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fantabeto/4_player_match_dataset_creation.ipynb
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Giuseppe Musicco b60a8a061c Release
2022-11-12 11:29:20 +01:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "8f597771",
"metadata": {},
"source": [
"Player/match dataset creation\n",
"\n",
"For each serie A (already happened) match and player, a database entry is generated, with this form:\n",
" \n",
"[y = player votes data, player data, team data, vs team data, opp team data, vs opp team data]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "3ecf3676",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"id": "a7d3a9d6",
"metadata": {},
"source": [
"Load team data from FBref"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "8a6867a5",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\nicol\\AppData\\Local\\Temp\\ipykernel_17612\\552672520.py:19: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" team_data['team_idx'][i] = team_data['team_idx'][i].split(' ')[-1]\n"
]
},
{
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" <th>Monza</th>\n",
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" <th>Sampdoria</th>\n",
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" <th>Sassuolo</th>\n",
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" <tr>\n",
" <th>Spezia</th>\n",
" <td>Spezia</td>\n",
" <td>24.0</td>\n",
" <td>46.9</td>\n",
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" <td>54.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Torino</th>\n",
" <td>Torino</td>\n",
" <td>23.0</td>\n",
" <td>51.3</td>\n",
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" <td>51.5</td>\n",
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" <th>Udinese</th>\n",
" <td>Udinese</td>\n",
" <td>22.0</td>\n",
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" <td>187.0</td>\n",
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"</table>\n",
"<p>20 rows × 313 columns</p>\n",
"</div>"
],
"text/plain": [
" team team_players_used team_possession team_games \\\n",
"team_idx \n",
"Atalanta Atalanta 23.0 46.4 14.0 \n",
"Bologna Bologna 23.0 51.1 14.0 \n",
"Cremonese Cremonese 27.0 43.2 14.0 \n",
"Empoli Empoli 25.0 46.0 14.0 \n",
"Fiorentina Fiorentina 25.0 58.7 14.0 \n",
"Verona Hellas Verona 29.0 43.9 14.0 \n",
"Inter Inter 23.0 54.6 14.0 \n",
"Juventus Juventus 26.0 50.5 14.0 \n",
"Lazio Lazio 21.0 50.0 14.0 \n",
"Lecce Lecce 24.0 40.7 14.0 \n",
"Milan Milan 27.0 53.9 14.0 \n",
"Monza Monza 29.0 55.5 14.0 \n",
"Napoli Napoli 24.0 59.8 14.0 \n",
"Roma Roma 23.0 50.8 14.0 \n",
"Salernitana Salernitana 24.0 47.1 14.0 \n",
"Sampdoria Sampdoria 24.0 50.8 14.0 \n",
"Sassuolo Sassuolo 26.0 48.1 14.0 \n",
"Spezia Spezia 24.0 46.9 14.0 \n",
"Torino Torino 23.0 51.3 14.0 \n",
"Udinese Udinese 22.0 50.6 14.0 \n",
"\n",
" team_games_starts team_minutes team_goals team_assists \\\n",
"team_idx \n",
"Atalanta 154.0 1260.0 19.0 14.0 \n",
"Bologna 154.0 1260.0 17.0 12.0 \n",
"Cremonese 154.0 1260.0 11.0 5.0 \n",
"Empoli 154.0 1260.0 10.0 5.0 \n",
"Fiorentina 154.0 1260.0 17.0 15.0 \n",
"Verona 154.0 1260.0 10.0 7.0 \n",
"Inter 154.0 1260.0 31.0 22.0 \n",
"Juventus 154.0 1260.0 21.0 17.0 \n",
"Lazio 154.0 1260.0 25.0 20.0 \n",
"Lecce 154.0 1260.0 12.0 8.0 \n",
"Milan 154.0 1260.0 26.0 21.0 \n",
"Monza 154.0 1260.0 13.0 8.0 \n",
"Napoli 154.0 1260.0 34.0 28.0 \n",
"Roma 154.0 1260.0 17.0 11.0 \n",
"Salernitana 154.0 1260.0 18.0 12.0 \n",
"Sampdoria 154.0 1260.0 6.0 6.0 \n",
"Sassuolo 154.0 1260.0 15.0 12.0 \n",
"Spezia 154.0 1260.0 10.0 6.0 \n",
"Torino 154.0 1260.0 15.0 10.0 \n",
"Udinese 154.0 1260.0 21.0 19.0 \n",
"\n",
" team_pens_made team_pens_att ... vs_team_fouls \\\n",
"team_idx ... \n",
"Atalanta 4.0 5.0 ... 150.0 \n",
"Bologna 3.0 3.0 ... 182.0 \n",
"Cremonese 1.0 3.0 ... 145.0 \n",
"Empoli 0.0 0.0 ... 176.0 \n",
"Fiorentina 1.0 3.0 ... 186.0 \n",
"Verona 0.0 0.0 ... 130.0 \n",
"Inter 2.0 2.0 ... 182.0 \n",
"Juventus 1.0 2.0 ... 161.0 \n",
"Lazio 1.0 2.0 ... 197.0 \n",
"Lecce 1.0 2.0 ... 184.0 \n",
"Milan 2.0 2.0 ... 164.0 \n",
"Monza 1.0 1.0 ... 207.0 \n",
"Napoli 3.0 3.0 ... 195.0 \n",
"Roma 2.0 3.0 ... 198.0 \n",
"Salernitana 1.0 1.0 ... 150.0 \n",
"Sampdoria 0.0 0.0 ... 220.0 \n",
"Sassuolo 1.0 2.0 ... 177.0 \n",
"Spezia 1.0 1.0 ... 136.0 \n",
"Torino 1.0 1.0 ... 148.0 \n",
