49.5 \n", - "6 46.0 56.6 \n", - "7 71.0 53.6 \n", - "8 30.0 59.5 \n", - "9 26.0 59.4 \n", - "10 51.0 37.0 \n", - "11 43.0 55.7 \n", - "12 42.0 44.0 \n", - "13 45.0 45.1 \n", - "14 35.0 57.3 \n", - "15 54.0 58.5 \n", - "16 86.0 38.6 \n", - "17 50.0 42.5 \n", - "18 63.0 48.4 \n", - "19 52.0 55.2 \n", + "0 97.0 52.9 \n", + "1 47.0 60.8 \n", + "2 92.0 43.6 \n", + "3 82.0 42.3 \n", + "4 96.0 43.9 \n", + "5 79.0 50.3 \n", + "6 66.0 55.7 \n", + "7 116.0 50.2 \n", + "8 46.0 62.6 \n", + "9 41.0 62.0 \n", + "10 66.0 44.5 \n", + "11 67.0 52.1 \n", + "12 65.0 48.4 \n", + "13 74.0 43.1 \n", + "14 52.0 51.9 \n", + "15 83.0 55.6 \n", + "16 120.0 40.6 \n", + "17 85.0 39.3 \n", + "18 93.0 46.9 \n", + "19 68.0 59.8 \n", "\n", "[20 rows x 152 columns]" ] @@ -2239,482 +2269,482 @@ " \n", " 0\n", " vs Atalanta\n", - " 23.0\n", - " 50.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 49.5\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 5.0\n", " 4.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", " 1\n", " vs Bologna\n", - " 22.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 45.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", " 4.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 71.0\n", + " 70.0\n", + " 16.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 207.0\n", - " 34.0\n", - " 46.0\n", - " 42.5\n", + " 292.0\n", + " 47.0\n", + " 73.0\n", + " 39.2\n", " \n", " \n", " 2\n", " vs Cagliari\n", - " 21.0\n", - " 62.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", + " 22.0\n", + " 61.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 6.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 38.0\n", - " 41.0\n", - " 5.0\n", + " 50.0\n", + " 65.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 220.0\n", - " 60.0\n", - " 51.0\n", - " 54.1\n", + " 332.0\n", + " 92.0\n", + " 71.0\n", + " 56.4\n", " \n", " \n", " 3\n", " vs Empoli\n", - " 27.0\n", - " 52.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 11.0\n", + " 28.0\n", + " 54.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 8.0\n", " 1.0\n", " 2.0\n", " ...\n", - " 60.0\n", - " 42.0\n", - " 8.0\n", + " 84.0\n", + " 74.0\n", + " 10.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 54.0\n", - " 39.0\n", - " 58.1\n", + " 313.0\n", + " 82.0\n", + " 60.0\n", + " 57.7\n", " \n", " \n", " 4\n", " vs Fiorentina\n", - " 22.0\n", - " 39.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 24.0\n", + " 42.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", " 8.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 5.0\n", + " 75.0\n", + " 63.0\n", + " 8.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 202.0\n", - " 56.0\n", - " 53.0\n", - " 51.4\n", + " 311.0\n", + " 96.0\n", + " 75.0\n", + " 56.1\n", " \n", " \n", " 5\n", " vs Frosinone\n", - " 23.0\n", - " 51.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 50.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", " 6.0\n", - " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 50.0\n", - " 39.0\n", - " 6.0\n", + " 73.0\n", + " 54.0\n", + " 15.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 212.0\n", - " 53.0\n", - " 52.0\n", - " 50.5\n", + " 325.0\n", + " 79.0\n", + " 80.0\n", + " 49.7\n", " \n", " \n", " 6\n", " vs Genoa\n", - " 19.0\n", - " 66.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 22.0\n", + " 65.7\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 8.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 43.0\n", - " 9.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 200.0\n", - " 46.0\n", + " 67.0\n", " 60.0\n", - " 43.4\n", + " 12.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 295.0\n", + " 66.0\n", + " 83.0\n", + " 44.3\n", " \n", " \n", " 7\n", " vs Hellas Verona\n", - " 21.0\n", - " 56.5\n", + " 22.0\n", + " 54.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 2.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 47.0\n", - " 63.0\n", - " 7.0\n", + " 84.0\n", + " 84.0\n", + " 11.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 190.0\n", - " 71.0\n", - " 82.0\n", - " 46.4\n", + " 326.0\n", + " 116.0\n", + " 117.0\n", + " 49.8\n", " \n", " \n", " 8\n", " vs Inter\n", - " 19.0\n", - " 51.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 22.0\n", + " 46.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 3.0\n", + " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 47.0\n", - " 44.0\n", - " 5.0\n", + " 70.0\n", + " 64.0\n", + " 9.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 163.0\n", - " 30.0\n", - " 44.0\n", - " 40.5\n", + " 248.0\n", + " 46.0\n", + " 77.0\n", + " 37.4\n", " \n", " \n", " 9\n", " vs Juventus\n", - " 21.0\n", - " 51.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 2.0\n", - " 2.0\n", + " 22.0\n", + " 49.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 5.0\n", + " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 52.0\n", - " 49.0\n", - " 5.0\n", + " 80.0\n", + " 71.0\n", + " 6.0\n", " 0.0\n", " 2.0\n", - " 0.0\n", - " 173.0\n", - " 26.0\n", + " 1.0\n", + " 267.0\n", + " 41.0\n", + " 67.0\n", " 38.0\n", - " 40.6\n", " \n", " \n", " 10\n", " vs Lazio\n", " 20.0\n", - " 44.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 46.0\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 49.0\n", - " 44.0\n", - " 7.0\n", + " 69.0\n", + " 67.0\n", + " 10.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", - " 0.0\n", - " 196.0\n", - " 51.0\n", - " 30.0\n", - " 63.0\n", + " 282.0\n", + " 66.0\n", + " 53.0\n", + " 55.5\n", " \n", " \n", " 11\n", " vs Lecce\n", - " 19.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 4.0\n", + " 22.0\n", + " 53.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 5.0\n", + " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 64.0\n", - " 53.0\n", + " 88.0\n", + " 78.0\n", " 5.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 203.0\n", - " 43.0\n", - " 54.0\n", - " 44.3\n", + " 295.0\n", + " 67.0\n", + " 73.0\n", + " 47.9\n", " \n", " \n", " 12\n", " vs Milan\n", - " 19.0\n", - " 44.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 23.0\n", + " 43.2\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 7.0\n", + " 80.0\n", + " 60.0\n", + " 8.0\n", " 1.0\n", " 3.0\n", " 0.0\n", - " 176.0\n", - " 42.0\n", - " 33.0\n", - " 56.0\n", + " 281.0\n", + " 65.0\n", + " 61.0\n", + " 51.6\n", " \n", " \n", " 13\n", " vs Monza\n", - " 22.0\n", - " 43.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 45.8\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.0\n", " 5.0\n", - " 1.0\n", - " 1.0\n", + " 2.0\n", + " 2.0\n", " ...\n", - " 37.0\n", - " 52.0\n", - " 6.0\n", - " 1.0\n", + " 65.0\n", + " 68.0\n", + " 11.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", - " 187.0\n", - " 45.0\n", - " 37.0\n", - " 54.9\n", + " 281.0\n", + " 74.0\n", + " 56.0\n", + " 56.9\n", " \n", " \n", " 14\n", " vs Napoli\n", - " 19.0\n", - " 38.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 20.0\n", + " 39.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 5.0\n", - " 4.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 47.0\n", - " 39.0\n", - " 7.0\n", + " 73.0\n", + " 60.0\n", + " 9.0\n", " 1.0\n", - " 2.0\n", + " 4.0\n", " 0.0\n", - " 173.0\n", - " 35.0\n", - " 47.0\n", - " 42.7\n", + " 254.0\n", + " 52.0\n", + " 56.0\n", + " 48.1\n", " \n", " \n", " 15\n", " vs Roma\n", " 23.0\n", - " 43.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 40.3\n", " 6.0\n", - " 4.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 9.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", + " 58.0\n", + " 67.0\n", " 4.0\n", " 1.0\n", " 1.0\n", " 1.0\n", - " 159.0\n", - " 54.0\n", - " 76.0\n", - " 41.5\n", + " 267.0\n", + " 83.0\n", + " 104.0\n", + " 44.4\n", " \n", " \n", " 16\n", " vs Salernitana\n", - " 21.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 5.0\n", + " 22.0\n", + " 47.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", + " 94.0\n", + " 70.0\n", + " 12.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 86.0\n", - " 54.0\n", - " 61.4\n", + " 311.0\n", + " 120.0\n", + " 82.0\n", + " 59.4\n", " \n", " \n", " 17\n", " vs Sassuolo\n", - " 24.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 25.0\n", + " 57.7\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 8.0\n", " 2.0\n", " 3.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.0\n", + " 55.0\n", + " 20.0\n", " 2.0\n", " 1.0\n", - " 0.0\n", - " 207.0\n", - " 50.0\n", - " 37.0\n", - " 57.5\n", + " 1.0\n", + " 299.0\n", + " 85.0\n", + " 55.0\n", + " 60.7\n", " \n", " \n", " 18\n", " vs Torino\n", - " 22.0\n", - " 48.8\n", + " 23.0\n", + " 50.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 2.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 44.0\n", - " 48.0\n", + " 61.0\n", + " 64.0\n", " 7.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 207.0\n", - " 63.0\n", - " 59.0\n", - " 51.6\n", + " 302.0\n", + " 93.0\n", + " 82.0\n", + " 53.1\n", " \n", " \n", " 19\n", " vs Udinese\n", - " 22.0\n", - " 51.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", - " 1.0\n", - " 1.0\n", - " ...\n", - " 43.0\n", - " 51.0\n", + " 24.0\n", + " 53.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 10.0\n", + " 6.0\n", + " 2.0\n", + " 2.0\n", + " ...\n", + " 65.0\n", + " 74.0\n", + " 11.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 188.0\n", - " 52.0\n", - " 64.0\n", - " 44.8\n", + " 297.0\n", + " 68.0\n", + " 101.0\n", + " 40.2\n", " \n", " \n", "\n", @@ -2723,92 +2753,92 @@ ], "text/plain": [ " team players_used possession games games_starts minutes \\\n", - "0 vs Atalanta 23.0 50.5 4.0 44.0 360.0 \n", - "1 vs Bologna 22.0 43.5 4.0 44.0 360.0 \n", - "2 vs Cagliari 21.0 62.3 4.0 44.0 360.0 \n", - "3 vs Empoli 27.0 52.3 4.0 44.0 360.0 \n", - "4 vs Fiorentina 22.0 39.0 4.0 44.0 360.0 \n", - "5 vs Frosinone 23.0 51.8 4.0 44.0 360.0 \n", - "6 vs Genoa 19.0 66.8 4.0 44.0 360.0 \n", - "7 vs Hellas Verona 21.0 56.5 4.0 44.0 360.0 \n", - "8 vs Inter 19.0 51.3 4.0 44.0 360.0 \n", - "9 vs Juventus 21.0 51.3 4.0 44.0 360.0 \n", - "10 vs Lazio 20.0 44.0 4.0 44.0 360.0 \n", - "11 vs Lecce 19.0 56.5 4.0 44.0 360.0 \n", - "12 vs Milan 19.0 44.8 4.0 44.0 360.0 \n", - "13 vs Monza 22.0 43.3 4.0 44.0 360.0 \n", - "14 vs Napoli 19.0 38.3 4.0 44.0 360.0 \n", - "15 vs Roma 23.0 43.0 4.0 44.0 360.0 \n", - "16 vs Salernitana 21.0 48.5 4.0 44.0 360.0 \n", - "17 vs Sassuolo 24.0 56.5 4.0 44.0 360.0 \n", - "18 vs Torino 22.0 48.8 4.0 44.0 360.0 \n", - "19 vs Udinese 22.0 51.5 4.0 44.0 360.0 \n", + "0 vs Atalanta 24.0 49.5 6.0 66.0 540.0 \n", + "1 vs Bologna 23.0 45.3 6.0 66.0 540.0 \n", + "2 vs Cagliari 22.0 61.8 6.0 66.0 540.0 \n", + "3 vs Empoli 28.0 54.7 6.0 66.0 540.0 \n", + "4 vs Fiorentina 24.0 42.8 6.0 66.0 540.0 \n", + "5 vs Frosinone 24.0 50.8 6.0 66.0 540.0 \n", + "6 vs Genoa 22.0 65.7 6.0 66.0 540.0 \n", + "7 vs Hellas Verona 22.0 54.8 6.0 66.0 540.0 \n", + "8 vs Inter 22.0 46.8 6.0 66.0 540.0 \n", + "9 vs Juventus 22.0 49.7 6.0 66.0 540.0 \n", + "10 vs Lazio 20.0 46.0 6.0 66.0 540.0 \n", + "11 vs Lecce 22.0 53.3 6.0 66.0 540.0 \n", + "12 vs Milan 23.0 43.2 6.0 66.0 540.0 \n", + "13 vs Monza 23.0 45.8 6.0 66.0 540.0 \n", + "14 vs Napoli 20.0 39.3 6.0 66.0 540.0 \n", + "15 vs Roma 23.0 40.3 6.0 66.0 540.0 \n", + "16 vs Salernitana 22.0 47.7 6.0 66.0 540.0 \n", + "17 vs Sassuolo 25.0 57.7 6.0 66.0 540.0 \n", + "18 vs Torino 23.0 50.8 6.0 66.0 540.0 \n", + "19 vs Udinese 24.0 53.8 6.0 66.0 540.0 \n", "\n", " goals assists pens_made pens_att ... fouls fouled offsides \\\n", - "0 5.0 4.0 0.0 0.0 ... 36.0 47.0 2.0 \n", - "1 4.0 4.0 0.0 0.0 ... 50.0 40.0 12.0 \n", - "2 4.0 3.0 0.0 1.0 ... 38.0 41.0 5.0 \n", - "3 11.0 8.0 1.0 2.0 ... 60.0 42.0 8.0 \n", - "4 9.0 8.0 1.0 1.0 ... 56.0 43.0 5.0 \n", - "5 6.0 5.0 0.0 0.0 ... 50.0 39.0 6.0 \n", - "6 7.0 6.0 0.0 0.0 ... 43.0 43.0 9.0 \n", - "7 4.0 2.0 1.0 1.0 ... 47.0 63.0 7.0 \n", - "8 1.0 1.0 0.0 0.0 ... 47.0 44.0 5.0 \n", - "9 2.0 2.0 0.0 0.0 ... 52.0 49.0 5.0 \n", - "10 7.0 5.0 0.0 0.0 ... 49.0 44.0 7.0 \n", - "11 4.0 4.0 0.0 0.0 ... 64.0 53.0 5.0 \n", - "12 7.0 6.0 1.0 1.0 ... 56.0 43.0 7.0 \n", - "13 6.0 5.0 1.0 1.0 ... 37.0 52.0 6.0 \n", - "14 5.0 4.0 1.0 1.0 ... 47.0 39.0 7.0 \n", - "15 6.0 4.0 1.0 1.0 ... 46.0 51.0 4.0 \n", - "16 8.0 5.0 1.0 1.0 ... 64.0 46.0 4.0 \n", - "17 9.0 6.0 2.0 3.0 ... 45.0 34.0 15.0 \n", - "18 4.0 2.0 2.0 2.0 ... 44.0 48.0 7.0 \n", - "19 4.0 3.0 1.0 1.0 ... 43.0 51.0 10.0 \n", + "0 5.0 4.0 0.0 0.0 ... 57.0 74.0 4.0 \n", + "1 4.0 4.0 0.0 1.0 ... 71.0 70.0 16.0 \n", + "2 9.0 6.0 0.0 1.0 ... 50.0 65.0 11.0 \n", + "3 12.0 8.0 1.0 2.0 ... 84.0 74.0 10.0 \n", + "4 10.0 8.0 1.0 1.0 ... 75.0 63.0 8.0 \n", + "5 8.0 6.0 0.0 0.0 ... 73.0 54.0 15.0 \n", + "6 9.0 8.0 0.0 0.0 ... 67.0 60.0 12.0 \n", + "7 6.0 4.0 1.0 1.0 ... 84.0 84.0 11.0 \n", + "8 3.0 3.0 0.0 0.0 ... 70.0 64.0 9.0 \n", + "9 5.0 3.0 0.0 0.0 ... 80.0 71.0 6.0 \n", + "10 8.0 5.0 0.0 0.0 ... 69.0 67.0 10.0 \n", + "11 5.0 5.0 0.0 0.0 ... 88.0 78.0 5.0 \n", + "12 8.0 7.0 1.0 1.0 ... 80.0 60.0 8.0 \n", + "13 7.0 5.0 2.0 2.0 ... 65.0 68.0 11.0 \n", + "14 6.0 5.0 1.0 1.0 ... 73.0 60.0 9.0 \n", + "15 11.0 9.0 1.0 1.0 ... 58.0 67.0 4.0 \n", + "16 10.0 7.0 1.0 1.0 ... 94.0 70.0 12.0 \n", + "17 11.0 8.0 2.0 3.0 ... 63.0 55.0 20.0 \n", + "18 7.0 4.0 2.0 2.0 ... 61.0 64.0 7.0 \n", + "19 10.0 6.0 2.0 2.0 ... 65.0 74.0 11.0 \n", "\n", " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 212.0 65.0 \n", - "1 0.0 1.0 0.0 207.0 34.0 \n", - "2 0.0 0.0 0.0 220.0 60.0 \n", - "3 1.0 0.0 0.0 203.0 54.0 \n", - "4 1.0 0.0 0.0 202.0 56.0 \n", - "5 0.0 2.0 0.0 212.0 53.0 \n", - "6 0.0 0.0 0.0 200.0 46.0 \n", - "7 1.0 0.0 0.0 190.0 71.0 \n", - "8 0.0 2.0 0.0 163.0 30.0 \n", - "9 0.0 2.0 0.0 173.0 26.0 \n", - "10 0.0 0.0 0.0 196.0 51.0 \n", - "11 0.0 2.0 0.0 203.0 43.0 \n", - "12 1.0 3.0 0.0 176.0 42.0 \n", - "13 1.0 0.0 0.0 187.0 45.0 \n", - "14 1.0 2.0 0.0 173.0 35.0 \n", - "15 1.0 1.0 1.0 159.0 54.0 \n", - "16 0.0 0.0 0.0 203.0 86.0 \n", - "17 2.0 1.0 0.0 207.0 50.0 \n", - "18 1.0 0.0 0.0 207.0 63.0 \n", - "19 0.0 0.0 0.0 188.0 52.0 \n", + "0 0.0 0.0 0.0 347.0 97.0 \n", + "1 0.0 1.0 0.0 292.0 47.0 \n", + "2 0.0 0.0 0.0 332.0 92.0 \n", + "3 1.0 0.0 0.0 313.0 82.0 \n", + "4 1.0 0.0 0.0 311.0 96.0 \n", + "5 0.0 2.0 0.0 325.0 79.0 \n", + "6 0.0 0.0 0.0 295.0 66.0 \n", + "7 1.0 0.0 0.0 326.0 116.0 \n", + "8 0.0 2.0 0.0 248.0 46.0 \n", + "9 0.0 2.0 1.0 267.0 41.0 \n", + "10 0.0 1.0 0.0 282.0 66.0 \n", + "11 0.0 2.0 0.0 295.0 67.0 \n", + "12 1.0 3.0 0.0 281.0 65.0 \n", + "13 2.0 0.0 0.0 281.0 74.0 \n", + "14 1.0 4.0 0.0 254.0 52.0 \n", + "15 1.0 1.0 1.0 267.0 83.0 \n", + "16 0.0 0.0 0.0 311.0 120.0 \n", + "17 2.0 1.0 1.0 299.0 85.0 \n", + "18 1.0 0.0 0.0 302.0 93.0 \n", + "19 1.0 0.0 0.0 297.0 68.0 \n", "\n", " aerials_lost aerials_won_pct \n", - "0 60.0 52.0 \n", - "1 46.0 42.5 \n", - "2 51.0 54.1 \n", - "3 39.0 58.1 \n", - "4 53.0 51.4 \n", - "5 52.0 50.5 \n", - "6 60.0 43.4 \n", - "7 82.0 46.4 \n", - "8 44.0 40.5 \n", - "9 38.0 40.6 \n", - "10 30.0 63.0 \n", - "11 54.0 44.3 \n", - "12 33.0 56.0 \n", - "13 37.0 54.9 \n", - "14 47.0 42.7 \n", - "15 76.0 41.5 \n", - "16 54.0 61.4 \n", - "17 37.0 57.5 \n", - "18 59.0 51.6 \n", - "19 64.0 44.8 \n", + "0 109.0 47.1 \n", + "1 73.0 39.2 \n", + "2 71.0 56.4 \n", + "3 60.0 57.7 \n", + "4 75.0 56.1 \n", + "5 80.0 49.7 \n", + "6 83.0 44.3 \n", + "7 117.0 49.8 \n", + "8 77.0 37.4 \n", + "9 67.0 38.0 \n", + "10 53.0 55.5 \n", + "11 73.0 47.9 \n", + "12 61.0 51.6 \n", + "13 56.0 56.9 \n", + "14 56.0 48.1 \n", + "15 104.0 44.4 \n", + "16 82.0 59.4 \n", + "17 55.0 60.7 \n", + "18 82.0 53.1 \n", + "19 101.0 40.2 \n", "\n", "[20 rows x 152 columns]" ] diff --git a/.ipynb_checkpoints/3_players_dataset_creation-checkpoint.ipynb b/.ipynb_checkpoints/3_players_dataset_creation-checkpoint.ipynb index dfc64dd..bb1bfef 100644 --- a/.ipynb_checkpoints/3_players_dataset_creation-checkpoint.ipynb +++ b/.ipynb_checkpoints/3_players_dataset_creation-checkpoint.ipynb @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 11, "id": "b2d7073e", "metadata": {}, "outputs": [], @@ -48,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "id": "667970f6", "metadata": {}, "outputs": [ @@ -85,23 +85,23 @@ " \n", " \n", " 1\n", + " Yacine Adli\n", + " Milan\n", + " \n", + " \n", + " 2\n", " Michel Aebischer\n", " Bologna\n", " \n", " \n", - " 2\n", - " Luis Alberto\n", - " Lazio\n", - " \n", - " \n", " 3\n", - " Pontus Almqvist\n", - " Lecce\n", + " Jean-Daniel Akpa-Akpro\n", + " Monza\n", " \n", " \n", " 4\n", - " Lorenzo Amatucci\n", - " Fiorentina\n", + " Luis Alberto\n", + " Lazio\n", " \n", " \n", " ...\n", @@ -109,53 +109,53 @@ " ...\n", " \n", " \n", - " 452\n", - " Yann Sommer\n", - " Inter\n", - " \n", - " \n", - " 453\n", + " 482\n", " Alessandro Sorrentino\n", " Monza\n", " \n", " \n", - " 454\n", + " 483\n", + " Marco Sportiello\n", + " Milan\n", + " \n", + " \n", + " 484\n", " Wojciech Szczęsny\n", " Juventus\n", " \n", " \n", - " 455\n", + " 485\n", " Pietro Terracciano\n", " Fiorentina\n", " \n", " \n", - " 456\n", + " 486\n", " Stefano Turati\n", " Frosinone\n", " \n", " \n", "\n", - "

457 rows × 2 columns

\n", + "

487 rows × 2 columns

\n", "" ], "text/plain": [ - " player team\n", - "0 Francesco Acerbi Inter\n", - "1 Michel Aebischer Bologna\n", - "2 Luis Alberto Lazio\n", - "3 Pontus Almqvist Lecce\n", - "4 Lorenzo Amatucci Fiorentina\n", - ".. ... ...\n", - "452 Yann Sommer Inter\n", - "453 Alessandro Sorrentino Monza\n", - "454 Wojciech Szczęsny Juventus\n", - "455 Pietro Terracciano Fiorentina\n", - "456 Stefano Turati Frosinone\n", + " player team\n", + "0 Francesco Acerbi Inter\n", + "1 Yacine Adli Milan\n", + "2 Michel Aebischer Bologna\n", + "3 Jean-Daniel Akpa-Akpro Monza\n", + "4 Luis Alberto Lazio\n", + ".. ... ...\n", + "482 Alessandro Sorrentino Monza\n", + "483 Marco Sportiello Milan\n", + "484 Wojciech Szczęsny Juventus\n", + "485 Pietro Terracciano Fiorentina\n", + "486 Stefano Turati Frosinone\n", "\n", - "[457 rows x 2 columns]" + "[487 rows x 2 columns]" ] }, - "execution_count": 3, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -170,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "id": "e1e64596", "metadata": {}, "outputs": [], @@ -185,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "id": "3078d6f3", "metadata": {}, "outputs": [], @@ -203,7 +203,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "id": "ffd6091c", "metadata": {}, "outputs": [ @@ -213,462 +213,492 @@ "text": [ " player surname\n", "0 Francesco Acerbi Acerbi\n", - "1 Michel Aebischer Aebischer\n", - "2 Luis Alberto Alberto\n", - "3 Pontus Almqvist Almqvist\n", - "4 Lorenzo Amatucci Amatucci\n", - "5 Bruno Amione Amione\n", - "6 Felipe Anderson Anderson\n", - "7 Houssem Aouar Aouar\n", - "8 Marko Arnautović Arnautovic\n", - "9 Kristjan Asllani Asllani\n", - "10 Tommaso Augello Augello\n", - "11 Yann Aurel Bisseck Bisseck\n", - "12 Sardar Azmoun Azmoun\n", - "13 Paulo Azzi Azzi\n", - "14 Oussama El Azzouzi Azzouzi\n", - "15 Milan Badelj Badelj\n", - "16 Jaime Báez Baez\n", - "17 Nedim Bajrami Bajrami\n", - "18 Mitchel Bakker Bakker\n", - "19 Tommaso Baldanzi Baldanzi\n", - "20 Lameck Banda Banda\n", - "21 Mattia Bani Bani\n", - "22 Antonín Barák Barak\n", - "23 Nicolò Barella Barella\n", - "24 Enzo Barrenechea Barrenechea\n", - "25 Federico Baschirotto Baschirotto\n", - "26 Alessandro Bastoni Bastoni\n", - "27 Simone Bastoni Bastoni\n", - "28 Raoul Bellanova Bellanova\n", - "29 Andrea Belotti Belotti\n", - "30 Lucas Beltrán Beltran\n", - "31 Domenico Berardi Berardi\n", - "32 Bartosz Bereszyński Bereszynski\n", - "33 Etrit Berisha Berisha\n", - "34 Victor Bernth Kristiansen Kristiansen\n", - "35 Beto Beto\n", - "36 Sam Beukema Beukema\n", - "37 Jaka Bijol Bijol\n", - "38 Cristiano Biraghi Biraghi\n", - "39 Davide Biraschi Biraschi\n", - "40 Samuele Birindelli Birindelli\n", - "41 Alexis Blin Blin\n", - "42 Emil Bohinen Bohinen\n", - "43 Daniel Boloca Boloca\n", - "44 Giacomo Bonaventura Bonaventura\n", - "45 Federico Bonazzoli Bonazzoli\n", - "46 Warren Bondo Bondo\n", - "47 Gennaro Borrelli Borrelli\n", - "48 Erik Botheim Botheim\n", - "49 Edoardo Bove Bove\n", - "50 Domagoj Bradarić Bradaric\n", - "51 Josip Brekalo Brekalo\n", - "52 Gleison Bremer Bremer\n", - "53 Marco Brescianini Brescianini\n", - "54 Alessandro Buongiorno Buongiorno\n", - "55 Rareș-Cătălin Burnete Burnete\n", - "56 Juan Cabal Cabal\n", - "57 Jovane Cabral Cabral\n", - "58 Liberato Cacace Cacace\n", - "59 Jens Cajuste Cajuste\n", - "60 Davide Calabria Calabria\n", - "61 Riccardo Calafiori Calafiori\n", - "62 Luca Caldirola Caldirola\n", - "63 Hakan Çalhanoğlu Calhanoglu\n", - "64 Nicolò Cambiaghi Cambiaghi\n", - "65 Andrea Cambiaso Cambiaso\n", - "66 Matteo Cancellieri Cancellieri\n", - "67 Antonio Candreva Candreva\n", - "68 Luigi Canotto Canotto\n", - "69 Gianluca Caprari Caprari\n", - "70 Elia Caprile Caprile\n", - "71 Francesco Caputo Caputo\n", - "72 Andrea Carboni Carboni\n", - "73 Valentin Carboni Carboni\n", - "74 Carlos Carlos\n", - "75 Marco Carnesecchi Carnesecchi\n", - "76 Nicolò Casale Casale\n", - "77 Giuseppe Caso Caso\n", - "78 Valentín Castellanos Castellanos\n", - "79 Samu Castillejo Castillejo\n", - "80 Danilo Cataldi Cataldi\n", - "81 Emil Ceide Ceide\n", - "82 Zeki Çelik Celik\n", - "83 Michele Cerofolini Cerofolini\n", - "84 Walid Cheddira Cheddira\n", - "85 Federico Chiesa Chiesa\n", - "86 Oliver Christensen Christensen\n", - "87 Samuel Chukwueze Chukwueze\n", - "88 Patrick Ciurria Ciurria\n", - "89 Lorenzo Colombo Colombo\n", - "90 Andrea Colpani Colpani\n", - "91 Andrea Consigli Consigli\n", - "92 Diego Coppola Coppola\n", - "93 Tommaso Corazza Corazza\n", - "94 Lassana Coulibaly Coulibaly\n", - "95 Mamadou Coulibaly Coulibaly\n", - "96 Alessio Cragno Cragno\n", - "97 Bryan Cristante Cristante\n", - "98 Juan Cuadrado Cuadrado\n", - "99 Marvin Cuni Cuni\n", - "100 Danilo D'Ambrosio DAmbrosio\n", - "101 Danilo Danilo\n", - "102 Matteo Darmian Darmian\n", - "103 Paweł Dawidowicz Dawidowicz\n", - "104 Charles De Ketelaere Ketelaere\n", - "105 Lorenzo De Silvestri Silvestri\n", - "106 Koni De Winter Winter\n", - "107 Grégoire Defrel Defrel\n", - "108 Alessandro Deiola Deiola\n", - "109 Mattia Destro Destro\n", - "110 Federico Di Francesco Francesco\n", - "111 Michele Di Gregorio Gregorio\n", - "112 Giovanni Di Lorenzo Lorenzo\n", - "113 Alessandro Di Pardo Pardo\n", - "114 Boulaye Dia Dia\n", - "115 Federico Dimarco Dimarco\n", - "116 Berat Djimsiti Djimsiti\n", - "117 Dodô Dodo\n", - "118 Josh Doig Doig\n", - "119 Nicolás Domínguez Dominguez\n", - "120 Patrick Dorgu Dorgu\n", - "121 Alberto Dossena Dossena\n", - "122 Radu Drăgușin Dragusin\n", - "123 Ondrej Duda Duda\n", - "124 Denzel Dumfries Dumfries\n", - "125 Alfred Duncan Duncan\n", - "126 Paulo Dybala Dybala\n", - "127 Festy Ebosele Ebosele\n", - "128 Enzo Ebosse Ebosse\n", - "129 Tyronne Ebuehi Ebuehi\n", - "130 Éderson Ederson\n", - "131 Emmanuel Ekong Ekong\n", - "132 Caleb Ekuban Ekuban\n", - "133 Elif Elmas Elmas\n", - "134 Martin Erlic Erlic\n", - "135 Giovanni Fabbian Fabbian\n", - "136 Nicolò Fagioli Fagioli\n", - "137 Wladimiro Falcone Falcone\n", - "138 Davide Faraoni Faraoni\n", - "139 Federico Fazio Fazio\n", - "140 Jacopo Fazzini Fazzini\n", - "141 Lewis Ferguson Ferguson\n", - "142 João Ferreira Ferreira\n", - "143 Alessandro Florenzi Florenzi\n", - "144 Michael Folorunsho Folorunsho\n", - "145 Davide Frattesi Frattesi\n", - "146 Morten Frendrup Frendrup\n", - "147 Remo Freuler Freuler\n", - "148 Roberto Gagliardini Gagliardini\n", - "149 Antonino Gallo Gallo\n", - "150 Luca Garritano Garritano\n", - "151 Federico Gatti Gatti\n", - "152 Francesco Gelli Gelli\n", - "153 Valentin Gendrey Gendrey\n", - "154 Gvidas Gineitis Gineitis\n", - "155 Olivier Giroud Giroud\n", - "156 Edoardo Goldaniga Goldaniga\n", - "157 Joan Gonzàlez Gonzalez\n", - "158 Nicolás González Gonzalez\n", - "159 Alberto Grassi Grassi\n", - "160 Mattéo Guendouzi Guendouzi\n", - "161 Axel Guessand Guessand\n", - "162 Albert Guðmundsson Gumundsson\n", - "163 Emmanuel Gyasi Gyasi\n", - "164 Norbert Gyömbér Gyomber\n", - "165 Nicolas Haas Haas\n", - "166 Abdou Harroui Harroui\n", - "167 Pantelis Hatzidiakos Hatzidiakos\n", - "168 Silvan Hefti Hefti\n", - "169 Liam Henderson Henderson\n", - "170 Matheus Henrique Henrique\n", - "171 Theo Hernández Hernandez\n", - "172 Isak Hien Hien\n", - "173 Emil Holm Holm\n", - "174 Martin Hongla Hongla\n", - "175 Sydney van Hooijdonk Hooijdonk\n", - "176 Elseid Hysaj Hysaj\n", - "177 Chukwubuikem Ikwuemesi Ikwuemesi\n", - "178 Ivan Ilić Ilic\n", - "179 Samuel Iling-Junior Iling-Junior\n", - "180 Ciro Immobile Immobile\n", - "181 Gino Infantino Infantino\n", - "182 Gustav Isaksen Isaksen\n", - "183 Ardian Ismajli Ismajli\n", - "184 Armando Izzo Izzo\n", - "185 Filip Jagiełło Jagieo\n", - "186 Jakub Jankto Jankto\n", - "187 Juan Jesus Jesus\n", - "188 Luka Jović Jovic\n", - "189 Mohamed Kaba Kaba\n", - "190 Christian Kabasele Kabasele\n", - "191 Pierre Kalulu Kalulu\n", - "192 Daichi Kamada Kamada\n", - "193 Hassane Kamara Kamara\n", - "194 Yann Karamoh Karamoh\n", - "195 Jesper Karlsson Karlsson\n", - "196 Rick Karsdorp Karsdorp\n", - "197 Grigoris Kastanos Kastanos\n", - "198 Michael Kayode Kayode\n", - "199 Moise Kean Kean\n", - "200 Simon Kjær Kjr\n", - "201 Sead Kolašinac Kolasinac\n", - "202 Teun Koopmeiners Koopmeiners\n", - "203 Filip Kostić Kostic\n", - "204 Christian Kouamé Kouame\n", - "205 Viktor Kovalenko Kovalenko\n", - "206 Nikola Krstović Krstovic\n", - "207 Rade Krunić Krunic\n", - "208 Berkan Kutlu Kutlu\n", - "209 Khvicha Kvaratskhelia Kvaratskhelia\n", - "210 Giorgi Kvernadze Kvernadze\n", - "211 Giorgos Kyriakopoulos Kyriakopoulos\n", - "212 Armand Lauriente Lauriente\n", - "213 Valentino Lazaro Lazaro\n", - "214 Darko Lazović Lazovic\n", - "215 Manuel Lazzari Lazzari\n", - "216 Rafael Leão Leao\n", - "217 Jesper Lindstrøm Lindstrm\n", - "218 Karol Linetty Linetty\n", - "219 Pol Lirola Lirola\n", - "220 Diego Llorente Llorente\n", - "221 Stanislav Lobotka Lobotka\n", - "222 Manuel Locatelli Locatelli\n", - "223 Ruben Loftus-Cheek Loftus-Cheek\n", - "224 Ademola Lookman Lookman\n", - "225 Maxime Lopez Lopez\n", - "226 Matteo Lovato Lovato\n", - "227 Sandi Lovrić Lovric\n", - "228 Lorenzo Lucca Lucca\n", - "229 Jhon Lucumí Lucumi\n", - "230 José Luis Palomino Palomino\n", - "231 Romelu Lukaku Lukaku\n", - "232 Sebastiano Luperto Luperto\n", - "233 Charalambos Lykogiannis Lykogiannis\n", - "234 Giulio Maggiore Maggiore\n", - "235 Giangiacomo Magnani Magnani\n", - "236 Mike Maignan Maignan\n", - "237 Antoine Makoumbou Makoumbou\n", - "238 Youssef Maleh Maleh\n", - "239 Ruslan Malinovskyi Malinovskyi\n", - "240 Gianluca Mancini Mancini\n", - "241 Rolando Mandragora Mandragora\n", - "242 Riccardo Marchizza Marchizza\n", - "243 Pablo Marí Mari\n", - "244 Mirko Marić Maric\n", - "245 Răzvan Marin Marin\n", - "246 Agustín Martegani Martegani\n", - "247 Aarón Martín Martin\n", - "248 Josep Martinez Martinez\n", - "249 Lautaro Martínez Martinez\n", - "250 Lucas Martínez Quarta Quarta\n", - "251 Adam Marušić Marusic\n", - "252 Luca Mazzitelli Mazzitelli\n", - "253 Pasquale Mazzocchi Mazzocchi\n", - "254 Jordi Mboula Mboula\n", - "255 Weston McKennie McKennie\n", - "256 Arthur Melo Melo\n", - "257 Alex Meret Meret\n", - "258 Nikola Milenković Milenkovic\n", - "259 Arkadiusz Milik Milik\n", - "260 Vanja Milinković-Savić Milinkovic-Savic\n", - "261 Aleksei Miranchuk Miranchuk\n", - "262 Kevin Miranda Miranda\n", - "263 Fabio Miretti Miretti\n", - "264 Filippo Missori Missori\n", - "265 Henrikh Mkhitaryan Mkhitaryan\n", - "266 Ilario Monterisi Monterisi\n", - "267 Lorenzo Montipò Montipo\n", - "268 Nikola Moro Moro\n", - "269 Dany Mota Mota\n", - "270 Samuele Mulattieri Mulattieri\n", - "271 Luis Muriel Muriel\n", - "272 Yunus Musah Musah\n", - "273 Juan Musso Musso\n", - "274 Obite N'Dicka NDicka\n", - "275 Nahitan Nández Nandez\n", - "276 Michel Ndary Adopo Adopo\n", - "277 Dan Ndoye Ndoye\n", - "278 Cyril Ngonge Ngonge\n", - "279 Rasmus Nissen Nissen\n", - "280 M'Bala Nzola Nzola\n", - "281 Adam Obert Obert\n", - "282 Guillermo Ochoa Ochoa\n", - "283 Noah Okafor Okafor\n", - "284 Caleb Okoli Okoli\n", - "285 Mathías Olivera Olivera\n", - "286 Gaetano Oristanio Oristanio\n", - "287 Riccardo Orsolini Orsolini\n", - "288 Victor Osimhen Osimhen\n", - "289 Anthony Oyono Oyono\n", - "290 Riccardo Pagano Pagano\n", - "291 Leandro Paredes Paredes\n", - "292 Fabiano Parisi Parisi\n", - "293 Mario Pašalić Pasalic\n", - "294 Patric Patric\n", - "295 Rui Patrício Patricio\n", - "296 Leonardo Pavoletti Pavoletti\n", - "297 Martín Payero Payero\n", - "298 Marcus Pedersen Pedersen\n", - "299 Pedro Pedro\n", - "300 Pietro Pellegri Pellegri\n", - "301 Lorenzo Pellegrini Pellegrini\n", - "302 Luca Pellegrini Pellegrini\n", - "303 Pepín Pepin\n", - "304 Pedro Pereira Pereira\n", - "305 Roberto Pereyra Pereyra\n", - "306 Nehuén Pérez Perez\n", - "307 Mattia Perin Perin\n", - "308 Samuele Perisan Perisan\n", - "309 Matteo Pessina Pessina\n", - "310 Andrea Petagna Petagna\n", - "311 Giuseppe Pezzella Pezzella\n", - "312 Roberto Piccoli Piccoli\n", - "313 Roberto Piccoli Piccoli\n", - "314 Andrea Pinamonti Pinamonti\n", - "315 Lorenzo Pirola Pirola\n", - "316 Tommaso Pobega Pobega\n", - "317 Paul Pogba Pogba\n", - "318 Matteo Politano Politano\n", - "319 Marin Pongračić Pongracic\n", - "320 Stefan Posch Posch\n", - "321 Matteo Prati Prati\n", - "322 Ivan Provedel Provedel\n", - "323 Christian Pulisic Pulisic\n", - "324 Domingos Quina Quina\n", - "325 Adrien Rabiot Rabiot\n", - "326 Uroš Račić Racic\n", - "327 Nemanja Radonjić Radonjic\n", - "328 Boris Radunović Radunovic\n", - "329 Hamza Rafia Rafia\n", - "330 Ylber Ramadani Ramadani\n", - "331 Luca Ranieri Ranieri\n", - "332 Giacomo Raspadori Raspadori\n", - "333 Tijjani Reijnders Reijnders\n", - "334 Mateo Retegui Retegui\n", - "335 Samuele Ricci Ricci\n", - "336 Ricardo Rodríguez Rodriguez\n", - "337 Alessio Romagnoli Romagnoli\n", - "338 Simone Romagnoli Romagnoli\n", - "339 Marten de Roon Roon\n", - "340 Nicolò Rovella Rovella\n", - "341 Amir Rrahmani Rrahmani\n", - "342 Ruan Ruan\n", - "343 Matteo Ruggeri Ruggeri\n", - "344 Mário Rui Rui\n", - "345 Stefano Sabelli Sabelli\n", - "346 Lazar Samardzic Samardzic\n", - "347 Junior Sambia Sambia\n", - "348 Antonio Sanabria Sanabria\n", - "349 Renato Sanches Sanches\n", - "350 Alex Sandro Sandro\n", - "351 Riccardo Saponara Saponara\n", - "352 Giorgio Scalvini Scalvini\n", - "353 Gianluca Scamacca Scamacca\n", - "354 Perr Schuurs Schuurs\n", - "355 Demba Seck Seck\n", - "356 Vivaldo Semedo Semedo\n", - "357 Stefano Sensi Sensi\n", - "358 Suat Serdar Serdar\n", - "359 Stephan El Shaarawy Shaarawy\n", - "360 Eldor Shomurodov Shomurodov\n", - "361 Steven Shpendi Shpendi\n", - "362 Marco Silvestri Silvestri\n", - "363 Giovanni Simeone Simeone\n", - "364 Leo Skiri Østigård stigard\n", - "365 Łukasz Skorupski Skorupski\n", - "366 Chris Smalling Smalling\n", - "367 Ola Solbakken Solbakken\n", - "368 Yann Sommer Sommer\n", - "369 Brandon Soppy Soppy\n", - "370 Alessandro Sorrentino Sorrentino\n", - "371 Riccardo Sottil Sottil\n", - "372 Matìas Soulé Soule\n", - "373 Leonardo Spinazzola Spinazzola\n", - "374 Gabriel Strefezza Strefezza\n", - "375 Kevin Strootman Strootman\n", - "376 Isaac Success Success\n", - "377 Ibrahim Sulemana Sulemana\n", - "378 Tomáš Suslov Suslov\n", - "379 Wojciech Szczęsny Szczesny\n", - "380 Przemysław Szymiński Szyminski\n", - "381 Adrien Tameze Tameze\n", - "382 Loum Tchaouna Tchaouna\n", - "383 Filippo Terracciano Terracciano\n", - "384 Pietro Terracciano Terracciano\n", - "385 Florian Thauvin Thauvin\n", - "386 Malick Thiaw Thiaw\n", - "387 Morten Thorsby Thorsby\n", - "388 Kristian Thorstvedt Thorstvedt\n", - "389 Marcus Thuram Thuram\n", - "390 Jeremy Toljan Toljan\n", - "391 Rafael Tolói Toloi\n", - "392 Fikayo Tomori Tomori\n", - "393 Ahmed Touba Touba\n", - "394 Stefano Turati Turati\n", - "395 Kacper Urbanski Urbanski\n", - "396 Johan Vásquez Vasquez\n", - "397 Matías Vecino Vecino\n", - "398 Simone Verdi Verdi\n", - "399 Samuele Vignato Vignato\n", - "400 Matías Viña Vina\n", - "401 Mattia Viti Viti\n", - "402 Dušan Vlahović Vlahovic\n", - "403 Nikola Vlašić Vlasic\n", - "404 Mërgim Vojvoda Vojvoda\n", - "405 Cristian Volpato Volpato\n", - "406 Stefan de Vrij Vrij\n", - "407 Walace Walace\n", - "408 Sebastian Walukiewicz Walukiewicz\n", - "409 Timothy Weah Weah\n", - "410 Mateusz Wieteska Wieteska\n", - "411 Kenan Yıldız Yldz\n", - "412 Mattia Zaccagni Zaccagni\n", - "413 Nicola Zalewski Zalewski\n", - "414 Andre-Frank Zambo Anguissa Anguissa\n", - "415 Duván Zapata Zapata\n", - "416 Duván Zapata Zapata\n", - "417 Gabriele Zappa Zappa\n", - "418 Davide Zappacosta Zappacosta\n", - "419 Oier Zarraga Zarraga\n", - "420 Jordan Zemura Zemura\n", - "421 Alessio Zerbin Zerbin\n", - "422 Piotr Zieliński Zielinski\n", - "423 David Zima Zima\n", - "424 Joshua Zirkzee Zirkzee\n", - "425 Zito Zito\n", - "426 Nadir Zortea Zortea\n", - "427 Milan Đurić uric\n", - "428 Mateusz Łęgowski egowski\n", - "429 Etrit Berisha Berisha\n", - "430 Elia Caprile Caprile\n", - "431 Marco Carnesecchi Carnesecchi\n", - "432 Michele Cerofolini Cerofolini\n", - "433 Oliver Christensen Christensen\n", - "434 Andrea Consigli Consigli\n", - "435 Alessio Cragno Cragno\n", - "436 Michele Di Gregorio Gregorio\n", - "437 Wladimiro Falcone Falcone\n", - "438 Mike Maignan Maignan\n", - "439 Josep Martinez Martinez\n", - "440 Alex Meret Meret\n", - "441 Vanja Milinković-Savić Milinkovic-Savic\n", - "442 Lorenzo Montipò Montipo\n", - "443 Juan Musso Musso\n", - "444 Guillermo Ochoa Ochoa\n", - "445 Rui Patrício Patricio\n", - "446 Mattia Perin Perin\n", - "447 Samuele Perisan Perisan\n", - "448 Ivan Provedel Provedel\n", - "449 Boris Radunović Radunovic\n", - "450 Marco Silvestri Silvestri\n", - "451 Łukasz Skorupski Skorupski\n", - "452 Yann Sommer Sommer\n", - "453 Alessandro Sorrentino Sorrentino\n", - "454 Wojciech Szczęsny Szczesny\n", - "455 Pietro Terracciano Terracciano\n", - "456 Stefano Turati Turati\n" + "1 Yacine Adli Adli\n", + "2 Michel Aebischer Aebischer\n", + "3 Jean-Daniel Akpa-Akpro Akpa-Akpro\n", + "4 Luis Alberto Alberto\n", + "5 Pontus Almqvist Almqvist\n", + "6 Lorenzo Amatucci Amatucci\n", + "7 Bruno Amione Amione\n", + "8 Felipe Anderson Anderson\n", + "9 Houssem Aouar Aouar\n", + "10 Marko Arnautović Arnautovic\n", + "11 Kristjan Asllani Asllani\n", + "12 Tommaso Augello Augello\n", + "13 Yann Aurel Bisseck Bisseck\n", + "14 Sardar Azmoun Azmoun\n", + "15 Paulo Azzi Azzi\n", + "16 Oussama El Azzouzi Azzouzi\n", + "17 Milan Badelj Badelj\n", + "18 Jaime Báez Baez\n", + "19 Nedim Bajrami Bajrami\n", + "20 Mitchel Bakker Bakker\n", + "21 Tommaso Baldanzi Baldanzi\n", + "22 Lameck Banda Banda\n", + "23 Mattia Bani Bani\n", + "24 Antonín Barák Barak\n", + "25 Nicolò Barella Barella\n", + "26 Enzo Barrenechea Barrenechea\n", + "27 Davide Bartesaghi Bartesaghi\n", + "28 Federico Baschirotto Baschirotto\n", + "29 Alessandro Bastoni Bastoni\n", + "30 Simone Bastoni Bastoni\n", + "31 Raoul Bellanova Bellanova\n", + "32 Andrea Belotti Belotti\n", + "33 Lucas Beltrán Beltran\n", + "34 Domenico Berardi Berardi\n", + "35 Bartosz Bereszyński Bereszynski\n", + "36 Etrit Berisha Berisha\n", + "37 Victor Bernth Kristiansen Kristiansen\n", + "38 Beto Beto\n", + "39 Sam Beukema Beukema\n", + "40 Jaka Bijol Bijol\n", + "41 Cristiano Biraghi Biraghi\n", + "42 Davide Biraschi Biraschi\n", + "43 Samuele Birindelli Birindelli\n", + "44 Alexis Blin Blin\n", + "45 Emil Bohinen Bohinen\n", + "46 Daniel Boloca Boloca\n", + "47 Giacomo Bonaventura Bonaventura\n", + "48 Federico Bonazzoli Bonazzoli\n", + "49 Warren Bondo Bondo\n", + "50 Gennaro Borrelli Borrelli\n", + "51 Erik Botheim Botheim\n", + "52 Mehdi Bourabia Bourabia\n", + "53 Edoardo Bove Bove\n", + "54 Domagoj Bradarić Bradaric\n", + "55 Josip Brekalo Brekalo\n", + "56 Gleison Bremer Bremer\n", + "57 Marco Brescianini Brescianini\n", + "58 Alessandro Buongiorno Buongiorno\n", + "59 Rareș-Cătălin Burnete Burnete\n", + "60 Juan Cabal Cabal\n", + "61 Jovane Cabral Cabral\n", + "62 Liberato Cacace Cacace\n", + "63 Jens Cajuste Cajuste\n", + "64 Davide Calabria Calabria\n", + "65 Riccardo Calafiori Calafiori\n", + "66 Luca Caldirola Caldirola\n", + "67 Hakan Çalhanoğlu Calhanoglu\n", + "68 Nicolò Cambiaghi Cambiaghi\n", + "69 Andrea Cambiaso Cambiaso\n", + "70 Matteo Cancellieri Cancellieri\n", + "71 Antonio Candreva Candreva\n", + "72 Luigi Canotto Canotto\n", + "73 Gianluca Caprari Caprari\n", + "74 Elia Caprile Caprile\n", + "75 Francesco Caputo Caputo\n", + "76 Andrea Carboni Carboni\n", + "77 Valentin Carboni Carboni\n", + "78 Carlos Carlos\n", + "79 Marco Carnesecchi Carnesecchi\n", + "80 Nicolò Casale Casale\n", + "81 Giuseppe Caso Caso\n", + "82 Valentín Castellanos Castellanos\n", + "83 Samu Castillejo Castillejo\n", + "84 Danilo Cataldi Cataldi\n", + "85 Emil Ceide Ceide\n", + "86 Zeki Çelik Celik\n", + "87 Michele Cerofolini Cerofolini\n", + "88 Walid Cheddira Cheddira\n", + "89 Federico Chiesa Chiesa\n", + "90 Oliver Christensen Christensen\n", + "91 Samuel Chukwueze Chukwueze\n", + "92 Patrick Ciurria Ciurria\n", + "93 Lorenzo Colombo Colombo\n", + "94 Andrea Colpani Colpani\n", + "95 Andrea Consigli Consigli\n", + "96 Diego Coppola Coppola\n", + "97 Tommaso Corazza Corazza\n", + "98 Lassana Coulibaly Coulibaly\n", + "99 Mamadou Coulibaly Coulibaly\n", + "100 Alessio Cragno Cragno\n", + "101 Bryan Cristante Cristante\n", + "102 Juan Cuadrado Cuadrado\n", + "103 Marvin Cuni Cuni\n", + "104 Danilo D'Ambrosio DAmbrosio\n", + "105 Flavius Daniliuc Daniliuc\n", + "106 Danilo Danilo\n", + "107 Matteo Darmian Darmian\n", + "108 Paweł Dawidowicz Dawidowicz\n", + "109 Charles De Ketelaere Ketelaere\n", + "110 Lorenzo De Silvestri Silvestri\n", + "111 Koni De Winter Winter\n", + "112 Grégoire Defrel Defrel\n", + "113 Alessandro Deiola Deiola\n", + "114 Mattia Destro Destro\n", + "115 Federico Di Francesco Francesco\n", + "116 Michele Di Gregorio Gregorio\n", + "117 Giovanni Di Lorenzo Lorenzo\n", + "118 Alessandro Di Pardo Pardo\n", + "119 Boulaye Dia Dia\n", + "120 Federico Dimarco Dimarco\n", + "121 Berat Djimsiti Djimsiti\n", + "122 Dodô Dodo\n", + "123 Josh Doig Doig\n", + "124 Nicolás Domínguez Dominguez\n", + "125 Patrick Dorgu Dorgu\n", + "126 Alberto Dossena Dossena\n", + "127 Radu Drăgușin Dragusin\n", + "128 Ondrej Duda Duda\n", + "129 Denzel Dumfries Dumfries\n", + "130 Alfred Duncan Duncan\n", + "131 Paulo Dybala Dybala\n", + "132 Festy Ebosele Ebosele\n", + "133 Enzo Ebosse Ebosse\n", + "134 Tyronne Ebuehi Ebuehi\n", + "135 Éderson Ederson\n", + "136 Emmanuel Ekong Ekong\n", + "137 Caleb Ekuban Ekuban\n", + "138 Elif Elmas Elmas\n", + "139 Martin Erlic Erlic\n", + "140 Giovanni Fabbian Fabbian\n", + "141 Nicolò Fagioli Fagioli\n", + "142 Wladimiro Falcone Falcone\n", + "143 Davide Faraoni Faraoni\n", + "144 Federico Fazio Fazio\n", + "145 Jacopo Fazzini Fazzini\n", + "146 Lewis Ferguson Ferguson\n", + "147 João Ferreira Ferreira\n", + "148 Alessandro Florenzi Florenzi\n", + "149 Michael Folorunsho Folorunsho\n", + "150 Davide Frattesi Frattesi\n", + "151 Morten Frendrup Frendrup\n", + "152 Remo Freuler Freuler\n", + "153 Roberto Gagliardini Gagliardini\n", + "154 Antonino Gallo Gallo\n", + "155 Luca Garritano Garritano\n", + "156 Federico Gatti Gatti\n", + "157 Francesco Gelli Gelli\n", + "158 Valentin Gendrey Gendrey\n", + "159 Gvidas Gineitis Gineitis\n", + "160 Olivier Giroud Giroud\n", + "161 Edoardo Goldaniga Goldaniga\n", + "162 Joan Gonzàlez Gonzalez\n", + "163 Nicolás González Gonzalez\n", + "164 Alberto Grassi Grassi\n", + "165 Mattéo Guendouzi Guendouzi\n", + "166 Axel Guessand Guessand\n", + "167 Albert Guðmundsson Gumundsson\n", + "168 Emmanuel Gyasi Gyasi\n", + "169 Norbert Gyömbér Gyomber\n", + "170 Nicolas Haas Haas\n", + "171 Abdou Harroui Harroui\n", + "172 Hans Hateboer Hateboer\n", + "173 Pantelis Hatzidiakos Hatzidiakos\n", + "174 Silvan Hefti Hefti\n", + "175 Liam Henderson Henderson\n", + "176 Matheus Henrique Henrique\n", + "177 Thomas Henry Henry\n", + "178 Theo Hernández Hernandez\n", + "179 Isak Hien Hien\n", + "180 Emil Holm Holm\n", + "181 Martin Hongla Hongla\n", + "182 Sydney van Hooijdonk Hooijdonk\n", + "183 Elseid Hysaj Hysaj\n", + "184 Jonathan Ikone Ikone\n", + "185 Chukwubuikem Ikwuemesi Ikwuemesi\n", + "186 Ivan Ilić Ilic\n", + "187 Samuel Iling-Junior Iling-Junior\n", + "188 Ciro Immobile Immobile\n", + "189 Gino Infantino Infantino\n", + "190 Gustav Isaksen Isaksen\n", + "191 Ardian Ismajli Ismajli\n", + "192 Armando Izzo Izzo\n", + "193 Filip Jagiełło Jagieo\n", + "194 Jakub Jankto Jankto\n", + "195 Juan Jesus Jesus\n", + "196 Luka Jović Jovic\n", + "197 Mohamed Kaba Kaba\n", + "198 Christian Kabasele Kabasele\n", + "199 Pierre Kalulu Kalulu\n", + "200 Daichi Kamada Kamada\n", + "201 Hassane Kamara Kamara\n", + "202 Yann Karamoh Karamoh\n", + "203 Jesper Karlsson Karlsson\n", + "204 Rick Karsdorp Karsdorp\n", + "205 Grigoris Kastanos Kastanos\n", + "206 Michael Kayode Kayode\n", + "207 Moise Kean Kean\n", + "208 Simon Kjær Kjr\n", + "209 Davy Klaassen Klaassen\n", + "210 Sead Kolašinac Kolasinac\n", + "211 Teun Koopmeiners Koopmeiners\n", + "212 Filip Kostić Kostic\n", + "213 Christian Kouamé Kouame\n", + "214 Viktor Kovalenko Kovalenko\n", + "215 Thomas Kristensen Kristensen\n", + "216 Nikola Krstović Krstovic\n", + "217 Rade Krunić Krunic\n", + "218 Berkan Kutlu Kutlu\n", + "219 Khvicha Kvaratskhelia Kvaratskhelia\n", + "220 Giorgi Kvernadze Kvernadze\n", + "221 Giorgos Kyriakopoulos Kyriakopoulos\n", + "222 Armand Lauriente Lauriente\n", + "223 Valentino Lazaro Lazaro\n", + "224 Darko Lazović Lazovic\n", + "225 Manuel Lazzari Lazzari\n", + "226 Rafael Leão Leao\n", + "227 Jesper Lindstrøm Lindstrm\n", + "228 Karol Linetty Linetty\n", + "229 Pol Lirola Lirola\n", + "230 Diego Llorente Llorente\n", + "231 Stanislav Lobotka Lobotka\n", + "232 Manuel Locatelli Locatelli\n", + "233 Ruben Loftus-Cheek Loftus-Cheek\n", + "234 Ademola Lookman Lookman\n", + "235 Maxime Lopez Lopez\n", + "236 Maxime Lopez Lopez\n", + "237 Matteo Lovato Lovato\n", + "238 Sandi Lovrić Lovric\n", + "239 Lorenzo Lucca Lucca\n", + "240 Jhon Lucumí Lucumi\n", + "241 José Luis Palomino Palomino\n", + "242 Romelu Lukaku Lukaku\n", + "243 Sebastiano Luperto Luperto\n", + "244 Charalambos Lykogiannis Lykogiannis\n", + "245 Giulio Maggiore Maggiore\n", + "246 Giangiacomo Magnani Magnani\n", + "247 Mike Maignan Maignan\n", + "248 Antoine Makoumbou Makoumbou\n", + "249 Youssef Maleh Maleh\n", + "250 Ruslan Malinovskyi Malinovskyi\n", + "251 Gianluca Mancini Mancini\n", + "252 Rolando Mandragora Mandragora\n", + "253 Riccardo Marchizza Marchizza\n", + "254 Gian Marco Ferrari Ferrari\n", + "255 Pablo Marí Mari\n", + "256 Mirko Marić Maric\n", + "257 Răzvan Marin Marin\n", + "258 Agustín Martegani Martegani\n", + "259 Aarón Martín Martin\n", + "260 Josep Martinez Martinez\n", + "261 Lautaro Martínez Martinez\n", + "262 Lucas Martínez Quarta Quarta\n", + "263 Adam Marušić Marusic\n", + "264 Alan Matturro Matturro\n", + "265 Luca Mazzitelli Mazzitelli\n", + "266 Pasquale Mazzocchi Mazzocchi\n", + "267 Jordi Mboula Mboula\n", + "268 Weston McKennie McKennie\n", + "269 Arthur Melo Melo\n", + "270 Alex Meret Meret\n", + "271 Junior Messias Messias\n", + "272 Nikola Milenković Milenkovic\n", + "273 Arkadiusz Milik Milik\n", + "274 Vanja Milinković-Savić Milinkovic-Savic\n", + "275 Aleksei Miranchuk Miranchuk\n", + "276 Kevin Miranda Miranda\n", + "277 Fabio Miretti Miretti\n", + "278 Filippo Missori Missori\n", + "279 Henrikh Mkhitaryan Mkhitaryan\n", + "280 Ilario Monterisi Monterisi\n", + "281 Lorenzo Montipò Montipo\n", + "282 Nikola Moro Moro\n", + "283 Dany Mota Mota\n", + "284 Samuele Mulattieri Mulattieri\n", + "285 Luis Muriel Muriel\n", + "286 Yunus Musah Musah\n", + "287 Juan Musso Musso\n", + "288 Obite N'Dicka NDicka\n", + "289 Nahitan Nández Nandez\n", + "290 Natan Natan\n", + "291 Michel Ndary Adopo Adopo\n", + "292 Dan Ndoye Ndoye\n", + "293 Cyril Ngonge Ngonge\n", + "294 Rasmus Nissen Nissen\n", + "295 M'Bala Nzola Nzola\n", + "296 Adam Obert Obert\n", + "297 Guillermo Ochoa Ochoa\n", + "298 Noah Okafor Okafor\n", + "299 Caleb Okoli Okoli\n", + "300 Mathías Olivera Olivera\n", + "301 Gaetano Oristanio Oristanio\n", + "302 Riccardo Orsolini Orsolini\n", + "303 Victor Osimhen Osimhen\n", + "304 Remi Oudin Oudin\n", + "305 Anthony Oyono Oyono\n", + "306 Simone Pafundi Pafundi\n", + "307 Riccardo Pagano Pagano\n", + "308 Leandro Paredes Paredes\n", + "309 Fabiano Parisi Parisi\n", + "310 Mario Pašalić Pasalic\n", + "311 Patric Patric\n", + "312 Rui Patrício Patricio\n", + "313 Benjamin Pavard Pavard\n", + "314 Leonardo Pavoletti Pavoletti\n", + "315 Martín Payero Payero\n", + "316 Marcus Pedersen Pedersen\n", + "317 Pedro Pedro\n", + "318 Pietro Pellegri Pellegri\n", + "319 Lorenzo Pellegrini Pellegrini\n", + "320 Luca Pellegrini Pellegrini\n", + "321 Pepín Pepin\n", + "322 Pedro Pereira Pereira\n", + "323 Roberto Pereyra Pereyra\n", + "324 Nehuén Pérez Perez\n", + "325 Mattia Perin Perin\n", + "326 Samuele Perisan Perisan\n", + "327 Matteo Pessina Pessina\n", + "328 Andrea Petagna Petagna\n", + "329 Giuseppe Pezzella Pezzella\n", + "330 Roberto Piccoli Piccoli\n", + "331 Roberto Piccoli Piccoli\n", + "332 Andrea Pinamonti Pinamonti\n", + "333 Lorenzo Pirola Pirola\n", + "334 Tommaso Pobega Pobega\n", + "335 Paul Pogba Pogba\n", + "336 Matteo Politano Politano\n", + "337 Marin Pongračić Pongracic\n", + "338 Stefan Posch Posch\n", + "339 Matteo Prati Prati\n", + "340 Ivan Provedel Provedel\n", + "341 Christian Pulisic Pulisic\n", + "342 George Pușcaș Puscas\n", + "343 Domingos Quina Quina\n", + "344 Adrien Rabiot Rabiot\n", + "345 Uroš Račić Racic\n", + "346 Nemanja Radonjić Radonjic\n", + "347 Boris Radunović Radunovic\n", + "348 Hamza Rafia Rafia\n", + "349 Ylber Ramadani Ramadani\n", + "350 Luca Ranieri Ranieri\n", + "351 Filippo Ranocchia Ranocchia\n", + "352 Giacomo Raspadori Raspadori\n", + "353 Tijjani Reijnders Reijnders\n", + "354 Mateo Retegui Retegui\n", + "355 Samuele Ricci Ricci\n", + "356 Ricardo Rodríguez Rodriguez\n", + "357 Alessio Romagnoli Romagnoli\n", + "358 Simone Romagnoli Romagnoli\n", + "359 Luka Romero Romero\n", + "360 Marten de Roon Roon\n", + "361 Nicolò Rovella Rovella\n", + "362 Amir Rrahmani Rrahmani\n", + "363 Ruan Ruan\n", + "364 Daniele Rugani Rugani\n", + "365 Matteo Ruggeri Ruggeri\n", + "366 Mário Rui Rui\n", + "367 Stefano Sabelli Sabelli\n", + "368 Alexis Saelemaekers Saelemaekers\n", + "369 Lazar Samardzic Samardzic\n", + "370 Junior Sambia Sambia\n", + "371 Antonio Sanabria Sanabria\n", + "372 Renato Sanches Sanches\n", + "373 Alexis Sánchez Sanchez\n", + "374 Alex Sandro Sandro\n", + "375 Nicola Sansone Sansone\n", + "376 Riccardo Saponara Saponara\n", + "377 Saba Sazonov Sazonov\n", + "378 Giorgio Scalvini Scalvini\n", + "379 Gianluca Scamacca Scamacca\n", + "380 Perr Schuurs Schuurs\n", + "381 Demba Seck Seck\n", + "382 Vivaldo Semedo Semedo\n", + "383 Stefano Sensi Sensi\n", + "384 Suat Serdar Serdar\n", + "385 Stephan El Shaarawy Shaarawy\n", + "386 Eldor Shomurodov Shomurodov\n", + "387 Steven Shpendi Shpendi\n", + "388 Marco Silvestri Silvestri\n", + "389 Giovanni Simeone Simeone\n", + "390 Leo Skiri Østigård stigard\n", + "391 Łukasz Skorupski Skorupski\n", + "392 Chris Smalling Smalling\n", + "393 Ola Solbakken Solbakken\n", + "394 Yann Sommer Sommer\n", + "395 Brandon Soppy Soppy\n", + "396 Alessandro Sorrentino Sorrentino\n", + "397 Riccardo Sottil Sottil\n", + "398 Matìas Soulé Soule\n", + "399 Leonardo Spinazzola Spinazzola\n", + "400 Marco Sportiello Sportiello\n", + "401 Gabriel Strefezza Strefezza\n", + "402 Kevin Strootman Strootman\n", + "403 Isaac Success Success\n", + "404 Ibrahim Sulemana Sulemana\n", + "405 Tomáš Suslov Suslov\n", + "406 Wojciech Szczęsny Szczesny\n", + "407 Przemysław Szymiński Szyminski\n", + "408 Adrien Tameze Tameze\n", + "409 Loum Tchaouna Tchaouna\n", + "410 Filippo Terracciano Terracciano\n", + "411 Pietro Terracciano Terracciano\n", + "412 Florian Thauvin Thauvin\n", + "413 Malick Thiaw Thiaw\n", + "414 Morten Thorsby Thorsby\n", + "415 Kristian Thorstvedt Thorstvedt\n", + "416 Marcus Thuram Thuram\n", + "417 Jeremy Toljan Toljan\n", + "418 Rafael Tolói Toloi\n", + "419 Fikayo Tomori Tomori\n", + "420 Ahmed Touba Touba\n", + "421 Stefano Turati Turati\n", + "422 Kacper Urbanski Urbanski\n", + "423 Johan Vásquez Vasquez\n", + "424 Matías Vecino Vecino\n", + "425 Lorenzo Venuti Venuti\n", + "426 Simone Verdi Verdi\n", + "427 Samuele Vignato Vignato\n", + "428 Matías Viña Vina\n", + "429 Nicolas Viola Viola\n", + "430 Mattia Viti Viti\n", + "431 Dušan Vlahović Vlahovic\n", + "432 Nikola Vlašić Vlasic\n", + "433 Mërgim Vojvoda Vojvoda\n", + "434 Cristian Volpato Volpato\n", + "435 Stefan de Vrij Vrij\n", + "436 Walace Walace\n", + "437 Sebastian Walukiewicz Walukiewicz\n", + "438 Timothy Weah Weah\n", + "439 Mateusz Wieteska Wieteska\n", + "440 Kenan Yıldız Yldz\n", + "441 Mattia Zaccagni Zaccagni\n", + "442 Nicola Zalewski Zalewski\n", + "443 Andre-Frank Zambo Anguissa Anguissa\n", + "444 Duván Zapata Zapata\n", + "445 Duván Zapata Zapata\n", + "446 Gabriele Zappa Zappa\n", + "447 Davide Zappacosta Zappacosta\n", + "448 Oier Zarraga Zarraga\n", + "449 Jordan Zemura Zemura\n", + "450 Alessio Zerbin Zerbin\n", + "451 Piotr Zieliński Zielinski\n", + "452 David Zima Zima\n", + "453 Joshua Zirkzee Zirkzee\n", + "454 Zito Zito\n", + "455 Nadir Zortea Zortea\n", + "456 Milan Đurić uric\n", + "457 Mateusz Łęgowski egowski\n", + "458 Etrit Berisha Berisha\n", + "459 Elia Caprile Caprile\n", + "460 Marco Carnesecchi Carnesecchi\n", + "461 Michele Cerofolini Cerofolini\n", + "462 Oliver Christensen Christensen\n", + "463 Andrea Consigli Consigli\n", + "464 Alessio Cragno Cragno\n", + "465 Michele Di Gregorio Gregorio\n", + "466 Wladimiro Falcone Falcone\n", + "467 Mike Maignan Maignan\n", + "468 Josep Martinez Martinez\n", + "469 Alex Meret Meret\n", + "470 Vanja Milinković-Savić Milinkovic-Savic\n", + "471 Lorenzo Montipò Montipo\n", + "472 Juan Musso Musso\n", + "473 Guillermo Ochoa Ochoa\n", + "474 Rui Patrício Patricio\n", + "475 Mattia Perin Perin\n", + "476 Samuele Perisan Perisan\n", + "477 Ivan Provedel Provedel\n", + "478 Boris Radunović Radunovic\n", + "479 Marco Silvestri Silvestri\n", + "480 Łukasz Skorupski Skorupski\n", + "481 Yann Sommer Sommer\n", + "482 Alessandro Sorrentino Sorrentino\n", + "483 Marco Sportiello Sportiello\n", + "484 Wojciech Szczęsny Szczesny\n", + "485 Pietro Terracciano Terracciano\n", + "486 Stefano Turati Turati\n" ] } ], @@ -688,7 +718,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 16, "id": "3e759b1b", "metadata": {}, "outputs": [ @@ -829,7 +859,7 @@ "12 Kristensen Nissen Roma" ] }, - "execution_count": 7, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -858,7 +888,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "id": "f96eaaa1", "metadata": {}, "outputs": [ @@ -1013,7 +1043,7 @@ "[539 rows x 6 columns]" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1052,7 +1082,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 18, "id": "9c50e4b5", "metadata": {}, "outputs": [], @@ -1091,7 +1121,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 19, "id": "18f6c5f2", "metadata": {}, "outputs": [ @@ -1099,7 +1129,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sportiello not found\n", "Mirante not found\n", "Sepe not found\n", "Leali not found\n", @@ -1133,30 +1162,21 @@ "Borbei not found\n", "Okoye not found\n", "Mandas not found\n", - "Pavard not found\n", "Kristensen not found\n", - "Natan not found\n", "Mina not found\n", - "Hateboer not found\n", "Masina not found\n", "Djidji not found\n", "Tressoldi not found\n", "Ehizibue not found\n", "Vogliacco not found\n", - "Ferrari G. not found\n", - "Venuti not found\n", "Gunter not found\n", "Soumaoro not found\n", "Zanoli not found\n", - "Sazonov not found\n", - "Rugani not found\n", "De Sciglio not found\n", "Bonifazi not found\n", "Kumbulla not found\n", - "Daniliuc not found\n", "Haps not found\n", "Cittadini not found\n", - "Kristensen T. not found\n", "Dermaku not found\n", "Tonelli not found\n", "Capradossi not found\n", @@ -1166,7 +1186,6 @@ "Bronn not found\n", "Guarino not found\n", "Smajlovic not found\n", - "Matturro not found\n", "N'guessan not found\n", "Mateus Lusuardi not found\n", "Kalaj not found\n", @@ -1176,23 +1195,15 @@ "Pellegrino not found\n", "Comuzzo not found\n", "Lindstrom not found\n", - "Ikone' not found\n", "Bennacer not found\n", "Castrovilli not found\n", - "Klaassen not found\n", - "Messias not found\n", "Reinier not found\n", "Cajuste not found\n", "Mancosu not found\n", - "Oudin not found\n", "Machin not found\n", "Iling Junior not found\n", - "Bourabia not found\n", - "Saelemaekers not found\n", "Maldini not found\n", - "Ranocchia F. not found\n", "Tchatchoua not found\n", - "Romero L. not found\n", "Basic not found\n", "Gaetano not found\n", "Jagiello not found\n", @@ -1200,33 +1211,26 @@ "Akpa Akpro not found\n", "Hrustic not found\n", "Camara E. not found\n", - "Viola not found\n", "Lulic K. not found\n", "Rog not found\n", "Nicolussi Caviglia not found\n", "Demme not found\n", - "Pafundi not found\n", - "Adli not found\n", "Faticanti not found\n", "Belardinelli not found\n", "Lipani not found\n", "Joselito not found\n", "Legowski not found\n", "Ibrahimovic A. not found\n", - "Sanchez not found\n", "Toure' E. not found\n", "Lapadula not found\n", "Abraham not found\n", "Deulofeu not found\n", - "Henry not found\n", "Luvumbo not found\n", "Brenner not found\n", "Davis K. not found\n", - "Sansone not found\n", "Jovane not found\n", "Alvarez A. not found\n", "Cruz not found\n", - "Puscas not found\n", "Ake' M. not found\n", "Braaf not found\n", "Kallon not found\n", @@ -1240,7 +1244,7 @@ } ], "source": [ - "exceptions = ['pellegrini', 'bastoni'] # exceptions for such players that have the same surname as others (Berardi A., Luca Pellegrini)\n", + "exceptions = ['pellegrini', 'bastoni', 'kristensen'] # exceptions for such players that have the same surname as others (Berardi A., Luca Pellegrini)\n", "\n", "for i in range(fc_players.shape[0]):\n", " if(fc_players['fb_ID'][i] == -1):\n", @@ -1259,7 +1263,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 20, "id": "3b4a36af", "metadata": {}, "outputs": [ @@ -1302,7 +1306,7 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", + " 481\n", " \n", " \n", " 1\n", @@ -1312,7 +1316,7 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", + " 484\n", " \n", " \n", " 2\n", @@ -1322,7 +1326,7 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", + " 469\n", " \n", " \n", " 3\n", @@ -1332,7 +1336,7 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", + " 477\n", " \n", " \n", " 4\n", @@ -1342,7 +1346,7 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", + " 467\n", " \n", " \n", " ...\n", @@ -1362,7 +1366,7 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", + " 387\n", " \n", " \n", " 535\n", @@ -1372,7 +1376,7 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", + " 59\n", " \n", " \n", " 536\n", @@ -1411,14 +1415,14 @@ ], "text/plain": [ " id r name team surname initial fb_ID\n", - "0 2428 P Sommer Inter Sommer 452\n", - "1 453 P Szczesny Juventus Szczesny 454\n", - "2 572 P Meret Napoli Meret 440\n", - "3 2814 P Provedel Lazio Provedel 448\n", - "4 4312 P Maignan Milan Maignan 438\n", + "0 2428 P Sommer Inter Sommer 481\n", + "1 453 P Szczesny Juventus Szczesny 484\n", + "2 572 P Meret Napoli Meret 469\n", + "3 2814 P Provedel Lazio Provedel 477\n", + "4 4312 P Maignan Milan Maignan 467\n", ".. ... .. ... ... ... ... ...\n", - "534 6395 A Shpendi S. Empoli Shpendi S 361\n", - "535 6418 A Burnete Lecce Burnete 55\n", + "534 6395 A Shpendi S. Empoli Shpendi S 387\n", + "535 6418 A Burnete Lecce Burnete 59\n", "536 6419 A Corfitzen Lecce Corfitzen -1\n", "537 6427 A Stewart Salernitana Stewart -1\n", "538 6434 A Yildiz Juventus Yildiz -1\n", @@ -1426,7 +1430,7 @@ "[539 rows x 7 columns]" ] }, - "execution_count": 12, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1445,7 +1449,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 21, "id": "1d73a312", "metadata": {}, "outputs": [ @@ -1453,37 +1457,37 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n" ] } @@ -1504,7 +1508,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 22, "id": "7acb93e3", "metadata": {}, "outputs": [ @@ -1529,7 +1533,7 @@ " dtype='object')" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1540,7 +1544,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 23, "id": "eb9127a9", "metadata": {}, "outputs": [ @@ -1548,85 +1552,85 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n" ] } @@ -1648,7 +1652,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 24, "id": "da977789", "metadata": {}, "outputs": [ @@ -1705,21 +1709,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 30.8\n", - " 29\n", - " 20.7\n", - " 28.3\n", - " 41\n", + " 29.7\n", + " 39\n", + " 20.5\n", + " 27.3\n", + " 59\n", + " 5\n", + " 8.5\n", " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", + " 0.33\n", + " 9.6\n", " \n", " \n", " 1\n", @@ -1729,21 +1733,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 33.1\n", - " 6\n", - " 66.7\n", - " 52.0\n", - " 33\n", + " 33.2\n", + " 16\n", + " 50.0\n", + " 45.8\n", + " 59\n", " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", + " 1.7\n", + " 1\n", + " 0.25\n", + " 8.5\n", " \n", " \n", " 2\n", @@ -1753,21 +1757,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", - " 24.7\n", - " 11\n", + " 24.1\n", + " 21\n", " 0.0\n", - " 20.4\n", - " 27\n", + " 20.5\n", + " 53\n", " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", + " 1.9\n", + " 8\n", + " 1.33\n", + " 17.2\n", " \n", " \n", " 3\n", @@ -1777,21 +1781,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 26.4\n", - " 15\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", + " 28.8\n", + " 29\n", + " 27.6\n", + " 32.3\n", + " 63\n", + " 3\n", + " 4.8\n", + " 7\n", + " 1.17\n", + " 16.0\n", " \n", " \n", " 4\n", @@ -1801,8 +1805,8 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", @@ -1849,10 +1853,10 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0\n", @@ -1873,8 +1877,8 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", @@ -1968,36 +1972,36 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_passes_length_avg gk_goal_kicks \\\n", - "0 1988 0 ... 30.8 29 \n", - "1 1990 0 ... 33.1 6 \n", - "2 1997 0 ... 24.7 11 \n", - "3 1994 0 ... 26.4 15 \n", + "0 1988 0 ... 29.7 39 \n", + "1 1990 0 ... 33.2 16 \n", + "2 1997 0 ... 24.1 21 \n", + "3 1994 0 ... 28.8 29 \n", "4 1995 0 ... 29.2 23 \n", ".. ... ... ... ... ... \n", - "534 2003 3 ... 0.0 0 \n", + "534 2003 5 ... 0.0 0 \n", "535 2004 1 ... 0.0 0 \n", "536 0 0 ... 0.0 0 \n", "537 0 0 ... 0.0 0 \n", "538 0 0 ... 0.0 0 \n", "\n", " gk_pct_goal_kicks_launched gk_goal_kick_length_avg gk_crosses \\\n", - "0 20.7 28.3 41 \n", - "1 66.7 52.0 33 \n", - "2 0.0 20.4 27 \n", - "3 20.0 27.9 48 \n", + "0 20.5 27.3 59 \n", + "1 50.0 45.8 59 \n", + "2 0.0 20.5 53 \n", + "3 27.6 32.3 63 \n", "4 60.9 47.0 52 \n", ".. ... ... ... \n", "534 0.0 0.0 0 \n", @@ -2007,10 +2011,10 @@ "538 0.0 0.0 0 \n", "\n", " gk_crosses_stopped gk_crosses_stopped_pct \\\n", - "0 2 4.9 \n", - "1 1 3.0 \n", - "2 1 3.7 \n", - "3 2 4.2 \n", + "0 5 8.5 \n", + "1 1 1.7 \n", + "2 1 1.9 \n", + "3 3 4.8 \n", "4 12 23.1 \n", ".. ... ... \n", "534 0 0.0 \n", @@ -2020,10 +2024,10 @@ "538 0 0.0 \n", "\n", " gk_def_actions_outside_pen_area gk_def_actions_outside_pen_area_per90 \\\n", - "0 0 0.00 \n", - "1 0 0.00 \n", - "2 7 1.75 \n", - "3 6 1.50 \n", + "0 2 0.33 \n", + "1 1 0.25 \n", + "2 8 1.33 \n", + "3 7 1.17 \n", "4 3 0.75 \n", ".. ... ... \n", "534 0 0.00 \n", @@ -2033,10 +2037,10 @@ "538 0 0.00 \n", "\n", " gk_avg_distance_def_actions \n", - "0 6.5 \n", - "1 9.6 \n", - "2 18.2 \n", - "3 15.7 \n", + "0 9.6 \n", + "1 8.5 \n", + "2 17.2 \n", + "3 16.0 \n", "4 9.8 \n", ".. ... \n", "534 0.0 \n", @@ -2048,7 +2052,7 @@ "[539 rows x 158 columns]" ] }, - "execution_count": 16, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -2067,7 +2071,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 25, "id": "6a0e43cd", "metadata": {}, "outputs": [], @@ -2087,7 +2091,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 26, "id": "61fac91a", "metadata": {}, "outputs": [ @@ -2095,8 +2099,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "vote_avg 6.090909\n", - "vote_std 0.360285\n", + "vote_avg 6.096667\n", + "vote_std 0.387547\n", "dtype: float64\n" ] }, @@ -2128,23 +2132,23 @@ " \n", " \n", " 0\n", - " 6.000000\n", - " 0.000000\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", - " 6.750000\n", - " 0.250000\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", - " 5.750000\n", - " 0.250000\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", - " 6.375000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2153,120 +2157,138 @@ " \n", " \n", " 5\n", - " 5.875000\n", - " 0.544862\n", + " 5.833333\n", + " 0.471405\n", " \n", " \n", " 6\n", - " 6.125000\n", - " 0.216506\n", + " 6.250000\n", + " 0.250000\n", " \n", " \n", " 7\n", " 6.000000\n", - " 0.353553\n", + " 0.288675\n", " \n", " \n", " 8\n", " 6.500000\n", - " 0.707107\n", + " 0.547723\n", " \n", " \n", " 9\n", - " 6.625000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 10\n", - " 5.625000\n", - " 0.414578\n", + " 5.666667\n", + " 0.372678\n", " \n", " \n", " 11\n", - " 5.750000\n", - " 0.250000\n", + " 6.250000\n", + " 0.750000\n", " \n", " \n", " 12\n", - " 5.875000\n", - " 0.819680\n", - " \n", - " \n", - " 13\n", - " 6.500000\n", - " 0.353553\n", - " \n", - " \n", - " 14\n", - " 5.875000\n", - " 0.216506\n", - " \n", - " \n", - " 15\n", - " 6.125000\n", - " 0.649519\n", - " \n", - " \n", - " 16\n", - " 6.333333\n", - " 0.849837\n", - " \n", - " \n", - " 17\n", - " 5.833333\n", - " 0.235702\n", - " \n", - " \n", - " 18\n", - " 6.333333\n", - " 0.235702\n", - " \n", - " \n", - " 19\n", " 6.000000\n", " 0.000000\n", " \n", " \n", - " 20\n", + " 13\n", + " 5.833333\n", + " 0.799305\n", + " \n", + " \n", + " 14\n", + " 6.416667\n", + " 0.343592\n", + " \n", + " \n", + " 15\n", + " 5.916667\n", + " 0.186339\n", + " \n", + " \n", + " 16\n", + " 6.250000\n", + " 0.559017\n", + " \n", + " \n", + " 17\n", + " 6.500000\n", + " 0.707107\n", + " \n", + " \n", + " 18\n", " 6.000000\n", - " 0.500000\n", + " 0.353553\n", + " \n", + " \n", + " 19\n", + " 6.250000\n", + " 0.250000\n", + " \n", + " \n", + " 20\n", + " 6.250000\n", + " 0.250000\n", " \n", " \n", " 21\n", + " 6.000000\n", + " 0.000000\n", + " \n", + " \n", + " 22\n", + " 6.125000\n", + " 0.414578\n", + " \n", + " \n", + " 23\n", " 5.750000\n", " 0.250000\n", " \n", + " \n", + " 24\n", + " 6.250000\n", + " 0.250000\n", + " \n", " \n", "\n", "" ], "text/plain": [ " vote_avg vote_std\n", - "0 6.000000 0.000000\n", - "1 6.750000 0.250000\n", - "2 5.750000 0.250000\n", - "3 6.375000 0.414578\n", + "0 5.833333 0.372678\n", + "1 5.875000 1.138804\n", + "2 5.833333 0.235702\n", + "3 6.416667 0.448764\n", "4 6.000000 0.000000\n", - "5 5.875000 0.544862\n", - "6 6.125000 0.216506\n", - "7 6.000000 0.353553\n", - "8 6.500000 0.707107\n", - "9 6.625000 0.414578\n", - "10 5.625000 0.414578\n", - "11 5.750000 0.250000\n", - "12 5.875000 0.819680\n", - "13 6.500000 0.353553\n", - "14 5.875000 0.216506\n", - "15 6.125000 0.649519\n", - "16 6.333333 0.849837\n", - "17 5.833333 0.235702\n", - "18 6.333333 0.235702\n", - "19 6.000000 0.000000\n", - "20 6.000000 0.500000\n", - "21 5.750000 0.250000" + "5 5.833333 0.471405\n", + "6 6.250000 0.250000\n", + "7 6.000000 0.288675\n", + "8 6.500000 0.547723\n", + "9 6.416667 0.448764\n", + "10 5.666667 0.372678\n", + "11 6.250000 0.750000\n", + "12 6.000000 0.000000\n", + "13 5.833333 0.799305\n", + "14 6.416667 0.343592\n", + "15 5.916667 0.186339\n", + "16 6.250000 0.559017\n", + "17 6.500000 0.707107\n", + "18 6.000000 0.353553\n", + "19 6.250000 0.250000\n", + "20 6.250000 0.250000\n", + "21 6.000000 0.000000\n", + "22 6.125000 0.414578\n", + "23 5.750000 0.250000\n", + "24 6.250000 0.250000" ] }, - "execution_count": 18, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -2305,7 +2327,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 27, "id": "c9312080", "metadata": {}, "outputs": [ @@ -2337,23 +2359,23 @@ " \n", " \n", " 0\n", - " 6.000000\n", - " 0.000000\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", - " 6.750000\n", - " 0.250000\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", - " 5.750000\n", - " 0.250000\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", - " 6.375000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2367,28 +2389,28 @@ " \n", " \n", " 534\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -2397,28 +2419,28 @@ ], "text/plain": [ " vote_avg vote_std\n", - "0 6.000000 0.000000\n", - "1 6.750000 0.250000\n", - "2 5.750000 0.250000\n", - "3 6.375000 0.414578\n", + "0 5.833333 0.372678\n", + "1 5.875000 1.138804\n", + "2 5.833333 0.235702\n", + "3 6.416667 0.448764\n", "4 6.000000 0.000000\n", ".. ... ...\n", - "534 5.750000 0.250000\n", - "535 6.000000 0.000000\n", - "536 5.799850 0.000000\n", - "537 6.447669 0.000000\n", - "538 6.437600 0.000000\n", + "534 5.875000 0.216506\n", + "535 6.211157 0.443859\n", + "536 5.482051 0.490718\n", + "537 6.039974 0.448371\n", + "538 5.601015 0.337620\n", "\n", "[539 rows x 2 columns]" ] }, - "execution_count": 19, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "min_votes = 1 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", + "min_votes = 3 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", "\n", "#outfield players\n", "mean_def = 6\n", @@ -2457,7 +2479,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 28, "id": "b2570ce5", "metadata": {}, "outputs": [ @@ -2514,21 +2536,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", + " 20.5\n", + " 27.3\n", + " 59\n", + " 5\n", + " 8.5\n", " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", @@ -2538,21 +2560,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", + " 50.0\n", + " 45.8\n", + " 59\n", " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 1.7\n", + " 1\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", @@ -2562,21 +2584,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", + " 20.5\n", + " 53\n", " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 1.9\n", + " 8\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", @@ -2586,21 +2608,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63\n", + " 3\n", + " 4.8\n", + " 7\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2610,8 +2632,8 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", @@ -2658,10 +2680,10 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", @@ -2671,8 +2693,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", @@ -2682,8 +2704,8 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", @@ -2695,8 +2717,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", @@ -2719,8 +2741,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", @@ -2743,8 +2765,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", @@ -2767,8 +2789,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -2777,36 +2799,36 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_pct_goal_kicks_launched \\\n", - "0 1988 0 ... 20.7 \n", - "1 1990 0 ... 66.7 \n", + "0 1988 0 ... 20.5 \n", + "1 1990 0 ... 50.0 \n", "2 1997 0 ... 0.0 \n", - "3 1994 0 ... 20.0 \n", + "3 1994 0 ... 27.6 \n", "4 1995 0 ... 60.9 \n", ".. ... ... ... ... \n", - "534 2003 3 ... 0.0 \n", + "534 2003 5 ... 0.0 \n", "535 2004 1 ... 0.0 \n", "536 0 0 ... 0.0 \n", "537 0 0 ... 0.0 \n", "538 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 28.3 41 2 \n", - "1 52.0 33 1 \n", - "2 20.4 27 1 \n", - "3 27.9 48 2 \n", + "0 27.3 59 5 \n", + "1 45.8 59 1 \n", + "2 20.5 53 1 \n", + "3 32.3 63 3 \n", "4 47.0 52 12 \n", ".. ... ... ... \n", "534 0.0 0 0 \n", @@ -2816,10 +2838,10 @@ "538 0.0 0 0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.9 0 \n", - "1 3.0 0 \n", - "2 3.7 7 \n", - "3 4.2 6 \n", + "0 8.5 2 \n", + "1 1.7 1 \n", + "2 1.9 8 \n", + "3 4.8 7 \n", "4 23.1 3 \n", ".. ... ... \n", "534 0.0 0 \n", @@ -2829,10 +2851,10 @@ "538 0.0 0 \n", "\n", " gk_def_actions_outside_pen_area_per90 gk_avg_distance_def_actions \\\n", - "0 0.00 6.5 \n", - "1 0.00 9.6 \n", - "2 1.75 18.2 \n", - "3 1.50 15.7 \n", + "0 0.33 9.6 \n", + "1 0.25 8.5 \n", + "2 1.33 17.2 \n", + "3 1.17 16.0 \n", "4 0.75 9.8 \n", ".. ... ... \n", "534 0.00 0.0 \n", @@ -2842,22 +2864,22 @@ "538 0.00 0.0 \n", "\n", " vote_avg vote_std \n", - "0 6.000000 0.000000 \n", - "1 6.750000 0.250000 \n", - "2 5.750000 0.250000 \n", - "3 6.375000 0.414578 \n", + "0 5.833333 0.372678 \n", + "1 5.875000 1.138804 \n", + "2 5.833333 0.235702 \n", + "3 6.416667 0.448764 \n", "4 6.000000 0.000000 \n", ".. ... ... \n", - "534 5.750000 0.250000 \n", - "535 6.000000 0.000000 \n", - "536 5.799850 0.000000 \n", - "537 6.447669 0.000000 \n", - "538 6.437600 0.000000 \n", + "534 5.875000 0.216506 \n", + "535 6.211157 0.443859 \n", + "536 5.482051 0.490718 \n", + "537 6.039974 0.448371 \n", + "538 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 20, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -2870,7 +2892,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 29, "id": "f7620abe", "metadata": {}, "outputs": [ @@ -2880,7 +2902,7 @@ "'gk_games'" ] }, - "execution_count": 21, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -2903,7 +2925,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 30, "id": "700b7a7d", "metadata": {}, "outputs": [ @@ -2911,7 +2933,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sportiello, 0.0\n", + "Carnesecchi, 0.6666666666666667\n", + "Caprile, 0.33333333333333337\n", + "Cragno, 0.6666666666666667\n", + "Perin, 0.6666666666666667\n", + "Christensen O., 0.6666666666666667\n", + "Sportiello, 0.6666666666666667\n", "Mirante, 0.0\n", "Sepe, 0.0\n", "Leali, 0.0\n", @@ -2922,11 +2949,13 @@ "Padelli, 0.0\n", "Scuffet, 0.0\n", "Gollini, 0.0\n", + "Perisan, 0.33333333333333337\n", "Audero, 0.0\n", "Di Gennaro, 0.0\n", "Pinsoglio, 0.0\n", "Aresti, 0.0\n", "Fiorillo, 0.0\n", + "Cerofolini, 0.33333333333333337\n", "Rossi F., 0.0\n", "Costil, 0.0\n", "Ravaglia F., 0.0\n", @@ -2938,6 +2967,7 @@ "Boer, 0.0\n", "Bagnolini, 0.0\n", "Svilar, 0.0\n", + "Sorrentino A., 0.33333333333333337\n", "Martinelli T., 0.0\n", "Popa, 0.0\n", "Stubljar, 0.0\n", @@ -2949,7 +2979,7 @@ } ], "source": [ - "min_gk_games = 1 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", + "min_gk_games = 3 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", "\n", "fc_players_newgk = fc_players.copy()\n", "\n", @@ -2973,7 +3003,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 31, "id": "2d9eee99", "metadata": {}, "outputs": [ @@ -3030,21 +3060,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", - " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", + " 2.0\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", @@ -3054,21 +3084,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", - " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", + " 1.0\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", @@ -3078,21 +3108,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", - " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 20.5\n", + " 53.0\n", + " 1.0\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", @@ -3102,21 +3132,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -3126,17 +3156,17 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", " 60.9\n", " 47.0\n", - " 52\n", - " 12\n", + " 52.0\n", + " 12.0\n", " 23.1\n", - " 3\n", + " 3.0\n", " 0.75\n", " 9.8\n", " 6.000000\n", @@ -3174,21 +3204,21 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", @@ -3198,21 +3228,21 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", @@ -3229,14 +3259,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", @@ -3253,14 +3283,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", @@ -3277,14 +3307,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -3293,62 +3323,62 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_pct_goal_kicks_launched \\\n", - "0 1988 0 ... 20.7 \n", - "1 1990 0 ... 66.7 \n", + "0 1988 0 ... 20.5 \n", + "1 1990 0 ... 50.0 \n", "2 1997 0 ... 0.0 \n", - "3 1994 0 ... 20.0 \n", + "3 1994 0 ... 27.6 \n", "4 1995 0 ... 60.9 \n", ".. ... ... ... ... \n", - "534 2003 3 ... 0.0 \n", + "534 2003 5 ... 0.0 \n", "535 2004 1 ... 0.0 \n", "536 0 0 ... 0.0 \n", "537 0 0 ... 0.0 \n", "538 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 28.3 41 2 \n", - "1 52.0 33 1 \n", - "2 20.4 27 1 \n", - "3 27.9 48 2 \n", - "4 47.0 52 12 \n", + "0 27.3 59.0 5.0 \n", + "1 45.8 59.0 1.0 \n", + "2 20.5 53.0 1.0 \n", + "3 32.3 63.0 3.0 \n", + "4 47.0 52.0 12.0 \n", ".. ... ... ... \n", - "534 0.0 0 0 \n", - "535 0.0 0 0 \n", - "536 0.0 0 0 \n", - "537 0.0 0 0 \n", - "538 0.0 0 0 \n", + "534 0.0 0.0 0.0 \n", + "535 0.0 0.0 0.0 \n", + "536 0.0 0.0 0.0 \n", + "537 0.0 0.0 0.0 \n", + "538 0.0 0.0 0.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.9 0 \n", - "1 3.0 0 \n", - "2 3.7 7 \n", - "3 4.2 6 \n", - "4 23.1 3 \n", + "0 8.5 2.0 \n", + "1 1.7 1.0 \n", + "2 1.9 8.0 \n", + "3 4.8 7.0 \n", + "4 23.1 3.0 \n", ".. ... ... \n", - "534 0.0 0 \n", - "535 0.0 0 \n", - "536 0.0 0 \n", - "537 0.0 0 \n", - "538 0.0 0 \n", + "534 0.0 0.0 \n", + "535 0.0 0.0 \n", + "536 0.0 0.0 \n", + "537 0.0 0.0 \n", + "538 0.0 0.0 \n", "\n", " gk_def_actions_outside_pen_area_per90 gk_avg_distance_def_actions \\\n", - "0 0.00 6.5 \n", - "1 0.00 9.6 \n", - "2 1.75 18.2 \n", - "3 1.50 15.7 \n", + "0 0.33 9.6 \n", + "1 0.25 8.5 \n", + "2 1.33 17.2 \n", + "3 1.17 16.0 \n", "4 0.75 9.8 \n", ".. ... ... \n", "534 0.00 0.0 \n", @@ -3358,22 +3388,22 @@ "538 0.00 0.0 \n", "\n", " vote_avg vote_std \n", - "0 6.000000 0.000000 \n", - "1 6.750000 0.250000 \n", - "2 5.750000 0.250000 \n", - "3 6.375000 0.414578 \n", + "0 5.833333 0.372678 \n", + "1 5.875000 1.138804 \n", + "2 5.833333 0.235702 \n", + "3 6.416667 0.448764 \n", "4 6.000000 0.000000 \n", ".. ... ... \n", - "534 5.750000 0.250000 \n", - "535 6.000000 0.000000 \n", - "536 5.799850 0.000000 \n", - "537 6.447669 0.000000 \n", - "538 6.437600 0.000000 \n", + "534 5.875000 0.216506 \n", + "535 6.211157 0.443859 \n", + "536 5.482051 0.490718 \n", + "537 6.039974 0.448371 \n", + "538 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 23, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -3394,7 +3424,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 32, "id": "8336c025", "metadata": {}, "outputs": [], diff --git a/.ipynb_checkpoints/4_player_match_dataset_creation-checkpoint.ipynb b/.ipynb_checkpoints/4_player_match_dataset_creation-checkpoint.ipynb index cf38fbd..a28239c 100644 --- a/.ipynb_checkpoints/4_player_match_dataset_creation-checkpoint.ipynb +++ b/.ipynb_checkpoints/4_player_match_dataset_creation-checkpoint.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "3ecf3676", "metadata": {}, "outputs": [], @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "8a6867a5", "metadata": {}, "outputs": [ @@ -108,482 +108,482 @@ " \n", " Atalanta\n", " Atalanta\n", - " 23.0\n", - " 49.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 8.0\n", + " 24.0\n", + " 50.5\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", " Bologna\n", " Bologna\n", - " 22.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 54.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 3.0\n", " 2.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 71.0\n", + " 70.0\n", + " 16.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - 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" 19.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", - " 5.0\n", + " 22.0\n", + " 46.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 6.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 64.0\n", - " 53.0\n", + " 88.0\n", + " 78.0\n", " 5.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 203.0\n", - " 43.0\n", - " 54.0\n", - " 44.3\n", + " 295.0\n", + " 67.0\n", + " 73.0\n", + " 47.9\n", " \n", " \n", " Milan\n", " Milan\n", - " 19.0\n", - " 55.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 23.0\n", + " 56.8\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 13.0\n", + " 8.0\n", " 3.0\n", " 3.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 7.0\n", + " 80.0\n", + " 60.0\n", + " 8.0\n", " 1.0\n", " 3.0\n", " 0.0\n", - " 176.0\n", - " 42.0\n", - " 33.0\n", - " 56.0\n", + " 281.0\n", + " 65.0\n", + " 61.0\n", + " 51.6\n", " \n", " \n", " Monza\n", " Monza\n", - " 22.0\n", - " 56.8\n", + " 23.0\n", + " 54.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 37.0\n", - " 52.0\n", - " 6.0\n", - " 1.0\n", + " 65.0\n", + " 68.0\n", + " 11.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", - " 187.0\n", - " 45.0\n", - " 37.0\n", - " 54.9\n", + " 281.0\n", + " 74.0\n", + " 56.0\n", + " 56.9\n", " \n", " \n", " Napoli\n", " Napoli\n", - " 19.0\n", - " 61.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 5.0\n", - " 1.0\n", - " 2.0\n", - " ...\n", - " 47.0\n", - " 39.0\n", + " 20.0\n", + " 60.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 7.0\n", - " 1.0\n", " 2.0\n", + " 4.0\n", + " ...\n", + " 73.0\n", + " 60.0\n", + " 9.0\n", + " 1.0\n", + " 4.0\n", " 0.0\n", - " 173.0\n", - " 35.0\n", - " 47.0\n", - " 42.7\n", + " 254.0\n", + " 52.0\n", + " 56.0\n", + " 48.1\n", " \n", " \n", " Roma\n", " Roma\n", " 23.0\n", - " 57.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 10.0\n", - " 8.0\n", + " 59.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 9.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", + " 58.0\n", + " 67.0\n", " 4.0\n", " 1.0\n", " 1.0\n", " 1.0\n", - " 159.0\n", - " 54.0\n", - " 76.0\n", - " 41.5\n", + " 267.0\n", + " 83.0\n", + " 104.0\n", + " 44.4\n", " \n", " \n", " Salernitana\n", " Salernitana\n", - " 21.0\n", - " 51.5\n", + " 22.0\n", + " 52.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", + " 94.0\n", + " 70.0\n", + " 12.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 86.0\n", - " 54.0\n", - " 61.4\n", + " 311.0\n", + " 120.0\n", + " 82.0\n", + " 59.4\n", " \n", " \n", " Sassuolo\n", " Sassuolo\n", - " 24.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 4.0\n", + " 25.0\n", + " 42.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.0\n", + " 55.0\n", + " 20.0\n", " 2.0\n", " 1.0\n", - " 0.0\n", - " 207.0\n", - " 50.0\n", - " 37.0\n", - " 57.5\n", + " 1.0\n", + " 299.0\n", + " 85.0\n", + " 55.0\n", + " 60.7\n", " \n", " \n", " Torino\n", " Torino\n", - " 22.0\n", - " 51.3\n", + " 23.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 44.0\n", - " 48.0\n", + " 61.0\n", + " 64.0\n", " 7.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 207.0\n", - " 63.0\n", - " 59.0\n", - " 51.6\n", + " 302.0\n", + " 93.0\n", + " 82.0\n", + " 53.1\n", " \n", " \n", " Udinese\n", " Udinese\n", - " 22.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 24.0\n", + " 46.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 51.0\n", - " 10.0\n", + " 65.0\n", + " 74.0\n", + " 11.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 188.0\n", - " 52.0\n", - " 64.0\n", - " 44.8\n", + " 297.0\n", + " 68.0\n", + " 101.0\n", + " 40.2\n", " \n", " \n", "\n", @@ -593,95 +593,95 @@ "text/plain": [ " team team_players_used team_possession team_games \\\n", "team_idx \n", - "Atalanta Atalanta 23.0 49.5 4.0 \n", - "Bologna Bologna 22.0 56.5 4.0 \n", - "Cagliari Cagliari 21.0 37.8 4.0 \n", - "Empoli Empoli 27.0 47.8 4.0 \n", - "Fiorentina Fiorentina 22.0 61.0 4.0 \n", - "Frosinone Frosinone 23.0 48.3 4.0 \n", - "Genoa Genoa 19.0 33.3 4.0 \n", - "Verona Hellas Verona 21.0 43.5 4.0 \n", - "Inter Inter 19.0 48.8 4.0 \n", - "Juventus Juventus 21.0 48.8 4.0 \n", - "Lazio Lazio 20.0 56.0 4.0 \n", - "Lecce Lecce 19.0 43.5 4.0 \n", - "Milan Milan 19.0 55.3 4.0 \n", - "Monza Monza 22.0 56.8 4.0 \n", - "Napoli Napoli 19.0 61.8 4.0 \n", - "Roma Roma 23.0 57.0 4.0 \n", - "Salernitana Salernitana 21.0 51.5 4.0 \n", - "Sassuolo Sassuolo 24.0 43.5 4.0 \n", - "Torino Torino 22.0 51.3 4.0 \n", - "Udinese Udinese 22.0 48.5 4.0 \n", + "Atalanta Atalanta 24.0 50.5 6.0 \n", + "Bologna Bologna 23.0 54.7 6.0 \n", + "Cagliari Cagliari 22.0 38.2 6.0 \n", + "Empoli Empoli 28.0 45.3 6.0 \n", + "Fiorentina Fiorentina 24.0 57.2 6.0 \n", + "Frosinone Frosinone 24.0 49.2 6.0 \n", + "Genoa Genoa 22.0 34.3 6.0 \n", + "Verona Hellas Verona 22.0 45.2 6.0 \n", + "Inter Inter 22.0 53.2 6.0 \n", + "Juventus Juventus 22.0 50.3 6.0 \n", + "Lazio Lazio 20.0 54.0 6.0 \n", + "Lecce Lecce 22.0 46.7 6.0 \n", + "Milan Milan 23.0 56.8 6.0 \n", + "Monza Monza 23.0 54.2 6.0 \n", + "Napoli Napoli 20.0 60.7 6.0 \n", + "Roma Roma 23.0 59.7 6.0 \n", + "Salernitana Salernitana 22.0 52.3 6.0 \n", + "Sassuolo Sassuolo 25.0 42.3 6.0 \n", + "Torino Torino 23.0 49.2 6.0 \n", + "Udinese Udinese 24.0 46.2 6.0 \n", "\n", " team_games_starts team_minutes team_goals team_assists \\\n", "team_idx \n", - "Atalanta 44.0 360.0 8.0 8.0 \n", - "Bologna 44.0 360.0 3.0 2.0 \n", - "Cagliari 44.0 360.0 1.0 1.0 \n", - "Empoli 44.0 360.0 0.0 0.0 \n", - "Fiorentina 44.0 360.0 9.0 7.0 \n", - "Frosinone 44.0 360.0 7.0 4.0 \n", - "Genoa 44.0 360.0 4.0 3.0 \n", - "Verona 44.0 360.0 4.0 2.0 \n", - "Inter 44.0 360.0 13.0 11.0 \n", - "Juventus 44.0 360.0 9.0 7.0 \n", - "Lazio 44.0 360.0 4.0 4.0 \n", - "Lecce 44.0 360.0 7.0 5.0 \n", - "Milan 44.0 360.0 9.0 6.0 \n", - "Monza 44.0 360.0 3.0 3.0 \n", - "Napoli 44.0 360.0 8.0 5.0 \n", - "Roma 44.0 360.0 10.0 8.0 \n", - "Salernitana 44.0 360.0 3.0 3.0 \n", - "Sassuolo 44.0 360.0 5.0 4.0 \n", - "Torino 44.0 360.0 5.0 3.0 \n", - "Udinese 44.0 360.0 1.0 1.0 \n", + "Atalanta 66.0 540.0 11.0 11.0 \n", + "Bologna 66.0 540.0 3.0 2.0 \n", + "Cagliari 66.0 540.0 2.0 2.0 \n", + "Empoli 66.0 540.0 1.0 1.0 \n", + "Fiorentina 66.0 540.0 12.0 9.0 \n", + "Frosinone 66.0 540.0 9.0 5.0 \n", + "Genoa 66.0 540.0 8.0 7.0 \n", + "Verona 66.0 540.0 4.0 2.0 \n", + "Inter 66.0 540.0 15.0 12.0 \n", + "Juventus 66.0 540.0 11.0 9.0 \n", + "Lazio 66.0 540.0 7.0 6.0 \n", + "Lecce 66.0 540.0 8.0 6.0 \n", + "Milan 66.0 540.0 13.0 8.0 \n", + "Monza 66.0 540.0 4.0 3.0 \n", + "Napoli 66.0 540.0 12.0 7.0 \n", + "Roma 66.0 540.0 12.0 9.0 \n", + "Salernitana 66.0 540.0 4.0 3.0 \n", + "Sassuolo 66.0 540.0 10.0 7.0 \n", + "Torino 66.0 540.0 6.0 4.0 \n", + "Udinese 66.0 540.0 2.0 2.0 \n", "\n", " team_pens_made team_pens_att ... vs_team_fouls \\\n", "team_idx ... \n", - "Atalanta 0.0 0.0 ... 36.0 \n", - "Bologna 0.0 1.0 ... 50.0 \n", - "Cagliari 0.0 0.0 ... 38.0 \n", - "Empoli 0.0 0.0 ... 60.0 \n", - "Fiorentina 0.0 0.0 ... 56.0 \n", - "Frosinone 2.0 2.0 ... 50.0 \n", - "Genoa 0.0 0.0 ... 43.0 \n", - "Verona 0.0 0.0 ... 47.0 \n", - "Inter 2.0 2.0 ... 47.0 \n", - "Juventus 1.0 2.0 ... 52.0 \n", - "Lazio 0.0 0.0 ... 49.0 \n", - "Lecce 2.0 2.0 ... 64.0 \n", - "Milan 3.0 3.0 ... 56.0 \n", - "Monza 0.0 0.0 ... 37.0 \n", - "Napoli 1.0 2.0 ... 47.0 \n", - "Roma 1.0 1.0 ... 46.0 \n", - "Salernitana 0.0 0.0 ... 64.0 \n", - "Sassuolo 1.0 1.0 ... 45.0 \n", - "Torino 0.0 0.0 ... 44.0 \n", - "Udinese 0.0 0.0 ... 43.0 \n", + "Atalanta 0.0 0.0 ... 57.0 \n", + "Bologna 0.0 1.0 ... 71.0 \n", + "Cagliari 0.0 0.0 ... 50.0 \n", + "Empoli 0.0 0.0 ... 84.0 \n", + "Fiorentina 0.0 0.0 ... 75.0 \n", + "Frosinone 2.0 2.0 ... 73.0 \n", + "Genoa 0.0 0.0 ... 67.0 \n", + "Verona 0.0 0.0 ... 84.0 \n", + "Inter 2.0 2.0 ... 70.0 \n", + "Juventus 1.0 2.0 ... 80.0 \n", + "Lazio 1.0 1.0 ... 69.0 \n", + "Lecce 2.0 2.0 ... 88.0 \n", + "Milan 3.0 3.0 ... 80.0 \n", + "Monza 0.0 0.0 ... 65.0 \n", + "Napoli 2.0 4.0 ... 73.0 \n", + "Roma 1.0 1.0 ... 58.0 \n", + "Salernitana 0.0 0.0 ... 94.0 \n", + "Sassuolo 1.0 1.0 ... 63.0 \n", + "Torino 0.0 0.0 ... 61.0 \n", + "Udinese 0.0 0.0 ... 65.0 \n", "\n", " vs_team_fouled vs_team_offsides vs_team_pens_won \\\n", "team_idx \n", - "Atalanta 47.0 2.0 0.0 \n", - "Bologna 40.0 12.0 0.0 \n", - "Cagliari 41.0 5.0 0.0 \n", - "Empoli 42.0 8.0 1.0 \n", - "Fiorentina 43.0 5.0 1.0 \n", - "Frosinone 39.0 6.0 0.0 \n", - "Genoa 43.0 9.0 0.0 \n", - "Verona 63.0 7.0 1.0 \n", - "Inter 44.0 5.0 0.0 \n", - "Juventus 49.0 5.0 0.0 \n", - "Lazio 44.0 7.0 0.0 \n", - "Lecce 53.0 5.0 0.0 \n", - "Milan 43.0 7.0 1.0 \n", - "Monza 52.0 6.0 1.0 \n", - "Napoli 39.0 7.0 1.0 \n", - "Roma 51.0 4.0 1.0 \n", - "Salernitana 46.0 4.0 0.0 \n", - "Sassuolo 34.0 15.0 2.0 \n", - "Torino 48.0 7.0 1.0 \n", - "Udinese 51.0 10.0 0.0 \n", + "Atalanta 74.0 4.0 0.0 \n", + "Bologna 70.0 16.0 0.0 \n", + "Cagliari 65.0 11.0 0.0 \n", + "Empoli 74.0 10.0 1.0 \n", + "Fiorentina 63.0 8.0 1.0 \n", + "Frosinone 54.0 15.0 0.0 \n", + "Genoa 60.0 12.0 0.0 \n", + "Verona 84.0 11.0 1.0 \n", + "Inter 64.0 9.0 0.0 \n", + "Juventus 71.0 6.0 0.0 \n", + "Lazio 67.0 10.0 0.0 \n", + "Lecce 78.0 5.0 0.0 \n", + "Milan 60.0 8.0 1.0 \n", + "Monza 68.0 11.0 2.0 \n", + "Napoli 60.0 9.0 1.0 \n", + "Roma 67.0 4.0 1.0 \n", + "Salernitana 70.0 12.0 0.0 \n", + "Sassuolo 55.0 20.0 2.0 \n", + "Torino 64.0 7.0 1.0 \n", + "Udinese 74.0 11.0 1.0 \n", "\n", " vs_team_pens_conceded vs_team_own_goals \\\n", "team_idx \n", @@ -694,68 +694,68 @@ "Genoa 0.0 0.0 \n", "Verona 0.0 0.0 \n", "Inter 2.0 0.0 \n", - "Juventus 2.0 0.0 \n", - "Lazio 0.0 0.0 \n", + "Juventus 2.0 1.0 \n", + "Lazio 1.0 0.0 \n", "Lecce 2.0 0.0 \n", "Milan 3.0 0.0 \n", "Monza 0.0 0.0 \n", - "Napoli 2.0 0.0 \n", + "Napoli 4.0 0.0 \n", "Roma 1.0 1.0 \n", "Salernitana 0.0 0.0 \n", - "Sassuolo 1.0 0.0 \n", + "Sassuolo 1.0 1.0 \n", "Torino 0.0 0.0 \n", "Udinese 0.0 0.0 \n", "\n", " vs_team_ball_recoveries vs_team_aerials_won \\\n", "team_idx \n", - "Atalanta 212.0 65.0 \n", - "Bologna 207.0 34.0 \n", - "Cagliari 220.0 60.0 \n", - "Empoli 203.0 54.0 \n", - "Fiorentina 202.0 56.0 \n", - "Frosinone 212.0 53.0 \n", - "Genoa 200.0 46.0 \n", - "Verona 190.0 71.0 \n", - "Inter 163.0 30.0 \n", - "Juventus 173.0 26.0 \n", - "Lazio 196.0 51.0 \n", - "Lecce 203.0 43.0 \n", - "Milan 176.0 42.0 \n", - "Monza 187.0 45.0 \n", - "Napoli 173.0 35.0 \n", - "Roma 159.0 54.0 \n", - "Salernitana 203.0 86.0 \n", - "Sassuolo 207.0 50.0 \n", - "Torino 207.0 63.0 \n", - "Udinese 188.0 52.0 \n", + "Atalanta 347.0 97.0 \n", + "Bologna 292.0 47.0 \n", + "Cagliari 332.0 92.0 \n", + "Empoli 313.0 82.0 \n", + "Fiorentina 311.0 96.0 \n", + "Frosinone 325.0 79.0 \n", + "Genoa 295.0 66.0 \n", + "Verona 326.0 116.0 \n", + "Inter 248.0 46.0 \n", + "Juventus 267.0 41.0 \n", + "Lazio 282.0 66.0 \n", + "Lecce 295.0 67.0 \n", + "Milan 281.0 65.0 \n", + "Monza 281.0 74.0 \n", + "Napoli 254.0 52.0 \n", + "Roma 267.0 83.0 \n", + "Salernitana 311.0 120.0 \n", + "Sassuolo 299.0 85.0 \n", + "Torino 302.0 93.0 \n", + "Udinese 297.0 68.0 \n", "\n", " vs_team_aerials_lost vs_team_aerials_won_pct \n", "team_idx \n", - "Atalanta 60.0 52.0 \n", - "Bologna 46.0 42.5 \n", - "Cagliari 51.0 54.1 \n", - "Empoli 39.0 58.1 \n", - "Fiorentina 53.0 51.4 \n", - "Frosinone 52.0 50.5 \n", - "Genoa 60.0 43.4 \n", - "Verona 82.0 46.4 \n", - "Inter 44.0 40.5 \n", - "Juventus 38.0 40.6 \n", - "Lazio 30.0 63.0 \n", - "Lecce 54.0 44.3 \n", - "Milan 33.0 56.0 \n", - "Monza 37.0 54.9 \n", - "Napoli 47.0 42.7 \n", - "Roma 76.0 41.5 \n", - "Salernitana 54.0 61.4 \n", - "Sassuolo 37.0 57.5 \n", - "Torino 59.0 51.6 \n", - "Udinese 64.0 44.8 \n", + "Atalanta 109.0 47.1 \n", + "Bologna 73.0 39.2 \n", + "Cagliari 71.0 56.4 \n", + "Empoli 60.0 57.7 \n", + "Fiorentina 75.0 56.1 \n", + "Frosinone 80.0 49.7 \n", + "Genoa 83.0 44.3 \n", + "Verona 117.0 49.8 \n", + "Inter 77.0 37.4 \n", + "Juventus 67.0 38.0 \n", + "Lazio 53.0 55.5 \n", + "Lecce 73.0 47.9 \n", + "Milan 61.0 51.6 \n", + "Monza 56.0 56.9 \n", + "Napoli 56.0 48.1 \n", + "Roma 104.0 44.4 \n", + "Salernitana 82.0 59.4 \n", + "Sassuolo 55.0 60.7 \n", + "Torino 82.0 53.1 \n", + "Udinese 101.0 40.2 \n", "\n", "[20 rows x 303 columns]" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -789,7 +789,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "b6a3db98", "metadata": {}, "outputs": [], @@ -807,7 +807,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "c34eb398", "metadata": {}, "outputs": [ @@ -888,21 +888,21 @@ " Inter\n", " Sommer\n", " NaN\n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", - " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", + " 2.0\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " Szczesny\n", @@ -912,21 +912,21 @@ " Juventus\n", " Szczesny\n", " NaN\n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", - " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", + " 1.0\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " Meret\n", @@ -936,21 +936,21 @@ " Napoli\n", " Meret\n", " NaN\n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", - " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 20.5\n", + " 53.0\n", + " 1.0\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " Provedel\n", @@ -960,21 +960,21 @@ " Lazio\n", " Provedel\n", " NaN\n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " Maignan\n", @@ -984,17 +984,17 @@ " Milan\n", " Maignan\n", " NaN\n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", " 60.9\n", " 47.0\n", - " 52\n", - " 12\n", + " 52.0\n", + " 12.0\n", " 23.1\n", - " 3\n", + " 3.0\n", " 0.75\n", " 9.8\n", " 6.000000\n", @@ -1032,21 +1032,21 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " Burnete\n", @@ -1056,21 +1056,21 @@ " Lecce\n", " Burnete\n", " NaN\n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " Corfitzen\n", @@ -1087,14 +1087,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " Stewart\n", @@ -1111,14 +1111,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " Yildiz\n", @@ -1135,14 +1135,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -1152,66 +1152,66 @@ "text/plain": [ " Unnamed: 0 id r team surname initial fb_ID \\\n", "name \n", - "Sommer 0 2428 P Inter Sommer NaN 452 \n", - "Szczesny 1 453 P Juventus Szczesny NaN 454 \n", - "Meret 2 572 P Napoli Meret NaN 440 \n", - "Provedel 3 2814 P Lazio Provedel NaN 448 \n", - "Maignan 4 4312 P Milan Maignan NaN 438 \n", + "Sommer 0 2428 P Inter Sommer NaN 481 \n", + "Szczesny 1 453 P Juventus Szczesny NaN 484 \n", + "Meret 2 572 P Napoli Meret NaN 469 \n", + "Provedel 3 2814 P Lazio Provedel NaN 477 \n", + "Maignan 4 4312 P Milan Maignan NaN 467 \n", "... ... ... .. ... ... ... ... \n", - "Shpendi S. 534 6395 A Empoli Shpendi S 361 \n", - "Burnete 535 6418 A Lecce Burnete NaN 55 \n", + "Shpendi S. 534 6395 A Empoli Shpendi S 387 \n", + "Burnete 535 6418 A Lecce Burnete NaN 59 \n", "Corfitzen 536 6419 A Lecce Corfitzen NaN -1 \n", "Stewart 537 6427 A Salernitana Stewart NaN -1 \n", "Yildiz 538 6434 A Juventus Yildiz NaN -1 \n", "\n", " age birth_year games ... gk_pct_goal_kicks_launched \\\n", "name ... \n", - "Sommer 34-278 1988 0 ... 20.7 \n", - "Szczesny 33-156 1990 0 ... 66.7 \n", - "Meret 26-183 1997 0 ... 0.0 \n", - "Provedel 29-188 1994 0 ... 20.0 \n", - "Maignan 28-080 1995 0 ... 60.9 \n", + "Sommer 34-287 1988 0 ... 20.5 \n", + "Szczesny 33-165 1990 0 ... 50.0 \n", + "Meret 26-192 1997 0 ... 0.0 \n", + "Provedel 29-197 1994 0 ... 27.6 \n", + "Maignan 28-089 1995 0 ... 60.9 \n", "... ... ... ... ... ... \n", - "Shpendi S. 20-125 2003 3 ... 0.0 \n", - "Burnete 19-233 2004 1 ... 0.0 \n", + "Shpendi S. 20-134 2003 5 ... 0.0 \n", + "Burnete 19-242 2004 1 ... 0.0 \n", "Corfitzen 0 0 0 ... 0.0 \n", "Stewart 0 0 0 ... 0.0 \n", "Yildiz 0 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", "name \n", - "Sommer 28.3 41 2 \n", - "Szczesny 52.0 33 1 \n", - "Meret 20.4 27 1 \n", - "Provedel 27.9 48 2 \n", - "Maignan 47.0 52 12 \n", + "Sommer 27.3 59.0 5.0 \n", + "Szczesny 45.8 59.0 1.0 \n", + "Meret 20.5 53.0 1.0 \n", + "Provedel 32.3 63.0 3.0 \n", + "Maignan 47.0 52.0 12.0 \n", "... ... ... ... \n", - "Shpendi S. 0.0 0 0 \n", - "Burnete 0.0 0 0 \n", - "Corfitzen 0.0 0 0 \n", - "Stewart 0.0 0 0 \n", - "Yildiz 0.0 0 0 \n", + "Shpendi S. 0.0 0.0 0.0 \n", + "Burnete 0.0 0.0 0.0 \n", + "Corfitzen 0.0 0.0 0.0 \n", + "Stewart 0.0 0.0 0.0 \n", + "Yildiz 0.0 0.0 0.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", "name \n", - "Sommer 4.9 0 \n", - "Szczesny 3.0 0 \n", - "Meret 3.7 7 \n", - "Provedel 4.2 6 \n", - "Maignan 23.1 3 \n", + "Sommer 8.5 2.0 \n", + "Szczesny 1.7 1.0 \n", + "Meret 1.9 8.0 \n", + "Provedel 4.8 7.0 \n", + "Maignan 23.1 3.0 \n", "... ... ... \n", - "Shpendi S. 0.0 0 \n", - "Burnete 0.0 0 \n", - "Corfitzen 0.0 0 \n", - "Stewart 0.0 0 \n", - "Yildiz 0.0 0 \n", + "Shpendi S. 0.0 0.0 \n", + "Burnete 0.0 0.0 \n", + "Corfitzen 0.0 0.0 \n", + "Stewart 0.0 0.0 \n", + "Yildiz 0.0 0.0 \n", "\n", " gk_def_actions_outside_pen_area_per90 \\\n", "name \n", - "Sommer 0.00 \n", - "Szczesny 0.00 \n", - "Meret 1.75 \n", - "Provedel 1.50 \n", + "Sommer 0.33 \n", + "Szczesny 0.25 \n", + "Meret 1.33 \n", + "Provedel 1.17 \n", "Maignan 0.75 \n", "... ... \n", "Shpendi S. 0.00 \n", @@ -1222,22 +1222,22 @@ "\n", " gk_avg_distance_def_actions vote_avg vote_std \n", "name \n", - "Sommer 6.5 6.000000 0.000000 \n", - "Szczesny 9.6 6.750000 0.250000 \n", - "Meret 18.2 5.750000 0.250000 \n", - "Provedel 15.7 6.375000 0.414578 \n", + "Sommer 9.6 5.833333 0.372678 \n", + "Szczesny 8.5 5.875000 1.138804 \n", + "Meret 17.2 5.833333 0.235702 \n", + "Provedel 16.0 6.416667 0.448764 \n", "Maignan 9.8 6.000000 0.000000 \n", "... ... ... ... \n", - "Shpendi S. 0.0 5.750000 0.250000 \n", - "Burnete 0.0 6.000000 0.000000 \n", - "Corfitzen 0.0 5.799850 0.000000 \n", - "Stewart 0.0 6.447669 0.000000 \n", - "Yildiz 0.0 6.437600 0.000000 \n", + "Shpendi S. 0.0 5.875000 0.216506 \n", + "Burnete 0.0 6.211157 0.443859 \n", + "Corfitzen 0.0 5.482051 0.490718 \n", + "Stewart 0.0 6.039974 0.448371 \n", + "Yildiz 0.0 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -1259,7 +1259,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "71c8804e", "metadata": {}, "outputs": [], @@ -1294,7 +1294,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "7eb4e666", "metadata": {}, "outputs": [ @@ -1351,21 +1351,21 @@ " Inter\n", " Barella\n", " NaN\n", - " 23\n", - " 26-226\n", + " 25\n", + " 26-235\n", " 1997\n", - " 4\n", + " 6\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", "\n", @@ -1374,27 +1374,27 @@ ], "text/plain": [ " Unnamed: 0 id r team surname initial fb_ID age \\\n", - "Barella 260 1870 C Inter Barella NaN 23 26-226 \n", + "Barella 260 1870 C Inter Barella NaN 25 26-235 \n", "\n", " birth_year games ... opp_vs_team_fouls opp_vs_team_fouled \\\n", - "Barella 1997 4 ... 36.0 47.0 \n", + "Barella 1997 6 ... 57.0 74.0 \n", "\n", " opp_vs_team_offsides opp_vs_team_pens_won \\\n", - "Barella 2.0 0.0 \n", + "Barella 4.0 0.0 \n", "\n", " opp_vs_team_pens_conceded opp_vs_team_own_goals \\\n", "Barella 0.0 0.0 \n", "\n", " opp_vs_team_ball_recoveries opp_vs_team_aerials_won \\\n", - "Barella 212.0 65.0 \n", + "Barella 347.0 97.0 \n", "\n", " opp_vs_team_aerials_lost opp_vs_team_aerials_won_pct \n", - "Barella 60.0 52.0 \n", + "Barella 109.0 47.1 \n", "\n", "[1 rows x 766 columns]" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1408,7 +1408,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "6b4c1b00", "metadata": {}, "outputs": [ @@ -1418,7 +1418,7 @@ "'Inter'" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1431,7 +1431,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "6ea6df1f", "metadata": {}, "outputs": [ @@ -1531,7 +1531,7 @@ " 'vs_team_aerials_won_pct']" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1563,7 +1563,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "47bc651f", "metadata": {}, "outputs": [], @@ -1717,7 +1717,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "3f43d509", "metadata": {}, "outputs": [], @@ -1748,7 +1748,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "930d00c7", "metadata": {}, "outputs": [ @@ -1800,25 +1800,25 @@ " \n", " Barella\n", " C\n", - " 4\n", - " 4\n", - " 281\n", - " 25.0\n", + " 6\n", + " 5\n", + " 391\n", + " 14.3\n", " 0.0\n", " 0.0\n", - " 86.2\n", - " 100.0\n", - " 48.8\n", + " 85.9\n", + " 66.7\n", + " 53.2\n", " ...\n", - " 0.003559\n", - " 0.0\n", - " 0.010676\n", - " 0.010676\n", - " 0.007117\n", - " 0.0\n", - " 0.494662\n", - " 0.024911\n", - " 0.021352\n", + " 0.012788\n", + " 0.005115\n", + " 0.007673\n", + " 0.007673\n", + " 0.005115\n", + " 0.002558\n", + " 0.534527\n", + " 0.028133\n", + " 0.02046\n", " 0.0\n", " \n", " \n", @@ -1828,24 +1828,24 @@ ], "text/plain": [ " r games games_starts minutes shots_on_target_pct goals_per_shot \\\n", - "Barella C 4 4 281 25.0 0.0 \n", + "Barella C 6 5 391 14.3 0.0 \n", "\n", " goals_per_shot_on_target passes_pct aerials_won_pct \\\n", - "Barella 0.0 86.2 100.0 \n", + "Barella 0.0 85.9 66.7 \n", "\n", " team_possession ... miscontrols dispossessed fouls fouled \\\n", - "Barella 48.8 ... 0.003559 0.0 0.010676 0.010676 \n", + "Barella 53.2 ... 0.012788 0.005115 0.007673 0.007673 \n", "\n", " aerials_won aerials_lost carries progressive_carries \\\n", - "Barella 0.007117 0.0 0.494662 0.024911 \n", + "Barella 0.005115 0.002558 0.534527 0.028133 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", - "Barella 0.021352 0.0 \n", + "Barella 0.02046 0.0 \n", "\n", "[1 rows x 112 columns]" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -1868,7 +1868,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "3ae718d2", "metadata": {}, "outputs": [ @@ -1985,11 +1985,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -1998,60 +1998,60 @@ " 5.5\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", + " 4.5\n", " \n", " \n", "\n", - "

1159 rows × 10 columns

\n", + "

1731 rows × 10 columns

\n", "" ], "text/plain": [ @@ -2062,11 +2062,11 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote \n", "0 0.0 6.5 \n", @@ -2075,16 +2075,16 @@ "3 0.0 6.5 \n", "4 0.0 10.0 \n", "... ... ... \n", - "1154 0.5 5.5 \n", - "1155 0.5 5.5 \n", - "1156 0.0 6.0 \n", - "1157 0.0 5.5 \n", - "1158 0.0 5.5 \n", + "1726 0.5 5.5 \n", + "1727 0.0 6.0 \n", + "1728 0.0 5.5 \n", + "1729 0.0 6.0 \n", + "1730 0.5 4.5 \n", "\n", - "[1159 rows x 10 columns]" + "[1731 rows x 10 columns]" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -2104,7 +2104,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "ec0bc56b", "metadata": {}, "outputs": [ @@ -2123,7 +2123,13 @@ "800\n", "900\n", "1000\n", - "1100\n" + "1100\n", + "1200\n", + "1300\n", + "1400\n", + "1500\n", + "1600\n", + "1700\n" ] } ], @@ -2151,7 +2157,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "b292f9f9", "metadata": {}, "outputs": [ @@ -2237,16 +2243,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 2\n", @@ -2261,13 +2267,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -2285,16 +2291,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 4\n", @@ -2345,11 +2351,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -2357,116 +2363,116 @@ " 0.5\n", " 5.5\n", " ...\n", - " 0.028846\n", - " 0.009615\n", - " 0.019231\n", - " 0.000000\n", - " 0.009615\n", - " 0.038462\n", - " 0.182692\n", - " 0.000000\n", - " 0.000000\n", + " 0.018219\n", + " 0.008097\n", + " 0.016194\n", + " 0.030364\n", + " 0.022267\n", + " 0.044534\n", + " 0.228745\n", + " 0.010121\n", + " 0.012146\n", " 0.000000\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.015152\n", + " 0.030303\n", + " 0.030303\n", + " 0.030303\n", + " 0.015152\n", + " 0.000000\n", + " 0.287879\n", + " 0.000000\n", + " 0.030303\n", + " 0.000000\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 0.048193\n", + " 0.016064\n", + " 0.008032\n", + " 0.028112\n", + " 0.012048\n", + " 0.020080\n", + " 0.289157\n", + " 0.012048\n", + " 0.016064\n", + " 0.008032\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.055556\n", + " 0.000000\n", + " 0.055556\n", + " 0.055556\n", + " 0.055556\n", + " 0.111111\n", + " 0.277778\n", + " 0.000000\n", + " 0.055556\n", + " 0.000000\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", + " 4.5\n", " ...\n", - " 0.000000\n", - " 0.000000\n", - " 0.095238\n", - " 0.047619\n", - " 0.000000\n", - " 0.000000\n", - " 0.142857\n", - " 0.000000\n", - " 0.047619\n", - " 0.000000\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 0.047297\n", - " 0.006757\n", - " 0.006757\n", - " 0.040541\n", - " 0.013514\n", - " 0.020270\n", - " 0.324324\n", - " 0.020270\n", - " 0.013514\n", - " 0.013514\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.026316\n", - " 0.006579\n", - " 0.046053\n", - " 0.006579\n", - " 0.138158\n", - " 0.092105\n", - " 0.171053\n", - " 0.000000\n", - " 0.013158\n", - " 0.000000\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.019355\n", - " 0.012903\n", - " 0.032258\n", - " 0.009677\n", - " 0.012903\n", - " 0.022581\n", - " 0.206452\n", - " 0.035484\n", - " 0.012903\n", - " 0.016129\n", + " 0.030369\n", + " 0.008677\n", + " 0.028200\n", + " 0.010846\n", + " 0.023861\n", + " 0.041215\n", + " 0.221258\n", + " 0.026030\n", + " 0.013015\n", + " 0.013015\n", " \n", " \n", "\n", - "

1159 rows × 122 columns

\n", + "

1731 rows × 122 columns

\n", "" ], "text/plain": [ @@ -2477,55 +2483,55 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote ... miscontrols dispossessed fouls \\\n", "0 0.0 6.5 ... 0.000000 0.000000 0.000000 \n", - "1 0.0 6.5 ... 0.020161 0.012097 0.012097 \n", - "2 0.0 6.0 ... 0.007874 0.000000 0.007874 \n", - "3 0.0 6.5 ... 0.002786 0.002786 0.002786 \n", + "1 0.0 6.5 ... 0.018349 0.009174 0.009174 \n", + "2 0.0 6.0 ... 0.004608 0.000000 0.011521 \n", + "3 0.0 6.5 ... 0.009276 0.001855 0.009276 \n", "4 0.0 10.0 ... 0.000000 0.020833 0.031250 \n", "... ... ... ... ... ... ... \n", - "1154 0.5 5.5 ... 0.028846 0.009615 0.019231 \n", - "1155 0.5 5.5 ... 0.000000 0.000000 0.095238 \n", - "1156 0.0 6.0 ... 0.047297 0.006757 0.006757 \n", - "1157 0.0 5.5 ... 0.026316 0.006579 0.046053 \n", - "1158 0.0 5.5 ... 0.019355 0.012903 0.032258 \n", + "1726 0.5 5.5 ... 0.018219 0.008097 0.016194 \n", + "1727 0.0 6.0 ... 0.015152 0.030303 0.030303 \n", + "1728 0.0 5.5 ... 0.048193 0.016064 0.008032 \n", + "1729 0.0 6.0 ... 0.055556 0.000000 0.055556 \n", + "1730 0.5 4.5 ... 0.030369 0.008677 0.028200 \n", "\n", " fouled aerials_won aerials_lost carries progressive_carries \\\n", "0 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "1 0.016129 0.008065 0.016129 0.391129 0.040323 \n", - "2 0.000000 0.019685 0.027559 0.350394 0.000000 \n", - "3 0.011142 0.013928 0.022284 0.412256 0.019499 \n", + "1 0.015291 0.009174 0.015291 0.376147 0.033639 \n", + "2 0.002304 0.034562 0.020737 0.299539 0.000000 \n", + "3 0.014842 0.016698 0.022263 0.378479 0.014842 \n", "4 0.000000 0.000000 0.010417 0.447917 0.062500 \n", "... ... ... ... ... ... \n", - "1154 0.000000 0.009615 0.038462 0.182692 0.000000 \n", - "1155 0.047619 0.000000 0.000000 0.142857 0.000000 \n", - "1156 0.040541 0.013514 0.020270 0.324324 0.020270 \n", - "1157 0.006579 0.138158 0.092105 0.171053 0.000000 \n", - "1158 0.009677 0.012903 0.022581 0.206452 0.035484 \n", + "1726 0.030364 0.022267 0.044534 0.228745 0.010121 \n", + "1727 0.030303 0.015152 0.000000 0.287879 0.000000 \n", + "1728 0.028112 0.012048 0.020080 0.289157 0.012048 \n", + "1729 0.055556 0.055556 0.111111 0.277778 0.000000 \n", + "1730 0.010846 0.023861 0.041215 0.221258 0.026030 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", "0 0.000000 0.000000 \n", - "1 0.020161 0.012097 \n", + "1 0.015291 0.012232 \n", "2 0.000000 0.000000 \n", - "3 0.025070 0.002786 \n", + "3 0.016698 0.001855 \n", "4 0.041667 0.010417 \n", "... ... ... \n", - "1154 0.000000 0.000000 \n", - "1155 0.047619 0.000000 \n", - "1156 0.013514 0.013514 \n", - "1157 0.013158 0.000000 \n", - "1158 0.012903 0.016129 \n", + "1726 0.012146 0.000000 \n", + "1727 0.030303 0.000000 \n", + "1728 0.016064 0.008032 \n", + "1729 0.055556 0.000000 \n", + "1730 0.013015 0.013015 \n", "\n", - "[1159 rows x 122 columns]" + "[1731 rows x 122 columns]" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -2544,7 +2550,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "1db9f77f", "metadata": {}, "outputs": [], @@ -2556,7 +2562,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "f56df3ca", "metadata": {}, "outputs": [ @@ -2618,16 +2624,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 2\n", @@ -2642,13 +2648,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -2666,16 +2672,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 4\n", @@ -2714,16 +2720,16 @@ " 0.0\n", " 7.5\n", " ...\n", - " 0.012384\n", - " 0.003096\n", - " 0.012384\n", - " 0.006192\n", - " 0.003096\n", - " 0.027864\n", - " 0.408669\n", - " 0.015480\n", - " 0.012384\n", - " 0.003096\n", + " 0.010204\n", + " 0.002041\n", + " 0.014286\n", + " 0.004082\n", + " 0.010204\n", + " 0.020408\n", + " 0.357143\n", + " 0.016327\n", + " 0.014286\n", + " 0.004082\n", " \n", " \n", " ...\n", @@ -2750,11 +2756,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -2762,116 +2768,116 @@ " 0.5\n", " 5.5\n", " ...\n", - " 0.028846\n", - " 0.009615\n", - " 0.019231\n", - " 0.000000\n", - " 0.009615\n", - " 0.038462\n", - " 0.182692\n", - " 0.000000\n", - " 0.000000\n", + " 0.018219\n", + " 0.008097\n", + " 0.016194\n", + " 0.030364\n", + " 0.022267\n", + " 0.044534\n", + " 0.228745\n", + " 0.010121\n", + " 0.012146\n", " 0.000000\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.015152\n", + " 0.030303\n", + " 0.030303\n", + " 0.030303\n", + " 0.015152\n", + " 0.000000\n", + " 0.287879\n", + " 0.000000\n", + " 0.030303\n", + " 0.000000\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 0.048193\n", + " 0.016064\n", + " 0.008032\n", + " 0.028112\n", + " 0.012048\n", + " 0.020080\n", + " 0.289157\n", + " 0.012048\n", + " 0.016064\n", + " 0.008032\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.055556\n", + " 0.000000\n", + " 0.055556\n", + " 0.055556\n", + " 0.055556\n", + " 0.111111\n", + " 0.277778\n", + " 0.000000\n", + " 0.055556\n", + " 0.000000\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", + " 4.5\n", " ...\n", - " 0.000000\n", - " 0.000000\n", - " 0.095238\n", - " 0.047619\n", - " 0.000000\n", - " 0.000000\n", - " 0.142857\n", - " 0.000000\n", - " 0.047619\n", - " 0.000000\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 0.047297\n", - " 0.006757\n", - " 0.006757\n", - " 0.040541\n", - " 0.013514\n", - " 0.020270\n", - " 0.324324\n", - " 0.020270\n", - " 0.013514\n", - " 0.013514\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.026316\n", - " 0.006579\n", - " 0.046053\n", - " 0.006579\n", - " 0.138158\n", - " 0.092105\n", - " 0.171053\n", - " 0.000000\n", - " 0.013158\n", - " 0.000000\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.019355\n", - " 0.012903\n", - " 0.032258\n", - " 0.009677\n", - " 0.012903\n", - " 0.022581\n", - " 0.206452\n", - " 0.035484\n", - " 0.012903\n", - " 0.016129\n", + " 0.030369\n", + " 0.008677\n", + " 0.028200\n", + " 0.010846\n", + " 0.023861\n", + " 0.041215\n", + " 0.221258\n", + " 0.026030\n", + " 0.013015\n", + " 0.013015\n", " \n", " \n", "\n", - "

1070 rows × 122 columns

\n", + "

1601 rows × 122 columns

\n", "" ], "text/plain": [ @@ -2882,55 +2888,55 @@ "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "5 1 Ruggeri Atalanta Sassuolo 0 6.5 0 1 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote ... miscontrols dispossessed fouls \\\n", - "1 0.0 6.5 ... 0.020161 0.012097 0.012097 \n", - "2 0.0 6.0 ... 0.007874 0.000000 0.007874 \n", - "3 0.0 6.5 ... 0.002786 0.002786 0.002786 \n", + "1 0.0 6.5 ... 0.018349 0.009174 0.009174 \n", + "2 0.0 6.0 ... 0.004608 0.000000 0.011521 \n", + "3 0.0 6.5 ... 0.009276 0.001855 0.009276 \n", "4 0.0 10.0 ... 0.000000 0.020833 0.031250 \n", - "5 0.0 7.5 ... 0.012384 0.003096 0.012384 \n", + "5 0.0 7.5 ... 0.010204 0.002041 0.014286 \n", "... ... ... ... ... ... ... \n", - "1154 0.5 5.5 ... 0.028846 0.009615 0.019231 \n", - "1155 0.5 5.5 ... 0.000000 0.000000 0.095238 \n", - "1156 0.0 6.0 ... 0.047297 0.006757 0.006757 \n", - "1157 0.0 5.5 ... 0.026316 0.006579 0.046053 \n", - "1158 0.0 5.5 ... 0.019355 0.012903 0.032258 \n", + "1726 0.5 5.5 ... 0.018219 0.008097 0.016194 \n", + "1727 0.0 6.0 ... 0.015152 0.030303 0.030303 \n", + "1728 0.0 5.5 ... 0.048193 0.016064 0.008032 \n", + "1729 0.0 6.0 ... 0.055556 0.000000 0.055556 \n", + "1730 0.5 4.5 ... 0.030369 0.008677 0.028200 \n", "\n", " fouled aerials_won aerials_lost carries progressive_carries \\\n", - "1 0.016129 0.008065 0.016129 0.391129 0.040323 \n", - "2 0.000000 0.019685 0.027559 0.350394 0.000000 \n", - "3 0.011142 0.013928 0.022284 0.412256 0.019499 \n", + "1 0.015291 0.009174 0.015291 0.376147 0.033639 \n", + "2 0.002304 0.034562 0.020737 0.299539 0.000000 \n", + "3 0.014842 0.016698 0.022263 0.378479 0.014842 \n", "4 0.000000 0.000000 0.010417 0.447917 0.062500 \n", - "5 0.006192 0.003096 0.027864 0.408669 0.015480 \n", + "5 0.004082 0.010204 0.020408 0.357143 0.016327 \n", "... ... ... ... ... ... \n", - "1154 0.000000 0.009615 0.038462 0.182692 0.000000 \n", - "1155 0.047619 0.000000 0.000000 0.142857 0.000000 \n", - "1156 0.040541 0.013514 0.020270 0.324324 0.020270 \n", - "1157 0.006579 0.138158 0.092105 0.171053 0.000000 \n", - "1158 0.009677 0.012903 0.022581 0.206452 0.035484 \n", + "1726 0.030364 0.022267 0.044534 0.228745 0.010121 \n", + "1727 0.030303 0.015152 0.000000 0.287879 0.000000 \n", + "1728 0.028112 0.012048 0.020080 0.289157 0.012048 \n", + "1729 0.055556 0.055556 0.111111 0.277778 0.000000 \n", + "1730 0.010846 0.023861 0.041215 0.221258 0.026030 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", - "1 0.020161 0.012097 \n", + "1 0.015291 0.012232 \n", "2 0.000000 0.000000 \n", - "3 0.025070 0.002786 \n", + "3 0.016698 0.001855 \n", "4 0.041667 0.010417 \n", - "5 0.012384 0.003096 \n", + "5 0.014286 0.004082 \n", "... ... ... \n", - "1154 0.000000 0.000000 \n", - "1155 0.047619 0.000000 \n", - "1156 0.013514 0.013514 \n", - "1157 0.013158 0.000000 \n", - "1158 0.012903 0.016129 \n", + "1726 0.012146 0.000000 \n", + "1727 0.030303 0.000000 \n", + "1728 0.016064 0.008032 \n", + "1729 0.055556 0.000000 \n", + "1730 0.013015 0.013015 \n", "\n", - "[1070 rows x 122 columns]" + "[1601 rows x 122 columns]" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -2949,7 +2955,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "df26c8e0", "metadata": {}, "outputs": [], @@ -2967,7 +2973,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "4d06576a", "metadata": {}, "outputs": [ @@ -3107,7 +3113,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "01bb7413", "metadata": {}, "outputs": [ @@ -3182,7 +3188,7 @@ " 'vs_team_aerials_won_pct']" ] }, - "execution_count": 19, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -3201,7 +3207,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "02f961d8", "metadata": {}, "outputs": [], @@ -3314,7 +3320,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "id": "5e3694a0", "metadata": {}, "outputs": [], @@ -3338,7 +3344,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "id": "9b671646", "metadata": {}, "outputs": [ @@ -3389,27 +3395,27 @@ " \n", " \n", " Consigli\n", - " 3\n", - " 3\n", - " 270\n", - " 1.67\n", + " 4.0\n", + " 4.0\n", + " 360\n", + " 1.5\n", " 66.7\n", " 0.0\n", - " -0.58\n", - " 23.9\n", - " 38.9\n", - " 37.1\n", + " -0.47\n", + " 26.1\n", + " 45.7\n", + " 39.4\n", " ...\n", - " 3.3\n", - " 0.19\n", - " -1.7\n", - " 11.0\n", - " 46.0\n", - " 95.0\n", - " 10.0\n", - " 34.0\n", - " 46.0\n", - " 2.0\n", + " 4.1\n", + " 0.21\n", + " -1.9\n", + " 18.0\n", + " 69.0\n", + " 127.0\n", + " 14.0\n", + " 42.0\n", + " 73.0\n", + " 4.0\n", " \n", " \n", "\n", @@ -3418,30 +3424,30 @@ ], "text/plain": [ " gk_games gk_games_starts gk_minutes gk_goals_against_per90 \\\n", - "Consigli 3 3 270 1.67 \n", + "Consigli 4.0 4.0 360 1.5 \n", "\n", " gk_save_pct gk_clean_sheets_pct gk_psxg_net_per90 \\\n", - "Consigli 66.7 0.0 -0.58 \n", + "Consigli 66.7 0.0 -0.47 \n", "\n", " gk_passes_pct_launched gk_pct_passes_launched \\\n", - "Consigli 23.9 38.9 \n", + "Consigli 26.1 45.7 \n", "\n", " gk_passes_length_avg ... gk_psxg \\\n", - "Consigli 37.1 ... 3.3 \n", + "Consigli 39.4 ... 4.1 \n", "\n", " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "Consigli 0.19 -1.7 \n", + "Consigli 0.21 -1.9 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "Consigli 11.0 46.0 95.0 \n", + "Consigli 18.0 69.0 127.0 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "Consigli 10.0 34.0 46.0 2.0 \n", + "Consigli 14.0 42.0 73.0 4.0 \n", "\n", "[1 rows x 92 columns]" ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -3456,7 +3462,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "id": "33f805a9", "metadata": {}, "outputs": [ @@ -3475,7 +3481,13 @@ "800\n", "900\n", "1000\n", - "1100\n" + "1100\n", + "1200\n", + "1300\n", + "1400\n", + "1500\n", + "1600\n", + "1700\n" ] } ], @@ -3505,7 +3517,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "id": "4d484846", "metadata": {}, "outputs": [ @@ -3570,13 +3582,13 @@ " 2.1\n", " 0.21\n", " 0.1\n", - " 11.0\n", - " 34.0\n", - " 88.0\n", - " 18.0\n", - " 18.0\n", + " 14.0\n", + " 48.0\n", + " 119.0\n", + " 25.0\n", " 28.0\n", - " 2.0\n", + " 43.0\n", + " 4.0\n", " \n", " \n", " 1\n", @@ -3699,11 +3711,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -3723,89 +3735,89 @@ " NaN\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", + " 4.5\n", " ...\n", " NaN\n", " NaN\n", @@ -3820,7 +3832,7 @@ " \n", " \n", "\n", - "

1159 rows × 102 columns

\n", + "

1731 rows × 102 columns

\n", "" ], "text/plain": [ @@ -3831,68 +3843,68 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", - " cards_malus fantavote ... gk_psxg \\\n", - "0 0.0 6.5 ... 2.1 \n", - "1 0.0 6.5 ... NaN \n", - "2 0.0 6.0 ... NaN \n", - "3 0.0 6.5 ... NaN \n", - "4 0.0 10.0 ... NaN \n", - "... ... ... ... ... \n", - "1154 0.5 5.5 ... NaN \n", - "1155 0.5 5.5 ... NaN \n", - "1156 0.0 6.0 ... NaN \n", - "1157 0.0 5.5 ... NaN \n", - "1158 0.0 5.5 ... NaN \n", + " cards_malus fantavote ... gk_psxg \\\n", + "0 0.0 6.5 ... 2.1 \n", + "1 0.0 6.5 ... NaN \n", + "2 0.0 6.0 ... NaN \n", + "3 0.0 6.5 ... NaN \n", + "4 0.0 10.0 ... NaN \n", + "... ... ... ... ... \n", + "1726 0.5 5.5 ... NaN \n", + "1727 0.0 6.0 ... NaN \n", + "1728 0.0 5.5 ... NaN \n", + "1729 0.0 6.0 ... NaN \n", + "1730 0.5 4.5 ... NaN \n", "\n", - " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "0 0.21 0.1 \n", - "1 NaN NaN \n", - "2 NaN NaN \n", - "3 NaN NaN \n", - "4 NaN NaN \n", - "... ... ... \n", - "1154 NaN NaN \n", - "1155 NaN NaN \n", - "1156 NaN NaN \n", - "1157 NaN NaN \n", - "1158 NaN NaN \n", + " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", + "0 0.21 0.1 \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "... ... ... \n", + "1726 NaN NaN \n", + "1727 NaN NaN \n", + "1728 NaN NaN \n", + "1729 NaN NaN \n", + "1730 NaN NaN \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.0 34.0 88.0 \n", + "0 14.0 48.0 119.0 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN \n", "... ... ... ... \n", - "1154 NaN NaN NaN \n", - "1155 NaN NaN NaN \n", - "1156 NaN NaN NaN \n", - "1157 NaN NaN NaN \n", - "1158 NaN NaN NaN \n", + "1726 NaN NaN NaN \n", + "1727 NaN NaN NaN \n", + "1728 NaN NaN NaN \n", + "1729 NaN NaN NaN \n", + "1730 NaN NaN NaN \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.0 18.0 28.0 2.0 \n", + "0 25.0 28.0 43.0 4.0 \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "... ... ... ... ... \n", - "1154 NaN NaN NaN NaN \n", - "1155 NaN NaN NaN NaN \n", - "1156 NaN NaN NaN NaN \n", - "1157 NaN NaN NaN NaN \n", - "1158 NaN NaN NaN NaN \n", + "1726 NaN NaN NaN NaN \n", + "1727 NaN NaN NaN NaN \n", + "1728 NaN NaN NaN NaN \n", + "1729 NaN NaN NaN NaN \n", + "1730 NaN NaN NaN NaN \n", "\n", - "[1159 rows x 102 columns]" + "[1731 rows x 102 columns]" ] }, - "execution_count": 24, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -3903,7 +3915,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "id": "adab3577", "metadata": {}, "outputs": [], @@ -3913,7 +3925,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "id": "e7ae792d", "metadata": {}, "outputs": [ @@ -3975,16 +3987,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 2.1\n", - " 0.21\n", + " 2.100000\n", + " 0.210000\n", " 0.1\n", - " 11.0\n", - " 34.0\n", - " 88.0\n", - " 18.0\n", - " 18.0\n", - " 28.0\n", - " 2.0\n", + " 14.000000\n", + " 48.000000\n", + " 119.0\n", + " 25.000000\n", + " 28.000000\n", + " 43.000000\n", + " 4.0\n", " \n", " \n", " 16\n", @@ -3999,16 +4011,16 @@ " 0.0\n", " 4.0\n", " ...\n", - " 3.2\n", - " 0.32\n", - " -0.8\n", - " 17.0\n", - " 45.0\n", - " 106.0\n", - " 17.0\n", - " 22.0\n", - " 57.0\n", - " 2.0\n", + " 4.200000\n", + " 0.250000\n", + " 0.2\n", + " 28.000000\n", + " 60.000000\n", + " 159.0\n", + " 25.000000\n", + " 34.000000\n", + " 89.000000\n", + " 3.0\n", " \n", " \n", " 29\n", @@ -4023,16 +4035,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 4.1\n", - " 0.33\n", - " 0.1\n", - " 24.0\n", - " 54.0\n", - " 76.0\n", - " 18.0\n", - " 40.0\n", - " 62.0\n", - " 4.0\n", + " 8.700000\n", + " 0.360000\n", + " -0.3\n", + " 33.000000\n", + " 80.000000\n", + " 124.0\n", + " 23.000000\n", + " 57.000000\n", + " 87.000000\n", + " 5.0\n", " \n", " \n", " 44\n", @@ -4047,15 +4059,15 @@ " 0.0\n", " 4.0\n", " ...\n", - " 0.4\n", - " 0.11\n", - " -0.6\n", - " 4.0\n", - " 20.0\n", - " 37.0\n", - " 9.0\n", - " 4.0\n", - " 10.0\n", + " 4.933333\n", + " 0.203333\n", + " -1.4\n", + " 8.666667\n", + " 38.666667\n", + " 83.0\n", + " 17.666667\n", + " 17.333333\n", + " 36.666667\n", " 2.0\n", " \n", " \n", @@ -4071,16 +4083,16 @@ " 0.0\n", " 5.0\n", " ...\n", - " 1.0\n", - " 0.17\n", - " -2.0\n", - " 13.0\n", - " 20.0\n", - " 85.0\n", - " 10.0\n", - " 9.0\n", - " 16.0\n", - " 1.0\n", + " 4.100000\n", + " 0.240000\n", + " 0.1\n", + " 28.000000\n", + " 57.000000\n", + " 151.0\n", + " 14.000000\n", + " 22.000000\n", + " 44.000000\n", + " 3.0\n", " \n", " \n", " ...\n", @@ -4107,200 +4119,200 @@ " ...\n", " \n", " \n", - " 1085\n", - " 4\n", + " 1657\n", + " 6\n", " Ochoa\n", " Salernitana\n", - " Torino\n", - " 1\n", - " 5.0\n", - " -3\n", + " Empoli\n", + " 0\n", + " 6.5\n", + " -1\n", " 0\n", " 0.0\n", - " 2.0\n", + " 5.5\n", " ...\n", - " 4.7\n", - " 0.21\n", - " -3.3\n", - " 13.0\n", - " 55.0\n", - " 89.0\n", - " 14.0\n", - " 35.0\n", - " 63.0\n", + " 6.800000\n", + " 0.220000\n", + " -3.2\n", + " 20.000000\n", + " 85.000000\n", + " 160.0\n", + " 22.000000\n", + " 47.000000\n", + " 88.000000\n", " 4.0\n", " \n", " \n", - " 1101\n", - " 4\n", - " Cragno\n", + " 1672\n", + " 6\n", + " Consigli\n", " Sassuolo\n", - " Frosinone\n", + " Inter\n", " 0\n", " 6.5\n", + " -1\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 4.100000\n", + " 0.210000\n", + " -1.9\n", + " 18.000000\n", + " 69.000000\n", + " 127.0\n", + " 14.000000\n", + " 42.000000\n", + " 73.000000\n", + " 4.0\n", + " \n", + " \n", + " 1686\n", + " 6\n", + " Milinkovic-Savic V.\n", + " Torino\n", + " Lazio\n", + " 0\n", + " 6.0\n", + " -2\n", + " 0\n", + " 0.0\n", + " 4.0\n", + " ...\n", + " 5.800000\n", + " 0.180000\n", + " -1.2\n", + " 42.000000\n", + " 117.000000\n", + " 193.0\n", + " 37.000000\n", + " 50.000000\n", + " 47.000000\n", + " 4.0\n", + " \n", + " \n", + " 1700\n", + " 6\n", + " Silvestri\n", + " Udinese\n", + " Napoli\n", + " 0\n", + " 5.5\n", " -4\n", " 0\n", " 0.0\n", - " 2.5\n", + " 1.5\n", " ...\n", - " 2.8\n", - " 0.30\n", - " -1.2\n", - " 5.0\n", - " 15.0\n", - " 24.0\n", - " 3.0\n", - " 9.0\n", - " 9.0\n", - " 0.0\n", + " 10.100000\n", + " 0.370000\n", + " 0.1\n", + " 19.000000\n", + " 50.000000\n", + " 132.0\n", + " 23.000000\n", + " 45.000000\n", + " 69.000000\n", + " 1.0\n", " \n", " \n", - " 1117\n", - " 4\n", - " Milinkovic-Savic V.\n", - " Torino\n", - " Salernitana\n", - " 0\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 4.6\n", - " 0.18\n", - " 0.6\n", - " 29.0\n", - " 79.0\n", - " 117.0\n", - " 23.0\n", - " 36.0\n", - " 33.0\n", - " 3.0\n", - " \n", - " \n", - " 1129\n", - " 4\n", - " Silvestri\n", - " Udinese\n", - " Cagliari\n", - " 0\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 3.9\n", - " 0.29\n", - " -0.1\n", - " 11.0\n", - " 34.0\n", - " 94.0\n", - " 14.0\n", - " 32.0\n", - " 49.0\n", - " 0.0\n", - " \n", - " \n", - " 1143\n", - " 4\n", + " 1716\n", + " 6\n", " Montipo'\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", - " 7.0\n", - " 0\n", + " 6.0\n", + " -1\n", " 0\n", " 0.0\n", - " 7.0\n", + " 5.0\n", " ...\n", - " 4.9\n", - " 0.19\n", - " 0.9\n", - " 35.0\n", - " 93.0\n", - " 109.0\n", - " 8.0\n", - " 35.0\n", - " 54.0\n", + " 6.700000\n", + " 0.210000\n", + " 0.7\n", + " 55.000000\n", + " 156.000000\n", + " 183.0\n", + " 16.000000\n", + " 50.000000\n", + " 72.000000\n", " 1.0\n", " \n", " \n", "\n", - "

80 rows × 102 columns

\n", + "

120 rows × 102 columns

\n", "" ], "text/plain": [ - " matchday player team oppteam home vote \\\n", - "0 1 Musso Atalanta Sassuolo 0 6.5 \n", - "16 1 Skorupski Bologna Milan 1 6.0 \n", - "29 1 Radunovic Cagliari Torino 0 6.5 \n", - "44 1 Caprile Empoli Verona 1 5.0 \n", - "57 1 Terracciano Fiorentina Genoa 0 6.0 \n", - "... ... ... ... ... ... ... \n", - "1085 4 Ochoa Salernitana Torino 1 5.0 \n", - "1101 4 Cragno Sassuolo Frosinone 0 6.5 \n", - "1117 4 Milinkovic-Savic V. Torino Salernitana 0 6.0 \n", - "1129 4 Silvestri Udinese Cagliari 0 6.0 \n", - "1143 4 Montipo' Verona Bologna 1 7.0 \n", + " matchday player team oppteam home vote goals \\\n", + "0 1 Musso Atalanta Sassuolo 0 6.5 0 \n", + "16 1 Skorupski Bologna Milan 1 6.0 -2 \n", + "29 1 Radunovic Cagliari Torino 0 6.5 0 \n", + "44 1 Caprile Empoli Verona 1 5.0 -1 \n", + "57 1 Terracciano Fiorentina Genoa 0 6.0 -1 \n", + "... ... ... ... ... ... ... ... \n", + "1657 6 Ochoa Salernitana Empoli 0 6.5 -1 \n", + "1672 6 Consigli Sassuolo Inter 0 6.5 -1 \n", + "1686 6 Milinkovic-Savic V. Torino Lazio 0 6.0 -2 \n", + "1700 6 Silvestri Udinese Napoli 0 5.5 -4 \n", + "1716 6 Montipo' Verona Atalanta 1 6.0 -1 \n", "\n", - " goals assists cards_malus fantavote ... gk_psxg \\\n", - "0 0 0 0.0 6.5 ... 2.1 \n", - "16 -2 0 0.0 4.0 ... 3.2 \n", - "29 0 0 0.0 6.5 ... 4.1 \n", - "44 -1 0 0.0 4.0 ... 0.4 \n", - "57 -1 0 0.0 5.0 ... 1.0 \n", - "... ... ... ... ... ... ... \n", - "1085 -3 0 0.0 2.0 ... 4.7 \n", - "1101 -4 0 0.0 2.5 ... 2.8 \n", - "1117 0 0 0.0 6.0 ... 4.6 \n", - "1129 0 0 0.0 6.0 ... 3.9 \n", - "1143 0 0 0.0 7.0 ... 4.9 \n", + " assists cards_malus fantavote ... gk_psxg \\\n", + "0 0 0.0 6.5 ... 2.100000 \n", + "16 0 0.0 4.0 ... 4.200000 \n", + "29 0 0.0 6.5 ... 8.700000 \n", + "44 0 0.0 4.0 ... 4.933333 \n", + "57 0 0.0 5.0 ... 4.100000 \n", + "... ... ... ... ... ... \n", + "1657 0 0.0 5.5 ... 6.800000 \n", + "1672 0 0.0 5.5 ... 4.100000 \n", + "1686 0 0.0 4.0 ... 5.800000 \n", + "1700 0 0.0 1.5 ... 10.100000 \n", + "1716 0 0.0 5.0 ... 6.700000 \n", "\n", - " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "0 0.21 0.1 \n", - "16 0.32 -0.8 \n", - "29 0.33 0.1 \n", - "44 0.11 -0.6 \n", - "57 0.17 -2.0 \n", - "... ... ... \n", - "1085 0.21 -3.3 \n", - "1101 0.30 -1.2 \n", - "1117 0.18 0.6 \n", - "1129 0.29 -0.1 \n", - "1143 0.19 0.9 \n", + " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", + "0 0.210000 0.1 \n", + "16 0.250000 0.2 \n", + "29 0.360000 -0.3 \n", + "44 0.203333 -1.4 \n", + "57 0.240000 0.1 \n", + "... ... ... \n", + "1657 0.220000 -3.2 \n", + "1672 0.210000 -1.9 \n", + "1686 0.180000 -1.2 \n", + "1700 0.370000 0.1 \n", + "1716 0.210000 0.7 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.0 34.0 88.0 \n", - "16 17.0 45.0 106.0 \n", - "29 24.0 54.0 76.0 \n", - "44 4.0 20.0 37.0 \n", - "57 13.0 20.0 85.0 \n", + "0 14.000000 48.000000 119.0 \n", + "16 28.000000 60.000000 159.0 \n", + "29 33.000000 80.000000 124.0 \n", + "44 8.666667 38.666667 83.0 \n", + "57 28.000000 57.000000 151.0 \n", "... ... ... ... \n", - "1085 13.0 55.0 89.0 \n", - "1101 5.0 15.0 24.0 \n", - "1117 29.0 79.0 117.0 \n", - "1129 11.0 34.0 94.0 \n", - "1143 35.0 93.0 109.0 \n", + "1657 20.000000 85.000000 160.0 \n", + "1672 18.000000 69.000000 127.0 \n", + "1686 42.000000 117.000000 193.0 \n", + "1700 19.000000 50.000000 132.0 \n", + "1716 55.000000 156.000000 183.0 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.0 18.0 28.0 2.0 \n", - "16 17.0 22.0 57.0 2.0 \n", - "29 18.0 40.0 62.0 4.0 \n", - "44 9.0 4.0 10.0 2.0 \n", - "57 10.0 9.0 16.0 1.0 \n", + "0 25.000000 28.000000 43.000000 4.0 \n", + "16 25.000000 34.000000 89.000000 3.0 \n", + "29 23.000000 57.000000 87.000000 5.0 \n", + "44 17.666667 17.333333 36.666667 2.0 \n", + "57 14.000000 22.000000 44.000000 3.0 \n", "... ... ... ... ... \n", - "1085 14.0 35.0 63.0 4.0 \n", - "1101 3.0 9.0 9.0 0.0 \n", - "1117 23.0 36.0 33.0 3.0 \n", - "1129 14.0 32.0 49.0 0.0 \n", - "1143 8.0 35.0 54.0 1.0 \n", + "1657 22.000000 47.000000 88.000000 4.0 \n", + "1672 14.000000 42.000000 73.000000 4.0 \n", + "1686 37.000000 50.000000 47.000000 4.0 \n", + "1700 23.000000 45.000000 69.000000 1.0 \n", + "1716 16.000000 50.000000 72.000000 1.0 \n", "\n", - "[80 rows x 102 columns]" + "[120 rows x 102 columns]" ] }, - "execution_count": 26, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -4319,7 +4331,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "id": "d8b8b6da", "metadata": {}, "outputs": [], @@ -4329,7 +4341,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "id": "54519b24", "metadata": {}, "outputs": [ diff --git a/.ipynb_checkpoints/5_scraping_match_probable_players-checkpoint.ipynb b/.ipynb_checkpoints/5_scraping_match_probable_players-checkpoint.ipynb index 4d57e90..2561ce8 100644 --- a/.ipynb_checkpoints/5_scraping_match_probable_players-checkpoint.ipynb +++ b/.ipynb_checkpoints/5_scraping_match_probable_players-checkpoint.ipynb @@ -71,33 +71,33 @@ " \n", " \n", " 0\n", - " Ochoa\n", + " Falcone\n", " 1\n", " 90.0\n", " \n", " \n", " 1\n", - " Lovato\n", + " Gendrey\n", " 1\n", - " 80.0\n", + " 90.0\n", " \n", " \n", " 2\n", - " Gyomber\n", + " Baschirotto\n", " 1\n", - " 80.0\n", + " 90.0\n", " \n", " \n", " 3\n", - " Pirola\n", + " Pongracic\n", " 1\n", " 80.0\n", " \n", " \n", " 4\n", - " Mazzocchi\n", + " Gallo\n", " 1\n", - " 80.0\n", + " 60.0\n", " \n", " \n", " ...\n", @@ -106,55 +106,55 @@ " ...\n", " \n", " \n", - " 471\n", - " Pisilli\n", + " 462\n", + " Oristanio\n", + " 0\n", + " 50.0\n", + " \n", + " \n", + " 463\n", + " Jankto\n", + " 0\n", + " 15.0\n", + " \n", + " \n", + " 464\n", + " Mancosu\n", " 0\n", " 10.0\n", " \n", " \n", - " 472\n", - " Aouar\n", + " 465\n", + " Pavoletti\n", " 0\n", " 55.0\n", " \n", " \n", - " 473\n", - " El Shaarawy\n", - " 0\n", - " 55.0\n", - " \n", - " \n", - " 474\n", - " Belotti\n", + " 466\n", + " Shomurodov\n", " 0\n", " 60.0\n", " \n", - " \n", - " 475\n", - " Azmoun\n", - " 0\n", - " 35.0\n", - " \n", " \n", "\n", - "

476 rows × 3 columns

\n", + "

467 rows × 3 columns

\n", "" ], "text/plain": [ " player starter percentage\n", - "0 Ochoa 1 90.0\n", - "1 Lovato 1 80.0\n", - "2 Gyomber 1 80.0\n", - "3 Pirola 1 80.0\n", - "4 Mazzocchi 1 80.0\n", + "0 Falcone 1 90.0\n", + "1 Gendrey 1 90.0\n", + "2 Baschirotto 1 90.0\n", + "3 Pongracic 1 80.0\n", + "4 Gallo 1 60.0\n", ".. ... ... ...\n", - "471 Pisilli 0 10.0\n", - "472 Aouar 0 55.0\n", - "473 El Shaarawy 0 55.0\n", - "474 Belotti 0 60.0\n", - "475 Azmoun 0 35.0\n", + "462 Oristanio 0 50.0\n", + "463 Jankto 0 15.0\n", + "464 Mancosu 0 10.0\n", + "465 Pavoletti 0 55.0\n", + "466 Shomurodov 0 60.0\n", "\n", - "[476 rows x 3 columns]" + "[467 rows x 3 columns]" ] }, "execution_count": 3, @@ -235,302 +235,356 @@ " \n", " \n", " 0\n", - " Ikwuemesi\n", - " Botheim\n", - " 55.0\n", + " Gallo\n", + " Dorgu\n", + " 60.0\n", " \n", " \n", " 1\n", - " Jovane\n", - " Kastanos\n", - " 55.0\n", + " Blin\n", + " Gonzalez J.\n", + " 60.0\n", " \n", " \n", " 2\n", - " Okoli\n", - " Monterisi\n", - " 55.0\n", + " Politano\n", + " Lindstrom\n", + " 60.0\n", " \n", " \n", " 3\n", - " Caso\n", - " Baez\n", - " 55.0\n", + " Zambo Anguissa\n", + " Cajuste\n", + " 60.0\n", " \n", " \n", " 4\n", - " Vasquez\n", - " Martin\n", - " 60.0\n", + " Zielinski\n", + " Raspadori\n", + " 55.0\n", " \n", " \n", " 5\n", - " Malinovskyi\n", - " De Winter\n", - " 60.0\n", - " \n", - " \n", - " 6\n", - " Kjaer\n", - " Thiaw\n", - " 60.0\n", - " \n", - " \n", - " 7\n", - " Rafael Leao\n", - " Chukwueze\n", - " 60.0\n", - " \n", - " \n", - " 8\n", - " Giroud\n", - " Jovic\n", - " 60.0\n", - " \n", - " \n", - " 9\n", - " Bonazzoli\n", - " Djuric\n", - " 60.0\n", - " \n", - " \n", - " 10\n", - " Mboula\n", - " Folorunsho\n", - " 55.0\n", - " \n", - " \n", - " 11\n", - " Tressoldi\n", - " Viti\n", - " 60.0\n", - " \n", - " \n", - " 12\n", - " Vina\n", - " Pedersen\n", - " 65.0\n", - " \n", - " \n", - " 13\n", - " Bajrami\n", - " Thorstvedt\n", - " 60.0\n", - " \n", - " \n", - " 14\n", - " Fagioli\n", - " Miretti\n", - " 60.0\n", - " \n", - " \n", - " 15\n", - " Mckennie\n", - " Weah\n", - " 55.0\n", - " \n", - " \n", - " 16\n", - " Zaccagni\n", - " Pedro\n", - " 60.0\n", - " \n", - " \n", - " 17\n", - " Romagnoli\n", - " Patric\n", - " 60.0\n", - " \n", - " \n", - " 18\n", - " Guendouzi\n", - " Kamada\n", - " 55.0\n", - " \n", - " \n", - " 19\n", - " Birindelli\n", - " Kyriakopoulos\n", - " 65.0\n", - " \n", - " \n", - " 20\n", - " Maleh\n", - " Bastoni S.\n", - " 55.0\n", - " \n", - " \n", - " 21\n", - " Fazzini\n", - " Grassi\n", - " 60.0\n", - " \n", - " \n", - " 22\n", - " Bereszynski\n", - " Ebuehi\n", - " 60.0\n", - " \n", - " \n", - " 23\n", - " Thuram\n", - " Arnautovic\n", - " 60.0\n", - " \n", - " \n", - " 24\n", - " Dimarco\n", - " Carlos Augusto\n", - " 55.0\n", - " \n", - " \n", - " 25\n", - " Pavard\n", - " Darmian\n", - " 60.0\n", - " \n", - " \n", - " 26\n", - " De Vrij\n", - " Acerbi\n", - " 60.0\n", - " \n", - " \n", - " 27\n", - " Frattesi\n", - " Mkhitaryan\n", - " 65.0\n", - " \n", - " \n", - " 28\n", - " Zappacosta\n", - " Zortea\n", - " 60.0\n", - " \n", - " \n", - " 29\n", - " Ruggeri\n", - " Bakker\n", - " 60.0\n", - " \n", - " \n", - " 30\n", - " Toloi\n", - " Djimsiti\n", - " 55.0\n", - " \n", - " \n", - " 31\n", - " Jankto\n", - " Deiola\n", - " 55.0\n", - " \n", - " \n", - " 32\n", - " Obert\n", - " Prati\n", - " 55.0\n", - " \n", - " \n", - " 33\n", - " Ebosele\n", - " Ferreira J.\n", - " 60.0\n", - " \n", - " \n", - " 34\n", - " Kamara H.\n", - " Zemura\n", - " 60.0\n", - " \n", - " \n", - " 35\n", - " Nzola\n", - " Beltran L.\n", - " 60.0\n", - " \n", - " \n", - " 36\n", - " Mandragora\n", - " Duncan\n", - " 55.0\n", - " \n", - " \n", - " 37\n", - " Ranieri L.\n", - " Martinez Quarta\n", - " 55.0\n", - " \n", - " \n", - " 38\n", - " Kouame'\n", - " Sottil\n", - " 55.0\n", - " \n", - " \n", - " 39\n", - " Moro N.\n", - " Aebischer\n", - " 55.0\n", - " \n", - " \n", - " 40\n", - " Ndoye\n", - " Orsolini\n", - " 55.0\n", - " \n", - " \n", - " 41\n", - " Zielinski\n", + " Kvaratskhelia\n", " Elmas\n", " 65.0\n", " \n", " \n", - " 42\n", - " Juan Jesus\n", - " Natan\n", - " 55.0\n", - " \n", - " \n", - " 43\n", - " Politano\n", - " Raspadori\n", - " 60.0\n", - " \n", - " \n", - " 44\n", + " 6\n", " Mario Rui\n", " Olivera\n", " 55.0\n", " \n", " \n", - " 45\n", - " Vlasic\n", - " Seck\n", - " 65.0\n", - " \n", - " \n", - " 46\n", - " Ilic\n", - " Tameze\n", + " 7\n", + " Calabria\n", + " Florenzi\n", " 55.0\n", " \n", " \n", - " 47\n", - " Paredes\n", - " Aouar\n", + " 8\n", + " Pulisic\n", + " Chukwueze\n", + " 55.0\n", + " \n", + " \n", + " 9\n", + " Reijnders\n", + " Musah\n", + " 65.0\n", + " \n", + " \n", + " 10\n", + " Romagnoli\n", + " Patric\n", + " 65.0\n", + " \n", + " \n", + " 11\n", + " Pellegrini Lu.\n", + " Marusic\n", + " 65.0\n", + " \n", + " \n", + " 12\n", + " Immobile\n", + " Castellanos\n", " 60.0\n", " \n", " \n", - " 48\n", - " Kristensen\n", + " 13\n", + " Luis Alberto\n", + " Guendouzi\n", + " 60.0\n", + " \n", + " \n", + " 14\n", + " Daniliuc\n", + " Lovato\n", + " 60.0\n", + " \n", + " \n", + " 15\n", + " Legowski\n", + " Bohinen\n", + " 60.0\n", + " \n", + " \n", + " 16\n", + " Martegani\n", + " Dia\n", + " 60.0\n", + " \n", + " \n", + " 17\n", + " Mkhitaryan\n", + " Klaassen\n", + " 55.0\n", + " \n", + " \n", + " 18\n", + " Sanchez\n", + " Martinez L.\n", + " 55.0\n", + " \n", + " \n", + " 19\n", + " Acerbi\n", + " Bastoni\n", + " 55.0\n", + " \n", + " \n", + " 20\n", + " Moro N.\n", + " Fabbian\n", + " 55.0\n", + " \n", + " \n", + " 21\n", + " Ferguson\n", + " Aebischer\n", + " 60.0\n", + " \n", + " \n", + " 22\n", + " Ndoye\n", + " Orsolini\n", + " 60.0\n", + " \n", + " \n", + " 23\n", + " Cancellieri\n", + " Shpendi S.\n", + " 60.0\n", + " \n", + " \n", + " 24\n", + " Fazzini\n", + " Ranocchia F.\n", + " 60.0\n", + " \n", + " \n", + " 25\n", + " Grassi\n", + " Marin\n", + " 60.0\n", + " \n", + " \n", + " 26\n", + " Success\n", + " Lucca\n", + " 55.0\n", + " \n", + " \n", + " 27\n", + " Ebosele\n", + " Ferreira J.\n", + " 60.0\n", + " \n", + " \n", + " 28\n", + " Kamara H.\n", + " Zemura\n", + " 60.0\n", + " \n", + " \n", + " 29\n", + " Martin\n", + " Matturro\n", + " 55.0\n", + " \n", + " \n", + " 30\n", + " Pasalic\n", + " Muriel\n", + " 60.0\n", + " \n", + " \n", + " 31\n", + " Ruggeri\n", + " Holm\n", + " 55.0\n", + " \n", + " \n", + " 32\n", + " Mckennie\n", + " Weah\n", + " 60.0\n", + " \n", + " \n", + " 33\n", + " Fagioli\n", + " Miretti\n", + " 60.0\n", + " \n", + " \n", + " 34\n", + " Chiesa\n", + " Milik\n", + " 55.0\n", + " \n", + " \n", + " 35\n", + " Dybala\n", + " El Shaarawy\n", + " 65.0\n", + " \n", + " \n", + " 36\n", + " Zalewski\n", + " Spinazzola\n", + " 55.0\n", + " \n", + " \n", + " 37\n", + " Paredes\n", " Celik\n", " 60.0\n", " \n", " \n", + " 38\n", + " Caso\n", + " Baez\n", + " 60.0\n", + " \n", + " \n", + " 39\n", + " Brescianini\n", + " Garritano\n", + " 60.0\n", + " \n", + " \n", + " 40\n", + " Romagnoli S.\n", + " Monterisi\n", + " 60.0\n", + " \n", + " \n", + " 41\n", + " Vina\n", + " Pedersen\n", + " 55.0\n", + " \n", + " \n", + " 42\n", + " Erlic\n", + " Viti\n", + " 60.0\n", + " \n", + " \n", + " 43\n", + " Bajrami\n", + " Castillejo\n", + " 60.0\n", + " \n", + " \n", + " 44\n", + " Colombo\n", + " Maric\n", + " 65.0\n", + " \n", + " \n", + " 45\n", + " Izzo\n", + " D'ambrosio\n", + " 60.0\n", + " \n", + " \n", + " 46\n", + " Birindelli\n", + " Kyriakopoulos\n", + " 60.0\n", + " \n", + " \n", + " 47\n", + " Bellanova\n", + " Soppy\n", + " 60.0\n", + " \n", + " \n", + " 48\n", + " Lazaro\n", + " Vojvoda\n", + " 60.0\n", + " \n", + " \n", " 49\n", - " Spinazzola\n", - " Zalewski\n", + " Zapata D.\n", + " Sanabria\n", + " 55.0\n", + " \n", + " \n", + " 50\n", + " Bonazzoli\n", + " Henry\n", + " 60.0\n", + " \n", + " \n", + " 51\n", + " Magnani\n", + " Coppola D.\n", + " 60.0\n", + " \n", + " \n", + " 52\n", + " Folorunsho\n", + " Saponara\n", + " 55.0\n", + " \n", + " \n", + " 53\n", + " Bonaventura\n", + " Barak\n", + " 60.0\n", + " \n", + " \n", + " 54\n", + " Lopez M.\n", + " Arthur Melo\n", + " 55.0\n", + " \n", + " \n", + " 55\n", + " Nzola\n", + " Beltran L.\n", + " 55.0\n", + " \n", + " \n", + " 56\n", + " Nandez\n", + " Deiola\n", + " 60.0\n", + " \n", + " \n", + " 57\n", + " Petagna\n", + " Shomurodov\n", + " 60.0\n", + " \n", + " \n", + " 58\n", + " Hatzidiakos\n", + " Obert\n", " 60.0\n", " \n", " \n", @@ -538,57 +592,66 @@ "" ], "text/plain": [ - " player1 player2 percentage\n", - "0 Ikwuemesi Botheim 55.0\n", - "1 Jovane Kastanos 55.0\n", - "2 Okoli Monterisi 55.0\n", - "3 Caso Baez 55.0\n", - "4 Vasquez Martin 60.0\n", - "5 Malinovskyi De Winter 60.0\n", - "6 Kjaer Thiaw 60.0\n", - "7 Rafael Leao Chukwueze 60.0\n", - "8 Giroud Jovic 60.0\n", - "9 Bonazzoli Djuric 60.0\n", - "10 Mboula Folorunsho 55.0\n", - "11 Tressoldi Viti 60.0\n", - "12 Vina Pedersen 65.0\n", - "13 Bajrami Thorstvedt 60.0\n", - "14 Fagioli Miretti 60.0\n", - "15 Mckennie Weah 55.0\n", - "16 Zaccagni Pedro 60.0\n", - "17 Romagnoli Patric 60.0\n", - "18 Guendouzi Kamada 55.0\n", - "19 Birindelli Kyriakopoulos 65.0\n", - "20 Maleh Bastoni S. 55.0\n", - "21 Fazzini Grassi 60.0\n", - "22 Bereszynski Ebuehi 60.0\n", - "23 Thuram Arnautovic 60.0\n", - "24 Dimarco Carlos Augusto 55.0\n", - "25 Pavard Darmian 60.0\n", - "26 De Vrij Acerbi 60.0\n", - "27 Frattesi Mkhitaryan 65.0\n", - "28 Zappacosta Zortea 60.0\n", - "29 Ruggeri Bakker 60.0\n", - "30 Toloi Djimsiti 55.0\n", - "31 Jankto Deiola 55.0\n", - "32 Obert Prati 55.0\n", - "33 Ebosele Ferreira J. 60.0\n", - "34 Kamara H. Zemura 60.0\n", - "35 Nzola Beltran L. 60.0\n", - "36 Mandragora Duncan 55.0\n", - "37 Ranieri L. Martinez Quarta 55.0\n", - "38 Kouame' Sottil 55.0\n", - "39 Moro N. Aebischer 55.0\n", - "40 Ndoye Orsolini 55.0\n", - "41 Zielinski Elmas 65.0\n", - "42 Juan Jesus Natan 55.0\n", - "43 Politano Raspadori 60.0\n", - "44 Mario Rui Olivera 55.0\n", - "45 Vlasic Seck 65.0\n", - "46 Ilic Tameze 55.0\n", - "47 Paredes Aouar 60.0\n", - "48 Kristensen Celik 60.0\n", - "49 Spinazzola Zalewski 60.0" + " player1 player2 percentage\n", + "0 Gallo Dorgu 60.0\n", + "1 Blin Gonzalez J. 60.0\n", + "2 Politano Lindstrom 60.0\n", + "3 Zambo Anguissa Cajuste 60.0\n", + "4 Zielinski Raspadori 55.0\n", + "5 Kvaratskhelia Elmas 65.0\n", + "6 Mario Rui Olivera 55.0\n", + "7 Calabria Florenzi 55.0\n", + "8 Pulisic Chukwueze 55.0\n", + "9 Reijnders Musah 65.0\n", + "10 Romagnoli Patric 65.0\n", + "11 Pellegrini Lu. Marusic 65.0\n", + "12 Immobile Castellanos 60.0\n", + "13 Luis Alberto Guendouzi 60.0\n", + "14 Daniliuc Lovato 60.0\n", + "15 Legowski Bohinen 60.0\n", + "16 Martegani Dia 60.0\n", + "17 Mkhitaryan Klaassen 55.0\n", + "18 Sanchez Martinez L. 55.0\n", + "19 Acerbi Bastoni 55.0\n", + "20 Moro N. Fabbian 55.0\n", + "21 Ferguson Aebischer 60.0\n", + "22 Ndoye Orsolini 60.0\n", + "23 Cancellieri Shpendi S. 60.0\n", + "24 Fazzini Ranocchia F. 60.0\n", + "25 Grassi Marin 60.0\n", + "26 Success Lucca 55.0\n", + "27 Ebosele Ferreira J. 60.0\n", + "28 Kamara H. Zemura 60.0\n", + "29 Martin Matturro 55.0\n", + "30 Pasalic Muriel 60.0\n", + "31 Ruggeri Holm 55.0\n", + "32 Mckennie Weah 60.0\n", + "33 Fagioli Miretti 60.0\n", + "34 Chiesa Milik 55.0\n", + "35 Dybala El Shaarawy 65.0\n", + "36 Zalewski Spinazzola 55.0\n", + "37 Paredes Celik 60.0\n", + "38 Caso Baez 60.0\n", + "39 Brescianini Garritano 60.0\n", + "40 Romagnoli S. Monterisi 60.0\n", + "41 Vina Pedersen 55.0\n", + "42 Erlic Viti 60.0\n", + "43 Bajrami Castillejo 60.0\n", + "44 Colombo Maric 65.0\n", + "45 Izzo D'ambrosio 60.0\n", + "46 Birindelli Kyriakopoulos 60.0\n", + "47 Bellanova Soppy 60.0\n", + "48 Lazaro Vojvoda 60.0\n", + "49 Zapata D. Sanabria 55.0\n", + "50 Bonazzoli Henry 60.0\n", + "51 Magnani Coppola D. 60.0\n", + "52 Folorunsho Saponara 55.0\n", + "53 Bonaventura Barak 60.0\n", + "54 Lopez M. Arthur Melo 55.0\n", + "55 Nzola Beltran L. 55.0\n", + "56 Nandez Deiola 60.0\n", + "57 Petagna Shomurodov 60.0\n", + "58 Hatzidiakos Obert 60.0" ] }, "execution_count": 5, @@ -653,29 +716,29 @@ " \n", " \n", " \n", - " Ochoa\n", + " Falcone\n", " 1\n", " 90.0\n", " \n", " \n", - " Lovato\n", + " Gendrey\n", + " 1\n", + " 90.0\n", + " \n", + " \n", + " Baschirotto\n", + " 1\n", + " 90.0\n", + " \n", + " \n", + " Pongracic\n", " 1\n", " 80.0\n", " \n", " \n", - " Gyomber\n", - " 1\n", - " 80.0\n", - " \n", - " \n", - " Pirola\n", - " 1\n", - " 80.0\n", - " \n", - " \n", - " Mazzocchi\n", - " 1\n", - " 80.0\n", + " Gallo\n", + " 0.6\n", + " 60.0\n", " \n", " \n", " ...\n", @@ -683,51 +746,51 @@ " ...\n", " \n", " \n", - " Pisilli\n", + " Oristanio\n", + " 0\n", + " 50.0\n", + " \n", + " \n", + " Jankto\n", + " 0\n", + " 15.0\n", + " \n", + " \n", + " Mancosu\n", " 0\n", " 10.0\n", " \n", " \n", - " Aouar\n", + " Pavoletti\n", + " 0\n", + " 55.0\n", + " \n", + " \n", + " Shomurodov\n", " 0.4\n", - " 55.0\n", - " \n", - " \n", - " El Shaarawy\n", - " 0\n", - " 55.0\n", - " \n", - " \n", - " Belotti\n", - " 0\n", " 60.0\n", " \n", - " \n", - " Azmoun\n", - " 0\n", - " 35.0\n", - " \n", " \n", "\n", - "

476 rows × 2 columns

\n", + "

467 rows × 2 columns

\n", "" ], "text/plain": [ " starter percentage\n", "player \n", - "Ochoa 1 90.0\n", - "Lovato 1 80.0\n", - "Gyomber 1 80.0\n", - "Pirola 1 80.0\n", - "Mazzocchi 1 80.0\n", + "Falcone 1 90.0\n", + "Gendrey 1 90.0\n", + "Baschirotto 1 90.0\n", + "Pongracic 1 80.0\n", + "Gallo 0.6 60.0\n", "... ... ...\n", - "Pisilli 0 10.0\n", - "Aouar 0.4 55.0\n", - "El Shaarawy 0 55.0\n", - "Belotti 0 60.0\n", - "Azmoun 0 35.0\n", + "Oristanio 0 50.0\n", + "Jankto 0 15.0\n", + "Mancosu 0 10.0\n", + "Pavoletti 0 55.0\n", + "Shomurodov 0.4 60.0\n", "\n", - "[476 rows x 2 columns]" + "[467 rows x 2 columns]" ] }, "execution_count": 6, diff --git a/.ipynb_checkpoints/6_neural_network_training_and_prediction-checkpoint.ipynb b/.ipynb_checkpoints/6_neural_network_training_and_prediction-checkpoint.ipynb index 78f7992..f1f5463 100644 --- a/.ipynb_checkpoints/6_neural_network_training_and_prediction-checkpoint.ipynb +++ b/.ipynb_checkpoints/6_neural_network_training_and_prediction-checkpoint.ipynb @@ -134,16 +134,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 1\n", @@ -158,13 +158,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -182,16 +182,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 3\n", @@ -230,16 +230,16 @@ " 0.0\n", " 7.5\n", " ...\n", - " 0.012384\n", - " 0.003096\n", - " 0.012384\n", - " 0.006192\n", - " 0.003096\n", - " 0.027864\n", - " 0.408669\n", - " 0.015480\n", - " 0.012384\n", - " 0.003096\n", + " 0.010204\n", + " 0.002041\n", + " 0.014286\n", + " 0.004082\n", + " 0.010204\n", + " 0.020408\n", + " 0.357143\n", + " 0.016327\n", + " 0.014286\n", + " 0.004082\n", " \n", " \n", " ...\n", @@ -266,7 +266,7 @@ " ...\n", " \n", " \n", - " 30064\n", + " 30595\n", " 38\n", " Miguel Veloso\n", " Verona\n", @@ -290,7 +290,7 @@ " 0.000860\n", " \n", " \n", - " 30065\n", + " 30596\n", " 38\n", " Tameze\n", " Verona\n", @@ -314,7 +314,7 @@ " 0.001320\n", " \n", " \n", - " 30066\n", + " 30597\n", " 38\n", " Sulemana I.\n", " Verona\n", @@ -338,7 +338,7 @@ " 0.000000\n", " \n", " \n", - " 30067\n", + " 30598\n", " 38\n", " Djuric\n", " Verona\n", @@ -362,7 +362,7 @@ " 0.002196\n", " \n", " \n", - " 30068\n", + " 30599\n", " 38\n", " Ngonge\n", " Verona\n", @@ -387,7 +387,7 @@ " \n", " \n", "\n", - "

30069 rows × 122 columns

\n", + "

30600 rows × 122 columns

\n", "" ], "text/plain": [ @@ -398,65 +398,65 @@ "3 1 Zortea Atalanta Sassuolo 0 7.0 1 \n", "4 1 Ruggeri Atalanta Sassuolo 0 6.5 0 \n", "... ... ... ... ... ... ... ... \n", - "30064 38 Miguel Veloso Verona Milan 0 5.5 0 \n", - "30065 38 Tameze Verona Milan 0 5.5 0 \n", - "30066 38 Sulemana I. Verona Milan 0 6.0 0 \n", - "30067 38 Djuric Verona Milan 0 5.5 0 \n", - "30068 38 Ngonge Verona Milan 0 5.5 0 \n", + "30595 38 Miguel Veloso Verona Milan 0 5.5 0 \n", + "30596 38 Tameze Verona Milan 0 5.5 0 \n", + "30597 38 Sulemana I. Verona Milan 0 6.0 0 \n", + "30598 38 Djuric Verona Milan 0 5.5 0 \n", + "30599 38 Ngonge Verona Milan 0 5.5 0 \n", "\n", " assists cards_malus fantavote ... miscontrols dispossessed \\\n", - "0 0 0.0 6.5 ... 0.020161 0.012097 \n", - "1 0 0.0 6.0 ... 0.007874 0.000000 \n", - "2 0 0.0 6.5 ... 0.002786 0.002786 \n", + "0 0 0.0 6.5 ... 0.018349 0.009174 \n", + "1 0 0.0 6.0 ... 0.004608 0.000000 \n", + "2 0 0.0 6.5 ... 0.009276 0.001855 \n", "3 0 0.0 10.0 ... 0.000000 0.020833 \n", - "4 1 0.0 7.5 ... 0.012384 0.003096 \n", + "4 1 0.0 7.5 ... 0.010204 0.002041 \n", "... ... ... ... ... ... ... \n", - "30064 0 0.0 5.5 ... 0.006019 0.006019 \n", - "30065 0 0.0 5.5 ... 0.012867 0.011217 \n", - "30066 0 0.5 5.5 ... 0.015361 0.013825 \n", - "30067 0 0.0 5.5 ... 0.019034 0.010981 \n", - "30068 0 0.0 5.5 ... 0.030872 0.016107 \n", + "30595 0 0.0 5.5 ... 0.006019 0.006019 \n", + "30596 0 0.0 5.5 ... 0.012867 0.011217 \n", + "30597 0 0.5 5.5 ... 0.015361 0.013825 \n", + "30598 0 0.0 5.5 ... 0.019034 0.010981 \n", + "30599 0 0.0 5.5 ... 0.030872 0.016107 \n", "\n", " fouls fouled aerials_won aerials_lost carries \\\n", - "0 0.012097 0.016129 0.008065 0.016129 0.391129 \n", - "1 0.007874 0.000000 0.019685 0.027559 0.350394 \n", - "2 0.002786 0.011142 0.013928 0.022284 0.412256 \n", + "0 0.009174 0.015291 0.009174 0.015291 0.376147 \n", + "1 0.011521 0.002304 0.034562 0.020737 0.299539 \n", + "2 0.009276 0.014842 0.016698 0.022263 0.378479 \n", "3 0.031250 0.000000 0.000000 0.010417 0.447917 \n", - "4 0.012384 0.006192 0.003096 0.027864 0.408669 \n", + "4 0.014286 0.004082 0.010204 0.020408 0.357143 \n", "... ... ... ... ... ... \n", - "30064 0.017197 0.006879 0.012038 0.012038 0.265692 \n", - "30065 0.010558 0.010228 0.008908 0.010228 0.235236 \n", - "30066 0.016897 0.004608 0.015361 0.018433 0.201229 \n", - "30067 0.017570 0.021230 0.144217 0.041728 0.191801 \n", - "30068 0.017450 0.014765 0.022819 0.046980 0.242953 \n", + "30595 0.017197 0.006879 0.012038 0.012038 0.265692 \n", + "30596 0.010558 0.010228 0.008908 0.010228 0.235236 \n", + "30597 0.016897 0.004608 0.015361 0.018433 0.201229 \n", + "30598 0.017570 0.021230 0.144217 0.041728 0.191801 \n", + "30599 0.017450 0.014765 0.022819 0.046980 0.242953 \n", "\n", " progressive_carries carries_into_final_third \\\n", - "0 0.040323 0.020161 \n", + "0 0.033639 0.015291 \n", "1 0.000000 0.000000 \n", - "2 0.019499 0.025070 \n", + "2 0.014842 0.016698 \n", "3 0.062500 0.041667 \n", - "4 0.015480 0.012384 \n", + "4 0.016327 0.014286 \n", "... ... ... \n", - "30064 0.014617 0.011178 \n", - "30065 0.010558 0.011217 \n", - "30066 0.006144 0.010753 \n", - "30067 0.001464 0.003660 \n", - "30068 0.024161 0.014765 \n", + "30595 0.014617 0.011178 \n", + "30596 0.010558 0.011217 \n", + "30597 0.006144 0.010753 \n", + "30598 0.001464 0.003660 \n", + "30599 0.024161 0.014765 \n", "\n", " carries_into_penalty_area \n", - "0 0.012097 \n", + "0 0.012232 \n", "1 0.000000 \n", - "2 0.002786 \n", + "2 0.001855 \n", "3 0.010417 \n", - "4 0.003096 \n", + "4 0.004082 \n", "... ... \n", - "30064 0.000860 \n", - "30065 0.001320 \n", - "30066 0.000000 \n", - "30067 0.002196 \n", - "30068 0.012081 \n", + "30595 0.000860 \n", + "30596 0.001320 \n", + "30597 0.000000 \n", + "30598 0.002196 \n", + "30599 0.012081 \n", "\n", - "[30069 rows x 122 columns]" + "[30600 rows x 122 columns]" ] }, "execution_count": 4, @@ -537,13 +537,13 @@ " 2.100000\n", " 0.210000\n", " 0.100000\n", - " 11.000000\n", - " 34.000000\n", - " 88.000000\n", - " 18.000000\n", - " 18.000000\n", + " 14.000000\n", + " 48.000000\n", + " 119.000000\n", + " 25.000000\n", " 28.000000\n", - " 2.000000\n", + " 43.000000\n", + " 4.000000\n", " \n", " \n", " 1\n", @@ -558,16 +558,16 @@ " 0.0\n", " 4.0\n", " ...\n", - " 3.200000\n", - " 0.320000\n", - " -0.800000\n", - " 17.000000\n", - " 45.000000\n", - " 106.000000\n", - " 17.000000\n", - " 22.000000\n", - " 57.000000\n", - " 2.000000\n", + " 4.200000\n", + " 0.250000\n", + " 0.200000\n", + " 28.000000\n", + " 60.000000\n", + " 159.000000\n", + " 25.000000\n", + " 34.000000\n", + " 89.000000\n", + " 3.000000\n", " \n", " \n", " 2\n", @@ -582,16 +582,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 4.100000\n", - " 0.330000\n", - " 0.100000\n", - " 24.000000\n", - " 54.000000\n", - " 76.000000\n", - " 18.000000\n", - " 40.000000\n", - " 62.000000\n", - " 4.000000\n", + " 8.700000\n", + " 0.360000\n", + " -0.300000\n", + " 33.000000\n", + " 80.000000\n", + " 124.000000\n", + " 23.000000\n", + " 57.000000\n", + " 87.000000\n", + " 5.000000\n", " \n", " \n", " 3\n", @@ -606,15 +606,15 @@ " 0.0\n", " 4.0\n", " ...\n", - " 0.400000\n", - " 0.110000\n", - " -0.600000\n", - " 4.000000\n", - " 20.000000\n", - " 37.000000\n", - " 9.000000\n", - " 4.000000\n", - " 10.000000\n", + " 4.933333\n", + " 0.203333\n", + " -1.400000\n", + " 8.666667\n", + " 38.666667\n", + " 83.000000\n", + " 17.666667\n", + " 17.333333\n", + " 36.666667\n", " 2.000000\n", " \n", " \n", @@ -630,16 +630,16 @@ " 0.0\n", " 5.0\n", " ...\n", - " 1.000000\n", - " 0.170000\n", - " -2.000000\n", - " 13.000000\n", - " 20.000000\n", - " 85.000000\n", - " 10.000000\n", - " 9.000000\n", - " 16.000000\n", - " 1.000000\n", + " 4.100000\n", + " 0.240000\n", + " 0.100000\n", + " 28.000000\n", + " 57.000000\n", + " 151.000000\n", + " 14.000000\n", + " 22.000000\n", + " 44.000000\n", + " 3.000000\n", " \n", " \n", " ...\n", @@ -666,7 +666,7 @@ " ...\n", " \n", " \n", - " 2364\n", + " 2404\n", " 38\n", " Russo A.\n", " Sassuolo\n", @@ -690,7 +690,7 @@ " 23.333333\n", " \n", " \n", - " 2365\n", + " 2405\n", " 38\n", " Zoet\n", " Spezia\n", @@ -714,7 +714,7 @@ " 5.500000\n", " \n", " \n", - " 2366\n", + " 2406\n", " 38\n", " Milinkovic-Savic V.\n", " Torino\n", @@ -738,7 +738,7 @@ " 36.000000\n", " \n", " \n", - " 2367\n", + " 2407\n", " 38\n", " Silvestri\n", " Udinese\n", @@ -762,7 +762,7 @@ " 13.000000\n", " \n", " \n", - " 2368\n", + " 2408\n", " 38\n", " Montipo'\n", " Verona\n", @@ -787,7 +787,7 @@ " \n", " \n", "\n", - "

2369 rows × 102 columns

\n", + "

