diff --git a/6_neural_network_training_and_prediction.ipynb b/6_neural_network_training_and_prediction.ipynb
index f1f5463..1668946 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",
- " 0.018349 | \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",
+ " 0.017157 | \n",
+ " 0.009804 | \n",
+ " 0.007353 | \n",
+ " 0.012255 | \n",
+ " 0.007353 | \n",
+ " 0.012255 | \n",
+ " 0.384804 | \n",
+ " 0.031863 | \n",
+ " 0.012255 | \n",
+ " 0.012255 | \n",
" \n",
" \n",
" | 1 | \n",
@@ -158,15 +158,15 @@
" 0.0 | \n",
" 6.0 | \n",
" ... | \n",
- " 0.004608 | \n",
- " 0.000000 | \n",
- " 0.011521 | \n",
- " 0.002304 | \n",
- " 0.034562 | \n",
- " 0.020737 | \n",
- " 0.299539 | \n",
+ " 0.003817 | \n",
" 0.000000 | \n",
+ " 0.011450 | \n",
+ " 0.001908 | \n",
+ " 0.032443 | \n",
+ " 0.020992 | \n",
+ " 0.351145 | \n",
" 0.000000 | \n",
+ " 0.001908 | \n",
" 0.000000 | \n",
"
\n",
" \n",
@@ -182,16 +182,16 @@
" | 0.0 | \n",
" 6.5 | \n",
" ... | \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",
+ " 0.008850 | \n",
+ " 0.001770 | \n",
+ " 0.008850 | \n",
+ " 0.014159 | \n",
+ " 0.015929 | \n",
+ " 0.023009 | \n",
+ " 0.385841 | \n",
+ " 0.014159 | \n",
+ " 0.017699 | \n",
+ " 0.001770 | \n",
"
\n",
" \n",
" | 3 | \n",
@@ -230,16 +230,16 @@
" 0.0 | \n",
" 7.5 | \n",
" ... | \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",
+ " 0.012174 | \n",
+ " 0.001739 | \n",
+ " 0.013913 | \n",
+ " 0.005217 | \n",
+ " 0.008696 | \n",
+ " 0.019130 | \n",
+ " 0.372174 | \n",
+ " 0.019130 | \n",
+ " 0.015652 | \n",
+ " 0.005217 | \n",
"
\n",
" \n",
" | ... | \n",
@@ -266,7 +266,7 @@
" ... | \n",
"
\n",
" \n",
- " | 30595 | \n",
+ " 30866 | \n",
" 38 | \n",
" Miguel Veloso | \n",
" Verona | \n",
@@ -290,7 +290,7 @@
" 0.000860 | \n",
"
\n",
" \n",
- " | 30596 | \n",
+ " 30867 | \n",
" 38 | \n",
" Tameze | \n",
" Verona | \n",
@@ -314,7 +314,7 @@
" 0.001320 | \n",
"
\n",
" \n",
- " | 30597 | \n",
+ " 30868 | \n",
" 38 | \n",
" Sulemana I. | \n",
" Verona | \n",
@@ -338,7 +338,7 @@
" 0.000000 | \n",
"
\n",
" \n",
- " | 30598 | \n",
+ " 30869 | \n",
" 38 | \n",
" Djuric | \n",
" Verona | \n",
@@ -362,7 +362,7 @@
" 0.002196 | \n",
"
\n",
" \n",
- " | 30599 | \n",
+ " 30870 | \n",
" 38 | \n",
" Ngonge | \n",
" Verona | \n",
@@ -387,7 +387,7 @@
"
\n",
" \n",
"\n",
- "30600 rows × 122 columns
\n",
+ "30871 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",
- "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",
+ "30866 38 Miguel Veloso Verona Milan 0 5.5 0 \n",
+ "30867 38 Tameze Verona Milan 0 5.5 0 \n",
+ "30868 38 Sulemana I. Verona Milan 0 6.0 0 \n",
+ "30869 38 Djuric Verona Milan 0 5.5 0 \n",
+ "30870 38 Ngonge Verona Milan 0 5.5 0 \n",
"\n",
" assists cards_malus fantavote ... miscontrols dispossessed \\\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",
+ "0 0 0.0 6.5 ... 0.017157 0.009804 \n",
+ "1 0 0.0 6.0 ... 0.003817 0.000000 \n",
+ "2 0 0.0 6.5 ... 0.008850 0.001770 \n",
"3 0 0.0 10.0 ... 0.000000 0.020833 \n",
- "4 1 0.0 7.5 ... 0.010204 0.002041 \n",
+ "4 1 0.0 7.5 ... 0.012174 0.001739 \n",
"... ... ... ... ... ... ... \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",
+ "30866 0 0.0 5.5 ... 0.006019 0.006019 \n",
+ "30867 0 0.0 5.5 ... 0.012867 0.011217 \n",
+ "30868 0 0.5 5.5 ... 0.015361 0.013825 \n",
+ "30869 0 0.0 5.5 ... 0.019034 0.010981 \n",
+ "30870 0 0.0 5.5 ... 0.030872 0.016107 \n",
"\n",
" fouls fouled aerials_won aerials_lost carries \\\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",
+ "0 0.007353 0.012255 0.007353 0.012255 0.384804 \n",
+ "1 0.011450 0.001908 0.032443 0.020992 0.351145 \n",
+ "2 0.008850 0.014159 0.015929 0.023009 0.385841 \n",
"3 0.031250 0.000000 0.000000 0.010417 0.447917 \n",
- "4 0.014286 0.004082 0.010204 0.020408 0.357143 \n",
+ "4 0.013913 0.005217 0.008696 0.019130 0.372174 \n",
"... ... ... ... ... ... \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",
+ "30866 0.017197 0.006879 0.012038 0.012038 0.265692 \n",
+ "30867 0.010558 0.010228 0.008908 0.010228 0.235236 \n",
+ "30868 0.016897 0.004608 0.015361 0.018433 0.201229 \n",
+ "30869 0.017570 0.021230 0.144217 0.041728 0.191801 \n",
+ "30870 0.017450 0.014765 0.022819 0.046980 0.242953 \n",
"\n",
" progressive_carries carries_into_final_third \\\n",
- "0 0.033639 0.015291 \n",
- "1 0.000000 0.000000 \n",
- "2 0.014842 0.016698 \n",
+ "0 0.031863 0.012255 \n",
+ "1 0.000000 0.001908 \n",
+ "2 0.014159 0.017699 \n",
"3 0.062500 0.041667 \n",
- "4 0.016327 0.014286 \n",
+ "4 0.019130 0.015652 \n",
"... ... ... \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",
+ "30866 0.014617 0.011178 \n",
+ "30867 0.010558 0.011217 \n",
+ "30868 0.006144 0.010753 \n",
+ "30869 0.001464 0.003660 \n",
+ "30870 0.024161 0.014765 \n",
"\n",
" carries_into_penalty_area \n",
- "0 0.012232 \n",
+ "0 0.012255 \n",
"1 0.000000 \n",
- "2 0.001855 \n",
+ "2 0.001770 \n",
"3 0.010417 \n",
- "4 0.004082 \n",
+ "4 0.005217 \n",
"... ... \n",
- "30595 0.000860 \n",
- "30596 0.001320 \n",
- "30597 0.000000 \n",
- "30598 0.002196 \n",
- "30599 0.012081 \n",
+ "30866 0.000860 \n",
+ "30867 0.001320 \n",
+ "30868 0.000000 \n",
+ "30869 0.002196 \n",
+ "30870 0.012081 \n",
"\n",
- "[30600 rows x 122 columns]"
+ "[30871 rows x 122 columns]"
]
},
"execution_count": 4,
@@ -534,16 +534,16 @@
" 0.0 | \n",
" 6.5 | \n",
" ... | \n",
- " 2.100000 | \n",
- " 0.210000 | \n",
- " 0.100000 | \n",
+ " 2.400000 | \n",
+ " 0.180000 | \n",
+ " 0.400000 | \n",
" 14.000000 | \n",
+ " 54.000000 | \n",
+ " 141.000000 | \n",
+ " 30.000000 | \n",
+ " 30.000000 | \n",
" 48.000000 | \n",
- " 119.000000 | \n",
- " 25.000000 | \n",
- " 28.000000 | \n",
- " 43.000000 | \n",
- " 4.000000 | \n",
+ " 5.000000 | \n",
" \n",
" \n",
" | 1 | \n",
@@ -558,15 +558,15 @@
" 0.0 | \n",
" 4.0 | \n",
" ... | \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",
+ " 4.900000 | \n",
+ " 0.230000 | \n",
+ " 0.900000 | \n",
+ " 33.000000 | \n",
+ " 68.000000 | \n",
+ " 185.000000 | \n",
+ " 29.000000 | \n",
+ " 43.000000 | \n",
+ " 108.000000 | \n",
" 3.000000 | \n",
"
\n",
" \n",
@@ -582,16 +582,16 @@
" | 0.0 | \n",
" 6.5 | \n",
" ... | \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",
+ " 10.100000 | \n",
+ " 0.380000 | \n",
+ " -0.900000 | \n",
+ " 41.000000 | \n",
+ " 91.000000 | \n",
+ " 156.000000 | \n",
+ " 31.000000 | \n",
+ " 66.000000 | \n",
+ " 98.000000 | \n",
+ " 6.000000 | \n",
"
\n",
" \n",
" | 3 | \n",
@@ -606,15 +606,15 @@
" 0.0 | \n",
" 4.0 | \n",
" ... | \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",
+ " 6.866667 | \n",
+ " 0.216667 | \n",
+ " -1.466667 | \n",
+ " 9.333333 | \n",
+ " 42.000000 | \n",
+ " 100.333333 | \n",
+ " 23.000000 | \n",
+ " 21.333333 | \n",
+ " 42.666667 | \n",
" 2.000000 | \n",
"
\n",
" \n",
@@ -630,15 +630,15 @@
" | 0.0 | \n",
" 5.0 | \n",
" ... | \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",
+ " 4.300000 | \n",
+ " 0.210000 | \n",
+ " 0.300000 | \n",
+ " 32.000000 | \n",
+ " 66.000000 | \n",
+ " 210.000000 | \n",
+ " 20.000000 | \n",
+ " 26.000000 | \n",
+ " 56.000000 | \n",
" 3.000000 | \n",
"
\n",
" \n",
@@ -666,7 +666,7 @@
" | ... | \n",
"
\n",
" \n",
- " | 2404 | \n",
+ " 2424 | \n",
" 38 | \n",
" Russo A. | \n",
" Sassuolo | \n",
@@ -690,7 +690,7 @@
" 23.333333 | \n",
"
\n",
" \n",
- " | 2405 | \n",
+ " 2425 | \n",
" 38 | \n",
" Zoet | \n",
" Spezia | \n",
@@ -714,7 +714,7 @@
" 5.500000 | \n",
"
\n",
" \n",
- " | 2406 | \n",
+ " 2426 | \n",
" 38 | \n",
" Milinkovic-Savic V. | \n",
" Torino | \n",
@@ -738,7 +738,7 @@
" 36.000000 | \n",
"
\n",
" \n",
- " | 2407 | \n",
+ " 2427 | \n",
" 38 | \n",
" Silvestri | \n",
" Udinese | \n",
@@ -762,7 +762,7 @@
" 13.000000 | \n",
"
\n",
" \n",
- " | 2408 | \n",
+ " 2428 | \n",
" 38 | \n",
" Montipo' | \n",
" Verona | \n",
@@ -787,7 +787,7 @@
"
\n",
" \n",
"\n",
- "2409 rows × 102 columns
\n",
+ "2429 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",
- "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",
+ "2424 38 Russo A. Sassuolo Fiorentina 1 5.0 \n",
+ "2425 38 Zoet Spezia Roma 0 5.5 \n",
+ "2426 38 Milinkovic-Savic V. Torino Inter 1 5.0 \n",
+ "2427 38 Silvestri Udinese Juventus 1 6.5 \n",
+ "2428 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 ... 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",
+ "0 0 0 0.0 6.5 ... 2.400000 \n",
+ "1 -2 0 0.0 4.0 ... 4.900000 \n",
+ "2 0 0 0.0 6.5 ... 10.100000 \n",
+ "3 -1 0 0.0 4.0 ... 6.866667 \n",
+ "4 -1 0 0.0 5.0 ... 4.300000 \n",
"... ... ... ... ... ... ... \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",
+ "2424 -3 0 0.0 2.0 ... 32.550000 \n",
+ "2425 -2 0 0.5 3.0 ... 10.016667 \n",
+ "2426 -1 0 0.0 4.0 ... 35.800000 \n",
+ "2427 -1 0 0.0 5.5 ... 48.700000 \n",
+ "2428 -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 0.250000 0.200000 \n",
- "2 0.360000 -0.300000 \n",
- "3 0.203333 -1.400000 \n",
- "4 0.240000 0.100000 \n",
+ "0 0.180000 0.400000 \n",
+ "1 0.230000 0.900000 \n",
+ "2 0.380000 -0.900000 \n",
+ "3 0.216667 -1.466667 \n",
+ "4 0.210000 0.300000 \n",
"... ... ... \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",
+ "2424 0.325000 -12.116667 \n",
+ "2425 0.158333 -1.816667 \n",
+ "2426 0.230000 -5.200000 \n",
+ "2427 0.310000 2.700000 \n",
+ "2428 0.270000 -6.400000 \n",
"\n",
" gk_passes_completed_launched gk_passes_launched gk_passes \\\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",
+ "0 14.000000 54.000000 141.000000 \n",
+ "1 33.000000 68.000000 185.000000 \n",
+ "2 41.000000 91.000000 156.000000 \n",
+ "3 9.333333 42.000000 100.333333 \n",
+ "4 32.000000 66.000000 210.000000 \n",
"... ... ... ... \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",
+ "2424 146.666667 365.333333 957.000000 \n",
+ "2425 46.000000 145.333333 254.166667 \n",
+ "2426 285.000000 939.000000 1506.000000 \n",
+ "2427 144.000000 380.000000 872.000000 \n",
+ "2428 360.000000 775.000000 905.000000 \n",
"\n",
" gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \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",
+ "0 30.000000 30.000000 48.000000 5.000000 \n",
+ "1 29.000000 43.000000 108.000000 3.000000 \n",
+ "2 31.000000 66.000000 98.000000 6.000000 \n",
+ "3 23.000000 21.333333 42.666667 2.000000 \n",
+ "4 20.000000 26.000000 56.000000 3.000000 \n",
"... ... ... ... ... \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",
+ "2424 156.166667 238.833333 391.500000 23.333333 \n",
+ "2425 37.333333 51.833333 130.333333 5.500000 \n",
+ "2426 185.000000 286.000000 469.000000 36.000000 \n",
+ "2427 142.000000 302.000000 547.000000 13.000000 \n",
+ "2428 124.000000 284.000000 496.000000 26.000000 \n",
"\n",
- "[2409 rows x 102 columns]"
+ "[2429 rows x 102 columns]"
]
},
"execution_count": 5,
@@ -918,7 +918,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "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",
+ "C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_27732\\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"
]
},
@@ -971,505 +971,505 @@
" Atalanta | \n",
" Atalanta | \n",
" 24.0 | \n",
- " 50.50 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 11.0 | \n",
+ " 50.7 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
" 11.00 | \n",
+ " 11.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 57.00 | \n",
- " 74.0 | \n",
- " 4.00 | \n",
+ " 64.0 | \n",
+ " 86.0 | \n",
+ " 5.00 | \n",
" 0.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 347.00 | \n",
- " 97.00 | \n",
- " 109.00 | \n",
- " 47.100 | \n",
+ " 398.00 | \n",
+ " 112.00 | \n",
+ " 114.00 | \n",
+ " 49.600 | \n",
" \n",
" \n",
" | Bologna | \n",
" Bologna | \n",
" 23.0 | \n",
- " 54.70 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 3.0 | \n",
- " 2.00 | \n",
+ " 55.1 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 6.00 | \n",
+ " 4.0 | \n",
" 0.00 | \n",
" 1.00 | \n",
" ... | \n",
- " 71.00 | \n",
- " 70.0 | \n",
- " 16.00 | \n",
+ " 87.0 | \n",
+ " 81.0 | \n",
+ " 17.00 | \n",
" 0.0 | \n",
" 1.00 | \n",
" 0.00 | \n",
- " 292.00 | \n",
- " 47.00 | \n",
- " 73.00 | \n",
- " 39.200 | \n",
+ " 349.00 | \n",
+ " 50.00 | \n",
+ " 78.00 | \n",
+ " 39.100 | \n",
"
\n",
" \n",
" | Cagliari | \n",
" Cagliari | \n",
" 22.0 | \n",
- " 38.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 2.0 | \n",
+ " 38.4 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
" 2.00 | \n",
+ " 2.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 50.00 | \n",
- " 65.0 | \n",
- " 11.00 | \n",
+ " 60.0 | \n",
+ " 75.0 | \n",
+ " 12.00 | \n",
" 0.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 332.00 | \n",
- " 92.00 | \n",
- " 71.00 | \n",
- " 56.400 | \n",
+ " 386.00 | \n",
+ " 104.00 | \n",
+ " 84.00 | \n",
+ " 55.300 | \n",
"
\n",
" \n",
" | Empoli | \n",
" Empoli | \n",
" 28.0 | \n",
- " 45.30 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 1.0 | \n",
+ " 44.9 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
" 1.00 | \n",
+ " 1.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 84.00 | \n",
- " 74.0 | \n",
- " 10.00 | \n",
+ " 95.0 | \n",
+ " 89.0 | \n",
+ " 12.00 | \n",
" 1.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 313.00 | \n",
- " 82.00 | \n",
- " 60.00 | \n",
- " 57.700 | \n",
+ " 369.00 | \n",
+ " 86.00 | \n",
+ " 64.00 | \n",
+ " 57.300 | \n",
"
\n",
" \n",
" | Fiorentina | \n",
" Fiorentina | \n",
" 24.0 | \n",
- " 57.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 12.0 | \n",
- " 9.00 | \n",
+ " 57.6 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 14.00 | \n",
+ " 11.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 75.00 | \n",
- " 63.0 | \n",
- " 8.00 | \n",
+ " 85.0 | \n",
+ " 72.0 | \n",
+ " 10.00 | \n",
" 1.0 | \n",
" 0.00 | \n",
- " 0.00 | \n",
- " 311.00 | \n",
- " 96.00 | \n",
- " 75.00 | \n",
- " 56.100 | \n",
+ " 1.00 | \n",
+ " 359.00 | \n",
+ " 109.00 | \n",
+ " 87.00 | \n",
+ " 55.600 | \n",
"
\n",
" \n",
" | Frosinone | \n",
" Frosinone | \n",
- " 24.0 | \n",
- " 49.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 9.0 | \n",
- " 5.00 | \n",
+ " 25.0 | \n",
+ " 49.3 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 9.00 | \n",
+ " 5.0 | \n",
" 2.00 | \n",
" 2.00 | \n",
" ... | \n",
- " 73.00 | \n",
- " 54.0 | \n",
- " 15.00 | \n",
+ " 85.0 | \n",
+ " 64.0 | \n",
+ " 17.00 | \n",
" 0.0 | \n",
" 2.00 | \n",
" 0.00 | \n",
- " 325.00 | \n",
- " 79.00 | \n",
- " 80.00 | \n",
- " 49.700 | \n",
+ " 384.00 | \n",
+ " 87.00 | \n",
+ " 90.00 | \n",
+ " 49.200 | \n",
"
\n",
" \n",
" | Genoa | \n",
" Genoa | \n",
- " 22.0 | \n",
- " 34.30 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 8.0 | \n",
- " 7.00 | \n",
+ " 23.0 | \n",
+ " 35.3 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 10.00 | \n",
+ " 9.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 67.00 | \n",
- " 60.0 | \n",
- " 12.00 | \n",
+ " 79.0 | \n",
+ " 72.0 | \n",
+ " 13.00 | \n",
" 0.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 295.00 | \n",
- " 66.00 | \n",
- " 83.00 | \n",
- " 44.300 | \n",
+ " 349.00 | \n",
+ " 79.00 | \n",
+ " 97.00 | \n",
+ " 44.900 | \n",
"
\n",
" \n",
" | Verona | \n",
" Hellas Verona | \n",
- " 22.0 | \n",
- " 45.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 4.0 | \n",
- " 2.00 | \n",
+ " 23.0 | \n",
+ " 45.1 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 4.00 | \n",
+ " 2.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 84.00 | \n",
- " 84.0 | \n",
- " 11.00 | \n",
+ " 90.0 | \n",
+ " 94.0 | \n",
+ " 12.00 | \n",
" 1.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 326.00 | \n",
- " 116.00 | \n",
- " 117.00 | \n",
- " 49.800 | \n",
+ " 387.00 | \n",
+ " 135.00 | \n",
+ " 128.00 | \n",
+ " 51.300 | \n",
"
\n",
" \n",
" | Inter | \n",
" Inter | \n",
- " 22.0 | \n",
- " 53.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
+ " 23.0 | \n",
+ " 54.7 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 19.00 | \n",
" 15.0 | \n",
- " 12.00 | \n",
- " 2.00 | \n",
- " 2.00 | \n",
+ " 3.00 | \n",
+ " 3.00 | \n",
" ... | \n",
- " 70.00 | \n",
- " 64.0 | \n",
- " 9.00 | \n",
+ " 82.0 | \n",
+ " 74.0 | \n",
+ " 11.00 | \n",
" 0.0 | \n",
- " 2.00 | \n",
+ " 3.00 | \n",
" 0.00 | \n",
- " 248.00 | \n",
- " 46.00 | \n",
- " 77.00 | \n",
- " 37.400 | \n",
+ " 298.00 | \n",
+ " 57.00 | \n",
+ " 108.00 | \n",
+ " 34.500 | \n",
"
\n",
" \n",
" | Juventus | \n",
" Juventus | \n",
" 22.0 | \n",
- " 50.30 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 11.0 | \n",
- " 9.00 | \n",
+ " 50.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 11.00 | \n",
+ " 9.0 | \n",
" 1.00 | \n",
" 2.00 | \n",
" ... | \n",
- " 80.00 | \n",
- " 71.0 | \n",
+ " 93.0 | \n",
+ " 78.0 | \n",
" 6.00 | \n",
" 0.0 | \n",
" 2.00 | \n",
" 1.00 | \n",
- " 267.00 | \n",
- " 41.00 | \n",
- " 67.00 | \n",
- " 38.000 | \n",
+ " 318.00 | \n",
+ " 46.00 | \n",
+ " 82.00 | \n",
+ " 35.900 | \n",
"
\n",
" \n",
" | Lazio | \n",
" Lazio | \n",
" 20.0 | \n",
- " 54.00 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
+ " 53.3 | \n",
" 7.0 | \n",
- " 6.00 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 7.00 | \n",
+ " 6.0 | \n",
" 1.00 | \n",
" 1.00 | \n",
" ... | \n",
- " 69.00 | \n",
- " 67.0 | \n",
- " 10.00 | \n",
+ " 84.0 | \n",
+ " 72.0 | \n",
+ " 12.00 | \n",
" 0.0 | \n",
" 1.00 | \n",
" 0.00 | \n",
- " 282.00 | \n",
- " 66.00 | \n",
- " 53.00 | \n",
- " 55.500 | \n",
+ " 325.00 | \n",
+ " 71.00 | \n",
+ " 60.00 | \n",
+ " 54.200 | \n",
"
\n",
" \n",
" | Lecce | \n",
" Lecce | \n",
- " 22.0 | \n",
- " 46.70 | \n",
+ " 23.0 | \n",
+ " 46.3 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 8.00 | \n",
" 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 8.0 | \n",
- " 6.00 | \n",
" 2.00 | \n",
" 2.00 | \n",
" ... | \n",
- " 88.00 | \n",
- " 78.0 | \n",
- " 5.00 | \n",
- " 0.0 | \n",
+ " 99.0 | \n",
+ " 85.0 | \n",
+ " 6.00 | \n",
+ " 1.0 | \n",
" 2.00 | \n",
" 0.00 | \n",
- " 295.00 | \n",
- " 67.00 | \n",
- " 73.00 | \n",
- " 47.900 | \n",
+ " 354.00 | \n",
+ " 81.00 | \n",
+ " 81.00 | \n",
+ " 50.000 | \n",
"
\n",
" \n",
" | Milan | \n",
" Milan | \n",
" 23.0 | \n",
- " 56.80 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 13.0 | \n",
- " 8.00 | \n",
+ " 56.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 15.00 | \n",
+ " 10.0 | \n",
" 3.00 | \n",
" 3.00 | \n",
" ... | \n",
- " 80.00 | \n",
- " 60.0 | \n",
- " 8.00 | \n",
+ " 85.0 | \n",
+ " 74.0 | \n",
+ " 10.00 | \n",
" 1.0 | \n",
" 3.00 | \n",
" 0.00 | \n",
- " 281.00 | \n",
- " 65.00 | \n",
- " 61.00 | \n",
- " 51.600 | \n",
+ " 329.00 | \n",
+ " 72.00 | \n",
+ " 66.00 | \n",
+ " 52.200 | \n",
"
\n",
" \n",
" | Monza | \n",
" Monza | \n",
- " 23.0 | \n",
- " 54.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
+ " 24.0 | \n",
+ " 54.4 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 5.00 | \n",
" 4.0 | \n",
- " 3.00 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 65.00 | \n",
- " 68.0 | \n",
- " 11.00 | \n",
+ " 73.0 | \n",
+ " 78.0 | \n",
+ " 12.00 | \n",
" 2.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 281.00 | \n",
- " 74.00 | \n",
- " 56.00 | \n",
- " 56.900 | \n",
+ " 319.00 | \n",
+ " 83.00 | \n",
+ " 65.00 | \n",
+ " 56.100 | \n",
"
\n",
" \n",
" | Napoli | \n",
" Napoli | \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",
- " 73.00 | \n",
+ " 21.0 | \n",
" 60.0 | \n",
- " 9.00 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 16.00 | \n",
+ " 10.0 | \n",
+ " 3.00 | \n",
+ " 5.00 | \n",
+ " ... | \n",
+ " 84.0 | \n",
+ " 70.0 | \n",
+ " 12.00 | \n",
" 1.0 | \n",
- " 4.00 | \n",
+ " 5.00 | \n",
" 0.00 | \n",
- " 254.00 | \n",
- " 52.00 | \n",
- " 56.00 | \n",
- " 48.100 | \n",
+ " 304.00 | \n",
+ " 60.00 | \n",
+ " 70.00 | \n",
+ " 46.200 | \n",
"
\n",
" \n",
" | Roma | \n",
" Roma | \n",
" 23.0 | \n",
- " 59.70 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 12.0 | \n",
- " 9.00 | \n",
+ " 58.3 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 14.00 | \n",
+ " 11.0 | \n",
" 1.00 | \n",
" 1.00 | \n",
" ... | \n",
- " 58.00 | \n",
- " 67.0 | \n",
- " 4.00 | \n",
+ " 69.0 | \n",
+ " 79.0 | \n",
+ " 6.00 | \n",
" 1.0 | \n",
" 1.00 | \n",
" 1.00 | \n",
- " 267.00 | \n",
- " 83.00 | \n",
- " 104.00 | \n",
- " 44.400 | \n",
+ " 328.00 | \n",
+ " 93.00 | \n",
+ " 112.00 | \n",
+ " 45.400 | \n",
"
\n",
" \n",
" | Salernitana | \n",
" Salernitana | \n",
- " 22.0 | \n",
- " 52.30 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 4.0 | \n",
- " 3.00 | \n",
+ " 23.0 | \n",
+ " 50.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 4.00 | \n",
+ " 3.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 94.00 | \n",
- " 70.0 | \n",
- " 12.00 | \n",
- " 0.0 | \n",
+ " 104.0 | \n",
+ " 82.0 | \n",
+ " 13.00 | \n",
+ " 1.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 311.00 | \n",
- " 120.00 | \n",
- " 82.00 | \n",
- " 59.400 | \n",
+ " 357.00 | \n",
+ " 151.00 | \n",
+ " 93.00 | \n",
+ " 61.900 | \n",
"
\n",
" \n",
" | Sassuolo | \n",
" Sassuolo | \n",
" 25.0 | \n",
- " 42.30 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 10.0 | \n",
- " 7.00 | \n",
+ " 42.6 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 10.00 | \n",
+ " 7.0 | \n",
" 1.00 | \n",
" 1.00 | \n",
" ... | \n",
- " 63.00 | \n",
- " 55.0 | \n",
- " 20.00 | \n",
+ " 73.0 | \n",
+ " 63.0 | \n",
+ " 24.00 | \n",
" 2.0 | \n",
" 1.00 | \n",
" 1.00 | \n",
- " 299.00 | \n",
- " 85.00 | \n",
- " 55.00 | \n",
- " 60.700 | \n",
+ " 336.00 | \n",
+ " 95.00 | \n",
+ " 63.00 | \n",
+ " 60.100 | \n",
"
\n",
" \n",
" | Torino | \n",
" Torino | \n",
" 23.0 | \n",
- " 49.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
- " 6.0 | \n",
- " 4.00 | \n",
+ " 50.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 6.00 | \n",
+ " 4.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 61.00 | \n",
- " 64.0 | \n",
- " 7.00 | \n",
+ " 72.0 | \n",
+ " 70.0 | \n",