"Udinese 0.0 0.0 ... 176.0 \n",
"\n",
" vs_team_fouled vs_team_offsides vs_team_pens_won \\\n",
"team_idx \n",
"Atalanta 168.0 19.0 0.0 \n",
"Bologna 158.0 24.0 2.0 \n",
"Cremonese 188.0 19.0 2.0 \n",
"Empoli 151.0 28.0 2.0 \n",
"Fiorentina 176.0 35.0 1.0 \n",
"Verona 205.0 18.0 1.0 \n",
"Inter 154.0 14.0 1.0 \n",
"Juventus 156.0 21.0 0.0 \n",
"Lazio 124.0 35.0 1.0 \n",
"Lecce 184.0 27.0 3.0 \n",
"Milan 161.0 15.0 2.0 \n",
"Monza 178.0 24.0 0.0 \n",
"Napoli 116.0 18.0 1.0 \n",
"Roma 157.0 7.0 0.0 \n",
"Salernitana 157.0 34.0 4.0 \n",
"Sampdoria 192.0 42.0 1.0 \n",
"Sassuolo 120.0 47.0 2.0 \n",
"Spezia 177.0 32.0 1.0 \n",
"Torino 199.0 17.0 2.0 \n",
"Udinese 162.0 17.0 2.0 \n",
"\n",
" vs_team_pens_conceded vs_team_own_goals \\\n",
"team_idx \n",
"Atalanta 5.0 1.0 \n",
"Bologna 3.0 0.0 \n",
"Cremonese 3.0 0.0 \n",
"Empoli 0.0 0.0 \n",
"Fiorentina 3.0 0.0 \n",
"Verona 0.0 1.0 \n",
"Inter 2.0 0.0 \n",
"Juventus 2.0 0.0 \n",
"Lazio 2.0 1.0 \n",
"Lecce 2.0 0.0 \n",
"Milan 2.0 1.0 \n",
"Monza 1.0 0.0 \n",
"Napoli 3.0 0.0 \n",
"Roma 3.0 0.0 \n",
"Salernitana 1.0 1.0 \n",
"Sampdoria 0.0 0.0 \n",
"Sassuolo 2.0 0.0 \n",
"Spezia 1.0 2.0 \n",
"Torino 1.0 0.0 \n",
"Udinese 0.0 1.0 \n",
"\n",
" vs_team_ball_recoveries vs_team_aerials_won \\\n",
"team_idx \n",
"Atalanta 834.0 181.0 \n",
"Bologna 731.0 165.0 \n",
"Cremonese 744.0 242.0 \n",
"Empoli 723.0 163.0 \n",
"Fiorentina 694.0 193.0 \n",
"Verona 758.0 240.0 \n",
"Inter 596.0 126.0 \n",
"Juventus 674.0 184.0 \n",
"Lazio 746.0 151.0 \n",
"Lecce 703.0 216.0 \n",
"Milan 690.0 168.0 \n",
"Monza 692.0 141.0 \n",
"Napoli 687.0 142.0 \n",
"Roma 709.0 142.0 \n",
"Salernitana 750.0 169.0 \n",
"Sampdoria 742.0 215.0 \n",
"Sassuolo 710.0 146.0 \n",
"Spezia 776.0 212.0 \n",
"Torino 710.0 228.0 \n",
"Udinese 707.0 142.0 \n",
"\n",
" vs_team_aerials_lost vs_team_aerials_won_pct \n",
"team_idx \n",
"Atalanta 211.0 46.2 \n",
"Bologna 123.0 57.3 \n",
"Cremonese 184.0 56.8 \n",
"Empoli 135.0 54.7 \n",
"Fiorentina 224.0 46.3 \n",
"Verona 229.0 51.2 \n",
"Inter 172.0 42.3 \n",
"Juventus 166.0 52.6 \n",
"Lazio 126.0 54.5 \n",
"Lecce 188.0 53.5 \n",
"Milan 205.0 45.0 \n",
"Monza 160.0 46.8 \n",
"Napoli 181.0 44.0 \n",
"Roma 159.0 47.2 \n",
"Salernitana 175.0 49.1 \n",
"Sampdoria 217.0 49.8 \n",
"Sassuolo 130.0 52.9 \n",
"Spezia 179.0 54.2 \n",
"Torino 215.0 51.5 \n",
"Udinese 187.0 43.2 \n",
"\n",
"[20 rows x 313 columns]"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rcsv = pd.read_csv('fbref_data/teams.csv') \n",
"team = pd.DataFrame(rcsv)\n",
"\n",
"rcsv = pd.read_csv('fbref_data/teams_vs.csv') \n",
"vs_team = pd.DataFrame(rcsv)\n",
"\n",
"for i in range(1, team.shape[1]):\n",
" team = team.rename(columns = {team.columns[i] : 'team_' + team.columns[i]})\n",
" \n",
"for i in range(1, vs_team.shape[1]):\n",
" vs_team = vs_team.rename(columns = {vs_team.columns[i] : 'vs_team_' + vs_team.columns[i]})\n",
" \n",
"vs_team.pop('team')\n",
"\n",
"team_data = pd.concat([team, vs_team], axis = 1)\n",
"\n",
"team_data['team_idx'] = team_data['team']\n",
"for i in range(team_data.shape[0]):\n",
" team_data['team_idx'][i] = team_data['team_idx'][i].split(' ')[-1]\n",
"\n",
"team_data = team_data.set_index('team_idx')\n",
"\n",
"team_data\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "b6a3db98",
"metadata": {},
"outputs": [],
"source": [
"team_data.to_excel('mid_outputs/team_data.xlsx')"
]
},
{
"cell_type": "markdown",
"id": "cc50dde9",
"metadata": {},
"source": [
"Load data generated from players_dataset_creation"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "c34eb398",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>id</th>\n",
" <th>r</th>\n",
" <th>team</th>\n",
" <th>surname</th>\n",
" <th>initial</th>\n",
" <th>fb_ID</th>\n",
" <th>age</th>\n",
" <th>birth_year</th>\n",
" <th>games</th>\n",
" <th>...</th>\n",
" <th>gk_pct_goal_kicks_launched</th>\n",
" <th>gk_goal_kick_length_avg</th>\n",
" <th>gk_crosses</th>\n",
" <th>gk_crosses_stopped</th>\n",
" <th>gk_crosses_stopped_pct</th>\n",
" <th>gk_def_actions_outside_pen_area</th>\n",
" <th>gk_def_actions_outside_pen_area_per90</th>\n",
" <th>gk_avg_distance_def_actions</th>\n",
" <th>vote_avg</th>\n",
" <th>vote_std</th>\n",
" </tr>\n",
" <tr>\n",
" <th>name</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Meret</th>\n",
" <td>0</td>\n",
" <td>572</td>\n",