2409 rows × 102 columns

\n", "" ], "text/plain": [ @@ -798,65 +798,65 @@ "3 1 Caprile Empoli Verona 1 5.0 \n", "4 1 Terracciano Fiorentina Genoa 0 6.0 \n", "... ... ... ... ... ... ... \n", - "2364 38 Russo A. Sassuolo Fiorentina 1 5.0 \n", - "2365 38 Zoet Spezia Roma 0 5.5 \n", - "2366 38 Milinkovic-Savic V. Torino Inter 1 5.0 \n", - "2367 38 Silvestri Udinese Juventus 1 6.5 \n", - "2368 38 Montipo' Verona Milan 0 6.0 \n", + "2404 38 Russo A. Sassuolo Fiorentina 1 5.0 \n", + "2405 38 Zoet Spezia Roma 0 5.5 \n", + "2406 38 Milinkovic-Savic V. Torino Inter 1 5.0 \n", + "2407 38 Silvestri Udinese Juventus 1 6.5 \n", + "2408 38 Montipo' Verona Milan 0 6.0 \n", "\n", " goals assists cards_malus fantavote ... gk_psxg \\\n", "0 0 0 0.0 6.5 ... 2.100000 \n", - "1 -2 0 0.0 4.0 ... 3.200000 \n", - "2 0 0 0.0 6.5 ... 4.100000 \n", - "3 -1 0 0.0 4.0 ... 0.400000 \n", - "4 -1 0 0.0 5.0 ... 1.000000 \n", + "1 -2 0 0.0 4.0 ... 4.200000 \n", + "2 0 0 0.0 6.5 ... 8.700000 \n", + "3 -1 0 0.0 4.0 ... 4.933333 \n", + "4 -1 0 0.0 5.0 ... 4.100000 \n", "... ... ... ... ... ... ... \n", - "2364 -3 0 0.0 2.0 ... 32.550000 \n", - "2365 -2 0 0.5 3.0 ... 10.016667 \n", - "2366 -1 0 0.0 4.0 ... 35.800000 \n", - "2367 -1 0 0.0 5.5 ... 48.700000 \n", - "2368 -3 0 0.0 3.0 ... 49.600000 \n", + "2404 -3 0 0.0 2.0 ... 32.550000 \n", + "2405 -2 0 0.5 3.0 ... 10.016667 \n", + "2406 -1 0 0.0 4.0 ... 35.800000 \n", + "2407 -1 0 0.0 5.5 ... 48.700000 \n", + "2408 -3 0 0.0 3.0 ... 49.600000 \n", "\n", " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", "0 0.210000 0.100000 \n", - "1 0.320000 -0.800000 \n", - "2 0.330000 0.100000 \n", - "3 0.110000 -0.600000 \n", - "4 0.170000 -2.000000 \n", + "1 0.250000 0.200000 \n", + "2 0.360000 -0.300000 \n", + "3 0.203333 -1.400000 \n", + "4 0.240000 0.100000 \n", "... ... ... \n", - "2364 0.325000 -12.116667 \n", - "2365 0.158333 -1.816667 \n", - "2366 0.230000 -5.200000 \n", - "2367 0.310000 2.700000 \n", - "2368 0.270000 -6.400000 \n", + "2404 0.325000 -12.116667 \n", + "2405 0.158333 -1.816667 \n", + "2406 0.230000 -5.200000 \n", + "2407 0.310000 2.700000 \n", + "2408 0.270000 -6.400000 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.000000 34.000000 88.000000 \n", - "1 17.000000 45.000000 106.000000 \n", - "2 24.000000 54.000000 76.000000 \n", - "3 4.000000 20.000000 37.000000 \n", - "4 13.000000 20.000000 85.000000 \n", + "0 14.000000 48.000000 119.000000 \n", + "1 28.000000 60.000000 159.000000 \n", + "2 33.000000 80.000000 124.000000 \n", + "3 8.666667 38.666667 83.000000 \n", + "4 28.000000 57.000000 151.000000 \n", "... ... ... ... \n", - "2364 146.666667 365.333333 957.000000 \n", - "2365 46.000000 145.333333 254.166667 \n", - "2366 285.000000 939.000000 1506.000000 \n", - "2367 144.000000 380.000000 872.000000 \n", - "2368 360.000000 775.000000 905.000000 \n", + "2404 146.666667 365.333333 957.000000 \n", + "2405 46.000000 145.333333 254.166667 \n", + "2406 285.000000 939.000000 1506.000000 \n", + "2407 144.000000 380.000000 872.000000 \n", + "2408 360.000000 775.000000 905.000000 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.000000 18.000000 28.000000 2.000000 \n", - "1 17.000000 22.000000 57.000000 2.000000 \n", - "2 18.000000 40.000000 62.000000 4.000000 \n", - "3 9.000000 4.000000 10.000000 2.000000 \n", - "4 10.000000 9.000000 16.000000 1.000000 \n", + "0 25.000000 28.000000 43.000000 4.000000 \n", + "1 25.000000 34.000000 89.000000 3.000000 \n", + "2 23.000000 57.000000 87.000000 5.000000 \n", + "3 17.666667 17.333333 36.666667 2.000000 \n", + "4 14.000000 22.000000 44.000000 3.000000 \n", "... ... ... ... ... \n", - "2364 156.166667 238.833333 391.500000 23.333333 \n", - "2365 37.333333 51.833333 130.333333 5.500000 \n", - "2366 185.000000 286.000000 469.000000 36.000000 \n", - "2367 142.000000 302.000000 547.000000 13.000000 \n", - "2368 124.000000 284.000000 496.000000 26.000000 \n", + "2404 156.166667 238.833333 391.500000 23.333333 \n", + "2405 37.333333 51.833333 130.333333 5.500000 \n", + "2406 185.000000 286.000000 469.000000 36.000000 \n", + "2407 142.000000 302.000000 547.000000 13.000000 \n", + "2408 124.000000 284.000000 496.000000 26.000000 \n", "\n", - "[2369 rows x 102 columns]" + "[2409 rows x 102 columns]" ] }, "execution_count": 5, @@ -918,7 +918,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_5452\\661405348.py:3: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_6176\\661405348.py:3: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", " avg_row = pd.DataFrame(index = ['Avg'], data = [team_data.mean()], columns = team_data.columns)\n" ] }, @@ -970,506 +970,506 @@ " \n", " Atalanta\n", " Atalanta\n", - " 23.00\n", - " 49.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.00\n", - " 8.00\n", + " 24.0\n", + " 50.50\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 11.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", - " 0.0\n", + " 57.00\n", + " 74.0\n", + " 4.00\n", " 0.0\n", " 0.00\n", - " 212.00\n", - " 65.0\n", - " 60.0\n", - " 52.00\n", + " 0.00\n", + " 347.00\n", + " 97.00\n", + " 109.00\n", + " 47.100\n", " \n", " \n", " Bologna\n", " Bologna\n", - " 22.00\n", - " 56.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.00\n", + " 23.0\n", + " 54.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 3.0\n", " 2.00\n", " 0.00\n", - " 1.0\n", + " 1.00\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 71.00\n", + " 70.0\n", + " 16.00\n", " 0.0\n", - " 1.0\n", + " 1.00\n", " 0.00\n", - " 207.00\n", - " 34.0\n", - " 46.0\n", - " 42.50\n", + " 292.00\n", + " 47.00\n", + " 73.00\n", + " 39.200\n", " \n", " \n", " Cagliari\n", " Cagliari\n", - " 21.00\n", - " 37.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.00\n", - " 1.00\n", + " 22.0\n", + " 38.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 38.0\n", - " 41.0\n", - " 5.0\n", - " 0.0\n", + " 50.00\n", + " 65.0\n", + " 11.00\n", " 0.0\n", " 0.00\n", - " 220.00\n", - " 60.0\n", - " 51.0\n", - " 54.10\n", + " 0.00\n", + " 332.00\n", + " 92.00\n", + " 71.00\n", + " 56.400\n", " \n", " \n", " Empoli\n", " Empoli\n", - " 27.00\n", - " 47.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 0.00\n", - " 0.00\n", - " 0.00\n", - " 0.0\n", - " ...\n", - " 60.0\n", - " 42.0\n", - " 8.0\n", + " 28.0\n", + " 45.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 1.0\n", - " 0.0\n", + " 1.00\n", " 0.00\n", - " 203.00\n", - " 54.0\n", - " 39.0\n", - " 58.10\n", + " 0.00\n", + " ...\n", + " 84.00\n", + " 74.0\n", + " 10.00\n", + " 1.0\n", + " 0.00\n", + " 0.00\n", + " 313.00\n", + " 82.00\n", + " 60.00\n", + " 57.700\n", " \n", " \n", " Fiorentina\n", " Fiorentina\n", - " 22.00\n", - " 61.000\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 57.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 9.00\n", - " 7.00\n", " 0.00\n", - " 0.0\n", + " 0.00\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 5.0\n", + " 75.00\n", + " 63.0\n", + " 8.00\n", " 1.0\n", - " 0.0\n", " 0.00\n", - " 202.00\n", - " 56.0\n", - " 53.0\n", - " 51.40\n", + " 0.00\n", + " 311.00\n", + " 96.00\n", + " 75.00\n", + " 56.100\n", " \n", " \n", " Frosinone\n", " Frosinone\n", - " 23.00\n", - " 48.300\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.00\n", - " 4.00\n", - " 2.00\n", - " 2.0\n", - " ...\n", - " 50.0\n", - " 39.0\n", + " 24.0\n", + " 49.20\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 5.00\n", + " 2.00\n", + " 2.00\n", + " ...\n", + " 73.00\n", + " 54.0\n", + " 15.00\n", " 0.0\n", - " 2.0\n", + " 2.00\n", " 0.00\n", - " 212.00\n", - " 53.0\n", - " 52.0\n", - " 50.50\n", + " 325.00\n", + " 79.00\n", + " 80.00\n", + " 49.700\n", " \n", " \n", " Genoa\n", " Genoa\n", - " 19.00\n", - " 33.300\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.00\n", - " 3.00\n", + " 22.0\n", + " 34.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 7.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 43.0\n", - " 43.0\n", - " 9.0\n", - " 0.0\n", + " 67.00\n", + " 60.0\n", + " 12.00\n", " 0.0\n", " 0.00\n", - " 200.00\n", - " 46.0\n", - " 60.0\n", - " 43.40\n", + " 0.00\n", + " 295.00\n", + " 66.00\n", + " 83.00\n", + " 44.300\n", " \n", " \n", " Verona\n", " Hellas Verona\n", - " 21.00\n", - " 43.500\n", + " 22.0\n", + " 45.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.00\n", " 2.00\n", " 0.00\n", - " 0.0\n", - " ...\n", - " 47.0\n", - " 63.0\n", - " 7.0\n", - " 1.0\n", - " 0.0\n", " 0.00\n", - " 190.00\n", - " 71.0\n", - " 82.0\n", - " 46.40\n", + " ...\n", + " 84.00\n", + " 84.0\n", + " 11.00\n", + " 1.0\n", + " 0.00\n", + " 0.00\n", + " 326.00\n", + " 116.00\n", + " 117.00\n", + " 49.800\n", " \n", " \n", " Inter\n", " Inter\n", - " 19.00\n", - " 48.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 13.00\n", - " 11.00\n", + " 22.0\n", + " 53.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 15.0\n", + " 12.00\n", + " 2.00\n", " 2.00\n", - " 2.0\n", " ...\n", - " 47.0\n", - " 44.0\n", - " 5.0\n", + " 70.00\n", + " 64.0\n", + " 9.00\n", " 0.0\n", - " 2.0\n", + " 2.00\n", " 0.00\n", - " 163.00\n", - " 30.0\n", - " 44.0\n", - " 40.50\n", + " 248.00\n", + " 46.00\n", + " 77.00\n", + " 37.400\n", " \n", " \n", " Juventus\n", " Juventus\n", - " 21.00\n", - " 48.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 22.0\n", + " 50.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", " 9.00\n", - " 7.00\n", " 1.00\n", - " 2.0\n", + " 2.00\n", " ...\n", - " 52.0\n", - " 49.0\n", - " 5.0\n", + " 80.00\n", + " 71.0\n", + " 6.00\n", " 0.0\n", - " 2.0\n", - " 0.00\n", - " 173.00\n", - " 26.0\n", - " 38.0\n", - " 40.60\n", + " 2.00\n", + " 1.00\n", + " 267.00\n", + " 41.00\n", + " 67.00\n", + " 38.000\n", " \n", " \n", " Lazio\n", " Lazio\n", - " 20.00\n", - " 56.000\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.00\n", - " 4.00\n", - " 0.00\n", - " 0.0\n", - " ...\n", - " 49.0\n", - " 44.0\n", + " 20.0\n", + " 54.00\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 7.0\n", + " 6.00\n", + " 1.00\n", + " 1.00\n", + " ...\n", + " 69.00\n", + " 67.0\n", + " 10.00\n", " 0.0\n", - " 0.0\n", + " 1.00\n", " 0.00\n", - " 196.00\n", - " 51.0\n", - " 30.0\n", - " 63.00\n", + " 282.00\n", + " 66.00\n", + " 53.00\n", + " 55.500\n", " \n", " \n", " Lecce\n", " Lecce\n", - " 19.00\n", - " 43.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.00\n", - " 5.00\n", + " 22.0\n", + " 46.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 6.00\n", + " 2.00\n", " 2.00\n", - " 2.0\n", " ...\n", - " 64.0\n", - " 53.0\n", - " 5.0\n", + " 88.00\n", + " 78.0\n", + " 5.00\n", " 0.0\n", - " 2.0\n", + " 2.00\n", " 0.00\n", - " 203.00\n", - " 43.0\n", - " 54.0\n", - " 44.30\n", + " 295.00\n", + " 67.00\n", + " 73.00\n", + " 47.900\n", " \n", " \n", " Milan\n", " Milan\n", - " 19.00\n", - " 55.300\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.00\n", - " 6.00\n", + " 23.0\n", + " 56.80\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 13.0\n", + " 8.00\n", + " 3.00\n", " 3.00\n", - " 3.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 7.0\n", + " 80.00\n", + " 60.0\n", + " 8.00\n", " 1.0\n", - " 3.0\n", + " 3.00\n", " 0.00\n", - " 176.00\n", - " 42.0\n", - " 33.0\n", - " 56.00\n", + " 281.00\n", + " 65.00\n", + " 61.00\n", + " 51.600\n", " \n", " \n", " Monza\n", " Monza\n", - " 22.00\n", - " 56.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.00\n", - " 3.00\n", - " 0.00\n", - " 0.0\n", - " ...\n", - " 37.0\n", - " 52.0\n", + " 23.0\n", + " 54.20\n", " 6.0\n", - " 1.0\n", - " 0.0\n", + " 66.0\n", + " 540.0\n", + " 4.0\n", + " 3.00\n", " 0.00\n", - " 187.00\n", - " 45.0\n", - " 37.0\n", - " 54.90\n", + " 0.00\n", + " ...\n", + " 65.00\n", + " 68.0\n", + " 11.00\n", + " 2.0\n", + " 0.00\n", + " 0.00\n", + " 281.00\n", + " 74.00\n", + " 56.00\n", + " 56.900\n", " \n", " \n", " Napoli\n", " Napoli\n", - " 19.00\n", - " 61.800\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.00\n", - " 5.00\n", - " 1.00\n", - " 2.0\n", + " 20.0\n", + " 60.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 7.00\n", + " 2.00\n", + " 4.00\n", " ...\n", - " 47.0\n", - " 39.0\n", - " 7.0\n", + " 73.00\n", + " 60.0\n", + " 9.00\n", " 1.0\n", - " 2.0\n", + " 4.00\n", " 0.00\n", - " 173.00\n", - " 35.0\n", - " 47.0\n", - " 42.70\n", + " 254.00\n", + " 52.00\n", + " 56.00\n", + " 48.100\n", " \n", " \n", " Roma\n", " Roma\n", - " 23.00\n", - " 57.000\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 10.00\n", - " 8.00\n", + " 23.0\n", + " 59.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 9.00\n", + " 1.00\n", " 1.00\n", - " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", - " 4.0\n", - " 1.0\n", + " 58.00\n", + " 67.0\n", + " 4.00\n", " 1.0\n", " 1.00\n", - " 159.00\n", - " 54.0\n", - " 76.0\n", - " 41.50\n", + " 1.00\n", + " 267.00\n", + " 83.00\n", + " 104.00\n", + " 44.400\n", " \n", " \n", " Salernitana\n", " Salernitana\n", - " 21.00\n", - " 51.500\n", + " 22.0\n", + " 52.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.00\n", " 3.00\n", " 0.00\n", - " 0.0\n", + " 0.00\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", - " 0.0\n", + " 94.00\n", + " 70.0\n", + " 12.00\n", " 0.0\n", " 0.00\n", - " 203.00\n", - " 86.0\n", - " 54.0\n", - " 61.40\n", + " 0.00\n", + " 311.00\n", + " 120.00\n", + " 82.00\n", + " 59.400\n", " \n", " \n", " Sassuolo\n", " Sassuolo\n", - " 24.00\n", - " 43.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.00\n", - " 4.00\n", + " 25.0\n", + " 42.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.00\n", + " 1.00\n", " 1.00\n", - " 1.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.00\n", + " 55.0\n", + " 20.00\n", " 2.0\n", - " 1.0\n", - " 0.00\n", - " 207.00\n", - " 50.0\n", - " 37.0\n", - " 57.50\n", + " 1.00\n", + " 1.00\n", + " 299.00\n", + " 85.00\n", + " 55.00\n", + " 60.700\n", " \n", " \n", " Torino\n", " Torino\n", - " 22.00\n", - " 51.300\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.00\n", - " 3.00\n", + " 23.0\n", + " 49.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", + " 4.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 44.0\n", - " 48.0\n", - " 7.0\n", + " 61.00\n", + " 64.0\n", + " 7.00\n", " 1.0\n", - " 0.0\n", " 0.00\n", - " 207.00\n", - " 63.0\n", - " 59.0\n", - " 51.60\n", + " 0.00\n", + " 302.00\n", + " 93.00\n", + " 82.00\n", + " 53.100\n", " \n", " \n", " Udinese\n", " Udinese\n", - " 22.00\n", - " 48.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.00\n", - " 1.00\n", + " 24.0\n", + " 46.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 43.0\n", - " 51.0\n", - " 10.0\n", - " 0.0\n", - " 0.0\n", + " 65.00\n", + " 74.0\n", + " 11.00\n", + " 1.0\n", " 0.00\n", - " 188.00\n", - " 52.0\n", - " 64.0\n", - " 44.80\n", + " 0.00\n", + " 297.00\n", + " 68.00\n", + " 101.00\n", + " 40.200\n", " \n", " \n", " Avg\n", " Avg\n", - " 21.45\n", - " 50.025\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.65\n", - " 4.35\n", - " 0.65\n", - " 0.8\n", + " 22.9\n", + " 50.01\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.7\n", + " 5.75\n", + " 0.75\n", + " 0.95\n", " ...\n", - " 48.7\n", - " 45.6\n", - " 6.8\n", - " 0.5\n", - " 0.8\n", - " 0.05\n", - " 194.05\n", - " 50.8\n", - " 50.8\n", - " 49.86\n", + " 71.35\n", + " 67.1\n", + " 9.95\n", + " 0.6\n", + " 0.95\n", + " 0.15\n", + " 296.25\n", + " 76.75\n", + " 76.75\n", + " 49.675\n", " \n", " \n", "\n", @@ -1478,165 +1478,165 @@ ], "text/plain": [ " team team_players_used team_possession team_games \\\n", - "Atalanta Atalanta 23.00 49.500 4.0 \n", - "Bologna Bologna 22.00 56.500 4.0 \n", - "Cagliari Cagliari 21.00 37.800 4.0 \n", - "Empoli Empoli 27.00 47.800 4.0 \n", - "Fiorentina Fiorentina 22.00 61.000 4.0 \n", - "Frosinone Frosinone 23.00 48.300 4.0 \n", - "Genoa Genoa 19.00 33.300 4.0 \n", - "Verona Hellas Verona 21.00 43.500 4.0 \n", - "Inter Inter 19.00 48.800 4.0 \n", - "Juventus Juventus 21.00 48.800 4.0 \n", - "Lazio Lazio 20.00 56.000 4.0 \n", - "Lecce Lecce 19.00 43.500 4.0 \n", - "Milan Milan 19.00 55.300 4.0 \n", - "Monza Monza 22.00 56.800 4.0 \n", - "Napoli Napoli 19.00 61.800 4.0 \n", - "Roma Roma 23.00 57.000 4.0 \n", - "Salernitana Salernitana 21.00 51.500 4.0 \n", - "Sassuolo Sassuolo 24.00 43.500 4.0 \n", - "Torino Torino 22.00 51.300 4.0 \n", - "Udinese Udinese 22.00 48.500 4.0 \n", - "Avg Avg 21.45 50.025 4.0 \n", + "Atalanta Atalanta 24.0 50.50 6.0 \n", + "Bologna Bologna 23.0 54.70 6.0 \n", + "Cagliari Cagliari 22.0 38.20 6.0 \n", + "Empoli Empoli 28.0 45.30 6.0 \n", + "Fiorentina Fiorentina 24.0 57.20 6.0 \n", + "Frosinone Frosinone 24.0 49.20 6.0 \n", + "Genoa Genoa 22.0 34.30 6.0 \n", + "Verona Hellas Verona 22.0 45.20 6.0 \n", + "Inter Inter 22.0 53.20 6.0 \n", + "Juventus Juventus 22.0 50.30 6.0 \n", + "Lazio Lazio 20.0 54.00 6.0 \n", + "Lecce Lecce 22.0 46.70 6.0 \n", + "Milan Milan 23.0 56.80 6.0 \n", + "Monza Monza 23.0 54.20 6.0 \n", + "Napoli Napoli 20.0 60.70 6.0 \n", + "Roma Roma 23.0 59.70 6.0 \n", + "Salernitana Salernitana 22.0 52.30 6.0 \n", + "Sassuolo Sassuolo 25.0 42.30 6.0 \n", + "Torino Torino 23.0 49.20 6.0 \n", + "Udinese Udinese 24.0 46.20 6.0 \n", + "Avg Avg 22.9 50.01 6.0 \n", "\n", " team_games_starts team_minutes team_goals team_assists \\\n", - "Atalanta 44.0 360.0 8.00 8.00 \n", - "Bologna 44.0 360.0 3.00 2.00 \n", - "Cagliari 44.0 360.0 1.00 1.00 \n", - "Empoli 44.0 360.0 0.00 0.00 \n", - "Fiorentina 44.0 360.0 9.00 7.00 \n", - "Frosinone 44.0 360.0 7.00 4.00 \n", - "Genoa 44.0 360.0 4.00 3.00 \n", - "Verona 44.0 360.0 4.00 2.00 \n", - "Inter 44.0 360.0 13.00 11.00 \n", - "Juventus 44.0 360.0 9.00 7.00 \n", - "Lazio 44.0 360.0 4.00 4.00 \n", - "Lecce 44.0 360.0 7.00 5.00 \n", - "Milan 44.0 360.0 9.00 6.00 \n", - "Monza 44.0 360.0 3.00 3.00 \n", - "Napoli 44.0 360.0 8.00 5.00 \n", - "Roma 44.0 360.0 10.00 8.00 \n", - "Salernitana 44.0 360.0 3.00 3.00 \n", - "Sassuolo 44.0 360.0 5.00 4.00 \n", - "Torino 44.0 360.0 5.00 3.00 \n", - "Udinese 44.0 360.0 1.00 1.00 \n", - "Avg 44.0 360.0 5.65 4.35 \n", + "Atalanta 66.0 540.0 11.0 11.00 \n", + "Bologna 66.0 540.0 3.0 2.00 \n", + "Cagliari 66.0 540.0 2.0 2.00 \n", + "Empoli 66.0 540.0 1.0 1.00 \n", + "Fiorentina 66.0 540.0 12.0 9.00 \n", + "Frosinone 66.0 540.0 9.0 5.00 \n", + "Genoa 66.0 540.0 8.0 7.00 \n", + "Verona 66.0 540.0 4.0 2.00 \n", + "Inter 66.0 540.0 15.0 12.00 \n", + "Juventus 66.0 540.0 11.0 9.00 \n", + "Lazio 66.0 540.0 7.0 6.00 \n", + "Lecce 66.0 540.0 8.0 6.00 \n", + "Milan 66.0 540.0 13.0 8.00 \n", + "Monza 66.0 540.0 4.0 3.00 \n", + "Napoli 66.0 540.0 12.0 7.00 \n", + "Roma 66.0 540.0 12.0 9.00 \n", + "Salernitana 66.0 540.0 4.0 3.00 \n", + "Sassuolo 66.0 540.0 10.0 7.00 \n", + "Torino 66.0 540.0 6.0 4.00 \n", + "Udinese 66.0 540.0 2.0 2.00 \n", + "Avg 66.0 540.0 7.7 5.75 \n", "\n", " team_pens_made team_pens_att ... vs_team_fouls \\\n", - "Atalanta 0.00 0.0 ... 36.0 \n", - "Bologna 0.00 1.0 ... 50.0 \n", - "Cagliari 0.00 0.0 ... 38.0 \n", - "Empoli 0.00 0.0 ... 60.0 \n", - "Fiorentina 0.00 0.0 ... 56.0 \n", - "Frosinone 2.00 2.0 ... 50.0 \n", - "Genoa 0.00 0.0 ... 43.0 \n", - "Verona 0.00 0.0 ... 47.0 \n", - "Inter 2.00 2.0 ... 47.0 \n", - "Juventus 1.00 2.0 ... 52.0 \n", - "Lazio 0.00 0.0 ... 49.0 \n", - "Lecce 2.00 2.0 ... 64.0 \n", - "Milan 3.00 3.0 ... 56.0 \n", - "Monza 0.00 0.0 ... 37.0 \n", - "Napoli 1.00 2.0 ... 47.0 \n", - "Roma 1.00 1.0 ... 46.0 \n", - "Salernitana 0.00 0.0 ... 64.0 \n", - "Sassuolo 1.00 1.0 ... 45.0 \n", - "Torino 0.00 0.0 ... 44.0 \n", - "Udinese 0.00 0.0 ... 43.0 \n", - "Avg 0.65 0.8 ... 48.7 \n", + "Atalanta 0.00 0.00 ... 57.00 \n", + "Bologna 0.00 1.00 ... 71.00 \n", + "Cagliari 0.00 0.00 ... 50.00 \n", + "Empoli 0.00 0.00 ... 84.00 \n", + "Fiorentina 0.00 0.00 ... 75.00 \n", + "Frosinone 2.00 2.00 ... 73.00 \n", + "Genoa 0.00 0.00 ... 67.00 \n", + "Verona 0.00 0.00 ... 84.00 \n", + "Inter 2.00 2.00 ... 70.00 \n", + "Juventus 1.00 2.00 ... 80.00 \n", + "Lazio 1.00 1.00 ... 69.00 \n", + "Lecce 2.00 2.00 ... 88.00 \n", + "Milan 3.00 3.00 ... 80.00 \n", + "Monza 0.00 0.00 ... 65.00 \n", + "Napoli 2.00 4.00 ... 73.00 \n", + "Roma 1.00 1.00 ... 58.00 \n", + "Salernitana 0.00 0.00 ... 94.00 \n", + "Sassuolo 1.00 1.00 ... 63.00 \n", + "Torino 0.00 0.00 ... 61.00 \n", + "Udinese 0.00 0.00 ... 65.00 \n", + "Avg 0.75 0.95 ... 71.35 \n", "\n", " vs_team_fouled vs_team_offsides vs_team_pens_won \\\n", - "Atalanta 47.0 2.0 0.0 \n", - "Bologna 40.0 12.0 0.0 \n", - "Cagliari 41.0 5.0 0.0 \n", - "Empoli 42.0 8.0 1.0 \n", - "Fiorentina 43.0 5.0 1.0 \n", - "Frosinone 39.0 6.0 0.0 \n", - "Genoa 43.0 9.0 0.0 \n", - "Verona 63.0 7.0 1.0 \n", - "Inter 44.0 5.0 0.0 \n", - "Juventus 49.0 5.0 0.0 \n", - "Lazio 44.0 7.0 0.0 \n", - "Lecce 53.0 5.0 0.0 \n", - "Milan 43.0 7.0 1.0 \n", - "Monza 52.0 6.0 1.0 \n", - "Napoli 39.0 7.0 1.0 \n", - "Roma 51.0 4.0 1.0 \n", - "Salernitana 46.0 4.0 0.0 \n", - "Sassuolo 34.0 15.0 2.0 \n", - "Torino 48.0 7.0 1.0 \n", - "Udinese 51.0 10.0 0.0 \n", - "Avg 45.6 6.8 0.5 \n", + "Atalanta 74.0 4.00 0.0 \n", + "Bologna 70.0 16.00 0.0 \n", + "Cagliari 65.0 11.00 0.0 \n", + "Empoli 74.0 10.00 1.0 \n", + "Fiorentina 63.0 8.00 1.0 \n", + "Frosinone 54.0 15.00 0.0 \n", + "Genoa 60.0 12.00 0.0 \n", + "Verona 84.0 11.00 1.0 \n", + "Inter 64.0 9.00 0.0 \n", + "Juventus 71.0 6.00 0.0 \n", + "Lazio 67.0 10.00 0.0 \n", + "Lecce 78.0 5.00 0.0 \n", + "Milan 60.0 8.00 1.0 \n", + "Monza 68.0 11.00 2.0 \n", + "Napoli 60.0 9.00 1.0 \n", + "Roma 67.0 4.00 1.0 \n", + "Salernitana 70.0 12.00 0.0 \n", + "Sassuolo 55.0 20.00 2.0 \n", + "Torino 64.0 7.00 1.0 \n", + "Udinese 74.0 11.00 1.0 \n", + "Avg 67.1 9.95 0.6 \n", "\n", " vs_team_pens_conceded vs_team_own_goals \\\n", - "Atalanta 0.0 0.00 \n", - "Bologna 1.0 0.00 \n", - "Cagliari 0.0 0.00 \n", - "Empoli 0.0 0.00 \n", - "Fiorentina 0.0 0.00 \n", - "Frosinone 2.0 0.00 \n", - "Genoa 0.0 0.00 \n", - "Verona 0.0 0.00 \n", - "Inter 2.0 0.00 \n", - "Juventus 2.0 0.00 \n", - "Lazio 0.0 0.00 \n", - "Lecce 2.0 0.00 \n", - "Milan 3.0 0.00 \n", - "Monza 0.0 0.00 \n", - "Napoli 2.0 0.00 \n", - "Roma 1.0 1.00 \n", - "Salernitana 0.0 0.00 \n", - "Sassuolo 1.0 0.00 \n", - "Torino 0.0 0.00 \n", - "Udinese 0.0 0.00 \n", - "Avg 0.8 0.05 \n", + "Atalanta 0.00 0.00 \n", + "Bologna 1.00 0.00 \n", + "Cagliari 0.00 0.00 \n", + "Empoli 0.00 0.00 \n", + "Fiorentina 0.00 0.00 \n", + "Frosinone 2.00 0.00 \n", + "Genoa 0.00 0.00 \n", + "Verona 0.00 0.00 \n", + "Inter 2.00 0.00 \n", + "Juventus 2.00 1.00 \n", + "Lazio 1.00 0.00 \n", + "Lecce 2.00 0.00 \n", + "Milan 3.00 0.00 \n", + "Monza 0.00 0.00 \n", + "Napoli 4.00 0.00 \n", + "Roma 1.00 1.00 \n", + "Salernitana 0.00 0.00 \n", + "Sassuolo 1.00 1.00 \n", + "Torino 0.00 0.00 \n", + "Udinese 0.00 0.00 \n", + "Avg 0.95 0.15 \n", "\n", " vs_team_ball_recoveries vs_team_aerials_won \\\n", - "Atalanta 212.00 65.0 \n", - "Bologna 207.00 34.0 \n", - "Cagliari 220.00 60.0 \n", - "Empoli 203.00 54.0 \n", - "Fiorentina 202.00 56.0 \n", - "Frosinone 212.00 53.0 \n", - "Genoa 200.00 46.0 \n", - "Verona 190.00 71.0 \n", - "Inter 163.00 30.0 \n", - "Juventus 173.00 26.0 \n", - "Lazio 196.00 51.0 \n", - "Lecce 203.00 43.0 \n", - "Milan 176.00 42.0 \n", - "Monza 187.00 45.0 \n", - "Napoli 173.00 35.0 \n", - "Roma 159.00 54.0 \n", - "Salernitana 203.00 86.0 \n", - "Sassuolo 207.00 50.0 \n", - "Torino 207.00 63.0 \n", - "Udinese 188.00 52.0 \n", - "Avg 194.05 50.8 \n", + "Atalanta 347.00 97.00 \n", + "Bologna 292.00 47.00 \n", + "Cagliari 332.00 92.00 \n", + "Empoli 313.00 82.00 \n", + "Fiorentina 311.00 96.00 \n", + "Frosinone 325.00 79.00 \n", + "Genoa 295.00 66.00 \n", + "Verona 326.00 116.00 \n", + "Inter 248.00 46.00 \n", + "Juventus 267.00 41.00 \n", + "Lazio 282.00 66.00 \n", + "Lecce 295.00 67.00 \n", + "Milan 281.00 65.00 \n", + "Monza 281.00 74.00 \n", + "Napoli 254.00 52.00 \n", + "Roma 267.00 83.00 \n", + "Salernitana 311.00 120.00 \n", + "Sassuolo 299.00 85.00 \n", + "Torino 302.00 93.00 \n", + "Udinese 297.00 68.00 \n", + "Avg 296.25 76.75 \n", "\n", " vs_team_aerials_lost vs_team_aerials_won_pct \n", - "Atalanta 60.0 52.00 \n", - "Bologna 46.0 42.50 \n", - "Cagliari 51.0 54.10 \n", - "Empoli 39.0 58.10 \n", - "Fiorentina 53.0 51.40 \n", - "Frosinone 52.0 50.50 \n", - "Genoa 60.0 43.40 \n", - "Verona 82.0 46.40 \n", - "Inter 44.0 40.50 \n", - "Juventus 38.0 40.60 \n", - "Lazio 30.0 63.00 \n", - "Lecce 54.0 44.30 \n", - "Milan 33.0 56.00 \n", - "Monza 37.0 54.90 \n", - "Napoli 47.0 42.70 \n", - "Roma 76.0 41.50 \n", - "Salernitana 54.0 61.40 \n", - "Sassuolo 37.0 57.50 \n", - "Torino 59.0 51.60 \n", - "Udinese 64.0 44.80 \n", - "Avg 50.8 49.86 \n", + "Atalanta 109.00 47.100 \n", + "Bologna 73.00 39.200 \n", + "Cagliari 71.00 56.400 \n", + "Empoli 60.00 57.700 \n", + "Fiorentina 75.00 56.100 \n", + "Frosinone 80.00 49.700 \n", + "Genoa 83.00 44.300 \n", + "Verona 117.00 49.800 \n", + "Inter 77.00 37.400 \n", + "Juventus 67.00 38.000 \n", + "Lazio 53.00 55.500 \n", + "Lecce 73.00 47.900 \n", + "Milan 61.00 51.600 \n", + "Monza 56.00 56.900 \n", + "Napoli 56.00 48.100 \n", + "Roma 104.00 44.400 \n", + "Salernitana 82.00 59.400 \n", + "Sassuolo 55.00 60.700 \n", + "Torino 82.00 53.100 \n", + "Udinese 101.00 40.200 \n", + "Avg 76.75 49.675 \n", "\n", "[21 rows x 303 columns]" ] @@ -3639,7 +3639,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 12, "id": "6f8707b8", "metadata": {}, "outputs": [ @@ -3649,22 +3649,22 @@ "text": [ " \n", "Averaging players stats with past seasons:\n", - "Szczesny 0.41758241758241765\n", - "Meret 0.6877828054298643\n", - "Provedel 0.6153846153846154\n", + "Szczesny 0.8351648351648353\n", + "Meret 1\n", + "Provedel 0.9230769230769229\n", "Maignan 1\n", - "Rui Patricio 0.6681318681318682\n", - "Skorupski 0.632016632016632\n", - "Milinkovic-Savic V. 0.6153846153846154\n", - "Di Gregorio 0.47401247401247393\n", - "Falcone 0.6153846153846154\n", - "Silvestri 0.6153846153846154\n", - "Terracciano 0.40318302387267907\n", - "Carnesecchi 0.22735042735042738\n", - "Montipo' 0.632016632016632\n", + "Rui Patricio 1\n", + "Skorupski 0.9480249480249479\n", + "Milinkovic-Savic V. 0.9230769230769229\n", + "Di Gregorio 0.79002079002079\n", + "Falcone 0.9230769230769229\n", + "Silvestri 0.9230769230769229\n", + "Terracciano 0.8063660477453581\n", + "Carnesecchi 0.6062678062678064\n", + "Montipo' 0.9480249480249479\n", "Ochoa 1\n", - "Consigli 0.501098901098901\n", - "Musso 0.7307692307692307\n", + "Consigli 0.6681318681318682\n", + "Musso 0.9743589743589745\n", "Cragno 1\n", "Perin 1\n", "Berisha 1\n", @@ -3676,8 +3676,8 @@ "Perilli 1\n", "Padelli 1\n", "Gollini 1\n", - "Perisan 0.8351648351648353\n", - "Audero 0.9821538461538462\n", + "Perisan 1\n", + "Audero 1\n", "Pinsoglio 1\n", "Fiorillo 1\n", "Cerofolini 1\n", @@ -3690,164 +3690,164 @@ "Bagnolini 1\n", "Svilar 1\n", "Sorrentino A. 1\n", - "Dimarco 0.3543123543123543\n", - "Di Lorenzo 0.316008316008316\n", - "Hernandez T. 0.3653846153846154\n", - "Carlos Augusto 0.3507692307692308\n", - "Danilo 0.316008316008316\n", - "Zappacosta 0.5567765567765568\n", - "Schuurs 0.38974358974358975\n", - "Posch 0.38974358974358975\n", - "Bastoni 0.40318302387267907\n", + "Dimarco 0.5314685314685313\n", + "Di Lorenzo 0.47401247401247393\n", + "Hernandez T. 0.4567307692307692\n", + "Carlos Augusto 0.5261538461538462\n", + "Danilo 0.47401247401247393\n", + "Zappacosta 0.6959706959706958\n", + "Schuurs 0.5846153846153845\n", + "Posch 0.4871794871794871\n", + "Bastoni 0.6047745358090184\n", "Smalling 0.2740384615384615\n", - "Dumfries 0.3438914027149321\n", - "Romagnoli 0.3438914027149321\n", - "Pavard 0.0 (rookie)\n", + "Dumfries 0.42986425339366513\n", + "Romagnoli 0.5158371040723981\n", + "Pavard 0.10230769230769231 (rookie)\n", "Rrahmani 0.3023872679045092\n", - "Spinazzola 0.44970414201183434\n", - "Buongiorno 0.3438914027149321\n", - "Bremer 0.38974358974358975\n", - "Tomori 0.2657342657342657\n", - "Biraghi 0.2657342657342657\n", - "Mancini 0.3340659340659341\n", - "Darmian 0.3771712158808933\n", + "Spinazzola 0.6745562130177514\n", + "Buongiorno 0.5158371040723981\n", + "Bremer 0.5846153846153845\n", + "Tomori 0.4428904428904428\n", + "Biraghi 0.4428904428904428\n", + "Mancini 0.501098901098901\n", + "Darmian 0.5657568238213398\n", "Bakker 0.21923076923076926 (rookie)\n", - "Mazzocchi 0.4330484330484331\n", + "Mazzocchi 0.6495726495726495\n", "Doig 0.5314685314685315\n", "Calabria 0.4676923076923077\n", - "Acerbi 0.09429280397022333\n", + "Acerbi 0.2828784119106699\n", "Cuadrado 0.29702233250620347\n", - "Ebuehi 0.22485207100591717\n", - "Casale 0.3023872679045092\n", - "Holm 0.15346153846153848\n", - "Baschirotto 0.316008316008316\n", - "Bijol 0.3653846153846154\n", - "Thiaw 0.5846153846153846\n", - "Mario Rui 0.39860139860139854\n", - "Milenkovic 0.4330484330484331\n", - "Rodriguez R. 0.3340659340659341\n", - "Kolasinac 0.37202797202797205 (rookie)\n", - "N'dicka 0.10230769230769231 (rookie)\n", - "Scalvini 0.3653846153846154\n", - "Perez N. 0.3438914027149321\n", + "Ebuehi 0.44970414201183434\n", + "Casale 0.40318302387267907\n", + "Holm 0.4603846153846154\n", + "Baschirotto 0.395010395010395\n", + "Bijol 0.548076923076923\n", + "Thiaw 0.8769230769230768\n", + "Mario Rui 0.6643356643356643\n", + "Milenkovic 0.6495726495726495\n", + "Rodriguez R. 0.501098901098901\n", + "Kolasinac 0.558041958041958 (rookie)\n", + "N'dicka 0.3069230769230769 (rookie)\n", + "Scalvini 0.548076923076923\n", + "Perez N. 0.5158371040723981\n", "Kristensen 0.0 (rookie)\n", - "Izzo 0.29230769230769227\n", - "De Vrij 0.4330484330484331\n", - "Faraoni 0.38127090301003336\n", - "Toloi 0.09134615384615385\n", - "Kyriakopoulos 0.5115384615384616\n", - "Bellanova 0.6820512820512822\n", - "Mari' 0.38974358974358975\n", - "Dodo' 0.3543123543123543\n", - "Lucumi' 0.3543123543123543\n", - "Hien 0.1826923076923077\n", - "Hysaj 0.17194570135746606\n", - "D'ambrosio 0.40923076923076923\n", - "Luperto 0.3247863247863248\n", - "Djimsiti 0.36538461538461536\n", - "Marusic 0.3543123543123543\n", - "Martin 0.4384615384615385 (rookie)\n", + "Izzo 0.4871794871794871\n", + "De Vrij 0.6495726495726495\n", + "Faraoni 0.6354515050167223\n", + "Toloi 0.2740384615384615\n", + "Kyriakopoulos 1\n", + "Kyriakopoulos 0.423342175066313 (two seasons ago)\n", + "Bellanova 1\n", + "Mari' 0.5846153846153845\n", + "Dodo' 0.4428904428904428\n", + "Lucumi' 0.4428904428904428\n", + "Hien 0.3653846153846154\n", + "Hysaj 0.3438914027149321\n", + "D'ambrosio 0.6138461538461538\n", + "Luperto 0.4871794871794871\n", + "Djimsiti 0.6089743589743589\n", + "Marusic 0.5314685314685313\n", + "Martin 0.5480769230769231 (rookie)\n", "Mina 0.0 (rookie)\n", - "Toljan 0.3771712158808933\n", + "Toljan 0.5657568238213398\n", "Llorente D. 1\n", - "Martinez Quarta 0.21652421652421655\n", + "Martinez Quarta 0.4330484330484331\n", "Bastoni S. 0.16153846153846155\n", - "Dragusin 0.3230769230769231 (rookie)\n", - "Parisi 0.18601398601398603\n", - "Bradaric 0.3771712158808933\n", - "Olivera 0.38974358974358975\n", - "Gendrey 0.316008316008316\n", - "Kristiansen 0.5115384615384616 (rookie)\n", - "Beukema 0.47218934911242605 (rookie)\n", - "Dossena 0.5337792642140469 (rookie)\n", - "Pedersen 0.3175066312997347 (rookie)\n", + "Dragusin 0.4846153846153846 (rookie)\n", + "Parisi 0.279020979020979\n", + "Bradaric 0.5657568238213398\n", + "Olivera 0.4871794871794871\n", + "Gendrey 0.47401247401247393\n", + "Kristiansen 1 (rookie)\n", + "Beukema 0.7082840236686391 (rookie)\n", + "Dossena 0.8006688963210702 (rookie)\n", + "Pedersen 0.5291777188328912 (rookie)\n", "Juan Jesus 0.7794871794871795\n", - "Gyomber 0.4330484330484331\n", + "Gyomber 0.6495726495726495\n", "Alex Sandro 0.23384615384615384\n", - "Hateboer 0.0\n", - "Palomino 0.19487179487179487\n", + "Hateboer 0.17194570135746606\n", + "Palomino 0.38974358974358975\n", "Marchizza 1\n", - "Marchizza 0.6461538461538462 (two seasons ago)\n", - "Zappa 0.4676923076923077 (two seasons ago)\n", - "Gallo 0.3653846153846154\n", - "Caldirola 0.3771712158808933\n", + "Gallo 0.4567307692307692\n", + "Caldirola 0.4714640198511166\n", "Kalulu 0.17194570135746606\n", - "Erlic 0.41758241758241765\n", + "Erlic 0.6263736263736263\n", "Vojvoda 0.3023872679045092\n", - "Vasquez 0.4910769230769231\n", - "Cambiaso 0.3836538461538462\n", + "Vasquez 0.7366153846153846\n", + "Cambiaso 0.4795673076923077\n", "Pongracic 1\n", - "Viti 0.3410256410256411 (rookie)\n", - "Gatti 0.3247863247863248\n", - "Birindelli 0.3771712158808933\n", - "Azzi 0.7673076923076924 (rookie)\n", + "Viti 1 (rookie)\n", + "Viti 0.4603846153846154 (two seasons ago)\n", + "Gatti 0.6495726495726496\n", + "Birindelli 0.5657568238213398\n", + "Azzi 0.9591346153846154 (rookie)\n", "Masina 0.0\n", "Romagnoli S. 1\n", - "Romagnoli S. 0.6461538461538462 (two seasons ago)\n", - "Pezzella Giu. 0.7673076923076924\n", - "Sabelli 0.3069230769230769 (rookie)\n", - "Lazzari 0.20879120879120883\n", - "Bani 0.37202797202797205 (rookie)\n", + "Pezzella Giu. 1\n", + "Sabelli 0.5115384615384615 (rookie)\n", + "Lazzari 0.31318681318681313\n", + "Bani 0.558041958041958 (rookie)\n", "Djidji 0.0\n", - "Lazaro 0.38127090301003336\n", - "Augello 0.24885654885654884\n", + "Lazaro 0.6354515050167223\n", + "Augello 0.41476091476091476\n", "Zortea 0.9207692307692308\n", "Zortea 0.3762046521118139 (two seasons ago)\n", - "Dawidowicz 0.5083612040133779\n", - "Pirola 0.3372781065088757\n", - "Lovato 0.6877828054298643\n", - "Ruggeri 0.7794871794871795\n", - "Vina 0.47218934911242605 (two seasons ago)\n", + "Dawidowicz 0.7625418060200667\n", + "Pirola 0.5621301775147929\n", + "Lovato 1\n", + "Ruggeri 1\n", "Obert 1 (two seasons ago)\n", - "Terracciano F. 0.5846153846153846\n", - "Ebosele 0.6877828054298643\n", - "Patric 0.1623931623931624\n", - "Lykogiannis 0.2783882783882784\n", + "Terracciano F. 0.8769230769230768\n", + "Ebosele 1\n", + "Patric 0.3247863247863248\n", + "Lykogiannis 0.4175824175824175\n", "Pellegrini Lu. 1\n", - "Pellegrini Lu. 0.6820512820512822 (two seasons ago)\n", - "Magnani 0.4871794871794872\n", - "Ranieri L. 0.6495726495726496\n", - "Ranieri L. 0.5061947549127037 (two seasons ago)\n", + "Pellegrini Lu. 0.8525641025641026 (two seasons ago)\n", + "Magnani 0.7307692307692307\n", + "Ranieri L. 0.9743589743589742\n", + "Ranieri L. 0.35851413543721244 (two seasons ago)\n", "Calafiori 1 (two seasons ago)\n", "Monterisi 1 (rookie)\n", - "Ismajli 0.35076923076923067\n", - "De Winter 0.21923076923076926\n", + "Ismajli 0.4676923076923077\n", + "De Winter 0.6576923076923077\n", "Ehizibue 0.0\n", - "Ferrari G. 0.0\n", - "Venuti 0.0\n", + "Ferrari G. 0.17715617715617715\n", + "Venuti 0.18054298642533936\n", "Karsdorp 0.44970414201183434\n", - "Kjaer 0.5158371040723981\n", + "Kjaer 0.6877828054298643\n", "Gunter 0.0\n", "Soumaoro 0.0\n", "Zanoli 0.0\n", "Zima 0.3247863247863248\n", - "Hefti 0.548076923076923 (two seasons ago)\n", + "Hefti 0.7307692307692308 (two seasons ago)\n", "Ostigard 1\n", "Ostigard 1 (two seasons ago)\n", "Sambia 0.13286713286713286\n", - "Rugani 0.0\n", + "Rugani 0.3247863247863248\n", "De Sciglio 0.0\n", "Goldaniga 0.26573426573426573 (two seasons ago)\n", - "Florenzi 0.9743589743589745\n", - "Florenzi 0.2560815253122945 (two seasons ago)\n", - "De Silvestri 0.38974358974358975\n", + "Florenzi 1\n", + "Florenzi 0.4871794871794872 (two seasons ago)\n", + "De Silvestri 0.7794871794871795\n", "Fazio 0.41758241758241765\n", "Bereszynski 1\n", - "Bereszynski 0.1753846153846154 (two seasons ago)\n", + "Bereszynski 0.2630769230769231 (two seasons ago)\n", "Bonifazi 0.0\n", - "Walukiewicz 0.5314685314685315\n", - "Okoli 0.18054298642533936\n", + "Walukiewicz 1\n", + "Walukiewicz 1 (two seasons ago)\n", + "Okoli 0.5416289592760181\n", "Kumbulla 0.0\n", "Celik 0.1217948717948718\n", "Amione 0.11804733727810651\n", - "Daniliuc 0.0\n", - "Soppy 0.20461538461538462\n", + "Daniliuc 0.21652421652421655\n", + "Soppy 0.40923076923076923\n", "Haps 0.0 (two seasons ago)\n", "Coppola D. 0.3076923076923077\n", - "Cacace 0.4871794871794872\n", + "Cacace 0.7307692307692307\n", + "Cacace 1 (two seasons ago)\n", "Ebosse 0.14615384615384616\n", "Guessand A. 1\n", - "Cabal 0.5314685314685315\n", + "Cabal 0.7972027972027971\n", "Dermaku 0.0\n", "Tonelli 0.0\n", "Tonelli 0.20879120879120883 (two seasons ago)\n", @@ -3856,132 +3856,130 @@ "Bronn 0.0\n", "Guarino 0.0\n", "Carboni F. 1\n", - "Zaccagni 0.3340659340659341\n", - "Koopmeiners 0.3543123543123543\n", - "Luis Alberto 0.3340659340659341\n", - "Felipe Anderson 0.3076923076923077\n", - "Rabiot 0.3653846153846154\n", - "Zielinski 0.316008316008316\n", - "Barella 0.3340659340659341\n", - "Pulisic 0.5115384615384616 (rookie)\n", - "Orsolini 0.3653846153846154\n", - "Calhanoglu 0.3543123543123543\n", - "Strefezza 0.3340659340659341\n", - "Chukwueze 0.3318087318087318 (rookie)\n", - "Ferguson 0.3653846153846154\n", - "Candreva 0.3340659340659341\n", - "Frattesi 0.3410256410256411\n", - "Samardzic 0.316008316008316\n", - "Vlasic 0.25791855203619907\n", - "Bonaventura 0.38974358974358975\n", - "Politano 0.4330484330484331\n", - "El Shaarawy 0.40318302387267907\n", - "Mkhitaryan 0.3771712158808933\n", - "Aouar 0.5754807692307693 (rookie)\n", - "Malinovskyi 0.3069230769230769 (two seasons ago)\n", - "Gudmundsson A. 0.3410256410256411 (rookie)\n", + "Zaccagni 0.501098901098901\n", + "Koopmeiners 0.5314685314685313\n", + "Luis Alberto 0.501098901098901\n", + "Felipe Anderson 0.46153846153846145\n", + "Rabiot 0.548076923076923\n", + "Zielinski 0.47401247401247393\n", + "Barella 0.501098901098901\n", + "Pulisic 0.7673076923076924 (rookie)\n", + "Orsolini 0.548076923076923\n", + "Calhanoglu 0.5314685314685313\n", + "Strefezza 0.501098901098901\n", + "Chukwueze 0.41476091476091476 (rookie)\n", + "Ferguson 0.548076923076923\n", + "Candreva 0.501098901098901\n", + "Frattesi 0.5115384615384616\n", + "Samardzic 0.47401247401247393\n", + "Vlasic 0.42986425339366513\n", + "Bonaventura 0.5846153846153845\n", + "Politano 0.6495726495726495\n", + "El Shaarawy 0.6047745358090184\n", + "Mkhitaryan 0.5657568238213398\n", + "Aouar 0.7673076923076924 (rookie)\n", + "Malinovskyi 0.40923076923076923 (two seasons ago)\n", + "Gudmundsson A. 0.5115384615384616 (rookie)\n", "Kamada 0.3836538461538462 (rookie)\n", - "Pellegrini Lo. 0.1826923076923077\n", - "Kostic 0.158004158004158\n", - "Radonjic 0.41758241758241765\n", - "Baldanzi 0.44970414201183434\n", - "Lovric 0.316008316008316\n", + "Pellegrini Lo. 0.2740384615384615\n", + "Kostic 0.316008316008316\n", + "Radonjic 0.6263736263736263\n", + "Baldanzi 0.6745562130177514\n", + "Lovric 0.47401247401247393\n", "Lindstrom 0.0 (rookie)\n", - "Lazovic 0.09743589743589744\n", - "Pereyra 0.08597285067873303\n", + "Lazovic 0.29230769230769227\n", + "Pereyra 0.25791855203619907\n", "Renato Sanches 0.26688963210702343 (rookie)\n", - "Pessina 0.3340659340659341\n", - "Guendouzi 0.18601398601398603 (rookie)\n", - "Loftus-Cheek 0.4910769230769231 (rookie)\n", - "Zambo Anguissa 0.3247863247863248\n", - "Elmas 0.24358974358974356\n", - "Bajrami 0.6495726495726496\n", - "Ricci S. 0.41758241758241765\n", - "Colpani 0.4330484330484331\n", - "Ciurria 0.3247863247863248\n", - "De Roon 0.3340659340659341\n", + "Pessina 0.501098901098901\n", + "Guendouzi 0.37202797202797205 (rookie)\n", + "Loftus-Cheek 0.7366153846153846 (rookie)\n", + "Zambo Anguissa 0.4871794871794871\n", + "Elmas 0.405982905982906\n", + "Bajrami 0.9743589743589742\n", + "Ricci S. 0.521978021978022\n", + "Colpani 0.6495726495726495\n", + "Ciurria 0.4871794871794871\n", + "De Roon 0.501098901098901\n", "Pogba 0.9743589743589745\n", - "Cristante 0.3247863247863248\n", - "Locatelli 0.3653846153846154\n", - "Pasalic 0.1826923076923077\n", - "Lobotka 0.3076923076923077\n", - "Fagioli 0.3372781065088757\n", - "Ikone' 0.0\n", - "Ilic 0.6263736263736263\n", - "Ederson D.s. 0.3340659340659341\n", - "Reijnders 0.3610859728506787 (rookie)\n", - "Barak 0.09743589743589744\n", - "Saponara 0.2116710875331565\n", - "Mandragora 0.40318302387267907\n", - "Weah 0.423342175066313 (rookie)\n", + "Cristante 0.4871794871794871\n", + "Locatelli 0.548076923076923\n", + "Pasalic 0.3653846153846154\n", + "Lobotka 0.46153846153846145\n", + "Fagioli 0.5621301775147929\n", + "Ikone' 0.08857808857808858\n", + "Ilic 1\n", + "Ilic 0.4795673076923077 (two seasons ago)\n", + "Ederson D.s. 0.501098901098901\n", + "Reijnders 0.5416289592760181 (rookie)\n", + "Barak 0.19487179487179487\n", + "Saponara 0.423342175066313\n", + "Mandragora 0.6047745358090184\n", + "Weah 0.6350132625994694 (rookie)\n", "Bennacer 0.0\n", - "Duda 0.7794871794871795\n", + "Duda 1\n", "Castrovilli 0.0\n", - "Mckennie 0.5567765567765568 (two seasons ago)\n", - "Miranchuk 0.10583554376657825\n", - "Matheus Henrique 0.38974358974358975\n", - "De Ketelaere 0.3836538461538462\n", - "Paredes 0.4910769230769231\n", - "Sottil 0.4871794871794871\n", - "Klaassen 0.0 (rookie)\n", - "Thorsby 0.3507692307692308 (two seasons ago)\n", - "Nandez 0.37202797202797205 (rookie)\n", - "Tameze 0.1659043659043659\n", - "Marin 0.2657342657342657\n", - "Messias 0.0\n", + "Miranchuk 0.2116710875331565\n", + "Matheus Henrique 0.5846153846153845\n", + "De Ketelaere 0.5754807692307693\n", + "Paredes 0.7366153846153846\n", + "Sottil 0.6495726495726496\n", + "Klaassen 0.09300699300699301 (rookie)\n", + "Thorsby 0.43846153846153846 (two seasons ago)\n", + "Nandez 0.558041958041958 (rookie)\n", + "Tameze 0.3318087318087318\n", + "Marin 0.4428904428904428\n", + "Messias 0.12276923076923077\n", "Coulibaly L. 0.08351648351648353\n", - "Krunic 0.5083612040133779\n", - "Cataldi 0.40318302387267907\n", - "Strootman 0.3069230769230769 (rookie)\n", - "Duncan 0.35076923076923067\n", - "Freuler 0.10961538461538463 (rookie)\n", - "Gagliardini 0.6461538461538462\n", - "Kastanos 0.41758241758241765\n", - "Gyasi 0.2630769230769231\n", - "Zalewski 0.2657342657342657\n", + "Krunic 0.6354515050167223\n", + "Cataldi 0.5039787798408487\n", + "Strootman 0.5115384615384615 (rookie)\n", + "Duncan 0.5846153846153845\n", + "Freuler 0.21923076923076926 (rookie)\n", + "Gagliardini 0.9692307692307692\n", + "Kastanos 0.6263736263736263\n", + "Gyasi 0.3507692307692308\n", + "Zalewski 0.3543123543123543\n", "Harroui 0.4003344481605351\n", - "Frendrup 0.3318087318087318 (rookie)\n", - "Blin 0.3340659340659341\n", + "Frendrup 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0.32478632478632474\n", - "Fazzini 0.4175824175824175\n", - "Grassi 0.35076923076923067\n", - "Baez 0.7221719457013575 (rookie)\n", - "Deiola 0.3543123543123543 (two seasons ago)\n", - "Bourabia 0.0\n", - "Saelemaekers 0.0\n", + "Castillejo 0.3683076923076923 (rookie)\n", + "Rovella 0.3683076923076923\n", + "Pobega 0.6153846153846154\n", + "Miretti 0.5413105413105412\n", + "Fazzini 0.6959706959706958\n", + "Grassi 0.5846153846153845\n", + "Baez 1 (rookie)\n", + "Bourabia 0.1659043659043659\n", + "Saelemaekers 0.20461538461538462\n", "Maldini 0.0\n", "Kovalenko 0.17051282051282055\n", - "Maleh 0.3610859728506787\n", - "Bohinen 0.36538461538461536\n", - "Ranocchia F. 0.0\n", - "Folorunsho 0.45470085470085475 (rookie)\n", - "Adopo 0.6820512820512822\n", - "Romero L. 0.0\n", + "Maleh 0.7221719457013575\n", + "Bohinen 0.6089743589743589\n", + "Ranocchia F. 0.21923076923076926\n", + "Folorunsho 0.6820512820512821 (rookie)\n", + "Adopo 1\n", + "Romero L. 0.5115384615384616\n", + "Romero L. 1 (two seasons ago)\n", "Basic 0.0\n", "Asllani 0.2923076923076923\n", - "Sulemana I. 0.5754807692307693\n", + "Sulemana I. 0.9591346153846154\n", "Gaetano 0.0\n", "Obiang 0.0\n", - "Maggiore 0.1826923076923077\n", + "Maggiore 0.548076923076923\n", "Akpa Akpro 0.0\n", "Akpa Akpro 0.0 (two seasons ago)\n", "Urbanski 1\n", @@ -3989,97 +3987,97 @@ "Volpato 1 (two seasons ago)\n", "Vignato S. 1\n", "Hrustic 0.0\n", - "Viola 0.0 (two seasons ago)\n" + "Viola 1 (two seasons ago)\n", + "Rog 0.0 (two seasons ago)\n", + "Nicolussi Caviglia 0.0\n", + "Demme 0.0\n", + "Pafundi 0.3653846153846154\n", + "Adli 0.4871794871794872\n", + "Zerbin 0.2923076923076923\n", + "Carboni V. 1\n", + "Faticanti 0.0\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Rog 0.0 (two seasons ago)\n", - "Nicolussi Caviglia 0.0\n", - "Demme 0.0\n", - "Pafundi 0.0\n", - "Adli 0.0\n", - "Zerbin 0.2923076923076923\n", - "Carboni V. 1\n", - "Faticanti 0.0\n", - "Osimhen 0.3653846153846154\n", - "Martinez L. 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0.3023872679045092\n", "Lapadula 0.0 (rookie)\n", - "Jovic 0.0990074441687345\n", + "Jovic 0.198014888337469\n", "Abraham 0.0\n", - "Zirkzee 0.6153846153846154\n", - "Ngonge 0.8351648351648353\n", - "Petagna 0.0990074441687345\n", - "Simeone 0.35076923076923067\n", + "Zirkzee 0.9230769230769229\n", + "Ngonge 1\n", + "Petagna 0.29702233250620347\n", + "Simeone 0.5846153846153845\n", "Deulofeu 0.0\n", - "Pedro 0.24358974358974356\n", - "Shomurodov 0.8184615384615385\n", - "Shomurodov 0.6573550295857988 (two seasons ago)\n", - "Azmoun 0.13344481605351172 (rookie)\n", - "Cheddira 0.29702233250620347 (rookie)\n", - "Karlsson 0.4003344481605351 (rookie)\n", + "Pedro 0.3247863247863248\n", + "Shomurodov 1\n", + "Azmoun 0.26688963210702343 (rookie)\n", + "Cheddira 0.49503722084367247 (rookie)\n", + "Karlsson 0.6672240802675585 (rookie)\n", "Brekalo 1\n", - "Brekalo 0.3836538461538462 (two seasons ago)\n", - "Cambiaghi 0.31318681318681313\n", - "Henry 0.0\n", + "Brekalo 0.4795673076923077 (two seasons ago)\n", + "Cambiaghi 0.521978021978022\n", + "Henry 0.1826923076923077\n", "Mulattieri 0.423342175066313 (rookie)\n", - "Kean 0.20879120879120883\n", - "Karamoh 0.4175824175824175\n", - "Thauvin 0.7307692307692308\n", - "Kouame' 0.31318681318681313\n", - "Raspadori 0.4676923076923077\n", - "Colombo 0.18601398601398603\n", + "Kean 0.31318681318681313\n", + "Karamoh 0.5567765567765568\n", + "Thauvin 1\n", + "Kouame' 0.41758241758241765\n", + "Raspadori 0.7015384615384613\n", + "Colombo 0.37202797202797205\n", "Luvumbo 0.0 (rookie)\n", - "Mota 0.40318302387267907\n", - "Bonazzoli 0.5115384615384616\n", - "Djuric 0.41758241758241765\n", + "Mota 0.6047745358090184\n", + "Bonazzoli 0.7673076923076924\n", + "Djuric 0.521978021978022\n", "Banda 0.3247863247863248\n", - "Defrel 0.10826210826210828\n", - "Sansone 0.0\n", - "Pellegri 0.6495726495726496\n", - "Piccoli 0.47218934911242605\n", - "Success 0.29230769230769227\n", - "Botheim 0.41758241758241765\n", - "Lucca 0.876923076923077 (rookie)\n", - "Caso 0.2630769230769231 (rookie)\n", + "Defrel 0.32478632478632474\n", + "Sansone 0.3410256410256411\n", + "Pellegri 0.9743589743589742\n", + "Piccoli 0.9443786982248521\n", + "Piccoli 1 (two seasons ago)\n", + "Success 0.4871794871794871\n", + "Botheim 0.6263736263736263\n", + "Lucca 1 (rookie)\n", + "Caso 0.43846153846153846 (rookie)\n", "Jovane 0.0 (two seasons ago)\n", - "Soule' 0.47218934911242605\n", + "Soule' 0.9443786982248521\n", "Pavoletti 0.4003344481605351 (rookie)\n", - "Cancellieri 0.6138461538461539\n", - "Seck 0.3076923076923077\n", + "Cancellieri 0.9207692307692308\n", + "Seck 0.46153846153846145\n", "Alvarez A. 0.0\n", - "Ekuban 0.29230769230769227 (two seasons ago)\n", - "Destro 0.3438914027149321\n", + "Ekuban 0.38974358974358975 (two seasons ago)\n", + "Destro 0.5158371040723981\n", "Ceide 0.46153846153846145\n", "Ake' M. 0.0 (two seasons ago)\n", "Braaf 0.0\n", @@ -4088,36 +4086,36 @@ "Kaio Jorge 0.0 (two seasons ago)\n", "Vivaldo 0.0\n", "Players with low quantity of games:\n", - "Natan 0.0\n", - "Llorente D. 0.6666666666666667\n", - "Kamara H. 0.6666666666666667\n", - "Pongracic 0.6666666666666667\n", - "Wieteska 0.33333333333333337\n", + "Natan 0.33333333333333337\n", + "Kristiansen 0.6666666666666667\n", + "Azzi 0.908253205128205\n", + "Wieteska 0.5\n", "Lirola 0.16666666666666663\n", "Kabasele 0.6666666666666667\n", - "Obert 0.5\n", - "Zemura 0.5\n", - "Hatzidiakos 0.16666666666666663\n", + "Obert 0.6666666666666667\n", + "Zemura 0.8333333333333334\n", + "Hatzidiakos 0.5\n", "Carboni A. 0.33333333333333337\n", - "Calafiori 0.16666666666666663\n", - "Monterisi 0.6666666666666667\n", + "Calafiori 0.5\n", + "Monterisi 0.8333333333333334\n", "Tressoldi 0.0\n", "Vogliacco 0.0\n", - "Di Pardo 0.6666666666666667\n", - "Ostigard 0.5\n", + "Di Pardo 0.8333333333333334\n", + "Ostigard 0.8333333333333334\n", "Bisseck 0.16666666666666663\n", - "Oyono 0.6666666666666667\n", - "Ferreira J. 0.6666666666666667\n", - "Dorgu 0.6666666666666667\n", - "Touba 0.16666666666666663\n", - "Sazonov 0.0\n", + "Ferreira J. 0.8333333333333334\n", + "Touba 0.33333333333333337\n", + "Sazonov 0.16666666666666663\n", "Pereira P. 0.5\n", + "Walukiewicz 0.6666666666666667\n", "Cittadini 0.0\n", + "Cacace 0.9038461538461539\n", "Guessand A. 0.16666666666666663\n", + "Cabal 0.7703962703962706\n", "Missori 0.16666666666666663\n", - "Kayode 0.16666666666666663\n", - "Corazza 0.33333333333333337\n", - "Kristensen T. 0.0\n", + "Kayode 0.5\n", + "Corazza 0.5\n", + "Kristensen T. 0.33333333333333337\n", "Dermaku 0.16666666666666663\n", "Capradossi 0.0\n", "Bettella 0.0\n", @@ -4126,7 +4124,7 @@ "Guarino 0.0\n", "Carboni F. 0.33333333333333337\n", "Smajlovic 0.0\n", - "Matturro 0.0\n", + "Matturro 0.16666666666666663\n", "N'guessan 0.0\n", "Mateus Lusuardi 0.0\n", "Kalaj 0.0\n", @@ -4136,80 +4134,76 @@ "Pellegrino 0.0\n", "Comuzzo 0.0\n", "Pogba 0.3504273504273504\n", - "Ndoye 0.6666666666666667\n", "Mboula 0.5\n", - "Arthur Melo 0.6666666666666667\n", - "Musah 0.33333333333333337\n", - "Mazzitelli 0.6666666666666667\n", + "Musah 0.6666666666666667\n", "Jankto 0.5\n", "Reinier 0.0\n", - "Ramadani 0.6666666666666667\n", "Cajuste 0.0\n", "Mancosu 0.0\n", - "Brescianini 0.5\n", - "Boloca 0.5\n", - "Rafia 0.6666666666666667\n", - "Kaba 0.6666666666666667\n", + "Brescianini 0.8333333333333334\n", + "Boloca 0.8333333333333334\n", "Machin 0.0\n", "Iling Junior 0.0\n", - "Oristanio 0.5\n", - "Serdar 0.5\n", - "Payero 0.16666666666666663\n", - "Garritano 0.5\n", + "Oristanio 0.8333333333333334\n", + "Serdar 0.6666666666666667\n", + "Payero 0.5\n", + "Garritano 0.8333333333333334\n", "Racic 0.33333333333333337\n", "Infantino 0.5\n", - "Martegani 0.5\n", - "Kutlu 0.16666666666666663\n", + "Martegani 0.8333333333333334\n", + "Kutlu 0.33333333333333337\n", "Tchatchoua 0.0\n", "Quina 0.33333333333333337\n", - "Adopo 0.7042735042735042\n", - "Tchaouna 0.33333333333333337\n", - "Barrenechea 0.6666666666666667\n", + "Adopo 0.5\n", + "Romero L. 0.5737179487179487\n", + "Tchaouna 0.5\n", + "Sulemana I. 0.908253205128205\n", "Gelli 0.6666666666666667\n", - "Suslov 0.16666666666666663\n", + "Suslov 0.5\n", "Jagiello 0.0\n", "Akpa Akpro 0.0\n", "Urbanski 0.33333333333333337\n", "Volpato 0.7282051282051283\n", - "Vignato S. 0.33333333333333337\n", + "Vignato S. 0.6666666666666667\n", "Zarraga 0.33333333333333337\n", "Camara E. 0.0\n", "Amatucci 0.16666666666666663\n", "Pagano 0.5\n", "Prati 0.16666666666666663\n", + "Viola 0.33333333333333337\n", "Lulic K. 0.0\n", + "Pafundi 0.9070512820512819\n", + "Adli 0.5940170940170939\n", "Bondo 0.16666666666666663\n", "Carboni V. 0.33333333333333337\n", "Faticanti 0.0\n", "Gineitis 0.16666666666666663\n", "Belardinelli 0.0\n", - "El Azzouzi 0.5\n", + "El Azzouzi 0.8333333333333334\n", "Lipani 0.0\n", "Joselito 0.0\n", "Legowski 0.0\n", "Ibrahimovic A. 0.0\n", - "Okafor 0.6666666666666667\n", "Toure' E. 0.0\n", - "Krstovic 0.5\n", - "Ngonge 0.9413919413919412\n", - "Castellanos 0.6666666666666667\n", - "Almqvist 0.6666666666666667\n", - "Isaksen 0.5\n", + "Krstovic 0.8333333333333334\n", + "Castellanos 0.8333333333333334\n", + "Isaksen 0.8333333333333334\n", "Brenner 0.0\n", "Davis K. 0.0\n", - "Lucca 0.8717948717948717\n", + "Piccoli 0.7500986193293885\n", "Jovane 0.0\n", - "Cuni 0.5\n", - "Maric 0.5\n", + "Soule' 0.7500986193293885\n", + "Cuni 0.8333333333333334\n", + "Maric 0.8333333333333334\n", "Cruz 0.0\n", - "Van Hooijdonk 0.16666666666666663\n", - "Kvernadze 0.16666666666666663\n", - "Ikwuemesi 0.5\n", - "Puscas 0.0\n", + "Van Hooijdonk 0.33333333333333337\n", + "Kvernadze 0.33333333333333337\n", + "Ikwuemesi 0.6666666666666667\n", + "Puscas 0.16666666666666663\n", "Ake' M. 0.6666666666666667\n", "Vivaldo 0.0\n", "Bidaoui 0.0\n", - "Shpendi S. 0.5\n", + "Shpendi S. 0.8333333333333334\n", "Burnete 0.16666666666666663\n", "Corfitzen 0.0\n", "Stewart 0.0\n", @@ -4341,7 +4335,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "49c28b07", "metadata": {}, "outputs": [ @@ -4359,7 +4353,7 @@ " dtype='object', length=151)" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4370,7 +4364,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "d29102e5", "metadata": {}, "outputs": [ @@ -4522,7 +4516,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "f19304f6", "metadata": {}, "outputs": [], @@ -4562,7 +4556,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "370d41d2", "metadata": {}, "outputs": [], @@ -4578,7 +4572,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "id": "a7b1fb52", "metadata": {}, "outputs": [ @@ -4698,7 +4692,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "id": "5a7cf079", "metadata": {}, "outputs": [], @@ -4722,7 +4716,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "0bc0568b", "metadata": {}, "outputs": [], @@ -4844,7 +4838,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "id": "8aad9652", "metadata": {}, "outputs": [ @@ -4853,27 +4847,35 @@ "output_type": "stream", "text": [ "Epoch 1/1000\n", - "94/94 [==============================] - 4s 9ms/step - loss: 2.1251 - distribution_lambda_loss: 0.8284 - distribution_lambda_1_loss: 1.2967 - val_loss: 2.0962 - val_distribution_lambda_loss: 0.8157 - val_distribution_lambda_1_loss: 1.2804\n", + "96/96 [==============================] - 4s 11ms/step - loss: 2.1171 - distribution_lambda_loss: 0.8241 - distribution_lambda_1_loss: 1.2930 - val_loss: 2.0956 - val_distribution_lambda_loss: 0.8197 - val_distribution_lambda_1_loss: 1.2759\n", "Epoch 2/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1244 - distribution_lambda_loss: 0.8284 - distribution_lambda_1_loss: 1.2960 - val_loss: 2.1000 - val_distribution_lambda_loss: 0.8174 - val_distribution_lambda_1_loss: 1.2826\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1179 - distribution_lambda_loss: 0.8238 - distribution_lambda_1_loss: 1.2940 - val_loss: 2.0975 - val_distribution_lambda_loss: 0.8208 - val_distribution_lambda_1_loss: 1.2767\n", "Epoch 3/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1246 - distribution_lambda_loss: 0.8271 - distribution_lambda_1_loss: 1.2976 - val_loss: 2.1027 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2832\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1124 - distribution_lambda_loss: 0.8215 - distribution_lambda_1_loss: 1.2909 - val_loss: 2.0966 - val_distribution_lambda_loss: 0.8195 - val_distribution_lambda_1_loss: 1.2771\n", "Epoch 4/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1244 - distribution_lambda_loss: 0.8265 - distribution_lambda_1_loss: 1.2978 - val_loss: 2.1046 - val_distribution_lambda_loss: 0.8192 - val_distribution_lambda_1_loss: 1.2854\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1125 - distribution_lambda_loss: 0.8226 - distribution_lambda_1_loss: 1.2899 - val_loss: 2.1005 - val_distribution_lambda_loss: 0.8228 - val_distribution_lambda_1_loss: 1.2777\n", "Epoch 5/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1229 - distribution_lambda_loss: 0.8260 - distribution_lambda_1_loss: 1.2969 - val_loss: 2.1029 - val_distribution_lambda_loss: 0.8188 - val_distribution_lambda_1_loss: 1.2841\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1162 - distribution_lambda_loss: 0.8239 - distribution_lambda_1_loss: 1.2924 - val_loss: 2.0953 - val_distribution_lambda_loss: 0.8193 - val_distribution_lambda_1_loss: 1.2760\n", "Epoch 6/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1190 - distribution_lambda_loss: 0.8258 - distribution_lambda_1_loss: 1.2932 - val_loss: 2.1034 - val_distribution_lambda_loss: 0.8197 - val_distribution_lambda_1_loss: 1.2837\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1138 - distribution_lambda_loss: 0.8226 - distribution_lambda_1_loss: 1.2912 - val_loss: 2.0971 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2777\n", "Epoch 7/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1207 - distribution_lambda_loss: 0.8258 - distribution_lambda_1_loss: 1.2949 - val_loss: 2.1039 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2845\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1162 - distribution_lambda_loss: 0.8238 - distribution_lambda_1_loss: 1.2924 - val_loss: 2.0987 - val_distribution_lambda_loss: 0.8205 - val_distribution_lambda_1_loss: 1.2782\n", "Epoch 8/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1272 - distribution_lambda_loss: 0.8285 - distribution_lambda_1_loss: 1.2987 - val_loss: 2.1043 - val_distribution_lambda_loss: 0.8193 - val_distribution_lambda_1_loss: 1.2851\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1099 - distribution_lambda_loss: 0.8210 - distribution_lambda_1_loss: 1.2890 - val_loss: 2.1007 - val_distribution_lambda_loss: 0.8221 - val_distribution_lambda_1_loss: 1.2787\n", "Epoch 9/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1213 - distribution_lambda_loss: 0.8262 - distribution_lambda_1_loss: 1.2951 - val_loss: 2.1100 - val_distribution_lambda_loss: 0.8225 - val_distribution_lambda_1_loss: 1.2874\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1124 - distribution_lambda_loss: 0.8222 - distribution_lambda_1_loss: 1.2902 - val_loss: 2.1003 - val_distribution_lambda_loss: 0.8213 - val_distribution_lambda_1_loss: 1.2790\n", "Epoch 10/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1201 - distribution_lambda_loss: 0.8256 - distribution_lambda_1_loss: 1.2945 - val_loss: 2.1039 - val_distribution_lambda_loss: 0.8196 - val_distribution_lambda_1_loss: 1.2843\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1128 - distribution_lambda_loss: 0.8224 - distribution_lambda_1_loss: 1.2905 - val_loss: 2.0984 - val_distribution_lambda_loss: 0.8200 - val_distribution_lambda_1_loss: 1.2784\n", "Epoch 11/1000\n", - "94/94 [==============================] - 0s 2ms/step - loss: 2.1259 - distribution_lambda_loss: 0.8294 - distribution_lambda_1_loss: 1.2965 - val_loss: 2.1056 - val_distribution_lambda_loss: 0.8199 - val_distribution_lambda_1_loss: 1.2857\n" + "96/96 [==============================] - 0s 3ms/step - loss: 2.1155 - distribution_lambda_loss: 0.8234 - distribution_lambda_1_loss: 1.2921 - val_loss: 2.1033 - val_distribution_lambda_loss: 0.8219 - val_distribution_lambda_1_loss: 1.2814\n", + "Epoch 12/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1129 - distribution_lambda_loss: 0.8218 - distribution_lambda_1_loss: 1.2911 - val_loss: 2.1035 - val_distribution_lambda_loss: 0.8227 - val_distribution_lambda_1_loss: 1.2808\n", + "Epoch 13/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1085 - distribution_lambda_loss: 0.8194 - distribution_lambda_1_loss: 1.2891 - val_loss: 2.1037 - val_distribution_lambda_loss: 0.8229 - val_distribution_lambda_1_loss: 1.2808\n", + "Epoch 14/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1067 - distribution_lambda_loss: 0.8190 - distribution_lambda_1_loss: 1.2876 - val_loss: 2.1064 - val_distribution_lambda_loss: 0.8235 - val_distribution_lambda_1_loss: 1.2828\n", + "Epoch 15/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1131 - distribution_lambda_loss: 0.8217 - distribution_lambda_1_loss: 1.2914 - val_loss: 2.1054 - val_distribution_lambda_loss: 0.8233 - val_distribution_lambda_1_loss: 1.2821\n" ] } ], @@ -4947,7 +4949,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "id": "4e2bf9dc", "metadata": {}, "outputs": [], @@ -4967,7 +4969,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "id": "c2674211", "metadata": {}, "outputs": [ @@ -4975,13 +4977,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.14232313843838407\n", - "0.16748424431848907\n" + "0.14248994674439097\n", + "0.16946807672801856\n" ] }, { "data": { - "image/png": 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EHqdMX4VZKw5h7aEsAMDobtGYe18XNPFlt9VY8ZUnIiKPcvpqKaZ+nYKTOaXw1mrwyj0d8XDfOGg0zFdpzBiwEBGRx9jwRzae+/4gSvVVCA/UYeGkRCTFhbi7WeQBGLAQEZHbVRmMeG9TBhbtPA0A6BUfgvkTuiM80M/NLSNPwYCFiIjcKq9Uj+nL0rDndB4A4K/94/F8cgf4eGnd3DLyJAxYiIjIbdIvFOKJJSnIKipHE18vvHP/bRjVNdrdzSIPxICFiIhuOkEQsOz3C3htzRFUGIxoExaARZOTkBAR6O6mkYdiwEJERDdVeaUBr6z6A9+nXAQAjOgUgfce7IpAPx83t4w8GQMWIiK6aS7kX8PUJSk4crkYWg3wjxEdMHVQGy5ZphoxYCEioptix4kczPg2HUXXKxES4It547vj9lvC3N0sqicYsBARkUsZjQLmbz+F/27JgCAAXVsFY8GkJLRs5u/uplE9woCFiIhcpuh6JWYuT8fW4zkAgAm9Y/HqqI7QeXu5uWVU3zBgISIilziWVYypS1JwPu8afL21eHNMZ4ztEePuZlE9xYCFiIjq3Mq0i5j942GUVxrRqrk/Fk1KQueWwe5uFtVjDFiIiKjOVFQZ8ebao/hq73kAwMCEFvhwXDc0D/B1c8uovmPAQkREdSK7qBzTlqYgNbMQAPD0Hbdgxp0J8NJyyTLdOAYsRER0w347k4envklFbmkFAv288cG4bhh6a4S7m0UNCAMWIiKqNUEQ8Pnus5i7/jgMRgEdIgOxaFISWocFuLtp1MAwYCEiolop1Vfh+R8OYe3hLADAvd1bYs69XeDvyyXLVPcYsBARkdNO5ZRi6pIUnMophbdWg3+O6ojJfeJYYp9cRuvsDXbt2oVRo0YhOjoaGo0Gq1atUlz/6KOPQqPRKL769OlT43lXrFiBjh07QqfToWPHjli5cqWzTSMioptgwx9ZGPPxrziVU4qIIB2WT+mDh/u2ZrBCLuV0wFJWVoauXbti/vz5qseMHDkSWVlZ0te6devsnnPv3r0YN24cJk+ejIMHD2Ly5MkYO3Ys9u3b52zziIjIRaoMRsxdfwxTl6SiVF+FXvEh+Gl6fyTFhbi7adQIaARBEGp9Y40GK1euxJgxY6TLHn30URQWFlqNvNgzbtw4FBcXY/369dJlI0eORPPmzbFs2TKHzlFcXIzg4GAUFRUhKCjI4fsmIqKa5Zbq8fSyNOw5nQcA+Gv/eDyf3AE+Xk5/7iVScLT/dsk7bceOHQgPD0dCQgL+9re/IScnx+7xe/fuxfDhwxWXjRgxAnv27FG9jV6vR3FxseKLiIjqXlpmAUbN2409p/PQxNcL8yd0x8v3dGSwQjdVnb/bkpOTsXTpUmzbtg3vv/8+9u/fjzvuuAN6vV71NtnZ2YiIUK7Xj4iIQHZ2tupt5s6di+DgYOkrJob7UxAR1SVBELDkt/MY98lvyCoqR5sWAVj95O2457ZodzeNGqE6XyU0btw46efOnTujR48eiIuLw9q1a3Hfffep3s4yWUsQBLsJXLNnz8bMmTOl34uLixm0EBHVkfJKA15a+QdWpF4EAIzsFIl/P3gbAv183Nwyaqxcvqw5KioKcXFxOHnypOoxkZGRVqMpOTk5VqMucjqdDjqdrs7aSUREogv51zDl6xQczSqGVgPMGtkBUwa24SogciuXT0Dm5eXhwoULiIqKUj2mb9++2Lx5s+KyTZs2oV+/fq5uHhERyWw/kYN75u3G0axihAT4YsljvTF1UFsGK+R2To+wlJaW4tSpU9LvZ8+eRXp6OkJCQhASEoLXXnsN999/P6KionDu3Dm8+OKLCAsLw7333ivd5uGHH0bLli0xd+5cAMCMGTMwcOBAvPPOOxg9ejRWr16NLVu2YPfu3XXwEImIqCZGo4B5207hg60ZEASga0wzLJyYiOhm/u5uGhGAWgQsBw4cwJAhQ6TfzXkkjzzyCBYuXIjDhw/jq6++QmFhIaKiojBkyBAsX74cgYGB0m0yMzOh1VYP7vTr1w/ffvstXn75Zbzyyito27Ytli9fjt69e9/IYyMiIgcUXavEs9+lY9txcUXnxN6x+OeojtB5s8Q+eY4bqsPiSViHhYjIeUcuF+GJJanIzL8GnbcWb47pjAd7cAED3TyO9t/cS4iIqJH6MfUiZv94GPoqI1o198eiSUno3DLY3c0isokBCxFRI1NRZcQbPx/F17+dBwAMSmiBDx/qhmZNfN3cMiJ1DFiIiBqR7KJyPLE0BWmZhQCAGUPb4emh7eCl5Sog8mwMWIiIGom9p/MwfVkqcksrEOTnjQ8e6oY7OqjXuyLyJAxYiIgaOEEQ8NkvZ/DOhhMwGAXcGhWERZMSERca4O6mETmMAQsRUQNWqq/CrB8OYt1hsZr4fd1b4q17u8Dfl0uWqX5hwEJE1ECdyinFlK8P4PTVMvh4afDPezpiUp84Vq2leokBCxFRA7T+cBae+/4gyioMiAjSYcHEJCTFNXd3s4hqjQELEVEDUmUw4t8bT+CTXWcAAL3jQzB/QiJaBHKzWKrfGLAQETUQuaV6TP8mDXvP5AEAHh/YBrNGtIe3l8v3uSVyOQYsREQNQGpmAaYtSUV2cTkCfL3w7we74q4uUe5uFlGdYcBCRFSPCYKAJfsy8a+fjqDSIKBNiwB8OjkJt4QH1nxjonqEAQsRUT1VXmnASyv/wIrUiwCA5M6RePeB2xDo5+PmlhHVPQYsRET1UGbeNUxdkoKjWcXQaoDnR3bA4wPbcMkyNVgMWIiI6pntx3PwzPJ0FF2vRGiAL+ZN6I5+bcPc3Swil2LAQkRUTxiNAj7cehIfbTsJQQC6xTTDwkmJiAr2d3fTiFyOAQsRUT1QeK0Czy5Px/YTVwEAk/rE4pV7OkLnzRL71DgwYCEi8nBHLhdh6pIUXMi/Dp23Fm/d2wUPJLVyd7OIbioGLEREHmxFykW8uPIw9FVGxIT4Y9GkJHSKDnZ3s4huOgYsREQeSF9lwBs/H8WS3zIBAEPat8AH47ojuAmXLFPjxICFiMjDZBVdxxNLUpF+oRAaDTBjaDs8fUc7aLVcskyNFwMWIiIPsud0LqZ/k4a8sgoE+Xnjw4e6Y0iHcHc3i8jtGLAQEXkAQRDw6a4zeGfDcRgF4NaoIHwyKQmxoU3c3TQij8CAhYjIzUr1VfjH9wex/o9sAMB9iS3x1pgu8PflkmUiMwYsRERudCqnBFO+TsHpq2Xw8dLgn6M6YVLvWJbYJ7LAgIWIyE3WHsrCrB8OoqzCgMggPyyYlIjE2ObubhaRR2LAQkR0k1UZjHh34wl8uusMAKBPmxDMn5CIsKY6N7eMyHMxYCEiuomulugxfVkqfjuTDwCYMrAN/jGiPby9tG5uGZFnY8BCRHSTpGYWYNqSVGQXlyPA1wv/frAr7uoS5e5mEdULDFiIiFxMEAQs+e08/vXzUVQaBLRtEYBPJifhlvBAdzeNqN5gwEJE5ELXKwx4adVh/Jh6CQBwV5dIvPtAVzTV8d8vkTOcnjTdtWsXRo0ahejoaGg0GqxatUq6rrKyEs8//zy6dOmCgIAAREdH4+GHH8bly5ftnnPx4sXQaDRWX+Xl5U4/ICIiT3E+rwz3LdyDH1MvQasBXryrAz6ekMhghagWnA5YysrK0LVrV8yfP9/qumvXriE1NRWvvPIKUlNT8eOPPyIjIwN/+tOfajxvUFAQsrKyFF9+fn7ONo+IyCNsO34Fo+btxrGsYoQG+GLJX3vj8YFtWV+FqJacDvOTk5ORnJxs87rg4GBs3rxZcdm8efPQq1cvZGZmIjY2VvW8Go0GkZGRzjaHiMijGI0CPtx6Eh9uPQkA6B7bDAsmJiIq2N/NLSOq31w+LllUVASNRoNmzZrZPa60tBRxcXEwGAzo1q0b3njjDXTv3l31eL1eD71eL/1eXFxcV00mIqqVwmsVeGZ5OnacuAoAmNwnDi/fcyt03iyxT3SjXLrwv7y8HC+88AImTJiAoKAg1eM6dOiAxYsXY82aNVi2bBn8/Pxw++234+TJk6q3mTt3LoKDg6WvmJgYVzwEIiKH/HGpCKPm78aOE1eh89bi/Qe74o0xnRmsENURjSAIQq1vrNFg5cqVGDNmjNV1lZWVePDBB5GZmYkdO3bYDVgsGY1GJCYmYuDAgfjoo49sHmNrhCUmJgZFRUVO3RcR0Y36IeUiXlp5GPoqI2JDmmDhpER0ig52d7OI6oXi4mIEBwfX2H+7ZEqosrISY8eOxdmzZ7Ft2zanAwitVouePXvaHWHR6XTQ6VjGmojcR19lwL9+Ooql+zIBAEPat8AH47ojuImPm1tG1PDUecBiDlZOnjyJ7du3IzQ01OlzCIKA9PR0dOnSpa6bR0RUJ7KKruOJJalIv1AIjQaYMbQdnr6jHbRargIicgWnA5bS0lKcOnVK+v3s2bNIT09HSEgIoqOj8cADDyA1NRU///wzDAYDsrOzAQAhISHw9fUFADz88MNo2bIl5s6dCwB4/fXX0adPH7Rr1w7FxcX46KOPkJ6ejo8//rguHiMRUZ3acyoX05elIa+sAsH+PvjgoW4Y0j7c3c0iatCcDlgOHDiAIUOGSL/PnDkTAPDII4/gtddew5o1awAA3bp1U9xu+/btGDx4MAAgMzMTWm11vm9hYSEef/xxZGdnIzg4GN27d8euXbvQq1cvZ5tHROQygiDgk11n8O6G4zAKQMeoICyalITY0CbubhpRg3dDSbeexNGkHSKi2igpr8Q/vj+EDUfEUeP7E1vhrXs7w8+Hq4CIboRbk26JiBqSk1dKMGVJCs5cLYOPlwavjuqEib1jWbWW6CZiwEJEZMfaQ1n4xw8Hca3CgMggPyyclIjusc3d3SyiRocBCxGRDVUGI97ZcByf/XIWANC3TSjmTeiOsKYsp0DkDgxYiIgsXC3R46lvUrHvbD4AYMqgNvjH8Pbw9nJpcXAisoMBCxGRTMr5AkxbmoIrxXoE+HrhvQe7IrlLlLubRdToMWAhIoK4ZPnr387jjZ+PotIg4Jbwplg0KQm3hDd1d9OICAxYiIhwvcKAF1cexsq0SwCAu7tE4Z0HbkNTHf9FEnkK/jUSUaN2Pq8MU75OwfHsEnhpNXhhZAf8dUA8lywTeRgGLETUaG09dgXPLE9HSXkVwpr6Yt74RPRt6/z+Z0TkegxYiKjRMRgFfLj1JD7aKu4InxjbDAsmJiEy2M/NLSMiNQxYiKhRKbxWgRnfpmNnxlUAwMN94/Dy3R3h680ly0SejAELETUaf1wqwtQlKbhYcB1+PlrMubcL7kts5e5mEZEDGLAQUaPw/YELeHnVH9BXGREb0gSLJiWhYzQ3SiWqLxiwEFGDpq8y4PWfjuKbfZkAgDs6hOO/Y7shuImPm1tGRM5gwEJEDdblwut4YmkqDl4ohEYDPHtnAp4acgu0Wi5ZJqpvGLAQUYP066lcTF+WhvyyCgT7++DDh7phcPtwdzeLiGqJAQsRNSiCIGDRzjP498bjMApAp+ggLJqUhJiQJu5uGhHdAAYsRNRglJRX4rnvD2LjkSsAgAeSWuHNMZ3h5+Pl5pYR0Y1iwEJEDcLJKyWY8nUKzuSWwddLi1f/1BETesWyxD5RA8GAhYjqvZ8PXcasHw7hWoUBUcF+WDgpCd1imrm7WURUhxiwEFG9VWkw4p31x/G/3WcBAP3ahmLe+O4Ibapzc8uIqK4xYCGieimnpBxPfZOG38/mAwCmDmqL54YnwNuLJfaJGiIGLERU76Scz8e0pam4UqxHU5033nvwNozsHOXuZhGRCzFgIaJ6QxAEfLX3PN74+SiqjAJuCW+KRZOScEt4U3c3jYhcjAELEdUL1ysMeHHlYaxMuwQAuPu2KLx7/20I0PHfGFFjwL90IvJ453LLMHVJCo5nl8BLq8Hs5A54rH88lywTNSIMWIjIo205egXPfpeOkvIqhDX1xfwJiejTJtTdzSKim4wBCxF5JINRwAdbMjBv2ykAQGJsMyyYmITIYD83t4yI3IEBCxF5nIKyCsxYno5dGVcBAI/0jcNLd3eErzeXLBM1VgxYiMij/HGpCFOXpOBiwXX4+Wgx974uuLd7K3c3i4jcjAELEXmM7w5cwMur/kBFlRFxoU2waFISbo0KcneziMgDOD2+umvXLowaNQrR0dHQaDRYtWqV4npBEPDaa68hOjoa/v7+GDx4MI4cOVLjeVesWIGOHTtCp9OhY8eOWLlypbNNI6J6Sl9lwOwfD2PWD4dQUWXE0A7hWPNUfwYrRCRxOmApKytD165dMX/+fJvXv/vuu/jPf/6D+fPnY//+/YiMjMSwYcNQUlKies69e/di3LhxmDx5Mg4ePIjJkydj7Nix2Ldvn7PNI6J65lLhdYxdtBfLfs+ERgP8fVgCPnu4B4L9fdzdNCLyIBpBEIRa31ijwcqVKzFmzBgA4uhKdHQ0nnnmGTz//PMAAL1ej4iICLzzzjuYMmWKzfOMGzcOxcXFWL9+vXTZyJEj0bx5cyxbtsyhthQXFyM4OBhFRUUICuKnMqL64NdTuZi+LA35ZRUI9vfBhw91w+D24e5uFhHdRI7233Wacn/27FlkZ2dj+PDh0mU6nQ6DBg3Cnj17VG+3d+9exW0AYMSIEXZvo9frUVxcrPgiovpBEAQs2HEKkz/fh/yyCnRuGYSfp/dnsEJEquo0YMnOzgYAREREKC6PiIiQrlO7nbO3mTt3LoKDg6WvmJiYG2g5Ed0sxeWVmLokBe9uOAGjADyY1Ao/TO2HmJAm7m4aEXkwlxQ1sCyXLQhCjSW0nb3N7NmzUVRUJH1duHCh9g0mopsi40oJxsz/FRuPXIGvl7hk+d0HboOfj5e7m0ZEHq5OlzVHRkYCEEdMoqKqt3rPycmxGkGxvJ3laEpNt9HpdNDpdDfYYiK6WX46eBmzfjiE65UGRAf7YcGkJHSLaebuZhFRPVGnIyzx8fGIjIzE5s2bpcsqKiqwc+dO9OvXT/V2ffv2VdwGADZt2mT3NkRUP1QajHjj56OYviwN1ysNuP2WUPw0vT+DFSJyitMjLKWlpTh16pT0+9mzZ5Geno6QkBDExsbimWeewZw5c9CuXTu0a9cOc+bMQZMmTTBhwgTpNg8//DBatmyJuXPnAgBmzJiBgQMH4p133sHo0aOxevVqbNmyBbt3766Dh0hE7pJTUo6nlqbh93P5AIAnBrfF34clwNuLJfaJyDlOBywHDhzAkCFDpN9nzpwJAHjkkUewePFizJo1C9evX8e0adNQUFCA3r17Y9OmTQgMDJRuk5mZCa22+h9Wv3798O233+Lll1/GK6+8grZt22L58uXo3bv3jTw2InKjA+fyMW1pKnJK9Giq88Z7D3bFyM6RtTpXRkYGTp8+jVtuuQXt2rWr45YSUX1wQ3VYPAnrsBB5BkEQ8OWec3hz7TFUGQW0C2+KTyYnoU2Lpk6fKz8/HxMmTcDG9Ruly0Ykj8CypcvQvHnzumw2EbmJo/039xIiojpzraIKs388jNXplwEA99wWhXfuvw0Butr9q5kwaQK27NoC3AcgDsB5YMvGLRg/cTw2rNtQdw0nIo/HgIUapc8//xw7duzA0KFD8eijj7q7OQ3CudwyTF2SguPZJfDSavDiXbfiL7e3Vi1PUNM0T0ZGhjiych+A20wX3gYYBAM2rtyIkydPcnqIqBFh5hs1KikpKfD188Vf//pXLFmyBH/+85/h6+eL9PR0dzetXtty9ApGzd+N49klCGuqwzd/7Y3H+sfbDFby8/Mx8q6RaN++Pe666y4kJCRg5F0jUVBQoDju9OnT4g9xFidoLX6TJ/8TUcPHERZqVPre3heVqFRMMVSurUSvPr1QUV7h7ubVOwajgA+2ZGDeNjF4SIprjgUTExER5Kd6mwfHPojtv25XvAab1m3CA2MfwNbNW6Xj2rZtK/5wHtUjLABwTvx2yy231OVDuemYSEzkHI6wUKPx+eefo1JfCdwNsQMMNn2/C6jUV2Lx4sVubV99U1BWgUe/+F0KVh7t1xrL/tbHbrCSkZGBbVu3QbhLULwGQrKAbVu24eTJk9KxCQkJGJE8Al4bvYCDAIoAHAS8NnlhRPKIetvJOzrCRERKDFio0dixY4f4g8oUw9atW0GOOXyxCPfM241fTubCz0eLD8Z1w2t/6gRfb/v/Unbu3Cn+oPIaSNebLFu6DHcOvBNYCeC/AFYCdw68E8uWOraLuydSJBI/C+A+YMsuMZGYiNQxYKFGY/DgweIP5y2uOCd+Gzp06E1sTf21fH8m7l+0B5cKryMutAlWTrsdY7q3dO4kKq+BJVdWXdi4cSP+9a9/WVXZdiVzIrFhhEExwmQYbsDG9RsVI0xEpMQcFmo0HnvsMTzx5BOoXFsJFANoCqAMwC7AR+fjsauFPCXXobzSgNd/OoJlv4sbjd55azjeH9sNwf4+Dp9j0KBBgAbAWgACxJGVcwDWAdCYrpeRRiOGAQgAcK16NKK2y5pPnz6N3n17I+9qnnRZaItQ7N+3H/Hx8bU6pzP3DcBuInF9neoicjUGLNSg1NS5b964GUOGDoGwpfqTu8ZLgy3bttT6nLU9tiaeVDRtd+oRvLT+HM6XABoN8PdhCZg2+BZotfZ3YbdJAFAFcZrHzMt0uYy0rDkSgGwQxBBRPRpRm+e4d9/eyCvOUyT95q3NQ8/ePZGbk+v0+ZxR20RiTwlaidyJU0LUIDiayDj3nbnQ+mkV+QNaPy3mvD2n1ud09lhHeUKuQ35+PgaM/RvGLz6I8yWA4XoxWp1ehYndw2oVrHz33XfiD6MBTAIwGMBkAH+yuB6m0QgNxGRb2XOAYgCa2i1r3rhxoziyYiPxOu9qnsunh5xNJK7N+yojIwPr16/n9BI1OAxYqEFwpHN3Nn/AmYDhgbEPYOPmjYrLNm7eiAfGPlCrx+MJuQ5Go4ChT7+LzNaj4NUkGPqsk8ha/Ax2r/zfDT0uAEAagCUAdgD4GkC6xfWAuN+YACAZyuBiJAAB8PZ2foB437594g8qUzJ79+51+pzOciaR+MGxD2LT9k2K9+Cm7ZtsPv9cfUQNHQMWqvcc7dydKUSmOGclgC0ADLYDhoyMDGzfut1qSgMCrJbqOsrdRdOKyysxcdFOFLQaAI3WC6VFm5AdOguGO3MAb2DbVtuPq6ZP91IhuUyLKzItrgdgNBrFH1Seg6qqKuceFICWLU3JwSpJv7GxsTZv58yoRU3HNm/eHBvWbUBGRgbWrVuHjIwMbFi3wWqaz5kl4EDdB81EnoYBC3m8mjoAReeeC+AkgDxYde6K/AG5c+I3ef6AdM41AH4CcBjAatPPUAYMO3fuFKcufKCcuvABoLFequsIaTdzlbbWZnTBUSeySzB6/q/Ym1kGoaoSeVfmIS/yIyC4Uuw4kwEIysfl6Kf7oqIiu89VUVGRdKwzr5dZTe+V6Ojo6qRf2ZSMOek3IiJCcbwrpwXbtWuH5ORk1ZwUZ5aAZ2RkYPu27WJWovx5tRNcOqM+TTPVp7aScxiwkMdytAOQOrZlAOYDWApgHoBvxIvNHVtCQgJ69Ophs7Pq1buXouNo27at2LF5QdkBeAHQKDvLK1euiKMrd0E5dWHq2K9cueL0Y8/MzBTvf51FW9eL93/+vGUvXjfWHLyMMR//irO5ZQjyrkL20lkoba781G7uMOUc/XSfk5NT/Vz5Q5waCoDN5yohIQF3DL0DmnUaYDfEaaNfAc16De648w7F6+Xoe0WaZmoOxZQMmsHmNJMz04IuyzlyYAn4zp077b4HaxM0A/Vrmqk+tZVqh6uEyGM5ulNvQkICvHXeqCqoUhyLtYC3zlvRsR04cEAMBCxWqPy+/3fFff/yyy9iB2BOzoTpuyDe9tdff5XOK30qV/kkbPmp3WECgCiLtsYDOFu709lTaTBi7rrj+L9fxZP3vyUMM3oFoddbJ8XnMhpAAYAQABfF25iXIEuf7n0hJs/Knn/zp3vzcyXVVdkA4JqsAU1U2lVVCaFCEKfkTAStgMrKSsVxjr5XMjNNc0/jIa5Uyjc9Jm8A/1UGgs5svlibjRprWvnj7BJwANWjjObXqrX1Ic6oT7tl16e2Uu1whIU8kjNJpxs3bkSVvsrmyo8qfZW08uOtt94CjLC9QsUIvP3229I5V69eLf6gEoSsXFkdRUh5DyqfhOPiLE9S/RjVhq6lzqg7gOkAJpq+d7O4vg7kFJdjwme/ScHKtMFt8eVfeiHYz0s8YDWUI1drlLeXPt3beP4tP90nJCSInbABypErAwCN6XqTjIwM/LLrFzEQkh/rC/yy6xfpeatVgvJ5AKEA2pm+n7M+xNGpRqtj5Wwc6+hIQEJCApqHNK9eAm4eDaoCmoc0VwQ50vtBZZSxNu8XxfMaDSAHQEvPLHJX2yR1Th/VLwxYyCM50wGsXbvW7rE///wzAGDNGlNPq7JCZdWqVdJN27RpI/6gEoRI18OUHGonL8IyOdSRDishIQF33GmaDrkIIBzARdvTITdi/7l83D1vN/afK0CgzhufTE7CrJEd4KXVVC8rVsk3Mb8G0jSOSsduNSVmJ7iRc3Saw5nAQhq1UJlqk3fsjk41Ko51IN/G0amjjIwMFOQViAG2PGj9E1CQV2C171JIWIg4siJ/rQqBkLCQWr1fpOc1zeLxp4sXqyV+uyMIcDZJndNH9ROnhMgjKToAfwCXAMQAKBUvlncA4eHh1cfaKMZlvr5Dhw7i1E8WFJVTsQuARrzebNq0afjwow/Fjk1eFfcX8dhp06ZJx1rlRZhFALhSQ16EnaHrzz75DL369ELeyuqKrCEtQvC/T/+n/sQ5SBAELN5zDm+tPYYqo4CEiKZYNCkJbVo0tX5c5oABUEyLWSX+LgOQLfvdxkzYpk2bxB9Upi42btxofSOVTshMEVjYuH+r5FwB4sovi2lBy4ApISEBoS1CkVeQZzXVGNoiVBEEmOurbNm4BQbBIE3feG3ywp3Jd9qeOrIctbCYOlJ0wvIZMNPjl1fFzcjIQH5uvtV5cReQvzK/VkX2pDyuLCgfvykQt3xe3Vno0NmCfJw+qp8YsJBHSkhIQP+B/bF71W5xGsdMCwwYNEDxz7dnz5525/p79eoFAAgJCRGvbwZF5VRzYBEWFiZdJOWwVECRPwGteB/yHBZFXsRViCMiMQDCcEN5EX99/K9iZymTV5CHvz7+V2zdXPuNGq9VVGH2j4exOv0yAOCe26Lwzv23IUCn/HcgPS6VgMH8uCIiIsTn3/zpXtaxW668KS4uFn9QCS5KSkqki6TRDpVOyHy9IrCQB6I7rQMLKQiIhTIXyPS7ZRCQdzXP6rWCAOStzLMKApYtXYbxE8dj48rqDvvOZGV9FcWoxY+y+48Xv8nv//Lly3afK/nIlTPndYqdgNWSO4MARwNGoHb5RuQZOCVEHuvo0aM2pyOOHDmiOM5oNCrLvcvm+iFUT8msX79e7FgLLc5ZBEAjm1oCsHTpUvFYX4id4BgAw02/a4AlS5ZYN3gZlFNN31gf4ujQtauWqZ7NLcO9H+/B6vTL8NZq8M97OmLe+O5WwYpCDatUpJU/d0O58sc0zZObW13uPiQkRBncyKYuoDFdb6KYFpNN31hOi0mBRXOIgegqAJsANBOr18qfK2m5eJbFYzLFBvJRI2enGcz1VTZu3IjXX38dmzZtsqqvYjVqYX78WbAatTh48KD4w1WL+zc9nWlpabU6r6NqXbfITYUOHS3I5+4aR1R7HGEhj7Rx40a7Q9ybN2/GsGHDAACpqanijUZDHDo/B6ANxHB8pfiPPzk5WSxKZucTo7xoWUFBgd3RmLy86pEPrVZrd4RB3gkq6qvYGDUwH2uVv2HR1p07d9r8FLhx40bs27cPffv2lZ4fs01HsvH37w6iRF+FFoE6fDwhEb3iQ6zOYabI95CPXFnke2zdahrtUVn5s2XLFrzwwgsAgOvXr9tdfXXtmvwEwA/f/WA1ajE8ebj1qIUG1SX8zc+/qZ3y0QUp30iAzddKnm/k7DSDw1MiDo5aSO8VFVbXOzEaYmZvpZLi8dtYJWazbpGdIMDVoxbmgPHkyZM4deqU6uqr2u7nRO7HgIU8klRCXWWIe+/evVKHfPz4cfFCeYd5GFKHaR6R8fPzEy9Q+acqXW/+2U4nKD/24MGDdjvhtLQ0aSdoqb7KeihzY3bDdn2VGvI3zOztQBwb1xr/2XwCH28XO5Uecc2xYGIiwoP8bJ/MJCEhAf0H9Mfu3buVnZ4WGDCwelquvLxcufLHIgiQByHSlI/K4yotLVVcLC2DtsOqhD+gmmuTmppq97UyB7fmx+/oNAPg2JSI0x27Oel5NJQ5JEblzR0pMmdZt6am4CohIQEDBg7AL6t/EV9bMy/raVlPCgLatWtnNzhSvK7FBulv0GuP7deVPAenhMgtalpJ0Lt3b7tD3H379pWODQsLq+4w5dM3pqWy5hyK69evizdQmeKQd6zSaEwylCM8pn1s5J9upeqsKqtUpLwNM8H0tQXi9MVmiB2QrG9W5G/YaKvlMtVefXpV70Bseq7yivPQc8BgPPrF71Kw8mi/1lj2eJ8agxWzqqoq8bmV0wBVldUjEVajJhYrf8rLy6VjDQaD3cdluaLKkRU1zpTwV+wlZOO1stxLyNFpBkenRJxZTZSXl1c9aiJ/D5pWSeXn50vHStOkKue1nEZ1dKXSkaNHbE5LWp7P2U0d3W3B/AVo1qSZ4m+wWZNmWPjxQvc2zIN5whJwjrDQTeXUSgIHh7gPHz5cvUrHxvSNORegrKysOjlXPrphWiUkD1jOnjVlZKqM8Jw5c0a6SOowVZIjpeshmz5SmZIwjwacPXvW7nTMuXPnpE5AMX0me658fW+BX7MX8cvJXPj7eOHt+7tgdLeWcFRGRgZ+2/ubmLcj/4S/VuzYzcmJV6+akixUAgZ5DovBYLD7uKSABo4nRzrz6V5ajq7yWsmXqwOOTzM4NXJi5/HLtW/fXvxB5T0or1kjTXWttzjvBvG88vego8+r2vsKgvW0LOBY0rGn+Nvjf0N+Sb7ibzB/Xf4NJ7Q3RO5c/WWJIyx0Uzn6yc6ZXXWvXr2qnL4xfxIsBqCB1KFmZ2dXL2mVj25UAhBM11ueU2WER+qkYepY7CSSyjuWHTt2VI9GWOTmQAC2b98OwJQAbCeR2FxbRjrW4rlqWjUMkbHvwjs4HAHGMqx8sp9TwQoAfPfdd3bb+t133wGQjaCofLqXRrbMBEj5RdLjMq2+knMqOdIcBMg+3dsKAqZNm2b3tZIvV5erad8fR0dOTp8+raxgbH78UQAE5WOSVr+pvAfNq98AwMvLSzxvsMV5g8Tz+vj4SMc6+rw6u7O1o5s6upuzm0o2di7bcqIWGLDQTePMSoLevXuLP6h0APIpoYCAAGUOg3lKwjR907SpWFtEmt6wUTkVGijKvRsMBrtFy+QjAevWrbM7JbJ+/XrpWCmxNw02i3GZSbVlLFM4BIvrYZHIK/ggpGI6QitnQKPxxbWTv2FI5e/oEBkESzUN8R44cMBuW/fv3w9AlsOiUjjPKmDRQJwCux1AX9N3I6yCC2lZr8p7wLysV0pQVgkC5JV2v//+e7uv1YoVK2w+FzU9V4opEdm+R5ZTIlJgo7JKST4atH79ervvwXXr1knHHjp0qHoFnHladBikFXBWK4qAGoMrZ/4G5RzJO3InZzaVbOw8YfWXHAMWummc+cQ8YsQIhLYItdkJhrYIVQxFO1ovBIDdDsAmB5Jepc5A5VhpFRNkK29UPjUPGTIEAJCSkmK3yqy8A+rUqROgAbx+aYHIwncRaBgBQTCiYM+XuLryLXTrVF0QD3C8ymdgYKDdtgYHBwMwBYLmKTl5wNAMimXlEsF03a8A9pq+B8PqNTh48GD1NMdG09cmSNMc8ucAgOo2BnJff/21+IPKa/Xll18qLnamIqojeREJCQnw0fmIj1WebwXAR+ejGME5dOiQ3bYePnxYuujatWvVQZt5afdmSEGbPI/I0eBqxIgR8NZ52/wb9NZ5W61Cq3fVY1UCMarmaUvAGbDQTeNMwiEA7N+3H6FBoYpOMDRIXPkiFxgYaPe85hEWSRzEZMsdAE7D/gZx56FMzjxnfYg0auLAP0CpZoxK0GTu3KXCdSrH7dixQzrnoEGD4BfXDVEPfQCdXzsYrhUh57tXUfzr94AgWCXoOjrEGxYWZrcNLVq0AADodDrxBuOh3KNpApTXS08YVKdk5MLDw6uL9+01fe0x/S5UjzIpll/LtjGwVW5fyqdRea3k+TaK50oWXKgNh097ahoKrxUqHlfhtUI88eQT0jEbN25Epb7SZs2YSn2ltO8VANx2221229qlSxfpIuk9qBK0WY56OBJcZWRkiHt0masCmwPRSnGPLstP154ydVDTaFhsbKzdKUS1vb8aI2f/Z7sak27ppklISMAdQ+/A9nXbxX+grQGcEwuBDblziFV+QHx8PHJzcrF582bs3bvXZm0RQLYEeR2qh9o1AFLF702aiOubNRqNeL8LAZTLTmDqT+V1WCSrYbWk01KTJk1wvfy6aqVd8/0DFvvuyLW2uN5M5ThzW41GAcsO5iN87L+g0WihzzqJq6vmwFB81WZbnanyKXXeNbQ1LCxMXAmlkshqDmwk8ikZ0/3bSqaOiooSX0dvWCX9wgi0bCnm5Jg3CSwoLLAqt2+5SSAAu8mpctJzFQlFMrchono43Nndmvft22d3ubx8uX5ycrK4PYTK++quu+6S2iT9DawFMABiQnkOpIRyf39/xWNzJOlUmhoZA7EQ4AVUb4+xUrlU2hOqxzqaHJqZmWl3J3Sr0gKNmLNL+12NIyx0c2kAoUpQfGITquzPectXONhy6tQp8R+QHspP4noAAqRPWoIgKFfomD/dm9tlOfdu7iwtlnRadmze3t52E2TlCY/Spz6VTyzm6ysqKuweV1FRgeLySkxZkoIvUvKg0WhRcnAjspfOEoMVQKrVYS7aBjg3xCvtraTShk6dOgEwBSR2Rk2sAhY79y/naIKytEmg5d2EWW8S6O/vbzc5Vd6xKwrSyadvTMnctdmtWUqOVcm38vX1lW4qdawqU23yjnXo0KHKrSRWQQyyTKNR8kDf6aTTOABtIY6ctYXN18oTpg6cHuFxYAqRHF/afzNwhIVumoyMDGzbsk38h9ISQD6kypnbVm6z+hRmrxhafHy8dNn169erk2nvhvKTeIVF9VQHP907c6xU9Xa09ePCSuU0w4kTJ+x+ws/IyAAA6PV6u/sjVQWE40/zduNc3jUIhkrkb16I0uObrEciKsR9j8ycqV4aHh5udwmuee+loqIiu8+VVKdG7rzsWMDm9FlWlmm4LA02l/Wak3KlzlI5iCAVDrRZjK0Q1fsOyTa1lJMK0gXDern8dWVBOkeXVtc0wiY9ZkAs2AeIU21VqH5feQP4r/i6/vWvfwUAJCYmmhoN5Yig6feuXbtKFzlaZC42Nrb6Mdl4r8inTm5G4Th7VXmdGeFRTCEmQ7WCM4kcXdp/M9R5wNK6dWubQ2rTpk3Dxx9/bHX5jh07pERDuWPHjil2z6X6T/EpLBhAqOkK07vQsmNJ7JGI4hJl0bW8/Dx0T+yOwoJC6TJpxY58L5sYiJ/EVypX9Ej3L9faTqPjYHNXYTkpqVTlccmTTps2bVpdOE4e+OjEy8zTR4GBgWIgVAWraY4mHQYiLHkGzuVdQ8tm/ji5+FWUnkixWS/D8vEnJCSgeWhzFKwusJrqah6qnD65cuWKcgmyWRPx3ObOt6Y6LDk5OcrL7QRiNpOfM+3/Lu2jcxlAP1S3+QCs9tGRnv9KKIMQ027N8nwnaWTPovnmvX3kr6ujQ+c1bc0gL0j4+++/Vx8bbX3sb7/9Jl2UmppqtyquvIKvpIagUXr8KtOitXn8teHIVI8zdXDMU9PbdmxTvq+9gTuG3uFxRe48RU0VhG+GOg9Y9u/fr/gH+ccff2DYsGF48MEH7d7uxIkTCAqqXnppcxiZ6jVnPoVt3LgRxYXFNvMwigqLrIpWAVDdy8aKA5/uJSp5GbU9rzTaU2FxhWlFtXkJsDQ1MRri47gIIMYLzf0fQ1DzPwEABrQLw4cPdUenDy+Jx6r8s5aPBGRkZKAgv0AcjboDip2NC/ILbOewyPN9ZL9bJqiqPX6r3CD59JmZKWCQCwgIsNsJK5KpBYjH7pGdQGd9zpYtW4pbOVgGRqbfY2JipIukIn8+sDlyJ39eAccKp5lXdKkFbOZpNkAWCKoEDPLn//fff7dbaFFeM8XRPaKkQFAlh8hy1MRVheMc2fLA2REeaY8qeRA0bIRHFrmjanUesFgGGm+//Tbatm1b4zBbeHg4mjVrVtfNIQ/izKewhQsX2u2sFixYYB2w6GH/d8D5T/cqO+XaPK9a9VLZeS9cuGC3EzQv0Zb21EkDcBbwCmiOsJYvwK+52KHp01Zj8ZxP4KXVVCf1qvyzDggIkC6SapaYV6mYmaoCyxMp8/Ly7LbVXBpeUYfFRgVhqzosgEUgBimRU06aklHphM2jEd99953d6sHfffcdXnrpJQCyPCYfAD0g5vmYR2MqlKMG+/fvtzvV9fvvvyveg47UHxk0aJDdgE3+f9Lb29tuwCAPmGpa2n/hwgXpIqdGGJyYQnXF1IGjUz3OjvB40jQHOc6lOSwVFRVYsmQJZs6caXsFhkz37t1RXl6Ojh074uWXX7Y5TSSn1+vFeX4Tq/1ayCMtmL9A3PdmZXVeSrMW1nt4nD171m5nde7cOeWJ7QQ3ikBEgNg52JjisOLoOc3nVVl1IFdZWWm3EzB3mFIOSxagm9AJYa2eh7cmBEZ9GXLX/ge4eAhe2k8ByOqlqARi8pHLK1eu2F2lIl+lJAUMKm01/02Xl5dXd8JbZA/W1AnLa4BI0iyem3jrQ6RNLVU64WPHjgGoObCQCuDBtAeOOWCrTu2RArajR49KF5nzidTuX7re5IGxD2D7zu2KyzZu3ogHxj5gXe69BZQjd2Hi/ctFRUWJr4fK44qMjJSOVeyTZSNoVd0F284IQ213YK7LqQNn2lCbER5PL3InZy+Hp7FwacCyatUqFBYWSjvV2hIVFYVPP/0USUlJ0Ov1+PrrrzF06FDs2LEDAwcOVL3d3Llz8frrr7ug1eRKUq2K4RADhWtA4a9irQrz8C4gG6lT+UcVGhqqvNxOcGPFctGRwcYxzp4TACwHEq5ZHyJ9Kq5h+sYcBARO+BOah/0FGo03KirP4erlOag6edmpaRarVVYCbG/qaPG4pH/mKm01X1/TKi6r602BmCJgsjHKJX0gUemEzYGQuYCdWjvlAZvVNg4WAZs83yYkJMTu/UvXQ+xMtm/bLk5D/Un5uLZtrU4ol0aDVO5fPhokBXoqj0v+gS0kJMShBGkzR0YYPGEHZmeSxJ0ZNfGk/XFqUp/a6mouDVg+//xzJCcnIzo6WvWY9u3bV2/yBbHc84ULF/Dee+/ZDVhmz56NmTNnSr8XFxcr5p/J89gc3gVgCLDO5B88eDC2bt2q+s/S5ghcHGpMkAUg5YtIqmweVX1OObVzakz3ayPpU94JK/bdsdMJw1uHsJHTEdBCnCIoO7oDeRvmQfAROyn5J0NpSkjlU7u8DowkDTZX3shJeyCpdBbm6xXTLDZGo6w+xZoDQcsdiC0CJo1GY3fkyDwlNHHiRLGCrUo7J02aJJ1Tq9XCWGWsXlYMKKeZvKqTXqVdwFXuXx4ESFNtKgGueartxIkTdgNG+aiNNI2j8l6RpoFg2tjT/L6zMXooTTFasDca4swGnHJ1ORKQkJCAIUOHYPua7cq/U2/gjjttJ8g6MsLz4NgHsf3X7YqgcdO6TbZHw1zIkefKkRyexsJlAcv58+exZcsW/PjjjzUfbKFPnz5YsmSJ3WN0Op11BU1yq5r++JwZ3pU2flP5Zynf+E3iSIKsM9M8gOMJugIcSvosKiqqXtYsz/fYLd6+sLAQZ66WInLy+/BtEQfBUIWCvM9RcstPwChIeRny80rLuotQvVT3GqSluvIpmYiICLsjHBER1U9aVFSU+INK0qe5cJv0+J0ZjXIgYJKWS6uMHBUWFoo3NS9xV2ln69atpYvCwsLETS5V3oPyICQ3N7d6RZH8/k0bNVolHQM1BrjO7MAsTQuqvFfkIyxSLRwjFKOX5jyi2ixi2Ldvn92pTnmRO8B1IwEajQYabw2EPwnS+1Wzzn6KgT3mOjSWeTGCINgsr+AKjj5XnlCQz5O4rHDcF198gfDwcNx9991O3zYtLa36nyV5PEf3EHGmzLOUl6CyoZ205NPMPMJRQ7l3e6XmrZg/XR+E1YZ+No8VYLMgnZyPj0/1smZ5gS9TwBTQvi9Gz/8Vvi3iUFWajyuXX0RJwE9WRdPkzp8/r6wXsgpiuXdTMTR5vk9sbKz6CIegrK0hL/9vi7lwm8SZ0SiV/YlsslEQDqjOoZEKvKkU+ZMXLZNWX6m8B+UJylJ9nTEQtxoYbPo+WrzYnHQMyJJlVc5rvn7s2LHiBSpLtaXrYSoiZ+e9Ii8yN378+OrXtR/EImj9IL2uEydOhLOkgLQ7bBZYk+q0mLiiNL+5dlNd7qzsCZsfOvpceUJBPk/ikhEWo9GIL774Ao888ojV0r/Zs2fj0qVL+OqrrwAAH3zwAVq3bo1OnTpJSborVqxQ3TWVPI+jQ5bOlOY/ceKE+EN3iLv5yleTnLVOeHSqIJyjHaudT/c2j7VVkdXi/rt164a9v+21XtGyTotmAychuO9YlOirUH7hCHJXvw1DeEGNyalSQqXKiiZ5wqU0jaDyCV9eQ+mPP/6wOyIlbc5n5sxolANTQn5+fuIP402PzfweCAPw3+o9impKDpb/D6qsrLQ7cidVGIYsTyoOYkdpirdRZHE9TO/tOx3cdsIcXMmfU9PKHzkvL9MQkcoSePnjkgrOqby3L126BGdFR0dXB+13wWpKTD4a56qRgNom/jrE0fdrHXPmufKEPCJP4pKAZcuWLcjMzMRf/vIXq+uysrIUc68VFRV47rnncOnSJfj7+6NTp05Yu3atYp8M8lxO/6PSoLo0v4ngbR0BSHPuKsP8JSUl1o1xNBBRyXWwyYHVHBIHpjmkYmyyzlXbJQhh0f+Af0B3AMBfbo/Hq2NGA4LBoeRUAHY7QasEXQ3EIms2lgDLZWVl2Z3qyc6WPTF2ggCbAZ4Dz1VsbKzY0apM9ZlHg5zZrVvaRkFlmkO+jYI0QqjSWchHWADZyhvZKpXhycMVq1SkXBeV4Eq+rNxgMNhdVi6vdyUF+CpttQrwHdC2bdvqqU75c2Wa6pR3lq4KLFzRYTtah8ZVnC1y50l7+bibSwKW4cOHqy4XW7x4seL3WbNmYdasWa5oBt0EzvzxOVOaX0r4U+mEz549CyuOfmJSCYKsmPNCbKzmsBkwOBBcXLxormsufvM1tkOLitnwDgiHsaIcRZs/xj/f3oZXjaYGOpAXIu0ArdIJyjs2aUpI5Vj5lJCjK5oAOLysG4DDz5W0NUABbAZX5t2apaXYKq+/fKl2VFSUOEXWHcA9UG6jcBaKqeiLFy9Wd2zyHBJTbpD0Wpo4skrFmc0vpX2HVF4raQQGsiJ3Kp2wvIKuo6SEV4ul2jBYJ7y6aiTAFR22uyvdOvtcuaogX33EvYTohjiz7FAR3MhX6rQWv8mDm5KSErv/rK3q7piHruX/rG2NRpiDIIsqr6q1VVRWk1ixMxIhJ9/UsGnsCIT4ToVG44PKiku4+vUcVOZaJEE4MGokBSQqx8oDFmdGI3r27CmOcKj8Y+3Zs6fyHCpBgBUHp4Sk3ByV94C5rVIiscrrL5+6OHPmjN1pDuk9CqBLly7Ytm2b+Iu8voxphKFLly42HpyDdUicmY5w4D0gCILdoLGmpedqHE14deVIgCs6bHdWuk1ISEBoi1Dkrc2zer+GtghlkTs7GLDQDXFm2aEU3KgM8cuDGynvQuWftWUhLIfzTQSoVnm1ydFpJvOxjiyr9vJByPWpCNSNAABcy9iL3A3/hXDdRuEWBzo2qTNSOdZmZ+XAeZOSkrBq9SrVQCApKan6YPOnexubydV2SshcGE7tNTAXecvJybE7dSFfzZOXl2f3vSI/dtq0afjwow+t841MIzzTpk2z8cDsy83NtTsSIr9/aXpK5bWSJ91KNWFUgkZ5zRhHKUZEHVhN46qRAFd02O4MAjIyMsQNXSOhfA9GAHlX8lTzfTxhLx93Y8BCN8yZT2HNQpqh8Gqh8opcoFlIM8UfY1lZmfiDyj9rq4AFUN0tWdlYOD7NY+f+bXJgWbVXUDha3Dsbush2EAQDCg1LUKz5ATAKtkeDHN1GwMFjY2Nj7R4rnxI6efKk3WW9ihUaLpgSqqlwnPn648ePi7fVQLmk1zR1c+TIEemmUvCm8l6xWWTP0WRuB0jTd5bPqY0if+Hh4cgvyFd9reRLlRU1Y2yMHFkWjnOEs3kprg4CHO2wnakD444gQHpeVXbhvqFE4gaOAQvdEGc+hWVkZIi7LPvCKi+lsKBQcaxUjEzlk6jNHKk42NwtWcGZaR5zB2BjfxybAUMBlHVQdiqP3ZVxFVGPfgAv/yAYDEXI9f83yr3S1dsgQFwhIr9cLbBycIRJ6jBVjpXvpXPw4MHqpM9BqA4EdortOnjwoPLkzk4J1fAa+Pj4oLKqUjWHxMdbHIHo0KGD9esKiK/DSuWGglICssp7RZ7r4YpE0rvvvhvz5s1TTea+5557pIuCg4PtvlZShV/IgkuVY2uz/Le2eSnuGgmoLxVhrZ5X83vQ9OfU2Fb+OIMBC9XI3icWZ/6pf/fdd3Y/scrLkldUVNjusE2f7uVFsySOjoY4Os1jnmawkb9g81jVqSYN5m87ifc3Z8DLPwj6rAxcDZ0Lg5dsHbKtNmggBnc2ggWbbXBgRZPUIauMMMgTaS9duqRcrl0AcVmxKRBQJJ2ag7sBEAOLHKgHd4BDr4Gfnx8qSyrFxyt/DUzvAXNNlcTERLvn7Nq1q+LxGwwGh3aWdkUi6YgRIxASFiKOnJiDW1MgHBIWoijEJiUAj4bNjSLlCcJS8Kjyuqanpzvd1vq2QqW+VIStb8+rJ2HAQqoc+cTizD91aRM6lY5l//790kVScqrlzJLG4nr55Y5OnzgzzaNSA8OKylSTxi8AYXfNxHubxGWlJekbkL/lE2B0Zc1tMAcL/gAuQeysbNR2sXf/lo9fkXRrY4RBnnQrLR1XyTdRLC13JriDqX3yx2WjcnxFRYXdZb3moDU1NbX6nDYSvw8ePIjk5GQAsqXCKqM28gRlAPaXa9fSgd8PoGfvnsjbXL0BaGiLUOzft19xXGBgoPhDGmzW4pGuh8W+QzZeV6u/FwfVJi/FHZv01beKsFz5UzsMWEiVI59YEhISoPHSQFgrWAULGi+N4p+ENI2j0rHIP91qNBoIEMTOSr6iZxfE2iKWPYZ5hEPemdtKprXXAdma5lHpLB1ZUeTjE4cWQS/BJyQavt5avDG6Ex565x7ngqsNUG6iaGNbILX7tzXNIuVzqARt8nwPb29v6Cv0qvkmimXN5hwSR3ODVkFZKM3Gqtuqqiq7I3Lm6StpV+fVsLlcXf6YAFSP3NkYtZG/rU6fPm03N6e2uQbBwcHo0aOH4oNAjx490KxZM8Vx0oaGKs+/PJG2po0aazslUl82FHRpgTkX4Mqf2mHAQjY5+onl888/h2AQxOkIi2BBuCJg8eLF0m7d0nSESscizx+Qhu6bweY0i3yTOom/xe+2OncBqhvE2TzWmYRL2T/LJlWDEBo3HVqNH6qKcrDmpXtxW6tmeMh8XpUVLVYsZ75szITZun8ANqdZ8vPz7QZMlsXQHM03kQKmGnaABuBwIOjobtGlpaV2l6tfv169jbaPj48YhKncv7xwnDR6qLILd21zDRyduggLC7P7/MsTaaWcL7VA+AY5kpfizimZ+loRlit/nMOAhWxy9BOLtN+MSsb71q1bpYAlKyvLbjE4qbw4xKJYBqNBtWiYvGgWAIdXnkgbxMl3VU6xcZyZo/kuMN1ntDeaG/+CoMA/ARrg+tlU5P70Hm5b+GdlG1RWtFi1VaUsfm1XNEn1bVQCJvk0j9TRqzwH8k0VATi0VBmAw4GgYkTOxuMyXy+NhKjkEMn3W/Hz8xOnklTuX9prCLJ6GQV5Vu9BW/UyHFGrqQsH3oMFBQXiY4iGzdEgy3296pq7p2SYF9I4uGzzQ6rfpNGO8xZXnBO/macDpMDhPJSdqOk4ea0IvV6v7KyCTd9NG/rJO0CDwWD3WKtcA/knUfOxtjY1FCCO2uwBsBfAr6bj7eVa2Hj8tnhtCUFEwVtisAKgcO+3yPn+NRivWxS5M49GyDepG6nS1jreqNFqCfAY03eteJlU+wQWr63cOfGbonqqBtXl/p81fb9sff8SBzphadRgvcXj2gDFSrGmTZsqc3jM918sHiff0FBKVFW5/+joaOkiqV6Gjfdg3tW8Wq28cWYzO2kTPpXnX75Jn5SjojIaVNscFkd5wiZ9y5Yuw50D71RslnrnQOaFNCQcYSGbjEZjdWchH2I2dRbm/AEpcFCZ5pH/o5SKYqn8U5MXzXKmeqvEkdEQB5NTpWMdzDXRxXRCi9EvwCugOYxCGXKz3sf1fRY7SjvbVmeOM48wWEzLWebwSCt/VJYAX758ufqigAAUFhWq5vw0bdpUef/OTJ85MBrk5eUlvs7BNh7X9eqgOSAgwG4OjzxgkZYCq9y/fKmwK/IinJm6yMzMtPs3KN+TLSgoyO42BvIEXVfwhCkZ5oU0fAxYyCZp4zOVzsL8D6hDhw52p3nkNTCkKQaVf2ryXAOJAx2bU8fa6dhsHqtSNE06RBAQ2GM0mg/5CzRaL1RozuGqbg6q2l5WX9HjaFudOQ5QnZaTq6w0LXNS6YSl6yEb5VJJOrUKGuPgWKVfBwPBJk2aoKS0BCiEcgmwafqsSRMxSUn69O7Ap3u9Xm838Vr+HnRm2wlHKcqyW9T3sZxm6tu3r7hpocrf4O233y5d1LVrV3Fps0rQKF/a7QqeNCXDvJCGiwEL2aSYv7eoFyH/xyrtYeLAxnstWrRAXn6eamchr9wJwPlKr46u/nEmL8XWNI1Jmb4Kz684hJChfxN/N+xAXsA8CBq9/fPa+dRslcPizA7I51G9VFgLm0uFfXx8xKk3lUBInnQqVV1VmWawClgcqPQLwKFAEJBt/lcJZW6KqRiaeUpKMX1p4zHJp65yc3Nt37/pnHl51UuNndl2wlHSNJMfrJaAm6eZzOe9/fbb8eWXXwJXLU5iGojs27evdFH//v3x1Vdfqb63+/fv73RbncWluuRqDFjIJsV+FxaJjPL9LnJycsTLVT5dS9cDaN++vZhDodJZJCQkKBvh4DSHdKyjpeEdHbXQQCzcZmM1iXezaNy74FdkXCmFYKhCwbb/oaT1z46d187IldVxzWwcp7bv0SrUuFRYmupTCQTlpeF9fHzsTjPI85PsHWczuBoDMQi+AEUxNLmmTZuisLBQ5cFWT3PEx8fjzNkzqsFdfHx19m9pqY0oTsbyeke3nXDU6dOnq58TG8+V1TSTndFLuUGDBok/qLy3petdiFMy5GoMWMgmaf5eZamw+R+rlJip8ula/oldyg/wgTLfxVv83WatBkeWKpupjAQoODq6AaiOHPn/0Qdhd89ExpVShAfqcGjhP6C/fAw4AsdGgwDVT821Ps68osjRmjEqgaB8ywNphENl9EyxUsvZHJY4iEGbadYFRSrHATXuETV48GBs3bpVNRAePHiwdFFISIjdIEhe28TZzf8codVq7T5X8to2zhwLwCVF7mqDUzLkKlwlRDa1bdu2eqnwMFSvJskCoKmev9+7d694A5WO9ddff5UuunTpkviDZS0RU17uhQsXlJeb71++8sN0/1bkn/DNxxbaOFZAdbn//5q+q5W6B5RD7IIWzdo+gvD7XoZW1wS9Wofg56f7Q3/pmDIIMJ+3mcp5zZ+a5W31ttFWR48zPy6VFVVyUlA4HsCfAHSBGBBMEC+Wd9g1JT7L9x2yd5xNDqy+UuTbhAJoZ/reWnn92LFjxQtUpu+k6wG0adPG7rHS9XDNyhepmrPKOX//vTpRW1oFpHLs9u3blW2VjzKa34NRAISbs0qHyNU4wkLqzFMSNvfHEV29etVuvRD5lFB6errdaRarzfQEOFa0zHxsHe6qKzENsWuFIIRVzIK/VzcAQPH+VVj61ifwkRewGw8xcDPv+RIGq6RXp9pam1ELudbWh0grexYCMK8iPwyxDguUK390OtOFKtMMfn5+ypM7M9XmwKaSXbp0wZUrV1TP26VLFwDiVKLWW2u90zIArbdW8WlfqrOihfX0mVFZh8UVK1+kvweVc8r/XoqKiuweW1xcvVxeamt32NyA0lMLpxE5gwEL2STNtRdBWWQtFdZz7XYCC3m5fSmhUaUTli9rlqjkxtjkyCd8O8GV2rJmX10CWsS8AG9NOIyV5chb/xGuHdsFH6/PlMc7mnTqaFudOQ5wKGDQ6XR2cyjkeSkBAQHVU2jy4GI3FKt0ADiXIG0e5ZInndo4Ljo62u40h7lmysaNG2E0GG0GwsYKIzZv3ixtKih17H+COC15BkAbSNWP5cGNK1a+3H333Zg3f57qY5Lv1tyzZ0+s+WmN6vPao0cP220dzsJp1DAxYCGbpPlzAWKRNTNTRVTz/LlUZ0UlsLBZsMqZTtiZIMDRZc13QcyNSYM4EpIM1VGbpreOQEj0VGg0PqjMv4Srq95C5dVM62OdTTqt62XNTiwVtjdyIx9hadq0afV7wMamhkFBQdWX2cmLsdlWlVE2eVszMjLsJlNnZIgbSq5du9buY/r555+lgEXa/HAtxPfBncrnSr6sG6j7lS8jRoxA85DmKCgssMq3aR7SXLFb89ixY/HKK6+orqiST3UBwIL5C9CrTy/kraxe6dSsRTMs/HhhrdpK5GkYsJBN0moSlU/i5vwF6R+8SmBh2QEAcK4TLkD1smrz/jD2ljXb2IHX6lgHNhTUePsiZNhUNL1tOADgWsZe5K79LwSNrUxeODd94+hohLMJwhqL+7OxP5G0/YFK0CgvHDdkyBAcOnxI9T0gT2YF4FAdGKmtDjxXERGmN5HKNIf5emnZsspjkicHh4eHi/dVBZsJuuHh4YpTuGLlS8r+FHG35quy3ZpDrHdrTkhIwIBBA/DL7l+UJ9AAAwYNsGrHtKemofBaoWLLh8JfC/HEk0+4fC8fopuBAQvZtGnTJrsdy9atW5GcnFw95ePMahZnpg6aw24OjeJYLZQjAbY2NdRAnAqwMxJyIf8aIia+C13kLRCMBhTu+grF+1aIV1psYaTg6PSVo6MRAhxb/mxmGRtWWR8SFRWFc+fOqQaNkZGR0kVHjhyx+x44evSo8uTmc4aafrdISVJwYJTtiSeewOo1q8X3RzKspk+mTZsGQFacUOUxdezYUbpo7NixeOWfr4jTgrdBfC79ARwDYLQetTCry5Uv8fHxyM3JxebNm7F371707dtXMbIit3rlanGER74D8vARViM8NvfyAWAIuDl7+RDdDAxYyKb169eLP6h0LGvXrsV7770nbpZnJy9EvpkeALufbm1yJhAyoubND80dsHxXYVlF2p0ZVzHj2zToIm+B4VoRcte/i/LbDoqrdOQ1MGy115npK0dGIyxHmFSSU318fFBZValar8PHu3pp+WOPPYa9v+1VDRoff/xx6VjFihYbgZh8RUutitzVMMoWHx9vt8hb69ZiQwYNGmT3/uU1SBISEjBgoGnUIk15zgEDrUctXGnYsGGqgYqZoyM8rthGgMjTMGAhm8rKysQfVDoW8/UVFRV2k25t5rCMhjj6YV5NY6NoGADnEmTttMFKGmzsKqxBcN+xePSL3yEIgP5yBq6umgvDsKuOT/PUJofF3miEObizUeVVLiIiAhcvXlQdCZGmVmBKVLUTNMqPDQ0NFVeqqARioaGh1ZcJcLzInYOjbFInrINyCs/0u1Xit0pgY8nRUQtPUtMIjyfs5UPkagxYSJ29T80mOp1OzFNR+WQnLY2VS4OyAm28yv07E4QAjq8SMu8qbAosNFsCEHb/39Hkll4QBGB8r1i8PfZewKD+uGy21c7IjVUbHM1hUZm6kB8nrexRaat85Y+U7zEaNouxyYuR9e/fX6wgqxKImcu9+/v743r5ddXRoCb+1UlC3t7eYv6TSr6NvNCg1AmPhM2quOZOWApsYqF8X5l+txxdaIgVWT1pLx8iV2HAQjZdv37d7goN8yZxUgd3HjY3iJN3QACUxeDsTd2YORowmNvgyCoh2UiET+fWaBH3Inx8oyFUVeDf43pgbM8YvG2odPycZjZHblTaYC5eZ2bx+KWOvRJWUxfyVVqALCBRaas8YJF2+I2DmB9jHiQxv4znz0vHFhYW2s1hMdcJCQoKEt8PFVCOBpkek3w1UWRkJC5euiiew7xcXgMgRfwuz6GxWqrbHTY74drWIGloFVm5lw81dAxYGpCMjAycPn26bj8xqnQC5hLu0t4rq6Est29KTrWZw+LMqIkzK4qc3PwwoGowQiqfgtbXD1VFV3B15RyMfU9WEdSZBGFnA7HWUI4GWPwu7aNjWQvN9Lt5Hx0A6NWrF46fOK7a1t69e1vfvwPPq5RQXUPQOGLECHHjPS2U7wHT7yNHjpQu6tGjhzh9pYHN5fLy2iKAY50wa5CIGuLIEZEcA5YGID8/HxMmTVDOySeLc/I29+dxgL+/v7JeRWsoOkFz0TCproVKwqfVjr6A46Mmzq4ocnjzQ2807/AYggyjAADXy1KQu/g9GMttBFcOLBWWjnUmEFMJBM2kKrL+UOZvmH6XT7W99NJLYsCgkpfy0ksvSRc5k6Dao0cPrF69WjW4MQcXEyZMEO9fZZppwoQJ0k1jYmLEH56AmMhrnuYxVQWWrjdxtBPm6EK1hjZyRGTGgKUBmDBpArbs2qL4dL9l4xaMnzi+1vUXQkNDxU/CKstvzQmXGo0GglFQnTbQykvXmzk6amIrkdJUNMumGoIAAPAKDEFYwAvwM4hLXQvzlqFo6TJAb13WXQqMbExd3ND0lbm+ykio1lcZPny4GASo5G/IRy0kKqMxVhxMUJWWAKsEjeYlwFJJfJVpJvmeQ3fffTfmzZtX/R4wb35oSjqWV3qVq6kT5ugCUcPHzQ/rOXP9BcMIg2LjO8NwAzauF+svqN1u/fr1qtebl4xiPIDpACaavps+LJs3iZM+6TuQ8AmgetTkIMSy/wdRPWpiSQOxIupwVG++6Gvn2HUQg5Rw03fLBOGYzoh6+EP4RXeEsbwUOT/8C0X/WwpEGtVHTaogTl3sNX2vgnrAdN7i93PWh/j7+yvrq/zX9D1IPK95L5sJEyZUP6ZSiMFYafVjko9aSEmnrS3uzPS7fOM7RYKqXKz1seYlwFJwY25rpXIJsGKFio3HL88hGTFiBELCQmy+B0LCQmpc5luTdu3aITk5mcEKUQPEEZZ6ztn6C45OH8XGmnowleW3rVq1AiAbiVEZNQkLC5MuqmmFiDyRFID1NAsgjjbYmmapYUrof7+cQcRDb0Gj9UKF/iyuCnNQ1SdLPL+NkRgA1VNd8lU6R2F336Gapq+mTJmCDz78QHVFjbkYmtFotPuY5KMWziSdOpuganMJ8IgR6jkkDqxQOfD7AbHSq6yEfGgL60qvRERyDFjqOWfrLzg6fSRt0qbSCZuH7sPCwsRVHyo5EfJaHRqNxu40i3yjRIkzq4RsdMKai34ITX4ab649Bo3WC6VHtiN/+3wIw/WO5cVYrtKxMSXVtGlTMflYJRCTJ8gOHz4cH3zwgTgFI19RY6rKO3ToUADOBRbOJJ06m6DqihwSZyq9EhFJhDr26quvChD/pUtfERERdm+zY8cOITExUdDpdEJ8fLywcOFCp++3qKhIACAUFRXVtun11ojkEYJXgJeAeyHgWQi4F4JXgJcwInmE4rgTJ06Ir8l9EPCa7Ote8XXKyMhQHB8S2lyAl/K1hBeEkNDm0jF33HGHeHm8xXGm34cOHSodq9VqxeuaWBxr+l2r1Vofq9JW+bEABGggQAfFc+Ad2VKIeuxjIe75n4W2s9cKgYn3SI/B8jGZfzbz9va2e6y3t7d07NChQ6vvvx8E9DV914ntGjZsmO3XYDIEDDZ9t/EaOPq6CoIg5OfnCyOSRyjaOiJ5hJCfn39DxzorIyNDWLdundV7iYhIjaP9t0sClk6dOglZWVnSV05OjurxZ86cEZo0aSLMmDFDOHr0qPDZZ58JPj4+wg8//ODU/TbmgMXRDmjdunXi9c9aBAHPirdZt26d4vgzZ84IYS1CFecNaxEqnDlzRjrmf//7X3UHPB0CJpq+mzrgL774Qjo2NDTUbmcdFhYmHdutWzebQYg5COjevbt0bEBAQHXQYmqnf0JfIeaZ74S4538WYp76SjhwLk+IiIiwG4RERkZK5+zatat4ndbiWNPv3bp1k46VghA/i2N1tgNBRwOR2gQWzgQMDC6IyBO4NWDp2rWrw8fPmjVL6NChg+KyKVOmCH369HHqfhtzwGJWUwfk7AiL2aZNm4TXX39d2LRpk83rvX29bQYW3r7eiuP+97//2Q1C5MHNG2+8IbbV2yIIMP3+5ptvSseOGTOmOmDQaIVmgx4R4p7/WYh7/mchYvxcYdSDEwVBEISHH35YvH8/COgOAR1M3/3E+3/kkUekc7755pt2g5C5c+cqHlvXbl1tjrB07dbV6vlyNhBhYEFEDZlbA5YmTZoIUVFRQuvWrYVx48YJp0+fVj1+wIABwtNPP6247McffxS8vb2FiooK1duVl5cLRUVF0teFCxcafcDiCGemGRyVlpYm+Oh8FB2wj85HSEtLszrWciRE/rucIrgaDQFdTN9tBFeffvqpAA0EbbMgIXzKW1Kw0vzOxwR4eQmfffaZIAiCsGHDBrsjLPKAbN26dWK7/C2CEH+xvZajUa4eDSEiaqgcDVjqfFlz79698dVXX2Hjxo347LPPkJ2djX79+iEvL8/m8dnZ2YoN1wBxA7aqqirk5qptzQvMnTsXwcHB0pdlwSmybdnSZbhz4J2KZap3DryxAlvdunVDRXkFvvjiC0yaNAlffPEFKsor0K1bN6tj09LS4OOrLNfv4+uDtLQ0xWUJCQkYOGigmPSrBXCn6fs6YOCggYrEz0GDBsE3MgFRkz6Ef7OuMFZcx9XVb6Pg8OeAwSAVQ5Pqhags6bVaeSNAXH4sX9ZsWn5smcxsTk7NyMjAunXrkJGRgQ3rNtgt3McluEREjtMIgqnGuouUlZWhbdu2mDVrFmbOnGl1fUJCAv785z9j9uzZ0mW//vor+vfvj6ysLMXeInJ6vR56vV76vbi4GDExMSgqKlLsXUK2ubvA1uLFi7F161YMHToUjz76qM1jCgoKrJfUWizBFgQB3/yeiZdWpANab1SWX8TVrLdQWXABml80GNJ/CLZu3gpArD3Tvn17cYWUjYqsGRkZiudi5F0jsWXXFhj6GaTlx157vHDnwDtrXZCPiIiUiouLERwcXGP/7fJlzQEBAejSpYtqgbLIyEhkZ2crLsvJyYG3t7dy+3oLOp3O9k7A5BB3l+9+9NFHVQMVs5qW1JZXGvDyqj/wQ8pFQOuNpkWncfT/XoBQIW7MODx5+A3tOSMt1V3Pcu9ERO7m8oBFr9fj2LFjGDBggM3r+/bti59++klx2aZNm9CjRw/rnX6pUbIVXF3Iv4apS1Jw5HIxtBrgHyM6YOqgu3BqZnKd1QthuXciIs9R51NCzz33HEaNGoXY2Fjk5OTgzTffxM6dO3H48GHExcVh9uzZuHTpkrhPCoCzZ8+ic+fOmDJlCv72t79h7969mDp1KpYtW4b777/f4ft1dEiJ6r8dJ3Iw49t0FF2vREiAL+aN747bbwmr+YYyDEKIiDyD26aELl68iPHjxyM3NxctWrRAnz598NtvvyEuLg4AkJWVhczMTOn4+Ph4rFu3Ds8++yw+/vhjREdH46OPPnIqWKHGwWgUMH/7Kfx3SwYEAega0wwLJyYiupm/0+dy95QYERE5x+VJtzcLR1gatqJrlXj2u3RsO54DAJjQOxavjuoInbeXm1tGREQ3wmOSbolu1NHLxZi6JAWZ+dfg663Fm2M6Y2wPLmMnImpMGLCQR1uZdhGzfzyM8kojWjX3x6JJSejcMtjdzSIiopuMAQt5pIoqI95cexRf7T0PABiY0AIfjuuG5gG+bm4ZERG5AwMW8jjZReWYtjQFqZmFAICn77gFM+5MgJdW496GERGR2zBgIY/y25k8PPVNKnJLKxDo540PxnXD0Fsjar4hERE1aAxYyCMIgoD//XIWb284DoNRQIfIQHwyOQlxoQHubhoREXkABizkdqX6Kjz/wyGsPZwFALi3e0vMubcL/H25ZJmIiEQMWMitTuWUYuqSFJzKKYW3VoN/juqIyX3ioNEwX4WIiKoxYCG32fBHFp77/hBK9VWICNJhwcREJMWFuLtZRETkgRiw0E1XZTDi35tO4JOdZwAAveNDMG9Cd4QH+rm5ZURE5KkYsNBNlVuqx/Rv0rD3TB4A4G8D4vH8yA7w9tK6uWVEROTJGLDQTZOWWYBpS1ORVVSOJr5e+PcDXXH3bVHubhYREdUDDFjI5QRBwNJ9mXj9pyOoNAho0yIAn0xKQruIQHc3jYiI6gkGLORS5ZUGvLTyD6xIvQgAGNkpEv9+8DYE+vm4uWVERFSfMGAhl7mQfw1Tvk7B0axiaDXA8yM74PGBbbhkmYiInMaAhVxi+4kcPPNtOoquVyI0wBfzxndHv1vC3N0sIiKqpxiwUJ0yGgV8tO0kPtx6EoIAdI1phoUTExHdzN/dTSMionqMAQvVmaJrlXhmeRq2n7gKAJjYOxb/HNUROm+W2CciohvDgIXqxJHLRXhiSSoy869B563Fm2M648EeMe5uFhERNRAMWOiG/Zh6EbN/PAx9lRExIf5YODEJnVsGu7tZRETUgDBgoVqrqDLijZ+P4uvfzgMABrdvgQ/GdUOzJr5ubhkRETU0DFioVrKKrmPa0lSkZRYCAGYMbYcZQ9tBq+WSZSIiqnsMWMhpe0/nYfqyVOSWViDIzxsfPNQNd3SIcHeziIioAWPAQg4TBAGf/XIG72w4AYNRwK1RQVg0KRFxoQHubhoRETVwDFjIIaX6Ksz64SDWHc4GANzXvSXeurcL/H25ZJmIiFyPAQvV6FROKaZ8fQCnr5bBx0uDf97TEZP6xLHEPhER3TQMWMiu9Yez8Nz3B1FWYUBEkA4LJiYhKa65u5tFRESNDAMWsqnKYMS/N57AJ7vOAAD6tAnBvPGJaBGoc3PLiIioMWLAQlZyS/V46ptU/HYmHwDw+MA2mDWiPby9tG5uGRERNVYMWEghNbMA05akIru4HAG+Xvj3g11xV5codzeLiIgaOQYsBEBcsrxkXyb+9dMRVBoEtG0RgE8mJ+GW8EB3N42IiAh1PsY/d+5c9OzZE4GBgQgPD8eYMWNw4sQJu7fZsWMHNBqN1dfx48frunlkw/UKA/7+/UG8suoPVBoEJHeOxOqn+jNYISIij1HnIyw7d+7Ek08+iZ49e6KqqgovvfQShg8fjqNHjyIgwH6BsRMnTiAoKEj6vUWLFnXdPLKQmXcNU5ak4FhWMbQa4IXkDvjbgDZcskxERB6lzgOWDRs2KH7/4osvEB4ejpSUFAwcONDubcPDw9GsWbO6bhKp2H48BzO+TUNxeRVCA3wxb0J39Gsb5u5mERERWXH5so+ioiIAQEhISI3Hdu/eHVFRURg6dCi2b99u91i9Xo/i4mLFFznGaBTw380Z+MuX+1FcXoVuMc3w89P9GawQEZHHcmnAIggCZs6cif79+6Nz586qx0VFReHTTz/FihUr8OOPP6J9+/YYOnQodu3apXqbuXPnIjg4WPqKiYlxxUNocAqvVeCxL/fjw60nIQjA5D5xWD6lD6KC/d3dNCIiIlUaQRAEV538ySefxNq1a7F79260atXKqduOGjUKGo0Ga9assXm9Xq+HXq+Xfi8uLkZMTAyKiooUeTBU7Y9LRXhiaQou5F+HzluLOfd2wf1Jzr0uREREdam4uBjBwcE19t8uW9Y8ffp0rFmzBrt27XI6WAGAPn36YMmSJarX63Q66HSsuuqoH1Iu4qWVh6GvMiImxB+LJiWhU3Swu5tFRETkkDoPWARBwPTp07Fy5Urs2LED8fHxtTpPWloaoqJYsOxG6asMeOPno1jyWyYAYEj7FvhgXHcEN/Fxc8uIiIgcV+cBy5NPPolvvvkGq1evRmBgILKzswEAwcHB8PcX8yRmz56NS5cu4auvvgIAfPDBB2jdujU6deqEiooKLFmyBCtWrMCKFSvqunmNSlbRdTyxJBXpFwqh0QAzhrbD03e0g1bLJctERFS/1HnAsnDhQgDA4MGDFZd/8cUXePTRRwEAWVlZyMzMlK6rqKjAc889h0uXLsHf3x+dOnXC2rVrcdddd9V18xqNPadzMf2bNOSVVSDIzxsfPtQdQzqEu7tZREREteLSpNubydGknYZOEAR8uusM3tlwHEYBuDUqCJ9MSkJsaBN3N42IiMiK25Nu6eYr1VfhH98fxPo/xGm4+xJb4q0xXeDv6+XmlhEREd0YBiwNxKmcEkz5OgWnr5bBx0uDf47qhEm9Y1lin4iIGgQGLA3A2kNZmPXDQZRVGBAZ5IcFkxKRGNvc3c0iIiKqMwxY6rEqgxHvbjyBT3edAQD0aROC+RMSEdaU9WmIiKhhYcBST10t0WP6slT8diYfADBlYBv8Y0R7eHu5fHsoIiKim44BSz2Ucr4ATy5NRXZxOQJ8vfDeg12R3IVF9oiIqOFiwFKPCIKAJb+dx79+PopKg4C2LQLwyeQeuCW8qbubRkRE5FIMWOqJ6xUGvLTyMH5MuwQAuKtLJN59oCua6vgSEhFRw8ferh44n1eGqUtScSyrGFoN8EJyB/xtQBsuWSYiokaDAYuH23b8Cp75Nh3F5VUIa+qLj8Z3R7+2Ye5uFhER0U3FgMVDGYwCPtx6Eh9tPQkA6B7bDAsmJiIq2N/NLSMiIrr5GLB4oMJrFZjxbTp2ZlwFADzcNw4v390Rvt5cskxERI0TAxYP88elIkxdkoKLBdeh89Zizr1dcH9SK3c3i4iIyK0YsHiQH1Iu4qWVh6GvMiI2pAkWTkpEp+hgdzeLiIjI7RiweAB9lQH/+ukolu7LBADc0SEc/x3bDcFNfNzcMiIiIs/AgMXNsoqu44klqUi/UAiNBnhmaAKm33ELtFouWSYiIjJjwOJGe07lYvqyNOSVVSDY3wcfPNQNQ9qHu7tZREREHocBixsIgoBPdp3BuxuOwygAHaOCsGhSEmJDm7i7aURERB6JActNVlJeiX98fwgbjmQDAO5PbIW37u0MPx8vN7eMiIjIczFguYlOXinBlCUpOHO1DD5eGrw6qhMm9o5liX0iIqIaMGC5SdYeysI/fjiIaxUGRAX7YcHERHSPbe7uZhEREdULDFhcrMpgxDsbjuOzX84CAPq2CcW8Cd0R1lTn5pYRERHVHwxYXOhqiR5PfZOKfWfzAQBTBrXBP4a3h7cXS+wTERE5gwGLi6Scz8e0pam4UqxHgK8X3nuwK5K7RLm7WURERPUSA5Y6JggCvv7tPN74+SgqDQJuCW+KRZOScEt4U3c3jYiIqN5iwFKHrlcY8OLKw1iZdgkAcHeXKLzzwG1oquPTTEREdCPYk9aR83llmPJ1Co5nl8BLq8Hs5A54rH88lywTERHVAQYsdWDrsSt4Znk6SsqrENbUF/MnJKJPm1B3N4uIiKjBYMByAwxGAR9uycBH204BABJjm2HBxCREBvu5uWVEREQNCwOWWiq8VoEZ36ZjZ8ZVAMDDfePw8t0d4evNJctERER1jQFLLfxxqQhTl6TgYsF1+PloMefeLrgvsZW7m0VERNRguWw4YMGCBYiPj4efnx+SkpLwyy+/2D1+586dSEpKgp+fH9q0aYNFixa5qmk35LsDF3D/wj24WHAdsSFN8OMTtzNYISIicjGXBCzLly/HM888g5deeglpaWkYMGAAkpOTkZmZafP4s2fP4q677sKAAQOQlpaGF198EU8//TRWrFjhiubVir7KgNk/HsasHw5BX2XE0A7h+Omp/ugYHeTuphERETV4GkEQhLo+ae/evZGYmIiFCxdKl916660YM2YM5s6da3X8888/jzVr1uDYsWPSZVOnTsXBgwexd+9eh+6zuLgYwcHBKCoqQlBQ3QYRlwuv44klKTh4sQgaDfDsnQl4asgt0Gq5ZJmIiOhGONp/1/kIS0VFBVJSUjB8+HDF5cOHD8eePXts3mbv3r1Wx48YMQIHDhxAZWWlzdvo9XoUFxcrvlzh11O5uGfebhy8WIRgfx988WhPPD20HYMVIiKim6jOA5bc3FwYDAZEREQoLo+IiEB2drbN22RnZ9s8vqqqCrm5uTZvM3fuXAQHB0tfMTExdfMAZK5VVGHGt2nIL6tAp+gg/Dy9Pwa3D6/z+yEiIiL7XJZ0a1nhVRAEu1VfbR1v63Kz2bNno6ioSPq6cOHCDbbYWhNfb/x3XDeM7dEKK57oh5iQJnV+H0RERFSzOl/WHBYWBi8vL6vRlJycHKtRFLPIyEibx3t7eyM01HbFWJ1OB51OVzeNtmNAuxYY0K6Fy++HiIiI1NX5CIuvry+SkpKwefNmxeWbN29Gv379bN6mb9++Vsdv2rQJPXr0gI+PT103kYiIiOoZl0wJzZw5E//73//wf//3fzh27BieffZZZGZmYurUqQDE6ZyHH35YOn7q1Kk4f/48Zs6ciWPHjuH//u//8Pnnn+O5555zRfOIiIionnFJpdtx48YhLy8P//rXv5CVlYXOnTtj3bp1iIuLAwBkZWUparLEx8dj3bp1ePbZZ/Hxxx8jOjoaH330Ee6//35XNI+IiIjqGZfUYXEHV9ZhISIiItdwWx0WIiIiorrGgIWIiIg8HgMWIiIi8ngMWIiIiMjjMWAhIiIij8eAhYiIiDweAxYiIiLyeAxYiIiIyOMxYCEiIiKP55LS/O5gLthbXFzs5pYQERGRo8z9dk2F9xtMwFJSUgIAiImJcXNLiIiIyFklJSUIDg5Wvb7B7CVkNBpx+fJlBAYGQqPR1Nl5i4uLERMTgwsXLnCPonqAr1f9wdeq/uBrVb/Ut9dLEASUlJQgOjoaWq16pkqDGWHRarVo1aqVy84fFBRUL154EvH1qj/4WtUffK3ql/r0etkbWTFj0i0RERF5PAYsRERE5PEYsNRAp9Ph1VdfhU6nc3dTyAF8veoPvlb1B1+r+qWhvl4NJumWiIiIGi6OsBAREZHHY8BCREREHo8BCxEREXk8BixERETk8Riw1GDBggWIj4+Hn58fkpKS8Msvv7i7SWThtddeg0ajUXxFRka6u1lksmvXLowaNQrR0dHQaDRYtWqV4npBEPDaa68hOjoa/v7+GDx4MI4cOeKexjZyNb1Wjz76qNXfWp8+fdzT2EZu7ty56NmzJwIDAxEeHo4xY8bgxIkTimMa2t8WAxY7li9fjmeeeQYvvfQS0tLSMGDAACQnJyMzM9PdTSMLnTp1QlZWlvR1+PBhdzeJTMrKytC1a1fMnz/f5vXvvvsu/vOf/2D+/PnYv38/IiMjMWzYMGl/MLp5anqtAGDkyJGKv7V169bdxBaS2c6dO/Hkk0/it99+w+bNm1FVVYXhw4ejrKxMOqbB/W0JpKpXr17C1KlTFZd16NBBeOGFF9zUIrLl1VdfFbp27eruZpADAAgrV66UfjcajUJkZKTw9ttvS5eVl5cLwcHBwqJFi9zQQjKzfK0EQRAeeeQRYfTo0W5pD9mXk5MjABB27twpCELD/NviCIuKiooKpKSkYPjw4YrLhw8fjj179ripVaTm5MmTiI6ORnx8PB566CGcOXPG3U0iB5w9exbZ2dmKvzOdTodBgwbx78xD7dixA+Hh4UhISMDf/vY35OTkuLtJBKCoqAgAEBISAqBh/m0xYFGRm5sLg8GAiIgIxeURERHIzs52U6vIlt69e+Orr77Cxo0b8dlnnyE7Oxv9+vVDXl6eu5tGNTD/LfHvrH5ITk7G0qVLsW3bNrz//vvYv38/7rjjDuj1enc3rVETBAEzZ85E//790blzZwAN82+rwezW7CoajUbxuyAIVpeReyUnJ0s/d+nSBX379kXbtm3x5ZdfYubMmW5sGTmKf2f1w7hx46SfO3fujB49eiAuLg5r167Ffffd58aWNW5PPfUUDh06hN27d1td15D+tjjCoiIsLAxeXl5WkWhOTo5VxEqeJSAgAF26dMHJkyfd3RSqgXk1F//O6qeoqCjExcXxb82Npk+fjjVr1mD79u1o1aqVdHlD/NtiwKLC19cXSUlJ2Lx5s+LyzZs3o1+/fm5qFTlCr9fj2LFjiIqKcndTqAbx8fGIjIxU/J1VVFRg586d/DurB/Ly8nDhwgX+rbmBIAh46qmn8OOPP2Lbtm2Ij49XXN8Q/7Y4JWTHzJkzMXnyZPTo0QN9+/bFp59+iszMTEydOtXdTSOZ5557DqNGjUJsbCxycnLw5ptvori4GI888oi7m0YASktLcerUKen3s2fPIj09HSEhIYiNjcUzzzyDOXPmoF27dmjXrh3mzJmDJk2aYMKECW5sdeNk77UKCQnBa6+9hvvvvx9RUVE4d+4cXnzxRYSFheHee+91Y6sbpyeffBLffPMNVq9ejcDAQGkkJTg4GP7+/tBoNA3vb8uta5TqgY8//liIi4sTfH19hcTERGnJGHmOcePGCVFRUYKPj48QHR0t3HfffcKRI0fc3Swy2b59uwDA6uuRRx4RBEFcfvnqq68KkZGRgk6nEwYOHCgcPnzYvY1upOy9VteuXROGDx8utGjRQvDx8RFiY2OFRx55RMjMzHR3sxslW68TAOGLL76Qjmlof1saQRCEmx8mERERETmOOSxERETk8RiwEBERkcdjwEJEREQejwELEREReTwGLEREROTxGLAQERGRx2PAQkRERB6PAQsRERF5PAYsRERE5PEYsBAREZHHY8BCREREHo8BCxEREXm8/wfzYAwK5Vkf1wAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -4993,13 +4995,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.13031966791602223\n", - "0.15463784705801664\n" + "0.13312004007562517\n", + "0.14674466840894407\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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- val_distribution_lambda_3_loss: 1.6433 - val_distribution_lambda_4_loss: 0.4875\n" ] } ], @@ -5246,7 +5248,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 24, "id": "39a9bdc6", "metadata": {}, "outputs": [], @@ -5266,7 +5268,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 25, "id": "c41cf448", "metadata": {}, "outputs": [ @@ -5274,13 +5276,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.0798265190543076\n", - "0.29563465147366164\n" + "0.0907258632073451\n", + "0.3000061215338464\n" ] }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -5292,13 +5294,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.02219365253550709\n", - "0.159869757007698\n" + "0.06439535566000021\n", + "0.21148355905367822\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -5343,7 +5345,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 26, "id": "cecf5392", "metadata": {}, "outputs": [], @@ -5375,7 +5377,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 27, "id": "ddf433f9", "metadata": {}, "outputs": [], @@ -5502,7 +5504,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 28, "id": "d31bad38", "metadata": {}, "outputs": [], @@ -5528,7 +5530,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 29, "id": "62b9f588", "metadata": {}, "outputs": [ @@ -5934,7 +5936,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 30, "id": "c58ba41d", "metadata": {}, "outputs": [], @@ -5972,7 +5974,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 31, "id": "f79792b6", "metadata": {}, "outputs": [ @@ -6008,29 +6010,29 @@ " \n", " \n", " \n", - " Ochoa\n", + " Falcone\n", " 1.0\n", " 90\n", " \n", " \n", - " Lovato\n", + " Gendrey\n", + " 1.0\n", + " 90\n", + " \n", + " \n", + " Baschirotto\n", + " 1.0\n", + " 90\n", + " \n", + " \n", + " Pongracic\n", " 1.0\n", " 80\n", " \n", " \n", - " Gyomber\n", - " 1.0\n", - " 80\n", - " \n", - " \n", - " Pirola\n", - " 1.0\n", - " 80\n", - " \n", - " \n", - " Mazzocchi\n", - " 1.0\n", - " 80\n", + " Gallo\n", + " 0.6\n", + " 60\n", " \n", " \n", " ...\n", @@ -6038,54 +6040,54 @@ " ...\n", " \n", " \n", - " Pisilli\n", + " Oristanio\n", + " 0.0\n", + " 50\n", + " \n", + " \n", + " Jankto\n", + " 0.0\n", + " 15\n", + " \n", + " \n", + " Mancosu\n", " 0.0\n", " 10\n", " \n", " \n", - " Aouar\n", + " Pavoletti\n", + " 0.0\n", + " 55\n", + " \n", + " \n", + " Shomurodov\n", " 0.4\n", - " 55\n", - " \n", - " \n", - " El Shaarawy\n", - " 0.0\n", - " 55\n", - " \n", - " \n", - " Belotti\n", - " 0.0\n", " 60\n", " \n", - " \n", - " Azmoun\n", - " 0.0\n", - " 35\n", - " \n", " \n", "\n", - "

476 rows × 2 columns

\n", + "

467 rows × 2 columns

\n", "" ], "text/plain": [ " starter percentage\n", "player \n", - "Ochoa 1.0 90\n", - "Lovato 1.0 80\n", - "Gyomber 1.0 80\n", - "Pirola 1.0 80\n", - "Mazzocchi 1.0 80\n", + "Falcone 1.0 90\n", + "Gendrey 1.0 90\n", + "Baschirotto 1.0 90\n", + "Pongracic 1.0 80\n", + "Gallo 0.6 60\n", "... ... ...\n", - "Pisilli 0.0 10\n", - "Aouar 0.4 55\n", - "El Shaarawy 0.0 55\n", - "Belotti 0.0 60\n", - "Azmoun 0.0 35\n", + "Oristanio 0.0 50\n", + "Jankto 0.0 15\n", + "Mancosu 0.0 10\n", + "Pavoletti 0.0 55\n", + "Shomurodov 0.4 60\n", "\n", - "[476 rows x 2 columns]" + "[467 rows x 2 columns]" ] }, - "execution_count": 33, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -6108,7 +6110,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 32, "id": "5e63c2b7", "metadata": { "scrolled": true @@ -6118,557 +6120,557 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sommer: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Szczesny: MV 6.17 ± 0.87; FV 5.13 + 1.42 (35.2% cs)\n", - "Meret: MV 6.19 ± 0.85; FV 5.46 + 1.32 (44.9% cs)\n", - "Provedel: MV 6.22 ± 0.89; FV 5.10 + 1.49 (27.3% cs)\n", - "Maignan: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Rui Patricio: MV 5.77 ± 0.99; FV 3.50 + 2.58 (1.2% cs)\n", - "Skorupski: MV 5.92 ± 0.99; FV 3.55 + 2.61 (1.7% cs)\n", - "Milinkovic-Savic V.: MV 5.86 ± 1.02; FV 3.48 + 2.71 (1.2% cs)\n", - "Di Gregorio: MV 6.23 ± 0.87; FV 5.10 + 1.53 (26.5% cs)\n", - "Falcone: MV 6.18 ± 0.90; FV 5.10 + 1.48 (31.0% cs)\n", - "Silvestri: MV 5.80 ± 0.99; FV 3.48 + 2.60 (1.3% cs)\n", - "Terracciano: MV 6.22 ± 0.86; FV 5.13 + 1.43 (35.2% cs)\n", - "Carnesecchi: MV 6.15 ± 0.89; FV 5.10 + 1.47 (24.5% cs)\n", - "Radunovic: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Montipo': MV 6.15 ± 0.92; FV 4.74 + 1.67 (12.2% cs)\n", - "Martinez Jo.: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Ochoa: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Caprile: MV 5.95 ± 0.98; FV 3.41 + 2.73 (1.1% cs)\n", - "Turati: MV 6.13 ± 0.89; FV 5.46 + 1.28 (34.2% cs)\n", - "Consigli: MV 6.03 ± 0.96; FV 3.45 + 2.68 (1.4% cs)\n", - "Musso: MV 6.19 ± 0.82; FV 5.78 + 1.26 (76.4% cs)\n", - "Cragno: MV 5.97 ± 1.01; FV 3.40 + 2.71 (1.1% cs)\n", - "Perin: MV 6.16 ± 0.88; FV 5.68 + 1.26 (67.6% cs)\n", - "Berisha: MV 5.93 ± 0.98; FV 3.40 + 2.70 (1.1% cs)\n", - "Christensen O.: MV 6.17 ± 0.87; FV 4.67 + 1.84 (12.3% cs)\n", - "Sportiello: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Mirante: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Sepe: MV 6.17 ± 0.90; FV 4.72 + 1.68 (12.4% cs)\n", - "Leali: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Lamanna: MV 6.21 ± 0.90; FV 5.10 + 1.49 (21.7% cs)\n", - "Sommariva: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Pegolo: MV 5.99 ± 0.97; FV 3.41 + 2.73 (1.2% cs)\n", - "Perilli: MV 6.27 ± 0.85; FV 5.10 + 1.49 (27.4% cs)\n", - "Padelli: MV 5.73 ± 1.03; FV 3.43 + 2.67 (1.2% cs)\n", - "Scuffet: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Gollini: MV 6.07 ± 0.88; FV 5.18 + 1.45 (19.8% cs)\n", - "Perisan: MV 5.82 ± 1.02; FV 3.40 + 2.72 (1.1% cs)\n", - "Audero: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Di Gennaro: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Pinsoglio: MV 6.14 ± 0.92; FV 5.10 + 1.47 (25.2% cs)\n", - "Aresti: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Fiorillo: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Cerofolini: MV 6.14 ± 0.92; FV 5.10 + 1.48 (23.1% cs)\n", - "Rossi F.: MV 6.20 ± 0.87; FV 5.10 + 1.48 (19.9% cs)\n", - "Costil: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Ravaglia F.: MV 5.88 ± 1.01; FV 3.48 + 2.61 (2.1% cs)\n", - "Frattali: MV 6.13 ± 0.89; FV 5.46 + 1.28 (34.2% cs)\n", - "Contini: MV 6.07 ± 0.88; FV 5.18 + 1.45 (19.8% cs)\n", - "Brancolini: MV 6.18 ± 0.90; FV 5.10 + 1.47 (29.3% cs)\n", - "Berardi A.: MV 6.27 ± 0.85; FV 5.10 + 1.49 (27.4% cs)\n", - "Gemello: MV 5.86 ± 0.99; FV 3.59 + 2.54 (1.5% cs)\n", - "Boer: MV 5.71 ± 1.04; FV 3.40 + 2.70 (1.1% cs)\n", - "Bagnolini: MV 5.88 ± 1.01; FV 3.48 + 2.61 (2.1% cs)\n", - "Svilar: MV 5.71 ± 1.04; FV 3.40 + 2.70 (1.1% cs)\n", - "Sorrentino A.: MV 6.04 ± 0.91; FV 4.65 + 1.69 (12.3% cs)\n", - "Martinelli T.: MV 6.25 ± 0.82; FV 5.12 + 1.47 (27.8% cs)\n", - "Popa: MV 5.86 ± 0.99; FV 3.59 + 2.54 (1.5% cs)\n", - "Stubljar: MV 5.95 ± 0.98; FV 3.41 + 2.73 (1.1% cs)\n", - "Gori: MV 6.21 ± 0.90; FV 5.10 + 1.49 (21.7% cs)\n", - "Borbei: MV 6.18 ± 0.90; FV 5.10 + 1.47 (29.3% cs)\n", - "Okoye: MV 5.73 ± 1.03; FV 3.43 + 2.67 (1.2% cs)\n", - "Mandas: MV 6.17 ± 0.90; FV 4.72 + 1.68 (12.4% cs)\n", - "Dimarco: MV 6.56 ± 0.78; FV 6.79 + 1.53\n", - "Di Lorenzo: MV 6.31 ± 1.10; FV 6.92 + 2.14\n", - "Hernandez T.: MV 6.22 ± 1.04; FV 6.79 + 2.05\n", - "Carlos Augusto: MV 6.50 ± 0.91; FV 7.04 + 2.15\n", - "Danilo: MV 6.39 ± 0.89; FV 6.85 + 1.87\n", - "Zappacosta: MV 6.17 ± 0.91; FV 6.52 + 1.55\n", - "Schuurs: MV 6.05 ± 1.14; FV 6.13 + 1.46\n", - "Posch: MV 5.98 ± 1.07; FV 6.21 + 1.56\n", - "Bastoni: MV 6.52 ± 0.75; FV 6.68 + 1.22\n", - "Smalling: MV 6.10 ± 0.92; FV 6.28 + 1.27\n", - "Dumfries: MV 6.48 ± 0.92; FV 7.04 + 2.17\n", - "Romagnoli: MV 6.13 ± 0.96; FV 6.32 + 1.40\n", - "Pavard: MV 6.43 ± 0.71; FV 6.62 + 1.21\n", - "Rrahmani: MV 6.06 ± 1.03; FV 6.21 + 1.30\n", - "Spinazzola: MV 6.17 ± 0.86; FV 6.48 + 1.43\n", - "Buongiorno: MV 6.03 ± 1.19; FV 6.17 + 1.66\n", - "Bremer: MV 6.24 ± 1.04; FV 6.69 + 1.89\n", - "Tomori: MV 6.14 ± 0.76; FV 6.19 + 0.86\n", - "Biraghi: MV 6.08 ± 0.89; FV 6.43 + 1.44\n", - "Mancini: MV 5.98 ± 0.99; FV 6.09 + 1.26\n", - "Darmian: MV 6.43 ± 0.74; FV 6.66 + 1.30\n", - "Bakker: MV 6.04 ± 0.55; FV 6.11 + 0.68\n", - "Mazzocchi: MV 5.92 ± 0.84; FV 6.11 + 1.18\n", - "Doig: MV 5.86 ± 1.08; FV 6.14 + 1.59\n", - "Calabria: MV 6.13 ± 0.82; FV 6.31 + 1.12\n", - "Acerbi: MV 6.37 ± 0.71; FV 6.47 + 0.99\n", - "Cuadrado: MV 6.36 ± 0.81; FV 6.61 + 1.39\n", - "Ebuehi: MV 5.53 ± 0.75; FV 5.50 + 0.77\n", - "Casale: MV 5.98 ± 0.82; FV 6.06 + 1.05\n", - "Holm: MV 6.11 ± 0.67; FV 6.23 + 0.86\n", - "Baschirotto: MV 6.11 ± 1.07; FV 6.41 + 1.59\n", - "Bijol: MV 5.77 ± 1.25; FV 5.65 + 1.55\n", - "Thiaw: MV 5.86 ± 1.15; FV 5.70 + 1.17\n", - "Mario Rui: MV 5.95 ± 0.80; FV 5.98 + 0.84\n", - "Milenkovic: MV 5.96 ± 0.89; FV 6.00 + 0.99\n", - "Rodriguez R.: MV 5.90 ± 0.99; FV 5.80 + 1.10\n", - "Kolasinac: MV 6.04 ± 0.65; FV 6.15 + 0.78\n", - "N'dicka: MV 5.98 ± 0.62; FV 5.96 + 0.61\n", - "Scalvini: MV 6.09 ± 0.87; FV 6.27 + 1.21\n", - "Perez N.: MV 5.79 ± 1.19; FV 5.67 + 1.45\n", - "Kristensen: MV 6.01 ± 0.75; FV 6.21 + 1.06\n", - "Izzo: MV 5.99 ± 0.91; FV 6.07 + 1.22\n", - "De Vrij: MV 6.48 ± 0.73; FV 6.62 + 1.14\n", - "Faraoni: MV 5.72 ± 0.79; FV 5.80 + 1.01\n", - "Toloi: MV 6.09 ± 0.75; FV 6.18 + 0.94\n", - "Kyriakopoulos: MV 5.88 ± 0.68; FV 5.89 + 0.80\n", - "Bellanova: MV 5.89 ± 1.08; FV 5.89 + 1.32\n", - "Mari': MV 5.82 ± 0.87; FV 5.83 + 1.04\n", - "Dodo': MV 5.96 ± 0.80; FV 6.00 + 0.88\n", - "Lucumi': MV 5.74 ± 1.04; FV 5.68 + 1.20\n", - "Hien: MV 5.70 ± 1.05; FV 5.66 + 1.25\n", - "Natan: MV 5.92 ± 0.90; FV 5.96 + 1.02\n", - "Hysaj: MV 5.98 ± 0.73; FV 6.08 + 1.02\n", - "D'ambrosio: MV 6.00 ± 0.67; FV 5.97 + 0.78\n", - "Luperto: MV 5.38 ± 1.16; FV 5.35 + 1.29\n", - "Djimsiti: MV 6.03 ± 0.63; FV 6.02 + 0.58\n", - "Marusic: MV 5.93 ± 0.81; FV 5.93 + 0.92\n", - "Martin: MV 5.85 ± 0.64; FV 5.93 + 0.80\n", - "Mina: MV 6.01 ± 0.71; FV 6.20 + 0.96\n", - "Toljan: MV 5.61 ± 0.86; FV 5.55 + 0.89\n", - "Llorente D.: MV 5.80 ± 0.98; FV 5.77 + 1.05\n", - "Martinez Quarta: MV 6.00 ± 0.85; FV 6.07 + 0.97\n", - "Bastoni S.: MV 5.55 ± 0.73; FV 5.49 + 0.78\n", - "Dragusin: MV 5.81 ± 0.84; FV 5.93 + 1.11\n", - "Parisi: MV 6.06 ± 0.79; FV 6.17 + 1.01\n", - "Bradaric: MV 5.83 ± 0.97; FV 5.91 + 1.24\n", - "Kamara H.: MV 5.96 ± 0.92; FV 5.97 + 1.09\n", - "Olivera: MV 5.98 ± 0.67; FV 6.08 + 0.75\n", - "Gendrey: MV 5.99 ± 0.71; FV 5.97 + 0.78\n", - "Kristiansen: MV 6.02 ± 0.86; FV 6.16 + 1.25\n", - "Beukema: MV 5.83 ± 1.11; FV 5.85 + 1.36\n", - "Dossena: MV 5.68 ± 0.85; FV 5.65 + 0.99\n", - "Pedersen: MV 5.77 ± 0.59; FV 5.78 + 0.62\n", - "Juan Jesus: MV 5.99 ± 0.60; FV 5.98 + 0.55\n", - "Gyomber: MV 5.83 ± 1.00; FV 5.78 + 1.10\n", - "Alex Sandro: MV 5.90 ± 0.90; FV 5.83 + 1.05\n", - "Hateboer: MV 6.04 ± 0.83; FV 6.28 + 1.29\n", - "Palomino: MV 5.98 ± 0.57; FV 5.99 + 0.58\n", - "Marchizza: MV 6.06 ± 0.79; FV 6.18 + 0.98\n", - "Zappa: MV 5.60 ± 0.86; FV 5.49 + 0.88\n", - "Gallo: MV 5.97 ± 0.87; FV 5.98 + 0.96\n", - "Caldirola: MV 5.80 ± 1.00; FV 5.85 + 1.33\n", - "Kalulu: MV 5.97 ± 0.84; FV 6.01 + 0.91\n", - "Erlic: MV 5.62 ± 0.99; FV 5.54 + 1.03\n", - "Vojvoda: MV 5.75 ± 0.87; FV 5.73 + 1.04\n", - "Vasquez: MV 5.91 ± 0.75; FV 5.88 + 0.81\n", - "Cambiaso: MV 6.18 ± 0.84; FV 6.38 + 1.29\n", - "Pongracic: MV 6.07 ± 0.83; FV 6.12 + 1.03\n", - "Viti: MV 5.92 ± 0.57; FV 6.01 + 0.74\n", - "Gatti: MV 6.18 ± 0.75; FV 6.26 + 0.99\n", - "Birindelli: MV 5.92 ± 0.77; FV 5.94 + 0.93\n", - "Azzi: MV 5.71 ± 0.73; FV 5.70 + 0.83\n", - "Wieteska: MV 5.75 ± 0.92; FV 5.73 + 1.09\n", - "Masina: MV 5.77 ± 1.20; FV 6.00 + 1.65\n", - "Romagnoli S.: MV 6.05 ± 0.94; FV 6.21 + 1.27\n", - "Pezzella Giu.: MV 5.40 ± 0.88; FV 5.34 + 0.81\n", - "Sabelli: MV 5.90 ± 0.60; FV 5.92 + 0.71\n", - "Lirola: MV 6.20 ± 0.89; FV 6.55 + 1.53\n", - "Lazzari: MV 6.01 ± 0.78; FV 6.01 + 0.92\n", - "Bani: MV 5.76 ± 1.04; FV 5.88 + 1.37\n", - "Djidji: MV 5.66 ± 1.00; FV 5.59 + 1.21\n", - "Kabasele: MV 5.67 ± 0.99; FV 5.56 + 1.17\n", - "Lazaro: MV 5.99 ± 0.83; FV 6.02 + 1.08\n", - "Augello: MV 5.66 ± 0.88; FV 5.69 + 1.01\n", - "Zortea: MV 6.11 ± 0.80; FV 6.40 + 1.25\n", - "Dawidowicz: MV 5.67 ± 1.02; FV 5.65 + 1.23\n", - "Pirola: MV 5.82 ± 1.05; FV 5.93 + 1.38\n", - "Lovato: MV 5.67 ± 0.88; FV 5.58 + 0.94\n", - "Ruggeri: MV 6.14 ± 0.93; FV 6.40 + 1.39\n", - "Vina: MV 5.70 ± 0.95; FV 5.68 + 1.02\n", - "Obert: MV 5.57 ± 1.01; FV 5.52 + 1.09\n", - "Terracciano F.: MV 6.02 ± 0.79; FV 6.12 + 1.04\n", - "Ebosele: MV 5.69 ± 0.90; FV 5.69 + 1.00\n", - "Zemura: MV 5.85 ± 0.89; FV 5.81 + 1.02\n", - "Hatzidiakos: MV 5.73 ± 0.90; FV 5.73 + 1.07\n", - "Patric: MV 6.02 ± 0.66; FV 6.01 + 0.67\n", - "Lykogiannis: MV 5.71 ± 0.73; FV 5.78 + 0.85\n", - "Pellegrini Lu.: MV 5.86 ± 0.66; FV 5.82 + 0.71\n", - "Magnani: MV 5.64 ± 1.15; FV 5.65 + 1.40\n", - "Ranieri L.: MV 5.90 ± 0.66; FV 5.89 + 0.70\n", - "Carboni A.: MV 5.96 ± 0.78; FV 6.03 + 0.97\n", - "Calafiori: MV 5.91 ± 0.97; FV 6.03 + 1.29\n", - "Monterisi: MV 6.19 ± 1.07; FV 6.73 + 2.09\n", - "Ismajli: MV 5.47 ± 0.86; FV 5.39 + 0.83\n" + "Sommer: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Szczesny: MV 5.98 ± 0.96; FV 4.94 + 1.44 (9.0% cs)\n", + "Meret: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Provedel: MV 6.13 ± 0.97; FV 3.79 + 2.12 (2.5% cs)\n", + "Maignan: MV 6.10 ± 0.92; FV 5.03 + 1.36 (22.9% cs)\n", + "Rui Patricio: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Skorupski: MV 6.14 ± 0.82; FV 5.82 + 1.23 (71.9% cs)\n", + "Milinkovic-Savic V.: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Di Gregorio: MV 6.27 ± 0.85; FV 5.05 + 1.41 (15.4% cs)\n", + "Falcone: MV 6.16 ± 0.91; FV 4.94 + 1.43 (15.0% cs)\n", + "Silvestri: MV 6.18 ± 0.91; FV 5.18 + 1.51 (32.2% cs)\n", + "Terracciano: MV 6.16 ± 0.84; FV 5.75 + 1.22 (68.0% cs)\n", + "Carnesecchi: MV 6.14 ± 0.96; FV 5.07 + 1.43 (20.7% cs)\n", + "Radunovic: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Montipo': MV 6.20 ± 0.82; FV 5.69 + 1.22 (55.2% cs)\n", + "Martinez Jo.: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Ochoa: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Caprile: MV 6.20 ± 0.91; FV 5.05 + 1.42 (21.4% cs)\n", + "Turati: MV 6.10 ± 0.97; FV 4.14 + 1.98 (4.6% cs)\n", + "Consigli: MV 6.13 ± 0.95; FV 4.94 + 1.47 (13.3% cs)\n", + "Musso: MV 6.17 ± 0.96; FV 5.04 + 1.37 (28.8% cs)\n", + "Cragno: MV 6.04 ± 0.98; FV 3.76 + 2.10 (2.3% cs)\n", + "Perin: MV 6.16 ± 0.93; FV 5.04 + 1.37 (20.1% cs)\n", + "Berisha: MV 6.23 ± 0.91; FV 5.04 + 1.38 (21.9% cs)\n", + "Christensen O.: MV 6.19 ± 0.88; FV 5.14 + 1.31 (31.1% cs)\n", + "Sportiello: MV 6.13 ± 0.92; FV 5.13 + 1.29 (32.9% cs)\n", + "Mirante: MV 6.10 ± 0.92; FV 5.03 + 1.36 (22.9% cs)\n", + "Sepe: MV 6.12 ± 0.97; FV 3.73 + 2.16 (2.3% cs)\n", + "Leali: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Lamanna: MV 6.26 ± 0.85; FV 5.04 + 1.38 (15.3% cs)\n", + "Sommariva: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Pegolo: MV 6.12 ± 0.95; FV 4.83 + 1.52 (12.1% cs)\n", + "Perilli: MV 6.20 ± 0.82; FV 5.71 + 1.22 (57.3% cs)\n", + "Padelli: MV 6.17 ± 0.91; FV 5.17 + 1.51 (31.5% cs)\n", + "Scuffet: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Gollini: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Perisan: MV 6.19 ± 0.87; FV 5.05 + 1.42 (25.8% cs)\n", + "Audero: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Di Gennaro: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Pinsoglio: MV 5.89 ± 0.98; FV 4.52 + 1.64 (3.3% cs)\n", + "Aresti: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Fiorillo: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Cerofolini: MV 6.08 ± 0.99; FV 3.63 + 2.32 (1.9% cs)\n", + "Rossi F.: MV 6.17 ± 0.96; FV 5.04 + 1.37 (28.9% cs)\n", + "Costil: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Ravaglia F.: MV 6.13 ± 0.82; FV 5.82 + 1.23 (71.7% cs)\n", + "Frattali: MV 6.10 ± 0.97; FV 4.14 + 1.98 (4.6% cs)\n", + "Contini: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Brancolini: MV 6.16 ± 0.90; FV 4.96 + 1.41 (16.4% cs)\n", + "Berardi A.: MV 6.20 ± 0.82; FV 5.71 + 1.22 (57.3% cs)\n", + "Gemello: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Boer: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Bagnolini: MV 6.13 ± 0.82; FV 5.82 + 1.23 (71.7% cs)\n", + "Svilar: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Sorrentino A.: MV 6.25 ± 0.85; FV 5.01 + 1.41 (10.6% cs)\n", + "Martinelli T.: MV 6.16 ± 0.84; FV 5.75 + 1.22 (66.1% cs)\n", + "Popa: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Stubljar: MV 6.23 ± 0.91; FV 5.04 + 1.38 (21.9% cs)\n", + "Gori: MV 6.26 ± 0.85; FV 5.04 + 1.38 (15.3% cs)\n", + "Borbei: MV 6.16 ± 0.90; FV 4.96 + 1.41 (16.4% cs)\n", + "Okoye: MV 6.17 ± 0.91; FV 5.17 + 1.51 (31.5% cs)\n", + "Mandas: MV 6.12 ± 0.97; FV 3.73 + 2.16 (2.3% cs)\n", + "Dimarco: MV 6.35 ± 0.79; FV 6.69 + 1.42\n", + "Di Lorenzo: MV 6.18 ± 0.97; FV 6.55 + 1.62\n", + "Hernandez T.: MV 6.22 ± 1.10; FV 6.75 + 2.07\n", + "Carlos Augusto: MV 6.24 ± 0.86; FV 6.63 + 1.47\n", + "Danilo: MV 6.02 ± 1.03; FV 6.18 + 1.39\n", + "Zappacosta: MV 5.99 ± 1.04; FV 6.21 + 1.47\n", + "Schuurs: MV 6.14 ± 0.71; FV 6.31 + 0.96\n", + "Posch: MV 6.21 ± 0.76; FV 6.52 + 1.38\n", + "Bastoni: MV 6.26 ± 0.77; FV 6.44 + 0.99\n", + "Smalling: MV 6.08 ± 0.85; FV 6.33 + 1.30\n", + "Dumfries: MV 6.30 ± 0.93; FV 6.81 + 1.82\n", + "Romagnoli: MV 5.95 ± 1.00; FV 6.01 + 1.24\n", + "Pavard: MV 6.12 ± 0.64; FV 6.25 + 0.78\n", + "Rrahmani: MV 6.00 ± 0.96; FV 6.13 + 1.24\n", + "Spinazzola: MV 6.15 ± 0.76; FV 6.44 + 1.31\n", + "Buongiorno: MV 6.11 ± 0.77; FV 6.35 + 1.22\n", + "Bremer: MV 5.80 ± 1.20; FV 5.91 + 1.51\n", + "Tomori: MV 6.22 ± 0.98; FV 6.58 + 1.69\n", + "Biraghi: MV 6.23 ± 0.98; FV 6.85 + 2.11\n", + "Mancini: MV 5.95 ± 1.02; FV 6.17 + 1.45\n", + "Darmian: MV 6.21 ± 0.75; FV 6.43 + 1.02\n", + "Bakker: MV 5.94 ± 0.66; FV 6.01 + 0.90\n", + "Mazzocchi: MV 5.61 ± 0.72; FV 5.57 + 0.74\n", + "Doig: MV 5.97 ± 0.96; FV 6.12 + 1.29\n", + "Calabria: MV 6.06 ± 0.92; FV 6.27 + 1.33\n", + "Acerbi: MV 6.13 ± 0.69; FV 6.20 + 0.71\n", + "Cuadrado: MV 6.11 ± 0.81; FV 6.26 + 1.00\n", + "Ebuehi: MV 5.90 ± 0.66; FV 5.91 + 0.74\n", + "Casale: MV 5.70 ± 1.08; FV 5.69 + 1.26\n", + "Holm: MV 5.98 ± 0.64; FV 6.05 + 0.82\n", + "Baschirotto: MV 5.76 ± 1.21; FV 5.84 + 1.45\n", + "Bijol: MV 5.83 ± 1.11; FV 5.97 + 1.52\n", + "Thiaw: MV 5.89 ± 1.23; FV 5.87 + 1.32\n", + "Mario Rui: MV 5.92 ± 0.67; FV 5.93 + 0.76\n", + "Milenkovic: MV 6.04 ± 0.96; FV 6.16 + 1.22\n", + "Rodriguez R.: MV 6.04 ± 0.64; FV 6.07 + 0.61\n", + "Kolasinac: MV 5.94 ± 0.78; FV 6.07 + 1.08\n", + "N'dicka: MV 5.91 ± 0.81; FV 5.93 + 0.98\n", + "Scalvini: MV 5.95 ± 1.17; FV 6.14 + 1.52\n", + "Perez N.: MV 5.78 ± 1.07; FV 5.78 + 1.25\n", + "Kristensen: MV 6.02 ± 0.68; FV 6.20 + 1.05\n", + "Izzo: MV 5.90 ± 0.93; FV 5.94 + 1.24\n", + "De Vrij: MV 6.22 ± 0.74; FV 6.36 + 0.83\n", + "Faraoni: MV 5.82 ± 0.70; FV 5.84 + 0.86\n", + "Toloi: MV 6.00 ± 1.00; FV 6.20 + 1.40\n", + "Kyriakopoulos: MV 6.03 ± 0.94; FV 6.20 + 1.44\n", + "Bellanova: MV 5.95 ± 0.88; FV 6.00 + 1.07\n", + "Mari': MV 5.84 ± 0.93; FV 5.87 + 1.20\n", + "Dodo': MV 6.04 ± 0.94; FV 6.14 + 1.23\n", + "Lucumi': MV 6.09 ± 0.64; FV 6.12 + 0.70\n", + "Hien: MV 5.87 ± 0.84; FV 5.82 + 0.87\n", + "Natan: MV 5.99 ± 0.76; FV 6.06 + 0.92\n", + "Hysaj: MV 5.70 ± 0.99; FV 5.69 + 1.15\n", + "D'ambrosio: MV 5.96 ± 0.72; FV 5.94 + 0.87\n", + "Luperto: MV 5.79 ± 1.05; FV 5.66 + 1.07\n", + "Djimsiti: MV 5.96 ± 0.77; FV 5.97 + 0.86\n", + "Marusic: MV 5.68 ± 1.10; FV 5.65 + 1.28\n", + "Martin: MV 6.02 ± 0.78; FV 6.11 + 1.02\n", + "Mina: MV 6.14 ± 0.78; FV 6.45 + 1.38\n", + "Toljan: MV 5.90 ± 0.80; FV 5.89 + 0.81\n", + "Llorente D.: MV 5.90 ± 0.79; FV 5.92 + 0.91\n", + "Martinez Quarta: MV 6.22 ± 1.04; FV 6.60 + 1.76\n", + "Bastoni S.: MV 5.98 ± 0.85; FV 6.19 + 1.29\n", + "Dragusin: MV 6.09 ± 0.75; FV 6.27 + 1.01\n", + "Parisi: MV 6.12 ± 0.90; FV 6.26 + 1.31\n", + "Bradaric: MV 5.61 ± 0.89; FV 5.58 + 0.96\n", + "Kamara H.: MV 5.93 ± 0.60; FV 5.91 + 0.64\n", + "Olivera: MV 5.95 ± 0.64; FV 6.00 + 0.77\n", + "Gendrey: MV 5.90 ± 0.80; FV 5.87 + 0.91\n", + "Kristiansen: MV 6.17 ± 0.68; FV 6.30 + 0.95\n", + "Beukema: MV 6.18 ± 0.72; FV 6.30 + 0.89\n", + "Dossena: MV 5.55 ± 1.06; FV 5.47 + 1.11\n", + "Pedersen: MV 5.90 ± 0.59; FV 5.89 + 0.57\n", + "Juan Jesus: MV 5.97 ± 0.64; FV 5.99 + 0.65\n", + "Gyomber: MV 5.60 ± 0.99; FV 5.54 + 1.09\n", + "Alex Sandro: MV 5.58 ± 1.23; FV 5.47 + 1.33\n", + "Hateboer: MV 5.85 ± 0.89; FV 5.91 + 1.16\n", + "Palomino: MV 5.98 ± 0.64; FV 6.02 + 0.80\n", + "Marchizza: MV 6.07 ± 1.07; FV 6.22 + 1.48\n", + "Zappa: MV 5.54 ± 1.01; FV 5.47 + 1.01\n", + "Gallo: MV 5.82 ± 0.99; FV 5.77 + 1.07\n", + "Caldirola: MV 5.73 ± 1.06; FV 5.79 + 1.39\n", + "Kalulu: MV 5.94 ± 0.94; FV 5.97 + 1.12\n", + "Erlic: MV 5.90 ± 0.83; FV 5.87 + 0.75\n", + "Vojvoda: MV 5.97 ± 0.61; FV 6.00 + 0.66\n", + "Vasquez: MV 6.14 ± 0.68; FV 6.18 + 0.66\n", + "Cambiaso: MV 5.80 ± 1.05; FV 5.84 + 1.25\n", + "Pongracic: MV 5.96 ± 0.90; FV 5.98 + 1.01\n", + "Viti: MV 5.94 ± 0.83; FV 5.89 + 0.79\n", + "Gatti: MV 5.62 ± 1.36; FV 5.55 + 1.49\n", + "Birindelli: MV 5.93 ± 0.75; FV 5.95 + 0.96\n", + "Azzi: MV 5.74 ± 0.76; FV 5.72 + 0.78\n", + "Wieteska: MV 5.67 ± 1.14; FV 5.63 + 1.30\n", + "Masina: MV 5.84 ± 1.09; FV 6.26 + 1.75\n", + "Romagnoli S.: MV 5.98 ± 1.26; FV 5.97 + 1.64\n", + "Pezzella Giu.: MV 5.67 ± 0.79; FV 5.60 + 0.72\n", + "Sabelli: MV 6.01 ± 0.52; FV 6.07 + 0.58\n", + "Lirola: MV 5.95 ± 1.16; FV 6.00 + 1.46\n", + "Lazzari: MV 5.90 ± 0.88; FV 5.87 + 1.01\n", + "Bani: MV 6.18 ± 0.92; FV 6.54 + 1.61\n", + "Djidji: MV 5.94 ± 0.65; FV 5.96 + 0.67\n", + "Kabasele: MV 5.88 ± 0.70; FV 5.82 + 0.79\n", + "Lazaro: MV 6.07 ± 0.63; FV 6.13 + 0.66\n", + "Augello: MV 5.62 ± 1.00; FV 5.64 + 1.06\n", + "Zortea: MV 5.91 ± 0.87; FV 6.07 + 1.20\n", + "Dawidowicz: MV 5.87 ± 0.76; FV 5.83 + 0.83\n", + "Pirola: MV 5.55 ± 0.90; FV 5.50 + 0.91\n", + "Lovato: MV 5.54 ± 0.88; FV 5.47 + 0.89\n", + "Ruggeri: MV 5.96 ± 1.14; FV 6.18 + 1.53\n", + "Vina: MV 5.77 ± 1.06; FV 5.74 + 1.20\n", + "Obert: MV 5.54 ± 1.08; FV 5.47 + 1.10\n", + "Terracciano F.: MV 6.03 ± 0.70; FV 6.09 + 0.77\n", + "Ebosele: MV 5.83 ± 0.89; FV 5.77 + 0.99\n", + "Zemura: MV 5.89 ± 0.61; FV 5.85 + 0.64\n", + "Hatzidiakos: MV 5.64 ± 1.13; FV 5.60 + 1.24\n", + "Patric: MV 5.78 ± 0.84; FV 5.70 + 0.89\n", + "Lykogiannis: MV 6.00 ± 0.49; FV 6.06 + 0.52\n", + "Pellegrini Lu.: MV 5.61 ± 0.86; FV 5.50 + 0.88\n", + "Magnani: MV 5.89 ± 0.93; FV 5.85 + 1.01\n", + "Ranieri L.: MV 5.98 ± 0.84; FV 6.03 + 1.04\n", + "Carboni A.: MV 5.96 ± 0.76; FV 6.02 + 1.02\n", + "Calafiori: MV 6.05 ± 0.70; FV 6.10 + 0.86\n", + "Monterisi: MV 5.92 ± 1.35; FV 6.08 + 2.01\n", + "Ismajli: MV 5.84 ± 0.80; FV 5.79 + 0.73\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "De Winter: MV 5.82 ± 0.83; FV 5.72 + 0.86\n", - "Tressoldi: MV 5.71 ± 0.86; FV 5.74 + 1.05\n", - "Ehizibue: MV 5.61 ± 1.06; FV 5.63 + 1.22\n", - "Vogliacco: MV 5.84 ± 0.85; FV 5.83 + 0.96\n", - "Ferrari G.: MV 5.60 ± 1.00; FV 5.63 + 1.14\n", - "Venuti: MV 5.89 ± 0.77; FV 5.86 + 0.79\n", - "Karsdorp: MV 5.87 ± 0.56; FV 5.85 + 0.51\n", - "Kjaer: MV 5.79 ± 0.54; FV 5.79 + 0.46\n", - "Gunter: MV 5.56 ± 1.17; FV 5.50 + 1.38\n", - "Soumaoro: MV 5.78 ± 1.30; FV 5.74 + 1.46\n", - "Di Pardo: MV 5.60 ± 0.97; FV 5.54 + 1.05\n", - "Zanoli: MV 6.08 ± 0.92; FV 6.39 + 1.42\n", - "Zima: MV 5.81 ± 0.75; FV 5.74 + 0.77\n", - "Hefti: MV 5.70 ± 0.82; FV 5.61 + 0.85\n", - "Ostigard: MV 5.76 ± 0.64; FV 5.75 + 0.59\n", - "Sambia: MV 5.95 ± 0.78; FV 5.99 + 0.93\n", - "Bisseck: MV 6.28 ± 0.75; FV 6.46 + 1.16\n", - "Oyono: MV 6.04 ± 0.72; FV 6.08 + 0.78\n", - "Ferreira J.: MV 5.62 ± 0.97; FV 5.54 + 1.07\n", - "Dorgu: MV 6.10 ± 0.67; FV 6.12 + 0.78\n", - "Touba: MV 6.05 ± 0.79; FV 6.12 + 1.00\n", - "Sazonov: MV 5.79 ± 1.12; FV 5.72 + 1.35\n", - "Rugani: MV 6.13 ± 0.60; FV 6.16 + 0.68\n", - "De Sciglio: MV 5.98 ± 0.68; FV 6.00 + 0.75\n", - "Goldaniga: MV 5.52 ± 0.98; FV 5.44 + 1.02\n", - "Florenzi: MV 6.05 ± 0.58; FV 6.08 + 0.60\n", - "De Silvestri: MV 5.83 ± 0.74; FV 5.90 + 0.90\n", - "Pereira P.: MV 5.91 ± 0.78; FV 5.94 + 0.95\n", - "Fazio: MV 5.84 ± 1.27; FV 5.98 + 1.65\n", - "Bereszynski: MV 5.42 ± 0.88; FV 5.36 + 0.83\n", - "Bonifazi: MV 5.61 ± 1.09; FV 5.47 + 1.18\n", - "Walukiewicz: MV 5.36 ± 0.80; FV 5.30 + 0.63\n", - "Okoli: MV 5.95 ± 0.73; FV 5.93 + 0.75\n", - "Kumbulla: MV 5.35 ± 1.44; FV 5.20 + 1.41\n", - "Celik: MV 5.61 ± 0.86; FV 5.49 + 0.84\n", - "Amione: MV 5.61 ± 0.97; FV 5.58 + 1.15\n", - "Daniliuc: MV 5.76 ± 1.07; FV 5.79 + 1.33\n", - "Soppy: MV 5.73 ± 0.86; FV 5.70 + 1.02\n", - "Haps: MV 5.78 ± 0.86; FV 5.83 + 1.08\n", - "Cittadini: MV 5.94 ± 0.88; FV 6.05 + 1.19\n", - "Coppola D.: MV 5.64 ± 0.87; FV 5.55 + 0.97\n", - "Cacace: MV 5.43 ± 0.74; FV 5.34 + 0.66\n", - "Ebosse: MV 5.48 ± 0.96; FV 5.41 + 0.93\n", - "Guessand A.: MV 5.67 ± 1.05; FV 5.61 + 1.24\n", - "Cabal: MV 5.73 ± 0.58; FV 5.63 + 0.59\n", - "Missori: MV 5.69 ± 0.77; FV 5.67 + 0.88\n", - "Kayode: MV 6.02 ± 0.67; FV 6.05 + 0.67\n", - "Corazza: MV 5.66 ± 0.84; FV 5.63 + 0.92\n", - "Kristensen T.: MV 5.75 ± 1.13; FV 5.70 + 1.44\n", - "Dermaku: MV 6.02 ± 0.85; FV 6.11 + 1.09\n", - "Tonelli: MV 5.41 ± 0.96; FV 5.35 + 0.94\n", - "Capradossi: MV 5.66 ± 1.03; FV 5.68 + 1.23\n", - "Bettella: MV 5.94 ± 0.88; FV 6.05 + 1.19\n", - "Amey: MV 5.76 ± 1.09; FV 5.83 + 1.37\n", - "Gila: MV 5.93 ± 0.78; FV 5.93 + 0.84\n", - "Bronn: MV 5.64 ± 0.91; FV 5.53 + 0.93\n", - "Guarino: MV 5.51 ± 0.90; FV 5.48 + 0.94\n", - "Carboni F.: MV 5.98 ± 0.78; FV 6.05 + 0.98\n", - "Smajlovic: MV 6.03 ± 0.88; FV 6.15 + 1.17\n", - "Matturro: MV 5.84 ± 0.85; FV 5.83 + 0.96\n", - "N'guessan: MV 5.79 ± 1.12; FV 5.72 + 1.35\n", - "Mateus Lusuardi: MV 6.05 ± 0.89; FV 6.20 + 1.15\n", - "Kalaj: MV 6.05 ± 0.89; FV 6.20 + 1.15\n", - "Pierozzi: MV 5.98 ± 0.72; FV 6.01 + 0.75\n", - "Huijsen: MV 6.10 ± 0.84; FV 6.32 + 1.33\n", - "Bonfanti: MV 6.06 ± 0.73; FV 6.14 + 0.89\n", - "Pellegrino: MV 6.02 ± 0.78; FV 6.08 + 0.88\n", - "Comuzzo: MV 5.98 ± 0.72; FV 6.01 + 0.75\n", - "Zaccagni: MV 6.34 ± 1.07; FV 7.04 + 2.49\n", - "Koopmeiners: MV 6.41 ± 1.04; FV 7.19 + 2.57\n", - "Luis Alberto: MV 6.41 ± 1.05; FV 7.19 + 2.62\n", - "Felipe Anderson: MV 6.15 ± 1.18; FV 6.87 + 2.56\n", - "Rabiot: MV 6.40 ± 1.17; FV 7.36 + 3.00\n", - "Zielinski: MV 6.27 ± 0.84; FV 6.58 + 1.44\n", - "Barella: MV 6.55 ± 0.86; FV 6.97 + 1.99\n", - "Pulisic: MV 6.26 ± 1.01; FV 6.79 + 1.96\n", - "Orsolini: MV 6.21 ± 1.25; FV 6.97 + 2.66\n", - "Calhanoglu: MV 6.61 ± 0.75; FV 6.79 + 1.50\n", - "Strefezza: MV 6.27 ± 1.04; FV 6.84 + 2.11\n", - "Chukwueze: MV 6.07 ± 0.75; FV 6.28 + 1.03\n", - "Ferguson: MV 6.21 ± 1.08; FV 6.74 + 2.06\n", - "Candreva: MV 6.21 ± 1.26; FV 6.97 + 2.68\n", - "Frattesi: MV 6.52 ± 1.02; FV 7.36 + 2.82\n", - "Samardzic: MV 6.07 ± 1.11; FV 6.59 + 1.98\n", - "Vlasic: MV 6.14 ± 1.13; FV 6.69 + 2.07\n", - "Bonaventura: MV 6.21 ± 0.98; FV 6.72 + 1.90\n", - "Politano: MV 6.33 ± 0.81; FV 6.63 + 1.48\n", - "El Shaarawy: MV 6.26 ± 0.92; FV 6.63 + 1.69\n", - "Mkhitaryan: MV 6.54 ± 0.94; FV 7.17 + 2.42\n", - "Aouar: MV 6.13 ± 1.01; FV 6.63 + 1.90\n", - "Malinovskyi: MV 5.95 ± 1.05; FV 6.42 + 1.86\n", - "Gudmundsson A.: MV 6.03 ± 0.88; FV 6.33 + 1.41\n", - "Kamada: MV 6.09 ± 0.98; FV 6.57 + 1.90\n", - "Pellegrini Lo.: MV 5.98 ± 1.15; FV 6.51 + 1.97\n", - "Kostic: MV 6.33 ± 1.04; FV 6.99 + 2.31\n", - "Radonjic: MV 6.34 ± 1.25; FV 7.23 + 2.88\n", - "Baldanzi: MV 5.59 ± 0.76; FV 5.61 + 0.86\n", - "Lovric: MV 6.14 ± 1.07; FV 6.60 + 1.88\n", - "Lindstrom: MV 6.10 ± 0.81; FV 6.34 + 1.23\n", - "Lazovic: MV 6.13 ± 1.02; FV 6.53 + 1.74\n", - "Pereyra: MV 6.20 ± 1.23; FV 6.83 + 2.49\n", - "Renato Sanches: MV 6.13 ± 0.77; FV 6.36 + 1.08\n", - "Pessina: MV 6.09 ± 0.94; FV 6.48 + 1.66\n", - "Guendouzi: MV 6.04 ± 0.69; FV 6.16 + 0.86\n", - "Loftus-Cheek: MV 6.12 ± 0.64; FV 6.15 + 0.66\n", - "Zambo Anguissa: MV 6.08 ± 0.93; FV 6.37 + 1.34\n", - "Elmas: MV 6.04 ± 0.98; FV 6.42 + 1.57\n", - "Bajrami: MV 5.90 ± 0.65; FV 5.95 + 0.74\n", - "Ricci S.: MV 6.02 ± 0.85; FV 6.14 + 1.21\n", - "Colpani: MV 6.35 ± 1.05; FV 7.08 + 2.50\n", - "Ciurria: MV 6.17 ± 1.02; FV 6.71 + 2.04\n", - "De Roon: MV 6.16 ± 0.81; FV 6.38 + 1.18\n", - "Pogba: MV 6.09 ± 0.72; FV 6.19 + 0.98\n", - "Cristante: MV 6.11 ± 1.04; FV 6.32 + 1.47\n", - "Locatelli: MV 6.17 ± 0.77; FV 6.33 + 1.15\n", - "Pasalic: MV 6.05 ± 0.80; FV 6.36 + 1.28\n", - "Lobotka: MV 6.06 ± 0.65; FV 6.11 + 0.66\n", - "Fagioli: MV 6.19 ± 1.02; FV 6.72 + 2.01\n", - "Ikone': MV 6.02 ± 0.93; FV 6.40 + 1.55\n", - "Ilic: MV 6.03 ± 0.97; FV 6.27 + 1.49\n", - "Ndoye: MV 5.83 ± 0.88; FV 5.96 + 1.14\n", - "Ederson D.s.: MV 6.13 ± 0.81; FV 6.31 + 1.10\n", - "Reijnders: MV 6.17 ± 0.76; FV 6.37 + 1.06\n", - "Barak: MV 5.95 ± 0.71; FV 6.05 + 0.81\n", - "Saponara: MV 6.02 ± 1.02; FV 6.42 + 1.69\n", - "Mandragora: MV 6.03 ± 0.90; FV 6.33 + 1.41\n", - "Weah: MV 6.09 ± 0.59; FV 6.21 + 0.74\n", - "Bennacer: MV 6.24 ± 0.82; FV 6.54 + 1.32\n", - "Duda: MV 6.17 ± 1.11; FV 6.71 + 2.09\n", - "Castrovilli: MV 6.04 ± 0.99; FV 6.46 + 1.69\n", - "Mckennie: MV 6.35 ± 0.94; FV 6.84 + 1.93\n", - "Miranchuk: MV 6.22 ± 0.84; FV 6.60 + 1.49\n", - "Matheus Henrique: MV 5.77 ± 0.78; FV 5.87 + 1.02\n", - "De Ketelaere: MV 6.06 ± 0.82; FV 6.27 + 1.10\n", - "Mboula: MV 5.62 ± 0.76; FV 5.60 + 0.82\n", - "Paredes: MV 5.77 ± 1.07; FV 5.70 + 1.16\n", - "Sottil: MV 6.01 ± 0.62; FV 6.11 + 0.69\n", - "Klaassen: MV 6.40 ± 0.83; FV 6.81 + 1.78\n", - "Arthur Melo: MV 6.03 ± 0.76; FV 6.06 + 0.78\n", - "Thorsby: MV 5.72 ± 0.90; FV 5.79 + 1.16\n", - "Nandez: MV 5.94 ± 0.71; FV 6.04 + 1.00\n", - "Tameze: MV 5.80 ± 0.87; FV 5.74 + 1.01\n", - "Marin: MV 5.56 ± 0.85; FV 5.54 + 0.93\n", - "Messias: MV 5.86 ± 1.02; FV 6.23 + 1.61\n", - "Musah: MV 6.03 ± 0.61; FV 6.03 + 0.63\n", - "Coulibaly L.: MV 6.05 ± 1.05; FV 6.36 + 1.62\n", - "Krunic: MV 6.05 ± 0.68; FV 6.04 + 0.69\n", - "Cataldi: MV 5.96 ± 0.69; FV 5.94 + 0.68\n", - "Strootman: MV 5.87 ± 0.69; FV 5.92 + 0.86\n", - "Duncan: MV 6.08 ± 0.76; FV 6.33 + 1.11\n", - "Freuler: MV 5.92 ± 0.65; FV 5.96 + 0.79\n", - "Gagliardini: MV 5.88 ± 0.75; FV 5.85 + 0.79\n", - "Mazzitelli: MV 6.27 ± 1.12; FV 6.89 + 2.24\n", - "Jankto: MV 5.82 ± 0.67; FV 5.79 + 0.73\n", - "Kastanos: MV 5.95 ± 0.75; FV 6.08 + 0.99\n", - "Gyasi: MV 5.52 ± 0.74; FV 5.45 + 0.77\n", - "Reinier: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Zalewski: MV 5.97 ± 0.75; FV 6.06 + 0.84\n", - "Harroui: MV 6.27 ± 0.92; FV 6.73 + 1.77\n", - "Frendrup: MV 5.94 ± 0.68; FV 6.00 + 0.87\n", - "Blin: MV 6.03 ± 0.61; FV 6.03 + 0.69\n", - "Fabbian: MV 6.09 ± 0.95; FV 6.48 + 1.69\n", - "Ramadani: MV 6.20 ± 0.90; FV 6.36 + 1.25\n", - "Cajuste : MV 5.92 ± 0.87; FV 5.94 + 0.96\n", - "Mancosu: MV 5.69 ± 0.99; FV 5.73 + 1.21\n", - "Vecino: MV 5.96 ± 0.82; FV 6.04 + 1.06\n", - "Sensi: MV 6.42 ± 0.87; FV 6.88 + 1.88\n", - "Walace: MV 5.65 ± 1.00; FV 5.61 + 1.10\n", - "Lopez M.: MV 5.90 ± 0.61; FV 5.85 + 0.54\n", - "Brescianini: MV 6.09 ± 0.69; FV 6.15 + 0.78\n", - "Bove: MV 6.02 ± 0.72; FV 6.17 + 0.90\n", - "Aebischer: MV 5.83 ± 0.72; FV 5.98 + 0.96\n", - "Thorstvedt: MV 5.86 ± 0.62; FV 5.89 + 0.70\n", - "Gonzalez J.: MV 5.98 ± 0.75; FV 6.07 + 1.03\n", - "Moro N.: MV 6.03 ± 0.85; FV 6.28 + 1.32\n", - "Oudin: MV 6.14 ± 0.94; FV 6.49 + 1.59\n", - "Boloca: MV 5.73 ± 0.88; FV 5.75 + 1.07\n", - "Rafia: MV 6.15 ± 0.74; FV 6.37 + 1.23\n", - "Makoumbou: MV 5.78 ± 0.70; FV 5.80 + 0.83\n", - "Kaba: MV 6.04 ± 0.57; FV 6.02 + 0.62\n", - "Badelj: MV 5.86 ± 0.75; FV 5.83 + 0.78\n", - "Machin: MV 5.95 ± 0.88; FV 6.06 + 1.20\n", - "Linetty: MV 5.81 ± 0.84; FV 5.78 + 1.02\n", - "Castillejo: MV 5.79 ± 0.59; FV 5.86 + 0.70\n", - "Rovella: MV 6.09 ± 0.95; FV 6.22 + 1.27\n", - "Pobega: MV 6.02 ± 0.64; FV 6.10 + 0.74\n", - "Hongla: MV 5.72 ± 0.82; FV 5.79 + 0.98\n", - "Miretti: MV 6.05 ± 0.75; FV 6.26 + 1.08\n", - "Fazzini: MV 5.55 ± 0.64; FV 5.42 + 0.65\n", - "Iling Junior: MV 6.09 ± 0.84; FV 6.30 + 1.33\n", - "Oristanio: MV 5.68 ± 0.84; FV 5.63 + 0.90\n", - "Serdar: MV 5.73 ± 0.83; FV 5.75 + 1.00\n", - "Payero: MV 5.80 ± 1.04; FV 5.79 + 1.30\n", - "Grassi: MV 5.51 ± 0.78; FV 5.42 + 0.78\n", - "Baez: MV 6.08 ± 0.75; FV 6.29 + 1.02\n", - "Deiola: MV 5.66 ± 0.97; FV 5.68 + 1.14\n", - "Garritano: MV 6.22 ± 0.67; FV 6.30 + 0.83\n", - "Bourabia: MV 6.07 ± 0.80; FV 6.25 + 1.05\n", - "Saelemaekers: MV 5.92 ± 0.90; FV 6.19 + 1.34\n", - "Maldini: MV 5.64 ± 0.73; FV 5.69 + 0.89\n", - "Racic: MV 5.85 ± 0.63; FV 5.83 + 0.68\n", - "Kovalenko: MV 5.61 ± 0.67; FV 5.54 + 0.73\n" + "De Winter: MV 6.07 ± 0.86; FV 6.09 + 0.87\n", + "Tressoldi: MV 5.97 ± 0.85; FV 6.01 + 1.01\n", + "Ehizibue: MV 5.78 ± 0.92; FV 5.88 + 1.30\n", + "Vogliacco: MV 6.04 ± 0.82; FV 6.06 + 0.86\n", + "Ferrari G.: MV 6.01 ± 0.87; FV 6.14 + 1.18\n", + "Venuti: MV 5.78 ± 0.84; FV 5.74 + 0.91\n", + "Karsdorp: MV 5.91 ± 0.57; FV 5.91 + 0.61\n", + "Kjaer: MV 5.69 ± 0.91; FV 5.60 + 0.91\n", + "Gunter: MV 5.69 ± 1.03; FV 5.58 + 1.07\n", + "Soumaoro: MV 6.13 ± 0.77; FV 6.19 + 0.95\n", + "Di Pardo: MV 5.58 ± 1.09; FV 5.51 + 1.14\n", + "Zanoli: MV 6.00 ± 0.89; FV 6.20 + 1.28\n", + "Zima: MV 6.05 ± 0.77; FV 6.09 + 0.77\n", + "Hefti: MV 5.91 ± 0.65; FV 5.88 + 0.56\n", + "Ostigard: MV 5.82 ± 0.72; FV 5.79 + 0.74\n", + "Sambia: MV 5.70 ± 0.77; FV 5.68 + 0.85\n", + "Bisseck: MV 6.07 ± 0.81; FV 6.20 + 0.99\n", + "Oyono: MV 5.79 ± 1.02; FV 5.64 + 1.13\n", + "Ferreira J.: MV 5.84 ± 0.66; FV 5.78 + 0.74\n", + "Dorgu: MV 5.91 ± 0.55; FV 5.87 + 0.53\n", + "Touba: MV 5.82 ± 1.03; FV 5.84 + 1.20\n", + "Sazonov: MV 6.01 ± 0.68; FV 6.06 + 0.74\n", + "Rugani: MV 5.92 ± 0.55; FV 5.92 + 0.57\n", + "De Sciglio: MV 5.72 ± 0.75; FV 5.64 + 0.76\n", + "Goldaniga: MV 5.55 ± 1.26; FV 5.46 + 1.44\n", + "Florenzi: MV 6.07 ± 0.75; FV 6.15 + 0.89\n", + "De Silvestri: MV 6.11 ± 0.51; FV 6.18 + 0.53\n", + "Pereira P.: MV 5.96 ± 0.81; FV 6.02 + 1.10\n", + "Fazio: MV 5.66 ± 1.26; FV 5.65 + 1.48\n", + "Bereszynski: MV 5.66 ± 0.88; FV 5.58 + 0.91\n", + "Bonifazi: MV 6.00 ± 0.61; FV 6.01 + 0.59\n", + "Walukiewicz: MV 5.75 ± 0.95; FV 5.69 + 1.00\n", + "Okoli: MV 5.65 ± 1.12; FV 5.49 + 1.24\n", + "Kumbulla: MV 5.55 ± 1.47; FV 5.32 + 1.45\n", + "Celik: MV 5.73 ± 0.91; FV 5.65 + 1.02\n", + "Amione: MV 5.66 ± 0.94; FV 5.63 + 1.06\n", + "Daniliuc: MV 5.58 ± 0.97; FV 5.54 + 1.08\n", + "Soppy: MV 5.97 ± 0.59; FV 5.98 + 0.62\n", + "Haps: MV 6.06 ± 0.83; FV 6.15 + 1.01\n", + "Cittadini: MV 5.92 ± 0.86; FV 5.96 + 1.19\n", + "Coppola D.: MV 5.82 ± 0.72; FV 5.76 + 0.72\n", + "Cacace: MV 5.76 ± 0.70; FV 5.71 + 0.66\n", + "Ebosse: MV 5.85 ± 0.75; FV 5.78 + 0.81\n", + "Guessand A.: MV 5.91 ± 0.91; FV 5.93 + 1.13\n", + "Cabal: MV 6.00 ± 0.89; FV 6.02 + 1.00\n", + "Missori: MV 6.00 ± 0.87; FV 6.06 + 1.05\n", + "Kayode: MV 6.14 ± 0.91; FV 6.25 + 1.14\n", + "Corazza: MV 6.00 ± 0.58; FV 6.01 + 0.64\n", + "Kristensen T.: MV 5.81 ± 0.81; FV 5.76 + 0.97\n", + "Dermaku: MV 5.79 ± 1.01; FV 5.84 + 1.22\n", + "Tonelli: MV 5.73 ± 0.85; FV 5.65 + 0.82\n", + "Capradossi: MV 5.66 ± 1.16; FV 5.64 + 1.29\n", + "Bettella: MV 5.92 ± 0.86; FV 5.96 + 1.19\n", + "Amey: MV 6.10 ± 0.70; FV 6.20 + 0.93\n", + "Gila: MV 5.69 ± 1.04; FV 5.64 + 1.17\n", + "Bronn: MV 5.52 ± 1.00; FV 5.44 + 1.09\n", + "Guarino: MV 5.89 ± 0.77; FV 5.88 + 0.84\n", + "Carboni F.: MV 6.01 ± 0.87; FV 6.13 + 1.25\n", + "Smajlovic: MV 5.80 ± 1.05; FV 5.87 + 1.30\n", + "Matturro: MV 6.03 ± 0.80; FV 6.04 + 0.80\n", + "N'guessan: MV 6.00 ± 0.73; FV 6.06 + 0.81\n", + "Mateus Lusuardi: MV 5.78 ± 1.20; FV 5.72 + 1.43\n", + "Kalaj: MV 5.78 ± 1.20; FV 5.72 + 1.43\n", + "Pierozzi: MV 6.05 ± 0.85; FV 6.12 + 1.04\n", + "Huijsen: MV 5.76 ± 1.10; FV 5.81 + 1.34\n", + "Bonfanti: MV 5.90 ± 1.04; FV 6.01 + 1.33\n", + "Pellegrino: MV 5.98 ± 0.88; FV 6.06 + 1.11\n", + "Comuzzo: MV 6.05 ± 0.85; FV 6.12 + 1.04\n", + "Zaccagni: MV 6.25 ± 1.08; FV 6.80 + 2.13\n", + "Koopmeiners: MV 6.30 ± 1.07; FV 6.90 + 2.21\n", + "Luis Alberto: MV 6.20 ± 1.10; FV 6.77 + 2.14\n", + "Felipe Anderson: MV 6.00 ± 1.06; FV 6.39 + 1.70\n", + "Rabiot: MV 6.07 ± 1.12; FV 6.54 + 1.93\n", + "Zielinski: MV 6.19 ± 0.87; FV 6.57 + 1.52\n", + "Barella: MV 6.29 ± 0.89; FV 6.73 + 1.65\n", + "Pulisic: MV 6.32 ± 1.15; FV 7.11 + 2.64\n", + "Orsolini: MV 6.25 ± 0.91; FV 6.88 + 2.16\n", + "Calhanoglu: MV 6.38 ± 0.78; FV 6.65 + 1.28\n", + "Strefezza: MV 6.00 ± 0.95; FV 6.28 + 1.49\n", + "Chukwueze: MV 5.93 ± 0.81; FV 6.17 + 1.14\n", + "Ferguson: MV 6.25 ± 0.74; FV 6.60 + 1.38\n", + "Candreva: MV 6.03 ± 1.24; FV 6.33 + 1.84\n", + "Frattesi: MV 6.30 ± 1.02; FV 6.93 + 2.18\n", + "Samardzic: MV 6.19 ± 0.99; FV 6.69 + 1.94\n", + "Vlasic: MV 6.10 ± 0.78; FV 6.35 + 1.22\n", + "Bonaventura: MV 6.40 ± 1.13; FV 7.25 + 2.73\n", + "Politano: MV 6.25 ± 0.91; FV 6.71 + 1.79\n", + "El Shaarawy: MV 6.17 ± 0.85; FV 6.53 + 1.56\n", + "Mkhitaryan: MV 6.35 ± 1.00; FV 6.99 + 2.19\n", + "Aouar: MV 6.07 ± 1.04; FV 6.58 + 1.92\n", + "Malinovskyi: MV 6.18 ± 0.90; FV 6.65 + 1.82\n", + "Gudmundsson A.: MV 6.30 ± 0.94; FV 6.86 + 1.99\n", + "Kamada: MV 5.98 ± 1.03; FV 6.33 + 1.59\n", + "Pellegrini Lo.: MV 5.98 ± 1.09; FV 6.45 + 1.89\n", + "Kostic: MV 6.07 ± 0.92; FV 6.36 + 1.44\n", + "Radonjic: MV 6.30 ± 1.08; FV 6.99 + 2.38\n", + "Baldanzi: MV 5.90 ± 0.98; FV 6.25 + 1.56\n", + "Lovric: MV 6.07 ± 0.84; FV 6.40 + 1.48\n", + "Lindstrom: MV 5.94 ± 0.73; FV 6.18 + 1.15\n", + "Lazovic: MV 6.10 ± 0.84; FV 6.37 + 1.36\n", + "Pereyra: MV 6.18 ± 1.23; FV 6.88 + 2.56\n", + "Renato Sanches: MV 6.16 ± 0.73; FV 6.43 + 1.22\n", + "Pessina: MV 6.07 ± 0.92; FV 6.39 + 1.58\n", + "Guendouzi: MV 5.86 ± 0.84; FV 6.00 + 1.07\n", + "Loftus-Cheek: MV 6.25 ± 0.91; FV 6.68 + 1.68\n", + "Zambo Anguissa: MV 6.03 ± 0.92; FV 6.23 + 1.29\n", + "Elmas: MV 5.93 ± 0.95; FV 6.23 + 1.48\n", + "Bajrami: MV 6.03 ± 0.68; FV 6.21 + 0.90\n", + "Ricci S.: MV 6.04 ± 0.73; FV 6.13 + 0.88\n", + "Colpani: MV 6.38 ± 1.13; FV 7.19 + 2.68\n", + "Ciurria: MV 6.02 ± 1.05; FV 6.47 + 1.94\n", + "De Roon: MV 6.06 ± 1.00; FV 6.33 + 1.51\n", + "Pogba: MV 5.94 ± 0.88; FV 6.00 + 1.15\n", + "Cristante: MV 6.12 ± 0.99; FV 6.50 + 1.66\n", + "Locatelli: MV 5.88 ± 0.82; FV 5.90 + 1.03\n", + "Pasalic: MV 5.97 ± 1.01; FV 6.35 + 1.63\n", + "Lobotka: MV 6.01 ± 0.72; FV 6.08 + 0.85\n", + "Fagioli: MV 5.95 ± 1.02; FV 6.23 + 1.53\n", + "Ikone': MV 6.21 ± 1.03; FV 6.76 + 2.04\n", + "Ilic: MV 6.05 ± 0.66; FV 6.11 + 0.74\n", + "Ndoye: MV 6.09 ± 0.64; FV 6.21 + 0.83\n", + "Ederson D.s.: MV 6.05 ± 1.00; FV 6.36 + 1.56\n", + "Reijnders: MV 6.18 ± 0.90; FV 6.56 + 1.57\n", + "Barak: MV 5.99 ± 0.78; FV 6.15 + 1.04\n", + "Saponara: MV 6.06 ± 0.76; FV 6.27 + 1.14\n", + "Mandragora: MV 6.14 ± 1.01; FV 6.59 + 1.81\n", + "Weah: MV 5.88 ± 0.57; FV 5.90 + 0.63\n", + "Bennacer: MV 6.21 ± 0.89; FV 6.60 + 1.58\n", + "Duda: MV 6.22 ± 1.00; FV 6.71 + 1.91\n", + "Castrovilli: MV 6.20 ± 1.08; FV 6.79 + 2.13\n", + "Mckennie: MV 6.13 ± 0.78; FV 6.34 + 1.11\n", + "Miranchuk: MV 6.17 ± 0.91; FV 6.52 + 1.57\n", + "Matheus Henrique: MV 6.03 ± 0.88; FV 6.23 + 1.28\n", + "De Ketelaere: MV 6.06 ± 1.01; FV 6.40 + 1.61\n", + "Mboula: MV 5.90 ± 0.76; FV 5.88 + 0.86\n", + "Paredes: MV 5.85 ± 0.99; FV 5.87 + 1.21\n", + "Sottil: MV 6.01 ± 0.63; FV 6.10 + 0.74\n", + "Klaassen: MV 6.21 ± 0.86; FV 6.60 + 1.54\n", + "Arthur Melo: MV 6.11 ± 0.76; FV 6.21 + 0.86\n", + "Thorsby: MV 6.16 ± 0.95; FV 6.64 + 1.82\n", + "Nandez: MV 5.94 ± 0.81; FV 6.09 + 1.12\n", + "Tameze: MV 5.93 ± 0.57; FV 5.91 + 0.52\n", + "Marin: MV 5.94 ± 0.67; FV 5.96 + 0.77\n", + "Messias: MV 6.18 ± 0.89; FV 6.65 + 1.79\n", + "Musah: MV 6.03 ± 0.70; FV 6.07 + 0.82\n", + "Coulibaly L.: MV 5.82 ± 0.93; FV 5.96 + 1.27\n", + "Krunic: MV 5.98 ± 0.74; FV 5.99 + 0.81\n", + "Cataldi: MV 5.89 ± 0.84; FV 5.85 + 0.97\n", + "Strootman: MV 6.04 ± 0.61; FV 6.14 + 0.75\n", + "Duncan: MV 6.25 ± 0.86; FV 6.68 + 1.62\n", + "Freuler: MV 6.00 ± 0.49; FV 6.03 + 0.50\n", + "Gagliardini: MV 6.15 ± 0.92; FV 6.53 + 1.69\n", + "Mazzitelli: MV 6.14 ± 1.39; FV 6.65 + 2.59\n", + "Jankto: MV 5.79 ± 0.80; FV 5.81 + 0.91\n", + "Kastanos: MV 5.86 ± 0.55; FV 5.96 + 0.72\n", + "Gyasi: MV 5.68 ± 0.77; FV 5.66 + 0.84\n", + "Reinier: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Zalewski: MV 5.89 ± 0.68; FV 5.99 + 0.83\n", + "Harroui: MV 6.18 ± 1.07; FV 6.67 + 1.92\n", + "Frendrup: MV 6.10 ± 0.61; FV 6.24 + 0.73\n", + "Blin: MV 5.92 ± 0.57; FV 5.92 + 0.62\n", + "Fabbian: MV 6.14 ± 0.75; FV 6.54 + 1.52\n", + "Ramadani: MV 6.05 ± 0.87; FV 6.17 + 1.12\n", + "Cajuste : MV 5.95 ± 0.89; FV 5.99 + 1.12\n", + "Mancosu: MV 5.68 ± 1.15; FV 5.69 + 1.31\n", + "Vecino: MV 5.86 ± 1.02; FV 6.02 + 1.39\n", + "Sensi: MV 6.19 ± 0.87; FV 6.59 + 1.47\n", + "Walace: MV 5.82 ± 0.75; FV 5.74 + 0.84\n", + "Lopez M.: MV 5.97 ± 0.76; FV 5.96 + 0.77\n", + "Brescianini: MV 5.93 ± 0.88; FV 5.89 + 1.04\n", + "Bove: MV 5.91 ± 0.87; FV 6.13 + 1.27\n", + "Aebischer: MV 6.05 ± 0.53; FV 6.14 + 0.60\n", + "Thorstvedt: MV 5.95 ± 0.66; FV 5.97 + 0.70\n", + "Gonzalez J.: MV 5.82 ± 0.83; FV 5.89 + 1.10\n", + "Moro N.: MV 6.14 ± 0.62; FV 6.31 + 0.83\n", + "Oudin: MV 5.97 ± 1.02; FV 6.30 + 1.61\n", + "Boloca: MV 6.04 ± 0.96; FV 6.12 + 1.20\n", + "Rafia: MV 5.80 ± 0.76; FV 5.94 + 1.05\n", + "Makoumbou: MV 5.71 ± 0.75; FV 5.77 + 0.86\n", + "Kaba: MV 5.78 ± 0.85; FV 5.66 + 0.95\n", + "Badelj: MV 5.96 ± 0.73; FV 5.96 + 0.72\n", + "Machin: MV 5.91 ± 0.87; FV 5.96 + 1.22\n", + "Linetty: MV 5.94 ± 0.62; FV 5.94 + 0.63\n", + "Castillejo: MV 5.99 ± 0.66; FV 6.12 + 0.91\n", + "Rovella: MV 5.97 ± 1.04; FV 6.06 + 1.32\n", + "Pobega: MV 5.94 ± 0.52; FV 5.97 + 0.57\n", + "Hongla: MV 5.90 ± 0.62; FV 5.88 + 0.62\n", + "Miretti: MV 5.77 ± 0.72; FV 5.79 + 0.83\n", + "Fazzini: MV 5.81 ± 0.63; FV 5.76 + 0.60\n", + "Iling Junior: MV 5.78 ± 1.06; FV 5.85 + 1.32\n", + "Oristanio: MV 5.71 ± 0.80; FV 5.71 + 0.85\n", + "Serdar: MV 5.91 ± 0.65; FV 5.89 + 0.69\n", + "Payero: MV 5.88 ± 0.75; FV 5.84 + 0.89\n", + "Grassi: MV 5.86 ± 0.70; FV 5.81 + 0.67\n", + "Baez: MV 5.86 ± 0.79; FV 5.88 + 0.92\n", + "Deiola: MV 5.52 ± 0.97; FV 5.49 + 0.90\n", + "Garritano: MV 6.09 ± 0.99; FV 6.20 + 1.30\n", + "Bourabia: MV 5.95 ± 0.95; FV 6.07 + 1.27\n", + "Saelemaekers: MV 6.09 ± 0.70; FV 6.31 + 1.08\n", + "Maldini: MV 5.96 ± 0.74; FV 6.15 + 1.06\n", + "Racic: MV 5.95 ± 0.69; FV 5.95 + 0.70\n", + "Kovalenko: MV 5.90 ± 0.68; FV 5.86 + 0.67\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Maleh: MV 5.56 ± 0.55; FV 5.41 + 0.57\n", - "Bohinen: MV 5.91 ± 0.58; FV 5.86 + 0.56\n", - "Ranocchia F.: MV 5.67 ± 0.66; FV 5.72 + 0.80\n", - "Folorunsho: MV 5.85 ± 0.93; FV 6.10 + 1.37\n", - "Infantino: MV 5.90 ± 0.53; FV 5.87 + 0.48\n", - "Martegani: MV 5.93 ± 0.95; FV 6.00 + 1.20\n", - "Kutlu: MV 5.86 ± 0.74; FV 5.83 + 0.82\n", - "Tchatchoua: MV 5.76 ± 0.97; FV 5.85 + 1.27\n", - "Quina: MV 5.99 ± 0.94; FV 6.06 + 1.20\n", - "Adopo: MV 5.97 ± 0.78; FV 6.00 + 0.81\n", - "Romero L.: MV 6.25 ± 0.88; FV 6.65 + 1.63\n", - "Basic: MV 6.04 ± 0.74; FV 6.14 + 1.01\n", - "Asllani: MV 6.10 ± 0.56; FV 6.15 + 0.54\n", - "Tchaouna: MV 5.86 ± 0.82; FV 5.87 + 1.00\n", - "Sulemana I.: MV 5.65 ± 0.72; FV 5.59 + 0.74\n", - "Barrenechea: MV 6.04 ± 0.76; FV 6.10 + 0.88\n", - "Gelli: MV 6.05 ± 0.86; FV 6.18 + 1.07\n", - "Suslov: MV 5.78 ± 0.89; FV 5.85 + 1.15\n", - "Gaetano: MV 6.04 ± 0.99; FV 6.54 + 1.83\n", - "Jagiello: MV 5.87 ± 0.84; FV 5.86 + 0.96\n", - "Obiang: MV 5.86 ± 0.55; FV 5.83 + 0.55\n", - "Maggiore: MV 5.89 ± 0.53; FV 5.85 + 0.53\n", - "Akpa Akpro: MV 5.95 ± 0.88; FV 6.06 + 1.20\n", - "Urbanski: MV 5.91 ± 0.78; FV 6.00 + 1.01\n", - "Volpato: MV 5.82 ± 0.72; FV 5.90 + 0.90\n", - "Vignato S.: MV 5.87 ± 0.79; FV 5.90 + 0.94\n", - "Hrustic: MV 5.54 ± 0.69; FV 5.57 + 0.74\n", - "Zarraga: MV 5.47 ± 0.98; FV 5.45 + 0.91\n", - "Camara E.: MV 5.79 ± 1.08; FV 5.80 + 1.39\n", - "Amatucci: MV 5.93 ± 0.66; FV 5.92 + 0.64\n", - "Pagano: MV 5.95 ± 0.62; FV 5.95 + 0.60\n", - "Prati: MV 5.70 ± 0.90; FV 5.69 + 1.03\n", - "Viola: MV 5.62 ± 0.79; FV 5.53 + 0.76\n", - "Lulic K.: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Rog: MV 5.71 ± 0.79; FV 5.69 + 0.85\n", - "Nicolussi Caviglia: MV 5.90 ± 0.88; FV 6.26 + 1.47\n", - "Demme: MV 5.98 ± 0.48; FV 5.93 + 0.39\n", - "Pafundi: MV 6.00 ± 0.80; FV 6.02 + 0.86\n", - "Adli: MV 5.98 ± 0.69; FV 6.02 + 0.72\n", - "Bondo: MV 5.95 ± 0.84; FV 6.06 + 1.11\n", - "Zerbin: MV 6.04 ± 0.61; FV 6.09 + 0.64\n", - "Carboni V.: MV 6.00 ± 0.78; FV 6.09 + 1.00\n", - "Faticanti: MV 6.03 ± 0.86; FV 6.14 + 1.14\n", - "Gineitis: MV 5.91 ± 0.92; FV 5.91 + 1.14\n", - "Belardinelli: MV 5.53 ± 0.86; FV 5.50 + 0.92\n", - "El Azzouzi: MV 5.93 ± 0.69; FV 6.02 + 0.87\n", - "Lipani: MV 5.76 ± 0.82; FV 5.81 + 1.02\n", - "Joselito: MV 5.76 ± 0.97; FV 5.85 + 1.27\n", - "Legowski: MV 5.96 ± 1.03; FV 6.12 + 1.39\n", - "Ibrahimovic A.: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Osimhen: MV 6.47 ± 1.55; FV 7.89 + 4.08\n", - "Martinez L.: MV 6.56 ± 1.27; FV 7.97 + 3.97\n", - "Rafael Leao: MV 6.50 ± 1.19; FV 7.58 + 3.28\n", - "Lukaku: MV 6.26 ± 1.46; FV 7.29 + 3.16\n", - "Berardi: MV 6.32 ± 1.38; FV 7.38 + 3.38\n", - "Immobile: MV 6.17 ± 1.35; FV 7.10 + 3.02\n", - "Vlahovic: MV 6.41 ± 1.47; FV 7.70 + 3.82\n", - "Dybala: MV 6.41 ± 1.49; FV 7.69 + 3.78\n", - "Kvaratskhelia: MV 6.42 ± 1.25; FV 7.47 + 3.19\n", - "Giroud: MV 6.46 ± 1.20; FV 7.54 + 3.25\n", - "Scamacca: MV 6.36 ± 1.30; FV 7.60 + 3.52\n", - "Thuram: MV 6.59 ± 1.03; FV 7.50 + 3.06\n", - "Lookman: MV 6.42 ± 1.29; FV 7.62 + 3.49\n", - "Dia: MV 6.30 ± 1.40; FV 7.39 + 3.41\n", - "Arnautovic: MV 6.52 ± 1.09; FV 7.49 + 3.08\n", - "Retegui: MV 5.91 ± 1.23; FV 6.42 + 1.94\n", - "Sanabria: MV 6.17 ± 1.33; FV 7.01 + 2.74\n", - "Nzola: MV 5.95 ± 1.18; FV 6.51 + 2.00\n", - "Lauriente': MV 6.08 ± 1.18; FV 6.56 + 2.17\n", - "Zapata D.: MV 5.97 ± 0.99; FV 6.36 + 1.60\n", - "Chiesa: MV 6.46 ± 1.19; FV 7.51 + 3.21\n", - "Milik: MV 6.31 ± 1.09; FV 7.06 + 2.53\n", - "Gonzalez N.: MV 6.23 ± 1.09; FV 7.02 + 2.56\n", - "Okafor: MV 6.01 ± 0.51; FV 6.00 + 0.49\n", - "Pinamonti: MV 5.83 ± 1.08; FV 6.21 + 1.68\n", - "Beltran L.: MV 6.04 ± 0.96; FV 6.51 + 1.76\n", - "Caprari: MV 6.04 ± 1.00; FV 6.50 + 1.79\n", - "Sanchez: MV 6.45 ± 0.96; FV 7.08 + 2.32\n", - "Caputo: MV 5.53 ± 0.73; FV 5.57 + 0.78\n", - "Toure' E.: MV 6.05 ± 0.74; FV 6.17 + 0.94\n", - "Krstovic: MV 6.38 ± 0.87; FV 6.82 + 1.82\n", - "Belotti: MV 6.10 ± 0.99; FV 6.62 + 1.91\n", - "Muriel: MV 6.18 ± 0.82; FV 6.47 + 1.38\n", - "Lapadula: MV 5.86 ± 0.93; FV 6.18 + 1.49\n", - "Jovic: MV 6.09 ± 1.18; FV 6.80 + 2.40\n", - "Abraham: MV 6.11 ± 1.24; FV 6.87 + 2.48\n", - "Zirkzee: MV 6.21 ± 1.02; FV 6.73 + 2.01\n", - "Ngonge: MV 5.98 ± 1.16; FV 6.53 + 2.01\n", - "Petagna: MV 5.88 ± 0.98; FV 6.21 + 1.53\n", - "Simeone: MV 5.84 ± 0.92; FV 6.24 + 1.42\n", - "Deulofeu: MV 6.35 ± 1.27; FV 7.35 + 3.17\n", - "Pedro: MV 6.05 ± 0.93; FV 6.42 + 1.61\n", - "Shomurodov: MV 5.70 ± 0.75; FV 5.88 + 1.01\n", - "Azmoun: MV 5.89 ± 0.82; FV 6.19 + 1.27\n", - "Castellanos: MV 5.96 ± 0.56; FV 5.95 + 0.57\n", - "Cheddira: MV 6.28 ± 1.16; FV 7.20 + 2.82\n", - "Karlsson: MV 6.12 ± 0.90; FV 6.47 + 1.58\n", - "Brekalo: MV 6.05 ± 1.02; FV 6.57 + 1.89\n", - "Cambiaghi: MV 5.69 ± 0.88; FV 5.81 + 1.11\n", - "Henry: MV 5.81 ± 0.97; FV 6.12 + 1.42\n", - "Mulattieri: MV 5.79 ± 0.61; FV 5.94 + 0.90\n", - "Almqvist: MV 6.21 ± 1.07; FV 6.75 + 2.05\n", - "Isaksen: MV 5.93 ± 0.76; FV 5.96 + 0.90\n", - "Kean: MV 6.03 ± 1.25; FV 6.69 + 2.43\n", - "Karamoh: MV 5.98 ± 0.84; FV 6.26 + 1.35\n", - "Thauvin: MV 5.60 ± 0.81; FV 5.73 + 0.89\n", - "Kouame': MV 6.04 ± 1.10; FV 6.67 + 2.17\n", - "Raspadori: MV 5.94 ± 0.98; FV 6.34 + 1.57\n", - "Colombo: MV 5.96 ± 1.16; FV 6.50 + 2.05\n", - "Luvumbo: MV 5.89 ± 0.74; FV 6.00 + 1.00\n", - "Mota: MV 5.89 ± 1.13; FV 6.33 + 1.83\n", - "Brenner: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Bonazzoli: MV 5.90 ± 0.98; FV 6.27 + 1.53\n", - "Djuric: MV 5.85 ± 0.74; FV 6.03 + 1.04\n", - "Davis K.: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Banda: MV 6.19 ± 0.86; FV 6.48 + 1.47\n", - "Defrel: MV 5.68 ± 0.68; FV 5.73 + 0.86\n", - "Sansone: MV 6.34 ± 1.14; FV 7.16 + 2.70\n", - "Pellegri: MV 5.71 ± 0.85; FV 5.89 + 1.07\n", - "Piccoli: MV 5.99 ± 0.81; FV 6.29 + 1.37\n", - "Success: MV 5.80 ± 0.92; FV 6.09 + 1.26\n", - "Botheim: MV 5.78 ± 0.75; FV 5.89 + 1.01\n", - "Lucca: MV 5.79 ± 0.95; FV 5.97 + 1.23\n", - "Caso: MV 6.26 ± 1.01; FV 6.82 + 2.03\n", - "Jovane: MV 5.96 ± 1.03; FV 6.15 + 1.41\n", - "Soule': MV 6.35 ± 0.87; FV 6.71 + 1.61\n", - "Pavoletti: MV 5.71 ± 0.72; FV 5.79 + 0.92\n", - "Cancellieri: MV 5.53 ± 0.62; FV 5.44 + 0.60\n", - "Seck: MV 6.14 ± 0.72; FV 6.29 + 1.00\n", - "Alvarez A.: MV 5.81 ± 0.68; FV 5.90 + 0.87\n", - "Cuni: MV 6.04 ± 0.63; FV 6.08 + 0.69\n", - "Ekuban: MV 5.79 ± 0.65; FV 5.90 + 0.78\n", - "Maric: MV 5.96 ± 0.72; FV 6.01 + 0.89\n", - "Cruz: MV 5.75 ± 0.96; FV 5.86 + 1.25\n", - "Destro: MV 5.50 ± 0.81; FV 5.47 + 0.82\n", - "Van Hooijdonk: MV 5.91 ± 0.92; FV 6.07 + 1.25\n", - "Ceide: MV 5.70 ± 0.72; FV 5.72 + 0.73\n", - "Kvernadze: MV 6.01 ± 0.81; FV 6.11 + 0.98\n", - "Ikwuemesi: MV 5.87 ± 0.85; FV 5.92 + 1.03\n", - "Puscas: MV 5.85 ± 0.85; FV 5.89 + 1.01\n", - "Ake' M.: MV 5.77 ± 1.02; FV 5.75 + 1.22\n", - "Braaf: MV 5.61 ± 0.69; FV 5.75 + 0.86\n", - "Kallon: MV 5.85 ± 0.86; FV 6.11 + 1.32\n", - "Kaio Jorge: MV 6.01 ± 0.61; FV 6.08 + 0.63\n", - "Vivaldo: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Bidaoui: MV 6.05 ± 0.89; FV 6.26 + 1.21\n", - "Shpendi S.: MV 5.53 ± 0.73; FV 5.47 + 0.75\n", - "Burnete: MV 6.05 ± 0.80; FV 6.14 + 1.05\n", - "Corfitzen: MV 6.04 ± 0.89; FV 6.21 + 1.25\n", - "Stewart: MV 5.96 ± 1.03; FV 6.15 + 1.41\n", - "Yildiz: MV 6.10 ± 0.87; FV 6.37 + 1.41\n" + "Maleh: MV 5.74 ± 0.91; FV 5.69 + 1.07\n", + "Bohinen: MV 5.82 ± 0.55; FV 5.77 + 0.56\n", + "Ranocchia F.: MV 5.99 ± 0.67; FV 6.13 + 0.84\n", + "Folorunsho: MV 5.83 ± 0.91; FV 6.06 + 1.31\n", + "Infantino: MV 6.00 ± 0.81; FV 6.03 + 0.89\n", + "Martegani: MV 5.90 ± 0.74; FV 5.94 + 0.97\n", + "Kutlu: MV 6.03 ± 0.80; FV 6.04 + 0.79\n", + "Tchatchoua: MV 5.93 ± 0.87; FV 5.95 + 1.06\n", + "Quina: MV 6.02 ± 0.81; FV 6.15 + 1.14\n", + "Adopo: MV 5.91 ± 1.10; FV 6.04 + 1.39\n", + "Romero L.: MV 6.01 ± 0.82; FV 6.12 + 1.06\n", + "Basic: MV 5.90 ± 0.79; FV 6.02 + 1.01\n", + "Asllani: MV 6.14 ± 0.76; FV 6.28 + 0.88\n", + "Tchaouna: MV 5.70 ± 0.76; FV 5.67 + 0.88\n", + "Sulemana I.: MV 5.58 ± 0.86; FV 5.56 + 0.86\n", + "Barrenechea: MV 5.92 ± 0.91; FV 5.87 + 1.10\n", + "Gelli: MV 5.88 ± 1.19; FV 5.89 + 1.46\n", + "Suslov: MV 5.92 ± 0.65; FV 5.91 + 0.72\n", + "Gaetano: MV 5.95 ± 0.89; FV 6.31 + 1.46\n", + "Jagiello: MV 6.04 ± 0.82; FV 6.08 + 0.86\n", + "Obiang: MV 5.91 ± 0.57; FV 5.88 + 0.53\n", + "Maggiore: MV 5.83 ± 0.55; FV 5.80 + 0.64\n", + "Akpa Akpro: MV 5.91 ± 0.87; FV 5.96 + 1.22\n", + "Urbanski: MV 6.04 ± 0.67; FV 6.11 + 0.86\n", + "Volpato: MV 6.02 ± 0.87; FV 6.16 + 1.23\n", + "Vignato S.: MV 5.77 ± 0.84; FV 5.70 + 1.01\n", + "Hrustic: MV 5.70 ± 0.60; FV 5.64 + 0.57\n", + "Zarraga: MV 5.80 ± 0.83; FV 5.76 + 1.02\n", + "Camara E.: MV 5.90 ± 0.94; FV 6.02 + 1.34\n", + "Amatucci: MV 6.03 ± 0.87; FV 6.10 + 1.04\n", + "Pagano: MV 6.13 ± 0.81; FV 6.31 + 1.13\n", + "Prati: MV 5.71 ± 1.14; FV 5.72 + 1.33\n", + "Viola: MV 5.70 ± 1.01; FV 5.69 + 1.14\n", + "Lulic K.: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Rog: MV 5.67 ± 0.96; FV 5.71 + 1.02\n", + "Nicolussi Caviglia: MV 5.70 ± 1.11; FV 5.73 + 1.27\n", + "Demme: MV 5.96 ± 0.51; FV 5.95 + 0.46\n", + "Pafundi: MV 5.98 ± 0.84; FV 6.02 + 1.01\n", + "Adli: MV 5.91 ± 0.85; FV 5.92 + 0.97\n", + "Bondo: MV 5.94 ± 0.84; FV 6.00 + 1.15\n", + "Zerbin: MV 5.90 ± 0.72; FV 5.88 + 0.86\n", + "Carboni V.: MV 5.81 ± 0.91; FV 5.83 + 1.20\n", + "Faticanti: MV 5.79 ± 1.02; FV 5.88 + 1.31\n", + "Gineitis: MV 5.99 ± 0.74; FV 6.03 + 0.82\n", + "Belardinelli: MV 5.91 ± 0.77; FV 5.89 + 0.85\n", + "El Azzouzi: MV 5.99 ± 0.58; FV 6.00 + 0.58\n", + "Lipani: MV 5.97 ± 0.86; FV 6.01 + 1.02\n", + "Joselito: MV 5.93 ± 0.87; FV 5.95 + 1.06\n", + "Legowski: MV 5.78 ± 0.90; FV 5.84 + 1.18\n", + "Ibrahimovic A.: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Osimhen: MV 6.44 ± 1.56; FV 7.80 + 3.97\n", + "Martinez L.: MV 6.51 ± 1.37; FV 8.00 + 4.04\n", + "Rafael Leao: MV 6.49 ± 1.25; FV 7.59 + 3.28\n", + "Lukaku: MV 6.32 ± 1.49; FV 7.50 + 3.55\n", + "Berardi: MV 6.49 ± 1.33; FV 7.84 + 3.77\n", + "Immobile: MV 5.99 ± 1.26; FV 6.62 + 2.25\n", + "Vlahovic: MV 6.16 ± 1.45; FV 7.09 + 3.05\n", + "Dybala: MV 6.36 ± 1.47; FV 7.58 + 3.67\n", + "Kvaratskhelia: MV 6.35 ± 1.22; FV 7.31 + 3.03\n", + "Giroud: MV 6.42 ± 1.30; FV 7.65 + 3.55\n", + "Scamacca: MV 6.24 ± 1.39; FV 7.22 + 3.16\n", + "Thuram: MV 6.47 ± 1.15; FV 7.46 + 3.04\n", + "Lookman: MV 6.30 ± 1.33; FV 7.32 + 3.20\n", + "Dia: MV 6.00 ± 1.33; FV 6.77 + 2.48\n", + "Arnautovic: MV 6.33 ± 1.03; FV 6.97 + 2.21\n", + "Retegui: MV 6.27 ± 1.30; FV 7.36 + 3.29\n", + "Sanabria: MV 6.13 ± 1.02; FV 6.79 + 2.22\n", + "Nzola: MV 6.01 ± 1.21; FV 6.72 + 2.36\n", + "Lauriente': MV 6.32 ± 1.20; FV 7.21 + 2.87\n", + "Zapata D.: MV 6.09 ± 0.71; FV 6.32 + 1.10\n", + "Chiesa: MV 6.33 ± 1.15; FV 7.13 + 2.66\n", + "Milik: MV 6.11 ± 0.93; FV 6.50 + 1.62\n", + "Gonzalez N.: MV 6.44 ± 1.19; FV 7.48 + 3.14\n", + "Okafor: MV 6.19 ± 0.96; FV 6.67 + 1.89\n", + "Pinamonti: MV 6.02 ± 1.22; FV 6.70 + 2.41\n", + "Beltran L.: MV 6.10 ± 0.84; FV 6.47 + 1.48\n", + "Caprari: MV 6.05 ± 1.02; FV 6.47 + 1.82\n", + "Sanchez: MV 6.21 ± 0.92; FV 6.70 + 1.82\n", + "Caputo: MV 5.74 ± 0.87; FV 6.02 + 1.25\n", + "Toure' E.: MV 5.92 ± 1.01; FV 6.07 + 1.34\n", + "Krstovic: MV 6.21 ± 1.11; FV 6.79 + 2.22\n", + "Belotti: MV 6.10 ± 1.04; FV 6.68 + 2.07\n", + "Muriel: MV 6.15 ± 0.89; FV 6.48 + 1.59\n", + "Lapadula: MV 5.92 ± 1.14; FV 6.44 + 1.87\n", + "Jovic: MV 6.09 ± 1.20; FV 6.76 + 2.37\n", + "Abraham: MV 6.17 ± 1.16; FV 6.98 + 2.61\n", + "Zirkzee: MV 6.37 ± 0.85; FV 6.87 + 1.87\n", + "Ngonge: MV 5.90 ± 1.11; FV 6.36 + 1.76\n", + "Petagna: MV 5.82 ± 1.09; FV 6.18 + 1.51\n", + "Simeone: MV 5.99 ± 1.11; FV 6.50 + 1.90\n", + "Deulofeu: MV 6.34 ± 1.23; FV 7.32 + 3.08\n", + "Pedro: MV 5.96 ± 0.98; FV 6.26 + 1.48\n", + "Shomurodov: MV 5.52 ± 0.78; FV 5.56 + 0.71\n", + "Azmoun: MV 5.97 ± 0.74; FV 6.24 + 1.23\n", + "Castellanos: MV 6.00 ± 0.78; FV 6.06 + 0.96\n", + "Cheddira: MV 6.14 ± 1.38; FV 6.99 + 2.78\n", + "Karlsson: MV 6.19 ± 0.76; FV 6.61 + 1.60\n", + "Brekalo: MV 6.22 ± 1.04; FV 6.83 + 2.14\n", + "Cambiaghi: MV 5.91 ± 0.86; FV 6.10 + 1.18\n", + "Henry: MV 5.84 ± 0.89; FV 6.12 + 1.34\n", + "Mulattieri: MV 6.01 ± 0.72; FV 6.32 + 1.33\n", + "Almqvist: MV 6.11 ± 1.13; FV 6.61 + 2.01\n", + "Isaksen: MV 5.75 ± 1.07; FV 5.79 + 1.28\n", + "Kean: MV 5.84 ± 1.09; FV 6.19 + 1.70\n", + "Karamoh: MV 6.09 ± 0.63; FV 6.26 + 0.87\n", + "Thauvin: MV 5.71 ± 0.70; FV 5.85 + 0.96\n", + "Kouame': MV 6.23 ± 1.19; FV 7.12 + 2.84\n", + "Raspadori: MV 5.94 ± 0.94; FV 6.30 + 1.53\n", + "Colombo: MV 5.88 ± 1.03; FV 6.31 + 1.72\n", + "Luvumbo: MV 5.85 ± 0.80; FV 6.08 + 1.13\n", + "Mota: MV 5.87 ± 0.99; FV 6.23 + 1.59\n", + "Brenner: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Bonazzoli: MV 5.91 ± 0.90; FV 6.24 + 1.40\n", + "Djuric: MV 5.99 ± 0.51; FV 6.06 + 0.59\n", + "Davis K.: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Banda: MV 5.97 ± 0.92; FV 6.25 + 1.39\n", + "Defrel: MV 5.76 ± 0.82; FV 5.94 + 1.11\n", + "Sansone: MV 6.03 ± 0.97; FV 6.41 + 1.61\n", + "Pellegri: MV 5.95 ± 0.61; FV 5.98 + 0.66\n", + "Piccoli: MV 5.84 ± 0.78; FV 5.85 + 0.90\n", + "Success: MV 5.91 ± 0.81; FV 6.16 + 1.28\n", + "Botheim: MV 5.57 ± 0.65; FV 5.57 + 0.64\n", + "Lucca: MV 5.76 ± 0.88; FV 6.01 + 1.34\n", + "Caso: MV 6.13 ± 1.03; FV 6.64 + 1.94\n", + "Jovane: MV 5.76 ± 0.91; FV 5.84 + 1.16\n", + "Soule': MV 6.27 ± 0.98; FV 6.72 + 1.76\n", + "Pavoletti: MV 5.70 ± 0.85; FV 5.93 + 1.10\n", + "Cancellieri: MV 5.77 ± 0.88; FV 5.86 + 1.11\n", + "Seck: MV 6.10 ± 0.60; FV 6.21 + 0.66\n", + "Alvarez A.: MV 5.95 ± 0.78; FV 6.16 + 1.10\n", + "Cuni: MV 5.73 ± 1.02; FV 5.67 + 1.17\n", + "Ekuban: MV 6.02 ± 0.54; FV 6.10 + 0.58\n", + "Maric: MV 5.96 ± 0.51; FV 5.97 + 0.58\n", + "Cruz: MV 5.93 ± 0.87; FV 5.99 + 1.08\n", + "Destro: MV 5.66 ± 0.79; FV 5.68 + 0.88\n", + "Van Hooijdonk: MV 6.13 ± 0.64; FV 6.25 + 0.84\n", + "Ceide: MV 5.86 ± 0.72; FV 5.86 + 0.68\n", + "Kvernadze: MV 5.74 ± 1.15; FV 5.69 + 1.39\n", + "Ikwuemesi: MV 5.65 ± 0.72; FV 5.60 + 0.74\n", + "Puscas: MV 6.04 ± 0.77; FV 6.11 + 0.86\n", + "Ake' M.: MV 5.94 ± 0.75; FV 5.96 + 0.95\n", + "Braaf: MV 5.67 ± 0.68; FV 5.73 + 0.74\n", + "Kallon: MV 5.86 ± 0.78; FV 6.04 + 1.05\n", + "Kaio Jorge: MV 5.92 ± 0.64; FV 5.99 + 0.74\n", + "Vivaldo: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Bidaoui: MV 5.84 ± 1.17; FV 5.86 + 1.45\n", + "Shpendi S.: MV 5.91 ± 0.53; FV 5.90 + 0.53\n", + "Burnete: MV 5.81 ± 1.00; FV 5.93 + 1.35\n", + "Corfitzen: MV 5.79 ± 1.02; FV 5.90 + 1.33\n", + "Stewart: MV 5.76 ± 0.91; FV 5.84 + 1.16\n", + "Yildiz: MV 5.78 ± 1.06; FV 5.88 + 1.32\n" ] }, { @@ -6737,113 +6739,113 @@ " \n", " \n", " \n", - " Musso\n", - " P\n", - " Atalanta\n", - " Cagliari\n", - " 1\n", - " 1.0\n", - " 70\n", - " 6.187904\n", - " 0.409565\n", - " 5.778299\n", - " 0.631974\n", - " 6.172151\n", - " 0.484012\n", - " 0.024084\n", - " 1.080489\n", - " 6.551383\n", - " 0.575009\n", - " -0.854511\n", - " 1.143475\n", - " 76.430595\n", - " \n", - " \n", " Carnesecchi\n", " P\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", " 0.0\n", " 5\n", - " 6.153384\n", - " 0.442585\n", - " 5.099182\n", - " 0.736154\n", - " 6.095662\n", - " 0.508426\n", - " 0.083887\n", - " 1.071720\n", - " 5.316064\n", - " 1.103085\n", - " -0.144701\n", - " 0.998809\n", - " 24.471429\n", + " 6.140590\n", + " 0.481707\n", + " 5.070139\n", + " 0.715923\n", + " 5.980216\n", + " 0.509892\n", + " 0.230396\n", + " 1.086084\n", + " 5.321455\n", + " 1.055452\n", + " -0.174796\n", + " 0.965320\n", + " 20.727640\n", + " \n", + " \n", + " Musso\n", + " P\n", + " Atalanta\n", + " Juventus\n", + " 1\n", + " 1.0\n", + " 70\n", + " 6.171150\n", + " 0.480294\n", + " 5.038867\n", + " 0.684976\n", + " 5.986030\n", + " 0.494852\n", + " 0.272883\n", + " 1.084060\n", + " 5.255883\n", + " 1.019420\n", + " -0.156479\n", + " 0.983446\n", + " 28.833491\n", " \n", " \n", " Rossi F.\n", " P\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", " 0.0\n", " 1\n", - " 6.202195\n", - " 0.436560\n", - " 5.098540\n", - " 0.738788\n", - " 6.170873\n", - " 0.510068\n", - " 0.045397\n", - " 1.057536\n", - " 5.311903\n", - " 1.107865\n", - " -0.141756\n", - " 0.997465\n", - " 19.948235\n", + " 6.170296\n", + " 0.480470\n", + " 5.037872\n", + " 0.684438\n", + " 5.984473\n", + " 0.494652\n", + " 0.273999\n", + " 1.084374\n", + " 5.254371\n", + " 1.018776\n", + " -0.156209\n", + " 0.983780\n", + " 28.943959\n", " \n", " \n", " Zappacosta\n", " D\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", - " 0.6\n", - " 60\n", - " 6.174058\n", - " 0.452587\n", - " 6.519552\n", - " 0.775398\n", - " 6.110474\n", - " 0.514245\n", - " 0.090884\n", - " 0.896925\n", - " 5.874933\n", - " 0.976198\n", - " 0.463032\n", - " 1.299677\n", + " 1.0\n", + " 90\n", + " 5.985259\n", + " 0.522062\n", + " 6.206951\n", + " 0.733274\n", + " 6.001576\n", + " 0.613546\n", + " -0.019559\n", + " 0.881605\n", + " 5.760596\n", + " 1.050439\n", + " 0.307981\n", + " 1.299815\n", " 0.000000\n", " \n", " \n", - " Zortea\n", + " Toloi\n", " D\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", - " 0.4\n", - " 40\n", - " 6.106819\n", - " 0.397738\n", - " 6.403875\n", - " 0.627450\n", - " 6.025298\n", - " 0.444725\n", - " 0.134716\n", - " 0.941082\n", - " 5.877332\n", - " 0.785433\n", - " 0.469323\n", - " 1.299658\n", + " 1.0\n", + " 90\n", + " 6.002894\n", + " 0.499877\n", + " 6.196084\n", + " 0.699952\n", + " 6.035264\n", + " 0.591494\n", + " -0.040256\n", + " 0.892304\n", + " 5.804792\n", + " 1.025037\n", + " 0.278035\n", + " 1.299814\n", " 0.000000\n", " \n", " \n", @@ -6872,110 +6874,110 @@ " Henry\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", - " 0.0\n", - " 0\n", - " 5.806732\n", - " 0.484893\n", - " 6.124626\n", - " 0.710677\n", - " 5.555864\n", - " 0.490855\n", - " 0.369405\n", - " 0.852631\n", - " 5.422048\n", - " 0.779401\n", - " 0.606238\n", - " 1.299682\n", - " 0.000000\n", - " \n", - " \n", - " Kallon\n", - " A\n", - " Verona\n", - " Milan\n", - " 0\n", - " 0.0\n", - " 0\n", - " 5.847151\n", - " 0.430028\n", - " 6.110572\n", - " 0.658053\n", - " 5.650604\n", - " 0.441275\n", - " 0.323210\n", - " 0.904855\n", - " 5.475328\n", - " 0.739265\n", - " 0.582358\n", - " 1.299658\n", + " 0.4\n", + " 60\n", + " 5.839920\n", + " 0.444240\n", + " 6.116677\n", + " 0.669289\n", + " 5.631952\n", + " 0.453545\n", + " 0.332464\n", + " 0.906913\n", + " 5.474079\n", + " 0.755754\n", + " 0.577176\n", + " 1.299852\n", " 0.000000\n", " \n", " \n", " Djuric\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", - " 0.4\n", - " 60\n", - " 5.847715\n", - " 0.371962\n", - " 6.031966\n", - " 0.518109\n", - " 5.712709\n", - " 0.393430\n", - " 0.250597\n", - " 0.961439\n", - " 5.599852\n", - " 0.651016\n", - " 0.465176\n", - " 1.299629\n", + " 0.0\n", + " 0\n", + " 5.988754\n", + " 0.256611\n", + " 6.065000\n", + " 0.293257\n", + " 6.035156\n", + " 0.320372\n", + " -0.107045\n", + " 1.115607\n", + " 5.977599\n", + " 0.469125\n", + " 0.137929\n", + " 1.299758\n", + " 0.000000\n", + " \n", + " \n", + " Kallon\n", + " A\n", + " Verona\n", + " Torino\n", + " 0\n", + " 0.0\n", + " 0\n", + " 5.863674\n", + " 0.392202\n", + " 6.044829\n", + " 0.522801\n", + " 5.719528\n", + " 0.414042\n", + " 0.254175\n", + " 0.962003\n", + " 5.592772\n", + " 0.641898\n", + " 0.490306\n", + " 1.299833\n", " 0.000000\n", " \n", " \n", " Cruz\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", " 0.0\n", " 15\n", - " 5.751310\n", - " 0.481451\n", - " 5.863318\n", - " 0.627091\n", - " 5.655169\n", - " 0.538907\n", - " 0.130959\n", - " 0.892866\n", - " 5.455123\n", - " 0.880195\n", - " 0.334536\n", - " 1.299594\n", + " 5.932667\n", + " 0.434699\n", + " 5.990185\n", + " 0.538253\n", + " 6.015219\n", + " 0.528602\n", + " -0.114888\n", + " 0.951150\n", + " 5.878494\n", + " 0.880338\n", + " 0.094197\n", + " 1.299773\n", " 0.000000\n", " \n", " \n", " Braaf\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", " 0.0\n", " 0\n", - " 5.613092\n", - " 0.346900\n", - " 5.750920\n", - " 0.428900\n", - " 5.477731\n", - " 0.361478\n", - " 0.273028\n", - " 0.988318\n", - " 5.428794\n", - " 0.569555\n", - " 0.402369\n", - " 1.299586\n", + " 5.665697\n", + " 0.341006\n", + " 5.725323\n", + " 0.370040\n", + " 5.561785\n", + " 0.367506\n", + " 0.207320\n", + " 1.019125\n", + " 5.506973\n", + " 0.534618\n", + " 0.296589\n", + " 1.299793\n", " 0.000000\n", " \n", " \n", @@ -6986,70 +6988,70 @@ "text/plain": [ " role team oppteam home starter vote% MV MV std \\\n", "player \n", - "Musso P Atalanta Cagliari 1 1.0 70 6.187904 0.409565 \n", - "Carnesecchi P Atalanta Cagliari 1 0.0 5 6.153384 0.442585 \n", - "Rossi F. P Atalanta Cagliari 1 0.0 1 6.202195 0.436560 \n", - "Zappacosta D Atalanta Cagliari 1 0.6 60 6.174058 0.452587 \n", - "Zortea D Atalanta Cagliari 1 0.4 40 6.106819 0.397738 \n", + "Carnesecchi P Atalanta Juventus 1 0.0 5 6.140590 0.481707 \n", + "Musso P Atalanta Juventus 1 1.0 70 6.171150 0.480294 \n", + "Rossi F. P Atalanta Juventus 1 0.0 1 6.170296 0.480470 \n", + "Zappacosta D Atalanta Juventus 1 1.0 90 5.985259 0.522062 \n", + "Toloi D Atalanta Juventus 1 1.0 90 6.002894 0.499877 \n", "... ... ... ... ... ... ... ... ... \n", - "Henry A Verona Milan 0 0.0 0 5.806732 0.484893 \n", - "Kallon A Verona Milan 0 0.0 0 5.847151 0.430028 \n", - "Djuric A Verona Milan 0 0.4 60 5.847715 0.371962 \n", - "Cruz A Verona Milan 0 0.0 15 5.751310 0.481451 \n", - "Braaf A Verona Milan 0 0.0 0 5.613092 0.346900 \n", + "Henry A Verona Torino 0 0.4 60 5.839920 0.444240 \n", + "Djuric A Verona Torino 0 0.0 0 5.988754 0.256611 \n", + "Kallon A Verona Torino 0 0.0 0 5.863674 0.392202 \n", + "Cruz A Verona Torino 0 0.0 15 5.932667 0.434699 \n", + "Braaf A Verona Torino 0 0.0 0 5.665697 0.341006 \n", "\n", " FV FV std MV loc MV scale MV skewness \\\n", "player \n", - "Musso 5.778299 0.631974 6.172151 0.484012 0.024084 \n", - "Carnesecchi 5.099182 0.736154 6.095662 0.508426 0.083887 \n", - "Rossi F. 5.098540 0.738788 6.170873 0.510068 0.045397 \n", - "Zappacosta 6.519552 0.775398 6.110474 0.514245 0.090884 \n", - "Zortea 6.403875 0.627450 6.025298 0.444725 0.134716 \n", + "Carnesecchi 5.070139 0.715923 5.980216 0.509892 0.230396 \n", + "Musso 5.038867 0.684976 5.986030 0.494852 0.272883 \n", + "Rossi F. 5.037872 0.684438 5.984473 0.494652 0.273999 \n", + "Zappacosta 6.206951 0.733274 6.001576 0.613546 -0.019559 \n", + "Toloi 6.196084 0.699952 6.035264 0.591494 -0.040256 \n", "... ... ... ... ... ... \n", - "Henry 6.124626 0.710677 5.555864 0.490855 0.369405 \n", - "Kallon 6.110572 0.658053 5.650604 0.441275 0.323210 \n", - "Djuric 6.031966 0.518109 5.712709 0.393430 0.250597 \n", - "Cruz 5.863318 0.627091 5.655169 0.538907 0.130959 \n", - "Braaf 5.750920 0.428900 5.477731 0.361478 0.273028 \n", + "Henry 6.116677 0.669289 5.631952 0.453545 0.332464 \n", + "Djuric 6.065000 0.293257 6.035156 0.320372 -0.107045 \n", + "Kallon 6.044829 0.522801 5.719528 0.414042 0.254175 \n", + "Cruz 5.990185 0.538253 6.015219 0.528602 -0.114888 \n", + "Braaf 5.725323 0.370040 5.561785 0.367506 0.207320 \n", "\n", " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", "player \n", - "Musso 1.080489 6.551383 0.575009 -0.854511 1.143475 \n", - "Carnesecchi 1.071720 5.316064 1.103085 -0.144701 0.998809 \n", - "Rossi F. 1.057536 5.311903 1.107865 -0.141756 0.997465 \n", - "Zappacosta 0.896925 5.874933 0.976198 0.463032 1.299677 \n", - "Zortea 0.941082 5.877332 0.785433 0.469323 1.299658 \n", + "Carnesecchi 1.086084 5.321455 1.055452 -0.174796 0.965320 \n", + "Musso 1.084060 5.255883 1.019420 -0.156479 0.983446 \n", + "Rossi F. 1.084374 5.254371 1.018776 -0.156209 0.983780 \n", + "Zappacosta 0.881605 5.760596 1.050439 0.307981 1.299815 \n", + "Toloi 0.892304 5.804792 1.025037 0.278035 1.299814 \n", "... ... ... ... ... ... \n", - "Henry 0.852631 5.422048 0.779401 0.606238 1.299682 \n", - "Kallon 0.904855 5.475328 0.739265 0.582358 1.299658 \n", - "Djuric 0.961439 5.599852 0.651016 0.465176 1.299629 \n", - "Cruz 0.892866 5.455123 0.880195 0.334536 1.299594 \n", - "Braaf 0.988318 5.428794 0.569555 0.402369 1.299586 \n", + "Henry 0.906913 5.474079 0.755754 0.577176 1.299852 \n", + "Djuric 1.115607 5.977599 0.469125 0.137929 1.299758 \n", + "Kallon 0.962003 5.592772 0.641898 0.490306 1.299833 \n", + "Cruz 0.951150 5.878494 0.880338 0.094197 1.299773 \n", + "Braaf 1.019125 5.506973 0.534618 0.296589 1.299793 \n", "\n", " Clean Sheet % \n", "player \n", - "Musso 76.430595 \n", - "Carnesecchi 24.471429 \n", - "Rossi F. 19.948235 \n", + "Carnesecchi 20.727640 \n", + "Musso 28.833491 \n", + "Rossi F. 28.943959 \n", "Zappacosta 0.000000 \n", - "Zortea 0.000000 \n", + "Toloi 0.000000 \n", "... ... \n", "Henry 0.000000 \n", - "Kallon 0.000000 \n", "Djuric 0.000000 \n", + "Kallon 0.000000 \n", "Cruz 0.000000 \n", "Braaf 0.000000 \n", "\n", "[539 rows x 19 columns]" ] }, - "execution_count": 42, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "matchday_out = 5\n", + "matchday_out = 7\n", "\n", "output = pd.DataFrame(columns = ['player', 'role', 'team', 'oppteam', 'home', 'starter', 'vote%', 'MV', 'MV std', 'FV', 'FV std', 'MV loc', 'MV scale', 'MV skewness', 'MV tailweight', 'FV loc', 'FV scale', 'FV skewness', 'FV tailweight', 'Clean Sheet %'])\n", "\n", @@ -7099,7 +7101,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 33, "id": "6befd611", "metadata": {}, "outputs": [], @@ -7125,7 +7127,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 34, "id": "2b637a15", "metadata": {}, "outputs": [], @@ -7137,7 +7139,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 35, "id": "60d73507", "metadata": {}, "outputs": [ @@ -7145,557 +7147,557 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sommer (6.16, 0.43); (5.75, 0.63)\n", - "Szczesny (6.16, 0.45); (5.10, 0.74)\n", - "Meret (6.06, 0.45); (5.09, 0.74)\n", - "Provedel (6.16, 0.45); (4.50, 0.98)\n", - "Maignan (6.16, 0.44); (4.61, 0.91)\n", - "Rui Patricio (5.81, 0.51); (3.74, 1.19)\n", - "Skorupski (5.90, 0.50); (3.96, 1.15)\n", - "Milinkovic-Savic V. (6.15, 0.44); (5.41, 0.66)\n", - "Di Gregorio (6.23, 0.43); (5.10, 0.78)\n", - "Falcone (6.21, 0.45); (5.11, 0.76)\n", - "Silvestri (5.99, 0.46); (4.59, 0.91)\n", - "Terracciano (6.14, 0.45); (4.81, 0.86)\n", - "Carnesecchi (5.87, 0.50); (3.43, 1.37)\n", - "Radunovic (6.21, 0.42); (5.13, 0.73)\n", - "Montipo' (6.19, 0.44); (5.13, 0.73)\n", - "Martinez Jo. (6.08, 0.46); (4.86, 0.86)\n", - "Ochoa (6.05, 0.47); (3.48, 1.32)\n", - "Caprile (5.81, 0.48); (3.58, 1.25)\n", - "Turati (6.10, 0.48); (5.07, 0.75)\n", - "Consigli (5.99, 0.48); (3.88, 1.20)\n", - "Musso (6.17, 0.43); (5.72, 0.63)\n", - "Cragno (6.00, 0.49); (3.42, 1.40)\n", - "Perin (6.16, 0.44); (5.19, 0.69)\n", - "Berisha (5.83, 0.52); (3.40, 1.36)\n", - "Christensen O. (6.05, 0.47); (3.70, 1.22)\n", - "Sportiello (6.16, 0.44); (4.61, 0.91)\n", - "Mirante (6.16, 0.44); (4.61, 0.91)\n", - "Sepe (6.14, 0.45); (4.03, 1.09)\n", - "Leali (6.08, 0.46); (4.86, 0.86)\n", - "Lamanna (6.16, 0.45); (4.95, 0.79)\n", - "Sommariva (6.08, 0.46); (4.86, 0.86)\n", - "Pegolo (5.94, 0.49); (3.70, 1.28)\n", - "Perilli (6.17, 0.43); (5.19, 0.69)\n", - "Padelli (5.96, 0.46); (4.71, 0.90)\n", - "Scuffet (6.21, 0.42); (5.13, 0.73)\n", - "Gollini (5.83, 0.51); (3.91, 1.18)\n", - "Perisan (5.61, 0.50); (3.25, 1.32)\n", - "Audero (6.16, 0.43); (5.74, 0.63)\n", - "Di Gennaro (6.16, 0.43); (5.75, 0.63)\n", - "Pinsoglio (6.12, 0.48); (5.10, 0.74)\n", - "Aresti (6.21, 0.42); (5.13, 0.73)\n", - "Fiorillo (6.05, 0.47); (3.48, 1.32)\n", - "Cerofolini (6.21, 0.46); (5.10, 0.75)\n", - "Rossi F. (5.96, 0.50); (3.41, 1.37)\n", - "Costil (6.05, 0.47); (3.48, 1.32)\n", - "Ravaglia F. (5.90, 0.49); (3.86, 1.18)\n", - "Frattali (6.10, 0.48); (5.07, 0.75)\n", - "Contini (5.83, 0.51); (3.91, 1.18)\n", - "Brancolini (6.17, 0.46); (5.10, 0.74)\n", - "Berardi A. (6.17, 0.43); (5.19, 0.69)\n", - "Gemello (6.16, 0.43); (5.64, 0.63)\n", - "Boer (5.74, 0.53); (3.41, 1.35)\n", - "Bagnolini (5.90, 0.49); (3.86, 1.18)\n", - "Svilar (5.74, 0.53); (3.41, 1.35)\n", - "Sorrentino A. (5.97, 0.47); (3.98, 1.09)\n", - "Martinelli T. (6.04, 0.47); (4.11, 1.09)\n", - "Popa (6.16, 0.43); (5.64, 0.63)\n", - "Stubljar (5.81, 0.48); (3.58, 1.25)\n", - "Gori (6.16, 0.45); (4.95, 0.79)\n", - "Borbei (6.17, 0.46); (5.10, 0.74)\n", - "Okoye (5.96, 0.46); (4.71, 0.90)\n", - "Mandas (6.14, 0.45); (4.03, 1.09)\n", - "Dimarco (6.34, 0.39); (6.61, 0.67)\n", - "Di Lorenzo (6.31, 0.57); (6.97, 1.14)\n", - "Hernandez T. (6.13, 0.62); (6.74, 1.18)\n", - "Carlos Augusto (6.28, 0.48); (6.76, 0.92)\n", - "Danilo (6.32, 0.43); (6.65, 0.77)\n", - "Zappacosta (6.10, 0.56); (6.57, 0.98)\n", - "Schuurs (6.09, 0.46); (6.24, 0.63)\n", - "Posch (5.97, 0.48); (6.21, 0.75)\n", - "Bastoni (6.29, 0.38); (6.42, 0.50)\n", - "Smalling (6.12, 0.45); (6.40, 0.71)\n", - "Dumfries (6.26, 0.47); (6.73, 0.90)\n", - "Romagnoli (6.02, 0.50); (6.09, 0.64)\n", - "Pavard (6.12, 0.33); (6.23, 0.43)\n", - "Rrahmani (6.07, 0.54); (6.27, 0.72)\n", - "Spinazzola (6.20, 0.42); (6.50, 0.73)\n", - "Buongiorno (6.07, 0.48); (6.34, 0.78)\n", - "Bremer (6.08, 0.51); (6.29, 0.73)\n", - "Tomori (6.04, 0.46); (6.12, 0.58)\n", - "Biraghi (6.08, 0.56); (6.61, 1.03)\n", - "Mancini (6.01, 0.50); (6.27, 0.73)\n", - "Darmian (6.16, 0.36); (6.34, 0.51)\n", - "Bakker (5.99, 0.32); (6.07, 0.42)\n", - "Mazzocchi (5.79, 0.39); (5.92, 0.52)\n", - "Doig (6.00, 0.52); (6.31, 0.80)\n", - "Calabria (6.01, 0.45); (6.21, 0.66)\n", - "Acerbi (6.08, 0.35); (6.12, 0.37)\n", - "Cuadrado (6.05, 0.40); (6.15, 0.50)\n", - "Ebuehi (5.67, 0.43); (5.72, 0.52)\n", - "Casale (5.87, 0.47); (5.89, 0.58)\n", - "Holm (6.05, 0.41); (6.28, 0.60)\n", - "Baschirotto (5.93, 0.54); (6.10, 0.72)\n", - "Bijol (5.81, 0.53); (5.91, 0.70)\n", - "Thiaw (5.66, 0.68); (5.55, 0.67)\n", - "Mario Rui (6.00, 0.45); (6.10, 0.56)\n", - "Milenkovic (5.78, 0.59); (5.86, 0.76)\n", - "Rodriguez R. (5.98, 0.38); (5.98, 0.41)\n", - "Kolasinac (5.98, 0.38); (6.13, 0.51)\n", - "N'dicka (6.01, 0.28); (6.01, 0.29)\n", - "Scalvini (5.95, 0.56); (6.13, 0.74)\n", - "Perez N. (5.82, 0.45); (5.82, 0.55)\n", - "Kristensen (6.01, 0.36); (6.19, 0.54)\n", - "Izzo (5.93, 0.46); (5.98, 0.58)\n", - "De Vrij (6.24, 0.37); (6.35, 0.47)\n", - "Faraoni (5.85, 0.38); (5.96, 0.52)\n", - "Toloi (6.01, 0.46); (6.14, 0.61)\n", - "Kyriakopoulos (5.86, 0.31); (5.84, 0.35)\n", - "Bellanova (5.97, 0.41); (6.06, 0.51)\n", - "Mari' (5.77, 0.45); (5.74, 0.53)\n", - "Dodo' (5.80, 0.56); (5.91, 0.73)\n", - "Lucumi' (5.83, 0.42); (5.76, 0.47)\n", - "Hien (5.85, 0.48); (5.81, 0.54)\n", - "Natan (5.92, 0.49); (5.97, 0.57)\n", - "Hysaj (5.93, 0.39); (6.00, 0.51)\n", - "D'ambrosio (5.99, 0.32); (5.95, 0.35)\n", - "Luperto (5.54, 0.58); (5.47, 0.67)\n", - "Djimsiti (5.99, 0.40); (6.01, 0.43)\n", - "Marusic (5.84, 0.47); (5.79, 0.53)\n", - "Martin (5.91, 0.35); (6.02, 0.45)\n", - "Mina (5.97, 0.42); (6.24, 0.66)\n", - "Toljan (5.69, 0.45); (5.62, 0.49)\n", - "Llorente D. (5.81, 0.48); (5.83, 0.55)\n", - "Martinez Quarta (5.94, 0.58); (6.07, 0.75)\n", - "Bastoni S. (5.69, 0.43); (5.75, 0.56)\n", - "Dragusin (5.92, 0.45); (6.10, 0.62)\n", - "Parisi (6.04, 0.49); (6.24, 0.73)\n", - "Bradaric (5.76, 0.47); (5.81, 0.59)\n", - "Kamara H. (5.97, 0.33); (5.98, 0.39)\n", - "Olivera (5.98, 0.37); (6.11, 0.46)\n", - "Gendrey (5.92, 0.36); (5.92, 0.40)\n", - "Kristiansen (6.03, 0.37); (6.11, 0.52)\n", - "Beukema (5.94, 0.43); (5.94, 0.50)\n", - "Dossena (5.88, 0.38); (5.89, 0.45)\n", - "Pedersen (5.84, 0.33); (5.83, 0.35)\n", - "Juan Jesus (6.01, 0.34); (6.02, 0.34)\n", - "Gyomber (5.79, 0.49); (5.73, 0.54)\n", - "Alex Sandro (5.79, 0.51); (5.66, 0.52)\n", - "Hateboer (5.85, 0.50); (6.08, 0.74)\n", - "Palomino (5.92, 0.35); (5.94, 0.40)\n", - "Marchizza (5.95, 0.41); (5.98, 0.49)\n", - "Zappa (5.79, 0.38); (5.73, 0.37)\n", - "Gallo (5.90, 0.43); (5.90, 0.49)\n", - "Caldirola (5.69, 0.55); (5.74, 0.69)\n", - "Kalulu (5.82, 0.52); (5.80, 0.58)\n", - "Erlic (5.72, 0.52); (5.60, 0.54)\n", - "Vojvoda (5.91, 0.34); (5.96, 0.42)\n", - "Vasquez (5.96, 0.40); (5.97, 0.44)\n", - "Cambiaso (6.07, 0.40); (6.16, 0.48)\n", - "Pongracic (5.94, 0.43); (5.96, 0.50)\n", - "Viti (6.06, 0.31); (6.22, 0.44)\n", - "Gatti (6.13, 0.39); (6.19, 0.45)\n", - "Birindelli (5.88, 0.38); (5.86, 0.42)\n", - "Azzi (5.90, 0.33); (5.94, 0.40)\n", - "Wieteska (5.96, 0.42); (5.97, 0.51)\n", - "Masina (5.76, 0.49); (6.03, 0.71)\n", - "Romagnoli S. (5.88, 0.47); (5.94, 0.61)\n", - "Pezzella Giu. (5.53, 0.45); (5.43, 0.47)\n", - "Sabelli (5.96, 0.32); (6.03, 0.42)\n", - "Lirola (6.07, 0.46); (6.28, 0.68)\n", - "Lazzari (5.98, 0.39); (5.99, 0.43)\n", - "Bani (5.90, 0.54); (6.09, 0.76)\n", - "Djidji (5.84, 0.39); (5.86, 0.46)\n", - "Kabasele (5.79, 0.37); (5.74, 0.43)\n", - "Lazaro (6.02, 0.35); (6.07, 0.44)\n", - "Augello (5.85, 0.40); (5.92, 0.51)\n", - "Zortea (6.05, 0.46); (6.35, 0.70)\n", - "Dawidowicz (5.83, 0.47); (5.81, 0.55)\n", - "Pirola (5.72, 0.51); (5.78, 0.64)\n", - "Lovato (5.65, 0.44); (5.55, 0.46)\n", - "Ruggeri (6.09, 0.55); (6.46, 0.88)\n", - "Vina (5.78, 0.50); (5.75, 0.55)\n", - "Obert (5.76, 0.43); (5.71, 0.46)\n", - "Terracciano F. (6.08, 0.36); (6.17, 0.46)\n", - "Ebosele (5.77, 0.37); (5.74, 0.42)\n", - "Zemura (5.93, 0.31); (5.92, 0.36)\n", - "Hatzidiakos (5.95, 0.41); (5.97, 0.48)\n", - "Patric (5.97, 0.39); (5.93, 0.40)\n", - "Lykogiannis (5.84, 0.32); (5.88, 0.38)\n", - "Pellegrini Lu. (5.72, 0.37); (5.64, 0.39)\n", - "Magnani (5.78, 0.52); (5.75, 0.60)\n", - "Ranieri L. (5.67, 0.46); (5.64, 0.53)\n", - "Carboni A. (5.94, 0.37); (5.96, 0.45)\n", - "Calafiori (5.95, 0.40); (6.01, 0.53)\n", - "Monterisi (5.99, 0.62); (6.38, 1.03)\n", - "Ismajli (5.63, 0.46); (5.52, 0.48)\n", - "De Winter (5.83, 0.44); (5.74, 0.43)\n", - "Tressoldi (5.80, 0.47); (5.81, 0.56)\n", - "Ehizibue (5.74, 0.43); (5.76, 0.56)\n", - "Vogliacco (5.89, 0.45); (5.87, 0.50)\n", - "Ferrari G. (5.69, 0.52); (5.73, 0.63)\n", - "Venuti (5.79, 0.40); (5.75, 0.43)\n", - "Karsdorp (5.89, 0.25); (5.87, 0.24)\n", - "Kjaer (5.52, 0.38); (5.49, 0.35)\n", - "Gunter (5.67, 0.53); (5.59, 0.59)\n", - "Soumaoro (5.82, 0.54); (5.77, 0.61)\n", - "Di Pardo (5.81, 0.41); (5.76, 0.43)\n", - "Zanoli (6.10, 0.50); (6.48, 0.83)\n", - "Zima (5.92, 0.30); (5.89, 0.30)\n", - "Hefti (5.75, 0.42); (5.68, 0.42)\n", - "Ostigard (5.64, 0.38); (5.60, 0.36)\n", - "Sambia (5.92, 0.36); (5.95, 0.40)\n", - "Bisseck (5.97, 0.38); (6.01, 0.43)\n", - "Oyono (5.96, 0.39); (5.96, 0.43)\n", - "Ferreira J. (5.77, 0.37); (5.72, 0.41)\n", - "Dorgu (6.02, 0.33); (6.05, 0.37)\n", - "Touba (5.96, 0.40); (6.01, 0.49)\n", - "Sazonov (5.94, 0.43); (5.99, 0.54)\n", - "Rugani (6.07, 0.29); (6.08, 0.30)\n", - "De Sciglio (5.91, 0.33); (5.89, 0.32)\n", - "Goldaniga (5.66, 0.44); (5.57, 0.45)\n", - "Florenzi (5.97, 0.33); (6.04, 0.38)\n", - "De Silvestri (5.92, 0.32); (5.95, 0.40)\n", - "Pereira P. (5.85, 0.40); (5.83, 0.45)\n", - "Fazio (5.74, 0.62); (5.84, 0.79)\n", - "Bereszynski (5.54, 0.47); (5.46, 0.51)\n", - "Bonifazi (5.71, 0.44); (5.61, 0.45)\n", - "Walukiewicz (5.46, 0.41); (5.36, 0.37)\n", - "Okoli (5.88, 0.40); (5.84, 0.41)\n", - "Kumbulla (5.49, 0.75); (5.25, 0.70)\n", - "Celik (5.66, 0.38); (5.57, 0.37)\n", - "Amione (5.70, 0.45); (5.68, 0.55)\n", - "Daniliuc (5.68, 0.52); (5.68, 0.63)\n", - "Soppy (5.87, 0.36); (5.92, 0.45)\n", - "Haps (5.86, 0.45); (5.93, 0.57)\n", - "Cittadini (5.87, 0.45); (5.93, 0.59)\n", - "Coppola D. (5.75, 0.39); (5.67, 0.42)\n", - "Cacace (5.54, 0.40); (5.43, 0.39)\n", - "Ebosse (5.74, 0.34); (5.65, 0.34)\n", - "Guessand A. (5.77, 0.41); (5.77, 0.50)\n" + "Sommer (6.16, 0.44); (5.74, 0.61)\n", + "Szczesny (6.18, 0.43); (5.77, 0.63)\n", + "Meret (5.86, 0.50); (4.14, 1.03)\n", + "Provedel (6.18, 0.46); (4.76, 0.82)\n", + "Maignan (6.14, 0.47); (4.99, 0.69)\n", + "Rui Patricio (5.82, 0.52); (3.28, 1.26)\n", + "Skorupski (6.12, 0.43); (5.58, 0.61)\n", + "Milinkovic-Savic V. (6.20, 0.44); (5.13, 0.68)\n", + "Di Gregorio (6.21, 0.46); (5.06, 0.69)\n", + "Falcone (6.18, 0.44); (5.10, 0.67)\n", + "Silvestri (5.93, 0.48); (4.16, 1.05)\n", + "Terracciano (6.20, 0.45); (5.08, 0.71)\n", + "Carnesecchi (6.12, 0.45); (5.20, 0.66)\n", + "Radunovic (6.17, 0.44); (5.04, 0.74)\n", + "Montipo' (6.19, 0.43); (5.25, 0.62)\n", + "Martinez Jo. (6.15, 0.47); (4.63, 0.86)\n", + "Ochoa (6.14, 0.47); (3.71, 1.14)\n", + "Caprile (6.06, 0.47); (4.00, 1.05)\n", + "Turati (6.22, 0.47); (5.05, 0.70)\n", + "Consigli (6.04, 0.49); (4.11, 1.00)\n", + "Musso (6.15, 0.43); (5.71, 0.61)\n", + "Cragno (6.04, 0.49); (3.72, 1.10)\n", + "Perin (6.17, 0.44); (5.57, 0.61)\n", + "Berisha (6.05, 0.49); (3.77, 1.13)\n", + "Christensen O. (6.12, 0.47); (4.45, 0.85)\n", + "Sportiello (6.16, 0.45); (5.28, 0.63)\n", + "Mirante (6.14, 0.47); (4.99, 0.69)\n", + "Sepe (6.16, 0.46); (4.55, 0.87)\n", + "Leali (6.15, 0.47); (4.63, 0.86)\n", + "Lamanna (6.19, 0.46); (5.04, 0.69)\n", + "Sommariva (6.15, 0.47); (4.63, 0.86)\n", + "Pegolo (6.06, 0.49); (3.98, 1.04)\n", + "Perilli (6.19, 0.42); (5.28, 0.62)\n", + "Padelli (5.92, 0.48); (3.93, 1.11)\n", + "Scuffet (6.17, 0.44); (5.04, 0.74)\n", + "Gollini (5.86, 0.50); (4.14, 1.03)\n", + "Perisan (5.90, 0.49); (3.73, 1.17)\n", + "Audero (6.16, 0.44); (5.74, 0.61)\n", + "Di Gennaro (6.16, 0.44); (5.74, 0.61)\n", + "Pinsoglio (6.18, 0.43); (5.78, 0.63)\n", + "Aresti (6.17, 0.44); (5.04, 0.74)\n", + "Fiorillo (6.14, 0.47); (3.71, 1.14)\n", + "Cerofolini (6.23, 0.47); (5.05, 0.70)\n", + "Rossi F. (6.15, 0.43); (5.71, 0.61)\n", + "Costil (6.14, 0.47); (3.71, 1.14)\n", + "Ravaglia F. (6.12, 0.43); (5.58, 0.61)\n", + "Frattali (6.22, 0.47); (5.05, 0.70)\n", + "Contini (5.86, 0.50); (4.14, 1.03)\n", + "Brancolini (6.17, 0.44); (5.10, 0.66)\n", + "Berardi A. (6.19, 0.42); (5.28, 0.62)\n", + "Gemello (6.21, 0.43); (5.16, 0.67)\n", + "Boer (5.82, 0.52); (3.28, 1.26)\n", + "Bagnolini (6.12, 0.43); (5.58, 0.61)\n", + "Svilar (5.82, 0.52); (3.28, 1.26)\n", + "Sorrentino A. (6.20, 0.46); (5.04, 0.69)\n", + "Martinelli T. (6.20, 0.45); (5.07, 0.70)\n", + "Popa (6.21, 0.43); (5.16, 0.67)\n", + "Stubljar (6.05, 0.49); (3.77, 1.13)\n", + "Gori (6.19, 0.46); (5.04, 0.69)\n", + "Borbei (6.17, 0.44); (5.10, 0.66)\n", + "Okoye (5.92, 0.48); (3.93, 1.11)\n", + "Mandas (6.16, 0.46); (4.55, 0.87)\n", + "Dimarco (6.28, 0.38); (6.61, 0.67)\n", + "Di Lorenzo (6.25, 0.51); (6.74, 0.94)\n", + "Hernandez T. (6.16, 0.55); (6.59, 0.95)\n", + "Carlos Augusto (6.15, 0.41); (6.46, 0.66)\n", + "Danilo (6.17, 0.47); (6.48, 0.75)\n", + "Zappacosta (6.11, 0.49); (6.43, 0.78)\n", + "Schuurs (6.08, 0.44); (6.27, 0.63)\n", + "Posch (5.98, 0.41); (6.10, 0.59)\n", + "Bastoni (6.22, 0.41); (6.38, 0.52)\n", + "Smalling (6.03, 0.42); (6.23, 0.60)\n", + "Dumfries (6.21, 0.45); (6.64, 0.82)\n", + "Romagnoli (6.08, 0.47); (6.20, 0.59)\n", + "Pavard (6.04, 0.31); (6.13, 0.37)\n", + "Rrahmani (6.05, 0.50); (6.22, 0.66)\n", + "Spinazzola (6.10, 0.37); (6.35, 0.61)\n", + "Buongiorno (6.04, 0.47); (6.26, 0.72)\n", + "Bremer (6.04, 0.48); (6.19, 0.66)\n", + "Tomori (6.15, 0.49); (6.41, 0.75)\n", + "Biraghi (6.09, 0.50); (6.54, 0.92)\n", + "Mancini (5.88, 0.52); (6.07, 0.72)\n", + "Darmian (6.14, 0.37); (6.33, 0.50)\n", + "Bakker (6.00, 0.32); (6.10, 0.44)\n", + "Mazzocchi (5.72, 0.39); (5.74, 0.43)\n", + "Doig (6.01, 0.49); (6.24, 0.72)\n", + "Calabria (6.02, 0.45); (6.17, 0.62)\n", + "Acerbi (6.04, 0.32); (6.09, 0.33)\n", + "Cuadrado (6.03, 0.39); (6.12, 0.48)\n", + "Ebuehi (5.78, 0.41); (5.81, 0.50)\n", + "Casale (5.94, 0.44); (5.96, 0.53)\n", + "Holm (6.03, 0.33); (6.14, 0.42)\n", + "Baschirotto (5.92, 0.53); (6.02, 0.66)\n", + "Bijol (5.77, 0.52); (5.83, 0.65)\n", + "Thiaw (5.82, 0.62); (5.77, 0.65)\n", + "Mario Rui (5.93, 0.36); (5.95, 0.40)\n", + "Milenkovic (5.85, 0.56); (5.90, 0.68)\n", + "Rodriguez R. (5.98, 0.37); (5.98, 0.38)\n", + "Kolasinac (6.00, 0.37); (6.12, 0.49)\n", + "N'dicka (5.86, 0.42); (5.85, 0.48)\n", + "Scalvini (6.01, 0.51); (6.16, 0.67)\n", + "Perez N. (5.80, 0.50); (5.81, 0.61)\n", + "Kristensen (5.97, 0.33); (6.14, 0.49)\n", + "Izzo (5.93, 0.46); (5.97, 0.56)\n", + "De Vrij (6.17, 0.38); (6.27, 0.42)\n", + "Faraoni (5.78, 0.37); (5.80, 0.45)\n", + "Toloi (6.05, 0.46); (6.18, 0.61)\n", + "Kyriakopoulos (6.05, 0.48); (6.22, 0.68)\n", + "Bellanova (5.73, 0.56); (5.77, 0.65)\n", + "Mari' (5.89, 0.47); (5.90, 0.56)\n", + "Dodo' (5.85, 0.54); (5.93, 0.69)\n", + "Lucumi' (5.93, 0.38); (5.92, 0.43)\n", + "Hien (5.91, 0.41); (5.87, 0.44)\n", + "Natan (6.03, 0.41); (6.12, 0.49)\n", + "Hysaj (5.92, 0.39); (5.95, 0.49)\n", + "D'ambrosio (5.93, 0.34); (5.90, 0.35)\n", + "Luperto (5.64, 0.59); (5.58, 0.66)\n", + "Djimsiti (6.01, 0.36); (6.03, 0.38)\n", + "Marusic (5.88, 0.46); (5.84, 0.52)\n", + "Martin (5.87, 0.45); (5.91, 0.57)\n", + "Mina (6.03, 0.41); (6.26, 0.63)\n", + "Toljan (5.86, 0.44); (5.86, 0.50)\n", + "Llorente D. (5.85, 0.39); (5.81, 0.40)\n", + "Martinez Quarta (6.06, 0.58); (6.30, 0.83)\n", + "Bastoni S. (5.94, 0.50); (6.20, 0.79)\n", + "Dragusin (6.03, 0.44); (6.19, 0.62)\n", + "Parisi (6.05, 0.50); (6.24, 0.72)\n", + "Bradaric (5.80, 0.44); (5.81, 0.52)\n", + "Kamara H. (5.92, 0.27); (5.92, 0.29)\n", + "Olivera (5.97, 0.34); (6.03, 0.41)\n", + "Gendrey (5.93, 0.35); (5.93, 0.38)\n", + "Kristiansen (6.00, 0.38); (6.07, 0.49)\n", + "Beukema (5.98, 0.41); (6.03, 0.49)\n", + "Dossena (5.73, 0.42); (5.66, 0.43)\n", + "Pedersen (5.91, 0.30); (5.90, 0.31)\n", + "Juan Jesus (6.00, 0.34); (6.05, 0.35)\n", + "Gyomber (5.80, 0.46); (5.74, 0.49)\n", + "Alex Sandro (5.82, 0.51); (5.70, 0.54)\n", + "Hateboer (5.92, 0.45); (6.07, 0.65)\n", + "Palomino (6.01, 0.31); (6.06, 0.35)\n", + "Marchizza (6.10, 0.43); (6.31, 0.62)\n", + "Zappa (5.75, 0.38); (5.69, 0.38)\n", + "Gallo (5.93, 0.42); (5.91, 0.45)\n", + "Caldirola (5.82, 0.51); (5.87, 0.64)\n", + "Kalulu (5.92, 0.50); (5.95, 0.59)\n", + "Erlic (5.89, 0.46); (5.83, 0.46)\n", + "Vojvoda (5.93, 0.36); (5.97, 0.44)\n", + "Vasquez (6.09, 0.36); (6.15, 0.37)\n", + "Cambiaso (6.00, 0.43); (6.07, 0.50)\n", + "Pongracic (6.03, 0.40); (6.06, 0.44)\n", + "Viti (5.89, 0.45); (5.82, 0.43)\n", + "Gatti (5.76, 0.62); (5.69, 0.64)\n", + "Birindelli (5.93, 0.35); (5.92, 0.39)\n", + "Azzi (5.90, 0.28); (5.89, 0.28)\n", + "Wieteska (5.92, 0.44); (5.92, 0.52)\n", + "Masina (5.78, 0.49); (6.08, 0.69)\n", + "Romagnoli S. (6.08, 0.53); (6.32, 0.81)\n", + "Pezzella Giu. (5.64, 0.44); (5.55, 0.46)\n", + "Sabelli (5.98, 0.28); (6.02, 0.34)\n", + "Lirola (6.03, 0.49); (6.21, 0.69)\n", + "Lazzari (5.99, 0.37); (6.01, 0.40)\n", + "Bani (6.07, 0.53); (6.31, 0.80)\n", + "Djidji (5.88, 0.38); (5.90, 0.45)\n", + "Kabasele (5.86, 0.35); (5.83, 0.41)\n", + "Lazaro (6.00, 0.35); (6.04, 0.40)\n", + "Augello (5.87, 0.36); (5.92, 0.45)\n", + "Zortea (6.04, 0.43); (6.29, 0.65)\n", + "Dawidowicz (5.90, 0.39); (5.86, 0.44)\n", + "Pirola (5.70, 0.45); (5.69, 0.51)\n", + "Lovato (5.69, 0.44); (5.60, 0.47)\n", + "Ruggeri (6.10, 0.53); (6.43, 0.83)\n", + "Vina (5.67, 0.56); (5.67, 0.63)\n", + "Obert (5.75, 0.42); (5.69, 0.44)\n", + "Terracciano F. (6.02, 0.36); (6.08, 0.42)\n", + "Ebosele (5.80, 0.41); (5.75, 0.46)\n", + "Zemura (5.89, 0.29); (5.86, 0.31)\n", + "Hatzidiakos (5.89, 0.42); (5.88, 0.46)\n", + "Patric (5.94, 0.33); (5.92, 0.33)\n", + "Lykogiannis (5.92, 0.27); (5.92, 0.32)\n", + "Pellegrini Lu. (5.81, 0.34); (5.74, 0.34)\n", + "Magnani (5.93, 0.46); (5.92, 0.52)\n", + "Ranieri L. (5.78, 0.50); (5.82, 0.61)\n", + "Carboni A. (5.97, 0.37); (6.01, 0.44)\n", + "Calafiori (5.84, 0.44); (5.82, 0.53)\n", + "Monterisi (5.98, 0.62); (6.40, 1.05)\n", + "Ismajli (5.78, 0.48); (5.69, 0.49)\n", + "De Winter (5.93, 0.46); (5.90, 0.50)\n", + "Tressoldi (5.91, 0.45); (5.94, 0.53)\n", + "Ehizibue (5.77, 0.44); (5.77, 0.56)\n", + "Vogliacco (5.94, 0.46); (5.94, 0.52)\n", + "Ferrari G. (5.91, 0.50); (5.97, 0.62)\n", + "Venuti (5.89, 0.36); (5.86, 0.39)\n", + "Karsdorp (5.89, 0.29); (5.87, 0.30)\n", + "Kjaer (5.67, 0.49); (5.54, 0.50)\n", + "Gunter (5.74, 0.52); (5.64, 0.55)\n", + "Soumaoro (5.88, 0.47); (5.84, 0.54)\n", + "Di Pardo (5.80, 0.41); (5.75, 0.43)\n", + "Zanoli (6.07, 0.48); (6.35, 0.75)\n", + "Zima (5.97, 0.46); (5.97, 0.50)\n", + "Hefti (5.84, 0.38); (5.79, 0.36)\n", + "Ostigard (5.83, 0.38); (5.79, 0.38)\n", + "Sambia (5.89, 0.38); (5.88, 0.41)\n", + "Bisseck (5.99, 0.42); (6.08, 0.52)\n", + "Oyono (5.89, 0.35); (5.85, 0.35)\n", + "Ferreira J. (5.82, 0.33); (5.77, 0.36)\n", + "Dorgu (5.95, 0.24); (5.94, 0.23)\n", + "Touba (5.96, 0.43); (6.02, 0.52)\n", + "Sazonov (5.96, 0.40); (5.99, 0.48)\n", + "Rugani (5.98, 0.26); (5.99, 0.25)\n", + "De Sciglio (5.88, 0.32); (5.86, 0.31)\n", + "Goldaniga (5.65, 0.58); (5.56, 0.62)\n", + "Florenzi (6.06, 0.38); (6.14, 0.45)\n", + "De Silvestri (6.02, 0.28); (6.06, 0.31)\n", + "Pereira P. (5.97, 0.42); (6.02, 0.51)\n", + "Fazio (5.86, 0.61); (5.96, 0.77)\n", + "Bereszynski (5.64, 0.48); (5.58, 0.54)\n", + "Bonifazi (5.84, 0.40); (5.79, 0.43)\n", + "Walukiewicz (5.70, 0.55); (5.69, 0.64)\n", + "Okoli (5.86, 0.41); (5.81, 0.42)\n", + "Kumbulla (5.50, 0.73); (5.27, 0.69)\n", + "Celik (5.75, 0.45); (5.68, 0.50)\n", + "Amione (5.72, 0.44); (5.70, 0.53)\n", + "Daniliuc (5.77, 0.47); (5.74, 0.56)\n", + "Soppy (5.93, 0.34); (5.93, 0.40)\n", + "Haps (5.96, 0.46); (6.02, 0.58)\n", + "Cittadini (5.95, 0.44); (6.02, 0.57)\n", + "Coppola D. (5.85, 0.35); (5.78, 0.36)\n", + "Cacace (5.64, 0.43); (5.54, 0.43)\n", + "Ebosse (5.83, 0.35); (5.76, 0.39)\n", + "Guessand A. (5.89, 0.43); (5.92, 0.55)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Cabal (5.87, 0.25); (5.83, 0.24)\n", - "Missori (5.76, 0.43); (5.73, 0.48)\n", - "Kayode (5.99, 0.44); (6.02, 0.52)\n", - "Corazza (5.71, 0.39); (5.67, 0.44)\n", - "Kristensen T. (5.81, 0.45); (5.85, 0.58)\n", - "Dermaku (5.91, 0.43); (5.96, 0.54)\n", - "Tonelli (5.56, 0.49); (5.44, 0.53)\n", - "Capradossi (5.90, 0.44); (5.91, 0.53)\n", - "Bettella (5.87, 0.45); (5.93, 0.59)\n", - "Amey (5.82, 0.46); (5.87, 0.59)\n", - "Gila (5.86, 0.44); (5.84, 0.49)\n", - "Bronn (5.62, 0.45); (5.50, 0.46)\n", - "Guarino (5.67, 0.50); (5.67, 0.59)\n", - "Carboni F. (5.96, 0.37); (5.99, 0.45)\n", - "Smajlovic (5.91, 0.45); (5.98, 0.57)\n", - "Matturro (5.89, 0.45); (5.87, 0.50)\n", - "N'guessan (5.94, 0.43); (5.99, 0.54)\n", - "Mateus Lusuardi (5.92, 0.46); (5.97, 0.56)\n", - "Kalaj (5.92, 0.46); (5.97, 0.56)\n", - "Pierozzi (5.88, 0.48); (5.92, 0.58)\n", - "Huijsen (5.99, 0.42); (6.10, 0.54)\n", - "Bonfanti (5.97, 0.46); (6.07, 0.59)\n", - "Pellegrino (5.93, 0.46); (6.01, 0.59)\n", - "Comuzzo (5.88, 0.48); (5.92, 0.58)\n", - "Zaccagni (6.32, 0.53); (6.95, 1.16)\n", - "Koopmeiners (6.38, 0.57); (7.20, 1.36)\n", - "Luis Alberto (6.38, 0.53); (7.09, 1.23)\n", - "Felipe Anderson (6.14, 0.58); (6.77, 1.17)\n", - "Rabiot (6.31, 0.55); (7.06, 1.28)\n", - "Zielinski (6.30, 0.46); (6.71, 0.86)\n", - "Barella (6.35, 0.45); (6.79, 0.89)\n", - "Pulisic (6.21, 0.54); (6.81, 1.09)\n", - "Orsolini (6.18, 0.59); (6.84, 1.25)\n", - "Calhanoglu (6.42, 0.39); (6.67, 0.69)\n", - "Strefezza (6.19, 0.50); (6.64, 0.92)\n", - "Chukwueze (5.95, 0.43); (6.24, 0.66)\n", - "Ferguson (6.22, 0.52); (6.74, 1.01)\n", - "Candreva (6.17, 0.65); (6.86, 1.30)\n", - "Frattesi (6.35, 0.53); (7.04, 1.20)\n", - "Samardzic (6.06, 0.51); (6.47, 0.87)\n", - "Vlasic (6.13, 0.51); (6.59, 0.93)\n", - "Bonaventura (6.28, 0.57); (6.97, 1.23)\n", - "Politano (6.35, 0.45); (6.77, 0.90)\n", - "El Shaarawy (6.28, 0.46); (6.70, 0.90)\n", - "Mkhitaryan (6.36, 0.51); (7.00, 1.11)\n", - "Aouar (6.17, 0.49); (6.64, 0.94)\n", - "Malinovskyi (6.02, 0.56); (6.61, 1.10)\n", - "Gudmundsson A. (6.12, 0.46); (6.47, 0.78)\n", - "Kamada (6.06, 0.50); (6.49, 0.87)\n", - "Pellegrini Lo. (6.08, 0.56); (6.63, 1.05)\n", - "Kostic (6.22, 0.48); (6.68, 0.90)\n", - "Radonjic (6.32, 0.57); (7.08, 1.31)\n", - "Baldanzi (5.75, 0.44); (5.97, 0.62)\n", - "Lovric (6.05, 0.46); (6.37, 0.76)\n", - "Lindstrom (6.05, 0.45); (6.40, 0.74)\n", - "Lazovic (6.17, 0.49); (6.57, 0.87)\n", - "Pereyra (6.14, 0.56); (6.68, 1.07)\n", - "Renato Sanches (6.14, 0.40); (6.37, 0.61)\n", - "Pessina (6.02, 0.48); (6.33, 0.80)\n", - "Guendouzi (6.03, 0.36); (6.16, 0.47)\n", - "Loftus-Cheek (6.06, 0.36); (6.14, 0.42)\n", - "Zambo Anguissa (6.10, 0.50); (6.49, 0.83)\n", - "Elmas (6.02, 0.54); (6.50, 0.93)\n", - "Bajrami (5.93, 0.36); (6.03, 0.43)\n", - "Ricci S. (6.04, 0.38); (6.18, 0.52)\n", - "Colpani (6.33, 0.53); (7.03, 1.22)\n", - "Ciurria (6.06, 0.54); (6.54, 1.00)\n", - "De Roon (6.12, 0.50); (6.46, 0.80)\n", - "Pogba (6.03, 0.35); (6.08, 0.41)\n", - "Cristante (6.14, 0.51); (6.50, 0.83)\n", - "Locatelli (6.12, 0.40); (6.23, 0.52)\n", - "Pasalic (5.95, 0.47); (6.31, 0.76)\n", - "Lobotka (6.08, 0.37); (6.16, 0.43)\n", - "Fagioli (6.09, 0.50); (6.48, 0.84)\n", - "Ikone' (6.04, 0.56); (6.60, 1.03)\n", - "Ilic (6.04, 0.43); (6.31, 0.69)\n", - "Ndoye (5.90, 0.39); (5.96, 0.50)\n", - "Ederson D.s. (6.09, 0.48); (6.42, 0.77)\n", - "Reijnders (6.09, 0.45); (6.39, 0.70)\n", - "Barak (5.81, 0.44); (6.03, 0.61)\n", - "Saponara (6.08, 0.48); (6.43, 0.79)\n", - "Mandragora (5.94, 0.55); (6.38, 0.90)\n", - "Weah (6.04, 0.27); (6.09, 0.30)\n", - "Bennacer (6.16, 0.46); (6.53, 0.78)\n", - "Duda (6.24, 0.53); (6.79, 1.06)\n", - "Castrovilli (6.03, 0.58); (6.59, 1.04)\n", - "Mckennie (6.25, 0.44); (6.58, 0.74)\n", - "Miranchuk (6.22, 0.50); (6.69, 0.93)\n", - "Matheus Henrique (5.81, 0.46); (6.06, 0.66)\n", - "De Ketelaere (5.98, 0.48); (6.32, 0.75)\n", - "Mboula (5.81, 0.33); (5.77, 0.35)\n", - "Paredes (5.79, 0.53); (5.78, 0.61)\n", - "Sottil (5.95, 0.39); (6.13, 0.52)\n", - "Klaassen (6.16, 0.40); (6.45, 0.67)\n", - "Arthur Melo (6.01, 0.47); (6.09, 0.57)\n", - "Thorsby (5.75, 0.48); (5.86, 0.63)\n", - "Nandez (6.02, 0.35); (6.15, 0.50)\n", - "Tameze (5.91, 0.34); (5.90, 0.37)\n", - "Marin (5.71, 0.48); (5.79, 0.62)\n", - "Messias (5.96, 0.53); (6.44, 0.96)\n", - "Musah (5.96, 0.36); (5.98, 0.41)\n", - "Coulibaly L. (5.91, 0.49); (6.16, 0.73)\n", - "Krunic (5.98, 0.38); (6.00, 0.44)\n", - "Cataldi (5.97, 0.36); (5.94, 0.38)\n", - "Strootman (5.95, 0.37); (6.06, 0.49)\n", - "Duncan (6.10, 0.45); (6.42, 0.74)\n", - "Freuler (5.95, 0.29); (5.94, 0.33)\n", - "Gagliardini (5.85, 0.38); (5.80, 0.39)\n", - "Mazzitelli (6.09, 0.65); (6.51, 1.06)\n", - "Jankto (5.95, 0.31); (5.94, 0.33)\n", - "Kastanos (5.86, 0.35); (5.98, 0.44)\n", - "Gyasi (5.63, 0.43); (5.62, 0.50)\n", - "Reinier (5.93, 0.46); (6.00, 0.57)\n", - "Zalewski (5.94, 0.36); (6.09, 0.46)\n", - "Harroui (6.19, 0.46); (6.59, 0.82)\n", - "Frendrup (6.01, 0.37); (6.13, 0.49)\n", - "Blin (5.95, 0.29); (5.96, 0.32)\n", - "Fabbian (6.05, 0.43); (6.36, 0.77)\n", - "Ramadani (6.11, 0.45); (6.26, 0.60)\n", - "Cajuste (5.92, 0.48); (5.98, 0.57)\n", - "Mancosu (5.91, 0.44); (5.94, 0.53)\n", - "Vecino (5.91, 0.44); (6.00, 0.58)\n", - "Sensi (6.15, 0.45); (6.49, 0.72)\n", - "Walace (5.81, 0.38); (5.76, 0.43)\n", - "Lopez M. (5.78, 0.40); (5.70, 0.41)\n", - "Brescianini (6.01, 0.37); (6.02, 0.41)\n", - "Bove (6.03, 0.35); (6.18, 0.48)\n", - "Aebischer (5.90, 0.33); (6.00, 0.43)\n", - "Thorstvedt (5.90, 0.34); (5.97, 0.41)\n", - "Gonzalez J. (5.89, 0.39); (5.98, 0.53)\n", - "Moro N. (6.01, 0.37); (6.19, 0.54)\n", - "Oudin (6.02, 0.48); (6.31, 0.76)\n", - "Boloca (5.80, 0.48); (5.80, 0.57)\n", - "Rafia (6.04, 0.37); (6.24, 0.55)\n", - "Makoumbou (5.91, 0.33); (5.95, 0.41)\n", - "Kaba (5.97, 0.27); (5.97, 0.29)\n", - "Badelj (5.87, 0.40); (5.85, 0.39)\n", - "Machin (5.85, 0.46); (5.92, 0.60)\n", - "Linetty (5.90, 0.35); (5.92, 0.41)\n", - "Castillejo (5.83, 0.36); (6.00, 0.50)\n", - "Rovella (6.05, 0.46); (6.17, 0.59)\n", - "Pobega (5.91, 0.37); (6.07, 0.50)\n", - "Hongla (5.86, 0.37); (5.90, 0.44)\n", - "Miretti (6.00, 0.35); (6.09, 0.42)\n", - "Fazzini (5.67, 0.33); (5.56, 0.35)\n", - "Iling Junior (5.99, 0.42); (6.11, 0.55)\n", - "Oristanio (5.89, 0.37); (5.86, 0.38)\n", - "Serdar (5.89, 0.38); (5.89, 0.45)\n", - "Payero (5.84, 0.41); (5.87, 0.52)\n", - "Grassi (5.67, 0.42); (5.56, 0.44)\n", - "Baez (5.99, 0.37); (6.11, 0.47)\n", - "Deiola (5.76, 0.46); (5.82, 0.59)\n", - "Garritano (6.13, 0.34); (6.18, 0.41)\n", - "Bourabia (5.97, 0.40); (6.07, 0.50)\n", - "Saelemaekers (5.95, 0.43); (6.21, 0.66)\n", - "Maldini (5.81, 0.45); (6.10, 0.69)\n", - "Racic (5.91, 0.35); (5.90, 0.39)\n", - "Kovalenko (5.78, 0.34); (5.73, 0.37)\n", - "Maleh (5.65, 0.30); (5.53, 0.32)\n", - "Bohinen (5.91, 0.26); (5.88, 0.25)\n", - "Ranocchia F. (5.88, 0.40); (6.11, 0.57)\n", - "Folorunsho (5.93, 0.47); (6.24, 0.76)\n", - "Infantino (5.82, 0.32); (5.77, 0.32)\n", - "Martegani (5.88, 0.45); (5.92, 0.54)\n", - "Kutlu (5.87, 0.40); (5.85, 0.41)\n", - "Tchatchoua (5.89, 0.46); (5.97, 0.59)\n", - "Quina (5.97, 0.35); (6.01, 0.43)\n", - "Adopo (5.85, 0.51); (5.87, 0.58)\n", - "Romero L. (6.19, 0.49); (6.68, 0.97)\n", - "Basic (5.96, 0.37); (6.05, 0.46)\n", - "Asllani (5.89, 0.31); (5.88, 0.27)\n", - "Tchaouna (5.81, 0.38); (5.81, 0.44)\n", - "Sulemana I. (5.83, 0.31); (5.78, 0.31)\n", - "Barrenechea (5.96, 0.42); (5.99, 0.48)\n", - "Gelli (5.94, 0.47); (6.01, 0.56)\n", - "Suslov (5.92, 0.42); (5.96, 0.53)\n", - "Gaetano (6.12, 0.53); (6.72, 1.06)\n", - "Jagiello (5.90, 0.45); (5.90, 0.50)\n", - "Obiang (5.90, 0.30); (5.86, 0.30)\n", - "Maggiore (5.89, 0.25); (5.86, 0.24)\n", - "Akpa Akpro (5.85, 0.46); (5.92, 0.60)\n", - "Urbanski (5.94, 0.34); (5.98, 0.44)\n", - "Volpato (5.92, 0.39); (6.05, 0.54)\n", - "Vignato S. (5.81, 0.40); (5.78, 0.45)\n", - "Hrustic (5.63, 0.32); (5.62, 0.34)\n", - "Zarraga (5.63, 0.39); (5.57, 0.41)\n", - "Camara E. (5.82, 0.45); (5.88, 0.59)\n", - "Amatucci (5.86, 0.41); (5.87, 0.48)\n", - "Pagano (5.98, 0.28); (5.98, 0.30)\n", - "Prati (5.91, 0.40); (5.91, 0.44)\n", - "Viola (5.85, 0.33); (5.82, 0.30)\n", - "Lulic K. (5.93, 0.46); (6.00, 0.57)\n", - "Rog (5.87, 0.36); (5.85, 0.36)\n", - "Nicolussi Caviglia (5.83, 0.48); (6.00, 0.67)\n", - "Demme (6.00, 0.26); (5.95, 0.22)\n", - "Pafundi (6.04, 0.31); (6.06, 0.32)\n", - "Adli (5.83, 0.40); (5.94, 0.51)\n", - "Bondo (5.91, 0.42); (5.96, 0.54)\n", - "Zerbin (6.05, 0.35); (6.12, 0.41)\n", - "Carboni V. (5.99, 0.37); (6.06, 0.47)\n", - "Faticanti (5.92, 0.44); (6.01, 0.57)\n", - "Gineitis (5.97, 0.37); (6.02, 0.47)\n", - "Belardinelli (5.69, 0.49); (5.71, 0.60)\n", - "El Azzouzi (5.96, 0.30); (5.98, 0.36)\n", - "Lipani (5.83, 0.46); (5.86, 0.56)\n", - "Joselito (5.89, 0.46); (5.97, 0.59)\n", - "Legowski (5.88, 0.48); (5.96, 0.61)\n", - "Ibrahimovic A. (5.93, 0.46); (6.00, 0.57)\n", + "Cabal (6.04, 0.46); (6.10, 0.55)\n", + "Missori (5.95, 0.45); (5.99, 0.54)\n", + "Kayode (6.03, 0.48); (6.10, 0.59)\n", + "Corazza (5.84, 0.37); (5.81, 0.42)\n", + "Kristensen T. (5.77, 0.41); (5.74, 0.47)\n", + "Dermaku (5.95, 0.42); (5.99, 0.52)\n", + "Tonelli (5.64, 0.49); (5.53, 0.51)\n", + "Capradossi (5.90, 0.44); (5.93, 0.53)\n", + "Bettella (5.95, 0.44); (6.02, 0.57)\n", + "Amey (5.92, 0.41); (5.97, 0.54)\n", + "Gila (5.89, 0.42); (5.86, 0.46)\n", + "Bronn (5.68, 0.45); (5.56, 0.47)\n", + "Guarino (5.78, 0.48); (5.81, 0.59)\n", + "Carboni F. (6.04, 0.44); (6.18, 0.59)\n", + "Smajlovic (5.96, 0.44); (6.03, 0.55)\n", + "Matturro (5.93, 0.45); (5.91, 0.48)\n", + "N'guessan (5.95, 0.43); (6.00, 0.53)\n", + "Mateus Lusuardi (5.95, 0.46); (6.01, 0.57)\n", + "Kalaj (5.95, 0.46); (6.01, 0.57)\n", + "Pierozzi (5.97, 0.47); (6.03, 0.59)\n", + "Huijsen (6.00, 0.44); (6.11, 0.56)\n", + "Bonfanti (6.00, 0.45); (6.10, 0.58)\n", + "Pellegrino (5.97, 0.46); (6.03, 0.57)\n", + "Comuzzo (5.97, 0.47); (6.03, 0.59)\n", + "Zaccagni (6.30, 0.53); (6.91, 1.12)\n", + "Koopmeiners (6.37, 0.55); (7.10, 1.25)\n", + "Luis Alberto (6.30, 0.54); (6.98, 1.19)\n", + "Felipe Anderson (6.10, 0.55); (6.60, 1.01)\n", + "Rabiot (6.23, 0.55); (6.86, 1.16)\n", + "Zielinski (6.28, 0.47); (6.77, 0.93)\n", + "Barella (6.23, 0.45); (6.64, 0.80)\n", + "Pulisic (6.26, 0.59); (7.02, 1.31)\n", + "Orsolini (6.03, 0.52); (6.48, 0.98)\n", + "Calhanoglu (6.34, 0.40); (6.63, 0.66)\n", + "Strefezza (6.09, 0.44); (6.42, 0.76)\n", + "Chukwueze (5.94, 0.39); (6.17, 0.57)\n", + "Ferguson (6.13, 0.43); (6.46, 0.75)\n", + "Candreva (6.21, 0.63); (6.94, 1.30)\n", + "Frattesi (6.22, 0.51); (6.75, 1.00)\n", + "Samardzic (6.11, 0.47); (6.53, 0.85)\n", + "Vlasic (6.04, 0.47); (6.40, 0.79)\n", + "Bonaventura (6.32, 0.55); (7.00, 1.20)\n", + "Politano (6.33, 0.50); (6.92, 1.07)\n", + "El Shaarawy (6.10, 0.40); (6.40, 0.69)\n", + "Mkhitaryan (6.29, 0.51); (6.90, 1.06)\n", + "Aouar (5.97, 0.53); (6.43, 0.89)\n", + "Malinovskyi (6.04, 0.56); (6.63, 1.11)\n", + "Gudmundsson A. (6.25, 0.49); (6.79, 0.99)\n", + "Kamada (6.07, 0.48); (6.42, 0.80)\n", + "Pellegrini Lo. (5.93, 0.53); (6.35, 0.87)\n", + "Kostic (6.14, 0.44); (6.49, 0.74)\n", + "Radonjic (6.26, 0.59); (7.04, 1.33)\n", + "Baldanzi (5.95, 0.53); (6.37, 0.88)\n", + "Lovric (6.00, 0.41); (6.27, 0.66)\n", + "Lindstrom (6.04, 0.39); (6.33, 0.66)\n", + "Lazovic (6.12, 0.44); (6.43, 0.73)\n", + "Pereyra (6.05, 0.56); (6.55, 1.01)\n", + "Renato Sanches (6.10, 0.36); (6.32, 0.56)\n", + "Pessina (6.07, 0.48); (6.31, 0.73)\n", + "Guendouzi (5.97, 0.36); (6.06, 0.47)\n", + "Loftus-Cheek (6.19, 0.45); (6.54, 0.75)\n", + "Zambo Anguissa (6.05, 0.46); (6.26, 0.65)\n", + "Elmas (6.00, 0.50); (6.35, 0.81)\n", + "Bajrami (6.08, 0.36); (6.28, 0.54)\n", + "Ricci S. (5.99, 0.41); (6.10, 0.55)\n", + "Colpani (6.34, 0.53); (7.03, 1.19)\n", + "Ciurria (6.03, 0.51); (6.39, 0.85)\n", + "De Roon (6.12, 0.47); (6.41, 0.73)\n", + "Pogba (6.04, 0.42); (6.15, 0.52)\n", + "Cristante (6.08, 0.50); (6.38, 0.78)\n", + "Locatelli (5.98, 0.38); (6.03, 0.45)\n", + "Pasalic (6.00, 0.52); (6.47, 0.91)\n", + "Lobotka (6.06, 0.40); (6.16, 0.48)\n", + "Fagioli (6.07, 0.49); (6.40, 0.78)\n", + "Ikone' (6.08, 0.53); (6.56, 0.96)\n", + "Ilic (6.00, 0.37); (6.05, 0.46)\n", + "Ndoye (5.94, 0.35); (5.99, 0.43)\n", + "Ederson D.s. (6.09, 0.46); (6.38, 0.72)\n", + "Reijnders (6.13, 0.44); (6.43, 0.70)\n", + "Barak (5.87, 0.44); (6.07, 0.61)\n", + "Saponara (6.06, 0.40); (6.31, 0.63)\n", + "Mandragora (6.02, 0.51); (6.36, 0.82)\n", + "Weah (5.96, 0.27); (5.99, 0.29)\n", + "Bennacer (6.16, 0.44); (6.49, 0.71)\n", + "Duda (6.26, 0.52); (6.82, 1.06)\n", + "Castrovilli (6.08, 0.54); (6.56, 0.97)\n", + "Mckennie (6.21, 0.39); (6.39, 0.52)\n", + "Miranchuk (6.24, 0.49); (6.69, 0.91)\n", + "Matheus Henrique (5.99, 0.46); (6.25, 0.69)\n", + "De Ketelaere (6.08, 0.51); (6.47, 0.85)\n", + "Mboula (5.92, 0.39); (5.93, 0.47)\n", + "Paredes (5.82, 0.49); (5.85, 0.60)\n", + "Sottil (5.94, 0.35); (6.08, 0.43)\n", + "Klaassen (6.10, 0.39); (6.38, 0.66)\n", + "Arthur Melo (6.06, 0.40); (6.15, 0.50)\n", + "Thorsby (5.92, 0.60); (6.36, 0.99)\n", + "Nandez (5.99, 0.34); (6.11, 0.48)\n", + "Tameze (5.92, 0.31); (5.90, 0.33)\n", + "Marin (5.89, 0.39); (5.97, 0.52)\n", + "Messias (6.03, 0.56); (6.59, 1.07)\n", + "Musah (6.01, 0.34); (6.06, 0.40)\n", + "Coulibaly L. (5.99, 0.49); (6.22, 0.73)\n", + "Krunic (5.97, 0.38); (5.99, 0.43)\n", + "Cataldi (5.98, 0.35); (5.98, 0.38)\n", + "Strootman (5.96, 0.34); (6.01, 0.44)\n", + "Duncan (6.17, 0.43); (6.51, 0.74)\n", + "Freuler (5.94, 0.28); (5.94, 0.33)\n", + "Gagliardini (6.14, 0.47); (6.48, 0.77)\n", + "Mazzitelli (6.10, 0.68); (6.75, 1.31)\n", + "Jankto (5.94, 0.30); (5.94, 0.33)\n", + "Kastanos (5.94, 0.30); (6.02, 0.36)\n", + "Gyasi (5.69, 0.40); (5.70, 0.47)\n", + "Reinier (5.96, 0.47); (6.05, 0.59)\n", + "Zalewski (5.86, 0.34); (5.94, 0.41)\n", + "Harroui (6.17, 0.45); (6.52, 0.76)\n", + "Frendrup (6.04, 0.33); (6.14, 0.41)\n", + "Blin (5.95, 0.26); (5.95, 0.27)\n", + "Fabbian (5.94, 0.39); (6.17, 0.67)\n", + "Ramadani (6.09, 0.41); (6.21, 0.50)\n", + "Cajuste (5.96, 0.47); (6.02, 0.58)\n", + "Mancosu (5.89, 0.45); (5.92, 0.55)\n", + "Vecino (6.00, 0.48); (6.16, 0.68)\n", + "Sensi (6.14, 0.45); (6.48, 0.72)\n", + "Walace (5.81, 0.37); (5.76, 0.43)\n", + "Lopez M. (5.92, 0.42); (5.89, 0.47)\n", + "Brescianini (5.94, 0.32); (5.93, 0.34)\n", + "Bove (5.88, 0.41); (6.07, 0.58)\n", + "Aebischer (5.95, 0.30); (6.00, 0.37)\n", + "Thorstvedt (5.95, 0.33); (6.01, 0.39)\n", + "Gonzalez J. (5.89, 0.38); (5.95, 0.49)\n", + "Moro N. (6.02, 0.35); (6.17, 0.51)\n", + "Oudin (6.07, 0.46); (6.38, 0.75)\n", + "Boloca (5.99, 0.49); (6.05, 0.60)\n", + "Rafia (5.94, 0.33); (6.09, 0.47)\n", + "Makoumbou (5.90, 0.30); (5.92, 0.36)\n", + "Kaba (5.85, 0.37); (5.76, 0.39)\n", + "Badelj (5.87, 0.44); (5.83, 0.47)\n", + "Machin (5.94, 0.45); (6.02, 0.59)\n", + "Linetty (5.93, 0.35); (5.94, 0.40)\n", + "Castillejo (5.91, 0.34); (6.07, 0.46)\n", + "Rovella (6.04, 0.45); (6.13, 0.57)\n", + "Pobega (5.94, 0.26); (5.97, 0.30)\n", + "Hongla (5.93, 0.31); (5.92, 0.33)\n", + "Miretti (5.92, 0.32); (5.94, 0.37)\n", + "Fazzini (5.74, 0.36); (5.67, 0.37)\n", + "Iling Junior (6.00, 0.45); (6.12, 0.58)\n", + "Oristanio (5.90, 0.30); (5.88, 0.31)\n", + "Serdar (5.93, 0.33); (5.93, 0.37)\n", + "Payero (5.82, 0.38); (5.80, 0.45)\n", + "Grassi (5.76, 0.43); (5.68, 0.46)\n", + "Baez (5.89, 0.32); (5.86, 0.35)\n", + "Deiola (5.66, 0.40); (5.62, 0.43)\n", + "Garritano (6.10, 0.40); (6.18, 0.47)\n", + "Bourabia (5.96, 0.38); (6.01, 0.47)\n", + "Saelemaekers (5.86, 0.39); (6.00, 0.54)\n", + "Maldini (5.93, 0.42); (6.21, 0.67)\n", + "Racic (5.97, 0.35); (5.99, 0.39)\n", + "Kovalenko (5.86, 0.39); (5.83, 0.43)\n", + "Maleh (5.70, 0.47); (5.67, 0.56)\n", + "Bohinen (5.91, 0.26); (5.88, 0.26)\n", + "Ranocchia F. (6.01, 0.41); (6.25, 0.61)\n", + "Folorunsho (5.86, 0.43); (6.08, 0.64)\n", + "Infantino (5.96, 0.44); (5.99, 0.52)\n", + "Martegani (5.98, 0.37); (6.02, 0.45)\n", + "Kutlu (5.98, 0.44); (5.99, 0.48)\n", + "Tchatchoua (5.95, 0.44); (6.02, 0.57)\n", + "Quina (5.99, 0.40); (6.08, 0.52)\n", + "Adopo (6.00, 0.49); (6.10, 0.62)\n", + "Romero L. (6.00, 0.41); (6.12, 0.55)\n", + "Basic (5.97, 0.36); (6.03, 0.44)\n", + "Asllani (6.08, 0.40); (6.16, 0.46)\n", + "Tchaouna (5.88, 0.39); (5.89, 0.48)\n", + "Sulemana I. (5.75, 0.34); (5.69, 0.34)\n", + "Barrenechea (5.93, 0.34); (5.90, 0.35)\n", + "Gelli (5.97, 0.47); (6.03, 0.57)\n", + "Suslov (5.94, 0.33); (5.95, 0.38)\n", + "Gaetano (6.05, 0.47); (6.53, 0.90)\n", + "Jagiello (5.96, 0.46); (5.97, 0.51)\n", + "Obiang (5.92, 0.28); (5.90, 0.29)\n", + "Maggiore (5.91, 0.27); (5.88, 0.29)\n", + "Akpa Akpro (5.94, 0.45); (6.02, 0.59)\n", + "Urbanski (5.85, 0.42); (5.87, 0.54)\n", + "Volpato (5.96, 0.45); (6.10, 0.62)\n", + "Vignato S. (5.85, 0.39); (5.82, 0.45)\n", + "Hrustic (5.69, 0.30); (5.65, 0.30)\n", + "Zarraga (5.76, 0.43); (5.75, 0.51)\n", + "Camara E. (5.85, 0.45); (5.91, 0.60)\n", + "Amatucci (5.98, 0.47); (6.07, 0.60)\n", + "Pagano (6.09, 0.39); (6.23, 0.50)\n", + "Prati (5.92, 0.45); (5.95, 0.53)\n", + "Viola (5.92, 0.37); (5.92, 0.41)\n", + "Lulic K. (5.96, 0.47); (6.05, 0.59)\n", + "Rog (5.87, 0.36); (5.85, 0.39)\n", + "Nicolussi Caviglia (5.83, 0.49); (5.91, 0.63)\n", + "Demme (5.99, 0.27); (5.98, 0.24)\n", + "Pafundi (5.93, 0.40); (5.93, 0.45)\n", + "Adli (5.91, 0.44); (5.91, 0.52)\n", + "Bondo (5.96, 0.43); (6.03, 0.56)\n", + "Zerbin (5.93, 0.38); (5.93, 0.45)\n", + "Carboni V. (5.89, 0.46); (5.94, 0.59)\n", + "Faticanti (5.96, 0.45); (6.03, 0.58)\n", + "Gineitis (5.96, 0.42); (6.02, 0.53)\n", + "Belardinelli (5.81, 0.47); (5.86, 0.60)\n", + "El Azzouzi (5.88, 0.36); (5.84, 0.39)\n", + "Lipani (5.95, 0.44); (6.00, 0.55)\n", + "Joselito (5.95, 0.44); (6.02, 0.57)\n", + "Legowski (5.95, 0.47); (6.07, 0.64)\n", + "Ibrahimovic A. (5.96, 0.47); (6.05, 0.59)\n", "Osimhen (6.47, 0.76); (7.90, 2.05)\n", - "Martinez L. (6.50, 0.67); (7.94, 1.98)\n", - "Rafael Leao (6.43, 0.67); (7.72, 1.86)\n", - "Lukaku (6.33, 0.72); (7.50, 1.75)\n", - "Berardi (6.40, 0.71); (7.68, 1.89)\n", - "Immobile (6.14, 0.67); (6.99, 1.42)\n", - "Vlahovic (6.35, 0.74); (7.45, 1.76)\n", - "Dybala (6.43, 0.73); (7.78, 1.95)\n", - "Kvaratskhelia (6.40, 0.66); (7.57, 1.74)\n", - "Giroud (6.38, 0.66); (7.58, 1.77)\n", - "Scamacca (6.28, 0.73); (7.33, 1.67)\n", - "Thuram (6.47, 0.53); (7.27, 1.35)\n", - "Lookman (6.37, 0.70); (7.53, 1.78)\n", - "Dia (6.24, 0.72); (7.26, 1.61)\n", - "Arnautovic (6.36, 0.56); (7.18, 1.33)\n", - "Retegui (6.03, 0.65); (6.71, 1.21)\n", - "Sanabria (6.18, 0.60); (6.99, 1.34)\n", - "Nzola (5.99, 0.62); (6.63, 1.10)\n", - "Lauriente' (6.23, 0.61); (6.98, 1.36)\n", - "Zapata D. (5.96, 0.46); (6.29, 0.74)\n", - "Chiesa (6.41, 0.56); (7.25, 1.38)\n" + "Martinez L. (6.47, 0.71); (7.97, 2.04)\n", + "Rafael Leao (6.45, 0.63); (7.59, 1.68)\n", + "Lukaku (6.25, 0.74); (7.33, 1.65)\n", + "Berardi (6.48, 0.66); (7.77, 1.83)\n", + "Immobile (6.15, 0.65); (7.02, 1.41)\n", + "Vlahovic (6.34, 0.75); (7.49, 1.78)\n", + "Dybala (6.32, 0.76); (7.48, 1.77)\n", + "Kvaratskhelia (6.39, 0.64); (7.46, 1.64)\n", + "Giroud (6.38, 0.65); (7.56, 1.74)\n", + "Scamacca (6.31, 0.72); (7.47, 1.74)\n", + "Thuram (6.43, 0.58); (7.37, 1.47)\n", + "Lookman (6.37, 0.68); (7.55, 1.75)\n", + "Dia (6.26, 0.72); (7.39, 1.68)\n", + "Arnautovic (6.25, 0.50); (6.81, 1.02)\n", + "Retegui (6.15, 0.69); (7.05, 1.49)\n", + "Sanabria (6.04, 0.56); (6.68, 1.10)\n", + "Nzola (5.95, 0.54); (6.43, 0.91)\n", + "Lauriente' (6.32, 0.59); (7.11, 1.35)\n", + "Zapata D. (6.03, 0.44); (6.36, 0.74)\n", + "Chiesa (6.42, 0.59); (7.39, 1.50)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Milik (6.20, 0.50); (6.71, 0.99)\n", - "Gonzalez N. (6.25, 0.64); (7.23, 1.53)\n", - "Okafor (5.95, 0.29); (5.95, 0.31)\n", - "Pinamonti (5.93, 0.59); (6.45, 1.01)\n", - "Beltran L. (5.98, 0.55); (6.50, 0.95)\n", - "Caprari (5.98, 0.52); (6.40, 0.89)\n", - "Sanchez (6.18, 0.46); (6.61, 0.86)\n", - "Caputo (5.69, 0.46); (5.95, 0.61)\n", - "Toure' E. (5.97, 0.45); (6.11, 0.59)\n", - "Krstovic (6.26, 0.43); (6.63, 0.79)\n", - "Belotti (6.11, 0.49); (6.59, 0.93)\n", - "Muriel (6.13, 0.46); (6.50, 0.81)\n", - "Lapadula (5.99, 0.51); (6.44, 0.94)\n", - "Jovic (6.00, 0.59); (6.59, 1.07)\n", - "Abraham (6.19, 0.60); (6.98, 1.31)\n", - "Zirkzee (6.21, 0.50); (6.73, 1.00)\n", - "Ngonge (6.08, 0.58); (6.70, 1.13)\n", - "Petagna (5.94, 0.50); (6.35, 0.87)\n", - "Simeone (5.82, 0.49); (6.25, 0.75)\n", - "Deulofeu (6.30, 0.59); (7.13, 1.41)\n", - "Pedro (6.04, 0.48); (6.38, 0.79)\n", - "Shomurodov (5.75, 0.39); (5.96, 0.56)\n", - "Azmoun (5.89, 0.38); (6.14, 0.58)\n", - "Castellanos (5.96, 0.29); (5.95, 0.31)\n", - "Cheddira (6.12, 0.63); (6.86, 1.30)\n", - "Karlsson (6.10, 0.44); (6.46, 0.79)\n", - "Brekalo (6.05, 0.60); (6.69, 1.12)\n", - "Cambiaghi (5.99, 0.57); (6.53, 1.05)\n", - "Henry (5.86, 0.51); (6.22, 0.79)\n", - "Mulattieri (5.91, 0.39); (6.22, 0.68)\n", - "Almqvist (6.05, 0.54); (6.48, 0.91)\n", - "Isaksen (5.86, 0.42); (5.90, 0.51)\n", - "Kean (5.87, 0.57); (6.31, 0.93)\n", - "Karamoh (5.96, 0.41); (6.22, 0.64)\n", - "Thauvin (5.71, 0.34); (5.82, 0.42)\n", - "Kouame' (6.10, 0.63); (6.86, 1.28)\n", - "Raspadori (5.93, 0.53); (6.36, 0.85)\n", - "Colombo (5.91, 0.55); (6.39, 0.95)\n", - "Luvumbo (5.96, 0.37); (6.11, 0.52)\n", - "Mota (5.87, 0.54); (6.29, 0.88)\n", - "Brenner (5.81, 0.45); (5.90, 0.59)\n", - "Bonazzoli (5.99, 0.48); (6.37, 0.80)\n", - "Djuric (5.95, 0.35); (6.10, 0.47)\n", - "Davis K. (5.81, 0.45); (5.90, 0.59)\n", - "Banda (6.08, 0.44); (6.35, 0.69)\n", - "Defrel (5.75, 0.42); (5.96, 0.59)\n", - "Sansone (6.19, 0.56); (6.85, 1.19)\n", - "Pellegri (5.79, 0.41); (6.00, 0.58)\n", - "Piccoli (5.87, 0.41); (6.14, 0.63)\n", - "Success (5.87, 0.41); (6.09, 0.61)\n", - "Botheim (5.71, 0.35); (5.84, 0.47)\n", - "Lucca (5.81, 0.38); (5.95, 0.53)\n", - "Caso (6.13, 0.47); (6.53, 0.84)\n", - "Jovane (5.86, 0.48); (5.99, 0.64)\n", - "Soule' (6.25, 0.42); (6.54, 0.71)\n", - "Pavoletti (5.80, 0.38); (5.97, 0.55)\n", - "Cancellieri (5.60, 0.34); (5.54, 0.35)\n", - "Seck (6.11, 0.34); (6.22, 0.42)\n", - "Alvarez A. (5.86, 0.43); (6.14, 0.66)\n", - "Cuni (5.97, 0.32); (5.98, 0.35)\n", - "Ekuban (5.83, 0.35); (5.95, 0.41)\n", - "Maric (5.95, 0.34); (5.98, 0.40)\n", - "Cruz (5.88, 0.47); (6.00, 0.62)\n", - "Destro (5.62, 0.46); (5.66, 0.53)\n", - "Van Hooijdonk (5.94, 0.40); (6.06, 0.55)\n", - "Ceide (5.72, 0.40); (5.80, 0.44)\n", - "Kvernadze (5.91, 0.42); (5.97, 0.51)\n", - "Ikwuemesi (5.82, 0.40); (5.87, 0.48)\n", - "Puscas (5.90, 0.45); (5.94, 0.51)\n", - "Ake' M. (5.86, 0.39); (5.88, 0.48)\n", - "Braaf (5.64, 0.35); (5.74, 0.41)\n", - "Kallon (5.84, 0.41); (6.05, 0.59)\n", - "Kaio Jorge (5.92, 0.29); (5.94, 0.30)\n", - "Vivaldo (5.81, 0.45); (5.90, 0.59)\n", - "Bidaoui (5.93, 0.47); (6.04, 0.61)\n", - "Shpendi S. (5.67, 0.43); (5.65, 0.49)\n", - "Burnete (5.96, 0.40); (6.05, 0.52)\n", - "Corfitzen (5.91, 0.46); (6.03, 0.62)\n", - "Stewart (5.86, 0.48); (5.99, 0.64)\n", - "Yildiz (6.00, 0.44); (6.14, 0.58)\n" + "Milik (6.18, 0.46); (6.62, 0.88)\n", + "Gonzalez N. (6.37, 0.58); (7.27, 1.42)\n", + "Okafor (6.14, 0.46); (6.55, 0.84)\n", + "Pinamonti (5.99, 0.59); (6.57, 1.07)\n", + "Beltran L. (5.96, 0.45); (6.34, 0.76)\n", + "Caprari (6.04, 0.50); (6.40, 0.82)\n", + "Sanchez (6.03, 0.44); (6.45, 0.81)\n", + "Caputo (5.77, 0.46); (6.08, 0.68)\n", + "Toure' E. (6.00, 0.45); (6.14, 0.60)\n", + "Krstovic (6.27, 0.52); (6.87, 1.09)\n", + "Belotti (6.04, 0.51); (6.57, 0.96)\n", + "Muriel (6.19, 0.46); (6.58, 0.86)\n", + "Lapadula (5.99, 0.50); (6.52, 0.97)\n", + "Jovic (6.03, 0.58); (6.61, 1.06)\n", + "Abraham (6.07, 0.58); (6.78, 1.16)\n", + "Zirkzee (6.22, 0.47); (6.68, 0.92)\n", + "Ngonge (5.94, 0.54); (6.41, 0.91)\n", + "Petagna (5.95, 0.52); (6.39, 0.90)\n", + "Simeone (6.08, 0.61); (6.78, 1.20)\n", + "Deulofeu (6.29, 0.58); (7.11, 1.37)\n", + "Pedro (6.00, 0.45); (6.27, 0.69)\n", + "Shomurodov (5.72, 0.29); (5.68, 0.27)\n", + "Azmoun (5.88, 0.36); (6.14, 0.57)\n", + "Castellanos (6.06, 0.36); (6.13, 0.42)\n", + "Cheddira (6.14, 0.63); (6.89, 1.30)\n", + "Karlsson (5.95, 0.41); (6.26, 0.69)\n", + "Brekalo (6.08, 0.56); (6.64, 1.04)\n", + "Cambiaghi (5.92, 0.48); (6.20, 0.76)\n", + "Henry (5.83, 0.43); (6.09, 0.64)\n", + "Mulattieri (6.02, 0.35); (6.32, 0.65)\n", + "Almqvist (6.15, 0.53); (6.61, 0.96)\n", + "Isaksen (5.87, 0.45); (5.89, 0.55)\n", + "Kean (5.99, 0.57); (6.48, 1.02)\n", + "Karamoh (6.03, 0.39); (6.27, 0.60)\n", + "Thauvin (5.70, 0.34); (5.81, 0.44)\n", + "Kouame' (6.09, 0.59); (6.79, 1.20)\n", + "Raspadori (5.97, 0.50); (6.40, 0.85)\n", + "Colombo (5.87, 0.50); (6.25, 0.82)\n", + "Luvumbo (5.97, 0.33); (6.14, 0.50)\n", + "Mota (5.84, 0.49); (6.15, 0.74)\n", + "Brenner (5.87, 0.44); (5.95, 0.59)\n", + "Bonazzoli (5.94, 0.45); (6.27, 0.72)\n", + "Djuric (5.98, 0.26); (6.06, 0.30)\n", + "Davis K. (5.87, 0.44); (5.95, 0.59)\n", + "Banda (6.06, 0.40); (6.28, 0.60)\n", + "Defrel (5.75, 0.40); (5.94, 0.55)\n", + "Sansone (6.12, 0.46); (6.53, 0.84)\n", + "Pellegri (5.85, 0.34); (5.88, 0.39)\n", + "Piccoli (5.95, 0.32); (5.99, 0.37)\n", + "Success (5.85, 0.39); (6.05, 0.58)\n", + "Botheim (5.63, 0.35); (5.67, 0.38)\n", + "Lucca (5.73, 0.42); (5.94, 0.59)\n", + "Caso (6.09, 0.45); (6.48, 0.82)\n", + "Jovane (5.94, 0.47); (6.09, 0.66)\n", + "Soule' (6.30, 0.40); (6.65, 0.73)\n", + "Pavoletti (5.81, 0.37); (6.01, 0.56)\n", + "Cancellieri (5.78, 0.46); (5.88, 0.62)\n", + "Seck (6.09, 0.33); (6.21, 0.40)\n", + "Alvarez A. (5.92, 0.41); (6.17, 0.62)\n", + "Cuni (5.84, 0.38); (5.80, 0.40)\n", + "Ekuban (5.94, 0.30); (5.97, 0.30)\n", + "Maric (5.95, 0.24); (5.95, 0.25)\n", + "Cruz (5.94, 0.44); (6.07, 0.60)\n", + "Destro (5.67, 0.41); (5.73, 0.48)\n", + "Van Hooijdonk (6.00, 0.36); (6.09, 0.48)\n", + "Ceide (5.81, 0.38); (5.85, 0.39)\n", + "Kvernadze (5.89, 0.44); (5.91, 0.53)\n", + "Ikwuemesi (5.81, 0.36); (5.81, 0.40)\n", + "Puscas (5.94, 0.45); (5.96, 0.51)\n", + "Ake' M. (5.92, 0.37); (5.96, 0.46)\n", + "Braaf (5.68, 0.33); (5.78, 0.40)\n", + "Kallon (5.85, 0.40); (6.05, 0.55)\n", + "Kaio Jorge (5.92, 0.27); (5.92, 0.28)\n", + "Vivaldo (5.87, 0.44); (5.95, 0.59)\n", + "Bidaoui (5.96, 0.47); (6.08, 0.62)\n", + "Shpendi S. (5.88, 0.29); (5.90, 0.33)\n", + "Burnete (6.01, 0.45); (6.16, 0.61)\n", + "Corfitzen (5.97, 0.45); (6.10, 0.61)\n", + "Stewart (5.94, 0.47); (6.09, 0.66)\n", + "Yildiz (6.01, 0.46); (6.16, 0.60)\n" ] }, { @@ -7764,6 +7766,28 @@ " \n", " \n", " \n", + " Rossi F.\n", + " P\n", + " Atalanta\n", + " Avg\n", + " 1\n", + " 0\n", + " 0\n", + " 6.154525\n", + " 0.429769\n", + " 5.710340\n", + " 0.608428\n", + " 6.061085\n", + " 0.478673\n", + " 0.143872\n", + " 1.092386\n", + " 6.415344\n", + " 0.598177\n", + " -0.769786\n", + " 1.148949\n", + " 56.114355\n", + " \n", + " \n", " Musso\n", " P\n", " Atalanta\n", @@ -7771,19 +7795,19 @@ " 1\n", " 1\n", " 100\n", - " 6.171178\n", - " 0.427645\n", - " 5.716592\n", - " 0.632592\n", - " 6.120677\n", - " 0.493384\n", - " 0.075656\n", - " 1.078080\n", - " 6.470728\n", - " 0.603981\n", - " -0.807733\n", - " 1.135469\n", - " 58.570200\n", + " 6.154517\n", + " 0.430199\n", + " 5.707846\n", + " 0.608343\n", + " 6.060265\n", + " 0.478830\n", + " 0.145062\n", + " 1.092329\n", + " 6.411938\n", + " 0.599186\n", + " -0.767992\n", + " 1.148581\n", + " 56.005341\n", " \n", " \n", " Carnesecchi\n", @@ -7793,41 +7817,19 @@ " 1\n", " 0\n", " 0\n", - " 5.869667\n", - " 0.502827\n", - " 3.425929\n", - " 1.371020\n", - " 6.030291\n", - " 0.638892\n", - " -0.184642\n", - " 1.097941\n", - " 4.448452\n", - " 1.535484\n", - " -0.582005\n", - " 0.860812\n", - " 1.164914\n", - " \n", - " \n", - " Rossi F.\n", - " P\n", - " Atalanta\n", - " Avg\n", - " 1\n", - " 0\n", - " 0\n", - " 5.960478\n", - " 0.501686\n", - " 3.407276\n", - " 1.365965\n", - " 5.941229\n", - " 0.593570\n", - " 0.024161\n", - " 1.093842\n", - " 4.423328\n", - " 1.528818\n", - " -0.581675\n", - " 0.862571\n", - " 1.128720\n", + " 6.121501\n", + " 0.449849\n", + " 5.199359\n", + " 0.664409\n", + " 6.049285\n", + " 0.510774\n", + " 0.106278\n", + " 1.092119\n", + " 5.646819\n", + " 0.903720\n", + " -0.364365\n", + " 1.027859\n", + " 27.208376\n", " \n", " \n", " Zappacosta\n", @@ -7836,19 +7838,19 @@ " Avg\n", " 1\n", " 1\n", - " 100\n", - " 6.098510\n", - " 0.555344\n", - " 6.568691\n", - " 0.979324\n", - " 5.952041\n", - " 0.611557\n", - " 0.174813\n", - " 0.810975\n", - " 5.694494\n", - " 1.174959\n", - " 0.514689\n", - " 1.299705\n", + " 83\n", + " 6.106201\n", + " 0.489143\n", + " 6.430954\n", + " 0.784539\n", + " 6.056791\n", + " 0.560162\n", + " 0.064960\n", + " 0.877353\n", + " 5.846407\n", + " 1.045597\n", + " 0.398034\n", + " 1.299841\n", " 0.000000\n", " \n", " \n", @@ -7859,18 +7861,18 @@ " 1\n", " 1\n", " 100\n", - " 6.087699\n", - " 0.554154\n", - " 6.456921\n", - " 0.876787\n", - " 6.054248\n", - " 0.637605\n", - " 0.038587\n", - " 0.828000\n", - " 5.812500\n", - " 1.175351\n", - " 0.391089\n", - " 1.299670\n", + " 6.100199\n", + " 0.525928\n", + " 6.427830\n", + " 0.829378\n", + " 6.077005\n", + " 0.608189\n", + " 0.028110\n", + " 0.853873\n", + " 5.837552\n", + " 1.127070\n", + " 0.374861\n", + " 1.299839\n", " 0.000000\n", " \n", " \n", @@ -7902,63 +7904,19 @@ " Avg\n", " 1\n", " 0\n", - " 0\n", - " 5.855402\n", - " 0.505158\n", - " 6.219285\n", - " 0.793892\n", - " 5.594287\n", - " 0.513562\n", - " 0.367600\n", - " 0.835252\n", - " 5.435407\n", - " 0.871782\n", - " 0.604878\n", - " 1.299692\n", - " 0.000000\n", - " \n", - " \n", - " Djuric\n", - " A\n", - " Verona\n", - " Avg\n", - " 1\n", - " 0\n", - " 100\n", - " 5.948880\n", - " 0.348636\n", - " 6.099661\n", - " 0.472785\n", - " 5.886502\n", - " 0.392925\n", - " 0.117059\n", - " 0.988531\n", - " 5.772749\n", - " 0.649155\n", - " 0.361159\n", - " 1.299597\n", - " 0.000000\n", - " \n", - " \n", - " Kallon\n", - " A\n", - " Verona\n", - " Avg\n", - " 1\n", - " 0\n", - " 0\n", - " 5.837097\n", - " 0.413428\n", - " 6.047479\n", - " 0.594338\n", - " 5.662558\n", - " 0.429064\n", - " 0.295895\n", - " 0.922908\n", - " 5.502729\n", - " 0.699002\n", - " 0.535697\n", - " 1.299641\n", + " 16\n", + " 5.828518\n", + " 0.428970\n", + " 6.086343\n", + " 0.642557\n", + " 5.631263\n", + " 0.438163\n", + " 0.326536\n", + " 0.922681\n", + " 5.474199\n", + " 0.730840\n", + " 0.569787\n", + " 1.299849\n", " 0.000000\n", " \n", " \n", @@ -7969,18 +7927,62 @@ " 1\n", " 0\n", " 0\n", - " 5.879865\n", - " 0.465164\n", - " 6.001499\n", - " 0.617923\n", - " 5.876376\n", - " 0.544286\n", - " 0.004557\n", - " 0.915138\n", - " 5.675189\n", - " 0.915135\n", - " 0.260538\n", - " 1.299582\n", + " 5.943305\n", + " 0.444352\n", + " 6.065740\n", + " 0.598042\n", + " 5.949132\n", + " 0.523503\n", + " -0.009082\n", + " 0.938780\n", + " 5.746909\n", + " 0.884158\n", + " 0.262632\n", + " 1.299802\n", + " 0.000000\n", + " \n", + " \n", + " Djuric\n", + " A\n", + " Verona\n", + " Avg\n", + " 1\n", + " 0\n", + " 83\n", + " 5.982239\n", + " 0.258992\n", + " 6.061640\n", + " 0.304934\n", + " 6.023319\n", + " 0.321768\n", + " -0.094447\n", + " 1.112615\n", + " 5.956068\n", + " 0.481284\n", + " 0.161987\n", + " 1.299765\n", + " 0.000000\n", + " \n", + " \n", + " Kallon\n", + " A\n", + " Verona\n", + " Avg\n", + " 1\n", + " 0\n", + " 0\n", + " 5.851457\n", + " 0.400450\n", + " 6.050725\n", + " 0.551621\n", + " 5.690024\n", + " 0.416988\n", + " 0.281836\n", + " 0.953169\n", + " 5.551819\n", + " 0.655438\n", + " 0.524593\n", + " 1.299838\n", " 0.000000\n", " \n", " \n", @@ -7991,18 +7993,18 @@ " 1\n", " 0\n", " 0\n", - " 5.644437\n", - " 0.345748\n", - " 5.742957\n", - " 0.413469\n", - " 5.520224\n", - " 0.365075\n", - " 0.248614\n", - " 0.991181\n", - " 5.455955\n", - " 0.567369\n", - " 0.362917\n", - " 1.299570\n", + " 5.675430\n", + " 0.331933\n", + " 5.783349\n", + " 0.401081\n", + " 5.554506\n", + " 0.348108\n", + " 0.253766\n", + " 1.031060\n", + " 5.487167\n", + " 0.536615\n", + " 0.393338\n", + " 1.299812\n", " 0.000000\n", " \n", " \n", @@ -8013,64 +8015,64 @@ "text/plain": [ " role team oppteam home starter vote% MV MV std \\\n", "player \n", - "Musso P Atalanta Avg 1 1 100 6.171178 0.427645 \n", - "Carnesecchi P Atalanta Avg 1 0 0 5.869667 0.502827 \n", - "Rossi F. P Atalanta Avg 1 0 0 5.960478 0.501686 \n", - "Zappacosta D Atalanta Avg 1 1 100 6.098510 0.555344 \n", - "Ruggeri D Atalanta Avg 1 1 100 6.087699 0.554154 \n", + "Rossi F. P Atalanta Avg 1 0 0 6.154525 0.429769 \n", + "Musso P Atalanta Avg 1 1 100 6.154517 0.430199 \n", + "Carnesecchi P Atalanta Avg 1 0 0 6.121501 0.449849 \n", + "Zappacosta D Atalanta Avg 1 1 83 6.106201 0.489143 \n", + "Ruggeri D Atalanta Avg 1 1 100 6.100199 0.525928 \n", "... ... ... ... ... ... ... ... ... \n", - "Henry A Verona Avg 1 0 0 5.855402 0.505158 \n", - "Djuric A Verona Avg 1 0 100 5.948880 0.348636 \n", - "Kallon A Verona Avg 1 0 0 5.837097 0.413428 \n", - "Cruz A Verona Avg 1 0 0 5.879865 0.465164 \n", - "Braaf A Verona Avg 1 0 0 5.644437 0.345748 \n", + "Henry A Verona Avg 1 0 16 5.828518 0.428970 \n", + "Cruz A Verona Avg 1 0 0 5.943305 0.444352 \n", + "Djuric A Verona Avg 1 0 83 5.982239 0.258992 \n", + "Kallon A Verona Avg 1 0 0 5.851457 0.400450 \n", + "Braaf A Verona Avg 1 0 0 5.675430 0.331933 \n", "\n", " FV FV std MV loc MV scale MV skewness \\\n", "player \n", - "Musso 5.716592 0.632592 6.120677 0.493384 0.075656 \n", - "Carnesecchi 3.425929 1.371020 6.030291 0.638892 -0.184642 \n", - "Rossi F. 3.407276 1.365965 5.941229 0.593570 0.024161 \n", - "Zappacosta 6.568691 0.979324 5.952041 0.611557 0.174813 \n", - "Ruggeri 6.456921 0.876787 6.054248 0.637605 0.038587 \n", + "Rossi F. 5.710340 0.608428 6.061085 0.478673 0.143872 \n", + "Musso 5.707846 0.608343 6.060265 0.478830 0.145062 \n", + "Carnesecchi 5.199359 0.664409 6.049285 0.510774 0.106278 \n", + "Zappacosta 6.430954 0.784539 6.056791 0.560162 0.064960 \n", + "Ruggeri 6.427830 0.829378 6.077005 0.608189 0.028110 \n", "... ... ... ... ... ... \n", - "Henry 6.219285 0.793892 5.594287 0.513562 0.367600 \n", - "Djuric 6.099661 0.472785 5.886502 0.392925 0.117059 \n", - "Kallon 6.047479 0.594338 5.662558 0.429064 0.295895 \n", - "Cruz 6.001499 0.617923 5.876376 0.544286 0.004557 \n", - "Braaf 5.742957 0.413469 5.520224 0.365075 0.248614 \n", + "Henry 6.086343 0.642557 5.631263 0.438163 0.326536 \n", + "Cruz 6.065740 0.598042 5.949132 0.523503 -0.009082 \n", + "Djuric 6.061640 0.304934 6.023319 0.321768 -0.094447 \n", + "Kallon 6.050725 0.551621 5.690024 0.416988 0.281836 \n", + "Braaf 5.783349 0.401081 5.554506 0.348108 0.253766 \n", "\n", " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", "player \n", - "Musso 1.078080 6.470728 0.603981 -0.807733 1.135469 \n", - "Carnesecchi 1.097941 4.448452 1.535484 -0.582005 0.860812 \n", - "Rossi F. 1.093842 4.423328 1.528818 -0.581675 0.862571 \n", - "Zappacosta 0.810975 5.694494 1.174959 0.514689 1.299705 \n", - "Ruggeri 0.828000 5.812500 1.175351 0.391089 1.299670 \n", + "Rossi F. 1.092386 6.415344 0.598177 -0.769786 1.148949 \n", + "Musso 1.092329 6.411938 0.599186 -0.767992 1.148581 \n", + "Carnesecchi 1.092119 5.646819 0.903720 -0.364365 1.027859 \n", + "Zappacosta 0.877353 5.846407 1.045597 0.398034 1.299841 \n", + "Ruggeri 0.853873 5.837552 1.127070 0.374861 1.299839 \n", "... ... ... ... ... ... \n", - "Henry 0.835252 5.435407 0.871782 0.604878 1.299692 \n", - "Djuric 0.988531 5.772749 0.649155 0.361159 1.299597 \n", - "Kallon 0.922908 5.502729 0.699002 0.535697 1.299641 \n", - "Cruz 0.915138 5.675189 0.915135 0.260538 1.299582 \n", - "Braaf 0.991181 5.455955 0.567369 0.362917 1.299570 \n", + "Henry 0.922681 5.474199 0.730840 0.569787 1.299849 \n", + "Cruz 0.938780 5.746909 0.884158 0.262632 1.299802 \n", + "Djuric 1.112615 5.956068 0.481284 0.161987 1.299765 \n", + "Kallon 0.953169 5.551819 0.655438 0.524593 1.299838 \n", + "Braaf 1.031060 5.487167 0.536615 0.393338 1.299812 \n", "\n", " Clean Sheet % \n", "player \n", - "Musso 58.570200 \n", - "Carnesecchi 1.164914 \n", - "Rossi F. 1.128720 \n", + "Rossi F. 56.114355 \n", + "Musso 56.005341 \n", + "Carnesecchi 27.208376 \n", "Zappacosta 0.000000 \n", "Ruggeri 0.000000 \n", "... ... \n", "Henry 0.000000 \n", + "Cruz 0.000000 \n", "Djuric 0.000000 \n", "Kallon 0.000000 \n", - "Cruz 0.000000 \n", "Braaf 0.000000 \n", "\n", "[539 rows x 19 columns]" ] }, - "execution_count": 45, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -8161,7 +8163,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 36, "id": "b47cbd63", "metadata": {}, "outputs": [], @@ -8261,7 +8263,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 37, "id": "4b9f5a7d", "metadata": {}, "outputs": [ @@ -8269,20 +8271,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "Osimhen: MV 6.52 ± 1.55; FV 8.32 + 5.10\n", - "Osimhen: MV 6.52 ± 1.55; FV 8.31 + 5.09\n" + "Osimhen: MV 6.47 ± 1.49; FV 7.95 + 4.15\n", + "Osimhen: MV 6.48 ± 1.46; FV 8.08 + 4.29\n" ] }, { "data": { "text/plain": [ - "[array([6.5154007 , 8.31434958]),\n", - " array([0.7731867, 2.543137 ], dtype=float32),\n", + "[array([6.48246781, 8.07706693]),\n", + " array([0.72848487, 2.14604 ], dtype=float32),\n", " [,\n", " ]]" ] }, - "execution_count": 55, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } diff --git a/.ipynb_checkpoints/7_lineup_simulation-checkpoint.ipynb b/.ipynb_checkpoints/7_lineup_simulation-checkpoint.ipynb index 7f84e58..27462ed 100644 --- a/.ipynb_checkpoints/7_lineup_simulation-checkpoint.ipynb +++ b/.ipynb_checkpoints/7_lineup_simulation-checkpoint.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "0d54533f", "metadata": {}, "outputs": [], @@ -25,7 +25,7 @@ "metadata": {}, "outputs": [], "source": [ - "file = 'outputs/pred_matchday_32.xlsx'" + "file = 'outputs/pred_matchday_7.xlsx'" ] }, { @@ -110,113 +110,113 @@ " \n", " \n", " \n", - " Sportiello\n", + " Carnesecchi\n", " P\n", " Atalanta\n", - " Torino\n", - " 0\n", - " 1.00\n", - " 75\n", - " 6.241850\n", - " 0.413980\n", - " 5.903749\n", - " 0.357296\n", - " 5.997854\n", - " 0.249647\n", - " 0.623392\n", - " 1.589839\n", - " 6.211304\n", - " 0.449493\n", - " -0.482876\n", - " 1.126529\n", - " 72.505307\n", + " Juventus\n", + " 1\n", + " 0.0\n", + " 5\n", + " 6.140590\n", + " 0.481707\n", + " 5.070139\n", + " 0.715923\n", + " 5.980216\n", + " 0.509892\n", + " 0.230396\n", + " 1.086084\n", + " 5.321455\n", + " 1.055452\n", + " -0.174796\n", + " 0.965320\n", + " 20.727640\n", " \n", " \n", " Musso\n", " P\n", " Atalanta\n", - " Torino\n", - " 0\n", - " 0.00\n", - " 5\n", - " 6.244259\n", - " 0.413018\n", - " 4.951720\n", - " 0.501229\n", - " 6.001830\n", - " 0.251322\n", - " 0.617146\n", - " 1.589903\n", - " 5.410236\n", - " 0.623711\n", - " -0.518807\n", - " 1.010690\n", - " 8.606489\n", + " Juventus\n", + " 1\n", + " 1.0\n", + " 70\n", + " 6.171150\n", + " 0.480294\n", + " 5.038867\n", + " 0.684976\n", + " 5.986030\n", + " 0.494852\n", + " 0.272883\n", + " 1.084060\n", + " 5.255883\n", + " 1.019420\n", + " -0.156479\n", + " 0.983446\n", + " 28.833491\n", " \n", " \n", " Rossi F.\n", " P\n", " Atalanta\n", - " Torino\n", - " 0\n", - " 0.00\n", + " Juventus\n", " 1\n", - " 6.244349\n", - " 0.411884\n", - " 4.080916\n", - " 0.677007\n", - " 6.003743\n", - " 0.253224\n", - " 0.610014\n", - " 1.589935\n", - " 4.909296\n", - " 0.706557\n", - " -0.788786\n", - " 0.969051\n", - " 0.049822\n", + " 0.0\n", + " 1\n", + " 6.170296\n", + " 0.480470\n", + " 5.037872\n", + " 0.684438\n", + " 5.984473\n", + " 0.494652\n", + " 0.273999\n", + " 1.084374\n", + " 5.254371\n", + " 1.018776\n", + " -0.156209\n", + " 0.983780\n", + " 28.943959\n", + " \n", + " \n", + " Zappacosta\n", + " D\n", + " Atalanta\n", + " Juventus\n", + " 1\n", + " 1.0\n", + " 90\n", + " 5.985259\n", + " 0.522062\n", + " 6.206951\n", + " 0.733274\n", + " 6.001576\n", + " 0.613546\n", + " -0.019559\n", + " 0.881605\n", + " 5.760596\n", + " 1.050439\n", + " 0.307981\n", + " 1.299815\n", + " 0.000000\n", " \n", " \n", " Toloi\n", " D\n", " Atalanta\n", - " Torino\n", - " 0\n", - " 1.00\n", + " Juventus\n", + " 1\n", + " 1.0\n", " 90\n", - " 6.048618\n", - " 0.485807\n", - " 6.310797\n", - " 0.700896\n", - " 6.011822\n", - " 0.564263\n", - " 0.048119\n", - " 0.996258\n", - " 5.822867\n", - " 0.983389\n", - " 0.352009\n", - " 1.599878\n", - " 0.000000\n", - " \n", - " \n", - " Scalvini\n", - " D\n", - " Atalanta\n", - " Torino\n", - " 0\n", - " 1.00\n", - " 90\n", - " 6.030435\n", - " 0.486777\n", - " 6.289715\n", - " 0.711306\n", - " 5.994397\n", - " 0.565685\n", - " 0.047012\n", - " 0.997348\n", - " 5.786789\n", - " 0.989334\n", - " 0.359811\n", - " 1.599874\n", + " 6.002894\n", + " 0.499877\n", + " 6.196084\n", + " 0.699952\n", + " 6.035264\n", + " 0.591494\n", + " -0.040256\n", + " 0.892304\n", + " 5.804792\n", + " 1.025037\n", + " 0.278035\n", + " 1.299814\n", " 0.000000\n", " \n", " \n", @@ -242,178 +242,178 @@ " ...\n", " \n", " \n", - " Gaich\n", + " Henry\n", " A\n", " Verona\n", - " Cremonese\n", + " Torino\n", " 0\n", - " 0.55\n", - " 55\n", - " 5.928611\n", - " 0.484392\n", - " 6.232841\n", - " 0.773308\n", - " 5.828736\n", - " 0.541676\n", - " 0.135760\n", - " 1.016715\n", - " 5.588240\n", - " 0.952320\n", - " 0.462596\n", - " 1.599856\n", + " 0.4\n", + " 60\n", + " 5.839920\n", + " 0.444240\n", + " 6.116677\n", + " 0.669289\n", + " 5.631952\n", + " 0.453545\n", + " 0.332464\n", + " 0.906913\n", + " 5.474079\n", + " 0.755754\n", + " 0.577176\n", + " 1.299852\n", " 0.000000\n", " \n", " \n", " Djuric\n", " A\n", " Verona\n", - " Cremonese\n", + " Torino\n", " 0\n", - " 0.45\n", - " 60\n", - " 6.043846\n", - " 0.364231\n", - " 6.231350\n", - " 0.482569\n", - " 5.988944\n", - " 0.416682\n", - " 0.097463\n", - " 1.133835\n", - " 5.930100\n", - " 0.713364\n", - " 0.303606\n", - " 1.599914\n", + " 0.0\n", + " 0\n", + " 5.988754\n", + " 0.256611\n", + " 6.065000\n", + " 0.293257\n", + " 6.035156\n", + " 0.320372\n", + " -0.107045\n", + " 1.115607\n", + " 5.977599\n", + " 0.469125\n", + " 0.137929\n", + " 1.299758\n", " 0.000000\n", " \n", " \n", " Kallon\n", " A\n", " Verona\n", - " Cremonese\n", + " Torino\n", " 0\n", - " 0.00\n", - " 40\n", - " 5.919705\n", - " 0.419731\n", - " 6.153088\n", - " 0.630338\n", - " 5.839579\n", - " 0.472310\n", - " 0.125181\n", - " 1.084553\n", - " 5.652873\n", - " 0.810479\n", - " 0.427306\n", - " 1.599881\n", + " 0.0\n", + " 0\n", + " 5.863674\n", + " 0.392202\n", + " 6.044829\n", + " 0.522801\n", + " 5.719528\n", + " 0.414042\n", + " 0.254175\n", + " 0.962003\n", + " 5.592772\n", + " 0.641898\n", + " 0.490306\n", + " 1.299833\n", + " 0.000000\n", + " \n", + " \n", + " Cruz\n", + " A\n", + " Verona\n", + " Torino\n", + " 0\n", + " 0.0\n", + " 15\n", + " 5.932667\n", + " 0.434699\n", + " 5.990185\n", + " 0.538253\n", + " 6.015219\n", + " 0.528602\n", + " -0.114888\n", + " 0.951150\n", + " 5.878494\n", + " 0.880338\n", + " 0.094197\n", + " 1.299773\n", " 0.000000\n", " \n", " \n", " Braaf\n", " A\n", " Verona\n", - " Cremonese\n", + " Torino\n", " 0\n", - " 0.00\n", - " 35\n", - " 5.899851\n", - " 0.388650\n", - " 5.974370\n", - " 0.471126\n", - " 5.875201\n", - " 0.457090\n", - " 0.039928\n", - " 1.106565\n", - " 5.744820\n", - " 0.753911\n", - " 0.222862\n", - " 1.599918\n", - " 0.000000\n", - " \n", - " \n", - " Lasagna\n", - " A\n", - " Verona\n", - " Cremonese\n", + " 0.0\n", " 0\n", - " 1.00\n", - " 80\n", - " 5.756107\n", - " 0.397228\n", - " 5.825053\n", - " 0.519855\n", - " 5.704176\n", - " 0.457359\n", - " 0.083996\n", - " 1.116621\n", - " 5.460384\n", - " 0.726297\n", - " 0.355810\n", - " 1.599896\n", + " 5.665697\n", + " 0.341006\n", + " 5.725323\n", + " 0.370040\n", + " 5.561785\n", + " 0.367506\n", + " 0.207320\n", + " 1.019125\n", + " 5.506973\n", + " 0.534618\n", + " 0.296589\n", + " 1.299793\n", " 0.000000\n", " \n", " \n", "\n", - "