+ " 8.00 | \n",
" 1.0 | \n",
" 0.00 | \n",
" 0.00 | \n",
- " 302.00 | \n",
- " 93.00 | \n",
- " 82.00 | \n",
- " 53.100 | \n",
+ " 371.00 | \n",
+ " 104.00 | \n",
+ " 101.00 | \n",
+ " 50.700 | \n",
"
\n",
" \n",
" | Udinese | \n",
" Udinese | \n",
" 24.0 | \n",
- " 46.20 | \n",
- " 6.0 | \n",
- " 66.0 | \n",
- " 540.0 | \n",
+ " 48.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 3.00 | \n",
" 2.0 | \n",
- " 2.00 | \n",
" 0.00 | \n",
" 0.00 | \n",
" ... | \n",
- " 65.00 | \n",
- " 74.0 | \n",
- " 11.00 | \n",
+ " 77.0 | \n",
+ " 86.0 | \n",
+ " 13.00 | \n",
" 1.0 | \n",
" 0.00 | \n",
- " 0.00 | \n",
- " 297.00 | \n",
- " 68.00 | \n",
- " 101.00 | \n",
- " 40.200 | \n",
+ " 1.00 | \n",
+ " 337.00 | \n",
+ " 82.00 | \n",
+ " 114.00 | \n",
+ " 41.800 | \n",
"
\n",
" \n",
" | Avg | \n",
" Avg | \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",
+ " 23.3 | \n",
+ " 50.0 | \n",
+ " 7.0 | \n",
+ " 77.0 | \n",
+ " 630.0 | \n",
+ " 8.75 | \n",
+ " 6.6 | \n",
+ " 0.85 | \n",
+ " 1.05 | \n",
" ... | \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",
+ " 82.0 | \n",
+ " 77.2 | \n",
+ " 11.55 | \n",
+ " 0.7 | \n",
+ " 1.05 | \n",
+ " 0.25 | \n",
+ " 347.85 | \n",
+ " 87.85 | \n",
+ " 87.85 | \n",
+ " 49.565 | \n",
"
\n",
" \n",
"\n",
@@ -1478,165 +1478,165 @@
],
"text/plain": [
" team team_players_used team_possession team_games \\\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",
+ "Atalanta Atalanta 24.0 50.7 7.0 \n",
+ "Bologna Bologna 23.0 55.1 7.0 \n",
+ "Cagliari Cagliari 22.0 38.4 7.0 \n",
+ "Empoli Empoli 28.0 44.9 7.0 \n",
+ "Fiorentina Fiorentina 24.0 57.6 7.0 \n",
+ "Frosinone Frosinone 25.0 49.3 7.0 \n",
+ "Genoa Genoa 23.0 35.3 7.0 \n",
+ "Verona Hellas Verona 23.0 45.1 7.0 \n",
+ "Inter Inter 23.0 54.7 7.0 \n",
+ "Juventus Juventus 22.0 50.0 7.0 \n",
+ "Lazio Lazio 20.0 53.3 7.0 \n",
+ "Lecce Lecce 23.0 46.3 7.0 \n",
+ "Milan Milan 23.0 56.0 7.0 \n",
+ "Monza Monza 24.0 54.4 7.0 \n",
+ "Napoli Napoli 21.0 60.0 7.0 \n",
+ "Roma Roma 23.0 58.3 7.0 \n",
+ "Salernitana Salernitana 23.0 50.0 7.0 \n",
+ "Sassuolo Sassuolo 25.0 42.6 7.0 \n",
+ "Torino Torino 23.0 50.0 7.0 \n",
+ "Udinese Udinese 24.0 48.0 7.0 \n",
+ "Avg Avg 23.3 50.0 7.0 \n",
"\n",
" team_games_starts team_minutes team_goals team_assists \\\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",
+ "Atalanta 77.0 630.0 11.00 11.0 \n",
+ "Bologna 77.0 630.0 6.00 4.0 \n",
+ "Cagliari 77.0 630.0 2.00 2.0 \n",
+ "Empoli 77.0 630.0 1.00 1.0 \n",
+ "Fiorentina 77.0 630.0 14.00 11.0 \n",
+ "Frosinone 77.0 630.0 9.00 5.0 \n",
+ "Genoa 77.0 630.0 10.00 9.0 \n",
+ "Verona 77.0 630.0 4.00 2.0 \n",
+ "Inter 77.0 630.0 19.00 15.0 \n",
+ "Juventus 77.0 630.0 11.00 9.0 \n",
+ "Lazio 77.0 630.0 7.00 6.0 \n",
+ "Lecce 77.0 630.0 8.00 6.0 \n",
+ "Milan 77.0 630.0 15.00 10.0 \n",
+ "Monza 77.0 630.0 5.00 4.0 \n",
+ "Napoli 77.0 630.0 16.00 10.0 \n",
+ "Roma 77.0 630.0 14.00 11.0 \n",
+ "Salernitana 77.0 630.0 4.00 3.0 \n",
+ "Sassuolo 77.0 630.0 10.00 7.0 \n",
+ "Torino 77.0 630.0 6.00 4.0 \n",
+ "Udinese 77.0 630.0 3.00 2.0 \n",
+ "Avg 77.0 630.0 8.75 6.6 \n",
"\n",
" team_pens_made team_pens_att ... vs_team_fouls \\\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",
+ "Atalanta 0.00 0.00 ... 64.0 \n",
+ "Bologna 0.00 1.00 ... 87.0 \n",
+ "Cagliari 0.00 0.00 ... 60.0 \n",
+ "Empoli 0.00 0.00 ... 95.0 \n",
+ "Fiorentina 0.00 0.00 ... 85.0 \n",
+ "Frosinone 2.00 2.00 ... 85.0 \n",
+ "Genoa 0.00 0.00 ... 79.0 \n",
+ "Verona 0.00 0.00 ... 90.0 \n",
+ "Inter 3.00 3.00 ... 82.0 \n",
+ "Juventus 1.00 2.00 ... 93.0 \n",
+ "Lazio 1.00 1.00 ... 84.0 \n",
+ "Lecce 2.00 2.00 ... 99.0 \n",
+ "Milan 3.00 3.00 ... 85.0 \n",
+ "Monza 0.00 0.00 ... 73.0 \n",
+ "Napoli 3.00 5.00 ... 84.0 \n",
+ "Roma 1.00 1.00 ... 69.0 \n",
+ "Salernitana 0.00 0.00 ... 104.0 \n",
+ "Sassuolo 1.00 1.00 ... 73.0 \n",
+ "Torino 0.00 0.00 ... 72.0 \n",
+ "Udinese 0.00 0.00 ... 77.0 \n",
+ "Avg 0.85 1.05 ... 82.0 \n",
"\n",
" vs_team_fouled vs_team_offsides vs_team_pens_won \\\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",
+ "Atalanta 86.0 5.00 0.0 \n",
+ "Bologna 81.0 17.00 0.0 \n",
+ "Cagliari 75.0 12.00 0.0 \n",
+ "Empoli 89.0 12.00 1.0 \n",
+ "Fiorentina 72.0 10.00 1.0 \n",
+ "Frosinone 64.0 17.00 0.0 \n",
+ "Genoa 72.0 13.00 0.0 \n",
+ "Verona 94.0 12.00 1.0 \n",
+ "Inter 74.0 11.00 0.0 \n",
+ "Juventus 78.0 6.00 0.0 \n",
+ "Lazio 72.0 12.00 0.0 \n",
+ "Lecce 85.0 6.00 1.0 \n",
+ "Milan 74.0 10.00 1.0 \n",
+ "Monza 78.0 12.00 2.0 \n",
+ "Napoli 70.0 12.00 1.0 \n",
+ "Roma 79.0 6.00 1.0 \n",
+ "Salernitana 82.0 13.00 1.0 \n",
+ "Sassuolo 63.0 24.00 2.0 \n",
+ "Torino 70.0 8.00 1.0 \n",
+ "Udinese 86.0 13.00 1.0 \n",
+ "Avg 77.2 11.55 0.7 \n",
"\n",
" vs_team_pens_conceded vs_team_own_goals \\\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",
+ "Fiorentina 0.00 1.00 \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",
+ "Inter 3.00 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",
+ "Napoli 5.00 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",
+ "Udinese 0.00 1.00 \n",
+ "Avg 1.05 0.25 \n",
"\n",
" vs_team_ball_recoveries vs_team_aerials_won \\\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",
+ "Atalanta 398.00 112.00 \n",
+ "Bologna 349.00 50.00 \n",
+ "Cagliari 386.00 104.00 \n",
+ "Empoli 369.00 86.00 \n",
+ "Fiorentina 359.00 109.00 \n",
+ "Frosinone 384.00 87.00 \n",
+ "Genoa 349.00 79.00 \n",
+ "Verona 387.00 135.00 \n",
+ "Inter 298.00 57.00 \n",
+ "Juventus 318.00 46.00 \n",
+ "Lazio 325.00 71.00 \n",
+ "Lecce 354.00 81.00 \n",
+ "Milan 329.00 72.00 \n",
+ "Monza 319.00 83.00 \n",
+ "Napoli 304.00 60.00 \n",
+ "Roma 328.00 93.00 \n",
+ "Salernitana 357.00 151.00 \n",
+ "Sassuolo 336.00 95.00 \n",
+ "Torino 371.00 104.00 \n",
+ "Udinese 337.00 82.00 \n",
+ "Avg 347.85 87.85 \n",
"\n",
" vs_team_aerials_lost vs_team_aerials_won_pct \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",
+ "Atalanta 114.00 49.600 \n",
+ "Bologna 78.00 39.100 \n",
+ "Cagliari 84.00 55.300 \n",
+ "Empoli 64.00 57.300 \n",
+ "Fiorentina 87.00 55.600 \n",
+ "Frosinone 90.00 49.200 \n",
+ "Genoa 97.00 44.900 \n",
+ "Verona 128.00 51.300 \n",
+ "Inter 108.00 34.500 \n",
+ "Juventus 82.00 35.900 \n",
+ "Lazio 60.00 54.200 \n",
+ "Lecce 81.00 50.000 \n",
+ "Milan 66.00 52.200 \n",
+ "Monza 65.00 56.100 \n",
+ "Napoli 70.00 46.200 \n",
+ "Roma 112.00 45.400 \n",
+ "Salernitana 93.00 61.900 \n",
+ "Sassuolo 63.00 60.100 \n",
+ "Torino 101.00 50.700 \n",
+ "Udinese 114.00 41.800 \n",
+ "Avg 87.85 49.565 \n",
"\n",
"[21 rows x 303 columns]"
]
@@ -3649,26 +3649,26 @@
"text": [
" \n",
"Averaging players stats with past seasons:\n",
- "Szczesny 0.8351648351648353\n",
+ "Skorupski 1\n",
+ "Di Gregorio 0.9480249480249479\n",
"Meret 1\n",
- "Provedel 0.9230769230769229\n",
+ "Provedel 1\n",
+ "Terracciano 1\n",
+ "Szczesny 1\n",
+ "Falcone 1\n",
+ "Milinkovic-Savic V. 1\n",
"Maignan 1\n",
+ "Montipo' 1\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",
+ "Consigli 0.8351648351648351\n",
+ "Musso 1\n",
+ "Carnesecchi 0.6820512820512821\n",
+ "Silvestri 1\n",
"Ochoa 1\n",
- "Consigli 0.6681318681318682\n",
- "Musso 0.9743589743589745\n",
- "Cragno 1\n",
- "Perin 1\n",
- "Berisha 1\n",
"Sportiello 1\n",
+ "Berisha 1\n",
+ "Perin 1\n",
+ "Cragno 1\n",
"Mirante 1\n",
"Sepe 1\n",
"Lamanna 1\n",
@@ -3691,393 +3691,394 @@
"Svilar 1\n",
"Sorrentino A. 1\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",
+ "Di Lorenzo 0.5530145530145528\n",
+ "Hernandez T. 0.548076923076923\n",
+ "Dumfries 0.5158371040723981\n",
+ "Carlos Augusto 0.6138461538461538\n",
+ "Schuurs 0.6820512820512818\n",
+ "Spinazzola 0.7869822485207099\n",
+ "Danilo 0.5530145530145528\n",
+ "Tomori 0.5314685314685313\n",
"Bastoni 0.6047745358090184\n",
- "Smalling 0.2740384615384615\n",
- "Dumfries 0.42986425339366513\n",
- "Romagnoli 0.5158371040723981\n",
- "Pavard 0.10230769230769231 (rookie)\n",
- "Rrahmani 0.3023872679045092\n",
- "Spinazzola 0.6745562130177514\n",
"Buongiorno 0.5158371040723981\n",
- "Bremer 0.5846153846153845\n",
- "Tomori 0.4428904428904428\n",
+ "Pavard 0.20461538461538462 (rookie)\n",
"Biraghi 0.4428904428904428\n",
- "Mancini 0.501098901098901\n",
- "Darmian 0.5657568238213398\n",
- "Bakker 0.21923076923076926 (rookie)\n",
- "Mazzocchi 0.6495726495726495\n",
- "Doig 0.5314685314685315\n",
- "Calabria 0.4676923076923077\n",
- "Acerbi 0.2828784119106699\n",
+ "Zappacosta 0.835164835164835\n",
+ "Mancini 0.5846153846153845\n",
+ "Darmian 0.6600496277915632\n",
+ "Martinez Quarta 0.5413105413105412\n",
+ "Posch 0.4871794871794871\n",
+ "Romagnoli S. 1\n",
+ "De Vrij 0.7578347578347576\n",
+ "Romagnoli 0.6018099547511311\n",
+ "Bremer 0.6820512820512818\n",
+ "Smalling 0.2740384615384615\n",
+ "Rrahmani 0.3023872679045092\n",
+ "Rodriguez R. 0.5846153846153845\n",
+ "Dragusin 0.5653846153846154 (rookie)\n",
+ "Vasquez 0.8593846153846153\n",
+ "Scalvini 0.6394230769230768\n",
+ "Holm 0.6138461538461539\n",
+ "Kristensen 0.0 (rookie)\n",
+ "Calabria 0.5846153846153845\n",
+ "Acerbi 0.3771712158808933\n",
"Cuadrado 0.29702233250620347\n",
- "Ebuehi 0.44970414201183434\n",
- "Casale 0.40318302387267907\n",
- "Holm 0.4603846153846154\n",
- "Baschirotto 0.395010395010395\n",
- "Bijol 0.548076923076923\n",
+ "Marchizza 1\n",
+ "Bani 0.651048951048951 (rookie)\n",
+ "Kolasinac 0.651048951048951 (rookie)\n",
+ "Toljan 0.6600496277915632\n",
+ "Bakker 0.32884615384615384 (rookie)\n",
+ "Ruggeri 1\n",
+ "Ebuehi 0.5621301775147929\n",
+ "Mazzocchi 0.7578347578347576\n",
+ "Doig 0.5314685314685315\n",
+ "Gendrey 0.5530145530145528\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 0.4871794871794871\n",
- "De Vrij 0.6495726495726495\n",
- "Faraoni 0.6354515050167223\n",
- "Toloi 0.2740384615384615\n",
+ "Milenkovic 0.7578347578347576\n",
"Kyriakopoulos 1\n",
- "Kyriakopoulos 0.423342175066313 (two seasons ago)\n",
- "Bellanova 1\n",
- "Mari' 0.5846153846153845\n",
- "Dodo' 0.4428904428904428\n",
+ "Kyriakopoulos 0.5291777188328912 (two seasons ago)\n",
+ "Casale 0.5039787798408487\n",
+ "Terracciano F. 1\n",
+ "Baschirotto 0.47401247401247393\n",
+ "Bijol 0.6394230769230768\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 0.5657568238213398\n",
- "Llorente D. 1\n",
- "Martinez Quarta 0.4330484330484331\n",
- "Bastoni S. 0.16153846153846155\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 0.6495726495726495\n",
- "Alex Sandro 0.23384615384615384\n",
- "Hateboer 0.17194570135746606\n",
- "Palomino 0.38974358974358975\n",
- "Marchizza 1\n",
- "Gallo 0.4567307692307692\n",
- "Caldirola 0.4714640198511166\n",
- "Kalulu 0.17194570135746606\n",
- "Erlic 0.6263736263736263\n",
- "Vojvoda 0.3023872679045092\n",
- "Vasquez 0.7366153846153846\n",
- "Cambiaso 0.4795673076923077\n",
+ "Beukema 0.8263313609467455 (rookie)\n",
+ "Faraoni 0.7625418060200667\n",
+ "Toloi 0.3653846153846154\n",
+ "Djimsiti 0.7307692307692307\n",
+ "Lazzari 0.31318681318681313\n",
+ "Lazaro 0.7625418060200667\n",
+ "Gallo 0.548076923076923\n",
+ "Bellanova 1\n",
+ "Mari' 0.6820512820512818\n",
+ "Erlic 0.7307692307692306\n",
+ "Bastoni S. 0.3230769230769231\n",
+ "Perez N. 0.6018099547511311\n",
+ "Pedersen 0.6350132625994694 (rookie)\n",
+ "Izzo 0.4871794871794871\n",
+ "D'ambrosio 0.8184615384615385\n",
+ "D'ambrosio 0.9202970414201184 (two seasons ago)\n",
+ "Luperto 0.5683760683760682\n",
+ "Florenzi 1\n",
+ "Florenzi 0.6089743589743589 (two seasons ago)\n",
+ "De Silvestri 0.9743589743589742\n",
+ "De Silvestri 0.4956416618947637 (two seasons ago)\n",
+ "Marusic 0.6200466200466198\n",
+ "Magnani 0.8525641025641024\n",
+ "N'dicka 0.40923076923076923 (rookie)\n",
+ "Augello 0.4977130977130977\n",
+ "Dawidowicz 0.8896321070234111\n",
+ "Caldirola 0.5657568238213398\n",
+ "Llorente D. 1\n",
+ "Parisi 0.37202797202797205\n",
+ "Cambiaso 0.5754807692307693\n",
+ "Bradaric 0.6600496277915632\n",
"Pongracic 1\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",
- "Pezzella Giu. 1\n",
- "Sabelli 0.5115384615384615 (rookie)\n",
- "Lazzari 0.31318681318681313\n",
- "Bani 0.558041958041958 (rookie)\n",
- "Djidji 0.0\n",
- "Lazaro 0.6354515050167223\n",
- "Augello 0.41476091476091476\n",
- "Zortea 0.9207692307692308\n",
- "Zortea 0.3762046521118139 (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. 0.8769230769230768\n",
+ "Ostigard 1\n",
+ "Olivera 0.5846153846153845\n",
"Ebosele 1\n",
- "Patric 0.3247863247863248\n",
- "Lykogiannis 0.4175824175824175\n",
- "Pellegrini Lu. 1\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",
+ "Dodo' 0.4428904428904428\n",
+ "Hien 0.3653846153846154\n",
+ "Azzi 0.9591346153846154 (rookie)\n",
+ "Hysaj 0.42986425339366513\n",
+ "Juan Jesus 0.7794871794871795\n",
+ "Sabelli 0.5115384615384615 (rookie)\n",
+ "Hateboer 0.17194570135746606\n",
+ "Martin 0.5480769230769231 (rookie)\n",
+ "Mina 0.0 (rookie)\n",
"Calafiori 1 (two seasons ago)\n",
"Monterisi 1 (rookie)\n",
+ "Kalulu 0.17194570135746606\n",
+ "Vojvoda 0.3023872679045092\n",
+ "De Winter 0.876923076923077\n",
+ "De Winter 1 (two seasons ago)\n",
+ "Gatti 0.811965811965812\n",
+ "Birindelli 0.6600496277915632\n",
+ "Masina 0.0\n",
+ "Gyomber 0.7578347578347576\n",
+ "Alex Sandro 0.23384615384615384\n",
+ "Palomino 0.38974358974358975\n",
+ "Pellegrini Lu. 1\n",
+ "Pellegrini Lu. 0.8525641025641026 (two seasons ago)\n",
+ "Djidji 0.0\n",
+ "Ranieri L. 0.9743589743589742\n",
+ "Ranieri L. 0.35851413543721244 (two seasons ago)\n",
+ "Zortea 0.9207692307692308\n",
+ "Zortea 0.3762046521118139 (two seasons ago)\n",
+ "Pirola 0.6745562130177514\n",
+ "Lovato 1\n",
"Ismajli 0.4676923076923077\n",
- "De Winter 0.6576923076923077\n",
- "Ehizibue 0.0\n",
- "Ferrari G. 0.17715617715617715\n",
+ "Obert 1 (two seasons ago)\n",
+ "Dossena 0.934113712374582 (rookie)\n",
+ "Patric 0.3247863247863248\n",
+ "Pezzella Giu. 1\n",
+ "Ferrari G. 0.2657342657342657\n",
"Venuti 0.18054298642533936\n",
- "Karsdorp 0.44970414201183434\n",
- "Kjaer 0.6877828054298643\n",
- "Gunter 0.0\n",
- "Soumaoro 0.0\n",
- "Zanoli 0.0\n",
- "Zima 0.3247863247863248\n",
+ "Karsdorp 0.6745562130177514\n",
+ "Kjaer 0.8597285067873303\n",
+ "Lykogiannis 0.5567765567765568\n",
+ "Walukiewicz 1\n",
+ "Walukiewicz 1 (two seasons ago)\n",
+ "Okoli 0.7221719457013575\n",
+ "Amione 0.23609467455621302\n",
"Hefti 0.7307692307692308 (two seasons ago)\n",
- "Ostigard 1\n",
- "Ostigard 1 (two seasons ago)\n",
- "Sambia 0.13286713286713286\n",
- "Rugani 0.3247863247863248\n",
- "De Sciglio 0.0\n",
+ "Ehizibue 0.0\n",
+ "Rugani 0.6495726495726496\n",
+ "Rugani 1 (two seasons ago)\n",
"Goldaniga 0.26573426573426573 (two seasons ago)\n",
- "Florenzi 1\n",
- "Florenzi 0.4871794871794872 (two seasons ago)\n",
- "De Silvestri 0.7794871794871795\n",
"Fazio 0.41758241758241765\n",
"Bereszynski 1\n",
"Bereszynski 0.2630769230769231 (two seasons ago)\n",
- "Bonifazi 0.0\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 0.21652421652421655\n",
- "Soppy 0.40923076923076923\n",
- "Haps 0.0 (two seasons ago)\n",
- "Coppola D. 0.3076923076923077\n",
- "Cacace 0.7307692307692307\n",
+ "Gunter 0.0\n",
+ "Soumaoro 0.0\n",
+ "Zanoli 0.0\n",
+ "Daniliuc 0.32478632478632474\n",
+ "Soppy 0.6138461538461538\n",
+ "Zima 0.3247863247863248\n",
+ "Haps 0.12276923076923077 (two seasons ago)\n",
+ "Coppola D. 0.46153846153846145\n",
+ "Cacace 0.9743589743589745\n",
"Cacace 1 (two seasons ago)\n",
- "Ebosse 0.14615384615384616\n",
+ "Sambia 0.13286713286713286\n",
"Guessand A. 1\n",
"Cabal 0.7972027972027971\n",
"Dermaku 0.0\n",
"Tonelli 0.0\n",
"Tonelli 0.20879120879120883 (two seasons ago)\n",
+ "De Sciglio 0.0\n",
+ "Bonifazi 0.0\n",
+ "Donati 0.0\n",
+ "Kumbulla 0.0\n",
+ "Celik 0.1217948717948718\n",
"Amey 0.0\n",
"Gila 0.0\n",
+ "Ebosse 0.14615384615384616\n",
"Bronn 0.0\n",
"Guarino 0.0\n",
"Carboni F. 1\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",
+ "Koopmeiners 0.6200466200466198\n",
+ "Zielinski 0.5530145530145528\n",
+ "Zaccagni 0.5846153846153845\n",
+ "Luis Alberto 0.5846153846153845\n",
+ "Pulisic 0.8951923076923077 (rookie)\n",
+ "Bonaventura 0.6820512820512818\n",
+ "Orsolini 0.6394230769230768\n",
+ "Calhanoglu 0.6200466200466198\n",
+ "Samardzic 0.5530145530145528\n",
+ "Felipe Anderson 0.5384615384615383\n",
+ "Politano 0.7578347578347576\n",
+ "Gudmundsson A. 0.5967948717948718 (rookie)\n",
"Candreva 0.501098901098901\n",
+ "Barella 0.5846153846153845\n",
+ "Rabiot 0.6394230769230768\n",
+ "Mkhitaryan 0.6600496277915632\n",
+ "Ferguson 0.6394230769230768\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. 0.2740384615384615\n",
- "Kostic 0.316008316008316\n",
- "Radonjic 0.6263736263736263\n",
- "Baldanzi 0.6745562130177514\n",
- "Lovric 0.47401247401247393\n",
+ "Loftus-Cheek 0.8593846153846153 (rookie)\n",
+ "Colpani 0.7578347578347576\n",
+ "Cristante 0.5683760683760682\n",
+ "Strefezza 0.5846153846153845\n",
+ "Chukwueze 0.4977130977130977 (rookie)\n",
+ "Radonjic 0.7307692307692306\n",
+ "Reijnders 0.6319004524886878 (rookie)\n",
+ "Pasalic 0.4567307692307692\n",
+ "Aouar 0.9591346153846154 (rookie)\n",
+ "Bajrami 1\n",
+ "Vlasic 0.5158371040723981\n",
+ "Ederson D.s. 0.5846153846153845\n",
+ "Baldanzi 0.7869822485207099\n",
+ "Kamada 0.4795673076923077 (rookie)\n",
"Lindstrom 0.0 (rookie)\n",
- "Lazovic 0.29230769230769227\n",
- "Pereyra 0.25791855203619907\n",
+ "De Roon 0.5846153846153845\n",
+ "Pellegrini Lo. 0.3653846153846154\n",
+ "El Shaarawy 0.6047745358090184\n",
+ "Mandragora 0.7055702917771881\n",
+ "Malinovskyi 0.5115384615384615 (two seasons ago)\n",
+ "Kostic 0.395010395010395\n",
+ "De Ketelaere 0.6713942307692308\n",
+ "Pereyra 0.3438914027149321\n",
"Renato Sanches 0.26688963210702343 (rookie)\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 0.4871794871794871\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",
+ "Pessina 0.5846153846153845\n",
+ "Guendouzi 0.46503496503496505 (rookie)\n",
+ "Zambo Anguissa 0.5683760683760682\n",
"Duda 1\n",
- "Castrovilli 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",
+ "Lovric 0.5530145530145528\n",
+ "Lazovic 0.38974358974358975\n",
+ "Duncan 0.7015384615384613\n",
+ "Gagliardini 1\n",
+ "Lobotka 0.5384615384615383\n",
+ "Fagioli 0.6745562130177514\n",
+ "Elmas 0.405982905982906\n",
+ "Messias 0.24553846153846154\n",
+ "Matheus Henrique 0.6820512820512818\n",
+ "Frendrup 0.5806652806652807 (rookie)\n",
+ "Ciurria 0.5683760683760682\n",
+ "Locatelli 0.6394230769230768\n",
+ "Ikone' 0.17715617715617715\n",
+ "Ilic 1\n",
+ "Ricci S. 0.6263736263736263\n",
+ "Saponara 0.5291777188328912\n",
+ "Vecino 0.4567307692307692\n",
+ "Pogba 0.9743589743589745\n",
+ "Barak 0.19487179487179487\n",
+ "Nandez 0.651048951048951 (rookie)\n",
+ "Strootman 0.5115384615384615 (rookie)\n",
+ "Klaassen 0.18601398601398603 (rookie)\n",
+ "Weah 0.7408488063660477 (rookie)\n",
+ "Marin 0.5314685314685313\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",
+ "Paredes 0.8593846153846153\n",
+ "Freuler 0.32884615384615384 (rookie)\n",
+ "Kastanos 0.7307692307692306\n",
+ "Bennacer 0.0\n",
+ "Castrovilli 0.0\n",
+ "Miranchuk 0.2116710875331565\n",
+ "Harroui 0.4003344481605351\n",
+ "Aebischer 0.6394230769230768\n",
+ "Oudin 0.2828784119106699\n",
+ "Sottil 0.6495726495726496\n",
+ "Tameze 0.41476091476091476\n",
+ "Pobega 0.7692307692307692\n",
+ "Bove 0.6643356643356643\n",
+ "Coulibaly L. 0.08351648351648353\n",
+ "Blin 0.5846153846153845\n",
+ "Moro N. 0.5621301775147929\n",
+ "Fabbian 0.2557692307692308 (rookie)\n",
+ "Machin 0.0\n",
+ "Linetty 0.4567307692307692\n",
+ "Walace 0.5530145530145528\n",
+ "Castillejo 0.4910769230769231 (rookie)\n",
+ "Gaetano 0.3653846153846154\n",
+ "Rovella 0.4910769230769231\n",
+ "Lopez M. 0.10230769230769231\n",
"Gyasi 0.3507692307692308\n",
"Zalewski 0.3543123543123543\n",
- "Harroui 0.4003344481605351\n",
- "Frendrup 0.4977130977130977 (rookie)\n",
- "Blin 0.501098901098901\n",
- "Fabbian 0.2557692307692308 (rookie)\n",
- "Vecino 0.3653846153846154\n",
- "Sensi 0.10961538461538463\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 0.18858560794044665\n",
- "Makoumbou 0.5115384615384616 (rookie)\n",
- "Machin 0.0\n",
- "Linetty 0.3653846153846154\n",
- "Castillejo 0.3683076923076923 (rookie)\n",
- "Rovella 0.3683076923076923\n",
- "Pobega 0.6153846153846154\n",
- "Miretti 0.5413105413105412\n",
- "Fazzini 0.6959706959706958\n",
+ "Bohinen 0.7307692307692307\n",
+ "Miretti 0.6495726495726495\n",
+ "Thorstvedt 0.4714640198511166\n",
+ "Fazzini 0.835164835164835\n",
+ "Makoumbou 0.5967948717948718 (rookie)\n",
+ "Folorunsho 0.7957264957264957 (rookie)\n",
"Grassi 0.5846153846153845\n",
"Baez 1 (rookie)\n",
- "Bourabia 0.1659043659043659\n",
+ "Sensi 0.10961538461538463\n",
+ "Maleh 0.9027149321266968\n",
+ "Adli 0.9743589743589745\n",
+ "Gonzalez J. 0.3340659340659341\n",
+ "Viola 1 (two seasons ago)\n",
+ "Bourabia 0.24885654885654884\n",
"Saelemaekers 0.20461538461538462\n",
"Maldini 0.0\n",
+ "Maggiore 0.7307692307692308\n",
"Kovalenko 0.17051282051282055\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",
+ "Asllani 0.4384615384615384\n",
+ "Vignato S. 1\n",
+ "Ranocchia F. 0.4384615384615385\n",
"Sulemana I. 0.9591346153846154\n",
- "Gaetano 0.0\n",
+ "Adopo 1\n",
+ "Basic 0.0\n",
+ "Rog 0.0 (two seasons ago)\n",
+ "Nicolussi Caviglia 0.0\n",
"Obiang 0.0\n",
- "Maggiore 0.548076923076923\n",
+ "Demme 0.0\n",
"Akpa Akpro 0.0\n",
"Akpa Akpro 0.0 (two seasons ago)\n",
"Urbanski 1\n",
"Volpato 0.4384615384615385\n",
"Volpato 1 (two seasons ago)\n",
- "Vignato S. 1\n",
- "Hrustic 0.0\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",
+ "Hrustic 0.0\n",
"Zerbin 0.2923076923076923\n",
"Carboni V. 1\n",
- "Faticanti 0.0\n"
+ "Faticanti 0.0\n",
+ "Martinez L. 0.5384615384615383\n",