" <td>P</td>\n",
" <td>Napoli</td>\n",
" <td>Meret</td>\n",
" <td>NaN</td>\n",
" <td>502</td>\n",
" <td>25-234</td>\n",
" <td>1997</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>19.6</td>\n",
" <td>26.6</td>\n",
" <td>142.0</td>\n",
" <td>6.0</td>\n",
" <td>4.2</td>\n",
" <td>10.0</td>\n",
" <td>0.71</td>\n",
" <td>15.1</td>\n",
" <td>6.214286</td>\n",
" <td>0.557875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Provedel</th>\n",
" <td>1</td>\n",
" <td>2814</td>\n",
" <td>P</td>\n",
" <td>Lazio</td>\n",
" <td>Provedel</td>\n",
" <td>NaN</td>\n",
" <td>509</td>\n",
" <td>28-239</td>\n",
" <td>1994</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>37.2</td>\n",
" <td>36.6</td>\n",
" <td>201.0</td>\n",
" <td>5.0</td>\n",
" <td>2.5</td>\n",
" <td>29.0</td>\n",
" <td>2.08</td>\n",
" <td>17.6</td>\n",
" <td>6.321429</td>\n",
" <td>0.305143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Maignan</th>\n",
" <td>2</td>\n",
" <td>4312</td>\n",
" <td>P</td>\n",
" <td>Milan</td>\n",
" <td>Maignan</td>\n",
" <td>NaN</td>\n",
" <td>500</td>\n",
" <td>27-131</td>\n",
" <td>1995</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>38.9</td>\n",
" <td>40.4</td>\n",
" <td>65.0</td>\n",
" <td>5.0</td>\n",
" <td>7.7</td>\n",
" <td>6.0</td>\n",
" <td>0.86</td>\n",
" <td>12.9</td>\n",
" <td>6.357143</td>\n",
" <td>0.440315</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Silvestri</th>\n",
" <td>3</td>\n",
" <td>2211</td>\n",
" <td>P</td>\n",
" <td>Udinese</td>\n",
" <td>Silvestri</td>\n",
" <td>NaN</td>\n",
" <td>512</td>\n",
" <td>31-254</td>\n",
" <td>1991</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>40.9</td>\n",
" <td>38.2</td>\n",
" <td>194.0</td>\n",
" <td>4.0</td>\n",
" <td>2.1</td>\n",
" <td>5.0</td>\n",
" <td>0.36</td>\n",
" <td>11.3</td>\n",
" <td>6.321429</td>\n",
" <td>0.485767</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sepe</th>\n",
" <td>4</td>\n",
" <td>159</td>\n",
" <td>P</td>\n",
" <td>Salernitana</td>\n",
" <td>Sepe</td>\n",
" <td>NaN</td>\n",
" <td>511</td>\n",
" <td>31-187</td>\n",
" <td>1991</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>48.4</td>\n",
" <td>41.7</td>\n",
" <td>187.0</td>\n",
" <td>14.0</td>\n",
" <td>7.5</td>\n",
" <td>9.0</td>\n",
" <td>0.64</td>\n",
" <td>13.7</td>\n",
" <td>6.428571</td>\n",
" <td>0.371154</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>De Luca</th>\n",
" <td>549</td>\n",
" <td>5512</td>\n",
" <td>A</td>\n",
" <td>Sampdoria</td>\n",
" <td>Luca</td>\n",
" <td>NaN</td>\n",
" <td>122</td>\n",
" <td>24-117</td>\n",
" <td>1998</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>5.877688</td>\n",
" <td>0.485814</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Soule'</th>\n",
" <td>550</td>\n",
" <td>5734</td>\n",
" <td>A</td>\n",
" <td>Juventus</td>\n",
" <td>Soule</td>\n",
" <td>NaN</td>\n",
" <td>422</td>\n",
" <td>19-210</td>\n",
" <td>2003</td>\n",
" <td>5</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>6.067846</td>\n",
" <td>0.581002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lazetic</th>\n",
" <td>551</td>\n",
" <td>5785</td>\n",
" <td>A</td>\n",
" <td>Milan</td>\n",
" <td>Lazetic</td>\n",
" <td>NaN</td>\n",
" <td>248</td>\n",
" <td>18-293</td>\n",
" <td>2004</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>6.170097</td>\n",
" <td>0.204814</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Voelkerling Persson</th>\n",
" <td>552</td>\n",
" <td>5837</td>\n",
" <td>A</td>\n",
" <td>Lecce</td>\n",
" <td>Persson</td>\n",
" <td>NaN</td>\n",
" <td>-1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>6.041983</td>\n",
" <td>0.689071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Sanca</th>\n",
" <td>553</td>\n",
" <td>6063</td>\n",
" <td>A</td>\n",
" <td>Spezia</td>\n",
" <td>Sanca</td>\n",
" <td>NaN</td>\n",
" <td>395</td>\n",
" <td>22-311</td>\n",
" <td>2000</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>5.991021</td>\n",
" <td>0.262247</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>554 rows × 165 columns</p>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 id r team surname initial \\\n",
"name \n",
"Meret 0 572 P Napoli Meret NaN \n",
"Provedel 1 2814 P Lazio Provedel NaN \n",
"Maignan 2 4312 P Milan Maignan NaN \n",
"Silvestri 3 2211 P Udinese Silvestri NaN \n",
"Sepe 4 159 P Salernitana Sepe NaN \n",