525 rows × 19 columns

\n", + "

539 rows × 19 columns

\n", "" ], "text/plain": [ - " role team oppteam home starter vote% MV \\\n", + " role team oppteam home starter vote% MV \\\n", "player \n", - "Sportiello P Atalanta Torino 0 1.00 75 6.241850 \n", - "Musso P Atalanta Torino 0 0.00 5 6.244259 \n", - "Rossi F. P Atalanta Torino 0 0.00 1 6.244349 \n", - "Toloi D Atalanta Torino 0 1.00 90 6.048618 \n", - "Scalvini D Atalanta Torino 0 1.00 90 6.030435 \n", - "... ... ... ... ... ... ... ... \n", - "Gaich A Verona Cremonese 0 0.55 55 5.928611 \n", - "Djuric A Verona Cremonese 0 0.45 60 6.043846 \n", - "Kallon A Verona Cremonese 0 0.00 40 5.919705 \n", - "Braaf A Verona Cremonese 0 0.00 35 5.899851 \n", - "Lasagna A Verona Cremonese 0 1.00 80 5.756107 \n", + "Carnesecchi P Atalanta Juventus 1 0.0 5 6.140590 \n", + "Musso P Atalanta Juventus 1 1.0 70 6.171150 \n", + "Rossi F. P Atalanta Juventus 1 0.0 1 6.170296 \n", + "Zappacosta D Atalanta Juventus 1 1.0 90 5.985259 \n", + "Toloi D Atalanta Juventus 1 1.0 90 6.002894 \n", + "... ... ... ... ... ... ... ... \n", + "Henry A Verona Torino 0 0.4 60 5.839920 \n", + "Djuric A Verona Torino 0 0.0 0 5.988754 \n", + "Kallon A Verona Torino 0 0.0 0 5.863674 \n", + "Cruz A Verona Torino 0 0.0 15 5.932667 \n", + "Braaf A Verona Torino 0 0.0 0 5.665697 \n", "\n", - " MV std FV FV std MV loc MV scale MV skewness \\\n", - "player \n", - "Sportiello 0.413980 5.903749 0.357296 5.997854 0.249647 0.623392 \n", - "Musso 0.413018 4.951720 0.501229 6.001830 0.251322 0.617146 \n", - "Rossi F. 0.411884 4.080916 0.677007 6.003743 0.253224 0.610014 \n", - "Toloi 0.485807 6.310797 0.700896 6.011822 0.564263 0.048119 \n", - "Scalvini 0.486777 6.289715 0.711306 5.994397 0.565685 0.047012 \n", - "... ... ... ... ... ... ... \n", - "Gaich 0.484392 6.232841 0.773308 5.828736 0.541676 0.135760 \n", - "Djuric 0.364231 6.231350 0.482569 5.988944 0.416682 0.097463 \n", - "Kallon 0.419731 6.153088 0.630338 5.839579 0.472310 0.125181 \n", - "Braaf 0.388650 5.974370 0.471126 5.875201 0.457090 0.039928 \n", - "Lasagna 0.397228 5.825053 0.519855 5.704176 0.457359 0.083996 \n", + " MV std FV FV std MV loc MV scale MV skewness \\\n", + "player \n", + "Carnesecchi 0.481707 5.070139 0.715923 5.980216 0.509892 0.230396 \n", + "Musso 0.480294 5.038867 0.684976 5.986030 0.494852 0.272883 \n", + "Rossi F. 0.480470 5.037872 0.684438 5.984473 0.494652 0.273999 \n", + "Zappacosta 0.522062 6.206951 0.733274 6.001576 0.613546 -0.019559 \n", + "Toloi 0.499877 6.196084 0.699952 6.035264 0.591494 -0.040256 \n", + "... ... ... ... ... ... ... \n", + "Henry 0.444240 6.116677 0.669289 5.631952 0.453545 0.332464 \n", + "Djuric 0.256611 6.065000 0.293257 6.035156 0.320372 -0.107045 \n", + "Kallon 0.392202 6.044829 0.522801 5.719528 0.414042 0.254175 \n", + "Cruz 0.434699 5.990185 0.538253 6.015219 0.528602 -0.114888 \n", + "Braaf 0.341006 5.725323 0.370040 5.561785 0.367506 0.207320 \n", "\n", - " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", - "player \n", - "Sportiello 1.589839 6.211304 0.449493 -0.482876 1.126529 \n", - "Musso 1.589903 5.410236 0.623711 -0.518807 1.010690 \n", - "Rossi F. 1.589935 4.909296 0.706557 -0.788786 0.969051 \n", - "Toloi 0.996258 5.822867 0.983389 0.352009 1.599878 \n", - "Scalvini 0.997348 5.786789 0.989334 0.359811 1.599874 \n", - "... ... ... ... ... ... \n", - "Gaich 1.016715 5.588240 0.952320 0.462596 1.599856 \n", - "Djuric 1.133835 5.930100 0.713364 0.303606 1.599914 \n", - "Kallon 1.084553 5.652873 0.810479 0.427306 1.599881 \n", - "Braaf 1.106565 5.744820 0.753911 0.222862 1.599918 \n", - "Lasagna 1.116621 5.460384 0.726297 0.355810 1.599896 \n", + " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", + "player \n", + "Carnesecchi 1.086084 5.321455 1.055452 -0.174796 0.965320 \n", + "Musso 1.084060 5.255883 1.019420 -0.156479 0.983446 \n", + "Rossi F. 1.084374 5.254371 1.018776 -0.156209 0.983780 \n", + "Zappacosta 0.881605 5.760596 1.050439 0.307981 1.299815 \n", + "Toloi 0.892304 5.804792 1.025037 0.278035 1.299814 \n", + "... ... ... ... ... ... \n", + "Henry 0.906913 5.474079 0.755754 0.577176 1.299852 \n", + "Djuric 1.115607 5.977599 0.469125 0.137929 1.299758 \n", + "Kallon 0.962003 5.592772 0.641898 0.490306 1.299833 \n", + "Cruz 0.951150 5.878494 0.880338 0.094197 1.299773 \n", + "Braaf 1.019125 5.506973 0.534618 0.296589 1.299793 \n", "\n", - " Clean Sheet % \n", - "player \n", - "Sportiello 72.505307 \n", - "Musso 8.606489 \n", - "Rossi F. 0.049822 \n", - "Toloi 0.000000 \n", - "Scalvini 0.000000 \n", - "... ... \n", - "Gaich 0.000000 \n", - "Djuric 0.000000 \n", - "Kallon 0.000000 \n", - "Braaf 0.000000 \n", - "Lasagna 0.000000 \n", + " Clean Sheet % \n", + "player \n", + "Carnesecchi 20.727640 \n", + "Musso 28.833491 \n", + "Rossi F. 28.943959 \n", + "Zappacosta 0.000000 \n", + "Toloi 0.000000 \n", + "... ... \n", + "Henry 0.000000 \n", + "Djuric 0.000000 \n", + "Kallon 0.000000 \n", + "Cruz 0.000000 \n", + "Braaf 0.000000 \n", "\n", - "[525 rows x 19 columns]" + "[539 rows x 19 columns]" ] }, "execution_count": 5, @@ -641,59 +641,27 @@ { "cell_type": "code", "execution_count": 9, - "id": "c8fa1df8", + "id": "dda9acb8", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "squad = ['Szczesny',\n", - " 'Di Lorenzo',\n", - " 'Kim',\n", - " 'Juan Jesus',\n", - " 'Carlos Augusto',\n", - " 'Kostic',\n", - " 'Frattesi',\n", - " 'Barella',\n", - " 'Strefezza',\n", - " 'Rafael Leao',\n", - " 'Lauriente\\'']\n", - "\n", "config_442 = [3, 6, 7, 9, 10, 15, 17, 19, 21, 27, 29];\n", - "\n", - "s = simulate_lineup(squad)\n", - "\n", - "plot_lineup(squad, config_442)" + "config_433 = [3, 6, 7, 9, 10, 13, 17, 19, 26, 28, 30];\n", + "config_343 = [3, 7, 8, 9, 11, 15, 17, 19, 26, 28, 30];\n", + "config_4231 = [3, 6, 7, 9, 10, 12, 19, 23, 25, 26, 28];\n", + "config_433_classic = [3, 6, 7, 9, 10, 17, 18, 19, 26, 28, 30];\n", + "config_343_classic = [3, 7, 8, 9, 16, 17, 19, 20, 26, 28, 30];" ] }, { "cell_type": "code", "execution_count": 10, - "id": "1a4fd2fe", + "id": "beea77cf", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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ffvpJrTs0NDRbl2CtVkvPnj3x8vLC0tISPz8/5s2bV+Dn4lmcP3+eu3fvMnnyZPz8/KhcuTITJkwgISGB2NhYvbJjx46lYsWKdOjQ4Yn13rp1i0uXLjFy5EiqVauGj48P06dPJzU1lT/++EOvrIODA66ururN0tKyUK9RCCGEEEXPcH6uF+I5srS01EscDJWpqSkhISFFHcYzmTZtWq77fHx86NKli/p41qxZuS7j4+HhofdczJs3L8eliSZMmFDgGFetWkXPnj05ceIE4eHh9O7dGw8PD3r16gVkdcu9ePEi27dvx87Ojs8//5yWLVsSFRVFUFAQc+fOZfz48Zw/fx4AGxsbAD766CNiYmLYsGEDpUuX5scff6R58+acO3cOHx8fIGt5pVmzZrFmzRqMjIz44IMPGDZsGGvXrmXYsGFER0eTlJTEihUrAChRogTXr1/Xi1+n01G2bFk2bdpEyZIlCQsLo3fv3ri5ueUrKQSIjY3F398/zzIffPBBrt1s/fz8KFmyJMuWLWP06NFotVqWLVtG5cqV8fDwUMsdPHiQH374gcjISLZu3frEuJycnKhUqRKrV68mICAAc3NzFi9eTKlSpahVq5Ze2QEDBvDxxx/j5eVFz5496d27t0H/ICWEEEKIgpOEVQhR7Li7uzNnzhw0Gg1+fn6cO3eOOXPm0KtXLzVR/fXXXwkKCgJg7dq1uLu7s23bNt5//33s7e3RaDS4urqqdV6+fJn169fz999/U7p0aQCGDRvG7t27WbFiBVOnTgWyuscuWrSIChUqAFlJ1+TJk4GsxNfS0pK0tDS9uv/N1NSUSZMmqY+9vLwICwtj06ZN+U5YS5cu/cRJnOzs7HLdZ2trS2hoKG3btmXKlCkA+Pr6smfPHrXr8u3btwkJCeH777/Ps67HaTQa9u3bR9u2bbG1tcXIyIhSpUqxe/duvfGvU6ZMoXHjxlhaWnLgwAGGDh3KrVu3GDt2bL7OI4QQQoiXgySsQohCNWrUqFz3/bv1a9iwYbmW/XeX6M8+++zZAnvMG2+8oVd/YGAgs2fPRqvVEh0djYmJCXXq1FH3Ozk54efnR3R0dK51nj59GkVR8PX11duelpaGk5OT+tjKykpNVgHc3NxISEgo8DUsWrSIpUuXcu3aNR48eEB6ejo1atTI9/EmJiZ4e3sX+LyPPHjwgB49elC3bl3Wr1+PVqtl1qxZtGzZklOnTmFpaUmvXr3o0qUL9evXz3e9iqLQr18/XFxcOHLkCJaWlixdupTWrVtz6tQp3NzcAPQS00fXPXnyZElYhRBCiFeMJKyiWEhJScHT0xPIWiLE2tq6aAPKRXp6ujoW8bPPPsPMzKyIIyq4gsT8vMo+i8fHsv57e17jinU6HcbGxkRERGBsbKy371GXYchqHX2cRqPJ9Zy52bRpE4MHD2b27NkEBgZia2vLzJkzOXHiRL7reNYuwevWrSMmJoZjx46pP0SsW7cOR0dHfvrpJzp16sTBgwfZvn07s2bNArKeQ51Oh4mJCd999x09evTIVu/BgwfZsWMHd+/eVVtlFyxYwL59+1i1ahUjR47MMZ433niDpKQkbty4QalSpfL9PAghhBDCsEnCKoqNW7duFXUI+ZLTOE1RuI4fP57tsY+PD8bGxvj7+5OZmcmJEyfULsG3b9/mwoULVKpUCchKnrVarV4dNWvWRKvVkpCQkO/ZcHOSU93/duTIEYKCgujXr5+67fLlywU6z7N2CU5NTcXIyEgviX/0WKfTAXDs2DG9a/npp5+YMWMGYWFhlClTJtd6H9X1OCMjI7XenJw5cwYLC4vnttyQEEIIIYqGJKxCiGLnr7/+YsiQIXzyySecPn2a+fPnM3v2bCBrYqi2bdvSq1cvFi9ejK2tLSNHjqRMmTK0bdsWAE9PT5KTkzlw4ADVq1fHysoKX19funbtSvfu3Zk9ezY1a9bk1q1bHDx4kKpVq9KyZct8xebp6cmePXs4f/48Tk5O2NvbZyvj7e3N6tWr2bNnD15eXqxZs4ZTp07h5eWV7+fgWbsEN23alOHDh9O/f38GDhyITqdj+vTpmJiY0KhRIwA1wX8kPDwcIyMjvfVkT548Sffu3Tlw4ABlypQhMDAQR0dHPvzwQ8aPH4+lpSVLlizh6tWrtGrVCoCff/6Z+Ph4AgMDsbS05NChQ4wZM4bevXtjbm7+1NckhBBCCMMj0ykKIYqd7t278+DBA15//XU14erdu7e6f8WKFdSqVYvWrVsTGBiIoijs3LlT7c4bFBREnz596NixI87Oznz55Zfqcd27d2fo0KH4+fnx9ttvc+LECdzd3fMdW69evfDz86N27do4Ozvz66+/ZivTp08f3n33XTp27EidOnW4ffu2Xmvri1CxYkV+/vlnfvvtNwIDA6lXrx7Xr19n9+7d6jjT/EhNTeX8+fPqbNElS5Zk9+7dJCcn89Zbb1G7dm2OHj3KTz/9RPXq1YGsbtULFiwgMDCQatWqMW/ePCZPnqz+6CCEEEKIV4dGKejgKQOVlJSEvb09iYmJ+Z6NUhQfKSkp6jjC5ORkgx7D+mhZmFGjRhnsGNaHDx9y9epVvLy8sLCwKOpwCqRhw4bUqFGDuXPnFnUo4gXK6zUrnx9CCCGE4ZIWViGEEEIIIYQQBkkSViGEEEIIIYQQBkkmXRLFgpGREbVr11bvGyqNRkPp0qXV+6LwhYaGFnUIQgghhBAinyRhFcWCpaUlp06dKuownsjU1JRevXoVdRhCCCGEEEIYBMNtahJCGLxXZM42UQzIa1UIIYR4OUnCKoQosEfLu6SmphZxJELkz6PX6qPXrhBCCCFeDtIlWBQLqamp+Pv7AxAVFYWVlVURR5SzjIwMvv32WwD69+9vsF+ujY2NcXBwICEhAQArKysZcysMkqIopKamkpCQgIODA8bGxkUdkhBCCCEKQBJWUSwoisK1a9fU+4ZKURQSExPV+4bM1dUVQE1ahTBkDg4O6mtWCCGEEC8PSViFEE9Fo9Hg5uaGi4sLGRkZRR2OELkyNTWVllUhhBDiJSUJqxDimRgbG0syIIQQQgghnguZdEkIIYQQQgghhEGShFUIIYQQQgghhEF6qoR1wYIFeHl5YWFhQa1atThy5EiuZePi4ujSpQt+fn4YGRkxaNCgHMtt2bIFf39/zM3N8ff358cff3ya0IQQQgghhBBCvCIKnLBu3LiRQYMGMWbMGM6cOUO9evVo0aIFsbGxOZZPS0vD2dmZMWPGUL169RzLHDt2jI4dO9KtWzfOnj1Lt27d6NChAydOnChoeELkSKPR4O/vj7+/v0Evv6LRaHB2dsbZ2dmg4xRCCCGEEOJF0CgFXDujTp06BAQEsHDhQnVbpUqVaNeuHdOmTcvz2IYNG1KjRg3mzp2rt71jx44kJSWxa9cudVvz5s1xdHRk/fr1OdaVlpZGWlqa+jgpKQl3d3cSExOxs7MryCUJIYQoxpKSkrC3t5fPDyGEEMIAFaiFNT09nYiICJo1a6a3vVmzZoSFhT11EMeOHctWZ3BwcJ51Tps2DXt7e/Xm7u7+1OcXQgghhBBCCGF4CpSw3rp1C61WS6lSpfS2lypVivj4+KcOIj4+vsB1jho1isTERPX2119/PfX5hRBCCCGEEEIYnqdah/XfY+sURXnm8XYFrdPc3Bxzc/NnOqcoPlJTU3nttdcAOHXqFFZWVkUcUc4yMjJYsmQJAL169cLU1LSIIxJCCCGEEKLoFChhLVmyJMbGxtlaPhMSErK1kBaEq6trodcpxOMURSEqKkq9b6gUReHmzZvqfSGEEEIIIYqzAnUJNjMzo1atWuzbt09v+759+wgKCnrqIAIDA7PVuXfv3meqUwghhBBCCCHEy63AXYKHDBlCt27dqF27NoGBgXz33XfExsbSp08fIGts6T///MPq1avVYyIjIwFITk7m5s2bREZGYmZmhr+/PwCfffYZ9evXZ8aMGbRt25affvqJ/fv3c/To0UK4RCGEEEIIIYQQL6MCJ6wdO3bk9u3bTJ48mbi4OKpUqcLOnTvx8PAAIC4uLtuarDVr1lTvR0REsG7dOjw8PIiJiQEgKCiIDRs2MHbsWMaNG0eFChXYuHEjderUeYZLE0IIIYQQQgjxMivwOqyGStbRE3lJSUnBxsYGyGrpt7a2LuKIcpaenq6uZzxq1CjMzMyKOCIhXn3y+SGEEEIYrgKNYRVCCCGEEEIIIV6Up1rWRoiXjUajUbutP+sSTM+TRqPB3t5evS+EEEIIIURxJl2ChRBCFGvy+SGEEEIYLukSLIQQQgghhBDCIEnCKoQQQgghhBDCIEnCKoqFBw8e8Nprr/Haa6/x4MGDog4nVxkZGSxZsoQlS5aQkZFR1OEIIYQQQhRIw4YNGTRo0HM9h0ajYdu2bc/1HMJwSMIqigWdTkd4eDjh4eHodLqiDidXiqJw/fp1rl+/zisyvFwIIQxCSEgIGo2GPn36ZNvXr18/NBoNISEhLz4wUayEhYVhbGxM8+bNn/u5PD090Wg0ud4aNmz4xOPnzp1b6HGtXLlSLw43Nzc6dOjA1atX811HXFwcLVq0KNA5HRwcniLawvPv6378lpCQkK38pUuXsLW1zVfcb7/9NuXKlcPCwgI3Nze6devG9evXcyx7+/ZtypYti0aj4d69e894VS+GJKxCCCGEKBbc3d3ZsGGDXk+bhw8fsn79esqVK1eEkYniYvny5QwcOJCjR48SGxv7XM916tQp4uLiiIuLY8uWLQCcP39e3bZ169bnev682NnZERcXx/Xr11m3bh2RkZG8/fbbaLXafB3v6uqKubn5c46ycHXs2FF97h/dgoODadCgAS4uLnplMzIy6Ny5M/Xq1ctX3Y0aNWLTpk2cP3+eLVu2cPnyZd57770cy/bs2ZNq1ao98/W8SJKwCiGEEKJYCAgIoFy5cnpf1Ldu3Yq7uzs1a9ZUt+XUslSjRg0mTpyoPp44cSLlypXD3Nyc0qVL8+mnn6r7FixYgI+PDxYWFpQqVUrvi2NaWhqffvopLi4uWFhY8Oabb3Lq1KnCv1hhcFJSUti0aRN9+/aldevWrFy5Ut0XGBjIyJEj9crfvHkTU1NTDh06BGS1KrZq1QpLS0u8vLxYt25dnq2gzs7OuLq64urqSokSJQBwcXFRtx06dIjKlStjbm6Op6cns2fPVo9t2LAh165dY/DgwWorIGS1znXu3JmyZctiZWVF1apVWb9+fYGfC41Gg6urK25ubjRq1IgJEybw+++/c+nSJQAWLlxIhQoVMDMzw8/PjzVr1mQ7/lGX4JiYGDQaDVu3bqVRo0ZYWVlRvXp1jh07BkBoaCgfffQRiYmJ6rU8ei/n9V4tbJaWlupz7+rqirGxMQcPHqRnz57Zyo4dO5aKFSvSoUOHfNU9ePBg3njjDTw8PAgKCmLkyJEcP3482/CyhQsXcu/ePYYNG1Yo1/SiSMIqhBBCiGLjo48+YsWKFerj5cuX06NHjwLVsXnzZubMmcPixYu5ePEi27Zto2rVqgCEh4fz6aefMnnyZM6fP8/u3bupX7++euyIESPYsmULq1at4vTp03h7exMcHMydO3cK5wKFwdq4cSN+fn74+fnxwQcfsGLFCnX4T9euXVm/fr3ecKCNGzdSqlQpGjRoAED37t25fv06oaGhbNmyhe+++y7HrqT5ERERQYcOHejUqRPnzp1j4sSJjBs3Tk2it27dStmyZZk8ebLaGghZPRJq1arFjh07+P333+nduzfdunXjxIkTz/DMZCVzkNWy+OOPP/LZZ58xdOhQfv/9dz755BM++ugjNXHPzZgxYxg2bBiRkZH4+vrSuXNnMjMzCQoKYu7cuWqrblxcHMOGDXvie/XfYmNjsbGxyfOW05CD3KxevRorK6tsSfLBgwf54Ycf+Pbbb/Nd1+Pu3LnD2rVrCQoKwtTUVN0eFRXF5MmTWb16NUZGL1cKaFLUAQghhBBCvCjdunVj1KhRaqvMr7/+yoYNGwgNDc13HbGxsbi6utKkSRNMTU0pV64cr7/+urrP2tqa1q1bY2tri4eHh9p6m5KSwsKFC1m5cqU6/m7JkiXs27ePZcuWMXz48EK/XmE4li1bxgcffABA8+bNSU5O5sCBAzRp0oSOHTsyePBgjh49qnYDXbduHV26dMHIyIg///yT/fv3c+rUKWrXrg3A0qVL8fHxeapYvvrqKxo3bsy4ceMA8PX1JSoqipkzZxISEkKJEiUwNjbG1tYWV1dX9bgyZcrotc4NHDiQ3bt388MPP1CnTp2niuXvv/9m5syZlC1bFl9fXz755BNCQkLo168fAEOGDOH48ePMmjWLRo0a5VrPsGHDaNWqFQCTJk2icuXKXLp0iYoVK2Jvb6+26j6S13s1J6VLlyYyMjLPaynIWt7Lly+nS5cuarIOWS3YISEhfP/99wVeF/zzzz/nm2++ITU1lTfeeIMdO3ao+9LS0ujcuTMzZ86kXLlyXLlypUB1F7WXK70WQgghhHgGJUuWpFWrVqxatYoVK1bQqlUrSpYsWaA63n//fR48eED58uXp1asXP/74I5mZmQA0bdoUDw8PypcvT7du3Vi7di2pqakAXL58mYyMDOrWravWZWpqyuuvv050dHThXaQwOOfPn+fkyZN06tQJABMTEzp27Mjy5cuBrO67TZs2Ze3atQBcvXqVY8eO0bVrV/V4ExMTAgIC1Dq9vb1xdHR8qniio6P1XocAdevW5eLFi3mOI9VqtXzxxRdUq1YNJycnbGxs2Lt3b4HH4yYmJmJjY4O1tTXu7u6kp6ezdetWzMzMco3tSe+Rx8dlurm5AeTZAp3XezUnJiYmeHt753n791jU3Bw7doyoqKhs3YF79epFly5d8mzpzc3w4cM5c+YMe/fuxdjYmO7du6st9qNGjaJSpUrqDyYvG0lYRbFRsmTJAn8pKQpWVlZYWVkVdRhCCPHK6tGjBytXrmTVqlU5dgc2MjLKNlP742PB3N3dOX/+PN9++y2Wlpb069eP+vXrk5GRga2tLadPn2b9+vW4ubkxfvx4qlevzr1799Q6H40HfERRlGzbxKtl2bJlZGZmUqZMGUxMTDAxMWHhwoVs3bqVu3fvAlndgjdv3kxGRgbr1q2jcuXKVK9eHSDXlQOedkWBnF5z+alr9uzZzJkzhxEjRnDw4EEiIyMJDg4mPT29QOe3tbUlMjKSc+fOkZycTEREBK+99pq6/2neI493f31UNq+VIfJ6r+akMLsEL126lBo1alCrVi297QcPHmTWrFnqa6Rnz54kJiZiYmKi/riRm5IlS+Lr60vTpk3ZsGEDO3fu5Pjx42q9P/zwg1pv48aN1WMmTJiQr5iLknQJFsWCtbU1N2/eLOownsjMzEy6hAkhxHPWvHlz9Qt2cHBwtv3Ozs7qmD2ApKSkbEtuWFpa8vbbb/P222/Tv39/KlasyLlz5wgICMDExIQmTZrQpEkTJkyYgIODAwcPHiQ4OBgzMzOOHj1Kly5dgKxEODw8/LmvWymKTmZmJqtXr2b27Nk0a9ZMb1/79u1Zu3YtAwYMoF27dnzyySfs3r2bdevW0a1bN7VcxYoVyczM5MyZM2qSc+nSpadelsTf35+jR4/qbQsLC8PX1xdjY2Mg6zvJv1tbjxw5Qtu2bdWWOp1Ox8WLF6lUqVKBzm9kZIS3t3eO+ypVqsTRo0fp3r27XmwFPcfjcroWINf36rvvvputbGF1CU5OTmbTpk1MmzYt275jx47pxfnTTz8xY8YMwsLCKFOmzBPrfuTRjw9paWkAbNmyRW929FOnTtGjRw+OHDlChQoV8l1vUZGEVQghhBDFirGxsdq98NGX88e99dZbrFy5kjZt2uDo6Mi4ceP0yq1cuRKtVkudOnWwsrJizZo1WFpa4uHhwY4dO7hy5Qr169fH0dGRnTt3otPp8PPzw9ramr59+zJ8+HBKlChBuXLl+PLLL0lNTc1xplDxatixYwd3796lZ8+e2Nvb6+177733WLZsGQMGDMDa2pq2bdsybtw4oqOj1R81ICthbdKkCb1792bhwoWYmpoydOhQLC0tn6p1fujQobz22mtMmTKFjh07cuzYMb755hsWLFiglvH09OS///0vnTp1wtzcnJIlS+Lt7c2WLVsICwvD0dGRr776ivj4+GdKJv9t+PDhdOjQgYCAABo3bszPP//M1q1b2b9//1PX6enpqY4Zrl69OlZWVhw8eDDX92pOHnUJflYbN24kMzNT7e79uH8/j+Hh4RgZGVGlShV128mTJ+nevTsHDhygTJkynDx5kpMnT/Lmm2/i6OjIlStXGD9+PBUqVCAwMBAgW1J669Yt9XxFvT5tfkiXYCGEEEIUO3Z2drm2howaNYr69evTunVrWrZsSbt27fS+8Dk4OLBkyRLq1q1LtWrVOHDgAD///DNOTk44ODiwdetW3nrrLSpVqsSiRYtYv349lStXBmD69Om0b9+ebt26ERAQwKVLl9izZ89Tj0UUhm/ZsmU0adIkW7IKWS2skZGRnD59GsjqFnz27Fnq1auXbW3g1atXU6pUKerXr88777xDr169sLW1xcLCosAxBQQEsGnTJjZs2ECVKlUYP348kydPJiQkRC0zefJkYmJiqFChAs7OzgCMGzeOgIAAgoODadiwIa6urrRr167A589Lu3btmDdvHjNnzqRy5cosXryYFStW0LBhw6euMygoiD59+tCxY0ecnZ358ssvn/hefV6WLVvGu++++9Tv+dTUVM6fP68OU7C0tGTr1q00btwYPz8/evToQZUqVTh8+PBLt1ZtbjTK03Z+NzBJSUnY29uTmJhY4Fm1xKvvwYMH6oyMu3bt0puRzZBkZGSoEy507dpVbzyGEOL5kM8PIcTL6O+//8bd3Z39+/erYxKFeBVJl2BRLOh0Og4fPqzeN1SKonDt2jX1vhBCCCEEZE2ck5ycTNWqVYmLi2PEiBF4eno+1YyyQrxMJGEVQgghhBDCwGVkZDB69GiuXLmCra0tQUFBrF27VnpjiVeeJKxCCCGEEEIYuODg4BxntRbiVSeTLgkhhBBCCCGEMEiSsAohhBBCCCGEMEiSsAohhBBCCCGeSkxMDBqNhsjIyOd2jpUrV74U64WK50MSVlFsWFlZYWVlVdRhPJGpqalMoCCEEIUoNDQUjUaT661Ro0ZFHeILpdFo2LZtW1GHUSyFhYVhbGxM8+bNX8j5Jk6ciEajyfF8X375JRqN5pnWN82vhg0bqu83c3NzfH19mTp1KlqtNl/Hd+zYkQsXLhT4nIMGDXqKaAvPH3/8Qfv27fH09ESj0TB37twCHX/p0iVsbW2zJetbt26ladOmODs7Y2dnR2BgIHv27Cm8wA2MJKyiWLC2tiYlJYWUlBSsra2LOpxcmZmZMXr0aEaPHo2ZmVlRhyOEEK+EoKAg4uList0WL16MRqOhX79+RR2iKCaWL1/OwIEDOXr0KLGxsS/knG5ubhw6dIi///5bb/uKFSsoV67cC4kBoFevXsTFxXH+/Hk+/fRTxo4dy6xZs/J1rKWlJS4uLs85wsKXmppK+fLlmT59Oq6urgU6NiMjg86dO1OvXr1s+/773//StGlTdu7cSUREBI0aNaJNmzacOXOmsEI3KJKwCiGEEOKVZmZmhqurq97t7t27DB8+nNGjR/P++++j1Wrp2bMnXl5eWFpa4ufnx7x58/TqCQkJoV27dkyaNAkXFxfs7Oz45JNPSE9PV8s0bNiQAQMGMGDAABwcHHBycmLs2LF6a2t///331K5dG1tbW1xdXenSpQsJCQl65/rjjz9o1aoVdnZ22NraUq9ePS5fvgxkrSc+efJkypYti7m5OTVq1GD37t3qsenp6QwYMAA3NzcsLCzw9PRk2rRpAHh6egLwzjvvoNFo1MeXL1+mbdu2lCpVChsbG1577TX2799faH8DASkpKWzatIm+ffvSunVrVq5cqe4LDAxk5MiReuVv3ryJqakphw4dAiAuLo5WrVphaWmJl5cX69atw9PT84mtdi4uLjRr1oxVq1ap28LCwrh16xatWrXSK/uk1xbAyZMnqVmzJhYWFtSuXTvfSZKVlRWurq54enoyYMAAGjdurLb03717l+7du+Po6IiVlRUtWrTg4sWL6rH/7hI8ceJEatSowZo1a/D09MTe3p5OnTpx//59IOu9evjwYebNm6e27MbExHD37l26du2Ks7MzlpaW+Pj4sGLFinzF/zRee+01Zs6cSadOnTA3Ny/QsWPHjqVixYp06NAh2765c+cyYsQIXnvtNXx8fJg6dSo+Pj78/PPPhRW6QZGEVQghhBDFyr1792jXrh0NGjRgypQpQNYX9bJly7Jp0yaioqIYP348o0ePZtOmTXrHHjhwgOjoaA4dOsT69ev58ccfmTRpkl6ZVatWYWJiwokTJ/j666+ZM2cOS5cuVfenp6czZcoUzp49y7Zt27h69SohISHq/n/++Yf69etjYWHBwYMHiYiIoEePHmRmZgIwb948Zs+ezaxZs/jtt98IDg7m7bffVr/gf/3112zfvp1NmzZx/vx5vv/+ezUxPXXqFJDVuhYXF6c+Tk5OpmXLluzfv58zZ84QHBxMmzZtXlgrYHGwceNG/Pz88PPz44MPPmDFihXqDxldu3Zl/fr1ej9sbNy4kVKlStGgQQMAunfvzvXr1wkNDWXLli1899132X7oyE2PHj30EuTly5fTtWvXbL25nvTaSklJoXXr1vj5+REREcHEiRMZNmzYUz0flpaWZGRkAFkJZnh4ONu3b+fYsWMoikLLli3V/Tm5fPky27ZtY8eOHezYsYPDhw8zffp09ToCAwPVVt24uDjc3d0ZN24cUVFR7Nq1i+joaBYuXEjJkiVzPcfUqVOxsbHJ83bkyJGnuv68HDx4kB9++IFvv/02X+V1Oh3379+nRIkShR6LQVBeEYmJiQqgJCYmFnUowgA9ePBAadmypdKyZUvlwYMHRR1OrjIyMpS1a9cqa9euVTIyMoo6HCGKBfn8KF60Wq3SokULpVKlSk/8m/fr109p3769+vjDDz9USpQooaSkpKjbFi5cqNjY2CharVZRFEVp0KCBUqlSJUWn06llPv/8c6VSpUq5nufkyZMKoNy/f19RFEUZNWqU4uXlpaSnp+dYvnTp0soXX3yht+21115T+vXrpyiKogwcOFB566239GJ4HKD8+OOPeVx5Fn9/f2X+/PlPLCfyJygoSJk7d66iKFmf9yVLllT27dunKIqiJCQkKCYmJsp///tftXxgYKAyfPhwRVEUJTo6WgGUU6dOqfsvXryoAMqcOXNyPeeECROU6tWrK+np6YqLi4ty+PBhJTk5WbG1tVXOnj2rfPbZZ0qDBg3U8k96bS1evDjH9wCgnDlzJtc4GjRooHz22WeKomS9B3ft2qWYmZkpI0aMUC5cuKAAyq+//qqWv3XrlmJpaals2rRJURRFWbFihWJvb693XVZWVkpSUpK6bfjw4UqdOnVyPOcjbdq0UT766KNc4/y327dvKxcvXszzlpqamq+6PDw88vxbPXLr1i3F3d1dOXz4sKIo2a89J19++aVSokQJ5caNG/mK5WVjUnSpshAvjlarZefOnep9Q6XT6dRfMXU6XRFHI4QQr57Ro0dz7NgxTp48iZ2dnd6+RYsWsXTpUq5du8aDBw9IT0+nRo0aemWqV6+uN4FfYGAgycnJ/PXXX3h4eADwxhtvoNFo9MrMnj0brVaLsbExZ86cYeLEiURGRnLnzh31/31sbCz+/v5ERkZSr169HCfgS0pK4vr169StW1dve926dTl79iyQ1VrVtGlT/Pz8aN68Oa1bt6ZZs2Z5Pi8pKSlMmjSJHTt2cP36dTIzM3nw4IG0sBaS8+fPc/LkSbZu3QqAiYkJHTt2ZPny5TRp0gRnZ2eaNm3K2rVrqVevHlevXuXYsWMsXLhQPd7ExISAgAC1Tm9vbxwdHfN1flNTU7VV98qVK/j6+lKtWjW9Mvl5bUVHR+f4HsiPBQsWsHTpUrULfbdu3ZgwYQL79+/HxMSEOnXqqGWdnJzw8/MjOjo61/o8PT2xtbVVH7u5uT2xxblv3760b9+e06dP06xZM9q1a0dQUFCu5UuUKPHCWy179epFly5dqF+/fr7Kr1+/nokTJ/LTTz+9lON880O6BAshhBCiWNi4cSOzZs1iw4YN+Pj46O3btGkTgwcPpkePHuzdu5fIyEg++ugjvfGpeXk8Qc1LSkoKzZo1w8bGhu+//55Tp07x448/AqjnsrS0LPD5FEVRtwUEBHD16lWmTJnCgwcP6NChA++9916e9Q0fPpwtW7bwxRdfcOTIESIjI6latWq+r1/kbdmyZWRmZlKmTBlMTEwwMTFh4cKFbN26lbt37wJZ3YI3b95MRkYG69ato3LlylSvXh1Ar6vw43LbnpMePXqo3Ux79OiRa7m8XlsFOd+/de3alcjISC5fvsyDBw9YtmwZVlZWeV5bXu+rf/+go9Fonvhjf4sWLbh27RqDBg3i+vXrNG7cOM8uzUXRJfjgwYPMmjVLfZ307NmTxMRETExMWL58uV7ZjRs30rNnTzZt2kSTJk0KNQ5DIi2sQgghhHjlRUZG0qNHD6ZPn05wcHC2/UeOHCEoKEhvxuBHkxw97uzZszx48EBNKo8fP46NjQ1ly5ZVyxw/flzvmOPHj+Pj44OxsTF//vknt27dYvr06bi7uwMQHh6uV75atWqsWrWKjIyMbF/K7ezsKF26NEePHtVrgQkLC+P111/XK9exY0c6duzIe++9R/Pmzblz5w4lSpTA1NQ0W2+jI0eOEBISwjvvvANkjWmNiYnJ/kSKAsvMzGT16tXMnj07W0t3+/btWbt2LQMGDKBdu3Z88skn7N69m3Xr1tGtWze1XMWKFcnMzOTMmTPUqlULyFry5N69e/mOo3LlylSuXJnffvuNLl26ZNufn9eWv78/a9asyfYeyA97e3u8vb2zbff39yczM5MTJ06orZ23b9/mwoULVKpUKd/X929mZmY59qpzdnYmJCSEkJAQ6tWrx/Dhw3OdrbhPnz45Tnr0uDJlyjx1jDk5duyYXtw//fQTM2bMICwsTO9c69evp0ePHqxfvz7b5FmvGklYhRBCCPFKu3XrFu3ataNhw4Z88MEHxMfH6+03NjbG29ub1atXs2fPHry8vFizZg2nTp3Cy8tLr2x6ejo9e/Zk7NixXLt2jQkTJjBgwACMjP6/09pff/3FkCFD+OSTTzh9+jTz589n9uzZAJQrVw4zMzPmz59Pnz59+P3339WJnx4ZMGAA8+fPp1OnTowaNQp7e3uOHz/O66+/jp+fH8OHD2fChAlUqFCBGjVqsGLFCiIjI1m7di0Ac+bMwc3NjRo1amBkZMQPP/yAq6urOsuqp6cnBw4coG7dupibm+Po6Ii3tzdbt26lTZs2aDQaxo0bJ0NTCsmOHTu4e/cuPXv2xN7eXm/fe++9x7JlyxgwYADW1ta0bduWcePGER0drZdUVqxYkSZNmtC7d28WLlyIqakpQ4cOxdLSMt+t+5DVepeRkZFtXc9HnvTa6tKlC2PGjFHfAzExMflemiY3Pj4+tG3bll69erF48WJsbW0ZOXIkZcqUoW3btk9dr6enJydOnCAmJgYbGxtKlCjBxIkTqVWrFpUrVyYtLY0dO3bkmRQ/a5fg9PR0oqKi1Pv//PMPkZGR2NjYqMn7N998w48//siBAwcAssUTHh6OkZERVapUUbetX7+e7t27M2/ePN544w31f5qlpWW219irQLoECyGEEOKV9ssvv3Dt2jV27tyJm5tbtttrr71Gnz59ePfdd+nYsSN16tTh9u3bOa7P2rhxY3x8fKhfvz4dOnSgTZs2TJw4Ua9M9+7defDgAa+//jr9+/dn4MCB9O7dG8hq3Vm5ciU//PAD/v7+TJ8+PdsXficnJw4ePEhycjINGjSgVq1aLFmyRG1t/fTTTxk6dChDhw6latWq7N69m+3bt6vdnG1sbJgxYwa1a9fmtddeIyYmhp07d6pJ9ezZs9m3bx/u7u7UrFkTyEpyHR0dCQoKok2bNgQHB+uNlxRPb9myZTRp0iTHRKJ9+/ZERkZy+vRpIKvb7NmzZ6lXr162NVJXr15NqVKlqF+/Pu+88w69evXC1tYWCwuLfMdibW2da7IK+Xtt/fzzz0RFRVGzZk3GjBnDjBkz8n3+3KxYsYJatWrRunVrAgMDURSFnTt35jiOO7+GDRuGsbEx/v7+ODs7Exsbi5mZGaNGjaJatWrUr18fY2NjNmzY8Mzx5+b69evUrFmTmjVrEhcXx6xZs6hZsyYff/yxWubWrVs59ubIy+LFi8nMzKR///56/8s+++yzwr4Eg6BRnqUzugFJSkrC3t6exMTEbJMoCJGSkoKNjQ2Q1c3J2tq6iCPKWXp6urpW3qhRo7JNNy+EKHzy+SHyKyQkhHv37qlrR+akYcOG1KhR44lrYwrxrP7++2/c3d3Zv38/jRs3LupwhHhupEuwEEIIIYQQBu5Rq3vVqlWJi4tjxIgReHp65ns2WSFeVpKwimLB2tr6mWa2e1HMzMyYMGFCUYchhBBCCAOTkZHB6NGjuXLlCra2tgQFBbF27dpn6jYrxMtAugQLIYQo1uTzQwghhDBcMumSEEIIIYQQQgiDJAmrKBYePnzI+++/z/vvv8/Dhw+LOpxcZWZm8sMPP/DDDz+QmZlZ1OEIIYQoAp6enjJpk3ihXqbXnEajyXPiM/HqkYRVFAtarZbNmzezefPmHBeRNhQ6nY6oqCiioqJk/TshhChEISEhaDQaNBoNpqamlC9fnmHDhpGSklLUoYliJCwsDGNjY5o3b/7CzpmUlMSYMWOoWLEiFhYWuLq60qRJE7Zu3Wpw83skJCTwySefUK5cOczNzXF1dSU4OJhjx4690DhCQ0PRaDTcu3fvhZ733+7evUu3bt2wt7fH3t6ebt26PTGmiRMnUrFiRaytrXF0dKRJkyacOHFCr0xaWhoDBw6kZMmSWFtb8/bbb/P3338/xyt5NpKwCiGEEKJYaN68OXFxcVy5coX//Oc/LFiwgGHDhhVJLFqtVn6YLIaWL1/OwIEDOXr0KLGxsc/9fPfu3SMoKIjVq1czatQoTp8+zX//+186duzIiBEjSExMfO4xFET79u05e/Ysq1at4sKFC2zfvp2GDRty586dog6tSHTp0oXIyEh2797N7t27iYyMpFu3bnke4+vryzfffMO5c+c4evQonp6eNGvWjJs3b6plBg0axI8//siGDRs4evQoycnJtG7d2nAbdZRXRGJiogIoiYmJRR2KMEDJyckKoABKcnJyUYeTq7S0NGXixInKxIkTlbS0tKIOR4hiQT4/iocPP/xQadu2rd62jz/+WHF1dVXWrFmj1KpVS7GxsVFKlSqldO7cWblx44aiKIqi1WqVMmXKKAsXLtQ7NiIiQgGUy5cvK4qiKLNnz1aqVKmiWFlZKWXLllX69u2r3L9/Xy2/YsUKxd7eXvn555+VSpUqKcbGxsqVK1eUGzduKK1bt1YsLCwUT09P5fvvv1c8PDyUOXPmPNfnQ7x4ycnJiq2trfLnn38qHTt2VCZNmqTue+ONN5TPP/9cr3xCQoJiYmKiHDx4UFEURbl+/brSsmVL9bWydu3aJ75W+vbtq1hbWyv//PNPtn33799XMjIyFEVRstVz7949pVevXoqzs7Nia2urNGrUSImMjFT3X7p0SXn77bcVFxcXxdraWqldu7ayb98+vfo9PDyUL774Qvnoo48UGxsbxd3dXVm8eHGusd69e1cBlNDQ0FzLKIqiAMqSJUuUdu3aKZaWloq3t7fy008/6ZX5448/lBYtWijW1taKi4uL8sEHHyg3b95U9+t0OmXGjBmKl5eXYmFhoVSrVk354YcfFEVRlKtXr6rfGR/dPvzwQ0VRFOWHH35QqlSpolhYWCglSpRQGjdu/Ny+V0ZFRSmAcvz4cXXbsWPHFED5888/813Po8+4/fv3K4qS9bc1NTVVNmzYoJb5559/FCMjI2X37t2FdwGFSFpYhRBCCFEsWVpakpGRQXp6OlOmTOHs2bNs27aNq1evEhISAoCRkRGdOnVi7dq1eseuW7eOwMBAypcvr5b7+uuv+f3331m1ahUHDx5kxIgResekpqYybdo0li5dyh9//IGLiwshISHExMRw8OBBNm/ezIIFC0hISHgh1y9erI0bN+Ln54efnx8ffPABK1asULvkdu3alfXr1+t10d24cSOlSpWiQYMGAHTv3p3r168TGhrKli1b+O677/J8reh0OjZs2EDXrl0pXbp0tv02NjaYmGRf4VJRFFq1akV8fDw7d+4kIiKCgIAAGjdurLZ0Jicn07JlS/bv38+ZM2cIDg6mTZs22VqNZ8+eTe3atTlz5gz9+vWjb9++/PnnnznGa2Njg42NDdu2bSMtLS3P53LSpEl06NCB3377jZYtW9K1a1c1tri4OBo0aECNGjUIDw9n9+7d3Lhxgw4dOqjHjx07lhUrVrBw4UL++OMPBg8ezAcffMDhw4dxd3dny5YtAJw/f564uDjmzZtHXFwcnTt3pkePHkRHRxMaGsq7776bZ7fqR9eU261Fixa5Hnvs2DHs7e2pU6eOuu2NN97A3t6esLCwPJ+fR9LT0/nuu++wt7enevXqAERERJCRkUGzZs3UcqVLl6ZKlSr5rveFK9p8ufDIL+QiL9LCKoTIjXx+FA//bmE9ceKE4uTkpHTo0CFb2ZMnTyqA2kJ6+vRpRaPRKDExMYqi/H+r67fffpvr+TZt2qQ4OTmpj1esWKEAeq1U58+fz9aCEh0drQDSwvoKCgoKUubOnasoiqJkZGQoJUuWVFslH7Wm/ve//1XLBwYGKsOHD1cU5f9fF6dOnVL3X7x4Mc/Xyo0bNxRA+eqrr54Y2+MtrAcOHFDs7OyUhw8f6pWpUKFCni2k/v7+yvz58/Xq/OCDD9THOp1OcXFxydZb4XGbN29WHB0dFQsLCyUoKEgZNWqUcvbsWb0ygDJ27Fj1cXJysqLRaJRdu3YpiqIo48aNU5o1a6Z3zF9//aUAyvnz55Xk5GTFwsJCCQsL0yvTs2dPpXPnzoqiKMqhQ4cUQLl79666/1Gvikf/B/Lj4sWLed7+/vvvXI/94osvFB8fn2zbfXx8lKlTp+Z53p9//lmxtrZWNBqNUrp0aeXkyZPqvrVr1ypmZmbZjmnatKnSu3fvfF/biyQtrEIIIYQoFnbs2IGNjQ0WFhYEBgZSv3595s+fz5kzZ2jbti0eHh7Y2trSsGFDALW1qGbNmlSsWJH169cDcPjwYRISEvRabA4dOkTTpk0pU6YMtra2dO/endu3b+tN6mRmZka1atXUx9HR0ZiYmFC7dm11W8WKFXFwcHiOz4IoCufPn+fkyZN06tQJABMTEzp27Mjy5csBcHZ2pmnTpmpL/tWrVzl27Bhdu3ZVjzcxMSEgIECt09vbG0dHx1zPqfyv5U+j0RQo1oiICJKTk3FyctJrDbx69SqXL18GICUlhREjRuDv74+DgwM2Njb8+eef2VpYH3+9azQaXF1d82wVbt++PdevX2f79u0EBwcTGhpKQEAAK1euzLVea2trbG1t1XojIiI4dOiQXuwVK1YE4PLly0RFRfHw4UOaNm2qV2b16tXq9eWkevXqNG7cmKpVq/L++++zZMkS7t69m+dz6e3tneetTJkyeR6f099OUZQn/k0bNWpEZGQkYWFhNG/enA4dOjyx50Z+6i0q2fsBCCGEEEK8gho1asTChQsxNTWldOnSmJqakpKSQrNmzWjWrBnff/89zs7OxMbGEhwcTHp6unps165dWbduHSNHjmTdunUEBwdTsmRJAK5du0bLli3p06cPU6ZMoUSJEhw9epSePXuSkZGh1mFpaan3hfBpEwrx8lm2bBmZmZl6CYqiKJiamnL37l0cHR3p2rUrn332GfPnz2fdunVUrlxZ7cap5NLtNLftkJUEOzo6Eh0dXaBYdTodbm5uhIaGZtv36MeU4cOHs2fPHmbNmoW3tzeWlpa89957eu8ZAFNTU73HGo3miZONWVhY0LRpU5o2bcr48eP5+OOPmTBhgtpN/0n16nQ62rRpw4wZM7LV7ebmxu+//w7AL7/8ki1hNDc3zzUuY2Nj9u3bR1hYGHv37mX+/PmMGTOGEydO4OXlleMxNjY2eV5rvXr12LVrV477XF1duXHjRrbtN2/epFSpUnnWa21trSbFb7zxBj4+PixbtoxRo0bh6upKenq6+rp7JCEhgaCgoDzrLSqSsIpiwcrKiuTkZPW+oTI1NWXUqFHqfSGEEIXn0Ze4x/3555/cunWL6dOn4+7uDkB4eHi2Y7t06cLYsWOJiIhg8+bNLFy4UN0XHh5OZmYms2fPxsgoq/Papk2bnhhPpUqVyMzMJDw8nNdffx3Iakkr6qU0ROHKzMxk9erVzJ49W2/cIGS1KK5du5YBAwbQrl07PvnkE3bv3s26dev0ZoOtWLEimZmZnDlzhlq1agFw6dKlPF8rRkZGdOzYkTVr1jBhwoRs41hTUlIwNzfPNo41ICCA+Ph4TExM8PT0zLHuI0eOEBISwjvvvANkjWmNiYnJ5zNSMP7+/gVadzUgIIAtW7bg6emZ4xhdf39/zM3NiY2NVccH/5uZmRlAtllzNRoNdevWpW7duowfPx4PDw9+/PFHhgwZkmM9kZGRecZqaWmZ677AwEASExM5efKk+v/hxIkTJCYmFjixVBRFHRdcq1YtTE1N2bdvn9pLJC4ujt9//50vv/yyQPW+KJKwimJBo9FgbW1d1GE8kUajUf9JCiGEeP7KlSuHmZkZ8+fPp0+fPvz+++9MmTIlWzkvLy+CgoLo2bMnmZmZtG3bVt1XoUIFMjMzmT9/Pm3atOHXX39l0aJFTzy3n58fzZs3p1evXnz33XeYmJgwaNCgPL/EipfPjh07uHv3Lj179sTe3l5v33vvvceyZcsYMGAA1tbWtG3blnHjxhEdHU2XLl3UchUrVqRJkyb07t1b7SUwdOjQbK32/zZ16lRCQ0OpU6cOX3zxBbVr18bU1JQjR44wbdo0Tp06la0LepMmTQgMDKRdu3bMmDEDPz8/rl+/zs6dO2nXrh21a9fG29ubrVu30qZNGzQaDePGjXvmZZpu377N+++/T48ePahWrRq2traEh4fz5Zdf6r3fnqR///4sWbKEzp07M3z4cEqWLMmlS5fYsGEDS5YswdbWlmHDhjF48GB0Oh1vvvkmSUlJhIWFYWNjw4cffoiHhwcajYYdO3bQsmVLLC0t+eOPPzhw4ADNmjXDxcWFEydOcPPmTSpVqpRrLP/+gawgKlWqpP5/WLx4MQC9e/emdevW+Pn5qeUqVqzItGnTeOedd0hJSeGLL77g7bffxs3Njdu3b7NgwQL+/vtv3n//fQDs7e3p2bMnQ4cOxcnJiRIlSjBs2DCqVq1KkyZNnjre56rohs8WLpk0QwghxNOQz4/iIadlbR5Zt26d4unpqZibmyuBgYHK9u3bFUA5c+aMXrlvv/1WAZTu3btnq+Orr75S3NzcFEtLSyU4OFhZvXq13qQtj5a1+be4uDilVatWirm5uVKuXDll9erVsqzNK6Z169ZKy5Ytc9z3aCKfiIgIRVEU5ZdfflEApX79+tnKXr9+XWnRooVibm6ueHh4KOvWrVNcXFyURYsW5Xn+e/fuKSNHjlR8fHwUMzMzpVSpUkqTJk2UH3/8UdHpdIqiZF/WJikpSRk4cKBSunRpxdTUVHF3d1e6du2qxMbGKoqStfRLo0aNFEtLS8Xd3V355ptvlAYNGiifffaZWkdOr+Pq1asrEyZMyDHOhw8fKiNHjlQCAgIUe3t7xcrKSvHz81PGjh2rpKamquUA5ccff9Q71t7eXlmxYoX6+MKFC8o777yjODg4KJaWlkrFihWVQYMGqder0+mUefPmKX5+foqpqani7OysBAcHK4cPH1brmDx5suLq6qpoNBrlww8/VKKiopTg4GDF2dlZMTc3V3x9ffUmmXoebt++rXTt2lWxtbVVbG1tla5du+pNBKUoWc/Ho2t/8OCB8s477yilS5dWzMzMFDc3N+Xtt9/Wm3TpUbkBAwYoJUqUUCwtLZXWrVurf1tDpFGUPDq/v0SSkpKwt7cnMTEROzu7og5HGJi0tDQ++eQTABYvXpznGIWilJmZyY4dOwBo3bp1jl1ZhBCFSz4/hBAvo7///ht3d3f2799P48aNizocIZ6bp5oleMGCBXh5eWFhYUGtWrU4cuRInuUPHz5MrVq1sLCwoHz58jl2k5k7dy5+fn5YWlri7u7O4MGDefjw4dOEJ0Q2mZmZrFq1ilWrVpGZmVnU4eRKp9Nx9uxZzp49+8xda4QQQgjx6jh48CDbt2/n6tWrhIWF0alTJzw9Palfv35RhybEc1XghHXjxo0MGjSIMWPGcObMGerVq0eLFi2yTWP9yNWrV2nZsiX16tXjzJkzjB49mk8//VRdkBdg7dq1jBw5kgkTJhAdHc2yZcvYuHGjOvmMEEIIIYQQxVlGRgajR4+mcuXKvPPOOzg7OxMaGiqTNIpXXoG7BNepU4eAgAC92fEqVapEu3btmDZtWrbyn3/+Odu3b9ebUrtPnz6cPXuWY8eOATBgwACio6M5cOCAWmbo0KGcPHnyia23j0iXLpGXlJQUdWrx5ORkg52AKT09XX0fjRo1SiZgEuIFkM8PIYQQwnAVqIU1PT2diIiIbFNyN2vWjLCwsByPOXbsWLbywcHBhIeHq2uTvfnmm0RERHDy5EkArly5ws6dO2nVqlWusaSlpZGUlKR3E0IIIYQQQgjx6ijQjC63bt1Cq9VmW6y2VKlSxMfH53hMfHx8juUzMzO5desWbm5udOrUiZs3b/Lmm2+iKAqZmZn07duXkSNH5hrLtGnTmDRpUkHCF0IIIYR4LkJCQrh3716B1osUQgjxZE816dK/13tSFCXPNaByKv/49tDQUL744gsWLFjA6dOn2bp1Kzt27MhxHbRHRo0aRWJionr766+/nuZShBBCCFFMxMfHM3DgQMqXL4+5uTnu7u60adNGb0iSoQsLC8PY2JjmzZsXdSi5atiwIYMGDSrqMIQQr4gCtbCWLFkSY2PjbK2pCQkJ2VpRH3F1dc2xvImJCU5OTgCMGzeObt268fHHHwNQtWpVUlJS6N27N2PGjMHIKHtebW5ubrBLkwghhBDCsMTExFC3bl0cHBz48ssvqVatGhkZGezZs4f+/fvz559/PlW9Wq02zx/tC9vy5csZOHAgS5cuJTY2lnLlyr2wcwshRFEoUAurmZkZtWrVYt++fXrb9+3bR1BQUI7HBAYGZiu/d+9eateurc5qlpqami0pNTY2RlEUXpFlYkURs7KyIiEhgYSEBKysrIo6nFyZmpoybNgwhg0bJrP+CSFEIerXrx8ajYaTJ0/y3nvv4evrS+XKlRkyZAjHjx9Xy3311VdUrVoVa2tr3N3d6devH8nJyer+lStX4uDgwI4dO/D398fc3Jxr165lO19aWhqffvopLi4uWFhY8Oabb3Lq1Cl1/927d+natSvOzs5YWlri4+PDihUr8ryGlJQUNm3aRN++fWndujUrV67U2/8otsdt27YtW0L9n//8BxcXF2xtbfn4448ZOXIkNWrUUPfn1ELarl07QkJC1McLFizAx8cHCwsLSpUqxXvvvQdkdY0+fPgw8+bNQ6PRoNFoiImJAbKWOXz99dcxNzfHzc2NkSNHGvRSc0IIw1DgLsFDhgxh6dKlLF++nOjoaAYPHkxsbCx9+vQBsrrqdu/eXS3fp08frl27xpAhQ4iOjmb58uUsW7aMYcOGqWXatGnDwoUL2bBhA1evXmXfvn2MGzeOt99+G2Nj40K4TFHcaTQanJ2dcXZ2fqG/hBeURqPB2toaa2trg45TCCFeJnfu3GH37t30798/x1niH0/yjIyM+Prrr/n9999ZtWoVBw8eZMSIEXrlU1NTmTZtGkuXLuWPP/7AxcUlW50jRoxgy5YtrFq1itOnT+Pt7U1wcDB37twBsnqXRUVFsWvXLqKjo1m4cCElS5bM8zo2btyIn58ffn5+fPDBB6xYsaLAP+yvXbuWL774ghkzZhAREUG5cuX0Vn7Ij/DwcD799FMmT57M+fPn2b17t7oW6Lx58wgMDKRXr17ExcURFxeHu7s7//zzDy1btuS1117j7NmzLFy4kGXLlvGf//ynQOcWQhQ/BeoSDNCxY0du377N5MmTiYuLo0qVKuzcuRMPDw8A4uLi9NZk9fLyYufOnQwePJhvv/2W0qVL8/XXX9O+fXu1zNixY9FoNIwdO5Z//vkHZ2dn2rRpwxdffFEIlyiEEEKI4uzSpUsoikLFihWfWPbxlkUvLy+mTJlC3759WbBggbo9IyODBQsWUL169RzrSElJYeHChaxcuZIWLVoAsGTJEvbt28eyZcsYPnw4sbGx1KxZk9q1awPg6en5xNiWLVvGBx98AEDz5s1JTk7mwIEDNGnS5InHPjJ//nx69uzJRx99BMD48ePZu3evXivyk8TGxmJtbU3r1q2xtbXFw8ODmjVrAmBvb4+ZmRlWVla4urqqxyxYsAB3d3e++eYbNBoNFStW5Pr163z++eeMHz8+x+FfQggBT5GwQla3mn79+uW479/dUwAaNGjA6dOncw/CxIQJEyYwYcKEpwlHiCdKS0tjyJAhQFZ3L0Md/5yZmcmePXuArOWfTEye6i0qhBDiMf+e7DEvhw4dYurUqURFRZGUlERmZiYPHz4kJSVFbZ01MzOjWrVqudZx+fJlMjIyqFu3rrrN1NSU119/XV2Xvm/fvrRv357Tp0/TrFkz2rVrl+vwKoDz589z8uRJtm7dCmR9d+rYsSPLly8vUMJ6/vz5bN/hXn/9dQ4ePJjvOpo2bYqHhwfly5enefPmNG/enHfeeSfPITfR0dEEBgbq/Q3q1q1LcnIyf//9t4zFFULkSn7OEsVCZmYmCxYsYMGCBQY9Xkan0xEeHk54eDg6na6owxFCiFeCj48PGo1GTRZzc+3aNVq2bEmVKlXYsmULERERfPvttwDq2vEAlpaWeSa/uSXIj6+q0KJFC65du8agQYO4fv06jRs31hsu9W/Lli0jMzOTMmXKYGJigomJCQsXLmTr1q3cvXsXyOrO/O8uwo/H/Uhuqzc88qR6bG1tOX36NOvXr8fNzY3x48dTvXp17t27l2v8Oa0oUZAfEoQQxZckrEIIIYR4pZUoUYLg4GC+/fZbUlJSsu1/lGiFh4eTmZnJ7NmzeeONN/D19eX69esFPp+3tzdmZmYcPXpU3ZaRkUF4eDiVKlVStzk7OxMSEsL333/P3Llz+e6773KsLzMzk9WrVzN79mwiIyPV29mzZ/Hw8GDt2rVqfffv39e7xsjISL26/Pz8OHnypN628PBwvcfOzs7ExcWpj7VaLb///rteGRMTE5o0acKXX37Jb7/9RkxMjNpKa2Zmhlar1Svv7+9PWFiYXiIcFhaGra0tZcqUyfG6hRACJGEVQgghRDGwYMECtFotr7/+Olu2bOHixYtER0fz9ddfExgYCECFChXIzMxk/vz5XLlyhTVr1rBo0aICn8va2pq+ffsyfPhwdu/eTVRUFL169SI1NZWePXsCWWNHf/rpJy5dusQff/zBjh079JLZx+3YsYO7d+/Ss2dPqlSpond77733WLZsGQB16tTBysqK0aNHc+nSJdatW5dtqNbAgQNZtmwZq1at4uLFi/znP//ht99+02vlfOutt/jll1/45Zdf+PPPP+nXr59e6+mOHTv4+uuviYyM5Nq1a6xevRqdToefnx+QNR73xIkTxMTEcOvWLXQ6Hf369eOvv/5i4MCB/Pnnn/z0009MmDCBIUOGyPhVIUSe5D+EEEIIIV55Xl5enD59mkaNGjF06FCqVKlC06ZNOXDggDpLbo0aNfjqq6+YMWMGVapUYe3atUybNu2pzjd9+nTat29Pt27dCAgI4NKlS+zZswdHR0cgqxVy1KhRVKtWjfr162NsbMyGDRtyrGvZsmU0adIEe3v7bPvat29PZGQkp0+fpkSJEnz//ffs3LmTqlWrsn79eiZOnKhXvmvXrowaNYphw4YREBDA1atXCQkJwcLCQi3To0cPPvzwQ7p3706DBg3w8vKiUaNG6n4HBwe2bt3KW2+9RaVKlVi0aBHr16+ncuXKAAwbNgxjY2P8/f1xdnYmNjaWMmXKsHPnTk6ePEn16tXp06cPPXv2ZOzYsU/1/Aohig+N8oosdJqUlIS9vT2JiYnY2dkVdTjCwKSkpGBjYwNAcnJyjssaGIL09HT1y9GoUaMwMzMr4oiEePXJ54co7po2bYqrqytr1qwp6lCEECIbmYJUCCGEEKKYSE1NZdGiRQQHB2NsbMz69evZv38/+/btK+rQhBAiR5KwCiGEEEIUExqNhp07d/Kf//yHtLQ0/Pz82LJlS4GWxhFCiBdJugSLYkGn0xEbGwtAuXLlDHaCB0VRSExMBLIWX5ep/oV4/uTzQwghhDBc0sIqigUjIyM8PT2LOown0mg0ODg4FHUYQgghhBBCGATDbGYSQgghhBBCCFHsScIqioX09HSGDx/O8OHDSU9PL+pwcqXVatm7dy979+7Ntui6EEKIpxcSEkK7du2KOgwhhBAFJAmrKBYyMjKYNWsWs2bNIiMjo6jDyZVWq+XYsWMcO3ZMElYhhHhFabVadDpdUYchhBAvBUlYhRBCCFGsffXVV1StWhVra2vc3d3p168fycnJ6v6GDRui0Wiy3WJiYvJ1/MqVK3FwcGDHjh34+/tjbm7OtWvXuHv3Lt27d8fR0RErKytatGjBxYsXX/TlCyGEQZOEVQghhBDFmpGREV9//TW///47q1at4uDBg4wYMULdv3XrVuLi4tTbu+++i5+fH6VKlcrX8ZC1/um0adNYunQpf/zxBy4uLoSEhBAeHs727ds5duwYiqLQsmVLg+4JJIQQL5rMEiyEEEKIYm3QoEHqfS8vL6ZMmULfvn1ZsGABACVKlFD3z5kzh4MHD3LixAksLS3zdTxkDU1ZsGAB1atXB+DixYts376dX3/9laCgIADWrl2Lu7s727Zt4/33339elyuEEC8VSViFEEIIUawdOnSIqVOnEhUVRVJSEpmZmTx8+JCUlBSsra3Vcrt27WLkyJH8/PPP+Pr6Fuh4MzMzqlWrph4THR2NiYkJderUUbc5OTnh5+dHdHT0C7hqIYR4OUiXYCGEEEIUW9euXaNly5ZUqVKFLVu2EBERwbfffgug1zU3KiqKTp06MX36dJo1a1bg4y0tLdFoNOpjRVFyjEdRFL1yQghR3EkLqxBCCCGKrfDwcDIzM5k9ezZGRlm/42/atEmvzO3bt2nTpg3vvvsugwcPLvDxOfH39yczM5MTJ06oXYJv377NhQsXqFSpUmFcmhBCvBIkYRXFgqWlJb///rt631CZmprSt29f9b4QQojCk5iYSGRkpN42Z2dnMjMzmT9/Pm3atOHXX39l0aJFemXeffddLC0tmThxIvHx8XrHVqhQ4YnH58THx4e2bdvSq1cvFi9ejK2tLSNHjqRMmTK0bdu2UK5XCCFeBRoltz4pL5mkpCTs7e1JTEzEzs6uqMMRQgjxkpDPj+IhJCSEVatWZdv+4YcfUr16dWbOnMm9e/eoX78+Xbt2pXv37ty9excHB4dcu+hevXoVT09P5syZk+fxK1euZNCgQdy7d0/v+Lt37/LZZ5+xfft20tPTqV+/PvPnz8fHx+d5PAVCCPFSkoRVCCFEsSafH0IIIYThki7BolhIT09n6tSpAIwePRozM7MijihnWq2WI0eOAFCvXj2MjY2LOCIhhBBCCCGKjiSs4qV25OJN9kfdwNTYiFbV3KhZzjHHchkZGUyaNAmA4cOHG3TCevjwYQCCgoIkYRVCCCGEEMWaJKzipaTTKYz76XfWnohVty09epWQup6Ma+WPsZEsCSCEEEIIIcTLTtZhFS+lhYcvs/ZELBrgDV8nAspntayu/DWGsdvOFW1wQgghhBBCiEIhCat46Vy9lcLc/RcAeD+oHB3qevBBAy+61PcAYP3Jv1h74lpRhiiEEKKYCAkJoV27doVa58qVK3FwcFAfT5w4kRo1ahTqOYQQ4mUhCat46czac54MrULFMna84VdS3V67ghPBNd0A+M8v0Vy/96CoQhRCCGFgQkJC0Gg0aDQaTExMKFeuHH379uXu3btFHVo2HTt25MKFC+rjYcOGceDAgSKMSAghio4krOKl8vfdVHb9HgdA69plsu1vUs2VciWteJCuZZR0DRZCCPGY5s2bExcXR0xMDEuXLuXnn3+mX79+RR1WNpaWlri4uKiPbWxscHJyKsKIhBCi6EjCKl4q3x+PRaeAj5stpUtYZttvbKTh/brl0ACH/7zJiau3X3yQQgghDJK5uTmurq6ULVuWZs2a0bFjR/bu3QtkzdLes2dPvLy8sLS0xM/Pj3nz5ukdr9VqGTJkCA4ODjg5OTFixAj+vZx9Wloan376KS4uLlhYWPDmm29y6tQpdX9oaCgajYYDBw5Qu3ZtrKysCAoK4vz582qZ/HQJXr58OZUrV8bc3Bw3NzcGDBhQSM+SEEIYFklYxUtDp1P4KfIfAOpWLJlruTIlrKjtXQKAyTuiALCwsODkyZOcPHkSCwuL5x/sUzIxMeHjjz/m448/xsREJvEWQojn5cqVK+zevRtTU1MAdDodZcuWZdOmTURFRTF+/HhGjx7Npk2b1GNmz57N8uXLWbZsGUePHuXOnTv8+OOPevWOGDGCLVu2sGrVKk6fPo23tzfBwcHcuXNHr9yYMWOYPXs24eHhmJiY0KNHj3zHvnDhQvr370/v3r05d+4c27dvx9vb+xmeDSGEMFzyjVi8NCL/vkdc4kPMTY2oVNY+z7LNa5bm9JW7/PFPEv+9eJP6Ps689tprLyjSp2dkZESZMtm7OgshhHh2O3bswMbGBq1Wy8OHDwH46quvADA1NVXX6wbw8vIiLCyMTZs20aFDBwDmzp3LqFGjaN++PQCLFi1iz5496jEpKSksXLiQlStX0qJFCwCWLFnCvn37WLZsGcOHD1fLfvHFFzRo0ACAkSNH0qpVKx4+fJivH1X/85//MHToUD777DN128vwGSeEEE9DWljFS2Pnb1ljVyu722NqkvdL19HGjNf+18o678DF5x6bEEIIw9eoUSMiIyM5ceIEAwcOJDg4mIEDB6r7Fy1aRO3atXF2dsbGxoYlS5YQG5u13ndiYiJxcXEEBgaq5U1MTKhdu7b6+PLly2RkZFC3bl11m6mpKa+//jrR0dF6sVSrVk297+aWNWFgQkLCE68hISGB69ev07hx4wJevRBCvJwkYRUvjf3RNwCo5uGQr/KNqpRCo4GImLucupzAzJkzmTlzJunp6c8xymej1Wr59ddf+fXXX9FqtUUdjhBCvFKsra3x9vamWrVqfP3116Slpamtqps2bWLw4MH06NGDvXv3EhkZyUcffVSgz4xH41k1Gk227f/e9qgr8uPldTrdE89haZl9/gYhhHiVScIqXgr/3HtAzO1UjDTgW9ouX8c421tQ/X/J7fxDfzJixAhGjBhBRkbGc4z02Wi1Wvbv38/+/fslYRVCiOdswoQJzJo1i+vXr3PkyBGCgoLo168fNWvWxNvbm8uXL6tl7e3tcXNz4/jx4+q2zMxMIiIi1Mfe3t6YmZlx9OhRdVtGRgbh4eFUqlSpUGK2tbXF09NTlrkRQhQbMoZVvBR+vXQLAPeS1liYGef7uPqVSxEZc4+j5289r9CEEEK8pBo2bEjlypWZOnUqPj4+rF69mj179uDl5cWaNWs4deoUXl5eavnPPvuM6dOn4+PjQ6VKlfjqq6+4d++eut/a2pq+ffsyfPhwSpQoQbly5fjyyy9JTU2lZ8+ehRb3xIkT6dOnDy4uLrRo0YL79+/z66+/6nVvFkKIV4UkrOKlEPa/hNXHzbZAx3k4W1GmhCV/xT98HmEJIYR4yQ0ZMoSPPvqICxcuEBkZSceOHdFoNHTu3Jl+/fqxa9cutezQoUOJi4sjJCQEIyMjevTowTvvvENiYqJaZvr06eh0Orp168b9+/epXbs2e/bswdHRsdBi/vDDD3n48CFz5sxh2LBhlCxZkvfee6/Q6hdCCEOiUf69gNhLKikpCXt7exITE7Gzy1+XUfFyUBSFOlMPkHA/jb7BPviULljSevzCLTYcusBfc7I+zJOTk7G2tn4eoT6z9PR0pk2bBsCoUaMwMzMr4oiEePXJ54cwNIsXL2bKlCn8/fffRR2KEEIUORnDKgze33cfkHA/DSMNeLgUPNGs6eVYoG7EQgghRFH566+/2LlzJ5UrVy7qUIQQwiBIl2Bh8M7+fQ+A0iWsMHvCcjY5MTc1plYFR2RxGyGEEIYuICCAMmXKsHLlyqIORQghDIIkrMLgRcbeA7LGoz6t2hVKsOF/9xOSH+JloF2ChRBCFG83b94s6hCEEMKgSMIqDN6jFtZyJZ8+ySzn6kiVT2ZzMymNLWcTGNbMqZCiK1wmJiZ8+OGH6n0hhBBCCCGKMxnDKgxahlbHuX+yZl8s9wwtrMbGxjQOboxFuWrsOHejsMIrdEZGRnh6euLp6YmRkbw9hRBCCCFE8SbfiIVBu3DjPg8zdFiYGuFsb/FMdQWUL4GxkYaYmymc/utuIUUohBBC5G3ixInUqFFDfRwSEkK7du2KLB4hhHiZSMIqDFrU9SQAyjhZYaTRPHU9mRkZHNmyBqvL+1G0mXx/IrawQixUWq2WkydPcvLkSbRabVGHI4QQr4yQkBA0Go16c3Jyonnz5vz2229FHZoQQog8SMIqDNr5+PsAlHa0fKZ6MjMyWDplDL9vmoOizWT/HzfI1OoKI8RCpdVq2bVrF7t27ZKEVQghClnz5s2Ji4sjLi6OAwcOYGJiQuvWrZ+6voyMjEKMTgghRE4kYRUG7fyNrITV9RkT1sdZmRuT9CCDfX8mFFqdQgghDJ+5uTmurq64urpSo0YNPv/8c/766y91Zt7PP/8cX19frKysKF++POPGjdNLSh917V2+fDnly5fH3NwcRVFITEykd+/euLi4YGdnx1tvvcXZs2fzHdfu3bt58803cXBwwMnJidatW3P58uVCv34hhHgZScIqDNqfj1pYSxRewlqlnD0AW8/8XWh1CiGEeLkkJyezdu1avL29cXLKmjne1taWlStXEhUVxbx581iyZAlz5szRO+7SpUts2rSJLVu2EBkZCUCrVq2Ij49n586dREREEBAQQOPGjblz506+YklJSWHIkCGcOnWKAwcOYGRkxDvvvINOZ3g9gYQQ4kWTdTOEwbqTks7N+2kAuDo824RLj6vu4Uj4tVR+vXCLhxlaLEyNC61uIYQQhmvHjh3Y2NgAWUmim5sbO3bsUGdlHzt2rFrW09OToUOHsnHjRkaMGKFuT09PZ82aNTg7OwNw8OBBzp07R0JCAubm5gDMmjWLbdu2sXnzZnr37v3EuNq3b6/3eNmyZbi4uBAVFUWVKlWe7aKFEOIlJy2swmD9GZ814ZKTrRnmhZhUepWywdbShNR0Lb/8Hldo9QohhDBsjRo1IjIyksjISE6cOEGzZs1o0aIF165dA2Dz5s28+eabuLq6YmNjw7hx44iN1Z+kz8PDQ01WASIiIkhOTsbJyQkbGxv1dvXq1Xx36718+TJdunShfPny2NnZ4eXlBZDt3EIIURxJC6swWI8mXHIrxPGrAEZGGmp4OnIk+ibbzl6nfc2yhVq/EEIIw2RtbY23t7f6uFatWtjb27NkyRJat25Np06dmDRpEsHBwdjb27NhwwZmz56drY7H6XQ63NzcCA0NzXY+BweHfMXVpk0b3N3dWbJkCaVLl0an01GlShXS09MLfI1CCPGqkYRVGKznlbAC1CyflbCevHSblLRMrM3lrSCEEMWNRqPByMiIBw8e8Ouvv+Lh4cGYMWPU/Y9aXvMSEBBAfHw8JiYmeHp6FjiG27dvEx0dzeLFi6lXrx4AR48eLXA9QgjxqnqqLsELFizAy8sLCwsLatWqxZEjR/Isf/jwYWrVqoWFhQXly5dn0aJF2crcu3eP/v374+bmhoWFBZUqVWLnzp1PE554RVy+mQxAqUIYv2pqZsboRasZvWg1pmZmeDhb42hjRlqmjm2/XX/m+guLiYkJnTt3pnPnzpiYSBIthBCFKS0tjfj4eOLj44mOjmbgwIEkJyfTpk0bvL29iY2NZcOGDVy+fJmvv/6aH3/88Yl1NmnShMDAQNq1a8eePXuIiYkhLCyMsWPHEh4e/sTjHR0dcXJy4rvvvuPSpUscPHiQIUOGFMblCiHEK6HACevGjRsZNGgQY8aM4cyZM9SrV48WLVrkOs7i6tWrtGzZknr16nHmzBlGjx7Np59+ypYtW9Qy6enpNG3alJiYGDZv3sz58+dZsmQJZcqUeforEy+9K7dSAHCxe/aE1djEhFoNm1CrYROMTUzQaLK6BQNsj/znmesvLEZGRvj6+uLr66tOAiKEEKJw7N69Gzc3N9zc3KhTpw6nTp3ihx9+oGHDhrRt25bBgwczYMAAatSoQVhYGOPGjXtinRqNhp07d1K/fn169OiBr68vnTp1IiYmhlKlSj3xeCMjIzZs2EBERARVqlRh8ODBzJw5szAuVwghXgkaRVGUghxQp04dAgICWLhwobqtUqVKtGvXjmnTpmUr//nnn7N9+3aio6PVbX369OHs2bMcO3YMgEWLFjFz5kz+/PNPTE1N8xVHWloaaWlp6uOkpCTc3d1JTEzEzs6uIJckDFDigwyqT9oLwNQPqj+XmXz/vp3KV9v/xNRYw+lxTbG1yN9rTwjxaklKSsLe3l4+P4QQQggDVKAmnPT0dCIiImjWrJne9mbNmhEWFpbjMceOHctWPjg4mPDwcHUx7u3btxMYGEj//v0pVaoUVapUYerUqWi12lxjmTZtGvb29urN3d29IJciDNzV/7Wu2lmZFkqympmRwcGtGzm4dSOZ/3vdlSlhSQkbMzK0Cj+fM4zZgrVarTqDZV6vfyGEEEIIIYqDAiWst27dQqvVZuviUqpUKeLj43M8Jj4+PsfymZmZ3Lp1C4ArV66wefNmtFotO3fuZOzYscyePZsvvvgi11hGjRpFYmKievvrr78KcinCwF29lTV+1cXOvFDqy8zI4NvRg/l29GA1YdVoNFTzcABgl4Esb6PVavnpp5/46aefJGEVQgghhBDF3lPN6qLRaPQeK4qSbduTyj++XafT4eLiwnfffYexsTG1atXi+vXrzJw5k/Hjx+dYp7m5ubpAt3j1XL2Z1cLqXAjjV/NS1cOB0D8SOHXlDg/StViaFX7XYyGEEEIIIcTTKVALa8mSJTE2Ns7WmpqQkJDrxAKurq45ljcxMcHJyQkANzc3fH19MTb+/2ShUqVKxMfHyxpkxdTl/3UJdrZ/vj9KeLhYY2tpwsMMHbuiDKOVVQghhBBCCJGlQAmrmZkZtWrVYt++fXrb9+3bR1BQUI7HBAYGZiu/d+9eateurU6wVLduXS5duoROp1PLXLhwATc3N8zMzAoSonhFqC2s9s+3hdVIo6Hq/7oF7zyXc7d2IYQQr77Q0FA0Gg337t3L9zGenp7MnTtXfazRaNi2bdsLiScmJgaNRkNkZGShnE8IIQxVgdfNGDJkCEuXLmX58uVER0czePBgYmNj6dOnD5A1trR79+5q+T59+nDt2jWGDBlCdHQ0y5cvZ9myZQwbNkwt07dvX27fvs1nn33GhQsX+OWXX5g6dSr9+/cvhEsULxtFUdRJl5wLaQxrXh6NYz1++TYZWl3ehYUQQrx0HiV/ud0aNWpEUFAQcXFx2NvbP/V54uLiaNGiRSFGnjt3d3fi4uKoUqXKCzmfEEIUlQKPYe3YsSO3b99m8uTJ6j/KnTt34uHhAWT9s358TVYvLy927tzJ4MGD+fbbbyldujRff/017du3V8u4u7uzd+9eBg8eTLVq1ShTpgyfffYZn3/+eSFconjZxCc95EGGFiMNONk+/4S1gqstVubGJD/M5MD5BJr7uz73cwohhHhxHiWj/7Z9+3b69OlDv379MDMzw9X12f7/P+vxBWFsbPxCzyeEEEWlwC2sAP369SMmJoa0tDQiIiKoX7++um/lypWEhobqlW/QoAGnT58mLS2Nq1evqq2xjwsMDOT48eM8fPiQy5cvM3r0aL0xraL4eNS66mRrjrFR7pN5FRZjIw2V3bN+Ud/x2/Xnfj4hhBAv1qNk9PHb3bt3GT58OKNHj+b999/PsQtuWFgY9evXx9LSEnd3dz799FNSUlJyPc/jXYIfddndunUrjRo1wsrKiurVq6tr0ANcu3aNNm3a4OjoiLW1NZUrV2bnzp051v3gwQNatWrFG2+8wZ07d6RLsBCi2HiqhFWI5+mvO6lA4baumpqZMXTuYobOXYxpDuOiH3ULPnrxFtoi7BZsYmLCe++9x3vvvYeJyVNN4i2EEOIJ7t27R7t27WjQoAFTpkzJscy5c+cIDg7m3Xff5bfffmPjxo0cPXqUAQMGFOhcY8aMYdiwYURGRuLr60vnzp3JzMwEoH///qSlpfHf//6Xc+fOMWPGDGxsbLLVkZiYSLNmzUhPT+fAgQOUKFGi4BcthBAvKflGLAzOX3ceAOBkW3gTbhmbmBDUvE2u+31L22FmYsS9lAzCrt6hnnfJQjt3QRgZGVG5cuUiObcQQhQHOp2OLl26YGxszPfff5/rsnwzZ86kS5cuDBo0CAAfHx++/vprGjRowMKFC7GwyN+kgMOGDaNVq1YATJo0icqVK3Pp0iUqVqxIbGws7du3p2rVqgCUL18+2/E3btygY8eOVKhQgfXr18tklEKIYkdaWIXB+etuVguro82LW2fX1MSISmXtAPjld1neRgghXlWjR4/m2LFj/PTTT9jZ2eVaLiIigpUrV2JjY6PegoOD0el0XL16Nd/nq1atmnrfzc0NyFreD+DTTz/lP//5D3Xr1mXChAn89ttv2Y5v0qQJ5cuXZ9OmTZKsCiGKJUlYhcH5/y7BhffBrM3MJGz3z4Tt/hnt/7pi/Zv//8axHr14q9DOW1A6nY4//viDP/74Q2+ZJyGEEM9u48aNzJo1iw0bNuDj45NnWZ1OxyeffEJkZKR6O3v2LBcvXqRChQr5PuejJfwAtTX30f/3jz/+mCtXrtCtWzfOnTtH7dq1mT9/vt7xrVq14siRI0RFReX7nEII8SqRLsHC4Px1N6tLcIlCbGHNSE9n9qBPAFh7+hLGOYwPrVTWDg3w9+1ULt+6T4WStoV2/vzKzMxk8+bNQNYSUfJruhBCFI7IyEh69OjB9OnTCQ4OfmL5gIAA/vjjD7y9vZ9rXO7u7vTp04c+ffowatQolixZwsCBA9X906dPx8bGhsaNGxMaGoq/v/9zjUcIIQyNtLAKg/IwQ8vN+2kAlCjEFtb8sLEwxcPFGoDtv0m3YCGEeFXcunWLdu3a0bBhQz744APi4+P1bjdv3sx2zOeff86xY8fo378/kZGRXLx4ke3bt+slk89q0KBB7Nmzh6tXr3L69GkOHjxIpUqVspWbNWsWXbt25a233uLPP/8stPMLIcTLQFpYhUH5+3/jVy1MjbAye/HLGlV2tycmIYVDf95k8Fu+L/z8QgghCt8vv/zCtWvXuHbtmjqO9HEeHh6sXLlSb1u1atU4fPgwY8aMoV69eiiKQoUKFejYsWOhxaXVaunfvz9///03dnZ2NG/enDlz5uRYds6cOWi1Wt566y1CQ0OlB44QotjQKIqiFHUQhSEpKQl7e3sSExPznERBGLZDfybw0cpTlC5hybC22X9lfloPU1PpGpDVrWvt6UtYWFnlWC7+7gO+3BaNibGGiLFNsLd8sV8I0tPTmTZtGiBdgoV4UeTzQwghhDBc0iVYGJRHMwQ72RRNolbKwYISNmZkahV2/RFfJDEIIYQQQgghskjCKgzKoxmCS9i+uCVtHqfRaNTZgvdF3yiSGIQQQgghhBBZJGEVBuWvO49mCC66rrCV/5ewnrpyB61WlpYRQgghhBCiqMikS8KgPOoSXNgtrCampvSfOke9n5cKrjaYmxiR9CCTsKu3qeftXKix5MXY2Ji2bduq94UQQgghhCjOpIVVGJRHXYILewyriakpb73bkbfe7fjEhNXE2Ai/MlkTr/zy+4sdx2psbEyNGjWoUaOGJKxCCPEK8PT0ZO7cuUUdhhBCvLQkYRUGI+lhBkkPMwFwLMIuwfD/3YLDLt0q0jiEEEIUjpCQENq1a/fCz3vq1Cl69+5dqHU2bNiQQYMGFfi4kJAQJk6cWKixCCHE8yYJqzAYcfceAmBtboy5aeG2LmozM4kI3U9E6H60mZlPLF+xbFYLa+ytVGL/1035RdDpdFy4cIELFy6g08n4WSGEeFmlp6cD4OzsjFUuS6kJIYR4MklYhcGIT8pKWO2sCr91NSM9nal9ujO1T3cy/vclIi+2lqaUdcr6gvEil7fJzMxk/fr1rF+/nsx8JNZCCCGe3VdffUXVqlWxtrbG3d2dfv36kZycrO6fOHEiNWrU0Dtm7ty5eHp6qo8fteBOmzaN0qVL4+vrC2TvEpyYmEjv3r1xcXHBzs6Ot956i7Nnz2Y715o1a/D09MTe3p5OnTpx//599TyHDx9m3rx5aDQaNBoNMTExAERFRdGyZUtsbGwoVaoU3bp149Yt6SkkhHi5ScIqDEZ8YtYMwQ7WeY8xfVEq/m8c6+ELCUUciRBCiOfJyMiIr7/+mt9//51Vq1Zx8OBBRowYUeB6Dhw4QHR0NPv27WPHjh3Z9iuKQqtWrYiPj2fnzp1EREQQEBBA48aNuXPnjlru8uXLbNu2jR07drBjxw4OHz7M9OnTAZg3bx6BgYH06tWLuLg44uLicHd3Jy4ujgYNGlCjRg3Cw8PZvXs3N27coEOHDk//xAghhAGQWYKFwYhLzGphtbcykIS1rB37f4vn7LV7ZGh1mBrL7ztCCPEqenw8qJeXF1OmTKFv374sWLCgQPVYW1uzdOlSzMxy7il06NAhzp07R0JCAubmWbPhz5o1i23btrF582Z1rKtOp2PlypXY2toC0K1bNw4cOMAXX3yBvb09ZmZmWFlZ4erqqta9cOFCAgICmDp1qrpt+fLluLu7c+HCBXx9fVm5cmWBrkcIIQyBJKzCYNz4X5dge+uinXDpEQ9nayzMjElJ0/Lr5Vs09HUp6pCEEEI8B4cOHWLq1KlERUWRlJREZmYmDx8+JCUlBWtr63zXU7Vq1VyTVYCIiAiSk5NxcnLS2/7gwQMuX76sPvb09FSTVQA3NzcSEvLu7RMREcGhQ4ewsbHJtu/y5ctqF2UhhHjZSMIqDMajFlYHA2lhNTbS4FfalrMx99gbfUMSViGEeAVdu3aNli1b0qdPH6ZMmUKJEiU4evQoPXv2JCMjA8jqMqwoit5xj/Y97knJrU6nw83NjdDQ0Gz7HBwc1Pum/1p+TaPRPHEiPp1OR5s2bZgxY0a2fW5ubnkeK4QQhkwSVmEw1C7BBtLCCuBXxo6zMfc4fvl2UYcihBDiOQgPDyczM5PZs2djZJQ19GPTpk16ZZydnYmPj0dRFDQaDQCRkZEFPldAQADx8fGYmJjoTdhUUGZmZmi12mx1b9myBU9PT0xM5OudEOLVIYPyhMGIN7AWVvj/iZeu3kwhLulBEUcjhBDiWSQmJhIZGal3c3Z2JjMzk/nz53PlyhXWrFnDokWL9I5r2LAhN2/e5Msvv+Ty5ct8++237Nq1q8Dnb9KkCYGBgbRr1449e/YQExNDWFgYY8eOJTw8PN/1eHp6cuLECWJiYrh16xY6nY7+/ftz584dOnfuzMmTJ7ly5Qp79+6lR48e2ZJbIYR4mUjCKgzCg3QtiQ+yulc9jxZWE1NTPh73BR+P+wIT0/wnxA7WZrg6WKAosPsFLG9jbGxMixYtaNGiBcbGhbsWrRBCFHehoaHUrFlT77Z8+XK++uorZsyYQZUqVVi7di3Tpk3TO65SpUosWLCAb7/9lurVq3Py5EmGDRtW4PNrNBp27txJ/fr16dGjB76+vnTq1ImYmBhKlSqV73qGDRuGsbEx/v7+ODs7ExsbS+nSpfn111/RarUEBwdTpUoVPvvsM+zt7dWWYyGEeBlplH8PynhJJSUlYW9vT2JiInZ2dkUdjiigq7dSaDQrFDMTI6Z9UF3tcmUItp/6m9DfE2hYyZmVH75e1OEIIQqZfH4IIYQQhkt+chMGQe0ObG1qUMkq/H+34NMxd5846YUQQgghhBCi8EjCKgxC/P/Gh9pbPZ8Jl7RaLb+fCOP3E2EFHstTvpQNZiZGJD3I5GTsvecS3yM6nY6YmBhiYmIkORZCCCGEEMWeJKzCIMQnpgFg/5wmXMpIS2PCh+8x4cP3yEhLK9CxJsZGeLtlrWu3N+r5jmPNzMxk1apVrFq1iszMzOd6LiGEEEIIIQydJKzCIMQnZrWwOlgbzgzBj/MrndUt+MQVWd5GCCGEEEKIF0USVmEQDHEN1sf5/i9hPR93n+S07IvFCyGEKD4mTpxIqVKl0Gg0bNu2rdDqrFGjRqHUJYQQrxJJWIVBiE/6X8JqQGuwPs7F3hx7K1MytQoHzt8s6nCEEEIUUEhICBqNBo1Gg4mJCeXKlaNv377cvXu3QPVER0czadIkFi9eTFxcHC1atHhOEeuLiYlBo9EQGRn5Qs4nhBCGQhJWYRAetbA6PKdJl56VRqPBt7QtAIcvSsIqhBAvo+bNmxMXF0dMTAxLly7l559/pl+/fgWq4/LlywC0bdsWV1dXzM3Nn0eoQggh/kcSVlHkMrQ6bt3/36RLBjqGFf6/W3DE1TtFHIkQQoinYW5ujqurK2XLlqVZs2Z07NiRvXv3qvu1Wi09e/bEy8sLS0tL/Pz8mDdvnrp/4sSJtGnTBgAjIyN1GbZTp07RtGlTSpYsib29PQ0aNOD06dN6505MTKR37964uLhgZ2fHW2+9xdmzZwvt2hRF4csvv6R8+fJYWlpSvXp1Nm/enO9rg6yZ6idPnkzZsmUxNzenRo0a7N69u9BiFEKIpyEJqyhyN++noQDGRhqsLUyKOpxc+bhltbDG3krl+v+W4RFCCPFyunLlCrt378bU9P9/KNXpdJQtW5ZNmzYRFRXF+PHjGT16NJs2bQJg2LBhrFixAoC4uDji4uIAuH//Ph9++CFHjhzh+PHj+Pj40LJlS+7fvw9kJZOtWrUiPj6enTt3EhERQUBAAI0bN+bOncL5EXTs2LGsWLGChQsX8scffzB48GA++OADDh8+nK9rA5g3bx6zZ89m1qxZ/PbbbwQHB/P2229z8eLFQolRCCGehuFmB6LYUCdcsjLF6H+/Vhc2YxMTug0fq95/GnZWprg6WBB/7yF7o24Q8oZnIUaYxdjYmCZNmqj3hRBCFJ4dO3ZgY2ODVqvl4cOsz56vvvpK3W9qasqkSZPUx15eXoSFhbFp0yY6dOiAjY0NDg4OALi6uqrl3nrrLb3zLF68GEdHRw4fPkzr1q05dOgQ586dIyEhQe1CPGvWLLZt28bmzZvp3bv3M11XSkoKX331FQcPHiQwMBCA8uXLc/ToURYvXkyDBg2eeG2PYvr888/p1KkTADNmzODQoUPMnTuXb7/99pliFEKIpyUJqyhy8YnPf8IlUzMz2vUs2DilnPiWtiP+3kOOXrr13BLWunXrFnq9QgghoFGjRixcuJDU1FSWLl3KhQsXGDhwoF6ZRYsWsXTpUq5du8aDBw9IT09/4uy9CQkJjB8/noMHD3Ljxg20Wi2pqanExsYCEBERQXJyMk5OTnrHPXjwQB0T+yyioqJ4+PAhTZs21duenp5OzZo183VtSUlJXL9+PdtnUN26dQu167IQQhSUJKyiyKkzBBvokjaP8y1ty3+jEoi8dg9FUdTxS0IIIQyftbU13t7eAHz99dc0atSISZMmMWXKFAA2bdrE4MGDmT17NoGBgdja2jJz5kxOnDiRZ70hISHcvHmTuXPn4uHhgbm5OYGBgaSnpwNZ3XHd3NwIDQ3NduyjFttnodPpAPjll18oU6aM3r5HLbr5vbZ/f67JZ50QoqhJwiqKXHxi1nhQh+fYwqrVarkadQ4AL/+qT93dtoKrDUYauHU/jej4JPzd7AszTHQ6nTomys3NDSMjGWYuhBDPy4QJE2jRogV9+/aldOnSHDlyhKCgIL2Zg/PTAnrkyBEWLFhAy5YtAfjrr7+4deuWuj8gIID4+HhMTEzw9PQs9Ovw9/fH3Nyc2NhYGjRokGuMeV2bnZ0dpUuX5ujRo9SvX1/dHhYWxuuvv17oMQshRH5JwiqKnDqG9TnOEJyRlsbn72d9kVh7+hLGVlZPVY+5qTGeLjZcuZHM3j8TCj1hzczMZOnSpQCMGjUKMzPDb3UWQoiXVcOGDalcuTJTp07lm2++wdvbm9WrV7Nnzx68vLxYs2YNp06dwsvLK896vL29WbNmDbVr1yYpKYnhw4djaWmp7m/SpAmBgYG0a9eOGTNm4Ofnx/Xr19m5cyft2rWjdu3a+Y75/Pnz2bb5+/szbNgwBg8ejE6n48033yQpKYmwsDBsbGz48MMP83Vtw4cPZ8KECVSoUIEaNWqwYsUKIiMjWbt2bb7jE0KIwiYJqyhyapdgA12D9d98Stty5UYyxy7fZlAjn6IORwghxDMYMmQIH330EZ9//jl9+vQhMjKSjh07otFo6Ny5M/369WPXrl151rF8+XJ69+5NzZo1KVeuHFOnTmXYsGHqfo1Gw86dOxkzZgw9evTg5s2buLq6Ur9+fUqVKlWgeB9NiPS4q1evMmXKFFxcXJg2bRpXrlzBwcGBgIAARo8eDZCva/v0009JSkpi6NChJCQk4O/vz/bt2/Hxkc86IUTR0SiKohR1EIUhKSkJe3t7EhMTsbOzK+pwRAHUnX6Qf+494NNWvni62DyXczxMTaVrQNa4pbWnL2HxlC2sAFdvJDN/5wWszI35bXwzTIwLr9tueno606ZNA6SFVYgXRT4/hBBCCMMlA+REkdLpFG68ZC2s5ZytMTc1IjVNy/GYwlk/TwghhBBCCJGdJKyiSN1JTSdTp6Aha53Tl4GxkQZvV1sADl24WcTRCCGEEEII8eqShFUUqUdrsNpammJs9PJMm+/tltV1+dRVaWEVQgghhBDieZGEVRSpFzFD8PPg7ZbVwvrn9SQeZmiLOBohhBBCCCFeTTJLsChSj2YIfp5rsAIYm5jQof8Q9f6zcnO0xNrcmJQ0Lb9euUVjv4LN8pgbY2NjdQ29p10rVgghxIsVGhpKo0aNuHv3Lg4ODkUdjhBCvFIkYRVFKj7xAQB2z3nCJVMzMzoOHPbkgvlkpNFQ3tWWc9fucfhi4SasDRs2LJS6hBBC/L+QkBDu3bvHtm3bijoUIYQQBSBdgkWRik9MA8DhJesSDODtmjWONVxmChZCCCGEEOK5kIRVFKn4pKwW1uc9hlWn0xF78TyxF8+j0+kKpU6f0lnjWC/G3SclPaNQ6lQUhYSEBBISEnhFlkgWQgiDd/jwYV5//XXMzc1xc3Nj5MiRZGZmqvvT0tL49NNPcXFxwcLCgjfffJNTp07lWt+DBw9o1aoVb7zxBnfu3CEmJgaNRsOmTZuoV68elpaWvPbaa1y4cIFTp05Ru3ZtbGxsaN68OTdv/v/s86dOnaJp06aULFkSe3t7GjRowOnTp/XOpdFoWLp0Ke+88w5WVlb4+Piwffv2wn+ShBCiiEjCKopU3L0XswZr+sOHDG7TiMFtGpH+8OH/tXfn8VHV9/7H37Mkk4UkJAESEgkSghIWFRP1AiJWuVBxKe4Lsvy0tNReZSmIW1VsBUWqQCmhWLze6q3a1uJyiwpSpCBRJCGorLIGQkIIkI0sM8mc3x8hAyELWedMyOv5eOTxOPM933PO53wdDB++W6vcMyosQCGBdrkqDf17T16r3NPlciklJUUpKSlyuVonCQYA1C8rK0ujR4/WVVddpa1btyolJUXLly/Xb3/7W0+dxx9/XO+//77+53/+R+np6UpISNCoUaN04kTtETYFBQUaOXKknE6n1qxZo4iICM+55557Ts8884zS09Nlt9t1//336/HHH9fChQu1fv167d27V88++6ynflFRkSZMmKD169frq6++Up8+fTR69GgVFRXVeObs2bN1zz336Ntvv9Xo0aM1duzYOmMDgPaIhBWmMQxD2V5adKktWCwW9T69H+v6H1onYQUAeNeSJUvUo0cPLV68WH379tWYMWM0e/Zs/e53v5Pb7dapU6eUkpKiV155RTfddJP69eun119/XYGBgVq+fHmNex09elTDhw9Xt27d9M9//lPBwcE1zs+YMUOjRo1SYmKipkyZovT0dP3617/W0KFDNWjQID388MNau3atp/4NN9ygBx98UImJiUpMTNQf//hHlZSUaN26dTXuO3HiRN1///1KSEjQnDlzdOrUKW3atKntGg0AvKhZCeuSJUvUq1cvBQQEKCkpSevXr2+w/rp165SUlKSAgADFx8dr6dKl9dZ99913ZbFYNGbMmOaEhnakqLxCpc6qLWHCgtu2h7WtVM9jTTtw0uRIAADNsWPHDg0ePFgWy5m9wIcOHari4mIdPnxYe/fulcvl0tChQz3n/fz8dPXVV2vHjh017jVixAjFx8frr3/9q/z9a/9eu+yyyzzHUVFVi/UNHDiwRllubq7nc25uriZPnqxLLrlEYWFhCgsLU3FxsTIzM+u9b3BwsEJCQmrcBwDasyYnrO+9956mTp2qp59+Wlu2bNGwYcN000031fqfZ7X9+/dr9OjRGjZsmLZs2aKnnnpKjz32mN5///1adQ8ePKgZM2Zo2LBhTX8TtDs5p/dgDfS3yd/ePjv7+5zej3XP0WIVlTGEFwDaG8MwaiSr1WVS1Uias4/Pd93NN9+s9evXa/v27XU+y8/vzGii6mvPLTt7nYWJEycqLS1NCxYs0MaNG5WRkaHIyEg5nc5671vXfQCgPWtylvDqq6/q4Ycf1k9/+lMlJiZqwYIF6tGjh1JSUuqsv3TpUsXFxWnBggVKTEzUT3/6Uz300EOaP39+jXqVlZUaO3asZs+erfj4+Oa9DdqV6oS1Pa4QXK1LqENhQX6qdBta+8Ox818AAPAp/fr108aNG2ssdLdx40aFhIQoNjZWCQkJ8vf314YNGzznXS6XNm/erMTExBr3eumllzRhwgTdeOON9SatTbF+/Xo99thjGj16tPr37y+Hw6G8PKagAOhYmpSwOp1OpaWlaeTIkTXKR44cqY0bN9Z5TWpqaq36o0aN0ubNm2ssKvPCCy+oa9euevjhhxsVS3l5uQoLC2v8oH3xJKxtvOBSW7JYLEo43cu6oZUWXgIAtI2CggJlZGTU+PnZz36mQ4cO6dFHH9XOnTv14Ycf6rnnntP06dNltVoVHBysX/ziF5o5c6Y+/fRTbd++XZMmTVJJSUmdf2eZP3++xo4dqxtuuEE7d+5sUbwJCQl66623tGPHDn399dcaO3asAgMDW3RPAGhv7E2pnJeXp8rKSs+8i2pRUVHKycmp85qcnJw661dUVCgvL0/du3fXl19+qeXLlysjI6PRscydO1ezZ89uSvjwMdmnE9bQdtzDKlUNC07be4J5rADg47744gsNGjSoRtmECRO0cuVKzZw5U5dffrkiIiL08MMP65lnnvHUeemll+R2uzVu3DgVFRUpOTlZn332mcLDw+t8zmuvvabKykrdcMMN+uKLL+qcz9oYb7zxhn72s59p0KBBiouL05w5czRjxoxm3QsA2qsmJazVGjOP43z1q8uLior04IMP6vXXX1eXLl0aHcOTTz6p6dOnez4XFhaqR48ejb4e5ssp9F4Pq81u120PTfYct6bqhZf25xbrZIlT4S14H5vNpsGDB3uOAQCt480339Sbb75Z7/mGVtUNCAjQokWLtGjRojrPX3/99bX2zj63/rnn67pm4sSJmjhxoufzoEGDau33etddd9X4XNee3fn5+fW+CwC0N036m3uXLl1ks9lq9abm5ubW6kWtFh0dXWd9u92uyMhIbdu2TQcOHNCtt97qOV+9UIDdbteuXbvUu3fvWvd1OBxyOBxNCR8+JqegVJIU5oUeVj9/f014/NnzV2yGiBCHIjr560SxU2t3H9MdV8Q2+142m63WEHoAAACgo2rSHFZ/f38lJSVp9erVNcpXr16tIUOG1HnN4MGDa9VftWqVkpOT5efnp759++q7776rMZ/ktttu049+9CNlZGTQa3oBqx4SHNYO92A915l5rCy8BAAAALSWJo+NnD59usaNG6fk5GQNHjxYy5YtU2ZmpiZPrhpu+eSTTyorK0t//vOfJUmTJ0/W4sWLNX36dE2aNEmpqalavny53nnnHUlVw2wGDBhQ4xmdO3eWpFrluLB4hgR7YQ9Wt9utvCNZkqQuMbGyWlt3G52E7p206YfjSj+Y36L7GIahgoICSVJYWFiDQ+0BAACAC12TE9Z7771Xx48f1wsvvKDs7GwNGDBAK1euVM+ePSVJ2dnZNfZk7dWrl1auXKlp06bpD3/4g2JiYrRo0SLdeeedrfcWaHfKXJXKL6laJdobPazOsjL9YsQ1kqT/Td+jgKCgVr1/QnRVD+vBvFPKKy5Xl07NG67ucrm0cOFCSVX/+NPchToAAACAC0GzVp955JFH9Mgjj9R5rq4FDYYPH6709PRG37+hRRFwYaje0sbfblWgf/tfXKhzsL+6hjp0rLBca3bl6t4khrIDAAAALdW64yKBRqoeDhwW5HfBDHvtfbqX9cu97McKAAAAtAYSVpgi5wJacKlan+5V29tsaeE8VgAAAABVSFhhiuoVgr2x4JK3VPewHj5eoqOne5ABAAAANB8JK0xRndB5Yw9WbwkN8lNU5wAZktbsyjU7HAAAAKDdI2GFKbILSiVJYUEXTg+rdGa1YOaxAgAAAC3XrFWCgZbKKSyXJHX20hxWm92mHz8wwXPcVhK6d9KXO481ex6r1WpVcnKy5xgAAADoyEhYYYqc6h5WL81h9fN3aNKzc9v8OdXzWI+cLNWR/BLFdG7afq92u10333xzW4QGAAAAtDt04cDrKirdOlZU1cN6Ia0SLEmdAuzqHh4oSfqceawAAABAi5CwwuuOFZfLbUhWi9Qp0Dud/IZhqODEcRWcOC7DMNr0WQmnt7fZuPd4k681DEOnTp3SqVOn2jxOAAAAwNeRsMLrqre0CQv2l9Vi8cozy0tL9dCQgXpoyECVl5a26bP6nB4W3Jx5rC6XS/Pnz9f8+fPlcrlaOTIAAACgfSFhhdflVCesF9hw4Grx0Z1kkXS0oEwHT5wyOxwAAACg3SJhhddVJ6zeWiHY24IcdsVGVs1jZT9WAAAAoPlIWOF1OYVnhgRfqKr3Y01txjxWAAAAAFVIWOF12Rf4kGBJSuhelbBmZOabGwgAAADQjpGwwuuOVg8JvoB7WOOjOslqkY4Vlmt/XrHZ4QAAAADtEgkrvC67oGqV3gu5hzXA36aLIoMksR8rAAAA0Fze2QQTOM0wjLPmsHovYbXZbbp+zD2eY29I6B6izLwSbdxzXJOGxjfqGqvVqssvv9xzDAAAAHRkJKzwqhOnnHJVGrJICg30XsLq5+/Qoy8t8NrzJKlP9xD967uj2nooX4ZhyNKIPWftdrvGjBnT9sEBAAAA7QBdOPCq6gWXOgXaZbdd2F+/i7sFy2a16ESxU3uOMY8VAAAAaKoLO2OAz8nxrBDs3QWXDMNQWUmJykpKZBiGV57p8LMprsvpeaw7GzeP1TAMOZ1OOZ1Or8UJAAAA+CoSVnhV9fzVzl6cvypJ5aWlGntlgsZemaDy0lKvPbd6e5vUfY3bj9Xlcmnu3LmaO3euXC5XW4YGAAAA+DwSVnhVTgfYg/VsCdFVCevWzHx6TAEAAIAmImGFVx05vaXNhbwH69l6np7HWlDi0o6cIrPDAQAAANoVElZ4laeH1ctDgs3ib7fq4m7BkqQ1u46aHA0AAADQvpCwwquqVwnuKD2s0plhwan7TpgcCQAAANC+kLDCawzDUHb1kGAvrxJspoTunSRJ3x1iHisAAADQFCSs8Jr8EpfKXG5JHWfRJUnq2TVYdptFRaUV+jarwOxwAAAAgHbDbnYA6DiqhwN3CrDLz+7dfyux2qwaPOoWz7E32W1W9erWST9kF2nNrlxdflHneutarVb169fPcwwAAAB0ZCSs8BrPcGATFlzydwRoxsJlXn9utT7dQ/RDdpG+3ndcurH+ena7XXfffbf3AgMAAAB8GF048Joj1QsudaD5q9U881gPF6iy0m1yNAAAAED7QMIKr8npYHuwnq1Hl2D5260qKa9U+uF8s8MBAAAA2gUSVnhNdr55e7CWlZTozr4xurNvjMpKSrz+fJvVovioql7Wtbty663ndDo1e/ZszZ49W06n01vhAQAAAD6JhBVe0xH3YD1b9bDgr/ezHysAAADQGCSs8BozF13yBQnRIZKk7VmFqmAeKwAAAHBeJKzwCsMwOnwPa2xkkAL8rCp1Vurrg/SyAgAAAOdDwgqvOFniUnlFVa9iWFDH7GG1WS2Kj64aFvyvnfXPYwUAAABQhYQVXnEkv2o4cKcAu+y2jvu1uyQmVJL01T56WAEAAIDz6biZA7wqp4MPB6526emEdVd2oYrLKkyOBgAAAPBtdrMDQMdg9oJLVptVVw6/0XNslm5hDnUO9lP+KZfW7M7VTy6LqXHearWqT58+nmMAAACgIyNhhVeYveCSvyNAT//xLVOefTaLxaJLYkK16YfjWrurdsJqt9v1wAMPmBQdAAAA4FvowoFXVCesHXXBpbNdGlO1vc037McKAAAANIiEFV5xZkhwx57DKkl9YkJlkZR1olSHTpaYHQ4AAADgs0hY4RXZ+VU9rOEmJaxlJSV6YFBvPTCot8pKzE0SOwXYFRsZJEn6dHtOjXNOp1Nz5szRnDlz5HQ6zQgPAAAA8BkkrGhzbreh7MLTQ4JNWnRJkspLS1VeWmra8892aWzVsOD1u/NqnXO5XHK5XN4OCQAAAPA5JKxoc3nF5XJWuGWxMCS4WvX2NlsOnlRlpdvkaAAAAADfRMKKNnc4v6pXMyzITzarxeRofMPF3YLlb7eqqKxC6YfzzQ4HAAAA8EkkrGhzh09WJawRnRwmR+I77Darekd3kiSt2n7U5GgAAAAA30TCijZ3+PRKuBGdGA58tuphwal7j5scCQAAAOCbSFjR5qp7WMNJWGuoXnhpZ3ahissqTI4GAAAA8D12swPAhS/LMyTYvITVYrWo/1WDPce+oFtYgDoH+yn/lEuf7czRnVdcJIvFop49e0qSLBbfiBMAAAAwCwkr2lz1kGAze1gdAYF64a33TXt+XSwWi/pdFKaNu/L0+fajuvOKi+Tn56eJEyeaHRoAAADgE5o1JHjJkiXq1auXAgIClJSUpPXr1zdYf926dUpKSlJAQIDi4+O1dOnSGudff/11DRs2TOHh4QoPD9eIESO0adOm5oQGH2MYBosuNSCxR5gk6et9J2QYhsnRAAAAAL6lyQnre++9p6lTp+rpp5/Wli1bNGzYMN10003KzMyss/7+/fs1evRoDRs2TFu2bNFTTz2lxx57TO+/f6a364svvtD999+vtWvXKjU1VXFxcRo5cqSysrKa/2bwCXnFTpVXuGWR1DnYz+xwfE6f7iGy2yw6UexUBtvbAAAAADVYjCZ261xzzTW68sorlZKS4ilLTEzUmDFjNHfu3Fr1Z82apY8++kg7duzwlE2ePFlbt25Vampqnc+orKxUeHi4Fi9erPHjxzcqrsLCQoWFhamgoEChoaFNeSW0oS2ZJ3X7ko3qHOSnZ+8daFocZSUl+sWNV0uSUtZsUkBQkGmxnGvZqj3amVWonw6P1+M39tbChQslSVOmTJG/PwtVAW2N3x8AAPiuJvWwOp1OpaWlaeTIkTXKR44cqY0bN9Z5TWpqaq36o0aN0ubNm+Vyueq8pqSkRC6XSxEREfXGUl5ersLCwho/8D1Z+b6zQnDhyRMqPHnC7DBq6Xd6WPD63cckVX3/S0pKzAwJAAAA8AlNSljz8vJUWVmpqKioGuVRUVHKycmp85qcnJw661dUVCgvL6/Oa5544gnFxsZqxIgR9cYyd+5chYWFeX569OjRlFeBlxz2gRWCfV2/i6p6dHbnFOn4qTKTowEAAAB8R7MWXTp3uw3DMBrcgqOu+nWVS9K8efP0zjvv6B//+IcCAgLqveeTTz6pgoICz8+hQ4ea8grwkjMrBLPgUn0iQhyK7hwgw5A+2XbU7HAAAAAAn9GkbW26dOkim81Wqzc1Nze3Vi9qtejo6Drr2+12RUZG1iifP3++5syZo88//1yXXXZZg7E4HA45HCRBvs7TwxpCD2tDEi8KU05+mdbtOqZ4s4MBAAAAfESTelj9/f2VlJSk1atX1yhfvXq1hgwZUuc1gwcPrlV/1apVSk5Olp/fmVVjX3nlFf3mN7/Rp59+quTk5KaEBR+WdTphDQ8mYW1Ivx5Vw4K3ZJ40ORIAAADAdzR5SPD06dP1pz/9SW+88YZ27NihadOmKTMzU5MnT5ZUNVT37JV9J0+erIMHD2r69OnasWOH3njjDS1fvlwzZszw1Jk3b56eeeYZvfHGG7r44ouVk5OjnJwcFRcXt8Irwixut6FDp4cE08PasIu7dVKgv00l5ZVmhwIAAAD4jCYNCZake++9V8ePH9cLL7yg7OxsDRgwQCtXrlTPnj0lSdnZ2TX2ZO3Vq5dWrlypadOm6Q9/+INiYmK0aNEi3XnnnZ46S5YskdPp1F133VXjWc8995yef/75Zr4azJZbVK4yl1tWixRh8hxWi9Wi3gMu9xz7GpvVosSLQrV133FVBHRWXERQg/PCAQAAgI6gyfuw+ir20fM9X+07rvuWfaXIEIeevqu/2eH4vG8PnNSba/erS4hD3zx1Iwkr4CX8/gAAwHc1a5VgoDEOHj8lSeoSyuJYjXFpbKj8bBblFZUrjbmsAAAAAAkr2s6B41XzV7uGkLA2hsPPpr6xVb07KzKyTI4GAAAAMB8JK9pMdQ9rpA/0sJaXlmjyDVdr8g1Xq7y0xOxw6jWwRyfd5fhWlRn/lMvlMjscAAAAwFQkrGgzB/JO97D6QMJqGNKxI4d17Mhh+fKs7cTYUIVYnQpUuXZkF5gdDgAAAGAqEla0CcMwmMPaDIGOMwt3f/jtERMjAQAAAMxHwoo2kVfs1ClnpSwWKaITe7A2xxe7jpkdAgAAAGAqEla0iere1fBgf9ltfM2a4+CxU9pzrMjsMAAAAADTkEmgTVSvEMxw4JZ5d/Mhs0MAAAAATEPCijZxIO/0CsFsadMin31/1OwQAAAAANPYz18FaLo9ucWSpG5hASZHUsVikS5KuMRz7LsscoSGy20YspZbdOh4ibYeztflF3U2OzAAAADA60hY0Sb2HKtKWKM6+0bC6ggM0sL/+8LsMM7LarfrktF3S5L6fL5X2w4V6N3Nh0hYAQAA0CExJBitzlXp9gwJjvKRHtb26Mr4cEnS6m1HZfjy5rEAAABAGyFhRas7eLxEFW5D/narOgf7mR1Ou9U/rrP87VblFZVrw948s8MBAAAAvI6EFa1uT27VVizdwgJk8ZEJo+WlJZpyy/Wacsv1Ki8tMTucerkrKrR75d+0e+XfZJdbA3t2liS98w2rBQMAAKDjYQ4rWl31gkvRPjJ/VZIMQzq8Z7fn2HcZKi886Tm+KiFCaXtPaO2OXJU6KxTozx9ZAAAAdBz0sKLVeVYI9qGEtb1K6B6iiE7+KnVW6r20w2aHAwAAAHgVCStanWeFYBZcajGrxaKr+kRKkv66mWHBAAAA6FhIWNGq3G5De3NPrxBMD2uruDohUhZJ27MKPfODAQAAgI6AhBWt6uCJEpW6KmW3WRQZ4jA7nAtCeCd/XRIbKkl6I/WAucEAAAAAXkTCila1/UihJKl7eKBsVt9YIfhCcM3pYcH/3JotZ0WlydEAAAAA3kHCila1PbtAkhQbEWhyJDVZLFLXmIvUNeYi+chOO/WwyC+ok/yCOkk6E+iAuDCFBNpVUOLS37dkmRceAAAA4EXskYFWtSO7ao5lTESQyZHU5AgM0tJ/bTI7jPOy2u3qe9sDtcrtNqsGX9pFqzJy9ObGA3rgqjgTogMAAAC8ix5WtKrqIcG+1sN6IRhyaVfZrBbtzi7SNwdPmB0OAAAA0OZIWNFqjheXK6ewTJLUnYS11YUG+emKXuGSpJR1e02OBgAAAGh7JKxoNdXDgbuEOBTgZzM5mprKy0r1+F036fG7blJ5WanZ4dTLXVGhPatWaM+qFXJXVNQ6PyyxqyRp3c5jyi4o83Z4AAAAgFeRsKLVfJuVL0mKjfS93lXDbWjv91u19/utMtyG2eE0wFDpiWMqPXFMUu0447oG6+Juwap0G1r4r93eDw8AAADwIhJWtJotmfmSpJ5dg80N5AJ342XRkqQV6Vk6carc5GgAAACAtkPCilZhGIYyDuVLImFta/0uClVMRKDKXW79fu0es8MBAAAA2gwJK1pFVn6pjhWVy2qRYiN9a0ubC43FYtGI072s7206pMJSp8kRAQAAAG2DhBWtono4cGxkkPztfK3a2mU9O6tbmEMlzkotopcVAAAAFygyC7QK5q96l9Vq0agrukuS3ko9qGNFrBgMAACACw8JK1rFpgPHJUkXd/PdhDU0PEKh4RFmh3FeNkeAbI6A89a7vFe4enQJUrnLrTmf7vRCZAAAAIB32c0OAO1ffolT244USpISokNMjqZuAUFB+u/U780O47ysdj/1u3184+paLLolOVYpn/6gD9OP6JfDE5TQrVMbRwgAAAB4Dz2saLGv9p2QYUhRnQMUGuRndjgdSp/uIeobGyq3YeipD76TYfjyHrMAAABA05CwosVS9+ZJqkqe4H0/uTpWNqtFm/ad0MffHjE7HAAAAKDVkLCixb7cWzV/NcGHE9byslI9O+5OPTvuTpWXlZodTr3cFRXat+Zj7VvzsdwVFY26JqpzoH40IEqS9PxH21Vc3rjrAAAAAF9HwooWyTxeoj25xbJapIRo350/abgNbfsmVdu+SZXh9uVhs4ZOHcvWqWPZkhof54jLoxUZ4q8Tp5x6/uNtbRceAAAA4EUkrGiRVdtzJEm9o0MU5GANL7P42626a3CcJOnvmw9rzc6jJkcEAAAAtBwJK1pk9faqxKh/jzCTI8GlsaEa2rerJOlXf92q48XlJkcEAAAAtAwJK5rteHG5Nh88KUkaEEfC6gtuvSpWUWEByi9x6Rd/SVelTw9/BgAAABpGwopm+2jrEVW6DfXoEqSIEIfZ4UBVQ4MfvP5i+dmqVg3+7T+3mx0SAAAA0GwkrGi2v6cdliQl944wORKcLTYiSPdd21OS9N9fHtBfNx8yOSIAAACgeUhY0SzbjxRq25FC2awWXRnfPhJWR2CgHIGBZodxXhabXRZbyxawGhQfoRsGVm118+Q/vvMsjgUAAAC0JyzrimZ548v9kqrmrgYH+P7XKCAoSH/ZstfsMM7LavfTgLsfapV7jU6KUUGJS2l7T+iX/5uu5ROu0nWXdG2VewMAAADeQA8rmuxoYZk+zMiSJF0/IMrkaFAfq8Wi+67tqQFxYXJVGnrozW/08dYjZocFAAAANBoJK5psydo9clUa6tUtWD27BpsdDhpgs1o0/vpeuqxnZ1W4DT32zhalrNsrw2D1YAAAAPg+ElY0yd5jxfrfrzMlST8eFGNyNI3nLC/Tiz8fpxd/Pk7O8jKzw6mXu7JCB9Z9ogPrPpG7sqJV7mm3WTX++l4a2reLDEkvf7JTk97arMIyV6vcHwAAAGgrJKxotEq3oSff/04VbkP9eoSqT0yI2SE1mrvSrfR1a5S+bo3clW6zw6mfYago+5CKsg9JrdgLarVadMd/9NAd/9FDNqtFn2/P1Y2/W6fPtrEYEwAAAHwXCSsaLeWLPdp04IQcdqtuv6aH2eGgiSwWi65N7KpHR1+iyBCHjhWV6+dvpen//fcm7cguNDs8AAAAoBYSVjTKii2HNX/VbknS7ddcpMgQh8kRobniugZr5phE3XhZlKwWae2uY7pp4XpNfjtNX+87zvxWAAAA+Azf348EpnK7Df1pwz7N/WSnJGl4/266+pIuJkeFlvK3W3VzUqySe0fqsy1HlHEgX59+n6NPv89RQrdOun1QrEb1j1JCt/Yz7BsAAAAXnmb1sC5ZskS9evVSQECAkpKStH79+gbrr1u3TklJSQoICFB8fLyWLl1aq87777+vfv36yeFwqF+/flqxYkVzQkMrMQxDX+87rvuWfaU5K3fKMKShfbvo1qtizQ4NrSiqc4DG/yheM36SqGsuiZS/3ao9ucV65bNdGvHqvzVs3r80829b9ddvDmlXTpHKKyrNDhkAAAAdSJN7WN977z1NnTpVS5Ys0dChQ/XHP/5RN910k7Zv3664uLha9ffv36/Ro0dr0qRJevvtt/Xll1/qkUceUdeuXXXnnXdKklJTU3XvvffqN7/5jW6//XatWLFC99xzjzZs2KBrrrmm5W+JBhmGocKyCuUWlmnX0SJ9e7hAa3Yc1d5jpyRV9cbdmhyrIX27yGKxmBwt2kJMRKDuHdpTt111kTL2n9R3B/P1Q3aRDp0o1aETh/W3tMOSJJvFop6RQYrv2kndwwIUFepQVGiAuoY4FBLgp9AAuzoF2BUS4KdgfxvfFwAAALSIxWjihLVrrrlGV155pVJSUjxliYmJGjNmjObOnVur/qxZs/TRRx9px44dnrLJkydr69atSk1NlSTde++9Kiws1CeffOKp8+Mf/1jh4eF655136oyjvLxc5eXlns8FBQWKi4vTj19cIbsjyFN+9sud/aZGHYX11zUaPK8a5bVP1HWvs8tr3rfueNSEumfuW/tZ5x47KypVUFqhCnftuO02i66Mj9Dw/l0V3ql9z1ktKynRpOsGSZJe//cWBQQFnecKc7grXNrxwduSpMQxD8pq9zMtljJnpQ4eO6WDucU6eKxER06WqtzVtBWW7TaL/GwW+Vmt8rNZZLdZ5W+zym6zyGKxyGqRLLKoOq+1WKqOLTpTbrFYqj5Xl5MEX7DM+i/rKjulT56+Xfn5+QoLCzMpCgAAUJcm9bA6nU6lpaXpiSeeqFE+cuRIbdy4sc5rUlNTNXLkyBplo0aN0vLly+VyueTn56fU1FRNmzatVp0FCxbUG8vcuXM1e/bsWuWfPn17I98GjbFf0vtmB9HKqhNXn/fSS2ZHAHQox48fJ2EFAMDHNClhzcvLU2VlpaKiomqUR0VFKSen7v0cc3Jy6qxfUVGhvLw8de/evd469d1Tkp588klNnz7d8zk/P189e/ZUZmYmf+FohsLCQvXo0UOHDh1SaGio2eG0O7Rfy9B+LUP7tUz1CJ2IiAizQwEAAOdo1irB5w7JMwyjwWF6ddU/t7yp93Q4HHI4ag9TDQsL4y9sLRAaGkr7tQDt1zK0X8vQfi1jtbLTGwAAvqZJv527dOkim81Wq+czNze3Vg9ptejo6Drr2+12RUZGNlinvnsCAAAAAC58TUpY/f39lZSUpNWrV9coX716tYYMGVLnNYMHD65Vf9WqVUpOTpafn1+Ddeq7JwAAAADgwtfkIcHTp0/XuHHjlJycrMGDB2vZsmXKzMzU5MmTJVXNLc3KytKf//xnSVUrAi9evFjTp0/XpEmTlJqaquXLl9dY/XfKlCm67rrr9PLLL+snP/mJPvzwQ33++efasGFDo+NyOBx67rnn6hwmjPOj/VqG9msZ2q9laL+Wof0AAPBdTd7WRpKWLFmiefPmKTs7WwMGDNBrr72m6667TpI0ceJEHThwQF988YWn/rp16zRt2jRt27ZNMTExmjVrlifBrfb3v/9dzzzzjPbt26fevXvrxRdf1B133NGytwMAAAAAtFvNSlgBAAAAAGhrLIkIAAAAAPBJJKwAAAAAAJ9EwgoAAAAA8EkkrAAAAAAAn9SuE9a5c+fKYrFo6tSpnjLDMPT8888rJiZGgYGBuv7667Vt2zbzgvQxWVlZevDBBxUZGamgoCBdccUVSktL85yn/epXUVGhZ555Rr169VJgYKDi4+P1wgsvyO12e+rQfmf8+9//1q233qqYmBhZLBZ98MEHNc43pq3Ky8v16KOPqkuXLgoODtZtt92mw4cPe/EtzNNQ+7lcLs2aNUsDBw5UcHCwYmJiNH78eB05cqTGPWi/+r9/Z/v5z38ui8WiBQsW1CjvyO0HAICvaLcJ6zfffKNly5bpsssuq1E+b948vfrqq1q8eLG++eYbRUdH6z//8z9VVFRkUqS+4+TJkxo6dKj8/Pz0ySefaPv27frd736nzp07e+rQfvV7+eWXtXTpUi1evFg7duzQvHnz9Morr+j3v/+9pw7td8apU6d0+eWXa/HixXWeb0xbTZ06VStWrNC7776rDRs2qLi4WLfccosqKyu99Rqmaaj9SkpKlJ6erl//+tdKT0/XP/7xD+3evVu33XZbjXq0X/3fv2offPCBvv76a8XExNQ615HbDwAAn2G0Q0VFRUafPn2M1atXG8OHDzemTJliGIZhuN1uIzo62njppZc8dcvKyoywsDBj6dKlJkXrO2bNmmVce+219Z6n/Rp28803Gw899FCNsjvuuMN48MEHDcOg/RoiyVixYoXnc2PaKj8/3/Dz8zPeffddT52srCzDarUan376qddi9wXntl9dNm3aZEgyDh48aBgG7Xe2+trv8OHDRmxsrPH9998bPXv2NF577TXPOdoPAADf0C57WH/5y1/q5ptv1ogRI2qU79+/Xzk5ORo5cqSnzOFwaPjw4dq4caO3w/Q5H330kZKTk3X33XerW7duGjRokF5//XXPedqvYddee63WrFmj3bt3S5K2bt2qDRs2aPTo0ZJov6ZoTFulpaXJ5XLVqBMTE6MBAwbQnnUoKCiQxWLxjJig/Rrmdrs1btw4zZw5U/379691nvYDAMA32M0OoKneffddpaWlafPmzbXO5eTkSJKioqJqlEdFRengwYNeic+X7du3TykpKZo+fbqeeuopbdq0SY899pgcDofGjx9P+53HrFmzVFBQoL59+8pms6myslIvvvii7r//fkl8/5qiMW2Vk5Mjf39/hYeH16pTfT2qlJWV6YknntADDzyg0NBQSbTf+bz88suy2+167LHH6jxP+wEA4BvaVcJ66NAhTZkyRatWrVJAQEC99SwWS43PhmHUKuuI3G63kpOTNWfOHEnSoEGDtG3bNqWkpGj8+PGeerRf3d577z29/fbb+stf/qL+/fsrIyNDU6dOVUxMjCZMmOCpR/s1XnPaivasyeVy6b777pPb7daSJUvOW5/2q+o9XbhwodLT05vcFrQfAADe1a6GBKelpSk3N1dJSUmy2+2y2+1at26dFi1aJLvd7umtOfdfv3Nzc2v15HRE3bt3V79+/WqUJSYmKjMzU5IUHR0tifarz8yZM/XEE0/ovvvu08CBAzVu3DhNmzZNc+fOlUT7NUVj2io6OlpOp1MnT56st05H53K5dM8992j//v1avXq1p3dVov0asn79euXm5iouLs7zu+TgwYP61a9+pYsvvlgS7QcAgK9oVwnrjTfeqO+++04ZGRmen+TkZI0dO1YZGRmKj49XdHS0Vq9e7bnG6XRq3bp1GjJkiImR+4ahQ4dq165dNcp2796tnj17SpJ69epF+zWgpKREVmvNPzI2m82zrQ3t13iNaaukpCT5+fnVqJOdna3vv/+e9tSZZPWHH37Q559/rsjIyBrnab/6jRs3Tt9++22N3yUxMTGaOXOmPvvsM0m0HwAAvqJdDQkOCQnRgAEDapQFBwcrMjLSUz516lTNmTNHffr0UZ8+fTRnzhwFBQXpgQceMCNknzJt2jQNGTJEc+bM0T333KNNmzZp2bJlWrZsmSR59rSl/ep266236sUXX1RcXJz69++vLVu26NVXX9VDDz0kifY7V3Fxsfbs2eP5vH//fmVkZCgiIkJxcXHnbauwsDA9/PDD+tWvfqXIyEhFRERoxowZGjhwYK0F1y5EDbVfTEyM7rrrLqWnp+v//u//VFlZ6emtjoiIkL+/P+13nu/fuQm+n5+foqOjdemll0ri+wcAgM8wcYXiVnH2tjaGUbVdxnPPPWdER0cbDofDuO6664zvvvvOvAB9zMcff2wMGDDAcDgcRt++fY1ly5bVOE/71a+wsNCYMmWKERcXZwQEBBjx8fHG008/bZSXl3vq0H5nrF271pBU62fChAmGYTSurUpLS43/+q//MiIiIozAwEDjlltuMTIzM014G+9rqP32799f5zlJxtq1az33oP3q//6d69xtbQyjY7cfAAC+wmIYhuHVDBkAAAAAgEZoV3NYAQAAAAAdBwkrAAAAAMAnkbACAAAAAHwSCSsAAAAAwCeRsAIAAAAAfBIJKwAAAADAJ5GwAgAAAAB8EgkrAAAAAMAnkbACAAAAAHwSCSsAAAAAwCeRsAIAAAAAfNL/BzgxmyZQYvKjAAAAAElFTkSuQmCC\n", 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Hr7/+upYsWaKjR4/qsssu08UXX6zy8vIzlt+xY0etXLlSBQUFeu2113T33Xdr7dq1zXnJgMcoLy/X1KlTNXbs2BqJ/xPdcMMNys3N1datW5WSkiKbzabbbrut3mUsXbpUP/30k3bs2KGvvvpK8+fPlyQ9/fTTqqioUGZmpnJycvT6668rJCSkxrHZ2dkaNWqUevbsqXfffVdWq7XR1woAdSEZAwAudu+99yo8PFxBQUF677339Mknn8jHx0eJiYmaMGGC/P39FRoaqvvvv19r1qxRVVWVpOrx9vfdd5/i4uIUHh6uOXPm1DjvO++8owceeEAJCQkKDg7Ws88+qy+//FJZWVmOfe655x61bdtW4eHhmjp1qjZt2nTGeD///HNZrVY9+uijCgoKkq+vr0aNGuXcmwK4yIn177LLLtMDDzygmJgYhYaG6sorr1RQUJD8/f318MMPa/fu3TXqT69evXTdddfJx8dHgYGBevHFFzV37lwlJyfLx8dHf/zjH3X8+HH98MMPZ4xj6tSpio+Pl8lk0qhRozRu3DitWrWqGa8c8By33XabysrK9Oqrr9a6PTs7WwsXLtQLL7zgqK9z587VBx98oMrKynqV8dBDDyk0NFRxcXGaMGGCo72zWq3KycnRnj17ZLFY1K9fP0VGRjqO279/v4YMGaLLL79czz77LMu9A2g2JGMAwMUef/xx5eXlKSMjQ3FxcY6hENnZ2ZoxY4bi4+MVGhqq4cOHq7y8XIWFhZKqu3R37NjRcZ4Tv5ekzMxMJSYmOn6Oi4uTn5+fMjMzHa/FxsY6vg8KCnKc+3TS0tLUpUsXHkjRKtjr3/Hjx7Vr1y69+eab+u9//6vjx4/r1ltvVWJiokJDQx116ejRo45jExISapwrNTVVV199tcLDwx1fx44dq1Hn6jJ//nwNGDBAERERCg8P17Jly2qUBbRWr7zyihYtWqRFixYpICCg1n1SU1NVVVWlzp07O+rWOeecI7PZrEOHDtWrnLrau7vvvlvDhg3TFVdcodjYWN1xxx06fvy4Y98PP/xQZrNZt9xySxOuEgDOjGQMALhJ+/bt9eqrr+qee+5RVlaW7r33XpWUlOinn35SQUGB1qxZI0mOYRJxcXE1xrWnp6fXOF+HDh1qzDFz6NAhlZWVqUOHDk2Ks2PHjtq3b1+N4RpAa5CUlKRJkybp888/1zPPPKNNmzbpu+++U0FBgaMunfh3bzbXfGyKj4/XRx99pLy8PMdXSUnJGZe/TU9P17XXXqunnnpK2dnZysvL08SJE6ljaPXWr1+vP//5z/rggw9qfHhwsvj4eJnNZmVlZdWoX6WlpWrfvn2TYggODtaTTz6pXbt2ad26dfr666/10ksvObb/9a9/1eDBgzVu3DgVFBQ0qSwAOB2SMQDgRgMGDNDIkSP12GOPqaCgQIGBgQoPD1dOTo4efvjhGvteddVVeuKJJxwPp3Pnzq2x/eqrr9Zjjz2mjIwMFRUV6c4779TYsWMVFxfXpBgnTZqksrIyPfjggyouLlZ5ebm++eabJp0T8ARpaWlatmyZevfurYKCAvn7+ysiIkJFRUX1Wsb2D3/4gx588EHt2rVLklRQUKDFixefscdZUVGRDMNQmzZtZDabtWzZMq1YscIp1wR4qkOHDmnq1KmaO3euxowZc9p9Y2Njdemll+q2225z9Bg7dOiQPvnkkybH8fnnn2v37t2qqqpSaGiorFarfHx8HNvNZrPeeOMN9ezZUxdccEGdkwYDQFORjAGAWljMFk3rMU3TekyTxWxp1rLuv/9+vfbaa7r99tu1d+9eRUREaMiQIZowYUKN/R544AENHDhQvXr1Ur9+/U5Z1eHee+/VuHHjNHjwYCUmJspms+ndd99tcnzBwcH66quvtGnTJiUkJKhdu3Z68cUXm3xe4GSuqHf33HOPgoODFRwcrCFDhmjs2LF68MEHdeedd8pisaht27bq1auXBg8efMZz3Xbbbbruuut02WWXKTQ0VGeddZYWLFhwxuN69Oih+++/X6NHj1ZUVJQ++OADTZ482RmXBzSYq9q7V155RVlZWZozZ46jDp74dbJ58+Y5hieFhoZq2LBh9Zrn7Ez27t2r8ePHKyQkRD169NDgwYNPGZJkMpn0yiuvqH///ho7dqyOHTvW5HIB4GQmgz6xQItWUFCgsLAw5efnKzQ01N3heL3S0lKlpKSoU6dO8vf3d3c49bZv3z4lJSWpuLhYgYGBbo2lrnvoqX/rnhqXt2qpddBTnO7+eeLfuifG5M2of03X0tpAAI1HzxgAgLZu3aq2bdu6PREDAAAAeAOfM+8CAGjNHnzwQb366qt69tln3R0KAAAA4BXoGQMAtSguL5bpYZNMD5tUXF7s7nCa1dy5c3Xw4EHNmDHD3aHAy3lTvQM8BfUOANyDZAwAAAAAAIALkYwBAAAAAABwIZIxAAAAAAAALkQyBgAAAAAAwIVIxgAAAAAAALgQyRgAAAAAAAAXIhkDALWwmC2amDxRE5MnymK2uCWG0tJSTZkyReHh4Ro0aJBbYgBcyRPq3Ymog/AGnlbv7Kh/AFo7kjEAUAt/H38tnbFUS2cslb+Pv1tiWLhwoXbt2qXDhw9rw4YNLi27rKxMf/nLX9SuXTsFBwerd+/eSk1NrXP/9957T2eddZaCg4N1zjnnaOPGjQ3aDkieUe9O1FLq4Pz58xUcHFzjy2Qy6dlnn5UkZWZm6vzzz1dUVJTCwsLUr18/ffLJJy68GngyT6t3di2l/kmSyWRSYGCgo/717dvXse1M9ROA9yIZAwAeKiUlRV27dpWfn5/Ly77++uu1b98+bdq0SYWFhfroo48UHh5e675r167V7NmzNW/ePOXn5+t3v/udJk6cqPz8/HptBzxVS6mDM2fOVFFRkeNr9erVMpvNuvzyyyVJERERmjdvnrKzs5Wfn6+XXnpJV199tVJSUlx4RUDDtJT6Z/f999876uCWLVscr5+pfgLwXiRjAMBFEhMT9fjjj+ucc85RUFCQJkyYoNzcXN16660KDw9XcnKyvv/+e0nSXXfdpblz5+rzzz9XcHCw5syZo759++rtt9+ucc4JEyboiSeecGqc27dv1+LFi/XGG28oLi5OJpNJ3bt3r/NBdPHixbrkkkt07rnnymKx6Oabb1ZwcLDjk/czbQdcpbXWwZO9/vrruvDCCxUfHy9JCgoKUteuXWU2m2UYhsxmsyorK0/7ST/gbN5S/87k5PoJwHuRjAGAWhSXFyvosSAFPRak4vJip533vffe08KFC3XgwAGlp6dr0KBBGj16tHJycjR9+nTNnj1bkvTMM8/ovvvu00UXXaSioiI9/PDDmjVrlt555x3HuQ4fPqyvv/5aM2fOrLUs+wNuXV/fffddrcetXr1anTt31pNPPqk2bdqoa9euevrpp+u8pqqqKhmGUeM1wzC0devWem0H7Jqr3p2oNdbBEx0/flwLFizQ7373u1O29enTR35+fho8eLCGDBmiYcOG1eucaN1cUe/sWnP9mzBhgmJiYjRmzBitX7++1n1OVz8BeB+SMQBQhxJbiUpsJU4956233qqEhASFh4dr0qRJio6O1rRp02SxWHTVVVdp27ZtKi8vr/XYmTNnavXq1Tpw4IAkacGCBRo2bFidn6699NJLysvLq/Nr6NChtR6Xm5urbdu2yTAMpaen65NPPtE///lPzZ8/v9b9L7roIn366adau3atbDabXnzxRaWnp6ugoKBe24ETNUe9O1FrrIMn+vjjj+Xr66vJkyefsm3r1q0qKirSkiVLNGHCBFksnjNZK9yrueudXWutfytXrlRqaqpSU1M1ceJEXXjhhUpPTz9lv9PVTwDeh2QMALhQbGys4/vAwMBTfjYMQyUltT8Qt2vXTqNHj3Y8EL799tu65pprnB5jcHCwLBaL5s6dK39/f/Xs2VM33HCDFi9eXOv+I0eO1L/+9S/ddNNNio2N1caNGzV27FhFRUXVazvgSq2xDp7o9ddf1zXXXCOr1Vrrdl9fX1100UX65ptv6pXcAZyptda/UaNGyc/PT0FBQbrrrrvUvXt3LVu27JT9zlQ/AXgXkjEA0ILYu2lv27ZNu3fv1tSpU+vcd/bs2aes4HDi17ffflvrcfZVIEwmU73juuGGG7Rjxw7l5OTo1Vdf1Y4dOzRixIh6bwdaCk+tg5K0d+/e/9/efcdHVef7H39PSe8dUqgJJaE3pbeVErAgKDaKnetad9d7bXtd3eYW/Xl1V3TVtaOri6LYd6WKKEU6SCekkJAE0nvm/P7IZiSQQMqUJPN6+siDyZwz5/v5Huebz5zPnPM9WrdunW6++eYLrltdXa2DBw+2aPuAu7Xn8Xcms/ncQ6yWjE8AnoFiDAB0IHPmzFFaWpp+8YtfaM6cOQoMDGxy3eeff77BHRzO/mlqvogJEyYoKSlJjz32mKqrq7V//369+uqruvzyyxtdv7q6Wtu3b5fNZlN+fr7uvPNO9ezZUzNmzGjWcqAjaY9jsN7LL7+s0aNHq3///g2eX7t2rTZu3KiqqipVVVXp1Vdf1erVq3XJJZe0fAcAbtQex9/u3bu1detWVVdXq6KiQs8884z27Nmj6dOnN1ivqfEJwHNRjAGADsTf319z587VF1984ZTTsyXJYrHoo48+0saNGxUaGqoZM2bonnvuaTBJ4pnfKlZXV+vGG29UcHCw+vTpo5qaGq1cudL+zeCFlgMdSXscg5JUW1ur1157rdGJQUtLS3X77bcrIiJCMTExWrp0qd55550m58wA2qv2OP5yc3N1ww03KDQ0VHFxcXr//ff1+eefq2fPnvb1zzc+AXguk3H2LS4AdChFRUUKCQlRYWGhgoOD3R1Op1FaVarA39d941byYIkCvAOa9bqKigodPXpUPXv2lK+vrzND7LSa2oft9b3eXuPqiFo77s7EGGyb8+2/9vheb48xdTSOGHf1GH9t19FyIIDWs7o7AABoj8wmsyZ2n2h/DMD5GHeA6zHuAMA9KMYAQCP8vPy0ZvEad4cBeBTGHeB6jDsAcA/K3wAAAAAAAC5EMQYAnIDpuFqPfQdH4H3UOuw3OALvo9Zj3wGeg2IMADSitKpUUX+KUtSfolRaVdrs13l5eUmSysrKnBVap1e/7+r3JTxHa8fdmSwWiySpqqrKkaF5jPr9Vr8f0fk5YtzVIwe2HTkQ8BzMGQMATcgry2vxaywWi0JDQ3Xy5ElJdbfhNJlMjg6tUzIMQ2VlZTp58qRCQ0M5GPRQrRl3Z7JarfL391dubq68vLy4hXoL2Gw25ebmyt/fX1YrHxE9SVvHXT1yYOuRAwHPQ6YFAAfr0qWLJNk/jKJlQkND7fsQaCmTyaSuXbvq6NGjSktLc3c4HY7ZbFa3bt04gEarkQPbhhwIeA6KMQDgYPUHg9HR0aqurnZ3OB2Kl5cX3wZ2Qrmlufrl6l/KbDLr8cmPK9I/0qnteXt7KykpiUuVWsHb25uziTqhLVlbJEkjYkc4vS1yYOuRAwHPQjEGAJzEYrHwoQoezzAMzXtvntalrZMkfZv9rbbctEVmk3MP+M1ms3x9fZ3aBtARPLr6UT2+7nFJ0s/H/lx//smfXdIuORAAzo+vPgAAgNOsS1tnL8RI0raMbXpp10tujAjwHAfyD+jX635t//3JDU9q1fFVbowIAFCPYgwAAHCad3a/I0kanTJa00dNlyT9v+/+nztDAjzGs989K0OGUnqkaFT/UZKkB1Y/4OaoAAASlykBQKPMJrP92npnX04BdFaGYejjgx9Lkgb2Hqi4qDj9a8u/9EPWD9p6cquGRw9vsD7jDnAcwzD0wQ8fSJLGDByjmPAYbd63WZuPbdbu/N0aEDFAEuMOANyFv7gA0Ag/Lz9tvnWzNt+6WX5efu4OB+iQDuQfUEZRhrwsXkqMT1RIQIj6JPSRJP1t19/OWZ9xBzjOtuxtyizOlLfVW30S+igyJNI+/p7Z9ox9PcYdALgHxRgAAOAUmzI3SZLio+PlbfWWJA1NGipJ+mTfJ26LC/AEq47WzQ3TJ6GPvKxekqRRyXWXKq3YvUKGYbgtNgAAxRgAAOAkm7M2S5K6xXSzPzew90BZzBZl5mfqu5zv3BUa0OltzNgoSeoZ29P+3IBeA+Rl8VJuYa7WnljrrtAAAKIYAwCNKqsuU4+ne6jH0z1UVl3m7nCADqn+zJgzizH+Pv72SyVe3/N6g/UZd4BjGIahjel1xZgeXXrYn/fx8lG/7v0kSW/seUMS4w4A3IViDAA0wjAMpRWmKa0wjVO5gVaotdVqe/Z2SQ2LMZI0qPcgSdJn+z9r8DzjDnCM9KJ0nSg5IbPJrITohAbL6sffl/u/lMS4AwB3oRgDAAAc7ljBMVXWVsrL4qWIkIgGywb0GiCTyaSjJ49q/6n9booQ6Lzqz0qLjYyVt5d3g2UpPVNkNpuVkZ+hLSe3uCM8AIAoxgAAACfYn19XZIkMjTzndrlB/kHqFdtLkvTq3lddHRrQ6e3M2SlJio+KP2eZv6+/kuKTJEmv7X3NpXEBAH5EMQYAADjcD3k/SJJiwmIaXV5/qcTKH1a6LCbAU+w+uVuS1CWiS6PL7ZcK/vBZo8sBAM5HMQYAADjc/ry6M2OiwqIaXV5/MLg3c68yizNdFhfgCeqLMV0juja6fFDvQTLJpMM5h3Ww4KArQwMA/AfFGAAA4HD1lyk1dWZMWFCYusV0kyFDr+99vdF1ALRceXW5Dp06JKnpYsyZlwq+vo/xBwDuQDEGABphMpmUHJWs5KhkmUwmd4cDdDj1xZjosOgm16k/O+b9fe9LYtwBjrA3d68MGQrwDVCQf1CT6w1K/PGuZow7AHA9q7sDAID2yN/LX3vu2OPuMIAOqaiySNkl2ZKk6NDzF2M+/uZjbUvfpvyyfEX4RzDugDY68xKl8xVXBvUepA/WfaD9J/br2M+OqVtQtybXBQA4HmfGAAAAh6qfLybYP1i+Pr5NrhcdFq2uEV1Va6vV2z+87arwgE7tQvPF1DvzUsFX9rziitAAAGegGAOgUzty+oiu+ec16v/X/rrh/Rt05PQRd4cEdHr1d1I63yVK9eovVXp337tOjQnwFLtO7pIkdY08fzFGkgYnDpYkrfhhhTNDAgA0gmIMgE7ryOkjGv3yaP1jzz/0Q94PemvXWxr8wmBtTN94wdeWVZcp5bkUpTyXorLqMhdEC3QezZkvpl59Mebbo98qpySHcQe0UXPPjJGkwb3rijHb07ar71/6Mu4AwIUoxgDolGyGTTe8f4NOlp5UbGSsbpp1k7p36a6SyhJNXzZdxwqOnff1hmFob+7euokQDcM1QQOdREuKMbGRsYoMiVR1bbWWH1zOuAPa4HT5afut4ruEd7ng+pGhkYqNjJUkHcg/wLgDABeiGAOgU1q+d7k2ZmyUj5ePbpl9iwb1HqQ75tyhhOgEFVcUa9a7s1Rjq3F3mECnVD9nTHOKMSaT6cdLlX7gUiWgLfbk1k2AHRoYKj8fv2a9Znjf4c4MCQDQBIoxADodwzD02NrHJEmTh01WeHC4JMnHy0eLUxfLz8dPe0/s1aNfP+rOMIFOqdZWq4OnDko6/52UzlRfjNl45MKXEAJoWksuUao3NGmo/fGWnC0OjwkA0DiKMQA6nXVp67Qnd498vHw0YciEBssigiN0xfgrJEl/Wvcn7cnjNrqAIx0vPK6KmgpZzBZ7IfRCunXppojgCFXVVDk5OqBz23OyLqe1pBgT4Bdgf/z8jucdHhMAoHEUYwB0On/f/ndJ0rA+w+Tv43/O8lH9R6lvQl9V11br+g+vl82wuTpEoNOqny8mKjRKZnPzPmaYTWaNGTjGmWEBHmFv3l5JUkx4TKte/8neT1RRXeHIkAAATaAYA6BTKaos0nt73pMkjUoe1eg6JpNJV0+9Wt5Wb+3I2KH/2/J/rgwR6NTq54uJCWvZweBF/S+S2cTHEqAtWnNmzJmKy4v1wu4XHBkSAKAJfOoB0Kms3L9S5TXlig6LVo8uPZpcLyI4QqmjUyVJj3z1iLKKshosN5lM6h7SXd1DustkMjkzZKBTsZ8ZExbVotcF+gdqcGLdbXb9vPwYd0AL5ZflK6c0R1LLiqEmmRQWFGaf8Pcv3/2FuyoBgAtQjAHQqXy4/0NJ0pDEIRc8mJsweIK6xXRTWWWZFn+6uMEyfy9/Hbv3mI7de0z+Xude6gSgcS25rfXZJg6ZKEmqqq3SybKTDo0L6Ozq76QUFhQmH2+fZr/O28tbj974qB5e8LCsFqsO5RzSV+lfOStMAMB/UIwB0GlU1lTqs0OfSZIG9BpwwfXNZrPmT5kvs8msf+3/l/6x9x/ODhHo9H7I+0FS64oxPbr2UGJcompttXrk60ccHRrQqbX1EqVA/0AN6ztMkvSbDb9xWFwAgMZRjAHQaaw6ukolVSUKCQhRfHR8s14TFxWnKcOnSJJ++tlPVVhR6MwQgU6tqLJIWcV1l/y1phgjSZeMvESS9N7295Rdku2w2IDOrv7MmC7hXVq9jclDJ0uS1h5Yq63ZWx0SFwCgcRRjAHQa9ZcoDeg1oEUTgU4bNU2RIZHKL8nXT7/8qSSpvLpcI18cqZEvjlR5dblT4gU6mwP5ByRJQf5Bjd7J7EKqaqr08Tcfy8vqpaqaKv33uv92dIhAp2UvxkS0rBhTVVOlJ995Uk++86QiQiLsczf9z5r/cXiMAIAfUYwB0CnYDJs+2v+RpOZdonQmb6u35k+ZL0l6a9tbWnlwpWyGTVuytmhL1hZufQ00U1suUZIkwzCUfjJd1TXVkqRlW5fpwKkDDosP6MzqL1Nq6Zkx9eMu/WS6DMPQ9FHTJUmr9q/StuxtDo8TAFCHYgyATmFz5madKDkhHy8fJcUltfj1SQlJGjdwnCRpwQcLdKL4hKNDBDq9+mJMl7DWXyZRLyk+SbW2Wt35rzvbvC2gs8stzVVuWa4kKSa8ZbeVP1tsZKwG9x4sQwbjDwCciGIMgE6h/hKl5B7JslqtrdrG5eMvV2xkrArLC3X1iqsdGR7gEVp7W+vGzBozSyaZ9K8f/qXPjnzW5u0BnVn9GSxRoVHy8Wr+nZSakjomVWazWd8c+UYrDq5o8/YAAOeiGAOgUzhzvpjW8rJ6adHMRfL28ta2DE7NBlqqrZcpnalrRFeNHjhaknTrx7cydxNwHtuzt0uS4qOaN3n9hcSExWj8oPGSpHu+uEc1thqHbBcA8COKMQA6vEOnDmlv7l6ZzWb179G/TduKCYvRdT+5zkGRAZ6j1larg/kHJdWNI0e4dMylCgkIUebpTP1i9S8csk2gM6o/MyYuMs5h25x+0XQF+AboeP5xPf7N4w7bLgCgDsUYAB3ehz/UnRWTGJfYqju4nG1I0hD7BIaStOLAijZvE+jsDp8+rMraSnlZvRQWFOaQbfr5+GnupLmSpOe/fV6r01Y7ZLtAZ7PtxH+KMVGOK8b4+/jr0rGXSpKeWPOE/cw3AIBjUIwB0OF9dKDuLkoDew102DYnD5ssq6Vu7plFHyzSygMrHbZtoDPambNTUt3lRWZz6z9eBPgGKMA3wP77oN6DNLzvcNkMm65Zfo1OlZ9qc6xAZ1JSVWK/rXx8dOsuUzp73NW7KPki9U3oq+raal374bXcXRAAHIhiDIAOLa8sT18f/1qSlNIzxWHb9fX21R/+6w8anDhYtbZazX13rj45+InDtg90Njuyd0iSYiNiW70NHy8f/fa23+q3t/22wSSkV02+SpEhkTpZfFJXf3A1B4TAGXbm7JQhQ8EBwQryD2rx65sad5JkMpk0f+p8+Xj5aHvGdj26/lFHhQ0AHo9iDIAO7ZMDn8hm2BQbGavw4HCHbttitmjh9IUa2Gugqmurdfk7l+vv2//u0DaAzmJHzn+KMVGtL8Y0xdfbV4tmLpLFbNFXB7/S/avud3gbQEe1JWuLJMdN3nu28OBwzZkwR5L0uzW/05q0NU5pBwA8DcUYAB1a/V2UHHmJ0pksFosWzVykYX2GqdZWq5s/vFm/WvsrGYbhlPaAjqr+MiVHTiB6poToBF09pe6W8099/ZRe3v6yU9oBOppv0r+RJPXs2tNpbVyUfJFG9B0hm2HTvH/OU05JjtPaAgBPQTEGQIdVVl2mLw5/Ialtt7RuTFVNlZ5d/qyeXf6sbIZNN0y/QVOGT5EkPbbmMV327mUqrCh0aJtAR1VQUaC0wjRJdXPGtNaZ466qpuqc5RclX6Spw6dKkm5feTtzOQH6sRjTo0uPVr3+QuNOqrtc6arJVyk6LFr5Jfma9vY0bjcPAG1EMQZAh/XxgY9VVl2m8OBwh5+ebRiGDmce1uHMwzIMQ2aTWZeNvUxXTb5KFrNFH//wsQb/bbD9DhaAJ6sfB2FBYfL3bf0dzc4ed42ZNWaWhiQNUa2tVvPenad/HflXq9sDOrr0wnSlF6XLbDKrW0y3Vm2jOeNOkny8fXTz7Jvl7+OvnVk7Ne/9eczfBABtQDEGQIf19u63JUnD+gyTyWRySZtjB47V3fPuVlhQmNJOp2nkSyP1v2v+V9W11S5pH2iPNmZslNT6b+Zbwmwya8G0BRrQc4Cqaqt06duX2s+QAzxN/diLjYyVj7fPBdZuu5iwGN006yZZzBZ9+sOnuv3T27lsFwBaiWIMgA6poKJAnx78VFJdMcaVunfprl9c8wsN6j1ItbZa/XrtrzX0xaH2SRQBT1N/QNi9S3eXtGexWLR45mL1695PlTWVmr1stt7Y+YZL2gbakzXH1kiSesX2clmbifGJuvYn10qSXtrykv7r8/+iIAMArUAxBkCHtHzvclXVVqlLeBfFRjr+7i0XEuAXoBtTb9SC6Qvk7+uvPTl7NOrFUVq0YpGyS7JdHg/gLoZh6NuMbyW55syYelarVbfMukVDk4aqxlajhR8s1G/W/4aDQniULw9/KUnqk9DHpe2O6DdC86fMlyS9sOkFLflsCZcsAUALUYwB0CG9+P2LkqSR/Ua6LQaTyaThfYfrwRse1Ih+I2TI0Os7Xlfis4n69dpfq6iyyG2xAa5y6NQh5ZXlyWK2OO3Wuk2xWq1aMGOBJgyZIEn65apf6or3rlBxZbFL4wDc4fCpwzp8+rDMZrMS4xNd3v7oAaPtdzj72+a/ac57c1RRU+HyOACgo6IYA6DD2XZim77L/E4Ws0Wjkke5OxwF+Qfphmk36J6r7lFCdIJKq0r1v2v+V92f7q7frvstB4bo1P595N+S6i5RslqtLm/fbDJrzvg5mjdpnixmiz7a95GGvDiEybXR6dWfFdOzS0/5evu6JYYxA8bohmk32Mfe+NfGc3YoADQTxRgAHc7zW56XJA1OHKwg/yCnteNt9Za31bvZ6/fs2lP3zb9PC6YvUHRYtAoqCvTI6kcU/3S87v/yfh0vPO60WAF3+fJI3QFh/+79HbK9lo47qe4stXGDxumuuXcpJCBER/KPMLk2Or33f3hfktS/R9vHXmvGXb0R/UZoyeVL5Ovtqy0ZWzTw+YFafXR1m2MCgM7OZHBxNdChFRUVKSQkRIWFhQoODnZ3OE53oviEev5fT1XWVuquuXepd1xvd4fUKJvNpu8PfK8vN32pkwUnJUkWk0WX97tcPx35U03qMUlmE/Xwlmiv7/X2GpcrVNdWK/JPkSqqLNLP5v+s1bfWdaSSshK9t/o97Ti8Q5KUHJ2s51Of1/ju490cWcfXHt/r7TEmV8gpyVHsU7GyGTY9sugRRYZEujsk5ZzO0aufvqoT+SdkNpn13+P+W7+a8Cv5WJ1/lydP4KnvdaAz40gAQIfyp2/+pMraSvXs2tOld49oKbPZrBH9RuiBGx7QLbNvUZ+EPqo1avX+vvc19fWp6v50d/3v6v/V4VOH3R0q0Gqrj61WUWWRAnwDXD5fTFMC/QO1OHVx3eTaPv7ae3KvJrw6QVe9d5XSCtLcHR7gEP/c+0/ZDJu6xXRrF4UYqe621/ddfZ9G9h8pm2HTE+uf0KAXBtkn+AYANEQxBkCHkVaQZr9EadqoaTKZTG6O6MLMZrMG9BqgO+bcof++7r81ZsAY+Xn7KaMoQ79e92slPpuokS+O1B++/oMO5B9wd7hAi7y9+21J0pCkITKb289HivrJtR9a8JDGDBgjk0z6595/KvHZRN328W0UZdChGYah57fW5cLhfYe7OZqGvL28df0l12vxzMUK9AvUgbwDGvPyGN3wwQ1KL0x3d3gA0K5wmRLQwXnSaavz3p2n5fuWq3dsb905906nFmOqa6r1yqevSJJuTL1RXlYvh227qqZKu4/s1qa9m7Q/fX+DW/H2j+qvOX3n6JLel2h0/GhO7z5De32vt9e4nK20qlSxT8WqqLLIYZcMOmvcZeRm6MP1H+pgxkFJktVs1fwB83XXyLs0Km5Uhyjstgft8b3eHmNyttVHV2vK61Pk7eWtX930K/n7+Ldpe84ad6XlpVrx9Qpt3rdZkuRj9dFPR/5UPx/9c8UGxTqkDU/iie91oLNz/W0PAKAVlu9druX7lstsMmvupLlOP3iyGTbtPbbX/tiRvK3eGtZnmIb1Gaai0iLtOrJLOw/v1MGMg9qXu0/7cvfpd1//Tn5efprQbYKm9Z6mCd0naHDMYHlZHFcUAtritR2vqaiySJEhkeoZ29Mh23TWuIuPitdPr/ypDmce1hebvtCB9AN6a+dbemvnWxradaiWDF+iuf3nKsI/wmFtAs5gGIZ+tfZXkqSR/Ua2uRAjOW/cBfgF6PpLrtf4QeP14dcf6nDmYT218Sk9u+lZ3TDoBt130X0aGDPQYe0BQEdDMQZAu3fo1CHd/NHNkqTJwyYrNrLzfKMWHBCssQPHauzAsSqrKNPeY3u1L22fDqQfUHFZsb44/IW+OPyFJMnX6qsRsSM0Jn6MRieM1vCuwxUfHM+3+nC5yppK/fmbP0uSJg6Z2GEmo+4d11t3zLlDx3OOa/2O9dp2cJu2ndim2z++XT/99Kea1nuarkm5RjMSZygqIMrd4QLn+HD/h1qXtk5eFi/9ZMRP3B1Os3SL6aY7r7xTe4/t1Vdbv9KRrCN6ZdsremXbKxrWdZhuHnqz5qfMpxgKwONQjAHQrmUUZeiSNy5RYWWhusd0V+rFqe4OyWn8ff01ot8Ijeg3QoZh6ET+Ce0/vl8HMw7q2IljKqss09fHv9bXx7+2vybUN1SDYwZrUMwgDY4ZrAHRA9Qnoo/C/MLc2BN0dk9ufFJHC44qOCBYo5JHuTucFusW003XT7tel4+/XJv2btLW/VuVmZepTw9+qk8PfiqTTBrWdZhmJs7U1F5TNTJ2pAK8A9wdNjxcTkmObv/4dknSxKETFRbUcf7Om0wmpfRMUUrPFB09cVRrvl+jXUd36fsT3+v7E9/r7s/u1thuY3VF3ys0q88sJYUn8UUDgE6PYgyAduub9G807915OlFyQpEhkbp59s2yWCzuDsslTCaTYiNjFRsZq8nDJstm2JR7OlfHso/p2IljSstOU/apbBVUFGht2lqtTVvb4PVhfmHqE95HSRFJSgxLVO/w3koITlB8cLziguPka/V1U8/Q0X19/Gs9uuZRSdKlYy6Vj1fHndco0C9QU4ZP0ZThU5RzKkffH/heu4/sVmZeprae2KqtJ7bqN+t/I4vJogExAzQ6brRGxI5QSnSKkqOSFezDvA1wjdPlp5W6LFUnS0+qa0RXTR813d0htVrPrj3Vc1ZPlZSVaMv+Ldq8b7My8zK1Lm2d1qWt08++/Jm6BHbRxO4TNaH7BI2MHamU6BT5e7X9kiwAaE8oxgBodw7kH9CfNvxJL297WYYMdQnvotsuu03BAZ574GM2mRUTHqOY8BhdlHyRJKmmpkbZp7OVlZelrLwsncg7oROnTqiotEiny0/ru8zv9F3md41uL8I/QgnBCYoLilPXwK6KCohSpH+kIv0jFeX/4+NI/0gFegfyDSUkSSv3r9R171+nGluNhiQO0Yh+I9wdksPEhMdo5sUzNfPimSosLdT+4/u1L22fjmYdVUFJgXZk79CO7B3S1h9fkxCSoJTIFPUM66keoT3UPaS7uod2V/eQ7ooKiJLVzMcstN26tHW66cObdPj0YQX6BTp8Unl3CfQP1KShkzRp6CTlFeZpz9E92n1kt45kHVF2Sbb+secf+seef0iqy4GJ4Yka0mWI+oT3Ua+wXvaf2KBYWcye8UUNgM6FTwkA3MZm2FRYUais4izty9un7dnb9eXhL7U5a7N9nZH9RmruxLny9eFMjrNZrVbFR8UrPiq+wfOVVZXKK8xTXmGecgtylVeQp/yifBWUFKigpEDVNdXKL8tXflm+tmdvv2A7ZpNZwT7BCvIOUrBPcN1jn/889q577O/lLz+rn3ytvvYfP68ffz9zmbfFW1azVV4WL1nNVvuPl/ms3y1eHWYuks6qqrZKaQVp2pC+QW/ufFNfHf1KkpQUn6Rrf3Jtpy3ShQSEaFT/URrVv+4SrILiAh3LrjsjLTMvU9mnslVUWqT0wvTz3q433C9c0QHRivKPUnRAtCL9I+1jqX4M1T8O8g6Sr9VXPlYf+Vh8Gv2X8dD52QybTpef1v78/fou4zv9c98/9U36N5KksKAw3XrprYoOi3ZzlI4XGRKpiUMmauKQiaqqqdLx7OM6nHVYRzKPKDMvUyXlJTqQf0AH8g+c81qLyaLIgEh1CeiimMAYRQdEKyYgRqG+oefkrmCfYAV4BzDGALQLFGOADq7+tshT/jZFFj+LDMOQIaPBsvrHZz7f1GNJMmS0+rG9PZ2/vZLKEhVUFDTZr37d+2ni0Inq2aWnVClVVFa0Zve0WmVNpfSfJiuKK2RYjfO/oJ2J8IlQRHSE+kb3bfC8YRgqrypXYWmhCksKVVhaqOKyYpVVlKmsokylFaUqLS+1/1tTWyObbCooL1CBCtzSl/rCjKXaYu9De1Ifz+QXJteNwUbG35m/Nzbe6n8/37KW/t5kHGretkqrS3Wq7FTDzpqk8YPGa9qoaTIqDFVUOHZcttdx5ytf9Yv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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "squad = ['Musso',\n", + " 'Zappacosta',\n", + " 'Pavard',\n", + " 'Carlos Augusto',\n", + " 'Lazaro',\n", + " 'Radonjic',\n", + " 'Barella',\n", + " 'Zielinski',\n", + " 'Lauriente\\'',\n", + " 'Rafael Leao',\n", + " 'Lookman']\n", + "\n", + "s = simulate_lineup(squad, MOD = True, CS = True)\n", + "\n", + "plot_lineup(squad, config_433_classic)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "fc4be108", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", "text/plain": [ "
" ] @@ -715,115 +728,19 @@ "source": [ "squad = ['Szczesny',\n", " 'Di Lorenzo',\n", - " 'Kim',\n", - " 'Juan Jesus',\n", - " 'Carlos Augusto',\n", - " 'Rovella',\n", - " 'Frattesi',\n", - " 'Barella',\n", - " 'Gonzalez N.',\n", - " 'Rafael Leao',\n", - " 'Lauriente\\'']\n", - "\n", - "config_433 = [3, 6, 7, 9, 10, 13, 17, 19, 26, 28, 30];\n", - "\n", - "s = simulate_lineup(squad)\n", - "\n", - "plot_lineup(squad, config_433)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "3943571c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "squad = ['Carnesecchi',\n", - " 'Danilo',\n", - " 'Ampadu',\n", - " 'Luperto',\n", - " 'Hernandez T.',\n", - " 'Zambo Anguissa',\n", - " 'Milinkovic-Savic',\n", - " 'Vlasic',\n", - " 'Kvaratskhelia',\n", - " 'Caprari',\n", - " 'Lukaku']\n", - "\n", - "config_4231 = [3, 6, 7, 9, 10, 12, 19, 23, 25, 26, 28];\n", - "\n", - "s = simulate_lineup(squad)\n", - "\n", - "plot_lineup(squad, config_4231)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "15d5b4ca", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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uu+02LV++XOvWrZPdbteVV17Zbpm8vDzddNNN+p//+R+VlpaqoqJC8+bN6/JdLc6WVxMTEzVjxgytXLlSL7/8sq655hoFBwe3205sbKyCgoJ0+PDh7ncUAIBuOD13Wa1WFRUVdekzYXBwcLtroXVVYmKicnNz20zLy8vr8vr9GcWYAcxkMumpp57Sf//3f+t///d/VVJSIqnlm7Z9+/Y5lps3b55KSkr0zDPPqKmpSZ9++qlWrlzZ4SHTp6uqqtL8+fN17733Ok57OnWen5+fYmJiZLVa9dhjj6mqqqrD7cTHx+vqq6/WPffc4/jm8fjx445z6l944QW9/vrrWrt2rYKCgrq1Hx599FG9/fbbXjOoAQCdW7x4sY4fP64f//jHWrZsmXx9fdstU1NTI8MwFBcXJ7PZrPXr1+uDDz7ochvXXXedPvnkE61Zs0bNzc16++239emnn2rx4sWOZZYtW6aXXnrpjPnWZDLpjjvu0E9+8hMdPnxYhmHowIED7d60AgDQWzfeeKOefvppZWVlqbGxUT//+c+VlJSkKVOmnHXdiRMnasWKFWpqatLOnTvbnIp7NldccYUKCwv1/PPPq6mpSe+99542btzYm670GxRj+gGL2aJrM6/VtZnXymK2dGvdq666Su+9957Wr1+v4cOHKywsTNOnT1dcXJzjokmRkZH6xz/+oVdeeUXR0dH6wQ9+oL/85S+aNm3aWbe/Y8cO7du3T48//nibux19+umnuummmzR69GgNHjxY6enpCgwMVEpKSqfbWr58ueP0pNY4W88lXLFihY4fP65hw4Y52pg7d26X9kFycrL+3//7fzp58mSb6a1xAgD6tt7kwdO1XjPt6NGjnZ6ilJmZqf/4j//QrFmzFB0drTfeeEMLFizochvDhg3T22+/rUceeUSRkZF67LHHtHr1aqWnpzuWueaaa5STkyOz2XzGc+N/+9vfavbs2brkkksUFham733veyovL+96hwEA/Yozc153LFu2TPfee6/mz5+v+Ph47dq1S2vXrpWPj89Z1/3Tn/6krVu3KiIiQg8++KBuuummLrcbFRWlNWvW6KmnnlJERIT++te/asmSJb3pSr9hMrp6zO0ZVFVVKTw8XJWVlY4Lt8J9GhoalJOToyFDhiggIMDT4fR7Z9qfvNYBnI6/C30LObF3yIEAuoO/C32LK3NgSkqKnnvuOc2bN8+p2+1L3J0DOTIGAAAAAAB0qLi4WCUlJW2O8ETvUYwBAAAAAADtfPjhhxo5cqTuvvtujRw50tPhDChnPwEMHldrrVXI4yGSpJqHahTs1/6OCwAADFTkQQCAt+hrOe+SSy5pd+1NOAdHxgAAAAAAALgRxRgAAAAAAAA3ohgDAAAAAADgRhRjAAAAAAAA3IhiDAAAAAAAgBtRjEEbDQ0NWrhwoSIiIjRlyhRPhwMAgMeQEwEA3ooc6HoUY/oBi9mieRnzNC9jnixmi0vbWrVqlQ4cOKDi4mJ99dVXLm3rVK+++qpCQkLaPEwmk5544okOl7darbr22muVlpYmk8mkd955p9Ntf/DBBzKZTLr//vtdEzwAwKXcmQdP1V9y4hdffKE5c+YoJiZGUVFRmjNnjrKyshzzCwoKdMEFFyg6Olrh4eGaMGGCVq9e7a7uAAC6wVM573SeyoGS1NjYqJ/+9KdKSEhQSEiIxo4dq6NHj3a6/GuvvaZRo0YpJCRE5557rrZt2+aYd7Yc6UkUY/qBAJ8AvXfDe3rvhvcU4BPg0rZycnI0fPhw+fv7u7Sd0y1ZskQ1NTWOx6ZNm2Q2m/W9732v03WmTZumFStWKDk5udNlamtrdd999+n88893RdgAADdwZx48VX/JiSdPntQtt9yiw4cP6/jx45oyZYouv/xyNTc3S5IiIyO1fPlylZaWqrKyUs8884xuvPFG5eTkuLNbAIAu8FTOO52ncqAk3XLLLcrOztbXX3+t6upqvfXWW4qIiOhw2S1btuiuu+7S8uXLVVlZqdtvv13z5s1TZWWlpLPnSE+iGDPApaWl6fHHH9e5556r4OBgzZ07V+Xl5br77rsVERGhjIwMff7555Kkn/zkJ3rssce0bt06hYSE6JFHHtH48eP18ssvt9nm3Llz9Zvf/Malcb/wwgu67LLLlJKS0uF8Pz8/3X///Zo+fbosls4rxj//+c+1ePFijRgxwlWhAgD6iYGaE+fOnavFixcrIiJCfn5+euCBB5Sfn6/c3FxJUnBwsIYPHy6z2SzDMGQ2m9Xc3HzGbxkBAANLf8mB+/bt05o1a/Tiiy8qMTFRJpNJI0eO7LQYs2bNGl111VU677zzZLFYdOeddyokJMRxBOjZcqQnUYzxAq+99ppWrVqlwsJC5eXlacqUKZo1a5bKysq0ePFi3XXXXZKkP/zhD3r44Yc1f/581dTU6Je//KWWLl2qFStWOLZVXFysjz76SEuWLOmwrdbB3Nnjs88+O2u89fX1WrlypW6//fZe9Xvbtm3asGGDHnrooV5tBwAwcHhDTty0aZMiIiKUmpraZvq4cePk7++vqVOn6sILL9T06dO7vE0AQP/XH3Lgpk2blJ6ert/+9reKi4vT8OHD9fvf/77TPtntdhmG0WaaYRjavXt3p9vvKEd6AsWYfqDWWqvgXwcr+NfBqrXWdnv9u+++W6mpqYqIiNAVV1yhmJgYXXvttbJYLLr++uu1d+9eWa3WDtddsmSJNm3apMLCQknSypUrNX369E6/nXvmmWdUUVHR6WPatGlnjffvf/+7/Pz8tGDBgm73tZXNZtMdd9yhZ555xiOH1gEAnKe3efBUAz0n5ubm6s4779Qf/vAH+fj4tJm3e/du1dTUaO3atZo7d+4ZjywFAHiGM3Pe6fpDDiwvL9fevXtlGIby8vK0evVq/fGPf9Srr77a4fLz58/XO++8oy1btshms+nPf/6z8vLyVFVV1W7ZM+VIT6AY00/U2epUZ6vr0brx8fGO50FBQe1+NwxDdXUdbzshIUGzZs1yvPhffvllLVu2rEdxdNULL7ygZcuWydfXt8fb+N3vfqdzzjlHM2fOdF5gAACP6U0ePNVAzokFBQWaPXu27rnnHt16660dLuPn56f58+fr448/7vSNLQDAs5yV807XH3JgSEiILBaLHnvsMQUEBGj06NG69dZbtWbNmg6Xnzlzpp566indcccdio+P17Zt23TJJZcoOjq6zXJdyZHuRjEGZ9V6SNrevXt18OBBLVq0qNNl77rrrnZ3gDj18emnn56xrcOHD2vz5s267bbbehXzBx98oDVr1ig+Pl7x8fF644039Pzzz2vq1Km92i4AwLv11ZxYWFioiy++WEuXLtXDDz981uVtNpsOHTp01uUAAGjljhw4fvx4SZLJZOpyXLfeequysrJUVlam559/XllZWZoxY4ZjfndzpLtQjMFZLVy4ULm5ufrpT3+qhQsXKiQkpNNln3322TZ3gDj9cbbz01944QVNnTpVo0aNOmtcjY2NamhokGEYstlsamhocFwV++2331ZWVpZ27typnTt3asGCBVqyZInWrl3bvc4DAHCKvpgTi4qKNHPmTF133XV65JFH2s3ftGmTtm7dKqvVKqvVquXLl+vjjz/WpZde2rVOAwAg9+TAiy66SBkZGfrlL38pm82mAwcOaPny5brqqqs6XN5ms2nnzp2y2+0qKyvTPffcoyFDhujyyy+XdPYc6UkUY3BWQUFBWrRokTZs2ODSw7Gbm5v10ksvdXqRwtMrqCNGjFBgYKDy8vL0/e9/X4GBgY6LSkVFRTmOiomPj1dgYKCCgoIUExPjsvgBAANfX8yJzz//vA4fPqwnn3yyw28da2trdeeddyo6OlqDBg3SX/7yF73++utdumYNAACt3JEDLRaL3n33XW3dulURERG6/PLL9aMf/ajNhYJPzXE2m0233HKLwsLCNHz4cDU1NWnt2rUym1tKHWfLkZ5kMk6/9HAPVFVVKTw8XJWVlQoLC3NGXDhFrbVWIY+3VB1rHqpRsF9wm/kNDQ3KycnRkCFDFBDguXvRDxRn2p+81gGcjr8Lrne2PHgqcmLvkAMBdAd/F5yvOznvdOTA3nF3DuTIGAAAAAAAADfy/P2ccFZmk1kzBs9wPAcAwJuQBwEA3oKc5z0oxvQDgb6B+uTmTzwdBgAAHkEeBAB4C3Ke96DUBgAAAAAA4EYUYwYQJ1yLGWI/AsBAwN/ynmG/AUD/x9/ynnH3fqMY0w/UWmsV+7tYxf4uVrXW2nbzLRaLJMlqtbo7tAGpdT+27lcAgGedLQ+eipzYO+RAAPCs7uS805EDe8fdOZBrxvQTJ+pOdDrPx8dHQUFBKi0tla+vr+Oe6ug+u92u0tJSBQUFyceH4QEAfcWZ8uCpyIk9Rw4EgL6hqznvdOTAnvNEDiTTDgAmk0kJCQnKyclRbm6up8Pp98xms1JTU2UymTwdCgCgm8iJvUMOBID+ixzYO+7OgRRjBgg/Pz9lZGRwSJoT+Pn5UUUGgH6MnNhz5EAA6N/IgT3n7hxIMWYAMZvNCggI8HQYAAB4HDkRAOCtyIH9A199AAAAAAAAuBHFGAAAAAAAADfiNKV+wGwya3LiZMdzAAC8CXkQAOAtyHneg2JMPxDoG6htd2zzdBgAAHgEeRAA0NftK9mnJW8vkUzSymtWKjM2s0fbIed5D0ptblJWV6bGpkZPhwEAAAAAcCLDMHTLmlu0q3iXdh3fpflvzpfdsHs6LPRxFGPc4D83/qdifhej1KdStad4j6fDAQAAAAA4ybaibdpW9N3RLDkncrR833LPBYR+gWKMi31V+JV+9emvJEklNSVauGpht6ukdbY6pT2ZprQn01Rnq3NFmAAA9FnkQQBAX7bu4DpJ0oRhEzR70mxJ0vM7n+/Rtsh53oNijIv9edufJUkjU0cqwC9A2aXZWrF/Rbe2YRiGcitzlVuZK8MwXBEmAAB9FnkQANCXbcjeIEnKHJKpySNbLr67LWebjtUd6/a2yHneg2KMC9mabVq9f7Ukac55c3TB2AskSU9vf9qTYQEAAAAAnMBu2B2XokiLT1NCdIISohPUbG/WK9++4uHo0JdRjHGhrwq/UrW1WsEBwRocP1jnZ54vSdpxdIdyq3I9HB0AAM5Vb6vXwx89rCVvL9Hu4t2eDgcAAJfLq8xTfVO9LGaLosOjJUmZaS13Ulp/aL0nQ0MfRzHGhf555J+SpOEpw2U2mRUXGafUQamyG3Y9t/c5D0cHAIBz3fuPe/X4Z49r5Z6VmrZ8mnIr+OIBADCw7S/dL0mKjYiVxWyRJI0eMlqStO3oNtmabR6LDX0bxRgX2lqwVZI0LHmYY9o5GedIktYdWOeRmAAAcIWckzl68ZsXJUlBAUGqbqjWnR/c6eGoAABwrf0nWoox8VHxjmmD4wcryD9ItQ21Wp/H0THoGMUYF9p1fJckKTk22TFtbPpYSdK+/H06Vtv9CzoBANAXvfDNCzJkaGTqSP3w6h9Kkj749gN9W/6thyMDAMB1Wo+MiYuKc0yzmC0aMXiEJOntg297JC70fRRjXKS4pljFtcUyyaSE6ATH9JiIGCVEJ8hu2PXKga5d0MlkMikzNlOZsZkymUyuChkAgB5rva3n5JGTlRKXohEpI2QYhn71xa96vW3yIACgr8o6kSVJGhQ5qM300Wktpyp9cviTbm2PnOc9fDwdwEC1q7jlqJiYiBj5+fq1mTcmfYyOlR3TmgNr9MDEB866rSDfIO27e59L4gQAoLeKa4odeW9Eass3gdPHT9eB/AN6d++7sl5mlZ+P35k2cUbkQQBAX2QYhuM0pUFRbYsxIwePlEkm5Z3I06GKQ8qIyOjSNsl53oMjY1yk9S4SSTFJ7ea1nqq0LWebam21bo0LAABn+yjnI0ktp+WGBoVKkkaljVJoUKiq66v16sFXPRkeAAAuUVpXqpP1J2WSSXGRcW3mhQSGaHD8YEnSq9+SB9EexRgXaf2GMDE2sd28lLgUhQeHy2qz6o1Db7g7NAAAnGpb4TZJ0tCkoY5pFrNFE4dPlCQt37XcE2EBAOBSrdeLiQqL6vAI0Na7Kr1/6H23xoX+gWKMi7RevDcxun0xxmQyadywcZKkN7PePOu26mx1Gv3MaI1+ZrTqbHXODRQAgF7aWbxTkpQU2/Zo0MkjJ0uStmZv1Yn6Ez3ePnkQANAXdXaKUqvMtExJ0jd536jW2rUzIsh53oNijAtYm62OgXn6G9NWE4ZNkCR9evhTNTY1nnF7hmEoqzRLWaVZMgzDqbECANAbhmFo5/Gdktqfmpscm6xBkYNka7bp//b+X6/aIA8CAPqa1iNjTr94b6vEmERFhETI2mTV6iOru7RNcp73oBjjAvtL96vJ3qRA/0BFhER0uMyQhCEKDQpVXWOd3s7mdmcAgP4przJPFQ0Vspgt7b4ZNJlMjqNjVu5a6YnwAABwmbMdGWMymTQqbZQkafXBrhVj4D0oxrhA6/VikmKSOr0dmdls1rihLacqrcziDSoAoH9qPSomPipePpb2N2k8d+S5MsmkfYX7lFWW5eboAABwHcdtrTspxkjf3eJ60+FNHOmCNijGuIDjejEx7a8Xc6rxw8ZLkj459IlszTaXxwUAgLM5TlHq5LTciNAIDU8ZLkn632/+111hAQDgUtWN1SqsKpTU+WlKkjQ8Zbj8fP1UVl2mD/I+cFd46AcoxrjA7pKW21qfrRgzNGmoggOCVVNfozcPn/1CvgAA9DWdXbz3VFMyp0iS3t7ztuyG3R1hAQDgUt+e+FaSFBoUqqCAoE6X8/P109j0sZKkF/e86JbY0D9QjHEywzC6fGSMxWzRxBEtt/386zd/dXlsAAA4W2cX7z3V2PSxCvALUGlVqdYdWeemyAAAcB3H9WLOcFRMq4nDWz7zvb//fTU1N7k0LvQfFGOc7HjNcZXWlcpkMik+Ov6sy5+XeZ4k6bNDn6m4trjDZUwmkwaHD9bg8MGdXoMGAAB3q2io0NGKo5KkxNjOv4Dw8/XTORnnSJKe+eaZbrdDHgQA9DWOOymd4XoxrUamjlRwQLCq6qrOevMWcp73oBjjZLuLW05Rio2IlZ+P31mXT45NVnJssprsTfrTzj91uEyQb5CO3n9UR+8/qiDfzg+BAwDAnVqPBI0MjVSQ/5nz03mjW758+Ojbj1RUU9StdsiDAIC+5mx3UjqVxWLRhIwJkqS/7PjLGZcl53kPijFO1nonpeSY5C6v03p0zPIdyzmXHgDQb7SeopQce/aclxafpsGDBqupuUm//vLXLo4MAADX6s5pSpJ0wZgLJEmbD21WXlWey+JC/0ExxslaizEJMQldXufckecqwC9AheWFev3A664KDQAAp2q9eO/ZrpHWasY5MyRJr+x4RQ22BleFBQCAS1mbrcouz5bUtSNjpJYL3Q9JGCK73a7/2fY/rgwP/QTFGCfr6sV7TxXgH+ColP52y2/bza+31evc58/Vuc+fq3pbvXMCBQCgl852W+vTjR86XhEhEaqsq9ST3zzZ5XbIgwCAvuRQ2SE1G80K8AtQeHB4l9ebNm6apJYvJeqsdR0uQ87zHhRjnKjeVu+4xVlXDtk+1UXjL5LZbNbugt36KO+jNvPshl3bi7Zre9F2TmMCAPQJ1mar9pXsk9T1YozFYtHFEy+WJP3+09+roalrR8eQBwEAfcmppyh15yK744eNV2RopCrrKvU/2zs+Ooac5z0oxjjRvtJ9ajaaFRIYorDgsG6tGxEaoXNHnitJ+rd//psMw3BFiAAAOMX+0v2y2W0K8AtQVGhUl9e7YMwFigiJUFlNmX7z5W9cGCEAAK7Reiel+Kiz3z33VD4WH10y+RJJ0v9+/r8c+eLlKMY4Uevh2okxiT26Ddnl510uH4uPdhfs1qqDq5wcHQAAzvPN8W8ktRwV052c5+vjq8umXCZJemLLEyqrK3NJfAAAuMq+0pYjQ7t6vZhTnTfqPEWEROhk7Uk9tvUxZ4eGfoRijBO1Xi+mu6cotYoMjdRF4y+SJP34gx+rsanRabEBAOBM3xxrKcb0JOedN+o8xUfFq7q+Wnf/825nhwYAgEu1FmPio7t3ZIwk+fj4aO75cyVJT372pAqqCpwaG/oPijFO1N27SnTkknMvUWhQqArKC/TgpgedFBkAAM516pEx3WWxWPS9i78nSXpz55v6OPdjp8YGAICr2JptOnDigKTun6bU6txR52pw/GA12Bp0x/t3ODM89CMUY5zEbtgdR8b05I1pqyD/IC2asUiS9PTnT2v7se1OiQ8AAGexG3bHqbk9PRp0aNJQTRk1RZJ0w+obVNlQ6azwAABwmcPlh2Wz2+Tv66/I0MgebcNsMuvamdfKZDLp/f3v66U9Lzk5SvQHFGOc5FDZIVVbq+Vr8VVcZFyvtjV+2HiNTR+rZnuzFr61UNWN1YoJilFMUIyTogUAoOeOnDyiamu1fCw+GhTZ/fPlW1190dWKCovS8crjWvLukjNevJ48CADoC069XkxPrhPaKiUuRZdOvlSSdM979yi/Mt8xj5znHSjGOMnWgq2SpJRBKbKYLb3alslk0nWzr1NESIQKThbotn/cppKflqj0gVIF+wU7I1wAAHqs9XoxCdEJslh6nvOC/IO0dM5SmU1mvbf/Pf3ys192uFywX7BKHyglDwIAPG5fSUsxJiE6odfbmjNljlLiUlTTWKM5r89Rna2OnOdFKMY4yRcFX0iS0uLTnLK9kMAQ3TT3JpnNZq3fv14/+egnTtkuAAC91Xq9mJS4lF5va0jCEC28aKEk6Zcbf6kVe1b0epsAALjK3tK9knp+vZhTWSwW3TT3JgUHBGv/8f36/urvy27Ye71d9A8UY5yk9ciYwfGDnbbNIQlD9P2Lvy9J+uOWP+p3X/zOadsGAKCnvir8SlLvrpF2qunjp2vGhBmSpFveuUWv7XvNKdsFAMDZvi76WpLzcmBMeIxuveJWWcwWvbf/Pd387s0UZLwExRgnqG6s1t6Slgqps46MaXX+6PM1Z8ocSdK/b/h3PbaZe9EDADynyd6kLwu/lNTypYGzXDXtKk0eMVnN9mYtWbVEL+x8wTGv3lavmctnaubymaq31TutTQAAuqOsrkw5FTmSpOS4nl3AviNDk4bqhktvkMlk0oqdK5T4RKJmLJ9BzhvgKMY4wRcFX8hu2BUZGqnwkHCnb//iiRc7nj/y8SP6yT9/QrUUAOARe0v2qsZaowC/AKccot3KbDbrhktv0JTMKTIMQ7evuV3/9sG/qdneLLth16bcTdqUu4n8BwDwmK+PtRwVExMeoyD/IKdue9KISVpy6RJJUnFNsTbnblZVY5VT20DfQjHGCT488qEkKSM5wyXbP/0q3U98/oTmvDpHFQ0VLmkPAIDOfJ7/uaSW03LNZue+jTCbzVo8e7Hj7hJ/3PpHzXplloqqi5zaDgAAPbG9aLskKXVQqku2P3nkZEdBRpIuevkifXviW5e0Bc+jGOMEH+a0FGNGpI5weVuLZy2Wr8VXH2Z/qLHPjdXm3M0ubxMAgFZb8rdIcu4pSqcym8y64oIrtHTOUvn6+GpzzmZNen6SS9oCAKA7Wq+Z5sxTlE43btg4x/ODpQd1zv+do+e+fk6GYbisTXgGxZheOlF3wnGLz+Epw13e3jkjztF937tPkaGRKqgo0MzlM/Wj93+kGmuNy9sGAHg3wzC0MWejJCk9Md2lbU0aMUk/XfxTpQ5KVXVjtWP67uLdLm0XAICO2A2744vw9ATX5sBWw5KGqcHWoLvW3aWLXrpI+0v3u6VduAfFmF56//D7MmQoITpBoUGhbmkzJS5FD97woM7PPF+GDP3vl/+roX8aqpd2vsS59AAAl9ldvFvHa47Lz8fPLW9EB0UN0o+u/ZEum3KZY9qFL16oxasWK6s0y+XtAwDQanfxbp1sOCl/X3+lxKW4pc3brrxNC6YtkK/FV5/lfqZxz47T/e/fr5LaEre0D9eiGNNLf8/6uyRp3NBxZ1nSuQL8A7T4ksW648o7FB0WrZKaEt285mZNeG6CVu9fTVEGAOB0G7I3SJKGJQ+Tj4+PW9q0WCyaPWm243dDht7Y+4bGPDNGi95cpM/yPuPQbQCAy31y9BNJ0pDEIbJYLG5p02wya9bEWfrZjT/T6LTRarI36akvn1LaU2l6+KOHVVpb6pY44BoUY3qhurFa7x9+X5I0fth4l7bl5+MnPx+/dtNHDxmtn934M82/YL78ff21p3iPrnnzGo3+y2i9vOtlNTQ1uDQuAID3WH9ovSRp5OCRbm+7NQ/ed+19Gps+VoYMvb3/bU3/23SN/sto/fmrP6usrsztcQEAvMMH2R9IkjKSXHPTllOd/tkvOjxadyy4Q3dedadS4lJUb6vX4589ruQ/JuvmNTdr5/GdLo8JzmcynPB1UlVVlcLDw1VZWamwsDBnxNUvvLzrZd30zk2KjYjVw0sfbnfXI3erqa/Rpp2b9OmuT9VgbSnCRARG6Nbxt+rOyXdqeLTrr2kz0Hnrax1A57zl70JRdZGSn0iWIUO/uPkXigqL8mw8J4q0eedmfX3wa9mabJIkH7OPLkm/RNePuV5XjbhK4QHhHo1xoPGW1zqArvOWvwtVjVWK/V2srM1W/WzJzxQfHe+xWAzD0N4je/XP7f9UXnGeY/rExIm6edzNWjxmsWKDYz0W30Dlitc6xZhemPrCVH1R8IXmT52vS869xNPhONQ11mnL7i36fO/nOll90jH9nIRzdMOYG/T90d9Xarhrbsc20Hnrax1A57zl78JTXzyl+zfcryEJQ/Sj7/3I0+E41DXWadv+bfoq6ysVnih0TPcx++jClAs1L2Oe5g6bqzFxYzz+pUl/5y2vdQBd5y1/F17f+7quX3W94iLj9NCND/WJfGIYho4eP6rNOzdr1+FdjstU+Jh9dGn6pVo4cqHmD5+vhNAED0c6MFCM6UO+Lvpak5+fLIvZokdvfdRtF+/tDrvdrv25+7VlzxZ9m/ttm+vITEyYqCsyrtC8jHk6N/FcWczuOe+xv/PG1zqAM/OGvwuGYWjCcxO0u3i3Fs1YpOnjp3s6pA4Vlxfrm0Pf6JuD36j4ZHGbefGh8ZqZOlPTUqdpWuo0jYkbQ+7rJm94rQPoHm/5u3DFyiu0/tB6XTL5Es2/YL6nw2mnuq5aOw7u0PZvtyu/JL/NvEmJk3RlxpWaNWSWpiRNkb+Pv4ei7N8oxvQhC15boLUH12rSiElaOmepS9uyNdn0t/V/kyTdMu8W+fr4dnsbNXU12pW9S98c/EbZhdky9N1/e1RglGYPma3pqdM1ffB0jY0byxvUTnjjax3AmXnD34WPcz7WrJdnyc/HT4/e+qiCAoLc2n5P8mBpRan25+7X/qP7dbjgsGzNtjbzQ/1DdV7SeZqUMEnnxJ+jiQkTNTRqqMwmLqfXGW94rQPoHm/4u5BbkashTw2RIUP/sew/FBvh2lOAevvZ73j5ce3O3q19R/Yptzi3zbwAnwBdkHKBZqXN0tSUqZqUMIlTervIFa9199wKYYDZnLtZaw+ulclk0pwpc1zent2wK+toluN5T4QEhejCsRfqwrEXqrK2Ut/mfqv9R/frQN4BldeX662st/RW1lsty/qF6IKUC3Re0nmON6ip4al94nA8AIB7GYahX336K0nSlFFT3F6IkXqWB2MjYhUbEauLxl8ka5NVucdzdaToiHKKcpRzLEfVjdX68MiH+vDIh451QvxCNH7QeI2JG6ORMSMdj9TwVIo0AOCl/vjFH2XI0PCU4S4vxEi9/+wXHxWv+Kh4XXbuZaqsrVRWTpYO5B/Q4YLDqqmv0cacjdqYs9Gx/PDo4ZqSNEWTEybrnIRzNDp2tKKDop3WH3SOYkw31dnqdPu7t0uSpo6eqrjIOA9H1H3hweE6L/M8nZd5nprtzco9nqvDhYd1pPCIco7lqMZaow+yP3BcMVySIgIiNDF+osbHj9eI6BGON6hxwXEUaQBgAFt3cJ025myUxWzRxRMv9nQ4PeLn46eM5AxlJLfcAaPZ3qyiE0XKL8lXQUmBCksLVXSiSDXWGm3J36It+VvarB/oE6iM6AwNjx6utPA0pUV89xgcMVghfiGe6BYAwMWOVhzVX7b/RZI0e9JsD0fTfeHB4Zo6ZqqmjpkqwzBUXF6sQwWHlF2YrbziPJVXl+tg2UEdLDuoV3a/4lgvLjhOY2LHaHTcaGXGZmpE9AilR6YrOSyZMyiciGJMN9gNu5atXqZD5YcUHhyu+Rf2vfMFu8titig9MV3pienSuS3XmSk6UaScYznKL81XYUmhjpUfU0VDhTYe3aiNRze2WT/MP0yjYkYpIzpDg8MHt7wxDR+swRGDlRqeqgCfAA/1DADQWyW1JfrBuh9IkmaeM1PR4QPjmzKL2aKUuBSlxKU4pjXbm1VyskSFpYUqOVmi4vJiFZ8sVmlFqeqb6rW7eLd2F+/ucHvRQdFKC09TQmiCEkMSlRCaoISQBCWGfvd8UMgg+Zh52wUA/YXdsOv2d2+XtdmqjOQMDU/p33emNZlMio+OV3x0vOPab9V11covyVdecZ7yi/N1rOyYyqvLVVJboo217T/7+Zp9NThisIZGDlV6ZLqGRAxRSniKkkKTlBSWpMTQRD7/dQPvCrqozlanm9+5Wav2r5KP2UfLLl+mIH/3H6rtamazWclxyUqOS3ZMa2pq0rHyYyosLdSxsmMqOVmikpMlKq8qV1Vjlb4s/FJfFn7Z4fbiguOUGp6q+JB4xQfHt/wMidegkEGO53HBcQr1C+UIGwDoQ8rryzX31bk6XnNc8VHxmnOe60/L9SSL2aKE6AQlRLe960SzvVnlVeUqOVmiE5UnVF5VrpPVJ1VeVa7yqnLVNdaprK5MZXVl0rHOt2+SSZGBkYoNilV0ULSiA6MVExTz3c9TpkUERCjMP0zhAeEK9QvlW0gAcDPDMPRvG/5NH+V8JF8fX31/1vcH5GeV0KBQZaZlKjMt0zGtwdqg4vJiHS8/3vIoO66yyjKVVZXJZrfpcPlhHS4/3Ok2IwMjlRya3FKcCUlUXHCcYoJiOnyE+YcNyP3aVRRjzqLZ3qzV367Wzz78mbJPZstitujGOTdqaNJQT4fmNj4+Pu2+QZRaLi51ovKEisuLdaLyhE5Wn3S8QT1ZfVKNtkaV1JaopLbkrG1YTBZFBkYqKjBKkQEtP099HhkYqTD/MIX4hTgeoX6h3z33D1WQbxDn9ANALxmGoQ+yP9Cd6+5UbmWuQgJDdMsVt8jPx8/ToXmExWxxXH+mI3WNdTpZ1ZL/quqqVFX73aOytlJVtVWqrquW3bCrvL5c5fXlUln3YgjxC1GYf1hLgcY/3FGoCfNrmRbsF6wg3yAF+7b8PPXROu/0R6BPoFe/AQaAzhRVF+m+f9ynVftXSZIWz17slmvF9BUBfgEaHD9Yg+MHt5lut9tVWVupE5UnHMWZssoyVdZUqrK2UpU1lbI123Sy/qRO1p/UnpI9Z23L1+yrqKCWz3zh/uEtue1fua719zZ5zz+sw1wX5BskP4tfv8trFGNO0djUqJMNJ5VzMkf7T+zX1vytWn94vYqqiyRJESERWnLZEsc5597O18e3w28RpZY383UNdSqvLldlTaWq66pVXVetqroqVdee8ryuWo22RjUbzTpRd0In6k70KqZg32CF+IcoyCdIAT4BCvQNVIBPQPuHpYNpPgHys/jJ1+IrX7Nvh89tdbazBwEA/UhDU4NKakuUVZqlrwq/0tv739au4l2SpOiwaN1+5e0aFDnIw1H2XUH+QQqKDVJSbFKny9jtdtU21Kqmvka19bWqbfjXo75WdQ11juet0+sb69VgbVBTc5MkqcZaoxprjeP9iLP4W/zl7+Pf5meAT0C7aa0/zVa+8AAwsBiGoarGKuVW5uqbY9/o/ez39c6376ihqUEWs0Xfu/h7mjRikqfD7BPMZrMiQyMVGRrZ4edhwzBU11inqtoqVdRUqLKmUlV1Vd/lvn/luZr6GtU21Mpqs8pmt6m4pljFNcW9j89k/u6LiFMKNoG+gfKz+Mnf4t/y06flp5/5u+et806df+o0V30OdEoxpvXu2Bc/d7EsgRbHbZNPvWt263NDRpvnrfNOX6ez5bqzjTbzz7CczW5TRX2FGpoaOuxfUECQzh99vi4af5EC/ALUUNXxcq7S2NQo/avJhuoGGT69vhu5W1hkUWxArGIDzlxJtjZbVd9Qr/rGlkddQ53qrd/9bJ3XaGuU1WZVo61RjU2Nslr/9dzWqNY7ddc21Kq2utZ1nWps+eGEO8IDGCA6yoGn/43oSp7rSW7sLE+2mdbJOnbDroqGCtVa2//NtFgsmjp6qmZPnq1A30C3573T9dc8eCpf+SrSN1KRvpFSF++I2dTcpAZrgxqtjaq31avR2qhGa6MarA2OR6OtUdYmq6w2q5qammRtssrWZJOtySarzSprs1U2279+b7KqubnZsf3Gf/3rMnIggNM4Kwc6czlHuzLOuI612aqyujI12Zva9Wtw/GDNv3C+UmJT+OzXDRZZWnJdZKQUeeZlrc1W1dW3fCHRYG1QQ2NLTmuwNqje2vLZr6GxwZH3Gq2NqrfWy9Z8So5rssqw/+t9jeyqqa9RjWpc0zkX5ECT4YStHTlyREOHes9pO0B2drbS09M9HQaAPoAcCG9DDgTQihwIb+PMHOiUI2OioqIkSXl5eQoPD3fGJrusqqpKKSkpys/PV1hYF79qou1+27an26+srFRqaqrjNQ8A5EDa9oa2JXIggPbIgbTtDW1LrsmBTinGmM0t5xCHh4d7ZMdIUlhYGG17Uduebr/1NQ8A5EDa9qa2JXIggO+QA2nbm9qWnJsDyaYAAAAAAABuRDEGAAAAAADAjZxSjPH399cjjzwif39/Z2yOtmm7z7bv6b4D6Hu89W8SbXtX232hfQB9j7f+TaRt72rbVe075W5KAAAAAAAA6BpOUwIAAAAAAHAjijEAAAAAAABuRDEGAAAAAADAjSjGAAAAAAAAuFG3izHr1q3TiBEjlJGRob/+9a/t5n/11VcaPXq0hg0bpscee8wpQUpSfn6+Zs6cqczMTI0bN05vvfVWu2XS0tI0btw4TZgwQfPmzXNa25Lk4+OjCRMmaMKECbr99tvbzXdVvw8cOOBod8KECQoMDNQ777zTZhln93vhwoWKjIzUtdde65jWlf5lZ2dr8uTJGjZsmO666y715NrQp7ddV1enefPmaeTIkRozZoz+9Kc/dbjezJkzNXLkSMd+6omO+t2VfeuMfgPoH8iB5EByYFvkQMB7kAPJgeTAtnrdb6MbbDabkZGRYRQUFBhVVVXGsGHDjLKysjbLTJ482di1a5dhs9mMyZMnG3v27OlOE50qKioyvvnmG8MwDKO4uNhISkoyampq2iwzePBgo7q62intnS46OvqM813V71NVV1cb0dHRLu/3xo0bjXfffddYtGiRY1pX+nfNNdcYa9euNQzDMK6++mrH8960XVtba3zyySeGYRhGTU2NMXLkSOPQoUPt1psxY0av93lH/e7KvnVGvwH0feTAzpEDyYGGQQ4EBjJyYOfIgeRAw+hZv7t1ZExrVSwpKUmhoaGaN2+eNmzY4JhfVFSkpqYmjRs3Tj4+Prrhhhu0du3a7lWHOpGQkOCodMXFxSkqKkrl5eVO2XZvubLfp3r33Xc1e/ZsBQcHO33bp7r44osVGhrq+L0r/TMMQ1u3btUVV1whSVq2bFmP9sHpbQcFBWnGjBmSpODgYGVkZOjYsWM96Va32+4KZ/UbQN9HDuwYOZAcSA4EBj5yYMfIgeTA3vS7W8WYoqIiJSUlOX5PTk5WYWFhl+c7y/bt22W325WSktJmuslk0kUXXaQpU6Zo1apVTm2zqqpKkyZN0rRp07Rp06Y289zV7zfffFPXXXddu+mu7LfUtf6VlZUpKipKJpOp02V6Kz8/X7t379bEiRM7nH/DDTdo4sSJeuaZZ5zW5tn2rTv6DaBvIAeSAyVy4KnIgYD3IAeSAyVy4Kmc0W+f7ixsdHAOVGvjXZnvDGVlZVq2bFmH5ylu2bJFiYmJKigo0KxZszR+/HgNGzbMKe0ePXpUiYmJ2rt3r6644grt2bNHYWFhktzT76qqKm3ZskWvv/56u3mu7LfUtf65eh80NDTouuuu0+9///sOK8IrV65UYmKiysvLdfnll2v06NGOSmpvnG3fuuP/HkDfQA4kB7YiB7YgBwLegxxIDmxFDmzhjH5368iYpKSkNtWegoICJSQkdHl+bzU2NmrhwoV66KGHdMEFF7Sbn5iYKKmlKjV79mzt3LnTaW23bnvMmDHKzMzUwYMHHfNc3W9JWrNmjebMmaOAgIBOY3NFv6Wu9S8mJkbl5eWOF6Uz94FhGLrppps0b968NhdVOlXrPoiKitKiRYu0bds2p7R9tn3ryn4D6FvIgeRAiRx4KnIg4D3IgeRAiRx4Kmf0u1vFmClTpmjv3r0qLCxUdXW11q9frzlz5rQJ2GKxaPfu3WpqatJrr72mK6+8slsBdcYwDN18882aNWuWli5d2m5+bW2tqqurJUkVFRXavHmzRo0a5ZS2T548qcbGRkktOzkrK0vp6emO+a7sd6vODk1zZb9bdaV/JpNJ559/vt577z1J0ssvv+y0ffDQQw8pKChIP//5zzuc39TUpBMnTkhqqZxu2LBBo0eP7nW7Xdm3ruw3gL6FHEgOJAeSAwFvRQ4kB5IDXZADu3W5X8Mw1qxZY2RkZBhDhw41nnvuOcMwDGPu3LlGYWGhYRiGsXXrViMzM9NIT083Hnnkke5uvlOffvqpYTKZjPHjxzseu3fvdrSdnZ1tjBs3zhg3bpwxZswY49lnn3Va21u2bDHGjBljjBs3zhg/fryxevVqwzDc02/DMIyKigojLi7OaGxsdExzZb8vu+wyIyYmxggMDDSSkpKMr776qtP+3Xbbbca2bdsMwzCMgwcPGhMnTjTS09ONO+64w2hubu5125s3bzYkGZmZmY7/9/fff79N2zU1NcbEiRONsWPHGpmZmcajjz7qlH5/8cUXne5bZ/cbQP9ADiQHkgPJgYC3IgeSA8mBzu23yTB6cBNwAAAAAAAA9Ei3TlMCAAAAAABA71CMAQAAAAAAcCOKMQAAAAAAAG5EMQYAAAAAAMCNKMYAAAAAAAC4EcUYAAAAAAAAN6IYAwAAAAAA4EYUYwAAAAAAANyIYgwAAAAAAIAbUYwBAAAAAABwo/8PtS5H5n1U6fkAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "squad = ['Di Gregorio',\n", - " 'Carlos Augusto',\n", " 'Rrahmani',\n", - " 'Baschirotto',\n", - " 'Valeri',\n", - " 'Frattesi',\n", - " 'Pereyra',\n", - " 'Lazovic',\n", - " 'Gonzalez N.',\n", - " 'Vlahovic',\n", - " 'Hojlund']\n", + " 'Bastoni',\n", + " 'Kristiansen',\n", + " 'Kostic',\n", + " 'Pellegrini Lo.',\n", + " 'Barella',\n", + " 'Strefezza',\n", + " 'Rafael Leao',\n", + " 'Osimhen']\n", "\n", - "config_433_classic = [3, 6, 7, 9, 10, 17, 18, 19, 26, 28, 30];\n", + "s = simulate_lineup(squad)\n", "\n", - "s = simulate_lineup(squad, MOD = True)\n", - "\n", - "plot_lineup(squad, config_433_classic)" + "plot_lineup(squad, config_442)" ] } ], diff --git a/1_scraping_fbref.ipynb b/1_scraping_fbref.ipynb index 7b85157..fc3f97c 100644 --- a/1_scraping_fbref.ipynb +++ b/1_scraping_fbref.ipynb @@ -287,119 +287,119 @@ " it ITA\n", " DF\n", " Inter\n", - " 35-223\n", + " 35-232\n", " 1988\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", + " 3.0\n", + " 3.0\n", + " 270.0\n", " 0.0\n", " ...\n", - " 2.0\n", - " 1.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 4.0\n", " 3.0\n", + " 4.0\n", " 0.0\n", - " 100.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 15.0\n", + " 10.0\n", + " 2.0\n", + " 83.3\n", " \n", " \n", " 1\n", + " Yacine Adli\n", + " fr FRA\n", + " MF\n", + " Milan\n", + " 23-063\n", + " 2000\n", + " 1.0\n", + " 1.0\n", + " 57.0\n", + " 0.0\n", + " ...\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 5.0\n", + " 0.0\n", + " 1.0\n", + " 0.0\n", + " \n", + " \n", + " 2\n", " Michel Aebischer\n", " ch SUI\n", " MF\n", " Bologna\n", - " 26-258\n", + " 26-267\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 347.0\n", + " 6.0\n", + " 6.0\n", + " 527.0\n", " 0.0\n", " ...\n", - " 7.0\n", - " 5.0\n", + " 10.0\n", + " 6.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 23.0\n", - " 2.0\n", - " 3.0\n", + " 29.0\n", + " 4.0\n", + " 6.0\n", " 40.0\n", " \n", " \n", - " 2\n", - " Luis Alberto\n", - " es ESP\n", - " MF\n", - " Lazio\n", - " 30-358\n", - " 1992\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 2.0\n", - " ...\n", - " 3.0\n", - " 5.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 24.0\n", - " 2.0\n", - " 4.0\n", - " 33.3\n", - " \n", - " \n", " 3\n", - " Pontus Almqvist\n", - " se SWE\n", - " FW\n", - " Lecce\n", - " 24-073\n", - " 1999\n", - " 4.0\n", - " 4.0\n", - " 347.0\n", + " Jean-Daniel Akpa-Akpro\n", + " ci CIV\n", + " MF\n", + " Monza\n", + " 30-354\n", + " 1992\n", " 1.0\n", + " 0.0\n", + " 7.0\n", + " 0.0\n", " ...\n", - " 3.0\n", - " 8.0\n", - " 1.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 15.0\n", - " 0.0\n", - " 3.0\n", " 0.0\n", " \n", " \n", " 4\n", - " Lorenzo Amatucci\n", - " it ITA\n", + " Luis Alberto\n", + " es ESP\n", " MF\n", - " Fiorentina\n", - " 19-228\n", - " 2004\n", - " 1.0\n", - " 0.0\n", - " 16.0\n", - " 0.0\n", + " Lazio\n", + " 31-002\n", + " 1992\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 2.0\n", " ...\n", - " 1.0\n", + " 6.0\n", + " 8.0\n", " 0.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", + " 36.0\n", + " 3.0\n", + " 5.0\n", + " 37.5\n", " \n", " \n", " ...\n", @@ -426,60 +426,60 @@ " ...\n", " \n", " \n", - " 424\n", + " 453\n", " Joshua Zirkzee\n", " nl NED\n", " FW\n", " Bologna\n", - " 22-122\n", + " 22-131\n", " 2001\n", - " 4.0\n", - " 4.0\n", - " 356.0\n", + " 6.0\n", + " 6.0\n", + " 520.0\n", " 1.0\n", " ...\n", - " 3.0\n", + " 5.0\n", " 1.0\n", - " 1.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 11.0\n", - " 9.0\n", " 2.0\n", - " 81.8\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 15.0\n", + " 12.0\n", + " 3.0\n", + " 80.0\n", " \n", " \n", - " 425\n", + " 454\n", " Zito\n", " ao ANG\n", " FW\n", " Cagliari\n", - " 21-196\n", + " 21-205\n", " 2002\n", - " 4.0\n", - " 3.0\n", - " 297.0\n", - " 1.0\n", - " ...\n", - " 3.0\n", - " 8.0\n", - " 5.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", " 6.0\n", - " 1.0\n", " 5.0\n", - " 16.7\n", + " 477.0\n", + " 2.0\n", + " ...\n", + " 5.0\n", + " 12.0\n", + " 6.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 9.0\n", + " 2.0\n", + " 7.0\n", + " 22.2\n", " \n", " \n", - " 426\n", + " 455\n", " Nadir Zortea\n", " it ITA\n", " DF\n", " Atalanta\n", - " 24-094\n", + " 24-103\n", " 1999\n", " 3.0\n", " 0.0\n", @@ -498,16 +498,16 @@ " 0.0\n", " \n", " \n", - " 427\n", + " 456\n", " Milan Đurić\n", " ba BIH\n", " FW,MF\n", " Hellas Verona\n", - " 33-122\n", + " 33-131\n", " 1990\n", - " 4.0\n", + " 5.0\n", " 1.0\n", - " 152.0\n", + " 154.0\n", " 0.0\n", " ...\n", " 7.0\n", @@ -517,21 +517,21 @@ " 0.0\n", " 0.0\n", " 4.0\n", - " 21.0\n", - " 14.0\n", - " 60.0\n", + " 23.0\n", + " 15.0\n", + " 60.5\n", " \n", " \n", - " 428\n", + " 457\n", " Mateusz Łęgowski\n", " pl POL\n", " MF\n", " Salernitana\n", - " 20-235\n", + " 20-244\n", " 2003\n", - " 4.0\n", + " 5.0\n", " 2.0\n", - " 161.0\n", + " 167.0\n", " 0.0\n", " ...\n", " 3.0\n", @@ -540,70 +540,70 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 14.0\n", + " 16.0\n", " 4.0\n", " 5.0\n", " 44.4\n", " \n", " \n", "\n", - "