+ "Osimhen 0.6394230769230768\n",
+ "Rafael Leao 0.5846153846153845\n",
+ "Berardi 0.5621301775147929\n",
+ "Lukaku 0.6138461538461538\n",
+ "Vlahovic 0.6495726495726495\n",
+ "Dybala 0.5846153846153845\n",
+ "Giroud 0.5314685314685313\n",
+ "Thuram 0.7161538461538461 (rookie)\n",
+ "Immobile 0.6600496277915632\n",
+ "Kvaratskhelia 0.5158371040723981\n",
+ "Retegui 1 (rookie)\n",
+ "Scamacca 0.3410256410256411 (two seasons ago)\n",
+ "Lookman 0.6600496277915632\n",
+ "Lauriente' 0.7307692307692306\n",
+ "Chiesa 0.974358974358974\n",
+ "Dia 0.3543123543123543\n",
+ "Zapata D. 0.6138461538461538\n",
+ "Gonzalez N. 0.7307692307692307\n",
+ "Sanabria 0.3543123543123543\n",
+ "Arnautovic 0.7307692307692307\n",
+ "Nzola 0.6930521091811415\n",
+ "Milik 0.6495726495726495\n",
+ "Pinamonti 0.6394230769230768\n",
+ "Zirkzee 1\n",
+ "Ngonge 1\n",
+ "Cheddira 0.5940446650124069 (rookie)\n",
+ "Simeone 0.7015384615384613\n",
+ "Sanchez 0.2630769230769231 (rookie)\n",
+ "Beltran L. 0.8593846153846153 (rookie)\n",
+ "Belotti 0.5657568238213398\n",
+ "Muriel 0.40318302387267907\n",
+ "Luvumbo 0.0 (rookie)\n",
+ "Lapadula 0.0 (rookie)\n",
+ "Caprari 0.316008316008316\n",
+ "Jovic 0.198014888337469\n",
+ "Abraham 0.0\n",
+ "Kouame' 0.521978021978022\n",
+ "Caputo 0.6959706959706958\n",
+ "Raspadori 0.8184615384615382\n",
+ "Colombo 0.46503496503496505\n",
+ "Soule' 1\n",
+ "Petagna 0.396029776674938\n",
+ "Bonazzoli 0.7673076923076924\n",
+ "Deulofeu 0.0\n",
+ "Pedro 0.405982905982906\n",
+ "Brekalo 1\n",
+ "Shomurodov 1\n",
+ "Azmoun 0.4003344481605351 (rookie)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "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 0.6138461538461538 (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 0.1753846153846154 (rookie)\n",
- "Caputo 0.5567765567765568\n",
- "Belotti 0.5657568238213398\n",
- "Muriel 0.3023872679045092\n",
- "Lapadula 0.0 (rookie)\n",
- "Jovic 0.198014888337469\n",
- "Abraham 0.0\n",
- "Zirkzee 0.9230769230769229\n",
- "Ngonge 1\n",
- "Petagna 0.29702233250620347\n",
- "Simeone 0.5846153846153845\n",
- "Deulofeu 0.0\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 0.4795673076923077 (two seasons ago)\n",
- "Cambiaghi 0.521978021978022\n",
- "Henry 0.1826923076923077\n",
- "Mulattieri 0.423342175066313 (rookie)\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 0.6047745358090184\n",
- "Bonazzoli 0.7673076923076924\n",
- "Djuric 0.521978021978022\n",
- "Banda 0.3247863247863248\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",
+ "Cambiaghi 0.6263736263736263\n",
+ "Henry 0.1826923076923077\n",
"Jovane 0.0 (two seasons ago)\n",
- "Soule' 0.9443786982248521\n",
- "Pavoletti 0.4003344481605351 (rookie)\n",
- "Cancellieri 0.9207692307692308\n",
- "Seck 0.46153846153846145\n",
- "Alvarez A. 0.0\n",
+ "Mota 0.7055702917771881\n",
+ "Mulattieri 0.5291777188328912 (rookie)\n",
+ "Lucca 1 (rookie)\n",
+ "Kean 0.41758241758241765\n",
+ "Karamoh 0.6959706959706958\n",
+ "Djuric 0.6263736263736263\n",
+ "Banda 0.3247863247863248\n",
+ "Sansone 0.3410256410256411\n",
+ "Success 0.5846153846153845\n",
+ "Defrel 0.32478632478632474\n",
+ "Piccoli 1\n",
+ "Piccoli 1 (two seasons ago)\n",
+ "Caso 0.5261538461538462 (rookie)\n",
+ "Pellegri 0.9743589743589742\n",
+ "Cancellieri 1\n",
+ "Seck 0.6153846153846154\n",
+ "Botheim 0.6263736263736263\n",
+ "Pavoletti 0.5337792642140469 (rookie)\n",
"Ekuban 0.38974358974358975 (two seasons ago)\n",
- "Destro 0.5158371040723981\n",
+ "Alvarez A. 0.0\n",
+ "Destro 0.6877828054298643\n",
"Ceide 0.46153846153846145\n",
"Ake' M. 0.0 (two seasons ago)\n",
"Braaf 0.0\n",
@@ -4086,45 +4087,42 @@
"Kaio Jorge 0.0 (two seasons ago)\n",
"Vivaldo 0.0\n",
"Players with low quantity of games:\n",
- "Natan 0.33333333333333337\n",
- "Kristiansen 0.6666666666666667\n",
+ "Kristiansen 0.8333333333333334\n",
+ "Natan 0.5\n",
+ "Carboni A. 0.33333333333333337\n",
"Azzi 0.908253205128205\n",
- "Wieteska 0.5\n",
+ "Kayode 0.6666666666666667\n",
+ "Calafiori 0.6666666666666667\n",
+ "De Winter 0.8717948717948717\n",
+ "Hatzidiakos 0.6666666666666667\n",
+ "Wieteska 0.6666666666666667\n",
"Lirola 0.16666666666666663\n",
"Kabasele 0.6666666666666667\n",
- "Obert 0.6666666666666667\n",
- "Zemura 0.8333333333333334\n",
- "Hatzidiakos 0.5\n",
- "Carboni A. 0.33333333333333337\n",
- "Calafiori 0.5\n",
- "Monterisi 0.8333333333333334\n",
+ "Obert 0.8333333333333334\n",
"Tressoldi 0.0\n",
- "Vogliacco 0.0\n",
- "Di Pardo 0.8333333333333334\n",
- "Ostigard 0.8333333333333334\n",
- "Bisseck 0.16666666666666663\n",
- "Ferreira J. 0.8333333333333334\n",
"Touba 0.33333333333333337\n",
- "Sazonov 0.16666666666666663\n",
+ "Sazonov 0.33333333333333337\n",
+ "Walukiewicz 0.8333333333333334\n",
+ "Vogliacco 0.0\n",
+ "Rugani 0.7421652421652423\n",
"Pereira P. 0.5\n",
- "Walukiewicz 0.6666666666666667\n",
- "Cittadini 0.0\n",
- "Cacace 0.9038461538461539\n",
+ "Cacace 0.7008547008547008\n",
"Guessand A. 0.16666666666666663\n",
"Cabal 0.7703962703962706\n",
"Missori 0.16666666666666663\n",
- "Kayode 0.5\n",
- "Corazza 0.5\n",
- "Kristensen T. 0.33333333333333337\n",
+ "Bisseck 0.16666666666666663\n",
+ "Corazza 0.6666666666666667\n",
+ "Kristensen T. 0.5\n",
"Dermaku 0.16666666666666663\n",
"Capradossi 0.0\n",
"Bettella 0.0\n",
"Amey 0.0\n",
+ "Cittadini 0.0\n",
"Gila 0.6666666666666667\n",
"Guarino 0.0\n",
"Carboni F. 0.33333333333333337\n",
"Smajlovic 0.0\n",
- "Matturro 0.16666666666666663\n",
+ "Matturro 0.33333333333333337\n",
"N'guessan 0.0\n",
"Mateus Lusuardi 0.0\n",
"Kalaj 0.0\n",
@@ -4133,81 +4131,75 @@
"Bonfanti 0.0\n",
"Pellegrino 0.0\n",
"Comuzzo 0.0\n",
+ "Bartesaghi 0.33333333333333337\n",
+ "Aouar 0.908253205128205\n",
+ "Gomez 0.16666666666666663\n",
"Pogba 0.3504273504273504\n",
- "Mboula 0.5\n",
- "Musah 0.6666666666666667\n",
- "Jankto 0.5\n",
+ "Musah 0.8333333333333334\n",
"Reinier 0.0\n",
- "Cajuste 0.0\n",
- "Mancosu 0.0\n",
- "Brescianini 0.8333333333333334\n",
- "Boloca 0.8333333333333334\n",
- "Machin 0.0\n",
- "Iling Junior 0.0\n",
- "Oristanio 0.8333333333333334\n",
- "Serdar 0.6666666666666667\n",
- "Payero 0.5\n",
+ "Mboula 0.5\n",
+ "Jankto 0.5\n",
"Garritano 0.8333333333333334\n",
+ "Iling Junior 0.0\n",
+ "Cajuste 0.0\n",
+ "Machin 0.0\n",
+ "Gaetano 0.9070512820512819\n",
+ "Kutlu 0.5\n",
+ "Payero 0.6666666666666667\n",
+ "Mancosu 0.0\n",
+ "Adli 0.3504273504273504\n",
+ "Serdar 0.6666666666666667\n",
+ "Suslov 0.6666666666666667\n",
+ "Viola 0.33333333333333337\n",
"Racic 0.33333333333333337\n",
- "Infantino 0.5\n",
- "Martegani 0.8333333333333334\n",
- "Kutlu 0.33333333333333337\n",
+ "Romero L. 0.5737179487179487\n",
+ "Vignato S. 0.8333333333333334\n",
+ "Sulemana I. 0.908253205128205\n",
+ "Infantino 0.6666666666666667\n",
"Tchatchoua 0.0\n",
"Quina 0.33333333333333337\n",
"Adopo 0.5\n",
- "Romero L. 0.5737179487179487\n",
- "Tchaouna 0.5\n",
- "Sulemana I. 0.908253205128205\n",
+ "Tchaouna 0.6666666666666667\n",
+ "Amatucci 0.16666666666666663\n",
"Gelli 0.6666666666666667\n",
- "Suslov 0.5\n",
+ "Legowski 0.0\n",
+ "Prati 0.33333333333333337\n",
+ "Lulic K. 0.0\n",
"Jagiello 0.0\n",
"Akpa Akpro 0.0\n",
"Urbanski 0.33333333333333337\n",
"Volpato 0.7282051282051283\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 0.8333333333333334\n",
+ "Zarraga 0.33333333333333337\n",
+ "Camara E. 0.0\n",
"Lipani 0.0\n",
"Joselito 0.0\n",
- "Legowski 0.0\n",
- "Ibrahimovic A. 0.0\n",
+ "Pagano 0.5\n",
+ "Ibrahimovic A. 0.16666666666666663\n",
"Toure' E. 0.0\n",
- "Krstovic 0.8333333333333334\n",
- "Castellanos 0.8333333333333334\n",
- "Isaksen 0.8333333333333334\n",
- "Brenner 0.0\n",
- "Davis K. 0.0\n",
- "Piccoli 0.7500986193293885\n",
+ "Soule' 0.8333333333333334\n",
"Jovane 0.0\n",
- "Soule' 0.7500986193293885\n",
- "Cuni 0.8333333333333334\n",
- "Maric 0.8333333333333334\n",
- "Cruz 0.0\n",
- "Van Hooijdonk 0.33333333333333337\n",
+ "Davis K. 0.0\n",
+ "Brenner 0.0\n",
+ "Piccoli 0.8333333333333334\n",
"Kvernadze 0.33333333333333337\n",
+ "Van Hooijdonk 0.5\n",
+ "Maric 0.8333333333333334\n",
"Ikwuemesi 0.6666666666666667\n",
- "Puscas 0.16666666666666663\n",
+ "Yildiz 0.0\n",
+ "Cruz 0.16666666666666663\n",
+ "Puscas 0.33333333333333337\n",
"Ake' M. 0.6666666666666667\n",
"Vivaldo 0.0\n",
"Bidaoui 0.0\n",
- "Shpendi S. 0.8333333333333334\n",
"Burnete 0.16666666666666663\n",
- "Corfitzen 0.0\n",
- "Stewart 0.0\n",
- "Yildiz 0.0\n"
+ "Corfitzen 0.16666666666666663\n",
+ "Stewart 0.16666666666666663\n"
]
}
],
@@ -4847,35 +4839,33 @@
"output_type": "stream",
"text": [
"Epoch 1/1000\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",
+ "97/97 [==============================] - 4s 9ms/step - loss: 2.1231 - distribution_lambda_loss: 0.8271 - distribution_lambda_1_loss: 1.2961 - val_loss: 2.0424 - val_distribution_lambda_loss: 0.7918 - val_distribution_lambda_1_loss: 1.2505\n",
"Epoch 2/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1228 - distribution_lambda_loss: 0.8266 - distribution_lambda_1_loss: 1.2962 - val_loss: 2.0378 - val_distribution_lambda_loss: 0.7895 - val_distribution_lambda_1_loss: 1.2483\n",
"Epoch 3/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1235 - distribution_lambda_loss: 0.8279 - distribution_lambda_1_loss: 1.2957 - val_loss: 2.0464 - val_distribution_lambda_loss: 0.7935 - val_distribution_lambda_1_loss: 1.2530\n",
"Epoch 4/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1266 - distribution_lambda_loss: 0.8293 - distribution_lambda_1_loss: 1.2973 - val_loss: 2.0375 - val_distribution_lambda_loss: 0.7873 - val_distribution_lambda_1_loss: 1.2502\n",
"Epoch 5/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1236 - distribution_lambda_loss: 0.8283 - distribution_lambda_1_loss: 1.2953 - val_loss: 2.0412 - val_distribution_lambda_loss: 0.7891 - val_distribution_lambda_1_loss: 1.2521\n",
"Epoch 6/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1209 - distribution_lambda_loss: 0.8254 - distribution_lambda_1_loss: 1.2955 - val_loss: 2.0491 - val_distribution_lambda_loss: 0.7929 - val_distribution_lambda_1_loss: 1.2561\n",
"Epoch 7/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1219 - distribution_lambda_loss: 0.8263 - distribution_lambda_1_loss: 1.2956 - val_loss: 2.0483 - val_distribution_lambda_loss: 0.7934 - val_distribution_lambda_1_loss: 1.2548\n",
"Epoch 8/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1211 - distribution_lambda_loss: 0.8262 - distribution_lambda_1_loss: 1.2948 - val_loss: 2.0477 - val_distribution_lambda_loss: 0.7933 - val_distribution_lambda_1_loss: 1.2544\n",
"Epoch 9/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1272 - distribution_lambda_loss: 0.8300 - distribution_lambda_1_loss: 1.2972 - val_loss: 2.0494 - val_distribution_lambda_loss: 0.7953 - val_distribution_lambda_1_loss: 1.2541\n",
"Epoch 10/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1239 - distribution_lambda_loss: 0.8272 - distribution_lambda_1_loss: 1.2967 - val_loss: 2.0431 - val_distribution_lambda_loss: 0.7905 - val_distribution_lambda_1_loss: 1.2526\n",
"Epoch 11/1000\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1211 - distribution_lambda_loss: 0.8268 - distribution_lambda_1_loss: 1.2943 - val_loss: 2.0435 - val_distribution_lambda_loss: 0.7904 - val_distribution_lambda_1_loss: 1.2531\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1212 - distribution_lambda_loss: 0.8269 - distribution_lambda_1_loss: 1.2942 - val_loss: 2.0461 - val_distribution_lambda_loss: 0.7929 - val_distribution_lambda_1_loss: 1.2532\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",
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1223 - distribution_lambda_loss: 0.8262 - distribution_lambda_1_loss: 1.2961 - val_loss: 2.0463 - val_distribution_lambda_loss: 0.7928 - val_distribution_lambda_1_loss: 1.2535\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"
+ "97/97 [==============================] - 0s 3ms/step - loss: 2.1211 - distribution_lambda_loss: 0.8265 - distribution_lambda_1_loss: 1.2946 - val_loss: 2.0430 - val_distribution_lambda_loss: 0.7908 - val_distribution_lambda_1_loss: 1.2522\n"
]
}
],
@@ -4977,13 +4967,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.14248994674439097\n",
- "0.16946807672801856\n"
+ "0.14318537713364876\n",
+ "0.16192383064613713\n"
]
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
@@ -4995,13 +4985,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.13312004007562517\n",
- "0.14674466840894407\n"
+ "0.1390455990767111\n",
+ "0.16511344994051125\n"
]
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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tPIK1R7IBAON6RmHBhG5o4svTVmPFV56IiNzK79dKMPPrNJzOLYG3WoVX7umM6f1ioFIxX6UxY8BCRERuY8NvOXjmf4dRoq9EWKAGi6f2QkJMsKubRW6AAQsREblcpcGIdzdlYsmO3wEAfWKDsXByPMIC/VzcMnIXDFiIiMil8kv0mLP8EPb8ng8A+L8BsXg+uRN8vNQubhm5EwYsRETkMhkXC/FYShqyi8rQxNcLb9/fHWN7RLm6WeSGGLAQEdFtJwgClv96Ea+tPoZygxFtWwRgybQExIUHurpp5KYYsBAR0W1VVmHAKz/+hv+lXQIAJHUJx7sP9kCgn4+LW0bujAELERHdNhcLbmBmShqOXdFBrQKeTeqEmYPbcsoy1YoBCxER3RbbT+XiyW8zUHSzAsEBvvj44Xjc1b6Fq5tFHoIBCxEROZXRKGDhtjN4f0smBAHo0UqLRVMT0LKZv6ubRh6EAQsRETlN0c0KzF2RgZ9P5gIAJie2xqtjO0Pj7eXilpGnYcBCREROcSJbh5kpabiQfwO+3mq8Ob4rJt4Z7epmkYdiwEJERPUu9dAlzPvhKMoqjGjV3B9Lpiaga0utq5tFHowBCxER1ZvySiPeXHscX+29AAAYFBeKDyf1RPMAXxe3jDwdAxYiIqoXOUVlmLUsDelZhQCAJ4a1x5Mj4uCl5pRlunUMWIiI6JbtO5uPx79JR15JOQL9vPHBpJ4Yfke4q5tFDQgDFiIiqjNBEPDF7nNYsP4kDEYBnSICsWRqAtq0CHB106iBYcBCRER1UqKvxPPfH8Hao9kAgPviW2L+fd3g78spy1T/GLAQEZHDzuSWYGZKGs7klsBbrcLfxnbGtL4xLLFPTqN29AY7d+7E2LFjERUVBZVKhR9//FFx/SOPPAKVSqX46du3b63HXblyJTp37gyNRoPOnTsjNTXV0aYREdFtsOG3bIz/5BecyS1BeJAGKx7ti+n92jBYIadyOGApLS1Fjx49sHDhQqv7jB49GtnZ2dLPunXrbB5z7969mDRpEqZNm4bDhw9j2rRpmDhxIvbv3+9o84iIyEkqDUYsWH8CM1PSUaKvRJ/YYPw0ZwASYoJd3TRqBFSCIAh1vrFKhdTUVIwfP17a9sgjj6CwsNCs58WWSZMmQafTYf369dK20aNHo3nz5li+fLldx9DpdNBqtSgqKkJQUJDd901ERLXLK9HjieWHsOf3fADA/w2IxfPJneDj5fD3XiIFe8/fTnmnbd++HWFhYYiLi8Of//xn5Obm2tx/7969GDVqlGJbUlIS9uzZY/U2er0eOp1O8UNERPXvUNZ1jP14N/b8no8mvl5YODkeL9/TmcEK3Vb1/m5LTk7GsmXLsHXrVrz33ns4cOAAhg0bBr1eb/U2OTk5CA9XztcPDw9HTk6O1dssWLAAWq1W+omO5voURET1SRAEpOy7gEmf7kN2URnahgZg1ey7cE/3KFc3jRqhep8lNGnSJOnvrl274s4770RMTAzWrl2LCRMmWL1dzWQtQRBsJnDNmzcPc+fOlS7rdDoGLURE9aSswoCXUn/DyvRLAIDRXSLwzwe7I9DPx8Uto8bK6dOaIyMjERMTg9OnT1vdJyIiwqw3JTc316zXRU6j0UCj0dRbO4mISHSx4AYe/ToNx7N1UKuA50Z3wqOD2nIWELmU0wcg8/PzcfHiRURGRlrdp1+/fti8ebNi26ZNm9C/f39nN4+IiGS2ncrFPR/vxvFsHYIDfJHyp0TMHNyOwQq5nMM9LCUlJThz5ox0+dy5c8jIyEBwcDCCg4Px2muv4f7770dkZCTOnz+PF198ES1atMB9990n3Wb69Olo2bIlFixYAAB48sknMWjQILz99tsYN24cVq1ahS1btmD37t318BCJiKg2RqOAj7eewQc/Z0IQgB7RzbB4Si9ENfN3ddOIANQhYDl48CCGDh0qXTblkcyYMQOLFy/G0aNH8dVXX6GwsBCRkZEYOnQoVqxYgcDAQOk2WVlZUKurO3f69++Pb7/9Fi+//DJeeeUVtGvXDitWrEBiYuKtPDYiIrJD0Y0KPP1dBraeFGd0Tklsjb+N7QyNN0vsk/u4pTos7oR1WIiIHHfsShEeS0lHVsENaLzVeHN8Vzx4Jycw0O1j7/mbawkRETVSP6RfwrwfjkJfaUSr5v5YMjUBXVtqXd0sIosYsBARNTLllUa8seY4vt53AQAwOC4UHz7UE82a+Lq4ZUTWMWAhImpEcorK8NiyNBzKKgQAPDm8A54Y3gFeas4CIvfGgIWIqJHY+3s+5ixPR15JOYL8vPHBQz0xrJP1eldE7oQBCxFRAycIAj7fdRZvbzgFg1HAHZFBWDK1F2JCAlzdNCK7MWAhImrASvSVeO77w1h3VKwmPiG+Jd66rxv8fTllmTwLAxYiogbqTG4JHv36IH6/VgofLxX+dk9nTO0bw6q15JEYsBARNUDrj2bjmf8dRmm5AeFBGiyakoCEmOaubhZRnTFgISJqQCoNRvxz4yl8uvMsACAxNhgLJ/dCaCAXiyXPxoCFiKiByCvRY843h7D3bD4A4C+D2uK5pI7w9nL6OrdETseAhYioAUjPuo5ZKenI0ZUhwNcL/3ywB8Z0i3R1s4jqDQMWIiIPJggCUvZn4e8/HUOFQUDb0AB8Ni0B7cMCa78xkQdhwEJE5KHKKgx4KfU3rEy/BABI7hqBdx7ojkA/Hxe3jKj+MWAhIvJAWfk3MDMlDcezdVCrgOdHd8JfBrXllGVqsBiwEBF5mG0nc/HUigwU3axASIAvPp4cj/7tWri6WUROxYCFiMhDGI0CPvz5ND7aehqCAPSMbobFU3shUuvv6qYROR0DFiIiD1B4oxxPr8jAtlPXAABT+7bGK/d0hsabJfapcWDAQkTk5o5dKcLMlDRcLLgJjbcab93XDQ8ktHJ1s4huKwYsRERubGXaJbyYehT6SiOig/2xZGoCukRpXd0sotuOAQsRkRvSVxrwxprjSNmXBQAY2jEUH0yKh7YJpyxT48SAhYjIzWQX3cRjKenIuFgIlQp4cngHPDGsA9RqTlmmxosBCxGRG9nzex7mfHMI+aXlCPLzxocPxWNopzBXN4vI5RiwEBG5AUEQ8NnOs3h7w0kYBeCOyCB8OjUBrUOauLppRG6BAQsRkYuV6Cvx7P8OY/1vOQCACb1a4q3x3eDvyynLRCYMWIiIXOhMbjEe/ToNv18rhY+XCn8b2wVTE1uzxD5RDQxYiIhcZO2RbDz3/WGUlhsQEeSHRVN7oVfr5q5uFpFbYsBCRHSbVRqMeGfjKXy28ywAoG/bYCyc3Astmmpc3DIi98WAhYjoNrpWrMec5enYd7YAAPDooLZ4NqkjvL3ULm4ZkXtjwEJEdJukZ13HrJR05OjKEODrhX8+2ANjukW6ullEHoEBCxGRkwmCgJR9F/D3NcdRYRDQLjQAn05LQPuwQFc3jchjMGAhInKim+UGvPTjUfyQfhkAMKZbBN55oAeaavjxS+QIhwdNd+7cibFjxyIqKgoqlQo//vijdF1FRQWef/55dOvWDQEBAYiKisL06dNx5coVm8dcunQpVCqV2U9ZWZnDD4iIyF1cyC/FhMV78EP6ZahVwItjOuGTyb0YrBDVgcMBS2lpKXr06IGFCxeaXXfjxg2kp6fjlVdeQXp6On744QdkZmbi3nvvrfW4QUFByM7OVvz4+fk52jwiIrew9eRVjP14N05k6xAS4IuU/0vEXwa1Y30VojpyOMxPTk5GcnKyxeu0Wi02b96s2Pbxxx+jT58+yMrKQuvWra0eV6VSISIiwtHmEBG5FaNRwIc/n8aHP58GAMS3boZFU3ohUuvv4pYReTan90sWFRVBpVKhWbNmNvcrKSlBTEwMDAYDevbsiTfeeAPx8fFW99fr9dDr9dJlnU5XX00mIqqTwhvleGpFBrafugYAmNY3Bi/fcwc03iyxT3SrnDrxv6ysDC+88AImT56MoKAgq/t16tQJS5cuxerVq7F8+XL4+fnhrrvuwunTp63eZsGCBdBqtdJPdHS0Mx4CEZFdfrtchLELd2P7qWvQeKvx3oM98Mb4rgxWiOqJShAEoc43VqmQmpqK8ePHm11XUVGBBx98EFlZWdi+fbvNgKUmo9GIXr16YdCgQfjoo48s7mOphyU6OhpFRUUO3RcR0a36Pu0SXko9Cn2lEa2Dm2Dx1F7oEqV1dbOIPIJOp4NWq631/O2UIaGKigpMnDgR586dw9atWx0OINRqNXr37m2zh0Wj0UCjYRlrInIdfaUBf//pOJbtzwIADO0Yig8mxUPbxMfFLSNqeOo9YDEFK6dPn8a2bdsQEhLi8DEEQUBGRga6detW380jIqoX2UU38VhKOjIuFkKlAp4c3gFPDOsAtZqzgIicweGApaSkBGfOnJEunzt3DhkZGQgODkZUVBQeeOABpKenY82aNTAYDMjJyQEABAcHw9fXFwAwffp0tGzZEgsWLAAAvP766+jbty86dOgAnU6Hjz76CBkZGfjkk0/q4zESEdWrPWfyMGf5IeSXlkPr74MPHuqJoR3DXN0sogbN4YDl4MGDGDp0qHR57ty5AIAZM2bgtddew+rVqwEAPXv2VNxu27ZtGDJkCAAgKysLanV1vm9hYSH+8pe/ICcnB1qtFvHx8di5cyf69OnjaPOIiJxGEAR8uvMs3tlwEkYB6BwZhCVTE9A6pImrm0bU4N1S0q07sTdph4ioLorLKvDs/45gwzGx1/j+Xq3w1n1d4efDWUBEt8KlSbdERA3J6avFeDQlDWevlcLHS4VXx3bBlMTWrFpLdBsxYCEismHtkWw8+/1h3Cg3ICLID4un9kJ86+aubhZRo8OAhYjIgkqDEW9vOInPd50DAPRrG4KPJ8ejRVOWUyByBQYsREQ1XCvW4/Fv0rH/XAEA4NHBbfHsqI7w9nJqcXAisoEBCxGRTNqF65i1LA1XdXoE+Hrh3Qd7ILlbpKubRdToMWAhIoI4ZfnrfRfwxprjqDAIaB/WFEumJqB9WFNXN42IwICFiAg3yw14MfUoUg9dBgDc3S0Sbz/QHU01/Igkchf8bySiRu1Cfike/ToNJ3OK4aVW4YXRnfB/A2M5ZZnIzTBgIaJG6+cTV/HUigwUl1WiRVNffPxwL/Rr5/j6Z0TkfAxYiKjRMRgFfPjzaXz0s7gifK/WzbBoSgIitH4ubhkRWcOAhYgalcIb5Xjy2wzsyLwGAJjeLwYv390Zvt6cskzkzhiwEFGj8dvlIsxMScOl6zfh56PG/Pu6YUKvVq5uFhHZgQELETUK/zt4ES//+Bv0lUa0Dm6CJVMT0DmKC6USeQoGLETUoOkrDXj9p+P4Zn8WAGBYpzC8P7EntE18XNwyInIEAxYiarCuFN7EY8vScfhiIVQq4OkRcXh8aHuo1ZyyTORpGLAQUYP0y5k8zFl+CAWl5dD6++DDh3piSMcwVzeLiOqIAQsRNSiCIGDJjrP458aTMApAl6ggLJmagOjgJq5uGhHdAgYsRNRgFJdV4Jn/HcbGY1cBAA8ktMKb47vCz8fLxS0jolvFgIWIGoTTV4vx6NdpOJtXCl8vNV69tzMm92nNEvtEDQQDFiLyeGuOXMFz3x/BjXIDIrV+WDw1AT2jm7m6WURUjxiwEJHHqjAY8fb6k/j37nMAgP7tQvDxw/EIaapxccuIqL4xYCEij5RbXIbHvzmEX88VAABmDm6HZ0bFwduLJfaJGiIGLETkcdIuFGDWsnRc1enRVOONdx/sjtFdI13dLCJyIgYsROQxBEHAV3sv4I01x1FpFNA+rCmWTE1A+7Cmrm4aETkZAxYi8gg3yw14MfUoUg9dBgDc3T0S79zfHQEafowRNQb8Tycit3c+rxQzU9JwMqcYXmoV5iV3wp8GxHLKMlEjwoCFiNzaluNX8fR3GSguq0SLpr5YOLkX+rYNcXWziOg2Y8BCRG7JYBTwwZZMfLz1DACgV+tmWDQlARFaPxe3jIhcgQELEbmd66XleHJFBnZmXgMAzOgXg5fu7gxfb05ZJmqsGLAQkVv57XIRZqak4dL1m/DzUWPBhG64L76Vq5tFRC7GgIWI3MZ3By/i5R9/Q3mlETEhTbBkagLuiAxydbOIyA043L+6c+dOjB07FlFRUVCpVPjxxx8V1wuCgNdeew1RUVHw9/fHkCFDcOzYsVqPu3LlSnTu3BkajQadO3dGamqqo00jIg+lrzRg3g9H8dz3R1BeacTwTmFY/fgABitEJHE4YCktLUWPHj2wcOFCi9e/8847+Ne//oWFCxfiwIEDiIiIwMiRI1FcXGz1mHv37sWkSZMwbdo0HD58GNOmTcPEiROxf/9+R5tHRB7mcuFNTFyyF8t/zYJKBfx1ZBw+n34ntP4+rm4aEbkRlSAIQp1vrFIhNTUV48ePByD2rkRFReGpp57C888/DwDQ6/UIDw/H22+/jUcffdTicSZNmgSdTof169dL20aPHo3mzZtj+fLldrVFp9NBq9WiqKgIQUH8VkbkCX45k4c5yw+hoLQcWn8ffPhQTwzpGObqZhHRbWTv+bteU+7PnTuHnJwcjBo1Stqm0WgwePBg7Nmzx+rt9u7dq7gNACQlJdm8jV6vh06nU/wQkWcQBAGLtp/BtC/2o6C0HF1bBmHNnAEMVojIqnoNWHJycgAA4eHhiu3h4eHSddZu5+htFixYAK1WK/1ER0ffQsuJ6HbRlVVgZkoa3tlwCkYBeDChFb6f2R/RwU1c3TQicmNOKWpQs1y2IAi1ltB29Dbz5s1DUVGR9HPx4sW6N5iIbovMq8UYv/AXbDx2Fb5e4pTldx7oDj8fL1c3jYjcXL1Oa46IiAAg9phERlYv9Z6bm2vWg1LzdjV7U2q7jUajgUajucUWE9Ht8tPhK3ju+yO4WWFAlNYPi6YmoGd0M1c3i4g8RL32sMTGxiIiIgKbN2+WtpWXl2PHjh3o37+/1dv169dPcRsA2LRpk83bEJFnqDAY8caa45iz/BBuVhhwV/sQ/DRnAIMVInKIwz0sJSUlOHPmjHT53LlzyMjIQHBwMFq3bo2nnnoK8+fPR4cOHdChQwfMnz8fTZo0weTJk6XbTJ8+HS1btsSCBQsAAE8++SQGDRqEt99+G+PGjcOqVauwZcsW7N69ux4eIhG5Sm5xGR5fdgi/ni8AADw2pB3+OjIO3l4ssU9EjnE4YDl48CCGDh0qXZ47dy4AYMaMGVi6dCmee+453Lx5E7NmzcL169eRmJiITZs2ITAwULpNVlYW1OrqD6z+/fvj22+/xcsvv4xXXnkF7dq1w4oVK5CYmHgrj42IXOjg+QLMWpaO3GI9mmq88e6DPTC6a4Srm0VEHuqW6rC4E9ZhIXIPgiDgv3vO4821J1BpFNAhrCk+nZaAtqFNXd00InJD9p6/uZYQEdWbG+WVmPfDUazKuAIAuKd7JN6+vzsCNPyoIaJbw08RIqoX5/NKMTMlDSdziuGlVuHFMXfgj3e1qbWkARGRPRiwENEt23L8Kp7+LgPFZZVo0VSDTybHI7FtiKubRUQNCAMWalAyMzPx+++/o3379ujQoYOrm9PgGYwCPtiSiY+3ijMHE2KaY9GUXggP8nNxy4iooWHAQg1CQUEBJk+djI3rN0rbkpKTsHzZcjRv3tyFLWu4rpeW44lvD2HX6TwAwCP92+DFMXfA15tTlomo/jFgoQZh8tTJ2LJzCzABQAyAC8CWjVvw8JSHsWHdBlc3r8E5eqkIM1PScLnwJvx81PjHhO4YH9/S1c0iogaMAQt5vMzMTLFnZQKA7lUbuwMGwYCNqRtx+vRpDg/VoxUHsvDKqmMorzQiJqQJlkxNwB2RLCVARM7FgIU83u+//y7+EVPjijbirzNnzjBgqQdlFQa8/tMxLP9VXGh0xB1heG9iT2j9fVzcMiJqDBiwkMdr166d+McFVPewAMB58Vf79u1vc4sansuFN/FYShqOXCqCSgX8dWQcZg1pD7WaU5ZvByaTE9Xz4odErhAXF4ek5CR4bfQCDgMoAnAY8NrkhaTkJH7A36Ldp/Nwz0e7cORSEZo18cF//9AHjw/rwGDlNigoKMDoMaPRsWNHjBkzBnFxcRg9ZjSuX7/u6qa5rczMTKxfvx6nT592dVOonjFgoQZh+bLlGDFoBJAK4H0AqcCIQSOwfNlyVzfNYxmNAj7ZdgbT/7Mf129UoFtLLX56fAAGxYXWy/F5YqmdIpn8aQATgC07xWRyUmJw1/BxLSFqUE6fPo0zZ86w6/wW6coq8NfvDmPz8asAgIl3tsLfx3WFn4/XLR/bXaagu/swS2ZmJjp27CgGK1EArgMIBnAJQKp4vTu221VGjxmNLTu3wJBkkGYKem30wohBIzhT0M1xLSFqMBw5sTSQ+NulTuUUY2ZKGs7llcLXS43Xx3XBw31a19vxXT0F3V0CptpIyeSHAPwguyJW/MVk8mp1nSno7kErKXFIiNyWI128jnYHOzIc4ayhC3ccEll9+ArGf/ILzuWVIkrrh//N7FevwYrpxGJIMognFi3EE8soAzau33hbngtPGWZp164doAKQDUVbkQ1AxWRyOXtmCspx+MgzMWAht+XIicXefZ0ZBNnLHT8sKwxG/P2n43hi+SHcrDBgQPsWWPPEQPSIbgbA/uCqtv0UJ5Y8AKcB5MPqiaW+uUPA5BABwBgo2orkqu0kUcwUlDsv/qoZ3HlK0OpO3OILltBAFBUVCQCEoqIiVzeF6sGpU6cEAAImQMBrsp/7IAAQMjMz67Tv0OFDBXiL26UfbwjDRgwza0NScpLgFeAlHvdp8fheAV5CUnLSLT02Zx23rq4W3RQeWPyLEPP8GiHm+TXC2+tPCJUGoyAIgpCfny8kJScpnq+k5CShoKBAcQx795Neq4gar0G4+WvlDOvWrRPv7+ka75Wnxftft26dU+/fEZ7UVncg/V/dV/Uc3Wf5/8qRzwuy/3/7Vth7/mYPC7klR7p47d03MzMT27ZuEzO35F3s3sDWn7cqvjnU9Zt4bd9C3O0b/oHzBbj74904cP46AjXe+HRaAp4b3QleVVOW7f0mau9+cXFxCG4RLCaQyl+DQiC4RbDT8wgc/SbuSp7UVndg70xBR