"... ... ... .. ... ... ... \n",
"De Luca 549 5512 A Sampdoria Luca NaN \n",
"Soule' 550 5734 A Juventus Soule NaN \n",
"Lazetic 551 5785 A Milan Lazetic NaN \n",
"Voelkerling Persson 552 5837 A Lecce Persson NaN \n",
"Sanca 553 6063 A Spezia Sanca NaN \n",
"\n",
" fb_ID age birth_year games ... \\\n",
"name ... \n",
"Meret 502 25-234 1997 0 ... \n",
"Provedel 509 28-239 1994 0 ... \n",
"Maignan 500 27-131 1995 0 ... \n",
"Silvestri 512 31-254 1991 0 ... \n",
"Sepe 511 31-187 1991 0 ... \n",
"... ... ... ... ... ... \n",
"De Luca 122 24-117 1998 1 ... \n",
"Soule' 422 19-210 2003 5 ... \n",
"Lazetic 248 18-293 2004 1 ... \n",
"Voelkerling Persson -1 0 0 0 ... \n",
"Sanca 395 22-311 2000 3 ... \n",
"\n",
" gk_pct_goal_kicks_launched gk_goal_kick_length_avg \\\n",
"name \n",
"Meret 19.6 26.6 \n",
"Provedel 37.2 36.6 \n",
"Maignan 38.9 40.4 \n",
"Silvestri 40.9 38.2 \n",
"Sepe 48.4 41.7 \n",
"... ... ... \n",
"De Luca 0.0 0.0 \n",
"Soule' 0.0 0.0 \n",
"Lazetic 0.0 0.0 \n",
"Voelkerling Persson 0.0 0.0 \n",
"Sanca 0.0 0.0 \n",
"\n",
" gk_crosses gk_crosses_stopped gk_crosses_stopped_pct \\\n",
"name \n",
"Meret 142.0 6.0 4.2 \n",
"Provedel 201.0 5.0 2.5 \n",
"Maignan 65.0 5.0 7.7 \n",
"Silvestri 194.0 4.0 2.1 \n",
"Sepe 187.0 14.0 7.5 \n",
"... ... ... ... \n",
"De Luca 0.0 0.0 0.0 \n",
"Soule' 0.0 0.0 0.0 \n",
"Lazetic 0.0 0.0 0.0 \n",
"Voelkerling Persson 0.0 0.0 0.0 \n",
"Sanca 0.0 0.0 0.0 \n",
"\n",
" gk_def_actions_outside_pen_area \\\n",
"name \n",
"Meret 10.0 \n",
"Provedel 29.0 \n",
"Maignan 6.0 \n",
"Silvestri 5.0 \n",
"Sepe 9.0 \n",
"... ... \n",
"De Luca 0.0 \n",
"Soule' 0.0 \n",
"Lazetic 0.0 \n",
"Voelkerling Persson 0.0 \n",
"Sanca 0.0 \n",
"\n",
" gk_def_actions_outside_pen_area_per90 \\\n",
"name \n",
"Meret 0.71 \n",
"Provedel 2.08 \n",
"Maignan 0.86 \n",
"Silvestri 0.36 \n",
"Sepe 0.64 \n",
"... ... \n",
"De Luca 0.00 \n",
"Soule' 0.00 \n",
"Lazetic 0.00 \n",
"Voelkerling Persson 0.00 \n",
"Sanca 0.00 \n",
"\n",
" gk_avg_distance_def_actions vote_avg vote_std \n",
"name \n",
"Meret 15.1 6.214286 0.557875 \n",
"Provedel 17.6 6.321429 0.305143 \n",
"Maignan 12.9 6.357143 0.440315 \n",
"Silvestri 11.3 6.321429 0.485767 \n",
"Sepe 13.7 6.428571 0.371154 \n",
"... ... ... ... \n",
"De Luca 0.0 5.877688 0.485814 \n",
"Soule' 0.0 6.067846 0.581002 \n",
"Lazetic 0.0 6.170097 0.204814 \n",
"Voelkerling Persson 0.0 6.041983 0.689071 \n",
"Sanca 0.0 5.991021 0.262247 \n",
"\n",
"[554 rows x 165 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rx = pd.read_excel('mid_outputs/players_stats.xlsx', index_col = 3) \n",
"players = pd.DataFrame(rx)\n",
"\n",
"players\n"
]
},
{
"cell_type": "markdown",
"id": "ae37dfe3",
"metadata": {},
"source": [
"Function for merging match data (player, team, opponent team)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "71c8804e",
"metadata": {},
"outputs": [],
"source": [
"def player_match_data(player, pteam, oppteam):\n",
" if(not(player in players.index)):\n",
" return None\n",
" \n",
" pdata = players.loc[[player]]\n",
" \n",
" pteam_stats = team_data.loc[[pteam]].rename(index = {pteam : player})\n",
" \n",
" oppteam_stats = team_data.loc[[oppteam]].rename(index = {oppteam : player})\n",
" \n",
" oppteam_stats = oppteam_stats.rename(lambda x: 'opp_' + x, axis='columns')\n",
" \n",
" out = pd.concat([pdata, pteam_stats, oppteam_stats], axis = 1)\n",
" \n",
" return(out)\n",
" "
]
},
{
"cell_type": "markdown",
"id": "a6fdd15b",
"metadata": {},
"source": [
"Output to excel file data for a player. \n",
"\n",
"The file is copied and there the desired features are manually selected and printed."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "7eb4e666",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>id</th>\n",
" <th>r</th>\n",
" <th>team</th>\n",
" <th>surname</th>\n",
" <th>initial</th>\n",
" <th>fb_ID</th>\n",
" <th>age</th>\n",
" <th>birth_year</th>\n",
" <th>games</th>\n",
" <th>...</th>\n",
" <th>opp_vs_team_fouls</th>\n",
" <th>opp_vs_team_fouled</th>\n",
" <th>opp_vs_team_offsides</th>\n",
" <th>opp_vs_team_pens_won</th>\n",
" <th>opp_vs_team_pens_conceded</th>\n",
" <th>opp_vs_team_own_goals</th>\n",
" <th>opp_vs_team_ball_recoveries</th>\n",
" <th>opp_vs_team_aerials_won</th>\n",
" <th>opp_vs_team_aerials_lost</th>\n",
" <th>opp_vs_team_aerials_won_pct</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Frattesi</th>\n",