429 rows × 115 columns

\n", + "

458 rows × 115 columns

\n", "" ], "text/plain": [ - " player nationality position team age birth_year \\\n", - "0 Francesco Acerbi it ITA DF Inter 35-223 1988 \n", - "1 Michel Aebischer ch SUI MF Bologna 26-258 1997 \n", - "2 Luis Alberto es ESP MF Lazio 30-358 1992 \n", - "3 Pontus Almqvist se SWE FW Lecce 24-073 1999 \n", - "4 Lorenzo Amatucci it ITA MF Fiorentina 19-228 2004 \n", - ".. ... ... ... ... ... ... \n", - "424 Joshua Zirkzee nl NED FW Bologna 22-122 2001 \n", - "425 Zito ao ANG FW Cagliari 21-196 2002 \n", - "426 Nadir Zortea it ITA DF Atalanta 24-094 1999 \n", - "427 Milan Đurić ba BIH FW,MF Hellas Verona 33-122 1990 \n", - "428 Mateusz Łęgowski pl POL MF Salernitana 20-235 2003 \n", + " player nationality position team age \\\n", + "0 Francesco Acerbi it ITA DF Inter 35-232 \n", + "1 Yacine Adli fr FRA MF Milan 23-063 \n", + "2 Michel Aebischer ch SUI MF Bologna 26-267 \n", + "3 Jean-Daniel Akpa-Akpro ci CIV MF Monza 30-354 \n", + "4 Luis Alberto es ESP MF Lazio 31-002 \n", + ".. ... ... ... ... ... \n", + "453 Joshua Zirkzee nl NED FW Bologna 22-131 \n", + "454 Zito ao ANG FW Cagliari 21-205 \n", + "455 Nadir Zortea it ITA DF Atalanta 24-103 \n", + "456 Milan Đurić ba BIH FW,MF Hellas Verona 33-131 \n", + "457 Mateusz Łęgowski pl POL MF Salernitana 20-244 \n", "\n", - " games games_starts minutes goals ... fouls fouled offsides \\\n", - "0 1.0 1.0 90.0 0.0 ... 2.0 1.0 0.0 \n", - "1 4.0 4.0 347.0 0.0 ... 7.0 5.0 0.0 \n", - "2 4.0 4.0 360.0 2.0 ... 3.0 5.0 0.0 \n", - "3 4.0 4.0 347.0 1.0 ... 3.0 8.0 1.0 \n", - "4 1.0 0.0 16.0 0.0 ... 1.0 0.0 0.0 \n", - ".. ... ... ... ... ... ... ... ... \n", - "424 4.0 4.0 356.0 1.0 ... 3.0 1.0 1.0 \n", - "425 4.0 3.0 297.0 1.0 ... 3.0 8.0 5.0 \n", - "426 3.0 0.0 96.0 1.0 ... 3.0 0.0 0.0 \n", - "427 4.0 1.0 152.0 0.0 ... 7.0 1.0 2.0 \n", - "428 4.0 2.0 161.0 0.0 ... 3.0 3.0 0.0 \n", + " birth_year games games_starts minutes goals ... fouls fouled \\\n", + "0 1988 3.0 3.0 270.0 0.0 ... 3.0 4.0 \n", + "1 2000 1.0 1.0 57.0 0.0 ... 0.0 0.0 \n", + "2 1997 6.0 6.0 527.0 0.0 ... 10.0 6.0 \n", + "3 1992 1.0 0.0 7.0 0.0 ... 0.0 0.0 \n", + "4 1992 6.0 6.0 540.0 2.0 ... 6.0 8.0 \n", + ".. ... ... ... ... ... ... ... ... \n", + "453 2001 6.0 6.0 520.0 1.0 ... 5.0 1.0 \n", + "454 2002 6.0 5.0 477.0 2.0 ... 5.0 12.0 \n", + "455 1999 3.0 0.0 96.0 1.0 ... 3.0 0.0 \n", + "456 1990 5.0 1.0 154.0 0.0 ... 7.0 1.0 \n", + "457 2003 5.0 2.0 167.0 0.0 ... 3.0 3.0 \n", "\n", - " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 4.0 3.0 \n", - "1 0.0 0.0 0.0 23.0 2.0 \n", - "2 0.0 0.0 0.0 24.0 2.0 \n", - "3 1.0 0.0 0.0 15.0 0.0 \n", - "4 0.0 0.0 0.0 1.0 0.0 \n", - ".. ... ... ... ... ... \n", - "424 0.0 0.0 0.0 11.0 9.0 \n", - "425 0.0 0.0 0.0 6.0 1.0 \n", - "426 0.0 0.0 0.0 4.0 0.0 \n", - "427 0.0 0.0 0.0 4.0 21.0 \n", - "428 0.0 0.0 0.0 14.0 4.0 \n", + " offsides pens_won pens_conceded own_goals ball_recoveries \\\n", + "0 0.0 0.0 0.0 0.0 15.0 \n", + "1 0.0 0.0 0.0 0.0 5.0 \n", + "2 0.0 0.0 0.0 0.0 29.0 \n", + "3 0.0 0.0 0.0 0.0 1.0 \n", + "4 0.0 0.0 0.0 0.0 36.0 \n", + ".. ... ... ... ... ... \n", + "453 2.0 0.0 0.0 0.0 15.0 \n", + "454 6.0 0.0 0.0 0.0 9.0 \n", + "455 0.0 0.0 0.0 0.0 4.0 \n", + "456 2.0 0.0 0.0 0.0 4.0 \n", + "457 0.0 0.0 0.0 0.0 16.0 \n", "\n", - " aerials_lost aerials_won_pct \n", - "0 0.0 100.0 \n", - "1 3.0 40.0 \n", - "2 4.0 33.3 \n", - "3 3.0 0.0 \n", - "4 1.0 0.0 \n", - ".. ... ... \n", - "424 2.0 81.8 \n", - "425 5.0 16.7 \n", - "426 1.0 0.0 \n", - "427 14.0 60.0 \n", - "428 5.0 44.4 \n", + " aerials_won aerials_lost aerials_won_pct \n", + "0 10.0 2.0 83.3 \n", + "1 0.0 1.0 0.0 \n", + "2 4.0 6.0 40.0 \n", + "3 0.0 0.0 0.0 \n", + "4 3.0 5.0 37.5 \n", + ".. ... ... ... \n", + "453 12.0 3.0 80.0 \n", + "454 2.0 7.0 22.2 \n", + "455 0.0 1.0 0.0 \n", + "456 23.0 15.0 60.5 \n", + "457 4.0 5.0 44.4 \n", "\n", - "[429 rows x 115 columns]" + "[458 rows x 115 columns]" ] }, "execution_count": 3, @@ -676,23 +676,23 @@ " al ALB\n", " GK\n", " Empoli\n", - " 34-195\n", + " 34-204\n", " 1989\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 9.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 10.0\n", " ...\n", - " 27.5\n", - " 9.0\n", - " 22.2\n", - " 27.0\n", - " 23.0\n", - " 1.0\n", - " 4.3\n", + " 32.1\n", + " 24.0\n", + " 58.3\n", + " 44.0\n", + " 50.0\n", " 2.0\n", - " 1.00\n", - " 15.7\n", + " 4.0\n", + " 3.0\n", + " 0.75\n", + " 12.7\n", " \n", " \n", " 1\n", @@ -700,7 +700,7 @@ " it ITA\n", " GK\n", " Empoli\n", - " 22-027\n", + " 22-036\n", " 2001\n", " 1.0\n", " 1.0\n", @@ -724,23 +724,23 @@ " it ITA\n", " GK\n", " Atalanta\n", - " 23-082\n", + " 23-091\n", " 2000\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", " 3.0\n", " ...\n", - " 36.8\n", - " 6.0\n", - " 83.3\n", - " 69.2\n", - " 13.0\n", - " 1.0\n", - " 7.7\n", + " 38.2\n", + " 15.0\n", + " 80.0\n", + " 60.7\n", + " 30.0\n", + " 3.0\n", + " 10.0\n", " 0.0\n", " 0.00\n", - " 14.5\n", + " 11.2\n", " \n", " \n", " 3\n", @@ -748,7 +748,7 @@ " it ITA\n", " GK\n", " Frosinone\n", - " 24-260\n", + " 24-269\n", " 1999\n", " 1.0\n", " 1.0\n", @@ -772,7 +772,7 @@ " dk DEN\n", " GK\n", " Fiorentina\n", - " 24-183\n", + " 24-192\n", " 1999\n", " 2.0\n", " 2.0\n", @@ -796,23 +796,23 @@ " it ITA\n", " GK\n", " Sassuolo\n", - " 36-237\n", + " 36-246\n", " 1987\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", - " 5.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 6.0\n", " ...\n", - " 37.1\n", - " 34.0\n", - " 26.5\n", - " 28.1\n", - " 46.0\n", - " 2.0\n", - " 4.3\n", + " 39.4\n", + " 42.0\n", + " 26.2\n", + " 28.3\n", + " 73.0\n", + " 4.0\n", + " 5.5\n", " 3.0\n", - " 1.00\n", - " 14.5\n", + " 0.75\n", + " 13.1\n", " \n", " \n", " 6\n", @@ -820,22 +820,22 @@ " it ITA\n", " GK\n", " Sassuolo\n", - " 29-085\n", + " 29-094\n", " 1994\n", - " 1.0\n", - " 1.0\n", - " 90.0\n", - " 4.0\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", + " 6.0\n", " ...\n", - " 37.1\n", - " 9.0\n", - " 33.3\n", - " 34.6\n", - " 9.0\n", + " 41.2\n", + " 19.0\n", + " 26.3\n", + " 29.4\n", + " 26.0\n", " 0.0\n", " 0.0\n", " 7.0\n", - " 7.00\n", + " 3.50\n", " 28.9\n", " \n", " \n", @@ -844,23 +844,23 @@ " it ITA\n", " GK\n", " Monza\n", - " 26-056\n", + " 26-065\n", " 1997\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", " 5.0\n", + " 5.0\n", + " 450.0\n", + " 6.0\n", " ...\n", - " 28.7\n", - " 22.0\n", - " 40.9\n", - " 40.3\n", - " 45.0\n", + " 30.4\n", + " 34.0\n", + " 52.9\n", + " 47.5\n", + " 73.0\n", " 2.0\n", - " 4.4\n", + " 2.7\n", " 2.0\n", - " 0.67\n", - " 11.7\n", + " 0.40\n", + " 10.5\n", " \n", " \n", " 8\n", @@ -868,23 +868,23 @@ " it ITA\n", " GK\n", " Lecce\n", - " 28-162\n", + " 28-171\n", " 1995\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 5.0\n", " ...\n", - " 31.0\n", - " 42.0\n", - " 52.4\n", - " 38.7\n", - " 54.0\n", - " 2.0\n", - " 3.7\n", - " 2.0\n", + " 30.9\n", + " 55.0\n", + " 47.3\n", + " 36.3\n", + " 80.0\n", + " 3.0\n", + " 3.8\n", + " 3.0\n", " 0.50\n", - " 10.3\n", + " 9.6\n", " \n", " \n", " 9\n", @@ -892,7 +892,7 @@ " fr FRA\n", " GK\n", " Milan\n", - " 28-080\n", + " 28-089\n", " 1995\n", " 4.0\n", " 4.0\n", @@ -916,23 +916,23 @@ " es ESP\n", " GK\n", " Genoa\n", - " 25-117\n", + " 25-126\n", " 1998\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 7.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 9.0\n", " ...\n", - " 39.7\n", - " 22.0\n", - " 95.5\n", - " 62.5\n", - " 75.0\n", - " 8.0\n", - " 10.7\n", + " 39.1\n", + " 37.0\n", + " 94.6\n", + " 62.1\n", + " 113.0\n", + " 12.0\n", + " 10.6\n", " 2.0\n", - " 0.50\n", - " 9.3\n", + " 0.33\n", + " 8.5\n", " \n", " \n", " 11\n", @@ -940,23 +940,23 @@ " it ITA\n", " GK\n", " Napoli\n", - " 26-183\n", + " 26-192\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 5.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 6.0\n", " ...\n", - " 24.7\n", - " 11.0\n", + " 24.1\n", + " 21.0\n", " 0.0\n", - " 20.4\n", - " 27.0\n", + " 20.5\n", + " 53.0\n", " 1.0\n", - " 3.7\n", - " 7.0\n", - " 1.75\n", - " 18.2\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", " \n", " \n", " 12\n", @@ -964,23 +964,23 @@ " rs SRB\n", " GK\n", " Torino\n", - " 26-213\n", + " 26-222\n", " 1997\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 7.0\n", " ...\n", - " 38.1\n", - " 36.0\n", - " 75.0\n", - " 61.3\n", - " 33.0\n", - " 3.0\n", - " 9.1\n", - " 5.0\n", - " 1.25\n", - " 15.8\n", + " 35.6\n", + " 50.0\n", + " 80.0\n", + " 62.9\n", + " 47.0\n", + " 4.0\n", + " 8.5\n", + " 9.0\n", + " 1.50\n", + " 17.5\n", " \n", " \n", " 13\n", @@ -988,23 +988,23 @@ " it ITA\n", " GK\n", " Hellas Verona\n", - " 27-213\n", + " 27-222\n", " 1996\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 6.0\n", " ...\n", - " 42.9\n", - " 35.0\n", - " 88.6\n", - " 62.7\n", - " 54.0\n", + " 45.2\n", + " 50.0\n", + " 84.0\n", + " 61.5\n", + " 72.0\n", " 1.0\n", - " 1.9\n", - " 8.0\n", + " 1.4\n", + " 12.0\n", " 2.00\n", - " 19.4\n", + " 20.0\n", " \n", " \n", " 14\n", @@ -1012,23 +1012,23 @@ " ar ARG\n", " GK\n", " Atalanta\n", - " 29-138\n", + " 29-147\n", " 1994\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", " 2.0\n", " ...\n", - " 29.3\n", - " 18.0\n", - " 55.6\n", - " 46.1\n", + " 29.0\n", " 28.0\n", - " 2.0\n", - " 7.1\n", - " 8.0\n", - " 2.67\n", - " 22.0\n", + " 64.3\n", + " 48.9\n", + " 43.0\n", + " 4.0\n", + " 9.3\n", + " 12.0\n", + " 3.00\n", + " 19.9\n", " \n", " \n", " 15\n", @@ -1036,23 +1036,23 @@ " mx MEX\n", " GK\n", " Salernitana\n", - " 38-070\n", + " 38-079\n", " 1985\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 8.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 10.0\n", " ...\n", - " 35.9\n", - " 35.0\n", - " 54.3\n", - " 43.6\n", - " 63.0\n", + " 35.6\n", + " 47.0\n", + " 46.8\n", + " 39.9\n", + " 88.0\n", " 4.0\n", - " 6.3\n", - " 1.0\n", - " 0.25\n", - " 7.8\n", + " 4.5\n", + " 3.0\n", + " 0.50\n", + " 13.5\n", " \n", " \n", " 16\n", @@ -1060,23 +1060,23 @@ " pt POR\n", " GK\n", " Roma\n", - " 35-218\n", + " 35-227\n", " 1988\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", " 6.0\n", + " 6.0\n", + " 540.0\n", + " 11.0\n", " ...\n", - " 29.3\n", - " 17.0\n", - " 11.8\n", - " 22.1\n", - " 34.0\n", - " 2.0\n", - " 5.9\n", + " 27.5\n", + " 31.0\n", + " 19.4\n", + " 24.2\n", + " 62.0\n", " 2.0\n", + " 3.2\n", + " 3.0\n", " 0.50\n", - " 12.2\n", + " 13.7\n", " \n", " \n", " 17\n", @@ -1084,7 +1084,7 @@ " it ITA\n", " GK\n", " Juventus\n", - " 30-315\n", + " 30-324\n", " 1992\n", " 2.0\n", " 2.0\n", @@ -1108,7 +1108,7 @@ " it ITA\n", " GK\n", " Empoli\n", - " 26-031\n", + " 26-040\n", " 1997\n", " 1.0\n", " 1.0\n", @@ -1132,23 +1132,23 @@ " it ITA\n", " GK\n", " Lazio\n", - " 29-188\n", + " 29-197\n", " 1994\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 7.0\n", - " ...\n", - " 26.4\n", - " 15.0\n", - " 20.0\n", - " 27.9\n", - " 48.0\n", - " 2.0\n", - " 4.2\n", " 6.0\n", - " 1.50\n", - " 15.7\n", + " 6.0\n", + " 540.0\n", + " 8.0\n", + " ...\n", + " 28.8\n", + " 29.0\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", " \n", " \n", " 20\n", @@ -1156,23 +1156,23 @@ " rs SRB\n", " GK\n", " Cagliari\n", - " 27-118\n", + " 27-127\n", " 1996\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 9.0\n", " ...\n", - " 37.8\n", - " 40.0\n", - " 65.0\n", - " 50.0\n", - " 62.0\n", + " 38.5\n", + " 57.0\n", + " 54.4\n", + " 45.1\n", + " 87.0\n", + " 5.0\n", + " 5.7\n", " 4.0\n", - " 6.5\n", - " 3.0\n", - " 0.75\n", - " 12.5\n", + " 0.67\n", + " 11.9\n", " \n", " \n", " 21\n", @@ -1180,23 +1180,23 @@ " it ITA\n", " GK\n", " Udinese\n", - " 32-203\n", + " 32-212\n", " 1991\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 4.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 10.0\n", " ...\n", - " 29.7\n", - " 32.0\n", - " 31.3\n", - " 35.4\n", - " 49.0\n", - " 0.0\n", - " 0.0\n", + " 30.2\n", + " 45.0\n", + " 26.7\n", + " 32.8\n", + " 69.0\n", + " 1.0\n", + " 1.4\n", " 3.0\n", - " 0.75\n", - " 14.0\n", + " 0.50\n", + " 13.6\n", " \n", " \n", " 22\n", @@ -1204,23 +1204,23 @@ " pl POL\n", " GK\n", " Bologna\n", - " 32-139\n", + " 32-148\n", " 1991\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", " 4.0\n", " ...\n", - " 32.1\n", - " 22.0\n", - " 31.8\n", - " 34.2\n", - " 57.0\n", + " 31.1\n", + " 34.0\n", + " 29.4\n", + " 33.6\n", + " 89.0\n", + " 3.0\n", + " 3.4\n", " 2.0\n", - " 3.5\n", - " 2.0\n", - " 0.50\n", - " 11.5\n", + " 0.33\n", + " 10.3\n", " \n", " \n", " 23\n", @@ -1228,23 +1228,23 @@ " ch SUI\n", " GK\n", " Inter\n", - " 34-278\n", + " 34-287\n", " 1988\n", - " 4.0\n", - " 4.0\n", - " 360.0\n", - " 1.0\n", + " 6.0\n", + " 6.0\n", + " 540.0\n", + " 3.0\n", " ...\n", - " 30.8\n", - " 29.0\n", - " 20.7\n", - " 28.3\n", - " 41.0\n", + " 29.7\n", + " 39.0\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", " 2.0\n", - " 4.9\n", - " 0.0\n", - " 0.00\n", - " 6.5\n", + " 0.33\n", + " 9.6\n", " \n", " \n", " 24\n", @@ -1252,7 +1252,7 @@ " it ITA\n", " GK\n", " Monza\n", - " 21-171\n", + " 21-180\n", " 2002\n", " 1.0\n", " 1.0\n", @@ -1272,263 +1272,293 @@ " \n", " \n", " 25\n", + " Marco Sportiello\n", + " it ITA\n", + " GK\n", + " Milan\n", + " 31-143\n", + " 1992\n", + " 2.0\n", + " 2.0\n", + " 180.0\n", + " 1.0\n", + " ...\n", + " 28.0\n", + " 2.0\n", + " 0.0\n", + " 28.5\n", + " 28.0\n", + " 2.0\n", + " 7.1\n", + " 2.0\n", + " 1.00\n", + " 13.2\n", + " \n", + " \n", + " 26\n", " Wojciech Szczęsny\n", " pl POL\n", " GK\n", " Juventus\n", - " 33-156\n", + " 33-165\n", " 1990\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 1.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 5.0\n", " ...\n", - " 33.1\n", - " 6.0\n", - " 66.7\n", - " 52.0\n", - " 33.0\n", + " 33.2\n", + " 16.0\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", " 1.0\n", - " 3.0\n", - " 0.0\n", - " 0.00\n", - " 9.6\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", " \n", " \n", - " 26\n", + " 27\n", " Pietro Terracciano\n", " it ITA\n", " GK\n", " Fiorentina\n", - " 33-197\n", + " 33-206\n", " 1990\n", - " 2.0\n", - " 2.0\n", - " 180.0\n", - " 3.0\n", + " 4.0\n", + " 4.0\n", + " 360.0\n", + " 4.0\n", " ...\n", - " 33.1\n", - " 9.0\n", - " 11.1\n", - " 25.0\n", - " 16.0\n", + " 34.7\n", + " 22.0\n", + " 45.5\n", + " 38.3\n", + " 44.0\n", + " 3.0\n", + " 6.8\n", " 1.0\n", - " 6.3\n", - " 1.0\n", - " 0.50\n", - " 13.7\n", + " 0.25\n", + " 10.2\n", " \n", " \n", - " 27\n", + " 28\n", " Stefano Turati\n", " it ITA\n", " GK\n", " Frosinone\n", - " 22-016\n", + " 22-025\n", " 2001\n", - " 3.0\n", - " 3.0\n", - " 270.0\n", " 5.0\n", + " 5.0\n", + " 450.0\n", + " 7.0\n", " ...\n", - " 26.0\n", - " 13.0\n", - " 53.8\n", - " 41.7\n", - " 33.0\n", + " 26.9\n", + " 16.0\n", + " 56.3\n", + " 43.5\n", + " 67.0\n", " 2.0\n", - " 6.1\n", " 3.0\n", - " 1.00\n", - " 16.3\n", + " 3.0\n", + " 0.60\n", + " 13.4\n", " \n", " \n", "\n", - "

28 rows × 47 columns

\n", + "

29 rows × 47 columns

\n", "" ], "text/plain": [ " player nationality position team age \\\n", - "0 Etrit Berisha al ALB GK Empoli 34-195 \n", - "1 Elia Caprile it ITA GK Empoli 22-027 \n", - "2 Marco Carnesecchi it ITA GK Atalanta 23-082 \n", - "3 Michele Cerofolini it ITA GK Frosinone 24-260 \n", - "4 Oliver Christensen dk DEN GK Fiorentina 24-183 \n", - "5 Andrea Consigli it ITA GK Sassuolo 36-237 \n", - "6 Alessio Cragno it ITA GK Sassuolo 29-085 \n", - "7 Michele Di Gregorio it ITA GK Monza 26-056 \n", - "8 Wladimiro Falcone it ITA GK Lecce 28-162 \n", - "9 Mike Maignan fr FRA GK Milan 28-080 \n", - "10 Josep Martinez es ESP GK Genoa 25-117 \n", - "11 Alex Meret it ITA GK Napoli 26-183 \n", - "12 Vanja Milinković-Savić rs SRB GK Torino 26-213 \n", - "13 Lorenzo Montipò it ITA GK Hellas Verona 27-213 \n", - "14 Juan Musso ar ARG GK Atalanta 29-138 \n", - "15 Guillermo Ochoa mx MEX GK Salernitana 38-070 \n", - "16 Rui Patrício pt POR GK Roma 35-218 \n", - "17 Mattia Perin it ITA GK Juventus 30-315 \n", - "18 Samuele Perisan it ITA GK Empoli 26-031 \n", - "19 Ivan Provedel it ITA GK Lazio 29-188 \n", - "20 Boris Radunović rs SRB GK Cagliari 27-118 \n", - "21 Marco Silvestri it ITA GK Udinese 32-203 \n", - "22 Łukasz Skorupski pl POL GK Bologna 32-139 \n", - "23 Yann Sommer ch SUI GK Inter 34-278 \n", - "24 Alessandro Sorrentino it ITA GK Monza 21-171 \n", - "25 Wojciech Szczęsny pl POL GK Juventus 33-156 \n", - "26 Pietro Terracciano it ITA GK Fiorentina 33-197 \n", - "27 Stefano Turati it ITA GK Frosinone 22-016 \n", + "0 Etrit Berisha al ALB GK Empoli 34-204 \n", + "1 Elia Caprile it ITA GK Empoli 22-036 \n", + "2 Marco Carnesecchi it ITA GK Atalanta 23-091 \n", + "3 Michele Cerofolini it ITA GK Frosinone 24-269 \n", + "4 Oliver Christensen dk DEN GK Fiorentina 24-192 \n", + "5 Andrea Consigli it ITA GK Sassuolo 36-246 \n", + "6 Alessio Cragno it ITA GK Sassuolo 29-094 \n", + "7 Michele Di Gregorio it ITA GK Monza 26-065 \n", + "8 Wladimiro Falcone it ITA GK Lecce 28-171 \n", + "9 Mike Maignan fr FRA GK Milan 28-089 \n", + "10 Josep Martinez es ESP GK Genoa 25-126 \n", + "11 Alex Meret it ITA GK Napoli 26-192 \n", + "12 Vanja Milinković-Savić rs SRB GK Torino 26-222 \n", + "13 Lorenzo Montipò it ITA GK Hellas Verona 27-222 \n", + "14 Juan Musso ar ARG GK Atalanta 29-147 \n", + "15 Guillermo Ochoa mx MEX GK Salernitana 38-079 \n", + "16 Rui Patrício pt POR GK Roma 35-227 \n", + "17 Mattia Perin it ITA GK Juventus 30-324 \n", + "18 Samuele Perisan it ITA GK Empoli 26-040 \n", + "19 Ivan Provedel it ITA GK Lazio 29-197 \n", + "20 Boris Radunović rs SRB GK Cagliari 27-127 \n", + "21 Marco Silvestri it ITA GK Udinese 32-212 \n", + "22 Łukasz Skorupski pl POL GK Bologna 32-148 \n", + "23 Yann Sommer ch SUI GK Inter 34-287 \n", + "24 Alessandro Sorrentino it ITA GK Monza 21-180 \n", + "25 Marco Sportiello it ITA GK Milan 31-143 \n", + "26 Wojciech Szczęsny pl POL GK Juventus 33-165 \n", + "27 Pietro Terracciano it ITA GK Fiorentina 33-206 \n", + "28 Stefano Turati it ITA GK Frosinone 22-025 \n", "\n", " birth_year gk_games gk_games_starts gk_minutes gk_goals_against ... \\\n", - "0 1989 2.0 2.0 180.0 9.0 ... \n", + "0 1989 4.0 4.0 360.0 10.0 ... \n", "1 2001 1.0 1.0 90.0 1.0 ... \n", - "2 2000 1.0 1.0 90.0 3.0 ... \n", + "2 2000 2.0 2.0 180.0 3.0 ... \n", "3 1999 1.0 1.0 90.0 1.0 ... \n", "4 1999 2.0 2.0 180.0 6.0 ... \n", - "5 1987 3.0 3.0 270.0 5.0 ... \n", - "6 1994 1.0 1.0 90.0 4.0 ... \n", - "7 1997 3.0 3.0 270.0 5.0 ... \n", - "8 1995 4.0 4.0 360.0 4.0 ... \n", + "5 1987 4.0 4.0 360.0 6.0 ... \n", + "6 1994 2.0 2.0 180.0 6.0 ... \n", + "7 1997 5.0 5.0 450.0 6.0 ... \n", + "8 1995 6.0 6.0 540.0 5.0 ... \n", "9 1995 4.0 4.0 360.0 7.0 ... \n", - "10 1998 4.0 4.0 360.0 7.0 ... \n", - "11 1997 4.0 4.0 360.0 5.0 ... \n", - "12 1997 4.0 4.0 360.0 4.0 ... \n", - "13 1996 4.0 4.0 360.0 4.0 ... \n", - "14 1994 3.0 3.0 270.0 2.0 ... \n", - "15 1985 4.0 4.0 360.0 8.0 ... \n", - "16 1988 4.0 4.0 360.0 6.0 ... \n", + "10 1998 6.0 6.0 540.0 9.0 ... \n", + "11 1997 6.0 6.0 540.0 6.0 ... \n", + "12 1997 6.0 6.0 540.0 7.0 ... \n", + "13 1996 6.0 6.0 540.0 6.0 ... \n", + "14 1994 4.0 4.0 360.0 2.0 ... \n", + "15 1985 6.0 6.0 540.0 10.0 ... \n", + "16 1988 6.0 6.0 540.0 11.0 ... \n", "17 1992 2.0 2.0 180.0 1.0 ... \n", "18 1997 1.0 1.0 90.0 2.0 ... \n", - "19 1994 4.0 4.0 360.0 7.0 ... \n", - "20 1996 4.0 4.0 360.0 4.0 ... \n", - "21 1991 4.0 4.0 360.0 4.0 ... \n", - "22 1991 4.0 4.0 360.0 4.0 ... \n", - "23 1988 4.0 4.0 360.0 1.0 ... \n", + "19 1994 6.0 6.0 540.0 8.0 ... \n", + "20 1996 6.0 6.0 540.0 9.0 ... \n", + "21 1991 6.0 6.0 540.0 10.0 ... \n", + "22 1991 6.0 6.0 540.0 4.0 ... \n", + "23 1988 6.0 6.0 540.0 3.0 ... \n", "24 2002 1.0 1.0 90.0 1.0 ... \n", - "25 1990 2.0 2.0 180.0 1.0 ... \n", - "26 1990 2.0 2.0 180.0 3.0 ... \n", - "27 2001 3.0 3.0 270.0 5.0 ... \n", + "25 1992 2.0 2.0 180.0 1.0 ... \n", + "26 1990 4.0 4.0 360.0 5.0 ... \n", + "27 1990 4.0 4.0 360.0 4.0 ... \n", + "28 2001 5.0 5.0 450.0 7.0 ... \n", "\n", " gk_passes_length_avg gk_goal_kicks gk_pct_goal_kicks_launched \\\n", - "0 27.5 9.0 22.2 \n", + "0 32.1 24.0 58.3 \n", "1 42.6 4.0 50.0 \n", - "2 36.8 6.0 83.3 \n", + "2 38.2 15.0 80.0 \n", "3 38.3 5.0 60.0 \n", "4 33.2 8.0 62.5 \n", - "5 37.1 34.0 26.5 \n", - "6 37.1 9.0 33.3 \n", - "7 28.7 22.0 40.9 \n", - "8 31.0 42.0 52.4 \n", + "5 39.4 42.0 26.2 \n", + "6 41.2 19.0 26.3 \n", + "7 30.4 34.0 52.9 \n", + "8 30.9 55.0 47.3 \n", "9 29.2 23.0 60.9 \n", - "10 39.7 22.0 95.5 \n", - "11 24.7 11.0 0.0 \n", - "12 38.1 36.0 75.0 \n", - "13 42.9 35.0 88.6 \n", - "14 29.3 18.0 55.6 \n", - "15 35.9 35.0 54.3 \n", - "16 29.3 17.0 11.8 \n", + "10 39.1 37.0 94.6 \n", + "11 24.1 21.0 0.0 \n", + "12 35.6 50.0 80.0 \n", + "13 45.2 50.0 84.0 \n", + "14 29.0 28.0 64.3 \n", + "15 35.6 47.0 46.8 \n", + "16 27.5 31.0 19.4 \n", "17 29.1 11.0 9.1 \n", "18 26.3 12.0 16.7 \n", - "19 26.4 15.0 20.0 \n", - "20 37.8 40.0 65.0 \n", - "21 29.7 32.0 31.3 \n", - "22 32.1 22.0 31.8 \n", - "23 30.8 29.0 20.7 \n", + "19 28.8 29.0 27.6 \n", + "20 38.5 57.0 54.4 \n", + "21 30.2 45.0 26.7 \n", + "22 31.1 34.0 29.4 \n", + "23 29.7 39.0 20.5 \n", "24 21.0 2.0 0.0 \n", - "25 33.1 6.0 66.7 \n", - "26 33.1 9.0 11.1 \n", - "27 26.0 13.0 53.8 \n", + "25 28.0 2.0 0.0 \n", + "26 33.2 16.0 50.0 \n", + "27 34.7 22.0 45.5 \n", + "28 26.9 16.0 56.3 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 27.0 23.0 1.0 \n", + "0 44.0 50.0 2.0 \n", "1 50.3 10.0 2.0 \n", - "2 69.2 13.0 1.0 \n", + "2 60.7 30.0 3.0 \n", "3 45.8 18.0 0.0 \n", "4 49.4 15.0 0.0 \n", - "5 28.1 46.0 2.0 \n", - "6 34.6 9.0 0.0 \n", - "7 40.3 45.0 2.0 \n", - "8 38.7 54.0 2.0 \n", + "5 28.3 73.0 4.0 \n", + "6 29.4 26.0 0.0 \n", + "7 47.5 73.0 2.0 \n", + "8 36.3 80.0 3.0 \n", "9 47.0 52.0 12.0 \n", - "10 62.5 75.0 8.0 \n", - "11 20.4 27.0 1.0 \n", - "12 61.3 33.0 3.0 \n", - "13 62.7 54.0 1.0 \n", - "14 46.1 28.0 2.0 \n", - "15 43.6 63.0 4.0 \n", - "16 22.1 34.0 2.0 \n", + "10 62.1 113.0 12.0 \n", + "11 20.5 53.0 1.0 \n", + "12 62.9 47.0 4.0 \n", + "13 61.5 72.0 1.0 \n", + "14 48.9 43.0 4.0 \n", + "15 39.9 88.0 4.0 \n", + "16 24.2 62.0 2.0 \n", "17 18.9 26.0 2.0 \n", "18 29.6 18.0 0.0 \n", - "19 27.9 48.0 2.0 \n", - "20 50.0 62.0 4.0 \n", - "21 35.4 49.0 0.0 \n", - "22 34.2 57.0 2.0 \n", - "23 28.3 41.0 2.0 \n", + "19 32.3 63.0 3.0 \n", + "20 45.1 87.0 5.0 \n", + "21 32.8 69.0 1.0 \n", + "22 33.6 89.0 3.0 \n", + "23 27.3 59.0 5.0 \n", "24 23.0 8.0 1.0 \n", - "25 52.0 33.0 1.0 \n", - "26 25.0 16.0 1.0 \n", - "27 41.7 33.0 2.0 \n", + "25 28.5 28.0 2.0 \n", + "26 45.8 59.0 1.0 \n", + "27 38.3 44.0 3.0 \n", + "28 43.5 67.0 2.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.3 2.0 \n", + "0 4.0 3.0 \n", "1 20.0 2.0 \n", - "2 7.7 0.0 \n", + "2 10.0 0.0 \n", "3 0.0 0.0 \n", "4 0.0 3.0 \n", - "5 4.3 3.0 \n", + "5 5.5 3.0 \n", "6 0.0 7.0 \n", - "7 4.4 2.0 \n", - "8 3.7 2.0 \n", + "7 2.7 2.0 \n", + "8 3.8 3.0 \n", "9 23.1 3.0 \n", - "10 10.7 2.0 \n", - "11 3.7 7.0 \n", - "12 9.1 5.0 \n", - "13 1.9 8.0 \n", - "14 7.1 8.0 \n", - "15 6.3 1.0 \n", - "16 5.9 2.0 \n", + "10 10.6 2.0 \n", + "11 1.9 8.0 \n", + "12 8.5 9.0 \n", + "13 1.4 12.0 \n", + "14 9.3 12.0 \n", + "15 4.5 3.0 \n", + "16 3.2 3.0 \n", "17 7.7 2.0 \n", "18 0.0 1.0 \n", - "19 4.2 6.0 \n", - "20 6.5 3.0 \n", - "21 0.0 3.0 \n", - "22 3.5 2.0 \n", - "23 4.9 0.0 \n", + "19 4.8 7.0 \n", + "20 5.7 4.0 \n", + "21 1.4 3.0 \n", + "22 3.4 2.0 \n", + "23 8.5 2.0 \n", "24 12.5 0.0 \n", - "25 3.0 0.0 \n", - 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" 53.0\n", - " 45.0\n", - " 7.0\n", + " 70.0\n", + " 57.0\n", + " 9.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 196.0\n", - " 76.0\n", - " 54.0\n", - " 58.5\n", + " 286.0\n", + " 104.0\n", + " 83.0\n", + " 55.6\n", " \n", " \n", " 16\n", " Salernitana\n", - " 21.0\n", - " 51.5\n", + " 22.0\n", + " 52.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 48.0\n", - " 62.0\n", - " 5.0\n", + " 73.0\n", + " 90.0\n", + " 10.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 183.0\n", - " 54.0\n", - " 86.0\n", - " 38.6\n", + " 298.0\n", + " 82.0\n", + " 120.0\n", + " 40.6\n", " \n", " \n", " 17\n", " Sassuolo\n", - " 24.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 4.0\n", + " 25.0\n", + " 42.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 36.0\n", - " 41.0\n", - " 3.0\n", + " 57.0\n", + " 58.0\n", + " 7.0\n", " 1.0\n", " 3.0\n", - " 0.0\n", - " 171.0\n", - " 37.0\n", - " 50.0\n", - " 42.5\n", + " 1.0\n", + " 265.0\n", + " 55.0\n", + " 85.0\n", + " 39.3\n", " \n", " \n", " 18\n", " Torino\n", - " 22.0\n", - " 51.3\n", + " 23.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 53.0\n", - " 43.0\n", - " 10.0\n", + " 71.0\n", + " 60.0\n", + " 11.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 193.0\n", - " 59.0\n", - " 63.0\n", - " 48.4\n", + " 301.0\n", + " 82.0\n", + " 93.0\n", + " 46.9\n", " \n", " \n", " 19\n", " Udinese\n", - " 22.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 24.0\n", + " 46.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 56.0\n", - " 42.0\n", - " 5.0\n", + " 79.0\n", + " 63.0\n", + " 6.0\n", " 0.0\n", - " 1.0\n", + " 2.0\n", " 0.0\n", - " 203.0\n", - " 64.0\n", - " 52.0\n", - " 55.2\n", + " 309.0\n", + " 101.0\n", + " 68.0\n", + " 59.8\n", " \n", " \n", "\n", @@ -2082,92 +2112,92 @@ ], "text/plain": [ " team players_used possession games games_starts minutes \\\n", - "0 Atalanta 23.0 49.5 4.0 44.0 360.0 \n", - "1 Bologna 22.0 56.5 4.0 44.0 360.0 \n", - "2 Cagliari 21.0 37.8 4.0 44.0 360.0 \n", - "3 Empoli 27.0 47.8 4.0 44.0 360.0 \n", - "4 Fiorentina 22.0 61.0 4.0 44.0 360.0 \n", - "5 Frosinone 23.0 48.3 4.0 44.0 360.0 \n", - "6 Genoa 19.0 33.3 4.0 44.0 360.0 \n", - "7 Hellas Verona 21.0 43.5 4.0 44.0 360.0 \n", - "8 Inter 19.0 48.8 4.0 44.0 360.0 \n", - "9 Juventus 21.0 48.8 4.0 44.0 360.0 \n", - "10 Lazio 20.0 56.0 4.0 44.0 360.0 \n", - "11 Lecce 19.0 43.5 4.0 44.0 360.0 \n", - "12 Milan 19.0 55.3 4.0 44.0 360.0 \n", - "13 Monza 22.0 56.8 4.0 44.0 360.0 \n", - "14 Napoli 19.0 61.8 4.0 44.0 360.0 \n", - "15 Roma 23.0 57.0 4.0 44.0 360.0 \n", - "16 Salernitana 21.0 51.5 4.0 44.0 360.0 \n", - "17 Sassuolo 24.0 43.5 4.0 44.0 360.0 \n", - "18 Torino 22.0 51.3 4.0 44.0 360.0 \n", - "19 Udinese 22.0 48.5 4.0 44.0 360.0 \n", + "0 Atalanta 24.0 50.5 6.0 66.0 540.0 \n", + "1 Bologna 23.0 54.7 6.0 66.0 540.0 \n", + "2 Cagliari 22.0 38.2 6.0 66.0 540.0 \n", + "3 Empoli 28.0 45.3 6.0 66.0 540.0 \n", + "4 Fiorentina 24.0 57.2 6.0 66.0 540.0 \n", + "5 Frosinone 24.0 49.2 6.0 66.0 540.0 \n", + "6 Genoa 22.0 34.3 6.0 66.0 540.0 \n", + "7 Hellas Verona 22.0 45.2 6.0 66.0 540.0 \n", + "8 Inter 22.0 53.2 6.0 66.0 540.0 \n", + "9 Juventus 22.0 50.3 6.0 66.0 540.0 \n", + "10 Lazio 20.0 54.0 6.0 66.0 540.0 \n", + "11 Lecce 22.0 46.7 6.0 66.0 540.0 \n", + "12 Milan 23.0 56.8 6.0 66.0 540.0 \n", + "13 Monza 23.0 54.2 6.0 66.0 540.0 \n", + "14 Napoli 20.0 60.7 6.0 66.0 540.0 \n", + "15 Roma 23.0 59.7 6.0 66.0 540.0 \n", + "16 Salernitana 22.0 52.3 6.0 66.0 540.0 \n", + "17 Sassuolo 25.0 42.3 6.0 66.0 540.0 \n", + "18 Torino 23.0 49.2 6.0 66.0 540.0 \n", + "19 Udinese 24.0 46.2 6.0 66.0 540.0 \n", "\n", " goals assists pens_made pens_att ... fouls fouled offsides \\\n", - "0 8.0 8.0 0.0 0.0 ... 48.0 34.0 9.0 \n", - "1 3.0 2.0 0.0 1.0 ... 42.0 41.0 4.0 \n", - "2 1.0 1.0 0.0 0.0 ... 46.0 35.0 7.0 \n", - "3 0.0 0.0 0.0 0.0 ... 43.0 59.0 7.0 \n", - "4 9.0 7.0 0.0 0.0 ... 49.0 52.0 4.0 \n", - "5 7.0 4.0 2.0 2.0 ... 43.0 49.0 11.0 \n", - "6 4.0 3.0 0.0 0.0 ... 51.0 35.0 5.0 \n", - "7 4.0 2.0 0.0 0.0 ... 66.0 46.0 12.0 \n", - "8 13.0 11.0 2.0 2.0 ... 47.0 45.0 5.0 \n", - "9 9.0 7.0 1.0 2.0 ... 51.0 48.0 10.0 \n", - "10 4.0 4.0 0.0 0.0 ... 47.0 46.0 4.0 \n", - "11 7.0 5.0 2.0 2.0 ... 55.0 62.0 3.0 \n", - "12 9.0 6.0 3.0 3.0 ... 45.0 53.0 6.0 \n", - "13 3.0 3.0 0.0 0.0 ... 53.0 35.0 5.0 \n", - "14 8.0 5.0 1.0 2.0 ... 42.0 39.0 14.0 \n", - "15 10.0 8.0 1.0 1.0 ... 53.0 45.0 7.0 \n", - "16 3.0 3.0 0.0 0.0 ... 48.0 62.0 5.0 \n", - "17 5.0 4.0 1.0 1.0 ... 36.0 41.0 3.0 \n", - "18 5.0 3.0 0.0 0.0 ... 53.0 43.0 10.0 \n", - "19 1.0 1.0 0.0 0.0 ... 56.0 42.0 5.0 \n", + "0 11.0 11.0 0.0 0.0 ... 79.0 55.0 17.0 \n", + "1 3.0 2.0 0.0 1.0 ... 73.0 61.0 8.0 \n", + "2 2.0 2.0 0.0 0.0 ... 70.0 47.0 8.0 \n", + "3 1.0 1.0 0.0 0.0 ... 76.0 83.0 12.0 \n", + "4 12.0 9.0 0.0 0.0 ... 71.0 70.0 10.0 \n", + "5 9.0 5.0 2.0 2.0 ... 61.0 69.0 16.0 \n", + "6 8.0 7.0 0.0 0.0 ... 68.0 57.0 5.0 \n", + "7 4.0 2.0 0.0 0.0 ... 87.0 78.0 14.0 \n", + "8 15.0 12.0 2.0 2.0 ... 68.0 67.0 9.0 \n", + "9 11.0 9.0 1.0 2.0 ... 73.0 75.0 12.0 \n", + "10 7.0 6.0 1.0 1.0 ... 72.0 64.0 7.0 \n", + "11 8.0 6.0 2.0 2.0 ... 82.0 86.0 5.0 \n", + "12 13.0 8.0 3.0 3.0 ... 63.0 77.0 8.0 \n", + "13 4.0 3.0 0.0 0.0 ... 69.0 61.0 9.0 \n", + "14 12.0 7.0 2.0 4.0 ... 65.0 64.0 16.0 \n", + "15 12.0 9.0 1.0 1.0 ... 70.0 57.0 9.0 \n", + "16 4.0 3.0 0.0 0.0 ... 73.0 90.0 10.0 \n", + "17 10.0 7.0 1.0 1.0 ... 57.0 58.0 7.0 \n", + "18 6.0 4.0 0.0 0.0 ... 71.0 60.0 11.0 \n", + "19 2.0 2.0 0.0 0.0 ... 79.0 63.0 6.0 \n", "\n", " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 232.0 60.0 \n", - "1 0.0 0.0 0.0 205.0 46.0 \n", - "2 0.0 1.0 0.0 241.0 51.0 \n", - "3 0.0 2.0 1.0 176.0 39.0 \n", - "4 0.0 1.0 0.0 196.0 53.0 \n", - "5 2.0 0.0 0.0 202.0 52.0 \n", - "6 0.0 0.0 0.0 177.0 60.0 \n", - "7 0.0 1.0 0.0 207.0 82.0 \n", - "8 2.0 0.0 0.0 187.0 44.0 \n", - "9 1.0 0.0 0.0 181.0 38.0 \n", - "10 0.0 0.0 0.0 188.0 30.0 \n", - "11 1.0 0.0 0.0 191.0 54.0 \n", - "12 2.0 1.0 0.0 169.0 33.0 \n", - "13 0.0 1.0 0.0 175.0 37.0 \n", - "14 1.0 1.0 0.0 208.0 47.0 \n", - "15 0.0 1.0 0.0 196.0 76.0 \n", - "16 0.0 1.0 0.0 183.0 54.0 \n", - "17 1.0 3.0 0.0 171.0 37.0 \n", - "18 0.0 2.0 0.0 193.0 59.0 \n", - "19 0.0 1.0 0.0 203.0 64.0 \n", + "0 0.0 0.0 0.0 362.0 109.0 \n", + "1 0.0 1.0 0.0 288.0 73.0 \n", + "2 0.0 1.0 0.0 349.0 71.0 \n", + "3 0.0 2.0 1.0 281.0 60.0 \n", + "4 0.0 1.0 0.0 315.0 75.0 \n", + "5 2.0 0.0 0.0 294.0 80.0 \n", + "6 0.0 0.0 0.0 265.0 83.0 \n", + "7 0.0 1.0 0.0 339.0 117.0 \n", + "8 2.0 0.0 0.0 278.0 77.0 \n", + "9 1.0 0.0 1.0 280.0 67.0 \n", + "10 1.0 0.0 0.0 284.0 53.0 \n", + "11 1.0 0.0 0.0 286.0 73.0 \n", + "12 2.0 1.0 0.0 287.0 61.0 \n", + "13 0.0 2.0 0.0 257.0 56.0 \n", + "14 2.0 1.0 0.0 301.0 56.0 \n", + "15 0.0 1.0 0.0 286.0 104.0 \n", + "16 0.0 1.0 0.0 298.0 82.0 \n", + "17 1.0 3.0 1.0 265.0 55.0 \n", + "18 0.0 2.0 0.0 301.0 82.0 \n", + "19 0.0 2.0 0.0 309.0 101.0 \n", "\n", " aerials_lost aerials_won_pct \n", - "0 65.0 48.0 \n", - "1 34.0 57.5 \n", - "2 60.0 45.9 \n", - "3 54.0 41.9 \n", - "4 56.0 48.6 \n", - "5 53.0 49.5 \n", - "6 46.0 56.6 \n", - "7 71.0 53.6 \n", - "8 30.0 59.5 \n", - "9 26.0 59.4 \n", - "10 51.0 37.0 \n", - "11 43.0 55.7 \n", - "12 42.0 44.0 \n", - "13 45.0 45.1 \n", - "14 35.0 57.3 \n", - "15 54.0 58.5 \n", - "16 86.0 38.6 \n", - "17 50.0 42.5 \n", - "18 63.0 48.4 \n", - "19 52.0 55.2 \n", + "0 97.0 52.9 \n", + "1 47.0 60.8 \n", + "2 92.0 43.6 \n", + "3 82.0 42.3 \n", + "4 96.0 43.9 \n", + "5 79.0 50.3 \n", + "6 66.0 55.7 \n", + "7 116.0 50.2 \n", + "8 46.0 62.6 \n", + "9 41.0 62.0 \n", + "10 66.0 44.5 \n", + "11 67.0 52.1 \n", + "12 65.0 48.4 \n", + "13 74.0 43.1 \n", + "14 52.0 51.9 \n", + "15 83.0 55.6 \n", + "16 120.0 40.6 \n", + "17 85.0 39.3 \n", + "18 93.0 46.9 \n", + "19 68.0 59.8 \n", "\n", "[20 rows x 152 columns]" ] @@ -2239,482 +2269,482 @@ " \n", " 0\n", " vs Atalanta\n", - " 23.0\n", - " 50.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 49.5\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 5.0\n", " 4.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", " 1\n", " vs Bologna\n", - " 22.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 45.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", " 4.0\n", " 0.0\n", - " 0.0\n", + " 1.0\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 71.0\n", + " 70.0\n", + " 16.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 207.0\n", - " 34.0\n", - " 46.0\n", - " 42.5\n", + " 292.0\n", + " 47.0\n", + " 73.0\n", + " 39.2\n", " \n", " \n", " 2\n", " vs Cagliari\n", - " 21.0\n", - " 62.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", + " 22.0\n", + " 61.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 6.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 38.0\n", - " 41.0\n", - " 5.0\n", + " 50.0\n", + " 65.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 220.0\n", - " 60.0\n", - " 51.0\n", - " 54.1\n", + " 332.0\n", + " 92.0\n", + " 71.0\n", + " 56.4\n", " \n", " \n", " 3\n", " vs Empoli\n", - " 27.0\n", - " 52.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 11.0\n", + " 28.0\n", + " 54.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 8.0\n", " 1.0\n", " 2.0\n", " ...\n", - " 60.0\n", - " 42.0\n", - " 8.0\n", + " 84.0\n", + " 74.0\n", + " 10.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 54.0\n", - " 39.0\n", - " 58.1\n", + " 313.0\n", + " 82.0\n", + " 60.0\n", + " 57.7\n", " \n", " \n", " 4\n", " vs Fiorentina\n", - " 22.0\n", - " 39.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 24.0\n", + " 42.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", " 8.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 5.0\n", + " 75.0\n", + " 63.0\n", + " 8.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 202.0\n", - " 56.0\n", - " 53.0\n", - " 51.4\n", + " 311.0\n", + " 96.0\n", + " 75.0\n", + " 56.1\n", " \n", " \n", " 5\n", " vs Frosinone\n", - " 23.0\n", - " 51.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 50.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", " 6.0\n", - " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 50.0\n", - " 39.0\n", - " 6.0\n", + " 73.0\n", + " 54.0\n", + " 15.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 212.0\n", - " 53.0\n", - " 52.0\n", - " 50.5\n", + " 325.0\n", + " 79.0\n", + " 80.0\n", + " 49.7\n", " \n", " \n", " 6\n", " vs Genoa\n", - " 19.0\n", - " 66.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 22.0\n", + " 65.7\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 8.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 43.0\n", - " 9.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 200.0\n", - " 46.0\n", + " 67.0\n", " 60.0\n", - " 43.4\n", + " 12.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 295.0\n", + " 66.0\n", + " 83.0\n", + " 44.3\n", " \n", " \n", " 7\n", " vs Hellas Verona\n", - " 21.0\n", - " 56.5\n", + " 22.0\n", + " 54.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 2.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 47.0\n", - " 63.0\n", - " 7.0\n", + " 84.0\n", + " 84.0\n", + " 11.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 190.0\n", - " 71.0\n", - " 82.0\n", - " 46.4\n", + " 326.0\n", + " 116.0\n", + " 117.0\n", + " 49.8\n", " \n", " \n", " 8\n", " vs Inter\n", - " 19.0\n", - " 51.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 22.0\n", + " 46.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 3.0\n", + " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 47.0\n", - " 44.0\n", - " 5.0\n", + " 70.0\n", + " 64.0\n", + " 9.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 163.0\n", - " 30.0\n", - " 44.0\n", - " 40.5\n", + " 248.0\n", + " 46.0\n", + " 77.0\n", + " 37.4\n", " \n", " \n", " 9\n", " vs Juventus\n", - " 21.0\n", - " 51.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 2.0\n", - " 2.0\n", + " 22.0\n", + " 49.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 5.0\n", + " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 52.0\n", - " 49.0\n", - " 5.0\n", + " 80.0\n", + " 71.0\n", + " 6.0\n", " 0.0\n", " 2.0\n", - " 0.0\n", - " 173.0\n", - " 26.0\n", + " 1.0\n", + " 267.0\n", + " 41.0\n", + " 67.0\n", " 38.0\n", - " 40.6\n", " \n", " \n", " 10\n", " vs Lazio\n", " 20.0\n", - " 44.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 46.0\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 49.0\n", - " 44.0\n", - " 7.0\n", + " 69.0\n", + " 67.0\n", + " 10.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", - " 0.0\n", - " 196.0\n", - " 51.0\n", - " 30.0\n", - " 63.0\n", + " 282.0\n", + " 66.0\n", + " 53.0\n", + " 55.5\n", " \n", " \n", " 11\n", " vs Lecce\n", - " 19.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 4.0\n", + " 22.0\n", + " 53.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 5.0\n", + " 5.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 64.0\n", - " 53.0\n", + " 88.0\n", + " 78.0\n", " 5.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 203.0\n", - " 43.0\n", - " 54.0\n", - " 44.3\n", + " 295.0\n", + " 67.0\n", + " 73.0\n", + " 47.9\n", " \n", " \n", " 12\n", " vs Milan\n", - " 19.0\n", - " 44.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", + " 23.0\n", + " 43.2\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 7.0\n", + " 80.0\n", + " 60.0\n", + " 8.0\n", " 1.0\n", " 3.0\n", " 0.0\n", - " 176.0\n", - " 42.0\n", - " 33.0\n", - " 56.0\n", + " 281.0\n", + " 65.0\n", + " 61.0\n", + " 51.6\n", " \n", " \n", " 13\n", " vs Monza\n", - " 22.0\n", - " 43.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 45.8\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.0\n", " 5.0\n", - " 1.0\n", - " 1.0\n", + " 2.0\n", + " 2.0\n", " ...\n", - " 37.0\n", - " 52.0\n", - " 6.0\n", - " 1.0\n", + " 65.0\n", + " 68.0\n", + " 11.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", - " 187.0\n", - " 45.0\n", - " 37.0\n", - " 54.9\n", + " 281.0\n", + " 74.0\n", + " 56.0\n", + " 56.9\n", " \n", " \n", " 14\n", " vs Napoli\n", - " 19.0\n", - " 38.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 20.0\n", + " 39.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 5.0\n", - " 4.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 47.0\n", - " 39.0\n", - " 7.0\n", + " 73.0\n", + " 60.0\n", + " 9.0\n", " 1.0\n", - " 2.0\n", + " 4.0\n", " 0.0\n", - " 173.0\n", - " 35.0\n", - " 47.0\n", - " 42.7\n", + " 254.0\n", + " 52.0\n", + " 56.0\n", + " 48.1\n", " \n", " \n", " 15\n", " vs Roma\n", " 23.0\n", - " 43.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 40.3\n", " 6.0\n", - " 4.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 9.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", + " 58.0\n", + " 67.0\n", " 4.0\n", " 1.0\n", " 1.0\n", " 1.0\n", - " 159.0\n", - " 54.0\n", - " 76.0\n", - " 41.5\n", + " 267.0\n", + " 83.0\n", + " 104.0\n", + " 44.4\n", " \n", " \n", " 16\n", " vs Salernitana\n", - " 21.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 5.0\n", + " 22.0\n", + " 47.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", + " 94.0\n", + " 70.0\n", + " 12.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 86.0\n", - " 54.0\n", - " 61.4\n", + " 311.0\n", + " 120.0\n", + " 82.0\n", + " 59.4\n", " \n", " \n", " 17\n", " vs Sassuolo\n", - " 24.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 25.0\n", + " 57.7\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 8.0\n", " 2.0\n", " 3.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.0\n", + " 55.0\n", + " 20.0\n", " 2.0\n", " 1.0\n", - " 0.0\n", - " 207.0\n", - " 50.0\n", - " 37.0\n", - " 57.5\n", + " 1.0\n", + " 299.0\n", + " 85.0\n", + " 55.0\n", + " 60.7\n", " \n", " \n", " 18\n", " vs Torino\n", - " 22.0\n", - " 48.8\n", + " 23.0\n", + " 50.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 2.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 44.0\n", - " 48.0\n", + " 61.0\n", + " 64.0\n", " 7.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 207.0\n", - " 63.0\n", - " 59.0\n", - " 51.6\n", + " 302.0\n", + " 93.0\n", + " 82.0\n", + " 53.1\n", " \n", " \n", " 19\n", " vs Udinese\n", - " 22.0\n", - " 51.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", - " 1.0\n", - " 1.0\n", - " ...\n", - " 43.0\n", - " 51.0\n", + " 24.0\n", + " 53.8\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 10.0\n", + " 6.0\n", + " 2.0\n", + " 2.0\n", + " ...\n", + " 65.0\n", + " 74.0\n", + " 11.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 188.0\n", - " 52.0\n", - " 64.0\n", - " 44.8\n", + " 297.0\n", + " 68.0\n", + " 101.0\n", + " 40.2\n", " \n", " \n", "\n", @@ -2723,92 +2753,92 @@ ], "text/plain": [ " team players_used possession games games_starts minutes \\\n", - "0 vs Atalanta 23.0 50.5 4.0 44.0 360.0 \n", - "1 vs Bologna 22.0 43.5 4.0 44.0 360.0 \n", - "2 vs Cagliari 21.0 62.3 4.0 44.0 360.0 \n", - "3 vs Empoli 27.0 52.3 4.0 44.0 360.0 \n", - "4 vs Fiorentina 22.0 39.0 4.0 44.0 360.0 \n", - "5 vs Frosinone 23.0 51.8 4.0 44.0 360.0 \n", - "6 vs Genoa 19.0 66.8 4.0 44.0 360.0 \n", - "7 vs Hellas Verona 21.0 56.5 4.0 44.0 360.0 \n", - "8 vs Inter 19.0 51.3 4.0 44.0 360.0 \n", - "9 vs Juventus 21.0 51.3 4.0 44.0 360.0 \n", - "10 vs Lazio 20.0 44.0 4.0 44.0 360.0 \n", - "11 vs Lecce 19.0 56.5 4.0 44.0 360.0 \n", - "12 vs Milan 19.0 44.8 4.0 44.0 360.0 \n", - "13 vs Monza 22.0 43.3 4.0 44.0 360.0 \n", - "14 vs Napoli 19.0 38.3 4.0 44.0 360.0 \n", - "15 vs Roma 23.0 43.0 4.0 44.0 360.0 \n", - "16 vs Salernitana 21.0 48.5 4.0 44.0 360.0 \n", - "17 vs Sassuolo 24.0 56.5 4.0 44.0 360.0 \n", - "18 vs Torino 22.0 48.8 4.0 44.0 360.0 \n", - "19 vs Udinese 22.0 51.5 4.0 44.0 360.0 \n", + "0 vs Atalanta 24.0 49.5 6.0 66.0 540.0 \n", + "1 vs Bologna 23.0 45.3 6.0 66.0 540.0 \n", + "2 vs Cagliari 22.0 61.8 6.0 66.0 540.0 \n", + "3 vs Empoli 28.0 54.7 6.0 66.0 540.0 \n", + "4 vs Fiorentina 24.0 42.8 6.0 66.0 540.0 \n", + "5 vs Frosinone 24.0 50.8 6.0 66.0 540.0 \n", + "6 vs Genoa 22.0 65.7 6.0 66.0 540.0 \n", + "7 vs Hellas Verona 22.0 54.8 6.0 66.0 540.0 \n", + "8 vs Inter 22.0 46.8 6.0 66.0 540.0 \n", + "9 vs Juventus 22.0 49.7 6.0 66.0 540.0 \n", + "10 vs Lazio 20.0 46.0 6.0 66.0 540.0 \n", + "11 vs Lecce 22.0 53.3 6.0 66.0 540.0 \n", + "12 vs Milan 23.0 43.2 6.0 66.0 540.0 \n", + "13 vs Monza 23.0 45.8 6.0 66.0 540.0 \n", + "14 vs Napoli 20.0 39.3 6.0 66.0 540.0 \n", + "15 vs Roma 23.0 40.3 6.0 66.0 540.0 \n", + "16 vs Salernitana 22.0 47.7 6.0 66.0 540.0 \n", + "17 vs Sassuolo 25.0 57.7 6.0 66.0 540.0 \n", + "18 vs Torino 23.0 50.8 6.0 66.0 540.0 \n", + "19 vs Udinese 24.0 53.8 6.0 66.0 540.0 \n", "\n", " goals assists pens_made pens_att ... fouls fouled offsides \\\n", - "0 5.0 4.0 0.0 0.0 ... 36.0 47.0 2.0 \n", - "1 4.0 4.0 0.0 0.0 ... 50.0 40.0 12.0 \n", - "2 4.0 3.0 0.0 1.0 ... 38.0 41.0 5.0 \n", - "3 11.0 8.0 1.0 2.0 ... 60.0 42.0 8.0 \n", - "4 9.0 8.0 1.0 1.0 ... 56.0 43.0 5.0 \n", - "5 6.0 5.0 0.0 0.0 ... 50.0 39.0 6.0 \n", - "6 7.0 6.0 0.0 0.0 ... 43.0 43.0 9.0 \n", - "7 4.0 2.0 1.0 1.0 ... 47.0 63.0 7.0 \n", - "8 1.0 1.0 0.0 0.0 ... 47.0 44.0 5.0 \n", - "9 2.0 2.0 0.0 0.0 ... 52.0 49.0 5.0 \n", - "10 7.0 5.0 0.0 0.0 ... 49.0 44.0 7.0 \n", - "11 4.0 4.0 0.0 0.0 ... 64.0 53.0 5.0 \n", - "12 7.0 6.0 1.0 1.0 ... 56.0 43.0 7.0 \n", - "13 6.0 5.0 1.0 1.0 ... 37.0 52.0 6.0 \n", - "14 5.0 4.0 1.0 1.0 ... 47.0 39.0 7.0 \n", - "15 6.0 4.0 1.0 1.0 ... 46.0 51.0 4.0 \n", - "16 8.0 5.0 1.0 1.0 ... 64.0 46.0 4.0 \n", - "17 9.0 6.0 2.0 3.0 ... 45.0 34.0 15.0 \n", - "18 4.0 2.0 2.0 2.0 ... 44.0 48.0 7.0 \n", - "19 4.0 3.0 1.0 1.0 ... 43.0 51.0 10.0 \n", + "0 5.0 4.0 0.0 0.0 ... 57.0 74.0 4.0 \n", + "1 4.0 4.0 0.0 1.0 ... 71.0 70.0 16.0 \n", + "2 9.0 6.0 0.0 1.0 ... 50.0 65.0 11.0 \n", + "3 12.0 8.0 1.0 2.0 ... 84.0 74.0 10.0 \n", + "4 10.0 8.0 1.0 1.0 ... 75.0 63.0 8.0 \n", + "5 8.0 6.0 0.0 0.0 ... 73.0 54.0 15.0 \n", + "6 9.0 8.0 0.0 0.0 ... 67.0 60.0 12.0 \n", + "7 6.0 4.0 1.0 1.0 ... 84.0 84.0 11.0 \n", + "8 3.0 3.0 0.0 0.0 ... 70.0 64.0 9.0 \n", + "9 5.0 3.0 0.0 0.0 ... 80.0 71.0 6.0 \n", + "10 8.0 5.0 0.0 0.0 ... 69.0 67.0 10.0 \n", + "11 5.0 5.0 0.0 0.0 ... 88.0 78.0 5.0 \n", + "12 8.0 7.0 1.0 1.0 ... 80.0 60.0 8.0 \n", + "13 7.0 5.0 2.0 2.0 ... 65.0 68.0 11.0 \n", + "14 6.0 5.0 1.0 1.0 ... 73.0 60.0 9.0 \n", + "15 11.0 9.0 1.0 1.0 ... 58.0 67.0 4.0 \n", + "16 10.0 7.0 1.0 1.0 ... 94.0 70.0 12.0 \n", + "17 11.0 8.0 2.0 3.0 ... 63.0 55.0 20.0 \n", + "18 7.0 4.0 2.0 2.0 ... 61.0 64.0 7.0 \n", + "19 10.0 6.0 2.0 2.0 ... 65.0 74.0 11.0 \n", "\n", " pens_won pens_conceded own_goals ball_recoveries aerials_won \\\n", - "0 0.0 0.0 0.0 212.0 65.0 \n", - "1 0.0 1.0 0.0 207.0 34.0 \n", - "2 0.0 0.0 0.0 220.0 60.0 \n", - "3 1.0 0.0 0.0 203.0 54.0 \n", - "4 1.0 0.0 0.0 202.0 56.0 \n", - "5 0.0 2.0 0.0 212.0 53.0 \n", - "6 0.0 0.0 0.0 200.0 46.0 \n", - "7 1.0 0.0 0.0 190.0 71.0 \n", - "8 0.0 2.0 0.0 163.0 30.0 \n", - "9 0.0 2.0 0.0 173.0 26.0 \n", - "10 0.0 0.0 0.0 196.0 51.0 \n", - "11 0.0 2.0 0.0 203.0 43.0 \n", - "12 1.0 3.0 0.0 176.0 42.0 \n", - "13 1.0 0.0 0.0 187.0 45.0 \n", - "14 1.0 2.0 0.0 173.0 35.0 \n", - "15 1.0 1.0 1.0 159.0 54.0 \n", - "16 0.0 0.0 0.0 203.0 86.0 \n", - "17 2.0 1.0 0.0 207.0 50.0 \n", - "18 1.0 0.0 0.0 207.0 63.0 \n", - "19 0.0 0.0 0.0 188.0 52.0 \n", + "0 0.0 0.0 0.0 347.0 97.0 \n", + "1 0.0 1.0 0.0 292.0 47.0 \n", + "2 0.0 0.0 0.0 332.0 92.0 \n", + "3 1.0 0.0 0.0 313.0 82.0 \n", + "4 1.0 0.0 0.0 311.0 96.0 \n", + "5 0.0 2.0 0.0 325.0 79.0 \n", + "6 0.0 0.0 0.0 295.0 66.0 \n", + "7 1.0 0.0 0.0 326.0 116.0 \n", + "8 0.0 2.0 0.0 248.0 46.0 \n", + "9 0.0 2.0 1.0 267.0 41.0 \n", + "10 0.0 1.0 0.0 282.0 66.0 \n", + "11 0.0 2.0 0.0 295.0 67.0 \n", + "12 1.0 3.0 0.0 281.0 65.0 \n", + "13 2.0 0.0 0.0 281.0 74.0 \n", + "14 1.0 4.0 0.0 254.0 52.0 \n", + "15 1.0 1.0 1.0 267.0 83.0 \n", + "16 0.0 0.0 0.0 311.0 120.0 \n", + "17 2.0 1.0 1.0 299.0 85.0 \n", + "18 1.0 0.0 0.0 302.0 93.0 \n", + "19 1.0 0.0 0.0 297.0 68.0 \n", "\n", " aerials_lost aerials_won_pct \n", - "0 60.0 52.0 \n", - "1 46.0 42.5 \n", - "2 51.0 54.1 \n", - "3 39.0 58.1 \n", - "4 53.0 51.4 \n", - "5 52.0 50.5 \n", - "6 60.0 43.4 \n", - "7 82.0 46.4 \n", - "8 44.0 40.5 \n", - "9 38.0 40.6 \n", - "10 30.0 63.0 \n", - "11 54.0 44.3 \n", - "12 33.0 56.0 \n", - "13 37.0 54.9 \n", - "14 47.0 42.7 \n", - "15 76.0 41.5 \n", - "16 54.0 61.4 \n", - "17 37.0 57.5 \n", - "18 59.0 51.6 \n", - "19 64.0 44.8 \n", + "0 109.0 47.1 \n", + "1 73.0 39.2 \n", + "2 71.0 56.4 \n", + "3 60.0 57.7 \n", + "4 75.0 56.1 \n", + "5 80.0 49.7 \n", + "6 83.0 44.3 \n", + "7 117.0 49.8 \n", + "8 77.0 37.4 \n", + "9 67.0 38.0 \n", + "10 53.0 55.5 \n", + "11 73.0 47.9 \n", + "12 61.0 51.6 \n", + "13 56.0 56.9 \n", + "14 56.0 48.1 \n", + "15 104.0 44.4 \n", + "16 82.0 59.4 \n", + "17 55.0 60.7 \n", + "18 82.0 53.1 \n", + "19 101.0 40.2 \n", "\n", "[20 rows x 152 columns]" ] diff --git a/3_players_dataset_creation.ipynb b/3_players_dataset_creation.ipynb index dfc64dd..bb1bfef 100644 --- a/3_players_dataset_creation.ipynb +++ b/3_players_dataset_creation.ipynb @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 11, "id": "b2d7073e", "metadata": {}, "outputs": [], @@ -48,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "id": "667970f6", "metadata": {}, "outputs": [ @@ -85,23 +85,23 @@ " \n", " \n", " 1\n", + " Yacine Adli\n", + " Milan\n", + " \n", + " \n", + " 2\n", " Michel Aebischer\n", " Bologna\n", " \n", " \n", - " 2\n", - " Luis Alberto\n", - " Lazio\n", - " \n", - " \n", " 3\n", - " Pontus Almqvist\n", - " Lecce\n", + " Jean-Daniel Akpa-Akpro\n", + " Monza\n", " \n", " \n", " 4\n", - " Lorenzo Amatucci\n", - " Fiorentina\n", + " Luis Alberto\n", + " Lazio\n", " \n", " \n", " ...\n", @@ -109,53 +109,53 @@ " ...\n", " \n", " \n", - " 452\n", - " Yann Sommer\n", - " Inter\n", - " \n", - " \n", - " 453\n", + " 482\n", " Alessandro Sorrentino\n", " Monza\n", " \n", " \n", - " 454\n", + " 483\n", + " Marco Sportiello\n", + " Milan\n", + " \n", + " \n", + " 484\n", " Wojciech Szczęsny\n", " Juventus\n", " \n", " \n", - " 455\n", + " 485\n", " Pietro Terracciano\n", " Fiorentina\n", " \n", " \n", - " 456\n", + " 486\n", " Stefano Turati\n", " Frosinone\n", " \n", " \n", "\n", - "

457 rows × 2 columns

\n", + "

487 rows × 2 columns

\n", "" ], "text/plain": [ - " player team\n", - "0 Francesco Acerbi Inter\n", - "1 Michel Aebischer Bologna\n", - "2 Luis Alberto Lazio\n", - "3 Pontus Almqvist Lecce\n", - "4 Lorenzo Amatucci Fiorentina\n", - ".. ... ...\n", - "452 Yann Sommer Inter\n", - "453 Alessandro Sorrentino Monza\n", - "454 Wojciech Szczęsny Juventus\n", - "455 Pietro Terracciano Fiorentina\n", - "456 Stefano Turati Frosinone\n", + " player team\n", + "0 Francesco Acerbi Inter\n", + "1 Yacine Adli Milan\n", + "2 Michel Aebischer Bologna\n", + "3 Jean-Daniel Akpa-Akpro Monza\n", + "4 Luis Alberto Lazio\n", + ".. ... ...\n", + "482 Alessandro Sorrentino Monza\n", + "483 Marco Sportiello Milan\n", + "484 Wojciech Szczęsny Juventus\n", + "485 Pietro Terracciano Fiorentina\n", + "486 Stefano Turati Frosinone\n", "\n", - "[457 rows x 2 columns]" + "[487 rows x 2 columns]" ] }, - "execution_count": 3, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -170,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "id": "e1e64596", "metadata": {}, "outputs": [], @@ -185,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "id": "3078d6f3", "metadata": {}, "outputs": [], @@ -203,7 +203,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "id": "ffd6091c", "metadata": {}, "outputs": [ @@ -213,462 +213,492 @@ "text": [ " player surname\n", "0 Francesco Acerbi Acerbi\n", - "1 Michel Aebischer Aebischer\n", - "2 Luis Alberto Alberto\n", - "3 Pontus Almqvist Almqvist\n", - "4 Lorenzo Amatucci Amatucci\n", - "5 Bruno Amione Amione\n", - "6 Felipe Anderson Anderson\n", - "7 Houssem Aouar Aouar\n", - "8 Marko Arnautović Arnautovic\n", - "9 Kristjan Asllani Asllani\n", - "10 Tommaso Augello Augello\n", - "11 Yann Aurel Bisseck Bisseck\n", - "12 Sardar Azmoun Azmoun\n", - "13 Paulo Azzi Azzi\n", - "14 Oussama El Azzouzi Azzouzi\n", - "15 Milan Badelj Badelj\n", - "16 Jaime Báez Baez\n", - "17 Nedim Bajrami Bajrami\n", - "18 Mitchel Bakker Bakker\n", - "19 Tommaso Baldanzi Baldanzi\n", - "20 Lameck Banda Banda\n", - "21 Mattia Bani Bani\n", - "22 Antonín Barák Barak\n", - "23 Nicolò Barella Barella\n", - "24 Enzo Barrenechea Barrenechea\n", - "25 Federico Baschirotto Baschirotto\n", - "26 Alessandro Bastoni Bastoni\n", - "27 Simone Bastoni Bastoni\n", - "28 Raoul Bellanova Bellanova\n", - "29 Andrea Belotti Belotti\n", - "30 Lucas Beltrán Beltran\n", - "31 Domenico Berardi Berardi\n", - "32 Bartosz Bereszyński Bereszynski\n", - "33 Etrit Berisha Berisha\n", - "34 Victor Bernth Kristiansen Kristiansen\n", - "35 Beto Beto\n", - "36 Sam Beukema Beukema\n", - "37 Jaka Bijol Bijol\n", - "38 Cristiano Biraghi Biraghi\n", - "39 Davide Biraschi Biraschi\n", - "40 Samuele Birindelli Birindelli\n", - "41 Alexis Blin Blin\n", - "42 Emil Bohinen Bohinen\n", - "43 Daniel Boloca Boloca\n", - "44 Giacomo Bonaventura Bonaventura\n", - "45 Federico Bonazzoli Bonazzoli\n", - "46 Warren Bondo Bondo\n", - "47 Gennaro Borrelli Borrelli\n", - "48 Erik Botheim Botheim\n", - "49 Edoardo Bove Bove\n", - "50 Domagoj Bradarić Bradaric\n", - "51 Josip Brekalo Brekalo\n", - "52 Gleison Bremer Bremer\n", - "53 Marco Brescianini Brescianini\n", - "54 Alessandro Buongiorno Buongiorno\n", - "55 Rareș-Cătălin Burnete Burnete\n", - "56 Juan Cabal Cabal\n", - "57 Jovane Cabral Cabral\n", - "58 Liberato Cacace Cacace\n", - "59 Jens Cajuste Cajuste\n", - "60 Davide Calabria Calabria\n", - "61 Riccardo Calafiori Calafiori\n", - "62 Luca Caldirola Caldirola\n", - "63 Hakan Çalhanoğlu Calhanoglu\n", - "64 Nicolò Cambiaghi Cambiaghi\n", - "65 Andrea Cambiaso Cambiaso\n", - "66 Matteo Cancellieri Cancellieri\n", - "67 Antonio Candreva Candreva\n", - "68 Luigi Canotto Canotto\n", - "69 Gianluca Caprari Caprari\n", - "70 Elia Caprile Caprile\n", - "71 Francesco Caputo Caputo\n", - "72 Andrea Carboni Carboni\n", - "73 Valentin Carboni Carboni\n", - "74 Carlos Carlos\n", - "75 Marco Carnesecchi Carnesecchi\n", - "76 Nicolò Casale Casale\n", - "77 Giuseppe Caso Caso\n", - "78 Valentín Castellanos Castellanos\n", - "79 Samu Castillejo Castillejo\n", - "80 Danilo Cataldi Cataldi\n", - "81 Emil Ceide Ceide\n", - "82 Zeki Çelik Celik\n", - "83 Michele Cerofolini Cerofolini\n", - "84 Walid Cheddira Cheddira\n", - "85 Federico Chiesa Chiesa\n", - "86 Oliver Christensen Christensen\n", - "87 Samuel Chukwueze Chukwueze\n", - "88 Patrick Ciurria Ciurria\n", - "89 Lorenzo Colombo Colombo\n", - "90 Andrea Colpani Colpani\n", - "91 Andrea Consigli Consigli\n", - "92 Diego Coppola Coppola\n", - "93 Tommaso Corazza Corazza\n", - "94 Lassana Coulibaly Coulibaly\n", - "95 Mamadou Coulibaly Coulibaly\n", - "96 Alessio Cragno Cragno\n", - "97 Bryan Cristante Cristante\n", - "98 Juan Cuadrado Cuadrado\n", - "99 Marvin Cuni Cuni\n", - "100 Danilo D'Ambrosio DAmbrosio\n", - "101 Danilo Danilo\n", - "102 Matteo Darmian Darmian\n", - "103 Paweł Dawidowicz Dawidowicz\n", - "104 Charles De Ketelaere Ketelaere\n", - "105 Lorenzo De Silvestri Silvestri\n", - "106 Koni De Winter Winter\n", - "107 Grégoire Defrel Defrel\n", - "108 Alessandro Deiola Deiola\n", - "109 Mattia Destro Destro\n", - "110 Federico Di Francesco Francesco\n", - "111 Michele Di Gregorio Gregorio\n", - "112 Giovanni Di Lorenzo Lorenzo\n", - "113 Alessandro Di Pardo Pardo\n", - "114 Boulaye Dia Dia\n", - "115 Federico Dimarco Dimarco\n", - "116 Berat Djimsiti Djimsiti\n", - "117 Dodô Dodo\n", - "118 Josh Doig Doig\n", - "119 Nicolás Domínguez Dominguez\n", - "120 Patrick Dorgu Dorgu\n", - "121 Alberto Dossena Dossena\n", - "122 Radu Drăgușin Dragusin\n", - "123 Ondrej Duda Duda\n", - "124 Denzel Dumfries Dumfries\n", - "125 Alfred Duncan Duncan\n", - "126 Paulo Dybala Dybala\n", - "127 Festy Ebosele Ebosele\n", - "128 Enzo Ebosse Ebosse\n", - "129 Tyronne Ebuehi Ebuehi\n", - "130 Éderson Ederson\n", - "131 Emmanuel Ekong Ekong\n", - "132 Caleb Ekuban Ekuban\n", - "133 Elif Elmas Elmas\n", - "134 Martin Erlic Erlic\n", - "135 Giovanni Fabbian Fabbian\n", - "136 Nicolò Fagioli Fagioli\n", - "137 Wladimiro Falcone Falcone\n", - "138 Davide Faraoni Faraoni\n", - "139 Federico Fazio Fazio\n", - "140 Jacopo Fazzini Fazzini\n", - "141 Lewis Ferguson Ferguson\n", - "142 João Ferreira Ferreira\n", - "143 Alessandro Florenzi Florenzi\n", - "144 Michael Folorunsho Folorunsho\n", - "145 Davide Frattesi Frattesi\n", - "146 Morten Frendrup Frendrup\n", - "147 Remo Freuler Freuler\n", - "148 Roberto Gagliardini Gagliardini\n", - "149 Antonino Gallo Gallo\n", - "150 Luca Garritano Garritano\n", - "151 Federico Gatti Gatti\n", - "152 Francesco Gelli Gelli\n", - "153 Valentin Gendrey Gendrey\n", - "154 Gvidas Gineitis Gineitis\n", - "155 Olivier Giroud Giroud\n", - "156 Edoardo Goldaniga Goldaniga\n", - "157 Joan Gonzàlez Gonzalez\n", - "158 Nicolás González Gonzalez\n", - "159 Alberto Grassi Grassi\n", - "160 Mattéo Guendouzi Guendouzi\n", - "161 Axel Guessand Guessand\n", - "162 Albert Guðmundsson Gumundsson\n", - "163 Emmanuel Gyasi Gyasi\n", - "164 Norbert Gyömbér Gyomber\n", - "165 Nicolas Haas Haas\n", - "166 Abdou Harroui Harroui\n", - "167 Pantelis Hatzidiakos Hatzidiakos\n", - "168 Silvan Hefti Hefti\n", - "169 Liam Henderson Henderson\n", - "170 Matheus Henrique Henrique\n", - "171 Theo Hernández Hernandez\n", - "172 Isak Hien Hien\n", - "173 Emil Holm Holm\n", - "174 Martin Hongla Hongla\n", - "175 Sydney van Hooijdonk Hooijdonk\n", - "176 Elseid Hysaj Hysaj\n", - "177 Chukwubuikem Ikwuemesi Ikwuemesi\n", - "178 Ivan Ilić Ilic\n", - "179 Samuel Iling-Junior Iling-Junior\n", - "180 Ciro Immobile Immobile\n", - "181 Gino Infantino Infantino\n", - "182 Gustav Isaksen Isaksen\n", - "183 Ardian Ismajli Ismajli\n", - "184 Armando Izzo Izzo\n", - "185 Filip Jagiełło Jagieo\n", - "186 Jakub Jankto Jankto\n", - "187 Juan Jesus Jesus\n", - "188 Luka Jović Jovic\n", - "189 Mohamed Kaba Kaba\n", - "190 Christian Kabasele Kabasele\n", - "191 Pierre Kalulu Kalulu\n", - "192 Daichi Kamada Kamada\n", - "193 Hassane Kamara Kamara\n", - "194 Yann Karamoh Karamoh\n", - "195 Jesper Karlsson Karlsson\n", - "196 Rick Karsdorp Karsdorp\n", - "197 Grigoris Kastanos Kastanos\n", - "198 Michael Kayode Kayode\n", - "199 Moise Kean Kean\n", - "200 Simon Kjær Kjr\n", - "201 Sead Kolašinac Kolasinac\n", - "202 Teun Koopmeiners Koopmeiners\n", - "203 Filip Kostić Kostic\n", - "204 Christian Kouamé Kouame\n", - "205 Viktor Kovalenko Kovalenko\n", - "206 Nikola Krstović Krstovic\n", - "207 Rade Krunić Krunic\n", - "208 Berkan Kutlu Kutlu\n", - "209 Khvicha Kvaratskhelia Kvaratskhelia\n", - "210 Giorgi Kvernadze Kvernadze\n", - "211 Giorgos Kyriakopoulos Kyriakopoulos\n", - "212 Armand Lauriente Lauriente\n", - "213 Valentino Lazaro Lazaro\n", - "214 Darko Lazović Lazovic\n", - "215 Manuel Lazzari Lazzari\n", - "216 Rafael Leão Leao\n", - "217 Jesper Lindstrøm Lindstrm\n", - "218 Karol Linetty Linetty\n", - "219 Pol Lirola Lirola\n", - "220 Diego Llorente Llorente\n", - "221 Stanislav Lobotka Lobotka\n", - "222 Manuel Locatelli Locatelli\n", - "223 Ruben Loftus-Cheek Loftus-Cheek\n", - "224 Ademola Lookman Lookman\n", - "225 Maxime Lopez Lopez\n", - "226 Matteo Lovato Lovato\n", - "227 Sandi Lovrić Lovric\n", - "228 Lorenzo Lucca Lucca\n", - "229 Jhon Lucumí Lucumi\n", - "230 José Luis Palomino Palomino\n", - "231 Romelu Lukaku Lukaku\n", - "232 Sebastiano Luperto Luperto\n", - "233 Charalambos Lykogiannis Lykogiannis\n", - "234 Giulio Maggiore Maggiore\n", - "235 Giangiacomo Magnani Magnani\n", - "236 Mike Maignan Maignan\n", - "237 Antoine Makoumbou Makoumbou\n", - "238 Youssef Maleh Maleh\n", - "239 Ruslan Malinovskyi Malinovskyi\n", - "240 Gianluca Mancini Mancini\n", - "241 Rolando Mandragora Mandragora\n", - "242 Riccardo Marchizza Marchizza\n", - "243 Pablo Marí Mari\n", - "244 Mirko Marić Maric\n", - "245 Răzvan Marin Marin\n", - "246 Agustín Martegani Martegani\n", - "247 Aarón Martín Martin\n", - "248 Josep Martinez Martinez\n", - "249 Lautaro Martínez Martinez\n", - "250 Lucas Martínez Quarta Quarta\n", - "251 Adam Marušić Marusic\n", - "252 Luca Mazzitelli Mazzitelli\n", - "253 Pasquale Mazzocchi Mazzocchi\n", - "254 Jordi Mboula Mboula\n", - "255 Weston McKennie McKennie\n", - "256 Arthur Melo Melo\n", - "257 Alex Meret Meret\n", - "258 Nikola Milenković Milenkovic\n", - "259 Arkadiusz Milik Milik\n", - "260 Vanja Milinković-Savić Milinkovic-Savic\n", - "261 Aleksei Miranchuk Miranchuk\n", - "262 Kevin Miranda Miranda\n", - "263 Fabio Miretti Miretti\n", - "264 Filippo Missori Missori\n", - "265 Henrikh Mkhitaryan Mkhitaryan\n", - "266 Ilario Monterisi Monterisi\n", - "267 Lorenzo Montipò Montipo\n", - "268 Nikola Moro Moro\n", - "269 Dany Mota Mota\n", - "270 Samuele Mulattieri Mulattieri\n", - "271 Luis Muriel Muriel\n", - "272 Yunus Musah Musah\n", - "273 Juan Musso Musso\n", - "274 Obite N'Dicka NDicka\n", - "275 Nahitan Nández Nandez\n", - "276 Michel Ndary Adopo Adopo\n", - "277 Dan Ndoye Ndoye\n", - "278 Cyril Ngonge Ngonge\n", - "279 Rasmus Nissen Nissen\n", - "280 M'Bala Nzola Nzola\n", - "281 Adam Obert Obert\n", - "282 Guillermo Ochoa Ochoa\n", - "283 Noah Okafor Okafor\n", - "284 Caleb Okoli Okoli\n", - "285 Mathías Olivera Olivera\n", - "286 Gaetano Oristanio Oristanio\n", - "287 Riccardo Orsolini Orsolini\n", - "288 Victor Osimhen Osimhen\n", - "289 Anthony Oyono Oyono\n", - "290 Riccardo Pagano Pagano\n", - "291 Leandro Paredes Paredes\n", - "292 Fabiano Parisi Parisi\n", - "293 Mario Pašalić Pasalic\n", - "294 Patric Patric\n", - "295 Rui Patrício Patricio\n", - "296 Leonardo Pavoletti Pavoletti\n", - "297 Martín Payero Payero\n", - "298 Marcus Pedersen Pedersen\n", - "299 Pedro Pedro\n", - "300 Pietro Pellegri Pellegri\n", - "301 Lorenzo Pellegrini Pellegrini\n", - "302 Luca Pellegrini Pellegrini\n", - "303 Pepín Pepin\n", - "304 Pedro Pereira Pereira\n", - "305 Roberto Pereyra Pereyra\n", - "306 Nehuén Pérez Perez\n", - "307 Mattia Perin Perin\n", - "308 Samuele Perisan Perisan\n", - "309 Matteo Pessina Pessina\n", - "310 Andrea Petagna Petagna\n", - "311 Giuseppe Pezzella Pezzella\n", - "312 Roberto Piccoli Piccoli\n", - "313 Roberto Piccoli Piccoli\n", - "314 Andrea Pinamonti Pinamonti\n", - "315 Lorenzo Pirola Pirola\n", - "316 Tommaso Pobega Pobega\n", - "317 Paul Pogba Pogba\n", - "318 Matteo Politano Politano\n", - "319 Marin Pongračić Pongracic\n", - "320 Stefan Posch Posch\n", - "321 Matteo Prati Prati\n", - "322 Ivan Provedel Provedel\n", - "323 Christian Pulisic Pulisic\n", - "324 Domingos Quina Quina\n", - "325 Adrien Rabiot Rabiot\n", - "326 Uroš Račić Racic\n", - "327 Nemanja Radonjić Radonjic\n", - "328 Boris Radunović Radunovic\n", - "329 Hamza Rafia Rafia\n", - "330 Ylber Ramadani Ramadani\n", - "331 Luca Ranieri Ranieri\n", - "332 Giacomo Raspadori Raspadori\n", - "333 Tijjani Reijnders Reijnders\n", - "334 Mateo Retegui Retegui\n", - "335 Samuele Ricci Ricci\n", - "336 Ricardo Rodríguez Rodriguez\n", - "337 Alessio Romagnoli Romagnoli\n", - "338 Simone Romagnoli Romagnoli\n", - "339 Marten de Roon Roon\n", - "340 Nicolò Rovella Rovella\n", - "341 Amir Rrahmani Rrahmani\n", - "342 Ruan Ruan\n", - "343 Matteo Ruggeri Ruggeri\n", - "344 Mário Rui Rui\n", - "345 Stefano Sabelli Sabelli\n", - "346 Lazar Samardzic Samardzic\n", - "347 Junior Sambia Sambia\n", - "348 Antonio Sanabria Sanabria\n", - "349 Renato Sanches Sanches\n", - "350 Alex Sandro Sandro\n", - "351 Riccardo Saponara Saponara\n", - "352 Giorgio Scalvini Scalvini\n", - "353 Gianluca Scamacca Scamacca\n", - "354 Perr Schuurs Schuurs\n", - "355 Demba Seck Seck\n", - "356 Vivaldo Semedo Semedo\n", - "357 Stefano Sensi Sensi\n", - "358 Suat Serdar Serdar\n", - "359 Stephan El Shaarawy Shaarawy\n", - "360 Eldor Shomurodov Shomurodov\n", - "361 Steven Shpendi Shpendi\n", - "362 Marco Silvestri Silvestri\n", - "363 Giovanni Simeone Simeone\n", - "364 Leo Skiri Østigård stigard\n", - "365 Łukasz Skorupski Skorupski\n", - "366 Chris Smalling Smalling\n", - "367 Ola Solbakken Solbakken\n", - "368 Yann Sommer Sommer\n", - "369 Brandon Soppy Soppy\n", - "370 Alessandro Sorrentino Sorrentino\n", - "371 Riccardo Sottil Sottil\n", - "372 Matìas Soulé Soule\n", - "373 Leonardo Spinazzola Spinazzola\n", - "374 Gabriel Strefezza Strefezza\n", - "375 Kevin Strootman Strootman\n", - "376 Isaac Success Success\n", - "377 Ibrahim Sulemana Sulemana\n", - "378 Tomáš Suslov Suslov\n", - "379 Wojciech Szczęsny Szczesny\n", - "380 Przemysław Szymiński Szyminski\n", - "381 Adrien Tameze Tameze\n", - "382 Loum Tchaouna Tchaouna\n", - "383 Filippo Terracciano Terracciano\n", - "384 Pietro Terracciano Terracciano\n", - "385 Florian Thauvin Thauvin\n", - "386 Malick Thiaw Thiaw\n", - "387 Morten Thorsby Thorsby\n", - "388 Kristian Thorstvedt Thorstvedt\n", - "389 Marcus Thuram Thuram\n", - "390 Jeremy Toljan Toljan\n", - "391 Rafael Tolói Toloi\n", - "392 Fikayo Tomori Tomori\n", - "393 Ahmed Touba Touba\n", - "394 Stefano Turati Turati\n", - "395 Kacper Urbanski Urbanski\n", - "396 Johan Vásquez Vasquez\n", - "397 Matías Vecino Vecino\n", - "398 Simone Verdi Verdi\n", - "399 Samuele Vignato Vignato\n", - "400 Matías Viña Vina\n", - "401 Mattia Viti Viti\n", - "402 Dušan Vlahović Vlahovic\n", - "403 Nikola Vlašić Vlasic\n", - "404 Mërgim Vojvoda Vojvoda\n", - "405 Cristian Volpato Volpato\n", - "406 Stefan de Vrij Vrij\n", - "407 Walace Walace\n", - "408 Sebastian Walukiewicz Walukiewicz\n", - "409 Timothy Weah Weah\n", - "410 Mateusz Wieteska Wieteska\n", - "411 Kenan Yıldız Yldz\n", - "412 Mattia Zaccagni Zaccagni\n", - "413 Nicola Zalewski Zalewski\n", - "414 Andre-Frank Zambo Anguissa Anguissa\n", - "415 Duván Zapata Zapata\n", - "416 Duván Zapata Zapata\n", - "417 Gabriele Zappa Zappa\n", - "418 Davide Zappacosta Zappacosta\n", - "419 Oier Zarraga Zarraga\n", - "420 Jordan Zemura Zemura\n", - "421 Alessio Zerbin Zerbin\n", - "422 Piotr Zieliński Zielinski\n", - "423 David Zima Zima\n", - "424 Joshua Zirkzee Zirkzee\n", - "425 Zito Zito\n", - "426 Nadir Zortea Zortea\n", - "427 Milan Đurić uric\n", - "428 Mateusz Łęgowski egowski\n", - "429 Etrit Berisha Berisha\n", - "430 Elia Caprile Caprile\n", - "431 Marco Carnesecchi Carnesecchi\n", - "432 Michele Cerofolini Cerofolini\n", - "433 Oliver Christensen Christensen\n", - "434 Andrea Consigli Consigli\n", - "435 Alessio Cragno Cragno\n", - "436 Michele Di Gregorio Gregorio\n", - "437 Wladimiro Falcone Falcone\n", - "438 Mike Maignan Maignan\n", - "439 Josep Martinez Martinez\n", - "440 Alex Meret Meret\n", - "441 Vanja Milinković-Savić Milinkovic-Savic\n", - "442 Lorenzo Montipò Montipo\n", - "443 Juan Musso Musso\n", - "444 Guillermo Ochoa Ochoa\n", - "445 Rui Patrício Patricio\n", - "446 Mattia Perin Perin\n", - "447 Samuele Perisan Perisan\n", - "448 Ivan Provedel Provedel\n", - "449 Boris Radunović Radunovic\n", - "450 Marco Silvestri Silvestri\n", - "451 Łukasz Skorupski Skorupski\n", - "452 Yann Sommer Sommer\n", - "453 Alessandro Sorrentino Sorrentino\n", - "454 Wojciech Szczęsny Szczesny\n", - "455 Pietro Terracciano Terracciano\n", - "456 Stefano Turati Turati\n" + "1 Yacine Adli Adli\n", + "2 Michel Aebischer Aebischer\n", + "3 Jean-Daniel Akpa-Akpro Akpa-Akpro\n", + "4 Luis Alberto Alberto\n", + "5 Pontus Almqvist Almqvist\n", + "6 Lorenzo Amatucci Amatucci\n", + "7 Bruno Amione Amione\n", + "8 Felipe Anderson Anderson\n", + "9 Houssem Aouar Aouar\n", + "10 Marko Arnautović Arnautovic\n", + "11 Kristjan Asllani Asllani\n", + "12 Tommaso Augello Augello\n", + "13 Yann Aurel Bisseck Bisseck\n", + "14 Sardar Azmoun Azmoun\n", + "15 Paulo Azzi Azzi\n", + "16 Oussama El Azzouzi Azzouzi\n", + "17 Milan Badelj Badelj\n", + "18 Jaime Báez Baez\n", + "19 Nedim Bajrami Bajrami\n", + "20 Mitchel Bakker Bakker\n", + "21 Tommaso Baldanzi Baldanzi\n", + "22 Lameck Banda Banda\n", + "23 Mattia Bani Bani\n", + "24 Antonín Barák Barak\n", + "25 Nicolò Barella Barella\n", + "26 Enzo Barrenechea Barrenechea\n", + "27 Davide Bartesaghi Bartesaghi\n", + "28 Federico Baschirotto Baschirotto\n", + "29 Alessandro Bastoni Bastoni\n", + "30 Simone Bastoni Bastoni\n", + "31 Raoul Bellanova Bellanova\n", + "32 Andrea Belotti Belotti\n", + "33 Lucas Beltrán Beltran\n", + "34 Domenico Berardi Berardi\n", + "35 Bartosz Bereszyński Bereszynski\n", + "36 Etrit Berisha Berisha\n", + "37 Victor Bernth Kristiansen Kristiansen\n", + "38 Beto Beto\n", + "39 Sam Beukema Beukema\n", + "40 Jaka Bijol Bijol\n", + "41 Cristiano Biraghi Biraghi\n", + "42 Davide Biraschi Biraschi\n", + "43 Samuele Birindelli Birindelli\n", + "44 Alexis Blin Blin\n", + "45 Emil Bohinen Bohinen\n", + "46 Daniel Boloca Boloca\n", + "47 Giacomo Bonaventura Bonaventura\n", + "48 Federico Bonazzoli Bonazzoli\n", + "49 Warren Bondo Bondo\n", + "50 Gennaro Borrelli Borrelli\n", + "51 Erik Botheim Botheim\n", + "52 Mehdi Bourabia Bourabia\n", + "53 Edoardo Bove Bove\n", + "54 Domagoj Bradarić Bradaric\n", + "55 Josip Brekalo Brekalo\n", + "56 Gleison Bremer Bremer\n", + "57 Marco Brescianini Brescianini\n", + "58 Alessandro Buongiorno Buongiorno\n", + "59 Rareș-Cătălin Burnete Burnete\n", + "60 Juan Cabal Cabal\n", + "61 Jovane Cabral Cabral\n", + "62 Liberato Cacace Cacace\n", + "63 Jens Cajuste Cajuste\n", + "64 Davide Calabria Calabria\n", + "65 Riccardo Calafiori Calafiori\n", + "66 Luca Caldirola Caldirola\n", + "67 Hakan Çalhanoğlu Calhanoglu\n", + "68 Nicolò Cambiaghi Cambiaghi\n", + "69 Andrea Cambiaso Cambiaso\n", + "70 Matteo Cancellieri Cancellieri\n", + "71 Antonio Candreva Candreva\n", + "72 Luigi Canotto Canotto\n", + "73 Gianluca Caprari Caprari\n", + "74 Elia Caprile Caprile\n", + "75 Francesco Caputo Caputo\n", + "76 Andrea Carboni Carboni\n", + "77 Valentin Carboni Carboni\n", + "78 Carlos Carlos\n", + "79 Marco Carnesecchi Carnesecchi\n", + "80 Nicolò Casale Casale\n", + "81 Giuseppe Caso Caso\n", + "82 Valentín Castellanos Castellanos\n", + "83 Samu Castillejo Castillejo\n", + "84 Danilo Cataldi Cataldi\n", + "85 Emil Ceide Ceide\n", + "86 Zeki Çelik Celik\n", + "87 Michele Cerofolini Cerofolini\n", + "88 Walid Cheddira Cheddira\n", + "89 Federico Chiesa Chiesa\n", + "90 Oliver Christensen Christensen\n", + "91 Samuel Chukwueze Chukwueze\n", + "92 Patrick Ciurria Ciurria\n", + "93 Lorenzo Colombo Colombo\n", + "94 Andrea Colpani Colpani\n", + "95 Andrea Consigli Consigli\n", + "96 Diego Coppola Coppola\n", + "97 Tommaso Corazza Corazza\n", + "98 Lassana Coulibaly Coulibaly\n", + "99 Mamadou Coulibaly Coulibaly\n", + "100 Alessio Cragno Cragno\n", + "101 Bryan Cristante Cristante\n", + "102 Juan Cuadrado Cuadrado\n", + "103 Marvin Cuni Cuni\n", + "104 Danilo D'Ambrosio DAmbrosio\n", + "105 Flavius Daniliuc Daniliuc\n", + "106 Danilo Danilo\n", + "107 Matteo Darmian Darmian\n", + "108 Paweł Dawidowicz Dawidowicz\n", + "109 Charles De Ketelaere Ketelaere\n", + "110 Lorenzo De Silvestri Silvestri\n", + "111 Koni De Winter Winter\n", + "112 Grégoire Defrel Defrel\n", + "113 Alessandro Deiola Deiola\n", + "114 Mattia Destro Destro\n", + "115 Federico Di Francesco Francesco\n", + "116 Michele Di Gregorio Gregorio\n", + "117 Giovanni Di Lorenzo Lorenzo\n", + "118 Alessandro Di Pardo Pardo\n", + "119 Boulaye Dia Dia\n", + "120 Federico Dimarco Dimarco\n", + "121 Berat Djimsiti Djimsiti\n", + "122 Dodô Dodo\n", + "123 Josh Doig Doig\n", + "124 Nicolás Domínguez Dominguez\n", + "125 Patrick Dorgu Dorgu\n", + "126 Alberto Dossena Dossena\n", + "127 Radu Drăgușin Dragusin\n", + "128 Ondrej Duda Duda\n", + "129 Denzel Dumfries Dumfries\n", + "130 Alfred Duncan Duncan\n", + "131 Paulo Dybala Dybala\n", + "132 Festy Ebosele Ebosele\n", + "133 Enzo Ebosse Ebosse\n", + "134 Tyronne Ebuehi Ebuehi\n", + "135 Éderson Ederson\n", + "136 Emmanuel Ekong Ekong\n", + "137 Caleb Ekuban Ekuban\n", + "138 Elif Elmas Elmas\n", + "139 Martin Erlic Erlic\n", + "140 Giovanni Fabbian Fabbian\n", + "141 Nicolò Fagioli Fagioli\n", + "142 Wladimiro Falcone Falcone\n", + "143 Davide Faraoni Faraoni\n", + "144 Federico Fazio Fazio\n", + "145 Jacopo Fazzini Fazzini\n", + "146 Lewis Ferguson Ferguson\n", + "147 João Ferreira Ferreira\n", + "148 Alessandro Florenzi Florenzi\n", + "149 Michael Folorunsho Folorunsho\n", + "150 Davide Frattesi Frattesi\n", + "151 Morten Frendrup Frendrup\n", + "152 Remo Freuler Freuler\n", + "153 Roberto Gagliardini Gagliardini\n", + "154 Antonino Gallo Gallo\n", + "155 Luca Garritano Garritano\n", + "156 Federico Gatti Gatti\n", + "157 Francesco Gelli Gelli\n", + "158 Valentin Gendrey Gendrey\n", + "159 Gvidas Gineitis Gineitis\n", + "160 Olivier Giroud Giroud\n", + "161 Edoardo Goldaniga Goldaniga\n", + "162 Joan Gonzàlez Gonzalez\n", + "163 Nicolás González Gonzalez\n", + "164 Alberto Grassi Grassi\n", + "165 Mattéo Guendouzi Guendouzi\n", + "166 Axel Guessand Guessand\n", + "167 Albert Guðmundsson Gumundsson\n", + "168 Emmanuel Gyasi Gyasi\n", + "169 Norbert Gyömbér Gyomber\n", + "170 Nicolas Haas Haas\n", + "171 Abdou Harroui Harroui\n", + "172 Hans Hateboer Hateboer\n", + "173 Pantelis Hatzidiakos Hatzidiakos\n", + "174 Silvan Hefti Hefti\n", + "175 Liam Henderson Henderson\n", + "176 Matheus Henrique Henrique\n", + "177 Thomas Henry Henry\n", + "178 Theo Hernández Hernandez\n", + "179 Isak Hien Hien\n", + "180 Emil Holm Holm\n", + "181 Martin Hongla Hongla\n", + "182 Sydney van Hooijdonk Hooijdonk\n", + "183 Elseid Hysaj Hysaj\n", + "184 Jonathan Ikone Ikone\n", + "185 Chukwubuikem Ikwuemesi Ikwuemesi\n", + "186 Ivan Ilić Ilic\n", + "187 Samuel Iling-Junior Iling-Junior\n", + "188 Ciro Immobile Immobile\n", + "189 Gino Infantino Infantino\n", + "190 Gustav Isaksen Isaksen\n", + "191 Ardian Ismajli Ismajli\n", + "192 Armando Izzo Izzo\n", + "193 Filip Jagiełło Jagieo\n", + "194 Jakub Jankto Jankto\n", + "195 Juan Jesus Jesus\n", + "196 Luka Jović Jovic\n", + "197 Mohamed Kaba Kaba\n", + "198 Christian Kabasele Kabasele\n", + "199 Pierre Kalulu Kalulu\n", + "200 Daichi Kamada Kamada\n", + "201 Hassane Kamara Kamara\n", + "202 Yann Karamoh Karamoh\n", + "203 Jesper Karlsson Karlsson\n", + "204 Rick Karsdorp Karsdorp\n", + "205 Grigoris Kastanos Kastanos\n", + "206 Michael Kayode Kayode\n", + "207 Moise Kean Kean\n", + "208 Simon Kjær Kjr\n", + "209 Davy Klaassen Klaassen\n", + "210 Sead Kolašinac Kolasinac\n", + "211 Teun Koopmeiners Koopmeiners\n", + "212 Filip Kostić Kostic\n", + "213 Christian Kouamé Kouame\n", + "214 Viktor Kovalenko Kovalenko\n", + "215 Thomas Kristensen Kristensen\n", + "216 Nikola Krstović Krstovic\n", + "217 Rade Krunić Krunic\n", + "218 Berkan Kutlu Kutlu\n", + "219 Khvicha Kvaratskhelia Kvaratskhelia\n", + "220 Giorgi Kvernadze Kvernadze\n", + "221 Giorgos Kyriakopoulos Kyriakopoulos\n", + "222 Armand Lauriente Lauriente\n", + "223 Valentino Lazaro Lazaro\n", + "224 Darko Lazović Lazovic\n", + "225 Manuel Lazzari Lazzari\n", + "226 Rafael Leão Leao\n", + "227 Jesper Lindstrøm Lindstrm\n", + "228 Karol Linetty Linetty\n", + "229 Pol Lirola Lirola\n", + "230 Diego Llorente Llorente\n", + "231 Stanislav Lobotka Lobotka\n", + "232 Manuel Locatelli Locatelli\n", + "233 Ruben Loftus-Cheek Loftus-Cheek\n", + "234 Ademola Lookman Lookman\n", + "235 Maxime Lopez Lopez\n", + "236 Maxime Lopez Lopez\n", + "237 Matteo Lovato Lovato\n", + "238 Sandi Lovrić Lovric\n", + "239 Lorenzo Lucca Lucca\n", + "240 Jhon Lucumí Lucumi\n", + "241 José Luis Palomino Palomino\n", + "242 Romelu Lukaku Lukaku\n", + "243 Sebastiano Luperto Luperto\n", + "244 Charalambos Lykogiannis Lykogiannis\n", + "245 Giulio Maggiore Maggiore\n", + "246 Giangiacomo Magnani Magnani\n", + "247 Mike Maignan Maignan\n", + "248 Antoine Makoumbou Makoumbou\n", + "249 Youssef Maleh Maleh\n", + "250 Ruslan Malinovskyi Malinovskyi\n", + "251 Gianluca Mancini Mancini\n", + "252 Rolando Mandragora Mandragora\n", + "253 Riccardo Marchizza Marchizza\n", + "254 Gian Marco Ferrari Ferrari\n", + "255 Pablo Marí Mari\n", + "256 Mirko Marić Maric\n", + "257 Răzvan Marin Marin\n", + "258 Agustín Martegani Martegani\n", + "259 Aarón Martín Martin\n", + "260 Josep Martinez Martinez\n", + "261 Lautaro Martínez Martinez\n", + "262 Lucas Martínez Quarta Quarta\n", + "263 Adam Marušić Marusic\n", + "264 Alan Matturro Matturro\n", + "265 Luca Mazzitelli Mazzitelli\n", + "266 Pasquale Mazzocchi Mazzocchi\n", + "267 Jordi Mboula Mboula\n", + "268 Weston McKennie McKennie\n", + "269 Arthur Melo Melo\n", + "270 Alex Meret Meret\n", + "271 Junior Messias Messias\n", + "272 Nikola Milenković Milenkovic\n", + "273 Arkadiusz Milik Milik\n", + "274 Vanja Milinković-Savić Milinkovic-Savic\n", + "275 Aleksei Miranchuk Miranchuk\n", + "276 Kevin Miranda Miranda\n", + "277 Fabio Miretti Miretti\n", + "278 Filippo Missori Missori\n", + "279 Henrikh Mkhitaryan Mkhitaryan\n", + "280 Ilario Monterisi Monterisi\n", + "281 Lorenzo Montipò Montipo\n", + "282 Nikola Moro Moro\n", + "283 Dany Mota Mota\n", + "284 Samuele Mulattieri Mulattieri\n", + "285 Luis Muriel Muriel\n", + "286 Yunus Musah Musah\n", + "287 Juan Musso Musso\n", + "288 Obite N'Dicka NDicka\n", + "289 Nahitan Nández Nandez\n", + "290 Natan Natan\n", + "291 Michel Ndary Adopo Adopo\n", + "292 Dan Ndoye Ndoye\n", + "293 Cyril Ngonge Ngonge\n", + "294 Rasmus Nissen Nissen\n", + "295 M'Bala Nzola Nzola\n", + "296 Adam Obert Obert\n", + "297 Guillermo Ochoa Ochoa\n", + "298 Noah Okafor Okafor\n", + "299 Caleb Okoli Okoli\n", + "300 Mathías Olivera Olivera\n", + "301 Gaetano Oristanio Oristanio\n", + "302 Riccardo Orsolini Orsolini\n", + "303 Victor Osimhen Osimhen\n", + "304 Remi Oudin Oudin\n", + "305 Anthony Oyono Oyono\n", + "306 Simone Pafundi Pafundi\n", + "307 Riccardo Pagano Pagano\n", + "308 Leandro Paredes Paredes\n", + "309 Fabiano Parisi Parisi\n", + "310 Mario Pašalić Pasalic\n", + "311 Patric Patric\n", + "312 Rui Patrício Patricio\n", + "313 Benjamin Pavard Pavard\n", + "314 Leonardo Pavoletti Pavoletti\n", + "315 Martín Payero Payero\n", + "316 Marcus Pedersen Pedersen\n", + "317 Pedro Pedro\n", + "318 Pietro Pellegri Pellegri\n", + "319 Lorenzo Pellegrini Pellegrini\n", + "320 Luca Pellegrini Pellegrini\n", + "321 Pepín Pepin\n", + "322 Pedro Pereira Pereira\n", + "323 Roberto Pereyra Pereyra\n", + "324 Nehuén Pérez Perez\n", + "325 Mattia Perin Perin\n", + "326 Samuele Perisan Perisan\n", + "327 Matteo Pessina Pessina\n", + "328 Andrea Petagna Petagna\n", + "329 Giuseppe Pezzella Pezzella\n", + "330 Roberto Piccoli Piccoli\n", + "331 Roberto Piccoli Piccoli\n", + "332 Andrea Pinamonti Pinamonti\n", + "333 Lorenzo Pirola Pirola\n", + "334 Tommaso Pobega Pobega\n", + "335 Paul Pogba Pogba\n", + "336 Matteo Politano Politano\n", + "337 Marin Pongračić Pongracic\n", + "338 Stefan Posch Posch\n", + "339 Matteo Prati Prati\n", + "340 Ivan Provedel Provedel\n", + "341 Christian Pulisic Pulisic\n", + "342 George Pușcaș Puscas\n", + "343 Domingos Quina Quina\n", + "344 Adrien Rabiot Rabiot\n", + "345 Uroš Račić Racic\n", + "346 Nemanja Radonjić Radonjic\n", + "347 Boris Radunović Radunovic\n", + "348 Hamza Rafia Rafia\n", + "349 Ylber Ramadani Ramadani\n", + "350 Luca Ranieri Ranieri\n", + "351 Filippo Ranocchia Ranocchia\n", + "352 Giacomo Raspadori Raspadori\n", + "353 Tijjani Reijnders Reijnders\n", + "354 Mateo Retegui Retegui\n", + "355 Samuele Ricci Ricci\n", + "356 Ricardo Rodríguez Rodriguez\n", + "357 Alessio Romagnoli Romagnoli\n", + "358 Simone Romagnoli Romagnoli\n", + "359 Luka Romero Romero\n", + "360 Marten de Roon Roon\n", + "361 Nicolò Rovella Rovella\n", + "362 Amir Rrahmani Rrahmani\n", + "363 Ruan Ruan\n", + "364 Daniele Rugani Rugani\n", + "365 Matteo Ruggeri Ruggeri\n", + "366 Mário Rui Rui\n", + "367 Stefano Sabelli Sabelli\n", + "368 Alexis Saelemaekers Saelemaekers\n", + "369 Lazar Samardzic Samardzic\n", + "370 Junior Sambia Sambia\n", + "371 Antonio Sanabria Sanabria\n", + "372 Renato Sanches Sanches\n", + "373 Alexis Sánchez Sanchez\n", + "374 Alex Sandro Sandro\n", + "375 Nicola Sansone Sansone\n", + "376 Riccardo Saponara Saponara\n", + "377 Saba Sazonov Sazonov\n", + "378 Giorgio Scalvini Scalvini\n", + "379 Gianluca Scamacca Scamacca\n", + "380 Perr Schuurs Schuurs\n", + "381 Demba Seck Seck\n", + "382 Vivaldo Semedo Semedo\n", + "383 Stefano Sensi Sensi\n", + "384 Suat Serdar Serdar\n", + "385 Stephan El Shaarawy Shaarawy\n", + "386 Eldor Shomurodov Shomurodov\n", + "387 Steven Shpendi Shpendi\n", + "388 Marco Silvestri Silvestri\n", + "389 Giovanni Simeone Simeone\n", + "390 Leo Skiri Østigård stigard\n", + "391 Łukasz Skorupski Skorupski\n", + "392 Chris Smalling Smalling\n", + "393 Ola Solbakken Solbakken\n", + "394 Yann Sommer Sommer\n", + "395 Brandon Soppy Soppy\n", + "396 Alessandro Sorrentino Sorrentino\n", + "397 Riccardo Sottil Sottil\n", + "398 Matìas Soulé Soule\n", + "399 Leonardo Spinazzola Spinazzola\n", + "400 Marco Sportiello Sportiello\n", + "401 Gabriel Strefezza Strefezza\n", + "402 Kevin Strootman Strootman\n", + "403 Isaac Success Success\n", + "404 Ibrahim Sulemana Sulemana\n", + "405 Tomáš Suslov Suslov\n", + "406 Wojciech Szczęsny Szczesny\n", + "407 Przemysław Szymiński Szyminski\n", + "408 Adrien Tameze Tameze\n", + "409 Loum Tchaouna Tchaouna\n", + "410 Filippo Terracciano Terracciano\n", + "411 Pietro Terracciano Terracciano\n", + "412 Florian Thauvin Thauvin\n", + "413 Malick Thiaw Thiaw\n", + "414 Morten Thorsby Thorsby\n", + "415 Kristian Thorstvedt Thorstvedt\n", + "416 Marcus Thuram Thuram\n", + "417 Jeremy Toljan Toljan\n", + "418 Rafael Tolói Toloi\n", + "419 Fikayo Tomori Tomori\n", + "420 Ahmed Touba Touba\n", + "421 Stefano Turati Turati\n", + "422 Kacper Urbanski Urbanski\n", + "423 Johan Vásquez Vasquez\n", + "424 Matías Vecino Vecino\n", + "425 Lorenzo Venuti Venuti\n", + "426 Simone Verdi Verdi\n", + "427 Samuele Vignato Vignato\n", + "428 Matías Viña Vina\n", + "429 Nicolas Viola Viola\n", + "430 Mattia Viti Viti\n", + "431 Dušan Vlahović Vlahovic\n", + "432 Nikola Vlašić Vlasic\n", + "433 Mërgim Vojvoda Vojvoda\n", + "434 Cristian Volpato Volpato\n", + "435 Stefan de Vrij Vrij\n", + "436 Walace Walace\n", + "437 Sebastian Walukiewicz Walukiewicz\n", + "438 Timothy Weah Weah\n", + "439 Mateusz Wieteska Wieteska\n", + "440 Kenan Yıldız Yldz\n", + "441 Mattia Zaccagni Zaccagni\n", + "442 Nicola Zalewski Zalewski\n", + "443 Andre-Frank Zambo Anguissa Anguissa\n", + "444 Duván Zapata Zapata\n", + "445 Duván Zapata Zapata\n", + "446 Gabriele Zappa Zappa\n", + "447 Davide Zappacosta Zappacosta\n", + "448 Oier Zarraga Zarraga\n", + "449 Jordan Zemura Zemura\n", + "450 Alessio Zerbin Zerbin\n", + "451 Piotr Zieliński Zielinski\n", + "452 David Zima Zima\n", + "453 Joshua Zirkzee Zirkzee\n", + "454 Zito Zito\n", + "455 Nadir Zortea Zortea\n", + "456 Milan Đurić uric\n", + "457 Mateusz Łęgowski egowski\n", + "458 Etrit Berisha Berisha\n", + "459 Elia Caprile Caprile\n", + "460 Marco Carnesecchi Carnesecchi\n", + "461 Michele Cerofolini Cerofolini\n", + "462 Oliver Christensen Christensen\n", + "463 Andrea Consigli Consigli\n", + "464 Alessio Cragno Cragno\n", + "465 Michele Di Gregorio Gregorio\n", + "466 Wladimiro Falcone Falcone\n", + "467 Mike Maignan Maignan\n", + "468 Josep Martinez Martinez\n", + "469 Alex Meret Meret\n", + "470 Vanja Milinković-Savić Milinkovic-Savic\n", + "471 Lorenzo Montipò Montipo\n", + "472 Juan Musso Musso\n", + "473 Guillermo Ochoa Ochoa\n", + "474 Rui Patrício Patricio\n", + "475 Mattia Perin Perin\n", + "476 Samuele Perisan Perisan\n", + "477 Ivan Provedel Provedel\n", + "478 Boris Radunović Radunovic\n", + "479 Marco Silvestri Silvestri\n", + "480 Łukasz Skorupski Skorupski\n", + "481 Yann Sommer Sommer\n", + "482 Alessandro Sorrentino Sorrentino\n", + "483 Marco Sportiello Sportiello\n", + "484 Wojciech Szczęsny Szczesny\n", + "485 Pietro Terracciano Terracciano\n", + "486 Stefano Turati Turati\n" ] } ], @@ -688,7 +718,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 16, "id": "3e759b1b", "metadata": {}, "outputs": [ @@ -829,7 +859,7 @@ "12 Kristensen Nissen Roma" ] }, - "execution_count": 7, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -858,7 +888,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "id": "f96eaaa1", "metadata": {}, "outputs": [ @@ -1013,7 +1043,7 @@ "[539 rows x 6 columns]" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1052,7 +1082,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 18, "id": "9c50e4b5", "metadata": {}, "outputs": [], @@ -1091,7 +1121,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 19, "id": "18f6c5f2", "metadata": {}, "outputs": [ @@ -1099,7 +1129,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sportiello not found\n", "Mirante not found\n", "Sepe not found\n", "Leali not found\n", @@ -1133,30 +1162,21 @@ "Borbei not found\n", "Okoye not found\n", "Mandas not found\n", - "Pavard not found\n", "Kristensen not found\n", - "Natan not found\n", "Mina not found\n", - "Hateboer not found\n", "Masina not found\n", "Djidji not found\n", "Tressoldi not found\n", "Ehizibue not found\n", "Vogliacco not found\n", - "Ferrari G. not found\n", - "Venuti not found\n", "Gunter not found\n", "Soumaoro not found\n", "Zanoli not found\n", - "Sazonov not found\n", - "Rugani not found\n", "De Sciglio not found\n", "Bonifazi not found\n", "Kumbulla not found\n", - "Daniliuc not found\n", "Haps not found\n", "Cittadini not found\n", - "Kristensen T. not found\n", "Dermaku not found\n", "Tonelli not found\n", "Capradossi not found\n", @@ -1166,7 +1186,6 @@ "Bronn not found\n", "Guarino not found\n", "Smajlovic not found\n", - "Matturro not found\n", "N'guessan not found\n", "Mateus Lusuardi not found\n", "Kalaj not found\n", @@ -1176,23 +1195,15 @@ "Pellegrino not found\n", "Comuzzo not found\n", "Lindstrom not found\n", - "Ikone' not found\n", "Bennacer not found\n", "Castrovilli not found\n", - "Klaassen not found\n", - "Messias not found\n", "Reinier not found\n", "Cajuste not found\n", "Mancosu not found\n", - "Oudin not found\n", "Machin not found\n", "Iling Junior not found\n", - "Bourabia not found\n", - "Saelemaekers not found\n", "Maldini not found\n", - "Ranocchia F. not found\n", "Tchatchoua not found\n", - "Romero L. not found\n", "Basic not found\n", "Gaetano not found\n", "Jagiello not found\n", @@ -1200,33 +1211,26 @@ "Akpa Akpro not found\n", "Hrustic not found\n", "Camara E. not found\n", - "Viola not found\n", "Lulic K. not found\n", "Rog not found\n", "Nicolussi Caviglia not found\n", "Demme not found\n", - "Pafundi not found\n", - "Adli not found\n", "Faticanti not found\n", "Belardinelli not found\n", "Lipani not found\n", "Joselito not found\n", "Legowski not found\n", "Ibrahimovic A. not found\n", - "Sanchez not found\n", "Toure' E. not found\n", "Lapadula not found\n", "Abraham not found\n", "Deulofeu not found\n", - "Henry not found\n", "Luvumbo not found\n", "Brenner not found\n", "Davis K. not found\n", - "Sansone not found\n", "Jovane not found\n", "Alvarez A. not found\n", "Cruz not found\n", - "Puscas not found\n", "Ake' M. not found\n", "Braaf not found\n", "Kallon not found\n", @@ -1240,7 +1244,7 @@ } ], "source": [ - "exceptions = ['pellegrini', 'bastoni'] # exceptions for such players that have the same surname as others (Berardi A., Luca Pellegrini)\n", + "exceptions = ['pellegrini', 'bastoni', 'kristensen'] # exceptions for such players that have the same surname as others (Berardi A., Luca Pellegrini)\n", "\n", "for i in range(fc_players.shape[0]):\n", " if(fc_players['fb_ID'][i] == -1):\n", @@ -1259,7 +1263,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 20, "id": "3b4a36af", "metadata": {}, "outputs": [ @@ -1302,7 +1306,7 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", + " 481\n", " \n", " \n", " 1\n", @@ -1312,7 +1316,7 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", + " 484\n", " \n", " \n", " 2\n", @@ -1322,7 +1326,7 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", + " 469\n", " \n", " \n", " 3\n", @@ -1332,7 +1336,7 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", + " 477\n", " \n", " \n", " 4\n", @@ -1342,7 +1346,7 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", + " 467\n", " \n", " \n", " ...\n", @@ -1362,7 +1366,7 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", + " 387\n", " \n", " \n", " 535\n", @@ -1372,7 +1376,7 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", + " 59\n", " \n", " \n", " 536\n", @@ -1411,14 +1415,14 @@ ], "text/plain": [ " id r name team surname initial fb_ID\n", - "0 2428 P Sommer Inter Sommer 452\n", - "1 453 P Szczesny Juventus Szczesny 454\n", - "2 572 P Meret Napoli Meret 440\n", - "3 2814 P Provedel Lazio Provedel 448\n", - "4 4312 P Maignan Milan Maignan 438\n", + "0 2428 P Sommer Inter Sommer 481\n", + "1 453 P Szczesny Juventus Szczesny 484\n", + "2 572 P Meret Napoli Meret 469\n", + "3 2814 P Provedel Lazio Provedel 477\n", + "4 4312 P Maignan Milan Maignan 467\n", ".. ... .. ... ... ... ... ...\n", - "534 6395 A Shpendi S. Empoli Shpendi S 361\n", - "535 6418 A Burnete Lecce Burnete 55\n", + "534 6395 A Shpendi S. Empoli Shpendi S 387\n", + "535 6418 A Burnete Lecce Burnete 59\n", "536 6419 A Corfitzen Lecce Corfitzen -1\n", "537 6427 A Stewart Salernitana Stewart -1\n", "538 6434 A Yildiz Juventus Yildiz -1\n", @@ -1426,7 +1430,7 @@ "[539 rows x 7 columns]" ] }, - "execution_count": 12, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1445,7 +1449,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 21, "id": "1d73a312", "metadata": {}, "outputs": [ @@ -1453,37 +1457,37 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\2053436513.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy] = 0\n" ] } @@ -1504,7 +1508,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 22, "id": "7acb93e3", "metadata": {}, "outputs": [ @@ -1529,7 +1533,7 @@ " dtype='object')" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1540,7 +1544,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 23, "id": "eb9127a9", "metadata": {}, "outputs": [ @@ -1548,85 +1552,85 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n", - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_2156\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_16756\\127446819.py:4: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n", " fc_players[columns_to_copy[2:]] = 0 # add columns but do not override age and birth_year\n" ] } @@ -1648,7 +1652,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 24, "id": "da977789", "metadata": {}, "outputs": [ @@ -1705,21 +1709,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 30.8\n", - " 29\n", - " 20.7\n", - " 28.3\n", - " 41\n", + " 29.7\n", + " 39\n", + " 20.5\n", + " 27.3\n", + " 59\n", + " 5\n", + " 8.5\n", " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", + " 0.33\n", + " 9.6\n", " \n", " \n", " 1\n", @@ -1729,21 +1733,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 33.1\n", - " 6\n", - " 66.7\n", - " 52.0\n", - " 33\n", + " 33.2\n", + " 16\n", + " 50.0\n", + " 45.8\n", + " 59\n", " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", + " 1.7\n", + " 1\n", + " 0.25\n", + " 8.5\n", " \n", " \n", " 2\n", @@ -1753,21 +1757,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", - " 24.7\n", - " 11\n", + " 24.1\n", + " 21\n", " 0.0\n", - " 20.4\n", - " 27\n", + " 20.5\n", + " 53\n", " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", + " 1.9\n", + " 8\n", + " 1.33\n", + " 17.2\n", " \n", " \n", " 3\n", @@ -1777,21 +1781,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 26.4\n", - " 15\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", + " 28.8\n", + " 29\n", + " 27.6\n", + " 32.3\n", + " 63\n", + " 3\n", + " 4.8\n", + " 7\n", + " 1.17\n", + " 16.0\n", " \n", " \n", " 4\n", @@ -1801,8 +1805,8 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", @@ -1849,10 +1853,10 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0\n", @@ -1873,8 +1877,8 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", @@ -1968,36 +1972,36 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_passes_length_avg gk_goal_kicks \\\n", - "0 1988 0 ... 30.8 29 \n", - "1 1990 0 ... 33.1 6 \n", - "2 1997 0 ... 24.7 11 \n", - "3 1994 0 ... 26.4 15 \n", + "0 1988 0 ... 29.7 39 \n", + "1 1990 0 ... 33.2 16 \n", + "2 1997 0 ... 24.1 21 \n", + "3 1994 0 ... 28.8 29 \n", "4 1995 0 ... 29.2 23 \n", ".. ... ... ... ... ... \n", - "534 2003 3 ... 0.0 0 \n", + "534 2003 5 ... 0.0 0 \n", "535 2004 1 ... 0.0 0 \n", "536 0 0 ... 0.0 0 \n", "537 0 0 ... 0.0 0 \n", "538 0 0 ... 0.0 0 \n", "\n", " gk_pct_goal_kicks_launched gk_goal_kick_length_avg gk_crosses \\\n", - "0 20.7 28.3 41 \n", - "1 66.7 52.0 33 \n", - "2 0.0 20.4 27 \n", - "3 20.0 27.9 48 \n", + "0 20.5 27.3 59 \n", + "1 50.0 45.8 59 \n", + "2 0.0 20.5 53 \n", + "3 27.6 32.3 63 \n", "4 60.9 47.0 52 \n", ".. ... ... ... \n", "534 0.0 0.0 0 \n", @@ -2007,10 +2011,10 @@ "538 0.0 0.0 0 \n", "\n", " gk_crosses_stopped gk_crosses_stopped_pct \\\n", - "0 2 4.9 \n", - "1 1 3.0 \n", - "2 1 3.7 \n", - "3 2 4.2 \n", + "0 5 8.5 \n", + "1 1 1.7 \n", + "2 1 1.9 \n", + "3 3 4.8 \n", "4 12 23.1 \n", ".. ... ... \n", "534 0 0.0 \n", @@ -2020,10 +2024,10 @@ "538 0 0.0 \n", "\n", " gk_def_actions_outside_pen_area gk_def_actions_outside_pen_area_per90 \\\n", - "0 0 0.00 \n", - "1 0 0.00 \n", - "2 7 1.75 \n", - "3 6 1.50 \n", + "0 2 0.33 \n", + "1 1 0.25 \n", + "2 8 1.33 \n", + "3 7 1.17 \n", "4 3 0.75 \n", ".. ... ... \n", "534 0 0.00 \n", @@ -2033,10 +2037,10 @@ "538 0 0.00 \n", "\n", " gk_avg_distance_def_actions \n", - "0 6.5 \n", - "1 9.6 \n", - "2 18.2 \n", - "3 15.7 \n", + "0 9.6 \n", + "1 8.5 \n", + "2 17.2 \n", + "3 16.0 \n", "4 9.8 \n", ".. ... \n", "534 0.0 \n", @@ -2048,7 +2052,7 @@ "[539 rows x 158 columns]" ] }, - "execution_count": 16, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -2067,7 +2071,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 25, "id": "6a0e43cd", "metadata": {}, "outputs": [], @@ -2087,7 +2091,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 26, "id": "61fac91a", "metadata": {}, "outputs": [ @@ -2095,8 +2099,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "vote_avg 6.090909\n", - "vote_std 0.360285\n", + "vote_avg 6.096667\n", + "vote_std 0.387547\n", "dtype: float64\n" ] }, @@ -2128,23 +2132,23 @@ " \n", " \n", " 0\n", - " 6.000000\n", - " 0.000000\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", - " 6.750000\n", - " 0.250000\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", - " 5.750000\n", - " 0.250000\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", - " 6.375000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2153,120 +2157,138 @@ " \n", " \n", " 5\n", - " 5.875000\n", - " 0.544862\n", + " 5.833333\n", + " 0.471405\n", " \n", " \n", " 6\n", - " 6.125000\n", - " 0.216506\n", + " 6.250000\n", + " 0.250000\n", " \n", " \n", " 7\n", " 6.000000\n", - " 0.353553\n", + " 0.288675\n", " \n", " \n", " 8\n", " 6.500000\n", - " 0.707107\n", + " 0.547723\n", " \n", " \n", " 9\n", - " 6.625000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 10\n", - " 5.625000\n", - " 0.414578\n", + " 5.666667\n", + " 0.372678\n", " \n", " \n", " 11\n", - " 5.750000\n", - " 0.250000\n", + " 6.250000\n", + " 0.750000\n", " \n", " \n", " 12\n", - " 5.875000\n", - " 0.819680\n", - " \n", - " \n", - " 13\n", - " 6.500000\n", - " 0.353553\n", - " \n", - " \n", - " 14\n", - " 5.875000\n", - " 0.216506\n", - " \n", - " \n", - " 15\n", - " 6.125000\n", - " 0.649519\n", - " \n", - " \n", - " 16\n", - " 6.333333\n", - " 0.849837\n", - " \n", - " \n", - " 17\n", - " 5.833333\n", - " 0.235702\n", - " \n", - " \n", - " 18\n", - " 6.333333\n", - " 0.235702\n", - " \n", - " \n", - " 19\n", " 6.000000\n", " 0.000000\n", " \n", " \n", - " 20\n", + " 13\n", + " 5.833333\n", + " 0.799305\n", + " \n", + " \n", + " 14\n", + " 6.416667\n", + " 0.343592\n", + " \n", + " \n", + " 15\n", + " 5.916667\n", + " 0.186339\n", + " \n", + " \n", + " 16\n", + " 6.250000\n", + " 0.559017\n", + " \n", + " \n", + " 17\n", + " 6.500000\n", + " 0.707107\n", + " \n", + " \n", + " 18\n", " 6.000000\n", - " 0.500000\n", + " 0.353553\n", + " \n", + " \n", + " 19\n", + " 6.250000\n", + " 0.250000\n", + " \n", + " \n", + " 20\n", + " 6.250000\n", + " 0.250000\n", " \n", " \n", " 21\n", + " 6.000000\n", + " 0.000000\n", + " \n", + " \n", + " 22\n", + " 6.125000\n", + " 0.414578\n", + " \n", + " \n", + " 23\n", " 5.750000\n", " 0.250000\n", " \n", + " \n", + " 24\n", + " 6.250000\n", + " 0.250000\n", + " \n", " \n", "\n", "" ], "text/plain": [ " vote_avg vote_std\n", - "0 6.000000 0.000000\n", - "1 6.750000 0.250000\n", - "2 5.750000 0.250000\n", - "3 6.375000 0.414578\n", + "0 5.833333 0.372678\n", + "1 5.875000 1.138804\n", + "2 5.833333 0.235702\n", + "3 6.416667 0.448764\n", "4 6.000000 0.000000\n", - "5 5.875000 0.544862\n", - "6 6.125000 0.216506\n", - "7 6.000000 0.353553\n", - "8 6.500000 0.707107\n", - "9 6.625000 0.414578\n", - "10 5.625000 0.414578\n", - "11 5.750000 0.250000\n", - "12 5.875000 0.819680\n", - "13 6.500000 0.353553\n", - "14 5.875000 0.216506\n", - "15 6.125000 0.649519\n", - "16 6.333333 0.849837\n", - "17 5.833333 0.235702\n", - "18 6.333333 0.235702\n", - "19 6.000000 0.000000\n", - "20 6.000000 0.500000\n", - "21 5.750000 0.250000" + "5 5.833333 0.471405\n", + "6 6.250000 0.250000\n", + "7 6.000000 0.288675\n", + "8 6.500000 0.547723\n", + "9 6.416667 0.448764\n", + "10 5.666667 0.372678\n", + "11 6.250000 0.750000\n", + "12 6.000000 0.000000\n", + "13 5.833333 0.799305\n", + "14 6.416667 0.343592\n", + "15 5.916667 0.186339\n", + "16 6.250000 0.559017\n", + "17 6.500000 0.707107\n", + "18 6.000000 0.353553\n", + "19 6.250000 0.250000\n", + "20 6.250000 0.250000\n", + "21 6.000000 0.000000\n", + "22 6.125000 0.414578\n", + "23 5.750000 0.250000\n", + "24 6.250000 0.250000" ] }, - "execution_count": 18, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -2305,7 +2327,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 27, "id": "c9312080", "metadata": {}, "outputs": [ @@ -2337,23 +2359,23 @@ " \n", " \n", " 0\n", - " 6.000000\n", - " 0.000000\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", - " 6.750000\n", - " 0.250000\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", - " 5.750000\n", - " 0.250000\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", - " 6.375000\n", - " 0.414578\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2367,28 +2389,28 @@ " \n", " \n", " 534\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -2397,28 +2419,28 @@ ], "text/plain": [ " vote_avg vote_std\n", - "0 6.000000 0.000000\n", - "1 6.750000 0.250000\n", - "2 5.750000 0.250000\n", - "3 6.375000 0.414578\n", + "0 5.833333 0.372678\n", + "1 5.875000 1.138804\n", + "2 5.833333 0.235702\n", + "3 6.416667 0.448764\n", "4 6.000000 0.000000\n", ".. ... ...\n", - "534 5.750000 0.250000\n", - "535 6.000000 0.000000\n", - "536 5.799850 0.000000\n", - "537 6.447669 0.000000\n", - "538 6.437600 0.000000\n", + "534 5.875000 0.216506\n", + "535 6.211157 0.443859\n", + "536 5.482051 0.490718\n", + "537 6.039974 0.448371\n", + "538 5.601015 0.337620\n", "\n", "[539 rows x 2 columns]" ] }, - "execution_count": 19, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "min_votes = 1 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", + "min_votes = 3 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", "\n", "#outfield players\n", "mean_def = 6\n", @@ -2457,7 +2479,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 28, "id": "b2570ce5", "metadata": {}, "outputs": [ @@ -2514,21 +2536,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", + " 20.5\n", + " 27.3\n", + " 59\n", + " 5\n", + " 8.5\n", " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", @@ -2538,21 +2560,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", + " 50.0\n", + " 45.8\n", + " 59\n", " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 1.7\n", + " 1\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", @@ -2562,21 +2584,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", + " 20.5\n", + " 53\n", " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 1.9\n", + " 8\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", @@ -2586,21 +2608,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63\n", + " 3\n", + " 4.8\n", + " 7\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -2610,8 +2632,8 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", @@ -2658,10 +2680,10 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", @@ -2671,8 +2693,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", @@ -2682,8 +2704,8 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", @@ -2695,8 +2717,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", @@ -2719,8 +2741,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", @@ -2743,8 +2765,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", @@ -2767,8 +2789,8 @@ " 0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -2777,36 +2799,36 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_pct_goal_kicks_launched \\\n", - "0 1988 0 ... 20.7 \n", - "1 1990 0 ... 66.7 \n", + "0 1988 0 ... 20.5 \n", + "1 1990 0 ... 50.0 \n", "2 1997 0 ... 0.0 \n", - "3 1994 0 ... 20.0 \n", + "3 1994 0 ... 27.6 \n", "4 1995 0 ... 60.9 \n", ".. ... ... ... ... \n", - "534 2003 3 ... 0.0 \n", + "534 2003 5 ... 0.0 \n", "535 2004 1 ... 0.0 \n", "536 0 0 ... 0.0 \n", "537 0 0 ... 0.0 \n", "538 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 28.3 41 2 \n", - "1 52.0 33 1 \n", - "2 20.4 27 1 \n", - "3 27.9 48 2 \n", + "0 27.3 59 5 \n", + "1 45.8 59 1 \n", + "2 20.5 53 1 \n", + "3 32.3 63 3 \n", "4 47.0 52 12 \n", ".. ... ... ... \n", "534 0.0 0 0 \n", @@ -2816,10 +2838,10 @@ "538 0.0 0 0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.9 0 \n", - "1 3.0 0 \n", - "2 3.7 7 \n", - "3 4.2 6 \n", + "0 8.5 2 \n", + "1 1.7 1 \n", + "2 1.9 8 \n", + "3 4.8 7 \n", "4 23.1 3 \n", ".. ... ... \n", "534 0.0 0 \n", @@ -2829,10 +2851,10 @@ "538 0.0 0 \n", "\n", " gk_def_actions_outside_pen_area_per90 gk_avg_distance_def_actions \\\n", - "0 0.00 6.5 \n", - "1 0.00 9.6 \n", - "2 1.75 18.2 \n", - "3 1.50 15.7 \n", + "0 0.33 9.6 \n", + "1 0.25 8.5 \n", + "2 1.33 17.2 \n", + "3 1.17 16.0 \n", "4 0.75 9.8 \n", ".. ... ... \n", "534 0.00 0.0 \n", @@ -2842,22 +2864,22 @@ "538 0.00 0.0 \n", "\n", " vote_avg vote_std \n", - "0 6.000000 0.000000 \n", - "1 6.750000 0.250000 \n", - "2 5.750000 0.250000 \n", - "3 6.375000 0.414578 \n", + "0 5.833333 0.372678 \n", + "1 5.875000 1.138804 \n", + "2 5.833333 0.235702 \n", + "3 6.416667 0.448764 \n", "4 6.000000 0.000000 \n", ".. ... ... \n", - "534 5.750000 0.250000 \n", - "535 6.000000 0.000000 \n", - "536 5.799850 0.000000 \n", - "537 6.447669 0.000000 \n", - "538 6.437600 0.000000 \n", + "534 5.875000 0.216506 \n", + "535 6.211157 0.443859 \n", + "536 5.482051 0.490718 \n", + "537 6.039974 0.448371 \n", + "538 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 20, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -2870,7 +2892,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 29, "id": "f7620abe", "metadata": {}, "outputs": [ @@ -2880,7 +2902,7 @@ "'gk_games'" ] }, - "execution_count": 21, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -2903,7 +2925,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 30, "id": "700b7a7d", "metadata": {}, "outputs": [ @@ -2911,7 +2933,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sportiello, 0.0\n", + "Carnesecchi, 0.6666666666666667\n", + "Caprile, 0.33333333333333337\n", + "Cragno, 0.6666666666666667\n", + "Perin, 0.6666666666666667\n", + "Christensen O., 0.6666666666666667\n", + "Sportiello, 0.6666666666666667\n", "Mirante, 0.0\n", "Sepe, 0.0\n", "Leali, 0.0\n", @@ -2922,11 +2949,13 @@ "Padelli, 0.0\n", "Scuffet, 0.0\n", "Gollini, 0.0\n", + "Perisan, 0.33333333333333337\n", "Audero, 0.0\n", "Di Gennaro, 0.0\n", "Pinsoglio, 0.0\n", "Aresti, 0.0\n", "Fiorillo, 0.0\n", + "Cerofolini, 0.33333333333333337\n", "Rossi F., 0.0\n", "Costil, 0.0\n", "Ravaglia F., 0.0\n", @@ -2938,6 +2967,7 @@ "Boer, 0.0\n", "Bagnolini, 0.0\n", "Svilar, 0.0\n", + "Sorrentino A., 0.33333333333333337\n", "Martinelli T., 0.0\n", "Popa, 0.0\n", "Stubljar, 0.0\n", @@ -2949,7 +2979,7 @@ } ], "source": [ - "min_gk_games = 1 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", + "min_gk_games = 3 # TO BE UPDATED WHEN SERIE A HAS MORE CALENDAR WEEKS PLAYED\n", "\n", "fc_players_newgk = fc_players.copy()\n", "\n", @@ -2973,7 +3003,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 31, "id": "2d9eee99", "metadata": {}, "outputs": [ @@ -3030,21 +3060,21 @@ " Inter\n", " Sommer\n", " \n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", - " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", + " 2.0\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " 1\n", @@ -3054,21 +3084,21 @@ " Juventus\n", " Szczesny\n", " \n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", - " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", + " 1.0\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " 2\n", @@ -3078,21 +3108,21 @@ " Napoli\n", " Meret\n", " \n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", - " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 20.5\n", + " 53.0\n", + " 1.0\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " 3\n", @@ -3102,21 +3132,21 @@ " Lazio\n", " Provedel\n", " \n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " 4\n", @@ -3126,17 +3156,17 @@ " Milan\n", " Maignan\n", " \n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", " 60.9\n", " 47.0\n", - " 52\n", - " 12\n", + " 52.0\n", + " 12.0\n", " 23.1\n", - " 3\n", + " 3.0\n", " 0.75\n", " 9.8\n", " 6.000000\n", @@ -3174,21 +3204,21 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " 535\n", @@ -3198,21 +3228,21 @@ " Lecce\n", " Burnete\n", " \n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " 536\n", @@ -3229,14 +3259,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " 537\n", @@ -3253,14 +3283,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " 538\n", @@ -3277,14 +3307,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -3293,62 +3323,62 @@ ], "text/plain": [ " id r name team surname initial fb_ID age \\\n", - "0 2428 P Sommer Inter Sommer 452 34-278 \n", - "1 453 P Szczesny Juventus Szczesny 454 33-156 \n", - "2 572 P Meret Napoli Meret 440 26-183 \n", - "3 2814 P Provedel Lazio Provedel 448 29-188 \n", - "4 4312 P Maignan Milan Maignan 438 28-080 \n", + "0 2428 P Sommer Inter Sommer 481 34-287 \n", + "1 453 P Szczesny Juventus Szczesny 484 33-165 \n", + "2 572 P Meret Napoli Meret 469 26-192 \n", + "3 2814 P Provedel Lazio Provedel 477 29-197 \n", + "4 4312 P Maignan Milan Maignan 467 28-089 \n", ".. ... .. ... ... ... ... ... ... \n", - "534 6395 A Shpendi S. Empoli Shpendi S 361 20-125 \n", - "535 6418 A Burnete Lecce Burnete 55 19-233 \n", + "534 6395 A Shpendi S. Empoli Shpendi S 387 20-134 \n", + "535 6418 A Burnete Lecce Burnete 59 19-242 \n", "536 6419 A Corfitzen Lecce Corfitzen -1 0 \n", "537 6427 A Stewart Salernitana Stewart -1 0 \n", "538 6434 A Yildiz Juventus Yildiz -1 0 \n", "\n", " birth_year games ... gk_pct_goal_kicks_launched \\\n", - "0 1988 0 ... 20.7 \n", - "1 1990 0 ... 66.7 \n", + "0 1988 0 ... 20.5 \n", + "1 1990 0 ... 50.0 \n", "2 1997 0 ... 0.0 \n", - "3 1994 0 ... 20.0 \n", + "3 1994 0 ... 27.6 \n", "4 1995 0 ... 60.9 \n", ".. ... ... ... ... \n", - "534 2003 3 ... 0.0 \n", + "534 2003 5 ... 0.0 \n", "535 2004 1 ... 0.0 \n", "536 0 0 ... 0.0 \n", "537 0 0 ... 0.0 \n", "538 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", - "0 28.3 41 2 \n", - "1 52.0 33 1 \n", - "2 20.4 27 1 \n", - "3 27.9 48 2 \n", - "4 47.0 52 12 \n", + "0 27.3 59.0 5.0 \n", + "1 45.8 59.0 1.0 \n", + "2 20.5 53.0 1.0 \n", + "3 32.3 63.0 3.0 \n", + "4 47.0 52.0 12.0 \n", ".. ... ... ... \n", - "534 0.0 0 0 \n", - "535 0.0 0 0 \n", - "536 0.0 0 0 \n", - "537 0.0 0 0 \n", - "538 0.0 0 0 \n", + "534 0.0 0.0 0.0 \n", + "535 0.0 0.0 0.0 \n", + "536 0.0 0.0 0.0 \n", + "537 0.0 0.0 0.0 \n", + "538 0.0 0.0 0.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", - "0 4.9 0 \n", - "1 3.0 0 \n", - "2 3.7 7 \n", - "3 4.2 6 \n", - "4 23.1 3 \n", + "0 8.5 2.0 \n", + "1 1.7 1.0 \n", + "2 1.9 8.0 \n", + "3 4.8 7.0 \n", + "4 23.1 3.0 \n", ".. ... ... \n", - "534 0.0 0 \n", - "535 0.0 0 \n", - "536 0.0 0 \n", - "537 0.0 0 \n", - "538 0.0 0 \n", + "534 0.0 0.0 \n", + "535 0.0 0.0 \n", + "536 0.0 0.0 \n", + "537 0.0 0.0 \n", + "538 0.0 0.0 \n", "\n", " gk_def_actions_outside_pen_area_per90 gk_avg_distance_def_actions \\\n", - "0 0.00 6.5 \n", - "1 0.00 9.6 \n", - "2 1.75 18.2 \n", - "3 1.50 15.7 \n", + "0 0.33 9.6 \n", + "1 0.25 8.5 \n", + "2 1.33 17.2 \n", + "3 1.17 16.0 \n", "4 0.75 9.8 \n", ".. ... ... \n", "534 0.00 0.0 \n", @@ -3358,22 +3388,22 @@ "538 0.00 0.0 \n", "\n", " vote_avg vote_std \n", - "0 6.000000 0.000000 \n", - "1 6.750000 0.250000 \n", - "2 5.750000 0.250000 \n", - "3 6.375000 0.414578 \n", + "0 5.833333 0.372678 \n", + "1 5.875000 1.138804 \n", + "2 5.833333 0.235702 \n", + "3 6.416667 0.448764 \n", "4 6.000000 0.000000 \n", ".. ... ... \n", - "534 5.750000 0.250000 \n", - "535 6.000000 0.000000 \n", - "536 5.799850 0.000000 \n", - "537 6.447669 0.000000 \n", - "538 6.437600 0.000000 \n", + "534 5.875000 0.216506 \n", + "535 6.211157 0.443859 \n", + "536 5.482051 0.490718 \n", + "537 6.039974 0.448371 \n", + "538 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 23, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -3394,7 +3424,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 32, "id": "8336c025", "metadata": {}, "outputs": [], diff --git a/4_player_match_dataset_creation.ipynb b/4_player_match_dataset_creation.ipynb index cf38fbd..a28239c 100644 --- a/4_player_match_dataset_creation.ipynb +++ b/4_player_match_dataset_creation.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "3ecf3676", "metadata": {}, "outputs": [], @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "8a6867a5", "metadata": {}, "outputs": [ @@ -108,482 +108,482 @@ " \n", " Atalanta\n", " Atalanta\n", - " 23.0\n", - " 49.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 8.0\n", + " 24.0\n", + " 50.5\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", " Bologna\n", " Bologna\n", - " 22.0\n", - " 56.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 23.0\n", + " 54.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 3.0\n", " 2.0\n", " 0.0\n", " 1.0\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 71.0\n", + " 70.0\n", + " 16.0\n", " 0.0\n", " 1.0\n", " 0.0\n", - " 207.0\n", - " 34.0\n", - " 46.0\n", - " 42.5\n", + " 292.0\n", + " 47.0\n", + " 73.0\n", + " 39.2\n", " \n", " \n", " Cagliari\n", " Cagliari\n", - " 21.0\n", - " 37.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 22.0\n", + " 38.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 38.0\n", - " 41.0\n", - " 5.0\n", + " 50.0\n", + " 65.0\n", + " 11.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 220.0\n", - " 60.0\n", - " 51.0\n", - " 54.1\n", + " 332.0\n", + " 92.0\n", + " 71.0\n", + " 56.4\n", " \n", " \n", " Empoli\n", " Empoli\n", - " 27.0\n", - " 47.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 60.0\n", - " 42.0\n", - " 8.0\n", + " 28.0\n", + " 45.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 1.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 54.0\n", - " 39.0\n", - " 58.1\n", + " ...\n", + " 84.0\n", + " 74.0\n", + " 10.0\n", + " 1.0\n", + " 0.0\n", + " 0.0\n", + " 313.0\n", + " 82.0\n", + " 60.0\n", + " 57.7\n", " \n", " \n", " Fiorentina\n", " Fiorentina\n", - " 22.0\n", - " 61.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 24.0\n", + " 57.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 9.0\n", - " 7.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 5.0\n", + " 75.0\n", + " 63.0\n", + " 8.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 202.0\n", - " 56.0\n", - " 53.0\n", - " 51.4\n", + " 311.0\n", + " 96.0\n", + " 75.0\n", + " 56.1\n", " \n", " \n", " Frosinone\n", " Frosinone\n", - " 23.0\n", - " 48.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", - " 4.0\n", + " 24.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 9.0\n", + " 5.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 50.0\n", - " 39.0\n", - " 6.0\n", + " 73.0\n", + " 54.0\n", + " 15.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 212.0\n", - " 53.0\n", - " 52.0\n", - " 50.5\n", + " 325.0\n", + " 79.0\n", + " 80.0\n", + " 49.7\n", " \n", " \n", " Genoa\n", " Genoa\n", - " 19.0\n", - " 33.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 3.0\n", + " 22.0\n", + " 34.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 7.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 43.0\n", - " 9.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 200.0\n", - " 46.0\n", + " 67.0\n", " 60.0\n", - " 43.4\n", + " 12.0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", + " 295.0\n", + " 66.0\n", + " 83.0\n", + " 44.3\n", " \n", " \n", " Verona\n", " Hellas Verona\n", - " 21.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 22.0\n", + " 45.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 47.0\n", - " 63.0\n", - " 7.0\n", + " 84.0\n", + " 84.0\n", + " 11.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 190.0\n", - " 71.0\n", - " 82.0\n", - " 46.4\n", + " 326.0\n", + " 116.0\n", + " 117.0\n", + " 49.8\n", " \n", " \n", " Inter\n", " Inter\n", - " 19.0\n", - " 48.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 13.0\n", - " 11.0\n", + " 22.0\n", + " 53.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 15.0\n", + " 12.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 47.0\n", - " 44.0\n", - " 5.0\n", + " 70.0\n", + " 64.0\n", + " 9.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 163.0\n", - " 30.0\n", - " 44.0\n", - " 40.5\n", + " 248.0\n", + " 46.0\n", + " 77.0\n", + " 37.4\n", " \n", " \n", " Juventus\n", " Juventus\n", - " 21.0\n", - " 48.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", + " 22.0\n", + " 50.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", " 9.0\n", - " 7.0\n", " 1.0\n", " 2.0\n", " ...\n", - " 52.0\n", - " 49.0\n", - " 5.0\n", + " 80.0\n", + " 71.0\n", + " 6.0\n", " 0.0\n", " 2.0\n", - " 0.0\n", - " 173.0\n", - " 26.0\n", + " 1.0\n", + " 267.0\n", + " 41.0\n", + " 67.0\n", " 38.0\n", - " 40.6\n", " \n", " \n", " Lazio\n", " Lazio\n", " 20.0\n", - " 56.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 4.0\n", - " 4.0\n", - " 0.0\n", - " 0.0\n", - " ...\n", - " 49.0\n", - " 44.0\n", + " 54.0\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 7.0\n", + " 6.0\n", + " 1.0\n", + " 1.0\n", + " ...\n", + " 69.0\n", + " 67.0\n", + " 10.0\n", " 0.0\n", + " 1.0\n", " 0.0\n", - " 0.0\n", - " 196.0\n", - " 51.0\n", - " 30.0\n", - " 63.0\n", + " 282.0\n", + " 66.0\n", + " 53.0\n", + " 55.5\n", " \n", " \n", " Lecce\n", " Lecce\n", - " 19.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 7.0\n", - " 5.0\n", + " 22.0\n", + " 46.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 8.0\n", + " 6.0\n", " 2.0\n", " 2.0\n", " ...\n", - " 64.0\n", - " 53.0\n", + " 88.0\n", + " 78.0\n", " 5.0\n", " 0.0\n", " 2.0\n", " 0.0\n", - " 203.0\n", - " 43.0\n", - " 54.0\n", - " 44.3\n", + " 295.0\n", + " 67.0\n", + " 73.0\n", + " 47.9\n", " \n", " \n", " Milan\n", " Milan\n", - " 19.0\n", - " 55.3\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 9.0\n", + " 23.0\n", + " 56.8\n", " 6.0\n", + " 66.0\n", + " 540.0\n", + " 13.0\n", + " 8.0\n", " 3.0\n", " 3.0\n", " ...\n", - " 56.0\n", - " 43.0\n", - " 7.0\n", + " 80.0\n", + " 60.0\n", + " 8.0\n", " 1.0\n", " 3.0\n", " 0.0\n", - " 176.0\n", - " 42.0\n", - " 33.0\n", - " 56.0\n", + " 281.0\n", + " 65.0\n", + " 61.0\n", + " 51.6\n", " \n", " \n", " Monza\n", " Monza\n", - " 22.0\n", - " 56.8\n", + " 23.0\n", + " 54.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 37.0\n", - " 52.0\n", - " 6.0\n", - " 1.0\n", + " 65.0\n", + " 68.0\n", + " 11.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", - " 187.0\n", - " 45.0\n", - " 37.0\n", - " 54.9\n", + " 281.0\n", + " 74.0\n", + " 56.0\n", + " 56.9\n", " \n", " \n", " Napoli\n", " Napoli\n", - " 19.0\n", - " 61.8\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.0\n", - " 5.0\n", - " 1.0\n", - " 2.0\n", - " ...\n", - " 47.0\n", - " 39.0\n", + " 20.0\n", + " 60.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", " 7.0\n", - " 1.0\n", " 2.0\n", + " 4.0\n", + " ...\n", + " 73.0\n", + " 60.0\n", + " 9.0\n", + " 1.0\n", + " 4.0\n", " 0.0\n", - " 173.0\n", - " 35.0\n", - " 47.0\n", - " 42.7\n", + " 254.0\n", + " 52.0\n", + " 56.0\n", + " 48.1\n", " \n", " \n", " Roma\n", " Roma\n", " 23.0\n", - " 57.0\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 10.0\n", - " 8.0\n", + " 59.7\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 9.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", + " 58.0\n", + " 67.0\n", " 4.0\n", " 1.0\n", " 1.0\n", " 1.0\n", - " 159.0\n", - " 54.0\n", - " 76.0\n", - " 41.5\n", + " 267.0\n", + " 83.0\n", + " 104.0\n", + " 44.4\n", " \n", " \n", " Salernitana\n", " Salernitana\n", - " 21.0\n", - " 51.5\n", + " 22.0\n", + " 52.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.0\n", " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", + " 94.0\n", + " 70.0\n", + " 12.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 203.0\n", - " 86.0\n", - " 54.0\n", - " 61.4\n", + " 311.0\n", + " 120.0\n", + " 82.0\n", + " 59.4\n", " \n", " \n", " Sassuolo\n", " Sassuolo\n", - " 24.0\n", - " 43.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 4.0\n", + " 25.0\n", + " 42.3\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.0\n", " 1.0\n", " 1.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.0\n", + " 55.0\n", + " 20.0\n", " 2.0\n", " 1.0\n", - " 0.0\n", - " 207.0\n", - " 50.0\n", - " 37.0\n", - " 57.5\n", + " 1.0\n", + " 299.0\n", + " 85.0\n", + " 55.0\n", + " 60.7\n", " \n", " \n", " Torino\n", " Torino\n", - " 22.0\n", - " 51.3\n", + " 23.0\n", + " 49.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.0\n", - " 3.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 44.0\n", - " 48.0\n", + " 61.0\n", + " 64.0\n", " 7.0\n", " 1.0\n", " 0.0\n", " 0.0\n", - " 207.0\n", - " 63.0\n", - " 59.0\n", - " 51.6\n", + " 302.0\n", + " 93.0\n", + " 82.0\n", + " 53.1\n", " \n", " \n", " Udinese\n", " Udinese\n", - " 22.0\n", - " 48.5\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.0\n", - " 1.0\n", + " 24.0\n", + " 46.2\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.0\n", " 0.0\n", " 0.0\n", " ...\n", - " 43.0\n", - " 51.0\n", - " 10.0\n", + " 65.0\n", + " 74.0\n", + " 11.0\n", + " 1.0\n", " 0.0\n", " 0.0\n", - " 0.0\n", - " 188.0\n", - " 52.0\n", - " 64.0\n", - " 44.8\n", + " 297.0\n", + " 68.0\n", + " 101.0\n", + " 40.2\n", " \n", " \n", "\n", @@ -593,95 +593,95 @@ "text/plain": [ " team team_players_used team_possession team_games \\\n", "team_idx \n", - "Atalanta Atalanta 23.0 49.5 4.0 \n", - "Bologna Bologna 22.0 56.5 4.0 \n", - "Cagliari Cagliari 21.0 37.8 4.0 \n", - "Empoli Empoli 27.0 47.8 4.0 \n", - "Fiorentina Fiorentina 22.0 61.0 4.0 \n", - "Frosinone Frosinone 23.0 48.3 4.0 \n", - "Genoa Genoa 19.0 33.3 4.0 \n", - "Verona Hellas Verona 21.0 43.5 4.0 \n", - "Inter Inter 19.0 48.8 4.0 \n", - "Juventus Juventus 21.0 48.8 4.0 \n", - "Lazio Lazio 20.0 56.0 4.0 \n", - "Lecce Lecce 19.0 43.5 4.0 \n", - "Milan Milan 19.0 55.3 4.0 \n", - "Monza Monza 22.0 56.8 4.0 \n", - "Napoli Napoli 19.0 61.8 4.0 \n", - "Roma Roma 23.0 57.0 4.0 \n", - "Salernitana Salernitana 21.0 51.5 4.0 \n", - "Sassuolo Sassuolo 24.0 43.5 4.0 \n", - "Torino Torino 22.0 51.3 4.0 \n", - "Udinese Udinese 22.0 48.5 4.0 \n", + "Atalanta Atalanta 24.0 50.5 6.0 \n", + "Bologna Bologna 23.0 54.7 6.0 \n", + "Cagliari Cagliari 22.0 38.2 6.0 \n", + "Empoli Empoli 28.0 45.3 6.0 \n", + "Fiorentina Fiorentina 24.0 57.2 6.0 \n", + "Frosinone Frosinone 24.0 49.2 6.0 \n", + "Genoa Genoa 22.0 34.3 6.0 \n", + "Verona Hellas Verona 22.0 45.2 6.0 \n", + "Inter Inter 22.0 53.2 6.0 \n", + "Juventus Juventus 22.0 50.3 6.0 \n", + "Lazio Lazio 20.0 54.0 6.0 \n", + "Lecce Lecce 22.0 46.7 6.0 \n", + "Milan Milan 23.0 56.8 6.0 \n", + "Monza Monza 23.0 54.2 6.0 \n", + "Napoli Napoli 20.0 60.7 6.0 \n", + "Roma Roma 23.0 59.7 6.0 \n", + "Salernitana Salernitana 22.0 52.3 6.0 \n", + "Sassuolo Sassuolo 25.0 42.3 6.0 \n", + "Torino Torino 23.0 49.2 6.0 \n", + "Udinese Udinese 24.0 46.2 6.0 \n", "\n", " team_games_starts team_minutes team_goals team_assists \\\n", "team_idx \n", - "Atalanta 44.0 360.0 8.0 8.0 \n", - "Bologna 44.0 360.0 3.0 2.0 \n", - "Cagliari 44.0 360.0 1.0 1.0 \n", - "Empoli 44.0 360.0 0.0 0.0 \n", - "Fiorentina 44.0 360.0 9.0 7.0 \n", - "Frosinone 44.0 360.0 7.0 4.0 \n", - "Genoa 44.0 360.0 4.0 3.0 \n", - "Verona 44.0 360.0 4.0 2.0 \n", - "Inter 44.0 360.0 13.0 11.0 \n", - "Juventus 44.0 360.0 9.0 7.0 \n", - "Lazio 44.0 360.0 4.0 4.0 \n", - "Lecce 44.0 360.0 7.0 5.0 \n", - "Milan 44.0 360.0 9.0 6.0 \n", - "Monza 44.0 360.0 3.0 3.0 \n", - "Napoli 44.0 360.0 8.0 5.0 \n", - "Roma 44.0 360.0 10.0 8.0 \n", - "Salernitana 44.0 360.0 3.0 3.0 \n", - "Sassuolo 44.0 360.0 5.0 4.0 \n", - "Torino 44.0 360.0 5.0 3.0 \n", - "Udinese 44.0 360.0 1.0 1.0 \n", + "Atalanta 66.0 540.0 11.0 11.0 \n", + "Bologna 66.0 540.0 3.0 2.0 \n", + "Cagliari 66.0 540.0 2.0 2.0 \n", + "Empoli 66.0 540.0 1.0 1.0 \n", + "Fiorentina 66.0 540.0 12.0 9.0 \n", + "Frosinone 66.0 540.0 9.0 5.0 \n", + "Genoa 66.0 540.0 8.0 7.0 \n", + "Verona 66.0 540.0 4.0 2.0 \n", + "Inter 66.0 540.0 15.0 12.0 \n", + "Juventus 66.0 540.0 11.0 9.0 \n", + "Lazio 66.0 540.0 7.0 6.0 \n", + "Lecce 66.0 540.0 8.0 6.0 \n", + "Milan 66.0 540.0 13.0 8.0 \n", + "Monza 66.0 540.0 4.0 3.0 \n", + "Napoli 66.0 540.0 12.0 7.0 \n", + "Roma 66.0 540.0 12.0 9.0 \n", + "Salernitana 66.0 540.0 4.0 3.0 \n", + "Sassuolo 66.0 540.0 10.0 7.0 \n", + "Torino 66.0 540.0 6.0 4.0 \n", + "Udinese 66.0 540.0 2.0 2.0 \n", "\n", " team_pens_made team_pens_att ... vs_team_fouls \\\n", "team_idx ... \n", - "Atalanta 0.0 0.0 ... 36.0 \n", - "Bologna 0.0 1.0 ... 50.0 \n", - "Cagliari 0.0 0.0 ... 38.0 \n", - "Empoli 0.0 0.0 ... 60.0 \n", - "Fiorentina 0.0 0.0 ... 56.0 \n", - "Frosinone 2.0 2.0 ... 50.0 \n", - "Genoa 0.0 0.0 ... 43.0 \n", - "Verona 0.0 0.0 ... 47.0 \n", - "Inter 2.0 2.0 ... 47.0 \n", - "Juventus 1.0 2.0 ... 52.0 \n", - "Lazio 0.0 0.0 ... 49.0 \n", - "Lecce 2.0 2.0 ... 64.0 \n", - "Milan 3.0 3.0 ... 56.0 \n", - "Monza 0.0 0.0 ... 37.0 \n", - "Napoli 1.0 2.0 ... 47.0 \n", - "Roma 1.0 1.0 ... 46.0 \n", - "Salernitana 0.0 0.0 ... 64.0 \n", - "Sassuolo 1.0 1.0 ... 45.0 \n", - "Torino 0.0 0.0 ... 44.0 \n", - "Udinese 0.0 0.0 ... 43.0 \n", + "Atalanta 0.0 0.0 ... 57.0 \n", + "Bologna 0.0 1.0 ... 71.0 \n", + "Cagliari 0.0 0.0 ... 50.0 \n", + "Empoli 0.0 0.0 ... 84.0 \n", + "Fiorentina 0.0 0.0 ... 75.0 \n", + "Frosinone 2.0 2.0 ... 73.0 \n", + "Genoa 0.0 0.0 ... 67.0 \n", + "Verona 0.0 0.0 ... 84.0 \n", + "Inter 2.0 2.0 ... 70.0 \n", + "Juventus 1.0 2.0 ... 80.0 \n", + "Lazio 1.0 1.0 ... 69.0 \n", + "Lecce 2.0 2.0 ... 88.0 \n", + "Milan 3.0 3.0 ... 80.0 \n", + "Monza 0.0 0.0 ... 65.0 \n", + "Napoli 2.0 4.0 ... 73.0 \n", + "Roma 1.0 1.0 ... 58.0 \n", + "Salernitana 0.0 0.0 ... 94.0 \n", + "Sassuolo 1.0 1.0 ... 63.0 \n", + "Torino 0.0 0.0 ... 61.0 \n", + "Udinese 0.0 0.0 ... 65.0 \n", "\n", " vs_team_fouled vs_team_offsides vs_team_pens_won \\\n", "team_idx \n", - "Atalanta 47.0 2.0 0.0 \n", - "Bologna 40.0 12.0 0.0 \n", - "Cagliari 41.0 5.0 0.0 \n", - "Empoli 42.0 8.0 1.0 \n", - "Fiorentina 43.0 5.0 1.0 \n", - "Frosinone 39.0 6.0 0.0 \n", - "Genoa 43.0 9.0 0.0 \n", - "Verona 63.0 7.0 1.0 \n", - "Inter 44.0 5.0 0.0 \n", - "Juventus 49.0 5.0 0.0 \n", - "Lazio 44.0 7.0 0.0 \n", - "Lecce 53.0 5.0 0.0 \n", - "Milan 43.0 7.0 1.0 \n", - "Monza 52.0 6.0 1.0 \n", - "Napoli 39.0 7.0 1.0 \n", - "Roma 51.0 4.0 1.0 \n", - "Salernitana 46.0 4.0 0.0 \n", - "Sassuolo 34.0 15.0 2.0 \n", - "Torino 48.0 7.0 1.0 \n", - "Udinese 51.0 10.0 0.0 \n", + "Atalanta 74.0 4.0 0.0 \n", + "Bologna 70.0 16.0 0.0 \n", + "Cagliari 65.0 11.0 0.0 \n", + "Empoli 74.0 10.0 1.0 \n", + "Fiorentina 63.0 8.0 1.0 \n", + "Frosinone 54.0 15.0 0.0 \n", + "Genoa 60.0 12.0 0.0 \n", + "Verona 84.0 11.0 1.0 \n", + "Inter 64.0 9.0 0.0 \n", + "Juventus 71.0 6.0 0.0 \n", + "Lazio 67.0 10.0 0.0 \n", + "Lecce 78.0 5.0 0.0 \n", + "Milan 60.0 8.0 1.0 \n", + "Monza 68.0 11.0 2.0 \n", + "Napoli 60.0 9.0 1.0 \n", + "Roma 67.0 4.0 1.0 \n", + "Salernitana 70.0 12.0 0.0 \n", + "Sassuolo 55.0 20.0 2.0 \n", + "Torino 64.0 7.0 1.0 \n", + "Udinese 74.0 11.0 1.0 \n", "\n", " vs_team_pens_conceded vs_team_own_goals \\\n", "team_idx \n", @@ -694,68 +694,68 @@ "Genoa 0.0 0.0 \n", "Verona 0.0 0.0 \n", "Inter 2.0 0.0 \n", - "Juventus 2.0 0.0 \n", - "Lazio 0.0 0.0 \n", + "Juventus 2.0 1.0 \n", + "Lazio 1.0 0.0 \n", "Lecce 2.0 0.0 \n", "Milan 3.0 0.0 \n", "Monza 0.0 0.0 \n", - "Napoli 2.0 0.0 \n", + "Napoli 4.0 0.0 \n", "Roma 1.0 1.0 \n", "Salernitana 0.0 0.0 \n", - "Sassuolo 1.0 0.0 \n", + "Sassuolo 1.0 1.0 \n", "Torino 0.0 0.0 \n", "Udinese 0.0 0.0 \n", "\n", " vs_team_ball_recoveries vs_team_aerials_won \\\n", "team_idx \n", - "Atalanta 212.0 65.0 \n", - "Bologna 207.0 34.0 \n", - "Cagliari 220.0 60.0 \n", - "Empoli 203.0 54.0 \n", - "Fiorentina 202.0 56.0 \n", - "Frosinone 212.0 53.0 \n", - "Genoa 200.0 46.0 \n", - "Verona 190.0 71.0 \n", - "Inter 163.0 30.0 \n", - "Juventus 173.0 26.0 \n", - "Lazio 196.0 51.0 \n", - "Lecce 203.0 43.0 \n", - "Milan 176.0 42.0 \n", - "Monza 187.0 45.0 \n", - "Napoli 173.0 35.0 \n", - "Roma 159.0 54.0 \n", - "Salernitana 203.0 86.0 \n", - "Sassuolo 207.0 50.0 \n", - "Torino 207.0 63.0 \n", - "Udinese 188.0 52.0 \n", + "Atalanta 347.0 97.0 \n", + "Bologna 292.0 47.0 \n", + "Cagliari 332.0 92.0 \n", + "Empoli 313.0 82.0 \n", + "Fiorentina 311.0 96.0 \n", + "Frosinone 325.0 79.0 \n", + "Genoa 295.0 66.0 \n", + "Verona 326.0 116.0 \n", + "Inter 248.0 46.0 \n", + "Juventus 267.0 41.0 \n", + "Lazio 282.0 66.0 \n", + "Lecce 295.0 67.0 \n", + "Milan 281.0 65.0 \n", + "Monza 281.0 74.0 \n", + "Napoli 254.0 52.0 \n", + "Roma 267.0 83.0 \n", + "Salernitana 311.0 120.0 \n", + "Sassuolo 299.0 85.0 \n", + "Torino 302.0 93.0 \n", + "Udinese 297.0 68.0 \n", "\n", " vs_team_aerials_lost vs_team_aerials_won_pct \n", "team_idx \n", - "Atalanta 60.0 52.0 \n", - "Bologna 46.0 42.5 \n", - "Cagliari 51.0 54.1 \n", - "Empoli 39.0 58.1 \n", - "Fiorentina 53.0 51.4 \n", - "Frosinone 52.0 50.5 \n", - "Genoa 60.0 43.4 \n", - "Verona 82.0 46.4 \n", - "Inter 44.0 40.5 \n", - "Juventus 38.0 40.6 \n", - "Lazio 30.0 63.0 \n", - "Lecce 54.0 44.3 \n", - "Milan 33.0 56.0 \n", - "Monza 37.0 54.9 \n", - "Napoli 47.0 42.7 \n", - "Roma 76.0 41.5 \n", - "Salernitana 54.0 61.4 \n", - "Sassuolo 37.0 57.5 \n", - "Torino 59.0 51.6 \n", - "Udinese 64.0 44.8 \n", + "Atalanta 109.0 47.1 \n", + "Bologna 73.0 39.2 \n", + "Cagliari 71.0 56.4 \n", + "Empoli 60.0 57.7 \n", + "Fiorentina 75.0 56.1 \n", + "Frosinone 80.0 49.7 \n", + "Genoa 83.0 44.3 \n", + "Verona 117.0 49.8 \n", + "Inter 77.0 37.4 \n", + "Juventus 67.0 38.0 \n", + "Lazio 53.0 55.5 \n", + "Lecce 73.0 47.9 \n", + "Milan 61.0 51.6 \n", + "Monza 56.0 56.9 \n", + "Napoli 56.0 48.1 \n", + "Roma 104.0 44.4 \n", + "Salernitana 82.0 59.4 \n", + "Sassuolo 55.0 60.7 \n", + "Torino 82.0 53.1 \n", + "Udinese 101.0 40.2 \n", "\n", "[20 rows x 303 columns]" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -789,7 +789,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "b6a3db98", "metadata": {}, "outputs": [], @@ -807,7 +807,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "c34eb398", "metadata": {}, "outputs": [ @@ -888,21 +888,21 @@ " Inter\n", " Sommer\n", " NaN\n", - " 452\n", - " 34-278\n", + " 481\n", + " 34-287\n", " 1988\n", " 0\n", " ...\n", - " 20.7\n", - " 28.3\n", - " 41\n", - " 2\n", - " 4.9\n", - " 0\n", - " 0.00\n", - " 6.5\n", - " 6.000000\n", - " 0.000000\n", + " 20.5\n", + " 27.3\n", + " 59.0\n", + " 5.0\n", + " 8.5\n", + " 2.0\n", + " 0.33\n", + " 9.6\n", + " 5.833333\n", + " 0.372678\n", " \n", " \n", " Szczesny\n", @@ -912,21 +912,21 @@ " Juventus\n", " Szczesny\n", " NaN\n", - " 454\n", - " 33-156\n", + " 484\n", + " 33-165\n", " 1990\n", " 0\n", " ...\n", - " 66.7\n", - " 52.0\n", - " 33\n", - " 1\n", - " 3.0\n", - " 0\n", - " 0.00\n", - " 9.6\n", - " 6.750000\n", - " 0.250000\n", + " 50.0\n", + " 45.8\n", + " 59.0\n", + " 1.0\n", + " 1.7\n", + " 1.0\n", + " 0.25\n", + " 8.5\n", + " 5.875000\n", + " 1.138804\n", " \n", " \n", " Meret\n", @@ -936,21 +936,21 @@ " Napoli\n", " Meret\n", " NaN\n", - " 440\n", - " 26-183\n", + " 469\n", + " 26-192\n", " 1997\n", " 0\n", " ...\n", " 0.0\n", - " 20.4\n", - " 27\n", - " 1\n", - " 3.7\n", - " 7\n", - " 1.75\n", - " 18.2\n", - " 5.750000\n", - " 0.250000\n", + " 20.5\n", + " 53.0\n", + " 1.0\n", + " 1.9\n", + " 8.0\n", + " 1.33\n", + " 17.2\n", + " 5.833333\n", + " 0.235702\n", " \n", " \n", " Provedel\n", @@ -960,21 +960,21 @@ " Lazio\n", " Provedel\n", " NaN\n", - " 448\n", - " 29-188\n", + " 477\n", + " 29-197\n", " 1994\n", " 0\n", " ...\n", - " 20.0\n", - " 27.9\n", - " 48\n", - " 2\n", - " 4.2\n", - " 6\n", - " 1.50\n", - " 15.7\n", - " 6.375000\n", - " 0.414578\n", + " 27.6\n", + " 32.3\n", + " 63.0\n", + " 3.0\n", + " 4.8\n", + " 7.0\n", + " 1.17\n", + " 16.0\n", + " 6.416667\n", + " 0.448764\n", " \n", " \n", " Maignan\n", @@ -984,17 +984,17 @@ " Milan\n", " Maignan\n", " NaN\n", - " 438\n", - " 28-080\n", + " 467\n", + " 28-089\n", " 1995\n", " 0\n", " ...\n", " 60.9\n", " 47.0\n", - " 52\n", - " 12\n", + " 52.0\n", + " 12.0\n", " 23.1\n", - " 3\n", + " 3.0\n", " 0.75\n", " 9.8\n", " 6.000000\n", @@ -1032,21 +1032,21 @@ " Empoli\n", " Shpendi\n", " S\n", - " 361\n", - " 20-125\n", + " 387\n", + " 20-134\n", " 2003\n", - " 3\n", + " 5\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.750000\n", - " 0.250000\n", + " 5.875000\n", + " 0.216506\n", " \n", " \n", " Burnete\n", @@ -1056,21 +1056,21 @@ " Lecce\n", " Burnete\n", " NaN\n", - " 55\n", - " 19-233\n", + " 59\n", + " 19-242\n", " 2004\n", " 1\n", " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.000000\n", - " 0.000000\n", + " 6.211157\n", + " 0.443859\n", " \n", " \n", " Corfitzen\n", @@ -1087,14 +1087,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 5.799850\n", - " 0.000000\n", + " 5.482051\n", + " 0.490718\n", " \n", " \n", " Stewart\n", @@ -1111,14 +1111,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.447669\n", - " 0.000000\n", + " 6.039974\n", + " 0.448371\n", " \n", " \n", " Yildiz\n", @@ -1135,14 +1135,14 @@ " ...\n", " 0.0\n", " 0.0\n", - " 0\n", - " 0\n", " 0.0\n", - " 0\n", + " 0.0\n", + " 0.0\n", + " 0.0\n", " 0.00\n", " 0.0\n", - " 6.437600\n", - " 0.000000\n", + " 5.601015\n", + " 0.337620\n", " \n", " \n", "\n", @@ -1152,66 +1152,66 @@ "text/plain": [ " Unnamed: 0 id r team surname initial fb_ID \\\n", "name \n", - "Sommer 0 2428 P Inter Sommer NaN 452 \n", - "Szczesny 1 453 P Juventus Szczesny NaN 454 \n", - "Meret 2 572 P Napoli Meret NaN 440 \n", - "Provedel 3 2814 P Lazio Provedel NaN 448 \n", - "Maignan 4 4312 P Milan Maignan NaN 438 \n", + "Sommer 0 2428 P Inter Sommer NaN 481 \n", + "Szczesny 1 453 P Juventus Szczesny NaN 484 \n", + "Meret 2 572 P Napoli Meret NaN 469 \n", + "Provedel 3 2814 P Lazio Provedel NaN 477 \n", + "Maignan 4 4312 P Milan Maignan NaN 467 \n", "... ... ... .. ... ... ... ... \n", - "Shpendi S. 534 6395 A Empoli Shpendi S 361 \n", - "Burnete 535 6418 A Lecce Burnete NaN 55 \n", + "Shpendi S. 534 6395 A Empoli Shpendi S 387 \n", + "Burnete 535 6418 A Lecce Burnete NaN 59 \n", "Corfitzen 536 6419 A Lecce Corfitzen NaN -1 \n", "Stewart 537 6427 A Salernitana Stewart NaN -1 \n", "Yildiz 538 6434 A Juventus Yildiz NaN -1 \n", "\n", " age birth_year games ... gk_pct_goal_kicks_launched \\\n", "name ... \n", - "Sommer 34-278 1988 0 ... 20.7 \n", - "Szczesny 33-156 1990 0 ... 66.7 \n", - "Meret 26-183 1997 0 ... 0.0 \n", - "Provedel 29-188 1994 0 ... 20.0 \n", - "Maignan 28-080 1995 0 ... 60.9 \n", + "Sommer 34-287 1988 0 ... 20.5 \n", + "Szczesny 33-165 1990 0 ... 50.0 \n", + "Meret 26-192 1997 0 ... 0.0 \n", + "Provedel 29-197 1994 0 ... 27.6 \n", + "Maignan 28-089 1995 0 ... 60.9 \n", "... ... ... ... ... ... \n", - "Shpendi S. 20-125 2003 3 ... 0.0 \n", - "Burnete 19-233 2004 1 ... 0.0 \n", + "Shpendi S. 20-134 2003 5 ... 0.0 \n", + "Burnete 19-242 2004 1 ... 0.0 \n", "Corfitzen 0 0 0 ... 0.0 \n", "Stewart 0 0 0 ... 0.0 \n", "Yildiz 0 0 0 ... 0.0 \n", "\n", " gk_goal_kick_length_avg gk_crosses gk_crosses_stopped \\\n", "name \n", - "Sommer 28.3 41 2 \n", - "Szczesny 52.0 33 1 \n", - "Meret 20.4 27 1 \n", - "Provedel 27.9 48 2 \n", - "Maignan 47.0 52 12 \n", + "Sommer 27.3 59.0 5.0 \n", + "Szczesny 45.8 59.0 1.0 \n", + "Meret 20.5 53.0 1.0 \n", + "Provedel 32.3 63.0 3.0 \n", + "Maignan 47.0 52.0 12.0 \n", "... ... ... ... \n", - "Shpendi S. 0.0 0 0 \n", - "Burnete 0.0 0 0 \n", - "Corfitzen 0.0 0 0 \n", - "Stewart 0.0 0 0 \n", - "Yildiz 0.0 0 0 \n", + "Shpendi S. 0.0 0.0 0.0 \n", + "Burnete 0.0 0.0 0.0 \n", + "Corfitzen 0.0 0.0 0.0 \n", + "Stewart 0.0 0.0 0.0 \n", + "Yildiz 0.0 0.0 0.0 \n", "\n", " gk_crosses_stopped_pct gk_def_actions_outside_pen_area \\\n", "name \n", - "Sommer 4.9 0 \n", - "Szczesny 3.0 0 \n", - "Meret 3.7 7 \n", - "Provedel 4.2 6 \n", - "Maignan 23.1 3 \n", + "Sommer 8.5 2.0 \n", + "Szczesny 1.7 1.0 \n", + "Meret 1.9 8.0 \n", + "Provedel 4.8 7.0 \n", + "Maignan 23.1 3.0 \n", "... ... ... \n", - "Shpendi S. 0.0 0 \n", - "Burnete 0.0 0 \n", - "Corfitzen 0.0 0 \n", - "Stewart 0.0 0 \n", - "Yildiz 0.0 0 \n", + "Shpendi S. 0.0 0.0 \n", + "Burnete 0.0 0.0 \n", + "Corfitzen 0.0 0.0 \n", + "Stewart 0.0 0.0 \n", + "Yildiz 0.0 0.0 \n", "\n", " gk_def_actions_outside_pen_area_per90 \\\n", "name \n", - "Sommer 0.00 \n", - "Szczesny 0.00 \n", - "Meret 1.75 \n", - "Provedel 1.50 \n", + "Sommer 0.33 \n", + "Szczesny 0.25 \n", + "Meret 1.33 \n", + "Provedel 1.17 \n", "Maignan 0.75 \n", "... ... \n", "Shpendi S. 0.00 \n", @@ -1222,22 +1222,22 @@ "\n", " gk_avg_distance_def_actions vote_avg vote_std \n", "name \n", - "Sommer 6.5 6.000000 0.000000 \n", - "Szczesny 9.6 6.750000 0.250000 \n", - "Meret 18.2 5.750000 0.250000 \n", - "Provedel 15.7 6.375000 0.414578 \n", + "Sommer 9.6 5.833333 0.372678 \n", + "Szczesny 8.5 5.875000 1.138804 \n", + "Meret 17.2 5.833333 0.235702 \n", + "Provedel 16.0 6.416667 0.448764 \n", "Maignan 9.8 6.000000 0.000000 \n", "... ... ... ... \n", - "Shpendi S. 0.0 5.750000 0.250000 \n", - "Burnete 0.0 6.000000 0.000000 \n", - "Corfitzen 0.0 5.799850 0.000000 \n", - "Stewart 0.0 6.447669 0.000000 \n", - "Yildiz 0.0 6.437600 0.000000 \n", + "Shpendi S. 0.0 5.875000 0.216506 \n", + "Burnete 0.0 6.211157 0.443859 \n", + "Corfitzen 0.0 5.482051 0.490718 \n", + "Stewart 0.0 6.039974 0.448371 \n", + "Yildiz 0.0 5.601015 0.337620 \n", "\n", "[539 rows x 160 columns]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -1259,7 +1259,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "71c8804e", "metadata": {}, "outputs": [], @@ -1294,7 +1294,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "7eb4e666", "metadata": {}, "outputs": [ @@ -1351,21 +1351,21 @@ " Inter\n", " Barella\n", " NaN\n", - " 23\n", - " 26-226\n", + " 25\n", + " 26-235\n", " 1997\n", - " 4\n", + " 6\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", + " 57.0\n", + " 74.0\n", + " 4.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 212.0\n", - " 65.0\n", - " 60.0\n", - " 52.0\n", + " 347.0\n", + " 97.0\n", + " 109.0\n", + " 47.1\n", " \n", " \n", "\n", @@ -1374,27 +1374,27 @@ ], "text/plain": [ " Unnamed: 0 id r team surname initial fb_ID age \\\n", - "Barella 260 1870 C Inter Barella NaN 23 26-226 \n", + "Barella 260 1870 C Inter Barella NaN 25 26-235 \n", "\n", " birth_year games ... opp_vs_team_fouls opp_vs_team_fouled \\\n", - "Barella 1997 4 ... 36.0 47.0 \n", + "Barella 1997 6 ... 57.0 74.0 \n", "\n", " opp_vs_team_offsides opp_vs_team_pens_won \\\n", - "Barella 2.0 0.0 \n", + "Barella 4.0 0.0 \n", "\n", " opp_vs_team_pens_conceded opp_vs_team_own_goals \\\n", "Barella 0.0 0.0 \n", "\n", " opp_vs_team_ball_recoveries opp_vs_team_aerials_won \\\n", - "Barella 212.0 65.0 \n", + "Barella 347.0 97.0 \n", "\n", " opp_vs_team_aerials_lost opp_vs_team_aerials_won_pct \n", - "Barella 60.0 52.0 \n", + "Barella 109.0 47.1 \n", "\n", "[1 rows x 766 columns]" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -1408,7 +1408,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "6b4c1b00", "metadata": {}, "outputs": [ @@ -1418,7 +1418,7 @@ "'Inter'" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1431,7 +1431,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "6ea6df1f", "metadata": {}, "outputs": [ @@ -1531,7 +1531,7 @@ " 'vs_team_aerials_won_pct']" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -1563,7 +1563,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "47bc651f", "metadata": {}, "outputs": [], @@ -1717,7 +1717,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "3f43d509", "metadata": {}, "outputs": [], @@ -1748,7 +1748,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "930d00c7", "metadata": {}, "outputs": [ @@ -1800,25 +1800,25 @@ " \n", " Barella\n", " C\n", - " 4\n", - " 4\n", - " 281\n", - " 25.0\n", + " 6\n", + " 5\n", + " 391\n", + " 14.3\n", " 0.0\n", " 0.0\n", - " 86.2\n", - " 100.0\n", - " 48.8\n", + " 85.9\n", + " 66.7\n", + " 53.2\n", " ...\n", - " 0.003559\n", - " 0.0\n", - " 0.010676\n", - " 0.010676\n", - " 0.007117\n", - " 0.0\n", - " 0.494662\n", - " 0.024911\n", - " 0.021352\n", + " 0.012788\n", + " 0.005115\n", + " 0.007673\n", + " 0.007673\n", + " 0.005115\n", + " 0.002558\n", + " 0.534527\n", + " 0.028133\n", + " 0.02046\n", " 0.0\n", " \n", " \n", @@ -1828,24 +1828,24 @@ ], "text/plain": [ " r games games_starts minutes shots_on_target_pct goals_per_shot \\\n", - "Barella C 4 4 281 25.0 0.0 \n", + "Barella C 6 5 391 14.3 0.0 \n", "\n", " goals_per_shot_on_target passes_pct aerials_won_pct \\\n", - "Barella 0.0 86.2 100.0 \n", + "Barella 0.0 85.9 66.7 \n", "\n", " team_possession ... miscontrols dispossessed fouls fouled \\\n", - "Barella 48.8 ... 0.003559 0.0 0.010676 0.010676 \n", + "Barella 53.2 ... 0.012788 0.005115 0.007673 0.007673 \n", "\n", " aerials_won aerials_lost carries progressive_carries \\\n", - "Barella 0.007117 0.0 0.494662 0.024911 \n", + "Barella 0.005115 0.002558 0.534527 0.028133 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", - "Barella 0.021352 0.0 \n", + "Barella 0.02046 0.0 \n", "\n", "[1 rows x 112 columns]" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -1868,7 +1868,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "3ae718d2", "metadata": {}, "outputs": [ @@ -1985,11 +1985,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -1998,60 +1998,60 @@ " 5.5\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", + " 4.5\n", " \n", " \n", "\n", - "

1159 rows × 10 columns

\n", + "

1731 rows × 10 columns

\n", "" ], "text/plain": [ @@ -2062,11 +2062,11 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote \n", "0 0.0 6.5 \n", @@ -2075,16 +2075,16 @@ "3 0.0 6.5 \n", "4 0.0 10.0 \n", "... ... ... \n", - "1154 0.5 5.5 \n", - "1155 0.5 5.5 \n", - "1156 0.0 6.0 \n", - "1157 0.0 5.5 \n", - "1158 0.0 5.5 \n", + "1726 0.5 5.5 \n", + "1727 0.0 6.0 \n", + "1728 0.0 5.5 \n", + "1729 0.0 6.0 \n", + "1730 0.5 4.5 \n", "\n", - "[1159 rows x 10 columns]" + "[1731 rows x 10 columns]" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -2104,7 +2104,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "ec0bc56b", "metadata": {}, "outputs": [ @@ -2123,7 +2123,13 @@ "800\n", "900\n", "1000\n", - "1100\n" + "1100\n", + "1200\n", + "1300\n", + "1400\n", + "1500\n", + "1600\n", + "1700\n" ] } ], @@ -2151,7 +2157,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "b292f9f9", "metadata": {}, "outputs": [ @@ -2237,16 +2243,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 2\n", @@ -2261,13 +2267,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -2285,16 +2291,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 4\n", @@ -2345,11 +2351,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -2357,116 +2363,116 @@ " 0.5\n", " 5.5\n", " ...\n", - " 0.028846\n", - " 0.009615\n", - " 0.019231\n", - " 0.000000\n", - " 0.009615\n", - " 0.038462\n", - " 0.182692\n", - " 0.000000\n", - " 0.000000\n", + " 0.018219\n", + " 0.008097\n", + " 0.016194\n", + " 0.030364\n", + " 0.022267\n", + " 0.044534\n", + " 0.228745\n", + " 0.010121\n", + " 0.012146\n", " 0.000000\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.015152\n", + " 0.030303\n", + " 0.030303\n", + " 0.030303\n", + " 0.015152\n", + " 0.000000\n", + " 0.287879\n", + " 0.000000\n", + " 0.030303\n", + " 0.000000\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 0.048193\n", + " 0.016064\n", + " 0.008032\n", + " 0.028112\n", + " 0.012048\n", + " 0.020080\n", + " 0.289157\n", + " 0.012048\n", + " 0.016064\n", + " 0.008032\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.055556\n", + " 0.000000\n", + " 0.055556\n", + " 0.055556\n", + " 0.055556\n", + " 0.111111\n", + " 0.277778\n", + " 0.000000\n", + " 0.055556\n", + " 0.000000\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", + " 4.5\n", " ...\n", - " 0.000000\n", - " 0.000000\n", - " 0.095238\n", - " 0.047619\n", - " 0.000000\n", - " 0.000000\n", - " 0.142857\n", - " 0.000000\n", - " 0.047619\n", - " 0.000000\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 0.047297\n", - " 0.006757\n", - " 0.006757\n", - " 0.040541\n", - " 0.013514\n", - " 0.020270\n", - " 0.324324\n", - " 0.020270\n", - " 0.013514\n", - " 0.013514\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.026316\n", - " 0.006579\n", - " 0.046053\n", - " 0.006579\n", - " 0.138158\n", - " 0.092105\n", - " 0.171053\n", - " 0.000000\n", - " 0.013158\n", - " 0.000000\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.019355\n", - " 0.012903\n", - " 0.032258\n", - " 0.009677\n", - " 0.012903\n", - " 0.022581\n", - " 0.206452\n", - " 0.035484\n", - " 0.012903\n", - " 0.016129\n", + " 0.030369\n", + " 0.008677\n", + " 0.028200\n", + " 0.010846\n", + " 0.023861\n", + " 0.041215\n", + " 0.221258\n", + " 0.026030\n", + " 0.013015\n", + " 0.013015\n", " \n", " \n", "\n", - "

1159 rows × 122 columns

\n", + "

1731 rows × 122 columns

\n", "" ], "text/plain": [ @@ -2477,55 +2483,55 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote ... miscontrols dispossessed fouls \\\n", "0 0.0 6.5 ... 0.000000 0.000000 0.000000 \n", - "1 0.0 6.5 ... 0.020161 0.012097 0.012097 \n", - "2 0.0 6.0 ... 0.007874 0.000000 0.007874 \n", - "3 0.0 6.5 ... 0.002786 0.002786 0.002786 \n", + "1 0.0 6.5 ... 0.018349 0.009174 0.009174 \n", + "2 0.0 6.0 ... 0.004608 0.000000 0.011521 \n", + "3 0.0 6.5 ... 0.009276 0.001855 0.009276 \n", "4 0.0 10.0 ... 0.000000 0.020833 0.031250 \n", "... ... ... ... ... ... ... \n", - "1154 0.5 5.5 ... 0.028846 0.009615 0.019231 \n", - "1155 0.5 5.5 ... 0.000000 0.000000 0.095238 \n", - "1156 0.0 6.0 ... 0.047297 0.006757 0.006757 \n", - "1157 0.0 5.5 ... 0.026316 0.006579 0.046053 \n", - "1158 0.0 5.5 ... 0.019355 0.012903 0.032258 \n", + "1726 0.5 5.5 ... 0.018219 0.008097 0.016194 \n", + "1727 0.0 6.0 ... 0.015152 0.030303 0.030303 \n", + "1728 0.0 5.5 ... 0.048193 0.016064 0.008032 \n", + "1729 0.0 6.0 ... 0.055556 0.000000 0.055556 \n", + "1730 0.5 4.5 ... 0.030369 0.008677 0.028200 \n", "\n", " fouled aerials_won aerials_lost carries progressive_carries \\\n", "0 0.000000 0.000000 0.000000 0.000000 0.000000 \n", - "1 0.016129 0.008065 0.016129 0.391129 0.040323 \n", - "2 0.000000 0.019685 0.027559 0.350394 0.000000 \n", - "3 0.011142 0.013928 0.022284 0.412256 0.019499 \n", + "1 0.015291 0.009174 0.015291 0.376147 0.033639 \n", + "2 0.002304 0.034562 0.020737 0.299539 0.000000 \n", + "3 0.014842 0.016698 0.022263 0.378479 0.014842 \n", "4 0.000000 0.000000 0.010417 0.447917 0.062500 \n", "... ... ... ... ... ... \n", - "1154 0.000000 0.009615 0.038462 0.182692 0.000000 \n", - "1155 0.047619 0.000000 0.000000 0.142857 0.000000 \n", - "1156 0.040541 0.013514 0.020270 0.324324 0.020270 \n", - "1157 0.006579 0.138158 0.092105 0.171053 0.000000 \n", - "1158 0.009677 0.012903 0.022581 0.206452 0.035484 \n", + "1726 0.030364 0.022267 0.044534 0.228745 0.010121 \n", + "1727 0.030303 0.015152 0.000000 0.287879 0.000000 \n", + "1728 0.028112 0.012048 0.020080 0.289157 0.012048 \n", + "1729 0.055556 0.055556 0.111111 0.277778 0.000000 \n", + "1730 0.010846 0.023861 0.041215 0.221258 0.026030 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", "0 0.000000 0.000000 \n", - "1 0.020161 0.012097 \n", + "1 0.015291 0.012232 \n", "2 0.000000 0.000000 \n", - "3 0.025070 0.002786 \n", + "3 0.016698 0.001855 \n", "4 0.041667 0.010417 \n", "... ... ... \n", - "1154 0.000000 0.000000 \n", - "1155 0.047619 0.000000 \n", - "1156 0.013514 0.013514 \n", - "1157 0.013158 0.000000 \n", - "1158 0.012903 0.016129 \n", + "1726 0.012146 0.000000 \n", + "1727 0.030303 0.000000 \n", + "1728 0.016064 0.008032 \n", + "1729 0.055556 0.000000 \n", + "1730 0.013015 0.013015 \n", "\n", - "[1159 rows x 122 columns]" + "[1731 rows x 122 columns]" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -2544,7 +2550,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "1db9f77f", "metadata": {}, "outputs": [], @@ -2556,7 +2562,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "f56df3ca", "metadata": {}, "outputs": [ @@ -2618,16 +2624,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 2\n", @@ -2642,13 +2648,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -2666,16 +2672,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 4\n", @@ -2714,16 +2720,16 @@ " 0.0\n", " 7.5\n", " ...\n", - " 0.012384\n", - " 0.003096\n", - " 0.012384\n", - " 0.006192\n", - " 0.003096\n", - " 0.027864\n", - " 0.408669\n", - " 0.015480\n", - " 0.012384\n", - " 0.003096\n", + " 0.010204\n", + " 0.002041\n", + " 0.014286\n", + " 0.004082\n", + " 0.010204\n", + " 0.020408\n", + " 0.357143\n", + " 0.016327\n", + " 0.014286\n", + " 0.004082\n", " \n", " \n", " ...\n", @@ -2750,11 +2756,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -2762,116 +2768,116 @@ " 0.5\n", " 5.5\n", " ...\n", - " 0.028846\n", - " 0.009615\n", - " 0.019231\n", - " 0.000000\n", - " 0.009615\n", - " 0.038462\n", - " 0.182692\n", - " 0.000000\n", - " 0.000000\n", + " 0.018219\n", + " 0.008097\n", + " 0.016194\n", + " 0.030364\n", + " 0.022267\n", + " 0.044534\n", + " 0.228745\n", + " 0.010121\n", + " 0.012146\n", " 0.000000\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.015152\n", + " 0.030303\n", + " 0.030303\n", + " 0.030303\n", + " 0.015152\n", + " 0.000000\n", + " 0.287879\n", + " 0.000000\n", + " 0.030303\n", + " 0.000000\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 0.048193\n", + " 0.016064\n", + " 0.008032\n", + " 0.028112\n", + " 0.012048\n", + " 0.020080\n", + " 0.289157\n", + " 0.012048\n", + " 0.016064\n", + " 0.008032\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " 0.055556\n", + " 0.000000\n", + " 0.055556\n", + " 0.055556\n", + " 0.055556\n", + " 0.111111\n", + " 0.277778\n", + " 0.000000\n", + " 0.055556\n", + " 0.000000\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", + " 4.5\n", " ...\n", - " 0.000000\n", - " 0.000000\n", - " 0.095238\n", - " 0.047619\n", - " 0.000000\n", - " 0.000000\n", - " 0.142857\n", - " 0.000000\n", - " 0.047619\n", - " 0.000000\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 0.047297\n", - " 0.006757\n", - " 0.006757\n", - " 0.040541\n", - " 0.013514\n", - " 0.020270\n", - " 0.324324\n", - " 0.020270\n", - " 0.013514\n", - " 0.013514\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.026316\n", - " 0.006579\n", - " 0.046053\n", - " 0.006579\n", - " 0.138158\n", - " 0.092105\n", - " 0.171053\n", - " 0.000000\n", - " 0.013158\n", - " 0.000000\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " 0.019355\n", - " 0.012903\n", - " 0.032258\n", - " 0.009677\n", - " 0.012903\n", - " 0.022581\n", - " 0.206452\n", - " 0.035484\n", - " 0.012903\n", - " 0.016129\n", + " 0.030369\n", + " 0.008677\n", + " 0.028200\n", + " 0.010846\n", + " 0.023861\n", + " 0.041215\n", + " 0.221258\n", + " 0.026030\n", + " 0.013015\n", + " 0.013015\n", " \n", " \n", "\n", - "

1070 rows × 122 columns

\n", + "

1601 rows × 122 columns

\n", "" ], "text/plain": [ @@ -2882,55 +2888,55 @@ "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "5 1 Ruggeri Atalanta Sassuolo 0 6.5 0 1 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", " cards_malus fantavote ... miscontrols dispossessed fouls \\\n", - "1 0.0 6.5 ... 0.020161 0.012097 0.012097 \n", - "2 0.0 6.0 ... 0.007874 0.000000 0.007874 \n", - "3 0.0 6.5 ... 0.002786 0.002786 0.002786 \n", + "1 0.0 6.5 ... 0.018349 0.009174 0.009174 \n", + "2 0.0 6.0 ... 0.004608 0.000000 0.011521 \n", + "3 0.0 6.5 ... 0.009276 0.001855 0.009276 \n", "4 0.0 10.0 ... 0.000000 0.020833 0.031250 \n", - "5 0.0 7.5 ... 0.012384 0.003096 0.012384 \n", + "5 0.0 7.5 ... 0.010204 0.002041 0.014286 \n", "... ... ... ... ... ... ... \n", - "1154 0.5 5.5 ... 0.028846 0.009615 0.019231 \n", - "1155 0.5 5.5 ... 0.000000 0.000000 0.095238 \n", - "1156 0.0 6.0 ... 0.047297 0.006757 0.006757 \n", - "1157 0.0 5.5 ... 0.026316 0.006579 0.046053 \n", - "1158 0.0 5.5 ... 0.019355 0.012903 0.032258 \n", + "1726 0.5 5.5 ... 0.018219 0.008097 0.016194 \n", + "1727 0.0 6.0 ... 0.015152 0.030303 0.030303 \n", + "1728 0.0 5.5 ... 0.048193 0.016064 0.008032 \n", + "1729 0.0 6.0 ... 0.055556 0.000000 0.055556 \n", + "1730 0.5 4.5 ... 0.030369 0.008677 0.028200 \n", "\n", " fouled aerials_won aerials_lost carries progressive_carries \\\n", - "1 0.016129 0.008065 0.016129 0.391129 0.040323 \n", - "2 0.000000 0.019685 0.027559 0.350394 0.000000 \n", - "3 0.011142 0.013928 0.022284 0.412256 0.019499 \n", + "1 0.015291 0.009174 0.015291 0.376147 0.033639 \n", + "2 0.002304 0.034562 0.020737 0.299539 0.000000 \n", + "3 0.014842 0.016698 0.022263 0.378479 0.014842 \n", "4 0.000000 0.000000 0.010417 0.447917 0.062500 \n", - "5 0.006192 0.003096 0.027864 0.408669 0.015480 \n", + "5 0.004082 0.010204 0.020408 0.357143 0.016327 \n", "... ... ... ... ... ... \n", - "1154 0.000000 0.009615 0.038462 0.182692 0.000000 \n", - "1155 0.047619 0.000000 0.000000 0.142857 0.000000 \n", - "1156 0.040541 0.013514 0.020270 0.324324 0.020270 \n", - "1157 0.006579 0.138158 0.092105 0.171053 0.000000 \n", - "1158 0.009677 0.012903 0.022581 0.206452 0.035484 \n", + "1726 0.030364 0.022267 0.044534 0.228745 0.010121 \n", + "1727 0.030303 0.015152 0.000000 0.287879 0.000000 \n", + "1728 0.028112 0.012048 0.020080 0.289157 0.012048 \n", + "1729 0.055556 0.055556 0.111111 0.277778 0.000000 \n", + "1730 0.010846 0.023861 0.041215 0.221258 0.026030 \n", "\n", " carries_into_final_third carries_into_penalty_area \n", - "1 0.020161 0.012097 \n", + "1 0.015291 0.012232 \n", "2 0.000000 0.000000 \n", - "3 0.025070 0.002786 \n", + "3 0.016698 0.001855 \n", "4 0.041667 0.010417 \n", - "5 0.012384 0.003096 \n", + "5 0.014286 0.004082 \n", "... ... ... \n", - "1154 0.000000 0.000000 \n", - "1155 0.047619 0.000000 \n", - "1156 0.013514 0.013514 \n", - "1157 0.013158 0.000000 \n", - "1158 0.012903 0.016129 \n", + "1726 0.012146 0.000000 \n", + "1727 0.030303 0.000000 \n", + "1728 0.016064 0.008032 \n", + "1729 0.055556 0.000000 \n", + "1730 0.013015 0.013015 \n", "\n", - "[1070 rows x 122 columns]" + "[1601 rows x 122 columns]" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -2949,7 +2955,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "df26c8e0", "metadata": {}, "outputs": [], @@ -2967,7 +2973,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "4d06576a", "metadata": {}, "outputs": [ @@ -3107,7 +3113,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "01bb7413", "metadata": {}, "outputs": [ @@ -3182,7 +3188,7 @@ " 'vs_team_aerials_won_pct']" ] }, - "execution_count": 19, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -3201,7 +3207,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "02f961d8", "metadata": {}, "outputs": [], @@ -3314,7 +3320,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "id": "5e3694a0", "metadata": {}, "outputs": [], @@ -3338,7 +3344,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "id": "9b671646", "metadata": {}, "outputs": [ @@ -3389,27 +3395,27 @@ " \n", " \n", " Consigli\n", - " 3\n", - " 3\n", - " 270\n", - " 1.67\n", + " 4.0\n", + " 4.0\n", + " 360\n", + " 1.5\n", " 66.7\n", " 0.0\n", - " -0.58\n", - " 23.9\n", - " 38.9\n", - " 37.1\n", + " -0.47\n", + " 26.1\n", + " 45.7\n", + " 39.4\n", " ...\n", - " 3.3\n", - " 0.19\n", - " -1.7\n", - " 11.0\n", - " 46.0\n", - " 95.0\n", - " 10.0\n", - " 34.0\n", - " 46.0\n", - " 2.0\n", + " 4.1\n", + " 0.21\n", + " -1.9\n", + " 18.0\n", + " 69.0\n", + " 127.0\n", + " 14.0\n", + " 42.0\n", + " 73.0\n", + " 4.0\n", " \n", " \n", "\n", @@ -3418,30 +3424,30 @@ ], "text/plain": [ " gk_games gk_games_starts gk_minutes gk_goals_against_per90 \\\n", - "Consigli 3 3 270 1.67 \n", + "Consigli 4.0 4.0 360 1.5 \n", "\n", " gk_save_pct gk_clean_sheets_pct gk_psxg_net_per90 \\\n", - "Consigli 66.7 0.0 -0.58 \n", + "Consigli 66.7 0.0 -0.47 \n", "\n", " gk_passes_pct_launched gk_pct_passes_launched \\\n", - "Consigli 23.9 38.9 \n", + "Consigli 26.1 45.7 \n", "\n", " gk_passes_length_avg ... gk_psxg \\\n", - "Consigli 37.1 ... 3.3 \n", + "Consigli 39.4 ... 4.1 \n", "\n", " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "Consigli 0.19 -1.7 \n", + "Consigli 0.21 -1.9 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "Consigli 11.0 46.0 95.0 \n", + "Consigli 18.0 69.0 127.0 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "Consigli 10.0 34.0 46.0 2.0 \n", + "Consigli 14.0 42.0 73.0 4.0 \n", "\n", "[1 rows x 92 columns]" ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -3456,7 +3462,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "id": "33f805a9", "metadata": {}, "outputs": [ @@ -3475,7 +3481,13 @@ "800\n", "900\n", "1000\n", - "1100\n" + "1100\n", + "1200\n", + "1300\n", + "1400\n", + "1500\n", + "1600\n", + "1700\n" ] } ], @@ -3505,7 +3517,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "id": "4d484846", "metadata": {}, "outputs": [ @@ -3570,13 +3582,13 @@ " 2.1\n", " 0.21\n", " 0.1\n", - " 11.0\n", - " 34.0\n", - " 88.0\n", - " 18.0\n", - " 18.0\n", + " 14.0\n", + " 48.0\n", + " 119.0\n", + " 25.0\n", " 28.0\n", - " 2.0\n", + " 43.0\n", + " 4.0\n", " \n", " \n", " 1\n", @@ -3699,11 +3711,11 @@ " ...\n", " \n", " \n", - " 1154\n", - " 4\n", - " Serdar\n", + " 1726\n", + " 6\n", + " Folorunsho\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", @@ -3723,89 +3735,89 @@ " NaN\n", " \n", " \n", - " 1155\n", - " 4\n", + " 1727\n", + " 6\n", " Suslov\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", " 6.0\n", " 0\n", " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1728\n", + " 6\n", + " Bonazzoli\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.5\n", + " 0\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1729\n", + " 6\n", + " Henry\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 6.0\n", + " 0\n", + " 0\n", + " 0.0\n", + " 6.0\n", + " ...\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1730\n", + " 6\n", + " Ngonge\n", + " Verona\n", + " Atalanta\n", + " 1\n", + " 5.0\n", + " 0\n", + " 0\n", " 0.5\n", - " 5.5\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1156\n", - " 4\n", - " Bonazzoli\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1157\n", - " 4\n", - " Djuric\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", - " ...\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " NaN\n", - " \n", - " \n", - " 1158\n", - " 4\n", - " Ngonge\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 5.5\n", - " 0\n", - " 0\n", - " 0.0\n", - " 5.5\n", + " 4.5\n", " ...\n", " NaN\n", " NaN\n", @@ -3820,7 +3832,7 @@ " \n", " \n", "\n", - "

1159 rows × 102 columns

\n", + "

1731 rows × 102 columns

\n", "" ], "text/plain": [ @@ -3831,68 +3843,68 @@ "3 1 Kolasinac Atalanta Sassuolo 0 6.5 0 0 \n", "4 1 Zortea Atalanta Sassuolo 0 7.0 1 0 \n", "... ... ... ... ... ... ... ... ... \n", - "1154 4 Serdar Verona Bologna 1 6.0 0 0 \n", - "1155 4 Suslov Verona Bologna 1 6.0 0 0 \n", - "1156 4 Bonazzoli Verona Bologna 1 6.0 0 0 \n", - "1157 4 Djuric Verona Bologna 1 5.5 0 0 \n", - "1158 4 Ngonge Verona Bologna 1 5.5 0 0 \n", + "1726 6 Folorunsho Verona Atalanta 1 6.0 0 0 \n", + "1727 6 Suslov Verona Atalanta 1 6.0 0 0 \n", + "1728 6 Bonazzoli Verona Atalanta 1 5.5 0 0 \n", + "1729 6 Henry Verona Atalanta 1 6.0 0 0 \n", + "1730 6 Ngonge Verona Atalanta 1 5.0 0 0 \n", "\n", - " cards_malus fantavote ... gk_psxg \\\n", - "0 0.0 6.5 ... 2.1 \n", - "1 0.0 6.5 ... NaN \n", - "2 0.0 6.0 ... NaN \n", - "3 0.0 6.5 ... NaN \n", - "4 0.0 10.0 ... NaN \n", - "... ... ... ... ... \n", - "1154 0.5 5.5 ... NaN \n", - "1155 0.5 5.5 ... NaN \n", - "1156 0.0 6.0 ... NaN \n", - "1157 0.0 5.5 ... NaN \n", - "1158 0.0 5.5 ... NaN \n", + " cards_malus fantavote ... gk_psxg \\\n", + "0 0.0 6.5 ... 2.1 \n", + "1 0.0 6.5 ... NaN \n", + "2 0.0 6.0 ... NaN \n", + "3 0.0 6.5 ... NaN \n", + "4 0.0 10.0 ... NaN \n", + "... ... ... ... ... \n", + "1726 0.5 5.5 ... NaN \n", + "1727 0.0 6.0 ... NaN \n", + "1728 0.0 5.5 ... NaN \n", + "1729 0.0 6.0 ... NaN \n", + "1730 0.5 4.5 ... NaN \n", "\n", - " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "0 0.21 0.1 \n", - "1 NaN NaN \n", - "2 NaN NaN \n", - "3 NaN NaN \n", - "4 NaN NaN \n", - "... ... ... \n", - "1154 NaN NaN \n", - "1155 NaN NaN \n", - "1156 NaN NaN \n", - "1157 NaN NaN \n", - "1158 NaN NaN \n", + " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", + "0 0.21 0.1 \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN \n", + "... ... ... \n", + "1726 NaN NaN \n", + "1727 NaN NaN \n", + "1728 NaN NaN \n", + "1729 NaN NaN \n", + "1730 NaN NaN \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.0 34.0 88.0 \n", + "0 14.0 48.0 119.0 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN \n", "... ... ... ... \n", - "1154 NaN NaN NaN \n", - "1155 NaN NaN NaN \n", - "1156 NaN NaN NaN \n", - "1157 NaN NaN NaN \n", - "1158 NaN NaN NaN \n", + "1726 NaN NaN NaN \n", + "1727 NaN NaN NaN \n", + "1728 NaN NaN NaN \n", + "1729 NaN NaN NaN \n", + "1730 NaN NaN NaN \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.0 18.0 28.0 2.0 \n", + "0 25.0 28.0 43.0 4.0 \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "... ... ... ... ... \n", - "1154 NaN NaN NaN NaN \n", - "1155 NaN NaN NaN NaN \n", - "1156 NaN NaN NaN NaN \n", - "1157 NaN NaN NaN NaN \n", - "1158 NaN NaN NaN NaN \n", + "1726 NaN NaN NaN NaN \n", + "1727 NaN NaN NaN NaN \n", + "1728 NaN NaN NaN NaN \n", + "1729 NaN NaN NaN NaN \n", + "1730 NaN NaN NaN NaN \n", "\n", - "[1159 rows x 102 columns]" + "[1731 rows x 102 columns]" ] }, - "execution_count": 24, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -3903,7 +3915,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "id": "adab3577", "metadata": {}, "outputs": [], @@ -3913,7 +3925,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "id": "e7ae792d", "metadata": {}, "outputs": [ @@ -3975,16 +3987,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 2.1\n", - " 0.21\n", + " 2.100000\n", + " 0.210000\n", " 0.1\n", - " 11.0\n", - " 34.0\n", - " 88.0\n", - " 18.0\n", - " 18.0\n", - " 28.0\n", - " 2.0\n", + " 14.000000\n", + " 48.000000\n", + " 119.0\n", + " 25.000000\n", + " 28.000000\n", + " 43.000000\n", + " 4.0\n", " \n", " \n", " 16\n", @@ -3999,16 +4011,16 @@ " 0.0\n", " 4.0\n", " ...\n", - " 3.2\n", - " 0.32\n", - " -0.8\n", - " 17.0\n", - " 45.0\n", - " 106.0\n", - " 17.0\n", - " 22.0\n", - " 57.0\n", - " 2.0\n", + " 4.200000\n", + " 0.250000\n", + " 0.2\n", + " 28.000000\n", + " 60.000000\n", + " 159.0\n", + " 25.000000\n", + " 34.000000\n", + " 89.000000\n", + " 3.0\n", " \n", " \n", " 29\n", @@ -4023,16 +4035,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 4.1\n", - " 0.33\n", - " 0.1\n", - " 24.0\n", - " 54.0\n", - " 76.0\n", - " 18.0\n", - " 40.0\n", - " 62.0\n", - " 4.0\n", + " 8.700000\n", + " 0.360000\n", + " -0.3\n", + " 33.000000\n", + " 80.000000\n", + " 124.0\n", + " 23.000000\n", + " 57.000000\n", + " 87.000000\n", + " 5.0\n", " \n", " \n", " 44\n", @@ -4047,15 +4059,15 @@ " 0.0\n", " 4.0\n", " ...\n", - " 0.4\n", - " 0.11\n", - " -0.6\n", - " 4.0\n", - " 20.0\n", - " 37.0\n", - " 9.0\n", - " 4.0\n", - " 10.0\n", + " 4.933333\n", + " 0.203333\n", + " -1.4\n", + " 8.666667\n", + " 38.666667\n", + " 83.0\n", + " 17.666667\n", + " 17.333333\n", + " 36.666667\n", " 2.0\n", " \n", " \n", @@ -4071,16 +4083,16 @@ " 0.0\n", " 5.0\n", " ...\n", - " 1.0\n", - " 0.17\n", - " -2.0\n", - " 13.0\n", - " 20.0\n", - " 85.0\n", - " 10.0\n", - " 9.0\n", - " 16.0\n", - " 1.0\n", + " 4.100000\n", + " 0.240000\n", + " 0.1\n", + " 28.000000\n", + " 57.000000\n", + " 151.0\n", + " 14.000000\n", + " 22.000000\n", + " 44.000000\n", + " 3.0\n", " \n", " \n", " ...\n", @@ -4107,200 +4119,200 @@ " ...\n", " \n", " \n", - " 1085\n", - " 4\n", + " 1657\n", + " 6\n", " Ochoa\n", " Salernitana\n", - " Torino\n", - " 1\n", - " 5.0\n", - " -3\n", + " Empoli\n", + " 0\n", + " 6.5\n", + " -1\n", " 0\n", " 0.0\n", - " 2.0\n", + " 5.5\n", " ...\n", - " 4.7\n", - " 0.21\n", - " -3.3\n", - " 13.0\n", - " 55.0\n", - " 89.0\n", - " 14.0\n", - " 35.0\n", - " 63.0\n", + " 6.800000\n", + " 0.220000\n", + " -3.2\n", + " 20.000000\n", + " 85.000000\n", + " 160.0\n", + " 22.000000\n", + " 47.000000\n", + " 88.000000\n", " 4.0\n", " \n", " \n", - " 1101\n", - " 4\n", - " Cragno\n", + " 1672\n", + " 6\n", + " Consigli\n", " Sassuolo\n", - " Frosinone\n", + " Inter\n", " 0\n", " 6.5\n", + " -1\n", + " 0\n", + " 0.0\n", + " 5.5\n", + " ...\n", + " 4.100000\n", + " 0.210000\n", + " -1.9\n", + " 18.000000\n", + " 69.000000\n", + " 127.0\n", + " 14.000000\n", + " 42.000000\n", + " 73.000000\n", + " 4.0\n", + " \n", + " \n", + " 1686\n", + " 6\n", + " Milinkovic-Savic V.\n", + " Torino\n", + " Lazio\n", + " 0\n", + " 6.0\n", + " -2\n", + " 0\n", + " 0.0\n", + " 4.0\n", + " ...\n", + " 5.800000\n", + " 0.180000\n", + " -1.2\n", + " 42.000000\n", + " 117.000000\n", + " 193.0\n", + " 37.000000\n", + " 50.000000\n", + " 47.000000\n", + " 4.0\n", + " \n", + " \n", + " 1700\n", + " 6\n", + " Silvestri\n", + " Udinese\n", + " Napoli\n", + " 0\n", + " 5.5\n", " -4\n", " 0\n", " 0.0\n", - " 2.5\n", + " 1.5\n", " ...\n", - " 2.8\n", - " 0.30\n", - " -1.2\n", - " 5.0\n", - " 15.0\n", - " 24.0\n", - " 3.0\n", - " 9.0\n", - " 9.0\n", - " 0.0\n", + " 10.100000\n", + " 0.370000\n", + " 0.1\n", + " 19.000000\n", + " 50.000000\n", + " 132.0\n", + " 23.000000\n", + " 45.000000\n", + " 69.000000\n", + " 1.0\n", " \n", " \n", - " 1117\n", - " 4\n", - " Milinkovic-Savic V.\n", - " Torino\n", - " Salernitana\n", - " 0\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 4.6\n", - " 0.18\n", - " 0.6\n", - " 29.0\n", - " 79.0\n", - " 117.0\n", - " 23.0\n", - " 36.0\n", - " 33.0\n", - " 3.0\n", - " \n", - " \n", - " 1129\n", - " 4\n", - " Silvestri\n", - " Udinese\n", - " Cagliari\n", - " 0\n", - " 6.0\n", - " 0\n", - " 0\n", - " 0.0\n", - " 6.0\n", - " ...\n", - " 3.9\n", - " 0.29\n", - " -0.1\n", - " 11.0\n", - " 34.0\n", - " 94.0\n", - " 14.0\n", - " 32.0\n", - " 49.0\n", - " 0.0\n", - " \n", - " \n", - " 1143\n", - " 4\n", + " 1716\n", + " 6\n", " Montipo'\n", " Verona\n", - " Bologna\n", + " Atalanta\n", " 1\n", - " 7.0\n", - " 0\n", + " 6.0\n", + " -1\n", " 0\n", " 0.0\n", - " 7.0\n", + " 5.0\n", " ...\n", - " 4.9\n", - " 0.19\n", - " 0.9\n", - " 35.0\n", - " 93.0\n", - " 109.0\n", - " 8.0\n", - " 35.0\n", - " 54.0\n", + " 6.700000\n", + " 0.210000\n", + " 0.7\n", + " 55.000000\n", + " 156.000000\n", + " 183.0\n", + " 16.000000\n", + " 50.000000\n", + " 72.000000\n", " 1.0\n", " \n", " \n", "\n", - "

80 rows × 102 columns

\n", + "

120 rows × 102 columns

\n", "" ], "text/plain": [ - " matchday player team oppteam home vote \\\n", - "0 1 Musso Atalanta Sassuolo 0 6.5 \n", - "16 1 Skorupski Bologna Milan 1 6.0 \n", - "29 1 Radunovic Cagliari Torino 0 6.5 \n", - "44 1 Caprile Empoli Verona 1 5.0 \n", - "57 1 Terracciano Fiorentina Genoa 0 6.0 \n", - "... ... ... ... ... ... ... \n", - "1085 4 Ochoa Salernitana Torino 1 5.0 \n", - "1101 4 Cragno Sassuolo Frosinone 0 6.5 \n", - "1117 4 Milinkovic-Savic V. Torino Salernitana 0 6.0 \n", - "1129 4 Silvestri Udinese Cagliari 0 6.0 \n", - "1143 4 Montipo' Verona Bologna 1 7.0 \n", + " matchday player team oppteam home vote goals \\\n", + "0 1 Musso Atalanta Sassuolo 0 6.5 0 \n", + "16 1 Skorupski Bologna Milan 1 6.0 -2 \n", + "29 1 Radunovic Cagliari Torino 0 6.5 0 \n", + "44 1 Caprile Empoli Verona 1 5.0 -1 \n", + "57 1 Terracciano Fiorentina Genoa 0 6.0 -1 \n", + "... ... ... ... ... ... ... ... \n", + "1657 6 Ochoa Salernitana Empoli 0 6.5 -1 \n", + "1672 6 Consigli Sassuolo Inter 0 6.5 -1 \n", + "1686 6 Milinkovic-Savic V. Torino Lazio 0 6.0 -2 \n", + "1700 6 Silvestri Udinese Napoli 0 5.5 -4 \n", + "1716 6 Montipo' Verona Atalanta 1 6.0 -1 \n", "\n", - " goals assists cards_malus fantavote ... gk_psxg \\\n", - "0 0 0 0.0 6.5 ... 2.1 \n", - "16 -2 0 0.0 4.0 ... 3.2 \n", - "29 0 0 0.0 6.5 ... 4.1 \n", - "44 -1 0 0.0 4.0 ... 0.4 \n", - "57 -1 0 0.0 5.0 ... 1.0 \n", - "... ... ... ... ... ... ... \n", - "1085 -3 0 0.0 2.0 ... 4.7 \n", - "1101 -4 0 0.0 2.5 ... 2.8 \n", - "1117 0 0 0.0 6.0 ... 4.6 \n", - "1129 0 0 0.0 6.0 ... 3.9 \n", - "1143 0 0 0.0 7.0 ... 4.9 \n", + " assists cards_malus fantavote ... gk_psxg \\\n", + "0 0 0.0 6.5 ... 2.100000 \n", + "16 0 0.0 4.0 ... 4.200000 \n", + "29 0 0.0 6.5 ... 8.700000 \n", + "44 0 0.0 4.0 ... 4.933333 \n", + "57 0 0.0 5.0 ... 4.100000 \n", + "... ... ... ... ... ... \n", + "1657 0 0.0 5.5 ... 6.800000 \n", + "1672 0 0.0 5.5 ... 4.100000 \n", + "1686 0 0.0 4.0 ... 5.800000 \n", + "1700 0 0.0 1.5 ... 10.100000 \n", + "1716 0 0.0 5.0 ... 6.700000 \n", "\n", - " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", - "0 0.21 0.1 \n", - "16 0.32 -0.8 \n", - "29 0.33 0.1 \n", - "44 0.11 -0.6 \n", - "57 0.17 -2.0 \n", - "... ... ... \n", - "1085 0.21 -3.3 \n", - "1101 0.30 -1.2 \n", - "1117 0.18 0.6 \n", - "1129 0.29 -0.1 \n", - "1143 0.19 0.9 \n", + " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", + "0 0.210000 0.1 \n", + "16 0.250000 0.2 \n", + "29 0.360000 -0.3 \n", + "44 0.203333 -1.4 \n", + "57 0.240000 0.1 \n", + "... ... ... \n", + "1657 0.220000 -3.2 \n", + "1672 0.210000 -1.9 \n", + "1686 0.180000 -1.2 \n", + "1700 0.370000 0.1 \n", + "1716 0.210000 0.7 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.0 34.0 88.0 \n", - "16 17.0 45.0 106.0 \n", - "29 24.0 54.0 76.0 \n", - "44 4.0 20.0 37.0 \n", - "57 13.0 20.0 85.0 \n", + "0 14.000000 48.000000 119.0 \n", + "16 28.000000 60.000000 159.0 \n", + "29 33.000000 80.000000 124.0 \n", + "44 8.666667 38.666667 83.0 \n", + "57 28.000000 57.000000 151.0 \n", "... ... ... ... \n", - "1085 13.0 55.0 89.0 \n", - "1101 5.0 15.0 24.0 \n", - "1117 29.0 79.0 117.0 \n", - "1129 11.0 34.0 94.0 \n", - "1143 35.0 93.0 109.0 \n", + "1657 20.000000 85.000000 160.0 \n", + "1672 18.000000 69.000000 127.0 \n", + "1686 42.000000 117.000000 193.0 \n", + "1700 19.000000 50.000000 132.0 \n", + "1716 55.000000 156.000000 183.0 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.0 18.0 28.0 2.0 \n", - "16 17.0 22.0 57.0 2.0 \n", - "29 18.0 40.0 62.0 4.0 \n", - "44 9.0 4.0 10.0 2.0 \n", - "57 10.0 9.0 16.0 1.0 \n", + "0 25.000000 28.000000 43.000000 4.0 \n", + "16 25.000000 34.000000 89.000000 3.0 \n", + "29 23.000000 57.000000 87.000000 5.0 \n", + "44 17.666667 17.333333 36.666667 2.0 \n", + "57 14.000000 22.000000 44.000000 3.0 \n", "... ... ... ... ... \n", - "1085 14.0 35.0 63.0 4.0 \n", - "1101 3.0 9.0 9.0 0.0 \n", - "1117 23.0 36.0 33.0 3.0 \n", - "1129 14.0 32.0 49.0 0.0 \n", - "1143 8.0 35.0 54.0 1.0 \n", + "1657 22.000000 47.000000 88.000000 4.0 \n", + "1672 14.000000 42.000000 73.000000 4.0 \n", + "1686 37.000000 50.000000 47.000000 4.0 \n", + "1700 23.000000 45.000000 69.000000 1.0 \n", + "1716 16.000000 50.000000 72.000000 1.0 \n", "\n", - "[80 rows x 102 columns]" + "[120 rows x 102 columns]" ] }, - "execution_count": 26, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -4319,7 +4331,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "id": "d8b8b6da", "metadata": {}, "outputs": [], @@ -4329,7 +4341,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "id": "54519b24", "metadata": {}, "outputs": [ diff --git a/5_scraping_match_probable_players.ipynb b/5_scraping_match_probable_players.ipynb index 4d57e90..2561ce8 100644 --- a/5_scraping_match_probable_players.ipynb +++ b/5_scraping_match_probable_players.ipynb @@ -71,33 +71,33 @@ " \n", " \n", " 0\n", - " Ochoa\n", + " Falcone\n", " 1\n", " 90.0\n", " \n", " \n", " 1\n", - " Lovato\n", + " Gendrey\n", " 1\n", - " 80.0\n", + " 90.0\n", " \n", " \n", " 2\n", - " Gyomber\n", + " Baschirotto\n", " 1\n", - " 80.0\n", + " 90.0\n", " \n", " \n", " 3\n", - " Pirola\n", + " Pongracic\n", " 1\n", " 80.0\n", " \n", " \n", " 4\n", - " Mazzocchi\n", + " Gallo\n", " 1\n", - " 80.0\n", + " 60.0\n", " \n", " \n", " ...\n", @@ -106,55 +106,55 @@ " ...\n", " \n", " \n", - " 471\n", - " Pisilli\n", + " 462\n", + " Oristanio\n", + " 0\n", + " 50.0\n", + " \n", + " \n", + " 463\n", + " Jankto\n", + " 0\n", + " 15.0\n", + " \n", + " \n", + " 464\n", + " Mancosu\n", " 0\n", " 10.0\n", " \n", " \n", - " 472\n", - " Aouar\n", + " 465\n", + " Pavoletti\n", " 0\n", " 55.0\n", " \n", " \n", - " 473\n", - " El Shaarawy\n", - " 0\n", - " 55.0\n", - " \n", - " \n", - " 474\n", - " Belotti\n", + " 466\n", + " Shomurodov\n", " 0\n", " 60.0\n", " \n", - " \n", - " 475\n", - " Azmoun\n", - " 0\n", - " 35.0\n", - " \n", " \n", "\n", - "

476 rows × 3 columns

\n", + "