4ePGjt36o1iwEJuyZEPa3v33bFjh80u9h07dkg3ddaYuLt8WAqCgC9/OYeHP9uHa8V6xIU3xarH70JSlwhpH3uDK0eCsMzMTBTkFQB3Q/kajAEK8gqcHrB5Us0eT2qrO2jevDk2rNuAzMxMrFu3DpmZmdiwboNZIjUDQfu52xcsBizklhz5sHb4g91KsCDnrDFxd/iwvFFeiadWZOD1n46j0ijgnu6RSJ11F9qGNlXsZ29w5UgQJgWFVvaVB43O4kk1e+rSVrfINXChDh06IDk52WpAx0DQfu7yBcuE05rJbS1fthwPT3kYG1Orp5+OSLb8Yb1o4SL06dsH+an50rZmoc2w+JPF0uXBgweLf1gp4S9dD/FDLSQ0BPlr88VemTZV+60DQkJDFB9qjkypNH1Ybtm4BQbBIB3Xa5MXRiSPcPrUy3N5pZj5dRpOXS2Gt1qFF8fcgT/c1QYqlXnVWnuXPKjT0ggXYF5b5DYxfRP3hJo9jrTVU6ZruwNHPlsaM7db9qTesmZcjEm3DVdmZqawbt06m8lwUsLdKAgYDwGjLCfcDRw8UIAGisQ8aCAMGjxIsZ8jyaGK5MjHIWAKBMyxnhxZUFBQr4ms9tr4W7bQ9W8bhJjn1wh3vrlZ2H82v9bb2JvIGBIaYvF5DQkNUewnPa9eNZ5XL9sJj6dOnar1PdCQ2fP465LM3difV3s+Wxo7ez8DboW9528GLOTxHMn679uvrwB1jZOlGkLf/n0Vx1QEIVMhYAgETLMchNR15kttH5b1NZuo0mAU3tlwQpoFdP+iX4SrRTftuq09wZUjj3/Dhg0CVGIwI39c0ECACsKmTZsU9387Zii4ij3BgsOzr+yc+dKQn1eqX/Z+wboVnCVEjYa9tT0yMzOxb+8+i8fYt2efYsxf6gpdDiAFwHYAXwP4Rtws7wo9d+6cWODLwswXqIDz589bvE/BRlVeRbJbFIBcAC0dT3YrKC3HI1/+ik+2ic/RI/3bYPlf+iIsyM++2xcU4ODBg4ptBw8eRGFhoXRZev4fBjAHwJSq35PFzfJx7pSUFPEjz0LSLYSq62WcOUPBVbkejtThsffxO5pr4E4zP8i92ZvMfDswYCGPpwguFgJYBuBjmAUX3333nRhY+EAZWPgAUFVdX8WUw2IpCKmZw7J27VqbJ+E1a9Yo2mvPCUtRll3+mDLEzfYkux25VIixH+/GrtN58PfxwocP9cRr93aBj5f9//aJ/RKRr8tXPAf5unz0Tuwt7aMY5w4B0KHq93lxszy4y87OFv+wcmK9fPmytKm+graaXF24z95gwZHH70gyd11mfjTURN6G+ricobZk5tuBAQt5vLi4OHj7elsMLrx9vaV/sAMHDtgMLOQ9CZmZmci/lm9x3/xr+YoPuLCwMPEPKydh6foq9pywbrUs+4oDWXhgyV5cLryJNiFNkDq7P8b1bGnzNjVt3LjR5nOwefPm6p1VANZBMesC66u2y0RGRop/WDmxtmxZ3cb6CNoseWDiA9i4eaNi28bNG/HAxAfqdDxHOBIsOPL4HZn54khvjKuDO2dpqI+roWPAQh5v48aNqCyvtHhirSyvlE6subm54g2sfFBL18OxD/WJEyeKf1g5CUvXw8FvtzZqxlhTVmHACyuP4PmVR1FeacSIO8Kxes4AdIpwfAXz/fv3i39YeQ727t0LoOq5EiB+msim30IttlX+XA0ZMsRmcDN06FBpX2espeNI8cC6svWt3ZH3laOP//lnn4exzKh4DYxlRrz4wouK/RzpjWmoQ0cN9XE1dAxYyOOtXbtW/MNKDotpSEbKGbHyQW00GqVN6enpNvc9fPiwtCkuLg7Ng5sDa6E8Ca8Dmgc3r9O3W0W9EguPyVK9kkvXb+DBJXvx7YGLUKmAZ5M64rNpCQjy8zHb1x6JiYniH1aeg379+gGQnViNAEYBGF/12wizE6vRaBSDm0gog5tIAAJQWVmpvK86BG22OFI80FH2fGt3uA6PA48/KTkJgregeA0EbwEjRo1Q7Gdvb4y7FQ2rLw31cTUGrMNCbq+2OiQnTpwQ/1gOIEd2Rbjy+sjISPHEuhZmtVWgkg1XoKp3wbRvVdoFVADSxN+m3gVT+64XXAciIJ58Zfd//ep1RR0Wh+saWHlMNe06fQ1PLD+E6zcq0LyJDz58KB6D4kIt72ynpKQkm7VoRo4cCaAq6Vh+YjUJAJAqJh2bHv+xY8fE6+IB3AOgANV1WM7Jrod9wV3N94PdNWusHPNWKL61xwC4AGzZKH5r37BuAwDH6vCYJZNfh/hcVbVV/vi/+OILVOgrlLWAACAAqEitwNKlS/HII49Im+2pQ1KX598TNNTH1RgwYCG3ZW8hrNzc3OpZOiMhnihvANgBQFU91HP16lXxxOoFZWDRBIBQdX2VvLw8cd8KAHtl+1YNc+TnVxeoU8ySqUT1SdgbwPsWPgBNQyLyIKBGvsfgwYOVM4+qToBYK+5nKnJnNApYvON3vLvpFAQB6BCiwYz25YhUFQK4tYAFAA7sP4Deib0VBflCQkNwYP8B6bJZD1eNE+uaNWuk4GbHjh3VgeAYmAWN27dvl46rCO4sFJmTB3f2vlccKR4oV1sg5EjxQHuLll25ckX8w0rQKn+/Ss+blZPwzz//rAhY7ClI53ZFw+pJQ31cjQEDFnIJe74JPzDxAWzbsU2xzZQc+fPmn6Vtbdu2xZEjR4DmAGR5oAgHcFW8HgCysrLE7aMhBjUXAUQDKAGQCly8eFG6aWlpafWMoruhDBjKgZKSEmlfsw/AkKorqkaN5B+A3333nXJIxCQWwDnx+pdeekncJk8QRtVvofp2urIK/PW7w9h8XDxxafOPYcu7L2OLoQJA/VQ5jY2NRV5uHjZv3oy9e/eiX79+UvBhIiUVWzmxypOOr127Vh0Iyh9/VSCYl5cnbYqLi0PzkOa4vuo6YJDt6wU0D1EOtdnTuyGxI2A0sTcQcuRbu73Vay9fvmwzaJXezxBzg1JSUqyehIcPH27+4CDO/LDZm+DAc+Up6lJtmtwDAxa6rew9AUjJkRoA96L6w3pddXKk6YNlzJgx+HHVj+JYvPyDveqDdcyYMQCAsrIy5bf7eCi+3d+8eVO6/4CAAJsBQ9Om1evuxMXFYdjwYdi2bpuYJ9NGPK5qvQpDRwxVfABKib3xALpW3X9biCfsc9XX17bmzv82/YJNNy7hfP4N+HqrEXx+Mw7++BEwzlD7CbsORo4caRaomPTu3dvmibVPnz7SvoGBgdWBYAKqk3UPAigHgoKqk4OloTZfAOOUx71eUD3U5kjvhpTDYiVg3LFjR50Cobp8a68tWGjZsqXN92Dr1q2lff/0pz/hsdmPoWJthdnwnY/GR9G7Yi8pmdrKc+XJQycsze+Z6j3ptk0bcV2Smj+zZ8+2uP/27dst7n/y5Mn6bhq5AXuz8x1Jjjx+/Li4b3KNfUeL+5reS+Xl5eJ+zaFM+Gwm7ldeXi4dU0rQtRIwGAwG5XYVIFQKiuMKleaZkT169BD/+BHATwCOAlhV9QMgPj5eeQMLyZlN7hiELy+F4Hz+DbRs5o9/jWmJ/cved1kSYW3TxX/99VdpX0EQql+DPRCH236B9BrIE5+l94CV45reA3VaoC0eYiDcDWIw1NN8F0eSM+uyoF5tNUCioqJsPq7wcGVC06/7foUPfBTvQR/44Nd9v6IupCAsHsBUAEMATIP0XHny0Ik7FUMj+9V7D8uBAwcUH+a//fYbRo4ciQcffNDm7U6dOqX4dhUaeuvj7+ReHPkmLLEjOXLr1q02992yZQsAsdekuLgY0NXYr1j81aRJE2nTpUtViRJWvjHXLHC2dctWMelWPiQSAmzdouwNioqKsjnUZDoJtW7d2kKCsBeal/4JQffeiwoBGNihBT58KB77d/5c/fhrSc50Bql+jZXn/8CB6nyXoqIi8XFZ6Q2TV9CVcjSsHNd0vSO9G8ePHxf/+BHiLCZADBqrvrrJvyg5mpxp77d2e3sZ1Wq1zcfl7a38+O7ZsyfKy8qxdOlS/Pzzzxg+fHidelZM4uLiMHT4UGxbvU3MzTLxBoaNGOaxvStytQ6JkVup94ClZqDxj3/8A+3atbOazGYSFhaGZs2a1XdzyI04cgJQJEdaSLiUv5+kfBIrH+ym6yMiIpBzNUfMh7AwdCGfJXT9+nWbM4oKCgqUj8vGkIj8cW3atMlmN//PP/+M5OTk6l4LlbjdK6A5Wox/AX5xXQAAPX1zsPQPY+ClVikr/VrIIbH2TdiRVaDt2tfK8y9fCfr69evK3rAaj18esNR2XBNHchL27t1rM2DcvXu3tK+jwzz25qY8OPFBbPtlm+K9smndJrPcLKPRKLZ1PZTvwQ0AVBamgFfp378/wsPD66UHpLKyUkxSlw/LrgUqKyzfN5EzOTWHpby8HCkpKZg7d67F5evl4uPjUVZWhs6dO+Pll19WFJCyRK/XQ6/XS5d1uppfm8ndOHICiIuLw8DBA7Fr1S6zhMuBgwcqTgSCINgMLkzDO9nZ2dXBgqzUOcYASJXNygDg4+NjMznU19dX2pSenm7zuIcPH0ZycjIAWf0WK0Gbqf7LwYMHxcekAjT3dUGLts/D2zsYRn0p8tb+C6oukfBS/0l6roKaBUGXW+N/4BoQ1CzI7KRp7zd8e/fVarU2kzO1Wq10W+kka+XxV1RUKLfbeF3l7O3d0Ov1NgNG+f3XNTnT1rf2zMxMbP15q1kvoyAI2Jq61XwKvACgHMr3oJfY3poBiSOvqz0yMzOxa8cus7ZCAHam7rTcI0rkRE4NWH788UcUFhba7JaMjIzEZ599hoSEBOj1enz99dcYPnw4tm/fjkGDBlm93YIFC/D66687odXkLM7Kzo+IiBBrgVgJLiIiIgDIvr0fAvCDbL9YKK+XqxlnW4i7v/jiC5vH/fzzz/HCCy8AEGdrbNu2zWrQNmrUKPHi+fOAAAQ+fC+at/gjVCpvlBvP49qV+ag8fQUXmlbnumRmZkJXpBOTU2v0GuiKdGYnFkdm1NjTG1BUVGQ5uKs6scqfVylHxUrPmTyHBYAy58ikavaXnL29G1KgaSVg8vFRFtmr7+TM2pKpayb9OuKesfdgb9pexWu1ce1G3D32buzZvcet2kpUF04NWL744gskJydXJ49Z0LFjR3Ts2FG63K9fP1y8eBHvvvuuzYBl3rx5mDt3rnRZp9MhOjq6fhpOTmPvCSAzMxO7du4SZwmNg2KW0K6duxQn4T59+ohd/WFQDomEArhaPUtF+nZfM5G16rK8i724uFgMTrxhNkMFRmWP3pUrV8R9r8DikJA83yUiIsJmr4EpuLpZYUSLsc8iIFQc+io9vh35Gz6G0ErsVZTPaFq0aJHNXoNFixbh/fffl55Xe/OI7O0NkGY+hdZ4/luIz/+1a9ekTVIy8yqY9ZwprpezUt/GktpyEvr37y8mAVsJGAcMGKDY395AyF5SXo6V+5fXVpEvxmmJfAp8ZmYm9u7Za7E3ZG/q3lvrDallSI7odnFawHLhwgVs2bIFP/zwQ+0719C3b1+zZeZr0mg00Gg0dW0euYi9JwCzWUKA4iQs/3YnlT5/GMA1iN/WoyGeMN+v/oZvMBhs5i/Ik8Wlv60EAfJ9pXLzVoaE5L0Gq1atslm8LjU1FYPufgDCiL8iwL8FBEMlrud/geL2PwFjIQU28uD87Nmz4h9WvglL18OxPCJ7v2H7+/uLG6w8/9L1JjYCQYsl9029MSbnLexjp86dO9sMGDt16mTxdvWVnBkeHm4zL0U+80caFvSBWdAOo3KxzkWLFol/WHmtFi9ejH/9618OtVVK/LYy1BcTU/PORI7kRhE5wmkBy5dffomwsDDcfffdDt/20KFDigRIanhqOwHYO0MEkC3SZyXpVLoesBlYWGTHLCWpV8DKkJC818DLq6orIQhiNV6TQPFyibYtxi38BeX+LVBZUoC86/+APvh4dVuTxbbKjxkcHCz+YeWbcIsWLaRNdaryWcs3bCl4svL8y09szZo1EwNIK4GgPNdCOnlb6Y2pOa3XHlK1YyvDTPL3lTMMHjxYvH+thfu/aaHSro2gXe7cuXPiH1ZeKylQdYDZuk8mVXVYaib91ncODVFNTglYjEYjvvzyS8yYMcNs6t28efNw+fJlfPXVVwCADz74AG3atEGXLl2kJN2VK1di5cqVzmgaeRo7uqOvXr1qc5ZOTk6O8gZWAgur9+8P4DKqq+LWICX9mlbVlX8TVimDi+joaMvLCOxUo9mgqfg9agSgr4RXwXlc+uYVGMKuA+fM2yqvCHvx4kWb34TPnz8v7avII9IZgKYASgGvPeZ5RNLyAFaOazq5ZmVl2Xz+L1yoHoPz8/MT/7ASCMp7TaX7t9IbU9vMQ0ukIMfKMFNdgiBHxMXFYdiIYdi2exuEkYL4+pcCql3mRQbbtGkj/mHluYqNrX7j9unTB6t/Wm31tTItVOkIKbi9WeOKqkC7ZnDrULVhojpwSsCyZcsWZGVl4Y9//KPZddnZ2YqS0uXl5XjmmWdw+fJl+Pv7o0uXLli7dq1UnZQaJ6nr3ErXvfzEcuPGDZs5HDduyLoybAQWFocjfkR1vQ7AeqlFG9+E5TPkwsPDq7/hVy0joPYPQosHn4V/lJhI+8e7YrH06adguHHdaluLi4ulYwYGBlZXjLUwzCSvbwQAixYuQp++fZC/pXp9oGahzbD4k8WK/UwVfLdu36o8rjcwbPgw5ZCcjedfPgVcCh6tBKLy4HLXrl02j/vLL784POQgVYc13X+NZRSsDXPUp++/+17M45L1RIxKHmWWx9WlSxdlW03Oi786d+4sbZKWPLDSGyLlGTkgLi5OXPzyer5ZIBoSGqJ47hW5UbLeS8MoGzWWiBzklIBl1KhRlpPnACxdulRx+bnnnsNzzz3njGaQB5O6zithceaJ/Nu1lE9i5ZuooiqtKbDwh9jTEg1pmMWMjXwXeXAj5ajYcf9SHk0hgAmAb5sOCMU8ePuEwVhehmFNr+BvY+/Gh48U2AyC5DNvxo4di1WrV4mBVX9UBy9VK0uPGzdO0aw//+XPKCguUJyECtYV4P/+8n+KOiAA8Pmnn4vBzTXZ4ofNQ/Dvz/4tXa6tKrDZZ4GNHA758+rogn72OHDggM1A+Ndff7W6BEF9sTePS+phstJW+f/AkSNHxD/iYXEVbGk6vQMyMzPF191CIm9+ar4iCJGGnKz0XnpyGX9yH1xLiNzbOIi5G/IP4BrBhY+PjxgIWPkmWnOqKjZAmT/SBJbZ+Hav2M10QrZy//IT9tmzZ6VApGnnJARXzIQKPqgov4xrX8+H173iInVNmjQReyasnKzlVXmlXINmEMvdm1TlZchzDRypAwIAsx6fhcIbhYrgpnBjIR6b/ZjUzS/1IFl5/GY1mGzkcMjVdUE/W06dOmUzhyUzM9PhY9aVXYm8Ntoq1717d2zbvs3qKtjdu3eHoxxJ0G7Xrp3N3ktPLuNP7qPe1xIiqg+KGSohADpU/W5T43pUJZWaci0OQ1rHxTR+L086hQrVlW6frvptgPXVZ618WJsxfROW37+FAmcZGRmAlw+C285BSMUcqOCDG+q9yMbTqMi7gLS0NACyeiE1p2Cfh/J6AMeOHRP/qNnrXzWbWCpHD/tm/pjYu5aOn5+fzccv5a1AFrxYaas8uBk4cKDN4951111wVEhI1RjQw1CujzO5xvVuQAoYHoY4Q8y07lFVW+VrJM2aNUtZC+f9qt8VAISq6x2kSNCWOy/+MgtC5D2CVe8V09pfRPWBPSzk3kxTWq9DUWBMrqKiwmbhMkX1VDt7TRT3b08NChvDV3I6gw8iprwDjVcHCDCg0DsFOu/vgZPijqZlBAoLC20mvMqHhPLz820OX+XnVw/nOFIHRPEN28YaRSqVymZPgLQmDmQJylbaKu+Neuutt2w+r2+99ZbZEHNtpODVyowmdwpYpIBhMYCyqo1HIdYmgjJg2LVrl/i8+gIYBLHX8AaAnQD0dcv3caTQo6PrLhHVBQMWqjeO1F/YuHEj9u/fj379+lnMGZDG561MaZWP30tDHj419vUWL5utueJor4kO0mwa7IT1BN1ahq92Zl6DccSz0GgCYLhZhLz8f6IsLEMRiJhO2FIQYCWJUt4ToVarbQZiZkm/NgIheTKzvWsUSUn0VmbeyJPsAdgdNErT0a0UpFNMV69S23tQenzXalyRV+N6NxAXFweVl0p8T9RIelV5qRSPb9myZeY5T4A4CykV+Prrr+u0EKK9hR7rNF2eyEEMWOiWOVJ/4ffff0div0RlEmdoCA7sP6CYpgnAdoExGX9/f2ndHUsrAMuHJADY1WsDoPrb/RbZNgu9JpIYiF3hpi/p0n+XCgu3nsZ7mzMBTQD02Zm4tnoBDIWys2bVcU1tleq1WEmilJcLcCTpVUpmttIbJQ8E4+Li0Cy4GQqvFSqPmwc0C24mnTAVFYQtzLwpLy+HGTuCxlatWok5J1aCi1atWkmbHFoB2dTDI39fVRVjq1mGwcQVxdC++OILCAZBbGeN4E5IFbB06VIpCJFmgll5XgMDA+vUBnsThJ217AaRHHNY6JYp6i9U5YVs2SnWX6gpsV8i8nX5in3zdfnondhbsd93332n/CZuGhMfA0BQli3Pz8+HYgVg076jxX3lQyIAxF6bhQCWAfgYwGorD8wUMMnzXbxhPd/Fwli/ShOA0Akv491NmRAEwCfrV+Qsex4Gvxpn4aqRClOCcNOmTat7Qi5BXHbgEqQgTJ50K+UyWMk1sFg0LLTG5Rbmu2RmZqLweqF4cpc/Bz5A4fVCKYclMjKyuq27AWQA+KW6rRaX5rDSVrmhQ4dWBxc17h8qZdKtve/B7du328y12LZtm2L/goICjB4zGh07dsSYMWMQFxeH0WNGV1dXdiJ7ZkmZPPbYY+IfVp7X2bNn31JbOnTogOTkZJuBx/JlyzFi0AhFDs2IQXVfd4moJvaw0C1xZG2ajRs32pwmuXnzZml4SJqtYeXDWj6bQ1pXx8q+8nV3HCoL70i+i4Xppz77YxA64yX4NI+Cr7cab4zrghcfegIwVogJpKbCcaUQT/QqZX0VWz0h8mGenJwcm9Nf5atQKxI5LZTRl+caSEGjlanVprVs/Pz8qlcVlvdGVS0+abE0vx3TmqWqtFbuPzs7G4Bj70HpebNzWNCVxdCkZQKsDLNIdVpQVUTOxntAKkLnRPW97hJRTexhoVtiT7KdiZRzYEriPA0gv3rfvXv3SvsqpsrKna9xvZwd39pt9dpYZG++izw59H2gycnBiHjoPfg0j0JlUS6+n9kPk3q3Fk+yQtV9b4ZYmG4zxFL9QnXhNGn9Hys9IfJek4iICGXSa9W3WzQTjylf5kKRl5ICYDuArwF8I26W5xrYGzRKCcA1X5Kqy/LCcQCU05pNba16/HJFRUU279+0AKUj70FpyMvKe2Xo0KHSJsUsqZrF0GSzpJwlLCzM5iwp+ew3Kbi08h6obSHF+mRPbwxRXbCHhW6JNAPEyrdAeU5AYmKi+IeVJE55+XCtVmvzG6NWq1U2xMa+ZsGIvUGI6XHZk+8CiL02Z73RPOqPCOp2LwDg5rl05P30Lrov/oN42dTbY2Var6IqLyAm/MoVw4w0PGQl6VXewxEXFyd+TbkO8zL6aihOMoo1iiw8B6brpaUBrOSFXLx4UdlgFZRLE1hJZpYCISvvLdP1jiR8Hj161OZ7RV5gzdnF0GrLi5F6mFRQ9rJpxLbLZ3RJlWytvAfqUumWyN0wYKFbYjQabXbxy2foJCUlwUfjg4rrFWYnSx+Nj2K2kJeXl80prWbF4CwNn1QNSZixd6oyYHWWkiVem4PR4t7n4ddK7Kov3PMtinZ/AwhG852t9EaYbTNAuebQDpid2DMyMsQ/rCS9yk/CX3zxhTj8ZWWoS57IKX2Dt/IcmK4vLS0VN1gZupGuNzG9rptrHLPGa1VaWmpzRpNp+MyR9ZGkwn1RsDj7Sr6ytbOKodmbICzN6BJQXcFYBamCsXxGU48ePcQ/rLwH4uPj69RWInfCgIVuSbt27WxWLq05xFChr7CYw1KRWqHINZAv7meJ2aq6pm/4ncX7RRMAx2BWRt+hnhgH8l000V0QOu4FeAU0h1EoRV72e7j566+WG2+jN0JxXFMXv/zEbqHKaUFBQXXQKJ+CXZUXI086/uabqrEf07Ccqdekjbg5JSVFCljy8vJsPgem10itVouBq5WeK3kdFsk41FrBuGnTpjandjdt2lTaZO/6SFJvjJXZV2Y9HTZyaOrK3ryY1q1bVwcp8grGVT0s8nWPoqKi7F57i8hTMWChW2JaIG/bL7WvPutIcamSkhKbJ3ZFIi1Q/cF+SLat6oPdbD/TOL+JhSBA2reWpFtBEBB45zg0H/pHqNReKFedxzXNfFS2uyKe6Cyd2Ow9Caog5i1YmKotf1zStOWaSa9VvRaCpW4mK8Ny8twgaUaNlefAVBW3efPmYlBkpedKGlqSi4GVKeDV7rzzTqxatcpqcNG7d/XMMnvXR2revHl1cHcXxOAuF1JwJ18o0hnF0BxJEJZ6L1UARqG6GNwumPVeSl8crAwfsQ4KNQQMWOjWqQChUlD0BAje5idJR3INDh8+bPPEfuiQPDJB9Um8Zl6GpZ4TK+P8FtnIdynVV+L5lUcQPPzP4mXDduQHfAxBpTfb1+JxLfRwKAionqoN1D5LyY7eoG7dumHrtq2Wc1hUQNeuXaV9a0t6lVfbtTV0Y5Edw3K9e/eu7jWwsD5Onz59ADi2PlLLli3FNgpQBndVJ3ZpNWc4pxiaI0GQVBBQ/h4ApGJw8vwwaVhs5xYY+huk4MXrsBdGDGMdFGoYOEuIbklmZia2btlqXscjBNi6Zav5TAobsx7kapuqbJacauoJkM3msDr75wKU6xOdt/rwrM4m8W4ehfsW/YI1R7IhGCpRsHkJ8s6+Wx2syPa1aDmUtWC+sbKfjYBJQd4TooXt2U927jt+/HjxDyvPwYQJEwBU5ZIIEGekpKJ6hopWPKZiqjZg93tAWtTRlG9iOm6UeFxTD4Mj6yNJQyem4Pbpqt9V7ZIPnZiCAK+NXoq2em3yQlJyUp2CAEfW56ltFfCaFZylOih7AOwFsId1UKhhYQ8L1crWbIbff//d5tCFxboeVoZkTHU9AFmippVvt2YBC2B1NoeCozksFvJC/Dv0RYu75yLzagnCAjU4svhZ6K+cEHNm7D2ulR4Os30dSRC2I7j57bffbO579OhRaVPXrl1tPl+m3hhp6KIIFmvLSCdeEwF2rbtUW76JWQ+HHc9VbcsY1Kx0a29pens5UhHW0R4e1kGhho4BC1llz2yGK1euVHdby3s3RgNIVSbHSnU9rBQtkxeDk3JYrJwsLX5rtzKbwyyR1Y6TpbSvfOhApUazodOg7f0gAKBPm2AsnBKP8JdPiNfbO0vJjtwY6TFZG2aRHVdKerVyYpPK/EMWPFyAxanK8jL+Ug6LoUbbvMX7//nnn/HII4/Ax8dH/LYvQJkgXDXMYrHc/TjUmnSrOLmPsn5yHzx4sM3nSr7cgKO9Fs4IAuwNgupa7r5Dhw4MVKhBYsBCVtkzm+Hy5cvizlZ6N+QL30kJnXYkfEonTiu9MWaJpKZ8F3nQlAzL+R52nCzFBkEaOlDHBKFF5XPwb9ITAKA78COWvfUpfLzU1fv6AuhVdRs1xOmnelgOWuwZ6hEgJtLWEgT5+PhAX663GtzJA4YpU6aI5edXweJU5WnTpkmbhgwZgpRlKeJ1w1Cd9LlDvK2pNH5ISAguXb4k3veoGvuplAXOFI9fC5tJt4Bs9k+q9dk/psTvrdu3mgVWw4YPu6VeC5P6DAIcCYLqu4eHyJMxYCGLFLMZalb5lM1mSExMtNm7IS8GJwU3Vhazu3TJQlW2GlXd0cR8F4k9Q0KoamOF7HIbK/tV9YT4do1DaPkL8PYNg9FYhvw1H+HGiZ3w8fpcuW8zKKefWpt9BNg31GOaJXUnxORZNYCDMJuqbTAYbNahMRiqI5OBAwfaTNC96667pH1btWpl3hsESEmfLVu2BCCbfmxlP/n0Y4ceP4BZj89C4Y1CRSBU+EshHpv9mGIK8PfffS+e2OW9gSOT6q3XwhnsCYLkPV5EjR0DFrLI3iqfsbGxNmfzyNcwuXz5ss2pyvI1byRZtVw2sXdICLDaw2NJ09gkBOtnQgUfVKgu45rhLVScsNAIFYBCO+/fzqEeKd/nlxptrREESXVOwmo8rlBxX3kdlB07dtQ6Vdl0El27dq14vZXeoDVr1mDkyJHVs4Ws7CdfKFCtVsMoGK32BqlV1W21OAUYgCHAfApwQ+21eHDig9j2yzbF+2rTuk14YOIDiunaRI0BAxayyN4qn45M0ywvL7cZ3Oj1euUx7JyqC8Cx2iZ2JLyqvH0RPHImmnqPAgDcUO9Fnu/7EE5ZSPZ15P5N+1ophmbWVivJzPK2BgcHi2sQWZmubbUOilwb813CwsLEP6z0hpiul3oBrOwn7yWQarZYySMKDqlua13qoNjTI+EpyamOTNcmagw4rZmsk5+EtVW/k6E4WUq9IlamaZpVpAUcn6rrD7GnJwC1L1RoYVFFi8e0MaX3YsENhE95B027j4JgNOD6tS9xrewtCEduVK8qbO3+7XlcgFiNV85SHCSgugaHqa2jYfb4pdopVqZrd+9eHUXUtvifPEFVqoOyDsopyFVBk6kOilSMzcpUZXnAJOXTPAExEO1W9fuJGtfDsSnABQUFGD1mNDp27IgxY8YgLi4Oo8eMVvTu1OTui/Q5Ml2bqDFgDwtZZO+328OHD9uczXPo0CFlqXfA6jdxi+X4N0B5MreVw2LvUI+NwGJH5jU8+e0haCLaw3CjCHm730HZocPKY9YMNkzsnYLsyLRmO4KgiIgIm69BRESEtG9cXByGjRiGbeu2QdAJ0nRtS5WJs7KyLOfGVPWGXLggRhK+vr42p6trNBpFW69evSo+5viqH0Ba80a+sjQAuwvS2Vvu3iM5MrWdqAFjwEIW2TuboqioyObJSqqWCtlidlZOrGaL5KkgzmQxLfxmSjp1Sm0TFbT9JuKRL3+FIAD6K5m4tmoBDOXXlLVFdtm4f3vyUgC7pjXXNlVZnpcSEhJic/pxSEgI5D7/9HOzdXeCQ4Px78/+DYtCoQwEW0CRRxMbG4sjR45YHZKSr3nzwAMP4PCRw1YXy7z//vulfX///Xebw2emoNmRcveexJHp2kSNAQMWsk4FqNcDRtmHpXoDYJR9u5UCEisnK3nA4u3tDYPeYDW4sbgCswoWF34zY0cQYHpMNU8Aqp8D0OL+v6JJ+z4QBODhPq3xj4n3AYYK8eQory1iKdfEdP92TEGW1NJz0qZNG5w9d9ZqcCdPZu7SRVwdGvdCDFrOAmhbdf+pQOfOnRXHlmbeyIK7wo3mM2+kE2YhLAZtphPmY489Jq75YwquaqwUPHv2bOmYkZGR4uPRwuJimaaZR4D9heOcseaPO3BkujZRY8AcFrLI9O12YCwUZdEHxgIQxJMAAAQGBoo3sJI/IV9Mzt+/ao6ylanK0vVyFTUuV5rvIrEnh0Q+xPE+4LO7DSIfel8MVirL8c793bFgQjcxWAHEk+UcAFOqfve0ct+m2U+jAIyv+u0D22vpyJ1XXgwKClIWuat6/lEpPgatVivtq/gmrgYwouq3hW/ipt4IQ5JBkRtjGGXAxvUbFUspmE6YqIQYtP1Y9btSecKMjY21mcNicaZYIcQgaHzV7yJxX3ndHkVp/EsQZ0FdMi+N70iui6f5/rvvkTQySbEtaWQSvv/uexe1iMh12MPSgNgqoe8o00mgoES53XTZdBKQiotZ6QkYOnSodFtpSMjKzCOLQ0JWpkBbXSPIgbH+gM5DEDz6cah9/FBZdBXXUudj4rtnlPdvZeG9Wod5AKkOiRk7ho/8/Pyqi9F1gpg34w/gJICyquurxMXFYcDAAdi9e7dZD8/AQQPrvGI2YF99E2noxqvG420CKbg1HTMxMbE6aJT3XFXlxcjr9gD2TUF2p9oq9c1TZjQR3Q4MWBoAe0roOyouLg4tQkNw9Gq+Irg4uhZoERoifWhGRUXZLFomX0xOWsfFyvRfeaVbAI5NFVbBal6EWXCh9kbzoX9CUMJYAMDNc2nIW/0ujGU1yv3LezhMrJXxB+zq4QkPDxeTTq0kspoSZBMTE7Fv3z6xB+SQ/AAAblad+GV8fX2h8lVBGCRIBdZUO1Vmw2zOWJ9GOuZoiEHaRYhLLpSIj1F+zNjYWPGPcbBYbVjeG2Pv/QOeVVulLlhun4hDQg2CYobE0wAmAFt2ijMk6iozMxN51/ItTgHOu5YvDR1IJ6uwGgcIFX/JT1ZSfoKVE7s8f0FizzAPoMyLMA2fBMEsuPBqGozw6fOlYKXwl+XIPfi6ebBSF7UM8wCyQKPGeoCmy3379gUAzJo1qzqRWD50UghAVXV9FdOK2cIYQUxQ7gmgPyAkC2YrZtd1BWJbU4AVxyyBOIxWYvmYih4e+RBiG3GzaajRkfsHqgObzMxMrFu3DpmZmdiwbkOdA3Yicj8MWDycIzkJjrBn6ACQnayKvRQnVq8S85PV2LFikGDtxH7vvfdKm6SpsFb2lU+VBaBcLbiqDdBBkUOiie6KyBkfwq9FZxiFEuTm/R1F8cuAHjWjB5nQGpctLIujVqtt1iuRz+hp1qxZ1Y1qHkT8ZcpNiYuLQ99+fcVEXnn+SDnQt19fh4d55JYvW44Rg0YogrsRg26tN8LeY0rPhZXX1eJCiQ5w99oqRFR3HBLycM6aIeHI0IHUHb/ednf8rFmz8OFHH1rNd5H3GkhBgLUS7uoaZ3xTD4s8L0JWM+Xfu84i/KG3oFJ7oTzvHK4Vz0dly2yr04+9vb1Raais7uEwzZDZKe7r7VX9r9OmTRucPXvW6jBPbNtYaZOULNsaytlGVZflybTr1qwzzx8Zbb4+jjOGeRxl7zGNRqPN4buaqyUTEZkwYPFwdV19tjaOJDLae7KKi4vDXf364pd9+8zyXe6q0WsQExODkydPWp0CLc918PX1RXlFucXgQuXrh9AxT+PNtSegUnuh5Ng2FGxZCKFMtgxAVWARHR0tbWrfvn31/dcMgq5C0dZu3bqJAYsV3bp1k/6+++678fHHH1udqnvPPfdI+zryvNYl6dQZeRG1HbNdu3Y2pzV78oweInIyoZ69+uqrAsSPJOknPDzc5m22b98u9OrVS9BoNEJsbKywePFih++3qKhIACAUFRXVtekeKyk5SfAK8BJwHwQ8DQH3QfAK8BKSkpNu6bgFBQVCUnKS4rVMSk4SCgoKbumYY2occ4yFY27YsEGACgI0EDASAsZX/dZAgArCpk2bpH1HjBghHstP+b7zjmgpRP7pEyHm+TVCu3lrhUff/cbiftCIv7/88kvpmNOmTROvexoC5kDAlKrfT4v7Tp8+Xdp36tSp4r4RNY4bbr6vIAhCSItg8T5lrxc0EEJaBN/S81rfr5WzSO9X2etaH+9XIvJM9p6/nRKwdOnSRcjOzpZ+cnNzre5/9uxZoUmTJsKTTz4pHD9+XPj8888FHx8f4fvvv3fofhtzwOLsk1VmZqawbt06ITMzs16OZ+8xAwIDBKhrBAFqCAGBAYr95syZUx1cTIOAIRD8/9xPiH7uOyHm+TVC3HPfCwfP5wufffaZGAT5QUB/COhX9dtPDII+//xz6ZgbNmwQjzkBAl6T/dwntkMeMDkSXAmC+J5vERqieFwtQkOEs2fP3pbn1dU8KbgiIuez9/ztlCEhb29vxfoltixZsgStW7fGBx98AAC44447cPDgQbz77ruKMt1knbNrNbhi6AAAjh4+it6JvZF/rbqEfEhICA7sP6DYT7GqcDc1mrWeBm3lgwCAsqyjmHKHCgkx9yMdqC71Lq+ea6F6bVJSEpoFN0Ph2kKzHJpmwc0wcuRIxb7aZlqxqq98+EgNaJtpFfsC4tTea7l52Lx5M/bu3Yt+/fqZ7VNXnjD9lbVFiKgunBKwnD59GlFRUdBoNEhMTMT8+fPRtm1bi/vu3bsXo0aNUmxLSkrCF198gYqKCvNy7VX0ej30+uo8BJ1OV38PwEN5wsnKEbGxsciz48Q+ceJEvPK3V6DeFoQWLZ+Hf5MeAABdeiqub12KR06cACCr+Golf6Tm2izpB9PFgClVFjCFmgdMAHAo7ZBdwZXcyJEj6y1Q8UQN7f1KRM5V7wFLYmIivvrqK8TFxeHq1at488030b9/fxw7dsxsETYAyMnJURQXA8TiWpWVlcjLyzNfvbXKggUL8Prrr9d388kN1XZij4uLQ5/kibgckwzvJqEwlt9E/voPceP0bgwcUF3pVbFScbJQvZbQevOVigH7AyZH9yUiIsepBEGwVrezXpSWlqJdu3Z47rnnMHfuXLPr4+Li8Ic//AHz5s2Ttv3yyy8YMGAAsrOzrQ4tWephiY6ORlFRkWL9GmrYBEHAN79m4bXVx1BhEFCRfwnXUt9CRf5Fi9V+r1+/bj5V+BarAhMRUd3pdDpotdpaz99On9YcEBCAbt26WS1gFhERgZycHMW23NxceHt7W+yRMdFoNObFw6hRKasw4OUff8P3aZcAAEldwvFYr3bIntDaal4E8yeIiDyT0wMWvV6PEydOYODAgRav79evH3766SfFtk2bNuHOO++0mr9CdLHgBmampOHYFR3UKuDZpE6YObgtVCoVenbpVOvtmT9BRORZ6r00/zPPPIMdO3bg3Llz2L9/Px544AHodDrMmDEDADBv3jxMnz5d2n/mzJm4cOEC5s6dixMnTuA///kPvvjiCzzzzDP13TRqILafysU9H+/GsSs6BAf44us/JeKxIe3MF08kIqIGo957WC5duoSHH34YeXl5CA0NRd++fbFv3z7ExIi147Ozs5GVlSXtHxsbi3Xr1uHpp5/GJ598gqioKHz00Uec0kxmjEYBC7edwftbMiEIQI/oZlg8pReimvm7umlERORkTk+6vV3sTdohz1R0owJPf5eBrSdzAQCTE1vj1bGdofH2cnHLiIjoVrhN0i3RrTp+RYeZKWnIKrgBX2813hzfFRPvjK79hkRE1GAwYCG3lnroEub9cBRlFUa0au6PJVMT0LWltvYbEhFRg8KAhdxSeaURb649jq/2XgAADIoLxYeTeqJ5gK+LW0ZERK7AgIXcTk5RGWYtS0N6ViEA4Ilh7fHkiDh4qTkLiIiosWLAQm5l39l8PP5NOvJKyhHo540PJvXE8DvCa78hERE1aAxYyC0IgoB/7zqHf2w4CYNRQKeIQHw6LQExIQGubhoREbkBBizkciX6Sjz//RGsPZoNALgvviXm39cN/r6cskxERCIGLORSZ3JLMDMlDWdyS+CtVuFvYztjWt8YVq0lIiIFBizkMht+y8Yz/zuCEn0lwoM0WDSlFxJigl3dLCIickMMWOi2qzQY8c9Np/DpjrMAgMTYYHw8OR5hgX4ubhkREbkrBix0W+WV6DHnm0PYezYfAPDngbF4fnQneHvV+zqcRETUgDBgodvmUNZ1zFqWjuyiMjTx9cI/H+iBu7tHurpZRETkARiwkNMJgoBl+7Pw+k/HUGEQ0DY0AJ9OTUCH8EBXN42IiDwEAxZyqrIKA15K/Q0r0y8BAEZ3icA/H+yOQD8fF7eMiIg8CQMWcpqLBTfw6NdpOJ6tg1oFPD+6E/4yqC2nLBMRkcMYsJBTbDuVi6e+zUDRzQqEBPji44fj0b99C1c3i4iIPBQDFqpXRqOAj7aexoc/n4YgAD2im2HxlF6Iaubv6qYREZEHY8BC9aboRgWeWnEI205dAwBMSWyNv43tDI03S+wTEdGtYcBC9eLYlSI8lpKOrIIb0Hir8eb4rnjwzmhXN4uIiBoIBix0y35Iv4R5PxyFvtKI6GB/LJ6SgK4tta5uFhERNSAMWKjOyiuNeGPNcXy97wIAYEjHUHwwqSeaNfF1ccuIiKihYcBCdZJddBOzlqXjUFYhAODJ4R3w5PAOUKs5ZZmIiOofAxZy2N7f8zFneTrySsoR5OeNDx7qiWGdwl3dLCIiasAYsJDdBEHA57vO4u0Np2AwCrgjMghLpvZCTEiAq5tGREQNHAMWskuJvhLPfX8Y647mAAAmxLfEW/d1g78vpywTEZHzMWChWp3JLcGjXx/E79dK4eOlwt/u6YypfWNYYp+IiG4bBixk0/qj2Xjmf4dRWm5AeJAGi6YkICGmuaubRUREjQwDFrKo0mDEPzeewqc7zwIA+rYNxscP90JooMbFLSMiosaIAQuZySvR4/Fv0rHvbAEA4C+D2uK5pI7w9lK7uGVERNRYMWAhhfSs65iVko4cXRkCfL3wzwd7YEy3SFc3i4iIGjkGLARAnLKcsj8Lf//pGCoMAtqFBuDTaQloHxbo6qYRERGh3vv4FyxYgN69eyMwMBBhYWEYP348Tp06ZfM227dvh0qlMvs5efJkfTePLLhZbsBf/3cYr/z4GyoMApK7RmDV4wMYrBARkduo9x6WHTt2YPbs2ejduzcqKyvx0ksvYdSoUTh+/DgCAmwXGDt16hSCgoKky6GhofXdPKohK/8GHk1Jw4lsHdQq4IXkTvjzwLacskxERG6l3gOWDRs2KC5/+eWXCAsLQ1paGgYNGmTztmFhYWjWrFl9N4ms2HYyF09+ewi6skqEBPji48nx6N+uhaubRUREZMbp0z6KiooAAMHBwbXuGx8fj8jISAwfPhzbtm2zua9er4dOp1P8kH2MRgHvb87EH/97ALqySvSMboY1TwxgsEJERG7LqQGLIAiYO3cuBgwYgK5du1rdLzIyEp999hlWrlyJH374AR07dsTw4cOxc+dOq7dZsGABtFqt9BMdHe2Mh9DgFN4ox5/+ewAf/nwaggBM6xuDFY/2RaTW39VNIyIiskolCILgrIPPnj0ba9euxe7du9GqVSuHbjt27FioVCqsXr3a4vV6vR56vV66rNPpEB0djaKiIkUeDFX77XIRHluWhosFN6HxVmP+fd1wf4JjrwsREVF90ul00Gq1tZ6/nTatec6cOVi9ejV27tzpcLACAH379kVKSorV6zUaDTQaVl211/dpl/BS6lHoK42IDvbHkqkJ6BKldXWziIiI7FLvAYsgCJgzZw5SU1Oxfft2xMbG1uk4hw4dQmQkC5bdKn2lAW+sOY6UfVkAgKEdQ/HBpHhom/i4uGVERET2q/eAZfbs2fjmm2+watUqBAYGIicnBwCg1Wrh7y/mScybNw+XL1/GV199BQD44IMP0KZNG3Tp0gXl5eVISUnBypUrsXLlyvpuXqOSXXQTj6WkI+NiIVQq4MnhHfDEsA5QqzllmYiIPEu9ByyLFy8GAAwZMkSx/csvv8QjjzwCAMjOzkZWVpZ0XXl5OZ555hlcvnwZ/v7+6NKlC9auXYsxY8bUd/MajT2/52HON4eQX1qOID9vfPhQPIZ2CnN1s4iIiOrEqUm3t5O9STsNnSAI+GznWby94SSMAnBHZBA+nZqA1iFNXN00IiIiMy5PuqXbr0RfiWf/dxjrfxOH4Sb0aom3xneDv6+Xi1tGRER0axiwNBBncovx6Ndp+P1aKXy8VPjb2C6YmtiaJfaJiKhBYMDSAKw9ko3nvj+M0nIDIoL8sGhqL/Rq3dzVzSIiIqo3DFg8WKXBiHc2nsJnO88CAPq2DcbCyb3Qoinr0xARUcPCgMVDXSvWY87ydOw7WwAAeHRQWzyb1BHeXk5fHoqIiOi2Y8DigdIuXMfsZenI0ZUhwNcL7z7YA8ndWGSPiIgaLgYsHkQQBKTsu4C/rzmOCoOAdqEB+HTanWgf1tTVTSMiInIqBiwe4ma5AS+lHsUPhy4DAMZ0i8A7D/RAUw1fQiIiavh4tvMAF/JLMTMlHSeydVCrgBeSO+HPA9tyyjIRETUaDFjc3NaTV/HUtxnQlVWiRVNffPRwPPq3a+HqZhEREd1WDFjclMEo4MOfT+Ojn08DAOJbN8OiKb0QqfV3ccuIiIhuPwYsbqjwRjme/DYDOzKvAQCm94vBy3d3hq83pywTEVHjxIDFzfx2uQgzU9Jw6fpNaLzVmH9fN9yf0MrVzSIiInIpBixu5Pu0S3gp9Sj0lUa0Dm6CxVN7oUuU1tXNIiIicjkGLG5AX2nA3386jmX7swAAwzqF4f2JPaFt4uPilhEREbkHBiwull10E4+lpCPjYiFUKuCp4XGYM6w91GpOWSYiIjJhwOJCe87kYc7yQ8gvLYfW3wcfPNQTQzuGubpZREREbocBiwsIgoBPd57FOxtOwigAnSODsGRqAlqHNHF104iIiNwSA5bbrLisAs/+7wg2HMsBANzfqxXeuq8r/Hy8XNwyIiIi98WA5TY6fbUYj6ak4ey1Uvh4qfDq2C6YktiaJfaJiIhqwYDlNll7JBvPfn8YN8oNiNT6YdGUXohv3dzVzSIiIvIIDFicrNJgxNsbTuLzXecAAP3ahuDjyfFo0VTj4pYRERF5DgYsTnStWI/Hv0nH/nMFAIBHB7fFs6M6wtuLJfaJiIgcwYDFSdIuFGDWsnRc1ekR4OuFdx/sgeRuka5uFhERkUdiwFLPBEHA1/su4I01x1FhENA+rCmWTE1A+7Cmrm4aERGRx2LAUo9ulhvwYupRpB66DAC4u1sk3n6gO5pq+DQTERHdCp5J68mF/FI8+nUaTuYUw0utwrzkTvjTgFhOWSYiIqoHDFjqwc8nruKpFRkoLqtEi6a+WDi5F/q2DXF1s4iIiBoMBiy3wGAU8OGWTHy09QwAoFfrZlg0JQERWj8Xt4yIiKhhYcBSR4U3yvHktxnYkXkNADC9XwxevrszfL05ZZmIiKi+MWCpg98uF2FmShouXb8JPx815t/XDRN6tXJ1s4iIiBosp3UHLFq0CLGxsfDz80NCQgJ27dplc/8dO3YgISEBfn5+aNu2LZYsWeKspt2S7w5exP2L9+DS9ZtoHdwEPzx2F4MVIiIiJ3NKwLJixQo89dRTeOmll3Do0CEMHDgQycnJyMrKsrj/uXPnMGbMGAwcOBCHDh3Ciy++iCeeeAIrV650RvPqRF9pwLwfjuK5749AX2nE8E5h+OnxAegcFeTqphERETV4KkEQhPo+aGJiInr16oXFixdL2+644w6MHz8eCxYsMNv/+eefx+rVq3HixAlp28yZM3H48GHs3bvXrvvU6XTQarUoKipCUFD9BhFXCm/isZQ0HL5UBJUKeHpEHB4f2h5qNacsExER3Qp7z9/13sNSXl6OtLQ0jBo1SrF91KhR2LNnj8Xb7N2712z/pKQkHDx4EBUVFRZvo9frodPpFD/O8MuZPNzz8W4cvlQErb8PvnykN54Y3oHBChER0W1U7wFLXl4eDAYDwsPDFdvDw8ORk5Nj8TY5OTkW96+srEReXp7F2yxYsABarVb6iY6Orp8HIHOjvBJPfnsIBaXl6BIVhDVzBmBIx7B6vx8iIiKyzWlJtzUrvAqCYLPqq6X9LW03mTdvHoqKiqSfixcv3mKLzTXx9cb7k3pi4p2tsPKx/ogOblLv90FERES1q/dpzS1atICXl5dZb0pubq5ZL4pJRESExf29vb0REmK5YqxGo4FGo6mfRtswsEMoBnYIdfr9EBERkXX13sPi6+uLhIQEbN68WbF98+bN6N+/v8Xb9OvXz2z/TZs24c4774SPj099N5GIiIg8jFOGhObOnYt///vf+M9//oMTJ07g6aefRlZWFmbOnAlAHM6ZPn26tP/MmTNx4cIFzJ07FydOnMB//vMffPHFF3jmmWec0TwiIiLyME6pdDtp0iTk5+fj73//O7Kzs9G1a1esW7cOMTExAIDs7GxFTZbY2FisW7cOTz/9ND755BNERUXho48+wv333++M5hEREZGHcUodFldwZh0WIiIicg6X1WEhIiIiqm8MWIiIiMjtMWAhIiIit8eAhYiIiNweAxYiIiJyewxYiIiIyO0xYCEiIiK3x4CFiIiI3B4DFiIiInJ7TinN7wqmgr06nc7FLSEiIiJ7mc7btRXebzABS3FxMQAgOjraxS0hIiIiRxUXF0Or1Vq9vsGsJWQ0GnHlyhUEBgZCpVLV23F1Oh2io6Nx8eJFrlHkAfh6eQ6+Vp6Dr5Vn8bTXSxAEFBcXIyoqCmq19UyVBtPDolar0apVK6cdPygoyCNeeBLx9fIcfK08B18rz+JJr5etnhUTJt0SERGR22PAQkRERG6PAUstNBoNXn31VWg0Glc3hezA18tz8LXyHHytPEtDfb0aTNItERERNVzsYSEiIiK3x4CFiIiI3B4DFiIiInJ7DFiIiIjI7TFgqcWiRYsQGxsLPz8/JCQkYNeuXa5uEtXw2muvQaVSKX4iIiJc3SyqsnPnTowdOxZRUVFQqVT48ccfFdcLgoDXXnsNUVFR8Pf3x5AhQ3Ds2DHXNLaRq+21euSRR8z+1/r27euaxjZyCxYsQO/evREYGIiwsDCMHz8ep06dUuzT0P63GLDYsGLFCjz11FN46aWXcOjQIQwcOBDJycnIyspyddOohi5duiA7O1v6OXr0qKubRFVKS0vRo0cPLFy40OL177zzDv71r39h4cKFOHDgACIiIjBy5EhpfTC6fWp7rQBg9OjRiv+1devW3cYWksmOHTswe/Zs7Nu3D5s3b0ZlZSVGjRqF0tJSaZ8G978lkFV9+vQRZs6cqdjWqVMn4YUXXnBRi8iSV199VejRo4erm0F2ACCkpqZKl41GoxARESH84x//kLaVlZUJWq1WWLJkiQtaSCY1XytBEIQZM2YI48aNc0l7yLbc3FwBgLBjxw5BEBrm/xZ7WKwoLy9HWloaRo0apdg+atQo7Nmzx0WtImtOnz6NqKgoxMbG4qGHHsLZs2dd3SSyw7lz55CTk6P4P9NoNBg8eDD/z9zU9u3bERYWhri4OPz5z39Gbm6uq5tEAIqKigAAwcHBABrm/xYDFivy8vJgMBgQHh6u2B4eHo6cnBwXtYosSUxMxFdffYWNGzfi888/R05ODvr374/8/HxXN41qYfpf4v+ZZ0hOTsayZcuwdetWvPfeezhw4ACGDRsGvV7v6qY1aoIgYO7cuRgwYAC6du0KoGH+bzWY1ZqdRaVSKS4LgmC2jVwrOTlZ+rtbt27o168f2rVrh//+97+YO3euC1tG9uL/mWeYNGmS9HfXrl1x5513IiYmBmvXrsWECRNc2LLG7fHHH8eRI0ewe/dus+sa0v8We1isaNGiBby8vMwi0dzcXLOIldxLQEAAunXrhtOnT7u6KVQL02wu/p95psjISMTExPB/zYXmzJmD1atXY9u2bWjVqpW0vSH+bzFgscLX1xcJCQnYvHmzYvvmzZvRv39/F7WK7KHX63HixAlERka6uilUi9jYWERERCj+z8rLy7Fjxw7+n3mA/Px8XLx4kf9rLiAIAh5//HH88MMP2Lp1K2JjYxXXN8T/LQ4J2TB37lxMmzYNd955J/r164fPPvsMWVlZmDlzpqubRjLPPPMMxo4di9atWyM3NxdvvvkmdDodZsyY4eqmEYCSkhKcOXNGunzu3DlkZGQgODgYrVu3xlNPPYX58+ejQ4cO6NChA+bPn48mTZpg8uTJLmx142TrtQoODsZrr72G+++/H5GRkTh//jxefPFFtGjRAvfdd58LW904zZ49G9988w1WrVqFwMBAqSdFq9XC398fKpWq4f1vuXSOkgf45JNPhJiYGMHX11fo1auXNGWM3MekSZOEyMhIwcfHR4iKihImTJggHDt2zNXNoirbtm0TAJj9zJgxQxAEcfrlq6++KkRERAgajUYYNGiQcPToUdc2upGy9VrduHFDGDVqlBAaGir4+PgIrVu3FmbMmCFkZWW5utmNkqXXCYDw5ZdfSvs0tP8tlSAIwu0Pk4iIiIjsxxwWIiIicnsMWIiIiMjtMWAhIiIit8eAhYiIiNweAxYiIiJyewxYiIiIyO0xYCEiIiK3x4CFiIiI3B4DFiIiInJ7DFiIiIjI7TFgISIiIrfHgIWIiIjc3v8DeuEi6vKaUFIAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