" <td>270</td>\n",
" <td>2848</td>\n",
" <td>C</td>\n",
" <td>Sassuolo</td>\n",
" <td>Frattesi</td>\n",
" <td>NaN</td>\n",
" <td>175</td>\n",
" <td>23-020</td>\n",
" <td>1999</td>\n",
" <td>14</td>\n",
" <td>...</td>\n",
" <td>150.0</td>\n",
" <td>168.0</td>\n",
" <td>19.0</td>\n",
" <td>0.0</td>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>834.0</td>\n",
" <td>181.0</td>\n",
" <td>211.0</td>\n",
" <td>46.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1 rows × 791 columns</p>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 id r team surname initial fb_ID age \\\n",
"Frattesi 270 2848 C Sassuolo Frattesi NaN 175 23-020 \n",
"\n",
" birth_year games ... opp_vs_team_fouls opp_vs_team_fouled \\\n",
"Frattesi 1999 14 ... 150.0 168.0 \n",
"\n",
" opp_vs_team_offsides opp_vs_team_pens_won \\\n",
"Frattesi 19.0 0.0 \n",
"\n",
" opp_vs_team_pens_conceded opp_vs_team_own_goals \\\n",
"Frattesi 5.0 1.0 \n",
"\n",
" opp_vs_team_ball_recoveries opp_vs_team_aerials_won \\\n",
"Frattesi 834.0 181.0 \n",
"\n",
" opp_vs_team_aerials_lost opp_vs_team_aerials_won_pct \n",
"Frattesi 211.0 46.2 \n",
"\n",
"[1 rows x 791 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test = player_match_data('Frattesi', 'Sassuolo', 'Atalanta')\n",
"test.to_excel('tmp/playermatchdata.xlsx')\n",
"\n",
"test"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "6b4c1b00",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Sassuolo'"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pteam = 'Sassuolo'\n",
"pteam_stats = team_data.loc[[pteam]]\n",
"pteam_stats.index[0]"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "6ea6df1f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['r',\n",
" 'fb_ID',\n",
" 'games',\n",
" 'games_starts',\n",
" 'minutes',\n",
" 'goals',\n",
" 'assists',\n",
" 'cards_yellow',\n",
" 'cards_red',\n",
" 'xg',\n",
" 'npxg',\n",
" 'shots_on_target',\n",
" 'shots_on_target_pct',\n",
" 'goals_per_shot',\n",
" 'goals_per_shot_on_target',\n",
" 'passes_completed',\n",
" 'passes_pct',\n",
" 'passes_into_final_third',\n",
" 'passes_into_penalty_area',\n",
" 'progressive_passes',\n",
" 'passes_live',\n",
" 'passes_dead',\n",
" 'through_balls',\n",
" 'passes_switches',\n",
" 'crosses',\n",
" 'corner_kicks',\n",
" 'dribble_tackles',\n",
" 'dribbles_vs',\n",
" 'dribble_tackles_pct',\n",
" 'dribbled_past',\n",
" 'blocks',\n",
" 'blocked_shots',\n",
" 'blocked_passes',\n",
" 'interceptions',\n",
" 'clearances',\n",
" 'errors',\n",
" 'touches',\n",
" 'touches_def_pen_area',\n",
" 'touches_def_3rd',\n",
" 'touches_mid_3rd',\n",
" 'touches_att_3rd',\n",
" 'touches_att_pen_area',\n",
" 'touches_live_ball',\n",
" 'dribbles_completed',\n",
" 'dribbles',\n",
" 'dribbles_completed_pct',\n",
" 'passes_received',\n",
" 'miscontrols',\n",
" 'dispossessed',\n",
" 'fouls',\n",
" 'fouled',\n",
" 'aerials_won',\n",
" 'aerials_lost',\n",
" 'aerials_won_pct',\n",
" 'team_possession',\n",
" 'team_goals_assists_per90',\n",
" 'team_goals_pens_per90',\n",
" 'team_goals_assists_pens_per90',\n",
" 'team_xg_per90',\n",
" 'team_gk_goals_against_per90',\n",
" 'team_gk_save_pct',\n",
" 'team_gk_clean_sheets_pct',\n",
" 'team_passes_pct',\n",
" 'team_passes_pct_medium',\n",
" 'team_passes_pct_long',\n",
" 'team_sca_per90',\n",
" 'team_gca_per90',\n",
" 'team_dribble_tackles_pct',\n",
" 'team_aerials_won_pct',\n",
" 'vs_team_possession',\n",
" 'vs_team_goals_per90',\n",
" 'vs_team_assists_per90',\n",
" 'vs_team_xg_per90',\n",
" 'vs_team_gk_save_pct',\n",
" 'vs_team_gk_clean_sheets_pct',\n",
" 'vs_team_gk_pct_passes_launched',\n",
" 'vs_team_gk_crosses_stopped_pct',\n",
" 'vs_team_shots_on_target_per90',\n",
" 'vs_team_passes_pct',\n",
" 'vs_team_passes_pct_short',\n",
" 'vs_team_passes_pct_medium',\n",
" 'vs_team_passes_pct_long',\n",
" 'vs_team_sca_per90',\n",
" 'vs_team_gca_per90',\n",
" 'vs_team_dribble_tackles_pct',\n",
" 'vs_team_dribbles_completed_pct',\n",
" 'vs_team_aerials_won_pct']"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rx = pd.read_excel('tmp/playermatchdata_sel.xlsx', index_col = 0, header = None) \n",
"\n",
"out = list()\n",
"\n",
"for i in range(1, rx.shape[1]):\n",
" if(rx[i][2] == \"x\"):\n",
" out.append(rx[i][0])\n",
" \n",
"out"
]
},
{
"cell_type": "markdown",
"id": "d4097382",
"metadata": {},
"source": [