467 rows × 3 columns

\n", "" ], "text/plain": [ " player starter percentage\n", - "0 Ochoa 1 90.0\n", - "1 Lovato 1 80.0\n", - "2 Gyomber 1 80.0\n", - "3 Pirola 1 80.0\n", - "4 Mazzocchi 1 80.0\n", + "0 Falcone 1 90.0\n", + "1 Gendrey 1 90.0\n", + "2 Baschirotto 1 90.0\n", + "3 Pongracic 1 80.0\n", + "4 Gallo 1 60.0\n", ".. ... ... ...\n", - "471 Pisilli 0 10.0\n", - "472 Aouar 0 55.0\n", - "473 El Shaarawy 0 55.0\n", - "474 Belotti 0 60.0\n", - "475 Azmoun 0 35.0\n", + "462 Oristanio 0 50.0\n", + "463 Jankto 0 15.0\n", + "464 Mancosu 0 10.0\n", + "465 Pavoletti 0 55.0\n", + "466 Shomurodov 0 60.0\n", "\n", - "[476 rows x 3 columns]" + "[467 rows x 3 columns]" ] }, "execution_count": 3, @@ -235,302 +235,356 @@ " \n", " \n", " 0\n", - " Ikwuemesi\n", - " Botheim\n", - " 55.0\n", + " Gallo\n", + " Dorgu\n", + " 60.0\n", " \n", " \n", " 1\n", - " Jovane\n", - " Kastanos\n", - " 55.0\n", + " Blin\n", + " Gonzalez J.\n", + " 60.0\n", " \n", " \n", " 2\n", - " Okoli\n", - " Monterisi\n", - " 55.0\n", + " Politano\n", + " Lindstrom\n", + " 60.0\n", " \n", " \n", " 3\n", - " Caso\n", - " Baez\n", - " 55.0\n", + " Zambo Anguissa\n", + " Cajuste\n", + " 60.0\n", " \n", " \n", " 4\n", - " Vasquez\n", - " Martin\n", - " 60.0\n", + " Zielinski\n", + " Raspadori\n", + " 55.0\n", " \n", " \n", " 5\n", - " Malinovskyi\n", - " De Winter\n", - " 60.0\n", - " \n", - " \n", - " 6\n", - " Kjaer\n", - " Thiaw\n", - " 60.0\n", - " \n", - " \n", - " 7\n", - " Rafael Leao\n", - " Chukwueze\n", - " 60.0\n", - " \n", - " \n", - " 8\n", - " Giroud\n", - " Jovic\n", - " 60.0\n", - " \n", - " \n", - " 9\n", - " Bonazzoli\n", - " Djuric\n", - " 60.0\n", - " \n", - " \n", - " 10\n", - " Mboula\n", - " Folorunsho\n", - " 55.0\n", - " \n", - " \n", - " 11\n", - " Tressoldi\n", - " Viti\n", - " 60.0\n", - " \n", - " \n", - " 12\n", - " Vina\n", - " Pedersen\n", - " 65.0\n", - " \n", - " \n", - " 13\n", - " Bajrami\n", - " Thorstvedt\n", - " 60.0\n", - " \n", - " \n", - " 14\n", - " Fagioli\n", - " Miretti\n", - " 60.0\n", - " \n", - " \n", - " 15\n", - " Mckennie\n", - " Weah\n", - " 55.0\n", - " \n", - " \n", - " 16\n", - " Zaccagni\n", - " Pedro\n", - " 60.0\n", - " \n", - " \n", - " 17\n", - " Romagnoli\n", - " Patric\n", - " 60.0\n", - " \n", - " \n", - " 18\n", - " Guendouzi\n", - " Kamada\n", - " 55.0\n", - " \n", - " \n", - " 19\n", - " Birindelli\n", - " Kyriakopoulos\n", - " 65.0\n", - " \n", - " \n", - " 20\n", - " Maleh\n", - " Bastoni S.\n", - " 55.0\n", - " \n", - " \n", - " 21\n", - " Fazzini\n", - " Grassi\n", - " 60.0\n", - " \n", - " \n", - " 22\n", - " Bereszynski\n", - " Ebuehi\n", - " 60.0\n", - " \n", - " \n", - " 23\n", - " Thuram\n", - " Arnautovic\n", - " 60.0\n", - " \n", - " \n", - " 24\n", - " Dimarco\n", - " Carlos Augusto\n", - " 55.0\n", - " \n", - " \n", - " 25\n", - " Pavard\n", - " Darmian\n", - " 60.0\n", - " \n", - " \n", - " 26\n", - " De Vrij\n", - " Acerbi\n", - " 60.0\n", - " \n", - " \n", - " 27\n", - " Frattesi\n", - " Mkhitaryan\n", - " 65.0\n", - " \n", - " \n", - " 28\n", - " Zappacosta\n", - " Zortea\n", - " 60.0\n", - " \n", - " \n", - " 29\n", - " Ruggeri\n", - " Bakker\n", - " 60.0\n", - " \n", - " \n", - " 30\n", - " Toloi\n", - " Djimsiti\n", - " 55.0\n", - " \n", - " \n", - " 31\n", - " Jankto\n", - " Deiola\n", - " 55.0\n", - " \n", - " \n", - " 32\n", - " Obert\n", - " Prati\n", - " 55.0\n", - " \n", - " \n", - " 33\n", - " Ebosele\n", - " Ferreira J.\n", - " 60.0\n", - " \n", - " \n", - " 34\n", - " Kamara H.\n", - " Zemura\n", - " 60.0\n", - " \n", - " \n", - " 35\n", - " Nzola\n", - " Beltran L.\n", - " 60.0\n", - " \n", - " \n", - " 36\n", - " Mandragora\n", - " Duncan\n", - " 55.0\n", - " \n", - " \n", - " 37\n", - " Ranieri L.\n", - " Martinez Quarta\n", - " 55.0\n", - " \n", - " \n", - " 38\n", - " Kouame'\n", - " Sottil\n", - " 55.0\n", - " \n", - " \n", - " 39\n", - " Moro N.\n", - " Aebischer\n", - " 55.0\n", - " \n", - " \n", - " 40\n", - " Ndoye\n", - " Orsolini\n", - " 55.0\n", - " \n", - " \n", - " 41\n", - " Zielinski\n", + " Kvaratskhelia\n", " Elmas\n", " 65.0\n", " \n", " \n", - " 42\n", - " Juan Jesus\n", - " Natan\n", - " 55.0\n", - " \n", - " \n", - " 43\n", - " Politano\n", - " Raspadori\n", - " 60.0\n", - " \n", - " \n", - " 44\n", + " 6\n", " Mario Rui\n", " Olivera\n", " 55.0\n", " \n", " \n", - " 45\n", - " Vlasic\n", - " Seck\n", - " 65.0\n", - " \n", - " \n", - " 46\n", - " Ilic\n", - " Tameze\n", + " 7\n", + " Calabria\n", + " Florenzi\n", " 55.0\n", " \n", " \n", - " 47\n", - " Paredes\n", - " Aouar\n", + " 8\n", + " Pulisic\n", + " Chukwueze\n", + " 55.0\n", + " \n", + " \n", + " 9\n", + " Reijnders\n", + " Musah\n", + " 65.0\n", + " \n", + " \n", + " 10\n", + " Romagnoli\n", + " Patric\n", + " 65.0\n", + " \n", + " \n", + " 11\n", + " Pellegrini Lu.\n", + " Marusic\n", + " 65.0\n", + " \n", + " \n", + " 12\n", + " Immobile\n", + " Castellanos\n", " 60.0\n", " \n", " \n", - " 48\n", - " Kristensen\n", + " 13\n", + " Luis Alberto\n", + " Guendouzi\n", + " 60.0\n", + " \n", + " \n", + " 14\n", + " Daniliuc\n", + " Lovato\n", + " 60.0\n", + " \n", + " \n", + " 15\n", + " Legowski\n", + " Bohinen\n", + " 60.0\n", + " \n", + " \n", + " 16\n", + " Martegani\n", + " Dia\n", + " 60.0\n", + " \n", + " \n", + " 17\n", + " Mkhitaryan\n", + " Klaassen\n", + " 55.0\n", + " \n", + " \n", + " 18\n", + " Sanchez\n", + " Martinez L.\n", + " 55.0\n", + " \n", + " \n", + " 19\n", + " Acerbi\n", + " Bastoni\n", + " 55.0\n", + " \n", + " \n", + " 20\n", + " Moro N.\n", + " Fabbian\n", + " 55.0\n", + " \n", + " \n", + " 21\n", + " Ferguson\n", + " Aebischer\n", + " 60.0\n", + " \n", + " \n", + " 22\n", + " Ndoye\n", + " Orsolini\n", + " 60.0\n", + " \n", + " \n", + " 23\n", + " Cancellieri\n", + " Shpendi S.\n", + " 60.0\n", + " \n", + " \n", + " 24\n", + " Fazzini\n", + " Ranocchia F.\n", + " 60.0\n", + " \n", + " \n", + " 25\n", + " Grassi\n", + " Marin\n", + " 60.0\n", + " \n", + " \n", + " 26\n", + " Success\n", + " Lucca\n", + " 55.0\n", + " \n", + " \n", + " 27\n", + " Ebosele\n", + " Ferreira J.\n", + " 60.0\n", + " \n", + " \n", + " 28\n", + " Kamara H.\n", + " Zemura\n", + " 60.0\n", + " \n", + " \n", + " 29\n", + " Martin\n", + " Matturro\n", + " 55.0\n", + " \n", + " \n", + " 30\n", + " Pasalic\n", + " Muriel\n", + " 60.0\n", + " \n", + " \n", + " 31\n", + " Ruggeri\n", + " Holm\n", + " 55.0\n", + " \n", + " \n", + " 32\n", + " Mckennie\n", + " Weah\n", + " 60.0\n", + " \n", + " \n", + " 33\n", + " Fagioli\n", + " Miretti\n", + " 60.0\n", + " \n", + " \n", + " 34\n", + " Chiesa\n", + " Milik\n", + " 55.0\n", + " \n", + " \n", + " 35\n", + " Dybala\n", + " El Shaarawy\n", + " 65.0\n", + " \n", + " \n", + " 36\n", + " Zalewski\n", + " Spinazzola\n", + " 55.0\n", + " \n", + " \n", + " 37\n", + " Paredes\n", " Celik\n", " 60.0\n", " \n", " \n", + " 38\n", + " Caso\n", + " Baez\n", + " 60.0\n", + " \n", + " \n", + " 39\n", + " Brescianini\n", + " Garritano\n", + " 60.0\n", + " \n", + " \n", + " 40\n", + " Romagnoli S.\n", + " Monterisi\n", + " 60.0\n", + " \n", + " \n", + " 41\n", + " Vina\n", + " Pedersen\n", + " 55.0\n", + " \n", + " \n", + " 42\n", + " Erlic\n", + " Viti\n", + " 60.0\n", + " \n", + " \n", + " 43\n", + " Bajrami\n", + " Castillejo\n", + " 60.0\n", + " \n", + " \n", + " 44\n", + " Colombo\n", + " Maric\n", + " 65.0\n", + " \n", + " \n", + " 45\n", + " Izzo\n", + " D'ambrosio\n", + " 60.0\n", + " \n", + " \n", + " 46\n", + " Birindelli\n", + " Kyriakopoulos\n", + " 60.0\n", + " \n", + " \n", + " 47\n", + " Bellanova\n", + " Soppy\n", + " 60.0\n", + " \n", + " \n", + " 48\n", + " Lazaro\n", + " Vojvoda\n", + " 60.0\n", + " \n", + " \n", " 49\n", - " Spinazzola\n", - " Zalewski\n", + " Zapata D.\n", + " Sanabria\n", + " 55.0\n", + " \n", + " \n", + " 50\n", + " Bonazzoli\n", + " Henry\n", + " 60.0\n", + " \n", + " \n", + " 51\n", + " Magnani\n", + " Coppola D.\n", + " 60.0\n", + " \n", + " \n", + " 52\n", + " Folorunsho\n", + " Saponara\n", + " 55.0\n", + " \n", + " \n", + " 53\n", + " Bonaventura\n", + " Barak\n", + " 60.0\n", + " \n", + " \n", + " 54\n", + " Lopez M.\n", + " Arthur Melo\n", + " 55.0\n", + " \n", + " \n", + " 55\n", + " Nzola\n", + " Beltran L.\n", + " 55.0\n", + " \n", + " \n", + " 56\n", + " Nandez\n", + " Deiola\n", + " 60.0\n", + " \n", + " \n", + " 57\n", + " Petagna\n", + " Shomurodov\n", + " 60.0\n", + " \n", + " \n", + " 58\n", + " Hatzidiakos\n", + " Obert\n", " 60.0\n", " \n", " \n", @@ -538,57 +592,66 @@ "" ], "text/plain": [ - " player1 player2 percentage\n", - "0 Ikwuemesi Botheim 55.0\n", - "1 Jovane Kastanos 55.0\n", - "2 Okoli Monterisi 55.0\n", - "3 Caso Baez 55.0\n", - "4 Vasquez Martin 60.0\n", - "5 Malinovskyi De Winter 60.0\n", - "6 Kjaer Thiaw 60.0\n", - "7 Rafael Leao Chukwueze 60.0\n", - "8 Giroud Jovic 60.0\n", - "9 Bonazzoli Djuric 60.0\n", - "10 Mboula Folorunsho 55.0\n", - "11 Tressoldi Viti 60.0\n", - "12 Vina Pedersen 65.0\n", - "13 Bajrami Thorstvedt 60.0\n", - "14 Fagioli Miretti 60.0\n", - "15 Mckennie Weah 55.0\n", - "16 Zaccagni Pedro 60.0\n", - "17 Romagnoli Patric 60.0\n", - "18 Guendouzi Kamada 55.0\n", - "19 Birindelli Kyriakopoulos 65.0\n", - "20 Maleh Bastoni S. 55.0\n", - "21 Fazzini Grassi 60.0\n", - "22 Bereszynski Ebuehi 60.0\n", - "23 Thuram Arnautovic 60.0\n", - "24 Dimarco Carlos Augusto 55.0\n", - "25 Pavard Darmian 60.0\n", - "26 De Vrij Acerbi 60.0\n", - "27 Frattesi Mkhitaryan 65.0\n", - "28 Zappacosta Zortea 60.0\n", - "29 Ruggeri Bakker 60.0\n", - "30 Toloi Djimsiti 55.0\n", - "31 Jankto Deiola 55.0\n", - "32 Obert Prati 55.0\n", - "33 Ebosele Ferreira J. 60.0\n", - "34 Kamara H. Zemura 60.0\n", - "35 Nzola Beltran L. 60.0\n", - "36 Mandragora Duncan 55.0\n", - "37 Ranieri L. Martinez Quarta 55.0\n", - "38 Kouame' Sottil 55.0\n", - "39 Moro N. Aebischer 55.0\n", - "40 Ndoye Orsolini 55.0\n", - "41 Zielinski Elmas 65.0\n", - "42 Juan Jesus Natan 55.0\n", - "43 Politano Raspadori 60.0\n", - "44 Mario Rui Olivera 55.0\n", - "45 Vlasic Seck 65.0\n", - "46 Ilic Tameze 55.0\n", - "47 Paredes Aouar 60.0\n", - "48 Kristensen Celik 60.0\n", - "49 Spinazzola Zalewski 60.0" + " player1 player2 percentage\n", + "0 Gallo Dorgu 60.0\n", + "1 Blin Gonzalez J. 60.0\n", + "2 Politano Lindstrom 60.0\n", + "3 Zambo Anguissa Cajuste 60.0\n", + "4 Zielinski Raspadori 55.0\n", + "5 Kvaratskhelia Elmas 65.0\n", + "6 Mario Rui Olivera 55.0\n", + "7 Calabria Florenzi 55.0\n", + "8 Pulisic Chukwueze 55.0\n", + "9 Reijnders Musah 65.0\n", + "10 Romagnoli Patric 65.0\n", + "11 Pellegrini Lu. Marusic 65.0\n", + "12 Immobile Castellanos 60.0\n", + "13 Luis Alberto Guendouzi 60.0\n", + "14 Daniliuc Lovato 60.0\n", + "15 Legowski Bohinen 60.0\n", + "16 Martegani Dia 60.0\n", + "17 Mkhitaryan Klaassen 55.0\n", + "18 Sanchez Martinez L. 55.0\n", + "19 Acerbi Bastoni 55.0\n", + "20 Moro N. Fabbian 55.0\n", + "21 Ferguson Aebischer 60.0\n", + "22 Ndoye Orsolini 60.0\n", + "23 Cancellieri Shpendi S. 60.0\n", + "24 Fazzini Ranocchia F. 60.0\n", + "25 Grassi Marin 60.0\n", + "26 Success Lucca 55.0\n", + "27 Ebosele Ferreira J. 60.0\n", + "28 Kamara H. Zemura 60.0\n", + "29 Martin Matturro 55.0\n", + "30 Pasalic Muriel 60.0\n", + "31 Ruggeri Holm 55.0\n", + "32 Mckennie Weah 60.0\n", + "33 Fagioli Miretti 60.0\n", + "34 Chiesa Milik 55.0\n", + "35 Dybala El Shaarawy 65.0\n", + "36 Zalewski Spinazzola 55.0\n", + "37 Paredes Celik 60.0\n", + "38 Caso Baez 60.0\n", + "39 Brescianini Garritano 60.0\n", + "40 Romagnoli S. Monterisi 60.0\n", + "41 Vina Pedersen 55.0\n", + "42 Erlic Viti 60.0\n", + "43 Bajrami Castillejo 60.0\n", + "44 Colombo Maric 65.0\n", + "45 Izzo D'ambrosio 60.0\n", + "46 Birindelli Kyriakopoulos 60.0\n", + "47 Bellanova Soppy 60.0\n", + "48 Lazaro Vojvoda 60.0\n", + "49 Zapata D. Sanabria 55.0\n", + "50 Bonazzoli Henry 60.0\n", + "51 Magnani Coppola D. 60.0\n", + "52 Folorunsho Saponara 55.0\n", + "53 Bonaventura Barak 60.0\n", + "54 Lopez M. Arthur Melo 55.0\n", + "55 Nzola Beltran L. 55.0\n", + "56 Nandez Deiola 60.0\n", + "57 Petagna Shomurodov 60.0\n", + "58 Hatzidiakos Obert 60.0" ] }, "execution_count": 5, @@ -653,29 +716,29 @@ " \n", " \n", " \n", - " Ochoa\n", + " Falcone\n", " 1\n", " 90.0\n", " \n", " \n", - " Lovato\n", + " Gendrey\n", + " 1\n", + " 90.0\n", + " \n", + " \n", + " Baschirotto\n", + " 1\n", + " 90.0\n", + " \n", + " \n", + " Pongracic\n", " 1\n", " 80.0\n", " \n", " \n", - " Gyomber\n", - " 1\n", - " 80.0\n", - " \n", - " \n", - " Pirola\n", - " 1\n", - " 80.0\n", - " \n", - " \n", - " Mazzocchi\n", - " 1\n", - " 80.0\n", + " Gallo\n", + " 0.6\n", + " 60.0\n", " \n", " \n", " ...\n", @@ -683,51 +746,51 @@ " ...\n", " \n", " \n", - " Pisilli\n", + " Oristanio\n", + " 0\n", + " 50.0\n", + " \n", + " \n", + " Jankto\n", + " 0\n", + " 15.0\n", + " \n", + " \n", + " Mancosu\n", " 0\n", " 10.0\n", " \n", " \n", - " Aouar\n", + " Pavoletti\n", + " 0\n", + " 55.0\n", + " \n", + " \n", + " Shomurodov\n", " 0.4\n", - " 55.0\n", - " \n", - " \n", - " El Shaarawy\n", - " 0\n", - " 55.0\n", - " \n", - " \n", - " Belotti\n", - " 0\n", " 60.0\n", " \n", - " \n", - " Azmoun\n", - " 0\n", - " 35.0\n", - " \n", " \n", "\n", - "

476 rows × 2 columns

\n", + "

467 rows × 2 columns

\n", "" ], "text/plain": [ " starter percentage\n", "player \n", - "Ochoa 1 90.0\n", - "Lovato 1 80.0\n", - "Gyomber 1 80.0\n", - "Pirola 1 80.0\n", - "Mazzocchi 1 80.0\n", + "Falcone 1 90.0\n", + "Gendrey 1 90.0\n", + "Baschirotto 1 90.0\n", + "Pongracic 1 80.0\n", + "Gallo 0.6 60.0\n", "... ... ...\n", - "Pisilli 0 10.0\n", - "Aouar 0.4 55.0\n", - "El Shaarawy 0 55.0\n", - "Belotti 0 60.0\n", - "Azmoun 0 35.0\n", + "Oristanio 0 50.0\n", + "Jankto 0 15.0\n", + "Mancosu 0 10.0\n", + "Pavoletti 0 55.0\n", + "Shomurodov 0.4 60.0\n", "\n", - "[476 rows x 2 columns]" + "[467 rows x 2 columns]" ] }, "execution_count": 6, diff --git a/6_neural_network_training_and_prediction.ipynb b/6_neural_network_training_and_prediction.ipynb index 78f7992..f1f5463 100644 --- a/6_neural_network_training_and_prediction.ipynb +++ b/6_neural_network_training_and_prediction.ipynb @@ -134,16 +134,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.020161\n", - " 0.012097\n", - " 0.012097\n", - " 0.016129\n", - " 0.008065\n", - " 0.016129\n", - " 0.391129\n", - " 0.040323\n", - " 0.020161\n", - " 0.012097\n", + " 0.018349\n", + " 0.009174\n", + " 0.009174\n", + " 0.015291\n", + " 0.009174\n", + " 0.015291\n", + " 0.376147\n", + " 0.033639\n", + " 0.015291\n", + " 0.012232\n", " \n", " \n", " 1\n", @@ -158,13 +158,13 @@ " 0.0\n", " 6.0\n", " ...\n", - " 0.007874\n", + " 0.004608\n", " 0.000000\n", - " 0.007874\n", - " 0.000000\n", - " 0.019685\n", - " 0.027559\n", - " 0.350394\n", + " 0.011521\n", + " 0.002304\n", + " 0.034562\n", + " 0.020737\n", + " 0.299539\n", " 0.000000\n", " 0.000000\n", " 0.000000\n", @@ -182,16 +182,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 0.002786\n", - " 0.002786\n", - " 0.002786\n", - " 0.011142\n", - " 0.013928\n", - " 0.022284\n", - " 0.412256\n", - " 0.019499\n", - " 0.025070\n", - " 0.002786\n", + " 0.009276\n", + " 0.001855\n", + " 0.009276\n", + " 0.014842\n", + " 0.016698\n", + " 0.022263\n", + " 0.378479\n", + " 0.014842\n", + " 0.016698\n", + " 0.001855\n", " \n", " \n", " 3\n", @@ -230,16 +230,16 @@ " 0.0\n", " 7.5\n", " ...\n", - " 0.012384\n", - " 0.003096\n", - " 0.012384\n", - " 0.006192\n", - " 0.003096\n", - " 0.027864\n", - " 0.408669\n", - " 0.015480\n", - " 0.012384\n", - " 0.003096\n", + " 0.010204\n", + " 0.002041\n", + " 0.014286\n", + " 0.004082\n", + " 0.010204\n", + " 0.020408\n", + " 0.357143\n", + " 0.016327\n", + " 0.014286\n", + " 0.004082\n", " \n", " \n", " ...\n", @@ -266,7 +266,7 @@ " ...\n", " \n", " \n", - " 30064\n", + " 30595\n", " 38\n", " Miguel Veloso\n", " Verona\n", @@ -290,7 +290,7 @@ " 0.000860\n", " \n", " \n", - " 30065\n", + " 30596\n", " 38\n", " Tameze\n", " Verona\n", @@ -314,7 +314,7 @@ " 0.001320\n", " \n", " \n", - " 30066\n", + " 30597\n", " 38\n", " Sulemana I.\n", " Verona\n", @@ -338,7 +338,7 @@ " 0.000000\n", " \n", " \n", - " 30067\n", + " 30598\n", " 38\n", " Djuric\n", " Verona\n", @@ -362,7 +362,7 @@ " 0.002196\n", " \n", " \n", - " 30068\n", + " 30599\n", " 38\n", " Ngonge\n", " Verona\n", @@ -387,7 +387,7 @@ " \n", " \n", "\n", - "

30069 rows × 122 columns

\n", + "

30600 rows × 122 columns

\n", "" ], "text/plain": [ @@ -398,65 +398,65 @@ "3 1 Zortea Atalanta Sassuolo 0 7.0 1 \n", "4 1 Ruggeri Atalanta Sassuolo 0 6.5 0 \n", "... ... ... ... ... ... ... ... \n", - "30064 38 Miguel Veloso Verona Milan 0 5.5 0 \n", - "30065 38 Tameze Verona Milan 0 5.5 0 \n", - "30066 38 Sulemana I. Verona Milan 0 6.0 0 \n", - "30067 38 Djuric Verona Milan 0 5.5 0 \n", - "30068 38 Ngonge Verona Milan 0 5.5 0 \n", + "30595 38 Miguel Veloso Verona Milan 0 5.5 0 \n", + "30596 38 Tameze Verona Milan 0 5.5 0 \n", + "30597 38 Sulemana I. Verona Milan 0 6.0 0 \n", + "30598 38 Djuric Verona Milan 0 5.5 0 \n", + "30599 38 Ngonge Verona Milan 0 5.5 0 \n", "\n", " assists cards_malus fantavote ... miscontrols dispossessed \\\n", - "0 0 0.0 6.5 ... 0.020161 0.012097 \n", - "1 0 0.0 6.0 ... 0.007874 0.000000 \n", - "2 0 0.0 6.5 ... 0.002786 0.002786 \n", + "0 0 0.0 6.5 ... 0.018349 0.009174 \n", + "1 0 0.0 6.0 ... 0.004608 0.000000 \n", + "2 0 0.0 6.5 ... 0.009276 0.001855 \n", "3 0 0.0 10.0 ... 0.000000 0.020833 \n", - "4 1 0.0 7.5 ... 0.012384 0.003096 \n", + "4 1 0.0 7.5 ... 0.010204 0.002041 \n", "... ... ... ... ... ... ... \n", - "30064 0 0.0 5.5 ... 0.006019 0.006019 \n", - "30065 0 0.0 5.5 ... 0.012867 0.011217 \n", - "30066 0 0.5 5.5 ... 0.015361 0.013825 \n", - "30067 0 0.0 5.5 ... 0.019034 0.010981 \n", - "30068 0 0.0 5.5 ... 0.030872 0.016107 \n", + "30595 0 0.0 5.5 ... 0.006019 0.006019 \n", + "30596 0 0.0 5.5 ... 0.012867 0.011217 \n", + "30597 0 0.5 5.5 ... 0.015361 0.013825 \n", + "30598 0 0.0 5.5 ... 0.019034 0.010981 \n", + "30599 0 0.0 5.5 ... 0.030872 0.016107 \n", "\n", " fouls fouled aerials_won aerials_lost carries \\\n", - "0 0.012097 0.016129 0.008065 0.016129 0.391129 \n", - "1 0.007874 0.000000 0.019685 0.027559 0.350394 \n", - "2 0.002786 0.011142 0.013928 0.022284 0.412256 \n", + "0 0.009174 0.015291 0.009174 0.015291 0.376147 \n", + "1 0.011521 0.002304 0.034562 0.020737 0.299539 \n", + "2 0.009276 0.014842 0.016698 0.022263 0.378479 \n", "3 0.031250 0.000000 0.000000 0.010417 0.447917 \n", - "4 0.012384 0.006192 0.003096 0.027864 0.408669 \n", + "4 0.014286 0.004082 0.010204 0.020408 0.357143 \n", "... ... ... ... ... ... \n", - "30064 0.017197 0.006879 0.012038 0.012038 0.265692 \n", - "30065 0.010558 0.010228 0.008908 0.010228 0.235236 \n", - "30066 0.016897 0.004608 0.015361 0.018433 0.201229 \n", - "30067 0.017570 0.021230 0.144217 0.041728 0.191801 \n", - "30068 0.017450 0.014765 0.022819 0.046980 0.242953 \n", + "30595 0.017197 0.006879 0.012038 0.012038 0.265692 \n", + "30596 0.010558 0.010228 0.008908 0.010228 0.235236 \n", + "30597 0.016897 0.004608 0.015361 0.018433 0.201229 \n", + "30598 0.017570 0.021230 0.144217 0.041728 0.191801 \n", + "30599 0.017450 0.014765 0.022819 0.046980 0.242953 \n", "\n", " progressive_carries carries_into_final_third \\\n", - "0 0.040323 0.020161 \n", + "0 0.033639 0.015291 \n", "1 0.000000 0.000000 \n", - "2 0.019499 0.025070 \n", + "2 0.014842 0.016698 \n", "3 0.062500 0.041667 \n", - "4 0.015480 0.012384 \n", + "4 0.016327 0.014286 \n", "... ... ... \n", - "30064 0.014617 0.011178 \n", - "30065 0.010558 0.011217 \n", - "30066 0.006144 0.010753 \n", - "30067 0.001464 0.003660 \n", - "30068 0.024161 0.014765 \n", + "30595 0.014617 0.011178 \n", + "30596 0.010558 0.011217 \n", + "30597 0.006144 0.010753 \n", + "30598 0.001464 0.003660 \n", + "30599 0.024161 0.014765 \n", "\n", " carries_into_penalty_area \n", - "0 0.012097 \n", + "0 0.012232 \n", "1 0.000000 \n", - "2 0.002786 \n", + "2 0.001855 \n", "3 0.010417 \n", - "4 0.003096 \n", + "4 0.004082 \n", "... ... \n", - "30064 0.000860 \n", - "30065 0.001320 \n", - "30066 0.000000 \n", - "30067 0.002196 \n", - "30068 0.012081 \n", + "30595 0.000860 \n", + "30596 0.001320 \n", + "30597 0.000000 \n", + "30598 0.002196 \n", + "30599 0.012081 \n", "\n", - "[30069 rows x 122 columns]" + "[30600 rows x 122 columns]" ] }, "execution_count": 4, @@ -537,13 +537,13 @@ " 2.100000\n", " 0.210000\n", " 0.100000\n", - " 11.000000\n", - " 34.000000\n", - " 88.000000\n", - " 18.000000\n", - " 18.000000\n", + " 14.000000\n", + " 48.000000\n", + " 119.000000\n", + " 25.000000\n", " 28.000000\n", - " 2.000000\n", + " 43.000000\n", + " 4.000000\n", " \n", " \n", " 1\n", @@ -558,16 +558,16 @@ " 0.0\n", " 4.0\n", " ...\n", - " 3.200000\n", - " 0.320000\n", - " -0.800000\n", - " 17.000000\n", - " 45.000000\n", - " 106.000000\n", - " 17.000000\n", - " 22.000000\n", - " 57.000000\n", - " 2.000000\n", + " 4.200000\n", + " 0.250000\n", + " 0.200000\n", + " 28.000000\n", + " 60.000000\n", + " 159.000000\n", + " 25.000000\n", + " 34.000000\n", + " 89.000000\n", + " 3.000000\n", " \n", " \n", " 2\n", @@ -582,16 +582,16 @@ " 0.0\n", " 6.5\n", " ...\n", - " 4.100000\n", - " 0.330000\n", - " 0.100000\n", - " 24.000000\n", - " 54.000000\n", - " 76.000000\n", - " 18.000000\n", - " 40.000000\n", - " 62.000000\n", - " 4.000000\n", + " 8.700000\n", + " 0.360000\n", + " -0.300000\n", + " 33.000000\n", + " 80.000000\n", + " 124.000000\n", + " 23.000000\n", + " 57.000000\n", + " 87.000000\n", + " 5.000000\n", " \n", " \n", " 3\n", @@ -606,15 +606,15 @@ " 0.0\n", " 4.0\n", " ...\n", - " 0.400000\n", - " 0.110000\n", - " -0.600000\n", - " 4.000000\n", - " 20.000000\n", - " 37.000000\n", - " 9.000000\n", - " 4.000000\n", - " 10.000000\n", + " 4.933333\n", + " 0.203333\n", + " -1.400000\n", + " 8.666667\n", + " 38.666667\n", + " 83.000000\n", + " 17.666667\n", + " 17.333333\n", + " 36.666667\n", " 2.000000\n", " \n", " \n", @@ -630,16 +630,16 @@ " 0.0\n", " 5.0\n", " ...\n", - " 1.000000\n", - " 0.170000\n", - " -2.000000\n", - " 13.000000\n", - " 20.000000\n", - " 85.000000\n", - " 10.000000\n", - " 9.000000\n", - " 16.000000\n", - " 1.000000\n", + " 4.100000\n", + " 0.240000\n", + " 0.100000\n", + " 28.000000\n", + " 57.000000\n", + " 151.000000\n", + " 14.000000\n", + " 22.000000\n", + " 44.000000\n", + " 3.000000\n", " \n", " \n", " ...\n", @@ -666,7 +666,7 @@ " ...\n", " \n", " \n", - " 2364\n", + " 2404\n", " 38\n", " Russo A.\n", " Sassuolo\n", @@ -690,7 +690,7 @@ " 23.333333\n", " \n", " \n", - " 2365\n", + " 2405\n", " 38\n", " Zoet\n", " Spezia\n", @@ -714,7 +714,7 @@ " 5.500000\n", " \n", " \n", - " 2366\n", + " 2406\n", " 38\n", " Milinkovic-Savic V.\n", " Torino\n", @@ -738,7 +738,7 @@ " 36.000000\n", " \n", " \n", - " 2367\n", + " 2407\n", " 38\n", " Silvestri\n", " Udinese\n", @@ -762,7 +762,7 @@ " 13.000000\n", " \n", " \n", - " 2368\n", + " 2408\n", " 38\n", " Montipo'\n", " Verona\n", @@ -787,7 +787,7 @@ " \n", " \n", "\n", - "

2369 rows × 102 columns

\n", + "

2409 rows × 102 columns

\n", "" ], "text/plain": [ @@ -798,65 +798,65 @@ "3 1 Caprile Empoli Verona 1 5.0 \n", "4 1 Terracciano Fiorentina Genoa 0 6.0 \n", "... ... ... ... ... ... ... \n", - "2364 38 Russo A. Sassuolo Fiorentina 1 5.0 \n", - "2365 38 Zoet Spezia Roma 0 5.5 \n", - "2366 38 Milinkovic-Savic V. Torino Inter 1 5.0 \n", - "2367 38 Silvestri Udinese Juventus 1 6.5 \n", - "2368 38 Montipo' Verona Milan 0 6.0 \n", + "2404 38 Russo A. Sassuolo Fiorentina 1 5.0 \n", + "2405 38 Zoet Spezia Roma 0 5.5 \n", + "2406 38 Milinkovic-Savic V. Torino Inter 1 5.0 \n", + "2407 38 Silvestri Udinese Juventus 1 6.5 \n", + "2408 38 Montipo' Verona Milan 0 6.0 \n", "\n", " goals assists cards_malus fantavote ... gk_psxg \\\n", "0 0 0 0.0 6.5 ... 2.100000 \n", - "1 -2 0 0.0 4.0 ... 3.200000 \n", - "2 0 0 0.0 6.5 ... 4.100000 \n", - "3 -1 0 0.0 4.0 ... 0.400000 \n", - "4 -1 0 0.0 5.0 ... 1.000000 \n", + "1 -2 0 0.0 4.0 ... 4.200000 \n", + "2 0 0 0.0 6.5 ... 8.700000 \n", + "3 -1 0 0.0 4.0 ... 4.933333 \n", + "4 -1 0 0.0 5.0 ... 4.100000 \n", "... ... ... ... ... ... ... \n", - "2364 -3 0 0.0 2.0 ... 32.550000 \n", - "2365 -2 0 0.5 3.0 ... 10.016667 \n", - "2366 -1 0 0.0 4.0 ... 35.800000 \n", - "2367 -1 0 0.0 5.5 ... 48.700000 \n", - "2368 -3 0 0.0 3.0 ... 49.600000 \n", + "2404 -3 0 0.0 2.0 ... 32.550000 \n", + "2405 -2 0 0.5 3.0 ... 10.016667 \n", + "2406 -1 0 0.0 4.0 ... 35.800000 \n", + "2407 -1 0 0.0 5.5 ... 48.700000 \n", + "2408 -3 0 0.0 3.0 ... 49.600000 \n", "\n", " gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n", "0 0.210000 0.100000 \n", - "1 0.320000 -0.800000 \n", - "2 0.330000 0.100000 \n", - "3 0.110000 -0.600000 \n", - "4 0.170000 -2.000000 \n", + "1 0.250000 0.200000 \n", + "2 0.360000 -0.300000 \n", + "3 0.203333 -1.400000 \n", + "4 0.240000 0.100000 \n", "... ... ... \n", - "2364 0.325000 -12.116667 \n", - "2365 0.158333 -1.816667 \n", - "2366 0.230000 -5.200000 \n", - "2367 0.310000 2.700000 \n", - "2368 0.270000 -6.400000 \n", + "2404 0.325000 -12.116667 \n", + "2405 0.158333 -1.816667 \n", + "2406 0.230000 -5.200000 \n", + "2407 0.310000 2.700000 \n", + "2408 0.270000 -6.400000 \n", "\n", " gk_passes_completed_launched gk_passes_launched gk_passes \\\n", - "0 11.000000 34.000000 88.000000 \n", - "1 17.000000 45.000000 106.000000 \n", - "2 24.000000 54.000000 76.000000 \n", - "3 4.000000 20.000000 37.000000 \n", - "4 13.000000 20.000000 85.000000 \n", + "0 14.000000 48.000000 119.000000 \n", + "1 28.000000 60.000000 159.000000 \n", + "2 33.000000 80.000000 124.000000 \n", + "3 8.666667 38.666667 83.000000 \n", + "4 28.000000 57.000000 151.000000 \n", "... ... ... ... \n", - "2364 146.666667 365.333333 957.000000 \n", - "2365 46.000000 145.333333 254.166667 \n", - "2366 285.000000 939.000000 1506.000000 \n", - "2367 144.000000 380.000000 872.000000 \n", - "2368 360.000000 775.000000 905.000000 \n", + "2404 146.666667 365.333333 957.000000 \n", + "2405 46.000000 145.333333 254.166667 \n", + "2406 285.000000 939.000000 1506.000000 \n", + "2407 144.000000 380.000000 872.000000 \n", + "2408 360.000000 775.000000 905.000000 \n", "\n", " gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n", - "0 18.000000 18.000000 28.000000 2.000000 \n", - "1 17.000000 22.000000 57.000000 2.000000 \n", - "2 18.000000 40.000000 62.000000 4.000000 \n", - "3 9.000000 4.000000 10.000000 2.000000 \n", - "4 10.000000 9.000000 16.000000 1.000000 \n", + "0 25.000000 28.000000 43.000000 4.000000 \n", + "1 25.000000 34.000000 89.000000 3.000000 \n", + "2 23.000000 57.000000 87.000000 5.000000 \n", + "3 17.666667 17.333333 36.666667 2.000000 \n", + "4 14.000000 22.000000 44.000000 3.000000 \n", "... ... ... ... ... \n", - "2364 156.166667 238.833333 391.500000 23.333333 \n", - "2365 37.333333 51.833333 130.333333 5.500000 \n", - "2366 185.000000 286.000000 469.000000 36.000000 \n", - "2367 142.000000 302.000000 547.000000 13.000000 \n", - "2368 124.000000 284.000000 496.000000 26.000000 \n", + "2404 156.166667 238.833333 391.500000 23.333333 \n", + "2405 37.333333 51.833333 130.333333 5.500000 \n", + "2406 185.000000 286.000000 469.000000 36.000000 \n", + "2407 142.000000 302.000000 547.000000 13.000000 \n", + "2408 124.000000 284.000000 496.000000 26.000000 \n", "\n", - "[2369 rows x 102 columns]" + "[2409 rows x 102 columns]" ] }, "execution_count": 5, @@ -918,7 +918,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_5452\\661405348.py:3: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", + "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_6176\\661405348.py:3: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", " avg_row = pd.DataFrame(index = ['Avg'], data = [team_data.mean()], columns = team_data.columns)\n" ] }, @@ -970,506 +970,506 @@ " \n", " Atalanta\n", " Atalanta\n", - " 23.00\n", - " 49.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 8.00\n", - " 8.00\n", + " 24.0\n", + " 50.50\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 11.0\n", + " 11.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 36.0\n", - " 47.0\n", - " 2.0\n", - " 0.0\n", + " 57.00\n", + " 74.0\n", + " 4.00\n", " 0.0\n", " 0.00\n", - " 212.00\n", - " 65.0\n", - " 60.0\n", - " 52.00\n", + " 0.00\n", + " 347.00\n", + " 97.00\n", + " 109.00\n", + " 47.100\n", " \n", " \n", " Bologna\n", " Bologna\n", - " 22.00\n", - " 56.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.00\n", + " 23.0\n", + " 54.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 3.0\n", " 2.00\n", " 0.00\n", - " 1.0\n", + " 1.00\n", " ...\n", - " 50.0\n", - " 40.0\n", - " 12.0\n", + " 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57.000\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 10.00\n", - " 8.00\n", + " 23.0\n", + " 59.70\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 12.0\n", + " 9.00\n", + " 1.00\n", " 1.00\n", - " 1.0\n", " ...\n", - " 46.0\n", - " 51.0\n", - " 4.0\n", - " 1.0\n", + " 58.00\n", + " 67.0\n", + " 4.00\n", " 1.0\n", " 1.00\n", - " 159.00\n", - " 54.0\n", - " 76.0\n", - " 41.50\n", + " 1.00\n", + " 267.00\n", + " 83.00\n", + " 104.00\n", + " 44.400\n", " \n", " \n", " Salernitana\n", " Salernitana\n", - " 21.00\n", - " 51.500\n", + " 22.0\n", + " 52.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", " 4.0\n", - " 44.0\n", - " 360.0\n", - " 3.00\n", " 3.00\n", " 0.00\n", - " 0.0\n", + " 0.00\n", " ...\n", - " 64.0\n", - " 46.0\n", - " 4.0\n", - " 0.0\n", + " 94.00\n", + " 70.0\n", + " 12.00\n", " 0.0\n", " 0.00\n", - " 203.00\n", - " 86.0\n", - " 54.0\n", - " 61.40\n", + " 0.00\n", + " 311.00\n", + " 120.00\n", + " 82.00\n", + " 59.400\n", " \n", " \n", " Sassuolo\n", " Sassuolo\n", - " 24.00\n", - " 43.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.00\n", - " 4.00\n", + " 25.0\n", + " 42.30\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 10.0\n", + " 7.00\n", + " 1.00\n", " 1.00\n", - " 1.0\n", " ...\n", - " 45.0\n", - " 34.0\n", - " 15.0\n", + " 63.00\n", + " 55.0\n", + " 20.00\n", " 2.0\n", - " 1.0\n", - " 0.00\n", - " 207.00\n", - " 50.0\n", - " 37.0\n", - " 57.50\n", + " 1.00\n", + " 1.00\n", + " 299.00\n", + " 85.00\n", + " 55.00\n", + " 60.700\n", " \n", " \n", " Torino\n", " Torino\n", - " 22.00\n", - " 51.300\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.00\n", - " 3.00\n", + " 23.0\n", + " 49.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 6.0\n", + " 4.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 44.0\n", - " 48.0\n", - " 7.0\n", + " 61.00\n", + " 64.0\n", + " 7.00\n", " 1.0\n", - " 0.0\n", " 0.00\n", - " 207.00\n", - " 63.0\n", - " 59.0\n", - " 51.60\n", + " 0.00\n", + " 302.00\n", + " 93.00\n", + " 82.00\n", + " 53.100\n", " \n", " \n", " Udinese\n", " Udinese\n", - " 22.00\n", - " 48.500\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 1.00\n", - " 1.00\n", + " 24.0\n", + " 46.20\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 2.0\n", + " 2.00\n", + " 0.00\n", " 0.00\n", - " 0.0\n", " ...\n", - " 43.0\n", - " 51.0\n", - " 10.0\n", - " 0.0\n", - " 0.0\n", + " 65.00\n", + " 74.0\n", + " 11.00\n", + " 1.0\n", " 0.00\n", - " 188.00\n", - " 52.0\n", - " 64.0\n", - " 44.80\n", + " 0.00\n", + " 297.00\n", + " 68.00\n", + " 101.00\n", + " 40.200\n", " \n", " \n", " Avg\n", " Avg\n", - " 21.45\n", - " 50.025\n", - " 4.0\n", - " 44.0\n", - " 360.0\n", - " 5.65\n", - " 4.35\n", - " 0.65\n", - " 0.8\n", + " 22.9\n", + " 50.01\n", + " 6.0\n", + " 66.0\n", + " 540.0\n", + " 7.7\n", + " 5.75\n", + " 0.75\n", + " 0.95\n", " ...\n", - " 48.7\n", - " 45.6\n", - " 6.8\n", - " 0.5\n", - " 0.8\n", - " 0.05\n", - " 194.05\n", - " 50.8\n", - " 50.8\n", - " 49.86\n", + " 71.35\n", + " 67.1\n", + " 9.95\n", + " 0.6\n", + " 0.95\n", + " 0.15\n", + " 296.25\n", + " 76.75\n", + " 76.75\n", + " 49.675\n", " \n", " \n", "\n", @@ -1478,165 +1478,165 @@ ], "text/plain": [ " team team_players_used team_possession team_games \\\n", - "Atalanta Atalanta 23.00 49.500 4.0 \n", - "Bologna Bologna 22.00 56.500 4.0 \n", - "Cagliari Cagliari 21.00 37.800 4.0 \n", - "Empoli Empoli 27.00 47.800 4.0 \n", - "Fiorentina Fiorentina 22.00 61.000 4.0 \n", - "Frosinone Frosinone 23.00 48.300 4.0 \n", - "Genoa Genoa 19.00 33.300 4.0 \n", - "Verona Hellas Verona 21.00 43.500 4.0 \n", - "Inter Inter 19.00 48.800 4.0 \n", - "Juventus Juventus 21.00 48.800 4.0 \n", - "Lazio Lazio 20.00 56.000 4.0 \n", - "Lecce Lecce 19.00 43.500 4.0 \n", - "Milan Milan 19.00 55.300 4.0 \n", - "Monza Monza 22.00 56.800 4.0 \n", - "Napoli Napoli 19.00 61.800 4.0 \n", - "Roma Roma 23.00 57.000 4.0 \n", - "Salernitana Salernitana 21.00 51.500 4.0 \n", - "Sassuolo Sassuolo 24.00 43.500 4.0 \n", - "Torino Torino 22.00 51.300 4.0 \n", - "Udinese Udinese 22.00 48.500 4.0 \n", - "Avg Avg 21.45 50.025 4.0 \n", + "Atalanta Atalanta 24.0 50.50 6.0 \n", + "Bologna Bologna 23.0 54.70 6.0 \n", + "Cagliari Cagliari 22.0 38.20 6.0 \n", + "Empoli Empoli 28.0 45.30 6.0 \n", + "Fiorentina Fiorentina 24.0 57.20 6.0 \n", + "Frosinone Frosinone 24.0 49.20 6.0 \n", + "Genoa Genoa 22.0 34.30 6.0 \n", + "Verona Hellas Verona 22.0 45.20 6.0 \n", + "Inter Inter 22.0 53.20 6.0 \n", + "Juventus Juventus 22.0 50.30 6.0 \n", + "Lazio Lazio 20.0 54.00 6.0 \n", + "Lecce Lecce 22.0 46.70 6.0 \n", + "Milan Milan 23.0 56.80 6.0 \n", + "Monza Monza 23.0 54.20 6.0 \n", + "Napoli Napoli 20.0 60.70 6.0 \n", + "Roma Roma 23.0 59.70 6.0 \n", + "Salernitana Salernitana 22.0 52.30 6.0 \n", + "Sassuolo Sassuolo 25.0 42.30 6.0 \n", + "Torino Torino 23.0 49.20 6.0 \n", + "Udinese Udinese 24.0 46.20 6.0 \n", + "Avg Avg 22.9 50.01 6.0 \n", "\n", " team_games_starts team_minutes team_goals team_assists \\\n", - "Atalanta 44.0 360.0 8.00 8.00 \n", - "Bologna 44.0 360.0 3.00 2.00 \n", - "Cagliari 44.0 360.0 1.00 1.00 \n", - "Empoli 44.0 360.0 0.00 0.00 \n", - "Fiorentina 44.0 360.0 9.00 7.00 \n", - "Frosinone 44.0 360.0 7.00 4.00 \n", - "Genoa 44.0 360.0 4.00 3.00 \n", - "Verona 44.0 360.0 4.00 2.00 \n", - "Inter 44.0 360.0 13.00 11.00 \n", - "Juventus 44.0 360.0 9.00 7.00 \n", - "Lazio 44.0 360.0 4.00 4.00 \n", - "Lecce 44.0 360.0 7.00 5.00 \n", - "Milan 44.0 360.0 9.00 6.00 \n", - "Monza 44.0 360.0 3.00 3.00 \n", - "Napoli 44.0 360.0 8.00 5.00 \n", - "Roma 44.0 360.0 10.00 8.00 \n", - "Salernitana 44.0 360.0 3.00 3.00 \n", - "Sassuolo 44.0 360.0 5.00 4.00 \n", - "Torino 44.0 360.0 5.00 3.00 \n", - "Udinese 44.0 360.0 1.00 1.00 \n", - "Avg 44.0 360.0 5.65 4.35 \n", + "Atalanta 66.0 540.0 11.0 11.00 \n", + "Bologna 66.0 540.0 3.0 2.00 \n", + "Cagliari 66.0 540.0 2.0 2.00 \n", + "Empoli 66.0 540.0 1.0 1.00 \n", + "Fiorentina 66.0 540.0 12.0 9.00 \n", + "Frosinone 66.0 540.0 9.0 5.00 \n", + "Genoa 66.0 540.0 8.0 7.00 \n", + "Verona 66.0 540.0 4.0 2.00 \n", + "Inter 66.0 540.0 15.0 12.00 \n", + "Juventus 66.0 540.0 11.0 9.00 \n", + "Lazio 66.0 540.0 7.0 6.00 \n", + "Lecce 66.0 540.0 8.0 6.00 \n", + "Milan 66.0 540.0 13.0 8.00 \n", + "Monza 66.0 540.0 4.0 3.00 \n", + "Napoli 66.0 540.0 12.0 7.00 \n", + "Roma 66.0 540.0 12.0 9.00 \n", + "Salernitana 66.0 540.0 4.0 3.00 \n", + "Sassuolo 66.0 540.0 10.0 7.00 \n", + "Torino 66.0 540.0 6.0 4.00 \n", + "Udinese 66.0 540.0 2.0 2.00 \n", + "Avg 66.0 540.0 7.7 5.75 \n", "\n", " team_pens_made team_pens_att ... vs_team_fouls \\\n", - "Atalanta 0.00 0.0 ... 36.0 \n", - "Bologna 0.00 1.0 ... 50.0 \n", - "Cagliari 0.00 0.0 ... 38.0 \n", - "Empoli 0.00 0.0 ... 60.0 \n", - "Fiorentina 0.00 0.0 ... 56.0 \n", - "Frosinone 2.00 2.0 ... 50.0 \n", - "Genoa 0.00 0.0 ... 43.0 \n", - "Verona 0.00 0.0 ... 47.0 \n", - "Inter 2.00 2.0 ... 47.0 \n", - "Juventus 1.00 2.0 ... 52.0 \n", - "Lazio 0.00 0.0 ... 49.0 \n", - "Lecce 2.00 2.0 ... 64.0 \n", - "Milan 3.00 3.0 ... 56.0 \n", - "Monza 0.00 0.0 ... 37.0 \n", - "Napoli 1.00 2.0 ... 47.0 \n", - "Roma 1.00 1.0 ... 46.0 \n", - "Salernitana 0.00 0.0 ... 64.0 \n", - "Sassuolo 1.00 1.0 ... 45.0 \n", - "Torino 0.00 0.0 ... 44.0 \n", - "Udinese 0.00 0.0 ... 43.0 \n", - "Avg 0.65 0.8 ... 48.7 \n", + "Atalanta 0.00 0.00 ... 57.00 \n", + "Bologna 0.00 1.00 ... 71.00 \n", + "Cagliari 0.00 0.00 ... 50.00 \n", + "Empoli 0.00 0.00 ... 84.00 \n", + "Fiorentina 0.00 0.00 ... 75.00 \n", + "Frosinone 2.00 2.00 ... 73.00 \n", + "Genoa 0.00 0.00 ... 67.00 \n", + "Verona 0.00 0.00 ... 84.00 \n", + "Inter 2.00 2.00 ... 70.00 \n", + "Juventus 1.00 2.00 ... 80.00 \n", + "Lazio 1.00 1.00 ... 69.00 \n", + "Lecce 2.00 2.00 ... 88.00 \n", + "Milan 3.00 3.00 ... 80.00 \n", + "Monza 0.00 0.00 ... 65.00 \n", + "Napoli 2.00 4.00 ... 73.00 \n", + "Roma 1.00 1.00 ... 58.00 \n", + "Salernitana 0.00 0.00 ... 94.00 \n", + "Sassuolo 1.00 1.00 ... 63.00 \n", + "Torino 0.00 0.00 ... 61.00 \n", + "Udinese 0.00 0.00 ... 65.00 \n", + "Avg 0.75 0.95 ... 71.35 \n", "\n", " vs_team_fouled vs_team_offsides vs_team_pens_won \\\n", - "Atalanta 47.0 2.0 0.0 \n", - "Bologna 40.0 12.0 0.0 \n", - "Cagliari 41.0 5.0 0.0 \n", - "Empoli 42.0 8.0 1.0 \n", - "Fiorentina 43.0 5.0 1.0 \n", - "Frosinone 39.0 6.0 0.0 \n", - "Genoa 43.0 9.0 0.0 \n", - "Verona 63.0 7.0 1.0 \n", - "Inter 44.0 5.0 0.0 \n", - "Juventus 49.0 5.0 0.0 \n", - "Lazio 44.0 7.0 0.0 \n", - "Lecce 53.0 5.0 0.0 \n", - "Milan 43.0 7.0 1.0 \n", - "Monza 52.0 6.0 1.0 \n", - "Napoli 39.0 7.0 1.0 \n", - "Roma 51.0 4.0 1.0 \n", - "Salernitana 46.0 4.0 0.0 \n", - "Sassuolo 34.0 15.0 2.0 \n", - "Torino 48.0 7.0 1.0 \n", - "Udinese 51.0 10.0 0.0 \n", - "Avg 45.6 6.8 0.5 \n", + "Atalanta 74.0 4.00 0.0 \n", + "Bologna 70.0 16.00 0.0 \n", + "Cagliari 65.0 11.00 0.0 \n", + "Empoli 74.0 10.00 1.0 \n", + "Fiorentina 63.0 8.00 1.0 \n", + "Frosinone 54.0 15.00 0.0 \n", + "Genoa 60.0 12.00 0.0 \n", + "Verona 84.0 11.00 1.0 \n", + "Inter 64.0 9.00 0.0 \n", + "Juventus 71.0 6.00 0.0 \n", + "Lazio 67.0 10.00 0.0 \n", + "Lecce 78.0 5.00 0.0 \n", + "Milan 60.0 8.00 1.0 \n", + "Monza 68.0 11.00 2.0 \n", + "Napoli 60.0 9.00 1.0 \n", + "Roma 67.0 4.00 1.0 \n", + "Salernitana 70.0 12.00 0.0 \n", + "Sassuolo 55.0 20.00 2.0 \n", + "Torino 64.0 7.00 1.0 \n", + "Udinese 74.0 11.00 1.0 \n", + "Avg 67.1 9.95 0.6 \n", "\n", " vs_team_pens_conceded vs_team_own_goals \\\n", - "Atalanta 0.0 0.00 \n", - "Bologna 1.0 0.00 \n", - "Cagliari 0.0 0.00 \n", - "Empoli 0.0 0.00 \n", - "Fiorentina 0.0 0.00 \n", - "Frosinone 2.0 0.00 \n", - "Genoa 0.0 0.00 \n", - "Verona 0.0 0.00 \n", - "Inter 2.0 0.00 \n", - "Juventus 2.0 0.00 \n", - "Lazio 0.0 0.00 \n", - "Lecce 2.0 0.00 \n", - "Milan 3.0 0.00 \n", - "Monza 0.0 0.00 \n", - "Napoli 2.0 0.00 \n", - "Roma 1.0 1.00 \n", - "Salernitana 0.0 0.00 \n", - "Sassuolo 1.0 0.00 \n", - "Torino 0.0 0.00 \n", - "Udinese 0.0 0.00 \n", - "Avg 0.8 0.05 \n", + "Atalanta 0.00 0.00 \n", + "Bologna 1.00 0.00 \n", + "Cagliari 0.00 0.00 \n", + "Empoli 0.00 0.00 \n", + "Fiorentina 0.00 0.00 \n", + "Frosinone 2.00 0.00 \n", + "Genoa 0.00 0.00 \n", + "Verona 0.00 0.00 \n", + "Inter 2.00 0.00 \n", + "Juventus 2.00 1.00 \n", + "Lazio 1.00 0.00 \n", + "Lecce 2.00 0.00 \n", + "Milan 3.00 0.00 \n", + "Monza 0.00 0.00 \n", + "Napoli 4.00 0.00 \n", + "Roma 1.00 1.00 \n", + "Salernitana 0.00 0.00 \n", + "Sassuolo 1.00 1.00 \n", + "Torino 0.00 0.00 \n", + "Udinese 0.00 0.00 \n", + "Avg 0.95 0.15 \n", "\n", " vs_team_ball_recoveries vs_team_aerials_won \\\n", - "Atalanta 212.00 65.0 \n", - "Bologna 207.00 34.0 \n", - "Cagliari 220.00 60.0 \n", - "Empoli 203.00 54.0 \n", - "Fiorentina 202.00 56.0 \n", - "Frosinone 212.00 53.0 \n", - "Genoa 200.00 46.0 \n", - "Verona 190.00 71.0 \n", - "Inter 163.00 30.0 \n", - "Juventus 173.00 26.0 \n", - "Lazio 196.00 51.0 \n", - "Lecce 203.00 43.0 \n", - "Milan 176.00 42.0 \n", - "Monza 187.00 45.0 \n", - "Napoli 173.00 35.0 \n", - "Roma 159.00 54.0 \n", - "Salernitana 203.00 86.0 \n", - "Sassuolo 207.00 50.0 \n", - "Torino 207.00 63.0 \n", - "Udinese 188.00 52.0 \n", - "Avg 194.05 50.8 \n", + "Atalanta 347.00 97.00 \n", + "Bologna 292.00 47.00 \n", + "Cagliari 332.00 92.00 \n", + "Empoli 313.00 82.00 \n", + "Fiorentina 311.00 96.00 \n", + "Frosinone 325.00 79.00 \n", + "Genoa 295.00 66.00 \n", + "Verona 326.00 116.00 \n", + "Inter 248.00 46.00 \n", + "Juventus 267.00 41.00 \n", + "Lazio 282.00 66.00 \n", + "Lecce 295.00 67.00 \n", + "Milan 281.00 65.00 \n", + "Monza 281.00 74.00 \n", + "Napoli 254.00 52.00 \n", + "Roma 267.00 83.00 \n", + "Salernitana 311.00 120.00 \n", + "Sassuolo 299.00 85.00 \n", + "Torino 302.00 93.00 \n", + "Udinese 297.00 68.00 \n", + "Avg 296.25 76.75 \n", "\n", " vs_team_aerials_lost vs_team_aerials_won_pct \n", - "Atalanta 60.0 52.00 \n", - "Bologna 46.0 42.50 \n", - "Cagliari 51.0 54.10 \n", - "Empoli 39.0 58.10 \n", - "Fiorentina 53.0 51.40 \n", - "Frosinone 52.0 50.50 \n", - "Genoa 60.0 43.40 \n", - "Verona 82.0 46.40 \n", - "Inter 44.0 40.50 \n", - "Juventus 38.0 40.60 \n", - "Lazio 30.0 63.00 \n", - "Lecce 54.0 44.30 \n", - "Milan 33.0 56.00 \n", - "Monza 37.0 54.90 \n", - "Napoli 47.0 42.70 \n", - "Roma 76.0 41.50 \n", - "Salernitana 54.0 61.40 \n", - "Sassuolo 37.0 57.50 \n", - "Torino 59.0 51.60 \n", - "Udinese 64.0 44.80 \n", - "Avg 50.8 49.86 \n", + "Atalanta 109.00 47.100 \n", + "Bologna 73.00 39.200 \n", + "Cagliari 71.00 56.400 \n", + "Empoli 60.00 57.700 \n", + "Fiorentina 75.00 56.100 \n", + "Frosinone 80.00 49.700 \n", + "Genoa 83.00 44.300 \n", + "Verona 117.00 49.800 \n", + "Inter 77.00 37.400 \n", + "Juventus 67.00 38.000 \n", + "Lazio 53.00 55.500 \n", + "Lecce 73.00 47.900 \n", + "Milan 61.00 51.600 \n", + "Monza 56.00 56.900 \n", + "Napoli 56.00 48.100 \n", + "Roma 104.00 44.400 \n", + "Salernitana 82.00 59.400 \n", + "Sassuolo 55.00 60.700 \n", + "Torino 82.00 53.100 \n", + "Udinese 101.00 40.200 \n", + "Avg 76.75 49.675 \n", "\n", "[21 rows x 303 columns]" ] @@ -3639,7 +3639,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 12, "id": "6f8707b8", "metadata": {}, "outputs": [ @@ -3649,22 +3649,22 @@ "text": [ " \n", "Averaging players stats with past seasons:\n", - "Szczesny 0.41758241758241765\n", - "Meret 0.6877828054298643\n", - "Provedel 0.6153846153846154\n", + "Szczesny 0.8351648351648353\n", + "Meret 1\n", + "Provedel 0.9230769230769229\n", "Maignan 1\n", - "Rui Patricio 0.6681318681318682\n", - "Skorupski 0.632016632016632\n", - "Milinkovic-Savic V. 0.6153846153846154\n", - "Di Gregorio 0.47401247401247393\n", - "Falcone 0.6153846153846154\n", - "Silvestri 0.6153846153846154\n", - "Terracciano 0.40318302387267907\n", - "Carnesecchi 0.22735042735042738\n", - "Montipo' 0.632016632016632\n", + "Rui Patricio 1\n", + "Skorupski 0.9480249480249479\n", + "Milinkovic-Savic V. 0.9230769230769229\n", + "Di Gregorio 0.79002079002079\n", + "Falcone 0.9230769230769229\n", + "Silvestri 0.9230769230769229\n", + "Terracciano 0.8063660477453581\n", + "Carnesecchi 0.6062678062678064\n", + "Montipo' 0.9480249480249479\n", "Ochoa 1\n", - "Consigli 0.501098901098901\n", - "Musso 0.7307692307692307\n", + "Consigli 0.6681318681318682\n", + "Musso 0.9743589743589745\n", "Cragno 1\n", "Perin 1\n", "Berisha 1\n", @@ -3676,8 +3676,8 @@ "Perilli 1\n", "Padelli 1\n", "Gollini 1\n", - "Perisan 0.8351648351648353\n", - "Audero 0.9821538461538462\n", + "Perisan 1\n", + "Audero 1\n", "Pinsoglio 1\n", "Fiorillo 1\n", "Cerofolini 1\n", @@ -3690,164 +3690,164 @@ "Bagnolini 1\n", "Svilar 1\n", "Sorrentino A. 1\n", - "Dimarco 0.3543123543123543\n", - "Di Lorenzo 0.316008316008316\n", - "Hernandez T. 0.3653846153846154\n", - "Carlos Augusto 0.3507692307692308\n", - "Danilo 0.316008316008316\n", - "Zappacosta 0.5567765567765568\n", - "Schuurs 0.38974358974358975\n", - "Posch 0.38974358974358975\n", - "Bastoni 0.40318302387267907\n", + "Dimarco 0.5314685314685313\n", + "Di Lorenzo 0.47401247401247393\n", + "Hernandez T. 0.4567307692307692\n", + "Carlos Augusto 0.5261538461538462\n", + "Danilo 0.47401247401247393\n", + "Zappacosta 0.6959706959706958\n", + "Schuurs 0.5846153846153845\n", + "Posch 0.4871794871794871\n", + "Bastoni 0.6047745358090184\n", "Smalling 0.2740384615384615\n", - "Dumfries 0.3438914027149321\n", - "Romagnoli 0.3438914027149321\n", - "Pavard 0.0 (rookie)\n", + "Dumfries 0.42986425339366513\n", + "Romagnoli 0.5158371040723981\n", + "Pavard 0.10230769230769231 (rookie)\n", "Rrahmani 0.3023872679045092\n", - "Spinazzola 0.44970414201183434\n", - "Buongiorno 0.3438914027149321\n", - "Bremer 0.38974358974358975\n", - "Tomori 0.2657342657342657\n", - "Biraghi 0.2657342657342657\n", - "Mancini 0.3340659340659341\n", - "Darmian 0.3771712158808933\n", + "Spinazzola 0.6745562130177514\n", + "Buongiorno 0.5158371040723981\n", + "Bremer 0.5846153846153845\n", + "Tomori 0.4428904428904428\n", + "Biraghi 0.4428904428904428\n", + "Mancini 0.501098901098901\n", + "Darmian 0.5657568238213398\n", "Bakker 0.21923076923076926 (rookie)\n", - "Mazzocchi 0.4330484330484331\n", + "Mazzocchi 0.6495726495726495\n", "Doig 0.5314685314685315\n", "Calabria 0.4676923076923077\n", - "Acerbi 0.09429280397022333\n", + "Acerbi 0.2828784119106699\n", "Cuadrado 0.29702233250620347\n", - "Ebuehi 0.22485207100591717\n", - "Casale 0.3023872679045092\n", - "Holm 0.15346153846153848\n", - "Baschirotto 0.316008316008316\n", - "Bijol 0.3653846153846154\n", - "Thiaw 0.5846153846153846\n", - "Mario Rui 0.39860139860139854\n", - "Milenkovic 0.4330484330484331\n", - "Rodriguez R. 0.3340659340659341\n", - "Kolasinac 0.37202797202797205 (rookie)\n", - "N'dicka 0.10230769230769231 (rookie)\n", - "Scalvini 0.3653846153846154\n", - "Perez N. 0.3438914027149321\n", + "Ebuehi 0.44970414201183434\n", + "Casale 0.40318302387267907\n", + "Holm 0.4603846153846154\n", + "Baschirotto 0.395010395010395\n", + "Bijol 0.548076923076923\n", + "Thiaw 0.8769230769230768\n", + "Mario Rui 0.6643356643356643\n", + "Milenkovic 0.6495726495726495\n", + "Rodriguez R. 0.501098901098901\n", + "Kolasinac 0.558041958041958 (rookie)\n", + "N'dicka 0.3069230769230769 (rookie)\n", + "Scalvini 0.548076923076923\n", + "Perez N. 0.5158371040723981\n", "Kristensen 0.0 (rookie)\n", - "Izzo 0.29230769230769227\n", - "De Vrij 0.4330484330484331\n", - "Faraoni 0.38127090301003336\n", - "Toloi 0.09134615384615385\n", - "Kyriakopoulos 0.5115384615384616\n", - "Bellanova 0.6820512820512822\n", - "Mari' 0.38974358974358975\n", - "Dodo' 0.3543123543123543\n", - "Lucumi' 0.3543123543123543\n", - "Hien 0.1826923076923077\n", - "Hysaj 0.17194570135746606\n", - "D'ambrosio 0.40923076923076923\n", - "Luperto 0.3247863247863248\n", - "Djimsiti 0.36538461538461536\n", - "Marusic 0.3543123543123543\n", - "Martin 0.4384615384615385 (rookie)\n", + "Izzo 0.4871794871794871\n", + "De Vrij 0.6495726495726495\n", + "Faraoni 0.6354515050167223\n", + "Toloi 0.2740384615384615\n", + "Kyriakopoulos 1\n", + "Kyriakopoulos 0.423342175066313 (two seasons ago)\n", + "Bellanova 1\n", + "Mari' 0.5846153846153845\n", + "Dodo' 0.4428904428904428\n", + "Lucumi' 0.4428904428904428\n", + "Hien 0.3653846153846154\n", + "Hysaj 0.3438914027149321\n", + "D'ambrosio 0.6138461538461538\n", + "Luperto 0.4871794871794871\n", + "Djimsiti 0.6089743589743589\n", + "Marusic 0.5314685314685313\n", + "Martin 0.5480769230769231 (rookie)\n", "Mina 0.0 (rookie)\n", - "Toljan 0.3771712158808933\n", + "Toljan 0.5657568238213398\n", "Llorente D. 1\n", - "Martinez Quarta 0.21652421652421655\n", + "Martinez Quarta 0.4330484330484331\n", "Bastoni S. 0.16153846153846155\n", - "Dragusin 0.3230769230769231 (rookie)\n", - "Parisi 0.18601398601398603\n", - "Bradaric 0.3771712158808933\n", - "Olivera 0.38974358974358975\n", - "Gendrey 0.316008316008316\n", - "Kristiansen 0.5115384615384616 (rookie)\n", - "Beukema 0.47218934911242605 (rookie)\n", - "Dossena 0.5337792642140469 (rookie)\n", - "Pedersen 0.3175066312997347 (rookie)\n", + "Dragusin 0.4846153846153846 (rookie)\n", + "Parisi 0.279020979020979\n", + "Bradaric 0.5657568238213398\n", + "Olivera 0.4871794871794871\n", + "Gendrey 0.47401247401247393\n", + "Kristiansen 1 (rookie)\n", + "Beukema 0.7082840236686391 (rookie)\n", + "Dossena 0.8006688963210702 (rookie)\n", + "Pedersen 0.5291777188328912 (rookie)\n", "Juan Jesus 0.7794871794871795\n", - "Gyomber 0.4330484330484331\n", + "Gyomber 0.6495726495726495\n", "Alex Sandro 0.23384615384615384\n", - "Hateboer 0.0\n", - "Palomino 0.19487179487179487\n", + "Hateboer 0.17194570135746606\n", + "Palomino 0.38974358974358975\n", "Marchizza 1\n", - "Marchizza 0.6461538461538462 (two seasons ago)\n", - "Zappa 0.4676923076923077 (two seasons ago)\n", - "Gallo 0.3653846153846154\n", - "Caldirola 0.3771712158808933\n", + "Gallo 0.4567307692307692\n", + "Caldirola 0.4714640198511166\n", "Kalulu 0.17194570135746606\n", - "Erlic 0.41758241758241765\n", + "Erlic 0.6263736263736263\n", "Vojvoda 0.3023872679045092\n", - "Vasquez 0.4910769230769231\n", - "Cambiaso 0.3836538461538462\n", + "Vasquez 0.7366153846153846\n", + "Cambiaso 0.4795673076923077\n", "Pongracic 1\n", - "Viti 0.3410256410256411 (rookie)\n", - "Gatti 0.3247863247863248\n", - "Birindelli 0.3771712158808933\n", - "Azzi 0.7673076923076924 (rookie)\n", + "Viti 1 (rookie)\n", + "Viti 0.4603846153846154 (two seasons ago)\n", + "Gatti 0.6495726495726496\n", + "Birindelli 0.5657568238213398\n", + "Azzi 0.9591346153846154 (rookie)\n", "Masina 0.0\n", "Romagnoli S. 1\n", - "Romagnoli S. 0.6461538461538462 (two seasons ago)\n", - "Pezzella Giu. 0.7673076923076924\n", - "Sabelli 0.3069230769230769 (rookie)\n", - "Lazzari 0.20879120879120883\n", - "Bani 0.37202797202797205 (rookie)\n", + "Pezzella Giu. 1\n", + "Sabelli 0.5115384615384615 (rookie)\n", + "Lazzari 0.31318681318681313\n", + "Bani 0.558041958041958 (rookie)\n", "Djidji 0.0\n", - "Lazaro 0.38127090301003336\n", - "Augello 0.24885654885654884\n", + "Lazaro 0.6354515050167223\n", + "Augello 0.41476091476091476\n", "Zortea 0.9207692307692308\n", "Zortea 0.3762046521118139 (two seasons ago)\n", - "Dawidowicz 0.5083612040133779\n", - "Pirola 0.3372781065088757\n", - "Lovato 0.6877828054298643\n", - "Ruggeri 0.7794871794871795\n", - "Vina 0.47218934911242605 (two seasons ago)\n", + "Dawidowicz 0.7625418060200667\n", + "Pirola 0.5621301775147929\n", + "Lovato 1\n", + "Ruggeri 1\n", "Obert 1 (two seasons ago)\n", - "Terracciano F. 0.5846153846153846\n", - "Ebosele 0.6877828054298643\n", - "Patric 0.1623931623931624\n", - "Lykogiannis 0.2783882783882784\n", + "Terracciano F. 0.8769230769230768\n", + "Ebosele 1\n", + "Patric 0.3247863247863248\n", + "Lykogiannis 0.4175824175824175\n", "Pellegrini Lu. 1\n", - "Pellegrini Lu. 0.6820512820512822 (two seasons ago)\n", - "Magnani 0.4871794871794872\n", - "Ranieri L. 0.6495726495726496\n", - "Ranieri L. 0.5061947549127037 (two seasons ago)\n", + "Pellegrini Lu. 0.8525641025641026 (two seasons ago)\n", + "Magnani 0.7307692307692307\n", + "Ranieri L. 0.9743589743589742\n", + "Ranieri L. 0.35851413543721244 (two seasons ago)\n", "Calafiori 1 (two seasons ago)\n", "Monterisi 1 (rookie)\n", - "Ismajli 0.35076923076923067\n", - "De Winter 0.21923076923076926\n", + "Ismajli 0.4676923076923077\n", + "De Winter 0.6576923076923077\n", "Ehizibue 0.0\n", - "Ferrari G. 0.0\n", - "Venuti 0.0\n", + "Ferrari G. 0.17715617715617715\n", + "Venuti 0.18054298642533936\n", "Karsdorp 0.44970414201183434\n", - "Kjaer 0.5158371040723981\n", + "Kjaer 0.6877828054298643\n", "Gunter 0.0\n", "Soumaoro 0.0\n", "Zanoli 0.0\n", "Zima 0.3247863247863248\n", - "Hefti 0.548076923076923 (two seasons ago)\n", + "Hefti 0.7307692307692308 (two seasons ago)\n", "Ostigard 1\n", "Ostigard 1 (two seasons ago)\n", "Sambia 0.13286713286713286\n", - "Rugani 0.0\n", + "Rugani 0.3247863247863248\n", "De Sciglio 0.0\n", "Goldaniga 0.26573426573426573 (two seasons ago)\n", - "Florenzi 0.9743589743589745\n", - "Florenzi 0.2560815253122945 (two seasons ago)\n", - "De Silvestri 0.38974358974358975\n", + "Florenzi 1\n", + "Florenzi 0.4871794871794872 (two seasons ago)\n", + "De Silvestri 0.7794871794871795\n", "Fazio 0.41758241758241765\n", "Bereszynski 1\n", - "Bereszynski 0.1753846153846154 (two seasons ago)\n", + "Bereszynski 0.2630769230769231 (two seasons ago)\n", "Bonifazi 0.0\n", - "Walukiewicz 0.5314685314685315\n", - "Okoli 0.18054298642533936\n", + "Walukiewicz 1\n", + "Walukiewicz 1 (two seasons ago)\n", + "Okoli 0.5416289592760181\n", "Kumbulla 0.0\n", "Celik 0.1217948717948718\n", "Amione 0.11804733727810651\n", - "Daniliuc 0.0\n", - "Soppy 0.20461538461538462\n", + "Daniliuc 0.21652421652421655\n", + "Soppy 0.40923076923076923\n", "Haps 0.0 (two seasons ago)\n", "Coppola D. 0.3076923076923077\n", - "Cacace 0.4871794871794872\n", + "Cacace 0.7307692307692307\n", + "Cacace 1 (two seasons ago)\n", "Ebosse 0.14615384615384616\n", "Guessand A. 1\n", - "Cabal 0.5314685314685315\n", + "Cabal 0.7972027972027971\n", "Dermaku 0.0\n", "Tonelli 0.0\n", "Tonelli 0.20879120879120883 (two seasons ago)\n", @@ -3856,132 +3856,130 @@ "Bronn 0.0\n", "Guarino 0.0\n", "Carboni F. 1\n", - "Zaccagni 0.3340659340659341\n", - "Koopmeiners 0.3543123543123543\n", - "Luis Alberto 0.3340659340659341\n", - "Felipe Anderson 0.3076923076923077\n", - "Rabiot 0.3653846153846154\n", - "Zielinski 0.316008316008316\n", - "Barella 0.3340659340659341\n", - "Pulisic 0.5115384615384616 (rookie)\n", - "Orsolini 0.3653846153846154\n", - "Calhanoglu 0.3543123543123543\n", - "Strefezza 0.3340659340659341\n", - "Chukwueze 0.3318087318087318 (rookie)\n", - "Ferguson 0.3653846153846154\n", - "Candreva 0.3340659340659341\n", - "Frattesi 0.3410256410256411\n", - "Samardzic 0.316008316008316\n", - "Vlasic 0.25791855203619907\n", - "Bonaventura 0.38974358974358975\n", - "Politano 0.4330484330484331\n", - "El Shaarawy 0.40318302387267907\n", - "Mkhitaryan 0.3771712158808933\n", - "Aouar 0.5754807692307693 (rookie)\n", - "Malinovskyi 0.3069230769230769 (two seasons ago)\n", - "Gudmundsson A. 0.3410256410256411 (rookie)\n", + "Zaccagni 0.501098901098901\n", + "Koopmeiners 0.5314685314685313\n", + "Luis Alberto 0.501098901098901\n", + "Felipe Anderson 0.46153846153846145\n", + "Rabiot 0.548076923076923\n", + "Zielinski 0.47401247401247393\n", + "Barella 0.501098901098901\n", + "Pulisic 0.7673076923076924 (rookie)\n", + "Orsolini 0.548076923076923\n", + "Calhanoglu 0.5314685314685313\n", + "Strefezza 0.501098901098901\n", + "Chukwueze 0.41476091476091476 (rookie)\n", + "Ferguson 0.548076923076923\n", + "Candreva 0.501098901098901\n", + "Frattesi 0.5115384615384616\n", + "Samardzic 0.47401247401247393\n", + "Vlasic 0.42986425339366513\n", + "Bonaventura 0.5846153846153845\n", + "Politano 0.6495726495726495\n", + "El Shaarawy 0.6047745358090184\n", + "Mkhitaryan 0.5657568238213398\n", + "Aouar 0.7673076923076924 (rookie)\n", + "Malinovskyi 0.40923076923076923 (two seasons ago)\n", + "Gudmundsson A. 0.5115384615384616 (rookie)\n", "Kamada 0.3836538461538462 (rookie)\n", - "Pellegrini Lo. 0.1826923076923077\n", - "Kostic 0.158004158004158\n", - "Radonjic 0.41758241758241765\n", - "Baldanzi 0.44970414201183434\n", - "Lovric 0.316008316008316\n", + "Pellegrini Lo. 0.2740384615384615\n", + "Kostic 0.316008316008316\n", + "Radonjic 0.6263736263736263\n", + "Baldanzi 0.6745562130177514\n", + "Lovric 0.47401247401247393\n", "Lindstrom 0.0 (rookie)\n", - "Lazovic 0.09743589743589744\n", - "Pereyra 0.08597285067873303\n", + "Lazovic 0.29230769230769227\n", + "Pereyra 0.25791855203619907\n", "Renato Sanches 0.26688963210702343 (rookie)\n", - "Pessina 0.3340659340659341\n", - "Guendouzi 0.18601398601398603 (rookie)\n", - "Loftus-Cheek 0.4910769230769231 (rookie)\n", - "Zambo Anguissa 0.3247863247863248\n", - "Elmas 0.24358974358974356\n", - "Bajrami 0.6495726495726496\n", - "Ricci S. 0.41758241758241765\n", - "Colpani 0.4330484330484331\n", - "Ciurria 0.3247863247863248\n", - "De Roon 0.3340659340659341\n", + "Pessina 0.501098901098901\n", + "Guendouzi 0.37202797202797205 (rookie)\n", + "Loftus-Cheek 0.7366153846153846 (rookie)\n", + "Zambo Anguissa 0.4871794871794871\n", + "Elmas 0.405982905982906\n", + "Bajrami 0.9743589743589742\n", + "Ricci S. 0.521978021978022\n", + "Colpani 0.6495726495726495\n", + "Ciurria 0.4871794871794871\n", + "De Roon 0.501098901098901\n", "Pogba 0.9743589743589745\n", - "Cristante 0.3247863247863248\n", - "Locatelli 0.3653846153846154\n", - "Pasalic 0.1826923076923077\n", - "Lobotka 0.3076923076923077\n", - "Fagioli 0.3372781065088757\n", - "Ikone' 0.0\n", - "Ilic 0.6263736263736263\n", - "Ederson D.s. 0.3340659340659341\n", - "Reijnders 0.3610859728506787 (rookie)\n", - "Barak 0.09743589743589744\n", - "Saponara 0.2116710875331565\n", - "Mandragora 0.40318302387267907\n", - "Weah 0.423342175066313 (rookie)\n", + "Cristante 0.4871794871794871\n", + "Locatelli 0.548076923076923\n", + "Pasalic 0.3653846153846154\n", + "Lobotka 0.46153846153846145\n", + "Fagioli 0.5621301775147929\n", + "Ikone' 0.08857808857808858\n", + "Ilic 1\n", + "Ilic 0.4795673076923077 (two seasons ago)\n", + "Ederson D.s. 0.501098901098901\n", + "Reijnders 0.5416289592760181 (rookie)\n", + "Barak 0.19487179487179487\n", + "Saponara 0.423342175066313\n", + "Mandragora 0.6047745358090184\n", + "Weah 0.6350132625994694 (rookie)\n", "Bennacer 0.0\n", - "Duda 0.7794871794871795\n", + "Duda 1\n", "Castrovilli 0.0\n", - "Mckennie 0.5567765567765568 (two seasons ago)\n", - "Miranchuk 0.10583554376657825\n", - "Matheus Henrique 0.38974358974358975\n", - "De Ketelaere 0.3836538461538462\n", - "Paredes 0.4910769230769231\n", - "Sottil 0.4871794871794871\n", - "Klaassen 0.0 (rookie)\n", - "Thorsby 0.3507692307692308 (two seasons ago)\n", - "Nandez 0.37202797202797205 (rookie)\n", - "Tameze 0.1659043659043659\n", - "Marin 0.2657342657342657\n", - "Messias 0.0\n", + "Miranchuk 0.2116710875331565\n", + "Matheus Henrique 0.5846153846153845\n", + "De Ketelaere 0.5754807692307693\n", + "Paredes 0.7366153846153846\n", + "Sottil 0.6495726495726496\n", + "Klaassen 0.09300699300699301 (rookie)\n", + "Thorsby 0.43846153846153846 (two seasons ago)\n", + "Nandez 0.558041958041958 (rookie)\n", + "Tameze 0.3318087318087318\n", + "Marin 0.4428904428904428\n", + "Messias 0.12276923076923077\n", "Coulibaly L. 0.08351648351648353\n", - "Krunic 0.5083612040133779\n", - "Cataldi 0.40318302387267907\n", - "Strootman 0.3069230769230769 (rookie)\n", - "Duncan 0.35076923076923067\n", - "Freuler 0.10961538461538463 (rookie)\n", - "Gagliardini 0.6461538461538462\n", - "Kastanos 0.41758241758241765\n", - "Gyasi 0.2630769230769231\n", - "Zalewski 0.2657342657342657\n", + "Krunic 0.6354515050167223\n", + "Cataldi 0.5039787798408487\n", + "Strootman 0.5115384615384615 (rookie)\n", + "Duncan 0.5846153846153845\n", + "Freuler 0.21923076923076926 (rookie)\n", + "Gagliardini 0.9692307692307692\n", + "Kastanos 0.6263736263736263\n", + "Gyasi 0.3507692307692308\n", + "Zalewski 0.3543123543123543\n", "Harroui 0.4003344481605351\n", - "Frendrup 0.3318087318087318 (rookie)\n", - "Blin 0.3340659340659341\n", + "Frendrup 0.4977130977130977 (rookie)\n", + "Blin 0.501098901098901\n", "Fabbian 0.2557692307692308 (rookie)\n", - "Vecino 0.1826923076923077\n", + "Vecino 0.3653846153846154\n", "Sensi 0.10961538461538463\n", - "Walace 0.316008316008316\n", - "Lopez M. 0.20461538461538462\n", - "Bove 0.39860139860139854\n", - "Aebischer 0.3653846153846154\n", + "Walace 0.47401247401247393\n", + "Lopez M. 0.10230769230769231\n", + "Bove 0.5314685314685315\n", + "Aebischer 0.548076923076923\n", "Thorstvedt 0.3771712158808933\n", "Gonzalez J. 0.2505494505494505\n", "Moro N. 0.44970414201183434\n", - "Oudin 0.0\n", - "Makoumbou 0.3410256410256411 (rookie)\n", - "Badelj 0.3438914027149321 (two seasons ago)\n", + "Oudin 0.18858560794044665\n", + "Makoumbou 0.5115384615384616 (rookie)\n", "Machin 0.0\n", "Linetty 0.3653846153846154\n", - "Castillejo 0.12276923076923077 (rookie)\n", - "Rovella 0.12276923076923077\n", - "Pobega 0.3076923076923077\n", - "Hongla 0.6495726495726496 (two seasons ago)\n", - "Miretti 0.32478632478632474\n", - "Fazzini 0.4175824175824175\n", - "Grassi 0.35076923076923067\n", - "Baez 0.7221719457013575 (rookie)\n", - "Deiola 0.3543123543123543 (two seasons ago)\n", - "Bourabia 0.0\n", - "Saelemaekers 0.0\n", + "Castillejo 0.3683076923076923 (rookie)\n", + "Rovella 0.3683076923076923\n", + "Pobega 0.6153846153846154\n", + "Miretti 0.5413105413105412\n", + "Fazzini 0.6959706959706958\n", + "Grassi 0.5846153846153845\n", + "Baez 1 (rookie)\n", + "Bourabia 0.1659043659043659\n", + "Saelemaekers 0.20461538461538462\n", "Maldini 0.0\n", "Kovalenko 0.17051282051282055\n", - "Maleh 0.3610859728506787\n", - "Bohinen 0.36538461538461536\n", - "Ranocchia F. 0.0\n", - "Folorunsho 0.45470085470085475 (rookie)\n", - "Adopo 0.6820512820512822\n", - "Romero L. 0.0\n", + "Maleh 0.7221719457013575\n", + "Bohinen 0.6089743589743589\n", + "Ranocchia F. 0.21923076923076926\n", + "Folorunsho 0.6820512820512821 (rookie)\n", + "Adopo 1\n", + "Romero L. 0.5115384615384616\n", + "Romero L. 1 (two seasons ago)\n", "Basic 0.0\n", "Asllani 0.2923076923076923\n", - "Sulemana I. 0.5754807692307693\n", + "Sulemana I. 0.9591346153846154\n", "Gaetano 0.0\n", "Obiang 0.0\n", - "Maggiore 0.1826923076923077\n", + "Maggiore 0.548076923076923\n", "Akpa Akpro 0.0\n", "Akpa Akpro 0.0 (two seasons ago)\n", "Urbanski 1\n", @@ -3989,97 +3987,97 @@ "Volpato 1 (two seasons ago)\n", "Vignato S. 1\n", "Hrustic 0.0\n", - "Viola 0.0 (two seasons ago)\n" + "Viola 1 (two seasons ago)\n", + "Rog 0.0 (two seasons ago)\n", + "Nicolussi Caviglia 0.0\n", + "Demme 0.0\n", + "Pafundi 0.3653846153846154\n", + "Adli 0.4871794871794872\n", + "Zerbin 0.2923076923076923\n", + "Carboni V. 1\n", + "Faticanti 0.0\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Rog 0.0 (two seasons ago)\n", - "Nicolussi Caviglia 0.0\n", - "Demme 0.0\n", - "Pafundi 0.0\n", - "Adli 0.0\n", - "Zerbin 0.2923076923076923\n", - "Carboni V. 1\n", - "Faticanti 0.0\n", - "Osimhen 0.3653846153846154\n", - "Martinez L. 0.3076923076923077\n", - "Rafael Leao 0.3340659340659341\n", - "Lukaku 0.24553846153846154\n", - "Berardi 0.22485207100591717\n", - "Immobile 0.3771712158808933\n", - "Vlahovic 0.4330484330484331\n", - "Dybala 0.23384615384615384\n", - "Kvaratskhelia 0.25791855203619907\n", - "Giroud 0.3543123543123543\n", + "Osimhen 0.548076923076923\n", + "Martinez L. 0.46153846153846145\n", + "Rafael Leao 0.501098901098901\n", + "Lukaku 0.4910769230769231\n", + "Berardi 0.44970414201183434\n", + "Immobile 0.5657568238213398\n", + "Vlahovic 0.6495726495726495\n", + "Dybala 0.4676923076923077\n", + "Kvaratskhelia 0.42986425339366513\n", + "Giroud 0.4428904428904428\n", "Scamacca 0.3410256410256411 (two seasons ago)\n", - "Thuram 0.40923076923076923 (rookie)\n", - "Lookman 0.3771712158808933\n", - "Dia 0.17715617715617715\n", - "Arnautovic 0.5846153846153845\n", - "Retegui 0.5846153846153845 (rookie)\n", - "Sanabria 0.17715617715617715\n", - "Nzola 0.396029776674938\n", - "Lauriente' 0.41758241758241765\n", - "Zapata D. 0.24553846153846154\n", - "Chiesa 0.5567765567765568\n", - "Milik 0.4330484330484331\n", - "Gonzalez N. 0.4871794871794872\n", - "Pinamonti 0.3653846153846154\n", - "Beltran L. 0.4910769230769231 (rookie)\n", + "Thuram 0.6138461538461538 (rookie)\n", + "Lookman 0.5657568238213398\n", + "Dia 0.2657342657342657\n", + "Arnautovic 0.7307692307692307\n", + "Retegui 0.8769230769230768 (rookie)\n", + "Sanabria 0.3543123543123543\n", + "Nzola 0.5940446650124069\n", + "Lauriente' 0.6263736263736263\n", + "Zapata D. 0.4910769230769231\n", + "Chiesa 0.835164835164835\n", + "Milik 0.6495726495726495\n", + "Gonzalez N. 0.6089743589743589\n", + "Pinamonti 0.548076923076923\n", + "Beltran L. 0.7366153846153846 (rookie)\n", "Caprari 0.316008316008316\n", - "Sanchez 0.0 (rookie)\n", + "Sanchez 0.1753846153846154 (rookie)\n", "Caputo 0.5567765567765568\n", - "Belotti 0.3771712158808933\n", - "Muriel 0.20159151193633953\n", + "Belotti 0.5657568238213398\n", + "Muriel 0.3023872679045092\n", "Lapadula 0.0 (rookie)\n", - "Jovic 0.0990074441687345\n", + "Jovic 0.198014888337469\n", "Abraham 0.0\n", - "Zirkzee 0.6153846153846154\n", - "Ngonge 0.8351648351648353\n", - "Petagna 0.0990074441687345\n", - "Simeone 0.35076923076923067\n", + "Zirkzee 0.9230769230769229\n", + "Ngonge 1\n", + "Petagna 0.29702233250620347\n", + "Simeone 0.5846153846153845\n", "Deulofeu 0.0\n", - "Pedro 0.24358974358974356\n", - "Shomurodov 0.8184615384615385\n", - "Shomurodov 0.6573550295857988 (two seasons ago)\n", - "Azmoun 0.13344481605351172 (rookie)\n", - "Cheddira 0.29702233250620347 (rookie)\n", - "Karlsson 0.4003344481605351 (rookie)\n", + "Pedro 0.3247863247863248\n", + "Shomurodov 1\n", + "Azmoun 0.26688963210702343 (rookie)\n", + "Cheddira 0.49503722084367247 (rookie)\n", + "Karlsson 0.6672240802675585 (rookie)\n", "Brekalo 1\n", - "Brekalo 0.3836538461538462 (two seasons ago)\n", - "Cambiaghi 0.31318681318681313\n", - "Henry 0.0\n", + "Brekalo 0.4795673076923077 (two seasons ago)\n", + "Cambiaghi 0.521978021978022\n", + "Henry 0.1826923076923077\n", "Mulattieri 0.423342175066313 (rookie)\n", - "Kean 0.20879120879120883\n", - "Karamoh 0.4175824175824175\n", - "Thauvin 0.7307692307692308\n", - "Kouame' 0.31318681318681313\n", - "Raspadori 0.4676923076923077\n", - "Colombo 0.18601398601398603\n", + "Kean 0.31318681318681313\n", + "Karamoh 0.5567765567765568\n", + "Thauvin 1\n", + "Kouame' 0.41758241758241765\n", + "Raspadori 0.7015384615384613\n", + "Colombo 0.37202797202797205\n", "Luvumbo 0.0 (rookie)\n", - "Mota 0.40318302387267907\n", - "Bonazzoli 0.5115384615384616\n", - "Djuric 0.41758241758241765\n", + "Mota 0.6047745358090184\n", + "Bonazzoli 0.7673076923076924\n", + "Djuric 0.521978021978022\n", "Banda 0.3247863247863248\n", - "Defrel 0.10826210826210828\n", - "Sansone 0.0\n", - "Pellegri 0.6495726495726496\n", - "Piccoli 0.47218934911242605\n", - "Success 0.29230769230769227\n", - "Botheim 0.41758241758241765\n", - "Lucca 0.876923076923077 (rookie)\n", - "Caso 0.2630769230769231 (rookie)\n", + "Defrel 0.32478632478632474\n", + "Sansone 0.3410256410256411\n", + "Pellegri 0.9743589743589742\n", + "Piccoli 0.9443786982248521\n", + "Piccoli 1 (two seasons ago)\n", + "Success 0.4871794871794871\n", + "Botheim 0.6263736263736263\n", + "Lucca 1 (rookie)\n", + "Caso 0.43846153846153846 (rookie)\n", "Jovane 0.0 (two seasons ago)\n", - "Soule' 0.47218934911242605\n", + "Soule' 0.9443786982248521\n", "Pavoletti 0.4003344481605351 (rookie)\n", - "Cancellieri 0.6138461538461539\n", - "Seck 0.3076923076923077\n", + "Cancellieri 0.9207692307692308\n", + "Seck 0.46153846153846145\n", "Alvarez A. 0.0\n", - "Ekuban 0.29230769230769227 (two seasons ago)\n", - "Destro 0.3438914027149321\n", + "Ekuban 0.38974358974358975 (two seasons ago)\n", + "Destro 0.5158371040723981\n", "Ceide 0.46153846153846145\n", "Ake' M. 0.0 (two seasons ago)\n", "Braaf 0.0\n", @@ -4088,36 +4086,36 @@ "Kaio Jorge 0.0 (two seasons ago)\n", "Vivaldo 0.0\n", "Players with low quantity of games:\n", - "Natan 0.0\n", - "Llorente D. 0.6666666666666667\n", - "Kamara H. 0.6666666666666667\n", - "Pongracic 0.6666666666666667\n", - "Wieteska 0.33333333333333337\n", + "Natan 0.33333333333333337\n", + "Kristiansen 0.6666666666666667\n", + "Azzi 0.908253205128205\n", + "Wieteska 0.5\n", "Lirola 0.16666666666666663\n", "Kabasele 0.6666666666666667\n", - "Obert 0.5\n", - "Zemura 0.5\n", - "Hatzidiakos 0.16666666666666663\n", + "Obert 0.6666666666666667\n", + "Zemura 0.8333333333333334\n", + "Hatzidiakos 0.5\n", "Carboni A. 0.33333333333333337\n", - "Calafiori 0.16666666666666663\n", - "Monterisi 0.6666666666666667\n", + "Calafiori 0.5\n", + "Monterisi 0.8333333333333334\n", "Tressoldi 0.0\n", "Vogliacco 0.0\n", - "Di Pardo 0.6666666666666667\n", - "Ostigard 0.5\n", + "Di Pardo 0.8333333333333334\n", + "Ostigard 0.8333333333333334\n", "Bisseck 0.16666666666666663\n", - "Oyono 0.6666666666666667\n", - "Ferreira J. 0.6666666666666667\n", - "Dorgu 0.6666666666666667\n", - "Touba 0.16666666666666663\n", - "Sazonov 0.0\n", + "Ferreira J. 0.8333333333333334\n", + "Touba 0.33333333333333337\n", + "Sazonov 0.16666666666666663\n", "Pereira P. 0.5\n", + "Walukiewicz 0.6666666666666667\n", "Cittadini 0.0\n", + "Cacace 0.9038461538461539\n", "Guessand A. 0.16666666666666663\n", + "Cabal 0.7703962703962706\n", "Missori 0.16666666666666663\n", - "Kayode 0.16666666666666663\n", - "Corazza 0.33333333333333337\n", - "Kristensen T. 0.0\n", + "Kayode 0.5\n", + "Corazza 0.5\n", + "Kristensen T. 0.33333333333333337\n", "Dermaku 0.16666666666666663\n", "Capradossi 0.0\n", "Bettella 0.0\n", @@ -4126,7 +4124,7 @@ "Guarino 0.0\n", "Carboni F. 0.33333333333333337\n", "Smajlovic 0.0\n", - "Matturro 0.0\n", + "Matturro 0.16666666666666663\n", "N'guessan 0.0\n", "Mateus Lusuardi 0.0\n", "Kalaj 0.0\n", @@ -4136,80 +4134,76 @@ "Pellegrino 0.0\n", "Comuzzo 0.0\n", "Pogba 0.3504273504273504\n", - "Ndoye 0.6666666666666667\n", "Mboula 0.5\n", - "Arthur Melo 0.6666666666666667\n", - "Musah 0.33333333333333337\n", - "Mazzitelli 0.6666666666666667\n", + "Musah 0.6666666666666667\n", "Jankto 0.5\n", "Reinier 0.0\n", - "Ramadani 0.6666666666666667\n", "Cajuste 0.0\n", "Mancosu 0.0\n", - "Brescianini 0.5\n", - "Boloca 0.5\n", - "Rafia 0.6666666666666667\n", - "Kaba 0.6666666666666667\n", + "Brescianini 0.8333333333333334\n", + "Boloca 0.8333333333333334\n", "Machin 0.0\n", "Iling Junior 0.0\n", - "Oristanio 0.5\n", - "Serdar 0.5\n", - "Payero 0.16666666666666663\n", - "Garritano 0.5\n", + "Oristanio 0.8333333333333334\n", + "Serdar 0.6666666666666667\n", + "Payero 0.5\n", + "Garritano 0.8333333333333334\n", "Racic 0.33333333333333337\n", "Infantino 0.5\n", - "Martegani 0.5\n", - "Kutlu 0.16666666666666663\n", + "Martegani 0.8333333333333334\n", + "Kutlu 0.33333333333333337\n", "Tchatchoua 0.0\n", "Quina 0.33333333333333337\n", - "Adopo 0.7042735042735042\n", - "Tchaouna 0.33333333333333337\n", - "Barrenechea 0.6666666666666667\n", + "Adopo 0.5\n", + "Romero L. 0.5737179487179487\n", + "Tchaouna 0.5\n", + "Sulemana I. 0.908253205128205\n", "Gelli 0.6666666666666667\n", - "Suslov 0.16666666666666663\n", + "Suslov 0.5\n", "Jagiello 0.0\n", "Akpa Akpro 0.0\n", "Urbanski 0.33333333333333337\n", "Volpato 0.7282051282051283\n", - "Vignato S. 0.33333333333333337\n", + "Vignato S. 0.6666666666666667\n", "Zarraga 0.33333333333333337\n", "Camara E. 0.0\n", "Amatucci 0.16666666666666663\n", "Pagano 0.5\n", "Prati 0.16666666666666663\n", + "Viola 0.33333333333333337\n", "Lulic K. 0.0\n", + "Pafundi 0.9070512820512819\n", + "Adli 0.5940170940170939\n", "Bondo 0.16666666666666663\n", "Carboni V. 0.33333333333333337\n", "Faticanti 0.0\n", "Gineitis 0.16666666666666663\n", "Belardinelli 0.0\n", - "El Azzouzi 0.5\n", + "El Azzouzi 0.8333333333333334\n", "Lipani 0.0\n", "Joselito 0.0\n", "Legowski 0.0\n", "Ibrahimovic A. 0.0\n", - "Okafor 0.6666666666666667\n", "Toure' E. 0.0\n", - "Krstovic 0.5\n", - "Ngonge 0.9413919413919412\n", - "Castellanos 0.6666666666666667\n", - "Almqvist 0.6666666666666667\n", - "Isaksen 0.5\n", + "Krstovic 0.8333333333333334\n", + "Castellanos 0.8333333333333334\n", + "Isaksen 0.8333333333333334\n", "Brenner 0.0\n", "Davis K. 0.0\n", - "Lucca 0.8717948717948717\n", + "Piccoli 0.7500986193293885\n", "Jovane 0.0\n", - "Cuni 0.5\n", - "Maric 0.5\n", + "Soule' 0.7500986193293885\n", + "Cuni 0.8333333333333334\n", + "Maric 0.8333333333333334\n", "Cruz 0.0\n", - "Van Hooijdonk 0.16666666666666663\n", - "Kvernadze 0.16666666666666663\n", - "Ikwuemesi 0.5\n", - "Puscas 0.0\n", + "Van Hooijdonk 0.33333333333333337\n", + "Kvernadze 0.33333333333333337\n", + "Ikwuemesi 0.6666666666666667\n", + "Puscas 0.16666666666666663\n", "Ake' M. 0.6666666666666667\n", "Vivaldo 0.0\n", "Bidaoui 0.0\n", - "Shpendi S. 0.5\n", + "Shpendi S. 0.8333333333333334\n", "Burnete 0.16666666666666663\n", "Corfitzen 0.0\n", "Stewart 0.0\n", @@ -4341,7 +4335,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "49c28b07", "metadata": {}, "outputs": [ @@ -4359,7 +4353,7 @@ " dtype='object', length=151)" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -4370,7 +4364,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "d29102e5", "metadata": {}, "outputs": [ @@ -4522,7 +4516,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "f19304f6", "metadata": {}, "outputs": [], @@ -4562,7 +4556,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "370d41d2", "metadata": {}, "outputs": [], @@ -4578,7 +4572,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "id": "a7b1fb52", "metadata": {}, "outputs": [ @@ -4698,7 +4692,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "id": "5a7cf079", "metadata": {}, "outputs": [], @@ -4722,7 +4716,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "0bc0568b", "metadata": {}, "outputs": [], @@ -4844,7 +4838,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "id": "8aad9652", "metadata": {}, "outputs": [ @@ -4853,27 +4847,35 @@ "output_type": "stream", "text": [ "Epoch 1/1000\n", - "94/94 [==============================] - 4s 9ms/step - loss: 2.1251 - distribution_lambda_loss: 0.8284 - distribution_lambda_1_loss: 1.2967 - val_loss: 2.0962 - val_distribution_lambda_loss: 0.8157 - val_distribution_lambda_1_loss: 1.2804\n", + "96/96 [==============================] - 4s 11ms/step - loss: 2.1171 - distribution_lambda_loss: 0.8241 - distribution_lambda_1_loss: 1.2930 - val_loss: 2.0956 - val_distribution_lambda_loss: 0.8197 - val_distribution_lambda_1_loss: 1.2759\n", "Epoch 2/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1244 - distribution_lambda_loss: 0.8284 - distribution_lambda_1_loss: 1.2960 - val_loss: 2.1000 - val_distribution_lambda_loss: 0.8174 - val_distribution_lambda_1_loss: 1.2826\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1179 - distribution_lambda_loss: 0.8238 - distribution_lambda_1_loss: 1.2940 - val_loss: 2.0975 - val_distribution_lambda_loss: 0.8208 - val_distribution_lambda_1_loss: 1.2767\n", "Epoch 3/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1246 - distribution_lambda_loss: 0.8271 - distribution_lambda_1_loss: 1.2976 - val_loss: 2.1027 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2832\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1124 - distribution_lambda_loss: 0.8215 - distribution_lambda_1_loss: 1.2909 - val_loss: 2.0966 - val_distribution_lambda_loss: 0.8195 - val_distribution_lambda_1_loss: 1.2771\n", "Epoch 4/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1244 - distribution_lambda_loss: 0.8265 - distribution_lambda_1_loss: 1.2978 - val_loss: 2.1046 - val_distribution_lambda_loss: 0.8192 - val_distribution_lambda_1_loss: 1.2854\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1125 - distribution_lambda_loss: 0.8226 - distribution_lambda_1_loss: 1.2899 - val_loss: 2.1005 - val_distribution_lambda_loss: 0.8228 - val_distribution_lambda_1_loss: 1.2777\n", "Epoch 5/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1229 - distribution_lambda_loss: 0.8260 - distribution_lambda_1_loss: 1.2969 - val_loss: 2.1029 - val_distribution_lambda_loss: 0.8188 - val_distribution_lambda_1_loss: 1.2841\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1162 - distribution_lambda_loss: 0.8239 - distribution_lambda_1_loss: 1.2924 - val_loss: 2.0953 - val_distribution_lambda_loss: 0.8193 - val_distribution_lambda_1_loss: 1.2760\n", "Epoch 6/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1190 - distribution_lambda_loss: 0.8258 - distribution_lambda_1_loss: 1.2932 - val_loss: 2.1034 - val_distribution_lambda_loss: 0.8197 - val_distribution_lambda_1_loss: 1.2837\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1138 - distribution_lambda_loss: 0.8226 - distribution_lambda_1_loss: 1.2912 - val_loss: 2.0971 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2777\n", "Epoch 7/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1207 - distribution_lambda_loss: 0.8258 - distribution_lambda_1_loss: 1.2949 - val_loss: 2.1039 - val_distribution_lambda_loss: 0.8194 - val_distribution_lambda_1_loss: 1.2845\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1162 - distribution_lambda_loss: 0.8238 - distribution_lambda_1_loss: 1.2924 - val_loss: 2.0987 - val_distribution_lambda_loss: 0.8205 - val_distribution_lambda_1_loss: 1.2782\n", "Epoch 8/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1272 - distribution_lambda_loss: 0.8285 - distribution_lambda_1_loss: 1.2987 - val_loss: 2.1043 - val_distribution_lambda_loss: 0.8193 - val_distribution_lambda_1_loss: 1.2851\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1099 - distribution_lambda_loss: 0.8210 - distribution_lambda_1_loss: 1.2890 - val_loss: 2.1007 - val_distribution_lambda_loss: 0.8221 - val_distribution_lambda_1_loss: 1.2787\n", "Epoch 9/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1213 - distribution_lambda_loss: 0.8262 - distribution_lambda_1_loss: 1.2951 - val_loss: 2.1100 - val_distribution_lambda_loss: 0.8225 - val_distribution_lambda_1_loss: 1.2874\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1124 - distribution_lambda_loss: 0.8222 - distribution_lambda_1_loss: 1.2902 - val_loss: 2.1003 - val_distribution_lambda_loss: 0.8213 - val_distribution_lambda_1_loss: 1.2790\n", "Epoch 10/1000\n", - "94/94 [==============================] - 0s 3ms/step - loss: 2.1201 - distribution_lambda_loss: 0.8256 - distribution_lambda_1_loss: 1.2945 - val_loss: 2.1039 - val_distribution_lambda_loss: 0.8196 - val_distribution_lambda_1_loss: 1.2843\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1128 - distribution_lambda_loss: 0.8224 - distribution_lambda_1_loss: 1.2905 - val_loss: 2.0984 - val_distribution_lambda_loss: 0.8200 - val_distribution_lambda_1_loss: 1.2784\n", "Epoch 11/1000\n", - "94/94 [==============================] - 0s 2ms/step - loss: 2.1259 - distribution_lambda_loss: 0.8294 - distribution_lambda_1_loss: 1.2965 - val_loss: 2.1056 - val_distribution_lambda_loss: 0.8199 - val_distribution_lambda_1_loss: 1.2857\n" + "96/96 [==============================] - 0s 3ms/step - loss: 2.1155 - distribution_lambda_loss: 0.8234 - distribution_lambda_1_loss: 1.2921 - val_loss: 2.1033 - val_distribution_lambda_loss: 0.8219 - val_distribution_lambda_1_loss: 1.2814\n", + "Epoch 12/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1129 - distribution_lambda_loss: 0.8218 - distribution_lambda_1_loss: 1.2911 - val_loss: 2.1035 - val_distribution_lambda_loss: 0.8227 - val_distribution_lambda_1_loss: 1.2808\n", + "Epoch 13/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1085 - distribution_lambda_loss: 0.8194 - distribution_lambda_1_loss: 1.2891 - val_loss: 2.1037 - val_distribution_lambda_loss: 0.8229 - val_distribution_lambda_1_loss: 1.2808\n", + "Epoch 14/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1067 - distribution_lambda_loss: 0.8190 - distribution_lambda_1_loss: 1.2876 - val_loss: 2.1064 - val_distribution_lambda_loss: 0.8235 - val_distribution_lambda_1_loss: 1.2828\n", + "Epoch 15/1000\n", + "96/96 [==============================] - 0s 3ms/step - loss: 2.1131 - distribution_lambda_loss: 0.8217 - distribution_lambda_1_loss: 1.2914 - val_loss: 2.1054 - val_distribution_lambda_loss: 0.8233 - val_distribution_lambda_1_loss: 1.2821\n" ] } ], @@ -4947,7 +4949,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "id": "4e2bf9dc", "metadata": {}, "outputs": [], @@ -4967,7 +4969,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "id": "c2674211", "metadata": {}, "outputs": [ @@ -4975,13 +4977,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.14232313843838407\n", - "0.16748424431848907\n" + "0.14248994674439097\n", + "0.16946807672801856\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -4993,13 +4995,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.13031966791602223\n", - "0.15463784705801664\n" + "0.13312004007562517\n", + "0.14674466840894407\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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- val_distribution_lambda_3_loss: 1.6433 - val_distribution_lambda_4_loss: 0.4875\n" ] } ], @@ -5246,7 +5248,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 24, "id": "39a9bdc6", "metadata": {}, "outputs": [], @@ -5266,7 +5268,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 25, "id": "c41cf448", "metadata": {}, "outputs": [ @@ -5274,13 +5276,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.0798265190543076\n", - "0.29563465147366164\n" + "0.0907258632073451\n", + "0.3000061215338464\n" ] }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -5292,13 +5294,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.02219365253550709\n", - "0.159869757007698\n" + "0.06439535566000021\n", + "0.21148355905367822\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -5343,7 +5345,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 26, "id": "cecf5392", "metadata": {}, "outputs": [], @@ -5375,7 +5377,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 27, "id": "ddf433f9", "metadata": {}, "outputs": [], @@ -5502,7 +5504,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 28, "id": "d31bad38", "metadata": {}, "outputs": [], @@ -5528,7 +5530,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 29, "id": "62b9f588", "metadata": {}, "outputs": [ @@ -5934,7 +5936,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 30, "id": "c58ba41d", "metadata": {}, "outputs": [], @@ -5972,7 +5974,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 31, "id": "f79792b6", "metadata": {}, "outputs": [ @@ -6008,29 +6010,29 @@ " \n", " \n", " \n", - " Ochoa\n", + " Falcone\n", " 1.0\n", " 90\n", " \n", " \n", - " Lovato\n", + " Gendrey\n", + " 1.0\n", + " 90\n", + " \n", + " \n", + " Baschirotto\n", + " 1.0\n", + " 90\n", + " \n", + " \n", + " Pongracic\n", " 1.0\n", " 80\n", " \n", " \n", - " Gyomber\n", - " 1.0\n", - " 80\n", - " \n", - " \n", - " Pirola\n", - " 1.0\n", - " 80\n", - " \n", - " \n", - " Mazzocchi\n", - " 1.0\n", - " 80\n", + " Gallo\n", + " 0.6\n", + " 60\n", " \n", " \n", " ...\n", @@ -6038,54 +6040,54 @@ " ...\n", " \n", " \n", - " Pisilli\n", + " Oristanio\n", + " 0.0\n", + " 50\n", + " \n", + " \n", + " Jankto\n", + " 0.0\n", + " 15\n", + " \n", + " \n", + " Mancosu\n", " 0.0\n", " 10\n", " \n", " \n", - " Aouar\n", + " Pavoletti\n", + " 0.0\n", + " 55\n", + " \n", + " \n", + " Shomurodov\n", " 0.4\n", - " 55\n", - " \n", - " \n", - " El Shaarawy\n", - " 0.0\n", - " 55\n", - " \n", - " \n", - " Belotti\n", - " 0.0\n", " 60\n", " \n", - " \n", - " Azmoun\n", - " 0.0\n", - " 35\n", - " \n", " \n", "\n", - "

476 rows × 2 columns

\n", + "

467 rows × 2 columns

\n", "" ], "text/plain": [ " starter percentage\n", "player \n", - "Ochoa 1.0 90\n", - "Lovato 1.0 80\n", - "Gyomber 1.0 80\n", - "Pirola 1.0 80\n", - "Mazzocchi 1.0 80\n", + "Falcone 1.0 90\n", + "Gendrey 1.0 90\n", + "Baschirotto 1.0 90\n", + "Pongracic 1.0 80\n", + "Gallo 0.6 60\n", "... ... ...\n", - "Pisilli 0.0 10\n", - "Aouar 0.4 55\n", - "El Shaarawy 0.0 55\n", - "Belotti 0.0 60\n", - "Azmoun 0.0 35\n", + "Oristanio 0.0 50\n", + "Jankto 0.0 15\n", + "Mancosu 0.0 10\n", + "Pavoletti 0.0 55\n", + "Shomurodov 0.4 60\n", "\n", - "[476 rows x 2 columns]" + "[467 rows x 2 columns]" ] }, - "execution_count": 33, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -6108,7 +6110,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 32, "id": "5e63c2b7", "metadata": { "scrolled": true @@ -6118,557 +6120,557 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sommer: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Szczesny: MV 6.17 ± 0.87; FV 5.13 + 1.42 (35.2% cs)\n", - "Meret: MV 6.19 ± 0.85; FV 5.46 + 1.32 (44.9% cs)\n", - "Provedel: MV 6.22 ± 0.89; FV 5.10 + 1.49 (27.3% cs)\n", - "Maignan: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Rui Patricio: MV 5.77 ± 0.99; FV 3.50 + 2.58 (1.2% cs)\n", - "Skorupski: MV 5.92 ± 0.99; FV 3.55 + 2.61 (1.7% cs)\n", - "Milinkovic-Savic V.: MV 5.86 ± 1.02; FV 3.48 + 2.71 (1.2% cs)\n", - "Di Gregorio: MV 6.23 ± 0.87; FV 5.10 + 1.53 (26.5% cs)\n", - "Falcone: MV 6.18 ± 0.90; FV 5.10 + 1.48 (31.0% cs)\n", - "Silvestri: MV 5.80 ± 0.99; FV 3.48 + 2.60 (1.3% cs)\n", - "Terracciano: MV 6.22 ± 0.86; FV 5.13 + 1.43 (35.2% cs)\n", - "Carnesecchi: MV 6.15 ± 0.89; FV 5.10 + 1.47 (24.5% cs)\n", - "Radunovic: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Montipo': MV 6.15 ± 0.92; FV 4.74 + 1.67 (12.2% cs)\n", - "Martinez Jo.: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Ochoa: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Caprile: MV 5.95 ± 0.98; FV 3.41 + 2.73 (1.1% cs)\n", - "Turati: MV 6.13 ± 0.89; FV 5.46 + 1.28 (34.2% cs)\n", - "Consigli: MV 6.03 ± 0.96; FV 3.45 + 2.68 (1.4% cs)\n", - "Musso: MV 6.19 ± 0.82; FV 5.78 + 1.26 (76.4% cs)\n", - "Cragno: MV 5.97 ± 1.01; FV 3.40 + 2.71 (1.1% cs)\n", - "Perin: MV 6.16 ± 0.88; FV 5.68 + 1.26 (67.6% cs)\n", - "Berisha: MV 5.93 ± 0.98; FV 3.40 + 2.70 (1.1% cs)\n", - "Christensen O.: MV 6.17 ± 0.87; FV 4.67 + 1.84 (12.3% cs)\n", - "Sportiello: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Mirante: MV 6.12 ± 0.97; FV 5.10 + 1.48 (22.0% cs)\n", - "Sepe: MV 6.17 ± 0.90; FV 4.72 + 1.68 (12.4% cs)\n", - "Leali: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Lamanna: MV 6.21 ± 0.90; FV 5.10 + 1.49 (21.7% cs)\n", - "Sommariva: MV 6.06 ± 0.95; FV 4.42 + 2.07 (6.8% cs)\n", - "Pegolo: MV 5.99 ± 0.97; FV 3.41 + 2.73 (1.2% cs)\n", - "Perilli: MV 6.27 ± 0.85; FV 5.10 + 1.49 (27.4% cs)\n", - "Padelli: MV 5.73 ± 1.03; FV 3.43 + 2.67 (1.2% cs)\n", - "Scuffet: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Gollini: MV 6.07 ± 0.88; FV 5.18 + 1.45 (19.8% cs)\n", - "Perisan: MV 5.82 ± 1.02; FV 3.40 + 2.72 (1.1% cs)\n", - "Audero: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Di Gennaro: MV 6.21 ± 0.80; FV 5.80 + 1.26 (83.0% cs)\n", - "Pinsoglio: MV 6.14 ± 0.92; FV 5.10 + 1.47 (25.2% cs)\n", - "Aresti: MV 5.74 ± 1.06; FV 3.38 + 2.73 (1.1% cs)\n", - "Fiorillo: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Cerofolini: MV 6.14 ± 0.92; FV 5.10 + 1.48 (23.1% cs)\n", - "Rossi F.: MV 6.20 ± 0.87; FV 5.10 + 1.48 (19.9% cs)\n", - "Costil: MV 6.08 ± 0.92; FV 3.59 + 2.49 (2.2% cs)\n", - "Ravaglia F.: MV 5.88 ± 1.01; FV 3.48 + 2.61 (2.1% cs)\n", - "Frattali: MV 6.13 ± 0.89; FV 5.46 + 1.28 (34.2% cs)\n", - "Contini: MV 6.07 ± 0.88; FV 5.18 + 1.45 (19.8% cs)\n", - "Brancolini: MV 6.18 ± 0.90; FV 5.10 + 1.47 (29.3% cs)\n", - "Berardi A.: MV 6.27 ± 0.85; FV 5.10 + 1.49 (27.4% cs)\n", - "Gemello: MV 5.86 ± 0.99; FV 3.59 + 2.54 (1.5% cs)\n", - "Boer: MV 5.71 ± 1.04; FV 3.40 + 2.70 (1.1% cs)\n", - "Bagnolini: MV 5.88 ± 1.01; FV 3.48 + 2.61 (2.1% cs)\n", - "Svilar: MV 5.71 ± 1.04; FV 3.40 + 2.70 (1.1% cs)\n", - "Sorrentino A.: MV 6.04 ± 0.91; FV 4.65 + 1.69 (12.3% cs)\n", - "Martinelli T.: MV 6.25 ± 0.82; FV 5.12 + 1.47 (27.8% cs)\n", - "Popa: MV 5.86 ± 0.99; FV 3.59 + 2.54 (1.5% cs)\n", - "Stubljar: MV 5.95 ± 0.98; FV 3.41 + 2.73 (1.1% cs)\n", - "Gori: MV 6.21 ± 0.90; FV 5.10 + 1.49 (21.7% cs)\n", - "Borbei: MV 6.18 ± 0.90; FV 5.10 + 1.47 (29.3% cs)\n", - "Okoye: MV 5.73 ± 1.03; FV 3.43 + 2.67 (1.2% cs)\n", - "Mandas: MV 6.17 ± 0.90; FV 4.72 + 1.68 (12.4% cs)\n", - "Dimarco: MV 6.56 ± 0.78; FV 6.79 + 1.53\n", - "Di Lorenzo: MV 6.31 ± 1.10; FV 6.92 + 2.14\n", - "Hernandez T.: MV 6.22 ± 1.04; FV 6.79 + 2.05\n", - "Carlos Augusto: MV 6.50 ± 0.91; FV 7.04 + 2.15\n", - "Danilo: MV 6.39 ± 0.89; FV 6.85 + 1.87\n", - "Zappacosta: MV 6.17 ± 0.91; FV 6.52 + 1.55\n", - "Schuurs: MV 6.05 ± 1.14; FV 6.13 + 1.46\n", - "Posch: MV 5.98 ± 1.07; FV 6.21 + 1.56\n", - "Bastoni: MV 6.52 ± 0.75; FV 6.68 + 1.22\n", - "Smalling: MV 6.10 ± 0.92; FV 6.28 + 1.27\n", - "Dumfries: MV 6.48 ± 0.92; FV 7.04 + 2.17\n", - "Romagnoli: MV 6.13 ± 0.96; FV 6.32 + 1.40\n", - "Pavard: MV 6.43 ± 0.71; FV 6.62 + 1.21\n", - "Rrahmani: MV 6.06 ± 1.03; FV 6.21 + 1.30\n", - "Spinazzola: MV 6.17 ± 0.86; FV 6.48 + 1.43\n", - "Buongiorno: MV 6.03 ± 1.19; FV 6.17 + 1.66\n", - "Bremer: MV 6.24 ± 1.04; FV 6.69 + 1.89\n", - "Tomori: MV 6.14 ± 0.76; FV 6.19 + 0.86\n", - "Biraghi: MV 6.08 ± 0.89; FV 6.43 + 1.44\n", - "Mancini: MV 5.98 ± 0.99; FV 6.09 + 1.26\n", - "Darmian: MV 6.43 ± 0.74; FV 6.66 + 1.30\n", - "Bakker: MV 6.04 ± 0.55; FV 6.11 + 0.68\n", - "Mazzocchi: MV 5.92 ± 0.84; FV 6.11 + 1.18\n", - "Doig: MV 5.86 ± 1.08; FV 6.14 + 1.59\n", - "Calabria: MV 6.13 ± 0.82; FV 6.31 + 1.12\n", - "Acerbi: MV 6.37 ± 0.71; FV 6.47 + 0.99\n", - "Cuadrado: MV 6.36 ± 0.81; FV 6.61 + 1.39\n", - "Ebuehi: MV 5.53 ± 0.75; FV 5.50 + 0.77\n", - "Casale: MV 5.98 ± 0.82; FV 6.06 + 1.05\n", - "Holm: MV 6.11 ± 0.67; FV 6.23 + 0.86\n", - "Baschirotto: MV 6.11 ± 1.07; FV 6.41 + 1.59\n", - "Bijol: MV 5.77 ± 1.25; FV 5.65 + 1.55\n", - "Thiaw: MV 5.86 ± 1.15; FV 5.70 + 1.17\n", - "Mario Rui: MV 5.95 ± 0.80; FV 5.98 + 0.84\n", - "Milenkovic: MV 5.96 ± 0.89; FV 6.00 + 0.99\n", - "Rodriguez R.: MV 5.90 ± 0.99; FV 5.80 + 1.10\n", - "Kolasinac: MV 6.04 ± 0.65; FV 6.15 + 0.78\n", - "N'dicka: MV 5.98 ± 0.62; FV 5.96 + 0.61\n", - "Scalvini: MV 6.09 ± 0.87; FV 6.27 + 1.21\n", - "Perez N.: MV 5.79 ± 1.19; FV 5.67 + 1.45\n", - "Kristensen: MV 6.01 ± 0.75; FV 6.21 + 1.06\n", - "Izzo: MV 5.99 ± 0.91; FV 6.07 + 1.22\n", - "De Vrij: MV 6.48 ± 0.73; FV 6.62 + 1.14\n", - "Faraoni: MV 5.72 ± 0.79; FV 5.80 + 1.01\n", - "Toloi: MV 6.09 ± 0.75; FV 6.18 + 0.94\n", - "Kyriakopoulos: MV 5.88 ± 0.68; FV 5.89 + 0.80\n", - "Bellanova: MV 5.89 ± 1.08; FV 5.89 + 1.32\n", - "Mari': MV 5.82 ± 0.87; FV 5.83 + 1.04\n", - "Dodo': MV 5.96 ± 0.80; FV 6.00 + 0.88\n", - "Lucumi': MV 5.74 ± 1.04; FV 5.68 + 1.20\n", - "Hien: MV 5.70 ± 1.05; FV 5.66 + 1.25\n", - "Natan: MV 5.92 ± 0.90; FV 5.96 + 1.02\n", - "Hysaj: MV 5.98 ± 0.73; FV 6.08 + 1.02\n", - "D'ambrosio: MV 6.00 ± 0.67; FV 5.97 + 0.78\n", - "Luperto: MV 5.38 ± 1.16; FV 5.35 + 1.29\n", - "Djimsiti: MV 6.03 ± 0.63; FV 6.02 + 0.58\n", - "Marusic: MV 5.93 ± 0.81; FV 5.93 + 0.92\n", - "Martin: MV 5.85 ± 0.64; FV 5.93 + 0.80\n", - "Mina: MV 6.01 ± 0.71; FV 6.20 + 0.96\n", - "Toljan: MV 5.61 ± 0.86; FV 5.55 + 0.89\n", - "Llorente D.: MV 5.80 ± 0.98; FV 5.77 + 1.05\n", - "Martinez Quarta: MV 6.00 ± 0.85; FV 6.07 + 0.97\n", - "Bastoni S.: MV 5.55 ± 0.73; FV 5.49 + 0.78\n", - "Dragusin: MV 5.81 ± 0.84; FV 5.93 + 1.11\n", - "Parisi: MV 6.06 ± 0.79; FV 6.17 + 1.01\n", - "Bradaric: MV 5.83 ± 0.97; FV 5.91 + 1.24\n", - "Kamara H.: MV 5.96 ± 0.92; FV 5.97 + 1.09\n", - "Olivera: MV 5.98 ± 0.67; FV 6.08 + 0.75\n", - "Gendrey: MV 5.99 ± 0.71; FV 5.97 + 0.78\n", - "Kristiansen: MV 6.02 ± 0.86; FV 6.16 + 1.25\n", - "Beukema: MV 5.83 ± 1.11; FV 5.85 + 1.36\n", - "Dossena: MV 5.68 ± 0.85; FV 5.65 + 0.99\n", - "Pedersen: MV 5.77 ± 0.59; FV 5.78 + 0.62\n", - "Juan Jesus: MV 5.99 ± 0.60; FV 5.98 + 0.55\n", - "Gyomber: MV 5.83 ± 1.00; FV 5.78 + 1.10\n", - "Alex Sandro: MV 5.90 ± 0.90; FV 5.83 + 1.05\n", - "Hateboer: MV 6.04 ± 0.83; FV 6.28 + 1.29\n", - "Palomino: MV 5.98 ± 0.57; FV 5.99 + 0.58\n", - "Marchizza: MV 6.06 ± 0.79; FV 6.18 + 0.98\n", - "Zappa: MV 5.60 ± 0.86; FV 5.49 + 0.88\n", - "Gallo: MV 5.97 ± 0.87; FV 5.98 + 0.96\n", - "Caldirola: MV 5.80 ± 1.00; FV 5.85 + 1.33\n", - "Kalulu: MV 5.97 ± 0.84; FV 6.01 + 0.91\n", - "Erlic: MV 5.62 ± 0.99; FV 5.54 + 1.03\n", - "Vojvoda: MV 5.75 ± 0.87; FV 5.73 + 1.04\n", - "Vasquez: MV 5.91 ± 0.75; FV 5.88 + 0.81\n", - "Cambiaso: MV 6.18 ± 0.84; FV 6.38 + 1.29\n", - "Pongracic: MV 6.07 ± 0.83; FV 6.12 + 1.03\n", - "Viti: MV 5.92 ± 0.57; FV 6.01 + 0.74\n", - "Gatti: MV 6.18 ± 0.75; FV 6.26 + 0.99\n", - "Birindelli: MV 5.92 ± 0.77; FV 5.94 + 0.93\n", - "Azzi: MV 5.71 ± 0.73; FV 5.70 + 0.83\n", - "Wieteska: MV 5.75 ± 0.92; FV 5.73 + 1.09\n", - "Masina: MV 5.77 ± 1.20; FV 6.00 + 1.65\n", - "Romagnoli S.: MV 6.05 ± 0.94; FV 6.21 + 1.27\n", - "Pezzella Giu.: MV 5.40 ± 0.88; FV 5.34 + 0.81\n", - "Sabelli: MV 5.90 ± 0.60; FV 5.92 + 0.71\n", - "Lirola: MV 6.20 ± 0.89; FV 6.55 + 1.53\n", - "Lazzari: MV 6.01 ± 0.78; FV 6.01 + 0.92\n", - "Bani: MV 5.76 ± 1.04; FV 5.88 + 1.37\n", - "Djidji: MV 5.66 ± 1.00; FV 5.59 + 1.21\n", - "Kabasele: MV 5.67 ± 0.99; FV 5.56 + 1.17\n", - "Lazaro: MV 5.99 ± 0.83; FV 6.02 + 1.08\n", - "Augello: MV 5.66 ± 0.88; FV 5.69 + 1.01\n", - "Zortea: MV 6.11 ± 0.80; FV 6.40 + 1.25\n", - "Dawidowicz: MV 5.67 ± 1.02; FV 5.65 + 1.23\n", - "Pirola: MV 5.82 ± 1.05; FV 5.93 + 1.38\n", - "Lovato: MV 5.67 ± 0.88; FV 5.58 + 0.94\n", - "Ruggeri: MV 6.14 ± 0.93; FV 6.40 + 1.39\n", - "Vina: MV 5.70 ± 0.95; FV 5.68 + 1.02\n", - "Obert: MV 5.57 ± 1.01; FV 5.52 + 1.09\n", - "Terracciano F.: MV 6.02 ± 0.79; FV 6.12 + 1.04\n", - "Ebosele: MV 5.69 ± 0.90; FV 5.69 + 1.00\n", - "Zemura: MV 5.85 ± 0.89; FV 5.81 + 1.02\n", - "Hatzidiakos: MV 5.73 ± 0.90; FV 5.73 + 1.07\n", - "Patric: MV 6.02 ± 0.66; FV 6.01 + 0.67\n", - "Lykogiannis: MV 5.71 ± 0.73; FV 5.78 + 0.85\n", - "Pellegrini Lu.: MV 5.86 ± 0.66; FV 5.82 + 0.71\n", - "Magnani: MV 5.64 ± 1.15; FV 5.65 + 1.40\n", - "Ranieri L.: MV 5.90 ± 0.66; FV 5.89 + 0.70\n", - "Carboni A.: MV 5.96 ± 0.78; FV 6.03 + 0.97\n", - "Calafiori: MV 5.91 ± 0.97; FV 6.03 + 1.29\n", - "Monterisi: MV 6.19 ± 1.07; FV 6.73 + 2.09\n", - "Ismajli: MV 5.47 ± 0.86; FV 5.39 + 0.83\n" + "Sommer: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Szczesny: MV 5.98 ± 0.96; FV 4.94 + 1.44 (9.0% cs)\n", + "Meret: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Provedel: MV 6.13 ± 0.97; FV 3.79 + 2.12 (2.5% cs)\n", + "Maignan: MV 6.10 ± 0.92; FV 5.03 + 1.36 (22.9% cs)\n", + "Rui Patricio: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Skorupski: MV 6.14 ± 0.82; FV 5.82 + 1.23 (71.9% cs)\n", + "Milinkovic-Savic V.: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Di Gregorio: MV 6.27 ± 0.85; FV 5.05 + 1.41 (15.4% cs)\n", + "Falcone: MV 6.16 ± 0.91; FV 4.94 + 1.43 (15.0% cs)\n", + "Silvestri: MV 6.18 ± 0.91; FV 5.18 + 1.51 (32.2% cs)\n", + "Terracciano: MV 6.16 ± 0.84; FV 5.75 + 1.22 (68.0% cs)\n", + "Carnesecchi: MV 6.14 ± 0.96; FV 5.07 + 1.43 (20.7% cs)\n", + "Radunovic: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Montipo': MV 6.20 ± 0.82; FV 5.69 + 1.22 (55.2% cs)\n", + "Martinez Jo.: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Ochoa: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Caprile: MV 6.20 ± 0.91; FV 5.05 + 1.42 (21.4% cs)\n", + "Turati: MV 6.10 ± 0.97; FV 4.14 + 1.98 (4.6% cs)\n", + "Consigli: MV 6.13 ± 0.95; FV 4.94 + 1.47 (13.3% cs)\n", + "Musso: MV 6.17 ± 0.96; FV 5.04 + 1.37 (28.8% cs)\n", + "Cragno: MV 6.04 ± 0.98; FV 3.76 + 2.10 (2.3% cs)\n", + "Perin: MV 6.16 ± 0.93; FV 5.04 + 1.37 (20.1% cs)\n", + "Berisha: MV 6.23 ± 0.91; FV 5.04 + 1.38 (21.9% cs)\n", + "Christensen O.: MV 6.19 ± 0.88; FV 5.14 + 1.31 (31.1% cs)\n", + "Sportiello: MV 6.13 ± 0.92; FV 5.13 + 1.29 (32.9% cs)\n", + "Mirante: MV 6.10 ± 0.92; FV 5.03 + 1.36 (22.9% cs)\n", + "Sepe: MV 6.12 ± 0.97; FV 3.73 + 2.16 (2.3% cs)\n", + "Leali: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Lamanna: MV 6.26 ± 0.85; FV 5.04 + 1.38 (15.3% cs)\n", + "Sommariva: MV 6.21 ± 0.90; FV 5.05 + 1.38 (23.2% cs)\n", + "Pegolo: MV 6.12 ± 0.95; FV 4.83 + 1.52 (12.1% cs)\n", + "Perilli: MV 6.20 ± 0.82; FV 5.71 + 1.22 (57.3% cs)\n", + "Padelli: MV 6.17 ± 0.91; FV 5.17 + 1.51 (31.5% cs)\n", + "Scuffet: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Gollini: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Perisan: MV 6.19 ± 0.87; FV 5.05 + 1.42 (25.8% cs)\n", + "Audero: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Di Gennaro: MV 6.12 ± 0.86; FV 5.77 + 1.22 (56.3% cs)\n", + "Pinsoglio: MV 5.89 ± 0.98; FV 4.52 + 1.64 (3.3% cs)\n", + "Aresti: MV 5.74 ± 1.10; FV 3.20 + 2.62 (1.0% cs)\n", + "Fiorillo: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Cerofolini: MV 6.08 ± 0.99; FV 3.63 + 2.32 (1.9% cs)\n", + "Rossi F.: MV 6.17 ± 0.96; FV 5.04 + 1.37 (28.9% cs)\n", + "Costil: MV 6.19 ± 0.98; FV 3.43 + 2.43 (1.3% cs)\n", + "Ravaglia F.: MV 6.13 ± 0.82; FV 5.82 + 1.23 (71.7% cs)\n", + "Frattali: MV 6.10 ± 0.97; FV 4.14 + 1.98 (4.6% cs)\n", + "Contini: MV 5.71 ± 1.07; FV 3.21 + 2.69 (1.1% cs)\n", + "Brancolini: MV 6.16 ± 0.90; FV 4.96 + 1.41 (16.4% cs)\n", + "Berardi A.: MV 6.20 ± 0.82; FV 5.71 + 1.22 (57.3% cs)\n", + "Gemello: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Boer: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Bagnolini: MV 6.13 ± 0.82; FV 5.82 + 1.23 (71.7% cs)\n", + "Svilar: MV 6.01 ± 0.91; FV 4.39 + 1.69 (2.5% cs)\n", + "Sorrentino A.: MV 6.25 ± 0.85; FV 5.01 + 1.41 (10.6% cs)\n", + "Martinelli T.: MV 6.16 ± 0.84; FV 5.75 + 1.22 (66.1% cs)\n", + "Popa: MV 6.13 ± 0.88; FV 5.66 + 1.21 (54.3% cs)\n", + "Stubljar: MV 6.23 ± 0.91; FV 5.04 + 1.38 (21.9% cs)\n", + "Gori: MV 6.26 ± 0.85; FV 5.04 + 1.38 (15.3% cs)\n", + "Borbei: MV 6.16 ± 0.90; FV 4.96 + 1.41 (16.4% cs)\n", + "Okoye: MV 6.17 ± 0.91; FV 5.17 + 1.51 (31.5% cs)\n", + "Mandas: MV 6.12 ± 0.97; FV 3.73 + 2.16 (2.3% cs)\n", + "Dimarco: MV 6.35 ± 0.79; FV 6.69 + 1.42\n", + "Di Lorenzo: MV 6.18 ± 0.97; FV 6.55 + 1.62\n", + "Hernandez T.: MV 6.22 ± 1.10; FV 6.75 + 2.07\n", + "Carlos Augusto: MV 6.24 ± 0.86; FV 6.63 + 1.47\n", + "Danilo: MV 6.02 ± 1.03; FV 6.18 + 1.39\n", + "Zappacosta: MV 5.99 ± 1.04; FV 6.21 + 1.47\n", + "Schuurs: MV 6.14 ± 0.71; FV 6.31 + 0.96\n", + "Posch: MV 6.21 ± 0.76; FV 6.52 + 1.38\n", + "Bastoni: MV 6.26 ± 0.77; FV 6.44 + 0.99\n", + "Smalling: MV 6.08 ± 0.85; FV 6.33 + 1.30\n", + "Dumfries: MV 6.30 ± 0.93; FV 6.81 + 1.82\n", + "Romagnoli: MV 5.95 ± 1.00; FV 6.01 + 1.24\n", + "Pavard: MV 6.12 ± 0.64; FV 6.25 + 0.78\n", + "Rrahmani: MV 6.00 ± 0.96; FV 6.13 + 1.24\n", + "Spinazzola: MV 6.15 ± 0.76; FV 6.44 + 1.31\n", + "Buongiorno: MV 6.11 ± 0.77; FV 6.35 + 1.22\n", + "Bremer: MV 5.80 ± 1.20; FV 5.91 + 1.51\n", + "Tomori: MV 6.22 ± 0.98; FV 6.58 + 1.69\n", + "Biraghi: MV 6.23 ± 0.98; FV 6.85 + 2.11\n", + "Mancini: MV 5.95 ± 1.02; FV 6.17 + 1.45\n", + "Darmian: MV 6.21 ± 0.75; FV 6.43 + 1.02\n", + "Bakker: MV 5.94 ± 0.66; FV 6.01 + 0.90\n", + "Mazzocchi: MV 5.61 ± 0.72; FV 5.57 + 0.74\n", + "Doig: MV 5.97 ± 0.96; FV 6.12 + 1.29\n", + "Calabria: MV 6.06 ± 0.92; FV 6.27 + 1.33\n", + "Acerbi: MV 6.13 ± 0.69; FV 6.20 + 0.71\n", + "Cuadrado: MV 6.11 ± 0.81; FV 6.26 + 1.00\n", + "Ebuehi: MV 5.90 ± 0.66; FV 5.91 + 0.74\n", + "Casale: MV 5.70 ± 1.08; FV 5.69 + 1.26\n", + "Holm: MV 5.98 ± 0.64; FV 6.05 + 0.82\n", + "Baschirotto: MV 5.76 ± 1.21; FV 5.84 + 1.45\n", + "Bijol: MV 5.83 ± 1.11; FV 5.97 + 1.52\n", + "Thiaw: MV 5.89 ± 1.23; FV 5.87 + 1.32\n", + "Mario Rui: MV 5.92 ± 0.67; FV 5.93 + 0.76\n", + "Milenkovic: MV 6.04 ± 0.96; FV 6.16 + 1.22\n", + "Rodriguez R.: MV 6.04 ± 0.64; FV 6.07 + 0.61\n", + "Kolasinac: MV 5.94 ± 0.78; FV 6.07 + 1.08\n", + "N'dicka: MV 5.91 ± 0.81; FV 5.93 + 0.98\n", + "Scalvini: MV 5.95 ± 1.17; FV 6.14 + 1.52\n", + "Perez N.: MV 5.78 ± 1.07; FV 5.78 + 1.25\n", + "Kristensen: MV 6.02 ± 0.68; FV 6.20 + 1.05\n", + "Izzo: MV 5.90 ± 0.93; FV 5.94 + 1.24\n", + "De Vrij: MV 6.22 ± 0.74; FV 6.36 + 0.83\n", + "Faraoni: MV 5.82 ± 0.70; FV 5.84 + 0.86\n", + "Toloi: MV 6.00 ± 1.00; FV 6.20 + 1.40\n", + "Kyriakopoulos: MV 6.03 ± 0.94; FV 6.20 + 1.44\n", + "Bellanova: MV 5.95 ± 0.88; FV 6.00 + 1.07\n", + "Mari': MV 5.84 ± 0.93; FV 5.87 + 1.20\n", + "Dodo': MV 6.04 ± 0.94; FV 6.14 + 1.23\n", + "Lucumi': MV 6.09 ± 0.64; FV 6.12 + 0.70\n", + "Hien: MV 5.87 ± 0.84; FV 5.82 + 0.87\n", + "Natan: MV 5.99 ± 0.76; FV 6.06 + 0.92\n", + "Hysaj: MV 5.70 ± 0.99; FV 5.69 + 1.15\n", + "D'ambrosio: MV 5.96 ± 0.72; FV 5.94 + 0.87\n", + "Luperto: MV 5.79 ± 1.05; FV 5.66 + 1.07\n", + "Djimsiti: MV 5.96 ± 0.77; FV 5.97 + 0.86\n", + "Marusic: MV 5.68 ± 1.10; FV 5.65 + 1.28\n", + "Martin: MV 6.02 ± 0.78; FV 6.11 + 1.02\n", + "Mina: MV 6.14 ± 0.78; FV 6.45 + 1.38\n", + "Toljan: MV 5.90 ± 0.80; FV 5.89 + 0.81\n", + "Llorente D.: MV 5.90 ± 0.79; FV 5.92 + 0.91\n", + "Martinez Quarta: MV 6.22 ± 1.04; FV 6.60 + 1.76\n", + "Bastoni S.: MV 5.98 ± 0.85; FV 6.19 + 1.29\n", + "Dragusin: MV 6.09 ± 0.75; FV 6.27 + 1.01\n", + "Parisi: MV 6.12 ± 0.90; FV 6.26 + 1.31\n", + "Bradaric: MV 5.61 ± 0.89; FV 5.58 + 0.96\n", + "Kamara H.: MV 5.93 ± 0.60; FV 5.91 + 0.64\n", + "Olivera: MV 5.95 ± 0.64; FV 6.00 + 0.77\n", + "Gendrey: MV 5.90 ± 0.80; FV 5.87 + 0.91\n", + "Kristiansen: MV 6.17 ± 0.68; FV 6.30 + 0.95\n", + "Beukema: MV 6.18 ± 0.72; FV 6.30 + 0.89\n", + "Dossena: MV 5.55 ± 1.06; FV 5.47 + 1.11\n", + "Pedersen: MV 5.90 ± 0.59; FV 5.89 + 0.57\n", + "Juan Jesus: MV 5.97 ± 0.64; FV 5.99 + 0.65\n", + "Gyomber: MV 5.60 ± 0.99; FV 5.54 + 1.09\n", + "Alex Sandro: MV 5.58 ± 1.23; FV 5.47 + 1.33\n", + "Hateboer: MV 5.85 ± 0.89; FV 5.91 + 1.16\n", + "Palomino: MV 5.98 ± 0.64; FV 6.02 + 0.80\n", + "Marchizza: MV 6.07 ± 1.07; FV 6.22 + 1.48\n", + "Zappa: MV 5.54 ± 1.01; FV 5.47 + 1.01\n", + "Gallo: MV 5.82 ± 0.99; FV 5.77 + 1.07\n", + "Caldirola: MV 5.73 ± 1.06; FV 5.79 + 1.39\n", + "Kalulu: MV 5.94 ± 0.94; FV 5.97 + 1.12\n", + "Erlic: MV 5.90 ± 0.83; FV 5.87 + 0.75\n", + "Vojvoda: MV 5.97 ± 0.61; FV 6.00 + 0.66\n", + "Vasquez: MV 6.14 ± 0.68; FV 6.18 + 0.66\n", + "Cambiaso: MV 5.80 ± 1.05; FV 5.84 + 1.25\n", + "Pongracic: MV 5.96 ± 0.90; FV 5.98 + 1.01\n", + "Viti: MV 5.94 ± 0.83; FV 5.89 + 0.79\n", + "Gatti: MV 5.62 ± 1.36; FV 5.55 + 1.49\n", + "Birindelli: MV 5.93 ± 0.75; FV 5.95 + 0.96\n", + "Azzi: MV 5.74 ± 0.76; FV 5.72 + 0.78\n", + "Wieteska: MV 5.67 ± 1.14; FV 5.63 + 1.30\n", + "Masina: MV 5.84 ± 1.09; FV 6.26 + 1.75\n", + "Romagnoli S.: MV 5.98 ± 1.26; FV 5.97 + 1.64\n", + "Pezzella Giu.: MV 5.67 ± 0.79; FV 5.60 + 0.72\n", + "Sabelli: MV 6.01 ± 0.52; FV 6.07 + 0.58\n", + "Lirola: MV 5.95 ± 1.16; FV 6.00 + 1.46\n", + "Lazzari: MV 5.90 ± 0.88; FV 5.87 + 1.01\n", + "Bani: MV 6.18 ± 0.92; FV 6.54 + 1.61\n", + "Djidji: MV 5.94 ± 0.65; FV 5.96 + 0.67\n", + "Kabasele: MV 5.88 ± 0.70; FV 5.82 + 0.79\n", + "Lazaro: MV 6.07 ± 0.63; FV 6.13 + 0.66\n", + "Augello: MV 5.62 ± 1.00; FV 5.64 + 1.06\n", + "Zortea: MV 5.91 ± 0.87; FV 6.07 + 1.20\n", + "Dawidowicz: MV 5.87 ± 0.76; FV 5.83 + 0.83\n", + "Pirola: MV 5.55 ± 0.90; FV 5.50 + 0.91\n", + "Lovato: MV 5.54 ± 0.88; FV 5.47 + 0.89\n", + "Ruggeri: MV 5.96 ± 1.14; FV 6.18 + 1.53\n", + "Vina: MV 5.77 ± 1.06; FV 5.74 + 1.20\n", + "Obert: MV 5.54 ± 1.08; FV 5.47 + 1.10\n", + "Terracciano F.: MV 6.03 ± 0.70; FV 6.09 + 0.77\n", + "Ebosele: MV 5.83 ± 0.89; FV 5.77 + 0.99\n", + "Zemura: MV 5.89 ± 0.61; FV 5.85 + 0.64\n", + "Hatzidiakos: MV 5.64 ± 1.13; FV 5.60 + 1.24\n", + "Patric: MV 5.78 ± 0.84; FV 5.70 + 0.89\n", + "Lykogiannis: MV 6.00 ± 0.49; FV 6.06 + 0.52\n", + "Pellegrini Lu.: MV 5.61 ± 0.86; FV 5.50 + 0.88\n", + "Magnani: MV 5.89 ± 0.93; FV 5.85 + 1.01\n", + "Ranieri L.: MV 5.98 ± 0.84; FV 6.03 + 1.04\n", + "Carboni A.: MV 5.96 ± 0.76; FV 6.02 + 1.02\n", + "Calafiori: MV 6.05 ± 0.70; FV 6.10 + 0.86\n", + "Monterisi: MV 5.92 ± 1.35; FV 6.08 + 2.01\n", + "Ismajli: MV 5.84 ± 0.80; FV 5.79 + 0.73\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "De Winter: MV 5.82 ± 0.83; FV 5.72 + 0.86\n", - "Tressoldi: MV 5.71 ± 0.86; FV 5.74 + 1.05\n", - "Ehizibue: MV 5.61 ± 1.06; FV 5.63 + 1.22\n", - "Vogliacco: MV 5.84 ± 0.85; FV 5.83 + 0.96\n", - "Ferrari G.: MV 5.60 ± 1.00; FV 5.63 + 1.14\n", - "Venuti: MV 5.89 ± 0.77; FV 5.86 + 0.79\n", - "Karsdorp: MV 5.87 ± 0.56; FV 5.85 + 0.51\n", - "Kjaer: MV 5.79 ± 0.54; FV 5.79 + 0.46\n", - "Gunter: MV 5.56 ± 1.17; FV 5.50 + 1.38\n", - "Soumaoro: MV 5.78 ± 1.30; FV 5.74 + 1.46\n", - "Di Pardo: MV 5.60 ± 0.97; FV 5.54 + 1.05\n", - "Zanoli: MV 6.08 ± 0.92; FV 6.39 + 1.42\n", - "Zima: MV 5.81 ± 0.75; FV 5.74 + 0.77\n", - "Hefti: MV 5.70 ± 0.82; FV 5.61 + 0.85\n", - "Ostigard: MV 5.76 ± 0.64; FV 5.75 + 0.59\n", - "Sambia: MV 5.95 ± 0.78; FV 5.99 + 0.93\n", - "Bisseck: MV 6.28 ± 0.75; FV 6.46 + 1.16\n", - "Oyono: MV 6.04 ± 0.72; FV 6.08 + 0.78\n", - "Ferreira J.: MV 5.62 ± 0.97; FV 5.54 + 1.07\n", - "Dorgu: MV 6.10 ± 0.67; FV 6.12 + 0.78\n", - "Touba: MV 6.05 ± 0.79; FV 6.12 + 1.00\n", - "Sazonov: MV 5.79 ± 1.12; FV 5.72 + 1.35\n", - "Rugani: MV 6.13 ± 0.60; FV 6.16 + 0.68\n", - "De Sciglio: MV 5.98 ± 0.68; FV 6.00 + 0.75\n", - "Goldaniga: MV 5.52 ± 0.98; FV 5.44 + 1.02\n", - "Florenzi: MV 6.05 ± 0.58; FV 6.08 + 0.60\n", - "De Silvestri: MV 5.83 ± 0.74; FV 5.90 + 0.90\n", - "Pereira P.: MV 5.91 ± 0.78; FV 5.94 + 0.95\n", - "Fazio: MV 5.84 ± 1.27; FV 5.98 + 1.65\n", - "Bereszynski: MV 5.42 ± 0.88; FV 5.36 + 0.83\n", - "Bonifazi: MV 5.61 ± 1.09; FV 5.47 + 1.18\n", - "Walukiewicz: MV 5.36 ± 0.80; FV 5.30 + 0.63\n", - "Okoli: MV 5.95 ± 0.73; FV 5.93 + 0.75\n", - "Kumbulla: MV 5.35 ± 1.44; FV 5.20 + 1.41\n", - "Celik: MV 5.61 ± 0.86; FV 5.49 + 0.84\n", - "Amione: MV 5.61 ± 0.97; FV 5.58 + 1.15\n", - "Daniliuc: MV 5.76 ± 1.07; FV 5.79 + 1.33\n", - "Soppy: MV 5.73 ± 0.86; FV 5.70 + 1.02\n", - "Haps: MV 5.78 ± 0.86; FV 5.83 + 1.08\n", - "Cittadini: MV 5.94 ± 0.88; FV 6.05 + 1.19\n", - "Coppola D.: MV 5.64 ± 0.87; FV 5.55 + 0.97\n", - "Cacace: MV 5.43 ± 0.74; FV 5.34 + 0.66\n", - "Ebosse: MV 5.48 ± 0.96; FV 5.41 + 0.93\n", - "Guessand A.: MV 5.67 ± 1.05; FV 5.61 + 1.24\n", - "Cabal: MV 5.73 ± 0.58; FV 5.63 + 0.59\n", - "Missori: MV 5.69 ± 0.77; FV 5.67 + 0.88\n", - "Kayode: MV 6.02 ± 0.67; FV 6.05 + 0.67\n", - "Corazza: MV 5.66 ± 0.84; FV 5.63 + 0.92\n", - "Kristensen T.: MV 5.75 ± 1.13; FV 5.70 + 1.44\n", - "Dermaku: MV 6.02 ± 0.85; FV 6.11 + 1.09\n", - "Tonelli: MV 5.41 ± 0.96; FV 5.35 + 0.94\n", - "Capradossi: MV 5.66 ± 1.03; FV 5.68 + 1.23\n", - "Bettella: MV 5.94 ± 0.88; FV 6.05 + 1.19\n", - "Amey: MV 5.76 ± 1.09; FV 5.83 + 1.37\n", - "Gila: MV 5.93 ± 0.78; FV 5.93 + 0.84\n", - "Bronn: MV 5.64 ± 0.91; FV 5.53 + 0.93\n", - "Guarino: MV 5.51 ± 0.90; FV 5.48 + 0.94\n", - "Carboni F.: MV 5.98 ± 0.78; FV 6.05 + 0.98\n", - "Smajlovic: MV 6.03 ± 0.88; FV 6.15 + 1.17\n", - "Matturro: MV 5.84 ± 0.85; FV 5.83 + 0.96\n", - "N'guessan: MV 5.79 ± 1.12; FV 5.72 + 1.35\n", - "Mateus Lusuardi: MV 6.05 ± 0.89; FV 6.20 + 1.15\n", - "Kalaj: MV 6.05 ± 0.89; FV 6.20 + 1.15\n", - "Pierozzi: MV 5.98 ± 0.72; FV 6.01 + 0.75\n", - "Huijsen: MV 6.10 ± 0.84; FV 6.32 + 1.33\n", - "Bonfanti: MV 6.06 ± 0.73; FV 6.14 + 0.89\n", - "Pellegrino: MV 6.02 ± 0.78; FV 6.08 + 0.88\n", - "Comuzzo: MV 5.98 ± 0.72; FV 6.01 + 0.75\n", - "Zaccagni: MV 6.34 ± 1.07; FV 7.04 + 2.49\n", - "Koopmeiners: MV 6.41 ± 1.04; FV 7.19 + 2.57\n", - "Luis Alberto: MV 6.41 ± 1.05; FV 7.19 + 2.62\n", - "Felipe Anderson: MV 6.15 ± 1.18; FV 6.87 + 2.56\n", - "Rabiot: MV 6.40 ± 1.17; FV 7.36 + 3.00\n", - "Zielinski: MV 6.27 ± 0.84; FV 6.58 + 1.44\n", - "Barella: MV 6.55 ± 0.86; FV 6.97 + 1.99\n", - "Pulisic: MV 6.26 ± 1.01; FV 6.79 + 1.96\n", - "Orsolini: MV 6.21 ± 1.25; FV 6.97 + 2.66\n", - "Calhanoglu: MV 6.61 ± 0.75; FV 6.79 + 1.50\n", - "Strefezza: MV 6.27 ± 1.04; FV 6.84 + 2.11\n", - "Chukwueze: MV 6.07 ± 0.75; FV 6.28 + 1.03\n", - "Ferguson: MV 6.21 ± 1.08; FV 6.74 + 2.06\n", - "Candreva: MV 6.21 ± 1.26; FV 6.97 + 2.68\n", - "Frattesi: MV 6.52 ± 1.02; FV 7.36 + 2.82\n", - "Samardzic: MV 6.07 ± 1.11; FV 6.59 + 1.98\n", - "Vlasic: MV 6.14 ± 1.13; FV 6.69 + 2.07\n", - "Bonaventura: MV 6.21 ± 0.98; FV 6.72 + 1.90\n", - "Politano: MV 6.33 ± 0.81; FV 6.63 + 1.48\n", - "El Shaarawy: MV 6.26 ± 0.92; FV 6.63 + 1.69\n", - "Mkhitaryan: MV 6.54 ± 0.94; FV 7.17 + 2.42\n", - "Aouar: MV 6.13 ± 1.01; FV 6.63 + 1.90\n", - "Malinovskyi: MV 5.95 ± 1.05; FV 6.42 + 1.86\n", - "Gudmundsson A.: MV 6.03 ± 0.88; FV 6.33 + 1.41\n", - "Kamada: MV 6.09 ± 0.98; FV 6.57 + 1.90\n", - "Pellegrini Lo.: MV 5.98 ± 1.15; FV 6.51 + 1.97\n", - "Kostic: MV 6.33 ± 1.04; FV 6.99 + 2.31\n", - "Radonjic: MV 6.34 ± 1.25; FV 7.23 + 2.88\n", - "Baldanzi: MV 5.59 ± 0.76; FV 5.61 + 0.86\n", - "Lovric: MV 6.14 ± 1.07; FV 6.60 + 1.88\n", - "Lindstrom: MV 6.10 ± 0.81; FV 6.34 + 1.23\n", - "Lazovic: MV 6.13 ± 1.02; FV 6.53 + 1.74\n", - "Pereyra: MV 6.20 ± 1.23; FV 6.83 + 2.49\n", - "Renato Sanches: MV 6.13 ± 0.77; FV 6.36 + 1.08\n", - "Pessina: MV 6.09 ± 0.94; FV 6.48 + 1.66\n", - "Guendouzi: MV 6.04 ± 0.69; FV 6.16 + 0.86\n", - "Loftus-Cheek: MV 6.12 ± 0.64; FV 6.15 + 0.66\n", - "Zambo Anguissa: MV 6.08 ± 0.93; FV 6.37 + 1.34\n", - "Elmas: MV 6.04 ± 0.98; FV 6.42 + 1.57\n", - "Bajrami: MV 5.90 ± 0.65; FV 5.95 + 0.74\n", - "Ricci S.: MV 6.02 ± 0.85; FV 6.14 + 1.21\n", - "Colpani: MV 6.35 ± 1.05; FV 7.08 + 2.50\n", - "Ciurria: MV 6.17 ± 1.02; FV 6.71 + 2.04\n", - "De Roon: MV 6.16 ± 0.81; FV 6.38 + 1.18\n", - "Pogba: MV 6.09 ± 0.72; FV 6.19 + 0.98\n", - "Cristante: MV 6.11 ± 1.04; FV 6.32 + 1.47\n", - "Locatelli: MV 6.17 ± 0.77; FV 6.33 + 1.15\n", - "Pasalic: MV 6.05 ± 0.80; FV 6.36 + 1.28\n", - "Lobotka: MV 6.06 ± 0.65; FV 6.11 + 0.66\n", - "Fagioli: MV 6.19 ± 1.02; FV 6.72 + 2.01\n", - "Ikone': MV 6.02 ± 0.93; FV 6.40 + 1.55\n", - "Ilic: MV 6.03 ± 0.97; FV 6.27 + 1.49\n", - "Ndoye: MV 5.83 ± 0.88; FV 5.96 + 1.14\n", - "Ederson D.s.: MV 6.13 ± 0.81; FV 6.31 + 1.10\n", - "Reijnders: MV 6.17 ± 0.76; FV 6.37 + 1.06\n", - "Barak: MV 5.95 ± 0.71; FV 6.05 + 0.81\n", - "Saponara: MV 6.02 ± 1.02; FV 6.42 + 1.69\n", - "Mandragora: MV 6.03 ± 0.90; FV 6.33 + 1.41\n", - "Weah: MV 6.09 ± 0.59; FV 6.21 + 0.74\n", - "Bennacer: MV 6.24 ± 0.82; FV 6.54 + 1.32\n", - "Duda: MV 6.17 ± 1.11; FV 6.71 + 2.09\n", - "Castrovilli: MV 6.04 ± 0.99; FV 6.46 + 1.69\n", - "Mckennie: MV 6.35 ± 0.94; FV 6.84 + 1.93\n", - "Miranchuk: MV 6.22 ± 0.84; FV 6.60 + 1.49\n", - "Matheus Henrique: MV 5.77 ± 0.78; FV 5.87 + 1.02\n", - "De Ketelaere: MV 6.06 ± 0.82; FV 6.27 + 1.10\n", - "Mboula: MV 5.62 ± 0.76; FV 5.60 + 0.82\n", - "Paredes: MV 5.77 ± 1.07; FV 5.70 + 1.16\n", - "Sottil: MV 6.01 ± 0.62; FV 6.11 + 0.69\n", - "Klaassen: MV 6.40 ± 0.83; FV 6.81 + 1.78\n", - "Arthur Melo: MV 6.03 ± 0.76; FV 6.06 + 0.78\n", - "Thorsby: MV 5.72 ± 0.90; FV 5.79 + 1.16\n", - "Nandez: MV 5.94 ± 0.71; FV 6.04 + 1.00\n", - "Tameze: MV 5.80 ± 0.87; FV 5.74 + 1.01\n", - "Marin: MV 5.56 ± 0.85; FV 5.54 + 0.93\n", - "Messias: MV 5.86 ± 1.02; FV 6.23 + 1.61\n", - "Musah: MV 6.03 ± 0.61; FV 6.03 + 0.63\n", - "Coulibaly L.: MV 6.05 ± 1.05; FV 6.36 + 1.62\n", - "Krunic: MV 6.05 ± 0.68; FV 6.04 + 0.69\n", - "Cataldi: MV 5.96 ± 0.69; FV 5.94 + 0.68\n", - "Strootman: MV 5.87 ± 0.69; FV 5.92 + 0.86\n", - "Duncan: MV 6.08 ± 0.76; FV 6.33 + 1.11\n", - "Freuler: MV 5.92 ± 0.65; FV 5.96 + 0.79\n", - "Gagliardini: MV 5.88 ± 0.75; FV 5.85 + 0.79\n", - "Mazzitelli: MV 6.27 ± 1.12; FV 6.89 + 2.24\n", - "Jankto: MV 5.82 ± 0.67; FV 5.79 + 0.73\n", - "Kastanos: MV 5.95 ± 0.75; FV 6.08 + 0.99\n", - "Gyasi: MV 5.52 ± 0.74; FV 5.45 + 0.77\n", - "Reinier: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Zalewski: MV 5.97 ± 0.75; FV 6.06 + 0.84\n", - "Harroui: MV 6.27 ± 0.92; FV 6.73 + 1.77\n", - "Frendrup: MV 5.94 ± 0.68; FV 6.00 + 0.87\n", - "Blin: MV 6.03 ± 0.61; FV 6.03 + 0.69\n", - "Fabbian: MV 6.09 ± 0.95; FV 6.48 + 1.69\n", - "Ramadani: MV 6.20 ± 0.90; FV 6.36 + 1.25\n", - "Cajuste : MV 5.92 ± 0.87; FV 5.94 + 0.96\n", - "Mancosu: MV 5.69 ± 0.99; FV 5.73 + 1.21\n", - "Vecino: MV 5.96 ± 0.82; FV 6.04 + 1.06\n", - "Sensi: MV 6.42 ± 0.87; FV 6.88 + 1.88\n", - "Walace: MV 5.65 ± 1.00; FV 5.61 + 1.10\n", - "Lopez M.: MV 5.90 ± 0.61; FV 5.85 + 0.54\n", - "Brescianini: MV 6.09 ± 0.69; FV 6.15 + 0.78\n", - "Bove: MV 6.02 ± 0.72; FV 6.17 + 0.90\n", - "Aebischer: MV 5.83 ± 0.72; FV 5.98 + 0.96\n", - "Thorstvedt: MV 5.86 ± 0.62; FV 5.89 + 0.70\n", - "Gonzalez J.: MV 5.98 ± 0.75; FV 6.07 + 1.03\n", - "Moro N.: MV 6.03 ± 0.85; FV 6.28 + 1.32\n", - "Oudin: MV 6.14 ± 0.94; FV 6.49 + 1.59\n", - "Boloca: MV 5.73 ± 0.88; FV 5.75 + 1.07\n", - "Rafia: MV 6.15 ± 0.74; FV 6.37 + 1.23\n", - "Makoumbou: MV 5.78 ± 0.70; FV 5.80 + 0.83\n", - "Kaba: MV 6.04 ± 0.57; FV 6.02 + 0.62\n", - "Badelj: MV 5.86 ± 0.75; FV 5.83 + 0.78\n", - "Machin: MV 5.95 ± 0.88; FV 6.06 + 1.20\n", - "Linetty: MV 5.81 ± 0.84; FV 5.78 + 1.02\n", - "Castillejo: MV 5.79 ± 0.59; FV 5.86 + 0.70\n", - "Rovella: MV 6.09 ± 0.95; FV 6.22 + 1.27\n", - "Pobega: MV 6.02 ± 0.64; FV 6.10 + 0.74\n", - "Hongla: MV 5.72 ± 0.82; FV 5.79 + 0.98\n", - "Miretti: MV 6.05 ± 0.75; FV 6.26 + 1.08\n", - "Fazzini: MV 5.55 ± 0.64; FV 5.42 + 0.65\n", - "Iling Junior: MV 6.09 ± 0.84; FV 6.30 + 1.33\n", - "Oristanio: MV 5.68 ± 0.84; FV 5.63 + 0.90\n", - "Serdar: MV 5.73 ± 0.83; FV 5.75 + 1.00\n", - "Payero: MV 5.80 ± 1.04; FV 5.79 + 1.30\n", - "Grassi: MV 5.51 ± 0.78; FV 5.42 + 0.78\n", - "Baez: MV 6.08 ± 0.75; FV 6.29 + 1.02\n", - "Deiola: MV 5.66 ± 0.97; FV 5.68 + 1.14\n", - "Garritano: MV 6.22 ± 0.67; FV 6.30 + 0.83\n", - "Bourabia: MV 6.07 ± 0.80; FV 6.25 + 1.05\n", - "Saelemaekers: MV 5.92 ± 0.90; FV 6.19 + 1.34\n", - "Maldini: MV 5.64 ± 0.73; FV 5.69 + 0.89\n", - "Racic: MV 5.85 ± 0.63; FV 5.83 + 0.68\n", - "Kovalenko: MV 5.61 ± 0.67; FV 5.54 + 0.73\n" + "De Winter: MV 6.07 ± 0.86; FV 6.09 + 0.87\n", + "Tressoldi: MV 5.97 ± 0.85; FV 6.01 + 1.01\n", + "Ehizibue: MV 5.78 ± 0.92; FV 5.88 + 1.30\n", + "Vogliacco: MV 6.04 ± 0.82; FV 6.06 + 0.86\n", + "Ferrari G.: MV 6.01 ± 0.87; FV 6.14 + 1.18\n", + "Venuti: MV 5.78 ± 0.84; FV 5.74 + 0.91\n", + "Karsdorp: MV 5.91 ± 0.57; FV 5.91 + 0.61\n", + "Kjaer: MV 5.69 ± 0.91; FV 5.60 + 0.91\n", + "Gunter: MV 5.69 ± 1.03; FV 5.58 + 1.07\n", + "Soumaoro: MV 6.13 ± 0.77; FV 6.19 + 0.95\n", + "Di Pardo: MV 5.58 ± 1.09; FV 5.51 + 1.14\n", + "Zanoli: MV 6.00 ± 0.89; FV 6.20 + 1.28\n", + "Zima: MV 6.05 ± 0.77; FV 6.09 + 0.77\n", + "Hefti: MV 5.91 ± 0.65; FV 5.88 + 0.56\n", + "Ostigard: MV 5.82 ± 0.72; FV 5.79 + 0.74\n", + "Sambia: MV 5.70 ± 0.77; FV 5.68 + 0.85\n", + "Bisseck: MV 6.07 ± 0.81; FV 6.20 + 0.99\n", + "Oyono: MV 5.79 ± 1.02; FV 5.64 + 1.13\n", + "Ferreira J.: MV 5.84 ± 0.66; FV 5.78 + 0.74\n", + "Dorgu: MV 5.91 ± 0.55; FV 5.87 + 0.53\n", + "Touba: MV 5.82 ± 1.03; FV 5.84 + 1.20\n", + "Sazonov: MV 6.01 ± 0.68; FV 6.06 + 0.74\n", + "Rugani: MV 5.92 ± 0.55; FV 5.92 + 0.57\n", + "De Sciglio: MV 5.72 ± 0.75; FV 5.64 + 0.76\n", + "Goldaniga: MV 5.55 ± 1.26; FV 5.46 + 1.44\n", + "Florenzi: MV 6.07 ± 0.75; FV 6.15 + 0.89\n", + "De Silvestri: MV 6.11 ± 0.51; FV 6.18 + 0.53\n", + "Pereira P.: MV 5.96 ± 0.81; FV 6.02 + 1.10\n", + "Fazio: MV 5.66 ± 1.26; FV 5.65 + 1.48\n", + "Bereszynski: MV 5.66 ± 0.88; FV 5.58 + 0.91\n", + "Bonifazi: MV 6.00 ± 0.61; FV 6.01 + 0.59\n", + "Walukiewicz: MV 5.75 ± 0.95; FV 5.69 + 1.00\n", + "Okoli: MV 5.65 ± 1.12; FV 5.49 + 1.24\n", + "Kumbulla: MV 5.55 ± 1.47; FV 5.32 + 1.45\n", + "Celik: MV 5.73 ± 0.91; FV 5.65 + 1.02\n", + "Amione: MV 5.66 ± 0.94; FV 5.63 + 1.06\n", + "Daniliuc: MV 5.58 ± 0.97; FV 5.54 + 1.08\n", + "Soppy: MV 5.97 ± 0.59; FV 5.98 + 0.62\n", + "Haps: MV 6.06 ± 0.83; FV 6.15 + 1.01\n", + "Cittadini: MV 5.92 ± 0.86; FV 5.96 + 1.19\n", + "Coppola D.: MV 5.82 ± 0.72; FV 5.76 + 0.72\n", + "Cacace: MV 5.76 ± 0.70; FV 5.71 + 0.66\n", + "Ebosse: MV 5.85 ± 0.75; FV 5.78 + 0.81\n", + "Guessand A.: MV 5.91 ± 0.91; FV 5.93 + 1.13\n", + "Cabal: MV 6.00 ± 0.89; FV 6.02 + 1.00\n", + "Missori: MV 6.00 ± 0.87; FV 6.06 + 1.05\n", + "Kayode: MV 6.14 ± 0.91; FV 6.25 + 1.14\n", + "Corazza: MV 6.00 ± 0.58; FV 6.01 + 0.64\n", + "Kristensen T.: MV 5.81 ± 0.81; FV 5.76 + 0.97\n", + "Dermaku: MV 5.79 ± 1.01; FV 5.84 + 1.22\n", + "Tonelli: MV 5.73 ± 0.85; FV 5.65 + 0.82\n", + "Capradossi: MV 5.66 ± 1.16; FV 5.64 + 1.29\n", + "Bettella: MV 5.92 ± 0.86; FV 5.96 + 1.19\n", + "Amey: MV 6.10 ± 0.70; FV 6.20 + 0.93\n", + "Gila: MV 5.69 ± 1.04; FV 5.64 + 1.17\n", + "Bronn: MV 5.52 ± 1.00; FV 5.44 + 1.09\n", + "Guarino: MV 5.89 ± 0.77; FV 5.88 + 0.84\n", + "Carboni F.: MV 6.01 ± 0.87; FV 6.13 + 1.25\n", + "Smajlovic: MV 5.80 ± 1.05; FV 5.87 + 1.30\n", + "Matturro: MV 6.03 ± 0.80; FV 6.04 + 0.80\n", + "N'guessan: MV 6.00 ± 0.73; FV 6.06 + 0.81\n", + "Mateus Lusuardi: MV 5.78 ± 1.20; FV 5.72 + 1.43\n", + "Kalaj: MV 5.78 ± 1.20; FV 5.72 + 1.43\n", + "Pierozzi: MV 6.05 ± 0.85; FV 6.12 + 1.04\n", + "Huijsen: MV 5.76 ± 1.10; FV 5.81 + 1.34\n", + "Bonfanti: MV 5.90 ± 1.04; FV 6.01 + 1.33\n", + "Pellegrino: MV 5.98 ± 0.88; FV 6.06 + 1.11\n", + "Comuzzo: MV 6.05 ± 0.85; FV 6.12 + 1.04\n", + "Zaccagni: MV 6.25 ± 1.08; FV 6.80 + 2.13\n", + "Koopmeiners: MV 6.30 ± 1.07; FV 6.90 + 2.21\n", + "Luis Alberto: MV 6.20 ± 1.10; FV 6.77 + 2.14\n", + "Felipe Anderson: MV 6.00 ± 1.06; FV 6.39 + 1.70\n", + "Rabiot: MV 6.07 ± 1.12; FV 6.54 + 1.93\n", + "Zielinski: MV 6.19 ± 0.87; FV 6.57 + 1.52\n", + "Barella: MV 6.29 ± 0.89; FV 6.73 + 1.65\n", + "Pulisic: MV 6.32 ± 1.15; FV 7.11 + 2.64\n", + "Orsolini: MV 6.25 ± 0.91; FV 6.88 + 2.16\n", + "Calhanoglu: MV 6.38 ± 0.78; FV 6.65 + 1.28\n", + "Strefezza: MV 6.00 ± 0.95; FV 6.28 + 1.49\n", + "Chukwueze: MV 5.93 ± 0.81; FV 6.17 + 1.14\n", + "Ferguson: MV 6.25 ± 0.74; FV 6.60 + 1.38\n", + "Candreva: MV 6.03 ± 1.24; FV 6.33 + 1.84\n", + "Frattesi: MV 6.30 ± 1.02; FV 6.93 + 2.18\n", + "Samardzic: MV 6.19 ± 0.99; FV 6.69 + 1.94\n", + "Vlasic: MV 6.10 ± 0.78; FV 6.35 + 1.22\n", + "Bonaventura: MV 6.40 ± 1.13; FV 7.25 + 2.73\n", + "Politano: MV 6.25 ± 0.91; FV 6.71 + 1.79\n", + "El Shaarawy: MV 6.17 ± 0.85; FV 6.53 + 1.56\n", + "Mkhitaryan: MV 6.35 ± 1.00; FV 6.99 + 2.19\n", + "Aouar: MV 6.07 ± 1.04; FV 6.58 + 1.92\n", + "Malinovskyi: MV 6.18 ± 0.90; FV 6.65 + 1.82\n", + "Gudmundsson A.: MV 6.30 ± 0.94; FV 6.86 + 1.99\n", + "Kamada: MV 5.98 ± 1.03; FV 6.33 + 1.59\n", + "Pellegrini Lo.: MV 5.98 ± 1.09; FV 6.45 + 1.89\n", + "Kostic: MV 6.07 ± 0.92; FV 6.36 + 1.44\n", + "Radonjic: MV 6.30 ± 1.08; FV 6.99 + 2.38\n", + "Baldanzi: MV 5.90 ± 0.98; FV 6.25 + 1.56\n", + "Lovric: MV 6.07 ± 0.84; FV 6.40 + 1.48\n", + "Lindstrom: MV 5.94 ± 0.73; FV 6.18 + 1.15\n", + "Lazovic: MV 6.10 ± 0.84; FV 6.37 + 1.36\n", + "Pereyra: MV 6.18 ± 1.23; FV 6.88 + 2.56\n", + "Renato Sanches: MV 6.16 ± 0.73; FV 6.43 + 1.22\n", + "Pessina: MV 6.07 ± 0.92; FV 6.39 + 1.58\n", + "Guendouzi: MV 5.86 ± 0.84; FV 6.00 + 1.07\n", + "Loftus-Cheek: MV 6.25 ± 0.91; FV 6.68 + 1.68\n", + "Zambo Anguissa: MV 6.03 ± 0.92; FV 6.23 + 1.29\n", + "Elmas: MV 5.93 ± 0.95; FV 6.23 + 1.48\n", + "Bajrami: MV 6.03 ± 0.68; FV 6.21 + 0.90\n", + "Ricci S.: MV 6.04 ± 0.73; FV 6.13 + 0.88\n", + "Colpani: MV 6.38 ± 1.13; FV 7.19 + 2.68\n", + "Ciurria: MV 6.02 ± 1.05; FV 6.47 + 1.94\n", + "De Roon: MV 6.06 ± 1.00; FV 6.33 + 1.51\n", + "Pogba: MV 5.94 ± 0.88; FV 6.00 + 1.15\n", + "Cristante: MV 6.12 ± 0.99; FV 6.50 + 1.66\n", + "Locatelli: MV 5.88 ± 0.82; FV 5.90 + 1.03\n", + "Pasalic: MV 5.97 ± 1.01; FV 6.35 + 1.63\n", + "Lobotka: MV 6.01 ± 0.72; FV 6.08 + 0.85\n", + "Fagioli: MV 5.95 ± 1.02; FV 6.23 + 1.53\n", + "Ikone': MV 6.21 ± 1.03; FV 6.76 + 2.04\n", + "Ilic: MV 6.05 ± 0.66; FV 6.11 + 0.74\n", + "Ndoye: MV 6.09 ± 0.64; FV 6.21 + 0.83\n", + "Ederson D.s.: MV 6.05 ± 1.00; FV 6.36 + 1.56\n", + "Reijnders: MV 6.18 ± 0.90; FV 6.56 + 1.57\n", + "Barak: MV 5.99 ± 0.78; FV 6.15 + 1.04\n", + "Saponara: MV 6.06 ± 0.76; FV 6.27 + 1.14\n", + "Mandragora: MV 6.14 ± 1.01; FV 6.59 + 1.81\n", + "Weah: MV 5.88 ± 0.57; FV 5.90 + 0.63\n", + "Bennacer: MV 6.21 ± 0.89; FV 6.60 + 1.58\n", + "Duda: MV 6.22 ± 1.00; FV 6.71 + 1.91\n", + "Castrovilli: MV 6.20 ± 1.08; FV 6.79 + 2.13\n", + "Mckennie: MV 6.13 ± 0.78; FV 6.34 + 1.11\n", + "Miranchuk: MV 6.17 ± 0.91; FV 6.52 + 1.57\n", + "Matheus Henrique: MV 6.03 ± 0.88; FV 6.23 + 1.28\n", + "De Ketelaere: MV 6.06 ± 1.01; FV 6.40 + 1.61\n", + "Mboula: MV 5.90 ± 0.76; FV 5.88 + 0.86\n", + "Paredes: MV 5.85 ± 0.99; FV 5.87 + 1.21\n", + "Sottil: MV 6.01 ± 0.63; FV 6.10 + 0.74\n", + "Klaassen: MV 6.21 ± 0.86; FV 6.60 + 1.54\n", + "Arthur Melo: MV 6.11 ± 0.76; FV 6.21 + 0.86\n", + "Thorsby: MV 6.16 ± 0.95; FV 6.64 + 1.82\n", + "Nandez: MV 5.94 ± 0.81; FV 6.09 + 1.12\n", + "Tameze: MV 5.93 ± 0.57; FV 5.91 + 0.52\n", + "Marin: MV 5.94 ± 0.67; FV 5.96 + 0.77\n", + "Messias: MV 6.18 ± 0.89; FV 6.65 + 1.79\n", + "Musah: MV 6.03 ± 0.70; FV 6.07 + 0.82\n", + "Coulibaly L.: MV 5.82 ± 0.93; FV 5.96 + 1.27\n", + "Krunic: MV 5.98 ± 0.74; FV 5.99 + 0.81\n", + "Cataldi: MV 5.89 ± 0.84; FV 5.85 + 0.97\n", + "Strootman: MV 6.04 ± 0.61; FV 6.14 + 0.75\n", + "Duncan: MV 6.25 ± 0.86; FV 6.68 + 1.62\n", + "Freuler: MV 6.00 ± 0.49; FV 6.03 + 0.50\n", + "Gagliardini: MV 6.15 ± 0.92; FV 6.53 + 1.69\n", + "Mazzitelli: MV 6.14 ± 1.39; FV 6.65 + 2.59\n", + "Jankto: MV 5.79 ± 0.80; FV 5.81 + 0.91\n", + "Kastanos: MV 5.86 ± 0.55; FV 5.96 + 0.72\n", + "Gyasi: MV 5.68 ± 0.77; FV 5.66 + 0.84\n", + "Reinier: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Zalewski: MV 5.89 ± 0.68; FV 5.99 + 0.83\n", + "Harroui: MV 6.18 ± 1.07; FV 6.67 + 1.92\n", + "Frendrup: MV 6.10 ± 0.61; FV 6.24 + 0.73\n", + "Blin: MV 5.92 ± 0.57; FV 5.92 + 0.62\n", + "Fabbian: MV 6.14 ± 0.75; FV 6.54 + 1.52\n", + "Ramadani: MV 6.05 ± 0.87; FV 6.17 + 1.12\n", + "Cajuste : MV 5.95 ± 0.89; FV 5.99 + 1.12\n", + "Mancosu: MV 5.68 ± 1.15; FV 5.69 + 1.31\n", + "Vecino: MV 5.86 ± 1.02; FV 6.02 + 1.39\n", + "Sensi: MV 6.19 ± 0.87; FV 6.59 + 1.47\n", + "Walace: MV 5.82 ± 0.75; FV 5.74 + 0.84\n", + "Lopez M.: MV 5.97 ± 0.76; FV 5.96 + 0.77\n", + "Brescianini: MV 5.93 ± 0.88; FV 5.89 + 1.04\n", + "Bove: MV 5.91 ± 0.87; FV 6.13 + 1.27\n", + "Aebischer: MV 6.05 ± 0.53; FV 6.14 + 0.60\n", + "Thorstvedt: MV 5.95 ± 0.66; FV 5.97 + 0.70\n", + "Gonzalez J.: MV 5.82 ± 0.83; FV 5.89 + 1.10\n", + "Moro N.: MV 6.14 ± 0.62; FV 6.31 + 0.83\n", + "Oudin: MV 5.97 ± 1.02; FV 6.30 + 1.61\n", + "Boloca: MV 6.04 ± 0.96; FV 6.12 + 1.20\n", + "Rafia: MV 5.80 ± 0.76; FV 5.94 + 1.05\n", + "Makoumbou: MV 5.71 ± 0.75; FV 5.77 + 0.86\n", + "Kaba: MV 5.78 ± 0.85; FV 5.66 + 0.95\n", + "Badelj: MV 5.96 ± 0.73; FV 5.96 + 0.72\n", + "Machin: MV 5.91 ± 0.87; FV 5.96 + 1.22\n", + "Linetty: MV 5.94 ± 0.62; FV 5.94 + 0.63\n", + "Castillejo: MV 5.99 ± 0.66; FV 6.12 + 0.91\n", + "Rovella: MV 5.97 ± 1.04; FV 6.06 + 1.32\n", + "Pobega: MV 5.94 ± 0.52; FV 5.97 + 0.57\n", + "Hongla: MV 5.90 ± 0.62; FV 5.88 + 0.62\n", + "Miretti: MV 5.77 ± 0.72; FV 5.79 + 0.83\n", + "Fazzini: MV 5.81 ± 0.63; FV 5.76 + 0.60\n", + "Iling Junior: MV 5.78 ± 1.06; FV 5.85 + 1.32\n", + "Oristanio: MV 5.71 ± 0.80; FV 5.71 + 0.85\n", + "Serdar: MV 5.91 ± 0.65; FV 5.89 + 0.69\n", + "Payero: MV 5.88 ± 0.75; FV 5.84 + 0.89\n", + "Grassi: MV 5.86 ± 0.70; FV 5.81 + 0.67\n", + "Baez: MV 5.86 ± 0.79; FV 5.88 + 0.92\n", + "Deiola: MV 5.52 ± 0.97; FV 5.49 + 0.90\n", + "Garritano: MV 6.09 ± 0.99; FV 6.20 + 1.30\n", + "Bourabia: MV 5.95 ± 0.95; FV 6.07 + 1.27\n", + "Saelemaekers: MV 6.09 ± 0.70; FV 6.31 + 1.08\n", + "Maldini: MV 5.96 ± 0.74; FV 6.15 + 1.06\n", + "Racic: MV 5.95 ± 0.69; FV 5.95 + 0.70\n", + "Kovalenko: MV 5.90 ± 0.68; FV 5.86 + 0.67\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Maleh: MV 5.56 ± 0.55; FV 5.41 + 0.57\n", - "Bohinen: MV 5.91 ± 0.58; FV 5.86 + 0.56\n", - "Ranocchia F.: MV 5.67 ± 0.66; FV 5.72 + 0.80\n", - "Folorunsho: MV 5.85 ± 0.93; FV 6.10 + 1.37\n", - "Infantino: MV 5.90 ± 0.53; FV 5.87 + 0.48\n", - "Martegani: MV 5.93 ± 0.95; FV 6.00 + 1.20\n", - "Kutlu: MV 5.86 ± 0.74; FV 5.83 + 0.82\n", - "Tchatchoua: MV 5.76 ± 0.97; FV 5.85 + 1.27\n", - "Quina: MV 5.99 ± 0.94; FV 6.06 + 1.20\n", - "Adopo: MV 5.97 ± 0.78; FV 6.00 + 0.81\n", - "Romero L.: MV 6.25 ± 0.88; FV 6.65 + 1.63\n", - "Basic: MV 6.04 ± 0.74; FV 6.14 + 1.01\n", - "Asllani: MV 6.10 ± 0.56; FV 6.15 + 0.54\n", - "Tchaouna: MV 5.86 ± 0.82; FV 5.87 + 1.00\n", - "Sulemana I.: MV 5.65 ± 0.72; FV 5.59 + 0.74\n", - "Barrenechea: MV 6.04 ± 0.76; FV 6.10 + 0.88\n", - "Gelli: MV 6.05 ± 0.86; FV 6.18 + 1.07\n", - "Suslov: MV 5.78 ± 0.89; FV 5.85 + 1.15\n", - "Gaetano: MV 6.04 ± 0.99; FV 6.54 + 1.83\n", - "Jagiello: MV 5.87 ± 0.84; FV 5.86 + 0.96\n", - "Obiang: MV 5.86 ± 0.55; FV 5.83 + 0.55\n", - "Maggiore: MV 5.89 ± 0.53; FV 5.85 + 0.53\n", - "Akpa Akpro: MV 5.95 ± 0.88; FV 6.06 + 1.20\n", - "Urbanski: MV 5.91 ± 0.78; FV 6.00 + 1.01\n", - "Volpato: MV 5.82 ± 0.72; FV 5.90 + 0.90\n", - "Vignato S.: MV 5.87 ± 0.79; FV 5.90 + 0.94\n", - "Hrustic: MV 5.54 ± 0.69; FV 5.57 + 0.74\n", - "Zarraga: MV 5.47 ± 0.98; FV 5.45 + 0.91\n", - "Camara E.: MV 5.79 ± 1.08; FV 5.80 + 1.39\n", - "Amatucci: MV 5.93 ± 0.66; FV 5.92 + 0.64\n", - "Pagano: MV 5.95 ± 0.62; FV 5.95 + 0.60\n", - "Prati: MV 5.70 ± 0.90; FV 5.69 + 1.03\n", - "Viola: MV 5.62 ± 0.79; FV 5.53 + 0.76\n", - "Lulic K.: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Rog: MV 5.71 ± 0.79; FV 5.69 + 0.85\n", - "Nicolussi Caviglia: MV 5.90 ± 0.88; FV 6.26 + 1.47\n", - "Demme: MV 5.98 ± 0.48; FV 5.93 + 0.39\n", - "Pafundi: MV 6.00 ± 0.80; FV 6.02 + 0.86\n", - "Adli: MV 5.98 ± 0.69; FV 6.02 + 0.72\n", - "Bondo: MV 5.95 ± 0.84; FV 6.06 + 1.11\n", - "Zerbin: MV 6.04 ± 0.61; FV 6.09 + 0.64\n", - "Carboni V.: MV 6.00 ± 0.78; FV 6.09 + 1.00\n", - "Faticanti: MV 6.03 ± 0.86; FV 6.14 + 1.14\n", - "Gineitis: MV 5.91 ± 0.92; FV 5.91 + 1.14\n", - "Belardinelli: MV 5.53 ± 0.86; FV 5.50 + 0.92\n", - "El Azzouzi: MV 5.93 ± 0.69; FV 6.02 + 0.87\n", - "Lipani: MV 5.76 ± 0.82; FV 5.81 + 1.02\n", - "Joselito: MV 5.76 ± 0.97; FV 5.85 + 1.27\n", - "Legowski: MV 5.96 ± 1.03; FV 6.12 + 1.39\n", - "Ibrahimovic A.: MV 6.04 ± 0.87; FV 6.19 + 1.12\n", - "Osimhen: MV 6.47 ± 1.55; FV 7.89 + 4.08\n", - "Martinez L.: MV 6.56 ± 1.27; FV 7.97 + 3.97\n", - "Rafael Leao: MV 6.50 ± 1.19; FV 7.58 + 3.28\n", - "Lukaku: MV 6.26 ± 1.46; FV 7.29 + 3.16\n", - "Berardi: MV 6.32 ± 1.38; FV 7.38 + 3.38\n", - "Immobile: MV 6.17 ± 1.35; FV 7.10 + 3.02\n", - "Vlahovic: MV 6.41 ± 1.47; FV 7.70 + 3.82\n", - "Dybala: MV 6.41 ± 1.49; FV 7.69 + 3.78\n", - "Kvaratskhelia: MV 6.42 ± 1.25; FV 7.47 + 3.19\n", - "Giroud: MV 6.46 ± 1.20; FV 7.54 + 3.25\n", - "Scamacca: MV 6.36 ± 1.30; FV 7.60 + 3.52\n", - "Thuram: MV 6.59 ± 1.03; FV 7.50 + 3.06\n", - "Lookman: MV 6.42 ± 1.29; FV 7.62 + 3.49\n", - "Dia: MV 6.30 ± 1.40; FV 7.39 + 3.41\n", - "Arnautovic: MV 6.52 ± 1.09; FV 7.49 + 3.08\n", - "Retegui: MV 5.91 ± 1.23; FV 6.42 + 1.94\n", - "Sanabria: MV 6.17 ± 1.33; FV 7.01 + 2.74\n", - "Nzola: MV 5.95 ± 1.18; FV 6.51 + 2.00\n", - "Lauriente': MV 6.08 ± 1.18; FV 6.56 + 2.17\n", - "Zapata D.: MV 5.97 ± 0.99; FV 6.36 + 1.60\n", - "Chiesa: MV 6.46 ± 1.19; FV 7.51 + 3.21\n", - "Milik: MV 6.31 ± 1.09; FV 7.06 + 2.53\n", - "Gonzalez N.: MV 6.23 ± 1.09; FV 7.02 + 2.56\n", - "Okafor: MV 6.01 ± 0.51; FV 6.00 + 0.49\n", - "Pinamonti: MV 5.83 ± 1.08; FV 6.21 + 1.68\n", - "Beltran L.: MV 6.04 ± 0.96; FV 6.51 + 1.76\n", - "Caprari: MV 6.04 ± 1.00; FV 6.50 + 1.79\n", - "Sanchez: MV 6.45 ± 0.96; FV 7.08 + 2.32\n", - "Caputo: MV 5.53 ± 0.73; FV 5.57 + 0.78\n", - "Toure' E.: MV 6.05 ± 0.74; FV 6.17 + 0.94\n", - "Krstovic: MV 6.38 ± 0.87; FV 6.82 + 1.82\n", - "Belotti: MV 6.10 ± 0.99; FV 6.62 + 1.91\n", - "Muriel: MV 6.18 ± 0.82; FV 6.47 + 1.38\n", - "Lapadula: MV 5.86 ± 0.93; FV 6.18 + 1.49\n", - "Jovic: MV 6.09 ± 1.18; FV 6.80 + 2.40\n", - "Abraham: MV 6.11 ± 1.24; FV 6.87 + 2.48\n", - "Zirkzee: MV 6.21 ± 1.02; FV 6.73 + 2.01\n", - "Ngonge: MV 5.98 ± 1.16; FV 6.53 + 2.01\n", - "Petagna: MV 5.88 ± 0.98; FV 6.21 + 1.53\n", - "Simeone: MV 5.84 ± 0.92; FV 6.24 + 1.42\n", - "Deulofeu: MV 6.35 ± 1.27; FV 7.35 + 3.17\n", - "Pedro: MV 6.05 ± 0.93; FV 6.42 + 1.61\n", - "Shomurodov: MV 5.70 ± 0.75; FV 5.88 + 1.01\n", - "Azmoun: MV 5.89 ± 0.82; FV 6.19 + 1.27\n", - "Castellanos: MV 5.96 ± 0.56; FV 5.95 + 0.57\n", - "Cheddira: MV 6.28 ± 1.16; FV 7.20 + 2.82\n", - "Karlsson: MV 6.12 ± 0.90; FV 6.47 + 1.58\n", - "Brekalo: MV 6.05 ± 1.02; FV 6.57 + 1.89\n", - "Cambiaghi: MV 5.69 ± 0.88; FV 5.81 + 1.11\n", - "Henry: MV 5.81 ± 0.97; FV 6.12 + 1.42\n", - "Mulattieri: MV 5.79 ± 0.61; FV 5.94 + 0.90\n", - "Almqvist: MV 6.21 ± 1.07; FV 6.75 + 2.05\n", - "Isaksen: MV 5.93 ± 0.76; FV 5.96 + 0.90\n", - "Kean: MV 6.03 ± 1.25; FV 6.69 + 2.43\n", - "Karamoh: MV 5.98 ± 0.84; FV 6.26 + 1.35\n", - "Thauvin: MV 5.60 ± 0.81; FV 5.73 + 0.89\n", - "Kouame': MV 6.04 ± 1.10; FV 6.67 + 2.17\n", - "Raspadori: MV 5.94 ± 0.98; FV 6.34 + 1.57\n", - "Colombo: MV 5.96 ± 1.16; FV 6.50 + 2.05\n", - "Luvumbo: MV 5.89 ± 0.74; FV 6.00 + 1.00\n", - "Mota: MV 5.89 ± 1.13; FV 6.33 + 1.83\n", - "Brenner: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Bonazzoli: MV 5.90 ± 0.98; FV 6.27 + 1.53\n", - "Djuric: MV 5.85 ± 0.74; FV 6.03 + 1.04\n", - "Davis K.: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Banda: MV 6.19 ± 0.86; FV 6.48 + 1.47\n", - "Defrel: MV 5.68 ± 0.68; FV 5.73 + 0.86\n", - "Sansone: MV 6.34 ± 1.14; FV 7.16 + 2.70\n", - "Pellegri: MV 5.71 ± 0.85; FV 5.89 + 1.07\n", - "Piccoli: MV 5.99 ± 0.81; FV 6.29 + 1.37\n", - "Success: MV 5.80 ± 0.92; FV 6.09 + 1.26\n", - "Botheim: MV 5.78 ± 0.75; FV 5.89 + 1.01\n", - "Lucca: MV 5.79 ± 0.95; FV 5.97 + 1.23\n", - "Caso: MV 6.26 ± 1.01; FV 6.82 + 2.03\n", - "Jovane: MV 5.96 ± 1.03; FV 6.15 + 1.41\n", - "Soule': MV 6.35 ± 0.87; FV 6.71 + 1.61\n", - "Pavoletti: MV 5.71 ± 0.72; FV 5.79 + 0.92\n", - "Cancellieri: MV 5.53 ± 0.62; FV 5.44 + 0.60\n", - "Seck: MV 6.14 ± 0.72; FV 6.29 + 1.00\n", - "Alvarez A.: MV 5.81 ± 0.68; FV 5.90 + 0.87\n", - "Cuni: MV 6.04 ± 0.63; FV 6.08 + 0.69\n", - "Ekuban: MV 5.79 ± 0.65; FV 5.90 + 0.78\n", - "Maric: MV 5.96 ± 0.72; FV 6.01 + 0.89\n", - "Cruz: MV 5.75 ± 0.96; FV 5.86 + 1.25\n", - "Destro: MV 5.50 ± 0.81; FV 5.47 + 0.82\n", - "Van Hooijdonk: MV 5.91 ± 0.92; FV 6.07 + 1.25\n", - "Ceide: MV 5.70 ± 0.72; FV 5.72 + 0.73\n", - "Kvernadze: MV 6.01 ± 0.81; FV 6.11 + 0.98\n", - "Ikwuemesi: MV 5.87 ± 0.85; FV 5.92 + 1.03\n", - "Puscas: MV 5.85 ± 0.85; FV 5.89 + 1.01\n", - "Ake' M.: MV 5.77 ± 1.02; FV 5.75 + 1.22\n", - "Braaf: MV 5.61 ± 0.69; FV 5.75 + 0.86\n", - "Kallon: MV 5.85 ± 0.86; FV 6.11 + 1.32\n", - "Kaio Jorge: MV 6.01 ± 0.61; FV 6.08 + 0.63\n", - "Vivaldo: MV 5.77 ± 1.10; FV 5.79 + 1.40\n", - "Bidaoui: MV 6.05 ± 0.89; FV 6.26 + 1.21\n", - "Shpendi S.: MV 5.53 ± 0.73; FV 5.47 + 0.75\n", - "Burnete: MV 6.05 ± 0.80; FV 6.14 + 1.05\n", - "Corfitzen: MV 6.04 ± 0.89; FV 6.21 + 1.25\n", - "Stewart: MV 5.96 ± 1.03; FV 6.15 + 1.41\n", - "Yildiz: MV 6.10 ± 0.87; FV 6.37 + 1.41\n" + "Maleh: MV 5.74 ± 0.91; FV 5.69 + 1.07\n", + "Bohinen: MV 5.82 ± 0.55; FV 5.77 + 0.56\n", + "Ranocchia F.: MV 5.99 ± 0.67; FV 6.13 + 0.84\n", + "Folorunsho: MV 5.83 ± 0.91; FV 6.06 + 1.31\n", + "Infantino: MV 6.00 ± 0.81; FV 6.03 + 0.89\n", + "Martegani: MV 5.90 ± 0.74; FV 5.94 + 0.97\n", + "Kutlu: MV 6.03 ± 0.80; FV 6.04 + 0.79\n", + "Tchatchoua: MV 5.93 ± 0.87; FV 5.95 + 1.06\n", + "Quina: MV 6.02 ± 0.81; FV 6.15 + 1.14\n", + "Adopo: MV 5.91 ± 1.10; FV 6.04 + 1.39\n", + "Romero L.: MV 6.01 ± 0.82; FV 6.12 + 1.06\n", + "Basic: MV 5.90 ± 0.79; FV 6.02 + 1.01\n", + "Asllani: MV 6.14 ± 0.76; FV 6.28 + 0.88\n", + "Tchaouna: MV 5.70 ± 0.76; FV 5.67 + 0.88\n", + "Sulemana I.: MV 5.58 ± 0.86; FV 5.56 + 0.86\n", + "Barrenechea: MV 5.92 ± 0.91; FV 5.87 + 1.10\n", + "Gelli: MV 5.88 ± 1.19; FV 5.89 + 1.46\n", + "Suslov: MV 5.92 ± 0.65; FV 5.91 + 0.72\n", + "Gaetano: MV 5.95 ± 0.89; FV 6.31 + 1.46\n", + "Jagiello: MV 6.04 ± 0.82; FV 6.08 + 0.86\n", + "Obiang: MV 5.91 ± 0.57; FV 5.88 + 0.53\n", + "Maggiore: MV 5.83 ± 0.55; FV 5.80 + 0.64\n", + "Akpa Akpro: MV 5.91 ± 0.87; FV 5.96 + 1.22\n", + "Urbanski: MV 6.04 ± 0.67; FV 6.11 + 0.86\n", + "Volpato: MV 6.02 ± 0.87; FV 6.16 + 1.23\n", + "Vignato S.: MV 5.77 ± 0.84; FV 5.70 + 1.01\n", + "Hrustic: MV 5.70 ± 0.60; FV 5.64 + 0.57\n", + "Zarraga: MV 5.80 ± 0.83; FV 5.76 + 1.02\n", + "Camara E.: MV 5.90 ± 0.94; FV 6.02 + 1.34\n", + "Amatucci: MV 6.03 ± 0.87; FV 6.10 + 1.04\n", + "Pagano: MV 6.13 ± 0.81; FV 6.31 + 1.13\n", + "Prati: MV 5.71 ± 1.14; FV 5.72 + 1.33\n", + "Viola: MV 5.70 ± 1.01; FV 5.69 + 1.14\n", + "Lulic K.: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Rog: MV 5.67 ± 0.96; FV 5.71 + 1.02\n", + "Nicolussi Caviglia: MV 5.70 ± 1.11; FV 5.73 + 1.27\n", + "Demme: MV 5.96 ± 0.51; FV 5.95 + 0.46\n", + "Pafundi: MV 5.98 ± 0.84; FV 6.02 + 1.01\n", + "Adli: MV 5.91 ± 0.85; FV 5.92 + 0.97\n", + "Bondo: MV 5.94 ± 0.84; FV 6.00 + 1.15\n", + "Zerbin: MV 5.90 ± 0.72; FV 5.88 + 0.86\n", + "Carboni V.: MV 5.81 ± 0.91; FV 5.83 + 1.20\n", + "Faticanti: MV 5.79 ± 1.02; FV 5.88 + 1.31\n", + "Gineitis: MV 5.99 ± 0.74; FV 6.03 + 0.82\n", + "Belardinelli: MV 5.91 ± 0.77; FV 5.89 + 0.85\n", + "El Azzouzi: MV 5.99 ± 0.58; FV 6.00 + 0.58\n", + "Lipani: MV 5.97 ± 0.86; FV 6.01 + 1.02\n", + "Joselito: MV 5.93 ± 0.87; FV 5.95 + 1.06\n", + "Legowski: MV 5.78 ± 0.90; FV 5.84 + 1.18\n", + "Ibrahimovic A.: MV 5.85 ± 1.14; FV 5.85 + 1.41\n", + "Osimhen: MV 6.44 ± 1.56; FV 7.80 + 3.97\n", + "Martinez L.: MV 6.51 ± 1.37; FV 8.00 + 4.04\n", + "Rafael Leao: MV 6.49 ± 1.25; FV 7.59 + 3.28\n", + "Lukaku: MV 6.32 ± 1.49; FV 7.50 + 3.55\n", + "Berardi: MV 6.49 ± 1.33; FV 7.84 + 3.77\n", + "Immobile: MV 5.99 ± 1.26; FV 6.62 + 2.25\n", + "Vlahovic: MV 6.16 ± 1.45; FV 7.09 + 3.05\n", + "Dybala: MV 6.36 ± 1.47; FV 7.58 + 3.67\n", + "Kvaratskhelia: MV 6.35 ± 1.22; FV 7.31 + 3.03\n", + "Giroud: MV 6.42 ± 1.30; FV 7.65 + 3.55\n", + "Scamacca: MV 6.24 ± 1.39; FV 7.22 + 3.16\n", + "Thuram: MV 6.47 ± 1.15; FV 7.46 + 3.04\n", + "Lookman: MV 6.30 ± 1.33; FV 7.32 + 3.20\n", + "Dia: MV 6.00 ± 1.33; FV 6.77 + 2.48\n", + "Arnautovic: MV 6.33 ± 1.03; FV 6.97 + 2.21\n", + "Retegui: MV 6.27 ± 1.30; FV 7.36 + 3.29\n", + "Sanabria: MV 6.13 ± 1.02; FV 6.79 + 2.22\n", + "Nzola: MV 6.01 ± 1.21; FV 6.72 + 2.36\n", + "Lauriente': MV 6.32 ± 1.20; FV 7.21 + 2.87\n", + "Zapata D.: MV 6.09 ± 0.71; FV 6.32 + 1.10\n", + "Chiesa: MV 6.33 ± 1.15; FV 7.13 + 2.66\n", + "Milik: MV 6.11 ± 0.93; FV 6.50 + 1.62\n", + "Gonzalez N.: MV 6.44 ± 1.19; FV 7.48 + 3.14\n", + "Okafor: MV 6.19 ± 0.96; FV 6.67 + 1.89\n", + "Pinamonti: MV 6.02 ± 1.22; FV 6.70 + 2.41\n", + "Beltran L.: MV 6.10 ± 0.84; FV 6.47 + 1.48\n", + "Caprari: MV 6.05 ± 1.02; FV 6.47 + 1.82\n", + "Sanchez: MV 6.21 ± 0.92; FV 6.70 + 1.82\n", + "Caputo: MV 5.74 ± 0.87; FV 6.02 + 1.25\n", + "Toure' E.: MV 5.92 ± 1.01; FV 6.07 + 1.34\n", + "Krstovic: MV 6.21 ± 1.11; FV 6.79 + 2.22\n", + "Belotti: MV 6.10 ± 1.04; FV 6.68 + 2.07\n", + "Muriel: MV 6.15 ± 0.89; FV 6.48 + 1.59\n", + "Lapadula: MV 5.92 ± 1.14; FV 6.44 + 1.87\n", + "Jovic: MV 6.09 ± 1.20; FV 6.76 + 2.37\n", + "Abraham: MV 6.17 ± 1.16; FV 6.98 + 2.61\n", + "Zirkzee: MV 6.37 ± 0.85; FV 6.87 + 1.87\n", + "Ngonge: MV 5.90 ± 1.11; FV 6.36 + 1.76\n", + "Petagna: MV 5.82 ± 1.09; FV 6.18 + 1.51\n", + "Simeone: MV 5.99 ± 1.11; FV 6.50 + 1.90\n", + "Deulofeu: MV 6.34 ± 1.23; FV 7.32 + 3.08\n", + "Pedro: MV 5.96 ± 0.98; FV 6.26 + 1.48\n", + "Shomurodov: MV 5.52 ± 0.78; FV 5.56 + 0.71\n", + "Azmoun: MV 5.97 ± 0.74; FV 6.24 + 1.23\n", + "Castellanos: MV 6.00 ± 0.78; FV 6.06 + 0.96\n", + "Cheddira: MV 6.14 ± 1.38; FV 6.99 + 2.78\n", + "Karlsson: MV 6.19 ± 0.76; FV 6.61 + 1.60\n", + "Brekalo: MV 6.22 ± 1.04; FV 6.83 + 2.14\n", + "Cambiaghi: MV 5.91 ± 0.86; FV 6.10 + 1.18\n", + "Henry: MV 5.84 ± 0.89; FV 6.12 + 1.34\n", + "Mulattieri: MV 6.01 ± 0.72; FV 6.32 + 1.33\n", + "Almqvist: MV 6.11 ± 1.13; FV 6.61 + 2.01\n", + "Isaksen: MV 5.75 ± 1.07; FV 5.79 + 1.28\n", + "Kean: MV 5.84 ± 1.09; FV 6.19 + 1.70\n", + "Karamoh: MV 6.09 ± 0.63; FV 6.26 + 0.87\n", + "Thauvin: MV 5.71 ± 0.70; FV 5.85 + 0.96\n", + "Kouame': MV 6.23 ± 1.19; FV 7.12 + 2.84\n", + "Raspadori: MV 5.94 ± 0.94; FV 6.30 + 1.53\n", + "Colombo: MV 5.88 ± 1.03; FV 6.31 + 1.72\n", + "Luvumbo: MV 5.85 ± 0.80; FV 6.08 + 1.13\n", + "Mota: MV 5.87 ± 0.99; FV 6.23 + 1.59\n", + "Brenner: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Bonazzoli: MV 5.91 ± 0.90; FV 6.24 + 1.40\n", + "Djuric: MV 5.99 ± 0.51; FV 6.06 + 0.59\n", + "Davis K.: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Banda: MV 5.97 ± 0.92; FV 6.25 + 1.39\n", + "Defrel: MV 5.76 ± 0.82; FV 5.94 + 1.11\n", + "Sansone: MV 6.03 ± 0.97; FV 6.41 + 1.61\n", + "Pellegri: MV 5.95 ± 0.61; FV 5.98 + 0.66\n", + "Piccoli: MV 5.84 ± 0.78; FV 5.85 + 0.90\n", + "Success: MV 5.91 ± 0.81; FV 6.16 + 1.28\n", + "Botheim: MV 5.57 ± 0.65; FV 5.57 + 0.64\n", + "Lucca: MV 5.76 ± 0.88; FV 6.01 + 1.34\n", + "Caso: MV 6.13 ± 1.03; FV 6.64 + 1.94\n", + "Jovane: MV 5.76 ± 0.91; FV 5.84 + 1.16\n", + "Soule': MV 6.27 ± 0.98; FV 6.72 + 1.76\n", + "Pavoletti: MV 5.70 ± 0.85; FV 5.93 + 1.10\n", + "Cancellieri: MV 5.77 ± 0.88; FV 5.86 + 1.11\n", + "Seck: MV 6.10 ± 0.60; FV 6.21 + 0.66\n", + "Alvarez A.: MV 5.95 ± 0.78; FV 6.16 + 1.10\n", + "Cuni: MV 5.73 ± 1.02; FV 5.67 + 1.17\n", + "Ekuban: MV 6.02 ± 0.54; FV 6.10 + 0.58\n", + "Maric: MV 5.96 ± 0.51; FV 5.97 + 0.58\n", + "Cruz: MV 5.93 ± 0.87; FV 5.99 + 1.08\n", + "Destro: MV 5.66 ± 0.79; FV 5.68 + 0.88\n", + "Van Hooijdonk: MV 6.13 ± 0.64; FV 6.25 + 0.84\n", + "Ceide: MV 5.86 ± 0.72; FV 5.86 + 0.68\n", + "Kvernadze: MV 5.74 ± 1.15; FV 5.69 + 1.39\n", + "Ikwuemesi: MV 5.65 ± 0.72; FV 5.60 + 0.74\n", + "Puscas: MV 6.04 ± 0.77; FV 6.11 + 0.86\n", + "Ake' M.: MV 5.94 ± 0.75; FV 5.96 + 0.95\n", + "Braaf: MV 5.67 ± 0.68; FV 5.73 + 0.74\n", + "Kallon: MV 5.86 ± 0.78; FV 6.04 + 1.05\n", + "Kaio Jorge: MV 5.92 ± 0.64; FV 5.99 + 0.74\n", + "Vivaldo: MV 5.90 ± 0.95; FV 6.08 + 1.41\n", + "Bidaoui: MV 5.84 ± 1.17; FV 5.86 + 1.45\n", + "Shpendi S.: MV 5.91 ± 0.53; FV 5.90 + 0.53\n", + "Burnete: MV 5.81 ± 1.00; FV 5.93 + 1.35\n", + "Corfitzen: MV 5.79 ± 1.02; FV 5.90 + 1.33\n", + "Stewart: MV 5.76 ± 0.91; FV 5.84 + 1.16\n", + "Yildiz: MV 5.78 ± 1.06; FV 5.88 + 1.32\n" ] }, { @@ -6737,113 +6739,113 @@ " \n", " \n", " \n", - " Musso\n", - " P\n", - " Atalanta\n", - " Cagliari\n", - " 1\n", - " 1.0\n", - " 70\n", - " 6.187904\n", - " 0.409565\n", - " 5.778299\n", - " 0.631974\n", - " 6.172151\n", - " 0.484012\n", - " 0.024084\n", - " 1.080489\n", - " 6.551383\n", - " 0.575009\n", - " -0.854511\n", - " 1.143475\n", - " 76.430595\n", - " \n", - " \n", " Carnesecchi\n", " P\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", " 0.0\n", " 5\n", - " 6.153384\n", - " 0.442585\n", - " 5.099182\n", - " 0.736154\n", - " 6.095662\n", - " 0.508426\n", - " 0.083887\n", - " 1.071720\n", - " 5.316064\n", - " 1.103085\n", - " -0.144701\n", - " 0.998809\n", - " 24.471429\n", + " 6.140590\n", + " 0.481707\n", + " 5.070139\n", + " 0.715923\n", + " 5.980216\n", + " 0.509892\n", + " 0.230396\n", + " 1.086084\n", + " 5.321455\n", + " 1.055452\n", + " -0.174796\n", + " 0.965320\n", + " 20.727640\n", + " \n", + " \n", + " Musso\n", + " P\n", + " Atalanta\n", + " Juventus\n", + " 1\n", + " 1.0\n", + " 70\n", + " 6.171150\n", + " 0.480294\n", + " 5.038867\n", + " 0.684976\n", + " 5.986030\n", + " 0.494852\n", + " 0.272883\n", + " 1.084060\n", + " 5.255883\n", + " 1.019420\n", + " -0.156479\n", + " 0.983446\n", + " 28.833491\n", " \n", " \n", " Rossi F.\n", " P\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", " 0.0\n", " 1\n", - " 6.202195\n", - " 0.436560\n", - " 5.098540\n", - " 0.738788\n", - " 6.170873\n", - " 0.510068\n", - " 0.045397\n", - " 1.057536\n", - " 5.311903\n", - " 1.107865\n", - " -0.141756\n", - " 0.997465\n", - " 19.948235\n", + " 6.170296\n", + " 0.480470\n", + " 5.037872\n", + " 0.684438\n", + " 5.984473\n", + " 0.494652\n", + " 0.273999\n", + " 1.084374\n", + " 5.254371\n", + " 1.018776\n", + " -0.156209\n", + " 0.983780\n", + " 28.943959\n", " \n", " \n", " Zappacosta\n", " D\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", - " 0.6\n", - " 60\n", - " 6.174058\n", - " 0.452587\n", - " 6.519552\n", - " 0.775398\n", - " 6.110474\n", - " 0.514245\n", - " 0.090884\n", - " 0.896925\n", - " 5.874933\n", - " 0.976198\n", - " 0.463032\n", - " 1.299677\n", + " 1.0\n", + " 90\n", + " 5.985259\n", + " 0.522062\n", + " 6.206951\n", + " 0.733274\n", + " 6.001576\n", + " 0.613546\n", + " -0.019559\n", + " 0.881605\n", + " 5.760596\n", + " 1.050439\n", + " 0.307981\n", + " 1.299815\n", " 0.000000\n", " \n", " \n", - " Zortea\n", + " Toloi\n", " D\n", " Atalanta\n", - " Cagliari\n", + " Juventus\n", " 1\n", - " 0.4\n", - " 40\n", - " 6.106819\n", - " 0.397738\n", - " 6.403875\n", - " 0.627450\n", - " 6.025298\n", - " 0.444725\n", - " 0.134716\n", - " 0.941082\n", - " 5.877332\n", - " 0.785433\n", - " 0.469323\n", - " 1.299658\n", + " 1.0\n", + " 90\n", + " 6.002894\n", + " 0.499877\n", + " 6.196084\n", + " 0.699952\n", + " 6.035264\n", + " 0.591494\n", + " -0.040256\n", + " 0.892304\n", + " 5.804792\n", + " 1.025037\n", + " 0.278035\n", + " 1.299814\n", " 0.000000\n", " \n", " \n", @@ -6872,110 +6874,110 @@ " Henry\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", - " 0.0\n", - " 0\n", - " 5.806732\n", - " 0.484893\n", - " 6.124626\n", - " 0.710677\n", - " 5.555864\n", - " 0.490855\n", - " 0.369405\n", - " 0.852631\n", - " 5.422048\n", - " 0.779401\n", - " 0.606238\n", - " 1.299682\n", - " 0.000000\n", - " \n", - " \n", - " Kallon\n", - " A\n", - " Verona\n", - " Milan\n", - " 0\n", - " 0.0\n", - " 0\n", - " 5.847151\n", - " 0.430028\n", - " 6.110572\n", - " 0.658053\n", - " 5.650604\n", - " 0.441275\n", - " 0.323210\n", - " 0.904855\n", - " 5.475328\n", - " 0.739265\n", - " 0.582358\n", - " 1.299658\n", + " 0.4\n", + " 60\n", + " 5.839920\n", + " 0.444240\n", + " 6.116677\n", + " 0.669289\n", + " 5.631952\n", + " 0.453545\n", + " 0.332464\n", + " 0.906913\n", + " 5.474079\n", + " 0.755754\n", + " 0.577176\n", + " 1.299852\n", " 0.000000\n", " \n", " \n", " Djuric\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", - " 0.4\n", - " 60\n", - " 5.847715\n", - " 0.371962\n", - " 6.031966\n", - " 0.518109\n", - " 5.712709\n", - " 0.393430\n", - " 0.250597\n", - " 0.961439\n", - " 5.599852\n", - " 0.651016\n", - " 0.465176\n", - " 1.299629\n", + " 0.0\n", + " 0\n", + " 5.988754\n", + " 0.256611\n", + " 6.065000\n", + " 0.293257\n", + " 6.035156\n", + " 0.320372\n", + " -0.107045\n", + " 1.115607\n", + " 5.977599\n", + " 0.469125\n", + " 0.137929\n", + " 1.299758\n", + " 0.000000\n", + " \n", + " \n", + " Kallon\n", + " A\n", + " Verona\n", + " Torino\n", + " 0\n", + " 0.0\n", + " 0\n", + " 5.863674\n", + " 0.392202\n", + " 6.044829\n", + " 0.522801\n", + " 5.719528\n", + " 0.414042\n", + " 0.254175\n", + " 0.962003\n", + " 5.592772\n", + " 0.641898\n", + " 0.490306\n", + " 1.299833\n", " 0.000000\n", " \n", " \n", " Cruz\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", " 0.0\n", " 15\n", - " 5.751310\n", - " 0.481451\n", - " 5.863318\n", - " 0.627091\n", - " 5.655169\n", - " 0.538907\n", - " 0.130959\n", - " 0.892866\n", - " 5.455123\n", - " 0.880195\n", - " 0.334536\n", - " 1.299594\n", + " 5.932667\n", + " 0.434699\n", + " 5.990185\n", + " 0.538253\n", + " 6.015219\n", + " 0.528602\n", + " -0.114888\n", + " 0.951150\n", + " 5.878494\n", + " 0.880338\n", + " 0.094197\n", + " 1.299773\n", " 0.000000\n", " \n", " \n", " Braaf\n", " A\n", " Verona\n", - " Milan\n", + " Torino\n", " 0\n", " 0.0\n", " 0\n", - " 5.613092\n", - " 0.346900\n", - " 5.750920\n", - " 0.428900\n", - " 5.477731\n", - " 0.361478\n", - " 0.273028\n", - " 0.988318\n", - " 5.428794\n", - " 0.569555\n", - " 0.402369\n", - " 1.299586\n", + " 5.665697\n", + " 0.341006\n", + " 5.725323\n", + " 0.370040\n", + " 5.561785\n", + " 0.367506\n", + " 0.207320\n", + " 1.019125\n", + " 5.506973\n", + " 0.534618\n", + " 0.296589\n", + " 1.299793\n", " 0.000000\n", " \n", " \n", @@ -6986,70 +6988,70 @@ "text/plain": [ " role team oppteam home starter vote% MV MV std \\\n", "player \n", - "Musso P Atalanta Cagliari 1 1.0 70 6.187904 0.409565 \n", - "Carnesecchi P Atalanta Cagliari 1 0.0 5 6.153384 0.442585 \n", - "Rossi F. P Atalanta Cagliari 1 0.0 1 6.202195 0.436560 \n", - "Zappacosta D Atalanta Cagliari 1 0.6 60 6.174058 0.452587 \n", - "Zortea D Atalanta Cagliari 1 0.4 40 6.106819 0.397738 \n", + "Carnesecchi P Atalanta Juventus 1 0.0 5 6.140590 0.481707 \n", + "Musso P Atalanta Juventus 1 1.0 70 6.171150 0.480294 \n", + "Rossi F. P Atalanta Juventus 1 0.0 1 6.170296 0.480470 \n", + "Zappacosta D Atalanta Juventus 1 1.0 90 5.985259 0.522062 \n", + "Toloi D Atalanta Juventus 1 1.0 90 6.002894 0.499877 \n", "... ... ... ... ... ... ... ... ... \n", - "Henry A Verona Milan 0 0.0 0 5.806732 0.484893 \n", - "Kallon A Verona Milan 0 0.0 0 5.847151 0.430028 \n", - "Djuric A Verona Milan 0 0.4 60 5.847715 0.371962 \n", - "Cruz A Verona Milan 0 0.0 15 5.751310 0.481451 \n", - "Braaf A Verona Milan 0 0.0 0 5.613092 0.346900 \n", + "Henry A Verona Torino 0 0.4 60 5.839920 0.444240 \n", + "Djuric A Verona Torino 0 0.0 0 5.988754 0.256611 \n", + "Kallon A Verona Torino 0 0.0 0 5.863674 0.392202 \n", + "Cruz A Verona Torino 0 0.0 15 5.932667 0.434699 \n", + "Braaf A Verona Torino 0 0.0 0 5.665697 0.341006 \n", "\n", " FV FV std MV loc MV scale MV skewness \\\n", "player \n", - "Musso 5.778299 0.631974 6.172151 0.484012 0.024084 \n", - "Carnesecchi 5.099182 0.736154 6.095662 0.508426 0.083887 \n", - "Rossi F. 5.098540 0.738788 6.170873 0.510068 0.045397 \n", - "Zappacosta 6.519552 0.775398 6.110474 0.514245 0.090884 \n", - "Zortea 6.403875 0.627450 6.025298 0.444725 0.134716 \n", + "Carnesecchi 5.070139 0.715923 5.980216 0.509892 0.230396 \n", + "Musso 5.038867 0.684976 5.986030 0.494852 0.272883 \n", + "Rossi F. 5.037872 0.684438 5.984473 0.494652 0.273999 \n", + "Zappacosta 6.206951 0.733274 6.001576 0.613546 -0.019559 \n", + "Toloi 6.196084 0.699952 6.035264 0.591494 -0.040256 \n", "... ... ... ... ... ... \n", - "Henry 6.124626 0.710677 5.555864 0.490855 0.369405 \n", - "Kallon 6.110572 0.658053 5.650604 0.441275 0.323210 \n", - "Djuric 6.031966 0.518109 5.712709 0.393430 0.250597 \n", - "Cruz 5.863318 0.627091 5.655169 0.538907 0.130959 \n", - "Braaf 5.750920 0.428900 5.477731 0.361478 0.273028 \n", + "Henry 6.116677 0.669289 5.631952 0.453545 0.332464 \n", + "Djuric 6.065000 0.293257 6.035156 0.320372 -0.107045 \n", + "Kallon 6.044829 0.522801 5.719528 0.414042 0.254175 \n", + "Cruz 5.990185 0.538253 6.015219 0.528602 -0.114888 \n", + "Braaf 5.725323 0.370040 5.561785 0.367506 0.207320 \n", "\n", " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", "player \n", - "Musso 1.080489 6.551383 0.575009 -0.854511 1.143475 \n", - "Carnesecchi 1.071720 5.316064 1.103085 -0.144701 0.998809 \n", - "Rossi F. 1.057536 5.311903 1.107865 -0.141756 0.997465 \n", - "Zappacosta 0.896925 5.874933 0.976198 0.463032 1.299677 \n", - "Zortea 0.941082 5.877332 0.785433 0.469323 1.299658 \n", + "Carnesecchi 1.086084 5.321455 1.055452 -0.174796 0.965320 \n", + "Musso 1.084060 5.255883 1.019420 -0.156479 0.983446 \n", + "Rossi F. 1.084374 5.254371 1.018776 -0.156209 0.983780 \n", + "Zappacosta 0.881605 5.760596 1.050439 0.307981 1.299815 \n", + "Toloi 0.892304 5.804792 1.025037 0.278035 1.299814 \n", "... ... ... ... ... ... \n", - "Henry 0.852631 5.422048 0.779401 0.606238 1.299682 \n", - "Kallon 0.904855 5.475328 0.739265 0.582358 1.299658 \n", - "Djuric 0.961439 5.599852 0.651016 0.465176 1.299629 \n", - "Cruz 0.892866 5.455123 0.880195 0.334536 1.299594 \n", - "Braaf 0.988318 5.428794 0.569555 0.402369 1.299586 \n", + "Henry 0.906913 5.474079 0.755754 0.577176 1.299852 \n", + "Djuric 1.115607 5.977599 0.469125 0.137929 1.299758 \n", + "Kallon 0.962003 5.592772 0.641898 0.490306 1.299833 \n", + "Cruz 0.951150 5.878494 0.880338 0.094197 1.299773 \n", + "Braaf 1.019125 5.506973 0.534618 0.296589 1.299793 \n", "\n", " Clean Sheet % \n", "player \n", - "Musso 76.430595 \n", - "Carnesecchi 24.471429 \n", - "Rossi F. 19.948235 \n", + "Carnesecchi 20.727640 \n", + "Musso 28.833491 \n", + "Rossi F. 28.943959 \n", "Zappacosta 0.000000 \n", - "Zortea 0.000000 \n", + "Toloi 0.000000 \n", "... ... \n", "Henry 0.000000 \n", - "Kallon 0.000000 \n", "Djuric 0.000000 \n", + "Kallon 0.000000 \n", "Cruz 0.000000 \n", "Braaf 0.000000 \n", "\n", "[539 rows x 19 columns]" ] }, - "execution_count": 42, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "matchday_out = 5\n", + "matchday_out = 7\n", "\n", "output = pd.DataFrame(columns = ['player', 'role', 'team', 'oppteam', 'home', 'starter', 'vote%', 'MV', 'MV std', 'FV', 'FV std', 'MV loc', 'MV scale', 'MV skewness', 'MV tailweight', 'FV loc', 'FV scale', 'FV skewness', 'FV tailweight', 'Clean Sheet %'])\n", "\n", @@ -7099,7 +7101,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 33, "id": "6befd611", "metadata": {}, "outputs": [], @@ -7125,7 +7127,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 34, "id": "2b637a15", "metadata": {}, "outputs": [], @@ -7137,7 +7139,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 35, "id": "60d73507", "metadata": {}, "outputs": [ @@ -7145,557 +7147,557 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sommer (6.16, 0.43); (5.75, 0.63)\n", - "Szczesny (6.16, 0.45); (5.10, 0.74)\n", - "Meret (6.06, 0.45); (5.09, 0.74)\n", - "Provedel (6.16, 0.45); (4.50, 0.98)\n", - "Maignan (6.16, 0.44); (4.61, 0.91)\n", - "Rui Patricio (5.81, 0.51); (3.74, 1.19)\n", - "Skorupski (5.90, 0.50); (3.96, 1.15)\n", - "Milinkovic-Savic V. (6.15, 0.44); (5.41, 0.66)\n", - "Di Gregorio (6.23, 0.43); (5.10, 0.78)\n", - "Falcone (6.21, 0.45); (5.11, 0.76)\n", - "Silvestri (5.99, 0.46); (4.59, 0.91)\n", - "Terracciano (6.14, 0.45); (4.81, 0.86)\n", - "Carnesecchi (5.87, 0.50); (3.43, 1.37)\n", - "Radunovic (6.21, 0.42); (5.13, 0.73)\n", - "Montipo' (6.19, 0.44); (5.13, 0.73)\n", - "Martinez Jo. (6.08, 0.46); (4.86, 0.86)\n", - "Ochoa (6.05, 0.47); (3.48, 1.32)\n", - "Caprile (5.81, 0.48); (3.58, 1.25)\n", - "Turati (6.10, 0.48); (5.07, 0.75)\n", - "Consigli (5.99, 0.48); (3.88, 1.20)\n", - "Musso (6.17, 0.43); (5.72, 0.63)\n", - "Cragno (6.00, 0.49); (3.42, 1.40)\n", - "Perin (6.16, 0.44); (5.19, 0.69)\n", - "Berisha (5.83, 0.52); (3.40, 1.36)\n", - "Christensen O. (6.05, 0.47); (3.70, 1.22)\n", - "Sportiello (6.16, 0.44); (4.61, 0.91)\n", - "Mirante (6.16, 0.44); (4.61, 0.91)\n", - "Sepe (6.14, 0.45); (4.03, 1.09)\n", - "Leali (6.08, 0.46); (4.86, 0.86)\n", - "Lamanna (6.16, 0.45); (4.95, 0.79)\n", - "Sommariva (6.08, 0.46); (4.86, 0.86)\n", - "Pegolo (5.94, 0.49); (3.70, 1.28)\n", - "Perilli (6.17, 0.43); (5.19, 0.69)\n", - "Padelli (5.96, 0.46); (4.71, 0.90)\n", - "Scuffet (6.21, 0.42); (5.13, 0.73)\n", - "Gollini (5.83, 0.51); (3.91, 1.18)\n", - "Perisan (5.61, 0.50); (3.25, 1.32)\n", - "Audero (6.16, 0.43); (5.74, 0.63)\n", - "Di Gennaro (6.16, 0.43); (5.75, 0.63)\n", - "Pinsoglio (6.12, 0.48); (5.10, 0.74)\n", - "Aresti (6.21, 0.42); (5.13, 0.73)\n", - "Fiorillo (6.05, 0.47); (3.48, 1.32)\n", - "Cerofolini (6.21, 0.46); (5.10, 0.75)\n", - "Rossi F. (5.96, 0.50); (3.41, 1.37)\n", - "Costil (6.05, 0.47); (3.48, 1.32)\n", - "Ravaglia F. (5.90, 0.49); (3.86, 1.18)\n", - "Frattali (6.10, 0.48); (5.07, 0.75)\n", - "Contini (5.83, 0.51); (3.91, 1.18)\n", - "Brancolini (6.17, 0.46); (5.10, 0.74)\n", - "Berardi A. (6.17, 0.43); (5.19, 0.69)\n", - "Gemello (6.16, 0.43); (5.64, 0.63)\n", - "Boer (5.74, 0.53); (3.41, 1.35)\n", - "Bagnolini (5.90, 0.49); (3.86, 1.18)\n", - "Svilar (5.74, 0.53); (3.41, 1.35)\n", - "Sorrentino A. (5.97, 0.47); (3.98, 1.09)\n", - "Martinelli T. (6.04, 0.47); (4.11, 1.09)\n", - "Popa (6.16, 0.43); (5.64, 0.63)\n", - "Stubljar (5.81, 0.48); (3.58, 1.25)\n", - "Gori (6.16, 0.45); (4.95, 0.79)\n", - "Borbei (6.17, 0.46); (5.10, 0.74)\n", - "Okoye (5.96, 0.46); (4.71, 0.90)\n", - "Mandas (6.14, 0.45); (4.03, 1.09)\n", - "Dimarco (6.34, 0.39); (6.61, 0.67)\n", - "Di Lorenzo (6.31, 0.57); (6.97, 1.14)\n", - "Hernandez T. (6.13, 0.62); (6.74, 1.18)\n", - "Carlos Augusto (6.28, 0.48); (6.76, 0.92)\n", - "Danilo (6.32, 0.43); (6.65, 0.77)\n", - "Zappacosta (6.10, 0.56); (6.57, 0.98)\n", - "Schuurs (6.09, 0.46); (6.24, 0.63)\n", - "Posch (5.97, 0.48); (6.21, 0.75)\n", - "Bastoni (6.29, 0.38); (6.42, 0.50)\n", - "Smalling (6.12, 0.45); (6.40, 0.71)\n", - "Dumfries (6.26, 0.47); (6.73, 0.90)\n", - "Romagnoli (6.02, 0.50); (6.09, 0.64)\n", - "Pavard (6.12, 0.33); (6.23, 0.43)\n", - "Rrahmani (6.07, 0.54); (6.27, 0.72)\n", - "Spinazzola (6.20, 0.42); (6.50, 0.73)\n", - "Buongiorno (6.07, 0.48); (6.34, 0.78)\n", - "Bremer (6.08, 0.51); (6.29, 0.73)\n", - "Tomori (6.04, 0.46); (6.12, 0.58)\n", - "Biraghi (6.08, 0.56); (6.61, 1.03)\n", - "Mancini (6.01, 0.50); (6.27, 0.73)\n", - "Darmian (6.16, 0.36); (6.34, 0.51)\n", - "Bakker (5.99, 0.32); (6.07, 0.42)\n", - "Mazzocchi (5.79, 0.39); (5.92, 0.52)\n", - "Doig (6.00, 0.52); (6.31, 0.80)\n", - "Calabria (6.01, 0.45); (6.21, 0.66)\n", - "Acerbi (6.08, 0.35); (6.12, 0.37)\n", - "Cuadrado (6.05, 0.40); (6.15, 0.50)\n", - "Ebuehi (5.67, 0.43); (5.72, 0.52)\n", - "Casale (5.87, 0.47); (5.89, 0.58)\n", - "Holm (6.05, 0.41); (6.28, 0.60)\n", - "Baschirotto (5.93, 0.54); (6.10, 0.72)\n", - "Bijol (5.81, 0.53); (5.91, 0.70)\n", - "Thiaw (5.66, 0.68); (5.55, 0.67)\n", - "Mario Rui (6.00, 0.45); (6.10, 0.56)\n", - "Milenkovic (5.78, 0.59); (5.86, 0.76)\n", - "Rodriguez R. (5.98, 0.38); (5.98, 0.41)\n", - "Kolasinac (5.98, 0.38); (6.13, 0.51)\n", - "N'dicka (6.01, 0.28); (6.01, 0.29)\n", - "Scalvini (5.95, 0.56); (6.13, 0.74)\n", - "Perez N. (5.82, 0.45); (5.82, 0.55)\n", - "Kristensen (6.01, 0.36); (6.19, 0.54)\n", - "Izzo (5.93, 0.46); (5.98, 0.58)\n", - "De Vrij (6.24, 0.37); (6.35, 0.47)\n", - "Faraoni (5.85, 0.38); (5.96, 0.52)\n", - "Toloi (6.01, 0.46); (6.14, 0.61)\n", - "Kyriakopoulos (5.86, 0.31); (5.84, 0.35)\n", - "Bellanova (5.97, 0.41); (6.06, 0.51)\n", - "Mari' (5.77, 0.45); (5.74, 0.53)\n", - "Dodo' (5.80, 0.56); (5.91, 0.73)\n", - "Lucumi' (5.83, 0.42); (5.76, 0.47)\n", - "Hien (5.85, 0.48); (5.81, 0.54)\n", - "Natan (5.92, 0.49); (5.97, 0.57)\n", - "Hysaj (5.93, 0.39); (6.00, 0.51)\n", - "D'ambrosio (5.99, 0.32); (5.95, 0.35)\n", - "Luperto (5.54, 0.58); (5.47, 0.67)\n", - "Djimsiti (5.99, 0.40); (6.01, 0.43)\n", - "Marusic (5.84, 0.47); (5.79, 0.53)\n", - "Martin (5.91, 0.35); (6.02, 0.45)\n", - "Mina (5.97, 0.42); (6.24, 0.66)\n", - "Toljan (5.69, 0.45); (5.62, 0.49)\n", - "Llorente D. (5.81, 0.48); (5.83, 0.55)\n", - "Martinez Quarta (5.94, 0.58); (6.07, 0.75)\n", - "Bastoni S. (5.69, 0.43); (5.75, 0.56)\n", - "Dragusin (5.92, 0.45); (6.10, 0.62)\n", - "Parisi (6.04, 0.49); (6.24, 0.73)\n", - "Bradaric (5.76, 0.47); (5.81, 0.59)\n", - "Kamara H. (5.97, 0.33); (5.98, 0.39)\n", - "Olivera (5.98, 0.37); (6.11, 0.46)\n", - "Gendrey (5.92, 0.36); (5.92, 0.40)\n", - "Kristiansen (6.03, 0.37); (6.11, 0.52)\n", - "Beukema (5.94, 0.43); (5.94, 0.50)\n", - "Dossena (5.88, 0.38); (5.89, 0.45)\n", - "Pedersen (5.84, 0.33); (5.83, 0.35)\n", - "Juan Jesus (6.01, 0.34); (6.02, 0.34)\n", - "Gyomber (5.79, 0.49); (5.73, 0.54)\n", - "Alex Sandro (5.79, 0.51); (5.66, 0.52)\n", - "Hateboer (5.85, 0.50); (6.08, 0.74)\n", - "Palomino (5.92, 0.35); (5.94, 0.40)\n", - "Marchizza (5.95, 0.41); (5.98, 0.49)\n", - "Zappa (5.79, 0.38); (5.73, 0.37)\n", - "Gallo (5.90, 0.43); (5.90, 0.49)\n", - "Caldirola (5.69, 0.55); (5.74, 0.69)\n", - "Kalulu (5.82, 0.52); (5.80, 0.58)\n", - "Erlic (5.72, 0.52); (5.60, 0.54)\n", - "Vojvoda (5.91, 0.34); (5.96, 0.42)\n", - "Vasquez (5.96, 0.40); (5.97, 0.44)\n", - "Cambiaso (6.07, 0.40); (6.16, 0.48)\n", - "Pongracic (5.94, 0.43); (5.96, 0.50)\n", - "Viti (6.06, 0.31); (6.22, 0.44)\n", - "Gatti (6.13, 0.39); (6.19, 0.45)\n", - "Birindelli (5.88, 0.38); (5.86, 0.42)\n", - "Azzi (5.90, 0.33); (5.94, 0.40)\n", - "Wieteska (5.96, 0.42); (5.97, 0.51)\n", - "Masina (5.76, 0.49); (6.03, 0.71)\n", - "Romagnoli S. (5.88, 0.47); (5.94, 0.61)\n", - "Pezzella Giu. (5.53, 0.45); (5.43, 0.47)\n", - "Sabelli (5.96, 0.32); (6.03, 0.42)\n", - "Lirola (6.07, 0.46); (6.28, 0.68)\n", - "Lazzari (5.98, 0.39); (5.99, 0.43)\n", - "Bani (5.90, 0.54); (6.09, 0.76)\n", - "Djidji (5.84, 0.39); (5.86, 0.46)\n", - "Kabasele (5.79, 0.37); (5.74, 0.43)\n", - "Lazaro (6.02, 0.35); (6.07, 0.44)\n", - "Augello (5.85, 0.40); (5.92, 0.51)\n", - "Zortea (6.05, 0.46); (6.35, 0.70)\n", - "Dawidowicz (5.83, 0.47); (5.81, 0.55)\n", - "Pirola (5.72, 0.51); (5.78, 0.64)\n", - "Lovato (5.65, 0.44); (5.55, 0.46)\n", - "Ruggeri (6.09, 0.55); (6.46, 0.88)\n", - "Vina (5.78, 0.50); (5.75, 0.55)\n", - "Obert (5.76, 0.43); (5.71, 0.46)\n", - "Terracciano F. (6.08, 0.36); (6.17, 0.46)\n", - "Ebosele (5.77, 0.37); (5.74, 0.42)\n", - "Zemura (5.93, 0.31); (5.92, 0.36)\n", - "Hatzidiakos (5.95, 0.41); (5.97, 0.48)\n", - "Patric (5.97, 0.39); (5.93, 0.40)\n", - "Lykogiannis (5.84, 0.32); (5.88, 0.38)\n", - "Pellegrini Lu. (5.72, 0.37); (5.64, 0.39)\n", - "Magnani (5.78, 0.52); (5.75, 0.60)\n", - "Ranieri L. (5.67, 0.46); (5.64, 0.53)\n", - "Carboni A. (5.94, 0.37); (5.96, 0.45)\n", - "Calafiori (5.95, 0.40); (6.01, 0.53)\n", - "Monterisi (5.99, 0.62); (6.38, 1.03)\n", - "Ismajli (5.63, 0.46); (5.52, 0.48)\n", - "De Winter (5.83, 0.44); (5.74, 0.43)\n", - "Tressoldi (5.80, 0.47); (5.81, 0.56)\n", - "Ehizibue (5.74, 0.43); (5.76, 0.56)\n", - "Vogliacco (5.89, 0.45); (5.87, 0.50)\n", - "Ferrari G. (5.69, 0.52); (5.73, 0.63)\n", - "Venuti (5.79, 0.40); (5.75, 0.43)\n", - "Karsdorp (5.89, 0.25); (5.87, 0.24)\n", - "Kjaer (5.52, 0.38); (5.49, 0.35)\n", - "Gunter (5.67, 0.53); (5.59, 0.59)\n", - "Soumaoro (5.82, 0.54); (5.77, 0.61)\n", - "Di Pardo (5.81, 0.41); (5.76, 0.43)\n", - "Zanoli (6.10, 0.50); (6.48, 0.83)\n", - "Zima (5.92, 0.30); (5.89, 0.30)\n", - "Hefti (5.75, 0.42); (5.68, 0.42)\n", - "Ostigard (5.64, 0.38); (5.60, 0.36)\n", - "Sambia (5.92, 0.36); (5.95, 0.40)\n", - "Bisseck (5.97, 0.38); (6.01, 0.43)\n", - "Oyono (5.96, 0.39); (5.96, 0.43)\n", - "Ferreira J. (5.77, 0.37); (5.72, 0.41)\n", - "Dorgu (6.02, 0.33); (6.05, 0.37)\n", - "Touba (5.96, 0.40); (6.01, 0.49)\n", - "Sazonov (5.94, 0.43); (5.99, 0.54)\n", - "Rugani (6.07, 0.29); (6.08, 0.30)\n", - "De Sciglio (5.91, 0.33); (5.89, 0.32)\n", - "Goldaniga (5.66, 0.44); (5.57, 0.45)\n", - "Florenzi (5.97, 0.33); (6.04, 0.38)\n", - "De Silvestri (5.92, 0.32); (5.95, 0.40)\n", - "Pereira P. (5.85, 0.40); (5.83, 0.45)\n", - "Fazio (5.74, 0.62); (5.84, 0.79)\n", - "Bereszynski (5.54, 0.47); (5.46, 0.51)\n", - "Bonifazi (5.71, 0.44); (5.61, 0.45)\n", - "Walukiewicz (5.46, 0.41); (5.36, 0.37)\n", - "Okoli (5.88, 0.40); (5.84, 0.41)\n", - "Kumbulla (5.49, 0.75); (5.25, 0.70)\n", - "Celik (5.66, 0.38); (5.57, 0.37)\n", - "Amione (5.70, 0.45); (5.68, 0.55)\n", - "Daniliuc (5.68, 0.52); (5.68, 0.63)\n", - "Soppy (5.87, 0.36); (5.92, 0.45)\n", - "Haps (5.86, 0.45); (5.93, 0.57)\n", - "Cittadini (5.87, 0.45); (5.93, 0.59)\n", - "Coppola D. (5.75, 0.39); (5.67, 0.42)\n", - "Cacace (5.54, 0.40); (5.43, 0.39)\n", - "Ebosse (5.74, 0.34); (5.65, 0.34)\n", - "Guessand A. (5.77, 0.41); (5.77, 0.50)\n" + "Sommer (6.16, 0.44); (5.74, 0.61)\n", + "Szczesny (6.18, 0.43); (5.77, 0.63)\n", + "Meret (5.86, 0.50); (4.14, 1.03)\n", + "Provedel (6.18, 0.46); (4.76, 0.82)\n", + "Maignan (6.14, 0.47); (4.99, 0.69)\n", + "Rui Patricio (5.82, 0.52); (3.28, 1.26)\n", + "Skorupski (6.12, 0.43); (5.58, 0.61)\n", + "Milinkovic-Savic V. (6.20, 0.44); (5.13, 0.68)\n", + "Di Gregorio (6.21, 0.46); (5.06, 0.69)\n", + "Falcone (6.18, 0.44); (5.10, 0.67)\n", + "Silvestri (5.93, 0.48); (4.16, 1.05)\n", + "Terracciano (6.20, 0.45); (5.08, 0.71)\n", + "Carnesecchi (6.12, 0.45); (5.20, 0.66)\n", + "Radunovic (6.17, 0.44); (5.04, 0.74)\n", + "Montipo' (6.19, 0.43); (5.25, 0.62)\n", + "Martinez Jo. (6.15, 0.47); (4.63, 0.86)\n", + "Ochoa (6.14, 0.47); (3.71, 1.14)\n", + "Caprile (6.06, 0.47); (4.00, 1.05)\n", + "Turati (6.22, 0.47); (5.05, 0.70)\n", + "Consigli (6.04, 0.49); (4.11, 1.00)\n", + "Musso (6.15, 0.43); (5.71, 0.61)\n", + "Cragno (6.04, 0.49); (3.72, 1.10)\n", + "Perin (6.17, 0.44); (5.57, 0.61)\n", + "Berisha (6.05, 0.49); (3.77, 1.13)\n", + "Christensen O. (6.12, 0.47); (4.45, 0.85)\n", + "Sportiello (6.16, 0.45); (5.28, 0.63)\n", + "Mirante (6.14, 0.47); (4.99, 0.69)\n", + "Sepe (6.16, 0.46); (4.55, 0.87)\n", + "Leali (6.15, 0.47); (4.63, 0.86)\n", + "Lamanna (6.19, 0.46); (5.04, 0.69)\n", + "Sommariva (6.15, 0.47); (4.63, 0.86)\n", + "Pegolo (6.06, 0.49); (3.98, 1.04)\n", + "Perilli (6.19, 0.42); (5.28, 0.62)\n", + "Padelli (5.92, 0.48); (3.93, 1.11)\n", + "Scuffet (6.17, 0.44); (5.04, 0.74)\n", + "Gollini (5.86, 0.50); (4.14, 1.03)\n", + "Perisan (5.90, 0.49); (3.73, 1.17)\n", + "Audero (6.16, 0.44); (5.74, 0.61)\n", + "Di Gennaro (6.16, 0.44); (5.74, 0.61)\n", + "Pinsoglio (6.18, 0.43); (5.78, 0.63)\n", + "Aresti (6.17, 0.44); (5.04, 0.74)\n", + "Fiorillo (6.14, 0.47); (3.71, 1.14)\n", + "Cerofolini (6.23, 0.47); (5.05, 0.70)\n", + "Rossi F. (6.15, 0.43); (5.71, 0.61)\n", + "Costil (6.14, 0.47); (3.71, 1.14)\n", + "Ravaglia F. (6.12, 0.43); (5.58, 0.61)\n", + "Frattali (6.22, 0.47); (5.05, 0.70)\n", + "Contini (5.86, 0.50); (4.14, 1.03)\n", + "Brancolini (6.17, 0.44); (5.10, 0.66)\n", + "Berardi A. (6.19, 0.42); (5.28, 0.62)\n", + "Gemello (6.21, 0.43); (5.16, 0.67)\n", + "Boer (5.82, 0.52); (3.28, 1.26)\n", + "Bagnolini (6.12, 0.43); (5.58, 0.61)\n", + "Svilar (5.82, 0.52); (3.28, 1.26)\n", + "Sorrentino A. (6.20, 0.46); (5.04, 0.69)\n", + "Martinelli T. (6.20, 0.45); (5.07, 0.70)\n", + "Popa (6.21, 0.43); (5.16, 0.67)\n", + "Stubljar (6.05, 0.49); (3.77, 1.13)\n", + "Gori (6.19, 0.46); (5.04, 0.69)\n", + "Borbei (6.17, 0.44); (5.10, 0.66)\n", + "Okoye (5.92, 0.48); (3.93, 1.11)\n", + "Mandas (6.16, 0.46); (4.55, 0.87)\n", + "Dimarco (6.28, 0.38); (6.61, 0.67)\n", + "Di Lorenzo (6.25, 0.51); (6.74, 0.94)\n", + "Hernandez T. (6.16, 0.55); (6.59, 0.95)\n", + "Carlos Augusto (6.15, 0.41); (6.46, 0.66)\n", + "Danilo (6.17, 0.47); (6.48, 0.75)\n", + "Zappacosta (6.11, 0.49); (6.43, 0.78)\n", + "Schuurs (6.08, 0.44); (6.27, 0.63)\n", + "Posch (5.98, 0.41); (6.10, 0.59)\n", + "Bastoni (6.22, 0.41); (6.38, 0.52)\n", + "Smalling (6.03, 0.42); (6.23, 0.60)\n", + "Dumfries (6.21, 0.45); (6.64, 0.82)\n", + "Romagnoli (6.08, 0.47); (6.20, 0.59)\n", + "Pavard (6.04, 0.31); (6.13, 0.37)\n", + "Rrahmani (6.05, 0.50); (6.22, 0.66)\n", + "Spinazzola (6.10, 0.37); (6.35, 0.61)\n", + "Buongiorno (6.04, 0.47); (6.26, 0.72)\n", + "Bremer (6.04, 0.48); (6.19, 0.66)\n", + "Tomori (6.15, 0.49); (6.41, 0.75)\n", + "Biraghi (6.09, 0.50); (6.54, 0.92)\n", + "Mancini (5.88, 0.52); (6.07, 0.72)\n", + "Darmian (6.14, 0.37); (6.33, 0.50)\n", + "Bakker (6.00, 0.32); (6.10, 0.44)\n", + "Mazzocchi (5.72, 0.39); (5.74, 0.43)\n", + "Doig (6.01, 0.49); (6.24, 0.72)\n", + "Calabria (6.02, 0.45); (6.17, 0.62)\n", + "Acerbi (6.04, 0.32); (6.09, 0.33)\n", + "Cuadrado (6.03, 0.39); (6.12, 0.48)\n", + "Ebuehi (5.78, 0.41); (5.81, 0.50)\n", + "Casale (5.94, 0.44); (5.96, 0.53)\n", + "Holm (6.03, 0.33); (6.14, 0.42)\n", + "Baschirotto (5.92, 0.53); (6.02, 0.66)\n", + "Bijol (5.77, 0.52); (5.83, 0.65)\n", + "Thiaw (5.82, 0.62); (5.77, 0.65)\n", + "Mario Rui (5.93, 0.36); (5.95, 0.40)\n", + "Milenkovic (5.85, 0.56); (5.90, 0.68)\n", + "Rodriguez R. (5.98, 0.37); (5.98, 0.38)\n", + "Kolasinac (6.00, 0.37); (6.12, 0.49)\n", + "N'dicka (5.86, 0.42); (5.85, 0.48)\n", + "Scalvini (6.01, 0.51); (6.16, 0.67)\n", + "Perez N. (5.80, 0.50); (5.81, 0.61)\n", + "Kristensen (5.97, 0.33); (6.14, 0.49)\n", + "Izzo (5.93, 0.46); (5.97, 0.56)\n", + "De Vrij (6.17, 0.38); (6.27, 0.42)\n", + "Faraoni (5.78, 0.37); (5.80, 0.45)\n", + "Toloi (6.05, 0.46); (6.18, 0.61)\n", + "Kyriakopoulos (6.05, 0.48); (6.22, 0.68)\n", + "Bellanova (5.73, 0.56); (5.77, 0.65)\n", + "Mari' (5.89, 0.47); (5.90, 0.56)\n", + "Dodo' (5.85, 0.54); (5.93, 0.69)\n", + "Lucumi' (5.93, 0.38); (5.92, 0.43)\n", + "Hien (5.91, 0.41); (5.87, 0.44)\n", + "Natan (6.03, 0.41); (6.12, 0.49)\n", + "Hysaj (5.92, 0.39); (5.95, 0.49)\n", + "D'ambrosio (5.93, 0.34); (5.90, 0.35)\n", + "Luperto (5.64, 0.59); (5.58, 0.66)\n", + "Djimsiti (6.01, 0.36); (6.03, 0.38)\n", + "Marusic (5.88, 0.46); (5.84, 0.52)\n", + "Martin (5.87, 0.45); (5.91, 0.57)\n", + "Mina (6.03, 0.41); (6.26, 0.63)\n", + "Toljan (5.86, 0.44); (5.86, 0.50)\n", + "Llorente D. (5.85, 0.39); (5.81, 0.40)\n", + "Martinez Quarta (6.06, 0.58); (6.30, 0.83)\n", + "Bastoni S. (5.94, 0.50); (6.20, 0.79)\n", + "Dragusin (6.03, 0.44); (6.19, 0.62)\n", + "Parisi (6.05, 0.50); (6.24, 0.72)\n", + "Bradaric (5.80, 0.44); (5.81, 0.52)\n", + "Kamara H. (5.92, 0.27); (5.92, 0.29)\n", + "Olivera (5.97, 0.34); (6.03, 0.41)\n", + "Gendrey (5.93, 0.35); (5.93, 0.38)\n", + "Kristiansen (6.00, 0.38); (6.07, 0.49)\n", + "Beukema (5.98, 0.41); (6.03, 0.49)\n", + "Dossena (5.73, 0.42); (5.66, 0.43)\n", + "Pedersen (5.91, 0.30); (5.90, 0.31)\n", + "Juan Jesus (6.00, 0.34); (6.05, 0.35)\n", + "Gyomber (5.80, 0.46); (5.74, 0.49)\n", + "Alex Sandro (5.82, 0.51); (5.70, 0.54)\n", + "Hateboer (5.92, 0.45); (6.07, 0.65)\n", + "Palomino (6.01, 0.31); (6.06, 0.35)\n", + "Marchizza (6.10, 0.43); (6.31, 0.62)\n", + "Zappa (5.75, 0.38); (5.69, 0.38)\n", + "Gallo (5.93, 0.42); (5.91, 0.45)\n", + "Caldirola (5.82, 0.51); (5.87, 0.64)\n", + "Kalulu (5.92, 0.50); (5.95, 0.59)\n", + "Erlic (5.89, 0.46); (5.83, 0.46)\n", + "Vojvoda (5.93, 0.36); (5.97, 0.44)\n", + "Vasquez (6.09, 0.36); (6.15, 0.37)\n", + "Cambiaso (6.00, 0.43); (6.07, 0.50)\n", + "Pongracic (6.03, 0.40); (6.06, 0.44)\n", + "Viti (5.89, 0.45); (5.82, 0.43)\n", + "Gatti (5.76, 0.62); (5.69, 0.64)\n", + "Birindelli (5.93, 0.35); (5.92, 0.39)\n", + "Azzi (5.90, 0.28); (5.89, 0.28)\n", + "Wieteska (5.92, 0.44); (5.92, 0.52)\n", + "Masina (5.78, 0.49); (6.08, 0.69)\n", + "Romagnoli S. (6.08, 0.53); (6.32, 0.81)\n", + "Pezzella Giu. (5.64, 0.44); (5.55, 0.46)\n", + "Sabelli (5.98, 0.28); (6.02, 0.34)\n", + "Lirola (6.03, 0.49); (6.21, 0.69)\n", + "Lazzari (5.99, 0.37); (6.01, 0.40)\n", + "Bani (6.07, 0.53); (6.31, 0.80)\n", + "Djidji (5.88, 0.38); (5.90, 0.45)\n", + "Kabasele (5.86, 0.35); (5.83, 0.41)\n", + "Lazaro (6.00, 0.35); (6.04, 0.40)\n", + "Augello (5.87, 0.36); (5.92, 0.45)\n", + "Zortea (6.04, 0.43); (6.29, 0.65)\n", + "Dawidowicz (5.90, 0.39); (5.86, 0.44)\n", + "Pirola (5.70, 0.45); (5.69, 0.51)\n", + "Lovato (5.69, 0.44); (5.60, 0.47)\n", + "Ruggeri (6.10, 0.53); (6.43, 0.83)\n", + "Vina (5.67, 0.56); (5.67, 0.63)\n", + "Obert (5.75, 0.42); (5.69, 0.44)\n", + "Terracciano F. (6.02, 0.36); (6.08, 0.42)\n", + "Ebosele (5.80, 0.41); (5.75, 0.46)\n", + "Zemura (5.89, 0.29); (5.86, 0.31)\n", + "Hatzidiakos (5.89, 0.42); (5.88, 0.46)\n", + "Patric (5.94, 0.33); (5.92, 0.33)\n", + "Lykogiannis (5.92, 0.27); (5.92, 0.32)\n", + "Pellegrini Lu. (5.81, 0.34); (5.74, 0.34)\n", + "Magnani (5.93, 0.46); (5.92, 0.52)\n", + "Ranieri L. (5.78, 0.50); (5.82, 0.61)\n", + "Carboni A. (5.97, 0.37); (6.01, 0.44)\n", + "Calafiori (5.84, 0.44); (5.82, 0.53)\n", + "Monterisi (5.98, 0.62); (6.40, 1.05)\n", + "Ismajli (5.78, 0.48); (5.69, 0.49)\n", + "De Winter (5.93, 0.46); (5.90, 0.50)\n", + "Tressoldi (5.91, 0.45); (5.94, 0.53)\n", + "Ehizibue (5.77, 0.44); (5.77, 0.56)\n", + "Vogliacco (5.94, 0.46); (5.94, 0.52)\n", + "Ferrari G. (5.91, 0.50); (5.97, 0.62)\n", + "Venuti (5.89, 0.36); (5.86, 0.39)\n", + "Karsdorp (5.89, 0.29); (5.87, 0.30)\n", + "Kjaer (5.67, 0.49); (5.54, 0.50)\n", + "Gunter (5.74, 0.52); (5.64, 0.55)\n", + "Soumaoro (5.88, 0.47); (5.84, 0.54)\n", + "Di Pardo (5.80, 0.41); (5.75, 0.43)\n", + "Zanoli (6.07, 0.48); (6.35, 0.75)\n", + "Zima (5.97, 0.46); (5.97, 0.50)\n", + "Hefti (5.84, 0.38); (5.79, 0.36)\n", + "Ostigard (5.83, 0.38); (5.79, 0.38)\n", + "Sambia (5.89, 0.38); (5.88, 0.41)\n", + "Bisseck (5.99, 0.42); (6.08, 0.52)\n", + "Oyono (5.89, 0.35); (5.85, 0.35)\n", + "Ferreira J. (5.82, 0.33); (5.77, 0.36)\n", + "Dorgu (5.95, 0.24); (5.94, 0.23)\n", + "Touba (5.96, 0.43); (6.02, 0.52)\n", + "Sazonov (5.96, 0.40); (5.99, 0.48)\n", + "Rugani (5.98, 0.26); (5.99, 0.25)\n", + "De Sciglio (5.88, 0.32); (5.86, 0.31)\n", + "Goldaniga (5.65, 0.58); (5.56, 0.62)\n", + "Florenzi (6.06, 0.38); (6.14, 0.45)\n", + "De Silvestri (6.02, 0.28); (6.06, 0.31)\n", + "Pereira P. (5.97, 0.42); (6.02, 0.51)\n", + "Fazio (5.86, 0.61); (5.96, 0.77)\n", + "Bereszynski (5.64, 0.48); (5.58, 0.54)\n", + "Bonifazi (5.84, 0.40); (5.79, 0.43)\n", + "Walukiewicz (5.70, 0.55); (5.69, 0.64)\n", + "Okoli (5.86, 0.41); (5.81, 0.42)\n", + "Kumbulla (5.50, 0.73); (5.27, 0.69)\n", + "Celik (5.75, 0.45); (5.68, 0.50)\n", + "Amione (5.72, 0.44); (5.70, 0.53)\n", + "Daniliuc (5.77, 0.47); (5.74, 0.56)\n", + "Soppy (5.93, 0.34); (5.93, 0.40)\n", + "Haps (5.96, 0.46); (6.02, 0.58)\n", + "Cittadini (5.95, 0.44); (6.02, 0.57)\n", + "Coppola D. (5.85, 0.35); (5.78, 0.36)\n", + "Cacace (5.64, 0.43); (5.54, 0.43)\n", + "Ebosse (5.83, 0.35); (5.76, 0.39)\n", + "Guessand A. (5.89, 0.43); (5.92, 0.55)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Cabal (5.87, 0.25); (5.83, 0.24)\n", - "Missori (5.76, 0.43); (5.73, 0.48)\n", - "Kayode (5.99, 0.44); (6.02, 0.52)\n", - "Corazza (5.71, 0.39); (5.67, 0.44)\n", - "Kristensen T. (5.81, 0.45); (5.85, 0.58)\n", - "Dermaku (5.91, 0.43); (5.96, 0.54)\n", - "Tonelli (5.56, 0.49); (5.44, 0.53)\n", - "Capradossi (5.90, 0.44); (5.91, 0.53)\n", - "Bettella (5.87, 0.45); (5.93, 0.59)\n", - "Amey (5.82, 0.46); (5.87, 0.59)\n", - "Gila (5.86, 0.44); (5.84, 0.49)\n", - "Bronn (5.62, 0.45); (5.50, 0.46)\n", - "Guarino (5.67, 0.50); (5.67, 0.59)\n", - "Carboni F. (5.96, 0.37); (5.99, 0.45)\n", - "Smajlovic (5.91, 0.45); (5.98, 0.57)\n", - "Matturro (5.89, 0.45); (5.87, 0.50)\n", - "N'guessan (5.94, 0.43); (5.99, 0.54)\n", - "Mateus Lusuardi (5.92, 0.46); (5.97, 0.56)\n", - "Kalaj (5.92, 0.46); (5.97, 0.56)\n", - "Pierozzi (5.88, 0.48); (5.92, 0.58)\n", - "Huijsen (5.99, 0.42); (6.10, 0.54)\n", - "Bonfanti (5.97, 0.46); (6.07, 0.59)\n", - "Pellegrino (5.93, 0.46); (6.01, 0.59)\n", - "Comuzzo (5.88, 0.48); (5.92, 0.58)\n", - "Zaccagni (6.32, 0.53); (6.95, 1.16)\n", - "Koopmeiners (6.38, 0.57); (7.20, 1.36)\n", - "Luis Alberto (6.38, 0.53); (7.09, 1.23)\n", - "Felipe Anderson (6.14, 0.58); (6.77, 1.17)\n", - "Rabiot (6.31, 0.55); (7.06, 1.28)\n", - "Zielinski (6.30, 0.46); (6.71, 0.86)\n", - "Barella (6.35, 0.45); (6.79, 0.89)\n", - "Pulisic (6.21, 0.54); (6.81, 1.09)\n", - "Orsolini (6.18, 0.59); (6.84, 1.25)\n", - "Calhanoglu (6.42, 0.39); (6.67, 0.69)\n", - "Strefezza (6.19, 0.50); (6.64, 0.92)\n", - "Chukwueze (5.95, 0.43); (6.24, 0.66)\n", - "Ferguson (6.22, 0.52); (6.74, 1.01)\n", - "Candreva (6.17, 0.65); (6.86, 1.30)\n", - "Frattesi (6.35, 0.53); (7.04, 1.20)\n", - "Samardzic (6.06, 0.51); (6.47, 0.87)\n", - "Vlasic (6.13, 0.51); (6.59, 0.93)\n", - "Bonaventura (6.28, 0.57); (6.97, 1.23)\n", - "Politano (6.35, 0.45); (6.77, 0.90)\n", - "El Shaarawy (6.28, 0.46); (6.70, 0.90)\n", - "Mkhitaryan (6.36, 0.51); (7.00, 1.11)\n", - "Aouar (6.17, 0.49); (6.64, 0.94)\n", - "Malinovskyi (6.02, 0.56); (6.61, 1.10)\n", - "Gudmundsson A. (6.12, 0.46); (6.47, 0.78)\n", - "Kamada (6.06, 0.50); (6.49, 0.87)\n", - "Pellegrini Lo. (6.08, 0.56); (6.63, 1.05)\n", - "Kostic (6.22, 0.48); (6.68, 0.90)\n", - "Radonjic (6.32, 0.57); (7.08, 1.31)\n", - "Baldanzi (5.75, 0.44); (5.97, 0.62)\n", - "Lovric (6.05, 0.46); (6.37, 0.76)\n", - "Lindstrom (6.05, 0.45); (6.40, 0.74)\n", - "Lazovic (6.17, 0.49); (6.57, 0.87)\n", - "Pereyra (6.14, 0.56); (6.68, 1.07)\n", - "Renato Sanches (6.14, 0.40); (6.37, 0.61)\n", - "Pessina (6.02, 0.48); (6.33, 0.80)\n", - "Guendouzi (6.03, 0.36); (6.16, 0.47)\n", - "Loftus-Cheek (6.06, 0.36); (6.14, 0.42)\n", - "Zambo Anguissa (6.10, 0.50); (6.49, 0.83)\n", - "Elmas (6.02, 0.54); (6.50, 0.93)\n", - "Bajrami (5.93, 0.36); (6.03, 0.43)\n", - "Ricci S. (6.04, 0.38); (6.18, 0.52)\n", - "Colpani (6.33, 0.53); (7.03, 1.22)\n", - "Ciurria (6.06, 0.54); (6.54, 1.00)\n", - "De Roon (6.12, 0.50); (6.46, 0.80)\n", - "Pogba (6.03, 0.35); (6.08, 0.41)\n", - "Cristante (6.14, 0.51); (6.50, 0.83)\n", - "Locatelli (6.12, 0.40); (6.23, 0.52)\n", - "Pasalic (5.95, 0.47); (6.31, 0.76)\n", - "Lobotka (6.08, 0.37); (6.16, 0.43)\n", - "Fagioli (6.09, 0.50); (6.48, 0.84)\n", - "Ikone' (6.04, 0.56); (6.60, 1.03)\n", - "Ilic (6.04, 0.43); (6.31, 0.69)\n", - "Ndoye (5.90, 0.39); (5.96, 0.50)\n", - "Ederson D.s. (6.09, 0.48); (6.42, 0.77)\n", - "Reijnders (6.09, 0.45); (6.39, 0.70)\n", - "Barak (5.81, 0.44); (6.03, 0.61)\n", - "Saponara (6.08, 0.48); (6.43, 0.79)\n", - "Mandragora (5.94, 0.55); (6.38, 0.90)\n", - "Weah (6.04, 0.27); (6.09, 0.30)\n", - "Bennacer (6.16, 0.46); (6.53, 0.78)\n", - "Duda (6.24, 0.53); (6.79, 1.06)\n", - "Castrovilli (6.03, 0.58); (6.59, 1.04)\n", - "Mckennie (6.25, 0.44); (6.58, 0.74)\n", - "Miranchuk (6.22, 0.50); (6.69, 0.93)\n", - "Matheus Henrique (5.81, 0.46); (6.06, 0.66)\n", - "De Ketelaere (5.98, 0.48); (6.32, 0.75)\n", - "Mboula (5.81, 0.33); (5.77, 0.35)\n", - "Paredes (5.79, 0.53); (5.78, 0.61)\n", - "Sottil (5.95, 0.39); (6.13, 0.52)\n", - "Klaassen (6.16, 0.40); (6.45, 0.67)\n", - "Arthur Melo (6.01, 0.47); (6.09, 0.57)\n", - "Thorsby (5.75, 0.48); (5.86, 0.63)\n", - "Nandez (6.02, 0.35); (6.15, 0.50)\n", - "Tameze (5.91, 0.34); (5.90, 0.37)\n", - "Marin (5.71, 0.48); (5.79, 0.62)\n", - "Messias (5.96, 0.53); (6.44, 0.96)\n", - "Musah (5.96, 0.36); (5.98, 0.41)\n", - "Coulibaly L. (5.91, 0.49); (6.16, 0.73)\n", - "Krunic (5.98, 0.38); (6.00, 0.44)\n", - "Cataldi (5.97, 0.36); (5.94, 0.38)\n", - "Strootman (5.95, 0.37); (6.06, 0.49)\n", - "Duncan (6.10, 0.45); (6.42, 0.74)\n", - "Freuler (5.95, 0.29); (5.94, 0.33)\n", - "Gagliardini (5.85, 0.38); (5.80, 0.39)\n", - "Mazzitelli (6.09, 0.65); (6.51, 1.06)\n", - "Jankto (5.95, 0.31); (5.94, 0.33)\n", - "Kastanos (5.86, 0.35); (5.98, 0.44)\n", - "Gyasi (5.63, 0.43); (5.62, 0.50)\n", - "Reinier (5.93, 0.46); (6.00, 0.57)\n", - "Zalewski (5.94, 0.36); (6.09, 0.46)\n", - "Harroui (6.19, 0.46); (6.59, 0.82)\n", - "Frendrup (6.01, 0.37); (6.13, 0.49)\n", - "Blin (5.95, 0.29); (5.96, 0.32)\n", - "Fabbian (6.05, 0.43); (6.36, 0.77)\n", - "Ramadani (6.11, 0.45); (6.26, 0.60)\n", - "Cajuste (5.92, 0.48); (5.98, 0.57)\n", - "Mancosu (5.91, 0.44); (5.94, 0.53)\n", - "Vecino (5.91, 0.44); (6.00, 0.58)\n", - "Sensi (6.15, 0.45); (6.49, 0.72)\n", - "Walace (5.81, 0.38); (5.76, 0.43)\n", - "Lopez M. (5.78, 0.40); (5.70, 0.41)\n", - "Brescianini (6.01, 0.37); (6.02, 0.41)\n", - "Bove (6.03, 0.35); (6.18, 0.48)\n", - "Aebischer (5.90, 0.33); (6.00, 0.43)\n", - "Thorstvedt (5.90, 0.34); (5.97, 0.41)\n", - "Gonzalez J. (5.89, 0.39); (5.98, 0.53)\n", - "Moro N. (6.01, 0.37); (6.19, 0.54)\n", - "Oudin (6.02, 0.48); (6.31, 0.76)\n", - "Boloca (5.80, 0.48); (5.80, 0.57)\n", - "Rafia (6.04, 0.37); (6.24, 0.55)\n", - "Makoumbou (5.91, 0.33); (5.95, 0.41)\n", - "Kaba (5.97, 0.27); (5.97, 0.29)\n", - "Badelj (5.87, 0.40); (5.85, 0.39)\n", - "Machin (5.85, 0.46); (5.92, 0.60)\n", - "Linetty (5.90, 0.35); (5.92, 0.41)\n", - "Castillejo (5.83, 0.36); (6.00, 0.50)\n", - "Rovella (6.05, 0.46); (6.17, 0.59)\n", - "Pobega (5.91, 0.37); (6.07, 0.50)\n", - "Hongla (5.86, 0.37); (5.90, 0.44)\n", - "Miretti (6.00, 0.35); (6.09, 0.42)\n", - "Fazzini (5.67, 0.33); (5.56, 0.35)\n", - "Iling Junior (5.99, 0.42); (6.11, 0.55)\n", - "Oristanio (5.89, 0.37); (5.86, 0.38)\n", - "Serdar (5.89, 0.38); (5.89, 0.45)\n", - "Payero (5.84, 0.41); (5.87, 0.52)\n", - "Grassi (5.67, 0.42); (5.56, 0.44)\n", - "Baez (5.99, 0.37); (6.11, 0.47)\n", - "Deiola (5.76, 0.46); (5.82, 0.59)\n", - "Garritano (6.13, 0.34); (6.18, 0.41)\n", - "Bourabia (5.97, 0.40); (6.07, 0.50)\n", - "Saelemaekers (5.95, 0.43); (6.21, 0.66)\n", - "Maldini (5.81, 0.45); (6.10, 0.69)\n", - "Racic (5.91, 0.35); (5.90, 0.39)\n", - "Kovalenko (5.78, 0.34); (5.73, 0.37)\n", - "Maleh (5.65, 0.30); (5.53, 0.32)\n", - "Bohinen (5.91, 0.26); (5.88, 0.25)\n", - "Ranocchia F. (5.88, 0.40); (6.11, 0.57)\n", - "Folorunsho (5.93, 0.47); (6.24, 0.76)\n", - "Infantino (5.82, 0.32); (5.77, 0.32)\n", - "Martegani (5.88, 0.45); (5.92, 0.54)\n", - "Kutlu (5.87, 0.40); (5.85, 0.41)\n", - "Tchatchoua (5.89, 0.46); (5.97, 0.59)\n", - "Quina (5.97, 0.35); (6.01, 0.43)\n", - "Adopo (5.85, 0.51); (5.87, 0.58)\n", - "Romero L. (6.19, 0.49); (6.68, 0.97)\n", - "Basic (5.96, 0.37); (6.05, 0.46)\n", - "Asllani (5.89, 0.31); (5.88, 0.27)\n", - "Tchaouna (5.81, 0.38); (5.81, 0.44)\n", - "Sulemana I. (5.83, 0.31); (5.78, 0.31)\n", - "Barrenechea (5.96, 0.42); (5.99, 0.48)\n", - "Gelli (5.94, 0.47); (6.01, 0.56)\n", - "Suslov (5.92, 0.42); (5.96, 0.53)\n", - "Gaetano (6.12, 0.53); (6.72, 1.06)\n", - "Jagiello (5.90, 0.45); (5.90, 0.50)\n", - "Obiang (5.90, 0.30); (5.86, 0.30)\n", - "Maggiore (5.89, 0.25); (5.86, 0.24)\n", - "Akpa Akpro (5.85, 0.46); (5.92, 0.60)\n", - "Urbanski (5.94, 0.34); (5.98, 0.44)\n", - "Volpato (5.92, 0.39); (6.05, 0.54)\n", - "Vignato S. (5.81, 0.40); (5.78, 0.45)\n", - "Hrustic (5.63, 0.32); (5.62, 0.34)\n", - "Zarraga (5.63, 0.39); (5.57, 0.41)\n", - "Camara E. (5.82, 0.45); (5.88, 0.59)\n", - "Amatucci (5.86, 0.41); (5.87, 0.48)\n", - "Pagano (5.98, 0.28); (5.98, 0.30)\n", - "Prati (5.91, 0.40); (5.91, 0.44)\n", - "Viola (5.85, 0.33); (5.82, 0.30)\n", - "Lulic K. (5.93, 0.46); (6.00, 0.57)\n", - "Rog (5.87, 0.36); (5.85, 0.36)\n", - "Nicolussi Caviglia (5.83, 0.48); (6.00, 0.67)\n", - "Demme (6.00, 0.26); (5.95, 0.22)\n", - "Pafundi (6.04, 0.31); (6.06, 0.32)\n", - "Adli (5.83, 0.40); (5.94, 0.51)\n", - "Bondo (5.91, 0.42); (5.96, 0.54)\n", - "Zerbin (6.05, 0.35); (6.12, 0.41)\n", - "Carboni V. (5.99, 0.37); (6.06, 0.47)\n", - "Faticanti (5.92, 0.44); (6.01, 0.57)\n", - "Gineitis (5.97, 0.37); (6.02, 0.47)\n", - "Belardinelli (5.69, 0.49); (5.71, 0.60)\n", - "El Azzouzi (5.96, 0.30); (5.98, 0.36)\n", - "Lipani (5.83, 0.46); (5.86, 0.56)\n", - "Joselito (5.89, 0.46); (5.97, 0.59)\n", - "Legowski (5.88, 0.48); (5.96, 0.61)\n", - "Ibrahimovic A. (5.93, 0.46); (6.00, 0.57)\n", + "Cabal (6.04, 0.46); (6.10, 0.55)\n", + "Missori (5.95, 0.45); (5.99, 0.54)\n", + "Kayode (6.03, 0.48); (6.10, 0.59)\n", + "Corazza (5.84, 0.37); (5.81, 0.42)\n", + "Kristensen T. (5.77, 0.41); (5.74, 0.47)\n", + "Dermaku (5.95, 0.42); (5.99, 0.52)\n", + "Tonelli (5.64, 0.49); (5.53, 0.51)\n", + "Capradossi (5.90, 0.44); (5.93, 0.53)\n", + "Bettella (5.95, 0.44); (6.02, 0.57)\n", + "Amey (5.92, 0.41); (5.97, 0.54)\n", + "Gila (5.89, 0.42); (5.86, 0.46)\n", + "Bronn (5.68, 0.45); (5.56, 0.47)\n", + "Guarino (5.78, 0.48); (5.81, 0.59)\n", + "Carboni F. (6.04, 0.44); (6.18, 0.59)\n", + "Smajlovic (5.96, 0.44); (6.03, 0.55)\n", + "Matturro (5.93, 0.45); (5.91, 0.48)\n", + "N'guessan (5.95, 0.43); (6.00, 0.53)\n", + "Mateus Lusuardi (5.95, 0.46); (6.01, 0.57)\n", + "Kalaj (5.95, 0.46); (6.01, 0.57)\n", + "Pierozzi (5.97, 0.47); (6.03, 0.59)\n", + "Huijsen (6.00, 0.44); (6.11, 0.56)\n", + "Bonfanti (6.00, 0.45); (6.10, 0.58)\n", + "Pellegrino (5.97, 0.46); (6.03, 0.57)\n", + "Comuzzo (5.97, 0.47); (6.03, 0.59)\n", + "Zaccagni (6.30, 0.53); (6.91, 1.12)\n", + "Koopmeiners (6.37, 0.55); (7.10, 1.25)\n", + "Luis Alberto (6.30, 0.54); (6.98, 1.19)\n", + "Felipe Anderson (6.10, 0.55); (6.60, 1.01)\n", + "Rabiot (6.23, 0.55); (6.86, 1.16)\n", + "Zielinski (6.28, 0.47); (6.77, 0.93)\n", + "Barella (6.23, 0.45); (6.64, 0.80)\n", + "Pulisic (6.26, 0.59); (7.02, 1.31)\n", + "Orsolini (6.03, 0.52); (6.48, 0.98)\n", + "Calhanoglu (6.34, 0.40); (6.63, 0.66)\n", + "Strefezza (6.09, 0.44); (6.42, 0.76)\n", + "Chukwueze (5.94, 0.39); (6.17, 0.57)\n", + "Ferguson (6.13, 0.43); (6.46, 0.75)\n", + "Candreva (6.21, 0.63); (6.94, 1.30)\n", + "Frattesi (6.22, 0.51); (6.75, 1.00)\n", + "Samardzic (6.11, 0.47); (6.53, 0.85)\n", + "Vlasic (6.04, 0.47); (6.40, 0.79)\n", + "Bonaventura (6.32, 0.55); (7.00, 1.20)\n", + "Politano (6.33, 0.50); (6.92, 1.07)\n", + "El Shaarawy (6.10, 0.40); (6.40, 0.69)\n", + "Mkhitaryan (6.29, 0.51); (6.90, 1.06)\n", + "Aouar (5.97, 0.53); (6.43, 0.89)\n", + "Malinovskyi (6.04, 0.56); (6.63, 1.11)\n", + "Gudmundsson A. (6.25, 0.49); (6.79, 0.99)\n", + "Kamada (6.07, 0.48); (6.42, 0.80)\n", + "Pellegrini Lo. (5.93, 0.53); (6.35, 0.87)\n", + "Kostic (6.14, 0.44); (6.49, 0.74)\n", + "Radonjic (6.26, 0.59); (7.04, 1.33)\n", + "Baldanzi (5.95, 0.53); (6.37, 0.88)\n", + "Lovric (6.00, 0.41); (6.27, 0.66)\n", + "Lindstrom (6.04, 0.39); (6.33, 0.66)\n", + "Lazovic (6.12, 0.44); (6.43, 0.73)\n", + "Pereyra (6.05, 0.56); (6.55, 1.01)\n", + "Renato Sanches (6.10, 0.36); (6.32, 0.56)\n", + "Pessina (6.07, 0.48); (6.31, 0.73)\n", + "Guendouzi (5.97, 0.36); (6.06, 0.47)\n", + "Loftus-Cheek (6.19, 0.45); (6.54, 0.75)\n", + "Zambo Anguissa (6.05, 0.46); (6.26, 0.65)\n", + "Elmas (6.00, 0.50); (6.35, 0.81)\n", + "Bajrami (6.08, 0.36); (6.28, 0.54)\n", + "Ricci S. (5.99, 0.41); (6.10, 0.55)\n", + "Colpani (6.34, 0.53); (7.03, 1.19)\n", + "Ciurria (6.03, 0.51); (6.39, 0.85)\n", + "De Roon (6.12, 0.47); (6.41, 0.73)\n", + "Pogba (6.04, 0.42); (6.15, 0.52)\n", + "Cristante (6.08, 0.50); (6.38, 0.78)\n", + "Locatelli (5.98, 0.38); (6.03, 0.45)\n", + "Pasalic (6.00, 0.52); (6.47, 0.91)\n", + "Lobotka (6.06, 0.40); (6.16, 0.48)\n", + "Fagioli (6.07, 0.49); (6.40, 0.78)\n", + "Ikone' (6.08, 0.53); (6.56, 0.96)\n", + "Ilic (6.00, 0.37); (6.05, 0.46)\n", + "Ndoye (5.94, 0.35); (5.99, 0.43)\n", + "Ederson D.s. (6.09, 0.46); (6.38, 0.72)\n", + "Reijnders (6.13, 0.44); (6.43, 0.70)\n", + "Barak (5.87, 0.44); (6.07, 0.61)\n", + "Saponara (6.06, 0.40); (6.31, 0.63)\n", + "Mandragora (6.02, 0.51); (6.36, 0.82)\n", + "Weah (5.96, 0.27); (5.99, 0.29)\n", + "Bennacer (6.16, 0.44); (6.49, 0.71)\n", + "Duda (6.26, 0.52); (6.82, 1.06)\n", + "Castrovilli (6.08, 0.54); (6.56, 0.97)\n", + "Mckennie (6.21, 0.39); (6.39, 0.52)\n", + "Miranchuk (6.24, 0.49); (6.69, 0.91)\n", + "Matheus Henrique (5.99, 0.46); (6.25, 0.69)\n", + "De Ketelaere (6.08, 0.51); (6.47, 0.85)\n", + "Mboula (5.92, 0.39); (5.93, 0.47)\n", + "Paredes (5.82, 0.49); (5.85, 0.60)\n", + "Sottil (5.94, 0.35); (6.08, 0.43)\n", + "Klaassen (6.10, 0.39); (6.38, 0.66)\n", + "Arthur Melo (6.06, 0.40); (6.15, 0.50)\n", + "Thorsby (5.92, 0.60); (6.36, 0.99)\n", + "Nandez (5.99, 0.34); (6.11, 0.48)\n", + "Tameze (5.92, 0.31); (5.90, 0.33)\n", + "Marin (5.89, 0.39); (5.97, 0.52)\n", + "Messias (6.03, 0.56); (6.59, 1.07)\n", + "Musah (6.01, 0.34); (6.06, 0.40)\n", + "Coulibaly L. (5.99, 0.49); (6.22, 0.73)\n", + "Krunic (5.97, 0.38); (5.99, 0.43)\n", + "Cataldi (5.98, 0.35); (5.98, 0.38)\n", + "Strootman (5.96, 0.34); (6.01, 0.44)\n", + "Duncan (6.17, 0.43); (6.51, 0.74)\n", + "Freuler (5.94, 0.28); (5.94, 0.33)\n", + "Gagliardini (6.14, 0.47); (6.48, 0.77)\n", + "Mazzitelli (6.10, 0.68); (6.75, 1.31)\n", + "Jankto (5.94, 0.30); (5.94, 0.33)\n", + "Kastanos (5.94, 0.30); (6.02, 0.36)\n", + "Gyasi (5.69, 0.40); (5.70, 0.47)\n", + "Reinier (5.96, 0.47); (6.05, 0.59)\n", + "Zalewski (5.86, 0.34); (5.94, 0.41)\n", + "Harroui (6.17, 0.45); (6.52, 0.76)\n", + "Frendrup (6.04, 0.33); (6.14, 0.41)\n", + "Blin (5.95, 0.26); (5.95, 0.27)\n", + "Fabbian (5.94, 0.39); (6.17, 0.67)\n", + "Ramadani (6.09, 0.41); (6.21, 0.50)\n", + "Cajuste (5.96, 0.47); (6.02, 0.58)\n", + "Mancosu (5.89, 0.45); (5.92, 0.55)\n", + "Vecino (6.00, 0.48); (6.16, 0.68)\n", + "Sensi (6.14, 0.45); (6.48, 0.72)\n", + "Walace (5.81, 0.37); (5.76, 0.43)\n", + "Lopez M. (5.92, 0.42); (5.89, 0.47)\n", + "Brescianini (5.94, 0.32); (5.93, 0.34)\n", + "Bove (5.88, 0.41); (6.07, 0.58)\n", + "Aebischer (5.95, 0.30); (6.00, 0.37)\n", + "Thorstvedt (5.95, 0.33); (6.01, 0.39)\n", + "Gonzalez J. (5.89, 0.38); (5.95, 0.49)\n", + "Moro N. (6.02, 0.35); (6.17, 0.51)\n", + "Oudin (6.07, 0.46); (6.38, 0.75)\n", + "Boloca (5.99, 0.49); (6.05, 0.60)\n", + "Rafia (5.94, 0.33); (6.09, 0.47)\n", + "Makoumbou (5.90, 0.30); (5.92, 0.36)\n", + "Kaba (5.85, 0.37); (5.76, 0.39)\n", + "Badelj (5.87, 0.44); (5.83, 0.47)\n", + "Machin (5.94, 0.45); (6.02, 0.59)\n", + "Linetty (5.93, 0.35); (5.94, 0.40)\n", + "Castillejo (5.91, 0.34); (6.07, 0.46)\n", + "Rovella (6.04, 0.45); (6.13, 0.57)\n", + "Pobega (5.94, 0.26); (5.97, 0.30)\n", + "Hongla (5.93, 0.31); (5.92, 0.33)\n", + "Miretti (5.92, 0.32); (5.94, 0.37)\n", + "Fazzini (5.74, 0.36); (5.67, 0.37)\n", + "Iling Junior (6.00, 0.45); (6.12, 0.58)\n", + "Oristanio (5.90, 0.30); (5.88, 0.31)\n", + "Serdar (5.93, 0.33); (5.93, 0.37)\n", + "Payero (5.82, 0.38); (5.80, 0.45)\n", + "Grassi (5.76, 0.43); (5.68, 0.46)\n", + "Baez (5.89, 0.32); (5.86, 0.35)\n", + "Deiola (5.66, 0.40); (5.62, 0.43)\n", + "Garritano (6.10, 0.40); (6.18, 0.47)\n", + "Bourabia (5.96, 0.38); (6.01, 0.47)\n", + "Saelemaekers (5.86, 0.39); (6.00, 0.54)\n", + "Maldini (5.93, 0.42); (6.21, 0.67)\n", + "Racic (5.97, 0.35); (5.99, 0.39)\n", + "Kovalenko (5.86, 0.39); (5.83, 0.43)\n", + "Maleh (5.70, 0.47); (5.67, 0.56)\n", + "Bohinen (5.91, 0.26); (5.88, 0.26)\n", + "Ranocchia F. (6.01, 0.41); (6.25, 0.61)\n", + "Folorunsho (5.86, 0.43); (6.08, 0.64)\n", + "Infantino (5.96, 0.44); (5.99, 0.52)\n", + "Martegani (5.98, 0.37); (6.02, 0.45)\n", + "Kutlu (5.98, 0.44); (5.99, 0.48)\n", + "Tchatchoua (5.95, 0.44); (6.02, 0.57)\n", + "Quina (5.99, 0.40); (6.08, 0.52)\n", + "Adopo (6.00, 0.49); (6.10, 0.62)\n", + "Romero L. (6.00, 0.41); (6.12, 0.55)\n", + "Basic (5.97, 0.36); (6.03, 0.44)\n", + "Asllani (6.08, 0.40); (6.16, 0.46)\n", + "Tchaouna (5.88, 0.39); (5.89, 0.48)\n", + "Sulemana I. (5.75, 0.34); (5.69, 0.34)\n", + "Barrenechea (5.93, 0.34); (5.90, 0.35)\n", + "Gelli (5.97, 0.47); (6.03, 0.57)\n", + "Suslov (5.94, 0.33); (5.95, 0.38)\n", + "Gaetano (6.05, 0.47); (6.53, 0.90)\n", + "Jagiello (5.96, 0.46); (5.97, 0.51)\n", + "Obiang (5.92, 0.28); (5.90, 0.29)\n", + "Maggiore (5.91, 0.27); (5.88, 0.29)\n", + "Akpa Akpro (5.94, 0.45); (6.02, 0.59)\n", + "Urbanski (5.85, 0.42); (5.87, 0.54)\n", + "Volpato (5.96, 0.45); (6.10, 0.62)\n", + "Vignato S. (5.85, 0.39); (5.82, 0.45)\n", + "Hrustic (5.69, 0.30); (5.65, 0.30)\n", + "Zarraga (5.76, 0.43); (5.75, 0.51)\n", + "Camara E. (5.85, 0.45); (5.91, 0.60)\n", + "Amatucci (5.98, 0.47); (6.07, 0.60)\n", + "Pagano (6.09, 0.39); (6.23, 0.50)\n", + "Prati (5.92, 0.45); (5.95, 0.53)\n", + "Viola (5.92, 0.37); (5.92, 0.41)\n", + "Lulic K. (5.96, 0.47); (6.05, 0.59)\n", + "Rog (5.87, 0.36); (5.85, 0.39)\n", + "Nicolussi Caviglia (5.83, 0.49); (5.91, 0.63)\n", + "Demme (5.99, 0.27); (5.98, 0.24)\n", + "Pafundi (5.93, 0.40); (5.93, 0.45)\n", + "Adli (5.91, 0.44); (5.91, 0.52)\n", + "Bondo (5.96, 0.43); (6.03, 0.56)\n", + "Zerbin (5.93, 0.38); (5.93, 0.45)\n", + "Carboni V. (5.89, 0.46); (5.94, 0.59)\n", + "Faticanti (5.96, 0.45); (6.03, 0.58)\n", + "Gineitis (5.96, 0.42); (6.02, 0.53)\n", + "Belardinelli (5.81, 0.47); (5.86, 0.60)\n", + "El Azzouzi (5.88, 0.36); (5.84, 0.39)\n", + "Lipani (5.95, 0.44); (6.00, 0.55)\n", + "Joselito (5.95, 0.44); (6.02, 0.57)\n", + "Legowski (5.95, 0.47); (6.07, 0.64)\n", + "Ibrahimovic A. (5.96, 0.47); (6.05, 0.59)\n", "Osimhen (6.47, 0.76); (7.90, 2.05)\n", - "Martinez L. (6.50, 0.67); (7.94, 1.98)\n", - "Rafael Leao (6.43, 0.67); (7.72, 1.86)\n", - "Lukaku (6.33, 0.72); (7.50, 1.75)\n", - "Berardi (6.40, 0.71); (7.68, 1.89)\n", - "Immobile (6.14, 0.67); (6.99, 1.42)\n", - "Vlahovic (6.35, 0.74); (7.45, 1.76)\n", - "Dybala (6.43, 0.73); (7.78, 1.95)\n", - "Kvaratskhelia (6.40, 0.66); (7.57, 1.74)\n", - "Giroud (6.38, 0.66); (7.58, 1.77)\n", - "Scamacca (6.28, 0.73); (7.33, 1.67)\n", - "Thuram (6.47, 0.53); (7.27, 1.35)\n", - "Lookman (6.37, 0.70); (7.53, 1.78)\n", - "Dia (6.24, 0.72); (7.26, 1.61)\n", - "Arnautovic (6.36, 0.56); (7.18, 1.33)\n", - "Retegui (6.03, 0.65); (6.71, 1.21)\n", - "Sanabria (6.18, 0.60); (6.99, 1.34)\n", - "Nzola (5.99, 0.62); (6.63, 1.10)\n", - "Lauriente' (6.23, 0.61); (6.98, 1.36)\n", - "Zapata D. (5.96, 0.46); (6.29, 0.74)\n", - "Chiesa (6.41, 0.56); (7.25, 1.38)\n" + "Martinez L. (6.47, 0.71); (7.97, 2.04)\n", + "Rafael Leao (6.45, 0.63); (7.59, 1.68)\n", + "Lukaku (6.25, 0.74); (7.33, 1.65)\n", + "Berardi (6.48, 0.66); (7.77, 1.83)\n", + "Immobile (6.15, 0.65); (7.02, 1.41)\n", + "Vlahovic (6.34, 0.75); (7.49, 1.78)\n", + "Dybala (6.32, 0.76); (7.48, 1.77)\n", + "Kvaratskhelia (6.39, 0.64); (7.46, 1.64)\n", + "Giroud (6.38, 0.65); (7.56, 1.74)\n", + "Scamacca (6.31, 0.72); (7.47, 1.74)\n", + "Thuram (6.43, 0.58); (7.37, 1.47)\n", + "Lookman (6.37, 0.68); (7.55, 1.75)\n", + "Dia (6.26, 0.72); (7.39, 1.68)\n", + "Arnautovic (6.25, 0.50); (6.81, 1.02)\n", + "Retegui (6.15, 0.69); (7.05, 1.49)\n", + "Sanabria (6.04, 0.56); (6.68, 1.10)\n", + "Nzola (5.95, 0.54); (6.43, 0.91)\n", + "Lauriente' (6.32, 0.59); (7.11, 1.35)\n", + "Zapata D. (6.03, 0.44); (6.36, 0.74)\n", + "Chiesa (6.42, 0.59); (7.39, 1.50)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Milik (6.20, 0.50); (6.71, 0.99)\n", - "Gonzalez N. (6.25, 0.64); (7.23, 1.53)\n", - "Okafor (5.95, 0.29); (5.95, 0.31)\n", - "Pinamonti (5.93, 0.59); (6.45, 1.01)\n", - "Beltran L. (5.98, 0.55); (6.50, 0.95)\n", - "Caprari (5.98, 0.52); (6.40, 0.89)\n", - "Sanchez (6.18, 0.46); (6.61, 0.86)\n", - "Caputo (5.69, 0.46); (5.95, 0.61)\n", - "Toure' E. (5.97, 0.45); (6.11, 0.59)\n", - "Krstovic (6.26, 0.43); (6.63, 0.79)\n", - "Belotti (6.11, 0.49); (6.59, 0.93)\n", - "Muriel (6.13, 0.46); (6.50, 0.81)\n", - "Lapadula (5.99, 0.51); (6.44, 0.94)\n", - "Jovic (6.00, 0.59); (6.59, 1.07)\n", - "Abraham (6.19, 0.60); (6.98, 1.31)\n", - "Zirkzee (6.21, 0.50); (6.73, 1.00)\n", - "Ngonge (6.08, 0.58); (6.70, 1.13)\n", - "Petagna (5.94, 0.50); (6.35, 0.87)\n", - "Simeone (5.82, 0.49); (6.25, 0.75)\n", - "Deulofeu (6.30, 0.59); (7.13, 1.41)\n", - "Pedro (6.04, 0.48); (6.38, 0.79)\n", - "Shomurodov (5.75, 0.39); (5.96, 0.56)\n", - "Azmoun (5.89, 0.38); (6.14, 0.58)\n", - "Castellanos (5.96, 0.29); (5.95, 0.31)\n", - "Cheddira (6.12, 0.63); (6.86, 1.30)\n", - "Karlsson (6.10, 0.44); (6.46, 0.79)\n", - "Brekalo (6.05, 0.60); (6.69, 1.12)\n", - "Cambiaghi (5.99, 0.57); (6.53, 1.05)\n", - "Henry (5.86, 0.51); (6.22, 0.79)\n", - "Mulattieri (5.91, 0.39); (6.22, 0.68)\n", - "Almqvist (6.05, 0.54); (6.48, 0.91)\n", - "Isaksen (5.86, 0.42); (5.90, 0.51)\n", - "Kean (5.87, 0.57); (6.31, 0.93)\n", - "Karamoh (5.96, 0.41); (6.22, 0.64)\n", - "Thauvin (5.71, 0.34); (5.82, 0.42)\n", - "Kouame' (6.10, 0.63); (6.86, 1.28)\n", - "Raspadori (5.93, 0.53); (6.36, 0.85)\n", - "Colombo (5.91, 0.55); (6.39, 0.95)\n", - "Luvumbo (5.96, 0.37); (6.11, 0.52)\n", - "Mota (5.87, 0.54); (6.29, 0.88)\n", - "Brenner (5.81, 0.45); (5.90, 0.59)\n", - "Bonazzoli (5.99, 0.48); (6.37, 0.80)\n", - "Djuric (5.95, 0.35); (6.10, 0.47)\n", - "Davis K. (5.81, 0.45); (5.90, 0.59)\n", - "Banda (6.08, 0.44); (6.35, 0.69)\n", - "Defrel (5.75, 0.42); (5.96, 0.59)\n", - "Sansone (6.19, 0.56); (6.85, 1.19)\n", - "Pellegri (5.79, 0.41); (6.00, 0.58)\n", - "Piccoli (5.87, 0.41); (6.14, 0.63)\n", - "Success (5.87, 0.41); (6.09, 0.61)\n", - "Botheim (5.71, 0.35); (5.84, 0.47)\n", - "Lucca (5.81, 0.38); (5.95, 0.53)\n", - "Caso (6.13, 0.47); (6.53, 0.84)\n", - "Jovane (5.86, 0.48); (5.99, 0.64)\n", - "Soule' (6.25, 0.42); (6.54, 0.71)\n", - "Pavoletti (5.80, 0.38); (5.97, 0.55)\n", - "Cancellieri (5.60, 0.34); (5.54, 0.35)\n", - "Seck (6.11, 0.34); (6.22, 0.42)\n", - "Alvarez A. (5.86, 0.43); (6.14, 0.66)\n", - "Cuni (5.97, 0.32); (5.98, 0.35)\n", - "Ekuban (5.83, 0.35); (5.95, 0.41)\n", - "Maric (5.95, 0.34); (5.98, 0.40)\n", - "Cruz (5.88, 0.47); (6.00, 0.62)\n", - "Destro (5.62, 0.46); (5.66, 0.53)\n", - "Van Hooijdonk (5.94, 0.40); (6.06, 0.55)\n", - "Ceide (5.72, 0.40); (5.80, 0.44)\n", - "Kvernadze (5.91, 0.42); (5.97, 0.51)\n", - "Ikwuemesi (5.82, 0.40); (5.87, 0.48)\n", - "Puscas (5.90, 0.45); (5.94, 0.51)\n", - "Ake' M. (5.86, 0.39); (5.88, 0.48)\n", - "Braaf (5.64, 0.35); (5.74, 0.41)\n", - "Kallon (5.84, 0.41); (6.05, 0.59)\n", - "Kaio Jorge (5.92, 0.29); (5.94, 0.30)\n", - "Vivaldo (5.81, 0.45); (5.90, 0.59)\n", - "Bidaoui (5.93, 0.47); (6.04, 0.61)\n", - "Shpendi S. (5.67, 0.43); (5.65, 0.49)\n", - "Burnete (5.96, 0.40); (6.05, 0.52)\n", - "Corfitzen (5.91, 0.46); (6.03, 0.62)\n", - "Stewart (5.86, 0.48); (5.99, 0.64)\n", - "Yildiz (6.00, 0.44); (6.14, 0.58)\n" + "Milik (6.18, 0.46); (6.62, 0.88)\n", + "Gonzalez N. (6.37, 0.58); (7.27, 1.42)\n", + "Okafor (6.14, 0.46); (6.55, 0.84)\n", + "Pinamonti (5.99, 0.59); (6.57, 1.07)\n", + "Beltran L. (5.96, 0.45); (6.34, 0.76)\n", + "Caprari (6.04, 0.50); (6.40, 0.82)\n", + "Sanchez (6.03, 0.44); (6.45, 0.81)\n", + "Caputo (5.77, 0.46); (6.08, 0.68)\n", + "Toure' E. (6.00, 0.45); (6.14, 0.60)\n", + "Krstovic (6.27, 0.52); (6.87, 1.09)\n", + "Belotti (6.04, 0.51); (6.57, 0.96)\n", + "Muriel (6.19, 0.46); (6.58, 0.86)\n", + "Lapadula (5.99, 0.50); (6.52, 0.97)\n", + "Jovic (6.03, 0.58); (6.61, 1.06)\n", + "Abraham (6.07, 0.58); (6.78, 1.16)\n", + "Zirkzee (6.22, 0.47); (6.68, 0.92)\n", + "Ngonge (5.94, 0.54); (6.41, 0.91)\n", + "Petagna (5.95, 0.52); (6.39, 0.90)\n", + "Simeone (6.08, 0.61); (6.78, 1.20)\n", + "Deulofeu (6.29, 0.58); (7.11, 1.37)\n", + "Pedro (6.00, 0.45); (6.27, 0.69)\n", + "Shomurodov (5.72, 0.29); (5.68, 0.27)\n", + "Azmoun (5.88, 0.36); (6.14, 0.57)\n", + "Castellanos (6.06, 0.36); (6.13, 0.42)\n", + "Cheddira (6.14, 0.63); (6.89, 1.30)\n", + "Karlsson (5.95, 0.41); (6.26, 0.69)\n", + "Brekalo (6.08, 0.56); (6.64, 1.04)\n", + "Cambiaghi (5.92, 0.48); (6.20, 0.76)\n", + "Henry (5.83, 0.43); (6.09, 0.64)\n", + "Mulattieri (6.02, 0.35); (6.32, 0.65)\n", + "Almqvist (6.15, 0.53); (6.61, 0.96)\n", + "Isaksen (5.87, 0.45); (5.89, 0.55)\n", + "Kean (5.99, 0.57); (6.48, 1.02)\n", + "Karamoh (6.03, 0.39); (6.27, 0.60)\n", + "Thauvin (5.70, 0.34); (5.81, 0.44)\n", + "Kouame' (6.09, 0.59); (6.79, 1.20)\n", + "Raspadori (5.97, 0.50); (6.40, 0.85)\n", + "Colombo (5.87, 0.50); (6.25, 0.82)\n", + "Luvumbo (5.97, 0.33); (6.14, 0.50)\n", + "Mota (5.84, 0.49); (6.15, 0.74)\n", + "Brenner (5.87, 0.44); (5.95, 0.59)\n", + "Bonazzoli (5.94, 0.45); (6.27, 0.72)\n", + "Djuric (5.98, 0.26); (6.06, 0.30)\n", + "Davis K. (5.87, 0.44); (5.95, 0.59)\n", + "Banda (6.06, 0.40); (6.28, 0.60)\n", + "Defrel (5.75, 0.40); (5.94, 0.55)\n", + "Sansone (6.12, 0.46); (6.53, 0.84)\n", + "Pellegri (5.85, 0.34); (5.88, 0.39)\n", + "Piccoli (5.95, 0.32); (5.99, 0.37)\n", + "Success (5.85, 0.39); (6.05, 0.58)\n", + "Botheim (5.63, 0.35); (5.67, 0.38)\n", + "Lucca (5.73, 0.42); (5.94, 0.59)\n", + "Caso (6.09, 0.45); (6.48, 0.82)\n", + "Jovane (5.94, 0.47); (6.09, 0.66)\n", + "Soule' (6.30, 0.40); (6.65, 0.73)\n", + "Pavoletti (5.81, 0.37); (6.01, 0.56)\n", + "Cancellieri (5.78, 0.46); (5.88, 0.62)\n", + "Seck (6.09, 0.33); (6.21, 0.40)\n", + "Alvarez A. (5.92, 0.41); (6.17, 0.62)\n", + "Cuni (5.84, 0.38); (5.80, 0.40)\n", + "Ekuban (5.94, 0.30); (5.97, 0.30)\n", + "Maric (5.95, 0.24); (5.95, 0.25)\n", + "Cruz (5.94, 0.44); (6.07, 0.60)\n", + "Destro (5.67, 0.41); (5.73, 0.48)\n", + "Van Hooijdonk (6.00, 0.36); (6.09, 0.48)\n", + "Ceide (5.81, 0.38); (5.85, 0.39)\n", + "Kvernadze (5.89, 0.44); (5.91, 0.53)\n", + "Ikwuemesi (5.81, 0.36); (5.81, 0.40)\n", + "Puscas (5.94, 0.45); (5.96, 0.51)\n", + "Ake' M. (5.92, 0.37); (5.96, 0.46)\n", + "Braaf (5.68, 0.33); (5.78, 0.40)\n", + "Kallon (5.85, 0.40); (6.05, 0.55)\n", + "Kaio Jorge (5.92, 0.27); (5.92, 0.28)\n", + "Vivaldo (5.87, 0.44); (5.95, 0.59)\n", + "Bidaoui (5.96, 0.47); (6.08, 0.62)\n", + "Shpendi S. (5.88, 0.29); (5.90, 0.33)\n", + "Burnete (6.01, 0.45); (6.16, 0.61)\n", + "Corfitzen (5.97, 0.45); (6.10, 0.61)\n", + "Stewart (5.94, 0.47); (6.09, 0.66)\n", + "Yildiz (6.01, 0.46); (6.16, 0.60)\n" ] }, { @@ -7764,6 +7766,28 @@ " \n", " \n", " \n", + " Rossi F.\n", + " P\n", + " Atalanta\n", + " Avg\n", + " 1\n", + " 0\n", + " 0\n", + " 6.154525\n", + " 0.429769\n", + " 5.710340\n", + " 0.608428\n", + " 6.061085\n", + " 0.478673\n", + " 0.143872\n", + " 1.092386\n", + " 6.415344\n", + " 0.598177\n", + " -0.769786\n", + " 1.148949\n", + " 56.114355\n", + " \n", + " \n", " Musso\n", " P\n", " Atalanta\n", @@ -7771,19 +7795,19 @@ " 1\n", " 1\n", " 100\n", - " 6.171178\n", - " 0.427645\n", - " 5.716592\n", - " 0.632592\n", - " 6.120677\n", - " 0.493384\n", - " 0.075656\n", - " 1.078080\n", - " 6.470728\n", - " 0.603981\n", - " -0.807733\n", - " 1.135469\n", - " 58.570200\n", + " 6.154517\n", + " 0.430199\n", + " 5.707846\n", + " 0.608343\n", + " 6.060265\n", + " 0.478830\n", + " 0.145062\n", + " 1.092329\n", + " 6.411938\n", + " 0.599186\n", + " -0.767992\n", + " 1.148581\n", + " 56.005341\n", " \n", " \n", " Carnesecchi\n", @@ -7793,41 +7817,19 @@ " 1\n", " 0\n", " 0\n", - " 5.869667\n", - " 0.502827\n", - " 3.425929\n", - " 1.371020\n", - " 6.030291\n", - " 0.638892\n", - " -0.184642\n", - " 1.097941\n", - " 4.448452\n", - " 1.535484\n", - " -0.582005\n", - " 0.860812\n", - " 1.164914\n", - " \n", - " \n", - " Rossi F.\n", - " P\n", - " Atalanta\n", - " Avg\n", - " 1\n", - " 0\n", - " 0\n", - " 5.960478\n", - " 0.501686\n", - " 3.407276\n", - " 1.365965\n", - " 5.941229\n", - " 0.593570\n", - " 0.024161\n", - " 1.093842\n", - " 4.423328\n", - " 1.528818\n", - " -0.581675\n", - " 0.862571\n", - " 1.128720\n", + " 6.121501\n", + " 0.449849\n", + " 5.199359\n", + " 0.664409\n", + " 6.049285\n", + " 0.510774\n", + " 0.106278\n", + " 1.092119\n", + " 5.646819\n", + " 0.903720\n", + " -0.364365\n", + " 1.027859\n", + " 27.208376\n", " \n", " \n", " Zappacosta\n", @@ -7836,19 +7838,19 @@ " Avg\n", " 1\n", " 1\n", - " 100\n", - " 6.098510\n", - " 0.555344\n", - " 6.568691\n", - " 0.979324\n", - " 5.952041\n", - " 0.611557\n", - " 0.174813\n", - " 0.810975\n", - " 5.694494\n", - " 1.174959\n", - " 0.514689\n", - " 1.299705\n", + " 83\n", + " 6.106201\n", + " 0.489143\n", + " 6.430954\n", + " 0.784539\n", + " 6.056791\n", + " 0.560162\n", + " 0.064960\n", + " 0.877353\n", + " 5.846407\n", + " 1.045597\n", + " 0.398034\n", + " 1.299841\n", " 0.000000\n", " \n", " \n", @@ -7859,18 +7861,18 @@ " 1\n", " 1\n", " 100\n", - " 6.087699\n", - " 0.554154\n", - " 6.456921\n", - " 0.876787\n", - " 6.054248\n", - " 0.637605\n", - " 0.038587\n", - " 0.828000\n", - " 5.812500\n", - " 1.175351\n", - " 0.391089\n", - " 1.299670\n", + " 6.100199\n", + " 0.525928\n", + " 6.427830\n", + " 0.829378\n", + " 6.077005\n", + " 0.608189\n", + " 0.028110\n", + " 0.853873\n", + " 5.837552\n", + " 1.127070\n", + " 0.374861\n", + " 1.299839\n", " 0.000000\n", " \n", " \n", @@ -7902,63 +7904,19 @@ " Avg\n", " 1\n", " 0\n", - " 0\n", - " 5.855402\n", - " 0.505158\n", - " 6.219285\n", - " 0.793892\n", - " 5.594287\n", - " 0.513562\n", - " 0.367600\n", - " 0.835252\n", - " 5.435407\n", - " 0.871782\n", - " 0.604878\n", - " 1.299692\n", - " 0.000000\n", - " \n", - " \n", - " Djuric\n", - " A\n", - " Verona\n", - " Avg\n", - " 1\n", - " 0\n", - " 100\n", - " 5.948880\n", - " 0.348636\n", - " 6.099661\n", - " 0.472785\n", - " 5.886502\n", - " 0.392925\n", - " 0.117059\n", - " 0.988531\n", - " 5.772749\n", - " 0.649155\n", - " 0.361159\n", - " 1.299597\n", - " 0.000000\n", - " \n", - " \n", - " Kallon\n", - " A\n", - " Verona\n", - " Avg\n", - " 1\n", - " 0\n", - " 0\n", - " 5.837097\n", - " 0.413428\n", - " 6.047479\n", - " 0.594338\n", - " 5.662558\n", - " 0.429064\n", - " 0.295895\n", - " 0.922908\n", - " 5.502729\n", - " 0.699002\n", - " 0.535697\n", - " 1.299641\n", + " 16\n", + " 5.828518\n", + " 0.428970\n", + " 6.086343\n", + " 0.642557\n", + " 5.631263\n", + " 0.438163\n", + " 0.326536\n", + " 0.922681\n", + " 5.474199\n", + " 0.730840\n", + " 0.569787\n", + " 1.299849\n", " 0.000000\n", " \n", " \n", @@ -7969,18 +7927,62 @@ " 1\n", " 0\n", " 0\n", - " 5.879865\n", - " 0.465164\n", - " 6.001499\n", - " 0.617923\n", - " 5.876376\n", - " 0.544286\n", - " 0.004557\n", - " 0.915138\n", - " 5.675189\n", - " 0.915135\n", - " 0.260538\n", - " 1.299582\n", + " 5.943305\n", + " 0.444352\n", + " 6.065740\n", + " 0.598042\n", + " 5.949132\n", + " 0.523503\n", + " -0.009082\n", + " 0.938780\n", + " 5.746909\n", + " 0.884158\n", + " 0.262632\n", + " 1.299802\n", + " 0.000000\n", + " \n", + " \n", + " Djuric\n", + " A\n", + " Verona\n", + " Avg\n", + " 1\n", + " 0\n", + " 83\n", + " 5.982239\n", + " 0.258992\n", + " 6.061640\n", + " 0.304934\n", + " 6.023319\n", + " 0.321768\n", + " -0.094447\n", + " 1.112615\n", + " 5.956068\n", + " 0.481284\n", + " 0.161987\n", + " 1.299765\n", + " 0.000000\n", + " \n", + " \n", + " Kallon\n", + " A\n", + " Verona\n", + " Avg\n", + " 1\n", + " 0\n", + " 0\n", + " 5.851457\n", + " 0.400450\n", + " 6.050725\n", + " 0.551621\n", + " 5.690024\n", + " 0.416988\n", + " 0.281836\n", + " 0.953169\n", + " 5.551819\n", + " 0.655438\n", + " 0.524593\n", + " 1.299838\n", " 0.000000\n", " \n", " \n", @@ -7991,18 +7993,18 @@ " 1\n", " 0\n", " 0\n", - " 5.644437\n", - " 0.345748\n", - " 5.742957\n", - " 0.413469\n", - " 5.520224\n", - " 0.365075\n", - " 0.248614\n", - " 0.991181\n", - " 5.455955\n", - " 0.567369\n", - " 0.362917\n", - " 1.299570\n", + " 5.675430\n", + " 0.331933\n", + " 5.783349\n", + " 0.401081\n", + " 5.554506\n", + " 0.348108\n", + " 0.253766\n", + " 1.031060\n", + " 5.487167\n", + " 0.536615\n", + " 0.393338\n", + " 1.299812\n", " 0.000000\n", " \n", " \n", @@ -8013,64 +8015,64 @@ "text/plain": [ " role team oppteam home starter vote% MV MV std \\\n", "player \n", - "Musso P Atalanta Avg 1 1 100 6.171178 0.427645 \n", - "Carnesecchi P Atalanta Avg 1 0 0 5.869667 0.502827 \n", - "Rossi F. P Atalanta Avg 1 0 0 5.960478 0.501686 \n", - "Zappacosta D Atalanta Avg 1 1 100 6.098510 0.555344 \n", - "Ruggeri D Atalanta Avg 1 1 100 6.087699 0.554154 \n", + "Rossi F. P Atalanta Avg 1 0 0 6.154525 0.429769 \n", + "Musso P Atalanta Avg 1 1 100 6.154517 0.430199 \n", + "Carnesecchi P Atalanta Avg 1 0 0 6.121501 0.449849 \n", + "Zappacosta D Atalanta Avg 1 1 83 6.106201 0.489143 \n", + "Ruggeri D Atalanta Avg 1 1 100 6.100199 0.525928 \n", "... ... ... ... ... ... ... ... ... \n", - "Henry A Verona Avg 1 0 0 5.855402 0.505158 \n", - "Djuric A Verona Avg 1 0 100 5.948880 0.348636 \n", - "Kallon A Verona Avg 1 0 0 5.837097 0.413428 \n", - "Cruz A Verona Avg 1 0 0 5.879865 0.465164 \n", - "Braaf A Verona Avg 1 0 0 5.644437 0.345748 \n", + "Henry A Verona Avg 1 0 16 5.828518 0.428970 \n", + "Cruz A Verona Avg 1 0 0 5.943305 0.444352 \n", + "Djuric A Verona Avg 1 0 83 5.982239 0.258992 \n", + "Kallon A Verona Avg 1 0 0 5.851457 0.400450 \n", + "Braaf A Verona Avg 1 0 0 5.675430 0.331933 \n", "\n", " FV FV std MV loc MV scale MV skewness \\\n", "player \n", - "Musso 5.716592 0.632592 6.120677 0.493384 0.075656 \n", - "Carnesecchi 3.425929 1.371020 6.030291 0.638892 -0.184642 \n", - "Rossi F. 3.407276 1.365965 5.941229 0.593570 0.024161 \n", - "Zappacosta 6.568691 0.979324 5.952041 0.611557 0.174813 \n", - "Ruggeri 6.456921 0.876787 6.054248 0.637605 0.038587 \n", + "Rossi F. 5.710340 0.608428 6.061085 0.478673 0.143872 \n", + "Musso 5.707846 0.608343 6.060265 0.478830 0.145062 \n", + "Carnesecchi 5.199359 0.664409 6.049285 0.510774 0.106278 \n", + "Zappacosta 6.430954 0.784539 6.056791 0.560162 0.064960 \n", + "Ruggeri 6.427830 0.829378 6.077005 0.608189 0.028110 \n", "... ... ... ... ... ... \n", - "Henry 6.219285 0.793892 5.594287 0.513562 0.367600 \n", - "Djuric 6.099661 0.472785 5.886502 0.392925 0.117059 \n", - "Kallon 6.047479 0.594338 5.662558 0.429064 0.295895 \n", - "Cruz 6.001499 0.617923 5.876376 0.544286 0.004557 \n", - "Braaf 5.742957 0.413469 5.520224 0.365075 0.248614 \n", + "Henry 6.086343 0.642557 5.631263 0.438163 0.326536 \n", + "Cruz 6.065740 0.598042 5.949132 0.523503 -0.009082 \n", + "Djuric 6.061640 0.304934 6.023319 0.321768 -0.094447 \n", + "Kallon 6.050725 0.551621 5.690024 0.416988 0.281836 \n", + "Braaf 5.783349 0.401081 5.554506 0.348108 0.253766 \n", "\n", " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", "player \n", - "Musso 1.078080 6.470728 0.603981 -0.807733 1.135469 \n", - "Carnesecchi 1.097941 4.448452 1.535484 -0.582005 0.860812 \n", - "Rossi F. 1.093842 4.423328 1.528818 -0.581675 0.862571 \n", - "Zappacosta 0.810975 5.694494 1.174959 0.514689 1.299705 \n", - "Ruggeri 0.828000 5.812500 1.175351 0.391089 1.299670 \n", + "Rossi F. 1.092386 6.415344 0.598177 -0.769786 1.148949 \n", + "Musso 1.092329 6.411938 0.599186 -0.767992 1.148581 \n", + "Carnesecchi 1.092119 5.646819 0.903720 -0.364365 1.027859 \n", + "Zappacosta 0.877353 5.846407 1.045597 0.398034 1.299841 \n", + "Ruggeri 0.853873 5.837552 1.127070 0.374861 1.299839 \n", "... ... ... ... ... ... \n", - "Henry 0.835252 5.435407 0.871782 0.604878 1.299692 \n", - "Djuric 0.988531 5.772749 0.649155 0.361159 1.299597 \n", - "Kallon 0.922908 5.502729 0.699002 0.535697 1.299641 \n", - "Cruz 0.915138 5.675189 0.915135 0.260538 1.299582 \n", - "Braaf 0.991181 5.455955 0.567369 0.362917 1.299570 \n", + "Henry 0.922681 5.474199 0.730840 0.569787 1.299849 \n", + "Cruz 0.938780 5.746909 0.884158 0.262632 1.299802 \n", + "Djuric 1.112615 5.956068 0.481284 0.161987 1.299765 \n", + "Kallon 0.953169 5.551819 0.655438 0.524593 1.299838 \n", + "Braaf 1.031060 5.487167 0.536615 0.393338 1.299812 \n", "\n", " Clean Sheet % \n", "player \n", - "Musso 58.570200 \n", - "Carnesecchi 1.164914 \n", - "Rossi F. 1.128720 \n", + "Rossi F. 56.114355 \n", + "Musso 56.005341 \n", + "Carnesecchi 27.208376 \n", "Zappacosta 0.000000 \n", "Ruggeri 0.000000 \n", "... ... \n", "Henry 0.000000 \n", + "Cruz 0.000000 \n", "Djuric 0.000000 \n", "Kallon 0.000000 \n", - "Cruz 0.000000 \n", "Braaf 0.000000 \n", "\n", "[539 rows x 19 columns]" ] }, - "execution_count": 45, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -8161,7 +8163,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 36, "id": "b47cbd63", "metadata": {}, "outputs": [], @@ -8261,7 +8263,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 37, "id": "4b9f5a7d", "metadata": {}, "outputs": [ @@ -8269,20 +8271,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "Osimhen: MV 6.52 ± 1.55; FV 8.32 + 5.10\n", - "Osimhen: MV 6.52 ± 1.55; FV 8.31 + 5.09\n" + "Osimhen: MV 6.47 ± 1.49; FV 7.95 + 4.15\n", + "Osimhen: MV 6.48 ± 1.46; FV 8.08 + 4.29\n" ] }, { "data": { "text/plain": [ - "[array([6.5154007 , 8.31434958]),\n", - " array([0.7731867, 2.543137 ], dtype=float32),\n", + "[array([6.48246781, 8.07706693]),\n", + " array([0.72848487, 2.14604 ], dtype=float32),\n", " [,\n", " ]]" ] }, - "execution_count": 55, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } diff --git a/7_lineup_simulation.ipynb b/7_lineup_simulation.ipynb index ef1796b..27462ed 100644 --- a/7_lineup_simulation.ipynb +++ b/7_lineup_simulation.ipynb @@ -20,17 +20,17 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "d3654c88", "metadata": {}, "outputs": [], "source": [ - "file = 'outputs/pred_matchday_4.xlsx'" + "file = 'outputs/pred_matchday_7.xlsx'" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "f89d6b70", "metadata": {}, "outputs": [], @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "6f61a1fa", "metadata": {}, "outputs": [ @@ -110,113 +110,113 @@ " \n", " \n", " \n", - " Rossi F.\n", + " Carnesecchi\n", " P\n", " Atalanta\n", - " Fiorentina\n", - " 0\n", - " 0.0\n", + " Juventus\n", " 1\n", - " 6.109952\n", - " 0.455623\n", - " 5.139983\n", - " 0.751770\n", - " 6.129853\n", - " 0.545903\n", - " -0.026930\n", - " 1.024186\n", - " 5.328891\n", - " 1.142012\n", - " -0.122005\n", - " 1.029078\n", - " 3.029286\n", + " 0.0\n", + " 5\n", + " 6.140590\n", + " 0.481707\n", + " 5.070139\n", + " 0.715923\n", + " 5.980216\n", + " 0.509892\n", + " 0.230396\n", + " 1.086084\n", + " 5.321455\n", + " 1.055452\n", + " -0.174796\n", + " 0.965320\n", + " 20.727640\n", " \n", " \n", " Musso\n", " P\n", " Atalanta\n", - " Fiorentina\n", - " 0\n", + " Juventus\n", + " 1\n", " 1.0\n", - " 80\n", - " 6.026820\n", - " 0.479838\n", - " 4.632784\n", - " 0.883422\n", - " 6.040918\n", - " 0.574122\n", - " -0.018150\n", - " 1.038445\n", - " 5.058631\n", - " 1.267127\n", - " -0.248430\n", - " 0.992984\n", - " 1.178538\n", + " 70\n", + " 6.171150\n", + " 0.480294\n", + " 5.038867\n", + " 0.684976\n", + " 5.986030\n", + " 0.494852\n", + " 0.272883\n", + " 1.084060\n", + " 5.255883\n", + " 1.019420\n", + " -0.156479\n", + " 0.983446\n", + " 28.833491\n", " \n", " \n", - " Carnesecchi\n", + " Rossi F.\n", " P\n", " Atalanta\n", - " Fiorentina\n", - " 0\n", + " Juventus\n", + " 1\n", " 0.0\n", - " 5\n", - " 5.988562\n", - " 0.492755\n", - " 4.077794\n", - " 1.066340\n", - " 6.002525\n", - " 0.589996\n", - " -0.017496\n", - " 1.046207\n", - " 4.783760\n", - " 1.400133\n", - " -0.389061\n", - " 0.954299\n", - " 0.944095\n", + " 1\n", + " 6.170296\n", + " 0.480470\n", + " 5.037872\n", + " 0.684438\n", + " 5.984473\n", + " 0.494652\n", + " 0.273999\n", + " 1.084374\n", + " 5.254371\n", + " 1.018776\n", + " -0.156209\n", + " 0.983780\n", + " 28.943959\n", " \n", " \n", " Zappacosta\n", " D\n", " Atalanta\n", - " Fiorentina\n", - " 0\n", + " Juventus\n", + " 1\n", " 1.0\n", " 90\n", - " 6.083625\n", - " 0.627924\n", - " 6.479160\n", - " 1.053932\n", - " 5.897724\n", - " 0.687691\n", - " 0.197360\n", - " 0.773252\n", - " 5.540676\n", - " 1.267551\n", - " 0.512369\n", - " 1.299510\n", + " 5.985259\n", + " 0.522062\n", + " 6.206951\n", + " 0.733274\n", + " 6.001576\n", + " 0.613546\n", + " -0.019559\n", + " 0.881605\n", + " 5.760596\n", + " 1.050439\n", + " 0.307981\n", + " 1.299815\n", " 0.000000\n", " \n", " \n", - " Zortea\n", + " Toloi\n", " D\n", " Atalanta\n", - " Fiorentina\n", - " 0\n", - " 0.0\n", - " 0\n", - " 6.150186\n", - " 0.516681\n", - " 6.476537\n", - " 0.757362\n", - " 6.067196\n", - " 0.583386\n", - " 0.104385\n", - " 0.850812\n", - " 5.875261\n", - " 0.978617\n", - " 0.433943\n", - " 1.299440\n", + " Juventus\n", + " 1\n", + " 1.0\n", + " 90\n", + " 6.002894\n", + " 0.499877\n", + " 6.196084\n", + " 0.699952\n", + " 6.035264\n", + " 0.591494\n", + " -0.040256\n", + " 0.892304\n", + " 5.804792\n", + " 1.025037\n", + " 0.278035\n", + " 1.299814\n", " 0.000000\n", " \n", " \n", @@ -242,181 +242,181 @@ " ...\n", " \n", " \n", - " Bonazzoli\n", - " A\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 0.4\n", - " 60\n", - " 6.194463\n", - " 0.573160\n", - " 6.719338\n", - " 1.030227\n", - " 5.917695\n", - " 0.593300\n", - " 0.338062\n", - " 0.807901\n", - " 5.607124\n", - " 1.010478\n", - " 0.712825\n", - " 1.299556\n", - " 0.000000\n", - " \n", - " \n", " Henry\n", " A\n", " Verona\n", - " Bologna\n", - " 1\n", - " 0.0\n", + " Torino\n", " 0\n", - " 5.948657\n", - " 0.576159\n", - " 6.411596\n", - " 0.883478\n", - " 5.582782\n", - " 0.562697\n", - " 0.465999\n", - " 0.808078\n", - " 5.444796\n", - " 0.848190\n", - " 0.732595\n", - " 1.299526\n", - " 0.000000\n", - " \n", - " \n", - " Kallon\n", - " A\n", - " Verona\n", - " Bologna\n", - " 1\n", - " 0.0\n", - " 0\n", - " 5.984714\n", - " 0.458801\n", - " 6.300039\n", - " 0.708241\n", - " 5.767212\n", - " 0.467892\n", - " 0.336912\n", - " 0.899963\n", - " 5.570446\n", - " 0.741041\n", - " 0.651962\n", - " 1.299474\n", + " 0.4\n", + " 60\n", + " 5.839920\n", + " 0.444240\n", + " 6.116677\n", + " 0.669289\n", + " 5.631952\n", + " 0.453545\n", + " 0.332464\n", + " 0.906913\n", + " 5.474079\n", + " 0.755754\n", + " 0.577176\n", + " 1.299852\n", " 0.000000\n", " \n", " \n", " Djuric\n", " A\n", " Verona\n", - " Bologna\n", - " 1\n", + " Torino\n", + " 0\n", " 0.0\n", - " 60\n", - " 6.158875\n", - " 0.357994\n", - " 6.288688\n", - " 0.468988\n", - " 6.140615\n", - " 0.418206\n", - " 0.032221\n", - " 0.990635\n", - " 5.922352\n", - " 0.611119\n", - " 0.424342\n", - " 1.299342\n", + " 0\n", + " 5.988754\n", + " 0.256611\n", + " 6.065000\n", + " 0.293257\n", + " 6.035156\n", + " 0.320372\n", + " -0.107045\n", + " 1.115607\n", + " 5.977599\n", + " 0.469125\n", + " 0.137929\n", + " 1.299758\n", + " 0.000000\n", + " \n", + " \n", + " Kallon\n", + " A\n", + " Verona\n", + " Torino\n", + " 0\n", + " 0.0\n", + " 0\n", + " 5.863674\n", + " 0.392202\n", + " 6.044829\n", + " 0.522801\n", + " 5.719528\n", + " 0.414042\n", + " 0.254175\n", + " 0.962003\n", + " 5.592772\n", + " 0.641898\n", + " 0.490306\n", + " 1.299833\n", + " 0.000000\n", + " \n", + " \n", + " Cruz\n", + " A\n", + " Verona\n", + " Torino\n", + " 0\n", + " 0.0\n", + " 15\n", + " 5.932667\n", + " 0.434699\n", + " 5.990185\n", + " 0.538253\n", + " 6.015219\n", + " 0.528602\n", + " -0.114888\n", + " 0.951150\n", + " 5.878494\n", + " 0.880338\n", + " 0.094197\n", + " 1.299773\n", " 0.000000\n", " \n", " \n", " Braaf\n", " A\n", " Verona\n", - " Bologna\n", - " 1\n", + " Torino\n", + " 0\n", " 0.0\n", " 0\n", - " 5.610724\n", - " 0.386826\n", - " 5.801877\n", - " 0.469637\n", - " 5.429425\n", - " 0.389900\n", - " 0.336936\n", - " 0.966595\n", - " 5.391262\n", - " 0.572295\n", - " 0.498442\n", - " 1.299333\n", + " 5.665697\n", + " 0.341006\n", + " 5.725323\n", + " 0.370040\n", + " 5.561785\n", + " 0.367506\n", + " 0.207320\n", + " 1.019125\n", + " 5.506973\n", + " 0.534618\n", + " 0.296589\n", + " 1.299793\n", " 0.000000\n", " \n", " \n", "\n", - "