@@ -5057,53 +5047,53 @@
"output_type": "stream",
"text": [
"Epoch 1/2500\n",
- "16/16 [==============================] - 4s 48ms/step - loss: 2.8634 - distribution_lambda_2_loss: 0.8054 - distribution_lambda_3_loss: 1.5916 - distribution_lambda_4_loss: 0.4664 - val_loss: 2.8347 - val_distribution_lambda_2_loss: 0.7680 - val_distribution_lambda_3_loss: 1.5980 - val_distribution_lambda_4_loss: 0.4687\n",
+ "16/16 [==============================] - 4s 49ms/step - loss: 2.8318 - distribution_lambda_2_loss: 0.7818 - distribution_lambda_3_loss: 1.5811 - distribution_lambda_4_loss: 0.4689 - val_loss: 2.7879 - val_distribution_lambda_2_loss: 0.7363 - val_distribution_lambda_3_loss: 1.5952 - val_distribution_lambda_4_loss: 0.4564\n",
"Epoch 2/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8597 - distribution_lambda_2_loss: 0.7987 - distribution_lambda_3_loss: 1.5933 - distribution_lambda_4_loss: 0.4677 - val_loss: 2.8521 - val_distribution_lambda_2_loss: 0.7818 - val_distribution_lambda_3_loss: 1.6000 - val_distribution_lambda_4_loss: 0.4702\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8259 - distribution_lambda_2_loss: 0.7828 - distribution_lambda_3_loss: 1.5794 - distribution_lambda_4_loss: 0.4637 - val_loss: 2.7892 - val_distribution_lambda_2_loss: 0.7348 - val_distribution_lambda_3_loss: 1.5957 - val_distribution_lambda_4_loss: 0.4587\n",
"Epoch 3/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8666 - distribution_lambda_2_loss: 0.8008 - distribution_lambda_3_loss: 1.5961 - distribution_lambda_4_loss: 0.4697 - val_loss: 2.8481 - val_distribution_lambda_2_loss: 0.7775 - val_distribution_lambda_3_loss: 1.5995 - val_distribution_lambda_4_loss: 0.4710\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8180 - distribution_lambda_2_loss: 0.7852 - distribution_lambda_3_loss: 1.5736 - distribution_lambda_4_loss: 0.4592 - val_loss: 2.7863 - val_distribution_lambda_2_loss: 0.7288 - val_distribution_lambda_3_loss: 1.5961 - val_distribution_lambda_4_loss: 0.4614\n",
"Epoch 4/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8654 - distribution_lambda_2_loss: 0.7965 - distribution_lambda_3_loss: 1.5933 - distribution_lambda_4_loss: 0.4757 - val_loss: 2.8613 - val_distribution_lambda_2_loss: 0.7764 - val_distribution_lambda_3_loss: 1.6108 - val_distribution_lambda_4_loss: 0.4742\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8057 - distribution_lambda_2_loss: 0.7726 - distribution_lambda_3_loss: 1.5718 - distribution_lambda_4_loss: 0.4614 - val_loss: 2.7873 - val_distribution_lambda_2_loss: 0.7291 - val_distribution_lambda_3_loss: 1.5960 - val_distribution_lambda_4_loss: 0.4622\n",
"Epoch 5/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8774 - distribution_lambda_2_loss: 0.8120 - distribution_lambda_3_loss: 1.5895 - distribution_lambda_4_loss: 0.4760 - val_loss: 2.8584 - val_distribution_lambda_2_loss: 0.7727 - val_distribution_lambda_3_loss: 1.6103 - val_distribution_lambda_4_loss: 0.4753\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8367 - distribution_lambda_2_loss: 0.8118 - distribution_lambda_3_loss: 1.5704 - distribution_lambda_4_loss: 0.4545 - val_loss: 2.7873 - val_distribution_lambda_2_loss: 0.7271 - val_distribution_lambda_3_loss: 1.5995 - val_distribution_lambda_4_loss: 0.4607\n",
"Epoch 6/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8389 - distribution_lambda_2_loss: 0.7969 - distribution_lambda_3_loss: 1.5813 - distribution_lambda_4_loss: 0.4607 - val_loss: 2.8543 - val_distribution_lambda_2_loss: 0.7756 - val_distribution_lambda_3_loss: 1.6048 - val_distribution_lambda_4_loss: 0.4739\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8330 - distribution_lambda_2_loss: 0.7990 - distribution_lambda_3_loss: 1.5720 - distribution_lambda_4_loss: 0.4620 - val_loss: 2.7894 - val_distribution_lambda_2_loss: 0.7287 - val_distribution_lambda_3_loss: 1.5997 - val_distribution_lambda_4_loss: 0.4611\n",
"Epoch 7/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8535 - distribution_lambda_2_loss: 0.8020 - distribution_lambda_3_loss: 1.5900 - distribution_lambda_4_loss: 0.4615 - val_loss: 2.8538 - val_distribution_lambda_2_loss: 0.7707 - val_distribution_lambda_3_loss: 1.6086 - val_distribution_lambda_4_loss: 0.4744\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8403 - distribution_lambda_2_loss: 0.7903 - distribution_lambda_3_loss: 1.5759 - distribution_lambda_4_loss: 0.4741 - val_loss: 2.7913 - val_distribution_lambda_2_loss: 0.7276 - val_distribution_lambda_3_loss: 1.6007 - val_distribution_lambda_4_loss: 0.4630\n",
"Epoch 8/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8733 - distribution_lambda_2_loss: 0.8144 - distribution_lambda_3_loss: 1.5922 - distribution_lambda_4_loss: 0.4667 - val_loss: 2.8623 - val_distribution_lambda_2_loss: 0.7693 - val_distribution_lambda_3_loss: 1.6135 - val_distribution_lambda_4_loss: 0.4796\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8326 - distribution_lambda_2_loss: 0.7955 - distribution_lambda_3_loss: 1.5704 - distribution_lambda_4_loss: 0.4666 - val_loss: 2.7994 - val_distribution_lambda_2_loss: 0.7282 - val_distribution_lambda_3_loss: 1.6056 - val_distribution_lambda_4_loss: 0.4656\n",
"Epoch 9/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8270 - distribution_lambda_2_loss: 0.7838 - distribution_lambda_3_loss: 1.5817 - distribution_lambda_4_loss: 0.4615 - val_loss: 2.8680 - val_distribution_lambda_2_loss: 0.7716 - val_distribution_lambda_3_loss: 1.6155 - val_distribution_lambda_4_loss: 0.4809\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8316 - distribution_lambda_2_loss: 0.7943 - distribution_lambda_3_loss: 1.5766 - distribution_lambda_4_loss: 0.4606 - val_loss: 2.8037 - val_distribution_lambda_2_loss: 0.7307 - val_distribution_lambda_3_loss: 1.6069 - val_distribution_lambda_4_loss: 0.4662\n",
"Epoch 10/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8374 - distribution_lambda_2_loss: 0.7969 - distribution_lambda_3_loss: 1.5798 - distribution_lambda_4_loss: 0.4606 - val_loss: 2.8625 - val_distribution_lambda_2_loss: 0.7748 - val_distribution_lambda_3_loss: 1.6095 - val_distribution_lambda_4_loss: 0.4782\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8247 - distribution_lambda_2_loss: 0.7831 - distribution_lambda_3_loss: 1.5749 - distribution_lambda_4_loss: 0.4667 - val_loss: 2.8047 - val_distribution_lambda_2_loss: 0.7321 - val_distribution_lambda_3_loss: 1.6060 - val_distribution_lambda_4_loss: 0.4666\n",
"Epoch 11/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8299 - distribution_lambda_2_loss: 0.7855 - distribution_lambda_3_loss: 1.5782 - distribution_lambda_4_loss: 0.4662 - val_loss: 2.8628 - val_distribution_lambda_2_loss: 0.7741 - val_distribution_lambda_3_loss: 1.6107 - val_distribution_lambda_4_loss: 0.4780\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8082 - distribution_lambda_2_loss: 0.7760 - distribution_lambda_3_loss: 1.5706 - distribution_lambda_4_loss: 0.4616 - val_loss: 2.8034 - val_distribution_lambda_2_loss: 0.7312 - val_distribution_lambda_3_loss: 1.6054 - val_distribution_lambda_4_loss: 0.4668\n",
"Epoch 12/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8149 - distribution_lambda_2_loss: 0.7766 - distribution_lambda_3_loss: 1.5745 - distribution_lambda_4_loss: 0.4637 - val_loss: 2.8626 - val_distribution_lambda_2_loss: 0.7738 - val_distribution_lambda_3_loss: 1.6120 - val_distribution_lambda_4_loss: 0.4768\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8241 - distribution_lambda_2_loss: 0.7949 - distribution_lambda_3_loss: 1.5667 - distribution_lambda_4_loss: 0.4624 - val_loss: 2.8054 - val_distribution_lambda_2_loss: 0.7326 - val_distribution_lambda_3_loss: 1.6052 - val_distribution_lambda_4_loss: 0.4676\n",
"Epoch 13/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8214 - distribution_lambda_2_loss: 0.7819 - distribution_lambda_3_loss: 1.5710 - distribution_lambda_4_loss: 0.4685 - val_loss: 2.8787 - val_distribution_lambda_2_loss: 0.7779 - val_distribution_lambda_3_loss: 1.6187 - val_distribution_lambda_4_loss: 0.4822\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8073 - distribution_lambda_2_loss: 0.7710 - distribution_lambda_3_loss: 1.5735 - distribution_lambda_4_loss: 0.4629 - val_loss: 2.8044 - val_distribution_lambda_2_loss: 0.7309 - val_distribution_lambda_3_loss: 1.6057 - val_distribution_lambda_4_loss: 0.4678\n",
"Epoch 14/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8526 - distribution_lambda_2_loss: 0.8043 - distribution_lambda_3_loss: 1.5790 - distribution_lambda_4_loss: 0.4693 - val_loss: 2.8902 - val_distribution_lambda_2_loss: 0.7785 - val_distribution_lambda_3_loss: 1.6275 - val_distribution_lambda_4_loss: 0.4842\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8313 - distribution_lambda_2_loss: 0.7867 - distribution_lambda_3_loss: 1.5764 - distribution_lambda_4_loss: 0.4681 - val_loss: 2.8076 - val_distribution_lambda_2_loss: 0.7304 - val_distribution_lambda_3_loss: 1.6086 - val_distribution_lambda_4_loss: 0.4687\n",
"Epoch 15/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8415 - distribution_lambda_2_loss: 0.7869 - distribution_lambda_3_loss: 1.5878 - distribution_lambda_4_loss: 0.4669 - val_loss: 2.8766 - val_distribution_lambda_2_loss: 0.7740 - val_distribution_lambda_3_loss: 1.6202 - val_distribution_lambda_4_loss: 0.4824\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8342 - distribution_lambda_2_loss: 0.7911 - distribution_lambda_3_loss: 1.5761 - distribution_lambda_4_loss: 0.4669 - val_loss: 2.8109 - val_distribution_lambda_2_loss: 0.7330 - val_distribution_lambda_3_loss: 1.6093 - val_distribution_lambda_4_loss: 0.4685\n",
"Epoch 16/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8406 - distribution_lambda_2_loss: 0.7953 - distribution_lambda_3_loss: 1.5821 - distribution_lambda_4_loss: 0.4632 - val_loss: 2.8767 - val_distribution_lambda_2_loss: 0.7705 - val_distribution_lambda_3_loss: 1.6236 - val_distribution_lambda_4_loss: 0.4826\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8313 - distribution_lambda_2_loss: 0.7839 - distribution_lambda_3_loss: 1.5782 - distribution_lambda_4_loss: 0.4692 - val_loss: 2.8061 - val_distribution_lambda_2_loss: 0.7323 - val_distribution_lambda_3_loss: 1.6060 - val_distribution_lambda_4_loss: 0.4678\n",
"Epoch 17/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8358 - distribution_lambda_2_loss: 0.7966 - distribution_lambda_3_loss: 1.5799 - distribution_lambda_4_loss: 0.4593 - val_loss: 2.8819 - val_distribution_lambda_2_loss: 0.7741 - val_distribution_lambda_3_loss: 1.6259 - val_distribution_lambda_4_loss: 0.4819\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8055 - distribution_lambda_2_loss: 0.7820 - distribution_lambda_3_loss: 1.5624 - distribution_lambda_4_loss: 0.4610 - val_loss: 2.8131 - val_distribution_lambda_2_loss: 0.7344 - val_distribution_lambda_3_loss: 1.6096 - val_distribution_lambda_4_loss: 0.4691\n",
"Epoch 18/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8207 - distribution_lambda_2_loss: 0.7761 - distribution_lambda_3_loss: 1.5793 - distribution_lambda_4_loss: 0.4654 - val_loss: 2.8873 - val_distribution_lambda_2_loss: 0.7781 - val_distribution_lambda_3_loss: 1.6307 - val_distribution_lambda_4_loss: 0.4786\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8066 - distribution_lambda_2_loss: 0.7833 - distribution_lambda_3_loss: 1.5616 - distribution_lambda_4_loss: 0.4617 - val_loss: 2.8163 - val_distribution_lambda_2_loss: 0.7315 - val_distribution_lambda_3_loss: 1.6135 - val_distribution_lambda_4_loss: 0.4713\n",
"Epoch 19/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8326 - distribution_lambda_2_loss: 0.7955 - distribution_lambda_3_loss: 1.5738 - distribution_lambda_4_loss: 0.4633 - val_loss: 2.8983 - val_distribution_lambda_2_loss: 0.7804 - val_distribution_lambda_3_loss: 1.6367 - val_distribution_lambda_4_loss: 0.4811\n",
+ "16/16 [==============================] - 0s 5ms/step - loss: 2.8113 - distribution_lambda_2_loss: 0.7828 - distribution_lambda_3_loss: 1.5644 - distribution_lambda_4_loss: 0.4641 - val_loss: 2.8174 - val_distribution_lambda_2_loss: 0.7303 - val_distribution_lambda_3_loss: 1.6121 - val_distribution_lambda_4_loss: 0.4749\n",
"Epoch 20/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8445 - distribution_lambda_2_loss: 0.7884 - distribution_lambda_3_loss: 1.5865 - distribution_lambda_4_loss: 0.4695 - val_loss: 2.8826 - val_distribution_lambda_2_loss: 0.7820 - val_distribution_lambda_3_loss: 1.6184 - val_distribution_lambda_4_loss: 0.4822\n",
+ "16/16 [==============================] - 0s 5ms/step - loss: 2.8021 - distribution_lambda_2_loss: 0.7805 - distribution_lambda_3_loss: 1.5682 - distribution_lambda_4_loss: 0.4534 - val_loss: 2.8219 - val_distribution_lambda_2_loss: 0.7342 - val_distribution_lambda_3_loss: 1.6140 - val_distribution_lambda_4_loss: 0.4737\n",
"Epoch 21/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8374 - distribution_lambda_2_loss: 0.7835 - distribution_lambda_3_loss: 1.5854 - distribution_lambda_4_loss: 0.4685 - val_loss: 2.8846 - val_distribution_lambda_2_loss: 0.7769 - val_distribution_lambda_3_loss: 1.6229 - val_distribution_lambda_4_loss: 0.4848\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7970 - distribution_lambda_2_loss: 0.7893 - distribution_lambda_3_loss: 1.5631 - distribution_lambda_4_loss: 0.4445 - val_loss: 2.8205 - val_distribution_lambda_2_loss: 0.7343 - val_distribution_lambda_3_loss: 1.6152 - val_distribution_lambda_4_loss: 0.4710\n",
"Epoch 22/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8400 - distribution_lambda_2_loss: 0.7948 - distribution_lambda_3_loss: 1.5790 - distribution_lambda_4_loss: 0.4662 - val_loss: 2.8908 - val_distribution_lambda_2_loss: 0.7782 - val_distribution_lambda_3_loss: 1.6314 - val_distribution_lambda_4_loss: 0.4812\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8084 - distribution_lambda_2_loss: 0.7879 - distribution_lambda_3_loss: 1.5619 - distribution_lambda_4_loss: 0.4587 - val_loss: 2.8244 - val_distribution_lambda_2_loss: 0.7349 - val_distribution_lambda_3_loss: 1.6153 - val_distribution_lambda_4_loss: 0.4742\n",
"Epoch 23/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8472 - distribution_lambda_2_loss: 0.7877 - distribution_lambda_3_loss: 1.5840 - distribution_lambda_4_loss: 0.4755 - val_loss: 2.8999 - val_distribution_lambda_2_loss: 0.7811 - val_distribution_lambda_3_loss: 1.6391 - val_distribution_lambda_4_loss: 0.4797\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8083 - distribution_lambda_2_loss: 0.7804 - distribution_lambda_3_loss: 1.5672 - distribution_lambda_4_loss: 0.4607 - val_loss: 2.8277 - val_distribution_lambda_2_loss: 0.7357 - val_distribution_lambda_3_loss: 1.6169 - val_distribution_lambda_4_loss: 0.4751\n",
"Epoch 24/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8225 - distribution_lambda_2_loss: 0.7702 - distribution_lambda_3_loss: 1.5871 - distribution_lambda_4_loss: 0.4652 - val_loss: 2.8981 - val_distribution_lambda_2_loss: 0.7794 - val_distribution_lambda_3_loss: 1.6362 - val_distribution_lambda_4_loss: 0.4825\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7848 - distribution_lambda_2_loss: 0.7655 - distribution_lambda_3_loss: 1.5584 - distribution_lambda_4_loss: 0.4608 - val_loss: 2.8250 - val_distribution_lambda_2_loss: 0.7350 - val_distribution_lambda_3_loss: 1.6157 - val_distribution_lambda_4_loss: 0.4743\n",
"Epoch 25/2500\n"
]
},
@@ -5111,53 +5101,53 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8163 - distribution_lambda_2_loss: 0.7790 - distribution_lambda_3_loss: 1.5738 - distribution_lambda_4_loss: 0.4635 - val_loss: 2.8908 - val_distribution_lambda_2_loss: 0.7764 - val_distribution_lambda_3_loss: 1.6334 - val_distribution_lambda_4_loss: 0.4810\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8392 - distribution_lambda_2_loss: 0.8073 - distribution_lambda_3_loss: 1.5790 - distribution_lambda_4_loss: 0.4529 - val_loss: 2.8279 - val_distribution_lambda_2_loss: 0.7351 - val_distribution_lambda_3_loss: 1.6155 - val_distribution_lambda_4_loss: 0.4772\n",
"Epoch 26/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8344 - distribution_lambda_2_loss: 0.7955 - distribution_lambda_3_loss: 1.5742 - distribution_lambda_4_loss: 0.4646 - val_loss: 2.8899 - val_distribution_lambda_2_loss: 0.7748 - val_distribution_lambda_3_loss: 1.6302 - val_distribution_lambda_4_loss: 0.4848\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8193 - distribution_lambda_2_loss: 0.7785 - distribution_lambda_3_loss: 1.5722 - distribution_lambda_4_loss: 0.4686 - val_loss: 2.8286 - val_distribution_lambda_2_loss: 0.7346 - val_distribution_lambda_3_loss: 1.6168 - val_distribution_lambda_4_loss: 0.4772\n",
"Epoch 27/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8272 - distribution_lambda_2_loss: 0.7940 - distribution_lambda_3_loss: 1.5721 - distribution_lambda_4_loss: 0.4612 - val_loss: 2.8895 - val_distribution_lambda_2_loss: 0.7721 - val_distribution_lambda_3_loss: 1.6310 - val_distribution_lambda_4_loss: 0.4864\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8056 - distribution_lambda_2_loss: 0.7836 - distribution_lambda_3_loss: 1.5648 - distribution_lambda_4_loss: 0.4572 - val_loss: 2.8276 - val_distribution_lambda_2_loss: 0.7344 - val_distribution_lambda_3_loss: 1.6166 - val_distribution_lambda_4_loss: 0.4767\n",
"Epoch 28/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8510 - distribution_lambda_2_loss: 0.7977 - distribution_lambda_3_loss: 1.5849 - distribution_lambda_4_loss: 0.4685 - val_loss: 2.8974 - val_distribution_lambda_2_loss: 0.7757 - val_distribution_lambda_3_loss: 1.6330 - val_distribution_lambda_4_loss: 0.4887\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7948 - distribution_lambda_2_loss: 0.7694 - distribution_lambda_3_loss: 1.5693 - distribution_lambda_4_loss: 0.4562 - val_loss: 2.8227 - val_distribution_lambda_2_loss: 0.7330 - val_distribution_lambda_3_loss: 1.6146 - val_distribution_lambda_4_loss: 0.4750\n",
"Epoch 29/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8032 - distribution_lambda_2_loss: 0.7804 - distribution_lambda_3_loss: 1.5614 - distribution_lambda_4_loss: 0.4614 - val_loss: 2.9068 - val_distribution_lambda_2_loss: 0.7785 - val_distribution_lambda_3_loss: 1.6408 - val_distribution_lambda_4_loss: 0.4874\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7822 - distribution_lambda_2_loss: 0.7681 - distribution_lambda_3_loss: 1.5583 - distribution_lambda_4_loss: 0.4558 - val_loss: 2.8274 - val_distribution_lambda_2_loss: 0.7346 - val_distribution_lambda_3_loss: 1.6192 - val_distribution_lambda_4_loss: 0.4736\n",
"Epoch 30/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8399 - distribution_lambda_2_loss: 0.7932 - distribution_lambda_3_loss: 1.5785 - distribution_lambda_4_loss: 0.4683 - val_loss: 2.8928 - val_distribution_lambda_2_loss: 0.7740 - val_distribution_lambda_3_loss: 1.6321 - val_distribution_lambda_4_loss: 0.4866\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8158 - distribution_lambda_2_loss: 0.7959 - distribution_lambda_3_loss: 1.5680 - distribution_lambda_4_loss: 0.4518 - val_loss: 2.8341 - val_distribution_lambda_2_loss: 0.7354 - val_distribution_lambda_3_loss: 1.6206 - val_distribution_lambda_4_loss: 0.4781\n",