"Define and select the dataset features: abs features and rel features.\n",
" \n",
"Rel features are divided by the player minutes played.\n",
"\n",
"Rel features (game corrected) are divided by the player number of games instead of minutes. \n",
"For example, a player who plays 20 minutes and scores, would be to match for stats averaging. It is better to consider the goals made per match."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "47bc651f",
"metadata": {},
"outputs": [],
"source": [
"features_abs = ['r',\n",
" 'games',\n",
" 'games_starts', \n",
" 'minutes',\n",
" 'shots_on_target_pct',\n",
" 'goals_per_shot',\n",
" 'goals_per_shot_on_target',\n",
" 'passes_pct',\n",
" 'dribble_tackles_pct',\n",
" 'dribbles_completed_pct',\n",
" 'aerials_won_pct',\n",
" 'team_possession',\n",
" 'team_goals_assists_per90',\n",
" 'team_goals_pens_per90',\n",
" 'team_goals_assists_pens_per90',\n",
" 'team_xg_per90',\n",
" 'team_gk_goals_against_per90',\n",
" 'team_gk_save_pct',\n",
" 'team_gk_clean_sheets_pct',\n",
" 'team_passes_pct',\n",
" 'team_passes_pct_medium',\n",
" 'team_passes_pct_long',\n",
" 'team_sca_per90',\n",
" 'team_gca_per90',\n",
" 'team_dribble_tackles_pct',\n",
" 'team_aerials_won_pct',\n",
" 'vs_team_possession',\n",
" 'vs_team_goals_per90',\n",
" 'vs_team_assists_per90',\n",
" 'vs_team_xg_per90',\n",
" 'vs_team_gk_save_pct',\n",
" 'vs_team_gk_clean_sheets_pct',\n",
" 'vs_team_gk_pct_passes_launched',\n",
" 'vs_team_gk_crosses_stopped_pct',\n",
" 'vs_team_shots_on_target_per90',\n",
" 'vs_team_passes_pct',\n",
" 'vs_team_passes_pct_short',\n",
" 'vs_team_passes_pct_medium',\n",
" 'vs_team_passes_pct_long',\n",
" 'vs_team_sca_per90',\n",
" 'vs_team_gca_per90',\n",
" 'vs_team_dribble_tackles_pct',\n",
" 'vs_team_dribbles_completed_pct',\n",
" 'vs_team_aerials_won_pct',\n",
" 'opp_team_possession',\n",
" 'opp_team_goals_assists_per90',\n",
" 'opp_team_goals_pens_per90',\n",
" 'opp_team_goals_assists_pens_per90',\n",
" 'opp_team_xg_per90',\n",
" 'opp_team_gk_goals_against_per90',\n",
" 'opp_team_gk_save_pct',\n",
" 'opp_team_gk_clean_sheets_pct',\n",
" 'opp_team_passes_pct',\n",
" 'opp_team_passes_pct_medium',\n",
" 'opp_team_passes_pct_long',\n",
" 'opp_team_sca_per90',\n",
" 'opp_team_gca_per90',\n",
" 'opp_team_dribble_tackles_pct',\n",
" 'opp_team_aerials_won_pct',\n",
" 'opp_vs_team_possession',\n",
" 'opp_vs_team_goals_per90',\n",
" 'opp_vs_team_assists_per90',\n",
" 'opp_vs_team_xg_per90',\n",
" 'opp_vs_team_gk_save_pct',\n",
" 'opp_vs_team_gk_clean_sheets_pct',\n",
" 'opp_vs_team_gk_pct_passes_launched',\n",
" 'opp_vs_team_gk_crosses_stopped_pct',\n",
" 'opp_vs_team_shots_on_target_per90',\n",
" 'opp_vs_team_passes_pct',\n",
" 'opp_vs_team_passes_pct_short',\n",
" 'opp_vs_team_passes_pct_medium',\n",
" 'opp_vs_team_passes_pct_long',\n",
" 'opp_vs_team_sca_per90',\n",
" 'opp_vs_team_gca_per90',\n",
" 'opp_vs_team_dribble_tackles_pct',\n",
" 'opp_vs_team_dribbles_completed_pct',\n",
" 'opp_vs_team_aerials_won_pct',\n",
" \n",
" 'vote_avg',\n",
" 'vote_std']\n",
"\n",
"features_rel = [\n",
" 'goals',\n",
" 'assists',\n",
" 'cards_yellow',\n",
" 'cards_red',\n",
" 'xg',\n",
" 'npxg',\n",
" 'shots_on_target',\n",
" 'passes_completed',\n",
" 'passes_into_final_third',\n",
" 'passes_into_penalty_area',\n",
" 'progressive_passes',\n",
" 'passes_live',\n",
" 'passes_dead',\n",
" 'through_balls',\n",
" 'passes_switches',\n",
" 'crosses',\n",
" 'corner_kicks',\n",
" 'dribble_tackles',\n",
" 'dribbles_vs',\n",
" 'dribbled_past',\n",
" 'blocks',\n",
" 'blocked_shots',\n",
" 'blocked_passes',\n",
" 'interceptions',\n",
" 'clearances',\n",
" 'errors',\n",
" 'touches',\n",
" 'touches_def_pen_area',\n",
" 'touches_def_3rd',\n",
" 'touches_mid_3rd',\n",
" 'touches_att_3rd',\n",
" 'touches_att_pen_area',\n",
" 'touches_live_ball',\n",
" 'dribbles_completed',\n",
" 'dribbles',\n",
" 'passes_received',\n",
" 'miscontrols',\n",
" 'dispossessed',\n",
" 'fouls',\n",
" 'fouled',\n",
" 'aerials_won',\n",
" 'aerials_lost']\n",
"\n",
"features_rel_gamecorr = [\n",
" 'goals',\n",
" 'assists',\n",
" 'xg',\n",
" 'npxg',\n",
" 'cards_yellow',\n",
" 'cards_red'\n",
"]"
]
},
{
"cell_type": "markdown",
"id": "ced70285",
"metadata": {},
"source": [
"Function for merging match data (player, team, opponent team) and select only the desired features, applying the desired corrections."