535 rows × 19 columns

\n", + "

539 rows × 19 columns

\n", "" ], "text/plain": [ - " role team oppteam home starter vote% MV \\\n", - "player \n", - "Rossi F. P Atalanta Fiorentina 0 0.0 1 6.109952 \n", - "Musso P Atalanta Fiorentina 0 1.0 80 6.026820 \n", - "Carnesecchi P Atalanta Fiorentina 0 0.0 5 5.988562 \n", - "Zappacosta D Atalanta Fiorentina 0 1.0 90 6.083625 \n", - "Zortea D Atalanta Fiorentina 0 0.0 0 6.150186 \n", - "... ... ... ... ... ... ... ... \n", - "Bonazzoli A Verona Bologna 1 0.4 60 6.194463 \n", - "Henry A Verona Bologna 1 0.0 0 5.948657 \n", - "Kallon A Verona Bologna 1 0.0 0 5.984714 \n", - "Djuric A Verona Bologna 1 0.0 60 6.158875 \n", - "Braaf A Verona Bologna 1 0.0 0 5.610724 \n", + " role team oppteam home starter vote% MV \\\n", + "player \n", + "Carnesecchi P Atalanta Juventus 1 0.0 5 6.140590 \n", + "Musso P Atalanta Juventus 1 1.0 70 6.171150 \n", + "Rossi F. P Atalanta Juventus 1 0.0 1 6.170296 \n", + "Zappacosta D Atalanta Juventus 1 1.0 90 5.985259 \n", + "Toloi D Atalanta Juventus 1 1.0 90 6.002894 \n", + "... ... ... ... ... ... ... ... \n", + "Henry A Verona Torino 0 0.4 60 5.839920 \n", + "Djuric A Verona Torino 0 0.0 0 5.988754 \n", + "Kallon A Verona Torino 0 0.0 0 5.863674 \n", + "Cruz A Verona Torino 0 0.0 15 5.932667 \n", + "Braaf A Verona Torino 0 0.0 0 5.665697 \n", "\n", " MV std FV FV std MV loc MV scale MV skewness \\\n", "player \n", - "Rossi F. 0.455623 5.139983 0.751770 6.129853 0.545903 -0.026930 \n", - "Musso 0.479838 4.632784 0.883422 6.040918 0.574122 -0.018150 \n", - "Carnesecchi 0.492755 4.077794 1.066340 6.002525 0.589996 -0.017496 \n", - "Zappacosta 0.627924 6.479160 1.053932 5.897724 0.687691 0.197360 \n", - "Zortea 0.516681 6.476537 0.757362 6.067196 0.583386 0.104385 \n", + "Carnesecchi 0.481707 5.070139 0.715923 5.980216 0.509892 0.230396 \n", + "Musso 0.480294 5.038867 0.684976 5.986030 0.494852 0.272883 \n", + "Rossi F. 0.480470 5.037872 0.684438 5.984473 0.494652 0.273999 \n", + "Zappacosta 0.522062 6.206951 0.733274 6.001576 0.613546 -0.019559 \n", + "Toloi 0.499877 6.196084 0.699952 6.035264 0.591494 -0.040256 \n", "... ... ... ... ... ... ... \n", - "Bonazzoli 0.573160 6.719338 1.030227 5.917695 0.593300 0.338062 \n", - "Henry 0.576159 6.411596 0.883478 5.582782 0.562697 0.465999 \n", - "Kallon 0.458801 6.300039 0.708241 5.767212 0.467892 0.336912 \n", - "Djuric 0.357994 6.288688 0.468988 6.140615 0.418206 0.032221 \n", - "Braaf 0.386826 5.801877 0.469637 5.429425 0.389900 0.336936 \n", + "Henry 0.444240 6.116677 0.669289 5.631952 0.453545 0.332464 \n", + "Djuric 0.256611 6.065000 0.293257 6.035156 0.320372 -0.107045 \n", + "Kallon 0.392202 6.044829 0.522801 5.719528 0.414042 0.254175 \n", + "Cruz 0.434699 5.990185 0.538253 6.015219 0.528602 -0.114888 \n", + "Braaf 0.341006 5.725323 0.370040 5.561785 0.367506 0.207320 \n", "\n", " MV tailweight FV loc FV scale FV skewness FV tailweight \\\n", "player \n", - "Rossi F. 1.024186 5.328891 1.142012 -0.122005 1.029078 \n", - "Musso 1.038445 5.058631 1.267127 -0.248430 0.992984 \n", - "Carnesecchi 1.046207 4.783760 1.400133 -0.389061 0.954299 \n", - "Zappacosta 0.773252 5.540676 1.267551 0.512369 1.299510 \n", - "Zortea 0.850812 5.875261 0.978617 0.433943 1.299440 \n", + "Carnesecchi 1.086084 5.321455 1.055452 -0.174796 0.965320 \n", + "Musso 1.084060 5.255883 1.019420 -0.156479 0.983446 \n", + "Rossi F. 1.084374 5.254371 1.018776 -0.156209 0.983780 \n", + "Zappacosta 0.881605 5.760596 1.050439 0.307981 1.299815 \n", + "Toloi 0.892304 5.804792 1.025037 0.278035 1.299814 \n", "... ... ... ... ... ... \n", - "Bonazzoli 0.807901 5.607124 1.010478 0.712825 1.299556 \n", - "Henry 0.808078 5.444796 0.848190 0.732595 1.299526 \n", - "Kallon 0.899963 5.570446 0.741041 0.651962 1.299474 \n", - "Djuric 0.990635 5.922352 0.611119 0.424342 1.299342 \n", - "Braaf 0.966595 5.391262 0.572295 0.498442 1.299333 \n", + "Henry 0.906913 5.474079 0.755754 0.577176 1.299852 \n", + "Djuric 1.115607 5.977599 0.469125 0.137929 1.299758 \n", + "Kallon 0.962003 5.592772 0.641898 0.490306 1.299833 \n", + "Cruz 0.951150 5.878494 0.880338 0.094197 1.299773 \n", + "Braaf 1.019125 5.506973 0.534618 0.296589 1.299793 \n", "\n", " Clean Sheet % \n", "player \n", - "Rossi F. 3.029286 \n", - "Musso 1.178538 \n", - "Carnesecchi 0.944095 \n", + "Carnesecchi 20.727640 \n", + "Musso 28.833491 \n", + "Rossi F. 28.943959 \n", "Zappacosta 0.000000 \n", - "Zortea 0.000000 \n", + "Toloi 0.000000 \n", "... ... \n", - "Bonazzoli 0.000000 \n", "Henry 0.000000 \n", - "Kallon 0.000000 \n", "Djuric 0.000000 \n", + "Kallon 0.000000 \n", + "Cruz 0.000000 \n", "Braaf 0.000000 \n", "\n", - "[535 rows x 19 columns]" + "[539 rows x 19 columns]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -427,7 +427,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "aa1c6af5", "metadata": {}, "outputs": [], @@ -454,7 +454,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "d8456c70", "metadata": {}, "outputs": [], @@ -583,7 +583,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "852ef39e", "metadata": {}, "outputs": [], @@ -661,7 +661,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "squad = ['Musso',\n", + " 'Zappacosta',\n", + " 'Pavard',\n", + " 'Carlos Augusto',\n", + " 'Lazaro',\n", + " 'Radonjic',\n", + " 'Barella',\n", + " 'Zielinski',\n", + " 'Lauriente\\'',\n", + " 'Rafael Leao',\n", + " 'Lookman']\n", + "\n", + "s = simulate_lineup(squad, MOD = True, CS = True)\n", + "\n", + "plot_lineup(squad, config_433_classic)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "fc4be108", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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zw5q#!z3v)6A)mMDI)XmE2=nO_k{~fbtu&A?M}X^LP0cj-c%y*LbuFnZMq;~E!P*>EJo@vcCf@k zE;ocec$p*O1!=WB{S#qkz!s+#-zdAQ~Fx{85yskceZgUj!+wJFl(!_yT=^HtY2z8QmcH=qcQI?=*$m(zEk< z$+Agn^uIz+@bCMbOz4ckb@h07S@PB-`?mPf1=`Lu+`Oen8Ufb@mIldh&q4;at=~QH z=F8)`++htN3-a9)Z&03LERtavS)x`rvl%V3pFhXBenw91W8#_2;mY3G=8#f(YwN8t zzYr+Bpq!;^dXWwCbj15CgE1@Ai3t{iG9_H)qL8y@S$VZ^ zF>z^SQfPUv=@-e&V%z3?xcFMH^3&mHzZ0s8C$PDIU5S74B-TY*F`XwR8LJE@u&`us zv9K;+9sXq??O=ZoYJbl})8j7G*$8cX9v&cOVE#!yxQ+!3avI}$YtUli1hsYMzKZ_y z@P(0LrHY&2f(p=$7~?_>Y%H|h>*nBe$K1i;&T-#L5Eth+1ujy-!NQ`#xcCWZ0T=)E z#eWWQ>?9<_E>2wnV8^8cu;ZTtA;1m!dlJspQ0P5pV26Vb-s5J&7uy~u049Cv3>Mbe zKL^2LR6H2P`JRU@^uTsMd>7s-OUUqm3G^PBK#cOS6W}{;0+@WtKW9Ml^4L-Mj~fNk h_xN)Z?}5Mm8HYU)RYg2}biY&JM+Mw~xe4^&{tv5CAS3_) literal 0 HcmV?d00001 diff --git a/fbref_data/keepers_players.csv b/fbref_data/keepers_players.csv index b458798..9d7b52f 100644 --- a/fbref_data/keepers_players.csv +++ b/fbref_data/keepers_players.csv @@ -1,29 +1,30 @@ player,nationality,position,team,age,birth_year,gk_games,gk_games_starts,gk_minutes,gk_goals_against,gk_goals_against_per90,gk_shots_on_target_against,gk_saves,gk_save_pct,gk_wins,gk_ties,gk_losses,gk_clean_sheets,gk_clean_sheets_pct,gk_pens_att,gk_pens_allowed,gk_pens_saved,gk_pens_missed,minutes_90s,gk_free_kick_goals_against,gk_corner_kick_goals_against,gk_own_goals_against,gk_psxg,gk_psnpxg_per_shot_on_target_against,gk_psxg_net,gk_psxg_net_per90,gk_passes_completed_launched,gk_passes_launched,gk_passes_pct_launched,gk_passes,gk_passes_throws,gk_pct_passes_launched,gk_passes_length_avg,gk_goal_kicks,gk_pct_goal_kicks_launched,gk_goal_kick_length_avg,gk_crosses,gk_crosses_stopped,gk_crosses_stopped_pct,gk_def_actions_outside_pen_area,gk_def_actions_outside_pen_area_per90,gk_avg_distance_def_actions -Etrit Berisha,al ALB,GK,Empoli,34-195,1989,2.0,2.0,180.0,9.0,4.5,14.0,5.0,42.9,0.0,0.0,2.0,0.0,0.0,2.0,1.0,1.0,0.0,2.0,0.0,2.0,1.0,5.9,0.28,-2.1,-1.06,3.0,14.0,21.4,54.0,13.0,22.2,27.5,9.0,22.2,27.0,23.0,1.0,4.3,2.0,1.0,15.7 -Elia Caprile,it ITA,GK,Empoli,22-027,2001,1.0,1.0,90.0,1.0,1.0,4.0,3.0,75.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.4,0.11,-0.6,-0.57,4.0,20.0,20.0,37.0,9.0,48.6,42.6,4.0,50.0,50.3,10.0,2.0,20.0,2.0,2.0,12.4 -Marco Carnesecchi,it ITA,GK,Atalanta,23-082,2000,1.0,1.0,90.0,3.0,3.0,8.0,5.0,62.5,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.9,0.24,-1.1,-1.06,3.0,15.0,20.0,28.0,6.0,35.7,36.8,6.0,83.3,69.2,13.0,1.0,7.7,0.0,0.0,14.5 -Michele Cerofolini,it ITA,GK,Frosinone,24-260,1999,1.0,1.0,90.0,1.0,1.0,6.0,5.0,83.3,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.16,0.0,-0.04,2.0,18.0,11.1,27.0,2.0,55.6,38.3,5.0,60.0,45.8,18.0,0.0,0.0,0.0,0.0,0.0 -Oliver Christensen,dk DEN,GK,Fiorentina,24-183,1999,2.0,2.0,180.0,6.0,3.0,13.0,7.0,61.5,0.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,3.2,0.18,-2.8,-1.38,14.0,31.0,45.2,78.0,7.0,33.3,33.2,8.0,62.5,49.4,15.0,0.0,0.0,3.0,1.5,22.0 -Andrea Consigli,it ITA,GK,Sassuolo,36-237,1987,3.0,3.0,270.0,5.0,1.67,12.0,7.0,66.7,1.0,0.0,2.0,0.0,0.0,2.0,1.0,0.0,1.0,3.0,0.0,1.0,0.0,3.3,0.19,-1.7,-0.58,11.0,46.0,23.9,95.0,10.0,38.9,37.1,34.0,26.5,28.1,46.0,2.0,4.3,3.0,1.0,14.5 -Alessio Cragno,it ITA,GK,Sassuolo,29-085,1994,1.0,1.0,90.0,4.0,4.0,6.0,2.0,50.0,0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,2.8,0.3,-1.2,-1.21,5.0,15.0,33.3,24.0,3.0,50.0,37.1,9.0,33.3,34.6,9.0,0.0,0.0,7.0,7.0,28.9 -Michele Di Gregorio,it ITA,GK,Monza,26-056,1997,3.0,3.0,270.0,5.0,1.67,17.0,12.0,70.6,1.0,0.0,2.0,1.0,33.3,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0,4.2,0.25,-0.8,-0.25,7.0,32.0,21.9,111.0,16.0,20.7,28.7,22.0,40.9,40.3,45.0,2.0,4.4,2.0,0.67,11.7 -Wladimiro Falcone,it ITA,GK,Lecce,28-162,1995,4.0,4.0,360.0,4.0,1.0,17.0,13.0,76.5,2.0,2.0,0.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,4.6,0.27,0.6,0.15,20.0,52.0,38.5,78.0,18.0,38.5,31.0,42.0,52.4,38.7,54.0,2.0,3.7,2.0,0.5,10.3 -Mike Maignan,fr FRA,GK,Milan,28-080,1995,4.0,4.0,360.0,7.0,1.75,15.0,8.0,60.0,3.0,0.0,1.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.5,0.24,-2.5,-0.64,21.0,58.0,36.2,198.0,26.0,22.2,29.2,23.0,60.9,47.0,52.0,12.0,23.1,3.0,0.75,9.8 -Josep Martinez,es ESP,GK,Genoa,25-117,1998,4.0,4.0,360.0,7.0,1.75,14.0,7.0,50.0,1.0,1.0,2.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,3.7,0.27,-3.3,-0.82,38.0,78.0,48.7,125.0,10.0,45.6,39.7,22.0,95.5,62.5,75.0,8.0,10.7,2.0,0.5,9.3 -Alex Meret,it ITA,GK,Napoli,26-183,1997,4.0,4.0,360.0,5.0,1.25,7.0,2.0,42.9,2.0,1.0,1.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,0.0,3.4,0.37,-1.6,-0.4,3.0,12.0,25.0,86.0,8.0,14.0,24.7,11.0,0.0,20.4,27.0,1.0,3.7,7.0,1.75,18.2 -Vanja Milinković-Savić,rs SRB,GK,Torino,26-213,1997,4.0,4.0,360.0,4.0,1.0,15.0,11.0,86.7,2.0,1.0,1.0,3.0,75.0,2.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,4.6,0.18,0.6,0.16,29.0,79.0,36.7,117.0,23.0,44.4,38.1,36.0,75.0,61.3,33.0,3.0,9.1,5.0,1.25,15.8 -Lorenzo Montipò,it ITA,GK,Hellas Verona,27-213,1996,4.0,4.0,360.0,4.0,1.0,22.0,18.0,86.4,2.0,1.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.9,0.19,0.9,0.22,35.0,93.0,37.6,109.0,8.0,56.9,42.9,35.0,88.6,62.7,54.0,1.0,1.9,8.0,2.0,19.4 -Juan Musso,ar ARG,GK,Atalanta,29-138,1994,3.0,3.0,270.0,2.0,0.67,10.0,8.0,80.0,2.0,0.0,1.0,2.0,66.7,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0,2.1,0.21,0.1,0.04,11.0,34.0,32.4,88.0,18.0,27.3,29.3,18.0,55.6,46.1,28.0,2.0,7.1,8.0,2.67,22.0 -Guillermo Ochoa,mx MEX,GK,Salernitana,38-070,1985,4.0,4.0,360.0,8.0,2.0,18.0,10.0,61.1,0.0,2.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,0.0,4.7,0.21,-3.3,-0.82,13.0,55.0,23.6,89.0,14.0,40.4,35.9,35.0,54.3,43.6,63.0,4.0,6.3,1.0,0.25,7.8 -Rui Patrício,pt POR,GK,Roma,35-218,1988,4.0,4.0,360.0,6.0,1.5,11.0,5.0,54.5,1.0,1.0,2.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.0,0.28,-2.0,-0.5,10.0,18.0,55.6,76.0,9.0,21.1,29.3,17.0,11.8,22.1,34.0,2.0,5.9,2.0,0.5,12.2 -Mattia Perin,it ITA,GK,Juventus,30-315,1992,2.0,2.0,180.0,1.0,0.5,4.0,3.0,75.0,1.0,1.0,0.0,1.0,50.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.2,0.3,0.2,0.09,5.0,13.0,38.5,42.0,9.0,28.6,29.1,11.0,9.1,18.9,26.0,2.0,7.7,2.0,1.0,15.0 -Samuele Perisan,it ITA,GK,Empoli,26-031,1997,1.0,1.0,90.0,2.0,2.0,5.0,3.0,60.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.7,0.14,-1.3,-1.32,1.0,8.0,12.5,22.0,8.0,27.3,26.3,12.0,16.7,29.6,18.0,0.0,0.0,1.0,1.0,21.0 -Ivan Provedel,it ITA,GK,Lazio,29-188,1994,4.0,4.0,360.0,7.0,1.75,21.0,14.0,66.7,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.7,0.18,-3.3,-0.83,6.0,16.0,37.5,119.0,14.0,10.9,26.4,15.0,20.0,27.9,48.0,2.0,4.2,6.0,1.5,15.7 -Boris Radunović,rs SRB,GK,Cagliari,27-118,1996,4.0,4.0,360.0,4.0,1.0,13.0,9.0,69.2,0.0,2.0,2.0,2.0,50.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,4.1,0.33,0.1,0.03,24.0,54.0,44.4,76.0,18.0,36.8,37.8,40.0,65.0,50.0,62.0,4.0,6.5,3.0,0.75,12.5 -Marco Silvestri,it ITA,GK,Udinese,32-203,1991,4.0,4.0,360.0,4.0,1.0,10.0,6.0,70.0,0.0,3.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,3.9,0.29,-0.1,-0.02,11.0,34.0,32.4,94.0,14.0,25.5,29.7,32.0,31.3,35.4,49.0,0.0,0.0,3.0,0.75,14.0 -Łukasz Skorupski,pl POL,GK,Bologna,32-139,1991,4.0,4.0,360.0,4.0,1.0,10.0,6.0,60.0,1.0,2.0,1.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.2,0.32,-0.8,-0.21,17.0,45.0,37.8,106.0,17.0,35.8,32.1,22.0,31.8,34.2,57.0,2.0,3.5,2.0,0.5,11.5 -Yann Sommer,ch SUI,GK,Inter,34-278,1988,4.0,4.0,360.0,1.0,0.25,8.0,7.0,87.5,4.0,0.0,0.0,3.0,75.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,1.6,0.2,0.6,0.16,24.0,41.0,58.5,112.0,19.0,31.3,30.8,29.0,20.7,28.3,41.0,2.0,4.9,0.0,0.0,6.5 -Alessandro Sorrentino,it ITA,GK,Monza,21-171,2002,1.0,1.0,90.0,1.0,1.0,3.0,2.0,100.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,1.6,0.22,0.6,0.65,1.0,2.0,50.0,25.0,8.0,8.0,21.0,2.0,0.0,23.0,8.0,1.0,12.5,0.0,0.0,9.0 -Wojciech Szczęsny,pl POL,GK,Juventus,33-156,1990,2.0,2.0,180.0,1.0,0.5,10.0,9.0,90.0,2.0,0.0,0.0,1.0,50.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,2.3,0.24,1.3,0.67,13.0,28.0,46.4,60.0,10.0,40.0,33.1,6.0,66.7,52.0,33.0,1.0,3.0,0.0,0.0,9.6 -Pietro Terracciano,it ITA,GK,Fiorentina,33-197,1990,2.0,2.0,180.0,3.0,1.5,6.0,3.0,50.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,1.0,0.17,-2.0,-0.98,13.0,20.0,65.0,85.0,10.0,22.4,33.1,9.0,11.1,25.0,16.0,1.0,6.3,1.0,0.5,13.7 -Stefano Turati,it ITA,GK,Frosinone,22-016,2001,3.0,3.0,270.0,5.0,1.67,21.0,16.0,76.2,1.0,1.0,1.0,1.0,33.3,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,5.5,0.26,0.5,0.16,7.0,29.0,24.1,96.0,23.0,22.9,26.0,13.0,53.8,41.7,33.0,2.0,6.1,3.0,1.0,16.3 +Etrit Berisha,al ALB,GK,Empoli,34-204,1989,4.0,4.0,360.0,10.0,2.5,21.0,11.0,57.1,1.0,0.0,3.0,1.0,25.0,2.0,1.0,1.0,0.0,4.0,0.0,3.0,1.0,7.2,0.25,-1.8,-0.45,11.0,48.0,22.9,106.0,22.0,32.1,32.1,24.0,58.3,44.0,50.0,2.0,4.0,3.0,0.75,12.7 +Elia Caprile,it ITA,GK,Empoli,22-036,2001,1.0,1.0,90.0,1.0,1.0,4.0,3.0,75.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.4,0.11,-0.6,-0.57,4.0,20.0,20.0,37.0,9.0,48.6,42.6,4.0,50.0,50.3,10.0,2.0,20.0,2.0,2.0,12.4 +Marco Carnesecchi,it ITA,GK,Atalanta,23-091,2000,2.0,2.0,180.0,3.0,1.5,10.0,7.0,70.0,1.0,0.0,1.0,1.0,50.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,2.1,0.21,-0.9,-0.44,8.0,35.0,22.9,56.0,13.0,41.1,38.2,15.0,80.0,60.7,30.0,3.0,10.0,0.0,0.0,11.2 +Michele Cerofolini,it ITA,GK,Frosinone,24-269,1999,1.0,1.0,90.0,1.0,1.0,6.0,5.0,83.3,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.16,0.0,-0.04,2.0,18.0,11.1,27.0,2.0,55.6,38.3,5.0,60.0,45.8,18.0,0.0,0.0,0.0,0.0,0.0 +Oliver Christensen,dk DEN,GK,Fiorentina,24-192,1999,2.0,2.0,180.0,6.0,3.0,13.0,7.0,61.5,0.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,3.2,0.18,-2.8,-1.38,14.0,31.0,45.2,78.0,7.0,33.3,33.2,8.0,62.5,49.4,15.0,0.0,0.0,3.0,1.5,22.0 +Andrea Consigli,it ITA,GK,Sassuolo,36-246,1987,4.0,4.0,360.0,6.0,1.5,15.0,9.0,66.7,2.0,0.0,2.0,0.0,0.0,2.0,1.0,0.0,1.0,4.0,0.0,1.0,0.0,4.1,0.21,-1.9,-0.47,18.0,69.0,26.1,127.0,14.0,45.7,39.4,42.0,26.2,28.3,73.0,4.0,5.5,3.0,0.75,13.1 +Alessio Cragno,it ITA,GK,Sassuolo,29-094,1994,2.0,2.0,180.0,6.0,3.0,8.0,3.0,37.5,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,0.0,1.0,1.0,3.3,0.3,-1.7,-0.85,10.0,32.0,31.3,47.0,3.0,57.4,41.2,19.0,26.3,29.4,26.0,0.0,0.0,7.0,3.5,28.9 +Michele Di Gregorio,it ITA,GK,Monza,26-065,1997,5.0,5.0,450.0,6.0,1.2,23.0,17.0,78.3,1.0,2.0,2.0,2.0,40.0,1.0,1.0,0.0,0.0,5.0,0.0,1.0,0.0,6.0,0.22,0.0,-0.01,17.0,61.0,27.9,173.0,29.0,24.9,30.4,34.0,52.9,47.5,73.0,2.0,2.7,2.0,0.4,10.5 +Wladimiro Falcone,it ITA,GK,Lecce,28-171,1995,6.0,6.0,540.0,5.0,0.83,23.0,18.0,78.3,3.0,2.0,1.0,2.0,33.3,0.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0,5.9,0.26,0.9,0.15,24.0,67.0,35.8,121.0,31.0,33.9,30.9,55.0,47.3,36.3,80.0,3.0,3.8,3.0,0.5,9.6 +Mike Maignan,fr FRA,GK,Milan,28-089,1995,4.0,4.0,360.0,7.0,1.75,15.0,8.0,60.0,3.0,0.0,1.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.5,0.24,-2.5,-0.64,21.0,58.0,36.2,198.0,26.0,22.2,29.2,23.0,60.9,47.0,52.0,12.0,23.1,3.0,0.75,9.8 +Josep Martinez,es ESP,GK,Genoa,25-126,1998,6.0,6.0,540.0,9.0,1.5,20.0,11.0,55.0,2.0,1.0,3.0,1.0,16.7,0.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0,5.3,0.27,-3.7,-0.62,51.0,112.0,45.5,179.0,14.0,43.0,39.1,37.0,94.6,62.1,113.0,12.0,10.6,2.0,0.33,8.5 +Alex Meret,it ITA,GK,Napoli,26-192,1997,6.0,6.0,540.0,6.0,1.0,12.0,6.0,58.3,3.0,2.0,1.0,2.0,33.3,1.0,1.0,0.0,0.0,6.0,0.0,2.0,0.0,4.7,0.32,-1.3,-0.22,3.0,14.0,21.4,128.0,13.0,10.9,24.1,21.0,0.0,20.5,53.0,1.0,1.9,8.0,1.33,17.2 +Vanja Milinković-Savić,rs SRB,GK,Torino,26-222,1997,6.0,6.0,540.0,7.0,1.17,21.0,14.0,76.2,2.0,2.0,2.0,3.0,50.0,2.0,2.0,0.0,0.0,6.0,0.0,0.0,0.0,5.8,0.18,-1.2,-0.2,42.0,117.0,35.9,193.0,37.0,39.9,35.6,50.0,80.0,62.9,47.0,4.0,8.5,9.0,1.5,17.5 +Lorenzo Montipò,it ITA,GK,Hellas Verona,27-222,1996,6.0,6.0,540.0,6.0,1.0,28.0,22.0,82.1,2.0,1.0,3.0,2.0,33.3,1.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,6.7,0.21,0.7,0.11,55.0,156.0,35.3,183.0,16.0,62.3,45.2,50.0,84.0,61.5,72.0,1.0,1.4,12.0,2.0,20.0 +Juan Musso,ar ARG,GK,Atalanta,29-147,1994,4.0,4.0,360.0,2.0,0.5,10.0,8.0,80.0,3.0,0.0,1.0,3.0,75.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,2.1,0.21,0.1,0.03,14.0,48.0,29.2,119.0,25.0,25.2,29.0,28.0,64.3,48.9,43.0,4.0,9.3,12.0,3.0,19.9 +Guillermo Ochoa,mx MEX,GK,Salernitana,38-079,1985,6.0,6.0,540.0,10.0,1.67,27.0,17.0,66.7,0.0,3.0,3.0,0.0,0.0,1.0,1.0,0.0,0.0,6.0,0.0,3.0,0.0,6.8,0.22,-3.2,-0.53,20.0,85.0,23.5,160.0,22.0,39.4,35.6,47.0,46.8,39.9,88.0,4.0,4.5,3.0,0.5,13.5 +Rui Patrício,pt POR,GK,Roma,35-227,1988,6.0,6.0,540.0,11.0,1.83,19.0,8.0,47.4,1.0,2.0,3.0,1.0,16.7,1.0,1.0,0.0,0.0,6.0,0.0,1.0,0.0,7.0,0.32,-4.0,-0.67,12.0,27.0,44.4,117.0,18.0,17.9,27.5,31.0,19.4,24.2,62.0,2.0,3.2,3.0,0.5,13.7 +Mattia Perin,it ITA,GK,Juventus,30-324,1992,2.0,2.0,180.0,1.0,0.5,4.0,3.0,75.0,1.0,1.0,0.0,1.0,50.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.2,0.3,0.2,0.09,5.0,13.0,38.5,42.0,9.0,28.6,29.1,11.0,9.1,18.9,26.0,2.0,7.7,2.0,1.0,15.0 +Samuele Perisan,it ITA,GK,Empoli,26-040,1997,1.0,1.0,90.0,2.0,2.0,5.0,3.0,60.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.7,0.14,-1.3,-1.32,1.0,8.0,12.5,22.0,8.0,27.3,26.3,12.0,16.7,29.6,18.0,0.0,0.0,1.0,1.0,21.0 +Ivan Provedel,it ITA,GK,Lazio,29-197,1994,6.0,6.0,540.0,8.0,1.33,27.0,19.0,70.4,2.0,1.0,3.0,1.0,16.7,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,5.4,0.2,-2.6,-0.43,13.0,36.0,36.1,171.0,19.0,16.4,28.8,29.0,27.6,32.3,63.0,3.0,4.8,7.0,1.17,16.0 +Boris Radunović,rs SRB,GK,Cagliari,27-127,1996,6.0,6.0,540.0,9.0,1.5,25.0,16.0,64.0,0.0,2.0,4.0,2.0,33.3,1.0,0.0,0.0,1.0,6.0,0.0,1.0,0.0,8.7,0.36,-0.3,-0.04,33.0,80.0,41.3,124.0,23.0,39.5,38.5,57.0,54.4,45.1,87.0,5.0,5.7,4.0,0.67,11.9 +Marco Silvestri,it ITA,GK,Udinese,32-212,1991,6.0,6.0,540.0,10.0,1.67,22.0,12.0,63.6,0.0,3.0,3.0,2.0,33.3,2.0,2.0,0.0,0.0,6.0,0.0,0.0,0.0,10.1,0.37,0.1,0.02,19.0,50.0,38.0,132.0,23.0,28.8,30.2,45.0,26.7,32.8,69.0,1.0,1.4,3.0,0.5,13.6 +Łukasz Skorupski,pl POL,GK,Bologna,32-148,1991,6.0,6.0,540.0,4.0,0.67,17.0,13.0,76.5,1.0,4.0,1.0,3.0,50.0,1.0,0.0,0.0,1.0,6.0,0.0,0.0,0.0,4.2,0.25,0.2,0.04,28.0,60.0,46.7,159.0,25.0,31.4,31.1,34.0,29.4,33.6,89.0,3.0,3.4,2.0,0.33,10.3 +Yann Sommer,ch SUI,GK,Inter,34-287,1988,6.0,6.0,540.0,3.0,0.5,15.0,12.0,80.0,5.0,0.0,1.0,4.0,66.7,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,2.9,0.19,-0.1,-0.02,31.0,58.0,53.4,176.0,26.0,28.4,29.7,39.0,20.5,27.3,59.0,5.0,8.5,2.0,0.33,9.6 +Alessandro Sorrentino,it ITA,GK,Monza,21-180,2002,1.0,1.0,90.0,1.0,1.0,3.0,2.0,100.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,1.6,0.22,0.6,0.65,1.0,2.0,50.0,25.0,8.0,8.0,21.0,2.0,0.0,23.0,8.0,1.0,12.5,0.0,0.0,9.0 +Marco Sportiello,it ITA,GK,Milan,31-143,1992,2.0,2.0,180.0,1.0,0.5,8.0,7.0,87.5,2.0,0.0,0.0,1.0,50.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.3,0.16,0.3,0.14,5.0,15.0,33.3,69.0,13.0,21.7,28.0,2.0,0.0,28.5,28.0,2.0,7.1,2.0,1.0,13.2 +Wojciech Szczęsny,pl POL,GK,Juventus,33-165,1990,4.0,4.0,360.0,5.0,1.25,17.0,13.0,70.6,3.0,0.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,1.0,3.2,0.23,-0.8,-0.21,27.0,54.0,50.0,117.0,17.0,39.3,33.2,16.0,50.0,45.8,59.0,1.0,1.7,1.0,0.25,8.5 +Pietro Terracciano,it ITA,GK,Fiorentina,33-206,1990,4.0,4.0,360.0,4.0,1.0,17.0,13.0,76.5,3.0,1.0,0.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,4.1,0.24,0.1,0.03,28.0,57.0,49.1,151.0,14.0,31.1,34.7,22.0,45.5,38.3,44.0,3.0,6.8,1.0,0.25,10.2 +Stefano Turati,it ITA,GK,Frosinone,22-025,2001,5.0,5.0,450.0,7.0,1.4,33.0,26.0,78.8,1.0,3.0,1.0,1.0,20.0,0.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0,8.2,0.25,1.2,0.23,14.0,53.0,26.4,175.0,33.0,25.1,26.9,16.0,56.3,43.5,67.0,2.0,3.0,3.0,0.6,13.4 diff --git a/fbref_data/outfield_players.csv b/fbref_data/outfield_players.csv index 97b92ca..dd5e348 100644 --- a/fbref_data/outfield_players.csv +++ b/fbref_data/outfield_players.csv @@ -1,430 +1,459 @@ player,nationality,position,team,age,birth_year,games,games_starts,minutes,goals,assists,pens_made,pens_att,cards_yellow,cards_red,goals_per90,assists_per90,goals_assists_per90,goals_pens_per90,goals_assists_pens_per90,xg,npxg,xg_per90,npxg_per90,minutes_90s,shots_on_target,shots_free_kicks,shots_on_target_pct,shots_on_target_per90,goals_per_shot,goals_per_shot_on_target,npxg_per_shot,xg_net,npxg_net,passes_completed,passes,passes_pct,passes_total_distance,passes_progressive_distance,passes_completed_short,passes_short,passes_pct_short,passes_completed_medium,passes_medium,passes_pct_medium,passes_completed_long,passes_long,passes_pct_long,assisted_shots,passes_into_final_third,passes_into_penalty_area,crosses_into_penalty_area,progressive_passes,passes_live,passes_dead,passes_free_kicks,through_balls,passes_switches,crosses,corner_kicks,corner_kicks_in,corner_kicks_out,corner_kicks_straight,throw_ins,passes_offsides,passes_blocked,sca,sca_per90,sca_passes_live,sca_passes_dead,sca_shots,sca_fouled,gca,gca_per90,gca_passes_live,gca_passes_dead,gca_shots,gca_fouled,gca_defense,tackles,tackles_won,tackles_def_3rd,tackles_mid_3rd,tackles_att_3rd,blocks,blocked_shots,blocked_passes,interceptions,clearances,errors,touches,touches_def_pen_area,touches_def_3rd,touches_mid_3rd,touches_att_3rd,touches_att_pen_area,touches_live_ball,carries,progressive_carries,carries_into_final_third,carries_into_penalty_area,passes_received,miscontrols,dispossessed,cards_yellow_red,fouls,fouled,offsides,pens_won,pens_conceded,own_goals,ball_recoveries,aerials_won,aerials_lost,aerials_won_pct -Francesco Acerbi,it ITA,DF,Inter,35-223,1988,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.2,0.2,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,-0.2,-0.2,35.0,41.0,85.4,660.0,231.0,13.0,13.0,100.0,16.0,18.0,88.9,4.0,8.0,50.0,0.0,3.0,0.0,0.0,1.0,36.0,5.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,6.0,0.0,51.0,13.0,32.0,18.0,1.0,1.0,51.0,30.0,0.0,0.0,0.0,30.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,4.0,3.0,0.0,100.0 -Michel Aebischer,ch SUI,MF,Bologna,26-258,1997,4.0,4.0,347.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.9,1.0,0.0,50.0,0.26,0.0,0.0,0.05,-0.1,-0.1,231.0,239.0,96.7,3783.0,1073.0,121.0,125.0,96.8,89.0,91.0,97.8,17.0,19.0,89.5,2.0,20.0,1.0,1.0,23.0,226.0,13.0,10.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,7.0,1.82,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,6.0,2.0,4.0,2.0,1.0,0.0,259.0,7.0,68.0,159.0,34.0,2.0,259.0,158.0,7.0,4.0,1.0,205.0,2.0,0.0,0.0,7.0,5.0,0.0,0.0,0.0,0.0,23.0,2.0,3.0,40.0 -Luis Alberto,es ESP,MF,Lazio,30-358,1992,4.0,4.0,360.0,2.0,1.0,0.0,0.0,1.0,0.0,0.5,0.25,0.75,0.5,0.75,0.5,0.5,0.13,0.13,4.0,4.0,1.0,57.1,1.0,0.29,0.5,0.08,1.5,1.5,254.0,318.0,79.9,4147.0,1308.0,134.0,145.0,92.4,87.0,102.0,85.3,25.0,53.0,47.2,10.0,41.0,10.0,0.0,52.0,275.0,40.0,15.0,2.0,3.0,29.0,22.0,9.0,13.0,0.0,1.0,3.0,4.0,19.0,4.75,16.0,3.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,1.0,0.0,4.0,2.0,2.0,1.0,1.0,0.0,353.0,5.0,38.0,185.0,136.0,8.0,353.0,224.0,24.0,15.0,1.0,270.0,5.0,7.0,0.0,3.0,5.0,0.0,0.0,0.0,0.0,24.0,2.0,4.0,33.3 -Pontus Almqvist,se SWE,FW,Lecce,24-073,1999,4.0,4.0,347.0,1.0,0.0,0.0,0.0,0.0,0.0,0.26,0.0,0.26,0.26,0.26,0.2,0.2,0.06,0.06,3.9,3.0,0.0,60.0,0.78,0.2,0.33,0.04,0.8,0.8,76.0,96.0,79.2,1089.0,213.0,50.0,60.0,83.3,17.0,25.0,68.0,6.0,6.0,100.0,3.0,4.0,2.0,0.0,6.0,95.0,1.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,13.0,3.37,9.0,0.0,1.0,1.0,5.0,1.3,3.0,0.0,0.0,1.0,1.0,7.0,6.0,2.0,4.0,1.0,6.0,0.0,6.0,3.0,2.0,0.0,148.0,2.0,17.0,69.0,65.0,14.0,148.0,103.0,19.0,6.0,6.0,111.0,8.0,7.0,0.0,3.0,8.0,1.0,1.0,0.0,0.0,15.0,0.0,3.0,0.0 -Lorenzo Amatucci,it ITA,MF,Fiorentina,19-228,2004,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,17.0,88.2,304.0,47.0,4.0,4.0,100.0,10.0,10.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,1.0,17.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,1.0,12.0,4.0,0.0,17.0,12.0,1.0,0.0,0.0,13.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 -Bruno Amione,ar ARG,MF,Hellas Verona,21-261,2002,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,100.0,35.0,9.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,5.0,0.0,3.0,2.0,0.0,0.0,5.0,2.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Felipe Anderson,br BRA,FW,Lazio,30-159,1993,4.0,4.0,269.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.67,0.67,0.0,0.67,0.6,0.6,0.2,0.2,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.12,-0.6,-0.6,123.0,156.0,78.8,1880.0,448.0,66.0,75.0,88.0,44.0,55.0,80.0,8.0,15.0,53.3,4.0,9.0,7.0,1.0,16.0,156.0,0.0,0.0,1.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,11.0,3.67,8.0,0.0,0.0,0.0,3.0,1.0,2.0,0.0,0.0,0.0,1.0,6.0,3.0,3.0,2.0,1.0,5.0,0.0,5.0,3.0,2.0,0.0,194.0,1.0,23.0,79.0,93.0,9.0,194.0,120.0,15.0,7.0,3.0,158.0,5.0,0.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,9.0,0.0,5.0,0.0 -Houssem Aouar,dz ALG,MF,Roma,25-083,1998,3.0,2.0,164.0,1.0,0.0,0.0,0.0,1.0,0.0,0.55,0.0,0.55,0.55,0.55,0.5,0.5,0.29,0.29,1.8,1.0,0.0,50.0,0.55,0.5,1.0,0.26,0.5,0.5,57.0,74.0,77.0,932.0,248.0,30.0,34.0,88.2,22.0,27.0,81.5,5.0,7.0,71.4,3.0,6.0,0.0,0.0,3.0,65.0,9.0,2.0,0.0,0.0,5.0,5.0,4.0,1.0,0.0,2.0,0.0,3.0,4.0,2.2,1.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,1.0,3.0,0.0,2.0,0.0,2.0,2.0,0.0,0.0,88.0,0.0,9.0,50.0,30.0,4.0,88.0,48.0,2.0,2.0,1.0,53.0,3.0,2.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,15.0,4.0,3.0,57.1 -Marko Arnautović,at AUT,FW,Inter,34-155,1989,4.0,0.0,86.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.05,1.05,0.0,1.05,0.1,0.1,0.07,0.07,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,27.0,33.0,81.8,314.0,30.0,16.0,20.0,80.0,8.0,8.0,100.0,0.0,1.0,0.0,2.0,2.0,0.0,0.0,2.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,3.14,3.0,0.0,0.0,0.0,1.0,1.05,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,44.0,1.0,3.0,23.0,19.0,5.0,44.0,27.0,3.0,1.0,2.0,29.0,3.0,2.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0 -Kristjan Asllani,al ALB,MF,Inter,21-196,2002,2.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.23,0.23,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,9.0,13.0,69.2,157.0,8.0,5.0,5.0,100.0,3.0,4.0,75.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,0.0,10.0,3.0,2.0,0.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,16.0,0.0,6.0,7.0,3.0,1.0,16.0,10.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Tommaso Augello,it ITA,DF,Cagliari,29-022,1994,3.0,3.0,225.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.5,1.0,0.0,100.0,0.4,0.0,0.0,0.02,0.0,0.0,75.0,116.0,64.7,1294.0,582.0,40.0,42.0,95.2,26.0,40.0,65.0,8.0,27.0,29.6,4.0,8.0,2.0,2.0,7.0,90.0,26.0,5.0,0.0,0.0,15.0,5.0,1.0,4.0,0.0,16.0,0.0,3.0,8.0,3.2,5.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,5.0,0.0,129.0,7.0,41.0,56.0,32.0,1.0,129.0,61.0,10.0,1.0,0.0,71.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,11.0,4.0,1.0,80.0 -Yann Aurel Bisseck,de GER,DF,Inter,22-296,2000,1.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,100.0,42.0,6.0,1.0,1.0,100.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,2.0,1.0,1.0,3.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Sardar Azmoun,ir IRN,FW,Roma,28-263,1995,1.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Paulo Azzi,br BRA,"MF,DF",Cagliari,29-068,1994,4.0,1.0,166.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.16,0.16,1.8,1.0,0.0,25.0,0.54,0.0,0.0,0.07,-0.3,-0.3,50.0,81.0,61.7,862.0,311.0,26.0,32.0,81.3,21.0,30.0,70.0,3.0,15.0,20.0,2.0,6.0,1.0,0.0,7.0,66.0,14.0,2.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,12.0,1.0,1.0,2.0,1.08,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,1.0,1.0,0.0,1.0,3.0,0.0,102.0,5.0,30.0,38.0,36.0,2.0,102.0,55.0,6.0,8.0,1.0,56.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,1.0,2.0,33.3 -Oussama El Azzouzi,ma MAR,MF,Bologna,22-115,2001,3.0,0.0,32.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,36.0,88.9,461.0,62.0,19.0,19.0,100.0,12.0,14.0,85.7,1.0,3.0,33.3,1.0,3.0,0.0,0.0,0.0,35.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,5.63,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,40.0,2.0,9.0,24.0,7.0,1.0,40.0,18.0,0.0,0.0,0.0,26.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0 -Milan Badelj,hr CRO,MF,Genoa,34-208,1989,4.0,4.0,324.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,107.0,134.0,79.9,1839.0,591.0,39.0,42.0,92.9,57.0,68.0,83.8,7.0,19.0,36.8,0.0,11.0,0.0,0.0,9.0,125.0,9.0,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,0.83,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,4.0,3.0,0.0,4.0,0.0,4.0,9.0,10.0,0.0,170.0,17.0,61.0,96.0,15.0,0.0,170.0,74.0,1.0,3.0,0.0,102.0,2.0,3.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,22.0,1.0,3.0,25.0 -Jaime Báez,uy URU,"FW,MF",Frosinone,28-149,1995,4.0,3.0,205.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,2.3,1.0,1.0,20.0,0.44,0.0,0.0,0.03,-0.1,-0.1,56.0,78.0,71.8,874.0,385.0,28.0,34.0,82.4,19.0,23.0,82.6,6.0,15.0,40.0,3.0,6.0,5.0,0.0,13.0,73.0,5.0,2.0,0.0,0.0,9.0,3.0,0.0,3.0,0.0,0.0,0.0,1.0,8.0,3.51,4.0,2.0,0.0,2.0,2.0,0.88,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,4.0,3.0,1.0,0.0,100.0,4.0,15.0,43.0,44.0,7.0,100.0,50.0,4.0,2.0,2.0,63.0,1.0,5.0,0.0,3.0,8.0,2.0,1.0,0.0,0.0,17.0,3.0,3.0,50.0 -Nedim Bajrami,al ALB,"FW,MF",Sassuolo,24-205,1999,4.0,3.0,214.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.11,0.11,2.4,2.0,0.0,40.0,0.84,0.0,0.0,0.05,-0.3,-0.3,58.0,80.0,72.5,782.0,187.0,38.0,44.0,86.4,17.0,25.0,68.0,2.0,8.0,25.0,2.0,3.0,1.0,0.0,6.0,70.0,10.0,1.0,2.0,0.0,13.0,8.0,2.0,6.0,0.0,1.0,0.0,2.0,8.0,3.36,6.0,1.0,0.0,0.0,2.0,0.84,2.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,3.0,1.0,0.0,100.0,3.0,12.0,42.0,50.0,6.0,100.0,62.0,10.0,3.0,3.0,72.0,4.0,2.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,7.0,0.0,3.0,0.0 -Mitchel Bakker,nl NED,DF,Atalanta,23-093,2000,2.0,0.0,26.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,29.0,72.4,261.0,67.0,14.0,17.0,82.4,6.0,6.0,100.0,0.0,3.0,0.0,1.0,1.0,0.0,0.0,1.0,25.0,4.0,0.0,0.0,0.0,3.0,1.0,0.0,1.0,0.0,3.0,0.0,1.0,1.0,3.46,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,1.0,6.0,16.0,11.0,2.0,32.0,23.0,3.0,2.0,1.0,23.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 -Tommaso Baldanzi,it ITA,"FW,MF",Empoli,20-182,2003,4.0,3.0,271.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.0,1.0,0.0,25.0,0.33,0.0,0.0,0.02,-0.1,-0.1,77.0,91.0,84.6,1206.0,216.0,38.0,41.0,92.7,30.0,34.0,88.2,4.0,7.0,57.1,5.0,3.0,3.0,1.0,10.0,77.0,13.0,3.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,4.0,1.0,1.0,12.0,3.99,8.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,3.0,0.0,3.0,1.0,0.0,0.0,118.0,0.0,10.0,55.0,58.0,9.0,118.0,77.0,9.0,9.0,5.0,91.0,6.0,3.0,0.0,1.0,9.0,1.0,0.0,0.0,0.0,9.0,0.0,1.0,0.0 -Lameck Banda,zm ZAM,FW,Lecce,22-235,2001,4.0,4.0,308.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.58,0.58,0.0,0.58,0.3,0.3,0.08,0.08,3.4,5.0,0.0,62.5,1.46,0.0,0.0,0.04,-0.3,-0.3,61.0,79.0,77.2,930.0,167.0,35.0,41.0,85.4,19.0,25.0,76.0,3.0,8.0,37.5,9.0,2.0,4.0,3.0,6.0,76.0,3.0,1.0,1.0,0.0,9.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,12.0,3.51,8.0,0.0,2.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,7.0,7.0,3.0,3.0,1.0,4.0,0.0,4.0,1.0,3.0,0.0,133.0,1.0,16.0,49.0,71.0,16.0,133.0,98.0,16.0,4.0,10.0,93.0,12.0,7.0,0.0,9.0,10.0,1.0,0.0,0.0,0.0,19.0,0.0,1.0,0.0 -Mattia Bani,it ITA,DF,Genoa,29-285,1993,4.0,4.0,360.0,1.0,0.0,0.0,0.0,2.0,0.0,0.25,0.0,0.25,0.25,0.25,0.6,0.6,0.15,0.15,4.0,1.0,0.0,100.0,0.25,1.0,1.0,0.59,0.4,0.4,102.0,133.0,76.7,2119.0,979.0,30.0,35.0,85.7,57.0,65.0,87.7,14.0,28.0,50.0,0.0,7.0,0.0,0.0,6.0,129.0,3.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,3.0,2.0,0.0,11.0,7.0,4.0,4.0,23.0,0.0,184.0,39.0,137.0,46.0,2.0,1.0,184.0,79.0,1.0,0.0,0.0,93.0,1.0,0.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,17.0,8.0,5.0,61.5 -Antonín Barák,cz CZE,MF,Fiorentina,28-292,1994,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,100.0,39.0,0.0,2.0,2.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,5.0,0.0,0.0,2.0,3.0,0.0,5.0,4.0,0.0,1.0,0.0,6.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Nicolò Barella,it ITA,MF,Inter,26-226,1997,4.0,4.0,281.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.1,1.0,0.0,25.0,0.32,0.0,0.0,0.03,-0.1,-0.1,162.0,188.0,86.2,2848.0,1017.0,83.0,91.0,91.2,55.0,64.0,85.9,18.0,26.0,69.2,5.0,28.0,11.0,2.0,37.0,183.0,5.0,3.0,2.0,7.0,3.0,1.0,0.0,0.0,0.0,1.0,0.0,2.0,12.0,3.84,12.0,0.0,0.0,0.0,1.0,0.32,1.0,0.0,0.0,0.0,0.0,10.0,5.0,4.0,6.0,0.0,2.0,0.0,2.0,0.0,0.0,0.0,212.0,3.0,28.0,129.0,57.0,1.0,212.0,139.0,7.0,6.0,0.0,168.0,1.0,0.0,0.0,3.0,3.0,1.0,0.0,0.0,0.0,11.0,2.0,0.0,100.0 -Enzo Barrenechea,ar ARG,MF,Frosinone,22-122,2001,4.0,3.0,225.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,117.0,135.0,86.7,1975.0,408.0,51.0,54.0,94.4,44.0,51.0,86.3,14.0,20.0,70.0,0.0,8.0,1.0,0.0,10.0,129.0,6.0,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.2,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,6.0,1.0,4.0,1.0,4.0,1.0,3.0,4.0,3.0,0.0,159.0,7.0,43.0,97.0,19.0,1.0,159.0,85.0,1.0,2.0,0.0,110.0,1.0,1.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,16.0,0.0,2.0,0.0 -Federico Baschirotto,it ITA,DF,Lecce,27-001,1996,4.0,4.0,324.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.08,0.08,3.6,0.0,0.0,0.0,0.0,0.0,0.0,0.14,-0.3,-0.3,149.0,168.0,88.7,2704.0,815.0,46.0,50.0,92.0,90.0,98.0,91.8,11.0,17.0,64.7,0.0,5.0,0.0,0.0,9.0,157.0,11.0,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,3.0,0.83,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,4.0,3.0,1.0,2.0,12.0,0.0,190.0,26.0,97.0,86.0,7.0,3.0,190.0,127.0,7.0,2.0,0.0,129.0,2.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,15.0,6.0,3.0,66.7 -Alessandro Bastoni,it ITA,DF,Inter,24-161,1999,4.0,4.0,343.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.8,1.0,0.0,33.3,0.26,0.0,0.0,0.03,-0.1,-0.1,214.0,247.0,86.6,4217.0,1636.0,86.0,92.0,93.5,85.0,89.0,95.5,36.0,52.0,69.2,5.0,15.0,5.0,2.0,17.0,229.0,17.0,13.0,0.0,7.0,6.0,0.0,0.0,0.0,0.0,3.0,1.0,5.0,12.0,3.15,8.0,1.0,1.0,1.0,1.0,0.26,1.0,0.0,0.0,0.0,0.0,13.0,11.0,11.0,0.0,2.0,4.0,3.0,1.0,4.0,4.0,0.0,282.0,27.0,104.0,127.0,53.0,5.0,282.0,201.0,6.0,7.0,0.0,210.0,1.0,2.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,17.0,4.0,1.0,80.0 -Simone Bastoni,it ITA,MF,Empoli,26-320,1996,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,28.0,78.6,335.0,100.0,9.0,10.0,90.0,10.0,11.0,90.9,1.0,4.0,25.0,0.0,2.0,0.0,0.0,2.0,25.0,3.0,1.0,0.0,0.0,3.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,34.0,0.0,3.0,12.0,19.0,1.0,34.0,21.0,0.0,1.0,0.0,25.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Raoul Bellanova,it ITA,DF,Torino,23-127,2000,4.0,4.0,296.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.3,0.3,0.0,0.3,0.0,0.0,0.0,0.0,3.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,100.0,140.0,71.4,1892.0,499.0,46.0,54.0,85.2,39.0,54.0,72.2,15.0,25.0,60.0,3.0,3.0,4.0,3.0,7.0,112.0,27.0,0.0,0.0,0.0,17.0,0.0,0.0,0.0,0.0,27.0,1.0,4.0,8.0,2.43,8.0,0.0,0.0,0.0,3.0,0.91,3.0,0.0,0.0,0.0,0.0,3.0,2.0,3.0,0.0,0.0,2.0,0.0,2.0,3.0,1.0,0.0,166.0,7.0,36.0,67.0,64.0,3.0,166.0,98.0,12.0,5.0,1.0,102.0,6.0,1.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,11.0,1.0,5.0,16.7 -Andrea Belotti,it ITA,FW,Roma,29-275,1993,4.0,3.0,297.0,2.0,2.0,0.0,0.0,0.0,0.0,0.61,0.61,1.21,0.61,1.21,1.3,1.3,0.39,0.39,3.3,3.0,0.0,42.9,0.91,0.29,0.67,0.18,0.7,0.7,52.0,65.0,80.0,714.0,79.0,32.0,35.0,91.4,13.0,17.0,76.5,4.0,5.0,80.0,4.0,1.0,1.0,0.0,4.0,57.0,8.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,10.0,3.03,4.0,0.0,2.0,2.0,4.0,1.21,2.0,0.0,1.0,0.0,0.0,5.0,3.0,1.0,3.0,1.0,2.0,0.0,2.0,0.0,1.0,0.0,103.0,1.0,3.0,61.0,41.0,20.0,103.0,67.0,6.0,5.0,3.0,84.0,15.0,5.0,0.0,4.0,8.0,3.0,0.0,0.0,0.0,5.0,7.0,7.0,50.0 -Lucas Beltrán,ar ARG,FW,Fiorentina,22-176,2001,4.0,2.0,135.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,35.0,71.4,288.0,48.0,18.0,22.0,81.8,4.0,5.0,80.0,1.0,1.0,100.0,1.0,1.0,1.0,0.0,2.0,34.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,6.0,4.0,3.0,0.0,0.0,1.0,3.0,2.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,3.0,0.0,3.0,0.0,1.0,0.0,55.0,1.0,1.0,28.0,26.0,3.0,55.0,36.0,1.0,1.0,0.0,41.0,5.0,4.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,1.0,1.0,7.0,12.5 -Domenico Berardi,it ITA,"MF,FW",Sassuolo,29-051,1994,2.0,2.0,167.0,2.0,0.0,1.0,1.0,0.0,0.0,1.08,0.0,1.08,0.54,0.54,1.0,0.2,0.54,0.11,1.9,4.0,0.0,66.7,2.16,0.17,0.25,0.03,1.0,0.8,51.0,74.0,68.9,905.0,281.0,25.0,28.0,89.3,19.0,22.0,86.4,6.0,18.0,33.3,4.0,7.0,4.0,0.0,13.0,66.0,7.0,2.0,4.0,3.0,8.0,5.0,4.0,0.0,0.0,0.0,1.0,0.0,13.0,7.01,12.0,0.0,0.0,1.0,1.0,0.54,0.0,0.0,0.0,1.0,0.0,3.0,1.0,2.0,1.0,0.0,3.0,0.0,3.0,0.0,0.0,0.0,96.0,0.0,6.0,42.0,48.0,11.0,95.0,51.0,7.0,3.0,4.0,74.0,5.0,3.0,0.0,0.0,3.0,1.0,1.0,0.0,0.0,9.0,2.0,4.0,33.3 -Bartosz Bereszyński,pl POL,DF,Empoli,31-071,1992,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.0,1.0,0.0,100.0,0.5,0.0,0.0,0.02,0.0,0.0,102.0,117.0,87.2,1352.0,478.0,67.0,71.0,94.4,30.0,35.0,85.7,2.0,2.0,100.0,3.0,12.0,1.0,0.0,15.0,101.0,14.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,12.0,2.0,4.0,3.0,1.5,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,5.0,0.0,133.0,10.0,37.0,66.0,31.0,1.0,133.0,87.0,7.0,3.0,1.0,89.0,2.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,14.0,1.0,1.0,50.0 -Etrit Berisha,al ALB,GK,Empoli,34-195,1989,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,51.0,63.0,81.0,1119.0,631.0,11.0,11.0,100.0,32.0,32.0,100.0,8.0,20.0,40.0,0.0,1.0,0.0,0.0,0.0,47.0,16.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,67.0,63.0,67.0,0.0,0.0,0.0,67.0,42.0,0.0,0.0,0.0,31.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Victor Bernth Kristiansen,dk DEN,DF,Bologna,20-279,2002,2.0,2.0,169.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.53,0.53,0.0,0.53,0.1,0.1,0.05,0.05,1.9,1.0,0.0,50.0,0.53,0.0,0.0,0.05,-0.1,-0.1,87.0,109.0,79.8,1328.0,472.0,49.0,53.0,92.5,34.0,45.0,75.6,3.0,7.0,42.9,4.0,6.0,5.0,2.0,7.0,86.0,23.0,2.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,21.0,0.0,0.0,6.0,3.2,4.0,0.0,2.0,0.0,2.0,1.07,1.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,5.0,0.0,5.0,1.0,2.0,0.0,126.0,1.0,32.0,60.0,34.0,5.0,126.0,70.0,2.0,0.0,0.0,75.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,5.0,3.0,0.0,100.0 -Beto,gw GNB,FW,Udinese,25-233,1998,1.0,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,11.0,90.9,128.0,26.0,7.0,8.0,87.5,3.0,3.0,100.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,2.0,9.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,7.3,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,0.0,7.0,10.0,1.0,17.0,15.0,0.0,0.0,0.0,14.0,3.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0 -Sam Beukema,nl NED,DF,Bologna,24-308,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,287.0,303.0,94.7,5248.0,1793.0,119.0,121.0,98.3,138.0,144.0,95.8,26.0,32.0,81.3,1.0,17.0,0.0,0.0,14.0,294.0,8.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,3.0,0.75,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,6.0,2.0,0.0,4.0,1.0,3.0,2.0,13.0,0.0,332.0,35.0,145.0,188.0,1.0,0.0,332.0,231.0,4.0,2.0,1.0,249.0,0.0,1.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,29.0,4.0,3.0,57.1 -Jaka Bijol,si SVN,DF,Udinese,24-228,1999,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.14,-0.1,-0.1,173.0,203.0,85.2,3686.0,1678.0,49.0,55.0,89.1,90.0,103.0,87.4,32.0,42.0,76.2,0.0,15.0,2.0,0.0,18.0,198.0,5.0,4.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,7.0,8.0,3.0,0.0,5.0,4.0,1.0,4.0,21.0,0.0,248.0,40.0,123.0,123.0,2.0,1.0,248.0,142.0,2.0,0.0,0.0,147.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,16.0,13.0,6.0,68.4 -Cristiano Biraghi,it ITA,DF,Fiorentina,31-020,1992,3.0,2.0,197.0,1.0,1.0,0.0,0.0,1.0,0.0,0.46,0.46,0.91,0.46,0.91,0.0,0.0,0.01,0.01,2.2,1.0,0.0,100.0,0.46,1.0,1.0,0.03,1.0,1.0,170.0,213.0,79.8,3181.0,942.0,70.0,72.0,97.2,71.0,87.0,81.6,24.0,39.0,61.5,1.0,7.0,0.0,0.0,6.0,169.0,44.0,9.0,0.0,6.0,14.0,6.0,1.0,3.0,0.0,29.0,0.0,7.0,3.0,1.37,0.0,1.0,0.0,0.0,3.0,1.37,0.0,1.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,4.0,2.0,2.0,3.0,4.0,0.0,230.0,5.0,73.0,98.0,61.0,4.0,230.0,142.0,12.0,6.0,1.0,149.0,0.0,0.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,11.0,1.0,2.0,33.3 -Davide Biraschi,it ITA,DF,Genoa,29-081,1994,1.0,1.0,90.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.1,0.1,0.1,0.1,1.0,1.0,0.0,100.0,1.0,1.0,1.0,0.1,0.9,0.9,31.0,37.0,83.8,684.0,308.0,6.0,7.0,85.7,18.0,21.0,85.7,7.0,9.0,77.8,0.0,2.0,1.0,0.0,5.0,28.0,9.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,5.0,0.0,48.0,5.0,20.0,21.0,7.0,1.0,48.0,19.0,0.0,2.0,0.0,21.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 -Samuele Birindelli,it ITA,DF,Monza,24-064,1999,4.0,3.0,267.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.34,0.34,0.0,0.34,0.2,0.2,0.05,0.05,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,121.0,138.0,87.7,2142.0,462.0,57.0,60.0,95.0,53.0,58.0,91.4,11.0,15.0,73.3,4.0,6.0,7.0,3.0,9.0,114.0,24.0,1.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,23.0,0.0,5.0,5.0,1.69,4.0,0.0,0.0,1.0,1.0,0.34,1.0,0.0,0.0,0.0,0.0,6.0,4.0,3.0,3.0,0.0,6.0,3.0,3.0,4.0,5.0,0.0,174.0,10.0,54.0,65.0,55.0,10.0,174.0,84.0,4.0,2.0,1.0,114.0,8.0,1.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,60.0 -Alexis Blin,fr FRA,"DF,MF",Lecce,27-005,1996,4.0,0.0,96.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.15,0.15,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.16,-0.2,-0.2,41.0,50.0,82.0,786.0,257.0,12.0,15.0,80.0,25.0,28.0,89.3,3.0,4.0,75.0,0.0,5.0,1.0,0.0,5.0,45.0,5.0,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.94,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,4.0,0.0,64.0,6.0,21.0,37.0,6.0,2.0,64.0,35.0,0.0,0.0,0.0,35.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,6.0,4.0,2.0,66.7 -Emil Bohinen,no NOR,MF,Salernitana,24-193,1999,3.0,2.0,111.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.04,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,67.0,92.0,72.8,1075.0,330.0,31.0,37.0,83.8,24.0,35.0,68.6,7.0,9.0,77.8,1.0,2.0,0.0,0.0,6.0,90.0,2.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,1.62,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,2.0,0.0,3.0,1.0,1.0,113.0,2.0,30.0,65.0,18.0,1.0,113.0,53.0,1.0,0.0,0.0,66.0,4.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,11.0,6.0,5.0,54.5 -Daniel Boloca,ro ROU,MF,Sassuolo,24-273,1998,3.0,3.0,216.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.12,0.12,2.4,2.0,0.0,50.0,0.83,0.0,0.0,0.07,-0.3,-0.3,86.0,93.0,92.5,1331.0,387.0,38.0,40.0,95.0,41.0,43.0,95.3,2.0,3.0,66.7,0.0,6.0,0.0,0.0,9.0,91.0,2.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,1.26,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,3.0,0.0,0.0,0.0,0.0,1.0,3.0,0.0,111.0,8.0,36.0,54.0,21.0,4.0,111.0,51.0,1.0,2.0,0.0,76.0,2.0,1.0,0.0,6.0,1.0,0.0,0.0,1.0,0.0,13.0,1.0,1.0,50.0 -Giacomo Bonaventura,it ITA,MF,Fiorentina,34-030,1989,4.0,4.0,313.0,2.0,1.0,0.0,0.0,1.0,0.0,0.58,0.29,0.86,0.58,0.86,0.8,0.8,0.22,0.22,3.5,2.0,0.0,40.0,0.58,0.4,1.0,0.15,1.2,1.2,144.0,162.0,88.9,2256.0,410.0,66.0,75.0,88.0,63.0,66.0,95.5,8.0,10.0,80.0,2.0,9.0,4.0,0.0,17.0,158.0,4.0,1.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,1.44,5.0,0.0,0.0,0.0,2.0,0.58,2.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,0.0,3.0,5.0,0.0,5.0,4.0,2.0,0.0,203.0,3.0,23.0,112.0,70.0,8.0,203.0,150.0,6.0,5.0,2.0,160.0,9.0,5.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,11.0,2.0,3.0,40.0 -Federico Bonazzoli,it ITA,"FW,MF",Hellas Verona,26-123,1997,4.0,1.0,148.0,1.0,0.0,0.0,0.0,0.0,0.0,0.61,0.0,0.61,0.61,0.61,0.3,0.3,0.19,0.19,1.6,3.0,0.0,50.0,1.82,0.17,0.33,0.05,0.7,0.7,35.0,48.0,72.9,495.0,61.0,25.0,30.0,83.3,8.0,11.0,72.7,2.0,2.0,100.0,1.0,5.0,1.0,0.0,3.0,46.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,4.0,2.43,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,68.0,1.0,4.0,35.0,29.0,9.0,68.0,48.0,3.0,2.0,2.0,57.0,7.0,1.0,0.0,1.0,6.0,4.0,0.0,0.0,0.0,5.0,2.0,3.0,40.0 -Warren Bondo,fr FRA,MF,Monza,20-006,2003,1.0,0.0,25.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,168.0,43.0,7.0,8.0,87.5,4.0,4.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,0.0,2.0,10.0,4.0,0.0,16.0,10.0,2.0,1.0,0.0,14.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 -Gennaro Borrelli,it ITA,FW,Frosinone,23-195,2000,1.0,0.0,24.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Erik Botheim,no NOR,"FW,MF",Salernitana,23-254,2000,4.0,4.0,254.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,49.0,73.5,486.0,31.0,24.0,31.0,77.4,10.0,11.0,90.9,0.0,1.0,0.0,0.0,1.0,0.0,0.0,2.0,45.0,4.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.35,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,62.0,2.0,8.0,39.0,16.0,5.0,62.0,35.0,2.0,1.0,1.0,44.0,2.0,0.0,0.0,2.0,10.0,0.0,0.0,0.0,0.0,6.0,1.0,13.0,7.1 -Edoardo Bove,it ITA,MF,Roma,21-128,2002,3.0,1.0,130.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.69,0.69,0.0,0.69,0.5,0.5,0.31,0.31,1.4,1.0,0.0,33.3,0.69,0.0,0.0,0.15,-0.5,-0.5,52.0,60.0,86.7,860.0,175.0,23.0,26.0,88.5,25.0,26.0,96.2,3.0,3.0,100.0,2.0,7.0,0.0,0.0,6.0,60.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,2.08,2.0,0.0,0.0,1.0,1.0,0.69,1.0,0.0,0.0,0.0,0.0,7.0,5.0,1.0,5.0,1.0,3.0,0.0,3.0,1.0,0.0,0.0,79.0,1.0,12.0,48.0,19.0,4.0,79.0,49.0,1.0,0.0,0.0,53.0,3.0,1.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,8.0,3.0,1.0,75.0 -Domagoj Bradarić,hr CRO,DF,Salernitana,23-285,1999,4.0,3.0,276.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.33,0.33,0.0,0.33,0.0,0.0,0.01,0.01,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,124.0,160.0,77.5,1886.0,554.0,67.0,80.0,83.8,45.0,53.0,84.9,6.0,14.0,42.9,3.0,2.0,1.0,0.0,7.0,128.0,32.0,1.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,31.0,0.0,4.0,5.0,1.63,4.0,1.0,0.0,0.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,2.0,1.0,1.0,1.0,0.0,2.0,3.0,0.0,179.0,6.0,47.0,94.0,40.0,1.0,179.0,92.0,4.0,3.0,1.0,101.0,3.0,1.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,15.0,3.0,2.0,60.0 -Josip Brekalo,hr CRO,FW,Fiorentina,25-090,1998,4.0,2.0,242.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,2.7,2.0,0.0,50.0,0.74,0.0,0.0,0.03,-0.1,-0.1,98.0,122.0,80.3,1493.0,358.0,52.0,54.0,96.3,31.0,42.0,73.8,9.0,14.0,64.3,4.0,6.0,6.0,2.0,9.0,118.0,4.0,1.0,0.0,0.0,10.0,3.0,0.0,2.0,0.0,0.0,0.0,4.0,10.0,3.72,8.0,1.0,0.0,0.0,1.0,0.37,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,5.0,0.0,5.0,0.0,0.0,0.0,143.0,0.0,18.0,51.0,77.0,7.0,143.0,99.0,4.0,4.0,3.0,110.0,1.0,2.0,0.0,6.0,3.0,0.0,0.0,0.0,0.0,10.0,0.0,2.0,0.0 -Gleison Bremer,br BRA,DF,Juventus,26-187,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,-0.2,-0.2,198.0,225.0,88.0,3527.0,1043.0,76.0,85.0,89.4,103.0,107.0,96.3,15.0,26.0,57.7,0.0,3.0,0.0,0.0,5.0,198.0,25.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,2.0,0.5,2.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,6.0,6.0,5.0,1.0,0.0,4.0,3.0,1.0,5.0,14.0,0.0,264.0,49.0,156.0,96.0,12.0,5.0,264.0,141.0,1.0,1.0,1.0,163.0,2.0,2.0,0.0,6.0,0.0,1.0,0.0,0.0,0.0,18.0,6.0,7.0,46.2 -Marco Brescianini,it ITA,MF,Frosinone,23-244,2000,3.0,0.0,41.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.05,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,10.0,14.0,71.4,167.0,110.0,5.0,7.0,71.4,2.0,2.0,100.0,2.0,2.0,100.0,0.0,1.0,0.0,0.0,0.0,14.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,4.39,1.0,0.0,0.0,0.0,1.0,2.2,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,18.0,0.0,6.0,9.0,3.0,3.0,18.0,13.0,0.0,1.0,1.0,13.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 -Alessandro Buongiorno,it ITA,DF,Torino,24-107,1999,4.0,4.0,360.0,1.0,0.0,0.0,0.0,1.0,0.0,0.25,0.0,0.25,0.25,0.25,0.3,0.3,0.06,0.06,4.0,1.0,0.0,100.0,0.25,1.0,1.0,0.26,0.7,0.7,147.0,170.0,86.5,2518.0,808.0,63.0,67.0,94.0,77.0,82.0,93.9,6.0,17.0,35.3,1.0,1.0,0.0,0.0,6.0,168.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,4.0,3.0,0.0,3.0,1.0,2.0,6.0,17.0,0.0,214.0,21.0,108.0,103.0,3.0,1.0,214.0,121.0,0.0,1.0,1.0,119.0,5.0,1.0,0.0,12.0,3.0,0.0,0.0,1.0,0.0,21.0,10.0,11.0,47.6 -Rareș-Cătălin Burnete,ro ROU,FW,Lecce,19-233,2004,1.0,0.0,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,11.25,11.25,0.0,11.25,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,8.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,2.0,2.0,1.0,4.0,2.0,0.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Juan Cabal,co COL,DF,Hellas Verona,22-256,2001,2.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.09,0.09,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,12.0,15.0,80.0,280.0,123.0,4.0,4.0,100.0,5.0,6.0,83.3,3.0,4.0,75.0,0.0,4.0,0.0,0.0,4.0,14.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,0.0,0.0,14.0,2.0,0.0,16.0,11.0,1.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 -Jovane Cabral,cv CPV,"MF,DF",Salernitana,25-099,1998,3.0,2.0,209.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.26,0.26,2.3,4.0,0.0,40.0,1.72,0.0,0.0,0.06,-0.6,-0.6,73.0,90.0,81.1,1384.0,466.0,28.0,31.0,90.3,28.0,34.0,82.4,12.0,16.0,75.0,5.0,11.0,4.0,2.0,15.0,83.0,6.0,3.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,9.0,3.88,8.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,6.0,3.0,3.0,1.0,1.0,0.0,1.0,0.0,2.0,0.0,122.0,2.0,15.0,65.0,44.0,7.0,122.0,87.0,6.0,3.0,2.0,92.0,6.0,7.0,0.0,8.0,6.0,0.0,0.0,1.0,0.0,8.0,3.0,4.0,42.9 -Liberato Cacace,nz NZL,DF,Empoli,22-359,2000,2.0,2.0,131.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,74.0,101.0,73.3,1172.0,494.0,35.0,41.0,85.4,30.0,38.0,78.9,4.0,12.0,33.3,1.0,4.0,1.0,0.0,6.0,77.0,23.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,23.0,1.0,3.0,3.0,2.05,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,1.0,1.0,0.0,1.0,3.0,2.0,0.0,119.0,3.0,32.0,54.0,33.0,1.0,119.0,64.0,3.0,0.0,0.0,69.0,0.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,6.0,2.0,2.0,50.0 -Jens Cajuste,se SWE,MF,Napoli,24-042,1999,3.0,1.0,69.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,1.3,1.3,0.0,1.3,0.0,0.0,0.06,0.06,0.8,1.0,0.0,100.0,1.3,0.0,0.0,0.05,0.0,0.0,37.0,41.0,90.2,499.0,141.0,24.0,24.0,100.0,11.0,12.0,91.7,1.0,1.0,100.0,3.0,1.0,2.0,0.0,4.0,40.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,5.0,6.52,5.0,0.0,0.0,0.0,2.0,2.61,2.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,54.0,2.0,10.0,28.0,16.0,3.0,54.0,31.0,0.0,1.0,0.0,38.0,3.0,1.0,0.0,5.0,2.0,1.0,0.0,1.0,0.0,5.0,1.0,2.0,33.3 -Davide Calabria,it ITA,DF,Milan,26-289,1996,4.0,4.0,328.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.27,0.27,0.0,0.27,0.2,0.2,0.05,0.05,3.6,1.0,0.0,25.0,0.27,0.0,0.0,0.05,-0.2,-0.2,173.0,195.0,88.7,2872.0,740.0,78.0,82.0,95.1,81.0,89.0,91.0,10.0,18.0,55.6,3.0,10.0,3.0,2.0,12.0,174.0,21.0,5.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,16.0,0.0,1.0,4.0,1.1,3.0,0.0,0.0,1.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,7.0,2.0,5.0,1.0,1.0,4.0,1.0,3.0,6.0,8.0,0.0,229.0,10.0,69.0,129.0,31.0,2.0,229.0,126.0,2.0,5.0,0.0,154.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,12.0,1.0,4.0,20.0 -Riccardo Calafiori,it ITA,DF,Bologna,21-125,2002,1.0,0.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,12.0,100.0,252.0,86.0,3.0,3.0,100.0,7.0,7.0,100.0,2.0,2.0,100.0,1.0,0.0,2.0,1.0,1.0,12.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,16.36,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,0.0,4.0,5.0,4.0,1.0,13.0,10.0,0.0,1.0,0.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Luca Caldirola,it ITA,DF,Monza,32-232,1991,4.0,4.0,354.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,195.0,217.0,89.9,3660.0,1190.0,76.0,77.0,98.7,96.0,106.0,90.6,22.0,30.0,73.3,0.0,15.0,0.0,0.0,8.0,205.0,12.0,4.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,5.0,1.27,5.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,5.0,3.0,3.0,1.0,1.0,3.0,3.0,0.0,4.0,8.0,0.0,243.0,36.0,108.0,121.0,14.0,2.0,243.0,147.0,2.0,1.0,0.0,186.0,0.0,0.0,1.0,4.0,3.0,0.0,0.0,1.0,0.0,9.0,3.0,1.0,75.0 -Hakan Çalhanoğlu,tr TUR,MF,Inter,29-225,1994,4.0,4.0,337.0,2.0,0.0,2.0,2.0,1.0,0.0,0.53,0.0,0.53,0.0,0.0,1.9,0.3,0.51,0.09,3.7,1.0,2.0,16.7,0.27,0.0,0.0,0.05,0.1,-0.3,214.0,238.0,89.9,4111.0,1320.0,83.0,86.0,96.5,91.0,96.0,94.8,33.0,43.0,76.7,5.0,23.0,0.0,0.0,23.0,216.0,20.0,8.0,1.0,7.0,12.0,10.0,3.0,5.0,0.0,1.0,2.0,2.0,13.0,3.47,7.0,6.0,0.0,0.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,10.0,8.0,5.0,2.0,3.0,5.0,3.0,2.0,1.0,2.0,0.0,269.0,11.0,73.0,141.0,59.0,3.0,267.0,172.0,5.0,7.0,1.0,179.0,2.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,27.0,4.0,1.0,80.0 -Nicolò Cambiaghi,it ITA,FW,Empoli,22-267,2000,3.0,2.0,202.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.11,0.11,2.2,1.0,0.0,16.7,0.45,0.0,0.0,0.04,-0.2,-0.2,55.0,72.0,76.4,792.0,112.0,33.0,35.0,94.3,19.0,26.0,73.1,2.0,5.0,40.0,1.0,3.0,3.0,3.0,2.0,68.0,4.0,0.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,7.0,3.12,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,2.0,0.0,1.0,0.0,1.0,2.0,1.0,0.0,93.0,1.0,4.0,27.0,65.0,7.0,93.0,72.0,12.0,2.0,4.0,76.0,4.0,6.0,0.0,2.0,3.0,1.0,0.0,0.0,0.0,8.0,1.0,1.0,50.0 -Andrea Cambiaso,it ITA,DF,Juventus,23-213,2000,4.0,2.0,186.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.48,0.48,0.0,0.48,0.1,0.1,0.03,0.03,2.1,1.0,0.0,50.0,0.48,0.0,0.0,0.03,-0.1,-0.1,101.0,116.0,87.1,1555.0,323.0,57.0,60.0,95.0,37.0,43.0,86.0,4.0,5.0,80.0,2.0,0.0,3.0,1.0,6.0,96.0,19.0,2.0,0.0,1.0,7.0,6.0,0.0,2.0,0.0,11.0,1.0,4.0,7.0,3.39,5.0,1.0,0.0,1.0,1.0,0.48,1.0,0.0,0.0,0.0,0.0,6.0,4.0,3.0,3.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,141.0,4.0,34.0,57.0,51.0,2.0,141.0,79.0,6.0,5.0,2.0,101.0,3.0,0.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,6.0,1.0,0.0,100.0 -Matteo Cancellieri,it ITA,FW,Empoli,21-221,2002,4.0,3.0,203.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.1,0.1,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.2,-0.2,45.0,68.0,66.2,643.0,124.0,28.0,34.0,82.4,12.0,18.0,66.7,4.0,12.0,33.3,0.0,2.0,1.0,0.0,4.0,65.0,1.0,1.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,5.0,2.22,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,1.0,1.0,4.0,0.0,4.0,0.0,1.0,0.0,90.0,3.0,14.0,41.0,37.0,7.0,90.0,66.0,5.0,4.0,2.0,70.0,1.0,5.0,0.0,2.0,5.0,1.0,0.0,0.0,0.0,11.0,0.0,8.0,0.0 -Antonio Candreva,it ITA,MF,Salernitana,36-205,1987,4.0,4.0,360.0,2.0,1.0,0.0,0.0,1.0,0.0,0.5,0.25,0.75,0.5,0.75,0.9,0.9,0.22,0.22,4.0,5.0,1.0,62.5,1.25,0.25,0.4,0.11,1.1,1.1,138.0,190.0,72.6,2015.0,684.0,71.0,77.0,92.2,47.0,65.0,72.3,9.0,27.0,33.3,9.0,11.0,14.0,3.0,24.0,164.0,26.0,11.0,1.0,2.0,23.0,6.0,1.0,3.0,0.0,5.0,0.0,7.0,16.0,4.0,13.0,1.0,1.0,1.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,212.0,6.0,17.0,89.0,108.0,11.0,212.0,144.0,10.0,9.0,2.0,172.0,4.0,3.0,0.0,0.0,8.0,2.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 -Luigi Canotto,it ITA,FW,Frosinone,29-125,1994,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,66.7,21.0,9.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,2.0,0.0,0.0,4.0,5.0,0.0,0.0,0.0,3.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Gianluca Caprari,it ITA,"MF,FW",Monza,30-053,1993,4.0,4.0,255.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.1,0.1,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.3,-0.3,88.0,111.0,79.3,1602.0,463.0,44.0,47.0,93.6,28.0,35.0,80.0,15.0,21.0,71.4,10.0,9.0,7.0,0.0,15.0,102.0,9.0,1.0,0.0,0.0,6.0,5.0,1.0,3.0,0.0,2.0,0.0,6.0,15.0,5.27,10.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,138.0,1.0,18.0,58.0,64.0,9.0,138.0,98.0,11.0,9.0,5.0,107.0,9.0,9.0,0.0,2.0,3.0,2.0,0.0,0.0,0.0,11.0,0.0,4.0,0.0 -Elia Caprile,it ITA,GK,Empoli,22-027,2001,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,24.0,41.0,58.5,812.0,542.0,0.0,0.0,0.0,10.0,10.0,100.0,14.0,31.0,45.2,0.0,1.0,0.0,0.0,0.0,34.0,7.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,44.0,30.0,44.0,0.0,0.0,0.0,44.0,26.0,0.0,0.0,0.0,20.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Francesco Caputo,it ITA,FW,Empoli,36-046,1987,4.0,3.0,244.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.17,0.17,2.7,3.0,0.0,42.9,1.11,0.0,0.0,0.07,-0.5,-0.5,34.0,54.0,63.0,412.0,57.0,21.0,29.0,72.4,9.0,11.0,81.8,0.0,1.0,0.0,0.0,2.0,0.0,0.0,5.0,50.0,4.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,6.0,2.21,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,72.0,0.0,1.0,33.0,38.0,11.0,72.0,44.0,2.0,2.0,1.0,59.0,6.0,4.0,0.0,1.0,3.0,2.0,0.0,0.0,0.0,0.0,1.0,5.0,16.7 -Andrea Carboni,it ITA,DF,Monza,22-229,2001,2.0,0.0,70.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.31,0.31,0.8,1.0,0.0,100.0,1.29,0.0,0.0,0.24,-0.2,-0.2,55.0,64.0,85.9,992.0,249.0,22.0,23.0,95.7,28.0,29.0,96.6,4.0,9.0,44.4,0.0,5.0,0.0,0.0,0.0,62.0,2.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.29,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,69.0,5.0,19.0,39.0,11.0,4.0,69.0,46.0,1.0,2.0,0.0,54.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,4.0,2.0,1.0,66.7 -Valentin Carboni,ar ARG,"DF,MF",Monza,18-200,2005,2.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,2.21,2.21,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.2,-0.2,9.0,10.0,90.0,169.0,48.0,3.0,3.0,100.0,5.0,5.0,100.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,3.0,8.0,2.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,11.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,2.0,6.0,9.0,2.0,17.0,8.0,1.0,1.0,1.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Carlos,br BRA,DF,Inter,24-257,1999,4.0,0.0,92.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.15,0.15,1.0,1.0,0.0,50.0,0.98,0.0,0.0,0.08,-0.2,-0.2,31.0,41.0,75.6,445.0,135.0,15.0,17.0,88.2,14.0,17.0,82.4,1.0,3.0,33.3,0.0,0.0,0.0,0.0,2.0,35.0,5.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,5.0,1.0,2.0,1.0,0.98,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,50.0,2.0,14.0,16.0,21.0,4.0,50.0,32.0,3.0,2.0,1.0,34.0,2.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,8.0,5.0,0.0,100.0 -Marco Carnesecchi,it ITA,GK,Atalanta,23-082,2000,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,34.0,61.8,649.0,414.0,3.0,3.0,100.0,7.0,8.0,87.5,11.0,23.0,47.8,0.0,1.0,0.0,0.0,0.0,28.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,33.0,36.0,0.0,0.0,0.0,36.0,25.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 -Nicolò Casale,it ITA,DF,Lazio,25-219,1998,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,212.0,228.0,93.0,3845.0,1515.0,80.0,90.0,88.9,108.0,109.0,99.1,20.0,23.0,87.0,1.0,31.0,0.0,0.0,24.0,224.0,4.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,0.0,0.0,3.0,3.0,0.0,0.0,19.0,0.0,255.0,34.0,95.0,153.0,11.0,0.0,255.0,171.0,9.0,6.0,0.0,182.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,21.0,3.0,3.0,50.0 -Giuseppe Caso,it ITA,"MF,FW",Frosinone,24-286,1998,3.0,1.0,122.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,1.4,1.0,0.0,50.0,0.74,0.0,0.0,0.04,-0.1,-0.1,26.0,30.0,86.7,322.0,129.0,15.0,16.0,93.8,6.0,7.0,85.7,2.0,3.0,66.7,0.0,3.0,3.0,0.0,8.0,30.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.48,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,44.0,0.0,4.0,11.0,31.0,5.0,44.0,31.0,5.0,2.0,3.0,33.0,3.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Valentín Castellanos,ar ARG,"FW,MF",Lazio,24-353,1998,4.0,0.0,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,1.44,1.44,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.2,-0.6,-0.6,9.0,11.0,81.8,119.0,28.0,4.0,6.0,66.7,4.0,4.0,100.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,10.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,22.0,0.0,1.0,8.0,13.0,6.0,22.0,8.0,0.0,0.0,0.0,14.0,5.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,7.0,22.2 -Samu Castillejo,es ESP,FW,Sassuolo,28-246,1995,1.0,0.0,24.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.26,0.26,0.3,1.0,0.0,50.0,3.75,0.0,0.0,0.04,-0.1,-0.1,12.0,17.0,70.6,130.0,26.0,11.0,13.0,84.6,1.0,2.0,50.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,16.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,0.0,0.0,3.0,19.0,6.0,22.0,21.0,3.0,0.0,4.0,21.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Danilo Cataldi,it ITA,MF,Lazio,29-046,1994,4.0,4.0,300.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.3,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,167.0,185.0,90.3,2466.0,733.0,98.0,104.0,94.2,61.0,65.0,93.8,6.0,11.0,54.5,1.0,13.0,0.0,0.0,16.0,177.0,8.0,4.0,0.0,0.0,4.0,2.0,0.0,2.0,0.0,2.0,0.0,1.0,3.0,0.9,2.0,0.0,0.0,0.0,1.0,0.3,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,3.0,2.0,1.0,6.0,6.0,1.0,208.0,12.0,58.0,136.0,17.0,0.0,208.0,111.0,3.0,3.0,0.0,147.0,3.0,1.0,0.0,6.0,3.0,0.0,0.0,0.0,0.0,27.0,1.0,0.0,100.0 -Emil Ceide,no NOR,"MF,FW",Sassuolo,22-018,2001,3.0,0.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.1,-0.1,20.0,27.0,74.1,228.0,54.0,15.0,18.0,83.3,3.0,4.0,75.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0,2.0,27.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,4.44,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,0.0,0.0,0.0,37.0,0.0,5.0,13.0,21.0,3.0,37.0,20.0,3.0,1.0,2.0,27.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Zeki Çelik,tr TUR,DF,Roma,26-216,1997,1.0,1.0,69.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,33.0,81.8,487.0,258.0,14.0,17.0,82.4,10.0,12.0,83.3,3.0,4.0,75.0,0.0,1.0,0.0,0.0,3.0,29.0,4.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,38.0,2.0,14.0,18.0,6.0,0.0,38.0,20.0,0.0,2.0,0.0,24.0,1.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,50.0 -Michele Cerofolini,it ITA,GK,Frosinone,24-260,1999,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,32.0,50.0,342.0,254.0,5.0,5.0,100.0,7.0,7.0,100.0,4.0,20.0,20.0,0.0,0.0,0.0,0.0,0.0,24.0,8.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,34.0,30.0,34.0,0.0,0.0,0.0,34.0,23.0,0.0,0.0,0.0,22.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Walid Cheddira,ma MAR,FW,Frosinone,25-242,1998,3.0,3.0,250.0,1.0,1.0,1.0,1.0,0.0,0.0,0.36,0.36,0.72,0.0,0.36,1.7,0.9,0.61,0.32,2.8,1.0,0.0,25.0,0.36,0.0,0.0,0.22,-0.7,-0.9,32.0,48.0,66.7,366.0,36.0,19.0,29.0,65.5,9.0,12.0,75.0,1.0,1.0,100.0,4.0,1.0,0.0,0.0,1.0,46.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,7.0,2.52,4.0,0.0,2.0,1.0,2.0,0.72,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,70.0,2.0,3.0,31.0,36.0,12.0,69.0,40.0,5.0,1.0,3.0,56.0,7.0,3.0,0.0,3.0,4.0,5.0,1.0,0.0,0.0,5.0,4.0,8.0,33.3 -Federico Chiesa,it ITA,FW,Juventus,25-331,1997,4.0,4.0,313.0,3.0,0.0,0.0,0.0,0.0,0.0,0.86,0.0,0.86,0.86,0.86,1.0,1.0,0.3,0.3,3.5,3.0,0.0,42.9,0.86,0.43,1.0,0.15,2.0,2.0,63.0,96.0,65.6,903.0,254.0,33.0,45.0,73.3,24.0,35.0,68.6,2.0,7.0,28.6,5.0,0.0,8.0,0.0,9.0,87.0,7.0,3.0,1.0,0.0,11.0,2.0,1.0,1.0,0.0,2.0,2.0,2.0,12.0,3.44,9.0,1.0,0.0,0.0,2.0,0.57,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,3.0,1.0,2.0,3.0,3.0,0.0,134.0,3.0,15.0,35.0,85.0,20.0,134.0,83.0,19.0,10.0,8.0,100.0,5.0,3.0,0.0,1.0,6.0,2.0,0.0,0.0,0.0,9.0,0.0,1.0,0.0 -Oliver Christensen,dk DEN,GK,Fiorentina,24-183,1999,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,66.0,86.0,76.7,1928.0,1329.0,8.0,8.0,100.0,28.0,30.0,93.3,29.0,47.0,61.7,0.0,1.0,0.0,0.0,0.0,75.0,11.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,90.0,68.0,90.0,0.0,0.0,0.0,90.0,61.0,0.0,0.0,0.0,59.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0 -Samuel Chukwueze,ng NGA,"FW,MF",Milan,24-122,1999,4.0,0.0,92.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.08,0.08,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,23.0,31.0,74.2,300.0,61.0,15.0,17.0,88.2,6.0,9.0,66.7,1.0,4.0,25.0,0.0,1.0,1.0,0.0,3.0,29.0,2.0,0.0,0.0,0.0,3.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.99,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.0,1.0,9.0,17.0,16.0,4.0,42.0,28.0,5.0,3.0,1.0,31.0,2.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,6.0,2.0,3.0,40.0 -Patrick Ciurria,it ITA,DF,Monza,28-224,1995,4.0,4.0,358.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.25,0.25,0.0,0.25,0.3,0.3,0.09,0.09,4.0,1.0,0.0,14.3,0.25,0.0,0.0,0.05,-0.3,-0.3,200.0,250.0,80.0,3217.0,1115.0,111.0,124.0,89.5,72.0,91.0,79.1,13.0,21.0,61.9,8.0,13.0,10.0,4.0,19.0,213.0,37.0,2.0,1.0,1.0,20.0,1.0,0.0,0.0,0.0,34.0,0.0,9.0,16.0,4.02,14.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,6.0,3.0,2.0,2.0,2.0,3.0,2.0,1.0,3.0,4.0,0.0,283.0,9.0,61.0,95.0,130.0,9.0,283.0,157.0,8.0,15.0,2.0,204.0,3.0,1.0,0.0,6.0,1.0,1.0,0.0,0.0,0.0,12.0,2.0,2.0,50.0 -Lorenzo Colombo,it ITA,FW,Monza,21-197,2002,2.0,1.0,97.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.93,0.93,0.0,0.93,0.3,0.3,0.27,0.27,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.29,-0.3,-0.3,17.0,24.0,70.8,242.0,64.0,10.0,15.0,66.7,3.0,4.0,75.0,2.0,3.0,66.7,2.0,0.0,2.0,0.0,4.0,21.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,4.0,3.71,4.0,0.0,0.0,0.0,1.0,0.93,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,31.0,1.0,6.0,14.0,11.0,3.0,31.0,17.0,2.0,1.0,0.0,22.0,5.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,2.0,33.3 -Andrea Colpani,it ITA,MF,Monza,24-133,1999,4.0,4.0,311.0,3.0,0.0,0.0,0.0,0.0,0.0,0.87,0.0,0.87,0.87,0.87,1.0,1.0,0.3,0.3,3.5,5.0,1.0,45.5,1.45,0.27,0.6,0.09,2.0,2.0,107.0,136.0,78.7,2075.0,518.0,43.0,48.0,89.6,44.0,51.0,86.3,19.0,30.0,63.3,9.0,10.0,9.0,2.0,24.0,116.0,19.0,2.0,0.0,2.0,15.0,13.0,5.0,6.0,0.0,4.0,1.0,3.0,19.0,5.5,13.0,4.0,0.0,0.0,1.0,0.29,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,166.0,1.0,9.0,56.0,102.0,15.0,166.0,101.0,12.0,6.0,4.0,129.0,3.0,4.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,10.0,0.0,2.0,0.0 -Andrea Consigli,it ITA,GK,Sassuolo,36-237,1987,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,87.0,129.0,67.4,2284.0,1517.0,20.0,20.0,100.0,34.0,35.0,97.1,31.0,72.0,43.1,0.0,3.0,0.0,0.0,0.0,88.0,41.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,136.0,115.0,136.0,0.0,0.0,0.0,136.0,67.0,0.0,0.0,0.0,62.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Diego Coppola,it ITA,DF,Hellas Verona,19-267,2003,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,69.0,92.0,75.0,1290.0,389.0,29.0,34.0,85.3,29.0,35.0,82.9,10.0,18.0,55.6,0.0,0.0,0.0,0.0,1.0,88.0,4.0,3.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,2.0,0.0,4.0,2.0,2.0,2.0,16.0,0.0,129.0,21.0,90.0,37.0,3.0,1.0,129.0,58.0,0.0,0.0,0.0,60.0,1.0,1.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,14.0,13.0,5.0,72.2 -Tommaso Corazza,it ITA,DF,Bologna,19-084,2004,2.0,0.0,34.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,20.0,23.0,87.0,288.0,87.0,9.0,10.0,90.0,6.0,6.0,100.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,1.0,18.0,5.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,2.0,5.29,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,33.0,3.0,13.0,11.0,10.0,4.0,33.0,15.0,2.0,1.0,1.0,18.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0 -Lassana Coulibaly,ml MLI,MF,Salernitana,27-164,1996,3.0,3.0,240.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.37,0.37,0.0,0.37,0.0,0.0,0.01,0.01,2.7,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,85.0,103.0,82.5,1387.0,404.0,40.0,45.0,88.9,38.0,44.0,86.4,5.0,8.0,62.5,4.0,10.0,1.0,0.0,10.0,98.0,5.0,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,1.5,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,3.0,1.0,2.0,4.0,5.0,0.0,132.0,5.0,20.0,87.0,25.0,5.0,132.0,75.0,3.0,3.0,0.0,82.0,7.0,4.0,0.0,4.0,6.0,0.0,0.0,0.0,0.0,14.0,3.0,2.0,60.0 -Mamadou Coulibaly,sn SEN,DF,Salernitana,24-230,1999,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,33.3,6.0,1.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,1.0,2.0,0.0,3.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Alessio Cragno,it ITA,GK,Sassuolo,29-085,1994,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,33.0,63.6,539.0,385.0,6.0,6.0,100.0,8.0,8.0,100.0,7.0,19.0,36.8,0.0,0.0,0.0,0.0,0.0,22.0,11.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,39.0,30.0,39.0,0.0,0.0,0.0,39.0,16.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Bryan Cristante,it ITA,MF,Roma,28-202,1995,4.0,4.0,360.0,1.0,2.0,0.0,0.0,0.0,0.0,0.25,0.5,0.75,0.25,0.75,0.3,0.3,0.08,0.08,4.0,1.0,0.0,11.1,0.25,0.11,1.0,0.03,0.7,0.7,200.0,240.0,83.3,3451.0,1095.0,88.0,102.0,86.3,87.0,93.0,93.5,19.0,27.0,70.4,9.0,20.0,5.0,0.0,24.0,234.0,3.0,3.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,22.0,5.5,20.0,0.0,2.0,0.0,4.0,1.0,3.0,0.0,1.0,0.0,0.0,5.0,3.0,3.0,2.0,0.0,1.0,0.0,1.0,4.0,2.0,0.0,269.0,5.0,55.0,159.0,60.0,11.0,269.0,171.0,8.0,7.0,0.0,210.0,4.0,6.0,0.0,11.0,1.0,0.0,0.0,0.0,0.0,32.0,10.0,9.0,52.6 -Juan Cuadrado,co COL,DF,Inter,35-118,1988,3.0,0.0,65.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.38,1.38,0.0,1.38,0.1,0.1,0.09,0.09,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,36.0,43.0,83.7,632.0,114.0,16.0,16.0,100.0,12.0,14.0,85.7,5.0,9.0,55.6,3.0,1.0,1.0,1.0,1.0,41.0,2.0,0.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,4.0,5.54,4.0,0.0,0.0,0.0,1.0,1.38,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,52.0,0.0,10.0,24.0,19.0,6.0,52.0,37.0,8.0,3.0,4.0,40.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 -Marvin Cuni,al ALB,FW,Frosinone,22-073,2001,3.0,1.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,23.0,69.6,146.0,6.0,9.0,11.0,81.8,4.0,6.0,66.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,0.0,1.0,20.0,15.0,4.0,36.0,20.0,0.0,0.0,0.0,32.0,6.0,4.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,3.0,5.0,7.0,41.7 -Danilo D'Ambrosio,it ITA,DF,Monza,35-012,1988,2.0,1.0,89.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,70.0,75.0,93.3,1251.0,362.0,28.0,28.0,100.0,37.0,39.0,94.9,5.0,7.0,71.4,1.0,5.0,1.0,0.0,5.0,68.0,7.0,3.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,1.01,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,4.0,1.0,0.0,2.0,1.0,1.0,3.0,2.0,0.0,87.0,12.0,36.0,45.0,6.0,0.0,87.0,50.0,3.0,0.0,0.0,60.0,0.0,0.0,0.0,3.0,1.0,1.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 -Danilo,br BRA,DF,Juventus,32-068,1991,4.0,4.0,360.0,1.0,0.0,0.0,0.0,1.0,0.0,0.25,0.0,0.25,0.25,0.25,0.4,0.4,0.1,0.1,4.0,1.0,0.0,20.0,0.25,0.2,1.0,0.08,0.6,0.6,228.0,265.0,86.0,4322.0,1766.0,90.0,96.0,93.8,107.0,117.0,91.5,28.0,45.0,62.2,3.0,27.0,3.0,1.0,26.0,257.0,8.0,5.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,11.0,2.75,10.0,0.0,1.0,0.0,1.0,0.25,0.0,0.0,1.0,0.0,0.0,6.0,4.0,4.0,2.0,0.0,3.0,1.0,2.0,6.0,12.0,0.0,301.0,32.0,125.0,138.0,40.0,5.0,301.0,150.0,2.0,2.0,0.0,209.0,1.0,0.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,23.0,7.0,1.0,87.5 -Matteo Darmian,it ITA,DF,Inter,33-293,1989,4.0,4.0,353.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,153.0,175.0,87.4,2782.0,915.0,63.0,70.0,90.0,77.0,78.0,98.7,11.0,19.0,57.9,1.0,15.0,0.0,0.0,12.0,174.0,1.0,1.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,0.76,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,4.0,4.0,5.0,1.0,6.0,2.0,4.0,2.0,10.0,0.0,206.0,23.0,88.0,111.0,7.0,1.0,206.0,142.0,3.0,2.0,0.0,148.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,12.0,3.0,6.0,33.3 -Paweł Dawidowicz,pl POL,DF,Hellas Verona,28-124,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,186.0,226.0,82.3,4150.0,1560.0,38.0,50.0,76.0,109.0,121.0,90.1,37.0,51.0,72.5,1.0,9.0,1.0,0.0,14.0,213.0,12.0,8.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,1.0,2.0,0.5,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,5.0,3.0,4.0,0.0,2.0,1.0,1.0,3.0,15.0,0.0,255.0,24.0,125.0,128.0,5.0,1.0,255.0,157.0,2.0,2.0,0.0,158.0,2.0,1.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,26.0,14.0,2.0,87.5 -Charles De Ketelaere,be BEL,FW,Atalanta,22-195,2001,4.0,2.0,229.0,1.0,1.0,0.0,0.0,0.0,0.0,0.39,0.39,0.79,0.39,0.79,0.5,0.5,0.19,0.19,2.5,2.0,0.0,40.0,0.79,0.2,0.5,0.1,0.5,0.5,79.0,101.0,78.2,1137.0,320.0,43.0,55.0,78.2,25.0,31.0,80.6,5.0,7.0,71.4,5.0,6.0,4.0,1.0,15.0,96.0,5.0,3.0,1.0,0.0,5.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,7.0,2.75,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,1.0,1.0,4.0,3.0,0.0,3.0,1.0,1.0,0.0,134.0,0.0,7.0,54.0,77.0,13.0,134.0,87.0,11.0,8.0,4.0,100.0,6.0,6.0,0.0,3.0,1.0,2.0,0.0,0.0,0.0,11.0,5.0,3.0,62.5 -Lorenzo De Silvestri,it ITA,DF,Bologna,35-121,1988,2.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,45.0,48.0,93.8,756.0,234.0,19.0,19.0,100.0,25.0,28.0,89.3,1.0,1.0,100.0,0.0,0.0,1.0,1.0,4.0,45.0,3.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,1.0,1.34,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,0.0,58.0,5.0,25.0,31.0,2.0,0.0,58.0,36.0,0.0,0.0,0.0,39.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,100.0 -Koni De Winter,be BEL,DF,Genoa,21-101,2002,1.0,1.0,90.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.04,0.04,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,12.0,26.0,46.2,172.0,80.0,6.0,12.0,50.0,6.0,9.0,66.7,0.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,17.0,9.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,9.0,0.0,2.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,33.0,9.0,17.0,11.0,5.0,2.0,33.0,13.0,1.0,0.0,1.0,12.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,60.0 -Grégoire Defrel,mq MTQ,FW,Sassuolo,32-096,1991,1.0,1.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,18.0,83.3,264.0,62.0,5.0,6.0,83.3,8.0,10.0,80.0,2.0,2.0,100.0,1.0,3.0,0.0,0.0,3.0,17.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,2.34,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,21.0,2.0,5.0,11.0,5.0,2.0,21.0,16.0,0.0,0.0,0.0,17.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 -Alessandro Deiola,it ITA,MF,Cagliari,28-051,1995,4.0,1.0,125.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.9,0.68,0.68,1.4,0.0,1.0,0.0,0.0,0.0,0.0,0.14,-0.9,-0.9,32.0,45.0,71.1,519.0,171.0,17.0,19.0,89.5,13.0,16.0,81.3,2.0,7.0,28.6,1.0,3.0,0.0,0.0,7.0,45.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.44,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,59.0,1.0,13.0,27.0,19.0,6.0,59.0,33.0,2.0,1.0,0.0,30.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,9.0,2.0,1.0,66.7 -Mattia Destro,it ITA,FW,Empoli,32-185,1991,2.0,1.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,10.0,13.0,76.9,146.0,7.0,5.0,5.0,100.0,5.0,7.0,71.4,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,7.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,22.0,0.0,2.0,11.0,9.0,2.0,22.0,11.0,1.0,1.0,0.0,13.0,2.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,40.0 -Federico Di Francesco,it ITA,"FW,MF",Lecce,29-099,1994,2.0,0.0,15.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,6.0,6.0,6.0,0.1,0.1,0.53,0.53,0.2,1.0,0.0,50.0,6.0,0.5,1.0,0.04,0.9,0.9,6.0,8.0,75.0,90.0,43.0,1.0,2.0,50.0,2.0,2.0,100.0,1.0,2.0,50.0,0.0,1.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,0.0,2.0,8.0,5.0,3.0,15.0,9.0,1.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Michele Di Gregorio,it ITA,GK,Monza,26-056,1997,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,105.0,134.0,78.4,2487.0,1416.0,22.0,23.0,95.7,57.0,57.0,100.0,24.0,51.0,47.1,0.0,2.0,0.0,0.0,0.0,105.0,28.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,143.0,112.0,143.0,0.0,0.0,0.0,143.0,84.0,0.0,0.0,0.0,81.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Giovanni Di Lorenzo,it ITA,DF,Napoli,30-048,1993,4.0,4.0,360.0,1.0,2.0,0.0,0.0,0.0,0.0,0.25,0.5,0.75,0.25,0.75,0.5,0.5,0.14,0.14,4.0,1.0,0.0,33.3,0.25,0.33,1.0,0.18,0.5,0.5,205.0,249.0,82.3,3097.0,1060.0,121.0,129.0,93.8,67.0,87.0,77.0,13.0,21.0,61.9,12.0,18.0,14.0,4.0,24.0,215.0,33.0,4.0,1.0,0.0,17.0,0.0,0.0,0.0,0.0,29.0,1.0,4.0,20.0,5.0,19.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,10.0,8.0,5.0,5.0,0.0,2.0,1.0,1.0,2.0,3.0,0.0,275.0,5.0,48.0,132.0,97.0,13.0,275.0,174.0,17.0,7.0,4.0,204.0,2.0,1.0,0.0,2.0,3.0,1.0,0.0,0.0,0.0,13.0,0.0,2.0,0.0 -Alessandro Di Pardo,it ITA,"MF,DF",Cagliari,24-065,1999,4.0,0.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,43.0,64.0,67.2,708.0,296.0,23.0,28.0,82.1,16.0,22.0,72.7,3.0,7.0,42.9,1.0,2.0,2.0,1.0,5.0,57.0,7.0,0.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,7.0,0.0,4.0,1.0,0.62,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,1.0,1.0,2.0,2.0,0.0,80.0,7.0,29.0,29.0,23.0,1.0,80.0,47.0,1.0,0.0,0.0,40.0,1.0,2.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,16.0,1.0,1.0,50.0 -Boulaye Dia,sn SEN,"FW,DF",Salernitana,26-309,1996,2.0,1.0,115.0,1.0,0.0,0.0,0.0,0.0,0.0,0.78,0.0,0.78,0.78,0.78,0.3,0.3,0.22,0.22,1.3,1.0,0.0,100.0,0.78,1.0,1.0,0.29,0.7,0.7,18.0,21.0,85.7,336.0,90.0,11.0,13.0,84.6,4.0,5.0,80.0,3.0,3.0,100.0,1.0,4.0,1.0,0.0,3.0,19.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.78,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,31.0,1.0,1.0,14.0,16.0,4.0,31.0,19.0,0.0,2.0,2.0,23.0,2.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,6.0,14.3 -Federico Dimarco,it ITA,DF,Inter,25-315,1997,4.0,4.0,268.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,1.01,1.01,0.0,1.01,0.4,0.4,0.13,0.13,3.0,3.0,1.0,37.5,1.01,0.0,0.0,0.05,-0.4,-0.4,135.0,169.0,79.9,2225.0,836.0,69.0,76.0,90.8,44.0,54.0,81.5,15.0,29.0,51.7,13.0,7.0,14.0,8.0,20.0,137.0,32.0,2.0,0.0,3.0,30.0,9.0,2.0,7.0,0.0,21.0,0.0,1.0,25.0,8.4,20.0,3.0,1.0,0.0,4.0,1.34,3.0,0.0,1.0,0.0,0.0,8.0,6.0,4.0,3.0,1.0,2.0,1.0,1.0,2.0,5.0,0.0,199.0,7.0,33.0,69.0,101.0,9.0,199.0,117.0,7.0,3.0,0.0,125.0,4.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,18.0,0.0,1.0,0.0 -Berat Djimsiti,al ALB,DF,Atalanta,30-214,1993,3.0,3.0,254.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,119.0,135.0,88.1,2215.0,781.0,42.0,43.0,97.7,62.0,70.0,88.6,12.0,15.0,80.0,0.0,3.0,0.0,0.0,7.0,130.0,3.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.35,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,7.0,4.0,3.0,4.0,5.0,0.0,158.0,16.0,87.0,63.0,9.0,2.0,158.0,89.0,0.0,0.0,0.0,105.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,14.0,5.0,7.0,41.7 -Dodô,br BRA,DF,Fiorentina,24-308,1998,4.0,3.0,262.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,2.9,1.0,0.0,100.0,0.34,0.0,0.0,0.06,-0.1,-0.1,152.0,185.0,82.2,2804.0,957.0,59.0,67.0,88.1,73.0,86.0,84.9,18.0,26.0,69.2,6.0,14.0,6.0,2.0,26.0,158.0,26.0,4.0,1.0,1.0,8.0,0.0,0.0,0.0,0.0,22.0,1.0,0.0,6.0,2.06,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,2.0,0.0,2.0,3.0,6.0,0.0,209.0,9.0,43.0,113.0,54.0,1.0,209.0,142.0,12.0,6.0,1.0,147.0,4.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,10.0,1.0,0.0,100.0 -Josh Doig,sct SCO,DF,Hellas Verona,21-126,2002,4.0,4.0,298.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.06,0.06,3.3,1.0,0.0,20.0,0.3,0.0,0.0,0.04,-0.2,-0.2,88.0,116.0,75.9,1625.0,562.0,34.0,40.0,85.0,45.0,53.0,84.9,7.0,15.0,46.7,1.0,8.0,1.0,1.0,5.0,91.0,24.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,24.0,1.0,2.0,3.0,0.91,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,9.0,0.0,145.0,6.0,33.0,76.0,38.0,8.0,145.0,69.0,5.0,4.0,1.0,82.0,4.0,1.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,12.0,3.0,2.0,60.0 -Nicolás Domínguez,ar ARG,MF,Bologna,25-085,1998,2.0,1.0,101.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,83.0,92.0,90.2,1276.0,370.0,45.0,49.0,91.8,36.0,40.0,90.0,2.0,2.0,100.0,1.0,5.0,1.0,0.0,9.0,90.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,2.0,1.78,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,3.0,0.0,3.0,0.0,2.0,0.0,103.0,2.0,23.0,69.0,12.0,0.0,103.0,39.0,1.0,2.0,0.0,79.0,1.0,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,7.0,1.0,0.0,100.0 -Patrick Dorgu,dk DEN,DF,Lecce,18-330,2004,4.0,1.0,140.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,70.0,84.0,83.3,997.0,306.0,37.0,40.0,92.5,27.0,32.0,84.4,1.0,3.0,33.3,1.0,2.0,1.0,0.0,4.0,56.0,28.0,3.0,0.0,0.0,4.0,4.0,0.0,0.0,0.0,21.0,0.0,3.0,7.0,4.5,2.0,4.0,1.0,0.0,1.0,0.64,0.0,0.0,1.0,0.0,0.0,5.0,3.0,3.0,2.0,0.0,2.0,0.0,2.0,0.0,2.0,0.0,106.0,4.0,36.0,37.0,34.0,3.0,106.0,55.0,1.0,1.0,0.0,50.0,3.0,0.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,13.0,1.0,6.0,14.3 -Alberto Dossena,it ITA,DF,Cagliari,24-343,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.18,-0.2,-0.2,104.0,131.0,79.4,2223.0,770.0,28.0,34.0,82.4,57.0,67.0,85.1,18.0,25.0,72.0,0.0,10.0,0.0,0.0,12.0,127.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,5.0,1.0,0.0,8.0,5.0,3.0,4.0,24.0,1.0,181.0,41.0,118.0,60.0,5.0,2.0,181.0,91.0,1.0,0.0,0.0,76.0,2.0,1.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,37.0,9.0,11.0,45.0 -Radu Drăgușin,ro ROU,DF,Genoa,21-230,2002,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,88.0,108.0,81.5,1594.0,437.0,39.0,44.0,88.6,37.0,42.0,88.1,11.0,19.0,57.9,1.0,0.0,0.0,0.0,2.0,91.0,17.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,3.0,0.0,0.0,5.0,3.0,2.0,4.0,30.0,2.0,156.0,59.0,114.0,39.0,3.0,1.0,156.0,61.0,1.0,1.0,1.0,68.0,1.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,11.0,8.0,5.0,61.5 -Ondrej Duda,sk SVK,MF,Hellas Verona,28-290,1994,4.0,4.0,303.0,1.0,1.0,0.0,0.0,1.0,0.0,0.3,0.3,0.59,0.3,0.59,0.7,0.7,0.21,0.21,3.4,1.0,0.0,50.0,0.3,0.5,1.0,0.36,0.3,0.3,78.0,103.0,75.7,1502.0,550.0,31.0,37.0,83.8,32.0,36.0,88.9,15.0,24.0,62.5,10.0,10.0,3.0,0.0,13.0,85.0,16.0,10.0,2.0,2.0,12.0,6.0,3.0,3.0,0.0,0.0,2.0,5.0,14.0,4.17,7.0,5.0,0.0,1.0,1.0,0.3,1.0,0.0,0.0,0.0,0.0,5.0,2.0,1.0,3.0,1.0,3.0,1.0,2.0,4.0,4.0,0.0,133.0,7.0,32.0,71.0,33.0,3.0,133.0,66.0,1.0,0.0,0.0,62.0,7.0,0.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,22.0,0.0,3.0,0.0 -Denzel Dumfries,nl NED,DF,Inter,27-156,1996,4.0,4.0,295.0,1.0,2.0,0.0,0.0,0.0,0.0,0.31,0.61,0.92,0.31,0.92,0.5,0.5,0.14,0.14,3.3,1.0,0.0,20.0,0.31,0.2,1.0,0.09,0.5,0.5,76.0,111.0,68.5,1232.0,413.0,34.0,44.0,77.3,32.0,48.0,66.7,5.0,10.0,50.0,8.0,4.0,6.0,2.0,10.0,93.0,18.0,0.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,18.0,0.0,2.0,10.0,3.05,8.0,1.0,1.0,0.0,2.0,0.61,2.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,3.0,2.0,1.0,0.0,3.0,0.0,144.0,4.0,24.0,69.0,52.0,11.0,144.0,91.0,4.0,4.0,1.0,97.0,6.0,2.0,0.0,4.0,4.0,1.0,0.0,0.0,0.0,10.0,2.0,3.0,40.0 -Alfred Duncan,gh GHA,MF,Fiorentina,30-195,1993,3.0,2.0,178.0,1.0,2.0,0.0,0.0,0.0,0.0,0.51,1.01,1.52,0.51,1.52,0.7,0.7,0.35,0.35,2.0,1.0,0.0,50.0,0.51,0.5,1.0,0.34,0.3,0.3,68.0,81.0,84.0,1416.0,453.0,22.0,24.0,91.7,36.0,41.0,87.8,10.0,13.0,76.9,8.0,11.0,4.0,3.0,15.0,76.0,5.0,1.0,1.0,1.0,7.0,2.0,1.0,1.0,0.0,1.0,0.0,3.0,8.0,4.07,6.0,1.0,0.0,0.0,2.0,1.02,1.0,1.0,0.0,0.0,0.0,7.0,6.0,1.0,3.0,3.0,4.0,2.0,2.0,0.0,1.0,0.0,94.0,3.0,10.0,54.0,30.0,2.0,94.0,56.0,1.0,1.0,0.0,59.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,10.0,1.0,4.0,20.0 -Paulo Dybala,ar ARG,FW,Roma,29-310,1993,2.0,2.0,130.0,2.0,0.0,1.0,1.0,2.0,0.0,1.38,0.0,1.38,0.69,0.69,1.6,0.8,1.08,0.54,1.4,4.0,1.0,66.7,2.77,0.17,0.25,0.13,0.4,0.2,51.0,62.0,82.3,754.0,195.0,33.0,36.0,91.7,13.0,16.0,81.3,4.0,8.0,50.0,1.0,3.0,1.0,0.0,7.0,54.0,7.0,1.0,0.0,0.0,6.0,4.0,0.0,4.0,0.0,0.0,1.0,1.0,5.0,3.46,3.0,1.0,0.0,0.0,1.0,0.69,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,79.0,1.0,3.0,34.0,42.0,7.0,78.0,50.0,9.0,3.0,5.0,60.0,0.0,3.0,0.0,1.0,3.0,1.0,0.0,0.0,0.0,5.0,1.0,2.0,33.3 -Festy Ebosele,ie IRL,DF,Udinese,21-050,2002,4.0,2.0,172.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.02,-0.1,-0.1,37.0,50.0,74.0,490.0,210.0,23.0,29.0,79.3,10.0,13.0,76.9,2.0,3.0,66.7,1.0,2.0,2.0,0.0,4.0,43.0,7.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,7.0,0.0,2.0,7.0,3.66,4.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,5.0,0.0,0.0,3.0,0.0,3.0,0.0,1.0,0.0,70.0,3.0,19.0,19.0,33.0,6.0,70.0,42.0,10.0,1.0,3.0,42.0,4.0,2.0,0.0,2.0,3.0,0.0,0.0,1.0,0.0,7.0,0.0,3.0,0.0 -Enzo Ebosse,cm CMR,DF,Udinese,24-194,1999,1.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,222.0,57.0,4.0,4.0,100.0,7.0,9.0,77.8,1.0,2.0,50.0,0.0,1.0,0.0,0.0,1.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,11.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,17.0,5.0,9.0,8.0,0.0,0.0,17.0,12.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 -Tyronne Ebuehi,ng NGA,DF,Empoli,27-279,1995,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,66.0,93.0,71.0,1121.0,343.0,30.0,38.0,78.9,26.0,37.0,70.3,7.0,11.0,63.6,2.0,5.0,1.0,0.0,9.0,74.0,19.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,18.0,0.0,4.0,3.0,1.5,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,2.0,1.0,1.0,0.0,2.0,0.0,110.0,3.0,37.0,54.0,19.0,5.0,110.0,56.0,8.0,2.0,1.0,62.0,5.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,8.0,2.0,5.0,28.6 -Éderson,br BRA,MF,Atalanta,24-076,1999,4.0,3.0,315.0,1.0,1.0,0.0,0.0,0.0,0.0,0.29,0.29,0.57,0.29,0.57,0.4,0.4,0.1,0.1,3.5,2.0,0.0,40.0,0.57,0.2,0.5,0.07,0.6,0.6,162.0,195.0,83.1,2965.0,1042.0,62.0,70.0,88.6,83.0,90.0,92.2,15.0,25.0,60.0,5.0,23.0,7.0,1.0,32.0,192.0,2.0,2.0,1.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,11.0,3.14,11.0,0.0,0.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,15.0,7.0,7.0,6.0,2.0,6.0,0.0,6.0,10.0,5.0,0.0,243.0,11.0,52.0,137.0,56.0,3.0,243.0,166.0,5.0,7.0,0.0,167.0,1.0,6.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,22.0,7.0,2.0,77.8 -Emmanuel Ekong,se SWE,FW,Empoli,21-088,2002,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,12.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,18.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,3.0,1.0,1.0,4.0,4.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Caleb Ekuban,gh GHA,"FW,DF",Genoa,29-182,1994,3.0,0.0,69.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.11,0.11,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,8.0,15.0,53.3,157.0,79.0,3.0,8.0,37.5,3.0,3.0,100.0,2.0,2.0,100.0,2.0,2.0,1.0,0.0,3.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.14,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,28.0,0.0,2.0,13.0,15.0,3.0,28.0,16.0,0.0,1.0,1.0,17.0,4.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,66.7 -Elif Elmas,mk MKD,FW,Napoli,23-362,1999,3.0,1.0,67.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.7,1.0,0.0,100.0,1.34,0.0,0.0,0.02,0.0,0.0,40.0,42.0,95.2,519.0,88.0,29.0,30.0,96.7,9.0,9.0,100.0,1.0,1.0,100.0,2.0,1.0,0.0,0.0,3.0,40.0,2.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,3.0,4.09,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,52.0,1.0,4.0,25.0,23.0,4.0,52.0,31.0,2.0,3.0,1.0,40.0,2.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Martin Erlic,hr CRO,DF,Sassuolo,25-240,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,118.0,144.0,81.9,2230.0,988.0,53.0,57.0,93.0,50.0,63.0,79.4,14.0,23.0,60.9,0.0,5.0,0.0,0.0,9.0,137.0,7.0,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,4.0,10.0,0.0,0.0,7.0,4.0,3.0,5.0,13.0,0.0,183.0,33.0,114.0,66.0,3.0,2.0,183.0,73.0,1.0,1.0,1.0,96.0,1.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,17.0,7.0,2.0,77.8 -Giovanni Fabbian,it ITA,"MF,FW",Bologna,20-250,2003,3.0,0.0,19.0,1.0,0.0,0.0,0.0,0.0,0.0,4.74,0.0,4.74,4.74,4.74,0.8,0.8,4.02,4.02,0.2,1.0,0.0,50.0,4.74,0.5,1.0,0.42,0.2,0.2,3.0,5.0,60.0,22.0,2.0,3.0,5.0,60.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,3.0,3.0,4.0,3.0,10.0,9.0,0.0,0.0,0.0,7.0,2.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Nicolò Fagioli,it ITA,MF,Juventus,22-221,2001,3.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.14,0.14,1.6,1.0,1.0,25.0,0.63,0.0,0.0,0.06,-0.2,-0.2,55.0,62.0,88.7,974.0,282.0,27.0,27.0,100.0,20.0,22.0,90.9,7.0,11.0,63.6,2.0,7.0,4.0,1.0,9.0,56.0,6.0,0.0,0.0,1.0,6.0,4.0,0.0,3.0,0.0,2.0,0.0,0.0,6.0,3.8,4.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,81.0,0.0,8.0,37.0,36.0,2.0,81.0,47.0,3.0,1.0,1.0,55.0,5.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Wladimiro Falcone,it ITA,GK,Lecce,28-162,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,86.0,121.0,71.1,2082.0,1671.0,29.0,29.0,100.0,28.0,29.0,96.6,22.0,55.0,40.0,0.0,0.0,0.0,0.0,0.0,73.0,47.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,129.0,121.0,129.0,0.0,0.0,0.0,129.0,67.0,0.0,0.0,0.0,50.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Davide Faraoni,it ITA,DF,Hellas Verona,31-331,1991,3.0,2.0,174.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.52,0.52,0.0,0.52,0.1,0.1,0.03,0.03,1.9,1.0,0.0,50.0,0.52,0.0,0.0,0.03,-0.1,-0.1,63.0,92.0,68.5,1181.0,421.0,28.0,33.0,84.8,20.0,28.0,71.4,12.0,20.0,60.0,2.0,5.0,1.0,1.0,7.0,71.0,18.0,2.0,1.0,2.0,6.0,1.0,0.0,0.0,0.0,15.0,3.0,3.0,5.0,2.59,4.0,0.0,0.0,1.0,1.0,0.52,1.0,0.0,0.0,0.0,0.0,5.0,5.0,2.0,2.0,1.0,3.0,2.0,1.0,1.0,10.0,0.0,123.0,8.0,28.0,65.0,32.0,3.0,123.0,59.0,6.0,2.0,0.0,62.0,6.0,0.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,18.0,5.0,2.0,71.4 -Federico Fazio,ar ARG,DF,Salernitana,36-188,1987,2.0,1.0,113.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.3,1.0,0.0,100.0,0.8,0.0,0.0,0.11,-0.1,-0.1,57.0,74.0,77.0,987.0,422.0,27.0,29.0,93.1,23.0,31.0,74.2,5.0,10.0,50.0,0.0,4.0,0.0,0.0,2.0,71.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.59,2.0,0.0,0.0,0.0,1.0,0.8,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,2.0,3.0,0.0,83.0,4.0,39.0,40.0,4.0,2.0,83.0,60.0,0.0,0.0,0.0,55.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,10.0,6.0,1.0,85.7 -Jacopo Fazzini,it ITA,MF,Empoli,20-189,2003,3.0,2.0,150.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.1,0.1,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.2,-0.2,67.0,79.0,84.8,1091.0,308.0,31.0,33.0,93.9,28.0,30.0,93.3,5.0,13.0,38.5,5.0,5.0,0.0,0.0,9.0,69.0,10.0,3.0,0.0,0.0,7.0,6.0,2.0,3.0,0.0,1.0,0.0,0.0,7.0,4.2,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,2.0,0.0,2.0,0.0,2.0,2.0,0.0,0.0,102.0,2.0,18.0,57.0,29.0,2.0,102.0,56.0,1.0,2.0,0.0,60.0,1.0,5.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,11.0,0.0,4.0,0.0 -Lewis Ferguson,sct SCO,MF,Bologna,24-028,1999,4.0,4.0,356.0,1.0,0.0,0.0,0.0,1.0,0.0,0.25,0.0,0.25,0.25,0.25,0.5,0.5,0.13,0.13,4.0,2.0,0.0,20.0,0.51,0.1,0.5,0.05,0.5,0.5,209.0,238.0,87.8,2792.0,572.0,125.0,137.0,91.2,67.0,74.0,90.5,3.0,5.0,60.0,3.0,13.0,4.0,0.0,16.0,237.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,10.0,2.53,10.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,1.0,1.0,2.0,0.0,2.0,0.0,2.0,0.0,267.0,6.0,34.0,157.0,77.0,14.0,267.0,162.0,6.0,2.0,2.0,219.0,3.0,1.0,0.0,7.0,5.0,1.0,0.0,0.0,0.0,19.0,3.0,9.0,25.0 -João Ferreira,pt POR,DF,Udinese,22-183,2001,4.0,2.0,188.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.1,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,60.0,73.0,82.2,1009.0,337.0,31.0,34.0,91.2,21.0,24.0,87.5,5.0,10.0,50.0,1.0,3.0,1.0,1.0,2.0,59.0,14.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,14.0,0.0,1.0,3.0,1.44,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,1.0,1.0,2.0,0.0,2.0,3.0,2.0,0.0,95.0,4.0,25.0,39.0,31.0,1.0,95.0,54.0,2.0,3.0,0.0,49.0,5.0,3.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,13.0,0.0,0.0,0.0 -Alessandro Florenzi,it ITA,DF,Milan,32-194,1991,2.0,0.0,18.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,16.0,100.0,321.0,57.0,5.0,5.0,100.0,9.0,9.0,100.0,2.0,2.0,100.0,1.0,1.0,0.0,0.0,0.0,11.0,5.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,18.0,0.0,5.0,10.0,3.0,1.0,18.0,10.0,0.0,0.0,0.0,11.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Michael Folorunsho,ng NGA,"MF,FW",Hellas Verona,25-226,1998,4.0,4.0,314.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.5,1.0,0.0,50.0,0.29,0.0,0.0,0.03,-0.1,-0.1,45.0,71.0,63.4,765.0,148.0,21.0,25.0,84.0,17.0,28.0,60.7,5.0,9.0,55.6,2.0,1.0,1.0,0.0,6.0,69.0,1.0,0.0,1.0,2.0,5.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,4.0,1.15,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,1.0,1.0,5.0,0.0,5.0,0.0,7.0,0.0,109.0,7.0,12.0,66.0,34.0,3.0,109.0,66.0,4.0,6.0,0.0,65.0,7.0,3.0,0.0,6.0,11.0,2.0,0.0,0.0,0.0,16.0,6.0,15.0,28.6 -Davide Frattesi,it ITA,"MF,FW",Inter,23-334,1999,4.0,0.0,90.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,0.6,0.6,0.65,0.65,1.0,1.0,0.0,50.0,1.0,0.5,1.0,0.32,0.4,0.4,23.0,25.0,92.0,341.0,90.0,10.0,10.0,100.0,10.0,11.0,90.9,1.0,1.0,100.0,0.0,1.0,1.0,0.0,4.0,23.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,3.0,0.0,34.0,3.0,9.0,16.0,9.0,2.0,34.0,24.0,4.0,2.0,1.0,24.0,0.0,3.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,66.7 -Morten Frendrup,dk DEN,MF,Genoa,22-167,2001,4.0,4.0,360.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.25,0.25,0.0,0.25,0.1,0.1,0.02,0.02,4.0,1.0,0.0,50.0,0.25,0.0,0.0,0.04,-0.1,-0.1,78.0,108.0,72.2,1151.0,261.0,44.0,55.0,80.0,27.0,35.0,77.1,3.0,6.0,50.0,1.0,9.0,2.0,0.0,13.0,106.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,0.75,2.0,0.0,1.0,0.0,2.0,0.5,1.0,0.0,1.0,0.0,0.0,13.0,9.0,5.0,7.0,1.0,5.0,1.0,4.0,5.0,4.0,0.0,151.0,7.0,43.0,81.0,30.0,4.0,151.0,61.0,1.0,1.0,0.0,64.0,5.0,1.0,0.0,7.0,5.0,1.0,0.0,0.0,0.0,24.0,2.0,3.0,40.0 -Remo Freuler,ch SUI,MF,Bologna,31-159,1992,1.0,1.0,79.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.0,46.0,91.3,665.0,203.0,20.0,23.0,87.0,18.0,19.0,94.7,2.0,2.0,100.0,0.0,3.0,0.0,0.0,3.0,44.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,1.14,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,2.0,1.0,1.0,1.0,2.0,1.0,58.0,3.0,22.0,27.0,9.0,2.0,58.0,32.0,0.0,0.0,0.0,42.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0 -Roberto Gagliardini,it ITA,MF,Monza,29-167,1994,4.0,4.0,315.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.16,0.16,3.5,2.0,0.0,20.0,0.57,0.0,0.0,0.05,-0.5,-0.5,199.0,219.0,90.9,3550.0,749.0,85.0,88.0,96.6,100.0,110.0,90.9,11.0,15.0,73.3,2.0,18.0,1.0,0.0,18.0,213.0,6.0,3.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,2.0,0.0,2.0,10.0,2.86,9.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,10.0,9.0,7.0,1.0,3.0,1.0,2.0,4.0,4.0,0.0,272.0,12.0,54.0,146.0,74.0,7.0,272.0,173.0,10.0,8.0,1.0,201.0,2.0,6.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,20.0,7.0,2.0,77.8 -Antonino Gallo,it ITA,DF,Lecce,23-259,2000,4.0,3.0,220.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.41,0.41,0.0,0.41,0.0,0.0,0.0,0.0,2.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,90.0,119.0,75.6,1563.0,607.0,42.0,49.0,85.7,40.0,49.0,81.6,6.0,15.0,40.0,3.0,11.0,6.0,3.0,20.0,93.0,26.0,7.0,0.0,1.0,7.0,1.0,0.0,0.0,0.0,18.0,0.0,4.0,5.0,2.05,5.0,0.0,0.0,0.0,2.0,0.82,2.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,2.0,0.0,4.0,0.0,4.0,1.0,8.0,0.0,144.0,8.0,40.0,68.0,37.0,1.0,144.0,76.0,2.0,2.0,1.0,81.0,2.0,0.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,7.0,3.0,0.0,100.0 -Luca Garritano,it ITA,"FW,MF",Frosinone,29-222,1994,3.0,0.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.59,0.59,0.6,1.0,0.0,20.0,1.67,0.0,0.0,0.07,-0.4,-0.4,9.0,17.0,52.9,151.0,53.0,5.0,7.0,71.4,3.0,6.0,50.0,1.0,4.0,25.0,1.0,2.0,0.0,0.0,1.0,15.0,2.0,0.0,0.0,0.0,4.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,3.33,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,4.0,0.0,4.0,0.0,0.0,0.0,28.0,2.0,10.0,8.0,11.0,3.0,28.0,15.0,1.0,0.0,0.0,11.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 -Federico Gatti,it ITA,DF,Juventus,25-089,1998,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,52.0,59.0,88.1,881.0,335.0,24.0,24.0,100.0,21.0,24.0,87.5,6.0,10.0,60.0,1.0,3.0,0.0,0.0,5.0,57.0,2.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,2.0,2.0,0.0,1.0,7.0,0.0,82.0,9.0,40.0,33.0,10.0,6.0,82.0,45.0,1.0,2.0,0.0,51.0,2.0,1.0,0.0,1.0,5.0,0.0,1.0,0.0,0.0,8.0,2.0,1.0,66.7 -Francesco Gelli,it ITA,"FW,MF",Frosinone,26-341,1996,4.0,4.0,352.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,129.0,154.0,83.8,1718.0,454.0,84.0,89.0,94.4,32.0,37.0,86.5,5.0,13.0,38.5,2.0,6.0,7.0,1.0,13.0,137.0,17.0,4.0,0.0,0.0,11.0,11.0,4.0,2.0,0.0,0.0,0.0,5.0,6.0,1.53,4.0,1.0,1.0,0.0,1.0,0.26,0.0,1.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,4.0,2.0,2.0,4.0,2.0,0.0,198.0,3.0,46.0,83.0,73.0,6.0,198.0,126.0,6.0,3.0,1.0,142.0,15.0,4.0,0.0,6.0,5.0,0.0,0.0,0.0,0.0,17.0,3.0,3.0,50.0 -Valentin Gendrey,fr FRA,DF,Lecce,23-092,2000,4.0,4.0,334.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.27,0.27,0.0,0.27,0.1,0.1,0.02,0.02,3.7,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,120.0,156.0,76.9,1907.0,995.0,70.0,79.0,88.6,43.0,53.0,81.1,7.0,18.0,38.9,3.0,12.0,1.0,1.0,14.0,114.0,42.0,4.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,38.0,0.0,5.0,5.0,1.35,5.0,0.0,0.0,0.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,10.0,0.0,10.0,6.0,12.0,0.0,194.0,13.0,66.0,89.0,40.0,2.0,194.0,92.0,5.0,5.0,0.0,79.0,2.0,2.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,22.0,7.0,4.0,63.6 -Gvidas Gineitis,lt LTU,MF,Torino,19-159,2004,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,7.0,100.0,100.0,8.0,6.0,6.0,100.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,11.0,0.0,2.0,6.0,3.0,0.0,11.0,5.0,0.0,0.0,0.0,7.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Olivier Giroud,fr FRA,FW,Milan,36-356,1986,4.0,4.0,282.0,4.0,2.0,3.0,3.0,0.0,0.0,1.28,0.64,1.91,0.32,0.96,2.8,0.5,0.91,0.15,3.1,2.0,1.0,50.0,0.64,0.25,0.5,0.12,1.2,0.5,42.0,62.0,67.7,514.0,91.0,24.0,32.0,75.0,11.0,16.0,68.8,0.0,0.0,0.0,8.0,5.0,2.0,0.0,5.0,54.0,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,7.0,2.23,7.0,0.0,0.0,0.0,2.0,0.64,2.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,79.0,2.0,5.0,44.0,30.0,9.0,76.0,41.0,0.0,1.0,1.0,58.0,4.0,2.0,0.0,3.0,5.0,3.0,0.0,0.0,0.0,1.0,3.0,3.0,50.0 -Edoardo Goldaniga,it ITA,DF,Cagliari,29-323,1993,1.0,1.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,17.0,82.4,227.0,94.0,7.0,7.0,100.0,6.0,7.0,85.7,1.0,3.0,33.3,0.0,1.0,1.0,0.0,1.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,22.0,2.0,9.0,11.0,2.0,0.0,22.0,9.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 -Joan Gonzàlez,es ESP,MF,Lecce,21-232,2002,3.0,2.0,156.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,36.0,45.0,80.0,618.0,149.0,20.0,25.0,80.0,11.0,14.0,78.6,5.0,5.0,100.0,2.0,4.0,1.0,0.0,6.0,44.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.46,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,62.0,1.0,7.0,38.0,18.0,1.0,62.0,41.0,4.0,1.0,0.0,41.0,1.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,7.0,3.0,4.0,42.9 -Nicolás González,ar ARG,FW,Fiorentina,25-168,1998,4.0,4.0,277.0,2.0,1.0,0.0,0.0,0.0,0.0,0.65,0.32,0.97,0.65,0.97,0.7,0.7,0.22,0.22,3.1,3.0,0.0,37.5,0.97,0.25,0.67,0.08,1.3,1.3,79.0,112.0,70.5,1500.0,326.0,36.0,50.0,72.0,32.0,42.0,76.2,11.0,13.0,84.6,2.0,6.0,3.0,0.0,12.0,109.0,3.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,5.0,1.62,3.0,0.0,2.0,0.0,2.0,0.65,1.0,0.0,1.0,0.0,0.0,4.0,2.0,4.0,0.0,0.0,3.0,0.0,3.0,1.0,1.0,0.0,154.0,5.0,20.0,76.0,62.0,18.0,154.0,109.0,9.0,9.0,3.0,122.0,8.0,3.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,9.0,9.0,4.0,69.2 -Alberto Grassi,it ITA,MF,Empoli,28-198,1995,3.0,2.0,205.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,100.0,120.0,83.3,1717.0,618.0,42.0,46.0,91.3,48.0,57.0,84.2,6.0,11.0,54.5,1.0,14.0,0.0,0.0,9.0,113.0,7.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,3.0,1.32,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,2.0,0.0,2.0,4.0,2.0,0.0,143.0,6.0,25.0,104.0,15.0,2.0,143.0,85.0,2.0,1.0,0.0,94.0,4.0,0.0,0.0,4.0,6.0,0.0,0.0,0.0,1.0,13.0,5.0,4.0,55.6 -Mattéo Guendouzi,fr FRA,MF,Lazio,24-160,1999,2.0,0.0,39.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.26,0.26,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.1,-0.1,12.0,17.0,70.6,140.0,13.0,8.0,9.0,88.9,2.0,2.0,100.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,20.0,0.0,2.0,11.0,7.0,1.0,20.0,14.0,2.0,1.0,0.0,19.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.0 -Axel Guessand,fr FRA,DF,Udinese,18-319,2004,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,21.0,27.0,77.8,471.0,141.0,5.0,7.0,71.4,14.0,16.0,87.5,2.0,4.0,50.0,0.0,3.0,0.0,0.0,1.0,27.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,33.0,1.0,10.0,22.0,1.0,1.0,33.0,21.0,1.0,0.0,0.0,25.0,3.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 -Albert Guðmundsson,is ISL,"MF,FW",Genoa,26-098,1997,4.0,4.0,359.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,83.0,114.0,72.8,1455.0,430.0,38.0,42.0,90.5,33.0,40.0,82.5,9.0,18.0,50.0,8.0,8.0,5.0,4.0,12.0,97.0,15.0,7.0,0.0,0.0,15.0,6.0,0.0,5.0,0.0,0.0,2.0,7.0,10.0,2.51,6.0,4.0,0.0,0.0,1.0,0.25,0.0,1.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,3.0,0.0,3.0,4.0,1.0,0.0,152.0,3.0,25.0,74.0,61.0,6.0,152.0,95.0,14.0,10.0,1.0,101.0,5.0,5.0,0.0,5.0,5.0,1.0,0.0,0.0,0.0,18.0,1.0,3.0,25.0 -Emmanuel Gyasi,gh GHA,FW,Empoli,29-253,1994,3.0,2.0,146.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.22,0.22,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.18,-0.4,-0.4,21.0,28.0,75.0,256.0,35.0,15.0,18.0,83.3,4.0,6.0,66.7,0.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,28.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.23,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,43.0,2.0,6.0,15.0,22.0,4.0,43.0,31.0,3.0,4.0,0.0,36.0,2.0,4.0,0.0,4.0,5.0,2.0,0.0,0.0,0.0,5.0,0.0,4.0,0.0 -Norbert Gyömbér,sk SVK,DF,Salernitana,31-080,1992,4.0,4.0,315.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,122.0,142.0,85.9,2127.0,835.0,46.0,50.0,92.0,66.0,72.0,91.7,8.0,16.0,50.0,0.0,3.0,0.0,0.0,5.0,134.0,8.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,5.0,4.0,4.0,1.0,0.0,11.0,9.0,2.0,7.0,15.0,0.0,186.0,30.0,109.0,73.0,5.0,2.0,186.0,85.0,0.0,0.0,0.0,88.0,2.0,0.0,0.0,11.0,3.0,0.0,0.0,0.0,0.0,24.0,4.0,6.0,40.0 -Nicolas Haas,ch SUI,MF,Empoli,27-241,1996,1.0,1.0,90.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.1,0.1,1.0,1.0,0.0,100.0,1.0,0.0,0.0,0.1,-0.1,-0.1,46.0,51.0,90.2,865.0,312.0,20.0,21.0,95.2,21.0,21.0,100.0,5.0,6.0,83.3,0.0,7.0,1.0,0.0,6.0,50.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,1.0,2.0,2.0,1.0,0.0,1.0,1.0,1.0,0.0,63.0,4.0,15.0,36.0,12.0,1.0,63.0,35.0,0.0,1.0,0.0,41.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,9.0,3.0,0.0,100.0 -Abdou Harroui,nl NED,MF,Frosinone,25-251,1998,3.0,3.0,255.0,2.0,0.0,1.0,1.0,0.0,0.0,0.71,0.0,0.71,0.35,0.35,1.5,0.7,0.53,0.25,2.8,2.0,0.0,28.6,0.71,0.14,0.5,0.1,0.5,0.3,78.0,90.0,86.7,1088.0,239.0,46.0,49.0,93.9,22.0,27.0,81.5,4.0,5.0,80.0,3.0,5.0,2.0,0.0,8.0,82.0,6.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,10.0,3.53,8.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,5.0,1.0,5.0,0.0,4.0,0.0,4.0,2.0,0.0,0.0,130.0,1.0,19.0,68.0,46.0,11.0,129.0,70.0,9.0,7.0,2.0,82.0,6.0,2.0,0.0,3.0,3.0,1.0,0.0,0.0,0.0,16.0,2.0,3.0,40.0 -Pantelis Hatzidiakos,gr GRE,DF,Cagliari,26-246,1997,1.0,1.0,79.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,20.0,65.0,236.0,65.0,7.0,8.0,87.5,4.0,5.0,80.0,2.0,6.0,33.3,0.0,0.0,0.0,0.0,1.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,1.0,2.0,0.0,25.0,2.0,12.0,12.0,1.0,1.0,25.0,18.0,0.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,25.0 -Silvan Hefti,ch SUI,"DF,MF",Genoa,25-331,1997,3.0,1.0,84.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,27.0,59.3,194.0,105.0,12.0,16.0,75.0,3.0,6.0,50.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,1.0,21.0,6.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,2.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,38.0,3.0,17.0,15.0,6.0,0.0,38.0,9.0,0.0,0.0,0.0,14.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,100.0 -Liam Henderson,sct SCO,MF,Empoli,27-149,1996,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,5.0,40.0,40.0,0.0,1.0,2.0,50.0,1.0,1.0,100.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,4.0,1.0,0.0,5.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Matheus Henrique,br BRA,MF,Sassuolo,25-276,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,4.0,1.0,0.0,33.3,0.25,0.0,0.0,0.07,-0.2,-0.2,144.0,166.0,86.7,2575.0,901.0,59.0,68.0,86.8,60.0,64.0,93.8,16.0,22.0,72.7,5.0,16.0,2.0,0.0,18.0,161.0,5.0,3.0,1.0,6.0,2.0,1.0,1.0,0.0,0.0,1.0,0.0,2.0,11.0,2.75,10.0,1.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,8.0,5.0,4.0,4.0,0.0,1.0,0.0,1.0,3.0,4.0,1.0,190.0,10.0,48.0,97.0,46.0,2.0,190.0,110.0,5.0,4.0,0.0,140.0,3.0,3.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,17.0,2.0,0.0,100.0 -Theo Hernández,fr FRA,DF,Milan,25-350,1997,4.0,4.0,356.0,1.0,0.0,0.0,0.0,3.0,0.0,0.25,0.0,0.25,0.25,0.25,0.5,0.5,0.13,0.13,4.0,1.0,0.0,20.0,0.25,0.2,1.0,0.1,0.5,0.5,241.0,292.0,82.5,3624.0,963.0,125.0,138.0,90.6,99.0,106.0,93.4,10.0,23.0,43.5,1.0,15.0,5.0,1.0,18.0,257.0,33.0,16.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,17.0,2.0,10.0,9.0,2.28,6.0,0.0,1.0,0.0,2.0,0.51,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,3.0,3.0,0.0,318.0,6.0,78.0,188.0,56.0,7.0,318.0,228.0,13.0,12.0,2.0,236.0,3.0,1.0,0.0,5.0,4.0,0.0,0.0,1.0,0.0,24.0,3.0,0.0,100.0 -Isak Hien,se SWE,DF,Hellas Verona,24-251,1999,2.0,2.0,173.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,63.0,68.0,92.6,1358.0,526.0,17.0,19.0,89.5,38.0,39.0,97.4,7.0,9.0,77.8,0.0,5.0,0.0,0.0,5.0,65.0,3.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.0,3.0,3.0,0.0,1.0,0.0,1.0,1.0,7.0,0.0,88.0,9.0,38.0,50.0,4.0,0.0,88.0,51.0,5.0,3.0,0.0,43.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,2.0,0.0 -Emil Holm,se SWE,DF,Atalanta,23-131,2000,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.82,0.82,0.2,1.0,0.0,50.0,5.63,0.0,0.0,0.07,-0.1,-0.1,6.0,6.0,100.0,121.0,78.0,2.0,2.0,100.0,3.0,3.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,12.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,11.0,1.0,4.0,5.0,2.0,2.0,11.0,5.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,100.0 -Martin Hongla,cm CMR,MF,Hellas Verona,25-189,1998,4.0,4.0,305.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.4,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,68.0,91.0,74.7,1341.0,357.0,24.0,32.0,75.0,32.0,35.0,91.4,11.0,22.0,50.0,0.0,7.0,0.0,0.0,12.0,84.0,6.0,5.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,4.0,1.18,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,4.0,3.0,4.0,0.0,2.0,2.0,0.0,2.0,6.0,0.0,114.0,9.0,28.0,78.0,9.0,0.0,114.0,69.0,2.0,2.0,0.0,63.0,1.0,1.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,18.0,1.0,1.0,50.0 -Sydney van Hooijdonk,nl NED,FW,Bologna,23-227,2000,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,50.0,14.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,1.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Elseid Hysaj,al ALB,DF,Lazio,29-213,1994,2.0,2.0,125.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,62.0,70.0,88.6,882.0,303.0,33.0,37.0,89.2,22.0,24.0,91.7,1.0,2.0,50.0,0.0,4.0,0.0,0.0,4.0,67.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,4.0,0.0,4.0,2.0,8.0,0.0,86.0,8.0,39.0,39.0,8.0,0.0,86.0,45.0,1.0,0.0,0.0,57.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,8.0,3.0,1.0,75.0 -Chukwubuikem Ikwuemesi,ng NGA,"FW,DF",Salernitana,22-047,2001,3.0,0.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.18,0.18,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,13.0,17.0,76.5,170.0,39.0,7.0,10.0,70.0,5.0,5.0,100.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,3.0,15.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.11,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,30.0,1.0,1.0,16.0,13.0,9.0,30.0,18.0,2.0,1.0,1.0,25.0,3.0,1.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,4.0,42.9 -Ivan Ilić,rs SRB,MF,Torino,22-188,2001,3.0,2.0,151.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.6,0.6,0.0,0.6,0.0,0.0,0.0,0.0,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,87.0,104.0,83.7,1573.0,459.0,40.0,45.0,88.9,36.0,41.0,87.8,10.0,14.0,71.4,4.0,7.0,3.0,0.0,10.0,89.0,13.0,8.0,0.0,1.0,7.0,5.0,5.0,0.0,0.0,0.0,2.0,1.0,6.0,3.58,4.0,2.0,0.0,0.0,1.0,0.6,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,111.0,2.0,10.0,79.0,25.0,1.0,111.0,58.0,5.0,4.0,0.0,78.0,1.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,9.0,2.0,0.0,100.0 -Samuel Iling-Junior,eng ENG,DF,Juventus,19-352,2003,2.0,0.0,46.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.96,1.96,0.0,1.96,0.1,0.1,0.21,0.21,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.1,-0.1,16.0,24.0,66.7,211.0,48.0,12.0,13.0,92.3,3.0,5.0,60.0,1.0,3.0,33.3,1.0,0.0,1.0,1.0,2.0,20.0,4.0,0.0,0.0,0.0,4.0,2.0,2.0,0.0,0.0,2.0,0.0,4.0,2.0,3.91,2.0,0.0,0.0,0.0,1.0,1.96,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,3.0,1.0,2.0,0.0,0.0,0.0,36.0,1.0,12.0,8.0,16.0,1.0,36.0,14.0,4.0,1.0,0.0,21.0,2.0,0.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,2.0,1.0,1.0,50.0 -Ciro Immobile,it ITA,FW,Lazio,33-213,1990,4.0,4.0,337.0,1.0,0.0,0.0,0.0,1.0,0.0,0.27,0.0,0.27,0.27,0.27,1.2,1.2,0.33,0.33,3.7,3.0,0.0,50.0,0.8,0.17,0.33,0.2,-0.2,-0.2,80.0,107.0,74.8,1074.0,180.0,41.0,56.0,73.2,28.0,35.0,80.0,3.0,5.0,60.0,4.0,4.0,4.0,0.0,9.0,99.0,8.0,0.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,5.0,1.34,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,141.0,1.0,9.0,63.0,71.0,20.0,141.0,66.0,1.0,3.0,1.0,107.0,11.0,3.0,0.0,3.0,5.0,1.0,0.0,0.0,0.0,5.0,0.0,2.0,0.0 -Gino Infantino,ar ARG,MF,Fiorentina,20-125,2003,3.0,0.0,47.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.04,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,25.0,31.0,80.6,443.0,83.0,13.0,15.0,86.7,9.0,11.0,81.8,3.0,3.0,100.0,0.0,3.0,0.0,0.0,5.0,28.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,3.75,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,36.0,0.0,1.0,24.0,11.0,1.0,36.0,31.0,0.0,1.0,0.0,29.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,3.0,25.0 -Gustav Isaksen,dk DEN,FW,Lazio,22-155,2001,3.0,0.0,63.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,23.0,56.5,211.0,26.0,5.0,8.0,62.5,8.0,9.0,88.9,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,23.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,31.0,2.0,5.0,9.0,18.0,6.0,31.0,19.0,2.0,2.0,2.0,21.0,1.0,2.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Ardian Ismajli,al ALB,DF,Empoli,26-356,1996,3.0,2.0,225.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,82.0,109.0,75.2,1572.0,670.0,26.0,32.0,81.3,51.0,55.0,92.7,5.0,18.0,27.8,0.0,4.0,0.0,0.0,4.0,100.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,3.0,0.0,8.0,1.0,128.0,14.0,79.0,49.0,1.0,1.0,128.0,52.0,0.0,0.0,0.0,62.0,0.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,12.0,10.0,6.0,62.5 -Armando Izzo,it ITA,DF,Monza,31-203,1992,3.0,3.0,250.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,176.0,198.0,88.9,3076.0,849.0,75.0,79.0,94.9,86.0,94.0,91.5,13.0,21.0,61.9,1.0,9.0,1.0,0.0,13.0,186.0,12.0,8.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,3.0,1.08,3.0,0.0,0.0,0.0,1.0,0.36,1.0,0.0,0.0,0.0,0.0,7.0,5.0,4.0,3.0,0.0,4.0,2.0,2.0,4.0,4.0,1.0,222.0,20.0,97.0,102.0,24.0,3.0,222.0,128.0,5.0,3.0,0.0,161.0,4.0,0.0,0.0,8.0,3.0,0.0,0.0,0.0,0.0,28.0,0.0,3.0,0.0 -Filip Jagiełło,pl POL,MF,Genoa,26-044,1997,2.0,0.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,17.0,88.2,287.0,13.0,5.0,5.0,100.0,9.0,9.0,100.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,2.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,2.73,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,20.0,2.0,6.0,8.0,7.0,0.0,20.0,16.0,1.0,3.0,0.0,16.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 -Jakub Jankto,cz CZE,"MF,FW",Cagliari,27-245,1996,3.0,2.0,153.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,1.7,1.0,0.0,100.0,0.59,0.0,0.0,0.09,-0.1,-0.1,28.0,43.0,65.1,396.0,95.0,16.0,16.0,100.0,9.0,17.0,52.9,1.0,5.0,20.0,1.0,2.0,1.0,0.0,4.0,39.0,4.0,0.0,0.0,0.0,4.0,2.0,1.0,1.0,0.0,2.0,0.0,3.0,5.0,2.94,4.0,0.0,0.0,0.0,1.0,0.59,1.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,0.0,0.0,0.0,2.0,9.0,0.0,67.0,7.0,21.0,25.0,21.0,2.0,67.0,31.0,2.0,3.0,0.0,36.0,2.0,1.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,6.0,2.0,2.0,50.0 -Juan Jesus,br BRA,DF,Napoli,32-103,1991,4.0,4.0,359.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.08,0.08,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.31,-0.3,-0.3,299.0,319.0,93.7,5315.0,1777.0,114.0,117.0,97.4,163.0,169.0,96.4,18.0,28.0,64.3,2.0,4.0,0.0,0.0,12.0,309.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,0.75,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,5.0,8.0,1.0,1.0,3.0,2.0,1.0,4.0,9.0,0.0,349.0,18.0,150.0,190.0,9.0,3.0,349.0,238.0,1.0,1.0,0.0,259.0,1.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,26.0,6.0,5.0,54.5 -Luka Jović,rs SRB,FW,Milan,25-272,1997,1.0,0.0,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,80.0,71.0,1.0,1.0,2.0,50.0,3.0,3.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,4.0,1.0,0.0,5.0,2.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Mohamed Kaba,fr FRA,MF,Lecce,21-329,2001,4.0,2.0,222.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,2.5,1.0,0.0,100.0,0.41,0.0,0.0,0.06,-0.1,-0.1,53.0,68.0,77.9,786.0,236.0,30.0,37.0,81.1,19.0,25.0,76.0,2.0,2.0,100.0,1.0,3.0,0.0,0.0,7.0,66.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.41,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,3.0,2.0,1.0,4.0,0.0,4.0,2.0,3.0,0.0,99.0,5.0,21.0,50.0,28.0,3.0,99.0,50.0,3.0,0.0,1.0,60.0,10.0,3.0,0.0,7.0,4.0,0.0,0.0,0.0,0.0,12.0,10.0,6.0,62.5 -Christian Kabasele,be BEL,DF,Udinese,32-209,1991,4.0,4.0,307.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.4,1.0,0.0,50.0,0.29,0.0,0.0,0.07,-0.1,-0.1,136.0,166.0,81.9,2431.0,765.0,52.0,60.0,86.7,68.0,78.0,87.2,11.0,19.0,57.9,0.0,14.0,0.0,0.0,12.0,148.0,18.0,5.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,2.0,0.59,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,7.0,3.0,4.0,4.0,8.0,0.0,193.0,25.0,81.0,102.0,11.0,2.0,193.0,107.0,4.0,2.0,0.0,117.0,3.0,0.0,0.0,8.0,2.0,0.0,0.0,0.0,0.0,14.0,10.0,2.0,83.3 -Pierre Kalulu,fr FRA,DF,Milan,23-108,2000,2.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,253.0,113.0,2.0,3.0,66.7,7.0,7.0,100.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,1.0,19.0,4.0,15.0,4.0,0.0,0.0,19.0,12.0,0.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 -Daichi Kamada,jp JPN,MF,Lazio,27-047,1996,4.0,4.0,260.0,1.0,1.0,0.0,0.0,0.0,0.0,0.35,0.35,0.69,0.35,0.69,0.4,0.4,0.14,0.14,2.9,2.0,0.0,28.6,0.69,0.14,0.5,0.06,0.6,0.6,110.0,134.0,82.1,1610.0,259.0,65.0,71.0,91.5,40.0,46.0,87.0,3.0,9.0,33.3,4.0,10.0,1.0,0.0,11.0,132.0,2.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,5.0,1.73,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,6.0,1.0,1.0,4.0,1.0,3.0,1.0,2.0,0.0,164.0,6.0,27.0,91.0,46.0,9.0,164.0,89.0,2.0,0.0,2.0,124.0,3.0,4.0,0.0,10.0,2.0,0.0,0.0,0.0,0.0,6.0,1.0,2.0,33.3 -Hassane Kamara,ci CIV,DF,Udinese,29-200,1994,4.0,4.0,276.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,94.0,120.0,78.3,1508.0,544.0,46.0,50.0,92.0,35.0,46.0,76.1,8.0,15.0,53.3,4.0,5.0,6.0,6.0,10.0,97.0,22.0,1.0,0.0,0.0,14.0,0.0,0.0,0.0,0.0,21.0,1.0,2.0,10.0,3.26,9.0,0.0,0.0,0.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,5.0,4.0,3.0,2.0,0.0,1.0,0.0,1.0,6.0,4.0,0.0,156.0,8.0,38.0,59.0,61.0,5.0,156.0,84.0,7.0,4.0,1.0,89.0,4.0,4.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,17.0,3.0,3.0,50.0 -Yann Karamoh,fr FRA,MF,Torino,25-075,1998,3.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.04,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,20.0,27.0,74.1,293.0,66.0,12.0,16.0,75.0,7.0,8.0,87.5,1.0,2.0,50.0,0.0,2.0,0.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,44.0,1.0,4.0,19.0,25.0,4.0,44.0,31.0,5.0,5.0,2.0,34.0,5.0,2.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,5.0,1.0,1.0,50.0 -Jesper Karlsson,se SWE,FW,Bologna,25-058,1998,3.0,2.0,175.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.21,0.21,1.9,4.0,1.0,80.0,2.06,0.0,0.0,0.08,-0.4,-0.4,54.0,84.0,64.3,1025.0,220.0,23.0,32.0,71.9,21.0,29.0,72.4,8.0,16.0,50.0,3.0,7.0,4.0,1.0,10.0,73.0,10.0,3.0,0.0,0.0,11.0,6.0,3.0,1.0,0.0,1.0,1.0,3.0,8.0,4.11,6.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,96.0,1.0,12.0,36.0,49.0,6.0,96.0,66.0,4.0,1.0,4.0,69.0,1.0,5.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,11.0,0.0,2.0,0.0 -Rick Karsdorp,nl NED,"DF,FW",Roma,28-222,1995,2.0,0.0,66.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,34.0,43.0,79.1,600.0,223.0,15.0,16.0,93.8,13.0,16.0,81.3,4.0,7.0,57.1,1.0,1.0,2.0,1.0,2.0,35.0,8.0,1.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,3.0,4.09,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,46.0,2.0,14.0,14.0,19.0,1.0,46.0,28.0,3.0,2.0,0.0,29.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Grigoris Kastanos,cy CYP,"MF,DF",Salernitana,25-234,1998,4.0,3.0,246.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.7,2.0,0.0,50.0,0.73,0.0,0.0,0.03,-0.1,-0.1,81.0,110.0,73.6,1222.0,417.0,43.0,48.0,89.6,22.0,33.0,66.7,9.0,14.0,64.3,1.0,9.0,1.0,0.0,10.0,93.0,17.0,1.0,1.0,1.0,4.0,6.0,0.0,1.0,0.0,10.0,0.0,6.0,5.0,1.82,4.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,2.0,0.0,2.0,2.0,1.0,1.0,4.0,2.0,0.0,138.0,2.0,26.0,68.0,45.0,1.0,138.0,90.0,6.0,6.0,1.0,91.0,0.0,9.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,15.0,2.0,12.0,14.3 -Michael Kayode,it ITA,DF,Fiorentina,19-073,2004,1.0,1.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,57.0,69.0,82.6,986.0,297.0,33.0,35.0,94.3,17.0,19.0,89.5,7.0,9.0,77.8,0.0,1.0,1.0,0.0,3.0,59.0,10.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,10.0,0.0,5.0,1.0,1.11,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,83.0,7.0,42.0,31.0,12.0,4.0,83.0,43.0,5.0,3.0,2.0,50.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,4.0,1.0,80.0 -Moise Kean,it ITA,FW,Juventus,23-205,2000,2.0,0.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.56,0.56,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,2.0,3.0,66.7,51.0,21.0,1.0,1.0,100.0,0.0,0.0,0.0,1.0,1.0,100.0,1.0,1.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,11.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,2.0,4.0,1.0,6.0,4.0,2.0,0.0,1.0,4.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Simon Kjær,dk DEN,DF,Milan,34-179,1989,3.0,1.0,105.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,79.0,91.0,86.8,1553.0,697.0,25.0,26.0,96.2,47.0,50.0,94.0,6.0,13.0,46.2,0.0,6.0,0.0,0.0,11.0,88.0,3.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,3.0,1.0,1.0,2.0,1.0,1.0,0.0,5.0,0.0,103.0,7.0,36.0,66.0,2.0,0.0,103.0,80.0,2.0,1.0,0.0,76.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,3.0,1.0,75.0 -Sead Kolašinac,ba BIH,DF,Atalanta,30-093,1993,4.0,4.0,359.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,1.0,0.0,100.0,0.25,0.0,0.0,0.03,0.0,0.0,173.0,209.0,82.8,2588.0,812.0,94.0,106.0,88.7,71.0,79.0,89.9,5.0,14.0,35.7,1.0,13.0,1.0,0.0,17.0,197.0,10.0,4.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,6.0,2.0,5.0,5.0,1.25,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,2.0,0.0,3.0,0.0,3.0,3.0,4.0,0.0,227.0,7.0,85.0,101.0,41.0,2.0,227.0,148.0,7.0,9.0,1.0,150.0,1.0,1.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,29.0,5.0,8.0,38.5 -Teun Koopmeiners,nl NED,MF,Atalanta,25-205,1998,4.0,4.0,339.0,1.0,1.0,0.0,0.0,0.0,0.0,0.27,0.27,0.53,0.27,0.53,0.5,0.5,0.14,0.14,3.8,3.0,0.0,30.0,0.8,0.1,0.33,0.05,0.5,0.5,151.0,201.0,75.1,2840.0,1127.0,58.0,69.0,84.1,69.0,80.0,86.3,20.0,39.0,51.3,13.0,14.0,11.0,4.0,27.0,172.0,27.0,4.0,0.0,4.0,26.0,16.0,5.0,7.0,0.0,1.0,2.0,5.0,25.0,6.64,17.0,4.0,0.0,0.0,2.0,0.53,2.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,1.0,0.0,1.0,1.0,2.0,0.0,239.0,3.0,34.0,99.0,110.0,13.0,239.0,149.0,15.0,8.0,4.0,171.0,7.0,2.0,0.0,8.0,6.0,0.0,0.0,0.0,0.0,19.0,2.0,3.0,40.0 -Filip Kostić,rs SRB,DF,Juventus,30-324,1992,2.0,2.0,128.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.4,1.0,0.0,50.0,0.7,0.0,0.0,0.03,-0.1,-0.1,55.0,68.0,80.9,942.0,299.0,27.0,31.0,87.1,24.0,27.0,88.9,4.0,8.0,50.0,3.0,2.0,3.0,2.0,6.0,55.0,13.0,1.0,0.0,0.0,10.0,5.0,0.0,5.0,0.0,7.0,0.0,3.0,7.0,4.92,3.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,0.0,1.0,4.0,2.0,2.0,0.0,1.0,0.0,81.0,3.0,22.0,27.0,33.0,4.0,81.0,36.0,6.0,5.0,2.0,53.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Christian Kouamé,ci CIV,"FW,MF",Fiorentina,25-289,1997,3.0,1.0,81.0,1.0,0.0,0.0,0.0,0.0,0.0,1.11,0.0,1.11,1.11,1.11,0.3,0.3,0.39,0.39,0.9,2.0,0.0,50.0,2.22,0.25,0.5,0.09,0.7,0.7,27.0,37.0,73.0,390.0,76.0,17.0,21.0,81.0,8.0,11.0,72.7,2.0,4.0,50.0,0.0,0.0,0.0,0.0,2.0,37.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,0.0,0.0,0.0,52.0,0.0,7.0,25.0,21.0,5.0,52.0,33.0,2.0,2.0,1.0,35.0,2.0,3.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,8.0,8.0,3.0,72.7 -Viktor Kovalenko,ua UKR,MF,Empoli,27-219,1996,1.0,0.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,14.0,64.3,121.0,34.0,5.0,7.0,71.4,4.0,6.0,66.7,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,14.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,18.0,1.0,3.0,9.0,6.0,0.0,18.0,9.0,1.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Nikola Krstović,me MNE,FW,Lecce,23-169,2000,3.0,2.0,166.0,3.0,0.0,1.0,1.0,0.0,0.0,1.63,0.0,1.63,1.08,1.08,1.3,0.5,0.68,0.25,1.8,2.0,0.0,33.3,1.08,0.33,1.0,0.08,1.7,1.5,34.0,48.0,70.8,469.0,75.0,22.0,25.0,88.0,7.0,12.0,58.3,3.0,5.0,60.0,3.0,4.0,1.0,0.0,4.0,45.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.71,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,0.0,68.0,4.0,12.0,38.0,18.0,10.0,67.0,38.0,3.0,2.0,1.0,48.0,4.0,1.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,11.0,8.0,2.0,80.0 -Rade Krunić,ba BIH,MF,Milan,29-349,1993,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,219.0,233.0,94.0,3337.0,665.0,118.0,123.0,95.9,84.0,91.0,92.3,12.0,12.0,100.0,2.0,7.0,2.0,0.0,9.0,220.0,13.0,11.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,5.0,1.25,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,2.0,2.0,1.0,2.0,0.0,2.0,7.0,9.0,0.0,264.0,16.0,72.0,168.0,25.0,2.0,264.0,152.0,3.0,4.0,0.0,182.0,3.0,1.0,0.0,6.0,6.0,0.0,0.0,0.0,0.0,23.0,2.0,4.0,33.3 -Berkan Kutlu,tr TUR,MF,Genoa,25-239,1998,1.0,0.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.12,0.12,0.4,1.0,0.0,100.0,2.73,0.0,0.0,0.05,0.0,0.0,5.0,11.0,45.5,79.0,7.0,3.0,5.0,60.0,2.0,3.0,66.7,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,2.73,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,12.0,0.0,3.0,5.0,5.0,0.0,12.0,6.0,3.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Khvicha Kvaratskhelia,ge GEO,FW,Napoli,22-221,2001,3.0,2.0,183.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.49,0.49,0.0,0.49,0.6,0.6,0.31,0.31,2.0,2.0,1.0,18.2,0.98,0.0,0.0,0.06,-0.6,-0.6,77.0,91.0,84.6,1088.0,261.0,44.0,46.0,95.7,25.0,29.0,86.2,3.0,7.0,42.9,6.0,3.0,5.0,0.0,10.0,87.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,13.0,6.39,8.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,2.0,2.0,0.0,124.0,2.0,5.0,44.0,77.0,20.0,124.0,86.0,12.0,7.0,5.0,95.0,4.0,1.0,0.0,2.0,4.0,2.0,0.0,0.0,0.0,2.0,1.0,2.0,33.3 -Giorgi Kvernadze,ge GEO,FW,Frosinone,20-226,2003,1.0,0.0,24.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,8.0,100.0,125.0,41.0,4.0,4.0,100.0,4.0,4.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,7.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,14.0,0.0,3.0,9.0,2.0,0.0,14.0,10.0,0.0,1.0,0.0,11.0,2.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Giorgos Kyriakopoulos,gr GRE,DF,Monza,27-228,1996,2.0,1.0,87.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.14,0.14,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,52.0,57.0,91.2,978.0,192.0,22.0,22.0,100.0,22.0,23.0,95.7,6.0,7.0,85.7,2.0,4.0,2.0,2.0,4.0,46.0,11.0,1.0,0.0,0.0,6.0,1.0,0.0,1.0,0.0,9.0,0.0,3.0,4.0,4.14,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,61.0,1.0,5.0,30.0,26.0,2.0,61.0,38.0,4.0,1.0,0.0,47.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Armand Lauriente,fr FRA,"FW,MF",Sassuolo,24-291,1998,4.0,4.0,287.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.31,0.31,0.0,0.31,0.2,0.2,0.07,0.07,3.2,2.0,2.0,25.0,0.63,0.0,0.0,0.03,-0.2,-0.2,72.0,98.0,73.5,1006.0,396.0,48.0,57.0,84.2,18.0,25.0,72.0,4.0,8.0,50.0,5.0,5.0,2.0,0.0,5.0,85.0,13.0,1.0,1.0,0.0,13.0,12.0,8.0,0.0,0.0,0.0,0.0,5.0,12.0,3.76,7.0,3.0,0.0,2.0,1.0,0.31,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,2.0,0.0,2.0,4.0,1.0,0.0,137.0,0.0,11.0,55.0,77.0,9.0,137.0,86.0,13.0,12.0,4.0,90.0,7.0,6.0,0.0,2.0,7.0,1.0,0.0,0.0,0.0,19.0,0.0,2.0,0.0 -Valentino Lazaro,at AUT,DF,Torino,27-181,1996,3.0,1.0,131.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,58.0,78.0,74.4,946.0,542.0,34.0,36.0,94.4,15.0,24.0,62.5,8.0,15.0,53.3,3.0,10.0,0.0,0.0,8.0,64.0,14.0,3.0,0.0,0.0,10.0,2.0,1.0,1.0,0.0,9.0,0.0,1.0,4.0,2.75,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,4.0,0.0,85.0,4.0,18.0,39.0,30.0,0.0,85.0,47.0,4.0,3.0,0.0,54.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,5.0,2.0,71.4 -Darko Lazović,rs SRB,DF,Hellas Verona,33-006,1990,1.0,0.0,55.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,22.0,59.1,256.0,104.0,3.0,4.0,75.0,9.0,11.0,81.8,1.0,5.0,20.0,0.0,0.0,0.0,0.0,1.0,18.0,4.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,25.0,1.0,5.0,7.0,13.0,2.0,25.0,10.0,2.0,1.0,1.0,18.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Manuel Lazzari,it ITA,DF,Lazio,29-296,1993,2.0,2.0,161.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.08,0.08,1.8,1.0,0.0,25.0,0.56,0.0,0.0,0.04,-0.1,-0.1,99.0,122.0,81.1,1454.0,348.0,56.0,59.0,94.9,39.0,47.0,83.0,3.0,5.0,60.0,2.0,4.0,3.0,2.0,8.0,107.0,15.0,1.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,14.0,0.0,7.0,2.0,1.12,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,1.0,1.0,3.0,1.0,2.0,1.0,6.0,0.0,142.0,4.0,20.0,73.0,52.0,5.0,142.0,89.0,14.0,6.0,1.0,94.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,12.0,1.0,2.0,33.3 -Rafael Leão,pt POR,FW,Milan,24-103,1999,4.0,4.0,321.0,2.0,1.0,0.0,0.0,0.0,0.0,0.56,0.28,0.84,0.56,0.84,1.2,1.2,0.34,0.34,3.6,3.0,0.0,42.9,0.84,0.29,0.67,0.17,0.8,0.8,73.0,105.0,69.5,1167.0,336.0,37.0,48.0,77.1,29.0,40.0,72.5,6.0,12.0,50.0,7.0,9.0,7.0,3.0,14.0,102.0,3.0,1.0,2.0,0.0,9.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,14.0,3.93,11.0,0.0,0.0,1.0,3.0,0.84,2.0,0.0,0.0,1.0,0.0,3.0,3.0,1.0,1.0,1.0,5.0,0.0,5.0,0.0,0.0,0.0,149.0,1.0,7.0,62.0,82.0,29.0,149.0,115.0,15.0,8.0,11.0,128.0,10.0,8.0,0.0,1.0,11.0,3.0,1.0,0.0,0.0,6.0,2.0,5.0,28.6 -Jesper Lindstrøm,dk DEN,FW,Napoli,23-204,2000,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.16,0.16,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,8.0,11.0,72.7,91.0,26.0,6.0,6.0,100.0,2.0,3.0,66.7,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,10.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,0.0,4.0,13.0,1.0,17.0,8.0,0.0,0.0,0.0,11.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Karol Linetty,pl POL,MF,Torino,28-231,1995,4.0,1.0,155.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,68.0,85.0,80.0,1190.0,303.0,35.0,40.0,87.5,22.0,26.0,84.6,9.0,13.0,69.2,1.0,11.0,1.0,0.0,13.0,80.0,5.0,1.0,0.0,1.0,4.0,3.0,0.0,3.0,0.0,1.0,0.0,1.0,2.0,1.16,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,2.0,1.0,1.0,3.0,1.0,0.0,101.0,1.0,11.0,70.0,22.0,2.0,101.0,65.0,5.0,5.0,0.0,66.0,3.0,2.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,12.0,2.0,0.0,100.0 -Pol Lirola,es ESP,MF,Frosinone,26-039,1997,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,22.5,0.0,22.5,22.5,22.5,0.9,0.9,15.8,15.8,0.0,1.0,0.0,100.0,22.5,1.0,1.0,0.88,0.1,0.1,1.0,3.0,33.3,16.0,5.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,1.0,2.0,1.0,5.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 -Diego Llorente,es ESP,DF,Roma,30-036,1993,4.0,4.0,315.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.29,0.29,0.0,0.29,0.0,0.0,0.0,0.0,3.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,207.0,241.0,85.9,3808.0,1250.0,81.0,85.0,95.3,103.0,116.0,88.8,22.0,32.0,68.8,1.0,8.0,1.0,0.0,13.0,234.0,7.0,4.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,5.0,1.43,4.0,0.0,0.0,1.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,4.0,1.0,3.0,2.0,4.0,0.0,261.0,20.0,123.0,121.0,17.0,1.0,261.0,176.0,8.0,3.0,0.0,192.0,3.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,15.0,14.0,7.0,66.7 -Stanislav Lobotka,sk SVK,MF,Napoli,28-300,1994,4.0,4.0,336.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.7,1.0,0.0,25.0,0.27,0.0,0.0,0.02,-0.1,-0.1,253.0,268.0,94.4,3714.0,1227.0,147.0,154.0,95.5,86.0,90.0,95.6,11.0,15.0,73.3,0.0,27.0,5.0,1.0,23.0,266.0,2.0,2.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,2.95,9.0,0.0,0.0,1.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,4.0,4.0,0.0,3.0,1.0,3.0,1.0,2.0,1.0,1.0,0.0,289.0,7.0,48.0,193.0,49.0,1.0,289.0,196.0,3.0,8.0,0.0,237.0,3.0,1.0,0.0,3.0,8.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,100.0 -Manuel Locatelli,it ITA,MF,Juventus,25-256,1998,4.0,4.0,351.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.26,0.26,0.0,0.26,0.0,0.0,0.0,0.0,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,197.0,237.0,83.1,3949.0,1126.0,73.0,83.0,88.0,94.0,99.0,94.9,28.0,45.0,62.2,4.0,25.0,5.0,2.0,25.0,223.0,13.0,11.0,1.0,6.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,4.0,6.0,1.54,6.0,0.0,0.0,0.0,1.0,0.26,1.0,0.0,0.0,0.0,0.0,6.0,0.0,1.0,5.0,0.0,5.0,3.0,2.0,3.0,6.0,0.0,261.0,9.0,65.0,159.0,39.0,3.0,261.0,142.0,4.0,6.0,1.0,193.0,1.0,3.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,21.0,1.0,2.0,33.3 -Ruben Loftus-Cheek,eng ENG,MF,Milan,27-241,1996,4.0,4.0,286.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.31,0.31,0.0,0.31,0.4,0.4,0.11,0.11,3.2,1.0,0.0,20.0,0.31,0.0,0.0,0.07,-0.4,-0.4,95.0,117.0,81.2,1153.0,299.0,70.0,80.0,87.5,20.0,26.0,76.9,2.0,5.0,40.0,4.0,8.0,0.0,0.0,12.0,116.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,9.0,2.83,6.0,0.0,1.0,1.0,4.0,1.26,1.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,4.0,3.0,1.0,2.0,1.0,0.0,154.0,3.0,14.0,90.0,52.0,9.0,154.0,102.0,17.0,12.0,2.0,111.0,9.0,3.0,0.0,5.0,5.0,0.0,1.0,0.0,0.0,16.0,3.0,2.0,60.0 -Ademola Lookman,ng NGA,FW,Atalanta,25-336,1997,4.0,3.0,173.0,1.0,0.0,0.0,0.0,1.0,0.0,0.52,0.0,0.52,0.52,0.52,0.8,0.8,0.41,0.41,1.9,2.0,0.0,25.0,1.04,0.13,0.5,0.1,0.2,0.2,35.0,50.0,70.0,536.0,135.0,21.0,24.0,87.5,9.0,15.0,60.0,2.0,5.0,40.0,2.0,0.0,4.0,0.0,7.0,47.0,3.0,0.0,1.0,0.0,6.0,3.0,0.0,3.0,0.0,0.0,0.0,3.0,10.0,5.2,6.0,0.0,0.0,0.0,1.0,0.52,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,69.0,0.0,3.0,24.0,42.0,12.0,69.0,47.0,7.0,4.0,3.0,56.0,4.0,4.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,7.0,0.0,1.0,0.0 -Maxime Lopez,fr FRA,MF,Sassuolo,25-291,1997,2.0,2.0,140.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,124.0,136.0,91.2,2097.0,777.0,46.0,48.0,95.8,61.0,64.0,95.3,9.0,15.0,60.0,3.0,23.0,2.0,0.0,18.0,134.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,3.21,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,2.0,0.0,0.0,144.0,10.0,38.0,89.0,19.0,0.0,144.0,107.0,2.0,4.0,0.0,125.0,1.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,10.0,0.0,1.0,0.0 -Matteo Lovato,it ITA,DF,Salernitana,23-219,2000,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,130.0,160.0,81.3,2326.0,1211.0,55.0,61.0,90.2,58.0,66.0,87.9,13.0,24.0,54.2,0.0,13.0,0.0,0.0,12.0,149.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,5.0,7.0,1.0,1.0,6.0,4.0,2.0,4.0,11.0,0.0,200.0,25.0,95.0,96.0,11.0,1.0,200.0,98.0,0.0,1.0,0.0,112.0,1.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,15.0,8.0,4.0,66.7 -Sandi Lovrić,si SVN,MF,Udinese,25-177,1998,4.0,4.0,332.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.8,0.21,0.21,3.7,4.0,0.0,57.1,1.08,0.0,0.0,0.11,-0.8,-0.8,104.0,127.0,81.9,1751.0,427.0,63.0,70.0,90.0,24.0,30.0,80.0,13.0,19.0,68.4,7.0,9.0,3.0,2.0,10.0,110.0,17.0,5.0,0.0,2.0,17.0,9.0,3.0,3.0,0.0,3.0,0.0,2.0,16.0,4.34,10.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,3.0,0.0,3.0,1.0,3.0,0.0,158.0,3.0,12.0,72.0,75.0,6.0,158.0,99.0,8.0,8.0,2.0,109.0,6.0,6.0,0.0,5.0,3.0,1.0,0.0,0.0,0.0,21.0,0.0,3.0,0.0 -Lorenzo Lucca,it ITA,FW,Udinese,23-011,2000,4.0,3.0,246.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.37,0.37,0.0,0.37,0.7,0.7,0.26,0.26,2.7,3.0,0.0,50.0,1.1,0.0,0.0,0.12,-0.7,-0.7,24.0,45.0,53.3,277.0,46.0,10.0,19.0,52.6,7.0,15.0,46.7,0.0,0.0,0.0,6.0,2.0,1.0,0.0,3.0,42.0,2.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,8.0,2.93,6.0,0.0,0.0,1.0,1.0,0.37,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,1.0,2.0,0.0,2.0,0.0,2.0,0.0,84.0,2.0,4.0,35.0,45.0,14.0,84.0,54.0,3.0,4.0,1.0,73.0,12.0,1.0,0.0,6.0,7.0,0.0,0.0,0.0,0.0,6.0,8.0,9.0,47.1 -Jhon Lucumí,co COL,DF,Bologna,25-087,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,4.0,1.0,0.0,33.3,0.25,0.0,0.0,0.05,-0.2,-0.2,266.0,289.0,92.0,4848.0,1562.0,107.0,112.0,95.5,126.0,132.0,95.5,28.0,37.0,75.7,2.0,27.0,0.0,0.0,17.0,275.0,14.0,11.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,6.0,8.0,5.0,0.0,7.0,2.0,5.0,1.0,12.0,0.0,329.0,38.0,142.0,181.0,9.0,2.0,329.0,219.0,5.0,4.0,0.0,242.0,1.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,25.0,8.0,2.0,80.0 -José Luis Palomino,ar ARG,DF,Atalanta,33-259,1990,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,7.0,100.0,125.0,54.0,3.0,3.0,100.0,2.0,2.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,8.0,0.0,3.0,5.0,0.0,0.0,8.0,6.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Romelu Lukaku,be BEL,FW,Roma,30-131,1993,2.0,1.0,103.0,1.0,0.0,0.0,0.0,1.0,0.0,0.87,0.0,0.87,0.87,0.87,0.3,0.3,0.28,0.28,1.1,2.0,0.0,66.7,1.75,0.33,0.5,0.11,0.7,0.7,21.0,27.0,77.8,270.0,6.0,12.0,16.0,75.0,7.0,9.0,77.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,27.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.5,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,0.0,0.0,12.0,18.0,4.0,30.0,26.0,0.0,2.0,0.0,29.0,0.0,1.0,0.0,3.0,0.0,2.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 -Sebastiano Luperto,it ITA,DF,Empoli,27-015,1996,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,162.0,179.0,90.5,3129.0,952.0,48.0,53.0,90.6,99.0,102.0,97.1,12.0,20.0,60.0,0.0,4.0,0.0,0.0,7.0,172.0,7.0,3.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,1.0,0.0,7.0,4.0,3.0,1.0,6.0,0.0,200.0,38.0,114.0,85.0,2.0,0.0,200.0,131.0,0.0,0.0,0.0,136.0,0.0,0.0,0.0,5.0,2.0,0.0,0.0,0.0,0.0,14.0,5.0,2.0,71.4 -Charalambos Lykogiannis,gr GRE,DF,Bologna,29-334,1993,2.0,2.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.11,0.11,1.6,0.0,1.0,0.0,0.0,0.0,0.0,0.09,-0.2,-0.2,50.0,70.0,71.4,940.0,221.0,23.0,26.0,88.5,22.0,29.0,75.9,5.0,14.0,35.7,2.0,4.0,2.0,2.0,5.0,60.0,10.0,0.0,0.0,1.0,8.0,1.0,1.0,0.0,0.0,9.0,0.0,0.0,3.0,1.85,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,6.0,0.0,82.0,5.0,25.0,37.0,20.0,0.0,82.0,35.0,3.0,2.0,0.0,49.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,1.0,80.0 -Giulio Maggiore,it ITA,MF,Salernitana,25-193,1998,1.0,1.0,77.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,23.0,30.0,76.7,372.0,112.0,11.0,15.0,73.3,11.0,12.0,91.7,1.0,2.0,50.0,0.0,2.0,1.0,0.0,2.0,29.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,33.0,0.0,7.0,23.0,3.0,0.0,33.0,26.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,40.0 -Giangiacomo Magnani,it ITA,DF,Hellas Verona,27-352,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,114.0,131.0,87.0,2754.0,807.0,18.0,21.0,85.7,73.0,78.0,93.6,23.0,30.0,76.7,2.0,7.0,0.0,0.0,8.0,125.0,6.0,6.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,6.0,1.5,5.0,0.0,0.0,0.0,2.0,0.5,1.0,0.0,0.0,0.0,1.0,3.0,2.0,1.0,2.0,0.0,4.0,3.0,1.0,6.0,17.0,0.0,164.0,22.0,84.0,77.0,3.0,2.0,164.0,87.0,0.0,0.0,0.0,95.0,1.0,0.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,16.0,2.0,2.0,50.0 -Mike Maignan,fr FRA,GK,Milan,28-080,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,179.0,224.0,79.9,4527.0,3178.0,34.0,34.0,100.0,92.0,93.0,98.9,51.0,92.0,55.4,0.0,2.0,0.0,0.0,0.0,193.0,28.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,4.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,231.0,167.0,231.0,0.0,0.0,0.0,231.0,151.0,0.0,0.0,0.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,66.7 -Antoine Makoumbou,cg CGO,MF,Cagliari,25-065,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,149.0,166.0,89.8,2482.0,680.0,74.0,79.0,93.7,53.0,59.0,89.8,16.0,20.0,80.0,2.0,15.0,4.0,0.0,26.0,158.0,7.0,5.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,4.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,3.0,2.0,3.0,3.0,1.0,2.0,5.0,5.0,0.0,207.0,13.0,51.0,117.0,41.0,1.0,207.0,135.0,0.0,1.0,0.0,132.0,12.0,3.0,0.0,2.0,8.0,0.0,0.0,0.0,0.0,33.0,1.0,3.0,25.0 -Youssef Maleh,ma MAR,MF,Empoli,25-030,1998,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,46.0,55.0,83.6,558.0,158.0,30.0,32.0,93.8,14.0,17.0,82.4,0.0,1.0,0.0,1.0,6.0,2.0,0.0,5.0,53.0,1.0,1.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,5.0,0.0,4.0,1.0,4.0,0.0,4.0,2.0,0.0,0.0,72.0,1.0,9.0,34.0,30.0,1.0,72.0,45.0,3.0,2.0,0.0,51.0,4.0,4.0,0.0,8.0,0.0,0.0,0.0,1.0,0.0,8.0,0.0,1.0,0.0 -Ruslan Malinovskyi,ua UKR,MF,Genoa,30-140,1993,3.0,2.0,143.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,36.0,47.0,76.6,675.0,207.0,13.0,18.0,72.2,17.0,21.0,81.0,5.0,6.0,83.3,1.0,2.0,2.0,0.0,6.0,46.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.26,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,55.0,1.0,14.0,30.0,13.0,1.0,55.0,26.0,0.0,2.0,0.0,38.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,7.0,2.0,1.0,66.7 -Gianluca Mancini,it ITA,DF,Roma,27-157,1996,4.0,4.0,348.0,1.0,0.0,0.0,0.0,0.0,0.0,0.26,0.0,0.26,0.26,0.26,0.9,0.9,0.24,0.24,3.9,3.0,0.0,50.0,0.78,0.17,0.33,0.16,0.1,0.1,205.0,244.0,84.0,3672.0,1464.0,90.0,95.0,94.7,96.0,110.0,87.3,19.0,35.0,54.3,1.0,18.0,4.0,1.0,14.0,237.0,6.0,5.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,0.52,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,5.0,5.0,2.0,0.0,4.0,4.0,0.0,3.0,6.0,0.0,274.0,31.0,130.0,119.0,26.0,6.0,274.0,185.0,7.0,11.0,0.0,213.0,0.0,0.0,0.0,4.0,5.0,0.0,0.0,0.0,0.0,17.0,8.0,6.0,57.1 -Rolando Mandragora,it ITA,MF,Fiorentina,26-084,1997,4.0,3.0,253.0,1.0,0.0,0.0,0.0,0.0,0.0,0.36,0.0,0.36,0.36,0.36,0.3,0.3,0.11,0.11,2.8,2.0,0.0,50.0,0.71,0.25,0.5,0.07,0.7,0.7,136.0,155.0,87.7,2358.0,635.0,61.0,69.0,88.4,53.0,58.0,91.4,16.0,19.0,84.2,0.0,19.0,2.0,0.0,21.0,145.0,10.0,7.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.71,1.0,1.0,0.0,0.0,1.0,0.36,0.0,1.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,2.0,0.0,2.0,2.0,2.0,0.0,177.0,2.0,28.0,119.0,30.0,3.0,177.0,115.0,1.0,1.0,0.0,130.0,3.0,3.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,15.0,3.0,4.0,42.9 -Riccardo Marchizza,it ITA,DF,Frosinone,25-179,1998,4.0,4.0,360.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.25,0.25,0.0,0.25,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,108.0,138.0,78.3,1915.0,873.0,41.0,46.0,89.1,51.0,61.0,83.6,13.0,25.0,52.0,4.0,5.0,2.0,2.0,10.0,111.0,27.0,4.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,23.0,0.0,0.0,4.0,1.0,3.0,0.0,0.0,0.0,1.0,0.25,0.0,0.0,0.0,0.0,1.0,2.0,2.0,1.0,1.0,0.0,5.0,1.0,4.0,3.0,12.0,0.0,172.0,18.0,62.0,74.0,36.0,3.0,172.0,60.0,2.0,1.0,0.0,83.0,4.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,20.0,3.0,5.0,37.5 -Pablo Marí,es ESP,DF,Monza,30-021,1993,4.0,4.0,290.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,3.2,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,167.0,179.0,93.3,3505.0,1179.0,41.0,47.0,87.2,106.0,109.0,97.2,19.0,22.0,86.4,0.0,7.0,0.0,0.0,7.0,178.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,5.0,2.0,0.0,2.0,1.0,1.0,4.0,6.0,1.0,202.0,27.0,97.0,100.0,5.0,2.0,202.0,125.0,0.0,0.0,0.0,154.0,1.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,14.0,5.0,4.0,55.6 -Mirko Marić,hr CRO,FW,Monza,28-128,1995,3.0,1.0,103.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.36,0.36,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.4,-0.4,23.0,30.0,76.7,264.0,19.0,14.0,17.0,82.4,6.0,8.0,75.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,1.0,28.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,2.62,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,43.0,2.0,3.0,19.0,22.0,7.0,43.0,22.0,0.0,0.0,0.0,33.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,3.0,3.0,6.0,33.3 -Răzvan Marin,ro ROU,MF,Empoli,27-121,1996,3.0,3.0,234.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.08,0.08,2.6,3.0,2.0,60.0,1.15,0.0,0.0,0.04,-0.2,-0.2,106.0,141.0,75.2,2032.0,630.0,47.0,54.0,87.0,34.0,43.0,79.1,21.0,35.0,60.0,3.0,12.0,3.0,1.0,12.0,121.0,20.0,14.0,3.0,0.0,9.0,6.0,3.0,2.0,0.0,0.0,0.0,3.0,6.0,2.31,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,4.0,0.0,1.0,0.0,1.0,0.0,6.0,0.0,164.0,8.0,36.0,94.0,36.0,1.0,164.0,96.0,3.0,5.0,0.0,108.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,11.0,2.0,1.0,66.7 -Agustín Martegani,ar ARG,MF,Salernitana,23-124,2000,3.0,0.0,113.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.3,1.0,0.0,33.3,0.8,0.0,0.0,0.03,-0.1,-0.1,60.0,67.0,89.6,897.0,244.0,32.0,34.0,94.1,18.0,20.0,90.0,5.0,8.0,62.5,2.0,9.0,2.0,0.0,5.0,64.0,3.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.78,5.0,1.0,0.0,0.0,1.0,0.8,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,0.0,2.0,0.0,0.0,0.0,1.0,1.0,0.0,80.0,4.0,9.0,49.0,22.0,1.0,80.0,52.0,3.0,2.0,1.0,58.0,2.0,1.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0 -Aarón Martín,es ESP,DF,Genoa,26-152,1997,4.0,2.0,157.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,47.0,66.0,71.2,759.0,336.0,25.0,27.0,92.6,17.0,24.0,70.8,3.0,11.0,27.3,0.0,3.0,1.0,1.0,5.0,52.0,14.0,1.0,0.0,0.0,9.0,1.0,0.0,1.0,0.0,12.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,74.0,2.0,21.0,25.0,31.0,0.0,74.0,36.0,2.0,4.0,0.0,38.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,12.0,0.0,1.0,0.0 -Josep Martinez,es ESP,GK,Genoa,25-117,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,100.0,148.0,67.6,3647.0,2987.0,9.0,9.0,100.0,39.0,40.0,97.5,52.0,96.0,54.2,0.0,5.0,0.0,0.0,0.0,101.0,46.0,24.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,154.0,123.0,154.0,0.0,0.0,0.0,154.0,95.0,0.0,0.0,0.0,66.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,100.0 -Lautaro Martínez,ar ARG,FW,Inter,26-030,1997,4.0,4.0,349.0,5.0,1.0,0.0,0.0,1.0,0.0,1.29,0.26,1.55,1.29,1.55,2.9,2.9,0.74,0.74,3.9,7.0,0.0,43.8,1.81,0.31,0.71,0.18,2.1,2.1,75.0,97.0,77.3,1059.0,294.0,42.0,49.0,85.7,23.0,30.0,76.7,3.0,5.0,60.0,4.0,6.0,1.0,0.0,9.0,93.0,4.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,20.0,5.16,13.0,0.0,3.0,2.0,4.0,1.03,2.0,0.0,0.0,1.0,1.0,2.0,1.0,1.0,1.0,0.0,5.0,0.0,5.0,5.0,2.0,0.0,158.0,1.0,16.0,69.0,74.0,28.0,158.0,109.0,6.0,3.0,2.0,114.0,7.0,4.0,0.0,5.0,9.0,1.0,1.0,0.0,0.0,9.0,3.0,5.0,37.5 -Lucas Martínez Quarta,ar ARG,DF,Fiorentina,27-134,1996,2.0,2.0,180.0,1.0,0.0,0.0,0.0,1.0,0.0,0.5,0.0,0.5,0.5,0.5,0.3,0.3,0.13,0.13,2.0,2.0,0.0,66.7,1.0,0.33,0.5,0.09,0.7,0.7,83.0,101.0,82.2,1809.0,740.0,19.0,23.0,82.6,50.0,54.0,92.6,13.0,21.0,61.9,1.0,10.0,1.0,0.0,10.0,95.0,6.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,2.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,7.0,6.0,5.0,0.0,1.0,0.0,1.0,2.0,4.0,0.0,131.0,5.0,61.0,61.0,10.0,5.0,131.0,68.0,1.0,0.0,1.0,68.0,1.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,13.0,7.0,4.0,63.6 -Adam Marušić,me MNE,DF,Lazio,30-339,1992,4.0,4.0,335.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.7,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,177.0,215.0,82.3,2697.0,997.0,98.0,112.0,87.5,69.0,82.0,84.1,6.0,12.0,50.0,2.0,17.0,3.0,2.0,17.0,187.0,28.0,3.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,25.0,0.0,5.0,5.0,1.34,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,6.0,3.0,4.0,0.0,3.0,2.0,1.0,4.0,4.0,1.0,243.0,12.0,89.0,116.0,38.0,1.0,243.0,126.0,4.0,5.0,0.0,164.0,3.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,20.0,0.0,7.0,0.0 -Luca Mazzitelli,it ITA,MF,Frosinone,27-310,1995,4.0,4.0,340.0,2.0,0.0,0.0,0.0,1.0,0.0,0.53,0.0,0.53,0.53,0.53,0.4,0.4,0.12,0.12,3.8,3.0,0.0,42.9,0.79,0.29,0.67,0.06,1.6,1.6,151.0,203.0,74.4,2314.0,799.0,80.0,88.0,90.9,49.0,59.0,83.1,12.0,35.0,34.3,1.0,20.0,1.0,0.0,30.0,192.0,7.0,6.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,1.0,4.0,5.0,5.0,1.33,4.0,0.0,1.0,0.0,1.0,0.27,0.0,0.0,1.0,0.0,0.0,5.0,3.0,3.0,1.0,1.0,5.0,1.0,4.0,2.0,12.0,0.0,247.0,14.0,51.0,163.0,35.0,6.0,247.0,126.0,3.0,1.0,0.0,176.0,3.0,2.0,0.0,7.0,9.0,1.0,0.0,0.0,0.0,20.0,5.0,3.0,62.5 -Pasquale Mazzocchi,it ITA,DF,Salernitana,28-056,1995,4.0,3.0,245.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,2.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,86.0,122.0,70.5,1188.0,441.0,49.0,63.0,77.8,31.0,40.0,77.5,2.0,9.0,22.2,1.0,5.0,2.0,1.0,8.0,91.0,31.0,1.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,30.0,0.0,6.0,6.0,2.2,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,4.0,1.0,3.0,0.0,4.0,0.0,155.0,5.0,45.0,60.0,51.0,3.0,155.0,80.0,9.0,8.0,1.0,88.0,7.0,2.0,0.0,2.0,0.0,2.0,0.0,0.0,0.0,11.0,1.0,6.0,14.3 -Jordi Mboula,es ESP,"MF,FW",Hellas Verona,24-189,1999,3.0,2.0,116.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.3,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,16.0,26.0,61.5,231.0,46.0,9.0,13.0,69.2,5.0,6.0,83.3,1.0,1.0,100.0,0.0,0.0,0.0,0.0,2.0,25.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,0.0,5.0,17.0,11.0,4.0,33.0,25.0,3.0,1.0,1.0,26.0,3.0,4.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,3.0,2.0,6.0,25.0 -Weston McKennie,us USA,DF,Juventus,25-024,1998,4.0,2.0,208.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.43,0.43,0.0,0.43,0.2,0.2,0.09,0.09,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.2,-0.2,57.0,83.0,68.7,899.0,267.0,36.0,46.0,78.3,13.0,24.0,54.2,6.0,9.0,66.7,5.0,2.0,2.0,0.0,5.0,73.0,10.0,2.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,8.0,0.0,1.0,6.0,2.6,5.0,1.0,0.0,0.0,1.0,0.43,1.0,0.0,0.0,0.0,0.0,7.0,7.0,5.0,2.0,0.0,4.0,1.0,3.0,3.0,7.0,0.0,113.0,14.0,39.0,28.0,46.0,12.0,113.0,52.0,7.0,5.0,1.0,64.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,8.0,6.0,1.0,85.7 -Arthur Melo,br BRA,MF,Fiorentina,27-040,1996,4.0,3.0,262.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.34,0.34,0.0,0.34,0.0,0.0,0.0,0.0,2.9,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,175.0,187.0,93.6,3697.0,827.0,44.0,48.0,91.7,98.0,101.0,97.0,30.0,31.0,96.8,3.0,17.0,1.0,0.0,17.0,174.0,13.0,12.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,7.0,2.4,7.0,0.0,0.0,0.0,2.0,0.69,2.0,0.0,0.0,0.0,0.0,7.0,6.0,2.0,4.0,1.0,5.0,0.0,5.0,2.0,2.0,0.0,210.0,4.0,48.0,134.0,29.0,1.0,210.0,145.0,3.0,2.0,0.0,163.0,1.0,3.0,0.0,4.0,9.0,0.0,0.0,0.0,0.0,17.0,0.0,1.0,0.0 -Alex Meret,it ITA,GK,Napoli,26-183,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,87.0,97.0,89.7,1839.0,922.0,22.0,22.0,100.0,53.0,54.0,98.1,12.0,21.0,57.1,0.0,0.0,0.0,0.0,0.0,79.0,18.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0,72.0,99.0,1.0,0.0,0.0,100.0,66.0,0.0,0.0,0.0,60.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,1.0,0.0,100.0 -Nikola Milenković,rs SRB,DF,Fiorentina,25-344,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,211.0,248.0,85.1,4534.0,1418.0,58.0,66.0,87.9,120.0,130.0,92.3,32.0,43.0,74.4,0.0,8.0,0.0,0.0,10.0,243.0,4.0,4.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,3.0,0.75,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,2.0,3.0,0.0,5.0,3.0,2.0,1.0,9.0,0.0,270.0,18.0,147.0,122.0,1.0,1.0,270.0,184.0,0.0,1.0,0.0,189.0,1.0,0.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,21.0,8.0,2.0,80.0 -Arkadiusz Milik,pl POL,FW,Juventus,29-205,1994,4.0,0.0,59.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.53,1.53,0.0,1.53,0.8,0.8,1.19,1.19,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.13,-0.8,-0.8,27.0,30.0,90.0,374.0,53.0,15.0,16.0,93.8,9.0,10.0,90.0,1.0,1.0,100.0,2.0,1.0,0.0,0.0,0.0,29.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,3.1,1.0,0.0,1.0,0.0,1.0,1.55,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,45.0,1.0,5.0,22.0,18.0,8.0,45.0,32.0,1.0,0.0,1.0,36.0,3.0,1.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,5.0,2.0,2.0,50.0 -Vanja Milinković-Savić,rs SRB,GK,Torino,26-213,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,102.0,154.0,66.2,3382.0,2678.0,16.0,16.0,100.0,44.0,44.0,100.0,42.0,93.0,45.2,0.0,4.0,0.0,0.0,0.0,109.0,44.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,166.0,135.0,166.0,0.0,0.0,0.0,166.0,94.0,0.0,0.0,0.0,68.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,0.0,100.0 -Aleksei Miranchuk,ru RUS,DF,Atalanta,27-339,1995,1.0,0.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,11.0,63.6,125.0,24.0,3.0,3.0,100.0,3.0,4.0,75.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,2.0,11.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,0.0,1.0,9.0,3.0,0.0,13.0,11.0,2.0,1.0,0.0,11.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Kevin Miranda,it ITA,DF,Sassuolo,20-195,2003,1.0,0.0,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,10.0,90.0,165.0,43.0,3.0,3.0,100.0,5.0,6.0,83.3,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,11.0,1.0,7.0,5.0,0.0,0.0,11.0,8.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Fabio Miretti,it ITA,MF,Juventus,20-049,2003,3.0,3.0,164.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,48.0,64.0,75.0,779.0,255.0,21.0,23.0,91.3,22.0,25.0,88.0,3.0,8.0,37.5,2.0,4.0,4.0,2.0,4.0,57.0,6.0,2.0,1.0,0.0,4.0,4.0,0.0,1.0,0.0,0.0,1.0,3.0,6.0,3.29,4.0,1.0,0.0,0.0,1.0,0.55,1.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,86.0,2.0,18.0,36.0,34.0,7.0,86.0,51.0,4.0,3.0,0.0,58.0,3.0,0.0,0.0,5.0,6.0,0.0,0.0,0.0,0.0,9.0,0.0,2.0,0.0 -Filippo Missori,it ITA,DF,Sassuolo,19-181,2004,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.21,0.21,0.5,1.0,0.0,50.0,2.0,0.0,0.0,0.05,-0.1,-0.1,19.0,26.0,73.1,339.0,92.0,9.0,9.0,100.0,5.0,9.0,55.6,4.0,5.0,80.0,1.0,0.0,1.0,1.0,2.0,23.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,35.0,3.0,14.0,12.0,9.0,1.0,35.0,20.0,3.0,1.0,1.0,22.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,100.0 -Henrikh Mkhitaryan,am ARM,MF,Inter,34-243,1989,4.0,4.0,351.0,2.0,1.0,0.0,0.0,1.0,0.0,0.51,0.26,0.77,0.51,0.77,1.1,1.1,0.27,0.27,3.9,2.0,0.0,28.6,0.51,0.29,1.0,0.15,0.9,0.9,180.0,212.0,84.9,2570.0,569.0,103.0,111.0,92.8,59.0,69.0,85.5,8.0,14.0,57.1,5.0,24.0,4.0,0.0,23.0,208.0,4.0,3.0,3.0,2.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,6.0,14.0,3.59,13.0,1.0,0.0,0.0,3.0,0.77,3.0,0.0,0.0,0.0,0.0,6.0,3.0,1.0,4.0,1.0,1.0,0.0,1.0,4.0,5.0,0.0,244.0,3.0,46.0,129.0,73.0,13.0,244.0,160.0,8.0,6.0,3.0,179.0,4.0,0.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,27.0,2.0,2.0,50.0 -Ilario Monterisi,it ITA,DF,Frosinone,21-276,2001,4.0,4.0,315.0,1.0,0.0,0.0,0.0,0.0,0.0,0.29,0.0,0.29,0.29,0.29,0.3,0.3,0.09,0.09,3.5,1.0,0.0,100.0,0.29,1.0,1.0,0.31,0.7,0.7,196.0,233.0,84.1,3450.0,1735.0,85.0,91.0,93.4,88.0,94.0,93.6,18.0,36.0,50.0,1.0,10.0,1.0,0.0,9.0,217.0,15.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,2.0,0.57,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,3.0,2.0,0.0,5.0,5.0,0.0,1.0,15.0,0.0,262.0,55.0,172.0,88.0,4.0,1.0,262.0,151.0,0.0,1.0,0.0,175.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,23.0,14.0,8.0,63.6 -Lorenzo Montipò,it ITA,GK,Hellas Verona,27-213,1996,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,84.0,144.0,58.3,3127.0,2614.0,11.0,11.0,100.0,31.0,32.0,96.9,42.0,101.0,41.6,0.0,4.0,0.0,0.0,0.0,95.0,49.0,14.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,164.0,123.0,163.0,1.0,0.0,0.0,164.0,73.0,0.0,0.0,0.0,60.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.0,1.0,1.0,50.0 -Nikola Moro,hr CRO,"MF,FW",Bologna,25-193,1998,4.0,3.0,182.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,90.0,110.0,81.8,1703.0,386.0,37.0,42.0,88.1,38.0,40.0,95.0,13.0,18.0,72.2,2.0,10.0,2.0,1.0,10.0,109.0,1.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,1.98,4.0,0.0,0.0,0.0,1.0,0.49,1.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,4.0,0.0,4.0,2.0,2.0,0.0,132.0,3.0,22.0,84.0,30.0,1.0,132.0,73.0,3.0,6.0,0.0,103.0,3.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,10.0,2.0,0.0,100.0 -Dany Mota,pt POR,"FW,MF",Monza,25-142,1998,4.0,2.0,225.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.9,0.38,0.38,2.5,4.0,0.0,36.4,1.6,0.0,0.0,0.09,-0.9,-0.9,38.0,55.0,69.1,699.0,77.0,18.0,21.0,85.7,16.0,20.0,80.0,4.0,5.0,80.0,3.0,3.0,1.0,1.0,4.0,48.0,5.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,1.0,2.0,3.0,7.0,2.81,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,3.0,0.0,91.0,3.0,6.0,27.0,58.0,23.0,91.0,52.0,7.0,3.0,2.0,63.0,7.0,2.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,8.0,7.0,9.0,43.8 -Samuele Mulattieri,it ITA,FW,Sassuolo,22-349,2000,4.0,0.0,52.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.17,0.17,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.1,-0.1,16.0,18.0,88.9,186.0,10.0,10.0,10.0,100.0,4.0,4.0,100.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,15.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.46,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,34.0,2.0,4.0,20.0,10.0,3.0,34.0,17.0,3.0,1.0,2.0,21.0,5.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,5.0,37.5 -Luis Muriel,co COL,FW,Atalanta,32-158,1991,2.0,0.0,25.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.29,0.29,0.3,1.0,0.0,100.0,3.6,0.0,0.0,0.08,-0.1,-0.1,17.0,21.0,81.0,307.0,110.0,11.0,13.0,84.6,3.0,3.0,100.0,3.0,5.0,60.0,5.0,1.0,1.0,0.0,3.0,16.0,5.0,1.0,0.0,0.0,5.0,3.0,3.0,0.0,0.0,1.0,0.0,0.0,6.0,20.77,4.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,24.0,0.0,0.0,9.0,16.0,4.0,24.0,17.0,3.0,2.0,1.0,19.0,1.0,3.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,100.0 -Yunus Musah,us USA,MF,Milan,20-296,2002,2.0,0.0,30.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,15.0,86.7,160.0,6.0,11.0,12.0,91.7,2.0,2.0,100.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,19.0,1.0,4.0,12.0,3.0,0.0,19.0,18.0,1.0,0.0,0.0,17.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 -Juan Musso,ar ARG,GK,Atalanta,29-138,1994,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,81.0,106.0,76.4,2016.0,1333.0,18.0,18.0,100.0,40.0,40.0,100.0,22.0,47.0,46.8,0.0,0.0,0.0,0.0,0.0,85.0,21.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.33,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,112.0,88.0,111.0,1.0,0.0,0.0,112.0,75.0,0.0,0.0,0.0,55.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,0.0,0.0,0.0 -Obite N'Dicka,ci CIV,DF,Roma,24-032,1999,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,68.0,72.0,94.4,1046.0,427.0,35.0,35.0,100.0,31.0,33.0,93.9,2.0,3.0,66.7,0.0,3.0,0.0,0.0,3.0,72.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,2.0,0.0,2.0,0.0,2.0,0.0,80.0,15.0,51.0,28.0,1.0,0.0,80.0,59.0,0.0,0.0,0.0,64.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.0,1.0,75.0 -Nahitan Nández,uy URU,"MF,FW",Cagliari,27-267,1995,4.0,3.0,218.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.22,0.22,2.4,2.0,0.0,50.0,0.83,0.0,0.0,0.14,-0.5,-0.5,48.0,82.0,58.5,817.0,281.0,29.0,34.0,85.3,13.0,21.0,61.9,6.0,22.0,27.3,3.0,3.0,3.0,1.0,9.0,76.0,6.0,2.0,1.0,2.0,13.0,1.0,0.0,1.0,0.0,2.0,0.0,3.0,6.0,2.48,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,2.0,0.0,2.0,2.0,1.0,0.0,102.0,1.0,10.0,43.0,50.0,4.0,102.0,61.0,7.0,2.0,1.0,71.0,5.0,3.0,0.0,7.0,3.0,2.0,0.0,0.0,0.0,11.0,4.0,8.0,33.3 -Michel Ndary Adopo,fr FRA,MF,Atalanta,23-064,2000,2.0,0.0,21.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,4.29,4.29,0.0,4.29,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,17.0,70.6,239.0,89.0,4.0,7.0,57.1,8.0,9.0,88.9,0.0,0.0,0.0,1.0,2.0,0.0,0.0,2.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.29,1.0,0.0,0.0,0.0,1.0,4.29,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,19.0,1.0,4.0,11.0,4.0,1.0,19.0,15.0,0.0,0.0,0.0,17.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 -Dan Ndoye,ch SUI,"FW,MF",Bologna,22-331,2000,4.0,4.0,321.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.16,0.16,3.6,4.0,0.0,40.0,1.12,0.0,0.0,0.06,-0.6,-0.6,91.0,123.0,74.0,1459.0,325.0,50.0,61.0,82.0,27.0,33.0,81.8,10.0,17.0,58.8,5.0,9.0,3.0,1.0,10.0,116.0,6.0,0.0,0.0,1.0,13.0,5.0,3.0,1.0,0.0,1.0,1.0,4.0,16.0,4.49,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,5.0,2.0,0.0,5.0,0.0,5.0,0.0,3.0,0.0,184.0,2.0,24.0,77.0,86.0,13.0,184.0,122.0,18.0,12.0,3.0,133.0,14.0,2.0,0.0,3.0,11.0,0.0,0.0,0.0,0.0,21.0,3.0,3.0,50.0 -Cyril Ngonge,be BEL,"MF,FW",Hellas Verona,23-118,2000,4.0,4.0,310.0,2.0,0.0,0.0,0.0,0.0,0.0,0.58,0.0,0.58,0.58,0.58,0.6,0.6,0.16,0.16,3.4,3.0,0.0,42.9,0.87,0.29,0.67,0.08,1.4,1.4,51.0,74.0,68.9,1046.0,229.0,17.0,25.0,68.0,25.0,30.0,83.3,8.0,13.0,61.5,5.0,5.0,2.0,1.0,7.0,63.0,10.0,1.0,1.0,1.0,6.0,1.0,0.0,1.0,0.0,1.0,1.0,3.0,10.0,2.9,8.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,106.0,2.0,7.0,45.0,55.0,9.0,106.0,64.0,11.0,4.0,5.0,68.0,6.0,4.0,0.0,10.0,3.0,2.0,0.0,0.0,0.0,10.0,4.0,7.0,36.4 -Rasmus Nissen,dk DEN,"DF,FW",Roma,26-072,1997,3.0,3.0,199.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.45,0.45,0.0,0.45,0.0,0.0,0.0,0.0,2.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,88.0,122.0,72.1,1387.0,372.0,53.0,59.0,89.8,30.0,49.0,61.2,4.0,9.0,44.4,3.0,3.0,2.0,2.0,3.0,94.0,27.0,1.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,26.0,1.0,2.0,4.0,1.81,3.0,0.0,0.0,0.0,1.0,0.45,1.0,0.0,0.0,0.0,0.0,6.0,3.0,4.0,2.0,0.0,5.0,0.0,5.0,1.0,2.0,0.0,142.0,2.0,48.0,60.0,34.0,2.0,142.0,74.0,1.0,2.0,1.0,81.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,1.0,2.0,33.3 -M'Bala Nzola,ao ANG,FW,Fiorentina,27-034,1996,4.0,2.0,225.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.0,0.4,0.2,0.2,0.08,0.08,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.2,-0.2,51.0,59.0,86.4,672.0,65.0,39.0,43.0,90.7,5.0,7.0,71.4,4.0,4.0,100.0,2.0,3.0,1.0,0.0,2.0,53.0,6.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,2.0,0.8,1.0,0.0,1.0,0.0,1.0,0.4,0.0,0.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,2.0,1.0,0.0,1.0,0.0,2.0,0.0,87.0,2.0,3.0,43.0,43.0,7.0,87.0,61.0,1.0,2.0,0.0,70.0,13.0,8.0,0.0,6.0,1.0,2.0,0.0,0.0,0.0,8.0,7.0,7.0,50.0 -Adam Obert,sk SVK,DF,Cagliari,21-029,2002,3.0,2.0,187.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,63.0,86.0,73.3,1303.0,419.0,24.0,27.0,88.9,28.0,34.0,82.4,11.0,23.0,47.8,2.0,4.0,1.0,1.0,3.0,79.0,6.0,4.0,1.0,4.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,3.0,1.44,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,2.0,0.0,3.0,1.0,2.0,4.0,11.0,0.0,109.0,14.0,60.0,46.0,3.0,0.0,109.0,53.0,1.0,1.0,0.0,57.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,8.0,5.0,3.0,62.5 -Guillermo Ochoa,mx MEX,GK,Salernitana,38-070,1985,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,77.0,125.0,61.6,2062.0,1412.0,9.0,9.0,100.0,50.0,50.0,100.0,18.0,64.0,28.1,0.0,3.0,1.0,0.0,0.0,74.0,50.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,135.0,110.0,135.0,0.0,0.0,0.0,135.0,66.0,0.0,0.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 -Noah Okafor,ch SUI,FW,Milan,23-120,2000,4.0,0.0,71.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,7.0,57.1,47.0,16.0,1.0,1.0,100.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,17.0,2.0,3.0,8.0,7.0,2.0,17.0,14.0,2.0,1.0,1.0,15.0,2.0,2.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,2.0,1.0,3.0,25.0 -Caleb Okoli,it ITA,DF,Frosinone,22-070,2001,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,23.0,26.0,88.5,520.0,293.0,8.0,8.0,100.0,11.0,12.0,91.7,3.0,4.0,75.0,0.0,3.0,1.0,0.0,1.0,26.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,29.0,4.0,20.0,9.0,0.0,0.0,29.0,22.0,0.0,0.0,0.0,22.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Mathías Olivera,uy URU,DF,Napoli,25-325,1997,4.0,3.0,263.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.9,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,168.0,196.0,85.7,2506.0,525.0,100.0,109.0,91.7,58.0,65.0,89.2,7.0,9.0,77.8,4.0,9.0,3.0,2.0,9.0,166.0,29.0,4.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,25.0,1.0,8.0,8.0,2.74,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,3.0,1.0,1.0,3.0,0.0,3.0,2.0,3.0,0.0,223.0,6.0,53.0,113.0,58.0,14.0,223.0,116.0,7.0,7.0,0.0,140.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,12.0,9.0,6.0,60.0 -Gaetano Oristanio,it ITA,"FW,DF",Cagliari,20-358,2002,3.0,2.0,130.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.4,0.0,1.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,16.0,24.0,66.7,221.0,52.0,12.0,13.0,92.3,2.0,5.0,40.0,1.0,2.0,50.0,1.0,2.0,0.0,0.0,2.0,18.0,6.0,0.0,0.0,0.0,4.0,2.0,2.0,0.0,0.0,0.0,0.0,3.0,4.0,2.77,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,41.0,0.0,4.0,17.0,22.0,5.0,41.0,30.0,3.0,4.0,3.0,27.0,9.0,7.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,7.0,1.0,2.0,33.3 -Riccardo Orsolini,it ITA,FW,Bologna,26-240,1997,4.0,1.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.1,0.48,0.04,1.8,1.0,0.0,50.0,0.56,0.0,0.0,0.03,-0.9,-0.1,39.0,55.0,70.9,542.0,152.0,21.0,22.0,95.5,15.0,23.0,65.2,2.0,7.0,28.6,3.0,1.0,4.0,1.0,8.0,50.0,5.0,4.0,0.0,1.0,5.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,7.0,3.94,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,2.0,1.0,1.0,1.0,2.0,0.0,73.0,1.0,12.0,24.0,38.0,9.0,72.0,43.0,7.0,7.0,4.0,50.0,3.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,5.0,3.0,2.0,60.0 -Victor Osimhen,ng NGA,FW,Napoli,24-266,1998,4.0,4.0,350.0,3.0,0.0,1.0,1.0,0.0,0.0,0.77,0.0,0.77,0.51,0.51,2.6,1.8,0.67,0.47,3.9,3.0,0.0,16.7,0.77,0.11,0.67,0.1,0.4,0.2,32.0,47.0,68.1,381.0,89.0,16.0,19.0,84.2,9.0,13.0,69.2,0.0,1.0,0.0,5.0,4.0,0.0,0.0,4.0,36.0,8.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,7.0,1.8,4.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,4.0,0.0,100.0,4.0,6.0,37.0,58.0,31.0,99.0,51.0,9.0,4.0,2.0,67.0,12.0,2.0,0.0,7.0,4.0,7.0,0.0,0.0,0.0,6.0,9.0,10.0,47.4 -Anthony Oyono,ga GAB,DF,Frosinone,22-162,2001,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,164.0,198.0,82.8,2254.0,953.0,102.0,112.0,91.1,45.0,57.0,78.9,8.0,17.0,47.1,6.0,9.0,4.0,3.0,10.0,147.0,51.0,3.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,48.0,0.0,3.0,9.0,2.25,6.0,3.0,0.0,0.0,2.0,0.5,0.0,2.0,0.0,0.0,0.0,8.0,5.0,6.0,2.0,0.0,7.0,2.0,5.0,5.0,15.0,0.0,247.0,20.0,82.0,108.0,59.0,7.0,247.0,123.0,12.0,8.0,5.0,129.0,9.0,1.0,0.0,2.0,8.0,0.0,0.0,0.0,0.0,19.0,5.0,3.0,62.5 -Riccardo Pagano,it ITA,"MF,DF",Roma,18-297,2004,3.0,0.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.17,0.17,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,18.0,18.0,100.0,327.0,66.0,8.0,8.0,100.0,7.0,7.0,100.0,3.0,3.0,100.0,1.0,4.0,0.0,0.0,2.0,17.0,1.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,5.0,15.52,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,24.0,0.0,4.0,13.0,7.0,0.0,24.0,15.0,1.0,1.0,0.0,17.0,1.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Leandro Paredes,ar ARG,MF,Roma,29-084,1994,4.0,3.0,214.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.42,0.42,0.0,0.42,0.2,0.2,0.07,0.07,2.4,0.0,1.0,0.0,0.0,0.0,0.0,0.04,-0.2,-0.2,134.0,155.0,86.5,2498.0,898.0,56.0,58.0,96.6,63.0,71.0,88.7,14.0,24.0,58.3,2.0,14.0,0.0,0.0,11.0,137.0,18.0,10.0,1.0,2.0,9.0,6.0,5.0,1.0,0.0,2.0,0.0,2.0,7.0,2.94,4.0,2.0,0.0,1.0,1.0,0.42,0.0,1.0,0.0,0.0,0.0,6.0,2.0,4.0,1.0,1.0,1.0,0.0,1.0,3.0,3.0,0.0,169.0,7.0,39.0,103.0,29.0,0.0,169.0,109.0,0.0,7.0,0.0,122.0,1.0,1.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,12.0,2.0,0.0,100.0 -Fabiano Parisi,it ITA,DF,Fiorentina,22-316,2000,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,117.0,151.0,77.5,2224.0,841.0,50.0,53.0,94.3,49.0,66.0,74.2,17.0,24.0,70.8,1.0,7.0,2.0,1.0,10.0,117.0,34.0,5.0,1.0,2.0,6.0,0.0,0.0,0.0,0.0,29.0,0.0,7.0,4.0,2.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,1.0,3.0,2.0,1.0,1.0,3.0,1.0,0.0,173.0,6.0,46.0,97.0,34.0,0.0,173.0,109.0,6.0,6.0,0.0,96.0,4.0,1.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,22.0,0.0,5.0,0.0 -Mario Pašalić,hr CRO,"MF,FW",Atalanta,28-224,1995,2.0,1.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.12,0.12,0.9,1.0,0.0,100.0,1.17,0.0,0.0,0.1,-0.1,-0.1,19.0,24.0,79.2,368.0,56.0,8.0,9.0,88.9,9.0,10.0,90.0,2.0,4.0,50.0,0.0,3.0,0.0,0.0,1.0,24.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,2.34,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,0.0,28.0,2.0,8.0,14.0,6.0,2.0,28.0,18.0,1.0,0.0,1.0,20.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,4.0,20.0 -Patric,es ESP,DF,Lazio,30-157,1993,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,54.0,63.0,85.7,1063.0,385.0,15.0,15.0,100.0,31.0,32.0,96.9,8.0,16.0,50.0,1.0,3.0,1.0,0.0,3.0,58.0,5.0,5.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,1.0,1.0,0.0,3.0,0.0,69.0,6.0,35.0,34.0,0.0,0.0,69.0,51.0,0.0,0.0,0.0,55.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Rui Patrício,pt POR,GK,Roma,35-218,1988,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,84.0,93.0,90.3,2137.0,1299.0,20.0,20.0,100.0,40.0,40.0,100.0,24.0,33.0,72.7,0.0,0.0,0.0,0.0,0.0,73.0,20.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,98.0,88.0,98.0,0.0,0.0,0.0,98.0,65.0,0.0,0.0,0.0,54.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0 -Leonardo Pavoletti,it ITA,FW,Cagliari,34-299,1988,3.0,2.0,112.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.13,0.13,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,19.0,32.0,59.4,299.0,72.0,9.0,13.0,69.2,6.0,10.0,60.0,2.0,3.0,66.7,0.0,3.0,1.0,0.0,4.0,31.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,3.0,2.41,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,51.0,1.0,5.0,26.0,20.0,5.0,51.0,25.0,0.0,0.0,0.0,39.0,8.0,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,4.0,11.0,7.0,61.1 -Martín Payero,ar ARG,MF,Udinese,25-010,1998,1.0,0.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,15.0,100.0,185.0,60.0,11.0,11.0,100.0,3.0,3.0,100.0,1.0,1.0,100.0,0.0,2.0,1.0,0.0,1.0,14.