"Epoch 31/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8046 - distribution_lambda_2_loss: 0.7735 - distribution_lambda_3_loss: 1.5688 - distribution_lambda_4_loss: 0.4623 - val_loss: 2.8941 - val_distribution_lambda_2_loss: 0.7781 - val_distribution_lambda_3_loss: 1.6307 - val_distribution_lambda_4_loss: 0.4853\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8014 - distribution_lambda_2_loss: 0.7811 - distribution_lambda_3_loss: 1.5648 - distribution_lambda_4_loss: 0.4555 - val_loss: 2.8387 - val_distribution_lambda_2_loss: 0.7360 - val_distribution_lambda_3_loss: 1.6238 - val_distribution_lambda_4_loss: 0.4788\n",
"Epoch 32/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8254 - distribution_lambda_2_loss: 0.7854 - distribution_lambda_3_loss: 1.5765 - distribution_lambda_4_loss: 0.4635 - val_loss: 2.8962 - val_distribution_lambda_2_loss: 0.7771 - val_distribution_lambda_3_loss: 1.6321 - val_distribution_lambda_4_loss: 0.4870\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7946 - distribution_lambda_2_loss: 0.7758 - distribution_lambda_3_loss: 1.5592 - distribution_lambda_4_loss: 0.4596 - val_loss: 2.8409 - val_distribution_lambda_2_loss: 0.7346 - val_distribution_lambda_3_loss: 1.6271 - val_distribution_lambda_4_loss: 0.4792\n",
"Epoch 33/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8149 - distribution_lambda_2_loss: 0.7800 - distribution_lambda_3_loss: 1.5666 - distribution_lambda_4_loss: 0.4683 - val_loss: 2.8964 - val_distribution_lambda_2_loss: 0.7785 - val_distribution_lambda_3_loss: 1.6312 - val_distribution_lambda_4_loss: 0.4867\n",
+ "16/16 [==============================] - 0s 5ms/step - loss: 2.8158 - distribution_lambda_2_loss: 0.7904 - distribution_lambda_3_loss: 1.5677 - distribution_lambda_4_loss: 0.4577 - val_loss: 2.8404 - val_distribution_lambda_2_loss: 0.7335 - val_distribution_lambda_3_loss: 1.6267 - val_distribution_lambda_4_loss: 0.4803\n",
"Epoch 34/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8012 - distribution_lambda_2_loss: 0.7745 - distribution_lambda_3_loss: 1.5747 - distribution_lambda_4_loss: 0.4520 - val_loss: 2.9002 - val_distribution_lambda_2_loss: 0.7763 - val_distribution_lambda_3_loss: 1.6351 - val_distribution_lambda_4_loss: 0.4889\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7946 - distribution_lambda_2_loss: 0.7796 - distribution_lambda_3_loss: 1.5635 - distribution_lambda_4_loss: 0.4515 - val_loss: 2.8403 - val_distribution_lambda_2_loss: 0.7361 - val_distribution_lambda_3_loss: 1.6240 - val_distribution_lambda_4_loss: 0.4802\n",
"Epoch 35/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8321 - distribution_lambda_2_loss: 0.7890 - distribution_lambda_3_loss: 1.5795 - distribution_lambda_4_loss: 0.4636 - val_loss: 2.8999 - val_distribution_lambda_2_loss: 0.7754 - val_distribution_lambda_3_loss: 1.6353 - val_distribution_lambda_4_loss: 0.4892\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8137 - distribution_lambda_2_loss: 0.7850 - distribution_lambda_3_loss: 1.5682 - distribution_lambda_4_loss: 0.4606 - val_loss: 2.8423 - val_distribution_lambda_2_loss: 0.7361 - val_distribution_lambda_3_loss: 1.6249 - val_distribution_lambda_4_loss: 0.4813\n",
"Epoch 36/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8133 - distribution_lambda_2_loss: 0.7899 - distribution_lambda_3_loss: 1.5676 - distribution_lambda_4_loss: 0.4558 - val_loss: 2.8999 - val_distribution_lambda_2_loss: 0.7779 - val_distribution_lambda_3_loss: 1.6336 - val_distribution_lambda_4_loss: 0.4885\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8254 - distribution_lambda_2_loss: 0.7804 - distribution_lambda_3_loss: 1.5803 - distribution_lambda_4_loss: 0.4647 - val_loss: 2.8395 - val_distribution_lambda_2_loss: 0.7368 - val_distribution_lambda_3_loss: 1.6214 - val_distribution_lambda_4_loss: 0.4813\n",
"Epoch 37/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8430 - distribution_lambda_2_loss: 0.7943 - distribution_lambda_3_loss: 1.5770 - distribution_lambda_4_loss: 0.4717 - val_loss: 2.9023 - val_distribution_lambda_2_loss: 0.7807 - val_distribution_lambda_3_loss: 1.6317 - val_distribution_lambda_4_loss: 0.4899\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8213 - distribution_lambda_2_loss: 0.7868 - distribution_lambda_3_loss: 1.5731 - distribution_lambda_4_loss: 0.4614 - val_loss: 2.8386 - val_distribution_lambda_2_loss: 0.7363 - val_distribution_lambda_3_loss: 1.6209 - val_distribution_lambda_4_loss: 0.4814\n",
"Epoch 38/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8264 - distribution_lambda_2_loss: 0.7900 - distribution_lambda_3_loss: 1.5731 - distribution_lambda_4_loss: 0.4633 - val_loss: 2.9073 - val_distribution_lambda_2_loss: 0.7790 - val_distribution_lambda_3_loss: 1.6352 - val_distribution_lambda_4_loss: 0.4932\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8045 - distribution_lambda_2_loss: 0.7780 - distribution_lambda_3_loss: 1.5652 - distribution_lambda_4_loss: 0.4612 - val_loss: 2.8439 - val_distribution_lambda_2_loss: 0.7346 - val_distribution_lambda_3_loss: 1.6246 - val_distribution_lambda_4_loss: 0.4847\n",
"Epoch 39/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8115 - distribution_lambda_2_loss: 0.7816 - distribution_lambda_3_loss: 1.5664 - distribution_lambda_4_loss: 0.4635 - val_loss: 2.9025 - val_distribution_lambda_2_loss: 0.7739 - val_distribution_lambda_3_loss: 1.6362 - val_distribution_lambda_4_loss: 0.4924\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7939 - distribution_lambda_2_loss: 0.7592 - distribution_lambda_3_loss: 1.5697 - distribution_lambda_4_loss: 0.4650 - val_loss: 2.8463 - val_distribution_lambda_2_loss: 0.7363 - val_distribution_lambda_3_loss: 1.6265 - val_distribution_lambda_4_loss: 0.4835\n",
"Epoch 40/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8347 - distribution_lambda_2_loss: 0.7921 - distribution_lambda_3_loss: 1.5796 - distribution_lambda_4_loss: 0.4631 - val_loss: 2.9042 - val_distribution_lambda_2_loss: 0.7739 - val_distribution_lambda_3_loss: 1.6392 - val_distribution_lambda_4_loss: 0.4912\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7927 - distribution_lambda_2_loss: 0.7809 - distribution_lambda_3_loss: 1.5560 - distribution_lambda_4_loss: 0.4558 - val_loss: 2.8425 - val_distribution_lambda_2_loss: 0.7361 - val_distribution_lambda_3_loss: 1.6265 - val_distribution_lambda_4_loss: 0.4799\n",
"Epoch 41/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.7897 - distribution_lambda_2_loss: 0.7750 - distribution_lambda_3_loss: 1.5617 - distribution_lambda_4_loss: 0.4530 - val_loss: 2.9112 - val_distribution_lambda_2_loss: 0.7757 - val_distribution_lambda_3_loss: 1.6417 - val_distribution_lambda_4_loss: 0.4938\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7871 - distribution_lambda_2_loss: 0.7685 - distribution_lambda_3_loss: 1.5573 - distribution_lambda_4_loss: 0.4613 - val_loss: 2.8440 - val_distribution_lambda_2_loss: 0.7353 - val_distribution_lambda_3_loss: 1.6274 - val_distribution_lambda_4_loss: 0.4813\n",
"Epoch 42/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8251 - distribution_lambda_2_loss: 0.7946 - distribution_lambda_3_loss: 1.5715 - distribution_lambda_4_loss: 0.4591 - val_loss: 2.9113 - val_distribution_lambda_2_loss: 0.7758 - val_distribution_lambda_3_loss: 1.6388 - val_distribution_lambda_4_loss: 0.4967\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8238 - distribution_lambda_2_loss: 0.7881 - distribution_lambda_3_loss: 1.5737 - distribution_lambda_4_loss: 0.4620 - val_loss: 2.8522 - val_distribution_lambda_2_loss: 0.7362 - val_distribution_lambda_3_loss: 1.6299 - val_distribution_lambda_4_loss: 0.4861\n",
"Epoch 43/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8015 - distribution_lambda_2_loss: 0.7707 - distribution_lambda_3_loss: 1.5683 - distribution_lambda_4_loss: 0.4625 - val_loss: 2.9087 - val_distribution_lambda_2_loss: 0.7814 - val_distribution_lambda_3_loss: 1.6368 - val_distribution_lambda_4_loss: 0.4905\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7937 - distribution_lambda_2_loss: 0.7708 - distribution_lambda_3_loss: 1.5711 - distribution_lambda_4_loss: 0.4518 - val_loss: 2.8491 - val_distribution_lambda_2_loss: 0.7373 - val_distribution_lambda_3_loss: 1.6271 - val_distribution_lambda_4_loss: 0.4848\n",
"Epoch 44/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8238 - distribution_lambda_2_loss: 0.7827 - distribution_lambda_3_loss: 1.5784 - distribution_lambda_4_loss: 0.4626 - val_loss: 2.9051 - val_distribution_lambda_2_loss: 0.7797 - val_distribution_lambda_3_loss: 1.6353 - val_distribution_lambda_4_loss: 0.4901\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8023 - distribution_lambda_2_loss: 0.7787 - distribution_lambda_3_loss: 1.5687 - distribution_lambda_4_loss: 0.4549 - val_loss: 2.8461 - val_distribution_lambda_2_loss: 0.7375 - val_distribution_lambda_3_loss: 1.6263 - val_distribution_lambda_4_loss: 0.4822\n",
"Epoch 45/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8192 - distribution_lambda_2_loss: 0.7826 - distribution_lambda_3_loss: 1.5739 - distribution_lambda_4_loss: 0.4627 - val_loss: 2.9100 - val_distribution_lambda_2_loss: 0.7799 - val_distribution_lambda_3_loss: 1.6398 - val_distribution_lambda_4_loss: 0.4904\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.8141 - distribution_lambda_2_loss: 0.7850 - distribution_lambda_3_loss: 1.5684 - distribution_lambda_4_loss: 0.4607 - val_loss: 2.8474 - val_distribution_lambda_2_loss: 0.7375 - val_distribution_lambda_3_loss: 1.6259 - val_distribution_lambda_4_loss: 0.4839\n",
"Epoch 46/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8152 - distribution_lambda_2_loss: 0.7811 - distribution_lambda_3_loss: 1.5690 - distribution_lambda_4_loss: 0.4651 - val_loss: 2.9097 - val_distribution_lambda_2_loss: 0.7803 - val_distribution_lambda_3_loss: 1.6381 - val_distribution_lambda_4_loss: 0.4914\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7816 - distribution_lambda_2_loss: 0.7693 - distribution_lambda_3_loss: 1.5624 - distribution_lambda_4_loss: 0.4499 - val_loss: 2.8509 - val_distribution_lambda_2_loss: 0.7389 - val_distribution_lambda_3_loss: 1.6266 - val_distribution_lambda_4_loss: 0.4854\n",
"Epoch 47/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8123 - distribution_lambda_2_loss: 0.7940 - distribution_lambda_3_loss: 1.5635 - distribution_lambda_4_loss: 0.4548 - val_loss: 2.9142 - val_distribution_lambda_2_loss: 0.7813 - val_distribution_lambda_3_loss: 1.6402 - val_distribution_lambda_4_loss: 0.4927\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7844 - distribution_lambda_2_loss: 0.7717 - distribution_lambda_3_loss: 1.5564 - distribution_lambda_4_loss: 0.4562 - val_loss: 2.8501 - val_distribution_lambda_2_loss: 0.7381 - val_distribution_lambda_3_loss: 1.6265 - val_distribution_lambda_4_loss: 0.4855\n",
"Epoch 48/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.8110 - distribution_lambda_2_loss: 0.7743 - distribution_lambda_3_loss: 1.5747 - distribution_lambda_4_loss: 0.4620 - val_loss: 2.9071 - val_distribution_lambda_2_loss: 0.7818 - val_distribution_lambda_3_loss: 1.6357 - val_distribution_lambda_4_loss: 0.4896\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7855 - distribution_lambda_2_loss: 0.7730 - distribution_lambda_3_loss: 1.5588 - distribution_lambda_4_loss: 0.4536 - val_loss: 2.8556 - val_distribution_lambda_2_loss: 0.7367 - val_distribution_lambda_3_loss: 1.6320 - val_distribution_lambda_4_loss: 0.4869\n",
"Epoch 49/2500\n"
]
},
@@ -5165,11 +5155,15 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "16/16 [==============================] - 0s 5ms/step - loss: 2.7890 - distribution_lambda_2_loss: 0.7829 - distribution_lambda_3_loss: 1.5567 - distribution_lambda_4_loss: 0.4494 - val_loss: 2.9067 - val_distribution_lambda_2_loss: 0.7840 - val_distribution_lambda_3_loss: 1.6363 - val_distribution_lambda_4_loss: 0.4863\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7817 - distribution_lambda_2_loss: 0.7642 - distribution_lambda_3_loss: 1.5567 - distribution_lambda_4_loss: 0.4608 - val_loss: 2.8588 - val_distribution_lambda_2_loss: 0.7381 - val_distribution_lambda_3_loss: 1.6305 - val_distribution_lambda_4_loss: 0.4902\n",
"Epoch 50/2500\n",
- "16/16 [==============================] - 0s 5ms/step - loss: 2.8199 - distribution_lambda_2_loss: 0.7951 - distribution_lambda_3_loss: 1.5685 - distribution_lambda_4_loss: 0.4563 - val_loss: 2.9212 - val_distribution_lambda_2_loss: 0.7861 - val_distribution_lambda_3_loss: 1.6447 - val_distribution_lambda_4_loss: 0.4905\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7974 - distribution_lambda_2_loss: 0.7894 - distribution_lambda_3_loss: 1.5578 - distribution_lambda_4_loss: 0.4502 - val_loss: 2.8586 - val_distribution_lambda_2_loss: 0.7389 - val_distribution_lambda_3_loss: 1.6301 - val_distribution_lambda_4_loss: 0.4896\n",
"Epoch 51/2500\n",
- "16/16 [==============================] - 0s 4ms/step - loss: 2.7944 - distribution_lambda_2_loss: 0.7789 - distribution_lambda_3_loss: 1.5600 - distribution_lambda_4_loss: 0.4556 - val_loss: 2.9107 - val_distribution_lambda_2_loss: 0.7799 - val_distribution_lambda_3_loss: 1.6433 - val_distribution_lambda_4_loss: 0.4875\n"
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7851 - distribution_lambda_2_loss: 0.7654 - distribution_lambda_3_loss: 1.5580 - distribution_lambda_4_loss: 0.4616 - val_loss: 2.8592 - val_distribution_lambda_2_loss: 0.7364 - val_distribution_lambda_3_loss: 1.6328 - val_distribution_lambda_4_loss: 0.4899\n",
+ "Epoch 52/2500\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7983 - distribution_lambda_2_loss: 0.7811 - distribution_lambda_3_loss: 1.5583 - distribution_lambda_4_loss: 0.4589 - val_loss: 2.8614 - val_distribution_lambda_2_loss: 0.7400 - val_distribution_lambda_3_loss: 1.6351 - val_distribution_lambda_4_loss: 0.4863\n",
+ "Epoch 53/2500\n",
+ "16/16 [==============================] - 0s 4ms/step - loss: 2.7862 - distribution_lambda_2_loss: 0.7638 - distribution_lambda_3_loss: 1.5650 - distribution_lambda_4_loss: 0.4574 - val_loss: 2.8565 - val_distribution_lambda_2_loss: 0.7386 - val_distribution_lambda_3_loss: 1.6317 - val_distribution_lambda_4_loss: 0.4862\n"
]
}
],
@@ -5276,13 +5270,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.0907258632073451\n",
- "0.3000061215338464\n"
+ "0.11125466234353387\n",
+ "0.31109318411388387\n"
]
},
{
"data": {
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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
@@ -5294,13 +5288,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.06439535566000021\n",
- "0.21148355905367822\n"
+ "0.04536015796966664\n",
+ "0.23520934604862653\n"
]
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
@@ -6010,29 +6004,29 @@
" \n",
" \n",
" \n",
- " | Falcone | \n",
+ " Berisha | \n",
" 1.0 | \n",
" 90 | \n",
"
\n",
" \n",
- " | Gendrey | \n",
+ " Ebuehi | \n",
" 1.0 | \n",
" 90 | \n",
"
\n",
" \n",
- " | Baschirotto | \n",
- " 1.0 | \n",
- " 90 | \n",
- "
\n",
- " \n",
- " | Pongracic | \n",
+ " Ismajli | \n",
" 1.0 | \n",
" 80 | \n",
"
\n",
" \n",
- " | Gallo | \n",
- " 0.6 | \n",
- " 60 | \n",
+ " Luperto | \n",
+ " 1.0 | \n",
+ " 90 | \n",
+ "
\n",
+ " \n",
+ " | Bastoni S. | \n",
+ " 1.0 | \n",
+ " 85 | \n",
"
\n",
" \n",
" | ... | \n",
@@ -6040,51 +6034,51 @@
" ... | \n",
"
\n",
" \n",
- " | Oristanio | \n",
+ " Ikone' | \n",
" 0.0 | \n",
- " 50 | \n",
+ " 30 | \n",
"
\n",
" \n",
- " | Jankto | \n",
+ " Barak | \n",
" 0.0 | \n",
- " 15 | \n",
+ " 40 | \n",
"
\n",
" \n",
- " | Mancosu | \n",
+ " Sottil | \n",
" 0.0 | \n",
- " 10 | \n",
+ " 40 | \n",
"
\n",
" \n",
- " | Pavoletti | \n",
+ " Kouame' | \n",
" 0.0 | \n",
" 55 | \n",
"
\n",
" \n",
- " | Shomurodov | \n",
- " 0.4 | \n",
+ " Beltran L. | \n",
+ " 0.0 | \n",
" 60 | \n",
"
\n",
" \n",
"\n",
- "467 rows × 2 columns
\n",
+ "462 rows × 2 columns
\n",
""
],
"text/plain": [
- " starter percentage\n",
- "player \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",
- "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",
+ " starter percentage\n",
+ "player \n",
+ "Berisha 1.0 90\n",
+ "Ebuehi 1.0 90\n",
+ "Ismajli 1.0 80\n",
+ "Luperto 1.0 90\n",
+ "Bastoni S. 1.0 85\n",
+ "... ... ...\n",
+ "Ikone' 0.0 30\n",
+ "Barak 0.0 40\n",
+ "Sottil 0.0 40\n",
+ "Kouame' 0.0 55\n",
+ "Beltran L. 0.0 60\n",
"\n",
- "[467 rows x 2 columns]"
+ "[462 rows x 2 columns]"
]
},
"execution_count": 31,
@@ -6120,557 +6114,560 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "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"
+ "Sommer: MV 6.20 ± 0.78; FV 5.60 + 1.26 (63.2% cs)\n",
+ "Skorupski: MV 6.03 ± 0.91; FV 3.80 + 2.05 (1.6% cs)\n",
+ "Di Gregorio: MV 6.14 ± 0.77; FV 5.73 + 1.28 (74.7% cs)\n",
+ "Meret: MV 5.71 ± 0.99; FV 3.10 + 2.68 (0.8% cs)\n",
+ "Provedel: MV 6.21 ± 0.87; FV 4.88 + 1.44 (16.7% cs)\n",
+ "Terracciano: MV 6.19 ± 0.82; FV 4.74 + 1.52 (12.4% cs)\n",
+ "Szczesny: MV 6.14 ± 0.81; FV 5.53 + 1.26 (59.4% cs)\n",
+ "Falcone: MV 6.15 ± 0.86; FV 4.98 + 1.40 (14.9% cs)\n",
+ "Milinkovic-Savic V.: MV 6.24 ± 0.90; FV 5.07 + 1.60 (25.0% cs)\n",
+ "Maignan: MV 6.20 ± 0.93; FV 5.10 + 1.50 (22.0% cs)\n",
+ "Montipo': MV 6.16 ± 0.86; FV 4.97 + 1.38 (27.6% cs)\n",
+ "Rui Patricio: MV 6.16 ± 0.79; FV 5.03 + 1.35 (17.8% cs)\n",
+ "Turati: MV 6.12 ± 0.90; FV 4.97 + 1.37 (22.7% cs)\n",
+ "Consigli: MV 6.15 ± 0.91; FV 4.03 + 2.07 (2.8% cs)\n",
+ "Musso: MV 6.13 ± 0.79; FV 5.56 + 1.26 (54.3% cs)\n",
+ "Carnesecchi: MV 6.11 ± 0.85; FV 5.00 + 1.36 (21.2% cs)\n",
+ "Radunovic: MV 5.35 ± 1.05; FV 2.98 + 2.92 (0.9% cs)\n",
+ "Silvestri: MV 6.16 ± 0.80; FV 5.63 + 1.27 (59.2% cs)\n",
+ "Martinez Jo.: MV 6.04 ± 0.91; FV 3.74 + 2.11 (1.9% cs)\n",
+ "Ochoa: MV 6.20 ± 0.91; FV 3.71 + 2.22 (2.6% cs)\n",
+ "Sportiello: MV 6.15 ± 0.90; FV 5.05 + 1.38 (31.9% cs)\n",
+ "Berisha: MV 6.25 ± 0.91; FV 4.95 + 1.44 (12.6% cs)\n",
+ "Caprile: MV 6.23 ± 0.90; FV 4.90 + 1.55 (14.1% cs)\n",
+ "Perin: MV 6.16 ± 0.80; FV 5.40 + 1.26 (51.7% cs)\n",
+ "Cragno: MV 6.06 ± 0.93; FV 3.49 + 2.46 (1.1% cs)\n",
+ "Mirante: MV 6.20 ± 0.93; FV 5.10 + 1.50 (22.0% cs)\n",
+ "Sepe: MV 6.21 ± 0.87; FV 4.88 + 1.44 (16.7% cs)\n",
+ "Leali: MV 6.04 ± 0.91; FV 3.74 + 2.11 (1.9% cs)\n",
+ "Lamanna: MV 6.14 ± 0.77; FV 5.72 + 1.28 (74.0% cs)\n",
+ "Sommariva: MV 6.04 ± 0.91; FV 3.74 + 2.11 (1.9% cs)\n",
+ "Pegolo: MV 6.14 ± 0.91; FV 3.90 + 2.13 (2.0% cs)\n",
+ "Perilli: MV 6.16 ± 0.86; FV 4.97 + 1.38 (27.6% cs)\n",
+ "Padelli: MV 6.16 ± 0.80; FV 5.63 + 1.27 (59.2% cs)\n",
+ "Scuffet: MV 5.35 ± 1.05; FV 2.98 + 2.92 (0.9% cs)\n",
+ "Gollini: MV 5.71 ± 0.99; FV 3.10 + 2.68 (0.8% cs)\n",
+ "Perisan: MV 6.21 ± 0.88; FV 4.71 + 1.65 (10.9% cs)\n",
+ "Audero: MV 6.20 ± 0.78; FV 5.60 + 1.26 (63.2% cs)\n",
+ "Di Gennaro: MV 6.20 ± 0.78; FV 5.60 + 1.26 (63.2% cs)\n",
+ "Pinsoglio: MV 6.14 ± 0.81; FV 5.53 + 1.26 (59.4% cs)\n",
+ "Aresti: MV 5.35 ± 1.05; FV 2.98 + 2.92 (0.9% cs)\n",
+ "Fiorillo: MV 6.20 ± 0.91; FV 3.71 + 2.22 (2.6% cs)\n",
+ "Cerofolini: MV 6.12 ± 0.90; FV 4.98 + 1.37 (23.0% cs)\n",
+ "Rossi F.: MV 6.13 ± 0.79; FV 5.56 + 1.26 (54.3% cs)\n",
+ "Costil: MV 6.20 ± 0.91; FV 3.71 + 2.22 (2.6% cs)\n",
+ "Ravaglia F.: MV 6.03 ± 0.91; FV 3.80 + 2.05 (1.6% cs)\n",
+ "Frattali: MV 6.12 ± 0.90; FV 4.97 + 1.37 (22.7% cs)\n",
+ "Contini: MV 5.71 ± 0.99; FV 3.10 + 2.68 (0.8% cs)\n",
+ "Brancolini: MV 6.15 ± 0.86; FV 4.98 + 1.40 (14.9% cs)\n",
+ "Berardi A.: MV 6.16 ± 0.86; FV 4.97 + 1.38 (27.6% cs)\n",
+ "Gemello: MV 6.24 ± 0.90; FV 5.07 + 1.60 (25.0% cs)\n",
+ "Boer: MV 6.16 ± 0.79; FV 5.03 + 1.35 (17.8% cs)\n",
+ "Bagnolini: MV 6.03 ± 0.91; FV 3.80 + 2.05 (1.6% cs)\n",
+ "Svilar: MV 6.16 ± 0.79; FV 5.03 + 1.35 (17.8% cs)\n",
+ "Sorrentino A.: MV 6.14 ± 0.77; FV 5.75 + 1.28 (74.3% cs)\n",
+ "Martinelli T.: MV 6.19 ± 0.82; FV 4.74 + 1.52 (12.4% cs)\n",
+ "Popa: MV 6.24 ± 0.90; FV 5.07 + 1.60 (25.0% cs)\n",
+ "Stubljar: MV 6.25 ± 0.91; FV 4.95 + 1.44 (12.6% cs)\n",
+ "Gori: MV 6.14 ± 0.77; FV 5.72 + 1.28 (74.0% cs)\n",
+ "Christensen O.: MV 6.12 ± 0.84; FV 4.16 + 1.81 (3.6% cs)\n",
+ "Borbei: MV 6.15 ± 0.86; FV 4.98 + 1.40 (14.9% cs)\n",
+ "Okoye: MV 6.16 ± 0.80; FV 5.63 + 1.27 (59.2% cs)\n",
+ "Mandas: MV 6.21 ± 0.87; FV 4.88 + 1.44 (16.7% cs)\n",
+ "Dimarco: MV 6.30 ± 0.69; FV 6.53 + 1.05\n",
+ "Di Lorenzo: MV 6.22 ± 1.15; FV 6.58 + 1.76\n",
+ "Hernandez T.: MV 6.13 ± 1.24; FV 6.66 + 2.20\n",
+ "Dumfries: MV 6.26 ± 0.78; FV 6.56 + 1.27\n",
+ "Carlos Augusto: MV 6.23 ± 0.78; FV 6.45 + 1.13\n",
+ "Schuurs: MV 5.97 ± 0.86; FV 6.12 + 1.16\n",
+ "Spinazzola: MV 6.26 ± 0.79; FV 6.61 + 1.42\n",
+ "Danilo: MV 6.18 ± 0.90; FV 6.41 + 1.29\n",
+ "Tomori: MV 6.16 ± 1.10; FV 6.40 + 1.54\n",
+ "Bastoni: MV 6.26 ± 0.78; FV 6.33 + 0.81\n",
+ "Buongiorno: MV 5.85 ± 0.94; FV 6.03 + 1.25\n",
+ "Pavard: MV 6.15 ± 0.61; FV 6.24 + 0.69\n",
+ "Biraghi: MV 5.81 ± 1.09; FV 6.12 + 1.60\n",
+ "Zappacosta: MV 6.03 ± 0.97; FV 6.21 + 1.33\n",
+ "Mancini: MV 6.10 ± 0.98; FV 6.41 + 1.47\n",
+ "Darmian: MV 6.15 ± 0.64; FV 6.25 + 0.70\n",
+ "Martinez Quarta: MV 5.86 ± 1.27; FV 5.99 + 1.61\n",
+ "Posch: MV 5.61 ± 0.99; FV 5.66 + 1.12\n",
+ "Romagnoli S.: MV 6.19 ± 0.86; FV 6.48 + 1.44\n",
+ "De Vrij: MV 6.23 ± 0.69; FV 6.26 + 0.64\n",
+ "Romagnoli: MV 5.88 ± 0.99; FV 5.86 + 1.11\n",
+ "Bremer: MV 6.03 ± 0.85; FV 6.08 + 0.93\n",
+ "Smalling: MV 6.19 ± 0.85; FV 6.48 + 1.31\n",
+ "Rrahmani: MV 5.96 ± 1.12; FV 5.92 + 1.26\n",
+ "Rodriguez R.: MV 5.90 ± 0.75; FV 5.89 + 0.76\n",
+ "Dragusin: MV 5.90 ± 1.07; FV 6.06 + 1.38\n",
+ "Vasquez: MV 6.11 ± 0.66; FV 6.14 + 0.65\n",
+ "Scalvini: MV 6.07 ± 0.96; FV 6.23 + 1.26\n",
+ "Holm: MV 6.04 ± 0.65; FV 6.14 + 0.75\n",
+ "Kristensen: MV 6.05 ± 0.67; FV 6.30 + 1.01\n",
+ "Calabria: MV 6.04 ± 1.01; FV 6.26 + 1.42\n",