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "3f43d509",
"metadata": {},
"outputs": [],
"source": [
"def player_match_data_ext(player, pteam, oppteam):\n",
" pdata = player_match_data(player, pteam, oppteam)\n",
" \n",
" if(not isinstance(pdata, pd.DataFrame)):\n",
" return None\n",
" \n",
" out = pd.concat([pdata[features_abs], pdata[features_rel]], axis = 1)\n",
" \n",
" out[features_rel] = out[features_rel] / max(pdata['minutes'][0], 1)\n",
" \n",
" out[features_rel_gamecorr] = out[features_rel_gamecorr] * (pdata['minutes'][0] / max(pdata['games'][0], 1) / 90)\n",
" \n",
" return out\n",
" "
]
},
{
"cell_type": "markdown",
"id": "959bf152",
"metadata": {},
"source": [
"Columns variable for the match data, to be then added to votes data."
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "930d00c7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>r</th>\n",
" <th>games</th>\n",
" <th>games_starts</th>\n",
" <th>minutes</th>\n",
" <th>shots_on_target_pct</th>\n",
" <th>goals_per_shot</th>\n",
" <th>goals_per_shot_on_target</th>\n",
" <th>passes_pct</th>\n",
" <th>dribble_tackles_pct</th>\n",
" <th>dribbles_completed_pct</th>\n",
" <th>...</th>\n",
" <th>touches_live_ball</th>\n",
" <th>dribbles_completed</th>\n",
" <th>dribbles</th>\n",
" <th>passes_received</th>\n",
" <th>miscontrols</th>\n",
" <th>dispossessed</th>\n",
" <th>fouls</th>\n",
" <th>fouled</th>\n",
" <th>aerials_won</th>\n",
" <th>aerials_lost</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Frattesi</th>\n",
" <td>C</td>\n",
" <td>14</td>\n",
" <td>14</td>\n",
" <td>1129</td>\n",
" <td>50.0</td>\n",
" <td>0.13</td>\n",
" <td>0.27</td>\n",
" <td>75.6</td>\n",
" <td>52.6</td>\n",
" <td>57.6</td>\n",
" <td>...</td>\n",
" <td>0.476528</td>\n",
" <td>0.016829</td>\n",
" <td>0.029229</td>\n",
" <td>0.330381</td>\n",
" <td>0.019486</td>\n",
" <td>0.015943</td>\n",
" <td>0.011515</td>\n",
" <td>0.022143</td>\n",
" <td>0.009743</td>\n",
" <td>0.0062</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1 rows × 121 columns</p>\n",
"</div>"
],
"text/plain": [
" r games games_starts minutes shots_on_target_pct \\\n",
"Frattesi C 14 14 1129 50.0 \n",
"\n",
" goals_per_shot goals_per_shot_on_target passes_pct \\\n",
"Frattesi 0.13 0.27 75.6 \n",
"\n",
" dribble_tackles_pct dribbles_completed_pct ... touches_live_ball \\\n",
"Frattesi 52.6 57.6 ... 0.476528 \n",
"\n",
" dribbles_completed dribbles passes_received miscontrols \\\n",
"Frattesi 0.016829 0.029229 0.330381 0.019486 \n",
"\n",
" dispossessed fouls fouled aerials_won aerials_lost \n",
"Frattesi 0.015943 0.011515 0.022143 0.009743 0.0062 \n",
"\n",
"[1 rows x 121 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test = player_match_data_ext('Frattesi', 'Sassuolo', 'Atalanta')\n",
"\n",
"add_columns = test.columns\n",
"\n",
"test"
]
},
{
"cell_type": "markdown",
"id": "8d95c9ef",
"metadata": {},
"source": [
"Load Fantacalcio votes data for each match of the season."