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.74,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,20.0,0.0,4.0,10.0,6.0,0.0,20.0,10.0,1.0,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 -Marcus Pedersen,no NOR,DF,Sassuolo,23-067,2000,3.0,0.0,94.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,22.0,32.0,68.8,369.0,81.0,8.0,9.0,88.9,12.0,18.0,66.7,1.0,1.0,100.0,0.0,0.0,0.0,0.0,1.0,25.0,7.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,0.0,42.0,3.0,12.0,16.0,15.0,3.0,42.0,16.0,1.0,2.0,0.0,19.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0 -Pedro,es ESP,FW,Lazio,36-055,1987,3.0,0.0,48.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,26.0,80.8,257.0,68.0,12.0,13.0,92.3,6.0,7.0,85.7,0.0,1.0,0.0,2.0,0.0,0.0,0.0,1.0,26.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,5.63,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,2.0,0.0,2.0,0.0,0.0,0.0,34.0,0.0,5.0,15.0,15.0,2.0,34.0,25.0,3.0,4.0,1.0,27.0,3.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Pietro Pellegri,it ITA,FW,Torino,22-188,2001,4.0,0.0,122.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.14,0.14,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,15.0,21.0,71.4,168.0,21.0,12.0,14.0,85.7,2.0,4.0,50.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.48,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,0.0,5.0,14.0,20.0,5.0,38.0,24.0,2.0,2.0,0.0,29.0,6.0,3.0,0.0,3.0,7.0,3.0,0.0,0.0,0.0,2.0,5.0,7.0,41.7 -Lorenzo Pellegrini,it ITA,MF,Roma,27-094,1996,2.0,1.0,150.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.24,0.24,1.7,0.0,2.0,0.0,0.0,0.0,0.0,0.06,-0.4,-0.4,42.0,63.0,66.7,693.0,246.0,20.0,22.0,90.9,19.0,25.0,76.0,2.0,13.0,15.4,6.0,8.0,0.0,0.0,7.0,47.0,16.0,6.0,0.0,1.0,16.0,10.0,2.0,7.0,0.0,0.0,0.0,0.0,9.0,5.4,3.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,3.0,1.0,0.0,0.0,0.0,1.0,2.0,0.0,83.0,2.0,6.0,38.0,41.0,5.0,83.0,40.0,1.0,1.0,1.0,49.0,3.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,9.0,0.0,3.0,0.0 -Luca Pellegrini,it ITA,DF,Lazio,24-198,1999,4.0,0.0,99.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,53.0,73.0,72.6,825.0,227.0,27.0,32.0,84.4,22.0,29.0,75.9,2.0,6.0,33.3,1.0,6.0,2.0,0.0,16.0,63.0,10.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,10.0,0.0,4.0,4.0,3.64,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,88.0,2.0,19.0,30.0,41.0,1.0,88.0,54.0,6.0,1.0,0.0,58.0,3.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,5.0,2.0,3.0,40.0 -Pepín,gq EQG,MF,Monza,27-038,1996,2.0,0.0,36.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.09,0.09,0.4,0.0,1.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,25.0,29.0,86.2,440.0,139.0,10.0,11.0,90.9,12.0,12.0,100.0,2.0,4.0,50.0,0.0,1.0,0.0,0.0,3.0,27.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,35.0,2.0,5.0,23.0,7.0,0.0,35.0,21.0,0.0,2.0,0.0,24.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Pedro Pereira,pt POR,DF,Monza,25-242,1998,3.0,0.0,54.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,57.0,66.7,589.0,149.0,26.0,29.0,89.7,6.0,10.0,60.0,4.0,10.0,40.0,1.0,2.0,2.0,2.0,5.0,52.0,5.0,1.0,0.0,1.0,11.0,0.0,0.0,0.0,0.0,4.0,0.0,4.0,4.0,6.67,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,4.0,1.0,3.0,1.0,3.0,0.0,69.0,2.0,12.0,17.0,40.0,2.0,69.0,41.0,2.0,3.0,0.0,50.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,0.0 -Roberto Pereyra,ar ARG,FW,Udinese,32-257,1991,1.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,79.0,11.0,3.0,3.0,100.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,11.0,0.0,0.0,8.0,3.0,0.0,11.0,6.0,0.0,0.0,0.0,9.0,0.0,1.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Nehuén Pérez,ar ARG,DF,Udinese,23-089,2000,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.08,0.08,4.0,1.0,0.0,20.0,0.25,0.0,0.0,0.06,-0.3,-0.3,182.0,234.0,77.8,3322.0,1450.0,70.0,79.0,88.6,94.0,107.0,87.9,15.0,42.0,35.7,0.0,21.0,2.0,2.0,28.0,216.0,17.0,11.0,1.0,3.0,10.0,0.0,0.0,0.0,0.0,6.0,1.0,0.0,6.0,1.5,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,7.0,5.0,3.0,1.0,4.0,1.0,3.0,5.0,13.0,0.0,273.0,15.0,91.0,147.0,39.0,6.0,273.0,170.0,8.0,8.0,0.0,177.0,2.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,27.0,14.0,5.0,73.7 -Mattia Perin,it ITA,GK,Juventus,30-315,1992,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,44.0,53.0,83.0,969.0,570.0,12.0,12.0,100.0,21.0,21.0,100.0,10.0,19.0,52.6,0.0,0.0,0.0,0.0,0.0,37.0,16.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,56.0,45.0,55.0,1.0,0.0,0.0,56.0,30.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Samuele Perisan,it ITA,GK,Empoli,26-031,1997,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,34.0,79.4,551.0,340.0,10.0,10.0,100.0,11.0,11.0,100.0,5.0,12.0,41.7,0.0,0.0,0.0,0.0,0.0,21.0,13.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,32.0,33.0,0.0,0.0,0.0,33.0,13.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Matteo Pessina,it ITA,MF,Monza,26-153,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,4.0,1.0,0.0,50.0,0.25,0.0,0.0,0.06,-0.1,-0.1,276.0,309.0,89.3,5135.0,1174.0,105.0,117.0,89.7,134.0,141.0,95.0,33.0,40.0,82.5,3.0,36.0,6.0,1.0,32.0,297.0,11.0,7.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,5.0,14.0,3.5,12.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,3.0,4.0,1.0,4.0,1.0,3.0,2.0,6.0,0.0,340.0,12.0,58.0,205.0,82.0,3.0,340.0,224.0,13.0,12.0,0.0,250.0,5.0,0.0,0.0,6.0,3.0,0.0,0.0,0.0,0.0,29.0,3.0,1.0,75.0 -Andrea Petagna,it ITA,FW,Cagliari,28-083,1995,1.0,1.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,8.0,75.0,131.0,2.0,1.0,1.0,100.0,2.0,4.0,50.0,2.0,2.0,100.0,0.0,1.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,11.0,1.0,2.0,4.0,5.0,2.0,11.0,9.0,1.0,0.0,0.0,11.0,2.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,50.0 -Giuseppe Pezzella,it ITA,DF,Empoli,25-296,1997,4.0,2.0,229.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.5,1.0,0.0,100.0,0.39,0.0,0.0,0.1,-0.1,-0.1,156.0,187.0,83.4,2458.0,625.0,86.0,93.0,92.5,55.0,61.0,90.2,12.0,20.0,60.0,2.0,15.0,2.0,1.0,15.0,162.0,25.0,3.0,1.0,0.0,14.0,0.0,0.0,0.0,0.0,22.0,0.0,8.0,4.0,1.58,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,8.0,7.0,3.0,1.0,9.0,4.0,5.0,0.0,5.0,0.0,227.0,11.0,61.0,102.0,65.0,1.0,227.0,136.0,15.0,8.0,0.0,153.0,2.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,17.0,2.0,1.0,66.7 -Roberto Piccoli,it ITA,FW,Empoli,22-237,2001,2.0,0.0,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.12,0.12,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,4.0,6.0,66.7,47.0,16.0,3.0,4.0,75.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.74,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,4.0,6.0,1.0,10.0,5.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,33.3 -Roberto Piccoli,it ITA,FW,Lecce,22-237,2001,2.0,0.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,7.0,42.9,32.0,0.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,18.0,2.0,3.0,7.0,8.0,1.0,18.0,13.0,1.0,1.0,0.0,13.0,1.0,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,0.0 -Andrea Pinamonti,it ITA,FW,Sassuolo,24-125,1999,4.0,4.0,308.0,3.0,0.0,0.0,0.0,0.0,0.0,0.88,0.0,0.88,0.88,0.88,0.8,0.8,0.23,0.23,3.4,3.0,0.0,33.3,0.88,0.33,1.0,0.09,2.2,2.2,49.0,67.0,73.1,646.0,79.0,30.0,33.0,90.9,15.0,19.0,78.9,1.0,3.0,33.3,4.0,1.0,0.0,0.0,2.0,56.0,10.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,6.0,7.0,2.05,5.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,0.0,0.0,0.0,97.0,2.0,3.0,46.0,48.0,15.0,97.0,53.0,2.0,0.0,2.0,71.0,8.0,1.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,3.0,7.0,13.0,35.0 -Lorenzo Pirola,it ITA,DF,Salernitana,21-213,2002,3.0,3.0,252.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,108.0,138.0,78.3,1614.0,666.0,60.0,68.0,88.2,45.0,54.0,83.3,1.0,9.0,11.1,0.0,2.0,1.0,0.0,11.0,132.0,6.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,2.0,0.71,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,2.0,0.0,1.0,1.0,0.0,0.0,9.0,0.0,159.0,15.0,61.0,91.0,7.0,0.0,159.0,79.0,2.0,2.0,0.0,111.0,0.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,10.0,4.0,9.0,30.8 -Tommaso Pobega,it ITA,MF,Milan,24-068,1999,2.0,0.0,39.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.4,1.0,0.0,100.0,2.31,0.0,0.0,0.01,0.0,0.0,13.0,13.0,100.0,265.0,98.0,6.0,6.0,100.0,5.0,5.0,100.0,2.0,2.0,100.0,0.0,1.0,0.0,0.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,2.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,21.0,3.0,6.0,11.0,5.0,0.0,21.0,7.0,0.0,0.0,0.0,13.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Paul Pogba,fr FRA,MF,Juventus,30-190,1993,2.0,0.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,35.0,77.1,425.0,113.0,13.0,14.0,92.9,11.0,13.0,84.6,2.0,4.0,50.0,1.0,5.0,2.0,0.0,5.0,32.0,3.0,3.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,3.33,2.0,0.0,0.0,0.0,1.0,1.67,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,43.0,1.0,4.0,25.0,14.0,2.0,43.0,23.0,1.0,1.0,0.0,32.0,2.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 -Matteo Politano,it ITA,FW,Napoli,30-049,1993,4.0,3.0,255.0,2.0,0.0,0.0,0.0,0.0,0.0,0.71,0.0,0.71,0.71,0.71,0.5,0.5,0.19,0.19,2.8,2.0,0.0,40.0,0.71,0.4,1.0,0.11,1.5,1.5,99.0,132.0,75.0,1752.0,493.0,49.0,53.0,92.5,37.0,56.0,66.1,11.0,17.0,64.7,5.0,13.0,4.0,2.0,18.0,118.0,14.0,5.0,1.0,1.0,17.0,5.0,3.0,0.0,2.0,4.0,0.0,4.0,15.0,5.29,11.0,3.0,0.0,1.0,3.0,1.06,1.0,1.0,0.0,1.0,0.0,4.0,2.0,2.0,0.0,2.0,1.0,0.0,1.0,2.0,2.0,0.0,154.0,2.0,17.0,57.0,83.0,12.0,154.0,97.0,15.0,12.0,4.0,112.0,4.0,1.0,0.0,1.0,2.0,1.0,1.0,0.0,0.0,11.0,0.0,1.0,0.0 -Marin Pongračić,hr CRO,DF,Lecce,26-010,1997,4.0,4.0,360.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,169.0,203.0,83.3,3684.0,1589.0,33.0,42.0,78.6,115.0,126.0,91.3,20.0,30.0,66.7,1.0,9.0,0.0,0.0,14.0,184.0,18.0,18.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,5.0,1.25,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,7.0,4.0,3.0,5.0,20.0,0.0,241.0,45.0,130.0,105.0,10.0,3.0,241.0,152.0,4.0,3.0,0.0,144.0,2.0,1.0,0.0,7.0,2.0,0.0,0.0,0.0,0.0,17.0,10.0,2.0,83.3 -Stefan Posch,at AUT,DF,Bologna,26-130,1997,4.0,3.0,293.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.09,0.09,3.3,1.0,0.0,33.3,0.31,0.0,0.0,0.1,-0.3,-0.3,204.0,239.0,85.4,3386.0,1084.0,96.0,102.0,94.1,90.0,102.0,88.2,14.0,28.0,50.0,1.0,16.0,3.0,1.0,19.0,207.0,32.0,6.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,26.0,0.0,1.0,4.0,1.23,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,7.0,7.0,5.0,2.0,4.0,2.0,2.0,3.0,7.0,0.0,279.0,13.0,82.0,147.0,50.0,5.0,279.0,163.0,4.0,7.0,0.0,198.0,3.0,2.0,0.0,6.0,2.0,0.0,0.0,0.0,0.0,10.0,3.0,5.0,37.5 -Matteo Prati,it ITA,MF,Cagliari,19-267,2003,1.0,1.0,79.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,28.0,78.6,357.0,228.0,9.0,12.0,75.0,13.0,13.0,100.0,0.0,3.0,0.0,0.0,5.0,0.0,0.0,7.0,26.0,2.0,1.0,1.0,0.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.14,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,31.0,1.0,7.0,22.0,3.0,0.0,31.0,15.0,0.0,0.0,0.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 -Ivan Provedel,it ITA,GK,Lazio,29-188,1994,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,120.0,134.0,89.6,2821.0,1844.0,32.0,32.0,100.0,51.0,51.0,100.0,37.0,51.0,72.5,0.0,1.0,1.0,0.0,0.0,110.0,24.0,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,146.0,111.0,144.0,2.0,0.0,0.0,146.0,92.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,7.0,1.0,0.0,100.0 -Christian Pulisic,us USA,FW,Milan,25-003,1998,4.0,4.0,293.0,2.0,0.0,0.0,0.0,0.0,0.0,0.61,0.0,0.61,0.61,0.61,1.0,1.0,0.3,0.3,3.3,4.0,0.0,80.0,1.23,0.4,0.5,0.2,1.0,1.0,102.0,118.0,86.4,1368.0,351.0,63.0,71.0,88.7,29.0,31.0,93.5,5.0,6.0,83.3,4.0,10.0,7.0,2.0,13.0,113.0,5.0,0.0,1.0,0.0,9.0,4.0,0.0,4.0,0.0,1.0,0.0,3.0,11.0,3.37,7.0,2.0,1.0,1.0,2.0,0.61,2.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,1.0,1.0,2.0,0.0,2.0,2.0,1.0,0.0,138.0,1.0,11.0,68.0,61.0,3.0,138.0,109.0,8.0,8.0,2.0,112.0,3.0,3.0,0.0,4.0,5.0,0.0,0.0,0.0,0.0,10.0,1.0,6.0,14.3 -Domingos Quina,pt POR,MF,Udinese,23-307,1999,2.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,13.0,10.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 -Adrien Rabiot,fr FRA,MF,Juventus,28-171,1995,4.0,4.0,360.0,1.0,1.0,0.0,0.0,1.0,0.0,0.25,0.25,0.5,0.25,0.5,1.3,1.3,0.32,0.32,4.0,3.0,0.0,60.0,0.75,0.2,0.33,0.26,-0.3,-0.3,163.0,184.0,88.6,2450.0,517.0,88.0,95.0,92.6,61.0,69.0,88.4,10.0,11.0,90.9,7.0,14.0,2.0,0.0,16.0,179.0,5.0,2.0,1.0,2.0,3.0,0.0,0.0,0.0,0.0,3.0,0.0,4.0,11.0,2.75,10.0,0.0,1.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,12.0,6.0,5.0,5.0,2.0,6.0,1.0,5.0,5.0,5.0,0.0,227.0,6.0,39.0,124.0,68.0,14.0,227.0,134.0,7.0,10.0,2.0,149.0,4.0,1.0,0.0,6.0,2.0,2.0,0.0,0.0,0.0,26.0,4.0,3.0,57.1 -Uroš Račić,rs SRB,"MF,FW",Sassuolo,25-188,1998,2.0,0.0,35.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,0.06,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,9.0,11.0,81.8,156.0,36.0,4.0,5.0,80.0,5.0,5.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,10.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,15.0,2.0,4.0,7.0,4.0,0.0,15.0,5.0,0.0,0.0,0.0,8.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Nemanja Radonjić,rs SRB,MF,Torino,27-218,1996,4.0,2.0,207.0,3.0,0.0,0.0,0.0,0.0,0.0,1.3,0.0,1.3,1.3,1.3,1.6,1.6,0.68,0.68,2.3,4.0,0.0,44.4,1.74,0.33,0.75,0.17,1.4,1.4,32.0,47.0,68.1,467.0,91.0,19.0,26.0,73.1,9.0,12.0,75.0,2.0,5.0,40.0,1.0,2.0,2.0,1.0,4.0,46.0,0.0,0.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,5.0,2.17,2.0,0.0,2.0,0.0,1.0,0.43,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,81.0,0.0,9.0,23.0,49.0,9.0,81.0,55.0,6.0,2.0,3.0,62.0,9.0,3.0,0.0,0.0,3.0,3.0,0.0,0.0,0.0,8.0,0.0,2.0,0.0 -Boris Radunović,rs SRB,GK,Cagliari,27-118,1996,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,85.0,116.0,73.3,2989.0,2228.0,9.0,9.0,100.0,33.0,34.0,97.1,43.0,73.0,58.9,0.0,3.0,0.0,0.0,0.0,66.0,50.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,124.0,109.0,124.0,0.0,0.0,0.0,124.0,62.0,0.0,0.0,0.0,39.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 -Hamza Rafia,tn TUN,MF,Lecce,24-172,1999,4.0,4.0,250.0,1.0,0.0,0.0,0.0,1.0,0.0,0.36,0.0,0.36,0.36,0.36,0.2,0.2,0.07,0.07,2.8,1.0,0.0,25.0,0.36,0.25,1.0,0.05,0.8,0.8,80.0,113.0,70.8,1142.0,303.0,48.0,58.0,82.8,26.0,32.0,81.3,3.0,10.0,30.0,2.0,7.0,0.0,0.0,10.0,111.0,2.0,1.0,0.0,0.0,8.0,1.0,0.0,1.0,0.0,0.0,0.0,7.0,6.0,2.16,2.0,0.0,1.0,1.0,1.0,0.36,0.0,0.0,0.0,0.0,1.0,7.0,5.0,0.0,6.0,1.0,9.0,1.0,8.0,3.0,3.0,0.0,154.0,2.0,17.0,88.0,49.0,5.0,154.0,102.0,6.0,4.0,2.0,116.0,5.0,3.0,0.0,7.0,7.0,0.0,0.0,0.0,0.0,11.0,1.0,3.0,25.0 -Ylber Ramadani,al ALB,MF,Lecce,27-162,1996,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.12,0.12,4.0,2.0,0.0,18.2,0.5,0.0,0.0,0.05,-0.5,-0.5,120.0,148.0,81.1,2096.0,563.0,55.0,60.0,91.7,48.0,56.0,85.7,13.0,22.0,59.1,3.0,11.0,2.0,0.0,18.0,143.0,5.0,5.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,8.0,2.0,4.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,5.0,4.0,5.0,1.0,7.0,4.0,3.0,4.0,2.0,0.0,193.0,7.0,53.0,108.0,39.0,2.0,193.0,108.0,6.0,3.0,0.0,111.0,2.0,3.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,25.0,1.0,2.0,33.3 -Luca Ranieri,it ITA,DF,Fiorentina,24-151,1999,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,107.0,124.0,86.3,2281.0,879.0,33.0,38.0,86.8,53.0,58.0,91.4,19.0,26.0,73.1,1.0,5.0,0.0,0.0,2.0,122.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,0.0,135.0,9.0,75.0,59.0,2.0,0.0,135.0,93.0,0.0,2.0,0.0,103.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0 -Giacomo Raspadori,it ITA,"FW,MF",Napoli,23-215,2000,4.0,2.0,230.0,1.0,0.0,0.0,1.0,0.0,0.0,0.39,0.0,0.39,0.39,0.39,1.6,0.8,0.61,0.3,2.6,4.0,0.0,36.4,1.57,0.09,0.25,0.07,-0.6,0.2,80.0,102.0,78.4,1432.0,246.0,34.0,40.0,85.0,33.0,39.0,84.6,10.0,15.0,66.7,4.0,4.0,0.0,0.0,5.0,97.0,4.0,1.0,2.0,3.0,5.0,2.0,1.0,1.0,0.0,1.0,1.0,2.0,11.0,4.29,8.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,2.0,3.0,2.0,2.0,0.0,2.0,1.0,1.0,0.0,132.0,2.0,11.0,59.0,63.0,18.0,131.0,83.0,5.0,6.0,1.0,105.0,6.0,3.0,0.0,3.0,2.0,1.0,0.0,0.0,0.0,6.0,3.0,2.0,60.0 -Tijjani Reijnders,nl NED,MF,Milan,25-054,1998,4.0,4.0,346.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.26,0.26,0.0,0.26,0.4,0.4,0.1,0.1,3.8,2.0,0.0,33.3,0.52,0.0,0.0,0.06,-0.4,-0.4,137.0,154.0,89.0,2094.0,613.0,74.0,78.0,94.9,47.0,54.0,87.0,9.0,14.0,64.3,4.0,13.0,4.0,1.0,18.0,137.0,17.0,9.0,2.0,1.0,8.0,7.0,5.0,0.0,0.0,0.0,0.0,1.0,13.0,3.38,10.0,3.0,0.0,0.0,3.0,0.78,3.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,6.0,1.0,5.0,1.0,4.0,0.0,183.0,9.0,21.0,101.0,65.0,8.0,183.0,126.0,6.0,6.0,1.0,137.0,7.0,7.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,16.0,0.0,3.0,0.0 -Mateo Retegui,it ITA,FW,Genoa,24-145,1999,4.0,4.0,323.0,2.0,0.0,0.0,0.0,2.0,0.0,0.56,0.0,0.56,0.56,0.56,0.9,0.9,0.26,0.26,3.6,6.0,0.0,85.7,1.67,0.29,0.33,0.13,1.1,1.1,38.0,56.0,67.9,451.0,43.0,28.0,35.0,80.0,5.0,9.0,55.6,2.0,2.0,100.0,1.0,0.0,0.0,0.0,1.0,51.0,4.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,4.0,1.12,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,90.0,1.0,10.0,41.0,40.0,7.0,90.0,42.0,2.0,2.0,0.0,63.0,9.0,5.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,5.0,11.0,13.0,45.8 -Samuele Ricci,it ITA,MF,Torino,22-031,2001,4.0,4.0,334.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.27,0.27,0.0,0.27,0.0,0.0,0.01,0.01,3.7,1.0,0.0,33.3,0.27,0.0,0.0,0.01,0.0,0.0,159.0,184.0,86.4,2644.0,762.0,73.0,80.0,91.3,70.0,75.0,93.3,12.0,19.0,63.2,4.0,17.0,3.0,0.0,21.0,168.0,16.0,12.0,0.0,1.0,8.0,4.0,3.0,0.0,0.0,0.0,0.0,5.0,9.0,2.43,7.0,1.0,1.0,0.0,1.0,0.27,0.0,0.0,1.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,2.0,0.0,2.0,3.0,2.0,0.0,201.0,4.0,32.0,127.0,43.0,1.0,201.0,132.0,5.0,2.0,0.0,134.0,3.0,3.0,0.0,7.0,2.0,1.0,0.0,0.0,0.0,24.0,2.0,1.0,66.7 -Ricardo Rodríguez,ch SUI,DF,Torino,31-027,1992,4.0,4.0,344.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.8,0.0,1.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,182.0,210.0,86.7,2897.0,1201.0,94.0,98.0,95.9,73.0,83.0,88.0,11.0,22.0,50.0,1.0,20.0,1.0,1.0,20.0,206.0,4.0,4.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,1.05,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,4.0,2.0,2.0,3.0,7.0,0.0,234.0,14.0,78.0,130.0,26.0,0.0,234.0,151.0,7.0,11.0,0.0,170.0,0.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,11.0,8.0,5.0,61.5 -Alessio Romagnoli,it ITA,DF,Lazio,28-252,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.0,1.0,0.0,100.0,0.25,0.0,0.0,0.03,0.0,0.0,255.0,274.0,93.1,4162.0,1667.0,122.0,129.0,94.6,105.0,112.0,93.8,19.0,24.0,79.2,1.0,18.0,1.0,0.0,24.0,247.0,27.0,8.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.25,5.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,4.0,4.0,0.0,4.0,18.0,0.0,307.0,53.0,130.0,171.0,6.0,3.0,307.0,161.0,5.0,0.0,0.0,202.0,1.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,16.0,8.0,8.0,50.0 -Simone Romagnoli,it ITA,DF,Frosinone,33-224,1990,4.0,4.0,360.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.25,0.25,0.0,0.25,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,161.0,178.0,90.4,2644.0,1015.0,80.0,84.0,95.2,71.0,74.0,95.9,8.0,15.0,53.3,2.0,2.0,0.0,0.0,5.0,158.0,20.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,4.0,2.0,0.0,5.0,4.0,1.0,2.0,16.0,0.0,212.0,40.0,122.0,87.0,3.0,2.0,212.0,76.0,0.0,0.0,0.0,124.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,16.0,5.0,6.0,45.5 -Marten de Roon,nl NED,MF,Atalanta,32-176,1991,4.0,4.0,360.0,0.0,2.0,0.0,0.0,2.0,0.0,0.0,0.5,0.5,0.0,0.5,0.1,0.1,0.01,0.01,4.0,1.0,0.0,50.0,0.25,0.0,0.0,0.03,-0.1,-0.1,202.0,239.0,84.5,3902.0,1113.0,74.0,84.0,88.1,102.0,111.0,91.9,23.0,34.0,67.6,5.0,20.0,4.0,0.0,29.0,227.0,11.0,8.0,0.0,8.0,2.0,0.0,0.0,0.0,0.0,3.0,1.0,4.0,6.0,1.5,6.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,12.0,6.0,6.0,6.0,0.0,4.0,0.0,4.0,8.0,6.0,0.0,278.0,10.0,66.0,160.0,53.0,0.0,278.0,169.0,4.0,6.0,0.0,179.0,3.0,0.0,0.0,6.0,3.0,1.0,0.0,0.0,0.0,25.0,4.0,3.0,57.1 -Nicolò Rovella,it ITA,MF,Lazio,21-291,2001,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.14,0.14,0.5,0.0,1.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,37.0,39.0,94.9,570.0,133.0,18.0,18.0,100.0,17.0,17.0,100.0,1.0,1.0,100.0,0.0,3.0,0.0,0.0,4.0,38.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,4.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,46.0,2.0,8.0,30.0,8.0,0.0,46.0,21.0,2.0,1.0,0.0,33.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Amir Rrahmani,xk KVX,DF,Napoli,29-209,1994,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,228.0,259.0,88.0,4278.0,1464.0,88.0,92.0,95.7,112.0,122.0,91.8,27.0,41.0,65.9,1.0,16.0,0.0,0.0,13.0,251.0,7.0,5.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,8.0,2.67,6.0,0.0,1.0,0.0,2.0,0.67,2.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,3.0,0.0,3.0,4.0,4.0,0.0,276.0,21.0,105.0,163.0,8.0,6.0,276.0,201.0,0.0,0.0,0.0,208.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,25.0,6.0,2.0,75.0 -Ruan,br BRA,DF,Sassuolo,24-106,1999,3.0,3.0,270.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,88.0,101.0,87.1,1645.0,582.0,34.0,37.0,91.9,43.0,47.0,91.5,9.0,13.0,69.2,1.0,6.0,1.0,0.0,5.0,80.0,21.0,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,3.0,0.0,2.0,1.0,1.0,7.0,13.0,0.0,127.0,27.0,83.0,45.0,3.0,1.0,127.0,44.0,0.0,1.0,0.0,50.0,0.0,1.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,15.0,4.0,3.0,57.1 -Matteo Ruggeri,it ITA,DF,Atalanta,21-072,2002,4.0,4.0,323.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.56,0.56,0.0,0.56,0.0,0.0,0.0,0.0,3.6,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,152.0,184.0,82.6,2311.0,775.0,75.0,88.0,85.2,66.0,74.0,89.2,9.0,16.0,56.3,5.0,5.0,4.0,3.0,18.0,156.0,28.0,0.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,28.0,0.0,1.0,12.0,3.34,11.0,1.0,0.0,0.0,5.0,1.39,4.0,1.0,0.0,0.0,0.0,3.0,1.0,1.0,1.0,1.0,8.0,0.0,8.0,2.0,5.0,0.0,213.0,5.0,50.0,71.0,93.0,3.0,213.0,132.0,5.0,4.0,1.0,141.0,4.0,1.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,15.0,1.0,9.0,10.0 -Mário Rui,pt POR,DF,Napoli,32-117,1991,3.0,1.0,97.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,60.0,81.0,74.1,1036.0,333.0,28.0,31.0,90.3,24.0,31.0,77.4,6.0,12.0,50.0,1.0,7.0,0.0,0.0,8.0,69.0,12.0,6.0,0.0,0.0,7.0,1.0,0.0,1.0,0.0,5.0,0.0,3.0,2.0,1.86,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,0.0,2.0,2.0,0.0,2.0,1.0,2.0,0.0,91.0,2.0,17.0,49.0,26.0,1.0,91.0,43.0,0.0,1.0,0.0,54.0,1.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 -Stefano Sabelli,it ITA,"DF,MF",Genoa,30-251,1993,3.0,3.0,243.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,43.0,77.0,55.8,803.0,361.0,22.0,30.0,73.3,15.0,28.0,53.6,6.0,18.0,33.3,0.0,4.0,1.0,0.0,4.0,65.0,12.0,1.0,0.0,2.0,5.0,0.0,0.0,0.0,0.0,11.0,0.0,1.0,2.0,0.74,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,1.0,0.0,1.0,4.0,7.0,0.0,104.0,12.0,44.0,46.0,15.0,1.0,104.0,47.0,3.0,1.0,1.0,57.0,6.0,1.0,0.0,6.0,5.0,1.0,0.0,0.0,0.0,14.0,0.0,0.0,0.0 -Lazar Samardzic,rs SRB,MF,Udinese,21-209,2002,4.0,3.0,303.0,1.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.3,0.3,0.3,0.3,0.3,0.1,0.1,3.4,4.0,2.0,57.1,1.19,0.14,0.25,0.05,0.7,0.7,115.0,151.0,76.2,2068.0,595.0,53.0,64.0,82.8,32.0,41.0,78.0,22.0,32.0,68.8,9.0,14.0,3.0,1.0,10.0,134.0,16.0,3.0,2.0,3.0,10.0,11.0,3.0,4.0,0.0,2.0,1.0,3.0,20.0,5.94,10.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,177.0,1.0,27.0,88.0,65.0,3.0,177.0,109.0,9.0,5.0,1.0,120.0,7.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,20.0,1.0,3.0,25.0 -Junior Sambia,fr FRA,MF,Salernitana,27-014,1996,1.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,69.0,23.0,3.0,3.0,100.0,2.0,2.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,11.0,3.0,5.0,2.0,4.0,0.0,11.0,6.0,0.0,1.0,0.0,6.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,50.0 -Antonio Sanabria,py PAR,FW,Torino,27-201,1996,2.0,2.0,107.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.2,1.0,0.0,100.0,0.84,0.0,0.0,0.11,-0.1,-0.1,18.0,30.0,60.0,254.0,12.0,13.0,18.0,72.2,5.0,7.0,71.4,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,28.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.84,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,0.0,1.0,19.0,18.0,3.0,38.0,20.0,0.0,0.0,0.0,31.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,3.0,9.0,25.0 -Renato Sanches,pt POR,MF,Roma,26-034,1997,2.0,1.0,71.0,1.0,0.0,0.0,0.0,1.0,0.0,1.27,0.0,1.27,1.27,1.27,0.1,0.1,0.1,0.1,0.8,1.0,0.0,50.0,1.27,0.5,1.0,0.04,0.9,0.9,30.0,32.0,93.8,446.0,105.0,17.0,17.0,100.0,12.0,13.0,92.3,1.0,2.0,50.0,3.0,2.0,2.0,1.0,4.0,32.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.34,5.0,0.0,0.0,0.0,1.0,1.27,1.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,44.0,0.0,10.0,16.0,19.0,3.0,44.0,27.0,3.0,3.0,1.0,32.0,2.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,2.0,0.0 -Alex Sandro,br BRA,DF,Juventus,32-238,1991,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,143.0,167.0,85.6,2364.0,821.0,67.0,72.0,93.1,64.0,67.0,95.5,12.0,24.0,50.0,2.0,16.0,5.0,2.0,18.0,145.0,21.0,6.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,13.0,1.0,1.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,5.0,5.0,0.0,182.0,13.0,45.0,109.0,28.0,2.0,182.0,109.0,7.0,4.0,0.0,126.0,2.0,3.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,13.0,2.0,1.0,66.7 -Riccardo Saponara,it ITA,"FW,MF",Hellas Verona,31-274,1991,2.0,0.0,25.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,0.06,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,10.0,11.0,90.9,139.0,18.0,6.0,7.0,85.7,4.0,4.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,15.0,0.0,3.0,8.0,6.0,0.0,15.0,12.0,3.0,3.0,0.0,10.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Giorgio Scalvini,it ITA,DF,Atalanta,19-284,2003,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.1,0.1,4.0,1.0,0.0,50.0,0.25,0.0,0.0,0.2,-0.4,-0.4,178.0,205.0,86.8,2877.0,933.0,79.0,85.0,92.9,88.0,98.0,89.8,6.0,13.0,46.2,0.0,4.0,0.0,0.0,7.0,197.0,8.0,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,2.0,0.5,1.0,0.0,1.0,0.0,1.0,0.25,0.0,0.0,1.0,0.0,0.0,14.0,8.0,10.0,4.0,0.0,12.0,5.0,7.0,11.0,14.0,0.0,261.0,23.0,140.0,106.0,20.0,5.0,261.0,136.0,5.0,3.0,1.0,138.0,3.0,1.0,0.0,4.0,0.0,1.0,0.0,0.0,0.0,32.0,14.0,8.0,63.6 -Gianluca Scamacca,it ITA,FW,Atalanta,24-263,1999,4.0,1.0,165.0,2.0,0.0,0.0,0.0,0.0,0.0,1.09,0.0,1.09,1.09,1.09,0.9,0.9,0.47,0.47,1.8,3.0,0.0,33.3,1.64,0.22,0.67,0.1,1.1,1.1,41.0,61.0,67.2,807.0,135.0,17.0,29.0,58.6,11.0,14.0,78.6,10.0,11.0,90.9,2.0,4.0,1.0,0.0,4.0,57.0,3.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,7.0,3.84,7.0,0.0,0.0,0.0,1.0,0.55,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,89.0,1.0,3.0,40.0,47.0,14.0,89.0,67.0,5.0,1.0,1.0,78.0,5.0,7.0,0.0,3.0,4.0,1.0,0.0,0.0,0.0,2.0,5.0,6.0,45.5 -Perr Schuurs,nl NED,DF,Torino,23-299,1999,4.0,4.0,360.0,1.0,0.0,0.0,0.0,1.0,0.0,0.25,0.0,0.25,0.25,0.25,0.6,0.6,0.16,0.16,4.0,1.0,0.0,25.0,0.25,0.25,1.0,0.16,0.4,0.4,141.0,163.0,86.5,2495.0,698.0,54.0,60.0,90.0,76.0,82.0,92.7,9.0,18.0,50.0,0.0,6.0,0.0,0.0,9.0,153.0,10.0,8.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,5.0,5.0,3.0,1.0,5.0,0.0,5.0,5.0,8.0,0.0,204.0,20.0,90.0,98.0,21.0,3.0,204.0,109.0,6.0,4.0,0.0,112.0,6.0,2.0,0.0,4.0,0.0,0.0,0.0,1.0,0.0,23.0,3.0,4.0,42.9 -Demba Seck,sn SEN,MF,Torino,22-223,2001,2.0,1.0,104.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,26.0,34.0,76.5,431.0,91.0,12.0,17.0,70.6,12.0,14.0,85.7,2.0,2.0,100.0,0.0,4.0,2.0,0.0,3.0,34.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.73,1.0,0.0,0.0,1.0,1.0,0.87,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,51.0,1.0,4.0,25.0,24.0,3.0,51.0,39.0,5.0,5.0,1.0,37.0,3.0,3.0,0.0,4.0,5.0,0.0,0.0,0.0,0.0,7.0,2.0,4.0,33.3 -Vivaldo Semedo,pt POR,FW,Udinese,18-236,2005,1.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,2.0,1.0,1.0,3.0,3.0,1.0,0.0,1.0,3.0,1.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Stefano Sensi,it ITA,MF,Inter,28-047,1995,1.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,12.0,83.3,190.0,34.0,4.0,4.0,100.0,5.0,7.0,71.4,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,1.0,3.0,8.0,1.0,0.0,12.0,10.0,1.0,1.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Suat Serdar,de GER,MF,Hellas Verona,26-163,1997,3.0,0.0,104.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,27.0,77.8,362.0,87.0,9.0,9.0,100.0,9.0,12.0,75.0,2.0,2.0,100.0,0.0,2.0,0.0,0.0,3.0,26.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,2.0,1.0,0.0,0.0,0.0,2.0,2.0,0.0,39.0,4.0,10.0,20.0,9.0,0.0,39.0,19.0,0.0,0.0,0.0,22.0,3.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,20.0 -Stephan El Shaarawy,it ITA,"FW,DF",Roma,30-329,1992,4.0,2.0,212.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.14,0.14,2.4,2.0,1.0,40.0,0.85,0.0,0.0,0.06,-0.3,-0.3,63.0,76.0,82.9,1030.0,161.0,40.0,48.0,83.3,15.0,18.0,83.3,7.0,7.0,100.0,3.0,1.0,2.0,1.0,5.0,75.0,1.0,0.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,7.0,2.96,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,92.0,1.0,5.0,45.0,43.0,6.0,92.0,71.0,6.0,1.0,4.0,79.0,2.0,1.0,0.0,2.0,4.0,1.0,0.0,0.0,0.0,5.0,1.0,2.0,33.3 -Eldor Shomurodov,uz UZB,FW,Cagliari,28-084,1995,4.0,0.0,111.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,26.0,33.0,78.8,332.0,60.0,18.0,23.0,78.3,7.0,9.0,77.8,1.0,1.0,100.0,1.0,4.0,1.0,0.0,3.0,31.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.43,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,43.0,0.0,2.0,26.0,17.0,4.0,43.0,34.0,4.0,2.0,2.0,35.0,5.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,6.0,0.0,3.0,0.0 -Steven Shpendi,al ALB,"FW,MF",Empoli,20-125,2003,3.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.5,1.0,0.0,100.0,2.0,0.0,0.0,0.02,0.0,0.0,7.0,11.0,63.6,85.0,26.0,6.0,7.0,85.7,1.0,1.0,100.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,9.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,4.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,17.0,0.0,1.0,11.0,5.0,0.0,17.0,12.0,0.0,0.0,0.0,9.0,0.0,2.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0 -Marco Silvestri,it ITA,GK,Udinese,32-203,1991,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,98.0,126.0,77.8,2459.0,1735.0,20.0,21.0,95.2,56.0,57.0,98.2,22.0,48.0,45.8,0.0,0.0,0.0,0.0,0.0,82.0,44.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,134.0,118.0,134.0,0.0,0.0,0.0,134.0,65.0,0.0,0.0,0.0,51.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,0.0,0.0,0.0 -Giovanni Simeone,ar ARG,"FW,MF",Napoli,28-078,1995,3.0,0.0,24.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.41,0.41,0.3,2.0,0.0,100.0,7.5,0.0,0.0,0.06,-0.1,-0.1,7.0,10.0,70.0,93.0,39.0,4.0,4.0,100.0,2.0,2.0,100.0,0.0,0.0,0.0,1.0,2.0,1.0,0.0,4.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,7.5,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,17.0,0.0,0.0,6.0,11.0,5.0,17.0,11.0,2.0,1.0,1.0,13.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,100.0 -Leo Skiri Østigård,no NOR,DF,Napoli,23-297,1999,3.0,1.0,92.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,102.0,117.0,87.2,1724.0,648.0,41.0,44.0,93.2,55.0,61.0,90.2,4.0,8.0,50.0,1.0,9.0,1.0,0.0,11.0,116.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,1.0,0.98,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,123.0,7.0,26.0,86.0,12.0,1.0,123.0,87.0,7.0,4.0,0.0,89.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,10.0,3.0,0.0,100.0 -Łukasz Skorupski,pl POL,GK,Bologna,32-139,1991,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,98.0,129.0,76.0,2569.0,2009.0,25.0,25.0,100.0,43.0,43.0,100.0,30.0,60.0,50.0,0.0,0.0,0.0,0.0,0.0,95.0,33.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,135.0,124.0,135.0,0.0,0.0,0.0,135.0,73.0,0.0,0.0,0.0,72.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 -Chris Smalling,eng ENG,DF,Roma,33-303,1989,3.0,3.0,244.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.7,1.0,0.0,100.0,0.37,0.0,0.0,0.05,0.0,0.0,138.0,156.0,88.5,2681.0,1000.0,43.0,51.0,84.3,85.0,89.0,95.5,9.0,13.0,69.2,1.0,6.0,0.0,0.0,10.0,152.0,4.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.37,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,4.0,3.0,0.0,174.0,11.0,70.0,93.0,11.0,6.0,174.0,107.0,1.0,2.0,0.0,120.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,17.0,13.0,3.0,81.3 -Ola Solbakken,no NOR,FW,Roma,25-014,1998,1.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,8.0,75.0,96.0,4.0,4.0,5.0,80.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.91,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,2.0,2.0,4.0,0.0,8.0,5.0,1.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.0 -Yann Sommer,ch SUI,GK,Inter,34-278,1988,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,122.0,142.0,85.9,3266.0,2223.0,22.0,22.0,100.0,60.0,61.0,98.4,38.0,56.0,67.9,0.0,1.0,0.0,0.0,0.0,106.0,35.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,145.0,123.0,145.0,0.0,0.0,0.0,145.0,95.0,0.0,0.0,0.0,83.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Brandon Soppy,fr FRA,DF,Torino,21-212,2002,1.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,14.0,78.6,154.0,43.0,6.0,6.0,100.0,3.0,4.0,75.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,0.0,13.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,2.0,5.0,8.0,4.0,0.0,17.0,12.0,1.0,1.0,0.0,10.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Alessandro Sorrentino,it ITA,GK,Monza,21-171,2002,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,27.0,92.6,491.0,347.0,10.0,10.0,100.0,11.0,12.0,91.7,4.0,5.0,80.0,0.0,0.0,0.0,0.0,0.0,25.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,28.0,22.0,27.0,1.0,0.0,0.0,28.0,23.0,0.0,0.0,0.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Riccardo Sottil,it ITA,FW,Fiorentina,24-110,1999,3.0,1.0,128.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.24,0.24,1.4,3.0,1.0,100.0,2.11,0.0,0.0,0.11,-0.3,-0.3,34.0,42.0,81.0,491.0,116.0,19.0,19.0,100.0,12.0,13.0,92.3,1.0,1.0,100.0,0.0,3.0,0.0,0.0,4.0,42.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,1.41,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,55.0,0.0,3.0,23.0,32.0,7.0,55.0,45.0,9.0,5.0,2.0,44.0,2.0,2.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,7.0,0.0,1.0,0.0 -Matìas Soulé,ar ARG,"MF,FW",Frosinone,20-159,2003,2.0,2.0,153.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.59,0.59,0.0,0.59,0.6,0.6,0.35,0.35,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.15,-0.6,-0.6,65.0,85.0,76.5,1047.0,320.0,38.0,44.0,86.4,17.0,24.0,70.8,8.0,9.0,88.9,4.0,6.0,2.0,0.0,11.0,76.0,6.0,2.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,3.0,3.0,1.0,9.0,5.29,6.0,1.0,0.0,0.0,1.0,0.59,0.0,1.0,0.0,0.0,0.0,6.0,5.0,4.0,2.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,109.0,3.0,19.0,44.0,50.0,6.0,109.0,71.0,8.0,10.0,1.0,79.0,5.0,2.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,12.0,1.0,1.0,50.0 -Leonardo Spinazzola,it ITA,"DF,FW",Roma,30-180,1993,4.0,2.0,213.0,1.0,0.0,0.0,0.0,0.0,0.0,0.42,0.0,0.42,0.42,0.42,0.1,0.1,0.03,0.03,2.4,1.0,0.0,50.0,0.42,0.5,1.0,0.03,0.9,0.9,115.0,145.0,79.3,2017.0,542.0,54.0,59.0,91.5,49.0,58.0,84.5,11.0,22.0,50.0,5.0,6.0,6.0,2.0,10.0,123.0,21.0,1.0,0.0,2.0,14.0,0.0,0.0,0.0,0.0,20.0,1.0,3.0,12.0,5.09,10.0,1.0,0.0,0.0,2.0,0.85,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,2.0,0.0,2.0,1.0,3.0,0.0,167.0,5.0,47.0,69.0,52.0,4.0,167.0,110.0,26.0,14.0,3.0,112.0,3.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,14.0,3.0,0.0,100.0 -Gabriel Strefezza,br BRA,FW,Lecce,26-156,1997,4.0,2.0,212.0,1.0,0.0,1.0,1.0,1.0,0.0,0.42,0.0,0.42,0.0,0.0,1.2,0.4,0.52,0.18,2.4,1.0,1.0,16.7,0.42,0.0,0.0,0.07,-0.2,-0.4,51.0,72.0,70.8,853.0,251.0,29.0,32.0,90.6,14.0,24.0,58.3,7.0,12.0,58.3,9.0,1.0,5.0,3.0,7.0,50.0,21.0,7.0,0.0,0.0,14.0,8.0,3.0,0.0,0.0,1.0,1.0,0.0,15.0,6.37,11.0,2.0,1.0,1.0,1.0,0.42,1.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,4.0,0.0,102.0,3.0,8.0,28.0,68.0,10.0,101.0,57.0,11.0,8.0,2.0,61.0,5.0,5.0,0.0,7.0,5.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,0.0 -Kevin Strootman,nl NED,MF,Genoa,33-220,1990,3.0,3.0,202.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.45,0.45,0.0,0.45,0.0,0.0,0.0,0.0,2.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,53.0,67.0,79.1,899.0,240.0,28.0,32.0,87.5,20.0,22.0,90.9,4.0,8.0,50.0,4.0,4.0,0.0,0.0,8.0,65.0,2.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,5.0,2.23,5.0,0.0,0.0,0.0,1.0,0.45,1.0,0.0,0.0,0.0,0.0,8.0,3.0,4.0,4.0,0.0,5.0,1.0,4.0,1.0,4.0,0.0,91.0,7.0,29.0,54.0,8.0,1.0,91.0,44.0,2.0,1.0,0.0,54.0,2.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,10.0,1.0,1.0,50.0 -Isaac Success,ng NGA,FW,Udinese,27-257,1996,3.0,0.0,65.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.42,0.42,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.31,-0.3,-0.3,9.0,11.0,81.8,158.0,18.0,4.0,4.0,100.0,3.0,3.0,100.0,1.0,2.0,50.0,1.0,0.0,1.0,0.0,2.0,10.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,2.77,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,19.0,1.0,1.0,6.0,13.0,3.0,19.0,15.0,1.0,1.0,0.0,19.0,3.0,4.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,1.0,2.0,3.0,40.0 -Ibrahim Sulemana,gh GHA,MF,Cagliari,20-122,2003,3.0,3.0,264.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,2.9,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,78.0,105.0,74.3,1479.0,258.0,31.0,37.0,83.8,36.0,41.0,87.8,10.0,17.0,58.8,1.0,5.0,1.0,1.0,5.0,104.0,1.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,1.0,0.34,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,1.0,0.0,6.0,1.0,5.0,1.0,5.0,0.0,135.0,10.0,47.0,69.0,23.0,2.0,135.0,70.0,4.0,2.0,0.0,66.0,2.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,30.0,0.0,4.0,0.0 -Tomáš Suslov,sk SVK,MF,Hellas Verona,21-106,2002,1.0,0.0,21.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.15,0.15,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,2.0,4.0,50.0,26.0,7.0,1.0,2.0,50.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,0.0,1.0,4.0,4.0,0.0,9.0,3.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Wojciech Szczęsny,pl POL,GK,Juventus,33-156,1990,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,50.0,66.0,75.8,1430.0,1012.0,10.0,10.0,100.0,23.0,23.0,100.0,17.0,33.0,51.5,0.0,0.0,0.0,0.0,0.0,55.0,11.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,73.0,63.0,73.0,0.0,0.0,0.0,73.0,43.0,0.0,0.0,0.0,39.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 -Przemysław Szymiński,pl POL,MF,Frosinone,29-089,1994,1.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,50.0,9.0,10.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Adrien Tameze,cm CMR,MF,Torino,29-229,1994,2.0,2.0,153.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,63.0,75.0,84.0,958.0,253.0,35.0,37.0,94.6,23.0,29.0,79.3,3.0,5.0,60.0,1.0,5.0,1.0,0.0,8.0,73.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.59,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,0.0,2.0,1.0,6.0,2.0,4.0,4.0,0.0,0.0,93.0,2.0,12.0,58.0,26.0,2.0,93.0,46.0,2.0,2.0,1.0,57.0,1.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,10.0,2.0,2.0,50.0 -Loum Tchaouna,fr FRA,"MF,FW",Salernitana,20-013,2003,2.0,0.0,56.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,29.0,58.6,240.0,69.0,9.0,15.0,60.0,7.0,8.0,87.5,1.0,1.0,100.0,1.0,1.0,0.0,0.0,4.0,27.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,1.0,1.61,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,35.0,2.0,6.0,12.0,18.0,5.0,35.0,25.0,2.0,3.0,2.0,25.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,3.0,25.0 -Filippo Terracciano,it ITA,DF,Hellas Verona,20-225,2003,4.0,2.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.1,1.0,0.0,100.0,0.48,0.0,0.0,0.02,0.0,0.0,51.0,74.0,68.9,921.0,499.0,22.0,27.0,81.5,23.0,33.0,69.7,5.0,12.0,41.7,2.0,8.0,2.0,2.0,5.0,56.0,18.0,1.0,0.0,1.0,4.0,1.0,0.0,0.0,0.0,16.0,0.0,1.0,6.0,2.9,3.0,0.0,1.0,1.0,1.0,0.48,0.0,0.0,1.0,0.0,0.0,7.0,5.0,6.0,1.0,0.0,6.0,0.0,6.0,2.0,2.0,0.0,100.0,5.0,31.0,45.0,25.0,0.0,100.0,50.0,3.0,3.0,0.0,50.0,1.0,5.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,8.0,6.0,2.0,75.0 -Pietro Terracciano,it ITA,GK,Fiorentina,33-197,1990,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,85.0,94.0,90.4,2562.0,1700.0,6.0,6.0,100.0,46.0,46.0,100.0,33.0,42.0,78.6,1.0,1.0,1.0,0.0,0.0,81.0,13.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,96.0,83.0,96.0,0.0,0.0,0.0,96.0,63.0,0.0,0.0,0.0,61.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Florian Thauvin,fr FRA,FW,Udinese,30-238,1993,4.0,4.0,313.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.28,0.28,3.5,4.0,1.0,36.4,1.15,0.0,0.0,0.09,-1.0,-1.0,72.0,93.0,77.4,1320.0,413.0,35.0,42.0,83.3,25.0,33.0,75.8,10.0,12.0,83.3,4.0,11.0,5.0,3.0,14.0,85.0,8.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,12.0,3.45,9.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,138.0,1.0,3.0,63.0,74.0,17.0,138.0,80.0,8.0,6.0,4.0,93.0,7.0,7.0,0.0,3.0,2.0,1.0,0.0,0.0,0.0,10.0,6.0,6.0,50.0 -Malick Thiaw,de GER,DF,Milan,22-044,2001,4.0,4.0,345.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,236.0,252.0,93.7,4415.0,1335.0,78.0,81.0,96.3,141.0,144.0,97.9,15.0,22.0,68.2,1.0,6.0,1.0,0.0,18.0,245.0,7.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,0.78,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,5.0,2.0,4.0,0.0,6.0,2.0,4.0,4.0,13.0,0.0,286.0,27.0,144.0,137.0,6.0,0.0,286.0,197.0,5.0,2.0,0.0,216.0,1.0,1.0,0.0,6.0,2.0,0.0,0.0,0.0,0.0,18.0,5.0,1.0,83.3 -Morten Thorsby,no NOR,MF,Genoa,27-139,1996,4.0,1.0,158.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,25.0,52.0,48.1,411.0,143.0,10.0,24.0,41.7,11.0,17.0,64.7,1.0,4.0,25.0,0.0,4.0,1.0,0.0,7.0,52.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.14,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,6.0,0.0,6.0,1.0,5.0,0.0,78.0,6.0,13.0,43.0,22.0,1.0,78.0,26.0,0.0,1.0,0.0,45.0,4.0,2.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,6.0,13.0,7.0,65.0 -Kristian Thorstvedt,no NOR,MF,Sassuolo,24-192,1999,4.0,1.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.12,0.12,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,65.0,83.0,78.3,1143.0,530.0,35.0,41.0,85.4,23.0,28.0,82.1,7.0,9.0,77.8,7.0,16.0,1.0,0.0,20.0,82.0,1.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,14.0,8.63,11.0,0.0,2.0,0.0,1.0,0.62,0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,2.0,1.0,1.0,2.0,3.0,0.0,100.0,6.0,15.0,58.0,28.0,5.0,100.0,54.0,3.0,2.0,1.0,78.0,3.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,8.0,6.0,4.0,60.0 -Marcus Thuram,fr FRA,FW,Inter,26-046,1997,4.0,4.0,274.0,2.0,2.0,0.0,0.0,0.0,0.0,0.66,0.66,1.31,0.66,1.31,1.8,1.8,0.59,0.59,3.0,4.0,0.0,36.4,1.31,0.18,0.5,0.16,0.2,0.2,40.0,53.0,75.5,508.0,128.0,20.0,27.0,74.1,12.0,16.0,75.0,1.0,3.0,33.3,3.0,2.0,1.0,0.0,7.0,53.0,0.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,3.94,5.0,0.0,2.0,5.0,5.0,1.64,4.0,0.0,0.0,1.0,0.0,2.0,1.0,2.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,88.0,1.0,4.0,34.0,51.0,25.0,88.0,56.0,9.0,5.0,7.0,72.0,8.0,4.0,0.0,2.0,7.0,0.0,1.0,0.0,0.0,7.0,5.0,6.0,45.5 -Jeremy Toljan,de GER,DF,Sassuolo,29-044,1994,4.0,4.0,360.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.0,0.5,0.1,0.1,0.03,0.03,4.0,1.0,0.0,50.0,0.25,0.0,0.0,0.06,-0.1,-0.1,135.0,172.0,78.5,2141.0,990.0,69.0,73.0,94.5,52.0,68.0,76.5,9.0,21.0,42.9,3.0,7.0,2.0,0.0,12.0,134.0,37.0,4.0,0.0,0.0,9.0,1.0,0.0,0.0,0.0,32.0,1.0,4.0,5.0,1.25,5.0,0.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,2.0,0.0,2.0,2.0,6.0,0.0,197.0,9.0,72.0,84.0,41.0,6.0,197.0,90.0,10.0,6.0,2.0,116.0,5.0,3.0,0.0,1.0,2.0,0.0,0.0,1.0,0.0,20.0,1.0,3.0,25.0 -Rafael Tolói,it ITA,DF,Atalanta,32-346,1990,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,36.0,48.0,75.0,676.0,261.0,17.0,18.0,94.4,14.0,17.0,82.4,5.0,9.0,55.6,0.0,3.0,1.0,0.0,3.0,40.0,8.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,4.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,55.0,6.0,23.0,27.0,5.0,0.0,55.0,31.0,0.0,0.0,0.0,33.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 -Fikayo Tomori,eng ENG,DF,Milan,25-276,1997,3.0,3.0,240.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,2.7,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,208.0,221.0,94.1,3569.0,989.0,81.0,87.0,93.1,116.0,118.0,98.3,11.0,15.0,73.3,0.0,2.0,0.0,0.0,4.0,208.0,13.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,1.0,1.0,5.0,4.0,0.0,237.0,27.0,153.0,81.0,3.0,1.0,237.0,159.0,1.0,2.0,0.0,181.0,1.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,0.0,18.0,4.0,4.0,50.0 -Ahmed Touba,dz ALG,FW,Lecce,25-193,1998,1.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.19,0.19,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,1.0,3.0,33.3,28.0,0.0,0.0,0.0,0.0,1.0,2.0,50.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,7.0,2.0,4.0,2.0,1.0,1.0,7.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Stefano Turati,it ITA,GK,Frosinone,22-016,2001,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,80.0,109.0,73.4,1560.0,1232.0,40.0,40.0,100.0,24.0,25.0,96.0,14.0,42.0,33.3,0.0,1.0,0.0,0.0,0.0,93.0,16.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,120.0,111.0,119.0,1.0,0.0,0.0,120.0,77.0,0.0,0.0,0.0,63.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 -Kacper Urbanski,pl POL,MF,Bologna,19-014,2004,2.0,0.0,28.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.12,0.12,0.3,1.0,0.0,100.0,3.21,0.0,0.0,0.04,0.0,0.0,13.0,15.0,86.7,213.0,33.0,7.0,8.0,87.5,2.0,3.0,66.7,2.0,2.0,100.0,0.0,1.0,0.0,0.0,1.0,15.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,1.0,3.0,11.0,6.0,2.0,18.0,14.0,1.0,1.0,0.0,14.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 -Johan Vásquez,mx MEX,DF,Genoa,24-334,1998,4.0,2.0,212.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,66.0,90.0,73.3,1277.0,537.0,26.0,29.0,89.7,32.0,35.0,91.4,8.0,21.0,38.1,0.0,5.0,0.0,0.0,4.0,74.0,16.0,3.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,13.0,0.0,3.0,1.0,0.42,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,6.0,0.0,6.0,3.0,14.0,0.0,123.0,14.0,49.0,58.0,17.0,1.0,123.0,58.0,3.0,3.0,0.0,64.0,3.0,2.0,0.0,2.0,5.0,0.0,0.0,0.0,0.0,12.0,3.0,1.0,75.0 -Matías Vecino,uy URU,MF,Lazio,32-028,1991,2.0,0.0,61.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.32,0.32,0.7,1.0,0.0,33.3,1.48,0.0,0.0,0.07,-0.2,-0.2,23.0,30.0,76.7,391.0,136.0,12.0,16.0,75.0,9.0,11.0,81.8,2.0,2.0,100.0,0.0,5.0,0.0,0.0,5.0,28.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,1.48,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,3.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,39.0,1.0,3.0,22.0,14.0,2.0,39.0,21.0,1.0,2.0,0.0,20.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,4.0,42.9 -Simone Verdi,it ITA,FW,Torino,31-071,1992,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,7.0,5.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,22.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -Samuele Vignato,it ITA,MF,Monza,19-209,2004,2.0,0.0,40.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.97,0.97,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.43,-0.4,-0.4,20.0,21.0,95.2,194.0,14.0,17.0,18.0,94.4,2.0,2.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,20.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,2.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,0.0,0.0,16.0,9.0,1.0,25.0,16.0,1.0,0.0,0.0,23.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 -Matías Viña,uy URU,DF,Sassuolo,25-316,1997,4.0,4.0,221.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.41,0.41,0.0,0.41,0.0,0.0,0.02,0.02,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,84.0,121.0,69.4,1417.0,743.0,42.0,48.0,87.5,36.0,49.0,73.5,6.0,18.0,33.3,2.0,6.0,3.0,0.0,11.0,98.0,23.0,6.0,1.0,0.0,8.0,0.0,0.0,0.0,0.0,17.0,0.0,6.0,5.0,2.04,4.0,1.0,0.0,0.0,2.0,0.81,2.0,0.0,0.0,0.0,0.0,7.0,6.0,7.0,0.0,0.0,4.0,0.0,4.0,5.0,9.0,0.0,157.0,11.0,75.0,48.0,34.0,5.0,157.0,69.0,7.0,3.0,1.0,88.0,4.0,4.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,10.0,2.0,5.0,28.6 -Mattia Viti,it ITA,DF,Sassuolo,21-240,2002,1.0,1.0,76.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,30.0,100.0,483.0,126.0,13.0,13.0,100.0,16.0,16.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,23.0,7.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,1.0,4.0,0.0,38.0,13.0,28.0,11.0,0.0,0.0,38.0,17.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 -Dušan Vlahović,rs SRB,FW,Juventus,23-236,2000,4.0,4.0,327.0,4.0,1.0,1.0,2.0,2.0,0.0,1.1,0.28,1.38,0.83,1.1,2.5,0.9,0.69,0.26,3.6,6.0,0.0,54.5,1.65,0.27,0.5,0.08,1.5,2.1,42.0,64.0,65.6,600.0,97.0,24.0,30.0,80.0,15.0,22.0,68.2,1.0,5.0,20.0,2.0,1.0,1.0,0.0,6.0,57.0,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,10.0,2.76,8.0,0.0,1.0,1.0,2.0,0.55,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,91.0,2.0,7.0,40.0,44.0,22.0,89.0,55.0,4.0,3.0,3.0,65.0,7.0,2.0,0.0,4.0,4.0,3.0,0.0,0.0,0.0,7.0,2.0,1.0,66.7 -Nikola Vlašić,hr CRO,MF,Torino,25-352,1997,3.0,3.0,220.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.09,0.09,2.4,0.0,1.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,59.0,85.0,69.4,849.0,228.0,31.0,40.0,77.5,22.0,28.0,78.6,2.0,4.0,50.0,0.0,9.0,0.0,0.0,11.0,84.0,0.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,2.0,0.82,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,98.0,0.0,5.0,45.0,50.0,8.0,98.0,73.0,3.0,2.0,1.0,81.0,4.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,13.0,5.0,2.0,71.4 -Mërgim Vojvoda,xk KVX,DF,Torino,28-232,1995,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.2,-0.2,129.0,170.0,75.9,2136.0,845.0,69.0,78.0,88.5,52.0,65.0,80.0,7.0,19.0,36.8,2.0,5.0,7.0,0.0,22.0,145.0,23.0,2.0,0.0,6.0,9.0,1.0,1.0,0.0,0.0,20.0,2.0,3.0,3.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,2.0,0.0,2.0,2.0,3.0,0.0,182.0,5.0,38.0,83.0,63.0,2.0,182.0,115.0,8.0,8.0,0.0,124.0,1.0,0.0,0.0,3.0,1.0,1.0,0.0,0.0,0.0,13.0,1.0,1.0,50.0 -Cristian Volpato,it ITA,FW,Sassuolo,19-310,2003,1.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,12.0,100.0,238.0,41.0,4.0,4.0,100.0,7.0,7.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,2.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,1.0,1.0,11.0,3.0,0.0,15.0,13.0,1.0,1.0,0.0,13.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 -Stefan de Vrij,nl NED,DF,Inter,31-228,1992,4.0,3.0,287.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.2,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,128.0,145.0,88.3,2160.0,607.0,56.0,59.0,94.9,65.0,71.0,91.5,4.0,10.0,40.0,0.0,1.0,0.0,0.0,5.0,143.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.31,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,6.0,3.0,3.0,5.0,8.0,0.0,172.0,16.0,91.0,76.0,6.0,4.0,172.0,97.0,0.0,2.0,0.0,103.0,1.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,20.0,9.0,3.0,75.0 -Walace,br BRA,MF,Udinese,28-170,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,4.0,1.0,0.0,16.7,0.25,0.0,0.0,0.02,-0.1,-0.1,171.0,203.0,84.2,3211.0,979.0,68.0,76.0,89.5,85.0,97.0,87.6,17.0,26.0,65.4,3.0,30.0,2.0,0.0,22.0,197.0,6.0,6.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,6.0,1.5,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,3.0,0.0,3.0,11.0,2.0,1.0,235.0,9.0,49.0,155.0,32.0,1.0,235.0,163.0,9.0,6.0,0.0,160.0,1.0,2.0,0.0,2.0,9.0,0.0,0.0,0.0,0.0,26.0,2.0,0.0,100.0 -Sebastian Walukiewicz,pl POL,DF,Empoli,23-169,2000,2.0,2.0,135.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,84.0,94.0,89.4,1661.0,559.0,24.0,26.0,92.3,46.0,51.0,90.2,12.0,15.0,80.0,0.0,5.0,0.0,0.0,3.0,89.0,5.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,5.0,3.0,2.0,1.0,5.0,0.0,105.0,24.0,57.0,48.0,1.0,0.0,105.0,63.0,2.0,1.0,0.0,73.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.0,0.0,6.0,2.0,1.0,66.7 -Timothy Weah,us USA,DF,Juventus,23-211,2000,4.0,2.0,152.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.7,0.39,0.39,1.7,1.0,0.0,25.0,0.59,0.0,0.0,0.17,-0.7,-0.7,57.0,72.0,79.2,919.0,205.0,28.0,33.0,84.8,23.0,28.0,82.1,5.0,5.0,100.0,3.0,5.0,3.0,2.0,7.0,67.0,5.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,5.0,2.96,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,1.0,1.0,1.0,1.0,0.0,1.0,4.0,0.0,91.0,4.0,18.0,36.0,37.0,6.0,91.0,51.0,3.0,1.0,1.0,55.0,2.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,7.0,2.0,1.0,66.7 -Mateusz Wieteska,pl POL,DF,Cagliari,26-222,1997,2.0,2.0,179.0,0.0,1.0,0.0,0.0,2.0,1.0,0.0,0.5,0.5,0.0,0.5,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,75.0,91.0,82.4,1358.0,667.0,34.0,36.0,94.4,33.0,41.0,80.5,7.0,12.0,58.3,3.0,2.0,0.0,0.0,4.0,85.0,6.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,4.0,2.01,3.0,0.0,0.0,0.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,5.0,5.0,3.0,1.0,1.0,2.0,0.0,2.0,2.0,8.0,0.0,111.0,15.0,64.0,43.0,5.0,1.0,111.0,59.0,5.0,0.0,0.0,65.0,1.0,0.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,13.0,4.0,2.0,66.7 -Kenan Yıldız,tr TUR,"MF,FW",Juventus,18-140,2005,2.0,0.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,80.0,53.0,26.0,3.0,4.0,75.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,2.0,6.0,0.0,0.0,8.0,5.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 -Mattia Zaccagni,it ITA,FW,Lazio,28-097,1995,4.0,4.0,340.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.07,0.07,3.8,1.0,0.0,16.7,0.26,0.0,0.0,0.04,-0.3,-0.3,147.0,185.0,79.5,1982.0,350.0,86.0,100.0,86.0,44.0,53.0,83.0,7.0,14.0,50.0,5.0,5.0,4.0,2.0,7.0,176.0,9.0,4.0,1.0,0.0,10.0,4.0,0.0,0.0,0.0,1.0,0.0,6.0,15.0,3.97,9.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,2.0,3.0,0.0,4.0,1.0,3.0,8.0,4.0,0.0,231.0,6.0,25.0,90.0,120.0,14.0,231.0,148.0,17.0,7.0,5.0,180.0,7.0,3.0,0.0,5.0,11.0,2.0,0.0,0.0,0.0,9.0,3.0,1.0,75.0 -Nicola Zalewski,pl POL,"DF,FW",Roma,21-241,2002,3.0,2.0,166.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.08,0.08,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.2,-0.2,70.0,99.0,70.7,1210.0,413.0,28.0,29.0,96.6,36.0,48.0,75.0,5.0,12.0,41.7,1.0,4.0,5.0,0.0,7.0,77.0,22.0,3.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,19.0,0.0,6.0,4.0,2.17,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,5.0,1.0,4.0,0.0,3.0,2.0,1.0,1.0,1.0,0.0,119.0,6.0,24.0,56.0,40.0,8.0,119.0,61.0,10.0,5.0,4.0,72.0,2.0,0.0,0.0,3.0,8.0,0.0,0.0,0.0,0.0,10.0,4.0,1.0,80.0 -Andre-Frank Zambo Anguissa,cm CMR,MF,Napoli,27-309,1995,4.0,3.0,282.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.07,0.07,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.2,-0.2,195.0,225.0,86.7,2759.0,762.0,121.0,132.0,91.7,53.0,57.0,93.0,12.0,17.0,70.6,3.0,10.0,1.0,0.0,13.0,221.0,3.0,3.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,9.0,2.87,9.0,0.0,0.0,0.0,1.0,0.32,1.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,3.0,0.0,3.0,0.0,3.0,1.0,1.0,0.0,250.0,3.0,27.0,158.0,65.0,6.0,250.0,164.0,8.0,8.0,2.0,208.0,5.0,5.0,0.0,3.0,6.0,0.0,0.0,0.0,0.0,23.0,6.0,0.0,100.0 -Duván Zapata,co COL,FW,Torino,32-173,1991,2.0,2.0,150.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.12,0.12,1.7,1.0,0.0,33.3,0.6,0.0,0.0,0.07,-0.2,-0.2,29.0,41.0,70.7,409.0,44.0,17.0,20.0,85.0,6.0,10.0,60.0,3.0,3.0,100.0,1.0,0.0,0.0,0.0,2.0,36.0,3.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,2.0,3.0,1.8,1.0,0.0,1.0,1.0,1.0,0.6,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,0.0,2.0,0.0,61.0,3.0,3.0,24.0,34.0,11.0,61.0,39.0,3.0,4.0,1.0,48.0,8.0,0.0,0.0,3.0,4.0,1.0,0.0,0.0,0.0,4.0,6.0,4.0,60.0 -Duván Zapata,co COL,FW,Atalanta,32-173,1991,2.0,2.0,112.0,1.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.8,0.8,0.8,0.4,0.4,0.33,0.33,1.2,2.0,0.0,40.0,1.61,0.2,0.5,0.08,0.6,0.6,36.0,50.0,72.0,393.0,32.0,26.0,29.0,89.7,7.0,12.0,58.3,0.0,1.0,0.0,2.0,0.0,1.0,0.0,3.0,47.0,3.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,4.0,3.21,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,1.0,3.0,27.0,35.0,10.0,65.0,47.0,3.0,1.0,2.0,50.0,5.0,0.0,0.0,1.0,4.0,1.0,0.0,0.0,0.0,6.0,5.0,5.0,50.0 -Gabriele Zappa,it ITA,"DF,MF",Cagliari,23-273,1999,4.0,4.0,318.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.5,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,103.0,146.0,70.5,1662.0,1026.0,55.0,64.0,85.9,35.0,47.0,74.5,10.0,25.0,40.0,2.0,12.0,4.0,2.0,15.0,107.0,37.0,5.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,32.0,2.0,3.0,4.0,1.13,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,4.0,0.0,4.0,3.0,11.0,0.0,174.0,9.0,59.0,76.0,40.0,2.0,174.0,91.0,6.0,4.0,0.0,89.0,4.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,17.0,2.0,0.0,100.0 -Davide Zappacosta,it ITA,DF,Atalanta,31-102,1992,4.0,4.0,248.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.21,0.21,2.8,1.0,0.0,11.1,0.36,0.0,0.0,0.07,-0.6,-0.6,114.0,133.0,85.7,1520.0,546.0,73.0,81.0,90.1,32.0,34.0,94.1,5.0,7.0,71.4,1.0,6.0,1.0,0.0,12.0,108.0,25.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,24.0,0.0,4.0,3.0,1.08,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,3.0,1.0,2.0,0.0,4.0,0.0,163.0,4.0,38.0,59.0,70.0,13.0,163.0,97.0,10.0,5.0,3.0,105.0,5.0,3.0,0.0,3.0,4.0,1.0,0.0,0.0,0.0,17.0,2.0,4.0,33.3 -Oier Zarraga,es ESP,MF,Udinese,24-260,1999,2.0,1.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.12,0.12,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,14.0,16.0,87.5,172.0,58.0,12.0,13.0,92.3,2.0,2.0,100.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,2.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.67,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,23.0,2.0,8.0,7.0,8.0,2.0,23.0,15.0,2.0,3.0,1.0,17.0,3.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,50.0 -Jordan Zemura,zw ZIM,DF,Udinese,23-311,1999,3.0,0.0,84.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,20.0,28.0,71.4,227.0,87.0,13.0,14.0,92.9,6.0,6.0,100.0,0.0,4.0,0.0,1.0,2.0,0.0,0.0,3.0,22.0,6.0,1.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,5.0,0.0,1.0,1.0,1.07,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,37.0,1.0,10.0,15.0,12.0,1.0,37.0,18.0,2.0,1.0,2.0,21.0,2.0,1.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,4.0,2.0,4.0,33.3 -Alessio Zerbin,it ITA,FW,Napoli,24-202,1999,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,3.0,1.0,3.0,3.0,0.0,1.0,0.0,3.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 -Piotr Zieliński,pl POL,MF,Napoli,29-124,1994,4.0,4.0,345.0,1.0,1.0,0.0,0.0,0.0,0.0,0.26,0.26,0.52,0.26,0.52,0.4,0.4,0.1,0.1,3.8,3.0,1.0,33.3,0.78,0.11,0.33,0.04,0.6,0.6,183.0,219.0,83.6,3000.0,1252.0,102.0,108.0,94.4,59.0,69.0,85.5,18.0,32.0,56.3,14.0,27.0,15.0,0.0,34.0,195.0,21.0,3.0,1.0,2.0,18.0,17.0,4.0,10.0,0.0,0.0,3.0,1.0,24.0,6.26,14.0,8.0,2.0,0.0,4.0,1.04,3.0,0.0,1.0,0.0,0.0,3.0,0.0,0.0,1.0,2.0,3.0,1.0,2.0,1.0,0.0,0.0,248.0,2.0,20.0,127.0,104.0,8.0,248.0,163.0,10.0,13.0,3.0,192.0,6.0,4.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,15.0,0.0,1.0,0.0 -David Zima,cz CZE,DF,Torino,22-317,2000,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,72.0,12.0,1.0,1.0,100.0,3.0,4.0,75.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.63,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,9.0,2.0,5.0,4.0,0.0,0.0,9.0,4.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,0.0 -Joshua Zirkzee,nl NED,FW,Bologna,22-122,2001,4.0,4.0,356.0,1.0,1.0,0.0,0.0,1.0,0.0,0.25,0.25,0.51,0.25,0.51,0.4,0.4,0.1,0.1,4.0,3.0,0.0,42.9,0.76,0.14,0.33,0.06,0.6,0.6,72.0,99.0,72.7,869.0,175.0,48.0,66.0,72.7,12.0,17.0,70.6,3.0,3.0,100.0,10.0,3.0,4.0,0.0,8.0,90.0,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,17.0,4.3,13.0,0.0,2.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0,6.0,0.0,151.0,6.0,12.0,74.0,67.0,15.0,151.0,82.0,3.0,6.0,1.0,111.0,16.0,6.0,0.0,3.0,1.0,1.0,0.0,0.0,0.0,11.0,9.0,2.0,81.8 -Zito,ao ANG,FW,Cagliari,21-196,2002,4.0,3.0,297.0,1.0,0.0,0.0,0.0,1.0,0.0,0.3,0.0,0.3,0.3,0.3,0.5,0.5,0.17,0.17,3.3,1.0,0.0,11.1,0.3,0.11,1.0,0.06,0.5,0.5,23.0,34.0,67.6,363.0,59.0,10.0,12.0,83.3,9.0,15.0,60.0,1.0,3.0,33.3,4.0,1.0,1.0,1.0,3.0,32.0,2.0,0.0,0.0,1.0,7.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,13.0,3.94,4.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,86.0,0.0,4.0,22.0,60.0,17.0,86.0,73.0,14.0,6.0,8.0,71.0,16.0,10.0,0.0,3.0,8.0,5.0,0.0,0.0,0.0,6.0,1.0,5.0,16.7 -Nadir Zortea,it ITA,DF,Atalanta,24-094,1999,3.0,0.0,96.0,1.0,0.0,0.0,0.0,1.0,0.0,0.94,0.0,0.94,0.94,0.94,0.1,0.1,0.08,0.08,1.1,1.0,0.0,50.0,0.94,0.5,1.0,0.04,0.9,0.9,41.0,51.0,80.4,702.0,314.0,22.0,24.0,91.7,13.0,15.0,86.7,6.0,8.0,75.0,2.0,2.0,2.0,2.0,5.0,43.0,8.0,0.0,0.0,0.0,7.0,1.0,0.0,1.0,0.0,7.0,0.0,3.0,7.0,6.56,4.0,1.0,1.0,0.0,1.0,0.94,1.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,1.0,0.0,1.0,1.0,2.0,0.0,64.0,1.0,13.0,30.0,23.0,3.0,64.0,43.0,6.0,4.0,1.0,44.0,0.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0 -Milan Đurić,ba BIH,"FW,MF",Hellas Verona,33-122,1990,4.0,1.0,152.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.1,-0.1,24.0,48.0,50.0,328.0,43.0,16.0,31.0,51.6,4.0,9.0,44.4,2.0,3.0,66.7,2.0,1.0,1.0,0.0,1.0,48.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.78,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,60.0,4.0,10.0,24.0,26.0,4.0,60.0,26.0,0.0,2.0,0.0,47.0,4.0,1.0,0.0,7.0,1.0,2.0,0.0,0.0,0.0,4.0,21.0,14.0,60.0 -Mateusz Łęgowski,pl POL,MF,Salernitana,20-235,2003,4.0,2.0,161.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,71.0,87.0,81.6,948.0,301.0,46.0,50.0,92.0,18.0,22.0,81.8,4.0,8.0,50.0,1.0,2.0,0.0,0.0,4.0,86.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,2.24,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,99.0,2.0,18.0,60.0,22.0,1.0,99.0,66.0,3.0,4.0,1.0,72.0,4.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,14.0,4.0,5.0,44.4 +Francesco Acerbi,it ITA,DF,Inter,35-232,1988,3.0,3.0,270.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.11,0.11,3.0,1.0,0.0,50.0,0.33,0.0,0.0,0.16,-0.3,-0.3,156.0,177.0,88.1,2860.0,886.0,59.0,66.0,89.4,76.0,80.0,95.0,14.0,23.0,60.9,0.0,10.0,1.0,0.0,8.0,165.0,12.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,2.0,0.67,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,2.0,2.0,0.0,6.0,9.0,0.0,198.0,28.0,117.0,75.0,7.0,6.0,198.0,116.0,1.0,0.0,0.0,133.0,0.0,0.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,15.0,10.0,2.0,83.3 +Yacine Adli,fr FRA,MF,Milan,23-063,2000,1.0,1.0,57.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,72.0,78.0,92.3,1425.0,494.0,23.0,23.0,100.0,37.0,39.0,94.9,9.0,13.0,69.2,1.0,13.0,3.0,0.0,12.0,74.0,4.0,0.0,0.0,1.0,4.0,4.0,1.0,2.0,0.0,0.0,0.0,0.0,5.0,7.89,4.0,1.0,0.0,0.0,1.0,1.58,0.0,1.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,3.0,3.0,0.0,0.0,1.0,0.0,84.0,5.0,17.0,53.0,14.0,0.0,84.0,57.0,0.0,1.0,0.0,63.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0 +Michel Aebischer,ch SUI,MF,Bologna,26-267,1997,6.0,6.0,527.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,5.9,1.0,0.0,50.0,0.17,0.0,0.0,0.05,-0.1,-0.1,335.0,355.0,94.4,5438.0,1521.0,172.0,181.0,95.0,131.0,135.0,97.0,24.0,28.0,85.7,2.0,29.0,1.0,1.0,30.0,338.0,16.0,13.0,0.0,2.0,3.0,1.0,0.0,0.0,0.0,2.0,1.0,0.0,9.0,1.54,8.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,3.0,0.0,7.0,2.0,5.0,4.0,5.0,0.0,386.0,12.0,99.0,242.0,48.0,4.0,386.0,239.0,7.0,4.0,1.0,305.0,4.0,0.0,0.0,10.0,6.0,0.0,0.0,0.0,0.0,29.0,4.0,6.0,40.0 +Jean-Daniel Akpa-Akpro,ci CIV,MF,Monza,30-354,1992,1.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,80.0,54.0,4.0,3.0,3.0,100.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,6.0,1.0,2.0,4.0,0.0,0.0,6.0,1.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Luis Alberto,es ESP,MF,Lazio,31-002,1992,6.0,6.0,540.0,2.0,1.0,0.0,0.0,2.0,0.0,0.33,0.17,0.5,0.33,0.5,0.6,0.6,0.1,0.1,6.0,4.0,1.0,50.0,0.67,0.25,0.5,0.07,1.4,1.4,365.0,458.0,79.7,5881.0,1944.0,195.0,214.0,91.1,128.0,151.0,84.8,32.0,69.0,46.4,13.0,63.0,13.0,0.0,76.0,405.0,49.0,19.0,2.0,4.0,33.0,26.0,9.0,15.0,0.0,2.0,4.0,5.0,25.0,4.17,20.0,5.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,10.0,4.0,7.0,2.0,1.0,8.0,2.0,6.0,1.0,2.0,0.0,508.0,6.0,54.0,266.0,195.0,12.0,508.0,330.0,32.0,21.0,1.0,393.0,7.0,8.0,0.0,6.0,8.0,0.0,0.0,0.0,0.0,36.0,3.0,5.0,37.5 +Pontus Almqvist,se SWE,FW,Lecce,24-082,1999,6.0,6.0,527.0,1.0,0.0,0.0,0.0,1.0,0.0,0.17,0.0,0.17,0.17,0.17,0.4,0.4,0.06,0.06,5.9,4.0,0.0,44.4,0.68,0.11,0.25,0.04,0.6,0.6,112.0,140.0,80.0,1514.0,268.0,69.0,82.0,84.1,28.0,38.0,73.7,7.0,7.0,100.0,5.0,5.0,2.0,0.0,7.0,138.0,2.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,18.0,3.07,10.0,1.0,2.0,3.0,5.0,0.85,3.0,0.0,0.0,1.0,1.0,8.0,7.0,2.0,4.0,2.0,7.0,0.0,7.0,4.0,4.0,0.0,226.0,2.0,28.0,95.0,106.0,22.0,226.0,155.0,26.0,11.0,9.0,165.0,17.0,12.0,0.0,6.0,12.0,1.0,1.0,0.0,0.0,19.0,1.0,4.0,20.0 +Lorenzo Amatucci,it ITA,MF,Fiorentina,19-237,2004,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,17.0,88.2,304.0,47.0,4.0,4.0,100.0,10.0,10.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,1.0,17.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,1.0,12.0,4.0,0.0,17.0,12.0,1.0,0.0,0.0,13.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Bruno Amione,ar ARG,MF,Hellas Verona,21-270,2002,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,100.0,35.0,9.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,5.0,0.0,3.0,2.0,0.0,0.0,5.0,2.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Felipe Anderson,br BRA,FW,Lazio,30-168,1993,6.0,5.0,395.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.68,0.68,0.0,0.68,0.6,0.6,0.13,0.13,4.4,0.0,0.0,0.0,0.0,0.0,0.0,0.12,-0.6,-0.6,174.0,226.0,77.0,2580.0,675.0,96.0,109.0,88.1,63.0,81.0,77.8,9.0,19.0,47.4,5.0,11.0,14.0,1.0,26.0,225.0,1.0,0.0,2.0,0.0,12.0,0.0,0.0,0.0,0.0,1.0,0.0,7.0,15.0,3.41,12.0,0.0,0.0,0.0,5.0,1.14,4.0,0.0,0.0,0.0,1.0,10.0,7.0,4.0,4.0,2.0,7.0,0.0,7.0,4.0,2.0,0.0,276.0,2.0,33.0,109.0,136.0,11.0,276.0,168.0,19.0,10.0,3.0,221.0,5.0,0.0,0.0,5.0,4.0,0.0,0.0,0.0,0.0,15.0,0.0,5.0,0.0 +Houssem Aouar,dz ALG,MF,Roma,25-092,1998,4.0,2.0,177.0,1.0,0.0,0.0,0.0,2.0,0.0,0.51,0.0,0.51,0.51,0.51,0.7,0.7,0.34,0.34,2.0,1.0,0.0,33.3,0.51,0.33,1.0,0.22,0.3,0.3,79.0,98.0,80.6,1274.0,329.0,40.0,44.0,90.9,30.0,35.0,85.7,7.0,10.0,70.0,5.0,7.0,0.0,0.0,8.0,89.0,9.0,2.0,0.0,0.0,5.0,5.0,4.0,1.0,0.0,2.0,0.0,3.0,9.0,4.58,5.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,1.0,3.0,0.0,2.0,0.0,2.0,3.0,0.0,0.0,115.0,0.0,11.0,66.0,39.0,6.0,115.0,69.0,4.0,2.0,1.0,76.0,3.0,2.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,15.0,4.0,3.0,57.1 +Marko Arnautović,at AUT,FW,Inter,34-164,1989,5.0,0.0,105.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.86,0.86,0.0,0.86,0.2,0.2,0.16,0.16,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.09,-0.2,-0.2,32.0,42.0,76.2,397.0,51.0,17.0,23.0,73.9,12.0,12.0,100.0,0.0,1.0,0.0,3.0,2.0,1.0,0.0,4.0,42.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,4.33,5.0,0.0,0.0,0.0,1.0,0.87,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,57.0,1.0,3.0,30.0,25.0,8.0,57.0,39.0,3.0,1.0,2.0,42.0,5.0,3.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0 +Kristjan Asllani,al ALB,MF,Inter,21-205,2002,2.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.23,0.23,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,9.0,13.0,69.2,157.0,8.0,5.0,5.0,100.0,3.0,4.0,75.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,0.0,10.0,3.0,2.0,0.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,16.0,0.0,6.0,7.0,3.0,1.0,16.0,10.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Tommaso Augello,it ITA,DF,Cagliari,29-031,1994,5.0,4.0,342.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.01,0.01,3.8,1.0,1.0,50.0,0.26,0.0,0.0,0.03,-0.1,-0.1,119.0,169.0,70.4,1980.0,878.0,60.0,63.0,95.2,48.0,66.0,72.7,9.0,32.0,28.1,4.0,9.0,3.0,2.0,10.0,129.0,40.0,6.0,0.0,0.0,18.0,8.0,2.0,5.0,0.0,26.0,0.0,3.0,9.0,2.37,5.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,1.0,0.0,1.0,2.0,7.0,0.0,191.0,10.0,71.0,68.0,53.0,2.0,191.0,85.0,13.0,2.0,0.0,105.0,4.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,15.0,4.0,1.0,80.0 +Yann Aurel Bisseck,de GER,DF,Inter,22-305,2000,1.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,100.0,42.0,6.0,1.0,1.0,100.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,2.0,1.0,1.0,3.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Sardar Azmoun,ir IRN,"MF,FW",Roma,28-272,1995,2.0,0.0,20.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,33.3,8.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0,5.0,3.0,6.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 +Paulo Azzi,br BRA,"DF,MF",Cagliari,29-077,1994,5.0,2.0,243.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.12,0.12,2.7,1.0,0.0,20.0,0.37,0.0,0.0,0.06,-0.3,-0.3,72.0,119.0,60.5,1152.0,402.0,40.0,51.0,78.4,28.0,42.0,66.7,4.0,20.0,20.0,2.0,7.0,2.0,0.0,9.0,97.0,20.0,3.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,17.0,2.0,2.0,2.0,0.74,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,3.0,2.0,0.0,2.0,1.0,1.0,3.0,4.0,0.0,152.0,8.0,50.0,57.0,49.0,3.0,152.0,81.0,8.0,13.0,1.0,85.0,1.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,16.0,3.0,3.0,50.0 +Oussama El Azzouzi,ma MAR,MF,Bologna,22-124,2001,5.0,1.0,131.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,98.0,108.0,90.7,1551.0,309.0,54.0,58.0,93.1,35.0,37.0,94.6,8.0,11.0,72.7,1.0,12.0,0.0,0.0,6.0,107.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.37,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,2.0,1.0,2.0,1.0,1.0,3.0,2.0,0.0,122.0,6.0,23.0,82.0,18.0,1.0,122.0,72.0,1.0,0.0,0.0,88.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,17.0,1.0,2.0,33.3 +Milan Badelj,hr CRO,MF,Genoa,34-217,1989,6.0,6.0,409.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.5,1.0,0.0,100.0,0.22,0.0,0.0,0.03,0.0,0.0,150.0,187.0,80.2,2646.0,868.0,54.0,58.0,93.1,78.0,92.0,84.8,12.0,28.0,42.9,0.0,20.0,0.0,0.0,16.0,174.0,13.0,9.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,0.88,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,3.0,5.0,3.0,0.0,4.0,0.0,4.0,11.0,10.0,0.0,227.0,18.0,75.0,137.0,17.0,0.0,227.0,107.0,2.0,3.0,0.0,141.0,2.0,3.0,0.0,5.0,4.0,0.0,0.0,0.0,0.0,33.0,1.0,3.0,25.0 +Jaime Báez,uy URU,"FW,MF",Frosinone,28-158,1995,6.0,4.0,299.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,3.3,1.0,1.0,16.7,0.3,0.0,0.0,0.03,-0.2,-0.2,79.0,116.0,68.1,1276.0,528.0,39.0,51.0,76.5,29.0,39.0,74.4,8.0,18.0,44.4,4.0,8.0,7.0,0.0,18.0,108.0,8.0,2.0,0.0,0.0,12.0,6.0,1.0,4.0,0.0,0.0,0.0,2.0,9.0,2.71,4.0,3.0,0.0,2.0,2.0,0.6,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,4.0,0.0,4.0,4.0,1.0,0.0,144.0,4.0,21.0,64.0,62.0,10.0,144.0,80.0,5.0,3.0,2.0,99.0,4.0,7.0,0.0,4.0,10.0,4.0,1.0,0.0,0.0,21.0,4.0,4.0,50.0 +Nedim Bajrami,al ALB,"MF,FW",Sassuolo,24-214,1999,6.0,5.0,358.0,1.0,0.0,0.0,0.0,0.0,0.0,0.25,0.0,0.25,0.25,0.25,0.6,0.6,0.15,0.15,4.0,4.0,0.0,33.3,1.01,0.08,0.25,0.05,0.4,0.4,95.0,128.0,74.2,1407.0,337.0,52.0,62.0,83.9,35.0,45.0,77.8,5.0,15.0,33.3,3.0,5.0,1.0,0.0,10.0,109.0,19.0,2.0,2.0,0.0,18.0,14.0,6.0,6.0,0.0,1.0,0.0,3.0,12.0,3.02,9.0,2.0,0.0,0.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,4.0,1.0,0.0,163.0,4.0,20.0,72.0,77.0,10.0,163.0,90.0,13.0,3.0,3.0,108.0,5.0,4.0,0.0,5.0,2.0,1.0,0.0,0.0,0.0,16.0,0.0,3.0,0.0 +Mitchel Bakker,nl NED,DF,Atalanta,23-102,2000,2.0,0.0,26.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,21.0,29.0,72.4,261.0,67.0,14.0,17.0,82.4,6.0,6.0,100.0,0.0,3.0,0.0,1.0,1.0,0.0,0.0,1.0,25.0,4.0,0.0,0.0,0.0,3.0,1.0,0.0,1.0,0.0,3.0,0.0,1.0,1.0,3.46,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,1.0,6.0,16.0,11.0,2.0,32.0,23.0,3.0,2.0,1.0,23.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 +Tommaso Baldanzi,it ITA,"MF,FW",Empoli,20-191,2003,6.0,5.0,434.0,1.0,0.0,0.0,0.0,1.0,0.0,0.21,0.0,0.21,0.21,0.21,1.7,1.7,0.36,0.36,4.8,2.0,0.0,28.6,0.41,0.14,0.5,0.25,-0.7,-0.7,112.0,138.0,81.2,1778.0,394.0,54.0,63.0,85.7,44.0,50.0,88.0,7.0,10.0,70.0,7.0,7.0,4.0,1.0,19.0,121.0,14.0,4.0,0.0,0.0,5.0,2.0,0.0,0.0,0.0,4.0,3.0,4.0,20.0,4.15,12.0,2.0,0.0,4.0,1.0,0.21,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,5.0,0.0,5.0,2.0,0.0,0.0,189.0,0.0,14.0,91.0,91.0,17.0,189.0,125.0,12.0,11.0,5.0,138.0,11.0,4.0,0.0,4.0,12.0,1.0,0.0,0.0,0.0,19.0,0.0,3.0,0.0 +Lameck Banda,zm ZAM,FW,Lecce,22-244,2001,4.0,4.0,308.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.58,0.58,0.0,0.58,0.3,0.3,0.08,0.08,3.4,5.0,0.0,62.5,1.46,0.0,0.0,0.04,-0.3,-0.3,61.0,79.0,77.2,930.0,167.0,35.0,41.0,85.4,19.0,25.0,76.0,3.0,8.0,37.5,9.0,2.0,4.0,3.0,6.0,76.0,3.0,1.0,1.0,0.0,9.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,12.0,3.51,8.0,0.0,2.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,7.0,7.0,3.0,3.0,1.0,4.0,0.0,4.0,1.0,3.0,0.0,133.0,1.0,16.0,49.0,71.0,16.0,133.0,98.0,16.0,4.0,10.0,93.0,12.0,7.0,0.0,9.0,10.0,1.0,0.0,0.0,0.0,19.0,0.0,1.0,0.0 +Mattia Bani,it ITA,DF,Genoa,29-294,1993,6.0,6.0,540.0,1.0,0.0,0.0,0.0,3.0,0.0,0.17,0.0,0.17,0.17,0.17,0.6,0.6,0.1,0.1,6.0,1.0,0.0,50.0,0.17,0.5,1.0,0.3,0.4,0.4,162.0,205.0,79.0,3450.0,1356.0,40.0,46.0,87.0,98.0,109.0,89.9,23.0,45.0,51.1,1.0,8.0,0.0,0.0,7.0,197.0,7.0,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,4.0,2.0,0.0,18.0,10.0,8.0,4.0,34.0,0.0,280.0,53.0,192.0,82.0,7.0,5.0,280.0,131.0,2.0,0.0,0.0,149.0,1.0,0.0,0.0,2.0,5.0,1.0,0.0,0.0,0.0,25.0,11.0,9.0,55.0 +Antonín Barák,cz CZE,MF,Fiorentina,28-301,1994,2.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.78,0.78,0.3,1.0,0.0,100.0,3.91,0.0,0.0,0.2,-0.2,-0.2,15.0,16.0,93.8,196.0,29.0,8.0,9.0,88.9,6.0,6.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,15.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,21.0,0.0,3.0,6.0,12.0,1.0,21.0,14.0,1.0,2.0,0.0,18.0,1.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 +Nicolò Barella,it ITA,MF,Inter,26-235,1997,6.0,5.0,391.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.06,0.06,4.3,1.0,0.0,14.3,0.23,0.0,0.0,0.04,-0.3,-0.3,243.0,283.0,85.9,4162.0,1567.0,125.0,136.0,91.9,86.0,97.0,88.7,23.0,40.0,57.5,6.0,41.0,15.0,2.0,52.0,275.0,8.0,3.0,2.0,9.0,8.0,1.0,0.0,0.0,0.0,4.0,0.0,3.0,16.0,3.68,16.0,0.0,0.0,0.0,1.0,0.23,1.0,0.0,0.0,0.0,0.0,10.0,5.0,4.0,6.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,319.0,3.0,43.0,183.0,95.0,5.0,319.0,209.0,11.0,8.0,0.0,258.0,5.0,2.0,0.0,3.0,3.0,1.0,0.0,0.0,0.0,17.0,2.0,1.0,66.7 +Enzo Barrenechea,ar ARG,MF,Frosinone,22-131,2001,6.0,5.0,403.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,4.5,1.0,0.0,50.0,0.22,0.0,0.0,0.04,-0.1,-0.1,210.0,241.0,87.1,3430.0,763.0,98.0,105.0,93.3,81.0,88.0,92.0,19.0,30.0,63.3,1.0,10.0,2.0,0.0,15.0,228.0,12.0,10.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,4.0,0.89,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,9.0,3.0,6.0,1.0,7.0,2.0,5.0,6.0,11.0,0.0,293.0,19.0,98.0,168.0,28.0,3.0,293.0,136.0,1.0,3.0,0.0,187.0,2.0,3.0,0.0,8.0,2.0,0.0,0.0,0.0,0.0,25.0,4.0,5.0,44.4 +Davide Bartesaghi,it ITA,DF,Milan,17-275,2005,2.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,7.0,85.7,131.0,80.0,1.0,1.0,100.0,4.0,4.0,100.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,11.0,1.0,8.0,2.0,1.0,0.0,11.0,5.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Federico Baschirotto,it ITA,DF,Lecce,27-010,1996,5.0,5.0,414.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.06,0.06,4.6,0.0,0.0,0.0,0.0,0.0,0.0,0.14,-0.3,-0.3,203.0,228.0,89.0,3861.0,1191.0,60.0,64.0,93.8,116.0,124.0,93.5,24.0,33.0,72.7,0.0,10.0,0.0,0.0,15.0,216.0,11.0,6.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,3.0,0.65,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,6.0,4.0,2.0,3.0,14.0,0.0,255.0,32.0,121.0,127.0,7.0,3.0,255.0,175.0,9.0,2.0,0.0,180.0,2.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,19.0,9.0,3.0,75.0 +Alessandro Bastoni,it ITA,DF,Inter,24-170,1999,6.0,6.0,481.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,5.3,1.0,0.0,25.0,0.19,0.0,0.0,0.04,-0.1,-0.1,303.0,350.0,86.6,5953.0,2189.0,121.0,129.0,93.8,124.0,132.0,93.9,50.0,73.0,68.5,7.0,20.0,7.0,3.0,24.0,318.0,31.0,19.0,0.0,8.0,12.0,0.0,0.0,0.0,0.0,11.0,1.0,6.0,17.0,3.18,13.0,1.0,1.0,1.0,1.0,0.19,1.0,0.0,0.0,0.0,0.0,13.0,11.0,11.0,0.0,2.0,4.0,3.0,1.0,7.0,4.0,0.0,390.0,32.0,139.0,172.0,82.0,6.0,390.0,271.0,11.0,10.0,0.0,287.0,1.0,2.0,0.0,7.0,9.0,0.0,0.0,0.0,0.0,23.0,6.0,3.0,66.7 +Simone Bastoni,it ITA,MF,Empoli,26-329,1996,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,28.0,78.6,335.0,100.0,9.0,10.0,90.0,10.0,11.0,90.9,1.0,4.0,25.0,0.0,2.0,0.0,0.0,2.0,25.0,3.0,1.0,0.0,0.0,3.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,34.0,0.0,3.0,12.0,19.0,1.0,34.0,21.0,0.0,1.0,0.0,25.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Raoul Bellanova,it ITA,DF,Torino,23-136,2000,6.0,6.0,459.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.2,0.2,0.0,0.2,0.1,0.1,0.02,0.02,5.1,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.1,-0.1,159.0,215.0,74.0,2997.0,758.0,70.0,79.0,88.6,62.0,81.0,76.5,25.0,43.0,58.1,5.0,6.0,4.0,3.0,10.0,177.0,37.0,1.0,0.0,0.0,25.0,0.0,0.0,0.0,0.0,36.0,1.0,6.0,11.0,2.16,10.0,0.0,0.0,0.0,3.0,0.59,3.0,0.0,0.0,0.0,0.0,6.0,5.0,3.0,3.0,0.0,3.0,0.0,3.0,4.0,3.0,0.0,256.0,10.0,56.0,116.0,87.0,5.0,256.0,150.0,23.0,9.0,2.0,161.0,7.0,3.0,0.0,6.0,7.0,0.0,0.0,0.0,0.0,19.0,2.0,6.0,25.0 +Andrea Belotti,it ITA,"FW,DF",Roma,29-284,1993,6.0,3.0,346.0,2.0,2.0,0.0,0.0,0.0,0.0,0.52,0.52,1.04,0.52,1.04,1.4,1.4,0.38,0.38,3.8,4.0,0.0,44.4,1.04,0.22,0.5,0.16,0.6,0.6,59.0,78.0,75.6,803.0,87.0,38.0,44.0,86.4,13.0,18.0,72.2,5.0,6.0,83.3,5.0,1.0,1.0,0.0,5.0,70.0,8.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,11.0,2.86,5.0,0.0,2.0,2.0,4.0,1.04,2.0,0.0,1.0,0.0,0.0,6.0,3.0,1.0,3.0,2.0,2.0,0.0,2.0,0.0,2.0,0.0,122.0,2.0,6.0,65.0,53.0,23.0,122.0,76.0,8.0,6.0,3.0,97.0,16.0,6.0,0.0,5.0,9.0,3.0,0.0,0.0,0.0,5.0,8.0,11.0,42.1 +Lucas Beltrán,ar ARG,FW,Fiorentina,22-185,2001,6.0,2.0,171.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,43.0,74.4,390.0,60.0,23.0,27.0,85.2,5.0,6.0,83.3,2.0,2.0,100.0,1.0,1.0,1.0,0.0,2.0,41.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,7.0,3.71,4.0,0.0,0.0,1.0,4.0,2.12,3.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,5.0,0.0,5.0,0.0,1.0,0.0,70.0,1.0,3.0,32.0,35.0,4.0,70.0,47.0,1.0,1.0,0.0,54.0,7.0,6.0,0.0,2.0,5.0,1.0,0.0,0.0,0.0,1.0,1.0,9.0,10.0 +Domenico Berardi,it ITA,"FW,MF",Sassuolo,29-060,1994,4.0,4.0,347.0,4.0,1.0,1.0,1.0,1.0,0.0,1.04,0.26,1.3,0.78,1.04,1.2,0.4,0.31,0.11,3.9,7.0,0.0,63.6,1.82,0.27,0.43,0.04,2.8,2.6,106.0,154.0,68.8,1995.0,570.0,48.0,57.0,84.2,39.0,51.0,76.5,16.0,37.0,43.2,10.0,11.0,9.0,2.0,26.0,139.0,14.0,4.0,5.0,6.0,17.0,10.0,6.0,0.0,0.0,0.0,1.0,1.0,23.0,5.97,21.0,0.0,1.0,1.0,2.0,0.52,1.0,0.0,0.0,1.0,0.0,6.0,3.0,3.0,2.0,1.0,5.0,0.0,5.0,4.0,1.0,0.0,206.0,0.0,15.0,87.0,105.0,14.0,205.0,118.0,12.0,9.0,5.0,153.0,11.0,7.0,0.0,7.0,7.0,2.0,1.0,0.0,0.0,18.0,2.0,8.0,20.0 +Bartosz Bereszyński,pl POL,DF,Empoli,31-080,1992,3.0,3.0,196.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.2,1.0,0.0,100.0,0.46,0.0,0.0,0.02,0.0,0.0,113.0,133.0,85.0,1505.0,528.0,75.0,79.0,94.9,33.0,42.0,78.6,2.0,3.0,66.7,3.0,13.0,1.0,0.0,15.0,111.0,20.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,18.0,2.0,4.0,3.0,1.38,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,1.0,0.0,1.0,1.0,5.0,0.0,151.0,10.0,42.0,79.0,31.0,1.0,151.0,93.0,7.0,3.0,1.0,96.0,2.0,0.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,14.0,1.0,1.0,50.0 +Etrit Berisha,al ALB,GK,Empoli,34-204,1989,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,91.0,130.0,70.0,2275.0,1452.0,19.0,19.0,100.0,50.0,51.0,98.0,22.0,60.0,36.7,0.0,2.0,0.0,0.0,0.0,93.0,37.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,137.0,125.0,137.0,0.0,0.0,0.0,137.0,80.0,0.0,0.0,0.0,62.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Victor Bernth Kristiansen,dk DEN,DF,Bologna,20-288,2002,4.0,3.0,291.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.31,0.31,0.0,0.31,0.1,0.1,0.03,0.03,3.2,1.0,0.0,50.0,0.31,0.0,0.0,0.05,-0.1,-0.1,135.0,171.0,78.9,2032.0,626.0,78.0,84.0,92.9,48.0,64.0,75.0,7.0,14.0,50.0,4.0,13.0,6.0,2.0,10.0,135.0,35.0,3.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,32.0,1.0,2.0,6.0,1.86,4.0,0.0,2.0,0.0,2.0,0.62,1.0,0.0,1.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,6.0,0.0,6.0,2.0,5.0,0.0,198.0,5.0,60.0,88.0,50.0,5.0,198.0,110.0,2.0,1.0,0.0,122.0,3.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,6.0,4.0,0.0,100.0 +Beto,gw GNB,FW,Udinese,25-242,1998,1.0,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,11.0,90.9,128.0,26.0,7.0,8.0,87.5,3.0,3.0,100.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,2.0,9.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,7.3,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,0.0,7.0,10.0,1.0,17.0,15.0,0.0,0.0,0.0,14.0,3.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0 +Sam Beukema,nl NED,DF,Bologna,24-317,1998,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.05,0.05,6.0,1.0,0.0,50.0,0.17,0.0,0.0,0.16,-0.3,-0.3,404.0,433.0,93.3,7632.0,2737.0,154.0,160.0,96.3,208.0,219.0,95.0,37.0,46.0,80.4,1.0,21.0,0.0,0.0,18.0,420.0,12.0,9.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,3.0,0.5,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,5.0,7.0,3.0,0.0,5.0,1.0,4.0,3.0,21.0,0.0,477.0,54.0,224.0,253.0,2.0,1.0,477.0,324.0,4.0,2.0,1.0,353.0,0.0,1.0,0.0,7.0,3.0,0.0,0.0,0.0,0.0,38.0,9.0,4.0,69.2 +Jaka Bijol,si SVN,DF,Udinese,24-237,1999,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.03,0.03,6.0,1.0,0.0,50.0,0.17,0.0,0.0,0.09,-0.2,-0.2,238.0,289.0,82.4,4977.0,2259.0,71.0,82.0,86.6,124.0,141.0,87.9,40.0,59.0,67.8,1.0,21.0,2.0,0.0,25.0,280.0,9.0,8.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,9.0,13.0,3.0,0.0,7.0,4.0,3.0,7.0,29.0,1.0,358.0,59.0,190.0,164.0,5.0,4.0,358.0,200.0,2.0,0.0,0.0,204.0,1.0,0.0,0.0,7.0,4.0,0.0,0.0,0.0,0.0,24.0,21.0,9.0,70.0 +Cristiano Biraghi,it ITA,DF,Fiorentina,31-029,1992,5.0,4.0,332.0,1.0,1.0,0.0,0.0,1.0,0.0,0.27,0.27,0.54,0.27,0.54,0.0,0.0,0.01,0.01,3.7,1.0,0.0,100.0,0.27,1.0,1.0,0.03,1.0,1.0,245.0,320.0,76.6,4523.0,1408.0,102.0,108.0,94.4,108.0,134.0,80.6,30.0,58.0,51.7,1.0,13.0,1.0,1.0,14.0,239.0,80.0,13.0,0.0,6.0,23.0,13.0,3.0,6.0,0.0,54.0,1.0,12.0,5.0,1.36,1.0,2.0,0.0,0.0,5.0,1.36,1.0,2.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,6.0,3.0,3.0,3.0,8.0,0.0,348.0,10.0,94.0,157.0,99.0,5.0,348.0,195.0,13.0,8.0,1.0,210.0,1.0,0.0,0.0,9.0,4.0,0.0,0.0,0.0,0.0,16.0,1.0,3.0,25.0 +Davide Biraschi,it ITA,DF,Genoa,29-090,1994,1.0,1.0,90.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.1,0.1,0.1,0.1,1.0,1.0,0.0,100.0,1.0,1.0,1.0,0.1,0.9,0.9,31.0,37.0,83.8,684.0,308.0,6.0,7.0,85.7,18.0,21.0,85.7,7.0,9.0,77.8,0.0,2.0,1.0,0.0,5.0,28.0,9.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,5.0,0.0,48.0,5.0,20.0,21.0,7.0,1.0,48.0,19.0,0.0,2.0,0.0,21.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 +Samuele Birindelli,it ITA,"DF,MF",Monza,24-073,1999,6.0,3.0,308.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.29,0.29,0.0,0.29,0.2,0.2,0.05,0.05,3.4,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,141.0,162.0,87.0,2470.0,547.0,64.0,68.0,94.1,65.0,72.0,90.3,12.0,16.0,75.0,5.0,6.0,8.0,4.0,11.0,134.0,28.0,1.0,0.0,1.0,12.0,0.0,0.0,0.0,0.0,27.0,0.0,6.0,6.0,1.75,5.0,0.0,0.0,1.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,6.0,4.0,3.0,3.0,0.0,6.0,3.0,3.0,5.0,6.0,0.0,202.0,14.0,64.0,74.0,65.0,10.0,202.0,98.0,7.0,3.0,1.0,130.0,8.0,1.0,0.0,5.0,5.0,0.0,0.0,0.0,0.0,6.0,3.0,2.0,60.0 +Alexis Blin,fr FRA,"MF,DF",Lecce,27-014,1996,6.0,1.0,181.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.08,0.08,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.16,-0.2,-0.2,66.0,81.0,81.5,1163.0,370.0,28.0,32.0,87.5,32.0,37.0,86.5,5.0,7.0,71.4,0.0,7.0,1.0,0.0,6.0,74.0,7.0,6.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,3.0,5.0,0.0,104.0,7.0,27.0,66.0,11.0,2.0,104.0,53.0,0.0,0.0,0.0,58.0,2.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,10.0,5.0,3.0,62.5 +Emil Bohinen,no NOR,MF,Salernitana,24-202,1999,5.0,2.0,169.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.02,-0.1,-0.1,100.0,132.0,75.8,1588.0,436.0,47.0,55.0,85.5,34.0,46.0,73.9,10.0,14.0,71.4,2.0,3.0,0.0,0.0,10.0,128.0,4.0,4.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,1.07,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,4.0,2.0,2.0,4.0,2.0,1.0,161.0,3.0,38.0,92.0,31.0,2.0,161.0,79.0,2.0,2.0,0.0,96.0,5.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,16.0,7.0,6.0,53.8 +Daniel Boloca,ro ROU,MF,Sassuolo,24-282,1998,5.0,5.0,396.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.06,0.06,4.4,2.0,0.0,50.0,0.45,0.0,0.0,0.07,-0.3,-0.3,157.0,168.0,93.5,2568.0,728.0,68.0,72.0,94.4,75.0,77.0,97.4,8.0,10.0,80.0,6.0,14.0,1.0,1.0,14.0,166.0,2.0,2.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,14.0,3.19,13.0,0.0,0.0,0.0,2.0,0.46,2.0,0.0,0.0,0.0,0.0,6.0,4.0,1.0,5.0,0.0,4.0,2.0,2.0,3.0,7.0,0.0,201.0,18.0,64.0,98.0,40.0,4.0,201.0,103.0,3.0,5.0,0.0,129.0,3.0,3.0,0.0,7.0,2.0,0.0,0.0,1.0,0.0,28.0,2.0,1.0,66.7 +Giacomo Bonaventura,it ITA,MF,Fiorentina,34-039,1989,6.0,6.0,473.0,3.0,2.0,0.0,0.0,1.0,0.0,0.57,0.38,0.95,0.57,0.95,1.1,1.1,0.2,0.2,5.3,3.0,0.0,30.0,0.57,0.3,1.0,0.11,1.9,1.9,195.0,233.0,83.7,3089.0,623.0,85.0,102.0,83.3,85.0,92.0,92.4,13.0,20.0,65.0,7.0,15.0,6.0,0.0,26.0,226.0,7.0,2.0,5.0,1.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,11.0,2.09,10.0,1.0,0.0,0.0,3.0,0.57,3.0,0.0,0.0,0.0,0.0,5.0,4.0,1.0,0.0,4.0,5.0,0.0,5.0,4.0,3.0,0.0,290.0,4.0,29.0,159.0,105.0,10.0,290.0,204.0,10.0,12.0,3.0,221.0,13.0,6.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,22.0,2.0,4.0,33.3 +Federico Bonazzoli,it ITA,"FW,MF",Hellas Verona,26-132,1997,6.0,2.0,249.0,1.0,0.0,0.0,0.0,1.0,0.0,0.36,0.0,0.36,0.36,0.36,0.4,0.4,0.16,0.16,2.8,4.0,0.0,50.0,1.45,0.13,0.25,0.05,0.6,0.6,53.0,78.0,67.9,784.0,73.0,35.0,44.0,79.5,15.0,21.0,71.4,3.0,3.0,100.0,1.0,5.0,1.0,0.0,4.0,75.0,2.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,4.0,1.45,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,110.0,1.0,6.0,49.0,55.0,14.0,110.0,72.0,3.0,4.0,2.0,88.0,12.0,4.0,0.0,2.0,7.0,5.0,0.0,0.0,0.0,6.0,3.0,5.0,37.5 +Warren Bondo,fr FRA,MF,Monza,20-015,2003,1.0,0.0,25.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,168.0,43.0,7.0,8.0,87.5,4.0,4.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,0.0,2.0,10.0,4.0,0.0,16.0,10.0,2.0,1.0,0.0,14.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Gennaro Borrelli,it ITA,FW,Frosinone,23-204,2000,1.0,0.0,24.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 +Erik Botheim,no NOR,"FW,MF",Salernitana,23-263,2000,6.0,4.0,305.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.4,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.1,-0.1,48.0,65.0,73.8,653.0,76.0,32.0,41.0,78.0,12.0,14.0,85.7,1.0,2.0,50.0,0.0,2.0,1.0,0.0,5.0,61.0,4.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.3,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,3.0,0.0,3.0,0.0,2.0,0.0,86.0,2.0,11.0,49.0,27.0,7.0,86.0,47.0,3.0,1.0,2.0,57.0,3.0,0.0,0.0,2.0,11.0,0.0,0.0,0.0,0.0,7.0,2.0,17.0,10.5 +Mehdi Bourabia,ma MAR,MF,Frosinone,32-054,1991,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,100.0,54.0,34.0,1.0,1.0,100.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,1.0,2.0,2.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Edoardo Bove,it ITA,"MF,DF",Roma,21-137,2002,4.0,1.0,197.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.46,0.46,0.0,0.46,0.5,0.5,0.24,0.24,2.2,1.0,0.0,25.0,0.46,0.0,0.0,0.13,-0.5,-0.5,88.0,101.0,87.1,1303.0,263.0,46.0,51.0,90.2,32.0,33.0,97.0,5.0,6.0,83.3,2.0,10.0,0.0,0.0,8.0,101.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,1.83,3.0,0.0,0.0,1.0,1.0,0.46,1.0,0.0,0.0,0.0,0.0,8.0,6.0,1.0,5.0,2.0,4.0,0.0,4.0,2.0,1.0,1.0,127.0,3.0,19.0,73.0,35.0,7.0,127.0,75.0,1.0,2.0,0.0,88.0,4.0,1.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,11.0,4.0,4.0,50.0 +Domagoj Bradarić,hr CRO,DF,Salernitana,23-294,1999,6.0,5.0,448.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.2,0.2,0.0,0.2,0.1,0.1,0.02,0.02,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,209.0,271.0,77.1,3157.0,1022.0,117.0,135.0,86.7,71.0,86.0,82.6,10.0,26.0,38.5,5.0,4.0,2.0,1.0,14.0,218.0,53.0,4.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,49.0,0.0,8.0,8.0,1.61,7.0,1.0,0.0,0.0,1.0,0.2,1.0,0.0,0.0,0.0,0.0,8.0,5.0,2.0,3.0,3.0,2.0,1.0,1.0,5.0,5.0,0.0,308.0,7.0,85.0,146.0,80.0,3.0,308.0,156.0,10.0,10.0,1.0,182.0,6.0,1.0,0.0,2.0,6.0,0.0,0.0,0.0,0.0,22.0,7.0,4.0,63.6 +Josip Brekalo,hr CRO,FW,Fiorentina,25-099,1998,5.0,3.0,307.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.4,2.0,0.0,40.0,0.59,0.0,0.0,0.03,-0.1,-0.1,109.0,140.0,77.9,1707.0,458.0,57.0,61.0,93.4,36.0,49.0,73.5,10.0,15.0,66.7,4.0,7.0,6.0,2.0,12.0,135.0,4.0,1.0,0.0,0.0,13.0,3.0,0.0,2.0,0.0,0.0,1.0,5.0,10.0,2.94,8.0,1.0,0.0,0.0,1.0,0.29,1.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,5.0,0.0,5.0,0.0,0.0,0.0,166.0,1.0,21.0,59.0,89.0,9.0,166.0,113.0,4.0,5.0,3.0,126.0,1.0,2.0,0.0,7.0,5.0,0.0,0.0,0.0,0.0,12.0,0.0,3.0,0.0 +Gleison Bremer,br BRA,DF,Juventus,26-196,1997,6.0,6.0,540.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.2,-0.2,292.0,336.0,86.9,5330.0,1684.0,111.0,124.0,89.5,149.0,158.0,94.3,27.0,44.0,61.4,0.0,7.0,0.0,0.0,7.0,302.0,32.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,2.0,0.33,2.0,0.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,8.0,8.0,6.0,1.0,1.0,7.0,5.0,2.0,8.0,19.0,0.0,391.0,63.0,238.0,134.0,19.0,8.0,391.0,214.0,1.0,1.0,1.0,240.0,4.0,2.0,0.0,12.0,1.0,1.0,0.0,0.0,0.0,30.0,13.0,11.0,54.2 +Marco Brescianini,it ITA,MF,Frosinone,23-253,2000,5.0,2.0,167.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,36.0,48.0,75.0,558.0,251.0,21.0,24.0,87.5,11.0,15.0,73.3,3.0,4.0,75.0,1.0,2.0,3.0,0.0,6.0,46.0,2.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,5.0,2.69,3.0,0.0,1.0,0.0,1.0,0.54,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,68.0,2.0,16.0,34.0,19.0,3.0,68.0,38.0,2.0,3.0,1.0,46.0,6.0,2.0,0.0,6.0,0.0,1.0,0.0,0.0,0.0,4.0,3.0,2.0,60.0 +Alessandro Buongiorno,it ITA,DF,Torino,24-116,1999,6.0,6.0,476.0,1.0,0.0,0.0,0.0,1.0,0.0,0.19,0.0,0.19,0.19,0.19,0.3,0.3,0.05,0.05,5.3,1.0,0.0,100.0,0.19,1.0,1.0,0.26,0.7,0.7,180.0,218.0,82.6,3076.0,1018.0,76.0,84.0,90.5,92.0,104.0,88.5,9.0,22.0,40.9,1.0,3.0,0.0,0.0,11.0,216.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,0.76,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,4.0,6.0,3.0,0.0,4.0,1.0,3.0,11.0,23.0,0.0,281.0,27.0,136.0,142.0,3.0,1.0,281.0,144.0,0.0,1.0,1.0,138.0,8.0,1.0,0.0,14.0,3.0,0.0,0.0,1.0,0.0,32.0,16.0,15.0,51.6 +Rareș-Cătălin Burnete,ro ROU,FW,Lecce,19-242,2004,1.0,0.0,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,11.25,11.25,0.0,11.25,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,8.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,2.0,2.0,1.0,4.0,2.0,0.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Juan Cabal,co COL,DF,Hellas Verona,22-265,2001,3.0,0.0,28.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,18.0,25.0,72.0,416.0,160.0,7.0,8.0,87.5,7.0,8.0,87.5,4.0,8.0,50.0,1.0,5.0,2.0,2.0,4.0,23.0,2.0,0.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,3.1,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,28.0,0.0,2.0,19.0,9.0,1.0,28.0,20.0,2.0,0.0,0.0,21.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 +Jovane Cabral,cv CPV,"FW,MF",Salernitana,25-108,1998,5.0,4.0,383.0,1.0,0.0,0.0,0.0,0.0,0.0,0.23,0.0,0.23,0.23,0.23,0.8,0.8,0.19,0.19,4.3,8.0,0.0,42.1,1.88,0.05,0.13,0.04,0.2,0.2,106.0,139.0,76.3,1959.0,690.0,43.0,50.0,86.0,39.0,50.0,78.0,16.0,25.0,64.0,8.0,15.0,8.0,3.0,27.0,129.0,9.0,3.0,1.0,5.0,10.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,20.0,4.7,16.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,6.0,3.0,3.0,1.0,3.0,0.0,3.0,0.0,2.0,0.0,198.0,2.0,21.0,95.0,85.0,17.0,198.0,138.0,15.0,6.0,5.0,151.0,12.0,9.0,0.0,10.0,9.0,3.0,0.0,1.0,0.0,13.0,5.0,6.0,45.5 +Liberato Cacace,nz NZL,DF,Empoli,23-003,2000,3.0,2.0,209.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,117.0,157.0,74.5,1840.0,906.0,58.0,66.0,87.9,46.0,60.0,76.7,7.0,18.0,38.9,2.0,7.0,2.0,0.0,13.0,109.0,47.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,46.0,1.0,4.0,7.0,3.0,2.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,1.0,3.0,1.0,2.0,4.0,3.0,0.0,184.0,5.0,48.0,82.0,55.0,1.0,184.0,93.0,3.0,0.0,0.0,91.0,2.0,2.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,15.0,5.0,2.0,71.4 +Jens Cajuste,se SWE,MF,Napoli,24-051,1999,5.0,1.0,94.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.96,0.96,0.0,0.96,0.1,0.1,0.13,0.13,1.0,1.0,0.0,50.0,0.96,0.0,0.0,0.07,-0.1,-0.1,48.0,54.0,88.9,652.0,175.0,31.0,32.0,96.9,15.0,17.0,88.2,1.0,1.0,100.0,3.0,1.0,2.0,0.0,4.0,53.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,6.0,5.74,6.0,0.0,0.0,0.0,3.0,2.87,3.0,0.0,0.0,0.0,0.0,5.0,3.0,4.0,1.0,0.0,3.0,0.0,3.0,1.0,1.0,0.0,69.0,2.0,15.0,34.0,20.0,4.0,69.0,43.0,0.0,3.0,1.0,51.0,3.0,2.0,0.0,7.0,2.0,1.0,0.0,1.0,0.0,7.0,2.0,3.0,40.0 +Davide Calabria,it ITA,DF,Milan,26-298,1996,4.0,4.0,328.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.27,0.27,0.0,0.27,0.2,0.2,0.05,0.05,3.6,1.0,0.0,25.0,0.27,0.0,0.0,0.05,-0.2,-0.2,173.0,195.0,88.7,2872.0,740.0,78.0,82.0,95.1,81.0,89.0,91.0,10.0,18.0,55.6,3.0,10.0,3.0,2.0,12.0,174.0,21.0,5.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,16.0,0.0,1.0,4.0,1.1,3.0,0.0,0.0,1.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,7.0,2.0,5.0,1.0,1.0,4.0,1.0,3.0,6.0,8.0,0.0,229.0,10.0,69.0,129.0,31.0,2.0,229.0,126.0,2.0,5.0,0.0,154.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,12.0,1.0,4.0,20.0 +Riccardo Calafiori,it ITA,DF,Bologna,21-134,2002,3.0,1.0,126.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,71.0,74.0,95.9,1373.0,424.0,22.0,22.0,100.0,40.0,40.0,100.0,9.0,11.0,81.8,1.0,3.0,2.0,1.0,5.0,67.0,7.0,4.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,2.14,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,5.0,0.0,88.0,15.0,47.0,39.0,6.0,1.0,88.0,55.0,3.0,2.0,0.0,52.0,1.0,1.0,0.0,3.0,0.0,1.0,0.0,1.0,0.0,13.0,4.0,1.0,80.0 +Luca Caldirola,it ITA,DF,Monza,32-241,1991,5.0,5.0,444.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,4.9,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,230.0,255.0,90.2,4231.0,1354.0,91.0,92.0,98.9,115.0,126.0,91.3,23.0,33.0,69.7,0.0,15.0,0.0,0.0,9.0,241.0,14.0,5.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,5.0,1.01,5.0,0.0,0.0,0.0,1.0,0.2,1.0,0.0,0.0,0.0,0.0,6.0,3.0,4.0,1.0,1.0,4.0,3.0,1.0,7.0,10.0,0.0,292.0,43.0,137.0,140.0,15.0,2.0,292.0,172.0,2.0,1.0,0.0,215.0,2.0,0.0,1.0,4.0,5.0,0.0,0.0,1.0,0.0,14.0,3.0,2.0,60.0 +Hakan Çalhanoğlu,tr TUR,MF,Inter,29-234,1994,6.0,6.0,511.0,2.0,0.0,2.0,2.0,1.0,0.0,0.35,0.0,0.35,0.0,0.0,2.0,0.5,0.36,0.08,5.7,1.0,2.0,11.1,0.18,0.0,0.0,0.05,0.0,-0.5,376.0,419.0,89.7,7027.0,2178.0,161.0,170.0,94.7,148.0,157.0,94.3,54.0,70.0,77.1,11.0,44.0,5.0,2.0,35.0,386.0,31.0,12.0,2.0,11.0,21.0,17.0,6.0,7.0,0.0,1.0,2.0,4.0,23.0,4.05,16.0,7.0,0.0,0.0,1.0,0.18,1.0,0.0,0.0,0.0,0.0,16.0,10.0,8.0,5.0,3.0,6.0,4.0,2.0,4.0,2.0,0.0,467.0,12.0,120.0,247.0,106.0,7.0,465.0,303.0,7.0,14.0,1.0,327.0,3.0,0.0,0.0,14.0,3.0,0.0,0.0,0.0,0.0,41.0,6.0,3.0,66.7 +Nicolò Cambiaghi,it ITA,"FW,MF",Empoli,22-276,2000,5.0,3.0,297.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.1,0.1,3.3,1.0,0.0,12.5,0.3,0.0,0.0,0.04,-0.3,-0.3,68.0,89.0,76.4,988.0,169.0,38.0,41.0,92.7,26.0,35.0,74.3,2.0,5.0,40.0,1.0,3.0,3.0,3.0,5.0,85.0,4.0,0.0,0.0,0.0,14.0,0.0,0.0,0.0,0.0,4.0,0.0,3.0,9.0,2.73,6.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,3.0,0.0,1.0,0.0,1.0,2.0,1.0,0.0,128.0,1.0,8.0,43.0,80.0,12.0,128.0,100.0,14.0,4.0,4.0,104.0,11.0,8.0,0.0,4.0,7.0,1.0,0.0,0.0,0.0,13.0,1.0,3.0,25.0 +Andrea Cambiaso,it ITA,DF,Juventus,23-222,2000,5.0,3.0,257.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.35,0.35,0.0,0.35,0.1,0.1,0.04,0.04,2.9,1.0,0.0,33.3,0.35,0.0,0.0,0.04,-0.1,-0.1,131.0,156.0,84.0,1917.0,421.0,74.0,81.0,91.4,47.0,54.0,87.0,4.0,5.0,80.0,3.0,0.0,3.0,1.0,7.0,135.0,20.0,2.0,0.0,1.0,10.0,6.0,0.0,2.0,0.0,12.0,1.0,6.0,9.0,3.15,7.0,1.0,0.0,1.0,1.0,0.35,1.0,0.0,0.0,0.0,0.0,8.0,6.0,5.0,3.0,0.0,1.0,0.0,1.0,1.0,3.0,0.0,191.0,6.0,45.0,78.0,70.0,5.0,191.0,114.0,9.0,5.0,4.0,138.0,4.0,1.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,11.0,1.0,0.0,100.0 +Matteo Cancellieri,it ITA,"FW,MF",Empoli,21-230,2002,6.0,4.0,305.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.3,0.3,0.0,0.3,0.5,0.5,0.15,0.15,3.4,1.0,0.0,14.3,0.3,0.0,0.0,0.07,-0.5,-0.5,59.0,97.0,60.8,856.0,183.0,34.0,44.0,77.3,19.0,30.0,63.3,4.0,14.0,28.6,1.0,3.0,1.0,0.0,7.0,94.0,1.0,1.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,9.0,2.66,7.0,0.0,0.0,1.0,1.0,0.3,1.0,0.0,0.0,0.0,0.0,6.0,4.0,1.0,2.0,3.0,6.0,0.0,6.0,1.0,1.0,0.0,141.0,3.0,18.0,57.0,68.0,12.0,141.0,102.0,12.0,6.0,6.0,105.0,3.0,12.0,0.0,4.0,11.0,3.0,0.0,0.0,0.0,14.0,1.0,9.0,10.0 +Antonio Candreva,it ITA,MF,Salernitana,36-214,1987,6.0,6.0,495.0,2.0,1.0,0.0,0.0,1.0,0.0,0.36,0.18,0.55,0.36,0.55,1.3,1.3,0.23,0.23,5.5,7.0,1.0,50.0,1.27,0.14,0.29,0.09,0.7,0.7,187.0,260.0,71.9,2771.0,892.0,94.0,105.0,89.5,60.0,86.0,69.8,14.0,38.0,36.8,12.0,16.0,15.0,3.0,30.0,224.0,36.0,12.0,2.0,4.0,32.0,11.0,2.0,4.0,0.0,8.0,0.0,9.0,23.0,4.18,16.0,2.0,4.0,1.0,3.0,0.55,2.0,0.0,1.0,0.0,0.0,3.0,2.0,0.0,2.0,1.0,1.0,0.0,1.0,1.0,2.0,0.0,296.0,6.0,23.0,126.0,149.0,16.0,296.0,190.0,14.0,9.0,4.0,235.0,5.0,4.0,0.0,0.0,9.0,3.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0 +Luigi Canotto,it ITA,FW,Frosinone,29-134,1994,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,66.7,21.0,9.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,2.0,0.0,0.0,4.0,5.0,0.0,0.0,0.0,3.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Gianluca Caprari,it ITA,"MF,FW",Monza,30-062,1993,4.0,4.0,255.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.1,0.1,2.8,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.3,-0.3,88.0,111.0,79.3,1602.0,463.0,44.0,47.0,93.6,28.0,35.0,80.0,15.0,21.0,71.4,10.0,9.0,7.0,0.0,15.0,102.0,9.0,1.0,0.0,0.0,6.0,5.0,1.0,3.0,0.0,2.0,0.0,6.0,15.0,5.27,10.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,138.0,1.0,18.0,58.0,64.0,9.0,138.0,98.0,11.0,9.0,5.0,107.0,9.0,9.0,0.0,2.0,3.0,2.0,0.0,0.0,0.0,11.0,0.0,4.0,0.0 +Elia Caprile,it ITA,GK,Empoli,22-036,2001,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,24.0,41.0,58.5,812.0,542.0,0.0,0.0,0.0,10.0,10.0,100.0,14.0,31.0,45.2,0.0,1.0,0.0,0.0,0.0,34.0,7.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,44.0,30.0,44.0,0.0,0.0,0.0,44.0,26.0,0.0,0.0,0.0,20.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Francesco Caputo,it ITA,FW,Empoli,36-055,1987,4.0,3.0,244.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.17,0.17,2.7,3.0,0.0,42.9,1.11,0.0,0.0,0.07,-0.5,-0.5,34.0,54.0,63.0,412.0,57.0,21.0,29.0,72.4,9.0,11.0,81.8,0.0,1.0,0.0,0.0,2.0,0.0,0.0,5.0,50.0,4.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,6.0,2.21,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,72.0,0.0,1.0,33.0,38.0,11.0,72.0,44.0,2.0,2.0,1.0,59.0,6.0,4.0,0.0,1.0,3.0,2.0,0.0,0.0,0.0,0.0,1.0,5.0,16.7 +Andrea Carboni,it ITA,DF,Monza,22-238,2001,4.0,2.0,226.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.1,0.1,2.5,1.0,0.0,50.0,0.4,0.0,0.0,0.13,-0.3,-0.3,152.0,178.0,85.4,2765.0,780.0,61.0,66.0,92.4,77.0,85.0,90.6,12.0,22.0,54.5,0.0,11.0,0.0,0.0,7.0,175.0,3.0,2.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,2.0,0.8,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,1.0,0.0,2.0,0.0,2.0,1.0,10.0,1.0,202.0,29.0,83.0,102.0,17.0,5.0,202.0,110.0,2.0,2.0,0.0,152.0,3.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,10.0,5.0,1.0,83.3 +Valentin Carboni,ar ARG,"DF,MF",Monza,18-209,2005,2.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,2.21,2.21,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.2,-0.2,9.0,10.0,90.0,169.0,48.0,3.0,3.0,100.0,5.0,5.0,100.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,3.0,8.0,2.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,11.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,2.0,6.0,9.0,2.0,17.0,8.0,1.0,1.0,1.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Carlos,br BRA,DF,Inter,24-266,1999,6.0,0.0,124.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.11,0.11,1.4,1.0,0.0,50.0,0.73,0.0,0.0,0.08,-0.2,-0.2,53.0,69.0,76.8,861.0,309.0,27.0,30.0,90.0,18.0,22.0,81.8,6.0,10.0,60.0,2.0,1.0,4.0,3.0,4.0,57.0,10.0,1.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,9.0,2.0,3.0,3.0,2.18,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,1.0,4.0,0.0,81.0,4.0,21.0,30.0,31.0,4.0,81.0,46.0,5.0,3.0,1.0,55.0,2.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,9.0,6.0,0.0,100.0 +Marco Carnesecchi,it ITA,GK,Atalanta,23-091,2000,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.0,71.0,59.2,1252.0,864.0,6.0,6.0,100.0,19.0,20.0,95.0,17.0,45.0,37.8,0.0,1.0,0.0,0.0,0.0,53.0,18.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,74.0,69.0,74.0,0.0,0.0,0.0,74.0,48.0,0.0,0.0,0.0,32.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 +Nicolò Casale,it ITA,DF,Lazio,25-228,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,268.0,286.0,93.7,4994.0,1862.0,98.0,110.0,89.1,139.0,140.0,99.3,26.0,29.0,89.7,1.0,35.0,0.0,0.0,24.0,279.0,7.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,5.0,0.0,0.0,3.0,3.0,0.0,3.0,20.0,0.0,320.0,39.0,134.0,178.0,12.0,1.0,320.0,206.0,9.0,6.0,0.0,226.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,26.0,5.0,4.0,55.6 +Giuseppe Caso,it ITA,"FW,MF",Frosinone,24-295,1998,5.0,2.0,208.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,2.3,1.0,0.0,33.3,0.43,0.0,0.0,0.05,-0.1,-0.1,37.0,47.0,78.7,476.0,182.0,20.0,22.0,90.9,9.0,14.0,64.3,3.0,4.0,75.0,1.0,3.0,3.0,0.0,8.0,44.0,3.0,0.0,1.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,1.73,1.0,1.0,0.0,1.0,1.0,0.43,0.0,1.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,72.0,1.0,8.0,18.0,49.0,6.0,72.0,48.0,7.0,4.0,4.0,53.0,5.0,2.0,0.0,1.0,3.0,1.0,0.0,0.0,0.0,8.0,0.0,1.0,0.0 +Valentín Castellanos,ar ARG,"FW,MF",Lazio,24-362,1998,5.0,0.0,55.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.9,1.44,1.44,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.22,-0.9,-0.9,10.0,17.0,58.8,130.0,28.0,5.0,8.0,62.5,4.0,5.0,80.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,16.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,31.0,0.0,1.0,9.0,21.0,7.0,31.0,14.0,0.0,0.0,0.0,21.0,6.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,8.0,33.3 +Samu Castillejo,es ESP,"FW,MF",Sassuolo,28-255,1995,3.0,0.0,60.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.11,0.11,0.7,1.0,0.0,50.0,1.5,0.0,0.0,0.04,-0.1,-0.1,28.0,38.0,73.7,321.0,59.0,22.0,25.0,88.0,5.0,9.0,55.6,0.0,1.0,0.0,0.0,2.0,1.0,0.0,2.0,35.0,3.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,1.48,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,48.0,0.0,6.0,14.0,29.0,7.0,48.0,36.0,5.0,0.0,5.0,36.0,2.0,3.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0 +Danilo Cataldi,it ITA,MF,Lazio,29-055,1994,5.0,5.0,375.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.2,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,194.0,221.0,87.8,2904.0,910.0,111.0,120.0,92.5,73.0,80.0,91.3,8.0,14.0,57.1,4.0,17.0,1.0,0.0,18.0,209.0,11.0,6.0,0.0,0.0,6.0,3.0,0.0,3.0,0.0,2.0,1.0,1.0,8.0,1.92,5.0,2.0,0.0,0.0,1.0,0.24,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,4.0,2.0,2.0,7.0,7.0,1.0,250.0,14.0,65.0,160.0,30.0,0.0,250.0,131.0,3.0,3.0,0.0,166.0,3.0,1.0,0.0,6.0,3.0,0.0,0.0,0.0,0.0,37.0,1.0,0.0,100.0 +Emil Ceide,no NOR,"MF,FW",Sassuolo,22-027,2001,3.0,0.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.1,-0.1,20.0,27.0,74.1,228.0,54.0,15.0,18.0,83.3,3.0,4.0,75.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0,2.0,27.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,4.44,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,0.0,0.0,0.0,37.0,0.0,5.0,13.0,21.0,3.0,37.0,20.0,3.0,1.0,2.0,27.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Zeki Çelik,tr TUR,DF,Roma,26-225,1997,1.0,1.0,69.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,33.0,81.8,487.0,258.0,14.0,17.0,82.4,10.0,12.0,83.3,3.0,4.0,75.0,0.0,1.0,0.0,0.0,3.0,29.0,4.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,38.0,2.0,14.0,18.0,6.0,0.0,38.0,20.0,0.0,2.0,0.0,24.0,1.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,50.0 +Michele Cerofolini,it ITA,GK,Frosinone,24-269,1999,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,32.0,50.0,342.0,254.0,5.0,5.0,100.0,7.0,7.0,100.0,4.0,20.0,20.0,0.0,0.0,0.0,0.0,0.0,24.0,8.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,34.0,30.0,34.0,0.0,0.0,0.0,34.0,23.0,0.0,0.0,0.0,22.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Walid Cheddira,ma MAR,FW,Frosinone,25-251,1998,5.0,5.0,408.0,1.0,1.0,1.0,1.0,0.0,0.0,0.22,0.22,0.44,0.0,0.22,2.0,1.2,0.43,0.26,4.5,2.0,0.0,33.3,0.44,0.0,0.0,0.2,-1.0,-1.2,52.0,79.0,65.8,685.0,124.0,28.0,44.0,63.6,15.0,19.0,78.9,3.0,3.0,100.0,5.0,4.0,1.0,0.0,4.0,76.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,10.0,2.21,7.0,0.0,2.0,1.0,3.0,0.66,2.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,1.0,1.0,0.0,4.0,0.0,116.0,5.0,8.0,51.0,57.0,17.0,115.0,73.0,6.0,2.0,3.0,93.0,13.0,6.0,0.0,5.0,6.0,5.0,1.0,0.0,0.0,5.0,7.0,12.0,36.8 +Federico Chiesa,it ITA,FW,Juventus,25-340,1997,6.0,6.0,493.0,4.0,0.0,0.0,0.0,1.0,0.0,0.73,0.0,0.73,0.73,0.73,1.4,1.4,0.26,0.26,5.5,5.0,1.0,35.7,0.91,0.29,0.8,0.1,2.6,2.6,108.0,158.0,68.4,1634.0,528.0,61.0,81.0,75.3,32.0,46.0,69.6,9.0,18.0,50.0,7.0,5.0,13.0,4.0,16.0,144.0,12.0,4.0,1.0,1.0,21.0,5.0,2.0,1.0,0.0,3.0,2.0,3.0,20.0,3.64,13.0,3.0,0.0,1.0,2.0,0.36,1.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,3.0,1.0,2.0,3.0,4.0,0.0,221.0,3.0,18.0,58.0,146.0,38.0,221.0,144.0,33.0,19.0,15.0,168.0,10.0,7.0,0.0,3.0,11.0,2.0,0.0,0.0,0.0,14.0,0.0,1.0,0.0 +Oliver Christensen,dk DEN,GK,Fiorentina,24-192,1999,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,66.0,86.0,76.7,1928.0,1329.0,8.0,8.0,100.0,28.0,30.0,93.3,29.0,47.0,61.7,0.0,1.0,0.0,0.0,0.0,75.0,11.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,90.0,68.0,90.0,0.0,0.0,0.0,90.0,61.0,0.0,0.0,0.0,59.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,3.0,0.0,0.0,0.0 +Samuel Chukwueze,ng NGA,FW,Milan,24-131,1999,5.0,1.0,160.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,46.0,61.0,75.4,693.0,144.0,27.0,31.0,87.1,14.0,20.0,70.0,4.0,8.0,50.0,0.0,2.0,3.0,0.0,6.0,58.0,3.0,0.0,0.0,0.0,5.0,2.0,2.0,0.0,0.0,1.0,0.0,1.0,2.0,1.13,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,79.0,2.0,12.0,27.0,40.0,7.0,79.0,60.0,11.0,4.0,4.0,63.0,3.0,3.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,8.0,2.0,3.0,40.0 +Patrick Ciurria,it ITA,"DF,MF",Monza,28-233,1995,6.0,6.0,525.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.17,0.17,0.0,0.17,0.8,0.8,0.13,0.13,5.8,2.0,0.0,18.2,0.34,0.0,0.0,0.07,-0.8,-0.8,284.0,354.0,80.2,4624.0,1538.0,145.0,165.0,87.9,113.0,140.0,80.7,19.0,31.0,61.3,12.0,17.0,13.0,6.0,30.0,306.0,48.0,3.0,1.0,2.0,29.0,3.0,0.0,2.0,0.0,42.0,0.0,9.0,22.0,3.77,19.0,1.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,9.0,6.0,3.0,4.0,2.0,6.0,4.0,2.0,3.0,6.0,0.0,406.0,12.0,93.0,143.0,173.0,15.0,406.0,230.0,14.0,17.0,4.0,293.0,6.0,1.0,0.0,10.0,2.0,1.0,0.0,1.0,0.0,18.0,2.0,3.0,40.0 +Lorenzo Colombo,it ITA,FW,Monza,21-206,2002,4.0,3.0,257.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.35,0.35,0.0,0.35,0.5,0.5,0.19,0.19,2.9,1.0,0.0,16.7,0.35,0.0,0.0,0.09,-0.5,-0.5,42.0,58.0,72.4,587.0,112.0,25.0,34.0,73.5,10.0,14.0,71.4,3.0,4.0,75.0,2.0,0.0,2.0,0.0,4.0,55.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,8.0,2.8,8.0,0.0,0.0,0.0,1.0,0.35,1.0,0.0,0.0,0.0,0.0,5.0,5.0,2.0,3.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,82.0,1.0,7.0,40.0,36.0,14.0,82.0,46.0,3.0,1.0,1.0,59.0,9.0,5.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,11.0,5.0,12.0,29.4 +Andrea Colpani,it ITA,"MF,FW",Monza,24-142,1999,6.0,6.0,471.0,3.0,0.0,0.0,0.0,0.0,0.0,0.57,0.0,0.57,0.57,0.57,1.2,1.2,0.22,0.22,5.2,6.0,1.0,42.9,1.15,0.21,0.5,0.08,1.8,1.8,155.0,198.0,78.3,2929.0,741.0,67.0,74.0,90.5,59.0,69.0,85.5,25.0,42.0,59.5,12.0,11.0,12.0,2.0,34.0,170.0,24.0,3.0,1.0,7.0,20.0,17.0,6.0,8.0,0.0,4.0,4.0,3.0,27.0,5.16,21.0,4.0,0.0,0.0,2.0,0.38,1.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,1.0,1.0,0.0,242.0,1.0,16.0,78.0,149.0,19.0,242.0,152.0,18.0,13.0,6.0,190.0,5.0,9.0,0.0,3.0,8.0,0.0,0.0,0.0,0.0,14.0,0.0,4.0,0.0 +Andrea Consigli,it ITA,GK,Sassuolo,36-246,1987,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,111.0,169.0,65.7,3062.0,2009.0,22.0,22.0,100.0,44.0,45.0,97.8,43.0,100.0,43.0,0.0,3.0,0.0,0.0,0.0,114.0,55.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,179.0,153.0,178.0,1.0,0.0,0.0,179.0,91.0,0.0,0.0,0.0,79.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Diego Coppola,it ITA,DF,Hellas Verona,19-276,2003,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,69.0,92.0,75.0,1290.0,389.0,29.0,34.0,85.3,29.0,35.0,82.9,10.0,18.0,55.6,0.0,0.0,0.0,0.0,1.0,88.0,4.0,3.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,2.0,0.0,4.0,2.0,2.0,2.0,16.0,0.0,129.0,21.0,90.0,37.0,3.0,1.0,129.0,58.0,0.0,0.0,0.0,60.0,1.0,1.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,14.0,13.0,5.0,72.2 +Tommaso Corazza,it ITA,DF,Bologna,19-093,2004,3.0,0.0,66.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,40.0,47.0,85.1,545.0,192.0,22.0,24.0,91.7,12.0,13.0,92.3,2.0,4.0,50.0,0.0,1.0,0.0,0.0,3.0,39.0,8.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.0,0.0,3.0,2.0,2.73,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,0.0,0.0,2.0,0.0,2.0,3.0,1.0,0.0,60.0,3.0,22.0,21.0,18.0,4.0,60.0,35.0,3.0,1.0,1.0,37.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0 +Lassana Coulibaly,ml MLI,MF,Salernitana,27-173,1996,3.0,3.0,240.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.37,0.37,0.0,0.37,0.0,0.0,0.01,0.01,2.7,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,85.0,103.0,82.5,1387.0,404.0,40.0,45.0,88.9,38.0,44.0,86.4,5.0,8.0,62.5,4.0,10.0,1.0,0.0,10.0,98.0,5.0,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,1.5,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,3.0,1.0,2.0,4.0,5.0,0.0,132.0,5.0,20.0,87.0,25.0,5.0,132.0,75.0,3.0,3.0,0.0,82.0,7.0,4.0,0.0,4.0,6.0,0.0,0.0,0.0,0.0,14.0,3.0,2.0,60.0 +Mamadou Coulibaly,sn SEN,DF,Salernitana,24-239,1999,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,33.3,6.0,1.0,1.0,3.0,33.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,1.0,2.0,0.0,3.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Alessio Cragno,it ITA,GK,Sassuolo,29-094,1994,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,41.0,66.0,62.1,1105.0,787.0,12.0,12.0,100.0,14.0,14.0,100.0,15.0,40.0,37.5,0.0,1.0,0.0,0.0,0.0,41.0,25.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,73.0,61.0,73.0,0.0,0.0,0.0,73.0,31.0,0.0,0.0,0.0,36.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Bryan Cristante,it ITA,MF,Roma,28-211,1995,6.0,6.0,540.0,2.0,2.0,0.0,0.0,0.0,0.0,0.33,0.33,0.67,0.33,0.67,1.4,1.4,0.24,0.24,6.0,2.0,0.0,15.4,0.33,0.15,1.0,0.11,0.6,0.6,344.0,409.0,84.1,5918.0,1916.0,142.0,162.0,87.7,161.0,177.0,91.0,28.0,43.0,65.1,9.0,34.0,6.0,0.0,39.0,400.0,5.0,3.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,2.0,4.0,5.0,24.0,4.0,22.0,0.0,2.0,0.0,5.0,0.83,4.0,0.0,1.0,0.0,0.0,7.0,4.0,5.0,2.0,0.0,3.0,1.0,2.0,5.0,7.0,0.0,459.0,12.0,100.0,281.0,83.0,17.0,459.0,278.0,9.0,10.0,0.0,359.0,5.0,6.0,0.0,13.0,2.0,0.0,0.0,0.0,0.0,46.0,16.0,10.0,61.5 +Juan Cuadrado,co COL,DF,Inter,35-127,1988,3.0,0.0,65.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.38,1.38,0.0,1.38,0.1,0.1,0.09,0.09,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,36.0,43.0,83.7,632.0,114.0,16.0,16.0,100.0,12.0,14.0,85.7,5.0,9.0,55.6,3.0,1.0,1.0,1.0,1.0,41.0,2.0,0.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,4.0,5.54,4.0,0.0,0.0,0.0,1.0,1.38,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,52.0,0.0,10.0,24.0,19.0,6.0,52.0,37.0,8.0,3.0,4.0,40.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Marvin Cuni,al ALB,FW,Frosinone,22-082,2001,5.0,1.0,108.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,27.0,63.0,153.0,6.0,10.0,14.0,71.4,4.0,6.0,66.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.83,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,46.0,0.0,3.0,23.0,20.0,6.0,46.0,25.0,0.0,0.0,1.0,38.0,7.0,4.0,0.0,2.0,4.0,1.0,0.0,0.0,0.0,4.0,8.0,8.0,50.0 +Danilo D'Ambrosio,it ITA,DF,Monza,35-021,1988,3.0,1.0,111.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,80.0,89.0,89.9,1367.0,411.0,30.0,31.0,96.8,41.0,46.0,89.1,5.0,7.0,71.4,2.0,6.0,1.0,0.0,6.0,81.0,8.0,4.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,1.62,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,5.0,4.0,2.0,1.0,3.0,1.0,2.0,5.0,3.0,0.0,108.0,13.0,45.0,56.0,7.0,0.0,108.0,53.0,3.0,0.0,0.0,70.0,0.0,0.0,0.0,3.0,1.0,1.0,0.0,0.0,0.0,3.0,3.0,1.0,75.0 +Flavius Daniliuc,at AUT,DF,Salernitana,22-156,2001,2.0,0.0,51.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,39.0,43.0,90.7,751.0,264.0,9.0,9.0,100.0,22.0,23.0,95.7,5.0,5.0,100.0,1.0,5.0,0.0,0.0,6.0,41.0,2.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,3.53,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,55.0,5.0,28.0,22.0,5.0,1.0,55.0,23.0,0.0,0.0,0.0,29.0,2.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,11.0,2.0,1.0,66.7 +Danilo,br BRA,DF,Juventus,32-077,1991,6.0,6.0,540.0,1.0,0.0,0.0,0.0,2.0,0.0,0.17,0.0,0.17,0.17,0.17,0.6,0.6,0.1,0.1,6.0,1.0,0.0,14.3,0.17,0.14,1.0,0.09,0.4,0.4,327.0,392.0,83.4,6053.0,2360.0,132.0,141.0,93.6,157.0,176.0,89.2,34.0,66.0,51.5,6.0,33.0,5.0,1.0,38.0,369.0,23.0,9.0,1.0,5.0,5.0,0.0,0.0,0.0,0.0,13.0,0.0,2.0,17.0,2.83,14.0,1.0,1.0,0.0,1.0,0.17,0.0,0.0,1.0,0.0,0.0,10.0,5.0,6.0,4.0,0.0,4.0,2.0,2.0,15.0,22.0,0.0,457.0,45.0,174.0,228.0,57.0,7.0,457.0,231.0,2.0,2.0,0.0,300.0,1.0,0.0,0.0,7.0,4.0,0.0,0.0,0.0,0.0,35.0,14.0,1.0,93.3 +Matteo Darmian,it ITA,DF,Inter,33-302,1989,6.0,6.0,533.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.05,0.05,5.9,0.0,0.0,0.0,0.0,0.0,0.0,0.15,-0.3,-0.3,292.0,336.0,86.9,5173.0,1867.0,121.0,132.0,91.7,141.0,144.0,97.9,21.0,36.0,58.3,3.0,19.0,1.0,1.0,18.0,307.0,28.0,4.0,1.0,5.0,2.0,0.0,0.0,0.0,0.0,24.0,1.0,10.0,7.0,1.18,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,6.0,6.0,6.0,1.0,8.0,3.0,5.0,5.0,12.0,0.0,382.0,28.0,137.0,199.0,46.0,3.0,382.0,241.0,4.0,4.0,0.0,268.0,0.0,0.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,18.0,3.0,7.0,30.0 +Paweł Dawidowicz,pl POL,DF,Hellas Verona,28-133,1995,6.0,6.0,540.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,270.0,332.0,81.3,5690.0,2157.0,72.0,86.0,83.7,152.0,171.0,88.9,44.0,69.0,63.8,1.0,18.0,2.0,0.0,26.0,310.0,21.0,14.0,0.0,5.0,2.0,0.0,0.0,0.0,0.0,7.0,1.0,3.0,3.0,0.5,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,6.0,4.0,6.0,0.0,4.0,2.0,2.0,5.0,23.0,0.0,382.0,38.0,193.0,180.0,12.0,1.0,382.0,233.0,2.0,4.0,0.0,224.0,3.0,1.0,0.0,8.0,3.0,0.0,0.0,0.0,0.0,51.0,16.0,7.0,69.6 +Charles De Ketelaere,be BEL,FW,Atalanta,22-204,2001,6.0,3.0,340.0,1.0,2.0,0.0,0.0,0.0,0.0,0.26,0.53,0.79,0.26,0.79,1.3,1.3,0.34,0.34,3.8,3.0,0.0,37.5,0.79,0.13,0.33,0.16,-0.3,-0.3,109.0,151.0,72.2,1542.0,434.0,61.0,81.0,75.3,33.0,42.0,78.6,6.0,10.0,60.0,7.0,6.0,8.0,1.0,22.0,144.0,7.0,4.0,2.0,0.0,5.0,1.0,0.0,1.0,0.0,1.0,0.0,3.0,11.0,2.91,8.0,0.0,1.0,1.0,1.0,0.26,1.0,0.0,0.0,0.0,0.0,8.0,4.0,1.0,1.0,6.0,5.0,0.0,5.0,1.0,1.0,0.0,198.0,0.0,8.0,76.0,118.0,22.0,198.0,115.0,17.0,9.0,7.0,147.0,9.0,8.0,0.0,5.0,2.0,2.0,0.0,0.0,0.0,11.0,10.0,10.0,50.0 +Lorenzo De Silvestri,it ITA,DF,Bologna,35-130,1988,4.0,2.0,206.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,134.0,157.0,85.4,2072.0,742.0,67.0,73.0,91.8,58.0,69.0,84.1,6.0,10.0,60.0,0.0,12.0,1.0,1.0,16.0,138.0,18.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,16.0,1.0,1.0,1.0,0.44,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,0.0,2.0,8.0,0.0,176.0,12.0,57.0,97.0,23.0,0.0,176.0,104.0,6.0,1.0,0.0,123.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,6.0,5.0,1.0,83.3 +Koni De Winter,be BEL,DF,Genoa,21-110,2002,3.0,2.0,180.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.5,0.5,0.0,0.5,0.0,0.0,0.02,0.02,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,39.0,59.0,66.1,636.0,243.0,18.0,25.0,72.0,18.0,25.0,72.0,2.0,4.0,50.0,2.0,4.0,1.0,0.0,4.0,41.0,18.0,0.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,18.0,0.0,3.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,0.5,0.0,0.0,1.0,0.0,0.0,5.0,4.0,3.0,2.0,0.0,0.0,0.0,0.0,1.0,4.0,0.0,75.0,11.0,33.0,30.0,12.0,2.0,75.0,28.0,1.0,0.0,1.0,30.0,3.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,11.0,3.0,4.0,42.9 +Grégoire Defrel,mq MTQ,"FW,MF",Sassuolo,32-105,1991,3.0,1.0,96.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.1,1.0,0.0,100.0,0.94,0.0,0.0,0.08,-0.1,-0.1,19.0,24.0,79.2,296.0,69.0,9.0,10.0,90.0,8.0,11.0,72.7,2.0,2.0,100.0,1.0,4.0,0.0,0.0,3.0,22.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,2.0,1.89,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,3.0,0.0,31.0,3.0,6.0,13.0,12.0,3.0,31.0,24.0,1.0,0.0,0.0,25.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,33.3 +Alessandro Deiola,it ITA,MF,Cagliari,28-060,1995,6.0,2.0,177.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.51,0.51,2.0,1.0,1.0,11.1,0.51,0.0,0.0,0.11,-1.0,-1.0,41.0,61.0,67.2,735.0,271.0,21.0,25.0,84.0,16.0,20.0,80.0,4.0,10.0,40.0,2.0,7.0,1.0,1.0,10.0,61.0,0.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,2.03,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,3.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,77.0,1.0,15.0,36.0,26.0,6.0,77.0,42.0,2.0,2.0,0.0,44.0,1.0,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,14.0,2.0,1.0,66.7 +Mattia Destro,it ITA,"FW,MF",Empoli,32-194,1991,3.0,1.0,90.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,12.0,17.0,70.6,175.0,13.0,6.0,7.0,85.7,6.0,8.0,75.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,11.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,27.0,0.0,2.0,14.0,11.0,3.0,27.0,14.0,1.0,1.0,0.0,17.0,2.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,1.0,3.0,4.0,42.9 +Federico Di Francesco,it ITA,"FW,MF",Lecce,29-108,1994,2.0,0.0,15.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,6.0,6.0,6.0,0.1,0.1,0.53,0.53,0.2,1.0,0.0,50.0,6.0,0.5,1.0,0.04,0.9,0.9,6.0,8.0,75.0,90.0,43.0,1.0,2.0,50.0,2.0,2.0,100.0,1.0,2.0,50.0,0.0,1.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,0.0,2.0,8.0,5.0,3.0,15.0,9.0,1.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Michele Di Gregorio,it ITA,GK,Monza,26-065,1997,5.0,5.0,450.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,156.0,208.0,75.0,3975.0,2464.0,33.0,34.0,97.1,78.0,79.0,98.7,43.0,92.0,46.7,0.0,2.0,0.0,0.0,0.0,159.0,48.0,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.4,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,223.0,177.0,223.0,0.0,0.0,0.0,223.0,128.0,0.0,0.0,0.0,122.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 +Giovanni Di Lorenzo,it ITA,DF,Napoli,30-057,1993,6.0,6.0,540.0,1.0,2.0,0.0,0.0,0.0,0.0,0.17,0.33,0.5,0.17,0.5,0.6,0.6,0.09,0.09,6.0,1.0,0.0,25.0,0.17,0.25,1.0,0.14,0.4,0.4,328.0,395.0,83.0,4956.0,1900.0,191.0,203.0,94.1,104.0,136.0,76.5,25.0,37.0,67.6,15.0,29.0,19.0,5.0,37.0,335.0,59.0,7.0,1.0,0.0,24.0,0.0,0.0,0.0,0.0,52.0,1.0,7.0,25.0,4.17,23.0,0.0,1.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,13.0,10.0,7.0,6.0,0.0,2.0,1.0,1.0,3.0,4.0,0.0,434.0,8.0,100.0,198.0,144.0,17.0,434.0,268.0,20.0,9.0,5.0,313.0,5.0,2.0,0.0,2.0,3.0,1.0,0.0,0.0,0.0,27.0,1.0,5.0,16.7 +Alessandro Di Pardo,it ITA,"MF,DF",Cagliari,24-074,1999,5.0,0.0,156.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,48.0,73.0,65.8,797.0,342.0,26.0,33.0,78.8,17.0,24.0,70.8,4.0,9.0,44.4,1.0,2.0,2.0,1.0,5.0,63.0,10.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,10.0,0.0,4.0,2.0,1.15,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,1.0,1.0,2.0,2.0,0.0,90.0,7.0,30.0,32.0,29.0,2.0,90.0,51.0,1.0,0.0,0.0,44.0,1.0,3.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,17.0,1.0,1.0,50.0 +Boulaye Dia,sn SEN,"FW,DF",Salernitana,26-318,1996,3.0,1.0,141.0,1.0,0.0,0.0,0.0,0.0,0.0,0.64,0.0,0.64,0.64,0.64,0.3,0.3,0.18,0.18,1.6,1.0,0.0,100.0,0.64,1.0,1.0,0.29,0.7,0.7,21.0,24.0,87.5,387.0,97.0,12.0,14.0,85.7,4.0,5.0,80.0,4.0,4.0,100.0,1.0,4.0,2.0,0.0,4.0,22.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.64,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,36.0,1.0,2.0,15.0,19.0,4.0,36.0,24.0,0.0,2.0,2.0,29.0,4.0,3.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,6.0,14.3 +Federico Dimarco,it ITA,DF,Inter,25-324,1997,6.0,6.0,416.0,1.0,3.0,0.0,0.0,0.0,0.0,0.22,0.65,0.87,0.22,0.87,0.6,0.6,0.13,0.13,4.6,6.0,1.0,46.2,1.3,0.08,0.17,0.05,0.4,0.4,216.0,277.0,78.0,3534.0,1381.0,118.0,127.0,92.9,68.0,90.0,75.6,21.0,42.0,50.0,17.0,14.0,19.0,10.0,28.0,223.0,54.0,3.0,0.0,3.0,49.0,16.0,3.0,12.0,0.0,35.0,0.0,4.0,35.0,7.57,26.0,5.0,3.0,0.0,5.0,1.08,3.0,0.0,2.0,0.0,0.0,10.0,7.0,4.0,5.0,1.0,4.0,1.0,3.0,2.0,5.0,0.0,320.0,8.0,51.0,113.0,161.0,14.0,320.0,185.0,13.0,10.0,0.0,203.0,4.0,1.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,27.0,0.0,1.0,0.0 +Berat Djimsiti,al ALB,DF,Atalanta,30-223,1993,5.0,5.0,434.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.8,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,192.0,226.0,85.0,3849.0,1253.0,58.0,66.0,87.9,105.0,118.0,89.0,26.0,31.0,83.9,1.0,3.0,1.0,0.0,11.0,217.0,7.0,5.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,2.0,2.0,3.0,0.62,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,2.0,0.0,15.0,9.0,6.0,6.0,10.0,0.0,270.0,31.0,158.0,99.0,14.0,4.0,270.0,130.0,0.0,0.0,0.0,157.0,2.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,27.0,15.0,9.0,62.5 +Dodô,br BRA,DF,Fiorentina,24-317,1998,5.0,4.0,267.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.0,1.0,0.0,100.0,0.34,0.0,0.0,0.06,-0.1,-0.1,152.0,186.0,81.7,2804.0,957.0,59.0,67.0,88.1,73.0,87.0,83.9,18.0,26.0,69.2,6.0,14.0,6.0,2.0,26.0,158.0,27.0,4.0,1.0,1.0,8.0,0.0,0.0,0.0,0.0,23.0,1.0,0.0,6.0,2.02,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,2.0,0.0,2.0,3.0,6.0,0.0,210.0,9.0,43.0,114.0,54.0,1.0,210.0,142.0,12.0,6.0,1.0,147.0,4.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,10.0,1.0,0.0,100.0 +Josh Doig,sct SCO,DF,Hellas Verona,21-135,2002,4.0,4.0,298.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.06,0.06,3.3,1.0,0.0,20.0,0.3,0.0,0.0,0.04,-0.2,-0.2,88.0,116.0,75.9,1625.0,562.0,34.0,40.0,85.0,45.0,53.0,84.9,7.0,15.0,46.7,1.0,8.0,1.0,1.0,5.0,91.0,24.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,24.0,1.0,2.0,3.0,0.91,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,9.0,0.0,145.0,6.0,33.0,76.0,38.0,8.0,145.0,69.0,5.0,4.0,1.0,82.0,4.0,1.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,12.0,3.0,2.0,60.0 +Nicolás Domínguez,ar ARG,MF,Bologna,25-094,1998,2.0,1.0,101.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,83.0,92.0,90.2,1276.0,370.0,45.0,49.0,91.8,36.0,40.0,90.0,2.0,2.0,100.0,1.0,5.0,1.0,0.0,9.0,90.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,2.0,1.78,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,3.0,0.0,3.0,0.0,2.0,0.0,103.0,2.0,23.0,69.0,12.0,0.0,103.0,39.0,1.0,2.0,0.0,79.0,1.0,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,7.0,1.0,0.0,100.0 +Patrick Dorgu,dk DEN,DF,Lecce,18-339,2004,6.0,2.0,261.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.9,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,153.0,186.0,82.3,2369.0,650.0,78.0,83.0,94.0,59.0,72.0,81.9,10.0,20.0,50.0,1.0,6.0,1.0,0.0,12.0,146.0,40.0,5.0,0.0,0.0,9.0,4.0,0.0,0.0,0.0,31.0,0.0,3.0,7.0,2.41,2.0,4.0,1.0,0.0,1.0,0.34,0.0,0.0,1.0,0.0,0.0,9.0,5.0,6.0,3.0,0.0,5.0,1.0,4.0,1.0,4.0,0.0,223.0,8.0,67.0,97.0,61.0,3.0,223.0,128.0,4.0,4.0,0.0,125.0,5.0,4.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,25.0,3.0,8.0,27.3 +Alberto Dossena,it ITA,DF,Cagliari,24-352,1998,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.12,-0.2,-0.2,162.0,200.0,81.0,3324.0,1187.0,49.0,55.0,89.1,90.0,104.0,86.5,21.0,33.0,63.6,0.0,10.0,0.0,0.0,17.0,195.0,5.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,0.5,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,6.0,6.0,2.0,0.0,10.0,6.0,4.0,7.0,33.0,1.0,273.0,56.0,163.0,103.0,9.0,5.0,273.0,127.0,2.0,1.0,0.0,119.0,4.0,1.0,0.0,7.0,3.0,0.0,0.0,0.0,0.0,49.0,15.0,18.0,45.5 +Radu Drăgușin,ro ROU,DF,Genoa,21-239,2002,6.0,6.0,540.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.17,0.17,0.0,0.17,0.1,0.1,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,152.0,184.0,82.6,2681.0,904.0,66.0,71.0,93.0,68.0,75.0,90.7,15.0,32.0,46.9,2.0,3.0,0.0,0.0,2.0,156.0,28.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,5.0,3.0,3.0,2.0,0.0,7.0,3.0,4.0,8.0,40.0,2.0,253.0,73.0,157.0,85.0,11.0,3.0,253.0,107.0,1.0,1.0,1.0,122.0,1.0,1.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,16.0,10.0,5.0,66.7 +Ondrej Duda,sk SVK,MF,Hellas Verona,28-299,1994,6.0,6.0,444.0,1.0,1.0,0.0,0.0,1.0,0.0,0.2,0.2,0.41,0.2,0.41,0.8,0.8,0.16,0.16,4.9,1.0,1.0,25.0,0.2,0.25,1.0,0.2,0.2,0.2,142.0,179.0,79.3,2625.0,841.0,58.0,67.0,86.6,60.0,65.0,92.3,22.0,36.0,61.1,14.0,18.0,5.0,0.0,20.0,153.0,24.0,14.0,2.0,2.0,16.0,8.0,4.0,4.0,0.0,1.0,2.0,6.0,20.0,4.06,11.0,7.0,0.0,1.0,1.0,0.2,1.0,0.0,0.0,0.0,0.0,5.0,2.0,1.0,3.0,1.0,4.0,2.0,2.0,6.0,4.0,0.0,220.0,10.0,48.0,122.0,54.0,4.0,220.0,118.0,2.0,0.0,0.0,113.0,8.0,1.0,0.0,6.0,11.0,0.0,0.0,0.0,0.0,33.0,0.0,3.0,0.0 +Denzel Dumfries,nl NED,DF,Inter,27-165,1996,5.0,5.0,385.0,2.0,2.0,0.0,0.0,0.0,0.0,0.47,0.47,0.94,0.47,0.94,0.6,0.6,0.14,0.14,4.3,2.0,0.0,25.0,0.47,0.25,1.0,0.08,1.4,1.4,116.0,165.0,70.3,1828.0,608.0,50.0,63.0,79.4,47.0,69.0,68.1,8.0,15.0,53.3,12.0,9.0,9.0,3.0,14.0,138.0,27.0,0.0,0.0,0.0,13.0,0.0,0.0,0.0,0.0,27.0,0.0,3.0,14.0,3.27,11.0,1.0,1.0,0.0,3.0,0.7,2.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,3.0,2.0,1.0,0.0,3.0,0.0,207.0,4.0,32.0,85.0,92.0,23.0,207.0,125.0,12.0,8.0,4.0,145.0,8.0,3.0,0.0,6.0,5.0,1.0,0.0,0.0,0.0,13.0,8.0,5.0,61.5 +Alfred Duncan,gh GHA,MF,Fiorentina,30-204,1993,5.0,3.0,284.0,1.0,3.0,0.0,0.0,0.0,0.0,0.32,0.95,1.27,0.32,1.27,0.8,0.8,0.25,0.25,3.2,1.0,0.0,20.0,0.32,0.2,1.0,0.16,0.2,0.2,100.0,129.0,77.5,2176.0,753.0,32.0,38.0,84.2,51.0,58.0,87.9,16.0,23.0,69.6,11.0,16.0,7.0,3.0,26.0,119.0,9.0,2.0,2.0,1.0,12.0,5.0,1.0,4.0,0.0,1.0,1.0,6.0,14.0,4.45,11.0,1.0,0.0,0.0,3.0,0.95,2.0,1.0,0.0,0.0,0.0,9.0,6.0,2.0,3.0,4.0,6.0,2.0,4.0,1.0,1.0,0.0,154.0,5.0,17.0,79.0,59.0,6.0,154.0,86.0,3.0,3.0,1.0,92.0,2.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,23.0,1.0,5.0,16.7 +Paulo Dybala,ar ARG,"MF,FW",Roma,29-319,1993,4.0,4.0,310.0,2.0,0.0,1.0,1.0,2.0,0.0,0.58,0.0,0.58,0.29,0.29,1.7,0.9,0.5,0.27,3.4,5.0,1.0,50.0,1.45,0.1,0.2,0.09,0.3,0.1,120.0,150.0,80.0,1915.0,454.0,72.0,82.0,87.8,26.0,35.0,74.3,15.0,20.0,75.0,5.0,9.0,4.0,0.0,17.0,134.0,14.0,1.0,0.0,4.0,9.0,7.0,0.0,6.0,0.0,0.0,2.0,3.0,12.0,3.48,8.0,3.0,0.0,0.0,2.0,0.58,1.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,2.0,1.0,2.0,0.0,2.0,1.0,1.0,0.0,202.0,1.0,11.0,90.0,102.0,11.0,201.0,112.0,13.0,5.0,6.0,155.0,8.0,7.0,0.0,1.0,6.0,1.0,0.0,0.0,0.0,10.0,3.0,5.0,37.5 +Festy Ebosele,ie IRL,DF,Udinese,21-059,2002,6.0,4.0,320.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.6,1.0,0.0,25.0,0.28,0.0,0.0,0.03,-0.1,-0.1,78.0,108.0,72.2,1218.0,422.0,39.0,50.0,78.0,25.0,34.0,73.5,9.0,11.0,81.8,6.0,6.0,6.0,3.0,12.0,89.0,19.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,19.0,0.0,5.0,16.0,4.51,11.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,5.0,6.0,2.0,1.0,6.0,0.0,6.0,1.0,5.0,0.0,152.0,8.0,35.0,49.0,69.0,10.0,152.0,90.0,17.0,6.0,6.0,88.0,7.0,6.0,0.0,4.0,11.0,0.0,0.0,2.0,0.0,14.0,4.0,4.0,50.0 +Enzo Ebosse,cm CMR,DF,Udinese,24-203,1999,1.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,222.0,57.0,4.0,4.0,100.0,7.0,9.0,77.8,1.0,2.0,50.0,0.0,1.0,0.0,0.0,1.0,15.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,11.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,17.0,5.0,9.0,8.0,0.0,0.0,17.0,12.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 +Tyronne Ebuehi,ng NGA,DF,Empoli,27-288,1995,4.0,3.0,344.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,114.0,162.0,70.4,1849.0,583.0,56.0,67.0,83.6,44.0,62.0,71.0,10.0,20.0,50.0,2.0,5.0,1.0,0.0,11.0,128.0,34.0,1.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,33.0,0.0,9.0,4.0,1.05,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,2.0,0.0,4.0,2.0,2.0,1.0,8.0,0.0,194.0,13.0,83.0,79.0,32.0,7.0,194.0,103.0,11.0,4.0,2.0,108.0,5.0,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,17.0,2.0,7.0,22.2 +Éderson,br BRA,MF,Atalanta,24-085,1999,6.0,5.0,464.0,1.0,1.0,0.0,0.0,1.0,0.0,0.19,0.19,0.39,0.19,0.39,0.5,0.5,0.1,0.1,5.2,2.0,0.0,28.6,0.39,0.14,0.5,0.07,0.5,0.5,200.0,254.0,78.7,3653.0,1331.0,78.0,93.0,83.9,101.0,112.0,90.2,19.0,32.0,59.4,5.0,28.0,8.0,2.0,40.0,248.0,3.0,3.0,1.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,3.0,7.0,12.0,2.33,11.0,0.0,0.0,1.0,1.0,0.19,1.0,0.0,0.0,0.0,0.0,23.0,11.0,10.0,11.0,2.0,8.0,0.0,8.0,11.0,6.0,0.0,323.0,15.0,79.0,178.0,72.0,4.0,323.0,206.0,7.0,9.0,0.0,206.0,5.0,9.0,0.0,8.0,6.0,0.0,0.0,0.0,0.0,39.0,8.0,4.0,66.7 +Emmanuel Ekong,se SWE,FW,Empoli,21-097,2002,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,12.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,18.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,3.0,1.0,1.0,4.0,4.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Caleb Ekuban,gh GHA,"FW,DF",Genoa,29-191,1994,4.0,0.0,83.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.18,0.18,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,10.0,17.0,58.8,196.0,79.0,3.0,8.0,37.5,5.0,5.0,100.0,2.0,2.0,100.0,2.0,2.0,1.0,0.0,3.0,16.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,5.36,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,37.0,0.0,2.0,18.0,19.0,4.0,37.0,20.0,0.0,1.0,1.0,22.0,5.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,75.0 +Elif Elmas,mk MKD,FW,Napoli,24-006,1999,5.0,1.0,90.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.0,1.0,0.0,100.0,1.0,0.0,0.0,0.02,0.0,0.0,50.0,53.0,94.3,660.0,115.0,36.0,37.0,97.3,12.0,12.0,100.0,1.0,1.0,100.0,3.0,1.0,0.0,0.0,3.0,50.0,3.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,1.0,0.0,1.0,6.0,6.07,4.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,64.0,1.0,8.0,30.0,28.0,4.0,64.0,36.0,3.0,4.0,1.0,48.0,2.0,1.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Martin Erlic,hr CRO,DF,Sassuolo,25-249,1998,6.0,6.0,530.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.09,0.09,5.9,1.0,0.0,33.3,0.17,0.0,0.0,0.19,-0.6,-0.6,181.0,218.0,83.0,3501.0,1554.0,75.0,79.0,94.9,79.0,96.0,82.3,25.0,41.0,61.0,0.0,8.0,0.0,0.0,13.0,207.0,11.0,11.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.34,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,5.0,10.0,1.0,0.0,9.0,5.0,4.0,8.0,25.0,0.0,280.0,53.0,158.0,117.0,6.0,5.0,280.0,113.0,3.0,1.0,1.0,150.0,3.0,0.0,0.0,6.0,3.0,0.0,0.0,0.0,0.0,24.0,12.0,8.0,60.0 +Giovanni Fabbian,it ITA,"MF,FW",Bologna,20-259,2003,3.0,0.0,19.0,1.0,0.0,0.0,0.0,0.0,0.0,4.74,0.0,4.74,4.74,4.74,0.8,0.8,4.02,4.02,0.2,1.0,0.0,50.0,4.74,0.5,1.0,0.42,0.2,0.2,3.0,5.0,60.0,22.0,2.0,3.0,5.0,60.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,3.0,3.0,4.0,3.0,10.0,9.0,0.0,0.0,0.0,7.0,2.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Nicolò Fagioli,it ITA,MF,Juventus,22-230,2001,5.0,2.0,272.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.33,0.33,0.0,0.33,0.2,0.2,0.07,0.07,3.0,1.0,1.0,25.0,0.33,0.0,0.0,0.06,-0.2,-0.2,122.0,144.0,84.7,2166.0,533.0,61.0,64.0,95.3,41.0,47.0,87.2,18.0,27.0,66.7,8.0,12.0,5.0,1.0,18.0,127.0,17.0,4.0,0.0,4.0,17.0,9.0,1.0,6.0,0.0,3.0,0.0,2.0,13.0,4.29,7.0,5.0,1.0,0.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,2.0,0.0,2.0,2.0,0.0,0.0,172.0,1.0,18.0,84.0,71.0,4.0,172.0,111.0,4.0,4.0,1.0,121.0,7.0,2.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,11.0,1.0,0.0,100.0 +Wladimiro Falcone,it ITA,GK,Lecce,28-171,1995,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,130.0,177.0,73.4,3091.0,2258.0,36.0,36.0,100.0,47.0,48.0,97.9,35.0,80.0,43.8,0.0,0.0,0.0,0.0,0.0,115.0,61.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,188.0,176.0,188.0,0.0,0.0,0.0,188.0,99.0,0.0,0.0,0.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 +Davide Faraoni,it ITA,DF,Hellas Verona,31-340,1991,5.0,4.0,276.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.33,0.33,0.0,0.33,0.3,0.3,0.1,0.1,3.1,1.0,0.0,20.0,0.33,0.0,0.0,0.06,-0.3,-0.3,95.0,136.0,69.9,1792.0,760.0,41.0,49.0,83.7,33.0,44.0,75.0,18.0,31.0,58.1,2.0,10.0,2.0,1.0,10.0,103.0,29.0,3.0,1.0,3.0,6.0,1.0,0.0,0.0,0.0,25.0,4.0,3.0,7.0,2.28,4.0,1.0,0.0,1.0,1.0,0.33,1.0,0.0,0.0,0.0,0.0,6.0,6.0,2.0,3.0,1.0,4.0,2.0,2.0,1.0,14.0,0.0,179.0,11.0,40.0,98.0,44.0,6.0,179.0,89.0,6.0,3.0,0.0,93.0,6.0,1.0,0.0,7.0,6.0,0.0,0.0,0.0,0.0,25.0,6.0,2.0,75.0 +Federico Fazio,ar ARG,DF,Salernitana,36-197,1987,2.0,1.0,113.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.3,1.0,0.0,100.0,0.8,0.0,0.0,0.11,-0.1,-0.1,57.0,74.0,77.0,987.0,422.0,27.0,29.0,93.1,23.0,31.0,74.2,5.0,10.0,50.0,0.0,4.0,0.0,0.0,2.0,71.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.59,2.0,0.0,0.0,0.0,1.0,0.8,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,2.0,3.0,0.0,83.0,4.0,39.0,40.0,4.0,2.0,83.0,60.0,0.0,0.0,0.0,55.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,10.0,6.0,1.0,85.7 +Jacopo Fazzini,it ITA,MF,Empoli,20-198,2003,5.0,3.0,245.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.09,0.09,2.7,1.0,1.0,25.0,0.37,0.0,0.0,0.06,-0.3,-0.3,99.0,131.0,75.6,1742.0,522.0,44.0,53.0,83.0,37.0,44.0,84.1,14.0,26.0,53.8,8.0,7.0,1.0,0.0,14.0,107.0,23.0,6.0,0.0,0.0,18.0,15.0,6.0,6.0,0.0,2.0,1.0,1.0,10.0,3.67,6.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.0,3.0,2.0,1.0,5.0,0.0,5.0,4.0,1.0,0.0,170.0,4.0,31.0,86.0,56.0,5.0,170.0,82.0,1.0,3.0,0.0,88.0,3.0,8.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,17.0,3.0,8.0,27.3 +Lewis Ferguson,sct SCO,MF,Bologna,24-037,1999,6.0,6.0,536.0,1.0,0.0,0.0,0.0,1.0,0.0,0.17,0.0,0.17,0.17,0.17,0.6,0.6,0.09,0.09,6.0,3.0,0.0,25.0,0.5,0.08,0.33,0.05,0.4,0.4,304.0,346.0,87.9,4092.0,772.0,184.0,201.0,91.5,94.0,106.0,88.7,6.0,9.0,66.7,4.0,20.0,6.0,1.0,22.0,345.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,12.0,2.01,12.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,10.0,6.0,2.0,7.0,1.0,2.0,0.0,2.0,1.0,3.0,0.0,393.0,9.0,51.0,231.0,113.0,17.0,393.0,233.0,9.0,4.0,2.0,321.0,5.0,4.0,0.0,15.0,9.0,1.0,0.0,0.0,0.0,32.0,7.0,11.0,38.9 +João Ferreira,pt POR,DF,Udinese,22-192,2001,5.0,2.0,220.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.4,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,68.0,84.0,81.0,1218.0,417.0,34.0,39.0,87.2,23.0,26.0,88.5,8.0,13.0,61.5,2.0,4.0,3.0,3.0,2.0,68.0,16.0,1.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,15.0,0.0,1.0,5.0,2.04,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,5.0,4.0,3.0,1.0,3.0,0.0,3.0,3.0,2.0,0.0,110.0,4.0,27.0,48.0,35.0,1.0,110.0,63.0,3.0,5.0,0.0,59.0,5.0,4.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,13.0,0.0,1.0,0.0 +Alessandro Florenzi,it ITA,DF,Milan,32-203,1991,4.0,2.0,182.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,145.0,172.0,84.3,2680.0,747.0,55.0,60.0,91.7,68.0,72.0,94.4,17.0,33.0,51.5,2.0,8.0,0.0,0.0,11.0,147.0,25.0,8.0,0.0,3.0,10.0,2.0,2.0,0.0,0.0,15.0,0.0,1.0,5.0,2.47,4.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,2.0,1.0,2.0,1.0,1.0,4.0,3.0,0.0,189.0,9.0,56.0,94.0,40.0,1.0,189.0,125.0,4.0,7.0,0.0,128.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,12.0,1.0,2.0,33.3 +Michael Folorunsho,ng NGA,"MF,FW",Hellas Verona,25-235,1998,6.0,6.0,494.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.05,0.05,5.5,2.0,0.0,40.0,0.36,0.0,0.0,0.05,-0.3,-0.3,91.0,137.0,66.4,1475.0,346.0,41.0,49.0,83.7,40.0,58.0,69.0,6.0,13.0,46.2,2.0,5.0,1.0,0.0,15.0,132.0,4.0,2.0,1.0,3.0,7.0,0.0,0.0,0.0,0.0,2.0,1.0,4.0,6.0,1.09,3.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,8.0,6.0,1.0,2.0,8.0,0.0,8.0,2.0,8.0,0.0,198.0,8.0,27.0,120.0,55.0,7.0,198.0,113.0,5.0,6.0,0.0,112.0,9.0,4.0,0.0,8.0,15.0,2.0,0.0,0.0,0.0,30.0,11.0,22.0,33.3 +Davide Frattesi,it ITA,MF,Inter,23-343,1999,6.0,1.0,183.0,1.0,0.0,0.0,0.0,1.0,0.0,0.49,0.0,0.49,0.49,0.49,1.3,1.3,0.63,0.63,2.0,3.0,0.0,33.3,1.48,0.11,0.33,0.14,-0.3,-0.3,38.0,48.0,79.2,636.0,167.0,16.0,17.0,94.1,15.0,21.0,71.4,4.0,4.0,100.0,0.0,3.0,2.0,0.0,6.0,44.0,3.0,3.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.98,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,1.0,4.0,0.0,67.0,4.0,13.0,27.0,27.0,10.0,67.0,48.0,6.0,3.0,2.0,48.0,0.0,5.0,0.0,3.0,5.0,0.0,0.0,0.0,0.0,9.0,2.0,1.0,66.7 +Morten Frendrup,dk DEN,MF,Genoa,22-176,2001,6.0,6.0,540.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.33,0.33,0.0,0.33,0.1,0.1,0.02,0.02,6.0,1.0,0.0,33.3,0.17,0.0,0.0,0.03,-0.1,-0.1,127.0,170.0,74.7,1973.0,430.0,70.0,86.0,81.4,43.0,54.0,79.6,8.0,13.0,61.5,2.0,11.0,2.0,0.0,18.0,165.0,5.0,2.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,3.0,0.0,6.0,4.0,0.67,3.0,0.0,1.0,0.0,3.0,0.5,2.0,0.0,1.0,0.0,0.0,21.0,13.0,6.0,13.0,2.0,10.0,3.0,7.0,8.0,9.0,0.0,240.0,13.0,69.0,127.0,47.0,6.0,240.0,100.0,4.0,2.0,1.0,109.0,6.0,3.0,0.0,9.0,7.0,1.0,0.0,0.0,0.0,37.0,5.0,4.0,55.6 +Remo Freuler,ch SUI,MF,Bologna,31-168,1992,2.0,2.0,160.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,84.0,92.0,91.3,1198.0,291.0,46.0,50.0,92.0,32.0,33.0,97.0,2.0,4.0,50.0,0.0,6.0,0.0,0.0,4.0,86.0,6.0,4.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,1.0,0.56,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,5.0,2.0,3.0,0.0,4.0,1.0,3.0,2.0,4.0,1.0,115.0,5.0,37.0,58.0,20.0,4.0,115.0,56.0,1.0,2.0,1.0,86.0,3.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0 +Roberto Gagliardini,it ITA,MF,Monza,29-176,1994,6.0,6.0,495.0,1.0,0.0,0.0,0.0,1.0,0.0,0.18,0.0,0.18,0.18,0.18,1.0,1.0,0.18,0.18,5.5,3.0,0.0,23.1,0.55,0.08,0.33,0.08,0.0,0.0,288.0,322.0,89.4,5139.0,1111.0,123.0,130.0,94.6,141.0,152.0,92.8,20.0,28.0,71.4,4.0,28.0,2.0,0.0,25.0,311.0,10.0,6.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,3.0,1.0,3.0,13.0,2.36,12.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,20.0,12.0,9.0,8.0,3.0,6.0,1.0,5.0,6.0,5.0,0.0,392.0,15.0,81.0,220.0,94.0,10.0,392.0,237.0,12.0,10.0,1.0,281.0,6.0,7.0,0.0,3.0,10.0,0.0,0.0,0.0,0.0,31.0,8.0,4.0,66.7 +Antonino Gallo,it ITA,DF,Lecce,23-268,2000,5.0,4.0,279.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.32,0.32,0.0,0.32,0.0,0.0,0.0,0.0,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,120.0,156.0,76.9,2205.0,794.0,55.0,64.0,85.9,52.0,61.0,85.2,11.0,22.0,50.0,6.0,12.0,8.0,5.0,24.0,119.0,36.0,9.0,0.0,3.0,11.0,2.0,0.0,0.0,0.0,25.0,1.0,5.0,8.0,2.58,7.0,1.0,0.0,0.0,2.0,0.65,2.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,2.0,0.0,4.0,0.0,4.0,1.0,9.0,0.0,183.0,10.0,49.0,90.0,46.0,1.0,183.0,95.0,3.0,3.0,1.0,101.0,3.0,0.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,11.0,3.0,0.0,100.0 +Luca Garritano,it ITA,"MF,FW",Frosinone,29-231,1994,5.0,0.0,108.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.36,0.36,1.2,1.0,1.0,16.7,0.83,0.0,0.0,0.07,-0.4,-0.4,31.0,47.0,66.0,525.0,213.0,16.0,20.0,80.0,9.0,13.0,69.2,4.0,9.0,44.4,1.0,8.0,0.0,0.0,6.0,45.0,2.0,0.0,0.0,0.0,4.0,2.0,1.0,1.0,0.0,0.0,0.0,1.0,5.0,4.17,4.0,0.0,0.0,1.0,1.0,0.83,1.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,1.0,0.0,4.0,0.0,4.0,0.0,0.0,0.0,64.0,2.0,18.0,28.0,19.0,5.0,64.0,29.0,2.0,1.0,0.0,32.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,10.0,1.0,1.0,50.0 +Federico Gatti,it ITA,DF,Juventus,25-098,1998,4.0,3.0,289.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,112.0,129.0,86.8,2059.0,747.0,45.0,45.0,100.0,54.0,61.0,88.5,12.0,18.0,66.7,1.0,4.0,0.0,0.0,10.0,126.0,3.0,2.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,5.0,1.56,4.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,1.0,1.0,2.0,2.0,0.0,1.0,11.0,0.0,165.0,16.0,73.0,78.0,15.0,7.0,165.0,100.0,2.0,3.0,0.0,114.0,3.0,2.0,0.0,2.0,5.0,0.0,1.0,0.0,1.0,13.0,3.0,1.0,75.0 +Francesco Gelli,it ITA,"FW,MF",Frosinone,26-350,1996,4.0,4.0,352.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,129.0,154.0,83.8,1718.0,454.0,84.0,89.0,94.4,32.0,37.0,86.5,5.0,13.0,38.5,2.0,6.0,7.0,1.0,13.0,137.0,17.0,4.0,0.0,0.0,11.0,11.0,4.0,2.0,0.0,0.0,0.0,5.0,6.0,1.53,4.0,1.0,1.0,0.0,1.0,0.26,0.0,1.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,4.0,2.0,2.0,4.0,2.0,0.0,198.0,3.0,46.0,83.0,73.0,6.0,198.0,126.0,6.0,3.0,1.0,142.0,15.0,4.0,0.0,6.0,5.0,0.0,0.0,0.0,0.0,17.0,3.0,3.0,50.0 +Valentin Gendrey,fr FRA,DF,Lecce,23-101,2000,6.0,5.0,452.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.4,0.4,0.0,0.4,0.1,0.1,0.01,0.01,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,192.0,240.0,80.0,3124.0,1522.0,108.0,119.0,90.8,72.0,87.0,82.8,12.0,28.0,42.9,5.0,20.0,1.0,1.0,25.0,175.0,65.0,4.0,0.0,1.0,6.0,0.0,0.0,0.0,0.0,61.0,0.0,5.0,9.0,1.79,9.0,0.0,0.0,0.0,2.0,0.4,2.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,11.0,1.0,10.0,8.0,13.0,0.0,288.0,16.0,82.0,143.0,64.0,3.0,288.0,141.0,9.0,7.0,1.0,135.0,4.0,2.0,0.0,2.0,5.0,0.0,0.0,0.0,0.0,24.0,7.0,7.0,50.0 +Gvidas Gineitis,lt LTU,MF,Torino,19-168,2004,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,7.0,100.0,100.0,8.0,6.0,6.0,100.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,11.0,0.0,2.0,6.0,3.0,0.0,11.0,5.0,0.0,0.0,0.0,7.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Olivier Giroud,fr FRA,FW,Milan,37-000,1986,5.0,5.0,346.0,4.0,3.0,3.0,3.0,0.0,0.0,1.04,0.78,1.82,0.26,1.04,3.1,0.7,0.81,0.19,3.8,3.0,1.0,37.5,0.78,0.13,0.33,0.09,0.9,0.3,49.0,78.0,62.8,597.0,113.0,30.0,45.0,66.7,12.0,18.0,66.7,0.0,0.0,0.0,9.0,5.0,2.0,0.0,6.0,69.0,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,8.0,2.08,8.0,0.0,0.0,0.0,3.0,0.78,3.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,2.0,0.0,2.0,0.0,2.0,0.0,106.0,3.0,6.0,60.0,40.0,15.0,103.0,57.0,0.0,1.0,1.0,79.0,7.0,3.0,0.0,5.0,6.0,3.0,0.0,0.0,0.0,2.0,6.0,6.0,50.0 +Edoardo Goldaniga,it ITA,DF,Cagliari,29-332,1993,1.0,1.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,17.0,82.4,227.0,94.0,7.0,7.0,100.0,6.0,7.0,85.7,1.0,3.0,33.3,0.0,1.0,1.0,0.0,1.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,22.0,2.0,9.0,11.0,2.0,0.0,22.0,9.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 +Joan Gonzàlez,es ESP,MF,Lecce,21-241,2002,3.0,2.0,156.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,36.0,45.0,80.0,618.0,149.0,20.0,25.0,80.0,11.0,14.0,78.6,5.0,5.0,100.0,2.0,4.0,1.0,0.0,6.0,44.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.46,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,62.0,1.0,7.0,38.0,18.0,1.0,62.0,41.0,4.0,1.0,0.0,41.0,1.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,7.0,3.0,4.0,42.9 +Nicolás González,ar ARG,FW,Fiorentina,25-177,1998,5.0,5.0,367.0,3.0,1.0,0.0,0.0,0.0,0.0,0.74,0.25,0.98,0.74,0.98,0.9,0.9,0.22,0.22,4.1,4.0,0.0,36.4,0.98,0.27,0.75,0.08,2.1,2.1,100.0,144.0,69.4,1930.0,444.0,45.0,64.0,70.3,37.0,48.0,77.1,17.0,22.0,77.3,2.0,9.0,3.0,0.0,18.0,139.0,5.0,1.0,1.0,1.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,7.0,1.72,3.0,0.0,3.0,1.0,2.0,0.49,1.0,0.0,1.0,0.0,0.0,7.0,4.0,5.0,2.0,0.0,6.0,1.0,5.0,2.0,1.0,0.0,199.0,7.0,24.0,99.0,81.0,22.0,199.0,128.0,10.0,11.0,3.0,153.0,9.0,4.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,12.0,15.0,4.0,78.9 +Alberto Grassi,it ITA,MF,Empoli,28-207,1995,5.0,3.0,317.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,3.5,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,135.0,160.0,84.4,2388.0,814.0,56.0,62.0,90.3,61.0,72.0,84.7,13.0,18.0,72.2,1.0,20.0,1.0,0.0,14.0,152.0,8.0,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,3.0,0.85,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,5.0,2.0,3.0,7.0,4.0,0.0,203.0,10.0,38.0,144.0,22.0,3.0,203.0,115.0,3.0,1.0,0.0,122.0,5.0,0.0,0.0,6.0,7.0,0.0,0.0,0.0,1.0,20.0,7.0,5.0,58.3 +Mattéo Guendouzi,fr FRA,MF,Lazio,24-169,1999,4.0,1.0,110.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.1,-0.1,36.0,45.0,80.0,535.0,112.0,25.0,27.0,92.6,6.0,7.0,85.7,3.0,5.0,60.0,0.0,4.0,2.0,0.0,3.0,44.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,50.0,0.0,6.0,27.0,18.0,1.0,50.0,32.0,4.0,2.0,0.0,40.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,2.0,4.0,33.3 +Axel Guessand,fr FRA,DF,Udinese,18-328,2004,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,21.0,27.0,77.8,471.0,141.0,5.0,7.0,71.4,14.0,16.0,87.5,2.0,4.0,50.0,0.0,3.0,0.0,0.0,1.0,27.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,33.0,1.0,10.0,22.0,1.0,1.0,33.0,21.0,1.0,0.0,0.0,25.0,3.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 +Albert Guðmundsson,is ISL,"FW,MF",Genoa,26-107,1997,6.0,6.0,537.0,1.0,0.0,0.0,0.0,0.0,0.0,0.17,0.0,0.17,0.17,0.17,0.3,0.3,0.06,0.06,6.0,1.0,0.0,12.5,0.17,0.13,1.0,0.04,0.7,0.7,134.0,178.0,75.3,2289.0,707.0,63.0,69.0,91.3,49.0,60.0,81.7,16.0,30.0,53.3,11.0,9.0,7.0,4.0,16.0,152.0,24.0,11.0,0.0,0.0,24.0,10.0,2.0,7.0,0.0,1.0,2.0,8.0,19.0,3.18,9.0,8.0,1.0,1.0,4.0,0.67,2.0,2.0,0.0,0.0,0.0,8.0,4.0,5.0,2.0,1.0,4.0,0.0,4.0,4.0,1.0,0.0,244.0,5.0,42.0,116.0,97.0,9.0,244.0,147.0,18.0,14.0,3.0,162.0,17.0,7.0,0.0,6.0,7.0,1.0,0.0,0.0,0.0,29.0,1.0,4.0,20.0 +Emmanuel Gyasi,gh GHA,FW,Empoli,29-262,1994,4.0,2.0,163.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.53,0.53,1.8,1.0,0.0,33.3,0.55,0.0,0.0,0.32,-1.0,-1.0,24.0,32.0,75.0,282.0,51.0,18.0,22.0,81.8,4.0,6.0,66.7,0.0,1.0,0.0,0.0,1.0,1.0,0.0,2.0,32.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,1.66,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,53.0,2.0,6.0,22.0,25.0,5.0,53.0,38.0,4.0,4.0,1.0,44.0,3.0,6.0,0.0,5.0,5.0,2.0,0.0,0.0,0.0,5.0,1.0,5.0,16.7 +Norbert Gyömbér,sk SVK,DF,Salernitana,31-089,1992,6.0,6.0,495.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,5.5,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.1,-0.1,172.0,204.0,84.3,3029.0,1194.0,63.0,69.0,91.3,94.0,106.0,88.7,11.0,22.0,50.0,1.0,7.0,0.0,0.0,10.0,195.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.18,1.0,0.0,0.0,0.0,1.0,0.18,1.0,0.0,0.0,0.0,0.0,12.0,8.0,9.0,3.0,0.0,13.0,10.0,3.0,13.0,25.0,0.0,279.0,42.0,161.0,113.0,7.0,3.0,279.0,109.0,0.0,0.0,0.0,112.0,5.0,1.0,0.0,13.0,4.0,0.0,0.0,0.0,0.0,40.0,8.0,14.0,36.4 +Nicolas Haas,ch SUI,MF,Empoli,27-250,1996,1.0,1.0,90.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.1,0.1,1.0,1.0,0.0,100.0,1.0,0.0,0.0,0.1,-0.1,-0.1,46.0,51.0,90.2,865.0,312.0,20.0,21.0,95.2,21.0,21.0,100.0,5.0,6.0,83.3,0.0,7.0,1.0,0.0,6.0,50.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,1.0,2.0,2.0,1.0,0.0,1.0,1.0,1.0,0.0,63.0,4.0,15.0,36.0,12.0,1.0,63.0,35.0,0.0,1.0,0.0,41.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,9.0,3.0,0.0,100.0 +Abdou Harroui,nl NED,MF,Frosinone,25-260,1998,3.0,3.0,255.0,2.0,0.0,1.0,1.0,0.0,0.0,0.71,0.0,0.71,0.35,0.35,1.5,0.7,0.53,0.25,2.8,2.0,0.0,28.6,0.71,0.14,0.5,0.1,0.5,0.3,78.0,90.0,86.7,1088.0,239.0,46.0,49.0,93.9,22.0,27.0,81.5,4.0,5.0,80.0,3.0,5.0,2.0,0.0,8.0,82.0,6.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,10.0,3.53,8.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,5.0,1.0,5.0,0.0,4.0,0.0,4.0,2.0,0.0,0.0,130.0,1.0,19.0,68.0,46.0,11.0,129.0,70.0,9.0,7.0,2.0,82.0,6.0,2.0,0.0,3.0,3.0,1.0,0.0,0.0,0.0,16.0,2.0,3.0,40.0 +Hans Hateboer,nl NED,DF,Atalanta,29-264,1994,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.09,0.09,0.5,1.0,0.0,100.0,2.0,0.0,0.0,0.05,0.0,0.0,5.0,10.0,50.0,72.0,12.0,3.0,5.0,60.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,8.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,14.0,1.0,5.0,5.0,4.0,1.0,14.0,6.0,1.0,0.0,1.0,6.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Pantelis Hatzidiakos,gr GRE,DF,Cagliari,26-255,1997,3.0,3.0,232.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,70.0,89.0,78.7,1270.0,458.0,27.0,28.0,96.4,36.0,44.0,81.8,6.0,14.0,42.9,1.0,3.0,0.0,0.0,5.0,81.0,7.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,3.0,2.0,0.0,5.0,3.0,2.0,3.0,5.0,0.0,112.0,15.0,62.0,42.0,8.0,1.0,112.0,56.0,0.0,1.0,0.0,57.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,17.0,1.0,3.0,25.0 +Silvan Hefti,ch SUI,"DF,MF",Genoa,25-340,1997,4.0,1.0,99.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,20.0,33.0,60.6,282.0,107.0,13.0,18.0,72.2,5.0,8.0,62.5,1.0,3.0,33.3,0.0,1.0,0.0,0.0,1.0,24.0,9.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,2.0,3.0,1.0,2.0,0.0,2.0,0.0,1.0,0.0,46.0,3.0,17.0,21.0,8.0,0.0,46.0,10.0,0.0,0.0,0.0,14.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,50.0 +Liam Henderson,sct SCO,MF,Empoli,27-158,1996,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,5.0,40.0,40.0,0.0,1.0,2.0,50.0,1.0,1.0,100.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,4.0,1.0,0.0,5.0,3.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Matheus Henrique,br BRA,MF,Sassuolo,25-285,1997,6.0,6.0,540.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.17,0.17,0.0,0.17,0.2,0.2,0.03,0.03,6.0,1.0,0.0,33.3,0.17,0.0,0.0,0.07,-0.2,-0.2,204.0,236.0,86.4,3805.0,1346.0,83.0,95.0,87.4,83.0,88.0,94.3,29.0,38.0,76.3,7.0,24.0,3.0,0.0,22.0,229.0,6.0,4.0,1.0,8.0,2.0,1.0,1.0,0.0,0.0,1.0,1.0,3.0,14.0,2.33,13.0,1.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,13.0,9.0,6.0,7.0,0.0,3.0,1.0,2.0,6.0,7.0,1.0,279.0,20.0,72.0,150.0,62.0,2.0,279.0,168.0,9.0,7.0,0.0,198.0,5.0,6.0,0.0,2.0,8.0,0.0,0.0,0.0,0.0,33.0,3.0,2.0,60.0 +Thomas Henry,fr FRA,MF,Hellas Verona,29-010,1994,1.0,0.0,18.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,7.0,57.1,46.0,25.0,3.0,5.0,60.0,1.0,1.0,100.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,0.0,5.0,3.0,0.0,8.0,5.0,0.0,1.0,0.0,7.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,33.3 +Theo Hernández,fr FRA,DF,Milan,25-359,1997,5.0,5.0,439.0,1.0,0.0,0.0,0.0,3.0,0.0,0.21,0.0,0.21,0.21,0.21,0.5,0.5,0.11,0.11,4.9,2.0,0.0,33.3,0.41,0.17,0.5,0.09,0.5,0.5,310.0,365.0,84.9,4552.0,1204.0,166.0,180.0,92.2,118.0,126.0,93.7,13.0,27.0,48.1,7.0,19.0,7.0,2.0,22.0,321.0,42.0,19.0,0.0,2.0,7.0,0.0,0.0,0.0,0.0,23.0,2.0,10.0,17.0,3.49,13.0,0.0,2.0,0.0,3.0,0.62,2.0,0.0,1.0,0.0,0.0,2.0,2.0,2.0,0.0,0.0,3.0,2.0,1.0,4.0,3.0,0.0,400.0,7.0,98.0,232.0,75.0,11.0,400.0,288.0,17.0,13.0,3.0,296.0,4.0,2.0,0.0,5.0,5.0,0.0,0.0,1.0,0.0,29.0,4.0,0.0,100.0 +Isak Hien,se SWE,DF,Hellas Verona,24-260,1999,4.0,4.0,353.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.06,0.06,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.23,-0.2,-0.2,109.0,129.0,84.5,2334.0,876.0,28.0,35.0,80.0,67.0,72.0,93.1,13.0,21.0,61.9,0.0,7.0,0.0,0.0,8.0,123.0,6.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,5.0,4.0,5.0,0.0,2.0,1.0,1.0,3.0,10.0,0.0,167.0,14.0,89.0,76.0,7.0,2.0,167.0,86.0,5.0,3.0,0.0,69.0,0.0,3.0,0.0,6.0,2.0,0.0,0.0,0.0,0.0,33.0,8.0,9.0,47.1 +Emil Holm,se SWE,"DF,MF",Atalanta,23-140,2000,3.0,1.0,85.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.15,0.15,0.9,1.0,0.0,50.0,1.06,0.0,0.0,0.07,-0.1,-0.1,31.0,42.0,73.8,437.0,216.0,20.0,25.0,80.0,9.0,13.0,69.2,1.0,1.0,100.0,0.0,1.0,0.0,0.0,3.0,32.0,10.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,10.0,0.0,1.0,2.0,2.14,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,2.0,1.0,2.0,0.0,2.0,1.0,2.0,0.0,65.0,3.0,18.0,26.0,22.0,2.0,65.0,33.0,1.0,1.0,0.0,34.0,5.0,7.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,7.0,5.0,3.0,62.5 +Martin Hongla,cm CMR,MF,Hellas Verona,25-198,1998,6.0,6.0,477.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,5.3,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,143.0,178.0,80.3,2746.0,676.0,49.0,62.0,79.0,73.0,80.0,91.3,18.0,32.0,56.3,0.0,15.0,0.0,0.0,21.0,169.0,8.0,6.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,7.0,1.32,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,5.0,4.0,7.0,1.0,2.0,2.0,0.0,3.0,8.0,0.0,215.0,13.0,50.0,143.0,23.0,0.0,215.0,134.0,2.0,5.0,0.0,127.0,3.0,4.0,0.0,3.0,3.0,1.0,0.0,0.0,0.0,29.0,1.0,4.0,20.0 +Sydney van Hooijdonk,nl NED,FW,Bologna,23-236,2000,2.0,0.0,20.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.19,0.19,0.2,0.0,1.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,2.0,3.0,66.7,24.0,0.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,9.0,2.0,2.0,5.0,2.0,0.0,9.0,3.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 +Elseid Hysaj,al ALB,DF,Lazio,29-222,1994,4.0,3.0,191.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,111.0,124.0,89.5,1669.0,685.0,64.0,68.0,94.1,33.0,37.0,89.2,6.0,9.0,66.7,1.0,11.0,0.0,0.0,8.0,112.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,0.0,1.0,3.0,1.41,2.0,0.0,0.0,1.0,1.0,0.47,1.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,2.0,0.0,5.0,1.0,4.0,2.0,8.0,0.0,144.0,9.0,54.0,75.0,16.0,2.0,144.0,80.0,4.0,1.0,0.0,99.0,0.0,1.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,11.0,5.0,1.0,83.3 +Jonathan Ikone,fr FRA,FW,Fiorentina,25-151,1998,1.0,0.0,30.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,8.0,87.5,96.0,9.0,4.0,5.0,80.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,11.0,0.0,2.0,5.0,5.0,1.0,11.0,9.0,1.0,1.0,1.0,8.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Chukwubuikem Ikwuemesi,ng NGA,"FW,DF",Salernitana,22-056,2001,4.0,0.0,105.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.21,0.21,1.2,1.0,0.0,25.0,0.86,0.0,0.0,0.06,-0.2,-0.2,14.0,18.0,77.8,173.0,39.0,7.0,10.0,70.0,5.0,5.0,100.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,3.0,16.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.71,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,39.0,2.0,2.0,19.0,18.0,10.0,39.0,26.0,3.0,2.0,2.0,33.0,7.0,3.0,0.0,4.0,1.0,1.0,0.0,0.0,0.0,1.0,3.0,5.0,37.5 +Ivan Ilić,rs SRB,MF,Torino,22-197,2001,5.0,3.0,272.0,0.0,2.0,0.0,0.0,1.0,0.0,0.0,0.66,0.66,0.0,0.66,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,154.0,186.0,82.8,2682.0,832.0,70.0,78.0,89.7,67.0,77.0,87.0,14.0,21.0,66.7,6.0,18.0,3.0,0.0,18.0,163.0,21.0,12.0,0.0,1.0,12.0,9.0,9.0,0.0,0.0,0.0,2.0,2.0,9.0,2.98,5.0,4.0,0.0,0.0,2.0,0.66,1.0,1.0,0.0,0.0,0.0,4.0,3.0,1.0,2.0,1.0,1.0,0.0,1.0,2.0,3.0,0.0,205.0,5.0,29.0,138.0,41.0,1.0,205.0,97.0,6.0,5.0,0.0,133.0,3.0,4.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,22.0,3.0,2.0,60.0 +Samuel Iling-Junior,eng ENG,DF,Juventus,19-361,2003,3.0,0.0,91.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.99,0.99,0.0,0.99,0.1,0.1,0.1,0.1,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.11,-0.1,-0.1,33.0,44.0,75.0,426.0,88.0,24.0,25.0,96.0,7.0,11.0,63.6,1.0,4.0,25.0,1.0,1.0,1.0,1.0,2.0,39.0,5.0,0.0,0.0,0.0,5.0,2.0,2.0,0.0,0.0,3.0,0.0,4.0,4.0,3.96,4.0,0.0,0.0,0.0,2.0,1.98,2.0,0.0,0.0,0.0,0.0,5.0,4.0,4.0,1.0,0.0,4.0,1.0,3.0,1.0,1.0,0.0,67.0,2.0,24.0,20.0,23.0,2.0,67.0,30.0,5.0,1.0,0.0,39.0,4.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,3.0,2.0,1.0,66.7 +Ciro Immobile,it ITA,FW,Lazio,33-222,1990,6.0,6.0,500.0,2.0,0.0,1.0,1.0,2.0,0.0,0.36,0.0,0.36,0.18,0.18,2.1,1.3,0.37,0.23,5.6,3.0,0.0,37.5,0.54,0.13,0.33,0.16,-0.1,-0.3,111.0,148.0,75.0,1390.0,226.0,66.0,85.0,77.6,32.0,42.0,76.2,3.0,5.0,60.0,5.0,4.0,4.0,0.0,11.0,135.0,13.0,1.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,5.0,6.0,1.08,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,1.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,200.0,1.0,13.0,78.0,111.0,31.0,199.0,100.0,3.0,4.0,2.0,152.0,16.0,6.0,0.0,4.0,8.0,3.0,0.0,0.0,0.0,7.0,1.0,3.0,25.0 +Gino Infantino,ar ARG,MF,Fiorentina,20-134,2003,3.0,0.0,47.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.04,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,25.0,31.0,80.6,443.0,83.0,13.0,15.0,86.7,9.0,11.0,81.8,3.0,3.0,100.0,0.0,3.0,0.0,0.0,5.0,28.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,3.75,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,36.0,0.0,1.0,24.0,11.0,1.0,36.0,31.0,0.0,1.0,0.0,29.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,3.0,25.0 +Gustav Isaksen,dk DEN,FW,Lazio,22-164,2001,5.0,1.0,128.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,38.0,57.9,345.0,31.0,11.0,16.0,68.8,10.0,13.0,76.9,1.0,4.0,25.0,1.0,0.0,0.0,0.0,0.0,38.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,0.71,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,51.0,3.0,8.0,15.0,29.0,9.0,51.0,36.0,5.0,5.0,4.0,37.0,2.0,3.0,0.0,1.0,3.0,1.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Ardian Ismajli,al ALB,DF,Empoli,27-000,1996,4.0,3.0,275.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,98.0,130.0,75.4,1863.0,745.0,32.0,38.0,84.2,60.0,65.0,92.3,6.0,22.0,27.3,1.0,4.0,0.0,0.0,5.0,120.0,10.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,5.0,3.0,2.0,13.0,1.0,160.0,28.0,107.0,52.0,2.0,2.0,160.0,70.0,0.0,0.0,0.0,77.0,1.0,0.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,14.0,10.0,6.0,62.5 +Armando Izzo,it ITA,DF,Monza,31-212,1992,5.0,5.0,408.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,301.0,332.0,90.7,5512.0,1588.0,116.0,122.0,95.1,157.0,168.0,93.5,26.0,38.0,68.4,1.0,21.0,2.0,0.0,19.0,315.0,17.0,13.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,4.0,0.88,4.0,0.0,0.0,0.0,1.0,0.22,1.0,0.0,0.0,0.0,0.0,11.0,7.0,6.0,5.0,0.0,5.0,3.0,2.0,5.0,7.0,1.0,366.0,32.0,169.0,169.0,30.0,4.0,366.0,229.0,5.0,5.0,0.0,279.0,4.0,0.0,0.0,11.0,8.0,0.0,0.0,0.0,0.0,35.0,0.0,4.0,0.0 +Filip Jagiełło,pl POL,MF,Genoa,26-053,1997,2.0,0.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,17.0,88.2,287.0,13.0,5.0,5.0,100.0,9.0,9.0,100.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,2.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,2.73,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,20.0,2.0,6.0,8.0,7.0,0.0,20.0,16.0,1.0,3.0,0.0,16.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0 +Jakub Jankto,cz CZE,"MF,FW",Cagliari,27-254,1996,3.0,2.0,153.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,1.7,1.0,0.0,100.0,0.59,0.0,0.0,0.09,-0.1,-0.1,28.0,43.0,65.1,396.0,95.0,16.0,16.0,100.0,9.0,17.0,52.9,1.0,5.0,20.0,1.0,2.0,1.0,0.0,4.0,39.0,4.0,0.0,0.0,0.0,4.0,2.0,1.0,1.0,0.0,2.0,0.0,3.0,5.0,2.94,4.0,0.0,0.0,0.0,1.0,0.59,1.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,0.0,0.0,0.0,2.0,9.0,0.0,67.0,7.0,21.0,25.0,21.0,2.0,67.0,31.0,2.0,3.0,0.0,36.0,2.0,1.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,6.0,2.0,2.0,50.0 +Juan Jesus,br BRA,DF,Napoli,32-112,1991,4.0,4.0,359.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.08,0.08,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.31,-0.3,-0.3,299.0,319.0,93.7,5315.0,1777.0,114.0,117.0,97.4,163.0,169.0,96.4,18.0,28.0,64.3,2.0,4.0,0.0,0.0,12.0,309.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,0.75,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,5.0,8.0,1.0,1.0,3.0,2.0,1.0,4.0,9.0,0.0,349.0,18.0,150.0,190.0,9.0,3.0,349.0,238.0,1.0,1.0,0.0,259.0,1.0,0.0,0.0,2.0,3.0,0.0,0.0,0.0,0.0,26.0,6.0,5.0,54.5 +Luka Jović,rs SRB,FW,Milan,25-281,1997,2.0,0.0,40.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,11.0,72.7,137.0,43.0,3.0,5.0,60.0,5.0,6.0,83.3,0.0,0.0,0.0,1.0,1.0,0.0,0.0,2.0,9.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.25,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,16.0,2.0,2.0,11.0,3.0,0.0,16.0,11.0,0.0,0.0,0.0,13.0,1.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,50.0 +Mohamed Kaba,fr FRA,MF,Lecce,21-338,2001,6.0,3.0,321.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.6,1.0,0.0,100.0,0.28,0.0,0.0,0.06,-0.1,-0.1,89.0,109.0,81.7,1486.0,393.0,41.0,49.0,83.7,40.0,48.0,83.3,6.0,7.0,85.7,1.0,12.0,0.0,0.0,15.0,107.0,2.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.4,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,3.0,2.0,1.0,7.0,0.0,7.0,2.0,3.0,0.0,154.0,6.0,24.0,86.0,46.0,3.0,154.0,89.0,5.0,2.0,1.0,103.0,16.0,6.0,1.0,10.0,4.0,0.0,0.0,0.0,0.0,17.0,11.0,7.0,61.1 +Christian Kabasele,be BEL,DF,Udinese,32-218,1991,4.0,4.0,307.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.4,1.0,0.0,50.0,0.29,0.0,0.0,0.07,-0.1,-0.1,136.0,166.0,81.9,2431.0,765.0,52.0,60.0,86.7,68.0,78.0,87.2,11.0,19.0,57.9,0.0,14.0,0.0,0.0,12.0,148.0,18.0,5.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,2.0,0.59,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,7.0,3.0,4.0,4.0,8.0,0.0,193.0,25.0,81.0,102.0,11.0,2.0,193.0,107.0,4.0,2.0,0.0,117.0,3.0,0.0,0.0,8.0,2.0,0.0,0.0,0.0,0.0,14.0,10.0,2.0,83.3 +Pierre Kalulu,fr FRA,DF,Milan,23-117,2000,2.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,15.0,80.0,253.0,113.0,2.0,3.0,66.7,7.0,7.0,100.0,2.0,3.0,66.7,0.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,1.0,19.0,4.0,15.0,4.0,0.0,0.0,19.0,12.0,0.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 +Daichi Kamada,jp JPN,MF,Lazio,27-056,1996,4.0,4.0,260.0,1.0,1.0,0.0,0.0,0.0,0.0,0.35,0.35,0.69,0.35,0.69,0.4,0.4,0.14,0.14,2.9,2.0,0.0,28.6,0.69,0.14,0.5,0.06,0.6,0.6,110.0,134.0,82.1,1610.0,259.0,65.0,71.0,91.5,40.0,46.0,87.0,3.0,9.0,33.3,4.0,10.0,1.0,0.0,11.0,132.0,2.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,5.0,1.73,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,6.0,1.0,1.0,4.0,1.0,3.0,1.0,2.0,0.0,164.0,6.0,27.0,91.0,46.0,9.0,164.0,89.0,2.0,0.0,2.0,124.0,3.0,4.0,0.0,10.0,2.0,0.0,0.0,0.0,0.0,6.0,1.0,2.0,33.3 +Hassane Kamara,ci CIV,DF,Udinese,29-209,1994,6.0,6.0,421.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.03,0.03,4.7,1.0,0.0,20.0,0.21,0.0,0.0,0.03,-0.2,-0.2,134.0,174.0,77.0,2325.0,983.0,58.0,66.0,87.9,54.0,69.0,78.3,16.0,28.0,57.1,6.0,9.0,10.0,7.0,18.0,142.0,30.0,1.0,0.0,0.0,17.0,0.0,0.0,0.0,0.0,29.0,2.0,2.0,14.0,2.99,12.0,1.0,0.0,0.0,1.0,0.21,1.0,0.0,0.0,0.0,0.0,6.0,5.0,4.0,2.0,0.0,3.0,0.0,3.0,8.0,10.0,0.0,230.0,10.0,61.0,88.0,85.0,8.0,230.0,130.0,11.0,8.0,1.0,132.0,7.0,5.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,27.0,3.0,3.0,50.0 +Yann Karamoh,fr FRA,MF,Torino,25-084,1998,4.0,1.0,104.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.04,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,24.0,32.0,75.0,381.0,78.0,13.0,17.0,76.5,9.0,11.0,81.8,2.0,3.0,66.7,0.0,2.0,0.0,0.0,2.0,31.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,2.0,1.73,0.0,0.0,0.0,1.0,1.0,0.87,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,49.0,1.0,4.0,21.0,28.0,4.0,49.0,36.0,7.0,6.0,2.0,40.0,5.0,4.0,0.0,1.0,3.0,1.0,0.0,0.0,0.0,5.0,1.0,1.0,50.0 +Jesper Karlsson,se SWE,FW,Bologna,25-067,1998,5.0,4.0,314.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.12,0.12,3.5,4.0,1.0,66.7,1.15,0.0,0.0,0.07,-0.4,-0.4,92.0,137.0,67.2,1572.0,402.0,43.0,55.0,78.2,35.0,47.0,74.5,10.0,23.0,43.5,4.0,8.0,7.0,1.0,16.0,119.0,17.0,4.0,0.0,0.0,19.0,11.0,5.0,4.0,0.0,2.0,1.0,4.0,10.0,2.87,7.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,4.0,0.0,4.0,3.0,1.0,0.0,166.0,3.0,19.0,61.0,89.0,10.0,166.0,106.0,11.0,6.0,5.0,115.0,4.0,6.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,13.0,0.0,2.0,0.0 +Rick Karsdorp,nl NED,"DF,FW",Roma,28-231,1995,2.0,0.0,66.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,34.0,43.0,79.1,600.0,223.0,15.0,16.0,93.8,13.0,16.0,81.3,4.0,7.0,57.1,1.0,1.0,2.0,1.0,2.0,35.0,8.0,1.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,3.0,4.09,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,46.0,2.0,14.0,14.0,19.0,1.0,46.0,28.0,3.0,2.0,0.0,29.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 +Grigoris Kastanos,cy CYP,"MF,DF",Salernitana,25-243,1998,6.0,5.0,426.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.09,0.09,4.7,2.0,0.0,22.2,0.42,0.0,0.0,0.05,-0.4,-0.4,150.0,211.0,71.1,2469.0,737.0,69.0,81.0,85.2,44.0,66.0,66.7,21.0,33.0,63.6,6.0,18.0,2.0,1.0,17.0,171.0,40.0,3.0,1.0,3.0,9.0,11.0,0.0,1.0,0.0,26.0,0.0,9.0,15.0,3.16,7.0,7.0,0.0,1.0,1.0,0.21,0.0,1.0,0.0,0.0,0.0,8.0,7.0,4.0,1.0,3.0,3.0,1.0,2.0,6.0,3.0,0.0,264.0,4.0,50.0,119.0,100.0,7.0,264.0,147.0,10.0,6.0,3.0,163.0,7.0,11.0,0.0,5.0,9.0,0.0,0.0,0.0,0.0,26.0,5.0,15.0,25.0 +Michael Kayode,it ITA,DF,Fiorentina,19-082,2004,3.0,1.0,211.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,104.0,135.0,77.0,1949.0,660.0,49.0,58.0,84.5,32.0,37.0,86.5,19.0,30.0,63.3,2.0,3.0,2.0,1.0,5.0,111.0,24.0,1.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,23.0,0.0,5.0,4.0,1.71,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,4.0,5.0,1.0,1.0,3.0,2.0,1.0,2.0,9.0,0.0,171.0,17.0,78.0,66.0,30.0,4.0,171.0,85.0,7.0,4.0,2.0,92.0,0.0,4.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,22.0,4.0,5.0,44.4 +Moise Kean,it ITA,"FW,MF",Juventus,23-214,2000,3.0,0.0,30.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.29,0.29,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,3.0,5.0,60.0,60.0,21.0,2.0,3.0,66.7,0.0,0.0,0.0,1.0,1.0,100.0,1.0,1.0,0.0,0.0,2.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,5.81,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,5.0,5.0,1.0,10.0,5.0,2.0,0.0,1.0,6.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 +Simon Kjær,dk DEN,DF,Milan,34-188,1989,4.0,2.0,195.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,126.0,153.0,82.4,2497.0,1093.0,38.0,42.0,90.5,71.0,78.0,91.0,15.0,27.0,55.6,1.0,9.0,1.0,0.0,16.0,148.0,5.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.92,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,3.0,2.0,1.0,4.0,1.0,3.0,2.0,11.0,0.0,177.0,14.0,78.0,98.0,4.0,0.0,177.0,121.0,2.0,2.0,0.0,114.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,23.0,7.0,5.0,58.3 +Davy Klaassen,nl NED,MF,Inter,30-221,1993,1.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,100.0,43.0,13.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,2.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Sead Kolašinac,ba BIH,DF,Atalanta,30-102,1993,6.0,6.0,539.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,0.0,100.0,0.17,0.0,0.0,0.03,0.0,0.0,261.0,317.0,82.3,4030.0,1348.0,135.0,151.0,89.4,107.0,123.0,87.0,11.0,24.0,45.8,2.0,17.0,2.0,0.0,21.0,294.0,20.0,5.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,15.0,3.0,7.0,6.0,1.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,6.0,5.0,3.0,0.0,3.0,0.0,3.0,4.0,7.0,0.0,345.0,13.0,143.0,154.0,49.0,2.0,345.0,204.0,8.0,9.0,1.0,222.0,5.0,1.0,0.0,5.0,8.0,0.0,0.0,0.0,0.0,42.0,9.0,12.0,42.9 +Teun Koopmeiners,nl NED,"MF,FW",Atalanta,25-214,1998,6.0,6.0,519.0,2.0,1.0,0.0,0.0,0.0,0.0,0.35,0.17,0.52,0.35,0.52,0.8,0.8,0.15,0.15,5.8,4.0,0.0,30.8,0.69,0.15,0.5,0.07,1.2,1.2,226.0,300.0,75.3,4131.0,1566.0,94.0,109.0,86.2,93.0,112.0,83.0,30.0,54.0,55.6,17.0,26.0,13.0,5.0,38.0,260.0,35.0,10.0,0.0,6.0,31.0,18.0,6.0,7.0,0.0,1.0,5.0,6.0,30.0,5.2,20.0,6.0,0.0,0.0,2.0,0.35,2.0,0.0,0.0,0.0,0.0,6.0,3.0,3.0,2.0,1.0,4.0,1.0,3.0,1.0,7.0,0.0,361.0,9.0,60.0,157.0,150.0,18.0,361.0,209.0,24.0,11.0,5.0,255.0,13.0,2.0,0.0,12.0,7.0,1.0,0.0,0.0,0.0,33.0,2.0,6.0,25.0 +Filip Kostić,rs SRB,DF,Juventus,30-333,1992,4.0,3.0,192.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.1,1.0,0.0,25.0,0.47,0.0,0.0,0.02,-0.1,-0.1,79.0,97.0,81.4,1324.0,393.0,38.0,42.0,90.5,35.0,39.0,89.7,4.0,9.0,44.4,4.0,2.0,4.0,3.0,10.0,79.0,18.0,2.0,0.0,0.0,12.0,5.0,0.0,5.0,0.0,11.0,0.0,5.0,10.0,4.69,5.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,3.0,0.0,2.0,7.0,2.0,5.0,0.0,2.0,0.0,124.0,4.0,27.0,42.0,57.0,7.0,124.0,56.0,7.0,7.0,3.0,80.0,2.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Christian Kouamé,ci CIV,FW,Fiorentina,25-298,1997,4.0,2.0,145.0,1.0,0.0,0.0,0.0,0.0,0.0,0.62,0.0,0.62,0.62,0.62,0.4,0.4,0.25,0.25,1.6,2.0,0.0,40.0,1.24,0.2,0.5,0.08,0.6,0.6,49.0,65.0,75.4,660.0,141.0,33.0,40.0,82.5,14.0,18.0,77.8,2.0,4.0,50.0,1.0,1.0,1.0,0.0,5.0,65.0,0.