+ "Acerbi: MV 6.06 ± 0.55; FV 6.07 + 0.48\n",
+ "Cuadrado: MV 6.04 ± 0.69; FV 6.11 + 0.72\n",
+ "Marchizza: MV 6.09 ± 0.73; FV 6.24 + 0.86\n",
+ "Bani: MV 5.89 ± 1.30; FV 6.13 + 1.84\n",
+ "Kolasinac: MV 6.02 ± 0.73; FV 6.13 + 0.88\n",
+ "Toljan: MV 5.88 ± 0.84; FV 5.94 + 1.02\n",
+ "Bakker: MV 6.06 ± 0.65; FV 6.19 + 0.92\n",
+ "Ruggeri: MV 6.15 ± 0.98; FV 6.43 + 1.50\n",
+ "Ebuehi: MV 5.98 ± 0.73; FV 6.10 + 0.93\n",
+ "Mazzocchi: MV 5.67 ± 0.74; FV 5.64 + 0.73\n",
+ "Doig: MV 6.02 ± 1.00; FV 6.26 + 1.43\n",
+ "Gendrey: MV 5.91 ± 0.74; FV 5.93 + 0.86\n",
+ "Thiaw: MV 5.80 ± 1.39; FV 5.73 + 1.36\n",
+ "Mario Rui: MV 5.90 ± 0.92; FV 5.91 + 1.04\n",
+ "Milenkovic: MV 5.64 ± 1.27; FV 5.69 + 1.50\n",
+ "Kyriakopoulos: MV 6.20 ± 0.93; FV 6.36 + 1.31\n",
+ "Casale: MV 5.72 ± 0.93; FV 5.70 + 1.03\n",
+ "Kamara H.: MV 6.00 ± 0.49; FV 6.03 + 0.45\n",
+ "Terracciano F.: MV 5.96 ± 0.74; FV 6.00 + 0.80\n",
+ "Baschirotto: MV 5.93 ± 0.94; FV 6.01 + 1.24\n",
+ "Bijol: MV 6.07 ± 0.87; FV 6.23 + 1.17\n",
+ "Lucumi': MV 5.53 ± 1.00; FV 5.51 + 1.06\n",
+ "Kristiansen: MV 5.72 ± 0.88; FV 5.77 + 1.07\n",
+ "Beukema: MV 5.61 ± 1.09; FV 5.60 + 1.24\n",
+ "Natan: MV 6.00 ± 0.93; FV 6.03 + 1.08\n",
+ "Faraoni: MV 5.88 ± 0.73; FV 5.97 + 0.91\n",
+ "Toloi: MV 6.13 ± 0.94; FV 6.30 + 1.25\n",
+ "Djimsiti: MV 6.03 ± 0.68; FV 6.05 + 0.66\n",
+ "Lazzari: MV 5.93 ± 0.71; FV 5.93 + 0.73\n",
+ "Lazaro: MV 5.97 ± 0.71; FV 6.01 + 0.78\n",
+ "Gallo: MV 5.93 ± 0.82; FV 5.95 + 0.99\n",
+ "Bellanova: MV 5.63 ± 1.17; FV 5.65 + 1.30\n",
+ "Mari': MV 6.10 ± 0.83; FV 6.17 + 1.00\n",
+ "Erlic: MV 5.88 ± 0.81; FV 5.86 + 0.82\n",
+ "Bastoni S.: MV 6.02 ± 0.91; FV 6.36 + 1.53\n",
+ "Perez N.: MV 5.95 ± 0.71; FV 5.96 + 0.75\n",
+ "Pedersen: MV 5.92 ± 0.55; FV 5.91 + 0.55\n",
+ "Izzo: MV 6.11 ± 0.86; FV 6.19 + 1.08\n",
+ "D'ambrosio: MV 6.04 ± 0.57; FV 5.99 + 0.51\n",
+ "Luperto: MV 5.84 ± 0.94; FV 5.77 + 1.02\n",
+ "Florenzi: MV 6.15 ± 0.93; FV 6.31 + 1.22\n",
+ "De Silvestri: MV 5.62 ± 0.91; FV 5.66 + 1.01\n",
+ "Marusic: MV 5.69 ± 0.98; FV 5.63 + 1.06\n",
+ "Magnani: MV 5.93 ± 0.90; FV 5.94 + 0.99\n",
+ "N'dicka: MV 5.96 ± 0.71; FV 6.00 + 0.74\n",
+ "Augello: MV 5.76 ± 0.83; FV 5.76 + 0.95\n",
+ "Dawidowicz: MV 5.92 ± 0.75; FV 5.91 + 0.79\n",
+ "Carboni A.: MV 6.06 ± 0.75; FV 6.09 + 0.84\n",
+ "Caldirola: MV 6.10 ± 0.88; FV 6.22 + 1.20\n",
+ "Llorente D.: MV 5.99 ± 0.71; FV 6.04 + 0.71\n",
+ "Parisi: MV 5.83 ± 1.00; FV 6.00 + 1.37\n",
+ "Cambiaso: MV 5.99 ± 0.80; FV 6.03 + 0.78\n",
+ "Bradaric: MV 5.76 ± 0.84; FV 5.77 + 0.93\n",
+ "Pongracic: MV 5.92 ± 0.91; FV 5.89 + 1.09\n",
+ "Viti: MV 5.90 ± 0.78; FV 5.85 + 0.70\n",
+ "Ostigard: MV 5.91 ± 1.28; FV 6.27 + 2.08\n",
+ "Olivera: MV 5.96 ± 0.79; FV 6.05 + 0.97\n",
+ "Ebosele: MV 5.98 ± 0.76; FV 6.02 + 0.77\n",
+ "Dodo': MV 5.70 ± 1.25; FV 5.77 + 1.49\n",
+ "Hien: MV 5.90 ± 0.82; FV 5.88 + 0.85\n",
+ "Azzi: MV 5.86 ± 0.68; FV 5.86 + 0.72\n",
+ "Kayode: MV 5.96 ± 1.11; FV 6.03 + 1.28\n",
+ "Dorgu: MV 5.95 ± 0.53; FV 5.93 + 0.49\n",
+ "Hysaj: MV 5.74 ± 0.81; FV 5.76 + 0.93\n",
+ "Juan Jesus: MV 5.96 ± 0.87; FV 5.94 + 0.92\n",
+ "Sabelli: MV 5.95 ± 0.59; FV 6.01 + 0.73\n",
+ "Hateboer: MV 5.93 ± 0.86; FV 6.08 + 1.20\n",
+ "Martin: MV 5.66 ± 1.10; FV 5.70 + 1.31\n",
+ "Mina: MV 5.79 ± 0.85; FV 5.97 + 1.12\n",
+ "Zappa: MV 5.60 ± 0.86; FV 5.51 + 0.89\n",
+ "Calafiori: MV 5.51 ± 1.14; FV 5.51 + 1.26\n",
+ "Monterisi: MV 6.21 ± 1.03; FV 6.66 + 1.85\n",
+ "Kalulu: MV 5.83 ± 1.22; FV 5.87 + 1.38\n",
+ "Vojvoda: MV 5.79 ± 0.80; FV 5.86 + 0.94\n",
+ "De Winter: MV 5.77 ± 1.10; FV 5.76 + 1.26\n",
+ "Gatti: MV 5.80 ± 1.07; FV 5.64 + 1.10\n",
+ "Birindelli: MV 6.02 ± 0.70; FV 6.01 + 0.75\n",
+ "Zemura: MV 5.94 ± 0.47; FV 5.93 + 0.40\n",
+ "Hatzidiakos: MV 5.68 ± 1.10; FV 5.55 + 1.24\n",
+ "Wieteska: MV 5.63 ± 1.22; FV 5.47 + 1.40\n",
+ "Masina: MV 6.24 ± 0.93; FV 6.76 + 1.90\n",
+ "Gyomber: MV 5.71 ± 0.86; FV 5.64 + 0.86\n",
+ "Alex Sandro: MV 5.85 ± 1.01; FV 5.72 + 1.01\n",
+ "Lirola: MV 6.05 ± 0.88; FV 6.25 + 1.16\n",
+ "Palomino: MV 6.07 ± 0.82; FV 6.18 + 1.00\n",
+ "Pellegrini Lu.: MV 5.68 ± 0.72; FV 5.59 + 0.69\n",
+ "Djidji: MV 5.70 ± 0.87; FV 5.74 + 0.97\n",
+ "Kabasele: MV 5.98 ± 0.59; FV 6.00 + 0.60\n",
+ "Ranieri L.: MV 5.62 ± 1.14; FV 5.64 + 1.29\n",
+ "Zortea: MV 6.05 ± 0.84; FV 6.33 + 1.28\n",
+ "Pirola: MV 5.71 ± 0.79; FV 5.68 + 0.80\n",
+ "Lovato: MV 5.65 ± 0.83; FV 5.57 + 0.83\n",
+ "Ismajli: MV 5.91 ± 0.72; FV 5.89 + 0.63\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "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"
+ "Vina: MV 5.69 ± 1.01; FV 5.70 + 1.15\n",
+ "Obert: MV 5.66 ± 0.99; FV 5.55 + 1.08\n",
+ "Tressoldi: MV 5.92 ± 0.89; FV 5.98 + 1.08\n",
+ "Dossena: MV 5.51 ± 1.04; FV 5.39 + 1.15\n",
+ "Oyono: MV 5.92 ± 0.56; FV 5.90 + 0.46\n",
+ "Touba: MV 5.99 ± 0.82; FV 6.06 + 1.05\n",
+ "Sazonov: MV 5.89 ± 0.72; FV 5.92 + 0.81\n",
+ "Patric: MV 5.84 ± 0.68; FV 5.80 + 0.68\n",
+ "Pezzella Giu.: MV 5.77 ± 0.68; FV 5.70 + 0.68\n",
+ "Ferrari G.: MV 5.82 ± 0.85; FV 5.88 + 1.04\n",
+ "Venuti: MV 5.89 ± 0.67; FV 5.87 + 0.74\n",
+ "Karsdorp: MV 5.99 ± 0.54; FV 6.02 + 0.52\n",
+ "Kjaer: MV 5.67 ± 1.21; FV 5.53 + 1.21\n",
+ "Lykogiannis: MV 5.53 ± 0.72; FV 5.47 + 0.65\n",
+ "Walukiewicz: MV 5.78 ± 0.89; FV 5.71 + 0.94\n",
+ "Okoli: MV 5.89 ± 0.75; FV 5.87 + 0.69\n",
+ "Amione: MV 5.90 ± 0.85; FV 5.95 + 1.05\n",
+ "Di Pardo: MV 5.73 ± 0.92; FV 5.66 + 0.99\n",
+ "Hefti: MV 5.60 ± 1.00; FV 5.51 + 0.98\n",
+ "Ehizibue: MV 6.03 ± 0.88; FV 6.28 + 1.33\n",
+ "Vogliacco: MV 5.81 ± 1.11; FV 5.83 + 1.30\n",
+ "Rugani: MV 6.03 ± 0.53; FV 6.04 + 0.48\n",
+ "Goldaniga: MV 5.65 ± 1.17; FV 5.51 + 1.34\n",
+ "Pereira P.: MV 6.13 ± 0.83; FV 6.21 + 1.00\n",
+ "Fazio: MV 5.82 ± 1.13; FV 5.90 + 1.40\n",
+ "Bereszynski: MV 5.82 ± 0.80; FV 5.78 + 0.88\n",
+ "Gunter: MV 5.72 ± 0.96; FV 5.67 + 0.99\n",
+ "Soumaoro: MV 5.52 ± 1.24; FV 5.49 + 1.44\n",
+ "Zanoli: MV 6.03 ± 1.09; FV 6.17 + 1.45\n",
+ "Daniliuc: MV 5.77 ± 0.89; FV 5.75 + 0.99\n",
+ "Soppy: MV 5.93 ± 0.66; FV 5.97 + 0.75\n",
+ "Zima: MV 5.73 ± 1.01; FV 5.68 + 1.05\n",
+ "Haps: MV 5.65 ± 1.15; FV 5.68 + 1.34\n",
+ "Coppola D.: MV 5.82 ± 0.67; FV 5.78 + 0.68\n",
+ "Cacace: MV 5.85 ± 0.65; FV 5.81 + 0.66\n",
+ "Sambia: MV 5.88 ± 0.74; FV 5.87 + 0.76\n",
+ "Guessand A.: MV 6.10 ± 0.83; FV 6.24 + 1.05\n",
+ "Cabal: MV 5.99 ± 0.70; FV 6.02 + 0.74\n",
+ "Missori: MV 5.93 ± 0.98; FV 5.98 + 1.18\n",
+ "Bisseck: MV 6.11 ± 0.86; FV 6.22 + 0.99\n",
+ "Ferreira J.: MV 5.90 ± 0.48; FV 5.87 + 0.46\n",
+ "Corazza: MV 5.54 ± 0.82; FV 5.50 + 0.80\n",
+ "Kristensen T.: MV 5.90 ± 0.56; FV 5.87 + 0.58\n",
+ "Dermaku: MV 5.98 ± 0.83; FV 6.05 + 1.09\n",
+ "Tonelli: MV 5.85 ± 0.72; FV 5.81 + 0.66\n",
+ "De Sciglio: MV 5.90 ± 0.60; FV 5.88 + 0.50\n",
+ "Capradossi: MV 5.82 ± 1.12; FV 5.74 + 1.23\n",
+ "Bonifazi: MV 5.45 ± 1.04; FV 5.41 + 1.05\n",
+ "Donati: MV 6.22 ± 1.18; FV 6.44 + 1.64\n",
+ "Bettella: MV 6.11 ± 0.85; FV 6.24 + 1.11\n",
+ "Kumbulla: MV 5.71 ± 1.47; FV 5.42 + 1.25\n",
+ "Celik: MV 5.87 ± 0.74; FV 5.83 + 0.75\n",
+ "Amey: MV 5.55 ± 1.05; FV 5.58 + 1.17\n",
+ "Cittadini: MV 6.11 ± 0.85; FV 6.24 + 1.11\n",
+ "Gila: MV 5.76 ± 0.89; FV 5.71 + 0.94\n",
+ "Ebosse: MV 5.91 ± 0.52; FV 5.88 + 0.47\n",
+ "Bronn: MV 5.70 ± 0.77; FV 5.62 + 0.74\n",
+ "Guarino: MV 5.95 ± 0.79; FV 6.00 + 0.87\n",
+ "Carboni F.: MV 6.11 ± 0.81; FV 6.18 + 0.97\n",
+ "Smajlovic: MV 5.99 ± 0.85; FV 6.10 + 1.17\n",
+ "Matturro: MV 5.67 ± 1.18; FV 5.63 + 1.34\n",
+ "N'guessan: MV 5.79 ± 0.96; FV 5.88 + 1.17\n",
+ "Mateus Lusuardi: MV 6.01 ± 0.76; FV 6.06 + 0.77\n",
+ "Kalaj: MV 6.01 ± 0.76; FV 6.06 + 0.77\n",
+ "Pierozzi: MV 5.76 ± 1.11; FV 5.91 + 1.42\n",
+ "Huijsen: MV 6.01 ± 0.83; FV 6.08 + 0.91\n",
+ "Bonfanti: MV 6.02 ± 0.87; FV 6.14 + 1.10\n",
+ "Pellegrino: MV 5.96 ± 1.10; FV 6.17 + 1.47\n",
+ "Comuzzo: MV 5.76 ± 1.11; FV 5.91 + 1.42\n",
+ "Bartesaghi: MV 6.01 ± 0.98; FV 6.16 + 1.28\n",
+ "Koopmeiners: MV 6.36 ± 1.10; FV 7.01 + 2.31\n",
+ "Zielinski: MV 6.32 ± 1.02; FV 6.81 + 1.91\n",
+ "Zaccagni: MV 6.21 ± 1.02; FV 6.65 + 1.83\n",
+ "Luis Alberto: MV 6.14 ± 1.05; FV 6.61 + 1.87\n",
+ "Pulisic: MV 6.34 ± 1.31; FV 7.37 + 3.21\n",
+ "Bonaventura: MV 6.17 ± 1.11; FV 6.68 + 2.01\n",
+ "Orsolini: MV 5.97 ± 1.46; FV 6.19 + 2.14\n",
+ "Calhanoglu: MV 6.33 ± 0.79; FV 6.52 + 1.08\n",
+ "Samardzic: MV 6.30 ± 0.95; FV 6.80 + 1.84\n",
+ "Felipe Anderson: MV 5.91 ± 1.05; FV 6.25 + 1.66\n",
+ "Politano: MV 6.40 ± 1.08; FV 6.99 + 2.18\n",
+ "Gudmundsson A.: MV 6.29 ± 1.16; FV 6.94 + 2.31\n",
+ "Candreva: MV 6.09 ± 1.16; FV 6.66 + 2.23\n",
+ "Barella: MV 6.25 ± 0.81; FV 6.51 + 1.18\n",
+ "Rabiot: MV 6.23 ± 1.04; FV 6.76 + 2.01\n",
+ "Mkhitaryan: MV 6.36 ± 0.97; FV 6.86 + 1.86\n",
+ "Ferguson: MV 5.91 ± 0.96; FV 6.15 + 1.36\n",
+ "Frattesi: MV 6.20 ± 0.91; FV 6.59 + 1.53\n",
+ "Loftus-Cheek: MV 6.23 ± 0.99; FV 6.63 + 1.73\n",
+ "Colpani: MV 6.45 ± 1.08; FV 7.16 + 2.44\n",
+ "Cristante: MV 6.22 ± 1.00; FV 6.67 + 1.70\n",
+ "Strefezza: MV 6.08 ± 0.90; FV 6.42 + 1.55\n",
+ "Chukwueze: MV 5.99 ± 0.84; FV 6.24 + 1.22\n",
+ "Radonjic: MV 6.08 ± 1.15; FV 6.58 + 2.01\n",
+ "Reijnders: MV 6.18 ± 0.97; FV 6.51 + 1.56\n",
+ "Pasalic: MV 6.05 ± 1.05; FV 6.56 + 1.90\n",
+ "Aouar: MV 6.20 ± 1.08; FV 6.76 + 2.07\n",
+ "Bajrami: MV 6.04 ± 0.67; FV 6.21 + 0.94\n",
+ "Vlasic: MV 5.92 ± 0.90; FV 6.18 + 1.31\n",
+ "Ederson D.s.: MV 6.11 ± 0.92; FV 6.39 + 1.38\n",
+ "Baldanzi: MV 6.08 ± 1.07; FV 6.58 + 1.97\n",
+ "Kamada: MV 5.92 ± 0.94; FV 6.21 + 1.41\n",
+ "Lindstrom: MV 6.03 ± 0.84; FV 6.35 + 1.32\n",
+ "De Roon: MV 6.14 ± 0.95; FV 6.42 + 1.42\n",
+ "Pellegrini Lo.: MV 6.06 ± 1.22; FV 6.70 + 2.32\n",
+ "El Shaarawy: MV 6.20 ± 0.85; FV 6.54 + 1.45\n",
+ "Mandragora: MV 5.87 ± 1.09; FV 6.15 + 1.56\n",
+ "Malinovskyi: MV 5.95 ± 1.05; FV 6.32 + 1.70\n",
+ "Kostic: MV 6.15 ± 0.80; FV 6.42 + 1.16\n",
+ "De Ketelaere: MV 6.15 ± 1.03; FV 6.55 + 1.76\n",
+ "Gomez: MV 6.11 ± 0.86; FV 6.24 + 1.12\n",
+ "Pereyra: MV 6.23 ± 1.07; FV 6.82 + 2.12\n",
+ "Renato Sanches: MV 6.17 ± 0.68; FV 6.42 + 0.99\n",
+ "Pessina: MV 6.21 ± 0.89; FV 6.48 + 1.36\n",
+ "Guendouzi: MV 5.84 ± 0.83; FV 5.92 + 1.03\n",
+ "Zambo Anguissa: MV 6.01 ± 0.99; FV 6.19 + 1.30\n",
+ "Duda: MV 6.27 ± 0.99; FV 6.72 + 1.81\n",
+ "Thorsby: MV 5.89 ± 1.41; FV 6.28 + 2.17\n",
+ "Mckennie: MV 6.19 ± 0.81; FV 6.30 + 0.91\n",
+ "Lovric: MV 6.14 ± 0.89; FV 6.51 + 1.48\n",
+ "Lazovic: MV 6.12 ± 0.91; FV 6.44 + 1.48\n",
+ "Duncan: MV 6.06 ± 0.90; FV 6.36 + 1.40\n",
+ "Gagliardini: MV 6.22 ± 0.89; FV 6.57 + 1.46\n",
+ "Arthur Melo: MV 5.99 ± 0.82; FV 6.08 + 0.99\n",
+ "Lobotka: MV 6.05 ± 0.89; FV 6.16 + 1.06\n",
+ "Fagioli: MV 6.09 ± 0.87; FV 6.36 + 1.26\n",
+ "Elmas: MV 5.95 ± 1.06; FV 6.36 + 1.63\n",
+ "Messias: MV 5.94 ± 1.17; FV 6.40 + 1.96\n",
+ "Matheus Henrique: MV 5.91 ± 1.01; FV 6.14 + 1.47\n",
+ "Frendrup: MV 6.11 ± 0.85; FV 6.32 + 1.21\n",
+ "Ciurria: MV 6.24 ± 0.99; FV 6.74 + 1.91\n",
+ "Locatelli: MV 6.01 ± 0.70; FV 6.04 + 0.70\n",
+ "Mazzitelli: MV 6.15 ± 1.05; FV 6.70 + 2.01\n",
+ "Ikone': MV 5.96 ± 1.02; FV 6.30 + 1.57\n",
+ "Ilic: MV 5.82 ± 0.73; FV 5.91 + 0.89\n",
+ "Ricci S.: MV 5.90 ± 0.83; FV 6.00 + 1.05\n",
+ "Ndoye: MV 5.69 ± 0.79; FV 5.71 + 0.89\n",
+ "Saponara: MV 6.10 ± 0.83; FV 6.37 + 1.28\n",
+ "Vecino: MV 5.82 ± 1.03; FV 5.94 + 1.35\n",
+ "Pogba: MV 5.98 ± 0.75; FV 6.01 + 0.75\n",
+ "Barak: MV 5.86 ± 0.93; FV 6.11 + 1.34\n",
+ "Nandez: MV 5.93 ± 0.98; FV 6.02 + 1.23\n",
+ "Rafia: MV 6.01 ± 0.67; FV 6.23 + 1.11\n",
+ "Strootman: MV 5.90 ± 0.77; FV 5.99 + 0.99\n",
+ "Klaassen: MV 6.13 ± 0.71; FV 6.40 + 1.09\n",
+ "Weah: MV 5.98 ± 0.52; FV 6.01 + 0.48\n",
+ "Marin: MV 5.99 ± 0.68; FV 6.09 + 0.80\n",
+ "Musah: MV 6.19 ± 0.93; FV 6.37 + 1.25\n",
+ "Boloca: MV 6.05 ± 0.90; FV 6.17 + 1.09\n",
+ "Krunic: MV 6.01 ± 0.86; FV 6.07 + 1.04\n",
+ "Cataldi: MV 5.92 ± 0.70; FV 5.90 + 0.70\n",
+ "Paredes: MV 6.00 ± 0.90; FV 6.11 + 1.08\n",
+ "Freuler: MV 5.70 ± 0.62; FV 5.64 + 0.67\n",
+ "Kastanos: MV 5.91 ± 0.54; FV 5.92 + 0.56\n",
+ "Bennacer: MV 6.16 ± 0.97; FV 6.48 + 1.55\n",
+ "Castrovilli: MV 5.94 ± 1.09; FV 6.32 + 1.69\n",
+ "Brescianini: MV 5.98 ± 0.48; FV 5.98 + 0.41\n",
+ "Miranchuk: MV 6.18 ± 1.01; FV 6.60 + 1.74\n",
+ "Reinier: MV 6.02 ± 0.79; FV 6.07 + 0.81\n",
+ "Harroui: MV 6.17 ± 0.76; FV 6.45 + 1.09\n",
+ "Aebischer: MV 5.69 ± 0.72; FV 5.68 + 0.81\n",
+ "Oudin: MV 6.16 ± 1.04; FV 6.63 + 1.90\n",
+ "Mboula: MV 5.97 ± 0.97; FV 6.09 + 1.23\n",
+ "Ramadani: MV 5.98 ± 0.91; FV 6.10 + 1.22\n",
+ "Jankto: MV 5.89 ± 0.75; FV 5.89 + 0.87\n",
+ "Garritano: MV 6.14 ± 0.69; FV 6.18 + 0.64\n",
+ "Sottil: MV 5.78 ± 0.74; FV 5.92 + 0.86\n",
+ "Tameze: MV 5.89 ± 0.60; FV 5.87 + 0.59\n",
+ "Pobega: MV 5.98 ± 0.56; FV 6.02 + 0.67\n",
+ "Bove: MV 6.01 ± 0.77; FV 6.17 + 1.01\n",
+ "Coulibaly L.: MV 5.88 ± 0.97; FV 6.04 + 1.36\n",
+ "Blin: MV 5.92 ± 0.58; FV 5.90 + 0.60\n",
+ "Moro N.: MV 5.70 ± 0.80; FV 5.75 + 0.95\n",
+ "Iling Junior: MV 6.01 ± 0.84; FV 6.10 + 0.94\n",
+ "Fabbian: MV 5.70 ± 0.81; FV 5.77 + 1.02\n",
+ "Cajuste : MV 5.90 ± 1.05; FV 5.94 + 1.21\n",
+ "Machin: MV 6.10 ± 0.86; FV 6.23 + 1.14\n",
+ "Linetty: MV 5.84 ± 0.69; FV 5.84 + 0.74\n",
+ "Walace: MV 5.90 ± 0.58; FV 5.88 + 0.57\n",
+ "Castillejo: MV 5.89 ± 0.61; FV 6.01 + 0.75\n",
+ "Gaetano: MV 6.19 ± 0.97; FV 6.64 + 1.78\n",
+ "Rovella: MV 5.91 ± 0.88; FV 5.90 + 1.00\n",
+ "Lopez M.: MV 5.79 ± 0.96; FV 5.83 + 1.13\n",
+ "Gyasi: MV 5.69 ± 0.85; FV 5.75 + 1.02\n",
+ "Zalewski: MV 5.99 ± 0.69; FV 6.09 + 0.82\n",
+ "Hongla: MV 5.90 ± 0.62; FV 5.91 + 0.64\n",
+ "Bohinen: MV 5.89 ± 0.50; FV 5.86 + 0.44\n",
+ "Miretti: MV 5.93 ± 0.59; FV 5.94 + 0.57\n",
+ "Thorstvedt: MV 5.94 ± 0.60; FV 5.99 + 0.68\n",
+ "Fazzini: MV 5.90 ± 0.54; FV 5.88 + 0.52\n",
+ "Barrenechea: MV 6.01 ± 0.59; FV 6.00 + 0.51\n",
+ "Oristanio: MV 5.78 ± 0.62; FV 5.85 + 0.67\n",
+ "El Azzouzi: MV 5.86 ± 0.64; FV 5.85 + 0.77\n",
+ "Makoumbou: MV 5.88 ± 0.63; FV 5.91 + 0.72\n",
+ "Folorunsho: MV 5.94 ± 0.99; FV 6.22 + 1.47\n",
+ "Kaba: MV 5.89 ± 0.64; FV 5.80 + 0.74\n",
+ "Martegani: MV 5.91 ± 0.62; FV 5.90 + 0.61\n",
+ "Kutlu: MV 5.90 ± 0.96; FV 5.91 + 1.08\n",
+ "Payero: MV 5.92 ± 0.56; FV 5.91 + 0.56\n",
+ "Grassi: MV 5.91 ± 0.65; FV 5.88 + 0.59\n",
+ "Mancosu: MV 5.85 ± 1.10; FV 5.81 + 1.23\n",
+ "Badelj: MV 5.69 ± 1.05; FV 5.64 + 1.16\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "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"
+ "Baez: MV 5.93 ± 0.55; FV 5.92 + 0.47\n",
+ "Sensi: MV 6.10 ± 0.81; FV 6.33 + 1.10\n",
+ "Maleh: MV 5.72 ± 0.97; FV 5.83 + 1.25\n",
+ "Adli: MV 6.08 ± 1.00; FV 6.26 + 1.33\n",
+ "Gonzalez J.: MV 5.88 ± 0.71; FV 5.94 + 0.92\n",
+ "Serdar: MV 5.91 ± 0.66; FV 5.92 + 0.74\n",
+ "Suslov: MV 6.02 ± 0.68; FV 6.07 + 0.78\n",
+ "Viola: MV 5.89 ± 0.96; FV 5.86 + 1.10\n",
+ "Deiola: MV 5.51 ± 0.88; FV 5.48 + 0.82\n",
+ "Bourabia: MV 6.04 ± 0.68; FV 6.10 + 0.68\n",
+ "Saelemaekers: MV 5.70 ± 0.97; FV 5.81 + 1.18\n",
+ "Maldini: MV 6.11 ± 0.84; FV 6.42 + 1.36\n",
+ "Maggiore: MV 5.89 ± 0.52; FV 5.86 + 0.50\n",
+ "Racic: MV 6.03 ± 0.92; FV 6.15 + 1.15\n",
+ "Kovalenko: MV 6.03 ± 0.68; FV 6.07 + 0.68\n",
+ "Romero L.: MV 6.06 ± 0.98; FV 6.27 + 1.39\n",
+ "Asllani: MV 5.94 ± 0.55; FV 5.92 + 0.46\n",
+ "Vignato S.: MV 5.94 ± 0.64; FV 5.93 + 0.63\n",
+ "Ranocchia F.: MV 5.97 ± 0.57; FV 6.06 + 0.63\n",
+ "Sulemana I.: MV 5.69 ± 0.69; FV 5.62 + 0.71\n",
+ "Infantino: MV 5.87 ± 0.98; FV 5.95 + 1.19\n",
+ "Tchatchoua: MV 5.96 ± 0.92; FV 6.07 + 1.17\n",
+ "Quina: MV 6.14 ± 0.73; FV 6.25 + 0.85\n",
+ "Adopo: MV 5.99 ± 0.90; FV 6.10 + 1.10\n",
+ "Basic: MV 5.94 ± 0.70; FV 5.98 + 0.84\n",
+ "Tchaouna: MV 5.86 ± 0.64; FV 5.84 + 0.66\n",
+ "Amatucci: MV 5.82 ± 1.09; FV 6.00 + 1.45\n",
+ "Gelli: MV 6.00 ± 0.82; FV 6.02 + 0.77\n",
+ "Legowski: MV 5.91 ± 0.86; FV 5.98 + 1.06\n",
+ "Prati: MV 5.87 ± 1.01; FV 5.84 + 1.15\n",
+ "Lulic K.: MV 6.02 ± 0.79; FV 6.07 + 0.81\n",
+ "Rog: MV 5.86 ± 0.73; FV 5.88 + 0.83\n",
+ "Nicolussi Caviglia: MV 5.94 ± 0.88; FV 6.01 + 1.09\n",
+ "Jagiello: MV 5.82 ± 1.10; FV 5.87 + 1.31\n",
+ "Obiang: MV 5.94 ± 0.53; FV 5.92 + 0.52\n",
+ "Demme: MV 6.01 ± 0.63; FV 6.00 + 0.54\n",
+ "Akpa Akpro: MV 6.10 ± 0.86; FV 6.23 + 1.14\n",
+ "Urbanski: MV 5.63 ± 1.04; FV 5.70 + 1.23\n",
+ "Volpato: MV 6.00 ± 0.85; FV 6.16 + 1.17\n",
+ "Pafundi: MV 6.17 ± 0.76; FV 6.28 + 0.83\n",
+ "Hrustic: MV 5.59 ± 0.69; FV 5.59 + 0.65\n",
+ "Bondo: MV 6.10 ± 0.84; FV 6.19 + 1.03\n",
+ "Zerbin: MV 5.99 ± 0.81; FV 6.11 + 0.99\n",
+ "Carboni V.: MV 6.23 ± 0.92; FV 6.40 + 1.23\n",
+ "Faticanti: MV 5.97 ± 0.86; FV 6.06 + 1.17\n",
+ "Gineitis: MV 5.74 ± 0.89; FV 5.80 + 1.04\n",
+ "Belardinelli: MV 5.99 ± 0.79; FV 6.06 + 0.92\n",
+ "Zarraga: MV 5.98 ± 0.75; FV 6.03 + 0.85\n",
+ "Camara E.: MV 6.05 ± 0.82; FV 6.18 + 1.03\n",
+ "Lipani: MV 5.95 ± 0.87; FV 6.04 + 1.10\n",
+ "Joselito: MV 5.96 ± 0.92; FV 6.07 + 1.17\n",
+ "Pagano: MV 5.94 ± 0.71; FV 5.95 + 0.75\n",
+ "Ibrahimovic A.: MV 6.05 ± 0.75; FV 6.10 + 0.75\n",
+ "Martinez L.: MV 6.49 ± 1.39; FV 7.82 + 3.71\n",
+ "Osimhen: MV 6.44 ± 1.49; FV 7.81 + 3.97\n",
+ "Rafael Leao: MV 6.44 ± 1.27; FV 7.44 + 3.10\n",
+ "Berardi: MV 6.48 ± 1.29; FV 7.57 + 3.26\n",
+ "Lukaku: MV 6.37 ± 1.45; FV 7.58 + 3.64\n",
+ "Vlahovic: MV 6.32 ± 1.39; FV 7.39 + 3.37\n",
+ "Dybala: MV 6.39 ± 1.48; FV 7.56 + 3.64\n",
+ "Giroud: MV 6.36 ± 1.34; FV 7.45 + 3.38\n",
+ "Thuram: MV 6.49 ± 1.08; FV 7.22 + 2.52\n",
+ "Immobile: MV 5.92 ± 1.17; FV 6.40 + 1.90\n",
+ "Kvaratskhelia: MV 6.39 ± 1.29; FV 7.41 + 3.15\n",
+ "Retegui: MV 6.07 ± 1.36; FV 6.83 + 2.69\n",
+ "Scamacca: MV 6.31 ± 1.30; FV 7.36 + 3.23\n",
+ "Lookman: MV 6.31 ± 1.27; FV 7.29 + 3.10\n",
+ "Lauriente': MV 6.27 ± 1.15; FV 6.95 + 2.49\n",
+ "Chiesa: MV 6.42 ± 1.19; FV 7.29 + 2.80\n",
+ "Dia: MV 6.15 ± 1.33; FV 7.03 + 2.84\n",
+ "Zapata D.: MV 5.88 ± 0.88; FV 6.15 + 1.29\n",
+ "Gonzalez N.: MV 6.32 ± 1.09; FV 7.01 + 2.39\n",
+ "Sanabria: MV 5.88 ± 1.00; FV 6.28 + 1.58\n",
+ "Arnautovic: MV 6.23 ± 0.87; FV 6.62 + 1.54\n",
+ "Nzola: MV 5.85 ± 0.98; FV 6.20 + 1.46\n",
+ "Milik: MV 6.21 ± 0.84; FV 6.59 + 1.51\n",
+ "Pinamonti: MV 5.99 ± 1.18; FV 6.53 + 2.06\n",
+ "Okafor: MV 6.28 ± 1.10; FV 6.95 + 2.37\n",
+ "Zirkzee: MV 6.03 ± 0.93; FV 6.36 + 1.48\n",
+ "Krstovic: MV 6.32 ± 1.31; FV 7.38 + 3.27\n",
+ "Ngonge: MV 5.94 ± 1.06; FV 6.37 + 1.73\n",
+ "Almqvist: MV 6.23 ± 1.08; FV 6.78 + 2.09\n",
+ "Cheddira: MV 6.24 ± 1.11; FV 6.89 + 2.26\n",
+ "Simeone: MV 6.01 ± 1.18; FV 6.60 + 2.06\n",
+ "Sanchez: MV 6.16 ± 0.77; FV 6.49 + 1.32\n",
+ "Beltran L.: MV 5.86 ± 0.86; FV 6.11 + 1.24\n",
+ "Belotti: MV 6.23 ± 1.00; FV 6.76 + 1.97\n",
+ "Muriel: MV 6.18 ± 0.83; FV 6.46 + 1.38\n",
+ "Luvumbo: MV 5.98 ± 0.67; FV 6.11 + 0.90\n",
+ "Toure' E.: MV 6.01 ± 0.88; FV 6.18 + 1.16\n",
+ "Lapadula: MV 6.06 ± 1.04; FV 6.61 + 2.01\n",
+ "Caprari: MV 6.21 ± 0.97; FV 6.67 + 1.76\n",
+ "Jovic: MV 6.05 ± 1.15; FV 6.57 + 2.09\n",
+ "Abraham: MV 6.23 ± 1.22; FV 7.13 + 2.84\n",
+ "Kouame': MV 5.93 ± 1.00; FV 6.30 + 1.57\n",
+ "Caputo: MV 5.80 ± 0.95; FV 6.12 + 1.39\n",
+ "Raspadori: MV 6.04 ± 1.11; FV 6.56 + 1.91\n",
+ "Colombo: MV 6.20 ± 1.03; FV 6.76 + 2.06\n",
+ "Soule': MV 6.36 ± 0.70; FV 6.59 + 1.13\n",
+ "Petagna: MV 5.80 ± 0.96; FV 6.12 + 1.34\n",
+ "Bonazzoli: MV 5.96 ± 0.96; FV 6.33 + 1.52\n",
+ "Deulofeu: MV 6.44 ± 1.20; FV 7.38 + 2.94\n",
+ "Pedro: MV 5.91 ± 0.87; FV 6.16 + 1.25\n",
+ "Brekalo: MV 5.90 ± 0.89; FV 6.08 + 1.13\n",
+ "Shomurodov: MV 5.65 ± 0.63; FV 5.68 + 0.60\n",
+ "Azmoun: MV 6.02 ± 0.69; FV 6.24 + 1.07\n",
+ "Castellanos: MV 5.84 ± 0.52; FV 5.86 + 0.52\n",
+ "Karlsson: MV 5.72 ± 0.76; FV 5.90 + 0.99\n",
+ "Thauvin: MV 5.92 ± 0.67; FV 6.11 + 0.95\n",
+ "Cambiaghi: MV 5.99 ± 0.76; FV 6.17 + 1.03\n",
+ "Henry: MV 5.93 ± 1.03; FV 6.31 + 1.66\n",
+ "Jovane: MV 5.90 ± 0.88; FV 6.04 + 1.15\n",
+ "Mota: MV 6.10 ± 0.96; FV 6.48 + 1.61\n",
+ "Mulattieri: MV 6.05 ± 0.64; FV 6.29 + 1.13\n",
+ "Lucca: MV 6.09 ± 1.18; FV 6.81 + 2.39\n",
+ "Isaksen: MV 5.73 ± 0.88; FV 5.72 + 0.91\n",
+ "Kean: MV 6.06 ± 0.95; FV 6.42 + 1.52\n",
+ "Karamoh: MV 5.96 ± 0.72; FV 6.15 + 0.96\n",
+ "Djuric: MV 5.99 ± 0.65; FV 6.13 + 0.80\n",
+ "Davis K.: MV 6.06 ± 0.81; FV 6.26 + 1.09\n",
+ "Banda: MV 6.08 ± 0.78; FV 6.34 + 1.29\n",
+ "Brenner: MV 6.06 ± 0.81; FV 6.26 + 1.09\n",
+ "Sansone: MV 6.19 ± 1.06; FV 6.80 + 2.18\n",
+ "Success: MV 6.05 ± 0.88; FV 6.37 + 1.42\n",
+ "Defrel: MV 5.88 ± 0.87; FV 6.18 + 1.35\n",
+ "Piccoli: MV 5.93 ± 0.56; FV 5.95 + 0.60\n",
+ "Caso: MV 6.16 ± 0.79; FV 6.49 + 1.33\n",
+ "Pellegri: MV 5.72 ± 0.77; FV 5.72 + 0.77\n",
+ "Cancellieri: MV 5.77 ± 0.93; FV 6.00 + 1.31\n",
+ "Seck: MV 5.96 ± 0.73; FV 6.04 + 0.79\n",
+ "Botheim: MV 5.63 ± 0.72; FV 5.65 + 0.72\n",
+ "Cuni: MV 5.95 ± 0.39; FV 5.98 + 0.34\n",
+ "Pavoletti: MV 5.78 ± 0.72; FV 5.96 + 0.95\n",
+ "Ekuban: MV 5.82 ± 0.68; FV 5.90 + 0.72\n",
+ "Alvarez A.: MV 5.92 ± 0.80; FV 6.18 + 1.20\n",
+ "Kvernadze: MV 6.02 ± 0.71; FV 6.06 + 0.71\n",
+ "Shpendi S.: MV 5.95 ± 0.44; FV 5.97 + 0.42\n",
+ "Destro: MV 5.65 ± 0.82; FV 5.69 + 0.90\n",
+ "Van Hooijdonk: MV 5.59 ± 0.81; FV 5.59 + 0.84\n",
+ "Ceide: MV 5.82 ± 0.71; FV 5.86 + 0.72\n",
+ "Maric: MV 6.01 ± 0.48; FV 6.04 + 0.44\n",
+ "Ikwuemesi: MV 5.86 ± 0.62; FV 5.86 + 0.63\n",
+ "Yildiz: MV 6.02 ± 0.83; FV 6.13 + 0.96\n",
+ "Cruz: MV 5.94 ± 0.80; FV 6.04 + 1.00\n",
+ "Puscas: MV 5.96 ± 0.94; FV 6.02 + 1.14\n",
+ "Ake' M.: MV 6.02 ± 0.65; FV 6.08 + 0.69\n",
+ "Braaf: MV 5.66 ± 0.74; FV 5.77 + 0.82\n",
+ "Kallon: MV 5.87 ± 0.89; FV 6.11 + 1.22\n",
+ "Kaio Jorge: MV 5.97 ± 0.48; FV 5.99 + 0.42\n",
+ "Vivaldo: MV 6.06 ± 0.81; FV 6.26 + 1.09\n",
+ "Bidaoui: MV 6.02 ± 0.77; FV 6.11 + 0.85\n",
+ "Burnete: MV 5.94 ± 0.83; FV 6.03 + 1.12\n",
+ "Corfitzen: MV 5.97 ± 0.81; FV 6.08 + 1.09\n",
+ "Stewart: MV 5.92 ± 0.79; FV 6.01 + 0.98\n"
]
},
{
@@ -6739,113 +6736,113 @@
" \n",
" \n",
" \n",
- " | Carnesecchi | \n",