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.62,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,0.0,0.0,93.0,0.0,13.0,41.0,41.0,8.0,93.0,61.0,2.0,3.0,1.0,66.0,5.0,3.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,12.0,8.0,8.0,50.0 +Viktor Kovalenko,ua UKR,MF,Empoli,27-228,1996,1.0,0.0,19.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,14.0,64.3,121.0,34.0,5.0,7.0,71.4,4.0,6.0,66.7,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,14.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,18.0,1.0,3.0,9.0,6.0,0.0,18.0,9.0,1.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Thomas Kristensen,dk DEN,DF,Udinese,21-256,2002,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,66.0,73.0,90.4,1112.0,489.0,27.0,29.0,93.1,31.0,34.0,91.2,5.0,6.0,83.3,0.0,1.0,0.0,0.0,3.0,69.0,4.0,3.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,1.0,1.0,0.0,4.0,12.0,0.0,92.0,18.0,53.0,40.0,0.0,0.0,92.0,50.0,1.0,0.0,0.0,50.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,9.0,5.0,1.0,83.3 +Nikola Krstović,me MNE,FW,Lecce,23-178,2000,5.0,4.0,342.0,3.0,0.0,1.0,1.0,1.0,0.0,0.79,0.0,0.79,0.53,0.53,1.7,0.9,0.46,0.25,3.8,3.0,1.0,23.1,0.79,0.15,0.67,0.07,1.3,1.1,57.0,87.0,65.5,759.0,105.0,32.0,44.0,72.7,13.0,21.0,61.9,5.0,8.0,62.5,4.0,6.0,1.0,0.0,6.0,81.0,6.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,9.0,2.37,8.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,2.0,2.0,0.0,2.0,1.0,1.0,0.0,5.0,0.0,133.0,7.0,17.0,73.0,44.0,14.0,132.0,75.0,5.0,3.0,1.0,98.0,14.0,4.0,0.0,3.0,10.0,1.0,0.0,0.0,0.0,15.0,9.0,4.0,69.2 +Rade Krunić,ba BIH,MF,Milan,29-358,1993,5.0,5.0,424.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,249.0,269.0,92.6,3793.0,761.0,130.0,137.0,94.9,97.0,105.0,92.4,14.0,15.0,93.3,2.0,8.0,2.0,0.0,11.0,254.0,15.0,13.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,5.0,1.06,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,2.0,2.0,1.0,2.0,0.0,2.0,7.0,11.0,0.0,304.0,17.0,77.0,195.0,33.0,3.0,304.0,176.0,4.0,6.0,0.0,212.0,5.0,1.0,0.0,7.0,6.0,0.0,0.0,0.0,0.0,23.0,3.0,4.0,42.9 +Berkan Kutlu,tr TUR,MF,Genoa,25-248,1998,2.0,0.0,94.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.09,0.09,1.0,1.0,0.0,50.0,0.96,0.0,0.0,0.04,-0.1,-0.1,17.0,25.0,68.0,300.0,102.0,10.0,13.0,76.9,4.0,5.0,80.0,2.0,4.0,50.0,2.0,2.0,1.0,1.0,1.0,24.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,2.87,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,4.0,0.0,0.0,1.0,0.0,1.0,1.0,3.0,0.0,41.0,3.0,16.0,18.0,8.0,1.0,41.0,17.0,3.0,0.0,0.0,21.0,0.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,3.0,1.0,0.0,100.0 +Khvicha Kvaratskhelia,ge GEO,FW,Napoli,22-230,2001,5.0,4.0,340.0,1.0,2.0,0.0,0.0,1.0,0.0,0.26,0.53,0.79,0.26,0.79,2.3,2.3,0.61,0.61,3.8,6.0,1.0,28.6,1.59,0.05,0.17,0.11,-1.3,-1.3,121.0,155.0,78.1,1769.0,396.0,68.0,77.0,88.3,39.0,46.0,84.8,7.0,18.0,38.9,8.0,3.0,8.0,0.0,14.0,147.0,7.0,0.0,1.0,2.0,8.0,2.0,1.0,0.0,0.0,5.0,1.0,5.0,19.0,5.03,11.0,0.0,2.0,2.0,4.0,1.06,1.0,0.0,0.0,1.0,0.0,6.0,4.0,1.0,2.0,3.0,2.0,0.0,2.0,5.0,3.0,0.0,218.0,2.0,10.0,74.0,137.0,39.0,218.0,147.0,30.0,12.0,14.0,170.0,7.0,1.0,0.0,3.0,13.0,2.0,1.0,0.0,0.0,10.0,1.0,2.0,33.3 +Giorgi Kvernadze,ge GEO,FW,Frosinone,20-235,2003,2.0,0.0,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,13.0,84.6,170.0,44.0,6.0,6.0,100.0,5.0,5.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,22.0,0.0,5.0,10.0,7.0,0.0,22.0,15.0,0.0,1.0,0.0,15.0,3.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Giorgos Kyriakopoulos,gr GRE,"DF,MF",Monza,27-237,1996,4.0,3.0,239.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.09,0.09,2.7,1.0,0.0,16.7,0.38,0.0,0.0,0.04,-0.2,-0.2,126.0,151.0,83.4,2104.0,369.0,63.0,67.0,94.0,52.0,61.0,85.2,7.0,11.0,63.6,5.0,4.0,3.0,3.0,4.0,127.0,24.0,1.0,0.0,0.0,11.0,1.0,0.0,1.0,0.0,22.0,0.0,8.0,10.0,3.77,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,2.0,0.0,2.0,3.0,3.0,0.0,173.0,4.0,38.0,77.0,61.0,7.0,173.0,102.0,10.0,3.0,3.0,123.0,2.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,7.0,0.0,3.0,0.0 +Armand Lauriente,fr FRA,"FW,MF",Sassuolo,24-300,1998,6.0,6.0,461.0,1.0,1.0,0.0,0.0,0.0,0.0,0.2,0.2,0.39,0.2,0.39,1.0,1.0,0.19,0.19,5.1,5.0,2.0,31.3,0.98,0.06,0.2,0.07,0.0,0.0,107.0,144.0,74.3,1571.0,596.0,68.0,82.0,82.9,31.0,39.0,79.5,5.0,13.0,38.5,9.0,7.0,8.0,1.0,13.0,131.0,13.0,1.0,1.0,1.0,18.0,12.0,8.0,0.0,0.0,0.0,0.0,6.0,22.0,4.3,14.0,3.0,1.0,2.0,2.0,0.39,1.0,0.0,1.0,0.0,0.0,4.0,2.0,1.0,3.0,0.0,4.0,0.0,4.0,4.0,2.0,0.0,210.0,1.0,16.0,78.0,124.0,17.0,210.0,137.0,20.0,15.0,6.0,139.0,12.0,9.0,0.0,2.0,10.0,2.0,0.0,0.0,0.0,29.0,0.0,2.0,0.0 +Valentino Lazaro,at AUT,DF,Torino,27-190,1996,5.0,3.0,300.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.3,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,139.0,179.0,77.7,2268.0,942.0,68.0,75.0,90.7,55.0,71.0,77.5,10.0,22.0,45.5,7.0,15.0,2.0,1.0,18.0,146.0,32.0,4.0,0.0,0.0,16.0,6.0,4.0,1.0,0.0,22.0,1.0,3.0,9.0,2.71,6.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,3.0,1.0,1.0,0.0,1.0,3.0,9.0,0.0,204.0,9.0,47.0,84.0,76.0,4.0,204.0,114.0,7.0,5.0,2.0,132.0,8.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,16.0,5.0,3.0,62.5 +Darko Lazović,rs SRB,"DF,FW",Hellas Verona,33-015,1990,3.0,1.0,157.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,34.0,59.0,57.6,655.0,262.0,13.0,17.0,76.5,17.0,27.0,63.0,4.0,11.0,36.4,1.0,1.0,2.0,0.0,5.0,47.0,12.0,1.0,0.0,0.0,7.0,1.0,0.0,1.0,0.0,9.0,0.0,2.0,3.0,1.72,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,67.0,1.0,13.0,26.0,28.0,2.0,67.0,34.0,3.0,2.0,1.0,46.0,3.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,50.0 +Manuel Lazzari,it ITA,DF,Lazio,29-305,1993,3.0,3.0,240.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.37,0.37,0.0,0.37,0.1,0.1,0.06,0.06,2.7,1.0,0.0,25.0,0.37,0.0,0.0,0.04,-0.1,-0.1,144.0,171.0,84.2,2220.0,591.0,76.0,81.0,93.8,60.0,68.0,88.2,7.0,10.0,70.0,3.0,8.0,4.0,3.0,13.0,149.0,22.0,1.0,0.0,0.0,14.0,0.0,0.0,0.0,0.0,21.0,0.0,8.0,3.0,1.13,3.0,0.0,0.0,0.0,1.0,0.37,1.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,2.0,1.0,3.0,1.0,2.0,2.0,7.0,0.0,194.0,5.0,35.0,94.0,69.0,8.0,194.0,121.0,19.0,11.0,1.0,134.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,13.0,1.0,2.0,33.3 +Rafael Leão,pt POR,FW,Milan,24-112,1999,6.0,5.0,422.0,3.0,1.0,0.0,0.0,0.0,0.0,0.64,0.21,0.85,0.64,0.85,1.6,1.6,0.35,0.35,4.7,4.0,0.0,40.0,0.85,0.3,0.75,0.16,1.4,1.4,97.0,133.0,72.9,1479.0,397.0,50.0,62.0,80.6,38.0,51.0,74.5,6.0,13.0,46.2,8.0,9.0,8.0,4.0,15.0,129.0,4.0,1.0,2.0,0.0,11.0,0.0,0.0,0.0,0.0,3.0,0.0,2.0,17.0,3.63,13.0,1.0,0.0,1.0,3.0,0.64,2.0,0.0,0.0,1.0,0.0,3.0,3.0,1.0,1.0,1.0,5.0,0.0,5.0,0.0,0.0,0.0,196.0,2.0,9.0,86.0,104.0,34.0,196.0,150.0,23.0,14.0,15.0,169.0,14.0,9.0,0.0,2.0,12.0,3.0,1.0,0.0,0.0,8.0,2.0,6.0,25.0 +Jesper Lindstrøm,dk DEN,"FW,MF",Napoli,23-213,2000,2.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.19,0.19,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,26.0,30.0,86.7,332.0,99.0,16.0,16.0,100.0,7.0,9.0,77.8,1.0,2.0,50.0,1.0,3.0,2.0,1.0,3.0,28.0,2.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,4.0,8.18,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,40.0,0.0,3.0,17.0,20.0,1.0,40.0,23.0,2.0,0.0,0.0,33.0,2.0,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Karol Linetty,pl POL,MF,Torino,28-240,1995,4.0,1.0,155.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,68.0,85.0,80.0,1190.0,303.0,35.0,40.0,87.5,22.0,26.0,84.6,9.0,13.0,69.2,1.0,11.0,1.0,0.0,13.0,80.0,5.0,1.0,0.0,1.0,4.0,3.0,0.0,3.0,0.0,1.0,0.0,1.0,2.0,1.16,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,2.0,1.0,1.0,3.0,1.0,0.0,101.0,1.0,11.0,70.0,22.0,2.0,101.0,65.0,5.0,5.0,0.0,66.0,3.0,2.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,12.0,2.0,0.0,100.0 +Pol Lirola,es ESP,MF,Frosinone,26-048,1997,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,22.5,0.0,22.5,22.5,22.5,0.9,0.9,15.8,15.8,0.0,1.0,0.0,100.0,22.5,1.0,1.0,0.88,0.1,0.1,1.0,3.0,33.3,16.0,5.0,0.0,0.0,0.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,1.0,2.0,1.0,5.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 +Diego Llorente,es ESP,DF,Roma,30-045,1993,6.0,6.0,428.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.21,0.21,0.0,0.21,0.0,0.0,0.0,0.0,4.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,291.0,332.0,87.7,5342.0,1732.0,102.0,107.0,95.3,162.0,179.0,90.5,25.0,37.0,67.6,1.0,9.0,1.0,0.0,15.0,325.0,7.0,4.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,6.0,1.26,5.0,0.0,0.0,1.0,1.0,0.21,1.0,0.0,0.0,0.0,0.0,9.0,5.0,4.0,5.0,0.0,4.0,1.0,3.0,6.0,7.0,0.0,363.0,27.0,177.0,170.0,17.0,1.0,363.0,245.0,8.0,3.0,0.0,271.0,4.0,0.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,19.0,20.0,11.0,64.5 +Stanislav Lobotka,sk SVK,MF,Napoli,28-309,1994,6.0,6.0,511.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.01,0.01,5.7,1.0,0.0,25.0,0.18,0.0,0.0,0.02,-0.1,-0.1,368.0,388.0,94.8,5515.0,1839.0,206.0,214.0,96.3,133.0,140.0,95.0,17.0,22.0,77.3,1.0,35.0,8.0,1.0,34.0,382.0,6.0,6.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,2.82,14.0,0.0,0.0,1.0,2.0,0.35,2.0,0.0,0.0,0.0,0.0,10.0,5.0,2.0,6.0,2.0,4.0,1.0,3.0,2.0,2.0,0.0,425.0,13.0,73.0,279.0,74.0,1.0,425.0,260.0,4.0,10.0,0.0,331.0,4.0,1.0,0.0,6.0,12.0,0.0,0.0,0.0,0.0,44.0,1.0,0.0,100.0 +Manuel Locatelli,it ITA,MF,Juventus,25-265,1998,6.0,6.0,523.0,0.0,1.0,0.0,0.0,2.0,0.0,0.0,0.17,0.17,0.0,0.17,0.0,0.0,0.0,0.0,5.8,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,286.0,343.0,83.4,5476.0,1707.0,116.0,128.0,90.6,125.0,134.0,93.3,38.0,63.0,60.3,7.0,32.0,7.0,2.0,38.0,320.0,21.0,19.0,1.0,7.0,2.0,0.0,0.0,0.0,0.0,2.0,2.0,5.0,10.0,1.72,10.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,13.0,4.0,1.0,11.0,1.0,6.0,3.0,3.0,3.0,8.0,0.0,379.0,14.0,89.0,236.0,56.0,4.0,379.0,209.0,5.0,7.0,1.0,269.0,1.0,4.0,0.0,5.0,4.0,0.0,0.0,0.0,0.0,32.0,3.0,2.0,60.0 +Ruben Loftus-Cheek,eng ENG,MF,Milan,27-250,1996,6.0,5.0,402.0,1.0,1.0,0.0,0.0,2.0,0.0,0.22,0.22,0.45,0.22,0.45,0.5,0.5,0.12,0.12,4.5,2.0,0.0,25.0,0.45,0.13,0.5,0.07,0.5,0.5,141.0,168.0,83.9,1779.0,449.0,99.0,111.0,89.2,32.0,40.0,80.0,3.0,6.0,50.0,5.0,17.0,0.0,0.0,17.0,166.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,10.0,2.24,7.0,0.0,1.0,1.0,4.0,0.9,1.0,0.0,1.0,1.0,0.0,2.0,1.0,1.0,1.0,0.0,6.0,4.0,2.0,2.0,3.0,0.0,221.0,6.0,27.0,124.0,72.0,14.0,221.0,154.0,23.0,15.0,3.0,167.0,10.0,4.0,0.0,6.0,10.0,0.0,1.0,0.0,0.0,21.0,7.0,5.0,58.3 +Ademola Lookman,ng NGA,"FW,MF",Atalanta,25-345,1997,6.0,5.0,284.0,2.0,0.0,0.0,0.0,1.0,0.0,0.63,0.0,0.63,0.63,0.63,1.9,1.9,0.59,0.59,3.2,4.0,0.0,36.4,1.27,0.18,0.5,0.17,0.1,0.1,77.0,109.0,70.6,1012.0,273.0,50.0,56.0,89.3,16.0,26.0,61.5,3.0,11.0,27.3,4.0,3.0,5.0,0.0,13.0,102.0,7.0,0.0,1.0,1.0,11.0,5.0,0.0,4.0,0.0,1.0,0.0,5.0,18.0,5.7,12.0,0.0,0.0,0.0,2.0,0.63,2.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,2.0,0.0,2.0,1.0,0.0,0.0,137.0,0.0,7.0,53.0,78.0,21.0,137.0,92.0,13.0,7.0,5.0,111.0,7.0,6.0,0.0,5.0,2.0,5.0,0.0,0.0,0.0,15.0,0.0,2.0,0.0 +Maxime Lopez,fr FRA,MF,Fiorentina,25-300,1997,1.0,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,40.0,80.0,559.0,152.0,12.0,13.0,92.3,15.0,20.0,75.0,4.0,5.0,80.0,0.0,3.0,0.0,0.0,1.0,37.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,46.0,4.0,14.0,25.0,7.0,0.0,46.0,27.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Maxime Lopez,fr FRA,MF,Sassuolo,25-300,1997,2.0,2.0,140.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,124.0,136.0,91.2,2097.0,777.0,46.0,48.0,95.8,61.0,64.0,95.3,9.0,15.0,60.0,3.0,23.0,2.0,0.0,18.0,134.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,3.21,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,2.0,0.0,0.0,144.0,10.0,38.0,89.0,19.0,0.0,144.0,107.0,2.0,4.0,0.0,125.0,1.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,10.0,0.0,1.0,0.0 +Matteo Lovato,it ITA,DF,Salernitana,23-228,2000,6.0,6.0,534.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,187.0,232.0,80.6,3284.0,1580.0,77.0,84.0,91.7,90.0,105.0,85.7,15.0,31.0,48.4,1.0,18.0,2.0,1.0,20.0,211.0,18.0,17.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,5.0,0.84,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,7.0,11.0,2.0,1.0,8.0,4.0,4.0,8.0,19.0,0.0,293.0,44.0,148.0,131.0,18.0,2.0,293.0,130.0,0.0,1.0,0.0,152.0,4.0,2.0,0.0,3.0,4.0,0.0,0.0,0.0,0.0,26.0,10.0,5.0,66.7 +Sandi Lovrić,si SVN,MF,Udinese,25-186,1998,6.0,5.0,431.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.2,1.2,0.24,0.24,4.8,6.0,0.0,46.2,1.25,0.0,0.0,0.09,-1.2,-1.2,128.0,159.0,80.5,2132.0,548.0,73.0,81.0,90.1,34.0,45.0,75.6,14.0,21.0,66.7,8.0,12.0,3.0,2.0,13.0,141.0,18.0,6.0,0.0,2.0,20.0,9.0,3.0,3.0,0.0,3.0,0.0,3.0,17.0,3.56,10.0,5.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,3.0,0.0,3.0,2.0,5.0,0.0,212.0,3.0,24.0,95.0,95.0,11.0,212.0,139.0,12.0,9.0,2.0,146.0,10.0,7.0,0.0,5.0,4.0,1.0,0.0,0.0,0.0,28.0,0.0,4.0,0.0 +Lorenzo Lucca,it ITA,FW,Udinese,23-020,2000,6.0,5.0,426.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.21,0.21,0.0,0.21,1.7,1.7,0.36,0.36,4.7,3.0,0.0,30.0,0.63,0.0,0.0,0.17,-1.7,-1.7,42.0,74.0,56.8,520.0,59.0,21.0,37.0,56.8,12.0,21.0,57.1,1.0,1.0,100.0,10.0,2.0,1.0,0.0,3.0,68.0,5.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,13.0,2.75,10.0,0.0,1.0,1.0,1.0,0.21,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,1.0,3.0,0.0,3.0,0.0,4.0,0.0,135.0,4.0,8.0,60.0,67.0,21.0,135.0,81.0,3.0,4.0,2.0,110.0,15.0,7.0,0.0,8.0,9.0,1.0,0.0,0.0,0.0,8.0,14.0,9.0,60.9 +Jhon Lucumí,co COL,DF,Bologna,25-096,1998,5.0,5.0,425.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.03,0.03,4.7,1.0,0.0,33.3,0.21,0.0,0.0,0.05,-0.2,-0.2,303.0,328.0,92.4,5594.0,1764.0,120.0,125.0,96.0,144.0,150.0,96.0,34.0,44.0,77.3,2.0,28.0,0.0,0.0,20.0,311.0,17.0,12.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,0.85,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,7.0,9.0,6.0,0.0,7.0,2.0,5.0,1.0,18.0,0.0,376.0,48.0,170.0,201.0,9.0,2.0,376.0,242.0,5.0,4.0,0.0,271.0,2.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,32.0,8.0,3.0,72.7 +José Luis Palomino,ar ARG,DF,Atalanta,33-268,1990,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,11.0,72.7,137.0,66.0,4.0,5.0,80.0,2.0,3.0,66.7,1.0,2.0,50.0,0.0,1.0,0.0,0.0,1.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,14.0,0.0,7.0,7.0,0.0,0.0,14.0,6.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,100.0 +Romelu Lukaku,be BEL,FW,Roma,30-140,1993,4.0,3.0,283.0,2.0,0.0,0.0,0.0,1.0,0.0,0.64,0.0,0.64,0.64,0.64,0.8,0.8,0.27,0.27,3.1,3.0,0.0,37.5,0.95,0.25,0.67,0.11,1.2,1.2,50.0,66.0,75.8,675.0,85.0,25.0,34.0,73.5,18.0,21.0,85.7,1.0,1.0,100.0,0.0,2.0,2.0,1.0,4.0,63.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,9.0,2.86,6.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,1.0,0.0,87.0,1.0,2.0,33.0,52.0,12.0,87.0,59.0,5.0,5.0,3.0,70.0,5.0,1.0,0.0,3.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,9.0,25.0 +Sebastiano Luperto,it ITA,DF,Empoli,27-024,1996,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,213.0,238.0,89.5,4076.0,1321.0,64.0,73.0,87.7,131.0,136.0,96.3,14.0,24.0,58.3,0.0,9.0,0.0,0.0,12.0,228.0,10.0,4.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,5.0,3.0,0.0,9.0,6.0,3.0,3.0,10.0,0.0,277.0,52.0,157.0,116.0,5.0,2.0,277.0,171.0,0.0,1.0,0.0,171.0,1.0,0.0,0.0,6.0,2.0,0.0,0.0,0.0,0.0,24.0,9.0,7.0,56.3 +Charalambos Lykogiannis,gr GRE,DF,Bologna,29-343,1993,3.0,3.0,204.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.08,0.08,2.3,0.0,1.0,0.0,0.0,0.0,0.0,0.09,-0.2,-0.2,79.0,108.0,73.1,1354.0,352.0,42.0,45.0,93.3,29.0,37.0,78.4,7.0,23.0,30.4,3.0,7.0,2.0,2.0,9.0,93.0,14.0,0.0,0.0,3.0,11.0,1.0,1.0,0.0,0.0,13.0,1.0,0.0,4.0,1.76,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,8.0,0.0,122.0,7.0,28.0,58.0,36.0,0.0,122.0,66.0,9.0,4.0,0.0,82.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,2.0,4.0,2.0,66.7 +Giulio Maggiore,it ITA,MF,Salernitana,25-202,1998,3.0,3.0,244.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.11,0.11,2.7,1.0,0.0,25.0,0.37,0.0,0.0,0.07,-0.3,-0.3,75.0,104.0,72.1,1176.0,312.0,34.0,45.0,75.6,35.0,40.0,87.5,3.0,9.0,33.3,2.0,9.0,1.0,0.0,8.0,101.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,4.0,1.48,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0,3.0,8.0,0.0,130.0,9.0,34.0,78.0,19.0,6.0,130.0,66.0,0.0,0.0,0.0,89.0,4.0,1.0,0.0,5.0,9.0,0.0,0.0,0.0,0.0,14.0,7.0,6.0,53.8 +Giangiacomo Magnani,it ITA,DF,Hellas Verona,27-361,1995,6.0,6.0,540.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,-0.1,-0.1,165.0,206.0,80.1,3823.0,1076.0,36.0,45.0,80.0,97.0,110.0,88.2,32.0,48.0,66.7,2.0,13.0,0.0,0.0,15.0,194.0,12.0,12.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,6.0,1.0,5.0,0.0,0.0,0.0,2.0,0.33,1.0,0.0,0.0,0.0,1.0,7.0,3.0,4.0,3.0,0.0,5.0,4.0,1.0,8.0,22.0,0.0,257.0,31.0,123.0,124.0,10.0,5.0,257.0,138.0,0.0,2.0,0.0,140.0,3.0,0.0,0.0,5.0,6.0,0.0,0.0,0.0,0.0,35.0,5.0,5.0,50.0 +Mike Maignan,fr FRA,GK,Milan,28-089,1995,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,179.0,224.0,79.9,4527.0,3178.0,34.0,34.0,100.0,92.0,93.0,98.9,51.0,92.0,55.4,0.0,2.0,0.0,0.0,0.0,193.0,28.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,4.0,1.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,231.0,167.0,231.0,0.0,0.0,0.0,231.0,151.0,0.0,0.0,0.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,66.7 +Antoine Makoumbou,cg CGO,MF,Cagliari,25-074,1998,6.0,6.0,533.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,213.0,237.0,89.9,3684.0,866.0,101.0,108.0,93.5,82.0,91.0,90.1,24.0,28.0,85.7,3.0,18.0,5.0,0.0,30.0,228.0,8.0,6.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,6.0,1.01,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,6.0,4.0,4.0,3.0,4.0,1.0,3.0,6.0,7.0,0.0,294.0,18.0,82.0,167.0,47.0,1.0,294.0,183.0,0.0,1.0,0.0,192.0,13.0,5.0,0.0,4.0,9.0,0.0,0.0,0.0,0.0,44.0,1.0,5.0,16.7 +Youssef Maleh,ma MAR,MF,Empoli,25-039,1998,4.0,4.0,360.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.13,0.13,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.17,-0.5,-0.5,97.0,118.0,82.2,1333.0,518.0,58.0,61.0,95.1,30.0,37.0,81.1,4.0,9.0,44.4,2.0,11.0,3.0,0.0,14.0,115.0,2.0,2.0,1.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,4.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,9.0,2.0,9.0,1.0,8.0,2.0,6.0,5.0,4.0,0.0,163.0,7.0,42.0,74.0,49.0,3.0,163.0,94.0,4.0,3.0,0.0,95.0,4.0,4.0,0.0,13.0,2.0,0.0,0.0,1.0,0.0,26.0,1.0,2.0,33.3 +Ruslan Malinovskyi,ua UKR,MF,Genoa,30-149,1993,4.0,2.0,145.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.6,0.0,1.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,37.0,50.0,74.0,693.0,210.0,13.0,18.0,72.2,18.0,23.0,78.3,5.0,6.0,83.3,1.0,2.0,2.0,0.0,7.0,49.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.24,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,59.0,1.0,14.0,31.0,16.0,1.0,59.0,29.0,1.0,3.0,0.0,42.0,0.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,1.0,75.0 +Gianluca Mancini,it ITA,DF,Roma,27-166,1996,6.0,6.0,483.0,1.0,0.0,0.0,0.0,1.0,0.0,0.19,0.0,0.19,0.19,0.19,0.9,0.9,0.17,0.17,5.4,3.0,0.0,50.0,0.56,0.17,0.33,0.16,0.1,0.1,319.0,376.0,84.8,5904.0,2151.0,128.0,134.0,95.5,158.0,176.0,89.8,33.0,61.0,54.1,2.0,28.0,4.0,1.0,22.0,366.0,9.0,8.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,5.0,0.93,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,6.0,6.0,2.0,0.0,6.0,5.0,1.0,8.0,10.0,0.0,418.0,45.0,193.0,195.0,32.0,8.0,418.0,278.0,9.0,11.0,0.0,330.0,0.0,1.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,24.0,9.0,7.0,56.3 +Rolando Mandragora,it ITA,MF,Fiorentina,26-093,1997,6.0,4.0,347.0,1.0,0.0,0.0,0.0,1.0,0.0,0.26,0.0,0.26,0.26,0.26,0.3,0.3,0.08,0.08,3.9,2.0,0.0,40.0,0.52,0.2,0.5,0.06,0.7,0.7,165.0,195.0,84.6,2912.0,856.0,74.0,84.0,88.1,64.0,72.0,88.9,21.0,28.0,75.0,0.0,25.0,2.0,0.0,29.0,181.0,14.0,8.0,0.0,3.0,2.0,2.0,0.0,0.0,0.0,1.0,0.0,2.0,4.0,1.04,2.0,1.0,0.0,0.0,2.0,0.52,1.0,1.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,4.0,1.0,3.0,2.0,3.0,0.0,226.0,3.0,37.0,151.0,38.0,3.0,226.0,137.0,1.0,1.0,0.0,154.0,4.0,3.0,0.0,3.0,5.0,0.0,0.0,0.0,0.0,19.0,6.0,5.0,54.5 +Riccardo Marchizza,it ITA,DF,Frosinone,25-188,1998,6.0,6.0,540.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.33,0.33,0.0,0.33,0.0,0.0,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,181.0,240.0,75.4,3196.0,1650.0,69.0,80.0,86.3,90.0,108.0,83.3,18.0,40.0,45.0,7.0,12.0,5.0,3.0,16.0,191.0,49.0,5.0,0.0,1.0,12.0,0.0,0.0,0.0,0.0,44.0,0.0,4.0,8.0,1.33,7.0,0.0,0.0,0.0,2.0,0.33,1.0,0.0,0.0,0.0,1.0,3.0,3.0,1.0,2.0,0.0,7.0,1.0,6.0,4.0,15.0,0.0,284.0,24.0,107.0,116.0,62.0,6.0,284.0,115.0,2.0,1.0,0.0,150.0,4.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,27.0,3.0,6.0,33.3 +Gian Marco Ferrari,it ITA,DF,Sassuolo,31-227,1992,2.0,0.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,7.0,71.4,101.0,41.0,2.0,2.0,100.0,2.0,3.0,66.7,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,12.0,4.0,7.0,5.0,0.0,0.0,12.0,5.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,100.0 +Pablo Marí,es ESP,DF,Monza,30-030,1993,6.0,5.0,404.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.5,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,235.0,252.0,93.3,4793.0,1640.0,67.0,74.0,90.5,139.0,143.0,97.2,27.0,33.0,81.8,0.0,10.0,0.0,0.0,9.0,249.0,3.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,3.0,7.0,2.0,0.0,3.0,1.0,2.0,5.0,14.0,1.0,289.0,40.0,147.0,135.0,7.0,2.0,289.0,172.0,0.0,1.0,0.0,214.0,1.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,18.0,6.0,4.0,60.0 +Mirko Marić,hr CRO,FW,Monza,28-137,1995,5.0,1.0,123.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.3,0.3,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.4,-0.4,34.0,45.0,75.6,413.0,30.0,21.0,25.0,84.0,9.0,12.0,75.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,1.0,43.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,2.2,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,1.0,0.0,62.0,2.0,4.0,29.0,30.0,7.0,62.0,25.0,0.0,0.0,0.0,46.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,5.0,6.0,8.0,42.9 +Răzvan Marin,ro ROU,MF,Empoli,27-130,1996,5.0,4.0,319.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.07,0.07,3.5,3.0,3.0,42.9,0.85,0.0,0.0,0.04,-0.3,-0.3,126.0,168.0,75.0,2354.0,728.0,59.0,66.0,89.4,39.0,48.0,81.3,23.0,40.0,57.5,4.0,14.0,3.0,1.0,15.0,143.0,24.0,14.0,5.0,0.0,12.0,10.0,5.0,3.0,0.0,0.0,1.0,4.0,8.0,2.26,6.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,3.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,8.0,0.0,207.0,11.0,45.0,113.0,51.0,1.0,207.0,117.0,3.0,5.0,0.0,131.0,1.0,1.0,0.0,7.0,1.0,0.0,0.0,0.0,0.0,15.0,4.0,1.0,80.0 +Agustín Martegani,ar ARG,MF,Salernitana,23-133,2000,5.0,2.0,242.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.7,1.0,0.0,20.0,0.37,0.0,0.0,0.02,-0.1,-0.1,107.0,123.0,87.0,1630.0,448.0,57.0,60.0,95.0,32.0,37.0,86.5,10.0,13.0,76.9,3.0,14.0,2.0,0.0,13.0,117.0,4.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,10.0,3.72,9.0,1.0,0.0,0.0,1.0,0.37,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,0.0,2.0,1.0,0.0,1.0,1.0,1.0,0.0,144.0,5.0,16.0,85.0,47.0,2.0,144.0,91.0,6.0,7.0,1.0,106.0,3.0,3.0,0.0,5.0,8.0,0.0,0.0,0.0,0.0,21.0,1.0,1.0,50.0 +Aarón Martín,es ESP,DF,Genoa,26-161,1997,5.0,3.0,192.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,58.0,85.0,68.2,966.0,373.0,30.0,32.0,93.8,20.0,31.0,64.5,6.0,16.0,37.5,0.0,3.0,1.0,1.0,5.0,66.0,19.0,1.0,0.0,0.0,9.0,1.0,0.0,1.0,0.0,17.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,96.0,3.0,27.0,35.0,37.0,0.0,96.0,47.0,2.0,4.0,0.0,48.0,1.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,0.0,14.0,1.0,1.0,50.0 +Josep Martinez,es ESP,GK,Genoa,25-126,1998,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,145.0,217.0,66.8,5197.0,4151.0,11.0,11.0,100.0,62.0,65.0,95.4,72.0,138.0,52.2,0.0,7.0,0.0,0.0,0.0,147.0,69.0,32.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,224.0,182.0,222.0,2.0,0.0,0.0,224.0,137.0,0.0,0.0,0.0,99.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,4.0,5.0,0.0,100.0 +Lautaro Martínez,ar ARG,FW,Inter,26-039,1997,6.0,6.0,510.0,5.0,1.0,0.0,0.0,1.0,0.0,0.88,0.18,1.06,0.88,1.06,3.1,3.1,0.54,0.54,5.7,7.0,0.0,35.0,1.24,0.25,0.71,0.15,1.9,1.9,111.0,143.0,77.6,1609.0,430.0,63.0,73.0,86.3,32.0,40.0,80.0,7.0,11.0,63.6,6.0,8.0,3.0,0.0,16.0,136.0,7.0,0.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,26.0,4.59,18.0,0.0,3.0,2.0,4.0,0.71,2.0,0.0,0.0,1.0,1.0,6.0,3.0,2.0,4.0,0.0,7.0,0.0,7.0,6.0,3.0,0.0,225.0,2.0,19.0,102.0,105.0,38.0,225.0,152.0,10.0,3.0,6.0,164.0,12.0,6.0,0.0,8.0,12.0,3.0,1.0,0.0,0.0,15.0,4.0,7.0,36.4 +Lucas Martínez Quarta,ar ARG,DF,Fiorentina,27-143,1996,4.0,4.0,360.0,2.0,0.0,0.0,0.0,1.0,0.0,0.5,0.0,0.5,0.5,0.5,0.5,0.5,0.12,0.12,4.0,3.0,0.0,75.0,0.75,0.5,0.67,0.12,1.5,1.5,152.0,197.0,77.2,3285.0,1229.0,38.0,45.0,84.4,87.0,99.0,87.9,24.0,43.0,55.8,2.0,16.0,1.0,0.0,23.0,188.0,8.0,8.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,8.0,2.0,7.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,9.0,10.0,6.0,0.0,6.0,2.0,4.0,4.0,10.0,0.0,250.0,15.0,113.0,125.0,13.0,6.0,250.0,134.0,2.0,0.0,2.0,135.0,1.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,27.0,13.0,9.0,59.1 +Adam Marušić,me MNE,DF,Lazio,30-348,1992,6.0,6.0,515.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,5.7,1.0,0.0,50.0,0.17,0.0,0.0,0.02,0.0,0.0,301.0,361.0,83.4,4673.0,1895.0,168.0,188.0,89.4,112.0,130.0,86.2,14.0,30.0,46.7,2.0,34.0,4.0,2.0,25.0,313.0,48.0,6.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,42.0,0.0,6.0,5.0,0.87,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,8.0,6.0,4.0,0.0,4.0,3.0,1.0,8.0,6.0,1.0,401.0,16.0,135.0,197.0,70.0,2.0,401.0,221.0,8.0,11.0,0.0,276.0,3.0,3.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,31.0,4.0,10.0,28.6 +Alan Matturro,uy URU,DF,Genoa,18-354,2004,1.0,1.0,75.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,22.0,63.6,235.0,125.0,5.0,6.0,83.3,7.0,8.0,87.5,1.0,5.0,20.0,0.0,2.0,0.0,0.0,3.0,21.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,1.2,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,3.0,1.0,2.0,1.0,3.0,0.0,28.0,4.0,10.0,13.0,5.0,1.0,28.0,9.0,0.0,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,1.0,66.7 +Luca Mazzitelli,it ITA,MF,Frosinone,27-319,1995,6.0,6.0,520.0,2.0,0.0,0.0,0.0,2.0,0.0,0.35,0.0,0.35,0.35,0.35,0.6,0.6,0.1,0.1,5.8,5.0,1.0,50.0,0.87,0.2,0.4,0.06,1.4,1.4,229.0,313.0,73.2,3744.0,1344.0,112.0,129.0,86.8,81.0,98.0,82.7,22.0,56.0,39.3,1.0,31.0,4.0,1.0,45.0,300.0,9.0,6.0,0.0,3.0,9.0,0.0,0.0,0.0,0.0,1.0,4.0,6.0,7.0,1.21,4.0,0.0,1.0,0.0,1.0,0.17,0.0,0.0,1.0,0.0,0.0,9.0,6.0,3.0,4.0,2.0,5.0,1.0,4.0,2.0,14.0,0.0,373.0,20.0,86.0,229.0,60.0,8.0,373.0,197.0,5.0,2.0,0.0,272.0,6.0,4.0,0.0,8.0,12.0,1.0,0.0,0.0,0.0,31.0,7.0,5.0,58.3 +Pasquale Mazzocchi,it ITA,DF,Salernitana,28-065,1995,6.0,5.0,375.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,4.2,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,140.0,189.0,74.1,2010.0,871.0,82.0,101.0,81.2,49.0,62.0,79.0,4.0,13.0,30.8,6.0,9.0,6.0,4.0,14.0,148.0,41.0,1.0,0.0,1.0,17.0,0.0,0.0,0.0,0.0,40.0,0.0,8.0,14.0,3.36,13.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,6.0,8.0,1.0,0.0,5.0,2.0,3.0,1.0,4.0,0.0,235.0,7.0,65.0,80.0,91.0,7.0,235.0,119.0,19.0,13.0,3.0,139.0,13.0,4.0,0.0,4.0,0.0,2.0,0.0,0.0,0.0,20.0,1.0,8.0,11.1 +Jordi Mboula,es ESP,"MF,FW",Hellas Verona,24-198,1999,3.0,2.0,116.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.3,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,16.0,26.0,61.5,231.0,46.0,9.0,13.0,69.2,5.0,6.0,83.3,1.0,1.0,100.0,0.0,0.0,0.0,0.0,2.0,25.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,0.0,5.0,17.0,11.0,4.0,33.0,25.0,3.0,1.0,1.0,26.0,3.0,4.0,0.0,1.0,2.0,1.0,0.0,0.0,0.0,3.0,2.0,6.0,25.0 +Weston McKennie,us USA,DF,Juventus,25-033,1998,6.0,4.0,353.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.25,0.25,0.0,0.25,0.2,0.2,0.06,0.06,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.2,-0.2,125.0,165.0,75.8,2284.0,727.0,60.0,75.0,80.0,45.0,62.0,72.6,17.0,21.0,81.0,7.0,3.0,5.0,1.0,9.0,136.0,29.0,2.0,0.0,2.0,14.0,0.0,0.0,0.0,0.0,27.0,0.0,2.0,13.0,3.32,8.0,4.0,0.0,1.0,2.0,0.51,2.0,0.0,0.0,0.0,0.0,10.0,9.0,7.0,3.0,0.0,5.0,1.0,4.0,7.0,10.0,0.0,210.0,16.0,65.0,65.0,81.0,15.0,210.0,108.0,14.0,11.0,2.0,119.0,5.0,1.0,0.0,3.0,2.0,0.0,0.0,0.0,0.0,17.0,8.0,4.0,66.7 +Arthur Melo,br BRA,MF,Fiorentina,27-049,1996,6.0,4.0,348.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.26,0.26,0.0,0.26,0.0,0.0,0.0,0.0,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,226.0,243.0,93.0,4689.0,1009.0,64.0,69.0,92.8,121.0,125.0,96.8,37.0,40.0,92.5,4.0,23.0,1.0,0.0,20.0,228.0,15.0,13.0,1.0,3.0,2.0,1.0,0.0,0.0,1.0,1.0,0.0,4.0,9.0,2.33,9.0,0.0,0.0,0.0,2.0,0.52,2.0,0.0,0.0,0.0,0.0,7.0,6.0,2.0,4.0,1.0,9.0,1.0,8.0,2.0,2.0,0.0,276.0,5.0,61.0,173.0,43.0,1.0,276.0,184.0,3.0,4.0,0.0,210.0,3.0,4.0,0.0,4.0,10.0,0.0,0.0,0.0,0.0,22.0,0.0,3.0,0.0 +Alex Meret,it ITA,GK,Napoli,26-192,1997,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,136.0,149.0,91.3,2857.0,1421.0,34.0,34.0,100.0,82.0,83.0,98.8,20.0,32.0,62.5,0.0,0.0,0.0,0.0,0.0,117.0,32.0,11.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,154.0,120.0,152.0,2.0,0.0,0.0,154.0,96.0,0.0,0.0,0.0,87.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,1.0,0.0,100.0 +Junior Messias,br BRA,DF,Genoa,32-140,1991,1.0,0.0,15.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,6.0,6.0,6.0,0.2,0.2,1.33,1.33,0.2,1.0,0.0,50.0,6.0,0.5,1.0,0.11,0.8,0.8,2.0,3.0,66.7,25.0,10.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,7.0,2.0,2.0,0.0,5.0,2.0,7.0,5.0,1.0,1.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 +Nikola Milenković,rs SRB,DF,Fiorentina,25-353,1997,6.0,5.0,475.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.01,0.01,5.3,1.0,0.0,50.0,0.19,0.0,0.0,0.03,-0.1,-0.1,250.0,292.0,85.6,5384.0,1736.0,69.0,79.0,87.3,142.0,154.0,92.2,38.0,49.0,77.6,0.0,10.0,0.0,0.0,12.0,284.0,7.0,7.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,3.0,0.57,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,4.0,5.0,3.0,0.0,6.0,3.0,3.0,2.0,13.0,0.0,324.0,26.0,180.0,142.0,2.0,1.0,324.0,201.0,0.0,1.0,0.0,217.0,1.0,0.0,0.0,7.0,5.0,0.0,0.0,0.0,0.0,24.0,10.0,3.0,76.9 +Arkadiusz Milik,pl POL,FW,Juventus,29-214,1994,6.0,1.0,144.0,1.0,1.0,0.0,0.0,0.0,0.0,0.62,0.62,1.25,0.62,1.25,1.8,1.8,1.14,1.14,1.6,2.0,0.0,22.2,1.25,0.11,0.5,0.2,-0.8,-0.8,54.0,60.0,90.0,728.0,108.0,31.0,34.0,91.2,20.0,22.0,90.9,1.0,1.0,100.0,4.0,1.0,1.0,0.0,3.0,58.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,2.52,3.0,0.0,1.0,0.0,1.0,0.63,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,88.0,2.0,8.0,42.0,38.0,12.0,88.0,68.0,2.0,1.0,1.0,75.0,9.0,2.0,0.0,4.0,4.0,0.0,0.0,0.0,0.0,6.0,4.0,5.0,44.4 +Vanja Milinković-Savić,rs SRB,GK,Torino,26-222,1997,6.0,6.0,540.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,166.0,244.0,68.0,5105.0,3865.0,27.0,27.0,100.0,78.0,78.0,100.0,61.0,138.0,44.2,0.0,5.0,0.0,0.0,0.0,183.0,60.0,10.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,259.0,203.0,259.0,0.0,0.0,0.0,259.0,155.0,0.0,0.0,0.0,117.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,2.0,1.0,66.7 +Aleksei Miranchuk,ru RUS,"MF,DF",Atalanta,27-348,1995,2.0,0.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,21.0,66.7,210.0,35.0,8.0,9.0,88.9,5.0,7.0,71.4,1.0,3.0,33.3,0.0,0.0,1.0,0.0,3.0,21.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,26.0,0.0,1.0,18.0,7.0,1.0,26.0,19.0,3.0,2.0,1.0,22.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,50.0 +Kevin Miranda,it ITA,DF,Sassuolo,20-204,2003,1.0,0.0,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,10.0,90.0,165.0,43.0,3.0,3.0,100.0,5.0,6.0,83.3,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,11.0,1.0,7.0,5.0,0.0,0.0,11.0,8.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Fabio Miretti,it ITA,MF,Juventus,20-058,2003,5.0,4.0,214.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,2.4,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,71.0,91.0,78.0,1065.0,298.0,36.0,39.0,92.3,28.0,32.0,87.5,3.0,10.0,30.0,4.0,5.0,5.0,2.0,5.0,81.0,9.0,4.0,2.0,0.0,4.0,4.0,0.0,1.0,0.0,0.0,1.0,3.0,8.0,3.38,6.0,1.0,0.0,0.0,1.0,0.42,1.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,2.0,0.0,2.0,1.0,2.0,0.0,121.0,3.0,24.0,55.0,44.0,7.0,121.0,69.0,6.0,5.0,0.0,78.0,4.0,0.0,0.0,5.0,8.0,0.0,0.0,0.0,0.0,17.0,0.0,2.0,0.0 +Filippo Missori,it ITA,DF,Sassuolo,19-190,2004,1.0,0.0,45.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.21,0.21,0.5,1.0,0.0,50.0,2.0,0.0,0.0,0.05,-0.1,-0.1,19.0,26.0,73.1,339.0,92.0,9.0,9.0,100.0,5.0,9.0,55.6,4.0,5.0,80.0,1.0,0.0,1.0,1.0,2.0,23.0,3.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,1.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,35.0,3.0,14.0,12.0,9.0,1.0,35.0,20.0,3.0,1.0,1.0,22.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,100.0 +Henrikh Mkhitaryan,am ARM,MF,Inter,34-252,1989,6.0,6.0,508.0,2.0,1.0,0.0,0.0,1.0,0.0,0.35,0.18,0.53,0.35,0.53,1.1,1.1,0.2,0.2,5.6,2.0,0.0,25.0,0.35,0.25,1.0,0.14,0.9,0.9,253.0,304.0,83.2,3777.0,824.0,140.0,151.0,92.7,86.0,100.0,86.0,16.0,29.0,55.2,7.0,27.0,6.0,0.0,35.0,300.0,4.0,3.0,4.0,5.0,8.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,23.0,4.07,21.0,1.0,1.0,0.0,3.0,0.53,3.0,0.0,0.0,0.0,0.0,15.0,8.0,3.0,10.0,2.0,2.0,0.0,2.0,6.0,5.0,0.0,352.0,3.0,54.0,181.0,121.0,17.0,352.0,232.0,15.0,12.0,4.0,262.0,5.0,1.0,0.0,3.0,6.0,0.0,0.0,0.0,0.0,33.0,4.0,2.0,66.7 +Ilario Monterisi,it ITA,DF,Frosinone,21-285,2001,5.0,4.0,316.0,1.0,0.0,0.0,0.0,0.0,0.0,0.28,0.0,0.28,0.28,0.28,0.3,0.3,0.09,0.09,3.5,1.0,0.0,100.0,0.28,1.0,1.0,0.31,0.7,0.7,200.0,238.0,84.0,3487.0,1754.0,88.0,94.0,93.6,88.0,95.0,92.6,18.0,36.0,50.0,1.0,10.0,1.0,0.0,9.0,220.0,17.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,5.0,2.0,0.57,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,3.0,2.0,0.0,5.0,5.0,0.0,1.0,15.0,0.0,267.0,55.0,174.0,90.0,5.0,1.0,267.0,154.0,0.0,1.0,0.0,178.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,0.0,23.0,14.0,9.0,60.9 +Lorenzo Montipò,it ITA,GK,Hellas Verona,27-222,1996,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,128.0,233.0,54.9,4885.0,4144.0,13.0,13.0,100.0,48.0,49.0,98.0,67.0,171.0,39.2,0.0,12.0,0.0,0.0,0.0,162.0,71.0,21.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,258.0,190.0,257.0,1.0,0.0,0.0,258.0,121.0,0.0,0.0,0.0,104.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,9.0,1.0,1.0,50.0 +Nikola Moro,hr CRO,"MF,FW",Bologna,25-202,1998,4.0,3.0,182.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,90.0,110.0,81.8,1703.0,386.0,37.0,42.0,88.1,38.0,40.0,95.0,13.0,18.0,72.2,2.0,10.0,2.0,1.0,10.0,109.0,1.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,1.98,4.0,0.0,0.0,0.0,1.0,0.49,1.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,4.0,0.0,4.0,2.0,2.0,0.0,132.0,3.0,22.0,84.0,30.0,1.0,132.0,73.0,3.0,6.0,0.0,103.0,3.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,10.0,2.0,0.0,100.0 +Dany Mota,pt POR,"FW,MF",Monza,25-151,1998,6.0,4.0,356.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.26,0.26,4.0,5.0,0.0,38.5,1.26,0.0,0.0,0.08,-1.0,-1.0,73.0,106.0,68.9,1263.0,212.0,36.0,43.0,83.7,25.0,33.0,75.8,8.0,12.0,66.7,5.0,6.0,2.0,1.0,10.0,97.0,7.0,0.0,0.0,2.0,9.0,2.0,0.0,2.0,0.0,1.0,2.0,5.0,12.0,3.04,11.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,4.0,0.0,152.0,5.0,14.0,54.0,84.0,27.0,152.0,84.0,13.0,9.0,3.0,107.0,10.0,5.0,0.0,3.0,3.0,3.0,0.0,0.0,0.0,16.0,10.0,12.0,45.5 +Samuele Mulattieri,it ITA,FW,Sassuolo,22-358,2000,4.0,0.0,52.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.17,0.17,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.1,-0.1,-0.1,16.0,18.0,88.9,186.0,10.0,10.0,10.0,100.0,4.0,4.0,100.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,15.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.46,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,1.0,0.0,34.0,2.0,4.0,20.0,10.0,3.0,34.0,17.0,3.0,1.0,2.0,21.0,5.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,5.0,37.5 +Luis Muriel,co COL,"FW,MF",Atalanta,32-167,1991,3.0,0.0,56.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.61,1.61,0.0,1.61,0.1,0.1,0.13,0.13,0.6,1.0,0.0,100.0,1.61,0.0,0.0,0.08,-0.1,-0.1,44.0,52.0,84.6,779.0,263.0,25.0,29.0,86.2,12.0,13.0,92.3,7.0,10.0,70.0,6.0,2.0,3.0,1.0,8.0,45.0,7.0,1.0,1.0,0.0,7.0,5.0,4.0,0.0,0.0,1.0,0.0,0.0,7.0,11.05,5.0,2.0,0.0,0.0,1.0,1.58,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,55.0,0.0,0.0,21.0,35.0,5.0,55.0,35.0,4.0,2.0,2.0,46.0,1.0,4.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,100.0 +Yunus Musah,us USA,"FW,MF",Milan,20-305,2002,4.0,1.0,152.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,1.7,2.0,0.0,100.0,1.18,0.0,0.0,0.06,-0.1,-0.1,74.0,86.0,86.0,1072.0,236.0,47.0,50.0,94.0,22.0,26.0,84.6,3.0,7.0,42.9,2.0,3.0,1.0,1.0,2.0,78.0,8.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,8.0,0.0,1.0,2.0,1.18,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,1.0,2.0,1.0,1.0,0.0,2.0,1.0,0.0,106.0,2.0,29.0,51.0,27.0,1.0,106.0,71.0,4.0,1.0,1.0,67.0,2.0,2.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,12.0,1.0,2.0,33.3 +Juan Musso,ar ARG,GK,Atalanta,29-147,1994,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,110.0,147.0,74.8,2754.0,1799.0,22.0,22.0,100.0,58.0,58.0,100.0,29.0,66.0,43.9,0.0,1.0,0.0,0.0,0.0,113.0,34.0,6.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.25,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,156.0,122.0,155.0,1.0,0.0,0.0,156.0,94.0,0.0,0.0,0.0,74.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,1.0,0.0,100.0 +Obite N'Dicka,ci CIV,DF,Roma,24-041,1999,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.12,0.12,3.0,1.0,0.0,100.0,0.33,0.0,0.0,0.37,-0.4,-0.4,230.0,254.0,90.6,3725.0,1237.0,111.0,111.0,100.0,106.0,114.0,93.0,8.0,21.0,38.1,0.0,8.0,0.0,0.0,7.0,248.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,2.0,2.0,3.0,0.0,3.0,1.0,2.0,0.0,8.0,0.0,275.0,48.0,143.0,129.0,5.0,1.0,275.0,179.0,1.0,1.0,0.0,218.0,1.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,21.0,5.0,2.0,71.4 +Nahitan Nández,uy URU,"MF,FW",Cagliari,27-276,1995,6.0,5.0,398.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.23,0.23,0.0,0.23,0.6,0.6,0.13,0.13,4.4,2.0,0.0,33.3,0.45,0.0,0.0,0.1,-0.6,-0.6,105.0,165.0,63.6,1859.0,663.0,53.0,62.0,85.5,36.0,54.0,66.7,13.0,38.0,34.2,7.0,8.0,6.0,2.0,16.0,149.0,16.0,2.0,1.0,4.0,26.0,3.0,2.0,1.0,0.0,10.0,0.0,6.0,13.0,2.94,10.0,2.0,0.0,1.0,2.0,0.45,1.0,1.0,0.0,0.0,0.0,3.0,2.0,2.0,0.0,1.0,3.0,1.0,2.0,3.0,2.0,0.0,197.0,5.0,28.0,76.0,94.0,10.0,197.0,108.0,11.0,5.0,2.0,136.0,9.0,4.0,0.0,9.0,3.0,2.0,0.0,0.0,0.0,23.0,5.0,13.0,27.8 +Natan,br BRA,DF,Napoli,22-236,2001,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,115.0,125.0,92.0,2224.0,531.0,41.0,42.0,97.6,58.0,59.0,98.3,15.0,21.0,71.4,1.0,5.0,0.0,0.0,7.0,122.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,1.0,1.0,0.0,1.0,7.0,0.0,139.0,19.0,72.0,66.0,1.0,0.0,139.0,100.0,1.0,0.0,0.0,112.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,1.0,50.0 +Michel Ndary Adopo,fr FRA,"MF,DF",Atalanta,23-073,2000,3.0,0.0,32.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,2.81,2.81,0.0,2.81,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,23.0,28.0,82.1,364.0,147.0,12.0,15.0,80.0,9.0,10.0,90.0,1.0,1.0,100.0,1.0,4.0,0.0,0.0,4.0,28.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.81,1.0,0.0,0.0,0.0,1.0,2.81,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,30.0,1.0,7.0,18.0,5.0,1.0,30.0,20.0,0.0,0.0,0.0,27.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Dan Ndoye,ch SUI,"FW,MF",Bologna,22-340,2000,6.0,5.0,417.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.12,0.12,4.6,4.0,0.0,40.0,0.86,0.0,0.0,0.06,-0.6,-0.6,108.0,151.0,71.5,1679.0,414.0,60.0,74.0,81.1,31.0,39.0,79.5,11.0,21.0,52.4,5.0,10.0,3.0,1.0,10.0,143.0,7.0,0.0,0.0,1.0,17.0,6.0,3.0,2.0,0.0,1.0,1.0,6.0,18.0,3.88,12.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,4.0,7.0,3.0,0.0,7.0,1.0,6.0,0.0,3.0,0.0,228.0,6.0,37.0,96.0,102.0,16.0,228.0,155.0,28.0,17.0,6.0,165.0,16.0,4.0,0.0,7.0,17.0,0.0,0.0,0.0,0.0,29.0,3.0,3.0,50.0 +Cyril Ngonge,be BEL,"MF,FW",Hellas Verona,23-127,2000,6.0,6.0,461.0,2.0,0.0,0.0,0.0,1.0,0.0,0.39,0.0,0.39,0.39,0.39,0.6,0.6,0.12,0.12,5.1,3.0,0.0,30.0,0.59,0.2,0.67,0.06,1.4,1.4,76.0,118.0,64.4,1507.0,394.0,30.0,47.0,63.8,28.0,38.0,73.7,14.0,20.0,70.0,8.0,6.0,2.0,1.0,9.0,97.0,19.0,7.0,1.0,1.0,15.0,3.0,0.0,2.0,0.0,1.0,2.0,4.0,16.0,3.12,9.0,5.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,5.0,2.0,1.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,171.0,2.0,10.0,66.0,96.0,12.0,171.0,102.0,12.0,6.0,6.0,114.0,14.0,4.0,0.0,13.0,5.0,2.0,0.0,0.0,0.0,12.0,11.0,19.0,36.7 +Rasmus Nissen,dk DEN,"DF,FW",Roma,26-081,1997,5.0,5.0,379.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.24,0.24,0.0,0.24,0.0,0.0,0.0,0.0,4.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,214.0,281.0,76.2,3204.0,777.0,123.0,134.0,91.8,80.0,112.0,71.4,7.0,19.0,36.8,5.0,5.0,3.0,2.0,7.0,215.0,65.0,1.0,0.0,1.0,13.0,0.0,0.0,0.0,0.0,64.0,1.0,7.0,7.0,1.66,5.0,1.0,0.0,0.0,1.0,0.24,1.0,0.0,0.0,0.0,0.0,11.0,6.0,6.0,4.0,1.0,8.0,0.0,8.0,1.0,6.0,0.0,325.0,6.0,85.0,147.0,93.0,7.0,325.0,144.0,1.0,2.0,2.0,196.0,6.0,1.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,13.0,4.0,3.0,57.1 +M'Bala Nzola,ao ANG,FW,Fiorentina,27-043,1996,6.0,4.0,395.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.23,0.23,0.0,0.23,0.5,0.5,0.11,0.11,4.4,1.0,0.0,16.7,0.23,0.0,0.0,0.08,-0.5,-0.5,77.0,89.0,86.5,1001.0,109.0,57.0,63.0,90.5,12.0,15.0,80.0,4.0,4.0,100.0,4.0,4.0,2.0,0.0,5.0,82.0,7.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,8.0,1.82,5.0,0.0,1.0,1.0,1.0,0.23,0.0,0.0,1.0,0.0,0.0,4.0,3.0,0.0,0.0,4.0,2.0,0.0,2.0,0.0,11.0,0.0,150.0,12.0,13.0,65.0,74.0,16.0,150.0,100.0,4.0,3.0,3.0,108.0,21.0,16.0,0.0,11.0,2.0,6.0,0.0,0.0,0.0,14.0,9.0,18.0,33.3 +Adam Obert,sk SVK,"DF,MF",Cagliari,21-038,2002,4.0,3.0,277.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,100.0,137.0,73.0,2083.0,636.0,36.0,43.0,83.7,46.0,57.0,80.7,18.0,35.0,51.4,2.0,8.0,3.0,2.0,5.0,128.0,8.0,6.0,1.0,7.0,3.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,3.0,0.97,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,2.0,4.0,0.0,5.0,2.0,3.0,5.0,16.0,0.0,169.0,24.0,89.0,76.0,4.0,0.0,169.0,81.0,4.0,1.0,0.0,87.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,21.0,8.0,5.0,61.5 +Guillermo Ochoa,mx MEX,GK,Salernitana,38-079,1985,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,134.0,208.0,64.4,3600.0,2321.0,17.0,17.0,100.0,76.0,76.0,100.0,41.0,113.0,36.3,0.0,3.0,1.0,0.0,0.0,131.0,76.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,226.0,184.0,225.0,1.0,0.0,0.0,226.0,105.0,0.0,0.0,0.0,85.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,0.0,100.0 +Noah Okafor,ch SUI,FW,Milan,23-129,2000,6.0,1.0,172.0,1.0,0.0,0.0,0.0,1.0,0.0,0.52,0.0,0.52,0.52,0.52,0.8,0.8,0.43,0.43,1.9,2.0,0.0,40.0,1.05,0.2,0.5,0.16,0.2,0.2,19.0,30.0,63.3,250.0,77.0,9.0,11.0,81.8,8.0,11.0,72.7,0.0,2.0,0.0,0.0,1.0,0.0,0.0,5.0,26.0,2.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.52,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,50.0,3.0,6.0,23.0,24.0,11.0,50.0,33.0,6.0,3.0,3.0,36.0,5.0,5.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,8.0,3.0,4.0,42.9 +Caleb Okoli,it ITA,DF,Frosinone,22-079,2001,3.0,2.0,225.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,83.0,105.0,79.0,1650.0,650.0,29.0,33.0,87.9,45.0,49.0,91.8,8.0,19.0,42.1,0.0,4.0,1.0,0.0,2.0,98.0,7.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.4,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,3.0,0.0,5.0,5.0,0.0,1.0,10.0,1.0,130.0,20.0,85.0,43.0,3.0,1.0,130.0,69.0,0.0,0.0,0.0,80.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,11.0,3.0,0.0,100.0 +Mathías Olivera,uy URU,DF,Napoli,25-334,1997,5.0,4.0,308.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,3.4,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,200.0,233.0,85.8,3069.0,691.0,115.0,125.0,92.0,72.0,82.0,87.8,10.0,12.0,83.3,5.0,11.0,6.0,4.0,11.0,196.0,36.0,5.0,0.0,1.0,8.0,0.0,0.0,0.0,0.0,31.0,1.0,9.0,10.0,2.92,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,1.0,1.0,4.0,0.0,4.0,2.0,4.0,0.0,263.0,6.0,57.0,133.0,74.0,15.0,263.0,137.0,7.0,7.0,0.0,165.0,2.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,16.0,9.0,6.0,60.0 +Gaetano Oristanio,it ITA,"FW,MF",Cagliari,21-002,2002,5.0,2.0,188.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.2,0.2,2.1,1.0,1.0,20.0,0.48,0.0,0.0,0.08,-0.4,-0.4,29.0,40.0,72.5,446.0,145.0,19.0,21.0,90.5,7.0,10.0,70.0,2.0,4.0,50.0,2.0,3.0,1.0,0.0,5.0,34.0,6.0,0.0,0.0,1.0,5.0,2.0,2.0,0.0,0.0,0.0,0.0,4.0,8.0,3.83,5.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,62.0,1.0,8.0,23.0,33.0,10.0,62.0,42.0,5.0,6.0,4.0,41.0,9.0,7.0,0.0,7.0,2.0,0.0,0.0,0.0,0.0,10.0,1.0,3.0,25.0 +Riccardo Orsolini,it ITA,FW,Bologna,26-249,1997,6.0,2.0,227.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.2,0.4,0.08,2.5,2.0,0.0,66.7,0.79,0.0,0.0,0.07,-1.0,-0.2,58.0,84.0,69.0,873.0,247.0,33.0,37.0,89.2,19.0,30.0,63.3,5.0,14.0,35.7,4.0,2.0,4.0,1.0,9.0,76.0,8.0,5.0,0.0,2.0,10.0,3.0,3.0,0.0,0.0,0.0,0.0,2.0,10.0,3.96,9.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,3.0,1.0,2.0,1.0,3.0,0.0,107.0,2.0,14.0,38.0,56.0,10.0,106.0,62.0,8.0,7.0,4.0,76.0,3.0,2.0,0.0,2.0,5.0,1.0,0.0,0.0,0.0,7.0,3.0,2.0,60.0 +Victor Osimhen,ng NGA,FW,Napoli,24-275,1998,6.0,6.0,497.0,4.0,0.0,1.0,2.0,0.0,0.0,0.72,0.0,0.72,0.54,0.54,4.5,2.9,0.81,0.52,5.5,8.0,0.0,30.8,1.45,0.12,0.38,0.11,-0.5,0.1,41.0,65.0,63.1,487.0,109.0,24.0,31.0,77.4,10.0,15.0,66.7,0.0,1.0,0.0,5.0,5.0,0.0,0.0,4.0,54.0,8.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,3.0,6.0,9.0,1.63,5.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,5.0,0.0,138.0,5.0,7.0,46.0,86.0,42.0,136.0,77.0,13.0,5.0,3.0,97.0,15.0,3.0,0.0,8.0,5.0,8.0,0.0,0.0,0.0,9.0,11.0,12.0,47.8 +Remi Oudin,fr FRA,MF,Lecce,26-316,1996,2.0,1.0,93.0,1.0,0.0,0.0,0.0,0.0,0.0,0.97,0.0,0.97,0.97,0.97,0.1,0.1,0.05,0.05,1.0,1.0,0.0,50.0,0.97,0.5,1.0,0.03,0.9,0.9,29.0,43.0,67.4,506.0,129.0,11.0,12.0,91.7,13.0,18.0,72.2,3.0,9.0,33.3,3.0,1.0,0.0,0.0,3.0,39.0,4.0,2.0,0.0,1.0,7.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,4.0,3.87,3.0,1.0,0.0,0.0,1.0,0.97,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,52.0,2.0,5.0,21.0,27.0,1.0,52.0,27.0,0.0,2.0,0.0,35.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,1.0,50.0 +Anthony Oyono,ga GAB,DF,Frosinone,22-171,2001,6.0,6.0,540.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.0,0.0,226.0,272.0,83.1,3005.0,1190.0,146.0,159.0,91.8,60.0,76.0,78.9,9.0,21.0,42.9,7.0,10.0,4.0,3.0,11.0,202.0,70.0,3.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,67.0,0.0,5.0,11.0,1.83,7.0,4.0,0.0,0.0,2.0,0.33,0.0,2.0,0.0,0.0,0.0,18.0,12.0,12.0,6.0,0.0,9.0,2.0,7.0,6.0,21.0,0.0,348.0,28.0,135.0,145.0,71.0,10.0,348.0,159.0,14.0,9.0,5.0,171.0,11.0,4.0,0.0,5.0,9.0,0.0,0.0,0.0,0.0,35.0,6.0,5.0,54.5 +Simone Pafundi,it ITA,MF,Udinese,17-228,2006,1.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,67.0,18.0,1.0,1.0,100.0,3.0,3.0,100.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,4.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,0.0,3.0,4.0,2.0,0.0,9.0,4.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,100.0 +Riccardo Pagano,it ITA,"MF,DF",Roma,18-306,2004,3.0,0.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.17,0.17,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,18.0,18.0,100.0,327.0,66.0,8.0,8.0,100.0,7.0,7.0,100.0,3.0,3.0,100.0,1.0,4.0,0.0,0.0,2.0,17.0,1.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,5.0,15.52,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,24.0,0.0,4.0,13.0,7.0,0.0,24.0,15.0,1.0,1.0,0.0,17.0,1.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Leandro Paredes,ar ARG,MF,Roma,29-093,1994,6.0,5.0,381.0,0.0,1.0,0.0,0.0,3.0,0.0,0.0,0.24,0.24,0.0,0.24,0.2,0.2,0.06,0.06,4.2,0.0,1.0,0.0,0.0,0.0,0.0,0.03,-0.2,-0.2,265.0,303.0,87.5,4900.0,1500.0,114.0,117.0,97.4,119.0,132.0,90.2,29.0,46.0,63.0,2.0,25.0,1.0,0.0,26.0,278.0,25.0,14.0,1.0,4.0,12.0,7.0,5.0,2.0,0.0,4.0,0.0,5.0,12.0,2.83,9.0,2.0,0.0,1.0,1.0,0.24,0.0,1.0,0.0,0.0,0.0,9.0,4.0,4.0,4.0,1.0,4.0,0.0,4.0,5.0,5.0,0.0,330.0,13.0,70.0,208.0,55.0,0.0,330.0,217.0,3.0,7.0,0.0,244.0,2.0,2.0,0.0,4.0,6.0,0.0,0.0,0.0,0.0,28.0,2.0,1.0,66.7 +Fabiano Parisi,it ITA,DF,Fiorentina,22-325,2000,3.0,3.0,270.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.07,0.07,3.0,1.0,0.0,50.0,0.33,0.0,0.0,0.1,-0.2,-0.2,151.0,197.0,76.6,2827.0,1010.0,66.0,72.0,91.7,65.0,86.0,75.6,19.0,29.0,65.5,4.0,8.0,2.0,1.0,12.0,157.0,40.0,6.0,1.0,2.0,9.0,0.0,0.0,0.0,0.0,34.0,0.0,8.0,7.0,2.33,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,1.0,3.0,1.0,4.0,3.0,1.0,2.0,4.0,2.0,0.0,230.0,12.0,68.0,122.0,44.0,2.0,230.0,135.0,8.0,6.0,1.0,123.0,7.0,1.0,0.0,3.0,8.0,0.0,0.0,0.0,0.0,36.0,1.0,6.0,14.3 +Mario Pašalić,hr CRO,"FW,MF",Atalanta,28-233,1995,4.0,2.0,173.0,1.0,0.0,0.0,0.0,0.0,0.0,0.52,0.0,0.52,0.52,0.52,0.5,0.5,0.27,0.27,1.9,2.0,0.0,100.0,1.04,0.5,0.5,0.26,0.5,0.5,38.0,56.0,67.9,603.0,81.0,23.0,27.0,85.2,11.0,17.0,64.7,3.0,9.0,33.3,1.0,4.0,1.0,0.0,3.0,56.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,2.09,4.0,0.0,0.0,0.0,1.0,0.52,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,0.0,5.0,0.0,78.0,5.0,14.0,39.0,25.0,8.0,78.0,45.0,2.0,0.0,1.0,62.0,8.0,5.0,0.0,1.0,1.0,2.0,0.0,0.0,0.0,9.0,9.0,7.0,56.3 +Patric,es ESP,DF,Lazio,30-166,1993,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,108.0,122.0,88.5,2392.0,792.0,26.0,26.0,100.0,57.0,62.0,91.9,25.0,33.0,75.8,1.0,6.0,1.0,0.0,8.0,115.0,7.0,6.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,1.0,1.0,1.0,3.0,0.0,133.0,12.0,60.0,72.0,1.0,0.0,133.0,99.0,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,8.0,1.0,0.0,100.0 +Rui Patrício,pt POR,GK,Roma,35-227,1988,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,131.0,148.0,88.5,3061.0,1821.0,38.0,38.0,100.0,63.0,64.0,98.4,29.0,45.0,64.4,0.0,0.0,0.0,0.0,0.0,111.0,37.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,154.0,138.0,154.0,0.0,0.0,0.0,154.0,91.0,0.0,0.0,0.0,79.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,6.0,0.0,0.0,0.0 +Benjamin Pavard,fr FRA,DF,Inter,27-186,1996,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,50.0,61.0,82.0,875.0,345.0,25.0,29.0,86.2,19.0,23.0,82.6,6.0,8.0,75.0,0.0,1.0,0.0,0.0,2.0,60.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,4.0,1.0,3.0,2.0,2.0,0.0,70.0,9.0,41.0,26.0,3.0,1.0,70.0,46.0,0.0,1.0,0.0,47.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,7.0,2.0,0.0,100.0 +Leonardo Pavoletti,it ITA,FW,Cagliari,34-308,1988,3.0,2.0,112.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.13,0.13,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,19.0,32.0,59.4,299.0,72.0,9.0,13.0,69.2,6.0,10.0,60.0,2.0,3.0,66.7,0.0,3.0,1.0,0.0,4.0,31.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,3.0,2.41,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,51.0,1.0,5.0,26.0,20.0,5.0,51.0,25.0,0.0,0.0,0.0,39.0,8.0,1.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,4.0,11.0,7.0,61.1 +Martín Payero,ar ARG,MF,Udinese,25-019,1998,3.0,2.0,171.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.17,0.17,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.3,-0.3,52.0,65.0,80.0,821.0,316.0,25.0,28.0,89.3,20.0,24.0,83.3,5.0,9.0,55.6,3.0,7.0,2.0,0.0,12.0,55.0,10.0,6.0,1.0,0.0,6.0,4.0,1.0,3.0,0.0,0.0,0.0,1.0,8.0,4.21,6.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,4.0,0.0,86.0,4.0,16.0,45.0,28.0,3.0,86.0,50.0,2.0,2.0,0.0,53.0,4.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,8.0,3.0,3.0,50.0 +Marcus Pedersen,no NOR,DF,Sassuolo,23-076,2000,5.0,0.0,145.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,38.0,51.0,74.5,660.0,136.0,16.0,19.0,84.2,19.0,25.0,76.0,2.0,3.0,66.7,0.0,1.0,0.0,0.0,1.0,41.0,10.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,10.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,3.0,0.0,0.0,1.0,1.0,0.0,2.0,4.0,0.0,65.0,4.0,26.0,20.0,20.0,3.0,65.0,25.0,1.0,2.0,0.0,29.0,3.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,4.0,20.0 +Pedro,es ESP,FW,Lazio,36-064,1987,4.0,0.0,63.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,39.0,84.6,445.0,94.0,19.0,21.0,90.5,10.0,11.0,90.9,1.0,2.0,50.0,2.0,1.0,0.0,0.0,2.0,39.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.29,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,2.0,1.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,50.0,0.0,5.0,22.0,24.0,4.0,50.0,38.0,3.0,4.0,1.0,40.0,4.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0 +Pietro Pellegri,it ITA,"FW,DF",Torino,22-197,2001,6.0,0.0,139.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.12,0.12,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,16.0,22.0,72.7,180.0,21.0,13.0,15.0,86.7,2.0,4.0,50.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,1.29,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,40.0,0.0,6.0,14.0,22.0,5.0,40.0,26.0,3.0,3.0,0.0,31.0,7.0,3.0,0.0,3.0,7.0,3.0,0.0,0.0,0.0,3.0,5.0,7.0,41.7 +Lorenzo Pellegrini,it ITA,MF,Roma,27-103,1996,3.0,2.0,227.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.16,0.16,2.5,0.0,2.0,0.0,0.0,0.0,0.0,0.06,-0.4,-0.4,69.0,101.0,68.3,1160.0,303.0,28.0,32.0,87.5,31.0,40.0,77.5,6.0,21.0,28.6,6.0,9.0,1.0,0.0,11.0,81.0,20.0,7.0,0.0,2.0,21.0,13.0,5.0,7.0,0.0,0.0,0.0,0.0,12.0,4.76,6.0,3.0,1.0,0.0,1.0,0.4,1.0,0.0,0.0,0.0,0.0,6.0,3.0,1.0,4.0,1.0,0.0,0.0,0.0,1.0,2.0,0.0,128.0,2.0,10.0,66.0,54.0,5.0,128.0,63.0,1.0,1.0,1.0,79.0,5.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,12.0,2.0,4.0,33.3 +Luca Pellegrini,it ITA,DF,Lazio,24-207,1999,5.0,0.0,134.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.5,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,77.0,107.0,72.0,1129.0,310.0,40.0,45.0,88.9,32.0,42.0,76.2,2.0,8.0,25.0,1.0,8.0,2.0,0.0,19.0,94.0,12.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,12.0,1.0,6.0,4.0,2.69,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,2.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,128.0,2.0,30.0,49.0,52.0,2.0,128.0,79.0,9.0,4.0,1.0,81.0,4.0,1.0,0.0,4.0,2.0,0.0,0.0,0.0,0.0,8.0,3.0,3.0,50.0 +Pepín,gq EQG,"MF,FW",Monza,27-047,1996,3.0,0.0,49.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.18,0.18,0.5,0.0,2.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,30.0,39.0,76.9,506.0,157.0,14.0,16.0,87.5,13.0,16.0,81.3,2.0,5.0,40.0,0.0,1.0,0.0,0.0,5.0,36.0,3.0,1.0,2.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,3.67,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,47.0,2.0,5.0,29.0,13.0,0.0,47.0,29.0,0.0,2.0,0.0,33.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Pedro Pereira,pt POR,DF,Monza,25-251,1998,3.0,0.0,54.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,57.0,66.7,589.0,149.0,26.0,29.0,89.7,6.0,10.0,60.0,4.0,10.0,40.0,1.0,2.0,2.0,2.0,5.0,52.0,5.0,1.0,0.0,1.0,11.0,0.0,0.0,0.0,0.0,4.0,0.0,4.0,4.0,6.67,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,4.0,1.0,3.0,1.0,3.0,0.0,69.0,2.0,12.0,17.0,40.0,2.0,69.0,41.0,2.0,3.0,0.0,50.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,2.0,0.0 +Roberto Pereyra,ar ARG,"MF,FW",Udinese,32-266,1991,3.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,31.0,33.0,93.9,437.0,158.0,18.0,18.0,100.0,11.0,12.0,91.7,1.0,1.0,100.0,2.0,2.0,1.0,1.0,3.0,32.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,4.0,8.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,44.0,1.0,6.0,27.0,11.0,0.0,44.0,33.0,0.0,1.0,0.0,33.0,1.0,3.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,9.0,0.0,0.0,0.0 +Nehuén Pérez,ar ARG,DF,Udinese,23-098,2000,6.0,6.0,540.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.06,0.06,6.0,2.0,0.0,25.0,0.33,0.0,0.0,0.05,-0.4,-0.4,253.0,326.0,77.6,4407.0,1946.0,107.0,122.0,87.7,121.0,144.0,84.0,19.0,49.0,38.8,1.0,27.0,2.0,2.0,36.0,301.0,24.0,13.0,1.0,3.0,11.0,0.0,0.0,0.0,0.0,11.0,1.0,1.0,12.0,2.0,11.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,10.0,8.0,4.0,1.0,10.0,4.0,6.0,6.0,16.0,0.0,386.0,25.0,127.0,209.0,56.0,9.0,386.0,224.0,8.0,11.0,0.0,240.0,2.0,1.0,0.0,6.0,1.0,0.0,0.0,0.0,0.0,35.0,18.0,5.0,78.3 +Mattia Perin,it ITA,GK,Juventus,30-324,1992,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,44.0,53.0,83.0,969.0,570.0,12.0,12.0,100.0,21.0,21.0,100.0,10.0,19.0,52.6,0.0,0.0,0.0,0.0,0.0,37.0,16.0,5.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,56.0,45.0,55.0,1.0,0.0,0.0,56.0,30.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Samuele Perisan,it ITA,GK,Empoli,26-040,1997,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,34.0,79.4,551.0,340.0,10.0,10.0,100.0,11.0,11.0,100.0,5.0,12.0,41.7,0.0,0.0,0.0,0.0,0.0,21.0,13.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,32.0,33.0,0.0,0.0,0.0,33.0,13.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Matteo Pessina,it ITA,MF,Monza,26-162,1997,6.0,6.0,540.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.03,0.03,6.0,2.0,0.0,66.7,0.33,0.0,0.0,0.06,-0.2,-0.2,379.0,425.0,89.2,6949.0,1591.0,143.0,161.0,88.8,188.0,197.0,95.4,42.0,51.0,82.4,5.0,44.0,8.0,1.0,40.0,402.0,22.0,15.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,7.0,19.0,3.17,17.0,0.0,0.0,1.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,10.0,5.0,4.0,5.0,1.0,6.0,2.0,4.0,6.0,7.0,0.0,477.0,22.0,93.0,289.0,101.0,6.0,477.0,291.0,16.0,16.0,0.0,339.0,10.0,2.0,0.0,7.0,8.0,0.0,0.0,0.0,0.0,39.0,4.0,5.0,44.4 +Andrea Petagna,it ITA,FW,Cagliari,28-092,1995,3.0,2.0,124.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.15,0.15,1.4,1.0,0.0,25.0,0.73,0.0,0.0,0.05,-0.2,-0.2,20.0,27.0,74.1,361.0,73.0,6.0,8.0,75.0,8.0,11.0,72.7,4.0,5.0,80.0,2.0,3.0,2.0,0.0,4.0,24.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,2.18,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,36.0,1.0,4.0,18.0,15.0,8.0,36.0,22.0,1.0,0.0,0.0,32.0,2.0,3.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,50.0 +Giuseppe Pezzella,it ITA,DF,Empoli,25-305,1997,6.0,4.0,331.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.7,1.0,0.0,100.0,0.27,0.0,0.0,0.1,-0.1,-0.1,202.0,246.0,82.1,3184.0,969.0,114.0,123.0,92.7,68.0,78.0,87.2,16.0,29.0,55.2,2.0,19.0,5.0,4.0,21.0,210.0,36.0,8.0,1.0,0.0,19.0,0.0,0.0,0.0,0.0,28.0,0.0,10.0,6.0,1.64,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,8.0,7.0,3.0,1.0,12.0,4.0,8.0,0.0,9.0,0.0,294.0,15.0,79.0,141.0,76.0,1.0,294.0,178.0,22.0,10.0,0.0,198.0,2.0,2.0,0.0,2.0,5.0,0.0,0.0,0.0,0.0,22.0,3.0,1.0,75.0 +Roberto Piccoli,it ITA,FW,Empoli,22-246,2001,2.0,0.0,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.12,0.12,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.1,-0.1,4.0,6.0,66.7,47.0,16.0,3.0,4.0,75.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.74,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,4.0,6.0,1.0,10.0,5.0,0.0,0.0,0.0,6.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,33.3 +Roberto Piccoli,it ITA,FW,Lecce,22-246,2001,4.0,0.0,53.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,6.0,11.0,54.5,57.0,1.0,3.0,5.0,60.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.67,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,26.0,2.0,3.0,12.0,11.0,1.0,26.0,18.0,1.0,1.0,0.0,19.0,2.0,7.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,0.0 +Andrea Pinamonti,it ITA,FW,Sassuolo,24-134,1999,6.0,6.0,469.0,4.0,0.0,0.0,0.0,1.0,0.0,0.77,0.0,0.77,0.77,0.77,1.2,1.2,0.23,0.23,5.2,4.0,0.0,30.8,0.77,0.31,1.0,0.09,2.8,2.8,68.0,94.0,72.3,893.0,123.0,39.0,45.0,86.7,22.0,27.0,81.5,1.0,4.0,25.0,4.0,3.0,0.0,0.0,4.0,80.0,13.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,7.0,10.0,1.91,7.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,1.0,3.0,0.0,3.0,0.0,138.0,5.0,6.0,69.0,63.0,20.0,138.0,67.0,3.0,0.0,2.0,98.0,11.0,3.0,0.0,1.0,6.0,1.0,0.0,0.0,0.0,5.0,10.0,25.0,28.6 +Lorenzo Pirola,it ITA,DF,Salernitana,21-222,2002,5.0,5.0,387.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,4.3,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,169.0,213.0,79.3,2567.0,1060.0,86.0,96.0,89.6,74.0,91.0,81.3,3.0,14.0,21.4,0.0,3.0,1.0,0.0,17.0,203.0,10.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,3.0,0.7,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,3.0,2.0,3.0,0.0,1.0,1.0,0.0,2.0,12.0,0.0,246.0,26.0,105.0,129.0,13.0,3.0,246.0,121.0,2.0,3.0,0.0,167.0,1.0,2.0,0.0,5.0,3.0,1.0,0.0,0.0,0.0,17.0,7.0,13.0,35.0 +Tommaso Pobega,it ITA,MF,Milan,24-077,1999,4.0,0.0,83.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,0.9,1.0,0.0,100.0,1.08,0.0,0.0,0.01,0.0,0.0,34.0,38.0,89.5,632.0,231.0,15.0,17.0,88.2,15.0,16.0,93.8,4.0,5.0,80.0,0.0,3.0,0.0,0.0,3.0,38.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,4.0,0.0,0.0,3.0,1.0,2.0,1.0,1.0,0.0,53.0,4.0,14.0,31.0,10.0,0.0,53.0,31.0,1.0,0.0,0.0,35.0,1.0,1.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 +Paul Pogba,fr FRA,MF,Juventus,30-199,1993,2.0,0.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,27.0,35.0,77.1,425.0,113.0,13.0,14.0,92.9,11.0,13.0,84.6,2.0,4.0,50.0,1.0,5.0,2.0,0.0,5.0,32.0,3.0,3.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,3.33,2.0,0.0,0.0,0.0,1.0,1.67,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,43.0,1.0,4.0,25.0,14.0,2.0,43.0,23.0,1.0,1.0,0.0,32.0,2.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,4.0,1.0,0.0,100.0 +Matteo Politano,it ITA,FW,Napoli,30-058,1993,6.0,4.0,341.0,2.0,1.0,0.0,0.0,1.0,0.0,0.53,0.26,0.79,0.53,0.79,0.7,0.7,0.2,0.2,3.8,2.0,1.0,28.6,0.53,0.29,1.0,0.11,1.3,1.3,133.0,177.0,75.1,2410.0,712.0,65.0,70.0,92.9,46.0,66.0,69.7,17.0,28.0,60.7,9.0,18.0,7.0,3.0,29.0,161.0,16.0,5.0,2.0,5.0,19.0,7.0,4.0,0.0,2.0,4.0,0.0,7.0,21.0,5.54,15.0,3.0,1.0,2.0,4.0,1.06,2.0,1.0,0.0,1.0,0.0,6.0,3.0,2.0,2.0,2.0,1.0,0.0,1.0,3.0,2.0,0.0,206.0,2.0,26.0,79.0,105.0,15.0,206.0,127.0,17.0,13.0,4.0,154.0,5.0,1.0,0.0,2.0,4.0,1.0,1.0,0.0,0.0,12.0,0.0,1.0,0.0 +Marin Pongračić,hr CRO,DF,Lecce,26-019,1997,6.0,6.0,540.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.01,0.01,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,282.0,323.0,87.3,6258.0,2501.0,60.0,70.0,85.7,173.0,185.0,93.5,46.0,59.0,78.0,2.0,20.0,1.0,0.0,21.0,295.0,27.0,27.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,7.0,1.17,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,4.0,4.0,3.0,0.0,8.0,5.0,3.0,7.0,26.0,0.0,377.0,61.0,182.0,186.0,13.0,5.0,377.0,244.0,7.0,4.0,0.0,238.0,2.0,1.0,0.0,9.0,2.0,0.0,0.0,0.0,0.0,26.0,11.0,7.0,61.1 +Stefan Posch,at AUT,DF,Bologna,26-139,1997,5.0,4.0,302.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.09,0.09,3.4,1.0,0.0,33.3,0.3,0.0,0.0,0.1,-0.3,-0.3,207.0,242.0,85.5,3433.0,1096.0,98.0,104.0,94.2,91.0,103.0,88.3,14.0,28.0,50.0,1.0,16.0,3.0,1.0,19.0,207.0,35.0,8.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,27.0,0.0,1.0,4.0,1.19,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,14.0,7.0,7.0,5.0,2.0,4.0,2.0,2.0,3.0,7.0,0.0,283.0,13.0,82.0,150.0,51.0,5.0,283.0,164.0,4.0,7.0,0.0,199.0,4.0,2.0,0.0,7.0,2.0,0.0,0.0,0.0,0.0,10.0,3.0,5.0,37.5 +Matteo Prati,it ITA,MF,Cagliari,19-276,2003,1.0,1.0,79.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,22.0,28.0,78.6,357.0,228.0,9.0,12.0,75.0,13.0,13.0,100.0,0.0,3.0,0.0,0.0,5.0,0.0,0.0,7.0,26.0,2.0,1.0,1.0,0.0,2.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,1.14,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,31.0,1.0,7.0,22.0,3.0,0.0,31.0,15.0,0.0,0.0,0.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 +Ivan Provedel,it ITA,GK,Lazio,29-197,1994,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,172.0,200.0,86.0,4248.0,2777.0,41.0,41.0,100.0,68.0,68.0,100.0,62.0,90.0,68.9,0.0,1.0,1.0,0.0,0.0,161.0,39.0,10.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,215.0,167.0,212.0,3.0,0.0,0.0,215.0,134.0,0.0,0.0,0.0,121.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,9.0,2.0,0.0,100.0 +Christian Pulisic,us USA,"FW,MF",Milan,25-012,1998,6.0,6.0,440.0,2.0,1.0,0.0,0.0,1.0,0.0,0.41,0.2,0.61,0.41,0.61,1.1,1.1,0.23,0.23,4.9,5.0,0.0,83.3,1.02,0.33,0.4,0.18,0.9,0.9,148.0,180.0,82.2,1958.0,439.0,86.0,99.0,86.9,44.0,50.0,88.0,6.0,10.0,60.0,5.0,11.0,8.0,2.0,17.0,173.0,7.0,1.0,2.0,1.0,14.0,5.0,0.0,5.0,0.0,1.0,0.0,6.0,16.0,3.27,9.0,2.0,1.0,2.0,5.0,1.02,3.0,0.0,0.0,0.0,1.0,3.0,3.0,0.0,2.0,1.0,2.0,0.0,2.0,3.0,1.0,0.0,215.0,1.0,18.0,107.0,95.0,8.0,215.0,165.0,13.0,10.0,6.0,175.0,10.0,5.0,0.0,6.0,11.0,0.0,0.0,0.0,0.0,18.0,3.0,6.0,33.3 +George Pușcaș,ro ROU,FW,Genoa,27-175,1996,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,2.0,1.0,0.0,3.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Domingos Quina,pt POR,MF,Udinese,23-316,1999,2.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,13.0,10.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Adrien Rabiot,fr FRA,MF,Juventus,28-180,1995,6.0,6.0,540.0,1.0,2.0,0.0,0.0,3.0,0.0,0.17,0.33,0.5,0.17,0.5,1.5,1.5,0.26,0.26,6.0,6.0,0.0,50.0,1.0,0.08,0.17,0.13,-0.5,-0.5,234.0,266.0,88.0,3469.0,765.0,133.0,142.0,93.7,79.0,93.0,84.9,14.0,16.0,87.5,9.0,18.0,2.0,0.0,21.0,259.0,7.0,3.0,2.0,4.0,4.0,0.0,0.0,0.0,0.0,4.0,0.0,5.0,17.0,2.83,14.0,0.0,2.0,1.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,16.0,8.0,5.0,9.0,2.0,8.0,2.0,6.0,7.0,6.0,0.0,336.0,12.0,57.0,179.0,104.0,24.0,336.0,205.0,11.0,13.0,3.0,226.0,7.0,1.0,0.0,10.0,7.0,2.0,0.0,0.0,0.0,38.0,10.0,6.0,62.5 +Uroš Račić,rs SRB,"MF,FW",Sassuolo,25-197,1998,2.0,0.0,35.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,0.06,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,9.0,11.0,81.8,156.0,36.0,4.0,5.0,80.0,5.0,5.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,10.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,15.0,2.0,4.0,7.0,4.0,0.0,15.0,5.0,0.0,0.0,0.0,8.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Nemanja Radonjić,rs SRB,"MF,FW",Torino,27-227,1996,6.0,3.0,292.0,3.0,0.0,0.0,0.0,0.0,0.0,0.92,0.0,0.92,0.92,0.92,1.7,1.7,0.53,0.53,3.2,5.0,0.0,41.7,1.54,0.25,0.6,0.14,1.3,1.3,42.0,67.0,62.7,630.0,148.0,23.0,33.0,69.7,12.0,18.0,66.7,4.0,8.0,50.0,3.0,3.0,3.0,2.0,4.0,65.0,1.0,0.0,0.0,1.0,10.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,8.0,2.47,4.0,0.0,2.0,0.0,1.0,0.31,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,3.0,0.0,3.0,0.0,0.0,0.0,110.0,0.0,9.0,36.0,65.0,12.0,110.0,71.0,10.0,2.0,5.0,86.0,12.0,3.0,0.0,0.0,3.0,4.0,0.0,0.0,0.0,9.0,0.0,5.0,0.0 +Boris Radunović,rs SRB,GK,Cagliari,27-127,1996,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,131.0,181.0,72.4,4355.0,3117.0,18.0,18.0,100.0,49.0,51.0,96.1,64.0,112.0,57.1,0.0,6.0,0.0,0.0,0.0,107.0,74.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,2.0,196.0,170.0,195.0,1.0,0.0,0.0,196.0,91.0,0.0,0.0,0.0,68.0,1.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,5.0,1.0,1.0,50.0 +Hamza Rafia,tn TUN,MF,Lecce,24-181,1999,6.0,5.0,337.0,1.0,0.0,0.0,0.0,2.0,0.0,0.27,0.0,0.27,0.27,0.27,0.3,0.3,0.09,0.09,3.7,1.0,0.0,20.0,0.27,0.2,1.0,0.07,0.7,0.7,113.0,153.0,73.9,1623.0,360.0,64.0,75.0,85.3,37.0,47.0,78.7,5.0,13.0,38.5,2.0,11.0,0.0,0.0,13.0,151.0,2.0,1.0,0.0,0.0,10.0,1.0,0.0,1.0,0.0,0.0,0.0,8.0,8.0,2.14,4.0,0.0,1.0,1.0,1.0,0.27,0.0,0.0,0.0,0.0,1.0,7.0,5.0,0.0,6.0,1.0,12.0,1.0,11.0,3.0,4.0,0.0,203.0,2.0,24.0,115.0,64.0,6.0,203.0,138.0,7.0,4.0,2.0,157.0,6.0,8.0,0.0,10.0,9.0,0.0,0.0,0.0,0.0,18.0,2.0,5.0,28.6 +Ylber Ramadani,al ALB,MF,Lecce,27-171,1996,6.0,6.0,518.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.09,0.09,5.8,2.0,0.0,18.2,0.35,0.0,0.0,0.05,-0.5,-0.5,191.0,238.0,80.3,3549.0,866.0,73.0,86.0,84.9,91.0,100.0,91.0,21.0,38.0,55.3,5.0,17.0,3.0,1.0,26.0,232.0,6.0,6.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,13.0,2.26,8.0,1.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,7.0,5.0,6.0,1.0,7.0,4.0,3.0,7.0,5.0,0.0,304.0,11.0,78.0,175.0,61.0,2.0,304.0,169.0,8.0,9.0,0.0,178.0,6.0,6.0,0.0,3.0,7.0,0.0,0.0,0.0,0.0,40.0,5.0,3.0,62.5 +Luca Ranieri,it ITA,DF,Fiorentina,24-160,1999,3.0,3.0,270.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,141.0,169.0,83.4,2919.0,1118.0,47.0,53.0,88.7,69.0,75.0,92.0,23.0,37.0,62.2,1.0,8.0,0.0,0.0,4.0,167.0,2.0,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,4.0,1.0,6.0,8.0,0.0,190.0,17.0,104.0,85.0,2.0,0.0,190.0,128.0,0.0,2.0,0.0,134.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,10.0,2.0,5.0,28.6 +Filippo Ranocchia,it ITA,MF,Empoli,22-139,2001,1.0,1.0,68.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.05,0.05,0.8,1.0,1.0,100.0,1.32,0.0,0.0,0.04,0.0,0.0,26.0,28.0,92.9,460.0,121.0,12.0,12.0,100.0,13.0,13.0,100.0,1.0,2.0,50.0,0.0,4.0,1.0,0.0,2.0,26.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.32,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,4.0,0.0,40.0,4.0,15.0,22.0,3.0,0.0,40.0,20.0,0.0,0.0,0.0,23.0,2.0,1.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0 +Giacomo Raspadori,it ITA,"FW,MF",Napoli,23-224,2000,6.0,3.0,304.0,1.0,0.0,0.0,1.0,0.0,0.0,0.3,0.0,0.3,0.3,0.3,1.6,0.8,0.48,0.25,3.4,4.0,0.0,33.3,1.18,0.08,0.25,0.07,-0.6,0.2,106.0,134.0,79.1,1887.0,394.0,45.0,53.0,84.9,42.0,48.0,87.5,14.0,21.0,66.7,5.0,8.0,2.0,0.0,10.0,128.0,5.0,1.0,3.0,3.0,6.0,3.0,1.0,2.0,0.0,1.0,1.0,4.0,12.0,3.54,9.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,5.0,4.0,5.0,2.0,5.0,0.0,5.0,1.0,1.0,0.0,171.0,2.0,15.0,76.0,82.0,19.0,170.0,103.0,5.0,7.0,1.0,132.0,7.0,3.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,9.0,3.0,2.0,60.0 +Tijjani Reijnders,nl NED,MF,Milan,25-063,1998,6.0,6.0,494.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.18,0.18,0.0,0.18,0.6,0.6,0.1,0.1,5.5,2.0,0.0,20.0,0.36,0.0,0.0,0.06,-0.6,-0.6,211.0,237.0,89.0,3190.0,865.0,114.0,121.0,94.2,74.0,83.0,89.2,12.0,20.0,60.0,7.0,23.0,4.0,1.0,30.0,217.0,20.0,11.0,3.0,1.0,9.0,7.0,5.0,0.0,0.0,1.0,0.0,2.0,21.0,3.83,15.0,3.0,2.0,0.0,4.0,0.73,4.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,6.0,1.0,5.0,2.0,4.0,0.0,286.0,10.0,29.0,167.0,94.0,15.0,286.0,204.0,14.0,15.0,3.0,214.0,13.0,9.0,0.0,4.0,6.0,0.0,0.0,0.0,0.0,27.0,1.0,4.0,20.0 +Mateo Retegui,it ITA,FW,Genoa,24-154,1999,6.0,6.0,489.0,3.0,0.0,0.0,0.0,3.0,0.0,0.55,0.0,0.55,0.55,0.55,1.0,1.0,0.19,0.19,5.4,7.0,0.0,77.8,1.29,0.33,0.43,0.11,2.0,2.0,58.0,89.0,65.2,739.0,68.0,37.0,49.0,75.5,14.0,24.0,58.3,3.0,4.0,75.0,2.0,0.0,0.0,0.0,1.0,81.0,7.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,1.0,4.0,4.0,0.74,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,0.0,1.0,3.0,0.0,3.0,0.0,3.0,0.0,142.0,5.0,18.0,69.0,56.0,10.0,142.0,77.0,2.0,2.0,0.0,104.0,14.0,6.0,0.0,7.0,8.0,1.0,0.0,0.0,0.0,9.0,13.0,15.0,46.4 +Samuele Ricci,it ITA,MF,Torino,22-040,2001,5.0,5.0,424.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.21,0.21,0.0,0.21,0.1,0.1,0.01,0.01,4.7,1.0,0.0,25.0,0.21,0.0,0.0,0.02,-0.1,-0.1,222.0,255.0,87.1,3706.0,1030.0,108.0,116.0,93.1,92.0,98.0,93.9,17.0,30.0,56.7,4.0,20.0,3.0,0.0,27.0,234.0,21.0,17.0,0.0,1.0,10.0,4.0,3.0,0.0,0.0,0.0,0.0,5.0,9.0,1.91,7.0,1.0,1.0,0.0,1.0,0.21,0.0,0.0,1.0,0.0,0.0,5.0,2.0,4.0,1.0,0.0,3.0,0.0,3.0,5.0,2.0,0.0,279.0,4.0,54.0,179.0,47.0,1.0,279.0,185.0,6.0,2.0,0.0,194.0,3.0,4.0,0.0,9.0,4.0,1.0,0.0,0.0,0.0,27.0,2.0,1.0,66.7 +Ricardo Rodríguez,ch SUI,DF,Torino,31-036,1992,6.0,6.0,524.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,5.8,0.0,1.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,279.0,325.0,85.8,4755.0,1842.0,131.0,138.0,94.9,120.0,133.0,90.2,24.0,46.0,52.2,2.0,30.0,1.0,1.0,26.0,317.0,8.0,6.0,0.0,5.0,5.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,7.0,1.2,6.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,5.0,3.0,5.0,0.0,9.0,3.0,6.0,6.0,11.0,0.0,368.0,23.0,136.0,200.0,33.0,0.0,368.0,237.0,8.0,12.0,0.0,257.0,1.0,1.0,0.0,3.0,5.0,0.0,0.0,0.0,0.0,24.0,10.0,7.0,58.8 +Alessio Romagnoli,it ITA,DF,Lazio,28-261,1995,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,6.0,1.0,0.0,100.0,0.17,0.0,0.0,0.03,0.0,0.0,348.0,378.0,92.1,5954.0,2299.0,155.0,165.0,93.9,154.0,166.0,92.8,30.0,37.0,81.1,2.0,23.0,1.0,0.0,30.0,345.0,33.0,12.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,6.0,0.0,0.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,3.0,2.0,1.0,2.0,0.0,4.0,4.0,0.0,8.0,19.0,0.0,419.0,62.0,180.0,234.0,7.0,3.0,419.0,222.0,5.0,0.0,0.0,273.0,3.0,0.0,0.0,8.0,4.0,0.0,0.0,0.0,0.0,28.0,13.0,10.0,56.5 +Simone Romagnoli,it ITA,DF,Frosinone,33-233,1990,6.0,6.0,540.0,1.0,1.0,0.0,0.0,1.0,0.0,0.17,0.17,0.33,0.17,0.33,0.1,0.1,0.02,0.02,6.0,1.0,0.0,50.0,0.17,0.5,1.0,0.06,0.9,0.9,266.0,298.0,89.3,4298.0,1641.0,136.0,144.0,94.4,109.0,114.0,95.6,16.0,29.0,55.2,2.0,5.0,0.0,0.0,9.0,251.0,47.0,21.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.33,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,2.0,4.0,2.0,0.0,11.0,10.0,1.0,5.0,36.0,0.0,363.0,102.0,225.0,131.0,8.0,5.0,363.0,127.0,0.0,0.0,0.0,200.0,1.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,23.0,12.0,10.0,54.5 +Luka Romero,ar ARG,FW,Milan,18-316,2004,1.0,0.0,22.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,17.0,88.2,177.0,26.0,10.0,11.0,90.9,3.0,3.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,4.09,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,0.0,4.0,8.0,6.0,0.0,18.0,18.0,1.0,1.0,0.0,16.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0 +Marten de Roon,nl NED,MF,Atalanta,32-185,1991,6.0,6.0,540.0,0.0,3.0,0.0,0.0,3.0,0.0,0.0,0.5,0.5,0.0,0.5,0.1,0.1,0.02,0.02,6.0,1.0,0.0,33.3,0.17,0.0,0.0,0.03,-0.1,-0.1,274.0,333.0,82.3,5315.0,1565.0,97.0,111.0,87.4,136.0,152.0,89.5,35.0,54.0,64.8,6.0,28.0,6.0,0.0,38.0,319.0,13.0,10.0,1.0,8.0,4.0,0.0,0.0,0.0,0.0,3.0,1.0,5.0,7.0,1.17,7.0,0.0,0.0,0.0,3.0,0.5,3.0,0.0,0.0,0.0,0.0,16.0,6.0,8.0,8.0,0.0,5.0,0.0,5.0,10.0,9.0,0.0,388.0,14.0,104.0,213.0,75.0,0.0,388.0,224.0,5.0,8.0,0.0,259.0,5.0,1.0,0.0,8.0,6.0,2.0,0.0,0.0,0.0,41.0,5.0,3.0,62.5 +Nicolò Rovella,it ITA,MF,Lazio,21-300,2001,3.0,1.0,150.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,1.7,0.0,1.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,96.0,105.0,91.4,1591.0,255.0,49.0,51.0,96.1,37.0,38.0,97.4,8.0,9.0,88.9,0.0,6.0,0.0,0.0,5.0,103.0,2.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.8,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,4.0,3.0,1.0,0.0,2.0,0.0,2.0,6.0,2.0,0.0,129.0,5.0,30.0,84.0,16.0,0.0,129.0,62.0,2.0,2.0,0.0,91.0,1.0,1.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,10.0,0.0,0.0,0.0 +Amir Rrahmani,xk KVX,DF,Napoli,29-218,1994,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.1,-0.1,228.0,259.0,88.0,4278.0,1464.0,88.0,92.0,95.7,112.0,122.0,91.8,27.0,41.0,65.9,1.0,16.0,0.0,0.0,13.0,251.0,7.0,5.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,8.0,2.67,6.0,0.0,1.0,0.0,2.0,0.67,2.0,0.0,0.0,0.0,0.0,3.0,3.0,1.0,2.0,0.0,3.0,0.0,3.0,4.0,4.0,0.0,276.0,21.0,105.0,163.0,8.0,6.0,276.0,201.0,0.0,0.0,0.0,208.0,2.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,25.0,6.0,2.0,75.0 +Ruan,br BRA,DF,Sassuolo,24-115,1999,5.0,4.0,345.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.8,1.0,0.0,50.0,0.26,0.0,0.0,0.06,-0.1,-0.1,110.0,129.0,85.3,2100.0,692.0,42.0,49.0,85.7,52.0,57.0,91.2,14.0,19.0,73.7,2.0,6.0,2.0,0.0,6.0,104.0,25.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.52,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,0.0,3.0,1.0,2.0,1.0,1.0,10.0,16.0,0.0,165.0,33.0,102.0,60.0,7.0,3.0,165.0,58.0,0.0,1.0,0.0,66.0,1.0,1.0,0.0,7.0,4.0,0.0,0.0,1.0,0.0,18.0,7.0,3.0,70.0 +Daniele Rugani,it ITA,DF,Juventus,29-063,1994,1.0,1.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,40.0,95.0,751.0,298.0,11.0,11.0,100.0,24.0,26.0,92.3,3.0,3.0,100.0,0.0,4.0,0.0,0.0,2.0,39.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,44.0,2.0,17.0,23.0,4.0,1.0,44.0,32.0,0.0,2.0,0.0,29.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Matteo Ruggeri,it ITA,"DF,MF",Atalanta,21-081,2002,6.0,6.0,490.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.37,0.37,0.0,0.37,0.1,0.1,0.02,0.02,5.4,1.0,0.0,50.0,0.18,0.0,0.0,0.04,-0.1,-0.1,222.0,277.0,80.1,3221.0,1168.0,121.0,141.0,85.8,84.0,99.0,84.8,11.0,25.0,44.0,6.0,10.0,4.0,3.0,25.0,235.0,42.0,1.0,0.0,0.0,19.0,2.0,0.0,1.0,0.0,39.0,0.0,3.0,16.0,2.94,15.0,1.0,0.0,0.0,5.0,0.92,4.0,1.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,10.0,0.0,10.0,4.0,8.0,0.0,324.0,7.0,88.0,108.0,129.0,6.0,324.0,175.0,8.0,7.0,2.0,203.0,5.0,1.0,0.0,7.0,2.0,1.0,0.0,0.0,0.0,22.0,5.0,10.0,33.3 +Mário Rui,pt POR,DF,Napoli,32-126,1991,5.0,2.0,232.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.04,0.04,2.6,1.0,0.0,50.0,0.39,0.0,0.0,0.05,-0.1,-0.1,141.0,178.0,79.2,2421.0,789.0,71.0,77.0,92.2,52.0,64.0,81.3,14.0,28.0,50.0,3.0,12.0,2.0,0.0,12.0,149.0,29.0,11.0,0.0,2.0,11.0,2.0,0.0,2.0,0.0,16.0,0.0,3.0,6.0,2.33,4.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,5.0,5.0,1.0,4.0,2.0,0.0,2.0,4.0,4.0,0.0,202.0,5.0,56.0,102.0,46.0,2.0,202.0,96.0,1.0,1.0,0.0,130.0,2.0,1.0,0.0,7.0,5.0,0.0,0.0,0.0,0.0,13.0,1.0,4.0,20.0 +Stefano Sabelli,it ITA,"DF,MF",Genoa,30-260,1993,5.0,5.0,376.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,4.2,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,69.0,125.0,55.2,1206.0,519.0,36.0,47.0,76.6,25.0,45.0,55.6,7.0,27.0,25.9,0.0,5.0,1.0,0.0,5.0,109.0,16.0,1.0,0.0,2.0,12.0,0.0,0.0,0.0,0.0,15.0,0.0,3.0,2.0,0.48,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,2.0,6.0,2.0,0.0,3.0,0.0,3.0,5.0,9.0,0.0,164.0,14.0,58.0,71.0,36.0,2.0,164.0,83.0,6.0,6.0,1.0,96.0,6.0,2.0,0.0,8.0,6.0,1.0,0.0,0.0,0.0,17.0,0.0,0.0,0.0 +Alexis Saelemaekers,be BEL,FW,Bologna,24-095,1999,2.0,0.0,53.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,19.0,78.9,215.0,70.0,9.0,9.0,100.0,4.0,5.0,80.0,1.0,3.0,33.3,1.0,3.0,0.0,0.0,4.0,16.0,3.0,1.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,1.0,3.0,5.09,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,32.0,0.0,2.0,18.0,12.0,1.0,32.0,23.0,5.0,2.0,0.0,27.0,4.0,1.0,1.0,1.0,5.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,100.0 +Lazar Samardzic,rs SRB,MF,Udinese,21-218,2002,6.0,4.0,417.0,2.0,0.0,0.0,0.0,0.0,0.0,0.43,0.0,0.43,0.43,0.43,0.6,0.6,0.12,0.12,4.6,6.0,3.0,60.0,1.29,0.2,0.33,0.06,1.4,1.4,160.0,210.0,76.2,2792.0,878.0,75.0,88.0,85.2,48.0,58.0,82.8,27.0,45.0,60.0,11.0,19.0,5.0,2.0,15.0,180.0,29.0,5.0,2.0,4.0,21.0,20.0,10.0,6.0,0.0,4.0,1.0,4.0,27.0,5.83,13.0,7.0,1.0,0.0,2.0,0.43,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,2.0,1.0,1.0,2.0,0.0,0.0,247.0,3.0,37.0,126.0,89.0,4.0,247.0,142.0,13.0,6.0,2.0,158.0,8.0,0.0,0.0,7.0,1.0,0.0,0.0,0.0,0.0,31.0,4.0,6.0,40.0 +Junior Sambia,fr FRA,MF,Salernitana,27-023,1996,1.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,69.0,23.0,3.0,3.0,100.0,2.0,2.0,100.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,11.0,3.0,5.0,2.0,4.0,0.0,11.0,6.0,0.0,1.0,0.0,6.0,2.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,50.0 +Antonio Sanabria,py PAR,"MF,FW",Torino,27-210,1996,4.0,3.0,212.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,2.4,1.0,0.0,100.0,0.42,0.0,0.0,0.11,-0.1,-0.1,40.0,61.0,65.6,574.0,66.0,26.0,31.0,83.9,11.0,21.0,52.4,1.0,3.0,33.3,0.0,2.0,1.0,1.0,2.0,58.0,3.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.43,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,77.0,1.0,4.0,38.0,35.0,3.0,77.0,46.0,2.0,2.0,0.0,59.0,4.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,1.0,5.0,10.0,33.3 +Renato Sanches,pt POR,MF,Roma,26-043,1997,2.0,1.0,71.0,1.0,0.0,0.0,0.0,1.0,0.0,1.27,0.0,1.27,1.27,1.27,0.1,0.1,0.1,0.1,0.8,1.0,0.0,50.0,1.27,0.5,1.0,0.04,0.9,0.9,30.0,32.0,93.8,446.0,105.0,17.0,17.0,100.0,12.0,13.0,92.3,1.0,2.0,50.0,3.0,2.0,2.0,1.0,4.0,32.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.34,5.0,0.0,0.0,0.0,1.0,1.27,1.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,44.0,0.0,10.0,16.0,19.0,3.0,44.0,27.0,3.0,3.0,1.0,32.0,2.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,0.0,2.0,0.0 +Alexis Sánchez,cl CHI,FW,Inter,34-285,1988,2.0,0.0,33.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,18.0,83.3,191.0,57.0,7.0,9.0,77.8,3.0,3.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,1.0,18.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,26.0,0.0,1.0,17.0,8.0,1.0,26.0,19.0,1.0,0.0,0.0,22.0,3.0,0.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,1.0,2.0,1.0,66.7 +Alex Sandro,br BRA,DF,Juventus,32-247,1991,2.0,2.0,180.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,143.0,167.0,85.6,2364.0,821.0,67.0,72.0,93.1,64.0,67.0,95.5,12.0,24.0,50.0,2.0,16.0,5.0,2.0,18.0,145.0,21.0,6.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,13.0,1.0,1.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,0.0,2.0,0.0,2.0,1.0,1.0,5.0,5.0,0.0,182.0,13.0,45.0,109.0,28.0,2.0,182.0,109.0,7.0,4.0,0.0,126.0,2.0,3.0,0.0,4.0,3.0,0.0,0.0,0.0,0.0,13.0,2.0,1.0,66.7 +Nicola Sansone,it ITA,"MF,FW",Lecce,32-020,1991,2.0,0.0,40.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,8.0,87.5,95.0,3.0,5.0,5.0,100.0,2.0,2.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,11.0,0.0,2.0,7.0,2.0,0.0,11.0,6.0,0.0,0.0,0.0,8.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0 +Riccardo Saponara,it ITA,"MF,FW",Hellas Verona,31-283,1991,4.0,0.0,64.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.03,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,17.0,26.0,65.4,240.0,39.0,10.0,13.0,76.9,5.0,8.0,62.5,1.0,2.0,50.0,1.0,0.0,0.0,0.0,1.0,24.0,2.0,2.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,2.81,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,0.0,39.0,0.0,8.0,15.0,18.0,2.0,39.0,24.0,6.0,5.0,2.0,24.0,4.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Saba Sazonov,ge GEO,DF,Torino,21-241,2002,1.0,0.0,64.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,41.0,44.0,93.2,709.0,224.0,18.0,18.0,100.0,21.0,22.0,95.5,2.0,3.0,66.7,0.0,0.0,0.0,0.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,3.0,0.0,52.0,2.0,43.0,10.0,0.0,0.0,52.0,39.0,0.0,0.0,0.0,36.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,3.0,25.0 +Giorgio Scalvini,it ITA,DF,Atalanta,19-293,2003,6.0,5.0,463.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.08,0.08,5.1,1.0,0.0,50.0,0.19,0.0,0.0,0.2,-0.4,-0.4,233.0,280.0,83.2,3855.0,1403.0,105.0,115.0,91.3,108.0,123.0,87.8,13.0,29.0,44.8,1.0,9.0,2.0,0.0,10.0,261.0,18.0,9.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,9.0,1.0,3.0,4.0,0.78,3.0,0.0,1.0,0.0,1.0,0.19,0.0,0.0,1.0,0.0,0.0,16.0,9.0,11.0,5.0,0.0,15.0,5.0,10.0,12.0,19.0,0.0,348.0,33.0,184.0,140.0,30.0,5.0,348.0,168.0,5.0,3.0,1.0,182.0,4.0,1.0,0.0,6.0,0.0,1.0,0.0,0.0,0.0,40.0,18.0,10.0,64.3 +Gianluca Scamacca,it ITA,FW,Atalanta,24-272,1999,4.0,1.0,165.0,2.0,0.0,0.0,0.0,0.0,0.0,1.09,0.0,1.09,1.09,1.09,0.9,0.9,0.47,0.47,1.8,3.0,0.0,33.3,1.64,0.22,0.67,0.1,1.1,1.1,41.0,61.0,67.2,807.0,135.0,17.0,29.0,58.6,11.0,14.0,78.6,10.0,11.0,90.9,2.0,4.0,1.0,0.0,4.0,57.0,3.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,7.0,3.84,7.0,0.0,0.0,0.0,1.0,0.55,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,1.0,1.0,0.0,89.0,1.0,3.0,40.0,47.0,14.0,89.0,67.0,5.0,1.0,1.0,78.0,5.0,7.0,0.0,3.0,4.0,1.0,0.0,0.0,0.0,2.0,5.0,6.0,45.5 +Perr Schuurs,nl NED,DF,Torino,23-308,1999,6.0,6.0,540.0,1.0,0.0,0.0,0.0,2.0,0.0,0.17,0.0,0.17,0.17,0.17,0.7,0.7,0.11,0.11,6.0,1.0,0.0,20.0,0.17,0.2,1.0,0.13,0.3,0.3,238.0,272.0,87.5,4230.0,1167.0,93.0,105.0,88.6,124.0,131.0,94.7,18.0,30.0,60.0,0.0,9.0,1.0,1.0,13.0,262.0,10.0,8.0,0.0,5.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,4.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,13.0,9.0,8.0,4.0,1.0,8.0,0.0,8.0,8.0,13.0,0.0,336.0,31.0,160.0,150.0,31.0,6.0,336.0,193.0,8.0,5.0,0.0,206.0,8.0,4.0,0.0,7.0,0.0,0.0,0.0,1.0,0.0,32.0,6.0,4.0,60.0 +Demba Seck,sn SEN,MF,Torino,22-232,2001,3.0,2.0,179.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.08,0.08,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.03,-0.2,-0.2,39.0,50.0,78.0,654.0,111.0,17.0,23.0,73.9,19.0,22.0,86.4,3.0,3.0,100.0,0.0,6.0,2.0,0.0,6.0,50.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,1.5,2.0,0.0,0.0,1.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,75.0,1.0,7.0,34.0,38.0,6.0,75.0,62.0,12.0,11.0,3.0,61.0,6.0,8.0,0.0,5.0,5.0,0.0,0.0,0.0,0.0,10.0,2.0,4.0,33.3 +Vivaldo Semedo,pt POR,FW,Udinese,18-245,2005,1.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,2.0,1.0,1.0,3.0,3.0,1.0,0.0,1.0,3.0,1.0,2.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Stefano Sensi,it ITA,MF,Inter,28-056,1995,1.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,12.0,83.3,190.0,34.0,4.0,4.0,100.0,5.0,7.0,71.4,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,1.0,3.0,8.0,1.0,0.0,12.0,10.0,1.0,1.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Suat Serdar,de GER,MF,Hellas Verona,26-172,1997,4.0,0.0,112.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,1.2,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,23.0,29.0,79.3,390.0,95.0,10.0,10.0,100.0,10.0,13.0,76.9,2.0,2.0,100.0,0.0,3.0,0.0,0.0,3.0,28.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,2.0,1.0,0.0,0.0,0.0,2.0,3.0,0.0,43.0,5.0,11.0,21.0,11.0,0.0,43.0,20.0,0.0,0.0,0.0,23.0,3.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,20.0 +Stephan El Shaarawy,it ITA,"FW,MF",Roma,30-338,1992,6.0,3.0,294.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.18,0.18,3.3,2.0,1.0,28.6,0.61,0.0,0.0,0.08,-0.6,-0.6,91.0,107.0,85.0,1497.0,287.0,54.0,63.0,85.7,26.0,30.0,86.7,10.0,11.0,90.9,7.0,4.0,3.0,1.0,9.0,102.0,5.0,0.0,1.0,4.0,5.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,11.0,3.36,10.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,2.0,1.0,1.0,0.0,3.0,0.0,134.0,4.0,15.0,61.0,59.0,11.0,134.0,94.0,8.0,1.0,5.0,107.0,2.0,2.0,0.0,2.0,4.0,1.0,0.0,0.0,0.0,5.0,1.0,2.0,33.3 +Eldor Shomurodov,uz UZB,FW,Cagliari,28-093,1995,6.0,1.0,212.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.07,0.07,2.4,0.0,0.0,0.0,0.0,0.0,0.0,0.05,-0.2,-0.2,47.0,61.0,77.0,576.0,104.0,33.0,42.0,78.6,11.0,13.0,84.6,1.0,2.0,50.0,4.0,5.0,1.0,0.0,4.0,58.0,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,2.97,7.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,81.0,0.0,7.0,39.0,37.0,10.0,81.0,51.0,4.0,4.0,2.0,67.0,8.0,3.0,0.0,4.0,2.0,0.0,0.0,0.0,0.0,10.0,6.0,8.0,42.9 +Steven Shpendi,al ALB,"FW,MF",Empoli,20-134,2003,5.0,2.0,196.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.06,0.06,2.2,2.0,0.0,66.7,0.92,0.0,0.0,0.04,-0.1,-0.1,27.0,39.0,69.2,302.0,69.0,20.0,25.0,80.0,3.0,4.0,75.0,0.0,0.0,0.0,4.0,2.0,3.0,0.0,4.0,32.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,5.0,2.3,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,1.0,0.0,0.0,61.0,0.0,4.0,29.0,29.0,12.0,61.0,40.0,3.0,1.0,2.0,44.0,7.0,4.0,0.0,5.0,6.0,3.0,0.0,0.0,0.0,8.0,1.0,6.0,14.3 +Marco Silvestri,it ITA,GK,Udinese,32-212,1991,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,140.0,177.0,79.1,3533.0,2508.0,28.0,29.0,96.6,81.0,82.0,98.8,31.0,66.0,47.0,0.0,1.0,0.0,0.0,0.0,119.0,58.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.17,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,191.0,173.0,191.0,0.0,0.0,0.0,191.0,100.0,0.0,0.0,0.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0,0.0,0.0 +Giovanni Simeone,ar ARG,"FW,MF",Napoli,28-087,1995,5.0,0.0,57.0,1.0,0.0,0.0,0.0,1.0,0.0,1.58,0.0,1.58,1.58,1.58,0.6,0.6,0.88,0.88,0.6,5.0,0.0,100.0,7.89,0.2,0.2,0.11,0.4,0.4,11.0,14.0,78.6,147.0,46.0,6.0,6.0,100.0,4.0,4.0,100.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,4.0,13.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,6.32,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,2.0,0.0,2.0,0.0,0.0,0.0,27.0,0.0,0.0,8.0,19.0,10.0,27.0,20.0,2.0,2.0,2.0,22.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,100.0 +Leo Skiri Østigård,no NOR,DF,Napoli,23-306,1999,5.0,3.0,272.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,210.0,238.0,88.2,3896.0,1467.0,70.0,73.0,95.9,124.0,135.0,91.9,14.0,26.0,53.8,2.0,15.0,2.0,0.0,18.0,236.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,3.0,0.99,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,3.0,4.0,3.0,0.0,3.0,3.0,0.0,5.0,8.0,0.0,266.0,27.0,100.0,155.0,13.0,1.0,266.0,178.0,7.0,4.0,0.0,191.0,1.0,1.0,0.0,2.0,2.0,1.0,0.0,0.0,0.0,19.0,5.0,2.0,71.4 +Łukasz Skorupski,pl POL,GK,Bologna,32-148,1991,6.0,6.0,540.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,159.0,194.0,82.0,4255.0,3167.0,36.0,36.0,100.0,72.0,72.0,100.0,51.0,85.0,60.0,0.0,1.0,0.0,0.0,0.0,146.0,47.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,207.0,192.0,207.0,0.0,0.0,0.0,207.0,121.0,0.0,0.0,0.0,111.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0 +Chris Smalling,eng ENG,DF,Roma,33-312,1989,3.0,3.0,244.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,2.7,1.0,0.0,100.0,0.37,0.0,0.0,0.05,0.0,0.0,138.0,156.0,88.5,2681.0,1000.0,43.0,51.0,84.3,85.0,89.0,95.5,9.0,13.0,69.2,1.0,6.0,0.0,0.0,10.0,152.0,4.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.37,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,4.0,3.0,0.0,174.0,11.0,70.0,93.0,11.0,6.0,174.0,107.0,1.0,2.0,0.0,120.0,1.0,0.0,0.0,1.0,2.0,0.0,0.0,0.0,0.0,17.0,13.0,3.0,81.3 +Ola Solbakken,no NOR,FW,Roma,25-023,1998,1.0,0.0,23.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,8.0,75.0,96.0,4.0,4.0,5.0,80.0,1.0,1.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.91,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,2.0,2.0,4.0,0.0,8.0,5.0,1.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,2.0,0.0 +Yann Sommer,ch SUI,GK,Inter,34-287,1988,6.0,6.0,540.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,183.0,216.0,84.7,4660.0,3175.0,42.0,42.0,100.0,88.0,89.0,98.9,51.0,82.0,62.2,0.0,2.0,0.0,0.0,0.0,168.0,47.0,8.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,223.0,185.0,222.0,1.0,0.0,0.0,223.0,151.0,0.0,0.0,0.0,134.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Brandon Soppy,fr FRA,DF,Torino,21-221,2002,2.0,0.0,34.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,17.0,25.0,68.0,246.0,67.0,9.0,10.0,90.0,4.0,7.0,57.1,2.0,5.0,40.0,1.0,0.0,1.0,1.0,0.0,23.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,1.0,2.65,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,32.0,3.0,7.0,13.0,12.0,0.0,32.0,20.0,3.0,2.0,0.0,18.0,1.0,1.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,8.0,0.0,0.0,0.0 +Alessandro Sorrentino,it ITA,GK,Monza,21-180,2002,1.0,1.0,90.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,25.0,27.0,92.6,491.0,347.0,10.0,10.0,100.0,11.0,12.0,91.7,4.0,5.0,80.0,0.0,0.0,0.0,0.0,0.0,25.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,28.0,22.0,27.0,1.0,0.0,0.0,28.0,23.0,0.0,0.0,0.0,17.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Riccardo Sottil,it ITA,FW,Fiorentina,24-119,1999,4.0,2.0,188.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.7,0.34,0.34,2.1,4.0,1.0,80.0,1.91,0.0,0.0,0.14,-0.7,-0.7,48.0,61.0,78.7,681.0,157.0,26.0,27.0,96.3,19.0,21.0,90.5,1.0,2.0,50.0,1.0,3.0,1.0,0.0,7.0,61.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,5.0,2.39,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,1.0,1.0,2.0,2.0,0.0,2.0,1.0,0.0,0.0,90.0,0.0,4.0,35.0,54.0,11.0,90.0,65.0,13.0,7.0,4.0,66.0,5.0,3.0,0.0,1.0,4.0,2.0,0.0,0.0,0.0,11.0,0.0,1.0,0.0 +Matìas Soulé,ar ARG,"FW,MF",Frosinone,20-168,2003,4.0,4.0,318.0,1.0,1.0,0.0,0.0,1.0,0.0,0.28,0.28,0.57,0.28,0.57,1.2,1.2,0.33,0.33,3.5,1.0,0.0,12.5,0.28,0.13,1.0,0.14,-0.2,-0.2,128.0,164.0,78.0,2111.0,656.0,72.0,80.0,90.0,34.0,42.0,81.0,17.0,22.0,77.3,10.0,12.0,5.0,1.0,19.0,143.0,17.0,2.0,0.0,0.0,11.0,9.0,4.0,3.0,0.0,6.0,4.0,6.0,19.0,5.38,9.0,4.0,1.0,0.0,1.0,0.28,0.0,1.0,0.0,0.0,0.0,11.0,9.0,6.0,3.0,2.0,5.0,1.0,4.0,4.0,2.0,0.0,220.0,6.0,40.0,97.0,88.0,10.0,220.0,135.0,11.0,11.0,1.0,146.0,11.0,7.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,26.0,2.0,3.0,40.0 +Leonardo Spinazzola,it ITA,"DF,FW",Roma,30-189,1993,6.0,4.0,376.0,1.0,1.0,0.0,0.0,0.0,0.0,0.24,0.24,0.48,0.24,0.48,0.1,0.1,0.02,0.02,4.2,2.0,0.0,66.7,0.48,0.33,0.5,0.03,0.9,0.9,198.0,251.0,78.9,3413.0,912.0,95.0,104.0,91.3,85.0,103.0,82.5,16.0,34.0,47.1,8.0,10.0,12.0,4.0,18.0,215.0,35.0,1.0,1.0,2.0,20.0,0.0,0.0,0.0,0.0,34.0,1.0,6.0,16.0,3.84,14.0,1.0,0.0,0.0,3.0,0.72,2.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,2.0,0.0,3.0,1.0,2.0,1.0,4.0,0.0,282.0,9.0,77.0,123.0,83.0,5.0,282.0,180.0,34.0,21.0,3.0,193.0,5.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,25.0,3.0,0.0,100.0 +Marco Sportiello,it ITA,GK,Milan,31-143,1992,2.0,2.0,180.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,61.0,71.0,85.9,1464.0,989.0,14.0,14.0,100.0,32.0,32.0,100.0,15.0,25.0,60.0,0.0,1.0,0.0,0.0,0.0,65.0,6.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,0.0,1.0,0.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,75.0,62.0,75.0,0.0,0.0,0.0,75.0,61.0,0.0,0.0,0.0,44.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0 +Gabriel Strefezza,br BRA,FW,Lecce,26-165,1997,6.0,4.0,353.0,1.0,0.0,1.0,1.0,1.0,0.0,0.25,0.0,0.25,0.0,0.0,1.3,0.5,0.33,0.13,3.9,1.0,1.0,10.0,0.25,0.0,0.0,0.05,-0.3,-0.5,100.0,136.0,73.5,1547.0,415.0,53.0,59.0,89.8,34.0,50.0,68.0,8.0,16.0,50.0,10.0,5.0,5.0,3.0,18.0,109.0,26.0,9.0,1.0,0.0,20.0,10.0,4.0,0.0,0.0,2.0,1.0,3.0,17.0,4.35,13.0,2.0,1.0,1.0,1.0,0.26,1.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,1.0,1.0,4.0,0.0,4.0,0.0,4.0,0.0,179.0,3.0,14.0,64.0,104.0,11.0,178.0,115.0,14.0,11.0,2.0,127.0,7.0,9.0,0.0,9.0,10.0,1.0,0.0,0.0,0.0,12.0,0.0,2.0,0.0 +Kevin Strootman,nl NED,MF,Genoa,33-229,1990,5.0,5.0,321.0,0.0,2.0,0.0,0.0,2.0,0.0,0.0,0.56,0.56,0.0,0.56,0.0,0.0,0.0,0.0,3.6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,95.0,120.0,79.2,1655.0,481.0,46.0,51.0,90.2,39.0,44.0,88.6,9.0,17.0,52.9,6.0,9.0,1.0,1.0,12.0,116.0,4.0,3.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,7.0,1.96,7.0,0.0,0.0,0.0,2.0,0.56,2.0,0.0,0.0,0.0,0.0,13.0,6.0,6.0,7.0,0.0,8.0,3.0,5.0,1.0,7.0,0.0,161.0,11.0,45.0,102.0,16.0,1.0,161.0,87.0,3.0,2.0,0.0,97.0,4.0,1.0,0.0,5.0,2.0,0.0,0.0,0.0,0.0,17.0,2.0,4.0,33.3 +Isaac Success,ng NGA,FW,Udinese,27-266,1996,5.0,0.0,126.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.71,0.71,0.0,0.71,0.3,0.3,0.24,0.24,1.4,0.0,0.0,0.0,0.0,0.0,0.0,0.17,-0.3,-0.3,20.0,30.0,66.7,376.0,99.0,9.0,12.0,75.0,7.0,9.0,77.8,3.0,5.0,60.0,2.0,3.0,1.0,0.0,6.0,29.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,3.0,2.14,2.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,2.0,0.0,43.0,2.0,2.0,20.0,22.0,4.0,43.0,36.0,1.0,1.0,0.0,40.0,4.0,6.0,0.0,6.0,7.0,0.0,0.0,0.0,0.0,4.0,3.0,4.0,42.9 +Ibrahim Sulemana,gh GHA,MF,Cagliari,20-131,2003,5.0,5.0,393.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.04,0.04,4.4,1.0,0.0,25.0,0.23,0.0,0.0,0.05,-0.2,-0.2,115.0,146.0,78.8,2172.0,400.0,51.0,59.0,86.4,47.0,52.0,90.4,16.0,25.0,64.0,2.0,6.0,1.0,1.0,6.0,145.0,1.0,1.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,4.0,0.91,3.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,1.0,4.0,1.0,1.0,12.0,1.0,11.0,3.0,7.0,0.0,195.0,13.0,67.0,102.0,32.0,3.0,195.0,102.0,5.0,2.0,1.0,104.0,4.0,3.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,38.0,0.0,4.0,0.0 +Tomáš Suslov,sk SVK,"MF,FW",Hellas Verona,21-115,2002,3.0,0.0,66.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.07,0.07,0.7,1.0,0.0,50.0,1.36,0.0,0.0,0.03,-0.1,-0.1,12.0,19.0,63.2,177.0,21.0,7.0,10.0,70.0,3.0,4.0,75.0,1.0,2.0,50.0,0.0,1.0,0.0,0.0,2.0,18.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,29.0,0.0,4.0,17.0,8.0,0.0,29.0,19.0,0.0,2.0,0.0,16.0,1.0,2.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,6.0,1.0,0.0,100.0 +Wojciech Szczęsny,pl POL,GK,Juventus,33-165,1990,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,104.0,133.0,78.2,2987.0,2165.0,23.0,23.0,100.0,45.0,45.0,100.0,36.0,65.0,55.4,0.0,2.0,0.0,0.0,0.0,108.0,25.0,9.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,145.0,115.0,145.0,0.0,0.0,0.0,145.0,88.0,0.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 +Przemysław Szymiński,pl POL,MF,Frosinone,29-098,1994,1.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,50.0,9.0,10.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,3.0,1.0,3.0,0.0,0.0,0.0,3.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Adrien Tameze,cm CMR,MF,Torino,29-238,1994,4.0,4.0,288.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,3.2,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.0,0.0,126.0,152.0,82.9,1956.0,416.0,66.0,71.0,93.0,49.0,60.0,81.7,7.0,10.0,70.0,1.0,11.0,1.0,0.0,12.0,148.0,4.0,3.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,4.0,1.25,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,3.0,0.0,2.0,1.0,6.0,2.0,4.0,7.0,2.0,0.0,178.0,7.0,29.0,113.0,41.0,2.0,178.0,95.0,4.0,6.0,1.0,116.0,1.0,2.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,22.0,3.0,5.0,37.5 +Loum Tchaouna,fr FRA,"MF,FW",Salernitana,20-022,2003,3.0,0.0,64.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,34.0,52.9,264.0,69.0,9.0,17.0,52.9,8.0,10.0,80.0,1.0,2.0,50.0,2.0,1.0,0.0,0.0,4.0,32.0,1.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,1.0,1.0,3.0,2.0,2.81,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,43.0,2.0,7.0,15.0,22.0,5.0,43.0,30.0,3.0,3.0,2.0,32.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,4.0,20.0 +Filippo Terracciano,it ITA,DF,Hellas Verona,20-234,2003,6.0,4.0,364.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,4.0,2.0,0.0,66.7,0.49,0.0,0.0,0.02,-0.1,-0.1,132.0,192.0,68.8,2365.0,1183.0,60.0,73.0,82.2,60.0,85.0,70.6,10.0,27.0,37.0,6.0,13.0,4.0,3.0,15.0,149.0,43.0,1.0,1.0,2.0,13.0,2.0,1.0,0.0,0.0,40.0,0.0,4.0,13.0,3.21,9.0,0.0,1.0,1.0,1.0,0.25,0.0,0.0,1.0,0.0,0.0,17.0,11.0,12.0,4.0,1.0,11.0,0.0,11.0,2.0,4.0,0.0,250.0,8.0,76.0,111.0,67.0,1.0,250.0,127.0,8.0,5.0,0.0,130.0,6.0,10.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,22.0,9.0,4.0,69.2 +Pietro Terracciano,it ITA,GK,Fiorentina,33-206,1990,4.0,4.0,360.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,139.0,174.0,79.9,4221.0,2949.0,14.0,14.0,100.0,67.0,68.0,98.5,57.0,90.0,63.3,2.0,4.0,2.0,0.0,0.0,143.0,30.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,0.75,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,186.0,154.0,186.0,0.0,0.0,0.0,186.0,117.0,0.0,0.0,0.0,108.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,0.0,0.0,0.0 +Florian Thauvin,fr FRA,FW,Udinese,30-247,1993,6.0,6.0,432.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,1.6,1.6,0.34,0.34,4.8,7.0,1.0,38.9,1.46,0.0,0.0,0.09,-1.6,-1.6,94.0,124.0,75.8,1663.0,494.0,46.0,56.0,82.1,32.0,42.0,76.2,12.0,18.0,66.7,7.0,13.0,5.0,3.0,17.0,110.0,14.0,0.0,0.0,0.0,7.0,2.0,0.0,1.0,0.0,2.0,0.0,0.0,18.0,3.75,13.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,2.0,1.0,2.0,1.0,2.0,0.0,2.0,0.0,1.0,0.0,197.0,1.0,10.0,93.0,98.0,25.0,197.0,113.0,11.0,8.0,4.0,126.0,11.0,10.0,0.0,4.0,2.0,1.0,0.0,0.0,0.0,15.0,7.0,8.0,46.7 +Malick Thiaw,de GER,DF,Milan,22-053,2001,6.0,6.0,525.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.01,5.8,0.0,0.0,0.0,0.0,0.0,0.0,0.04,0.0,0.0,354.0,379.0,93.4,6530.0,2130.0,121.0,124.0,97.6,208.0,216.0,96.3,21.0,31.0,67.7,1.0,20.0,2.0,0.0,25.0,370.0,9.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,3.0,4.0,0.69,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,6.0,3.0,4.0,0.0,7.0,3.0,4.0,5.0,15.0,0.0,423.0,35.0,199.0,214.0,11.0,0.0,423.0,303.0,6.0,3.0,0.0,323.0,1.0,3.0,0.0,8.0,2.0,0.0,0.0,0.0,0.0,29.0,7.0,4.0,63.6 +Morten Thorsby,no NOR,MF,Genoa,27-148,1996,5.0,1.0,238.0,1.0,1.0,0.0,0.0,1.0,0.0,0.38,0.38,0.76,0.38,0.76,0.7,0.7,0.28,0.28,2.6,1.0,0.0,33.3,0.38,0.33,1.0,0.24,0.3,0.3,35.0,64.0,54.7,552.0,179.0,14.0,28.0,50.0,13.0,19.0,68.4,2.0,5.0,40.0,1.0,5.0,2.0,0.0,10.0,64.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,3.0,1.14,2.0,0.0,0.0,0.0,1.0,0.38,1.0,0.0,0.0,0.0,0.0,4.0,3.0,3.0,1.0,0.0,6.0,0.0,6.0,1.0,6.0,0.0,97.0,8.0,19.0,49.0,29.0,2.0,97.0,33.0,0.0,2.0,0.0,56.0,4.0,4.0,0.0,7.0,0.0,0.0,0.0,0.0,0.0,7.0,13.0,10.0,56.5 +Kristian Thorstvedt,no NOR,MF,Sassuolo,24-201,1999,4.0,1.0,146.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.12,0.12,1.6,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,65.0,83.0,78.3,1143.0,530.0,35.0,41.0,85.4,23.0,28.0,82.1,7.0,9.0,77.8,7.0,16.0,1.0,0.0,20.0,82.0,1.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,14.0,8.63,11.0,0.0,2.0,0.0,1.0,0.62,0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,2.0,1.0,1.0,2.0,3.0,0.0,100.0,6.0,15.0,58.0,28.0,5.0,100.0,54.0,3.0,2.0,1.0,78.0,3.0,2.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,8.0,6.0,4.0,60.0 +Marcus Thuram,fr FRA,FW,Inter,26-055,1997,6.0,6.0,421.0,2.0,3.0,0.0,0.0,0.0,0.0,0.43,0.64,1.07,0.43,1.07,2.3,2.3,0.49,0.49,4.7,5.0,0.0,29.4,1.07,0.12,0.4,0.14,-0.3,-0.3,64.0,89.0,71.9,795.0,174.0,40.0,51.0,78.4,13.0,21.0,61.9,2.0,5.0,40.0,7.0,3.0,3.0,0.0,10.0,87.0,1.0,0.0,2.0,3.0,2.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,18.0,3.85,11.0,0.0,2.0,5.0,6.0,1.28,5.0,0.0,0.0,1.0,0.0,2.0,1.0,2.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,133.0,1.0,4.0,51.0,79.0,36.0,133.0,84.0,13.0,7.0,10.0,115.0,11.0,6.0,0.0,2.0,9.0,2.0,1.0,0.0,0.0,7.0,9.0,9.0,50.0 +Jeremy Toljan,de GER,DF,Sassuolo,29-053,1994,6.0,6.0,540.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.5,0.5,0.0,0.5,0.2,0.2,0.03,0.03,6.0,2.0,0.0,66.7,0.33,0.0,0.0,0.06,-0.2,-0.2,196.0,261.0,75.1,3118.0,1425.0,103.0,112.0,92.0,75.0,100.0,75.0,13.0,34.0,38.2,6.0,11.0,5.0,1.0,21.0,200.0,59.0,5.0,0.0,0.0,12.0,1.0,0.0,0.0,0.0,53.0,2.0,7.0,9.0,1.5,9.0,0.0,0.0,0.0,3.0,0.5,3.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,1.0,1.0,2.0,0.0,2.0,4.0,11.0,0.0,300.0,18.0,108.0,129.0,64.0,7.0,300.0,138.0,13.0,8.0,2.0,177.0,7.0,4.0,0.0,2.0,2.0,0.0,0.0,1.0,0.0,30.0,1.0,4.0,20.0 +Rafael Tolói,it ITA,DF,Atalanta,32-355,1990,3.0,2.0,178.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,74.0,98.0,75.5,1351.0,541.0,32.0,34.0,94.1,32.0,41.0,78.0,9.0,16.0,56.3,0.0,3.0,1.0,0.0,5.0,86.0,11.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,10.0,1.0,5.0,1.0,0.51,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,2.0,0.0,0.0,0.0,0.0,0.0,3.0,9.0,0.0,113.0,11.0,53.0,52.0,9.0,0.0,113.0,64.0,0.0,0.0,0.0,62.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,15.0,3.0,1.0,75.0 +Fikayo Tomori,eng ENG,DF,Milan,25-285,1997,5.0,5.0,420.0,1.0,0.0,0.0,0.0,2.0,1.0,0.21,0.0,0.21,0.21,0.21,1.0,1.0,0.22,0.22,4.7,1.0,0.0,50.0,0.21,0.5,1.0,0.52,0.0,0.0,340.0,366.0,92.9,5778.0,1860.0,140.0,148.0,94.6,180.0,185.0,97.3,19.0,29.0,65.5,0.0,7.0,0.0,0.0,14.0,341.0,25.0,6.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.21,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,7.0,4.0,7.0,0.0,0.0,6.0,3.0,3.0,8.0,10.0,0.0,409.0,50.0,236.0,166.0,7.0,2.0,409.0,264.0,1.0,2.0,0.0,290.0,3.0,0.0,1.0,7.0,1.0,0.0,0.0,0.0,0.0,28.0,9.0,6.0,60.0 +Ahmed Touba,dz ALG,"DF,FW",Lecce,25-202,1998,2.0,1.0,103.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,1.1,0.0,0.0,0.0,0.0,0.0,0.0,0.03,0.0,0.0,55.0,64.0,85.9,1027.0,288.0,14.0,16.0,87.5,34.0,39.0,87.2,5.0,7.0,71.4,0.0,4.0,0.0,0.0,2.0,62.0,2.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.87,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,2.0,2.0,0.0,2.0,8.0,0.0,77.0,13.0,40.0,37.0,2.0,1.0,77.0,42.0,0.0,1.0,0.0,43.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,8.0,2.0,3.0,40.0 +Stefano Turati,it ITA,GK,Frosinone,22-025,2001,5.0,5.0,450.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,141.0,193.0,73.1,2887.0,2245.0,65.0,65.0,100.0,47.0,50.0,94.0,27.0,74.0,36.5,0.0,1.0,0.0,0.0,0.0,167.0,24.0,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.2,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,212.0,196.0,211.0,1.0,0.0,0.0,212.0,140.0,0.0,0.0,0.0,123.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,1.0,0.0 +Kacper Urbanski,pl POL,MF,Bologna,19-023,2004,2.0,0.0,28.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.12,0.12,0.3,1.0,0.0,100.0,3.21,0.0,0.0,0.04,0.0,0.0,13.0,15.0,86.7,213.0,33.0,7.0,8.0,87.5,2.0,3.0,66.7,2.0,2.0,100.0,0.0,1.0,0.0,0.0,1.0,15.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,18.0,1.0,3.0,11.0,6.0,2.0,18.0,14.0,1.0,1.0,0.0,14.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0 +Johan Vásquez,mx MEX,DF,Genoa,24-343,1998,6.0,3.0,347.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,103.0,139.0,74.1,1970.0,872.0,41.0,45.0,91.1,50.0,58.0,86.2,12.0,30.0,40.0,0.0,7.0,1.0,0.0,8.0,109.0,30.0,5.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,21.0,0.0,4.0,4.0,1.03,3.0,1.0,0.0,0.0,1.0,0.26,1.0,0.0,0.0,0.0,0.0,9.0,7.0,7.0,2.0,0.0,11.0,1.0,10.0,4.0,21.0,0.0,190.0,28.0,83.0,81.0,27.0,1.0,190.0,83.0,4.0,4.0,0.0,90.0,3.0,4.0,0.0,2.0,5.0,0.0,0.0,0.0,0.0,18.0,5.0,2.0,71.4 +Matías Vecino,uy URU,MF,Lazio,32-037,1991,4.0,1.0,170.0,1.0,0.0,0.0,0.0,0.0,0.0,0.53,0.0,0.53,0.53,0.53,0.4,0.4,0.2,0.2,1.9,2.0,0.0,40.0,1.06,0.2,0.5,0.08,0.6,0.6,63.0,80.0,78.8,978.0,242.0,33.0,40.0,82.5,27.0,33.0,81.8,3.0,4.0,75.0,0.0,7.0,1.0,0.0,10.0,78.0,2.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,1.0,0.53,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,2.0,0.0,3.0,0.0,4.0,2.0,2.0,1.0,1.0,0.0,102.0,3.0,12.0,59.0,31.0,6.0,102.0,60.0,2.0,3.0,0.0,71.0,5.0,0.0,0.0,4.0,0.0,1.0,0.0,0.0,0.0,10.0,4.0,6.0,40.0 +Lorenzo Venuti,it ITA,DF,Lecce,28-171,1995,1.0,1.0,62.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.0,51.0,82.4,901.0,312.0,14.0,14.0,100.0,18.0,22.0,81.8,10.0,15.0,66.7,0.0,6.0,0.0,0.0,2.0,44.0,7.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,3.0,2.0,1.0,2.0,5.0,0.0,61.0,8.0,26.0,29.0,6.0,0.0,61.0,36.0,0.0,0.0,0.0,39.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 +Simone Verdi,it ITA,FW,Torino,31-080,1992,1.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,100.0,7.0,5.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,22.5,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,1.0,0.0,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +Samuele Vignato,it ITA,"MF,FW",Monza,19-218,2004,4.0,0.0,89.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.8,0.8,0.79,0.79,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.39,-0.8,-0.8,34.0,40.0,85.0,427.0,73.0,24.0,27.0,88.9,9.0,11.0,81.8,0.0,0.0,0.0,0.0,3.0,1.0,0.0,2.0,37.0,3.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,3.0,3.03,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,49.0,0.0,2.0,28.0,19.0,2.0,49.0,29.0,1.0,2.0,0.0,40.0,2.0,4.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0 +Matías Viña,uy URU,DF,Sassuolo,25-325,1997,6.0,6.0,355.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.25,0.25,0.0,0.25,0.1,0.1,0.02,0.02,3.9,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.1,-0.1,128.0,187.0,68.4,2161.0,1086.0,63.0,71.0,88.7,58.0,83.0,69.9,7.0,25.0,28.0,3.0,16.0,4.0,1.0,17.0,152.0,35.0,7.0,1.0,0.0,13.0,0.0,0.0,0.0,0.0,28.0,0.0,8.0,7.0,1.77,6.0,1.0,0.0,0.0,2.0,0.51,2.0,0.0,0.0,0.0,0.0,12.0,8.0,11.0,0.0,1.0,4.0,0.0,4.0,5.0,16.0,0.0,239.0,16.0,109.0,81.0,50.0,7.0,239.0,105.0,12.0,7.0,1.0,136.0,7.0,5.0,0.0,4.0,3.0,0.0,0.0,0.0,1.0,15.0,3.0,9.0,25.0 +Nicolas Viola,it ITA,MF,Cagliari,33-353,1989,2.0,0.0,51.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.02,0.02,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.01,0.0,0.0,27.0,40.0,67.5,645.0,311.0,8.0,9.0,88.9,11.0,13.0,84.6,7.0,15.0,46.7,0.0,5.0,1.0,0.0,3.0,34.0,6.0,2.0,0.0,1.0,4.0,4.0,2.0,1.0,0.0,0.0,0.0,2.0,3.0,5.4,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,45.0,0.0,3.0,28.0,15.0,3.0,45.0,27.0,1.0,0.0,0.0,32.0,1.0,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,1.0,0.0 +Mattia Viti,it ITA,DF,Sassuolo,21-249,2002,3.0,2.0,181.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,71.0,75.0,94.7,1240.0,289.0,27.0,27.0,100.0,38.0,39.0,97.4,3.0,5.0,60.0,0.0,2.0,0.0,0.0,3.0,64.0,11.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,4.0,2.0,2.0,2.0,12.0,0.0,96.0,30.0,61.0,36.0,0.0,0.0,96.0,47.0,0.0,0.0,0.0,55.0,0.0,1.0,0.0,2.0,2.0,0.0,0.0,0.0,0.0,4.0,2.0,2.0,50.0 +Dušan Vlahović,rs SRB,FW,Juventus,23-245,2000,6.0,5.0,415.0,4.0,1.0,1.0,2.0,2.0,0.0,0.87,0.22,1.08,0.65,0.87,3.0,1.4,0.65,0.31,4.6,6.0,0.0,37.5,1.3,0.19,0.5,0.09,1.0,1.6,60.0,83.0,72.3,876.0,143.0,33.0,40.0,82.5,21.0,28.0,75.0,2.0,6.0,33.3,3.0,2.0,3.0,0.0,8.0,74.0,8.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,13.0,2.83,10.0,0.0,2.0,1.0,2.0,0.43,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,124.0,4.0,10.0,55.0,59.0,27.0,122.0,75.0,6.0,4.0,4.0,91.0,11.0,5.0,0.0,4.0,6.0,4.0,0.0,0.0,0.0,8.0,2.0,3.0,40.0 +Nikola Vlašić,hr CRO,MF,Torino,25-361,1997,5.0,4.0,346.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.3,0.3,0.07,0.07,3.8,1.0,1.0,16.7,0.26,0.0,0.0,0.04,-0.3,-0.3,95.0,131.0,72.5,1382.0,371.0,56.0,68.0,82.4,27.0,37.0,73.0,7.0,9.0,77.8,0.0,18.0,1.0,0.0,20.0,130.0,0.0,0.0,1.0,1.0,6.0,0.0,0.0,0.0,0.0,0.0,1.0,7.0,6.0,1.56,4.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,0.0,1.0,1.0,3.0,1.0,2.0,0.0,3.0,0.0,158.0,3.0,11.0,71.0,78.0,8.0,158.0,108.0,6.0,3.0,1.0,123.0,6.0,4.0,0.0,1.0,5.0,0.0,0.0,0.0,0.0,18.0,5.0,2.0,71.4 +Mërgim Vojvoda,xk KVX,DF,Torino,28-241,1995,3.0,3.0,270.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.2,-0.2,129.0,170.0,75.9,2136.0,845.0,69.0,78.0,88.5,52.0,65.0,80.0,7.0,19.0,36.8,2.0,5.0,7.0,0.0,22.0,145.0,23.0,2.0,0.0,6.0,9.0,1.0,1.0,0.0,0.0,20.0,2.0,3.0,3.0,1.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,2.0,0.0,2.0,2.0,3.0,0.0,182.0,5.0,38.0,83.0,63.0,2.0,182.0,115.0,8.0,8.0,0.0,124.0,1.0,0.0,0.0,3.0,1.0,1.0,0.0,0.0,0.0,13.0,1.0,1.0,50.0 +Cristian Volpato,it ITA,FW,Sassuolo,19-319,2003,1.0,0.0,13.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,12.0,12.0,100.0,238.0,41.0,4.0,4.0,100.0,7.0,7.0,100.0,1.0,1.0,100.0,0.0,1.0,0.0,0.0,2.0,12.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,15.0,1.0,1.0,11.0,3.0,0.0,15.0,13.0,1.0,1.0,0.0,13.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0 +Stefan de Vrij,nl NED,DF,Inter,31-237,1992,6.0,3.0,329.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.03,0.03,3.7,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.1,-0.1,158.0,179.0,88.3,2705.0,716.0,64.0,67.0,95.5,82.0,90.0,91.1,7.0,14.0,50.0,0.0,2.0,0.0,0.0,6.0,176.0,3.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.55,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,3.0,0.0,0.0,6.0,3.0,3.0,6.0,9.0,0.0,210.0,19.0,119.0,86.0,6.0,4.0,210.0,115.0,0.0,2.0,0.0,122.0,2.0,0.0,0.0,5.0,1.0,0.0,0.0,0.0,0.0,24.0,13.0,3.0,81.3 +Walace,br BRA,MF,Udinese,28-179,1995,6.0,6.0,492.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.02,0.02,5.5,1.0,0.0,16.7,0.18,0.0,0.0,0.02,-0.1,-0.1,211.0,251.0,84.1,4014.0,1245.0,83.0,96.0,86.5,102.0,114.0,89.5,24.0,34.0,70.6,4.0,35.0,3.0,0.0,29.0,244.0,7.0,7.0,0.0,5.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,8.0,1.46,8.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,9.0,3.0,7.0,2.0,0.0,6.0,1.0,5.0,11.0,4.0,1.0,300.0,13.0,74.0,191.0,38.0,1.0,300.0,202.0,9.0,7.0,0.0,194.0,3.0,4.0,0.0,2.0,10.0,0.0,0.0,0.0,0.0,42.0,2.0,0.0,100.0 +Sebastian Walukiewicz,pl POL,DF,Empoli,23-178,2000,4.0,3.0,265.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.9,1.0,0.0,100.0,0.34,0.0,0.0,0.01,0.0,0.0,130.0,156.0,83.3,2540.0,932.0,41.0,44.0,93.2,69.0,83.0,83.1,18.0,26.0,69.2,0.0,9.0,0.0,0.0,6.0,147.0,9.0,7.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.34,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,2.0,2.0,0.0,0.0,7.0,5.0,2.0,4.0,10.0,0.0,180.0,37.0,97.0,80.0,4.0,0.0,180.0,111.0,2.0,2.0,0.0,118.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,1.0,0.0,13.0,3.0,4.0,42.9 +Timothy Weah,us USA,DF,Juventus,23-220,2000,6.0,2.0,187.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.7,0.7,0.32,0.32,2.1,1.0,0.0,25.0,0.48,0.0,0.0,0.17,-0.7,-0.7,71.0,89.0,79.8,1164.0,261.0,38.0,45.0,84.4,25.0,30.0,83.3,7.0,7.0,100.0,3.0,6.0,4.0,3.0,7.0,82.0,6.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,6.0,1.0,2.0,5.0,2.39,4.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,3.0,2.0,1.0,1.0,1.0,1.0,0.0,1.0,7.0,0.0,114.0,6.0,24.0,46.0,44.0,8.0,114.0,60.0,4.0,1.0,2.0,69.0,2.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,7.0,2.0,1.0,66.7 +Mateusz Wieteska,pl POL,DF,Cagliari,26-231,1997,3.0,3.0,224.0,0.0,1.0,0.0,0.0,3.0,1.0,0.0,0.4,0.4,0.0,0.4,0.0,0.0,0.0,0.0,2.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,87.0,105.0,82.9,1589.0,828.0,39.0,41.0,95.1,38.0,47.0,80.9,9.0,15.0,60.0,3.0,3.0,0.0,0.0,5.0,99.0,6.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,4.0,1.61,3.0,0.0,0.0,0.0,1.0,0.4,1.0,0.0,0.0,0.0,0.0,5.0,5.0,3.0,1.0,1.0,2.0,0.0,2.0,2.0,10.0,0.0,127.0,20.0,77.0,46.0,5.0,1.0,127.0,65.0,5.0,0.0,0.0,75.0,1.0,0.0,1.0,4.0,1.0,0.0,0.0,0.0,0.0,13.0,4.0,3.0,57.1 +Kenan Yıldız,tr TUR,"MF,FW",Juventus,18-149,2005,2.0,0.0,15.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,5.0,80.0,53.0,26.0,3.0,4.0,75.0,1.0,1.0,100.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,8.0,0.0,2.0,6.0,0.0,0.0,8.0,5.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,3.0,1.0,1.0,50.0 +Mattia Zaccagni,it ITA,FW,Lazio,28-106,1995,6.0,6.0,494.0,1.0,0.0,0.0,0.0,2.0,0.0,0.18,0.0,0.18,0.18,0.18,0.7,0.7,0.13,0.13,5.5,2.0,0.0,20.0,0.36,0.1,0.5,0.07,0.3,0.3,220.0,271.0,81.2,3111.0,655.0,126.0,140.0,90.0,68.0,81.0,84.0,14.0,27.0,51.9,6.0,11.0,11.0,2.0,16.0,258.0,13.0,5.0,1.0,0.0,15.0,4.0,0.0,0.0,0.0,4.0,0.0,8.0,18.0,3.28,10.0,3.0,2.0,2.0,1.0,0.18,0.0,0.0,0.0,1.0,0.0,8.0,5.0,4.0,4.0,0.0,6.0,1.0,5.0,9.0,4.0,0.0,338.0,6.0,36.0,127.0,182.0,21.0,338.0,237.0,26.0,14.0,7.0,276.0,13.0,12.0,0.0,9.0,18.0,2.0,1.0,0.0,0.0,15.0,3.0,2.0,60.0 +Nicola Zalewski,pl POL,"DF,FW",Roma,21-250,2002,4.0,2.0,187.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.07,0.07,2.1,0.0,0.0,0.0,0.0,0.0,0.0,0.04,-0.2,-0.2,78.0,109.0,71.6,1368.0,450.0,30.0,31.0,96.8,41.0,55.0,74.5,6.0,13.0,46.2,2.0,4.0,6.0,1.0,8.0,87.0,22.0,3.0,0.0,0.0,10.0,0.0,0.0,0.0,0.0,19.0,0.0,6.0,5.0,2.41,3.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,5.0,1.0,5.0,0.0,3.0,2.0,1.0,2.0,1.0,0.0,132.0,7.0,28.0,63.0,43.0,8.0,132.0,68.0,12.0,5.0,4.0,79.0,2.0,0.0,0.0,3.0,8.0,0.0,0.0,0.0,0.0,11.0,4.0,2.0,66.7 +Andre-Frank Zambo Anguissa,cm CMR,MF,Napoli,27-318,1995,6.0,5.0,454.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.2,0.05,0.05,5.0,0.0,0.0,0.0,0.0,0.0,0.0,0.06,-0.2,-0.2,307.0,344.0,89.2,4464.0,1169.0,180.0,195.0,92.3,92.0,97.0,94.8,18.0,24.0,75.0,5.0,29.0,2.0,0.0,26.0,338.0,4.0,4.0,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,4.0,16.0,3.17,15.0,0.0,0.0,0.0,1.0,0.2,1.0,0.0,0.0,0.0,0.0,7.0,4.0,1.0,6.0,0.0,3.0,0.0,3.0,4.0,1.0,0.0,387.0,4.0,40.0,253.0,95.0,8.0,387.0,255.0,12.0,13.0,3.0,318.0,8.0,6.0,0.0,7.0,7.0,0.0,0.0,0.0,0.0,34.0,6.0,3.0,66.7 +Duván Zapata,co COL,FW,Torino,32-182,1991,4.0,4.0,299.0,1.0,0.0,0.0,0.0,0.0,0.0,0.3,0.0,0.3,0.3,0.3,1.0,1.0,0.31,0.31,3.3,5.0,0.0,55.6,1.51,0.11,0.2,0.11,0.0,0.0,59.0,76.0,77.6,875.0,72.0,30.0,36.0,83.3,16.0,21.0,76.2,5.0,5.0,100.0,4.0,2.0,0.0,0.0,3.0,67.0,7.0,0.0,0.0,1.0,3.0,0.0,0.0,0.0,0.0,1.0,2.0,2.0,7.0,2.11,5.0,0.0,1.0,1.0,1.0,0.3,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,1.0,2.0,0.0,2.0,0.0,117.0,3.0,5.0,46.0,66.0,20.0,117.0,77.0,5.0,8.0,2.0,95.0,13.0,4.0,0.0,7.0,8.0,1.0,0.0,0.0,0.0,9.0,11.0,13.0,45.8 +Duván Zapata,co COL,FW,Atalanta,32-182,1991,2.0,2.0,112.0,1.0,0.0,0.0,0.0,0.0,0.0,0.8,0.0,0.8,0.8,0.8,0.4,0.4,0.33,0.33,1.2,2.0,0.0,40.0,1.61,0.2,0.5,0.08,0.6,0.6,36.0,50.0,72.0,393.0,32.0,26.0,29.0,89.7,7.0,12.0,58.3,0.0,1.0,0.0,2.0,0.0,1.0,0.0,3.0,47.0,3.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,1.0,0.0,4.0,4.0,3.21,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,1.0,3.0,27.0,35.0,10.0,65.0,47.0,3.0,1.0,2.0,50.0,5.0,0.0,0.0,1.0,4.0,1.0,0.0,0.0,0.0,6.0,5.0,5.0,50.0 +Gabriele Zappa,it ITA,DF,Cagliari,23-282,1999,6.0,5.0,443.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.4,0.4,0.08,0.08,4.9,0.0,0.0,0.0,0.0,0.0,0.0,0.19,-0.4,-0.4,151.0,214.0,70.6,2554.0,1506.0,78.0,89.0,87.6,54.0,71.0,76.1,16.0,40.0,40.0,3.0,16.0,7.0,3.0,23.0,165.0,47.0,6.0,0.0,1.0,13.0,0.0,0.0,0.0,0.0,41.0,2.0,4.0,6.0,1.22,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,10.0,7.0,5.0,4.0,1.0,6.0,1.0,5.0,3.0,14.0,0.0,259.0,13.0,83.0,112.0,65.0,4.0,259.0,129.0,9.0,7.0,0.0,141.0,6.0,2.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,24.0,2.0,3.0,40.0 +Davide Zappacosta,it ITA,"DF,MF",Atalanta,31-111,1992,5.0,5.0,327.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.6,0.6,0.17,0.17,3.6,2.0,0.0,18.2,0.55,0.0,0.0,0.06,-0.6,-0.6,142.0,167.0,85.0,1900.0,708.0,91.0,101.0,90.1,39.0,42.0,92.9,6.0,8.0,75.0,1.0,8.0,3.0,0.0,15.0,139.0,28.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,27.0,0.0,6.0,6.0,1.65,2.0,0.0,2.0,0.0,1.0,0.27,1.0,0.0,0.0,0.0,0.0,2.0,2.0,1.0,0.0,1.0,5.0,1.0,4.0,0.0,5.0,0.0,207.0,5.0,52.0,76.0,83.0,15.0,207.0,123.0,11.0,5.0,4.0,133.0,6.0,3.0,0.0,3.0,5.0,1.0,0.0,0.0,0.0,20.0,3.0,5.0,37.5 +Oier Zarraga,es ESP,MF,Udinese,24-269,1999,2.0,1.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.12,0.12,0.6,0.0,0.0,0.0,0.0,0.0,0.0,0.07,-0.1,-0.1,14.0,16.0,87.5,172.0,58.0,12.0,13.0,92.3,2.0,2.0,100.0,0.0,1.0,0.0,1.0,2.0,0.0,0.0,2.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.67,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,1.0,23.0,2.0,8.0,7.0,8.0,2.0,23.0,15.0,2.0,3.0,1.0,17.0,3.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,1.0,1.0,50.0 +Jordan Zemura,zw ZIM,DF,Udinese,23-320,1999,5.0,0.0,119.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.3,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,38.0,51.0,74.5,445.0,221.0,27.0,29.0,93.1,9.0,12.0,75.0,0.0,4.0,0.0,2.0,2.0,0.0,0.0,4.0,38.0,13.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,0.0,12.0,0.0,2.0,4.0,3.03,2.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,1.0,5.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,66.0,1.0,18.0,27.0,23.0,1.0,66.0,31.0,3.0,2.0,2.0,33.0,5.0,1.0,0.0,4.0,1.0,0.0,0.0,0.0,0.0,6.0,4.0,4.0,50.0 +Alessio Zerbin,it ITA,FW,Napoli,24-211,1999,1.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0,0.0,0.0,3.0,1.0,3.0,3.0,0.0,1.0,0.0,3.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0 +Piotr Zieliński,pl POL,MF,Napoli,29-133,1994,6.0,6.0,505.0,2.0,1.0,1.0,1.0,0.0,0.0,0.36,0.18,0.53,0.18,0.36,1.3,0.5,0.23,0.09,5.6,3.0,2.0,25.0,0.53,0.08,0.33,0.04,0.7,0.5,258.0,317.0,81.4,4013.0,1581.0,144.0,153.0,94.1,86.0,106.0,81.1,20.0,41.0,48.8,19.0,37.0,18.0,0.0,47.0,283.0,30.0,4.0,2.0,2.0,26.0,23.0,4.0,15.0,0.0,0.0,4.0,3.0,35.0,6.24,23.0,9.0,2.0,0.0,4.0,0.71,3.0,0.0,1.0,0.0,0.0,7.0,3.0,1.0,4.0,2.0,3.0,1.0,2.0,1.0,3.0,0.0,360.0,6.0,39.0,180.0,145.0,11.0,359.0,214.0,13.0,15.0,3.0,272.0,7.0,4.0,0.0,2.0,1.0,0.0,0.0,0.0,0.0,20.0,1.0,2.0,33.3 +David Zima,cz CZE,DF,Torino,22-326,2000,1.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.2,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,6.0,83.3,72.0,12.0,1.0,1.0,100.0,3.0,4.0,75.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,5.63,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,2.0,0.0,9.0,2.0,5.0,4.0,0.0,0.0,9.0,4.0,0.0,0.0,0.0,4.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,2.0,0.0,3.0,0.0 +Joshua Zirkzee,nl NED,FW,Bologna,22-131,2001,6.0,6.0,520.0,1.0,1.0,0.0,0.0,1.0,0.0,0.17,0.17,0.35,0.17,0.35,0.7,0.7,0.12,0.12,5.8,7.0,0.0,58.3,1.21,0.08,0.14,0.06,0.3,0.3,108.0,146.0,74.0,1412.0,275.0,71.0,96.0,74.0,19.0,26.0,73.1,7.0,7.0,100.0,12.0,6.0,4.0,0.0,12.0,134.0,12.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,4.0,20.0,3.46,15.0,0.0,2.0,0.0,1.0,0.17,1.0,0.0,0.0,0.0,0.0,5.0,1.0,1.0,3.0,1.0,1.0,0.0,1.0,1.0,11.0,0.0,226.0,12.0,24.0,101.0,104.0,24.0,226.0,125.0,7.0,9.0,4.0,162.0,23.0,8.0,0.0,5.0,1.0,2.0,0.0,0.0,0.0,15.0,12.0,3.0,80.0 +Zito,ao ANG,FW,Cagliari,21-205,2002,6.0,5.0,477.0,2.0,0.0,0.0,0.0,2.0,0.0,0.38,0.0,0.38,0.38,0.38,0.9,0.9,0.17,0.17,5.3,3.0,0.0,21.4,0.57,0.14,0.67,0.06,1.1,1.1,57.0,79.0,72.2,898.0,187.0,28.0,31.0,90.3,24.0,35.0,68.6,2.0,5.0,40.0,8.0,2.0,6.0,5.0,7.0,72.0,7.0,0.0,0.0,2.0,14.0,3.0,0.0,1.0,0.0,1.0,0.0,3.0,24.0,4.53,12.0,0.0,2.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,0.0,2.0,0.0,0.0,0.0,150.0,0.0,7.0,38.0,106.0,34.0,150.0,115.0,22.0,10.0,13.0,121.0,22.0,15.0,0.0,5.0,12.0,6.0,0.0,0.0,0.0,9.0,2.0,7.0,22.2 +Nadir Zortea,it ITA,DF,Atalanta,24-103,1999,3.0,0.0,96.0,1.0,0.0,0.0,0.0,1.0,0.0,0.94,0.0,0.94,0.94,0.94,0.1,0.1,0.08,0.08,1.1,1.0,0.0,50.0,0.94,0.5,1.0,0.04,0.9,0.9,41.0,51.0,80.4,702.0,314.0,22.0,24.0,91.7,13.0,15.0,86.7,6.0,8.0,75.0,2.0,2.0,2.0,2.0,5.0,43.0,8.0,0.0,0.0,0.0,7.0,1.0,0.0,1.0,0.0,7.0,0.0,3.0,7.0,6.56,4.0,1.0,1.0,0.0,1.0,0.94,1.0,0.0,0.0,0.0,0.0,3.0,2.0,2.0,1.0,0.0,1.0,0.0,1.0,1.0,2.0,0.0,64.0,1.0,13.0,30.0,23.0,3.0,64.0,43.0,6.0,4.0,1.0,44.0,0.0,2.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0 +Milan Đurić,ba BIH,"FW,MF",Hellas Verona,33-131,1990,5.0,1.0,154.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.1,0.1,0.05,0.05,1.7,0.0,0.0,0.0,0.0,0.0,0.0,0.08,-0.1,-0.1,24.0,51.0,47.1,328.0,43.0,16.0,33.0,48.5,4.0,9.0,44.4,2.0,3.0,66.7,2.0,1.0,1.0,0.0,1.0,51.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,3.0,1.75,2.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,64.0,4.0,10.0,25.0,29.0,4.0,64.0,26.0,0.0,2.0,0.0,51.0,5.0,1.0,0.0,7.0,1.0,2.0,0.0,0.0,0.0,4.0,23.0,15.0,60.5 +Mateusz Łęgowski,pl POL,MF,Salernitana,20-244,2003,5.0,2.0,167.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.9,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,76.0,92.0,82.6,1023.0,301.0,48.0,52.0,92.3,21.0,25.0,84.0,4.0,8.0,50.0,1.0,2.0,0.0,0.0,5.0,91.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,3.0,4.0,2.16,4.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,106.0,2.0,19.0,65.0,24.0,1.0,106.0,73.0,4.0,5.0,1.0,77.0,4.0,1.0,0.0,3.0,3.0,0.0,0.0,0.0,0.0,16.0,4.0,5.0,44.4 diff --git a/fbref_data/teams.csv b/fbref_data/teams.csv index 443cd4d..939ff86 100644 --- a/fbref_data/teams.csv +++ b/fbref_data/teams.csv @@ -1,21 +1,21 @@ team,players_used,possession,games,games_starts,minutes,goals,assists,pens_made,pens_att,cards_yellow,cards_red,goals_per90,assists_per90,goals_assists_per90,goals_pens_per90,goals_assists_pens_per90,xg,npxg,xg_per90,npxg_per90,gk_games,gk_games_starts,gk_minutes,gk_goals_against,gk_goals_against_per90,gk_shots_on_target_against,gk_saves,gk_save_pct,gk_wins,gk_ties,gk_losses,gk_clean_sheets,gk_clean_sheets_pct,gk_pens_att,gk_pens_allowed,gk_pens_saved,gk_pens_missed,minutes_90s,gk_free_kick_goals_against,gk_corner_kick_goals_against,gk_own_goals_against,gk_psxg,gk_psnpxg_per_shot_on_target_against,gk_psxg_net,gk_psxg_net_per90,gk_passes_completed_launched,gk_passes_launched,gk_passes_pct_launched,gk_passes,gk_passes_throws,gk_pct_passes_launched,gk_passes_length_avg,gk_goal_kicks,gk_pct_goal_kicks_launched,gk_goal_kick_length_avg,gk_crosses,gk_crosses_stopped,gk_crosses_stopped_pct,gk_def_actions_outside_pen_area,gk_def_actions_outside_pen_area_per90,gk_avg_distance_def_actions,shots_on_target,shots_free_kicks,shots_on_target_pct,shots_on_target_per90,goals_per_shot,goals_per_shot_on_target,npxg_per_shot,xg_net,npxg_net,passes_completed,passes,passes_pct,passes_total_distance,passes_progressive_distance,passes_completed_short,passes_short,passes_pct_short,passes_completed_medium,passes_medium,passes_pct_medium,passes_completed_long,passes_long,passes_pct_long,assisted_shots,passes_into_final_third,passes_into_penalty_area,crosses_into_penalty_area,progressive_passes,passes_live,passes_dead,passes_free_kicks,through_balls,passes_switches,crosses,corner_kicks,corner_kicks_in,corner_kicks_out,corner_kicks_straight,throw_ins,passes_offsides,passes_blocked,sca,sca_per90,sca_passes_live,sca_passes_dead,sca_shots,sca_fouled,gca,gca_per90,gca_passes_live,gca_passes_dead,gca_shots,gca_fouled,gca_defense,tackles,tackles_won,tackles_def_3rd,tackles_mid_3rd,tackles_att_3rd,blocks,blocked_shots,blocked_passes,interceptions,clearances,errors,touches,touches_def_pen_area,touches_def_3rd,touches_mid_3rd,touches_att_3rd,touches_att_pen_area,touches_live_ball,carries,progressive_carries,carries_into_final_third,carries_into_penalty_area,passes_received,miscontrols,dispossessed,cards_yellow_red,fouls,fouled,offsides,pens_won,pens_conceded,own_goals,ball_recoveries,aerials_won,aerials_lost,aerials_won_pct -Atalanta,23.0,49.5,4.0,44.0,360.0,8.0,8.0,0.0,0.0,4.0,0.0,2.0,2.0,4.0,2.0,4.0,4.9,4.9,1.23,1.23,4.0,4.0,360.0,5.0,1.25,18.0,13.0,72.2,2.0,0.0,2.0,2.0,50.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,4.1,0.23,-0.9,-0.24,14.0,49.0,28.6,116.0,24.0,29.3,31.1,24.0,62.5,51.9,41.0,3.0,7.3,8.0,2.0,21.2,22.0,0.0,34.9,5.5,0.13,0.36,0.08,3.1,3.1,1710.0,2117.0,80.8,29680.0,10551.0,769.0,880.0,87.4,733.0,825.0,88.8,164.0,291.0,56.4,50.0,112.0,42.0,11.0,196.0,1927.0,181.0,38.0,4.0,18.0,87.0,25.0,8.0,13.0,0.0,85.0,9.0,45.0,114.0,28.5,89.0,9.0,6.0,0.0,15.0,3.75,13.0,1.0,1.0,0.0,0.0,70.0,39.0,37.0,24.0,9.0,52.0,11.0,41.0,43.0,59.0,1.0,2541.0,214.0,777.0,1068.0,723.0,104.0,2541.0,1603.0,92.0,65.0,24.0,1694.0,51.0,39.0,0.0,48.0,34.0,9.0,0.0,0.0,0.0,232.0,60.0,65.0,48.0 -Bologna,22.0,56.5,4.0,44.0,360.0,3.0,2.0,0.0,1.0,6.0,0.0,0.75,0.5,1.25,0.75,1.25,4.5,3.7,1.12,0.93,4.0,4.0,360.0,4.0,1.0,10.0,6.0,60.0,1.0,2.0,1.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.2,0.32,-0.8,-0.21,17.0,45.0,37.8,106.0,17.0,35.8,32.1,22.0,31.8,34.2,57.0,2.0,3.5,2.0,0.5,11.5,20.0,2.0,37.7,5.0,0.06,0.15,0.07,-1.5,-0.7,2029.0,2366.0,85.8,34439.0,11121.0,970.0,1061.0,91.4,828.0,919.0,90.1,174.0,278.0,62.6,41.0,145.0,36.0,12.0,166.0,2184.0,178.0,59.0,1.0,11.0,57.0,14.0,8.0,2.0,0.0,71.0,4.0,27.0,99.0,24.75,83.0,3.0,5.0,3.0,5.0,1.25,4.0,0.0,1.0,0.0,0.0,64.0,33.0,38.0,22.0,4.0,49.0,11.0,38.0,21.0,66.0,1.0,2780.0,258.0,847.0,1406.0,550.0,85.0,2779.0,1671.0,70.0,58.0,17.0,2013.0,52.0,25.0,0.0,42.0,41.0,4.0,0.0,0.0,0.0,205.0,46.0,34.0,57.5 -Cagliari,21.0,37.8,4.0,44.0,360.0,1.0,1.0,0.0,0.0,6.0,1.0,0.25,0.25,0.5,0.25,0.5,3.1,3.1,0.77,0.77,4.0,4.0,360.0,4.0,1.0,13.0,9.0,69.2,0.0,2.0,2.0,2.0,50.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,4.1,0.33,0.1,0.03,24.0,54.0,44.4,76.0,18.0,36.8,37.8,40.0,65.0,50.0,62.0,4.0,6.5,3.0,0.75,12.5,6.0,2.0,16.2,1.5,0.03,0.17,0.08,-2.1,-2.1,1072.0,1468.0,73.0,20258.0,8416.0,479.0,546.0,87.7,422.0,537.0,78.6,148.0,301.0,49.2,28.0,92.0,23.0,9.0,126.0,1281.0,180.0,41.0,4.0,15.0,72.0,13.0,4.0,8.0,0.0,77.0,7.0,35.0,66.0,16.5,48.0,3.0,1.0,5.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,54.0,33.0,31.0,17.0,6.0,34.0,12.0,22.0,32.0,91.0,2.0,1890.0,246.0,712.0,769.0,428.0,58.0,1890.0,1062.0,67.0,35.0,15.0,1054.0,72.0,37.0,1.0,46.0,35.0,7.0,0.0,1.0,0.0,241.0,51.0,60.0,45.9 -Empoli,27.0,47.8,4.0,44.0,360.0,0.0,0.0,0.0,0.0,9.0,0.0,0.0,0.0,0.0,0.0,0.0,2.2,2.2,0.56,0.56,4.0,4.0,360.0,12.0,3.0,23.0,11.0,52.2,0.0,0.0,4.0,0.0,0.0,2.0,1.0,1.0,0.0,4.0,0.0,3.0,1.0,7.0,0.22,-4.0,-1.0,8.0,42.0,19.0,113.0,30.0,31.9,32.2,25.0,24.0,32.0,51.0,3.0,5.9,5.0,1.25,14.4,12.0,2.0,27.9,3.0,0.0,0.0,0.05,-2.2,-2.2,1480.0,1855.0,79.8,25305.0,8387.0,672.0,754.0,89.1,631.0,722.0,87.4,129.0,260.0,49.6,27.0,108.0,20.0,6.0,128.0,1635.0,213.0,66.0,6.0,5.0,71.0,16.0,6.0,6.0,0.0,86.0,7.0,40.0,73.0,18.25,55.0,5.0,5.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,54.0,32.0,20.0,26.0,8.0,53.0,14.0,39.0,22.0,49.0,2.0,2236.0,256.0,708.0,1008.0,541.0,59.0,2236.0,1342.0,77.0,48.0,14.0,1464.0,42.0,39.0,0.0,43.0,59.0,7.0,0.0,2.0,1.0,176.0,39.0,54.0,41.9 -Fiorentina,22.0,61.0,4.0,44.0,360.0,9.0,7.0,0.0,0.0,6.0,0.0,2.25,1.75,4.0,2.25,4.0,3.8,3.8,0.95,0.95,4.0,4.0,360.0,9.0,2.25,19.0,10.0,57.9,2.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,4.0,0.0,1.0,0.0,4.3,0.18,-4.7,-1.18,27.0,51.0,52.9,163.0,17.0,27.6,33.2,17.0,35.3,36.5,31.0,1.0,3.2,4.0,1.0,16.4,19.0,1.0,47.5,4.75,0.23,0.47,0.1,5.2,5.2,1929.0,2315.0,83.3,37656.0,12547.0,729.0,814.0,89.6,869.0,984.0,88.3,288.0,391.0,73.7,33.0,133.0,33.0,8.0,174.0,2114.0,197.0,60.0,6.0,24.0,62.0,11.0,2.0,6.0,0.0,96.0,4.0,56.0,73.0,18.25,57.0,4.0,4.0,1.0,17.0,4.25,9.0,3.0,2.0,0.0,0.0,56.0,35.0,22.0,22.0,12.0,48.0,8.0,40.0,27.0,46.0,0.0,2705.0,230.0,836.0,1284.0,612.0,77.0,2705.0,1801.0,74.0,58.0,16.0,1904.0,55.0,38.0,0.0,49.0,52.0,4.0,0.0,1.0,0.0,196.0,53.0,56.0,48.6 -Frosinone,23.0,48.3,4.0,44.0,360.0,7.0,4.0,2.0,2.0,10.0,0.0,1.75,1.0,2.75,1.25,2.25,6.2,4.6,1.55,1.16,4.0,4.0,360.0,6.0,1.5,27.0,21.0,77.8,2.0,1.0,1.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,6.4,0.24,0.4,0.11,9.0,47.0,19.1,123.0,25.0,30.1,28.7,18.0,55.6,42.8,51.0,2.0,3.9,3.0,0.75,16.3,11.0,1.0,25.6,2.75,0.12,0.45,0.11,0.8,0.4,1449.0,1808.0,80.1,23024.0,9359.0,748.0,821.0,91.1,509.0,589.0,86.4,123.0,268.0,45.9,31.0,88.0,29.0,6.0,132.0,1606.0,191.0,53.0,2.0,5.0,45.0,17.0,5.0,6.0,0.0,78.0,11.0,27.0,72.0,18.0,51.0,7.0,6.0,4.0,11.0,2.75,3.0,4.0,1.0,2.0,1.0,53.0,36.0,28.0,21.0,4.0,53.0,19.0,34.0,30.0,80.0,1.0,2242.0,315.0,838.0,956.0,470.0,78.0,2240.0,1196.0,57.0,40.0,18.0,1433.0,66.0,30.0,0.0,43.0,49.0,11.0,2.0,0.0,0.0,202.0,52.0,53.0,49.5 -Genoa,19.0,33.3,4.0,44.0,360.0,4.0,3.0,0.0,0.0,12.0,0.0,1.0,0.75,1.75,1.0,1.75,2.1,2.1,0.53,0.53,4.0,4.0,360.0,7.0,1.75,14.0,7.0,50.0,1.0,1.0,2.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,3.7,0.27,-3.3,-0.82,38.0,78.0,48.7,125.0,10.0,45.6,39.7,22.0,95.5,62.5,75.0,8.0,10.7,2.0,0.5,9.3,10.0,0.0,41.7,2.5,0.17,0.4,0.09,1.9,1.9,953.0,1333.0,71.5,18653.0,8144.0,386.0,475.0,81.3,408.0,497.0,82.1,135.0,275.0,49.1,19.0,68.0,14.0,5.0,88.0,1162.0,166.0,51.0,1.0,5.0,45.0,7.0,0.0,6.0,0.0,59.0,5.0,32.0,41.0,10.25,28.0,6.0,3.0,1.0,6.0,1.5,2.0,1.0,2.0,0.0,0.0,63.0,33.0,36.0,25.0,2.0,53.0,13.0,40.0,41.0,113.0,2.0,1761.0,310.0,779.0,706.0,302.0,30.0,1761.0,823.0,35.0,35.0,5.0,941.0,45.0,25.0,0.0,51.0,35.0,5.0,0.0,0.0,0.0,177.0,60.0,46.0,56.6 -Hellas Verona,21.0,43.5,4.0,44.0,360.0,4.0,2.0,0.0,0.0,10.0,1.0,1.0,0.5,1.5,1.0,1.5,2.3,2.3,0.57,0.57,4.0,4.0,360.0,4.0,1.0,22.0,18.0,86.4,2.0,1.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.9,0.19,0.9,0.22,35.0,93.0,37.6,109.0,8.0,56.9,42.9,35.0,88.6,62.7,54.0,1.0,1.9,8.0,2.0,19.4,11.0,0.0,31.4,2.75,0.11,0.36,0.07,1.7,1.7,1095.0,1485.0,73.7,23212.0,9160.0,364.0,455.0,80.0,520.0,609.0,85.4,193.0,341.0,56.6,28.0,81.0,13.0,5.0,99.0,1299.0,174.0,54.0,6.0,24.0,48.0,9.0,3.0,4.0,0.0,68.0,12.0,29.0,63.0,15.75,42.0,8.0,4.0,5.0,5.0,1.25,3.0,0.0,1.0,0.0,1.0,62.0,44.0,29.0,28.0,5.0,36.0,12.0,24.0,24.0,105.0,0.0,1900.0,253.0,712.0,870.0,341.0,49.0,1900.0,1025.0,51.0,36.0,10.0,1066.0,56.0,24.0,0.0,66.0,46.0,12.0,0.0,1.0,0.0,207.0,82.0,71.0,53.6 -Inter,19.0,48.8,4.0,44.0,360.0,13.0,11.0,2.0,2.0,5.0,0.0,3.25,2.75,6.0,2.75,5.5,9.9,8.4,2.47,2.09,4.0,4.0,360.0,1.0,0.25,8.0,7.0,87.5,4.0,0.0,0.0,3.0,75.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,1.6,0.2,0.6,0.16,24.0,41.0,58.5,112.0,19.0,31.3,30.8,29.0,20.7,28.3,41.0,2.0,4.9,0.0,0.0,6.5,22.0,3.0,30.6,5.5,0.15,0.5,0.12,3.1,2.6,1672.0,1987.0,84.1,29759.0,10606.0,741.0,813.0,91.1,671.0,755.0,88.9,186.0,294.0,63.3,54.0,133.0,44.0,15.0,173.0,1827.0,155.0,46.0,11.0,36.0,70.0,21.0,5.0,13.0,0.0,53.0,5.0,27.0,133.0,33.25,100.0,12.0,8.0,8.0,23.0,5.75,19.0,0.0,1.0,2.0,1.0,73.0,45.0,38.0,27.0,8.0,40.0,15.0,25.0,25.0,56.0,0.0,2381.0,239.0,729.0,1068.0,607.0,120.0,2379.0,1549.0,74.0,54.0,22.0,1657.0,40.0,17.0,0.0,47.0,45.0,5.0,2.0,0.0,0.0,187.0,44.0,30.0,59.5 -Juventus,21.0,48.8,4.0,44.0,360.0,9.0,7.0,1.0,2.0,13.0,0.0,2.25,1.75,4.0,2.0,3.75,7.5,5.9,1.87,1.48,4.0,4.0,360.0,2.0,0.5,14.0,12.0,85.7,3.0,1.0,0.0,2.0,50.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.5,0.26,1.5,0.38,18.0,41.0,43.9,102.0,19.0,35.3,31.5,17.0,29.4,30.6,59.0,3.0,5.1,2.0,0.5,11.5,17.0,1.0,30.4,4.25,0.14,0.47,0.11,1.5,2.1,1629.0,1978.0,82.4,28577.0,9433.0,737.0,820.0,89.9,696.0,782.0,89.0,163.0,280.0,58.2,46.0,116.0,46.0,14.0,156.0,1788.0,180.0,52.0,7.0,20.0,64.0,23.0,3.0,12.0,0.0,58.0,10.0,35.0,103.0,25.75,81.0,7.0,8.0,3.0,15.0,3.75,13.0,0.0,1.0,0.0,0.0,65.0,44.0,32.0,28.0,5.0,40.0,17.0,23.0,36.0,73.0,0.0,2402.0,261.0,782.0,1019.0,615.0,122.0,2400.0,1326.0,82.0,60.0,24.0,1607.0,47.0,17.0,0.0,51.0,48.0,10.0,1.0,0.0,0.0,181.0,38.0,26.0,59.4 -Lazio,20.0,56.0,4.0,44.0,360.0,4.0,4.0,0.0,0.0,9.0,0.0,1.0,1.0,2.0,1.0,2.0,4.2,4.2,1.05,1.05,4.0,4.0,360.0,7.0,1.75,21.0,14.0,66.7,1.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.7,0.18,-3.3,-0.83,6.0,16.0,37.5,119.0,14.0,10.9,26.4,15.0,20.0,27.9,48.0,2.0,4.2,6.0,1.5,15.7,13.0,2.0,27.1,3.25,0.08,0.31,0.09,-0.2,-0.2,2028.0,2410.0,84.1,32596.0,10968.0,1012.0,1127.0,89.8,797.0,892.0,89.3,151.0,255.0,59.2,39.0,175.0,37.0,7.0,217.0,2219.0,187.0,55.0,9.0,7.0,84.0,28.0,9.0,15.0,0.0,59.0,4.0,41.0,84.0,21.0,64.0,6.0,4.0,2.0,6.0,1.5,5.0,0.0,0.0,0.0,1.0,51.0,30.0,27.0,20.0,4.0,45.0,19.0,26.0,30.0,80.0,2.0,2819.0,266.0,775.0,1357.0,714.0,87.0,2819.0,1655.0,111.0,63.0,16.0,2012.0,53.0,25.0,0.0,47.0,46.0,4.0,0.0,0.0,0.0,188.0,30.0,51.0,37.0 -Lecce,19.0,43.5,4.0,44.0,360.0,7.0,5.0,2.0,2.0,10.0,1.0,1.75,1.25,3.0,1.25,2.5,4.3,2.8,1.08,0.7,4.0,4.0,360.0,4.0,1.0,17.0,13.0,76.5,2.0,2.0,0.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,4.6,0.27,0.6,0.15,20.0,52.0,38.5,78.0,18.0,38.5,31.0,42.0,52.4,38.7,54.0,2.0,3.7,2.0,0.5,10.3,16.0,1.0,31.4,4.0,0.1,0.31,0.06,2.7,2.2,1247.0,1589.0,78.5,21864.0,8240.0,562.0,648.0,86.7,532.0,632.0,84.2,113.0,216.0,52.3,41.0,81.0,24.0,10.0,131.0,1370.0,216.0,66.0,1.0,7.0,54.0,15.0,4.0,1.0,0.0,81.0,3.0,27.0,93.0,23.25,66.0,7.0,10.0,3.0,12.0,3.0,8.0,0.0,1.0,1.0,2.0,66.0,41.0,27.0,33.0,6.0,65.0,14.0,51.0,29.0,81.0,0.0,2071.0,252.0,679.0,909.0,506.0,81.0,2069.0,1228.0,89.0,42.0,23.0,1236.0,62.0,40.0,0.0,55.0,62.0,3.0,1.0,0.0,0.0,191.0,54.0,43.0,55.7 -Milan,19.0,55.3,4.0,44.0,360.0,9.0,6.0,3.0,3.0,10.0,1.0,2.25,1.5,3.75,1.5,3.0,6.5,4.3,1.63,1.07,4.0,4.0,360.0,7.0,1.75,15.0,8.0,60.0,3.0,0.0,1.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.5,0.24,-2.5,-0.64,21.0,58.0,36.2,198.0,26.0,22.2,29.2,23.0,60.9,47.0,52.0,12.0,23.1,3.0,0.75,9.8,15.0,1.0,36.6,3.75,0.15,0.4,0.1,2.5,1.7,1869.0,2166.0,86.3,31610.0,10609.0,848.0,926.0,91.6,830.0,896.0,92.6,144.0,243.0,59.3,36.0,98.0,32.0,9.0,140.0,1999.0,161.0,58.0,7.0,5.0,41.0,13.0,7.0,4.0,0.0,44.0,6.0,26.0,82.0,20.5,65.0,5.0,3.0,4.0,17.0,4.25,13.0,0.0,1.0,2.0,0.0,37.0,23.0,21.0,11.0,5.0,43.0,14.0,29.0,31.0,52.0,1.0,2512.0,287.0,883.0,1200.0,448.0,77.0,2509.0,1677.0,80.0,65.0,21.0,1838.0,49.0,33.0,1.0,45.0,53.0,6.0,2.0,1.0,0.0,169.0,33.0,42.0,44.0 -Monza,22.0,56.8,4.0,44.0,360.0,3.0,3.0,0.0,0.0,11.0,1.0,0.75,0.75,1.5,0.75,1.5,5.3,5.3,1.33,1.33,4.0,4.0,360.0,6.0,1.5,20.0,14.0,75.0,1.0,1.0,2.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,1.0,0.0,5.9,0.25,-0.1,-0.03,8.0,34.0,23.5,136.0,24.0,18.4,27.3,24.0,37.5,38.8,53.0,3.0,5.7,2.0,0.5,11.3,14.0,2.0,21.5,3.5,0.05,0.21,0.08,-2.3,-2.3,2018.0,2355.0,85.7,36926.0,10818.0,846.0,915.0,92.5,928.0,1020.0,91.0,212.0,318.0,66.7,50.0,148.0,49.0,15.0,176.0,2149.0,201.0,41.0,3.0,17.0,79.0,22.0,7.0,10.0,0.0,90.0,5.0,50.0,114.0,28.5,96.0,7.0,2.0,3.0,6.0,1.5,5.0,0.0,0.0,0.0,0.0,77.0,44.0,39.0,31.0,7.0,35.0,16.0,19.0,33.0,51.0,2.0,2755.0,290.0,822.0,1195.0,753.0,104.0,2755.0,1665.0,88.0,70.0,16.0,2001.0,53.0,30.0,1.0,53.0,35.0,5.0,0.0,1.0,0.0,175.0,37.0,45.0,45.1 -Napoli,19.0,61.8,4.0,44.0,360.0,8.0,5.0,1.0,2.0,5.0,0.0,2.0,1.25,3.25,1.75,3.0,7.2,5.6,1.8,1.41,4.0,4.0,360.0,5.0,1.25,7.0,2.0,42.9,2.0,1.0,1.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,0.0,3.4,0.37,-1.6,-0.4,3.0,12.0,25.0,86.0,8.0,14.0,24.7,11.0,0.0,20.4,27.0,1.0,3.7,7.0,1.75,18.2,20.0,2.0,26.3,5.0,0.09,0.35,0.07,0.8,1.4,2160.0,2508.0,86.1,35123.0,11353.0,1090.0,1161.0,93.9,858.0,968.0,88.6,154.0,248.0,62.1,64.0,156.0,51.0,9.0,196.0,2327.0,167.0,49.0,5.0,14.0,81.0,26.0,8.0,12.0,2.0,70.0,14.0,39.0,142.0,35.5,108.0,13.0,11.0,4.0,15.0,3.75,12.0,1.0,1.0,1.0,0.0,70.0,42.0,27.0,26.0,17.0,30.0,5.0,25.0,24.0,36.0,0.0,2877.0,156.0,646.0,1472.0,775.0,148.0,2875.0,1849.0,98.0,84.0,23.0,2135.0,57.0,21.0,0.0,42.0,39.0,14.0,1.0,1.0,0.0,208.0,47.0,35.0,57.3 -Roma,23.0,57.0,4.0,44.0,360.0,10.0,8.0,1.0,1.0,7.0,0.0,2.5,2.0,4.5,2.25,4.25,6.5,5.7,1.63,1.43,4.0,4.0,360.0,6.0,1.5,11.0,5.0,54.5,1.0,1.0,2.0,1.0,25.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,4.0,0.28,-2.0,-0.5,10.0,18.0,55.6,76.0,9.0,21.1,29.3,17.0,11.8,22.1,34.0,2.0,5.9,2.0,0.5,12.2,20.0,5.0,32.3,5.0,0.15,0.45,0.09,3.5,3.3,1762.0,2128.0,82.8,31116.0,10526.0,796.0,873.0,91.2,777.0,894.0,86.9,166.0,270.0,61.5,47.0,117.0,31.0,8.0,140.0,1939.0,182.0,44.0,2.0,15.0,90.0,26.0,12.0,13.0,0.0,83.0,7.0,35.0,113.0,28.25,77.0,11.0,10.0,7.0,16.0,4.0,10.0,1.0,2.0,0.0,0.0,68.0,45.0,28.0,35.0,5.0,32.0,7.0,25.0,24.0,35.0,1.0,2468.0,200.0,768.0,1159.0,559.0,92.0,2467.0,1563.0,94.0,73.0,23.0,1754.0,46.0,25.0,0.0,53.0,45.0,7.0,0.0,1.0,0.0,196.0,76.0,54.0,58.5 -Salernitana,21.0,51.5,4.0,44.0,360.0,3.0,3.0,0.0,0.0,13.0,0.0,0.75,0.75,1.5,0.75,1.5,2.4,2.4,0.6,0.6,4.0,4.0,360.0,8.0,2.0,18.0,10.0,61.1,0.0,2.0,2.0,0.0,0.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,0.0,4.7,0.21,-3.3,-0.82,13.0,55.0,23.6,89.0,14.0,40.4,35.9,35.0,54.3,43.6,63.0,4.0,6.3,1.0,0.25,7.8,14.0,1.0,37.8,3.5,0.08,0.21,0.06,0.6,0.6,1392.0,1815.0,76.7,22797.0,8752.0,670.0,772.0,86.8,552.0,662.0,83.4,109.0,244.0,44.7,29.0,95.0,30.0,6.0,133.0,1600.0,210.0,67.0,2.0,10.0,54.0,14.0,1.0,4.0,0.0,82.0,5.0,47.0,69.0,17.25,60.0,5.0,2.0,2.0,6.0,1.5,6.0,0.0,0.0,0.0,0.0,50.0,36.0,30.0,12.0,8.0,34.0,20.0,14.0,30.0,70.0,2.0,2198.0,227.0,694.0,1044.0,474.0,59.0,2198.0,1259.0,53.0,49.0,15.0,1380.0,50.0,36.0,0.0,48.0,62.0,5.0,0.0,1.0,0.0,183.0,54.0,86.0,38.6 -Sassuolo,24.0,43.5,4.0,44.0,360.0,5.0,4.0,1.0,1.0,4.0,1.0,1.25,1.0,2.25,1.0,2.0,3.6,2.8,0.89,0.7,4.0,4.0,360.0,9.0,2.25,18.0,9.0,61.1,1.0,0.0,3.0,0.0,0.0,3.0,2.0,0.0,1.0,4.0,0.0,2.0,0.0,6.0,0.23,-3.0,-0.74,16.0,61.0,26.2,119.0,13.0,41.2,37.1,43.0,27.9,29.4,55.0,2.0,3.6,10.0,2.5,20.4,17.0,2.0,34.0,4.25,0.08,0.24,0.06,1.4,1.2,1346.0,1698.0,79.3,23299.0,9314.0,625.0,690.0,90.6,543.0,641.0,84.7,132.0,264.0,50.0,42.0,111.0,21.0,1.0,141.0,1482.0,213.0,57.0,11.0,14.0,59.0,27.0,15.0,6.0,0.0,63.0,3.0,38.0,94.0,23.5,77.0,7.0,4.0,3.0,10.0,2.5,8.0,0.0,1.0,1.0,0.0,52.0,32.0,32.0,18.0,2.0,38.0,12.0,26.0,38.0,70.0,1.0,2084.0,291.0,768.0,835.0,504.0,84.0,2083.0,1086.0,75.0,47.0,27.0,1332.0,54.0,31.0,0.0,36.0,41.0,3.0,1.0,3.0,0.0,171.0,37.0,50.0,42.5 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+Torino,23.0,49.2,6.0,66.0,540.0,6.0,4.0,0.0,0.0,12.0,0.0,1.0,0.67,1.67,1.0,1.67,4.9,4.9,0.81,0.81,6.0,6.0,540.0,7.0,1.17,21.0,14.0,76.2,2.0,2.0,2.0,3.0,50.0,2.0,2.0,0.0,0.0,6.0,0.0,0.0,0.0,5.8,0.18,-1.2,-0.2,42.0,117.0,35.9,193.0,37.0,39.9,35.6,50.0,80.0,62.9,47.0,4.0,8.5,9.0,1.5,17.5,15.0,2.0,25.4,2.5,0.1,0.4,0.08,1.1,1.1,2246.0,2823.0,79.6,39911.0,14201.0,1026.0,1150.0,89.2,937.0,1091.0,85.9,228.0,434.0,52.5,38.0,166.0,31.0,10.0,207.0,2571.0,241.0,66.0,1.0,25.0,109.0,24.0,18.0,4.0,0.0,88.0,11.0,47.0,92.0,15.33,65.0,9.0,7.0,6.0,10.0,1.67,5.0,1.0,2.0,1.0,0.0,66.0,43.0,31.0,28.0,7.0,53.0,10.0,43.0,54.0,87.0,0.0,3381.0,341.0,1059.0,1568.0,792.0,82.0,3381.0,2044.0,123.0,95.0,19.0,2204.0,99.0,51.0,0.0,71.0,60.0,11.0,0.0,2.0,0.0,301.0,82.0,93.0,46.9 +Udinese,24.0,46.2,6.0,66.0,540.0,2.0,2.0,0.0,0.0,9.0,0.0,0.33,0.33,0.67,0.33,0.67,6.9,6.9,1.16,1.16,6.0,6.0,540.0,10.0,1.67,22.0,12.0,63.6,0.0,3.0,3.0,2.0,33.3,2.0,2.0,0.0,0.0,6.0,0.0,0.0,0.0,10.1,0.37,0.1,0.02,19.0,50.0,38.0,132.0,23.0,28.8,30.2,45.0,26.7,32.8,69.0,1.0,1.4,3.0,0.5,13.6,29.0,4.0,33.0,4.83,0.02,0.07,0.08,-4.9,-4.9,1952.0,2471.0,79.0,35494.0,14117.0,823.0,956.0,86.1,831.0,979.0,84.9,229.0,397.0,57.7,72.0,185.0,45.0,23.0,218.0,2186.0,279.0,71.0,5.0,21.0,115.0,35.0,14.0,13.0,0.0,102.0,6.0,30.0,162.0,27.0,115.0,17.0,10.0,6.0,4.0,0.67,2.0,0.0,0.0,0.0,0.0,89.0,54.0,58.0,23.0,8.0,57.0,15.0,42.0,51.0,108.0,4.0,3146.0,362.0,991.0,1435.0,754.0,109.0,3146.0,1862.0,104.0,75.0,21.0,1932.0,96.0,59.0,0.0,79.0,63.0,6.0,0.0,2.0,0.0,309.0,101.0,68.0,59.8 diff --git a/fbref_data/teams_vs.csv b/fbref_data/teams_vs.csv index f474d6b..b989393 100644 --- a/fbref_data/teams_vs.csv +++ b/fbref_data/teams_vs.csv @@ -1,21 +1,21 @@ team,players_used,possession,games,games_starts,minutes,goals,assists,pens_made,pens_att,cards_yellow,cards_red,goals_per90,assists_per90,goals_assists_per90,goals_pens_per90,goals_assists_pens_per90,xg,npxg,xg_per90,npxg_per90,gk_games,gk_games_starts,gk_minutes,gk_goals_against,gk_goals_against_per90,gk_shots_on_target_against,gk_saves,gk_save_pct,gk_wins,gk_ties,gk_losses,gk_clean_sheets,gk_clean_sheets_pct,gk_pens_att,gk_pens_allowed,gk_pens_saved,gk_pens_missed,minutes_90s,gk_free_kick_goals_against,gk_corner_kick_goals_against,gk_own_goals_against,gk_psxg,gk_psnpxg_per_shot_on_target_against,gk_psxg_net,gk_psxg_net_per90,gk_passes_completed_launched,gk_passes_launched,gk_passes_pct_launched,gk_passes,gk_passes_throws,gk_pct_passes_launched,gk_passes_length_avg,gk_goal_kicks,gk_pct_goal_kicks_launched,gk_goal_kick_length_avg,gk_crosses,gk_crosses_stopped,gk_crosses_stopped_pct,gk_def_actions_outside_pen_area,gk_def_actions_outside_pen_area_per90,gk_avg_distance_def_actions,shots_on_target,shots_free_kicks,shots_on_target_pct,shots_on_target_per90,goals_per_shot,goals_per_shot_on_target,npxg_per_shot,xg_net,npxg_net,passes_completed,passes,passes_pct,passes_total_distance,passes_progressive_distance,passes_completed_short,passes_short,passes_pct_short,passes_completed_medium,passes_medium,passes_pct_medium,passes_completed_long,passes_long,passes_pct_long,assisted_shots,passes_into_final_third,passes_into_penalty_area,crosses_into_penalty_area,progressive_passes,passes_live,passes_dead,passes_free_kicks,through_balls,passes_switches,crosses,corner_kicks,corner_kicks_in,corner_kicks_out,corner_kicks_straight,throw_ins,passes_offsides,passes_blocked,sca,sca_per90,sca_passes_live,sca_passes_dead,sca_shots,sca_fouled,gca,gca_per90,gca_passes_live,gca_passes_dead,gca_shots,gca_fouled,gca_defense,tackles,tackles_won,tackles_def_3rd,tackles_mid_3rd,tackles_att_3rd,blocks,blocked_shots,blocked_passes,interceptions,clearances,errors,touches,touches_def_pen_area,touches_def_3rd,touches_mid_3rd,touches_att_3rd,touches_att_pen_area,touches_live_ball,carries,progressive_carries,carries_into_final_third,carries_into_penalty_area,passes_received,miscontrols,dispossessed,cards_yellow_red,fouls,fouled,offsides,pens_won,pens_conceded,own_goals,ball_recoveries,aerials_won,aerials_lost,aerials_won_pct -vs Atalanta,23.0,50.5,4.0,44.0,360.0,5.0,4.0,0.0,0.0,5.0,0.0,1.25,1.0,2.25,1.25,2.25,2.6,2.6,0.66,0.66,4.0,4.0,360.0,8.0,2.0,22.0,14.0,63.6,2.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0,4.3,0.19,-3.7,-0.93,16.0,51.0,31.4,164.0,17.0,28.0,32.6,25.0,20.0,26.4,59.0,2.0,3.4,3.0,0.75,17.5,18.0,1.0,38.3,4.5,0.11,0.28,0.06,2.4,2.4,1761.0,2153.0,81.8,30316.0,10955.0,818.0,897.0,91.2,726.0,831.0,87.4,170.0,312.0,54.5,40.0,131.0,29.0,7.0,136.0,1947.0,204.0,56.0,4.0,9.0,52.0,16.0,8.0,6.0,0.0,83.0,2.0,49.0,84.0,21.0,68.0,8.0,2.0,1.0,9.0,2.25,4.0,3.0,0.0,0.0,1.0,62.0,38.0,27.0,29.0,6.0,55.0,16.0,39.0,39.0,73.0,1.0,2584.0,323.0,916.0,1144.0,548.0,62.0,2584.0,1536.0,73.0,53.0,13.0,1736.0,58.0,38.0,0.0,36.0,47.0,2.0,0.0,0.0,0.0,212.0,65.0,60.0,52.0 -vs Bologna,22.0,43.5,4.0,44.0,360.0,4.0,4.0,0.0,0.0,10.0,0.0,1.0,1.0,2.0,1.0,2.0,2.6,2.6,0.65,0.65,4.0,4.0,360.0,3.0,0.75,20.0,17.0,85.0,1.0,2.0,1.0,2.0,50.0,1.0,0.0,0.0,1.0,4.0,0.0,0.0,0.0,4.1,0.21,1.1,0.27,22.0,55.0,40.0,106.0,20.0,34.9,33.2,29.0,62.1,47.1,45.0,5.0,11.1,3.0,0.75,11.5,10.0,2.0,25.6,2.5,0.1,0.4,0.07,1.4,1.4,1456.0,1810.0,80.4,25775.0,9073.0,619.0,697.0,88.8,653.0,741.0,88.1,142.0,254.0,55.9,30.0,118.0,31.0,13.0,150.0,1623.0,175.0,44.0,2.0,10.0,72.0,17.0,6.0,8.0,0.0,72.0,12.0,41.0,69.0,17.25,56.0,4.0,4.0,4.0,8.0,2.0,8.0,0.0,0.0,0.0,0.0,52.0,37.0,26.0,19.0,7.0,37.0,12.0,25.0,33.0,51.0,2.0,2202.0,227.0,681.0,1007.0,531.0,80.0,2202.0,1299.0,69.0,49.0,17.0,1431.0,62.0,30.0,0.0,50.0,40.0,12.0,0.0,1.0,0.0,207.0,34.0,46.0,42.5 -vs Cagliari,21.0,62.3,4.0,44.0,360.0,4.0,3.0,0.0,1.0,4.0,0.0,1.0,0.75,1.75,1.0,1.75,4.9,4.1,1.23,1.04,4.0,4.0,360.0,1.0,0.25,6.0,5.0,83.3,2.0,2.0,0.0,3.0,75.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,2.3,0.39,1.3,0.33,16.0,41.0,39.0,105.0,22.0,22.9,30.6,43.0,39.5,41.9,55.0,1.0,1.8,2.0,0.5,13.0,13.0,0.0,24.1,3.25,0.07,0.31,0.08,-0.9,-0.1,2074.0,2485.0,83.5,36018.0,12461.0,953.0,1055.0,90.3,866.0,969.0,89.4,189.0,332.0,56.9,38.0,173.0,41.0,11.0,206.0,2283.0,197.0,52.0,5.0,20.0,83.0,26.0,11.0,13.0,0.0,71.0,5.0,29.0,97.0,24.25,74.0,10.0,7.0,3.0,6.0,1.5,5.0,0.0,1.0,0.0,0.0,69.0,45.0,37.0,24.0,8.0,38.0,10.0,28.0,28.0,68.0,1.0,2890.0,229.0,812.0,1432.0,667.0,99.0,2889.0,1859.0,85.0,68.0,18.0,2050.0,61.0,27.0,0.0,38.0,41.0,5.0,0.0,0.0,0.0,220.0,60.0,51.0,54.1 -vs Empoli,27.0,52.3,4.0,44.0,360.0,11.0,8.0,1.0,2.0,8.0,0.0,2.75,2.0,4.75,2.5,4.5,7.5,5.9,1.88,1.49,4.0,4.0,360.0,0.0,0.0,12.0,12.0,100.0,4.0,0.0,0.0,4.0,100.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,1.7,0.15,1.7,0.43,19.0,51.0,37.3,118.0,16.0,32.2,33.6,28.0,46.4,41.5,54.0,6.0,11.1,6.0,1.5,14.8,21.0,2.0,35.0,5.25,0.17,0.48,0.1,3.5,4.1,1676.0,2041.0,82.1,31329.0,10367.0,731.0,815.0,89.7,709.0,806.0,88.0,215.0,338.0,63.6,49.0,101.0,42.0,16.0,144.0,1851.0,182.0,45.0,8.0,22.0,62.0,19.0,6.0,7.0,0.0,81.0,8.0,42.0,112.0,28.0,87.0,6.0,6.0,4.0,17.0,4.25,12.0,0.0,2.0,0.0,0.0,87.0,57.0,47.0,35.0,5.0,42.0,9.0,33.0,35.0,78.0,1.0,2493.0,274.0,897.0,1061.0,552.0,103.0,2491.0,1472.0,84.0,61.0,24.0,1661.0,50.0,22.0,0.0,60.0,42.0,8.0,1.0,0.0,0.0,203.0,54.0,39.0,58.1 -vs Fiorentina,22.0,39.0,4.0,44.0,360.0,9.0,8.0,1.0,1.0,8.0,0.0,2.25,2.0,4.25,2.0,4.0,4.8,4.1,1.21,1.02,4.0,4.0,360.0,9.0,2.25,19.0,10.0,52.6,1.0,1.0,2.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,2.0,0.0,5.1,0.27,-3.9,-0.98,25.0,64.0,39.1,102.0,13.0,48.0,37.9,19.0,78.9,55.0,45.0,4.0,8.9,0.0,0.0,8.8,18.0,1.0,43.9,4.5,0.2,0.44,0.1,4.2,3.9,1101.0,1465.0,75.2,20156.0,8085.0,469.0,560.0,83.8,473.0,562.0,84.2,126.0,238.0,52.9,33.0,69.0,28.0,9.0,123.0,1281.0,179.0,50.0,4.0,14.0,40.0,11.0,0.0,8.0,0.0,80.0,5.0,42.0,72.0,18.0,48.0,6.0,7.0,3.0,17.0,4.25,12.0,0.0,1.0,1.0,2.0,80.0,52.0,42.0,31.0,7.0,53.0,9.0,44.0,39.0,66.0,2.0,1877.0,234.0,684.0,824.0,391.0,59.0,1876.0,1043.0,53.0,40.0,11.0,1091.0,44.0,33.0,0.0,56.0,43.0,5.0,1.0,0.0,0.0,202.0,56.0,53.0,51.4 -vs Frosinone,23.0,51.8,4.0,44.0,360.0,6.0,5.0,0.0,0.0,9.0,0.0,1.5,1.25,2.75,1.5,2.75,5.9,5.9,1.48,1.48,4.0,4.0,360.0,7.0,1.75,13.0,6.0,61.5,1.0,1.0,2.0,1.0,25.0,2.0,2.0,0.0,0.0,4.0,0.0,2.0,0.0,4.8,0.22,-2.2,-0.54,15.0,47.0,31.9,98.0,11.0,35.7,32.6,32.0,37.5,36.3,33.0,0.0,0.0,12.0,3.0,23.0,27.0,2.0,40.3,6.75,0.09,0.22,0.09,0.1,0.1,1600.0,1980.0,80.8,27918.0,10232.0,735.0,825.0,89.1,685.0,785.0,87.3,147.0,271.0,54.2,54.0,125.0,37.0,7.0,190.0,1769.0,205.0,51.0,9.0,9.0,74.0,22.0,9.0,7.0,0.0,85.0,6.0,37.0,127.0,31.75,105.0,8.0,4.0,2.0,11.0,2.75,10.0,0.0,1.0,0.0,0.0,66.0,33.0,38.0,21.0,7.0,34.0,11.0,23.0,25.0,55.0,1.0,2375.0,218.0,661.0,1079.0,655.0,105.0,2375.0,1426.0,87.0,61.0,27.0,1588.0,51.0,28.0,0.0,50.0,39.0,6.0,0.0,2.0,0.0,212.0,53.0,52.0,50.5 -vs Genoa,19.0,66.8,4.0,44.0,360.0,7.0,6.0,0.0,0.0,11.0,0.0,1.75,1.5,3.25,1.75,3.25,3.8,3.8,0.95,0.95,4.0,4.0,360.0,4.0,1.0,10.0,6.0,60.0,2.0,1.0,1.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,3.0,0.0,2.3,0.25,-1.7,-0.43,5.0,16.0,31.3,94.0,16.0,13.8,28.1,20.0,15.0,27.6,33.0,1.0,3.0,4.0,1.0,17.9,14.0,3.0,29.8,3.5,0.15,0.5,0.08,3.2,3.2,2268.0,2703.0,83.9,38209.0,11424.0,1083.0,1177.0,92.0,947.0,1073.0,88.3,188.0,308.0,61.0,31.0,193.0,42.0,9.0,244.0,2498.0,196.0,53.0,4.0,15.0,102.0,24.0,8.0,13.0,0.0,91.0,9.0,52.0,77.0,19.25,59.0,5.0,3.0,4.0,13.0,3.25,7.0,1.0,2.0,0.0,0.0,47.0,31.0,15.0,26.0,6.0,31.0,4.0,27.0,24.0,48.0,0.0,3068.0,178.0,626.0,1590.0,878.0,105.0,3068.0,2108.0,132.0,103.0,21.0,2247.0,57.0,33.0,0.0,43.0,43.0,9.0,0.0,0.0,0.0,200.0,46.0,60.0,43.4 -vs Hellas Verona,21.0,56.5,4.0,44.0,360.0,4.0,2.0,1.0,1.0,8.0,0.0,1.0,0.5,1.5,0.75,1.25,4.6,3.8,1.14,0.95,4.0,4.0,360.0,4.0,1.0,11.0,7.0,63.6,1.0,1.0,2.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,2.4,0.22,-1.6,-0.39,18.0,64.0,28.1,131.0,19.0,42.7,36.5,24.0,33.3,35.3,33.0,3.0,9.1,2.0,0.5,12.1,21.0,5.0,35.6,5.25,0.05,0.14,0.07,-0.6,-0.8,1509.0,1936.0,77.9,26680.0,9898.0,656.0,749.0,87.6,668.0,791.0,84.5,143.0,296.0,48.3,43.0,86.0,29.0,5.0,127.0,1691.0,238.0,72.0,6.0,10.0,75.0,28.0,12.0,12.0,0.0,101.0,7.0,29.0,108.0,27.0,79.0,7.0,9.0,7.0,7.0,1.75,4.0,0.0,2.0,1.0,0.0,47.0,26.0,23.0,19.0,5.0,31.0,5.0,26.0,22.0,39.0,3.0,2281.0,215.0,755.0,1050.0,498.0,98.0,2280.0,1296.0,79.0,47.0,24.0,1488.0,49.0,37.0,0.0,47.0,63.0,7.0,1.0,0.0,0.0,190.0,71.0,82.0,46.4 -vs Inter,19.0,51.3,4.0,44.0,360.0,1.0,1.0,0.0,0.0,5.0,0.0,0.25,0.25,0.5,0.25,0.5,2.9,2.9,0.71,0.71,4.0,4.0,360.0,13.0,3.25,24.0,11.0,54.2,0.0,0.0,4.0,0.0,0.0,2.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,9.1,0.31,-3.9,-0.96,15.0,40.0,37.5,112.0,18.0,23.2,30.3,27.0,51.9,45.3,54.0,0.0,0.0,4.0,1.0,14.9,8.0,1.0,20.5,2.0,0.03,0.13,0.07,-1.9,-1.9,1754.0,2055.0,85.4,32260.0,10313.0,738.0,816.0,90.4,759.0,841.0,90.2,207.0,290.0,71.4,30.0,120.0,37.0,10.0,151.0,1872.0,178.0,50.0,2.0,23.0,59.0,8.0,0.0,7.0,0.0,65.0,5.0,35.0,69.0,17.25,58.0,1.0,1.0,2.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,36.0,22.0,21.0,10.0,5.0,41.0,18.0,23.0,31.0,80.0,1.0,2432.0,268.0,746.0,1156.0,546.0,69.0,2432.0,1630.0,79.0,66.0,14.0,1733.0,55.0,33.0,0.0,47.0,44.0,5.0,0.0,2.0,0.0,163.0,30.0,44.0,40.5 -vs Juventus,21.0,51.3,4.0,44.0,360.0,2.0,2.0,0.0,0.0,6.0,0.0,0.5,0.5,1.0,0.5,1.0,2.4,2.4,0.6,0.6,4.0,4.0,360.0,9.0,2.25,19.0,9.0,57.9,0.0,1.0,3.0,0.0,0.0,2.0,1.0,1.0,0.0,4.0,0.0,1.0,0.0,5.9,0.21,-3.1,-0.77,10.0,37.0,27.0,109.0,20.0,27.5,31.6,20.0,35.0,35.6,54.0,0.0,0.0,2.0,0.5,11.7,14.0,3.0,27.5,3.5,0.04,0.14,0.05,-0.4,-0.4,1747.0,2066.0,84.6,29660.0,9622.0,793.0,872.0,90.9,698.0,789.0,88.5,173.0,268.0,64.6,39.0,150.0,31.0,5.0,165.0,1877.0,184.0,57.0,3.0,9.0,79.0,21.0,9.0,6.0,0.0,61.0,5.0,30.0,91.0,22.75,73.0,5.0,5.0,3.0,2.0,0.5,2.0,0.0,0.0,0.0,0.0,46.0,27.0,27.0,13.0,6.0,47.0,12.0,35.0,23.0,56.0,3.0,2462.0,270.0,753.0,1101.0,631.0,66.0,2462.0,1453.0,96.0,61.0,14.0,1739.0,60.0,25.0,0.0,52.0,49.0,5.0,0.0,2.0,0.0,173.0,26.0,38.0,40.6 -vs Lazio,20.0,44.0,4.0,44.0,360.0,7.0,5.0,0.0,0.0,10.0,0.0,1.75,1.25,3.0,1.75,3.0,5.5,5.5,1.36,1.36,4.0,4.0,360.0,4.0,1.0,13.0,9.0,69.2,3.0,0.0,1.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.5,0.27,-0.5,-0.12,23.0,41.0,56.1,99.0,17.0,28.3,29.6,24.0,54.2,42.0,62.0,3.0,4.8,5.0,1.25,12.2,21.0,2.0,31.3,5.25,0.1,0.33,0.09,1.5,1.5,1519.0,1868.0,81.3,27353.0,9374.0,641.0,717.0,89.4,684.0,781.0,87.6,148.0,267.0,55.4,51.0,109.0,29.0,8.0,129.0,1684.0,177.0,48.0,2.0,15.0,61.0,20.0,5.0,8.0,1.0,65.0,7.0,29.0,122.0,30.5,87.0,15.0,12.0,4.0,13.0,3.25,11.0,1.0,1.0,0.0,0.0,53.0,24.0,31.0,14.0,8.0,50.0,15.0,35.0,44.0,94.0,1.0,2319.0,278.0,801.0,998.0,537.0,99.0,2319.0,1323.0,75.0,44.0,20.0,1506.0,53.0,22.0,0.0,49.0,44.0,7.0,0.0,0.0,0.0,196.0,51.0,30.0,63.0 -vs Lecce,19.0,56.5,4.0,44.0,360.0,4.0,4.0,0.0,0.0,12.0,1.0,1.0,1.0,2.0,1.0,2.0,6.2,6.2,1.54,1.54,4.0,4.0,360.0,7.0,1.75,18.0,11.0,72.2,0.0,2.0,2.0,0.0,0.0,2.0,2.0,0.0,0.0,4.0,0.0,0.0,0.0,5.5,0.2,-1.5,-0.38,13.0,32.0,40.6,117.0,22.0,22.2,27.1,13.0,46.2,35.8,40.0,3.0,7.5,3.0,0.75,12.2,17.0,3.0,30.4,4.25,0.07,0.24,0.11,-2.2,-2.2,1682.0,2064.0,81.5,30090.0,10531.0,708.0,795.0,89.1,760.0,864.0,88.0,171.0,275.0,62.2,43.0,115.0,45.0,7.0,192.0,1863.0,196.0,56.0,11.0,18.0,75.0,20.0,6.0,5.0,0.0,90.0,5.0,60.0,101.0,25.25,80.0,8.0,4.0,3.0,8.0,2.0,7.0,1.0,0.0,0.0,0.0,81.0,48.0,40.0,27.0,14.0,42.0,19.0,23.0,28.0,57.0,1.0,2480.0,205.0,684.0,1177.0,641.0,89.0,2480.0,1425.0,65.0,56.0,8.0,1663.0,56.0,40.0,1.0,64.0,53.0,5.0,0.0,2.0,0.0,203.0,43.0,54.0,44.3 -vs Milan,19.0,44.8,4.0,44.0,360.0,7.0,6.0,1.0,1.0,9.0,0.0,1.75,1.5,3.25,1.5,3.0,4.9,4.1,1.22,1.02,4.0,4.0,360.0,9.0,2.25,18.0,9.0,66.7,1.0,0.0,3.0,0.0,0.0,3.0,3.0,0.0,0.0,4.0,0.0,0.0,0.0,6.9,0.22,-2.1,-0.52,16.0,36.0,44.4,91.0,20.0,29.7,31.1,22.0,40.9,37.0,34.0,2.0,5.9,2.0,0.5,11.9,14.0,3.0,27.5,3.5,0.12,0.43,0.08,2.1,1.9,1454.0,1763.0,82.5,26524.0,9660.0,648.0,713.0,90.9,603.0,690.0,87.4,168.0,266.0,63.2,37.0,127.0,25.0,11.0,136.0,1603.0,153.0,47.0,3.0,25.0,63.0,12.0,6.0,4.0,0.0,56.0,7.0,33.0,91.0,22.75,68.0,6.0,5.0,6.0,11.0,2.75,8.0,0.0,1.0,1.0,0.0,57.0,26.0,22.0,31.0,4.0,36.0,12.0,24.0,25.0,44.0,0.0,2110.0,234.0,642.0,1020.0,470.0,71.0,2109.0,1233.0,68.0,54.0,16.0,1442.0,41.0,15.0,0.0,56.0,43.0,7.0,1.0,3.0,0.0,176.0,42.0,33.0,56.0 -vs Monza,22.0,43.3,4.0,44.0,360.0,6.0,5.0,1.0,1.0,4.0,1.0,1.5,1.25,2.75,1.25,2.5,5.8,5.0,1.45,1.25,4.0,4.0,360.0,3.0,0.75,14.0,11.0,78.6,2.0,1.0,1.0,2.0,50.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.0,0.21,0.0,-0.01,12.0,32.0,37.5,97.0,21.0,18.6,25.6,46.0,30.4,34.1,60.0,1.0,1.7,5.0,1.25,14.8,19.0,1.0,31.1,4.75,0.08,0.26,0.08,0.2,0.0,1510.0,1807.0,83.6,26285.0,9815.0,701.0,788.0,89.0,586.0,656.0,89.3,167.0,261.0,64.0,52.0,112.0,31.0,13.0,150.0,1622.0,179.0,55.0,9.0,19.0,70.0,21.0,5.0,10.0,0.0,50.0,6.0,25.0,110.0,27.5,80.0,11.0,8.0,3.0,11.0,2.75,8.0,0.0,1.0,1.0,1.0,60.0,40.0,32.0,21.0,7.0,59.0,19.0,40.0,31.0,76.0,0.0,2247.0,255.0,710.0,960.0,601.0,110.0,2246.0,1402.0,91.0,47.0,27.0,1497.0,52.0,44.0,0.0,37.0,52.0,6.0,1.0,0.0,0.0,187.0,45.0,37.0,54.9 -vs Napoli,19.0,38.3,4.0,44.0,360.0,5.0,4.0,1.0,1.0,9.0,1.0,1.25,1.0,2.25,1.0,2.0,2.9,2.1,0.71,0.52,4.0,4.0,360.0,8.0,2.0,21.0,13.0,66.7,1.0,1.0,2.0,0.0,0.0,2.0,1.0,0.0,1.0,4.0,0.0,0.0,0.0,5.8,0.23,-2.2,-0.56,18.0,50.0,36.0,118.0,16.0,29.7,31.5,29.0,51.7,40.1,62.0,1.0,1.6,3.0,0.75,10.5,6.0,1.0,26.1,1.5,0.17,0.67,0.09,2.1,1.9,1255.0,1566.0,80.1,19997.0,8148.0,663.0,733.0,90.5,444.0,519.0,85.5,96.0,205.0,46.8,20.0,70.0,14.0,2.0,104.0,1390.0,169.0,54.0,1.0,7.0,39.0,13.0,2.0,8.0,0.0,45.0,7.0,30.0,46.0,11.5,32.0,4.0,3.0,2.0,9.0,2.25,4.0,2.0,1.0,1.0,1.0,49.0,33.0,32.0,16.0,1.0,63.0,27.0,36.0,26.0,97.0,0.0,1987.0,350.0,906.0,784.0,323.0,47.0,1986.0,983.0,56.0,42.0,15.0,1243.0,56.0,33.0,0.0,47.0,39.0,7.0,1.0,2.0,0.0,173.0,35.0,47.0,42.7 -vs Roma,23.0,43.0,4.0,44.0,360.0,6.0,4.0,1.0,1.0,11.0,2.0,1.5,1.0,2.5,1.25,2.25,2.7,2.0,0.67,0.5,4.0,4.0,360.0,11.0,2.75,21.0,11.0,52.4,2.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,4.0,0.0,2.0,1.0,6.3,0.27,-3.7,-0.92,24.0,78.0,30.8,124.0,16.0,37.1,35.9,41.0,78.0,56.2,73.0,10.0,13.7,2.0,0.5,8.6,10.0,0.0,41.7,2.5,0.21,0.5,0.08,3.3,3.0,1356.0,1678.0,80.8,24302.0,8651.0,584.0,655.0,89.2,619.0,697.0,88.8,125.0,250.0,50.0,20.0,85.0,14.0,5.0,100.0,1495.0,179.0,59.0,0.0,13.0,44.0,13.0,5.0,4.0,0.0,51.0,4.0,29.0,45.0,11.25,33.0,3.0,3.0,3.0,11.0,2.75,7.0,0.0,2.0,1.0,1.0,46.0,33.0,21.0,19.0,6.0,42.0,13.0,29.0,33.0,83.0,1.0,2068.0,277.0,736.0,984.0,368.0,39.0,2067.0,1215.0,53.0,38.0,14.0,1342.0,47.0,33.0,1.0,46.0,51.0,4.0,1.0,1.0,1.0,159.0,54.0,76.0,41.5 -vs Salernitana,21.0,48.5,4.0,44.0,360.0,8.0,5.0,1.0,1.0,9.0,0.0,2.0,1.25,3.25,1.75,3.0,6.2,5.4,1.54,1.36,4.0,4.0,360.0,3.0,0.75,14.0,11.0,78.6,2.0,2.0,0.0,2.0,50.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,3.6,0.26,0.6,0.15,31.0,70.0,44.3,96.0,12.0,56.3,40.4,18.0,88.9,63.0,40.0,4.0,10.0,7.0,1.75,16.4,17.0,2.0,29.8,4.25,0.12,0.41,0.1,1.8,1.6,1318.0,1715.0,76.9,23999.0,9176.0,590.0,677.0,87.1,557.0,677.0,82.3,146.0,285.0,51.2,44.0,115.0,30.0,14.0,133.0,1520.0,191.0,50.0,1.0,13.0,77.0,22.0,13.0,2.0,0.0,85.0,4.0,17.0,101.0,25.25,67.0,13.0,11.0,4.0,13.0,3.25,9.0,1.0,2.0,0.0,0.0,62.0,41.0,24.0,31.0,7.0,44.0,4.0,40.0,39.0,62.0,0.0,2150.0,211.0,629.0,974.0,568.0,82.0,2149.0,1206.0,70.0,51.0,11.0,1301.0,71.0,22.0,0.0,64.0,46.0,4.0,0.0,0.0,0.0,203.0,86.0,54.0,61.4 -vs Sassuolo,24.0,56.5,4.0,44.0,360.0,9.0,6.0,2.0,3.0,7.0,0.0,2.25,1.5,3.75,1.75,3.25,8.2,5.9,2.06,1.48,4.0,4.0,360.0,5.0,1.25,18.0,13.0,77.8,3.0,0.0,1.0,2.0,50.0,1.0,1.0,0.0,0.0,4.0,0.0,0.0,0.0,5.1,0.23,0.1,0.04,10.0,42.0,23.8,123.0,20.0,27.6,27.7,14.0,57.1,44.7,39.0,3.0,7.7,5.0,1.25,18.4,16.0,0.0,24.6,4.0,0.11,0.44,0.09,0.8,1.1,1849.0,2203.0,83.9,32031.0,11238.0,865.0,944.0,91.6,751.0,833.0,90.2,187.0,308.0,60.7,53.0,116.0,42.0,10.0,176.0,2032.0,156.0,36.0,7.0,18.0,80.0,25.0,5.0,12.0,1.0,66.0,15.0,30.0,119.0,29.75,93.0,11.0,7.0,4.0,16.0,4.0,11.0,2.0,1.0,2.0,0.0,56.0,37.0,25.0,22.0,9.0,47.0,17.0,30.0,22.0,66.0,0.0,2599.0,250.0,853.0,1108.0,657.0,119.0,2596.0,1606.0,77.0,62.0,25.0,1819.0,52.0,25.0,0.0,45.0,34.0,15.0,2.0,1.0,0.0,207.0,50.0,37.0,57.5 -vs Torino,22.0,48.8,4.0,44.0,360.0,4.0,2.0,2.0,2.0,10.0,0.0,1.0,0.5,1.5,0.5,1.0,4.3,2.7,1.08,0.68,4.0,4.0,360.0,5.0,1.25,9.0,4.0,44.4,1.0,1.0,2.0,1.0,25.0,0.0,0.0,0.0,0.0,4.0,0.0,1.0,0.0,2.2,0.24,-2.8,-0.71,24.0,60.0,40.0,147.0,16.0,32.7,35.0,22.0,54.5,46.0,55.0,7.0,12.7,4.0,1.0,15.5,13.0,1.0,29.5,3.25,0.05,0.15,0.06,-0.3,-0.7,1371.0,1775.0,77.2,23561.0,9175.0,658.0,754.0,87.3,536.0,643.0,83.4,138.0,278.0,49.6,34.0,91.0,20.0,4.0,113.0,1601.0,167.0,60.0,7.0,7.0,42.0,6.0,3.0,3.0,0.0,62.0,7.0,29.0,84.0,21.0,63.0,7.0,1.0,7.0,7.0,1.75,5.0,0.0,0.0,1.0,0.0,58.0,35.0,32.0,20.0,6.0,31.0,10.0,21.0,35.0,63.0,1.0,2135.0,251.0,805.0,912.0,445.0,64.0,2133.0,1272.0,61.0,48.0,21.0,1337.0,48.0,28.0,0.0,44.0,48.0,7.0,1.0,0.0,0.0,207.0,63.0,59.0,51.6 -vs Udinese,22.0,51.5,4.0,44.0,360.0,4.0,3.0,1.0,1.0,11.0,1.0,1.0,0.75,1.75,0.75,1.5,5.7,4.9,1.42,1.23,4.0,4.0,360.0,1.0,0.25,18.0,17.0,94.4,1.0,3.0,0.0,3.0,75.0,0.0,0.0,0.0,0.0,4.0,0.0,0.0,0.0,4.1,0.24,3.1,0.79,19.0,53.0,35.8,106.0,18.0,36.8,34.3,31.0,45.2,40.7,60.0,4.0,6.7,4.0,1.0,13.4,9.0,0.0,23.1,2.25,0.08,0.33,0.13,-1.7,-1.9,1412.0,1816.0,77.8,24453.0,9422.0,660.0,752.0,87.8,562.0,660.0,85.2,145.0,299.0,48.5,31.0,95.0,31.0,10.0,135.0,1604.0,202.0,60.0,5.0,9.0,61.0,19.0,4.0,9.0,0.0,71.0,10.0,32.0,66.0,16.5,52.0,5.0,5.0,0.0,6.0,1.5,6.0,0.0,0.0,0.0,0.0,67.0,43.0,34.0,30.0,3.0,27.0,14.0,13.0,27.0,75.0,2.0,2213.0,267.0,750.0,993.0,488.0,77.0,2212.0,1216.0,71.0,49.0,16.0,1393.0,61.0,25.0,1.0,43.0,51.0,10.0,0.0,0.0,0.0,188.0,52.0,64.0,44.8 +vs Atalanta,24.0,49.5,6.0,66.0,540.0,5.0,4.0,0.0,0.0,9.0,0.0,0.83,0.67,1.5,0.83,1.5,3.9,3.9,0.64,0.64,6.0,6.0,540.0,11.0,1.83,30.0,19.0,63.3,2.0,0.0,4.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,2.0,0.0,7.3,0.24,-3.7,-0.62,35.0,107.0,32.7,239.0,21.0,38.9,37.1,38.0,36.8,37.1,79.0,3.0,3.8,6.0,1.0,18.1,20.0,2.0,29.4,3.33,0.07,0.25,0.06,1.1,1.1,2404.0,3068.0,78.4,43330.0,16035.0,1066.0,1198.0,89.0,1011.0,1193.0,84.7,271.0,516.0,52.5,52.0,186.0,43.0,13.0,197.0,2742.0,322.0,93.0,6.0,19.0,90.0,27.0,14.0,9.0,0.0,135.0,4.0,73.0,119.0,19.83,94.0,12.0,3.0,2.0,9.0,1.5,4.0,3.0,0.0,0.0,1.0,89.0,54.0,42.0,40.0,7.0,79.0,19.0,60.0,54.0,99.0,1.0,3706.0,431.0,1320.0,1633.0,785.0,93.0,3706.0,2098.0,91.0,73.0,17.0,2367.0,93.0,56.0,0.0,57.0,74.0,4.0,0.0,0.0,0.0,347.0,97.0,109.0,47.1 +vs Bologna,23.0,45.3,6.0,66.0,540.0,4.0,4.0,0.0,1.0,20.0,0.0,0.67,0.67,1.33,0.67,1.33,5.4,4.6,0.9,0.77,6.0,6.0,540.0,3.0,0.5,27.0,24.0,88.9,1.0,4.0,1.0,4.0,66.7,1.0,0.0,0.0,1.0,6.0,0.0,0.0,0.0,5.1,0.19,2.1,0.35,27.0,66.0,40.9,153.0,31.0,29.4,31.1,35.0,60.0,46.9,72.0,5.0,6.9,4.0,0.67,12.4,17.0,4.0,28.3,2.83,0.07,0.24,0.08,-1.4,-0.6,2292.0,2820.0,81.3,40249.0,13662.0,996.0,1112.0,89.6,1030.0,1166.0,88.3,209.0,378.0,55.3,43.0,183.0,45.0,17.0,223.0,2547.0,257.0,75.0,6.0,14.0,115.0,29.0,8.0,17.0,0.0,102.0,16.0,59.0,106.0,17.67,87.0,5.0,7.0,6.0,8.0,1.33,8.0,0.0,0.0,0.0,0.0,85.0,54.0,41.0,33.0,11.0,50.0,15.0,35.0,47.0,77.0,2.0,3402.0,336.0,1009.0,1587.0,833.0,119.0,3401.0,2001.0,109.0,70.0,28.0,2259.0,89.0,43.0,0.0,71.0,70.0,16.0,0.0,1.0,0.0,292.0,47.0,73.0,39.2 +vs Cagliari,22.0,61.8,6.0,66.0,540.0,9.0,6.0,0.0,1.0,6.0,0.0,1.5,1.0,2.5,1.5,2.5,8.8,8.0,1.47,1.34,6.0,6.0,540.0,2.0,0.33,12.0,10.0,83.3,4.0,2.0,0.0,4.0,66.7,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,3.1,0.25,1.1,0.18,21.0,60.0,35.0,166.0,38.0,21.1,29.1,55.0,45.5,43.6,83.0,4.0,4.8,7.0,1.17,14.3,25.0,0.0,30.9,4.17,0.11,0.36,0.1,0.2,1.0,3144.0,3739.0,84.1,54053.0,18433.0,1444.0,1588.0,90.9,1302.0,1445.0,90.1,283.0,495.0,57.2,58.0,261.0,60.0,13.0,308.0,3444.0,284.0,77.0,11.0,28.0,116.0,38.0,15.0,17.0,0.0,104.0,11.0,45.0,148.0,24.67,112.0,12.0,9.0,5.0,16.0,2.67,12.0,1.0,2.0,0.0,0.0,96.0,63.0,53.0,31.0,12.0,61.0,19.0,42.0,34.0,105.0,1.0,4347.0,355.0,1284.0,2078.0,1021.0,149.0,4346.0,2764.0,140.0,96.0,34.0,3107.0,95.0,41.0,0.0,50.0,65.0,11.0,0.0,0.0,0.0,332.0,92.0,71.0,56.4 +vs Empoli,28.0,54.7,6.0,66.0,540.0,12.0,8.0,1.0,2.0,11.0,0.0,2.0,1.33,3.33,1.83,3.17,9.8,8.2,1.63,1.37,6.0,6.0,540.0,1.0,0.17,19.0,18.0,94.7,5.0,0.0,1.0,5.0,83.3,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,3.7,0.19,2.7,0.44,25.0,73.0,34.2,192.0,25.0,29.7,32.4,38.0,42.1,37.9,79.0,7.0,8.9,7.0,1.17,14.1,28.0,2.0,28.9,4.67,0.11,0.39,0.09,2.2,2.8,2568.0,3162.0,81.2,46872.0,15809.0,1134.0,1271.0,89.2,1064.0,1225.0,86.9,312.0,501.0,62.3,82.0,152.0,62.0,24.0,224.0,2852.0,300.0,83.0,11.0,36.0,103.0,27.0,10.0,7.0,0.0,139.0,10.0,68.0,177.0,29.5,139.0,10.0,11.0,5.0,18.0,3.0,12.0,0.0,3.0,0.0,0.0,126.0,81.0,67.0,51.0,8.0,63.0,13.0,50.0,57.0,102.0,1.0,3829.0,415.0,1365.0,1578.0,912.0,154.0,3827.0,2267.0,123.0,95.0,34.0,2546.0,81.0,37.0,0.0,84.0,74.0,10.0,1.0,0.0,0.0,313.0,82.0,60.0,57.7 +vs Fiorentina,24.0,42.8,6.0,66.0,540.0,10.0,8.0,1.0,1.0,11.0,0.0,1.67,1.33,3.0,1.5,2.83,7.8,7.0,1.29,1.17,6.0,6.0,540.0,12.0,2.0,27.0,15.0,55.6,1.0,2.0,3.0,1.0,16.7,0.0,0.0,0.0,0.0,6.0,0.0,2.0,0.0,7.6,0.28,-4.4,-0.74,33.0,87.0,37.9,174.0,22.0,41.4,34.7,23.0,65.2,49.2,69.0,5.0,7.2,0.0,0.0,9.2,29.0,2.0,40.3,4.83,0.13,0.31,0.1,2.2,2.0,1785.0,2372.0,75.3,32087.0,13031.0,775.0,927.0,83.6,753.0,895.0,84.1,199.0,376.0,52.9,57.0,110.0,48.0,15.0,199.0,2073.0,291.0,77.0,6.0,20.0,76.0,29.0,8.0,15.0,0.0,128.0,8.0,67.0,122.0,20.33,83.0,12.0,13.0,4.0,19.0,3.17,14.0,0.0,1.0,1.0,2.0,117.0,73.0,65.0,42.0,10.0,75.0,17.0,58.0,54.0,113.0,3.0,3037.0,394.0,1150.0,1296.0,629.0,103.0,3036.0,1689.0,72.0,57.0,16.0,1767.0,72.0,60.0,0.0,75.0,63.0,8.0,1.0,0.0,0.0,311.0,96.0,75.0,56.1 +vs Frosinone,24.0,50.8,6.0,66.0,540.0,8.0,6.0,0.0,0.0,14.0,0.0,1.33,1.0,2.33,1.33,2.33,8.5,8.5,1.41,1.41,6.0,6.0,540.0,9.0,1.5,19.0,10.0,63.2,1.0,3.0,2.0,1.0,16.7,2.0,2.0,0.0,0.0,6.0,0.0,3.0,0.0,6.6,0.24,-2.4,-0.41,27.0,81.0,33.3,158.0,16.0,40.5,34.8,43.0,39.5,36.6,56.0,1.0,1.8,14.0,2.33,20.8,39.0,2.0,37.1,6.5,0.08,0.21,0.08,-0.5,-0.5,2278.0,2863.0,79.6,40437.0,14743.0,1008.0,1142.0,88.3,967.0,1118.0,86.5,232.0,428.0,54.2,83.0,185.0,56.0,13.0,283.0,2543.0,305.0,74.0,14.0,17.0,116.0,40.0,11.0,13.0,1.0,129.0,15.0,53.0,191.0,31.83,153.0,14.0,10.0,3.0,15.0,2.5,12.0,1.0,2.0,0.0,0.0,98.0,49.0,57.0,29.0,12.0,63.0,18.0,45.0,41.0,84.0,1.0,3496.0,330.0,981.0,1556.0,992.0,158.0,3496.0,1964.0,130.0,90.0,42.0,2259.0,89.0,41.0,0.0,73.0,54.0,15.0,0.0,2.0,0.0,325.0,79.0,80.0,49.7 +vs Genoa,22.0,65.7,6.0,66.0,540.0,9.0,8.0,0.0,0.0,15.0,0.0,1.5,1.33,2.83,1.5,2.83,6.0,6.0,1.01,1.01,6.0,6.0,540.0,8.0,1.33,15.0,7.0,46.7,3.0,1.0,2.0,2.0,33.3,0.0,0.0,0.0,0.0,6.0,0.0,4.0,0.0,4.4,0.3,-3.6,-0.6,6.0,21.0,28.6,129.0,30.0,11.6,26.8,30.0,20.0,28.9,53.0,1.0,1.9,5.0,0.83,17.8,20.0,4.0,25.6,3.33,0.12,0.45,0.08,3.0,3.0,3307.0,3918.0,84.4,56245.0,16636.0,1502.0,1639.0,91.6,1420.0,1593.0,89.1,284.0,450.0,63.1,55.0,271.0,55.0,13.0,348.0,3614.0,292.0,69.0,7.0,22.0,147.0,35.0,13.0,15.0,0.0,144.0,12.0,75.0,135.0,22.5,106.0,9.0,6.0,7.0,17.0,2.83,11.0,1.0,2.0,0.0,0.0,74.0,48.0,22.0,41.0,11.0,50.0,9.0,41.0,38.0,71.0,1.0,4485.0,264.0,934.0,2330.0,1257.0,142.0,4485.0,2931.0,170.0,133.0,25.0,3281.0,94.0,61.0,0.0,67.0,60.0,12.0,0.0,0.0,0.0,295.0,66.0,83.0,44.3 +vs Hellas Verona,22.0,54.8,6.0,66.0,540.0,6.0,4.0,1.0,1.0,16.0,0.0,1.0,0.67,1.67,0.83,1.5,6.7,5.9,1.12,0.99,6.0,6.0,540.0,4.0,0.67,15.0,11.0,73.3,3.0,1.0,2.0,3.0,50.0,0.0,0.0,0.0,0.0,6.0,0.0,1.0,0.0,3.2,0.21,-0.8,-0.14,26.0,94.0,27.7,198.0,30.0,39.9,35.7,33.0,45.5,40.7,65.0,6.0,9.2,3.0,0.5,12.0,27.0,5.0,35.5,4.5,0.07,0.19,0.08,-0.7,-0.9,2193.0,2873.0,76.3,38451.0,14796.0,964.0,1121.0,86.0,949.0,1145.0,82.9,211.0,439.0,48.1,56.0,122.0,42.0,9.0,190.0,2536.0,326.0,95.0,7.0,13.0,98.0,31.0,13.0,13.0,0.0,145.0,11.0,42.0,138.0,23.0,102.0,10.0,10.0,9.0,11.0,1.83,7.0,0.0,2.0,1.0,1.0,79.0,41.0,34.0,36.0,9.0,50.0,10.0,40.0,44.0,75.0,3.0,3444.0,347.0,1180.0,1572.0,725.0,135.0,3443.0,1950.0,110.0,73.0,37.0,2162.0,91.0,59.0,0.0,84.0,84.0,11.0,1.0,0.0,0.0,326.0,116.0,117.0,49.8 +vs Inter,22.0,46.8,6.0,66.0,540.0,3.0,3.0,0.0,0.0,8.0,0.0,0.5,0.5,1.0,0.5,1.0,4.1,4.1,0.69,0.69,6.0,6.0,540.0,15.0,2.5,32.0,17.0,59.4,1.0,0.0,5.0,0.0,0.0,2.0,2.0,0.0,0.0,6.0,0.0,1.0,0.0,11.2,0.29,-3.8,-0.64,28.0,79.0,35.4,173.0,29.0,31.8,33.2,45.0,53.3,44.7,101.0,2.0,2.0,5.0,0.83,12.1,15.0,2.0,25.4,2.5,0.05,0.2,0.07,-1.1,-1.1,2354.0,2822.0,83.4,43046.0,14627.0,1003.0,1120.0,89.6,1016.0,1131.0,89.8,270.0,420.0,64.3,46.0,171.0,53.0,15.0,216.0,2550.0,263.0,74.0,3.0,30.0,86.0,17.0,5.0,9.0,0.0,92.0,9.0,50.0,104.0,17.33,85.0,4.0,2.0,4.0,6.0,1.0,6.0,0.0,0.0,0.0,0.0,58.0,38.0,30.0,20.0,8.0,67.0,28.0,39.0,46.0,140.0,1.0,3425.0,449.0,1137.0,1563.0,751.0,103.0,3425.0,2206.0,111.0,81.0,19.0,2330.0,83.0,53.0,0.0,70.0,64.0,9.0,0.0,2.0,0.0,248.0,46.0,77.0,37.4 +vs Juventus,22.0,49.7,6.0,66.0,540.0,5.0,3.0,0.0,0.0,15.0,1.0,0.83,0.5,1.33,0.83,1.33,3.3,3.3,0.55,0.55,6.0,6.0,540.0,12.0,2.0,26.0,14.0,57.7,1.0,1.0,4.0,0.0,0.0,2.0,1.0,1.0,0.0,6.0,0.0,1.0,1.0,7.6,0.22,-3.4,-0.56,18.0,64.0,28.1,155.0,24.0,34.8,33.9,38.0,26.3,28.5,86.0,1.0,1.2,3.0,0.5,10.8,21.0,3.0,29.6,3.5,0.07,0.24,0.06,1.7,1.7,2445.0,2947.0,83.0,42991.0,13919.0,1061.0,1173.0,90.5,1000.0,1141.0,87.6,280.0,454.0,61.7,53.0,204.0,40.0,9.0,227.0,2649.0,292.0,81.0,4.0,16.0,109.0,28.0,13.0,6.0,0.0,110.0,6.0,45.0,123.0,20.5,99.0,6.0,6.0,4.0,4.0,0.67,3.0,0.0,1.0,0.0,0.0,74.0,40.0,41.0,24.0,9.0,65.0,20.0,45.0,40.0,97.0,3.0,3557.0,410.0,1097.0,1646.0,849.0,82.0,3557.0,2067.0,124.0,82.0,17.0,2427.0,93.0,44.0,1.0,80.0,71.0,6.0,0.0,2.0,1.0,267.0,41.0,67.0,38.0 +vs Lazio,20.0,46.0,6.0,66.0,540.0,8.0,5.0,0.0,0.0,16.0,0.0,1.33,0.83,2.17,1.33,2.17,7.0,7.0,1.16,1.16,6.0,6.0,540.0,7.0,1.17,17.0,10.0,64.7,3.0,1.0,2.0,1.0,16.7,1.0,1.0,0.0,0.0,6.0,0.0,0.0,0.0,5.5,0.27,-1.5,-0.25,37.0,79.0,46.8,181.0,32.0,29.8,30.9,40.0,62.5,49.2,80.0,3.0,3.8,7.0,1.17,12.5,27.0,2.0,30.0,4.5,0.09,0.3,0.08,1.0,1.0,2472.0,2997.0,82.5,44957.0,14546.0,1017.0,1128.0,90.2,1134.0,1287.0,88.1,247.0,431.0,57.3,68.0,162.0,40.0,12.0,190.0,2728.0,259.0,76.0,3.0,29.0,80.0,25.0,6.0,10.0,1.0,93.0,10.0,42.0,161.0,26.83,120.0,16.0,15.0,4.0,15.0,2.5,13.0,1.0,1.0,0.0,0.0,81.0,42.0,48.0,22.0,11.0,75.0,18.0,57.0,65.0,128.0,2.0,3639.0,425.0,1332.0,1568.0,764.0,128.0,3639.0,2131.0,108.0,71.0,28.0,2455.0,72.0,40.0,0.0,69.0,67.0,10.0,0.0,1.0,0.0,282.0,66.0,53.0,55.5 +vs 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Monza,23.0,45.8,6.0,66.0,540.0,7.0,5.0,2.0,2.0,9.0,2.0,1.17,0.83,2.0,0.83,1.67,7.4,5.8,1.23,0.97,6.0,6.0,540.0,4.0,0.67,21.0,17.0,81.0,2.0,3.0,1.0,3.0,50.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,0.0,5.3,0.25,1.3,0.21,16.0,39.0,41.0,136.0,27.0,17.6,26.4,59.0,25.4,31.2,85.0,2.0,2.4,6.0,1.0,15.1,24.0,2.0,32.0,4.0,0.07,0.21,0.08,-0.4,-0.8,2445.0,2926.0,83.6,41970.0,15013.0,1178.0,1314.0,89.6,931.0,1059.0,87.9,261.0,398.0,65.6,63.0,201.0,45.0,13.0,239.0,2658.0,257.0,72.0,11.0,26.0,101.0,27.0,8.0,13.0,0.0,88.0,11.0,42.0,137.0,22.83,99.0,15.0,8.0,6.0,13.0,2.17,9.0,0.0,1.0,2.0,1.0,87.0,55.0,45.0,33.0,9.0,74.0,24.0,50.0,51.0,105.0,0.0,3540.0,361.0,1016.0,1599.0,966.0,151.0,3538.0,2289.0,151.0,84.0,37.0,2427.0,71.0,58.0,1.0,65.0,68.0,11.0,2.0,0.0,0.0,281.0,74.0,56.0,56.9 +vs 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