- " P | \n",
- " Atalanta | \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",
- " Juventus | \n",
- " 1 | \n",
- " 1.0 | \n",
+ " Lazio | \n",
+ " 0 | \n",
+ " 1.00 | \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",
+ " 6.130588 | \n",
+ " 0.395458 | \n",
+ " 5.560176 | \n",
+ " 0.630095 | \n",
+ " 6.117671 | \n",
+ " 0.473347 | \n",
+ " 0.020254 | \n",
+ " 1.189104 | \n",
+ " 6.219871 | \n",
+ " 0.682691 | \n",
+ " -0.651437 | \n",
+ " 1.180653 | \n",
+ " 54.287124 | \n",
"
\n",
" \n",
" | Rossi F. | \n",
" P | \n",
" Atalanta | \n",
- " Juventus | \n",
+ " Lazio | \n",
+ " 0 | \n",
+ " 0.00 | \n",
" 1 | \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",
+ " 6.130588 | \n",
+ " 0.395458 | \n",
+ " 5.560176 | \n",
+ " 0.630095 | \n",
+ " 6.117671 | \n",
+ " 0.473347 | \n",
+ " 0.020254 | \n",
+ " 1.189104 | \n",
+ " 6.219871 | \n",
+ " 0.682691 | \n",
+ " -0.651437 | \n",
+ " 1.180653 | \n",
+ " 54.287124 | \n",
"
\n",
" \n",
- " | Zappacosta | \n",
+ " Carnesecchi | \n",
+ " P | \n",
+ " Atalanta | \n",
+ " Lazio | \n",
+ " 0 | \n",
+ " 0.00 | \n",
+ " 5 | \n",
+ " 6.111842 | \n",
+ " 0.423985 | \n",
+ " 4.999980 | \n",
+ " 0.679832 | \n",
+ " 6.061238 | \n",
+ " 0.492138 | \n",
+ " 0.076215 | \n",
+ " 1.184612 | \n",
+ " 5.243609 | \n",
+ " 1.016311 | \n",
+ " -0.176309 | \n",
+ " 1.051638 | \n",
+ " 21.158487 | \n",
+ "
\n",
+ " \n",
+ " | Ruggeri | \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",
+ " Lazio | \n",
+ " 0 | \n",
+ " 0.55 | \n",
+ " 55 | \n",
+ " 6.146059 | \n",
+ " 0.491973 | \n",
+ " 6.431080 | \n",
+ " 0.748339 | \n",
+ " 6.130273 | \n",
+ " 0.571970 | \n",
+ " 0.020303 | \n",
+ " 0.888866 | \n",
+ " 5.914506 | \n",
+ " 1.029078 | \n",
+ " 0.360306 | \n",
+ " 1.299918 | \n",
" 0.000000 | \n",
"
\n",
" \n",
- " | Toloi | \n",
+ " Zortea | \n",
" D | \n",
" Atalanta | \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",
+ " Lazio | \n",
+ " 0 | \n",
+ " 0.00 | \n",
+ " 30 | \n",
+ " 6.049477 | \n",
+ " 0.421663 | \n",
+ " 6.325981 | \n",
+ " 0.639571 | \n",
+ " 6.005404 | \n",
+ " 0.484718 | \n",
+ " 0.066981 | \n",
+ " 0.952244 | \n",
+ " 5.874121 | \n",
+ " 0.871703 | \n",
+ " 0.371244 | \n",
+ " 1.299916 | \n",
" 0.000000 | \n",
"
\n",
" \n",
@@ -6874,167 +6871,167 @@
" | Henry | \n",
" A | \n",
" Verona | \n",
- " Torino | \n",
+ " Frosinone | \n",
" 0 | \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",
+ " 0.00 | \n",
+ " 40 | \n",
+ " 5.930722 | \n",
+ " 0.516654 | \n",
+ " 6.314850 | \n",
+ " 0.830392 | \n",
+ " 5.676789 | \n",
+ " 0.529371 | \n",
+ " 0.347378 | \n",
+ " 0.843730 | \n",
+ " 5.485209 | \n",
+ " 0.900312 | \n",
+ " 0.617425 | \n",
+ " 1.299930 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | Djuric | \n",
" A | \n",
" Verona | \n",
- " Torino | \n",
+ " Frosinone | \n",
" 0 | \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",
+ " 0.45 | \n",
+ " 55 | \n",
+ " 5.990664 | \n",
+ " 0.324370 | \n",
+ " 6.125685 | \n",
+ " 0.401414 | \n",
+ " 5.981859 | \n",
+ " 0.383508 | \n",
+ " 0.016978 | \n",
+ " 1.054538 | \n",
+ " 5.903392 | \n",
+ " 0.589155 | \n",
+ " 0.274942 | \n",
+ " 1.299901 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | Kallon | \n",
" A | \n",
" Verona | \n",
- " Torino | \n",
+ " Frosinone | \n",
" 0 | \n",
- " 0.0 | \n",
+ " 0.00 | \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",
+ " 5.866126 | \n",
+ " 0.445314 | \n",
+ " 6.106137 | \n",
+ " 0.610579 | \n",
+ " 5.668099 | \n",
+ " 0.458100 | \n",
+ " 0.313946 | \n",
+ " 0.919495 | \n",
+ " 5.532506 | \n",
+ " 0.703259 | \n",
+ " 0.557121 | \n",
+ " 1.299925 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | Cruz | \n",
" A | \n",
" Verona | \n",
- " Torino | \n",
+ " Frosinone | \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",
+ " 0.55 | \n",
+ " 55 | \n",
+ " 5.938263 | \n",
+ " 0.397721 | \n",
+ " 6.035246 | \n",
+ " 0.497888 | \n",
+ " 5.988713 | \n",
+ " 0.482585 | \n",
+ " -0.077101 | \n",
+ " 0.999415 | \n",
+ " 5.859564 | \n",
+ " 0.784396 | \n",
+ " 0.165425 | \n",
+ " 1.299890 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | Braaf | \n",
" A | \n",
" Verona | \n",
- " Torino | \n",
+ " Frosinone | \n",
" 0 | \n",
- " 0.0 | \n",
+ " 0.00 | \n",
" 0 | \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",
+ " 5.657923 | \n",
+ " 0.371975 | \n",
+ " 5.771335 | \n",
+ " 0.409864 | \n",
+ " 5.519660 | \n",
+ " 0.390190 | \n",
+ " 0.258709 | \n",
+ " 1.001091 | \n",
+ " 5.480610 | \n",
+ " 0.557743 | \n",
+ " 0.373164 | \n",
+ " 1.299909 | \n",
" 0.000000 | \n",
"
\n",
" \n",
"\n",
- "539 rows × 19 columns
\n",
+ "542 rows × 19 columns
\n",
""
],
"text/plain": [
- " role team oppteam home starter vote% MV MV std \\\n",
- "player \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 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",
+ " role team oppteam home starter vote% MV MV std \\\n",
+ "player \n",
+ "Musso P Atalanta Lazio 0 1.00 70 6.130588 0.395458 \n",
+ "Rossi F. P Atalanta Lazio 0 0.00 1 6.130588 0.395458 \n",
+ "Carnesecchi P Atalanta Lazio 0 0.00 5 6.111842 0.423985 \n",
+ "Ruggeri D Atalanta Lazio 0 0.55 55 6.146059 0.491973 \n",
+ "Zortea D Atalanta Lazio 0 0.00 30 6.049477 0.421663 \n",
+ "... ... ... ... ... ... ... ... ... \n",
+ "Henry A Verona Frosinone 0 0.00 40 5.930722 0.516654 \n",
+ "Djuric A Verona Frosinone 0 0.45 55 5.990664 0.324370 \n",
+ "Kallon A Verona Frosinone 0 0.00 0 5.866126 0.445314 \n",
+ "Cruz A Verona Frosinone 0 0.55 55 5.938263 0.397721 \n",
+ "Braaf A Verona Frosinone 0 0.00 0 5.657923 0.371975 \n",
"\n",
" FV FV std MV loc MV scale MV skewness \\\n",
"player \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",
+ "Musso 5.560176 0.630095 6.117671 0.473347 0.020254 \n",
+ "Rossi F. 5.560176 0.630095 6.117671 0.473347 0.020254 \n",
+ "Carnesecchi 4.999980 0.679832 6.061238 0.492138 0.076215 \n",
+ "Ruggeri 6.431080 0.748339 6.130273 0.571970 0.020303 \n",
+ "Zortea 6.325981 0.639571 6.005404 0.484718 0.066981 \n",
"... ... ... ... ... ... \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",
+ "Henry 6.314850 0.830392 5.676789 0.529371 0.347378 \n",
+ "Djuric 6.125685 0.401414 5.981859 0.383508 0.016978 \n",
+ "Kallon 6.106137 0.610579 5.668099 0.458100 0.313946 \n",
+ "Cruz 6.035246 0.497888 5.988713 0.482585 -0.077101 \n",
+ "Braaf 5.771335 0.409864 5.519660 0.390190 0.258709 \n",
"\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",
+ "Musso 1.189104 6.219871 0.682691 -0.651437 1.180653 \n",
+ "Rossi F. 1.189104 6.219871 0.682691 -0.651437 1.180653 \n",
+ "Carnesecchi 1.184612 5.243609 1.016311 -0.176309 1.051638 \n",
+ "Ruggeri 0.888866 5.914506 1.029078 0.360306 1.299918 \n",
+ "Zortea 0.952244 5.874121 0.871703 0.371244 1.299916 \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",
+ "Henry 0.843730 5.485209 0.900312 0.617425 1.299930 \n",
+ "Djuric 1.054538 5.903392 0.589155 0.274942 1.299901 \n",
+ "Kallon 0.919495 5.532506 0.703259 0.557121 1.299925 \n",
+ "Cruz 0.999415 5.859564 0.784396 0.165425 1.299890 \n",
+ "Braaf 1.001091 5.480610 0.557743 0.373164 1.299909 \n",
"\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",
+ "Musso 54.287124 \n",
+ "Rossi F. 54.287124 \n",
+ "Carnesecchi 21.158487 \n",
+ "Ruggeri 0.000000 \n",
+ "Zortea 0.000000 \n",
"... ... \n",
"Henry 0.000000 \n",
"Djuric 0.000000 \n",
@@ -7042,7 +7039,7 @@
"Cruz 0.000000 \n",
"Braaf 0.000000 \n",
"\n",
- "[539 rows x 19 columns]"
+ "[542 rows x 19 columns]"
]
},
"execution_count": 32,
@@ -7051,7 +7048,7 @@
}
],
"source": [
- "matchday_out = 7\n",
+ "matchday_out = 8\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",
@@ -7139,7 +7136,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": null,
"id": "60d73507",
"metadata": {},
"outputs": [
@@ -7147,934 +7144,310 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "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"
+ "Sommer (6.17, 0.41); (5.61, 0.63)\n",
+ "Skorupski (6.12, 0.40); (5.49, 0.63)\n",
+ "Di Gregorio (6.15, 0.50); (4.97, 0.69)\n",
+ "Meret (6.00, 0.44); (4.56, 0.83)\n",
+ "Provedel (6.20, 0.45); (4.52, 0.86)\n",
+ "Terracciano (6.18, 0.43); (5.13, 0.66)\n",
+ "Szczesny (6.16, 0.40); (5.66, 0.63)\n",
+ "Falcone (6.19, 0.45); (5.02, 0.71)\n",
+ "Milinkovic-Savic V. (6.18, 0.41); (5.09, 0.66)\n",
+ "Maignan (6.19, 0.47); (4.98, 0.69)\n",
+ "Montipo' (6.17, 0.39); (5.19, 0.64)\n",
+ "Rui Patricio (5.84, 0.46); (3.85, 1.05)\n",
+ "Turati (6.20, 0.48); (4.97, 0.72)\n",
+ "Consigli (6.04, 0.46); (4.02, 1.02)\n",
+ "Musso (6.18, 0.38); (5.69, 0.64)\n",
+ "Carnesecchi (6.14, 0.43); (5.01, 0.68)\n",
+ "Radunovic (6.04, 0.44); (4.57, 0.88)\n",
+ "Silvestri (5.65, 0.47); (3.63, 1.23)\n",
+ "Martinez Jo. (6.08, 0.44); (4.57, 0.89)\n",
+ "Ochoa (6.14, 0.46); (3.61, 1.16)\n",
+ "Sportiello (6.16, 0.43); (5.06, 0.67)\n",
+ "Berisha (6.06, 0.46); (3.55, 1.19)\n",
+ "Caprile (6.11, 0.45); (3.83, 1.08)\n",
+ "Perin (6.16, 0.41); (5.15, 0.65)\n",
+ "Cragno (6.03, 0.46); (3.63, 1.14)\n",
+ "Mirante (6.19, 0.47); (4.98, 0.69)\n",
+ "Sepe (6.20, 0.45); (4.52, 0.86)\n",
+ "Leali (6.08, 0.44); (4.57, 0.89)\n",
+ "Lamanna (6.14, 0.50); (4.97, 0.69)\n",
+ "Sommariva (6.08, 0.44); (4.57, 0.89)\n",
+ "Pegolo (6.05, 0.46); (3.94, 1.04)\n",
+ "Perilli (6.17, 0.39); (5.19, 0.64)\n",
+ "Padelli (5.65, 0.47); (3.63, 1.23)\n",
+ "Scuffet (6.04, 0.44); (4.57, 0.88)\n",
+ "Gollini (6.00, 0.44); (4.56, 0.83)\n",
+ "Perisan (6.06, 0.46); (3.65, 1.15)\n",
+ "Audero (6.17, 0.41); (5.61, 0.63)\n",
+ "Di Gennaro (6.17, 0.41); (5.61, 0.63)\n",
+ "Pinsoglio (6.16, 0.40); (5.66, 0.63)\n",
+ "Aresti (6.04, 0.44); (4.57, 0.88)\n",
+ "Fiorillo (6.14, 0.46); (3.61, 1.16)\n",
+ "Cerofolini (6.18, 0.47); (4.69, 0.78)\n",
+ "Rossi F. (6.18, 0.38); (5.69, 0.64)\n",
+ "Costil (6.14, 0.46); (3.61, 1.16)\n",
+ "Ravaglia F. (6.12, 0.40); (5.49, 0.63)\n",
+ "Frattali (6.20, 0.48); (4.97, 0.72)\n",
+ "Contini (6.00, 0.44); (4.56, 0.83)\n",
+ "Brancolini (6.19, 0.45); (5.02, 0.71)\n",
+ "Berardi A. (6.17, 0.39); (5.19, 0.64)\n",
+ "Gemello (6.18, 0.41); (5.09, 0.66)\n",
+ "Boer (5.84, 0.46); (3.85, 1.05)\n",
+ "Bagnolini (6.12, 0.40); (5.49, 0.63)\n",
+ "Svilar (5.84, 0.46); (3.85, 1.05)\n",
+ "Sorrentino A. (6.16, 0.48); (4.97, 0.69)\n",
+ "Martinelli T. (6.18, 0.43); (5.13, 0.66)\n",
+ "Popa (6.18, 0.41); (5.09, 0.66)\n",
+ "Stubljar (6.06, 0.46); (3.55, 1.19)\n",
+ "Gori (6.14, 0.50); (4.97, 0.69)\n",
+ "Christensen O. (6.10, 0.45); (4.22, 0.92)\n",
+ "Borbei (6.19, 0.45); (5.02, 0.71)\n",
+ "Okoye (5.65, 0.47); (3.63, 1.23)\n",
+ "Mandas (6.20, 0.45); (4.52, 0.86)\n",
+ "Dimarco (6.34, 0.42); (6.68, 0.73)\n",
+ "Di Lorenzo (6.30, 0.51); (6.76, 0.91)\n",
+ "Hernandez T. (6.20, 0.54); (6.60, 0.91)\n",
+ "Dumfries (6.28, 0.47); (6.72, 0.84)\n",
+ "Carlos Augusto (6.25, 0.47); (6.60, 0.77)\n",
+ "Schuurs (6.09, 0.43); (6.27, 0.59)\n",
+ "Spinazzola (6.17, 0.37); (6.47, 0.64)\n",
+ "Danilo (6.16, 0.49); (6.41, 0.72)\n",
+ "Tomori (6.21, 0.49); (6.43, 0.72)\n",
+ "Bastoni (6.26, 0.44); (6.39, 0.53)\n",
+ "Buongiorno (6.04, 0.45); (6.25, 0.67)\n",
+ "Pavard (6.14, 0.35); (6.27, 0.44)\n",
+ "Biraghi (6.14, 0.48); (6.58, 0.89)\n",
+ "Zappacosta (5.98, 0.49); (6.11, 0.63)\n",
+ "Mancini (5.93, 0.51); (6.14, 0.71)\n",
+ "Darmian (6.15, 0.37); (6.28, 0.45)\n",
+ "Martinez Quarta (6.16, 0.56); (6.45, 0.85)\n",
+ "Posch (6.01, 0.44); (6.16, 0.61)\n",
+ "Romagnoli S. (6.06, 0.50); (6.24, 0.73)\n",
+ "De Vrij (6.23, 0.39); (6.29, 0.41)\n",
+ "Romagnoli (5.96, 0.48); (5.98, 0.55)\n",
+ "Bremer (6.05, 0.49); (6.17, 0.62)\n",
+ "Smalling (6.08, 0.42); (6.31, 0.63)\n",
+ "Rrahmani (6.13, 0.51); (6.30, 0.67)\n",
+ "Rodriguez R. (5.97, 0.36); (5.97, 0.33)\n",
+ "Dragusin (6.03, 0.46); (6.20, 0.62)\n",
+ "Vasquez (6.17, 0.31); (6.19, 0.30)\n",
+ "Scalvini (6.04, 0.50); (6.17, 0.62)\n",
+ "Holm (6.03, 0.33); (6.10, 0.36)\n",
+ "Kristensen (6.00, 0.33); (6.18, 0.48)\n",
+ "Calabria (6.04, 0.41); (6.17, 0.54)\n",
+ "Acerbi (6.06, 0.31); (6.09, 0.31)\n",
+ "Cuadrado (6.05, 0.40); (6.15, 0.48)\n",
+ "Marchizza (6.00, 0.41); (6.12, 0.54)\n",
+ "Bani (6.06, 0.56); (6.27, 0.77)\n",
+ "Kolasinac (6.02, 0.37); (6.12, 0.44)\n",
+ "Toljan (5.85, 0.44); (5.90, 0.52)\n",
+ "Bakker (6.03, 0.32); (6.14, 0.43)\n",
+ "Ruggeri (6.11, 0.50); (6.33, 0.70)\n",
+ "Ebuehi (5.82, 0.41); (5.92, 0.52)\n",
+ "Mazzocchi (5.66, 0.39); (5.65, 0.40)\n",
+ "Doig (5.96, 0.50); (6.16, 0.70)\n",
+ "Gendrey (5.90, 0.39); (5.91, 0.43)\n",
+ "Thiaw (5.88, 0.61); (5.82, 0.62)\n",
+ "Mario Rui (5.97, 0.35); (6.00, 0.39)\n",
+ "Milenkovic (5.84, 0.54); (5.88, 0.63)\n",
+ "Kyriakopoulos (6.00, 0.46); (6.09, 0.58)\n",
+ "Casale (5.86, 0.43); (5.85, 0.49)\n",
+ "Kamara H. (5.92, 0.26); (5.93, 0.26)\n",
+ "Terracciano F. (5.95, 0.38); (5.97, 0.39)\n",
+ "Baschirotto (5.84, 0.54); (5.93, 0.66)\n",
+ "Bijol (5.78, 0.53); (5.85, 0.65)\n",
+ "Lucumi' (5.94, 0.39); (5.93, 0.42)\n",
+ "Kristiansen (6.11, 0.42); (6.24, 0.54)\n",
+ "Beukema (6.04, 0.46); (6.06, 0.49)\n",
+ "Natan (6.15, 0.41); (6.26, 0.49)\n",
+ "Faraoni (5.81, 0.37); (5.87, 0.44)\n",
+ "Toloi (6.09, 0.47); (6.23, 0.59)\n",
+ "Djimsiti (6.03, 0.35); (6.05, 0.34)\n",
+ "Lazzari (5.99, 0.35); (6.00, 0.36)\n",
+ "Lazaro (6.05, 0.37); (6.10, 0.39)\n",
+ "Gallo (5.86, 0.44); (5.84, 0.48)\n",
+ "Bellanova (5.71, 0.55); (5.76, 0.64)\n",
+ "Mari' (5.89, 0.45); (5.89, 0.50)\n",
+ "Erlic (5.86, 0.43); (5.82, 0.44)\n",
+ "Bastoni S. (5.81, 0.48); (6.00, 0.67)\n",
+ "Perez N. (5.72, 0.49); (5.71, 0.54)\n",
+ "Pedersen (5.92, 0.28); (5.92, 0.29)\n",
+ "Izzo (5.93, 0.45); (5.96, 0.52)\n",
+ "D'ambrosio (5.96, 0.29); (5.93, 0.26)\n",
+ "Luperto (5.61, 0.59); (5.56, 0.67)\n",
+ "Florenzi (6.15, 0.39); (6.24, 0.44)\n",
+ "De Silvestri (5.99, 0.40); (6.11, 0.52)\n",
+ "Marusic (5.81, 0.45); (5.76, 0.50)\n",
+ "Magnani (5.96, 0.44); (5.97, 0.48)\n",
+ "N'dicka (5.87, 0.41); (5.89, 0.46)\n",
+ "Augello (5.86, 0.38); (5.94, 0.46)\n",
+ "Dawidowicz (5.94, 0.37); (5.93, 0.38)\n",
+ "Carboni A. (5.95, 0.40); (5.98, 0.45)\n",
+ "Caldirola (5.88, 0.48); (5.92, 0.59)\n",
+ "Llorente D. (5.87, 0.38); (5.87, 0.39)\n",
+ "Parisi (6.04, 0.44); (6.17, 0.61)\n",
+ "Cambiaso (5.96, 0.42); (6.02, 0.47)\n",
+ "Bradaric (5.72, 0.45); (5.76, 0.52)\n",
+ "Pongracic (5.84, 0.52); (5.79, 0.55)\n",
+ "Viti (5.89, 0.43); (5.81, 0.42)\n",
+ "Ostigard (6.13, 0.54); (6.56, 0.92)\n",
+ "Olivera (6.03, 0.34); (6.12, 0.40)\n",
+ "Ebosele (5.80, 0.42); (5.78, 0.45)\n",
+ "Dodo' (5.89, 0.54); (6.01, 0.70)\n",
+ "Hien (5.93, 0.40); (5.91, 0.40)\n",
+ "Azzi (5.90, 0.27); (5.90, 0.26)\n",
+ "Kayode (6.17, 0.47); (6.28, 0.58)\n",
+ "Dorgu (5.92, 0.26); (5.90, 0.22)\n",
+ "Hysaj (5.89, 0.37); (5.92, 0.44)\n",
+ "Juan Jesus (6.09, 0.35); (6.13, 0.35)\n",
+ "Sabelli (6.00, 0.27); (6.06, 0.33)\n",
+ "Hateboer (5.87, 0.43); (5.96, 0.57)\n",
+ "Martin (5.87, 0.45); (5.93, 0.55)\n",
+ "Mina (6.08, 0.38); (6.34, 0.63)\n",
+ "Zappa (5.72, 0.36); (5.66, 0.34)\n",
+ "Calafiori (5.90, 0.44); (5.90, 0.50)\n",
+ "Monterisi (6.06, 0.56); (6.45, 0.97)\n",
+ "Kalulu (5.92, 0.48); (5.95, 0.56)\n",
+ "Vojvoda (5.93, 0.37); (6.00, 0.45)\n",
+ "De Winter (5.92, 0.47); (5.92, 0.53)\n",
+ "Gatti (5.77, 0.59); (5.70, 0.60)\n",
+ "Birindelli (5.90, 0.36); (5.88, 0.38)\n",
+ "Zemura (5.87, 0.26); (5.84, 0.23)\n",
+ "Hatzidiakos (5.79, 0.44); (5.75, 0.47)\n",
+ "Wieteska (5.71, 0.57); (5.67, 0.67)\n",
+ "Masina (5.86, 0.47); (6.20, 0.71)\n",
+ "Gyomber (5.64, 0.50); (5.57, 0.52)\n",
+ "Alex Sandro (5.83, 0.53); (5.71, 0.56)\n",
+ "Lirola (5.93, 0.49); (6.07, 0.65)\n",
+ "Palomino (6.06, 0.41); (6.16, 0.49)\n",
+ "Pellegrini Lu. (5.80, 0.33); (5.74, 0.32)\n",
+ "Djidji (5.91, 0.38); (5.95, 0.45)\n",
+ "Kabasele (5.88, 0.34); (5.87, 0.39)\n",
+ "Ranieri L. (5.79, 0.49); (5.86, 0.61)\n",
+ "Zortea (6.03, 0.42); (6.26, 0.61)\n",
+ "Pirola (5.67, 0.43); (5.65, 0.46)\n",
+ "Lovato (5.59, 0.47); (5.52, 0.49)\n",
+ "Ismajli (5.76, 0.46); (5.69, 0.48)\n",
+ "Vina (5.65, 0.53); (5.66, 0.60)\n",
+ "Obert (5.76, 0.38); (5.71, 0.37)\n",
+ "Tressoldi (5.91, 0.45); (5.97, 0.55)\n",
+ "Dossena (5.67, 0.43); (5.60, 0.42)\n",
+ "Oyono (5.88, 0.33); (5.85, 0.32)\n",
+ "Touba (5.94, 0.43); (5.98, 0.50)\n",
+ "Sazonov (5.95, 0.35); (5.97, 0.38)\n",
+ "Patric (5.89, 0.32); (5.86, 0.31)\n",
+ "Pezzella Giu. (5.57, 0.43); (5.48, 0.42)\n",
+ "Ferrari G. (5.79, 0.44); (5.85, 0.53)\n",
+ "Venuti (5.88, 0.36); (5.88, 0.38)\n",
+ "Karsdorp (5.94, 0.28); (5.97, 0.29)\n",
+ "Kjaer (5.78, 0.48); (5.66, 0.50)\n",
+ "Lykogiannis (5.89, 0.26); (5.88, 0.27)\n",
+ "Walukiewicz (5.59, 0.56); (5.54, 0.62)\n",
+ "Okoli (5.78, 0.44); (5.71, 0.47)\n",
+ "Amione (5.87, 0.42); (5.91, 0.52)\n",
+ "Di Pardo (5.85, 0.34); (5.83, 0.33)\n",
+ "Hefti (5.82, 0.39); (5.78, 0.37)\n",
+ "Ehizibue (5.75, 0.46); (5.80, 0.57)\n",
+ "Vogliacco (5.94, 0.47); (5.97, 0.53)\n",
+ "Rugani (6.01, 0.28); (6.02, 0.28)\n",
+ "Goldaniga (5.72, 0.51); (5.65, 0.54)\n",
+ "Pereira P. (5.98, 0.43); (6.03, 0.49)\n",
+ "Fazio (5.77, 0.61); (5.88, 0.77)\n",
+ "Bereszynski (5.62, 0.50); (5.58, 0.54)\n",
+ "Gunter (5.75, 0.49); (5.69, 0.51)\n",
+ "Soumaoro (5.90, 0.49); (5.85, 0.54)\n",
+ "Zanoli (6.11, 0.47); (6.38, 0.72)\n",
+ "Daniliuc (5.72, 0.49); (5.71, 0.56)\n",
+ "Soppy (5.97, 0.34); (6.00, 0.38)\n",
+ "Zima (5.90, 0.45); (5.88, 0.48)\n",
+ "Haps (5.90, 0.46); (5.94, 0.55)\n",
+ "Coppola D. (5.82, 0.34); (5.77, 0.33)\n",
+ "Cacace (5.59, 0.45); (5.52, 0.46)\n",
+ "Sambia (5.84, 0.41); (5.84, 0.43)\n",
+ "Guessand A. (5.90, 0.47); (6.00, 0.59)\n",
+ "Cabal (5.98, 0.35); (6.00, 0.35)\n",
+ "Missori (5.92, 0.51); (6.00, 0.62)\n",
+ "Bisseck (6.10, 0.47); (6.29, 0.63)\n",
+ "Ferreira J. (5.76, 0.30); (5.70, 0.30)\n",
+ "Corazza (5.91, 0.33); (5.91, 0.35)\n",
+ "Kristensen T. (5.63, 0.41); (5.58, 0.41)\n",
+ "Dermaku (5.92, 0.43); (5.98, 0.52)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "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. (6.47, 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"
+ "Tonelli (5.62, 0.47); (5.53, 0.49)\n",
+ "De Sciglio (5.88, 0.31); (5.86, 0.29)\n",
+ "Capradossi (5.89, 0.46); (5.93, 0.54)\n",
+ "Bonifazi (5.85, 0.38); (5.80, 0.38)\n",
+ "Donati (5.95, 0.66); (6.01, 0.76)\n",
+ "Bettella (5.95, 0.44); (6.03, 0.54)\n",
+ "Kumbulla (5.52, 0.73); (5.28, 0.68)\n",
+ "Celik (5.73, 0.45); (5.67, 0.47)\n",
+ "Amey (5.94, 0.43); (6.00, 0.54)\n",
+ "Cittadini (5.95, 0.44); (6.03, 0.54)\n",
+ "Gila (5.88, 0.40); (5.86, 0.43)\n",
+ "Ebosse (5.82, 0.31); (5.77, 0.32)\n",
+ "Bronn (5.64, 0.42); (5.55, 0.42)\n",
+ "Guarino (5.81, 0.49); (5.88, 0.60)\n",
+ "Carboni F. (5.97, 0.42); (6.02, 0.49)\n",
+ "Smajlovic (5.93, 0.45); (6.00, 0.55)\n",
+ "Matturro (5.88, 0.49); (5.86, 0.53)\n",
+ "N'guessan (5.95, 0.43); (6.03, 0.52)\n",
+ "Mateus Lusuardi (5.93, 0.45); (6.00, 0.54)\n",
+ "Kalaj (5.93, 0.45); (6.00, 0.54)\n",
+ "Pierozzi (5.98, 0.46); (6.08, 0.57)\n",
+ "Huijsen (5.97, 0.43); (6.06, 0.53)\n",
+ "Bonfanti (6.00, 0.43); (6.11, 0.54)\n",
+ "Pellegrino (5.98, 0.44); (6.07, 0.54)\n",
+ "Comuzzo (5.98, 0.46); (6.08, 0.57)\n",
+ "Bartesaghi (6.03, 0.41); (6.10, 0.48)\n",
+ "Koopmeiners (6.33, 0.55); (6.94, 1.12)\n",
+ "Zielinski (6.34, 0.47); (6.77, 0.87)\n",
+ "Zaccagni (6.28, 0.52); (6.79, 1.01)\n",
+ "Luis Alberto (6.27, 0.54); (6.86, 1.09)\n",
+ "Pulisic (6.38, 0.60); (7.22, 1.38)\n",
+ "Bonaventura (6.33, 0.56); (6.98, 1.16)\n",
+ "Orsolini (6.18, 0.69); (6.89, 1.40)\n",
+ "Calhanoglu (6.33, 0.44); (6.62, 0.68)\n",
+ "Samardzic (6.14, 0.45); (6.50, 0.78)\n",
+ "Felipe Anderson (6.01, 0.55); (6.47, 0.94)\n",
+ "Politano (6.41, 0.51); (6.97, 1.06)\n",
+ "Gudmundsson A. (6.35, 0.51); (6.94, 1.07)\n",
+ "Candreva (6.16, 0.62); (6.79, 1.21)\n",
+ "Barella (6.27, 0.47); (6.67, 0.80)\n",
+ "Rabiot (6.19, 0.55); (6.71, 1.06)\n",
+ "Mkhitaryan (6.35, 0.53); (6.94, 1.05)\n",
+ "Ferguson (6.22, 0.49); (6.63, 0.85)\n",
+ "Frattesi (6.23, 0.51); (6.72, 0.95)\n",
+ "Loftus-Cheek (6.25, 0.47); (6.61, 0.78)\n",
+ "Colpani (6.32, 0.52); (6.89, 1.06)\n",
+ "Cristante (6.15, 0.50); (6.49, 0.79)\n",
+ "Strefezza (6.01, 0.44); (6.29, 0.69)\n",
+ "Chukwueze (5.92, 0.39); (6.14, 0.54)\n",
+ "Radonjic (6.21, 0.59); (6.87, 1.21)\n",
+ "Reijnders (6.19, 0.45); (6.47, 0.68)\n",
+ "Pasalic (6.00, 0.52); (6.45, 0.89)\n",
+ "Aouar (6.04, 0.56); (6.55, 1.00)\n",
+ "Bajrami (6.06, 0.36); (6.25, 0.51)\n",
+ "Vlasic (5.99, 0.47); (6.29, 0.71)\n",
+ "Ederson D.s. (6.08, 0.46); (6.31, 0.65)\n",
+ "Baldanzi (5.94, 0.54); (6.36, 0.90)\n",
+ "Kamada (6.00, 0.49); (6.37, 0.79)\n",
+ "Lindstrom (6.08, 0.39); (6.35, 0.64)\n",
+ "De Roon (6.12, 0.49); (6.35, 0.69)\n",
+ "Pellegrini Lo. (5.95, 0.58); (6.47, 0.98)\n",
+ "El Shaarawy (6.15, 0.42); (6.48, 0.73)\n",
+ "Mandragora (6.04, 0.52); (6.41, 0.84)\n",
+ "Malinovskyi (6.01, 0.54); (6.49, 0.96)\n",
+ "Kostic (6.13, 0.44); (6.44, 0.70)\n",
+ "De Ketelaere (6.12, 0.51); (6.47, 0.82)\n",
+ "Gomez (5.96, 0.44); (6.03, 0.55)\n"
]
- },
- {
- "name": "stdout",
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- "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"
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- " 0 | \n",
- " 5.943305 | \n",
- " 0.444352 | \n",
- " 6.065740 | \n",
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- " 5.746909 | \n",
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\n",
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- " 6.061640 | \n",
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- " 0.481284 | \n",
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\n",
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- " 0.348108 | \n",
- " 0.253766 | \n",
- " 1.031060 | \n",
- " 5.487167 | \n",
- " 0.536615 | \n",
- " 0.393338 | \n",
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539 rows × 19 columns
\n",
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