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "3ae718d2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>matchday</th>\n",
" <th>player</th>\n",
" <th>team</th>\n",
" <th>oppteam</th>\n",
" <th>home</th>\n",
" <th>vote</th>\n",
" <th>goals</th>\n",
" <th>assists</th>\n",
" <th>cards_malus</th>\n",
" <th>fantavote</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>Musso</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>Toloi</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>7.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>Djimsiti</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>Hateboer</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>Okoli</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>5.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>4010</th>\n",
" <td>14</td>\n",
" <td>Sulemana I.</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4011</th>\n",
" <td>14</td>\n",
" <td>Lasagna</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4012</th>\n",
" <td>14</td>\n",
" <td>Kallon</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>5.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4013</th>\n",
" <td>14</td>\n",
" <td>Djuric</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>5.5</td>\n",
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" <tr>\n",
" <th>4014</th>\n",
" <td>14</td>\n",
" <td>Henry</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
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"</table>\n",
"<p>4015 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" matchday player team oppteam home vote goals assists \\\n",
"0 1 Musso Atalanta Sampdoria 0 6.0 0 0 \n",
"1 1 Toloi Atalanta Sampdoria 0 7.0 1 0 \n",
"2 1 Djimsiti Atalanta Sampdoria 0 6.0 0 0 \n",
"3 1 Hateboer Atalanta Sampdoria 0 6.0 0 0 \n",
"4 1 Okoli Atalanta Sampdoria 0 5.5 0 0 \n",
"... ... ... ... ... ... ... ... ... \n",
"4010 14 Sulemana I. Verona Juventus 1 6.0 0 0 \n",
"4011 14 Lasagna Verona Juventus 1 6.0 0 0 \n",
"4012 14 Kallon Verona Juventus 1 5.5 0 0 \n",
"4013 14 Djuric Verona Juventus 1 6.0 0 0 \n",
"4014 14 Henry Verona Juventus 1 6.5 0 0 \n",
"\n",
" cards_malus fantavote \n",
"0 0.5 5.5 \n",
"1 0.0 10.0 \n",
"2 0.0 6.0 \n",
"3 0.5 5.5 \n",
"4 0.5 5.0 \n",
"... ... ... \n",
"4010 0.0 6.0 \n",
"4011 0.0 6.0 \n",
"4012 0.0 5.5 \n",
"4013 0.5 5.5 \n",
"4014 0.0 6.5 \n",
"\n",
"[4015 rows x 10 columns]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"votes = pd.read_excel('mid_outputs/players_votes.xlsx', index_col = 0)\n",
"votes"
]
},
{
"cell_type": "markdown",
"id": "8cf677e4",
"metadata": {},
"source": [
"Merge votes data with match data for the player."
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "ec0bc56b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"100\n",
"200\n",
"300\n",
"400\n",
"500\n",
"600\n",
"700\n",
"800\n",
"900\n",
"1000\n",
"1100\n",
"1300\n",
"1400\n",
"1500\n",
"1600\n",
"1700\n",
"1800\n",
"1900\n",
"2000\n",
"2100\n",
"2200\n",
"2300\n",
"2400\n",
"2500\n",
"2600\n",
"2700\n",
"2800\n",
"2900\n",
"3000\n",
"3100\n",
"3200\n",
"3300\n",
"3400\n",
"3500\n",
"3600\n",
"3700\n",
"3800\n",
"3900\n",
"4000\n"
]
}
],
"source": [
"db = votes.copy()\n",
"\n",
"delta = pd.DataFrame(columns = add_columns)\n",
"\n",
"for i in range(db.shape[0]):\n",
" ext_data = player_match_data_ext(db['player'][i], db['team'][i], db['oppteam'][i])\n",
" \n",
" if(not isinstance(ext_data, pd.DataFrame)):\n",
" continue\n",
" \n",
" ext_data = ext_data.rename(index = {db['player'][i] : i})\n",
" \n",
" delta = pd.concat([delta, ext_data], axis = 0)\n",
" \n",
" if(i % 100 == 0):\n",
" print(i)\n",
" \n",
"db = pd.concat([db, delta], axis = 1)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "b292f9f9",
"metadata": {},
"outputs": [
{
"data": {
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" <td>0</td>\n",
" <td>6.0</td>\n",
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" <tr>\n",
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" <tr>\n",
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" <td>0.024242</td>\n",
" <td>0.015152</td>\n",
" <td>0.039394</td>\n",
" <td>0.039394</td>\n",
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"</div>"
],
"text/plain": [
" matchday player team oppteam home vote goals assists \\\n",
"0 1 Musso Atalanta Sampdoria 0 6.0 0 0 \n",
"1 1 Toloi Atalanta Sampdoria 0 7.0 1 0 \n",
"2 1 Djimsiti Atalanta Sampdoria 0 6.0 0 0 \n",
"3 1 Hateboer Atalanta Sampdoria 0 6.0 0 0 \n",
"4 1 Okoli Atalanta Sampdoria 0 5.5 0 0 \n",
"... ... ... ... ... ... ... ... ... \n",
"4010 14 Sulemana I. Verona Juventus 1 6.0 0 0 \n",
"4011 14 Lasagna Verona Juventus 1 6.0 0 0 \n",
"4012 14 Kallon Verona Juventus 1 5.5 0 0 \n",
"4013 14 Djuric Verona Juventus 1 6.0 0 0 \n",
"4014 14 Henry Verona Juventus 1 6.5 0 0 \n",
"\n",
" cards_malus fantavote ... touches_live_ball dribbles_completed \\\n",
"0 0.5 5.5 ... 0.000000 0.000000 \n",
"1 0.0 10.0 ... 0.617096 0.001171 \n",
"2 0.0 6.0 ... 0.736842 0.000000 \n",
"3 0.5 5.5 ... 0.574423 0.002096 \n",
"4 0.5 5.0 ... 0.598540 0.000000 \n",
"... ... ... ... ... ... \n",
"4010 0.0 6.0 ... NaN NaN \n",
"4011 0.0 6.0 ... 0.279255 0.006649 \n",
"4012 0.0 5.5 ... 0.417949 0.007692 \n",
"4013 0.5 5.5 ... 0.473214 0.000000 \n",
"4014 0.0 6.5 ... 0.342424 0.003030 \n",
"\n",
" dribbles passes_received miscontrols dispossessed fouls fouled \\\n",
"0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"1 0.004684 0.357143 0.007026 0.001171 0.009368 0.005855 \n",
"2 0.002924 0.511696 0.002924 0.008772 0.002924 0.002924 \n",
"3 0.005241 0.339623 0.006289 0.005241 0.013627 0.002096 \n",
"4 0.001217 0.278589 0.013382 0.003650 0.015815 0.008516 \n",
"... ... ... ... ... ... ... \n",
"4010 NaN NaN NaN NaN NaN NaN \n",
"4011 0.018617 0.186170 0.038564 0.023936 0.021277 0.018617 \n",
"4012 0.038462 0.289744 0.038462 0.025641 0.017949 0.023077 \n",
"4013 0.000000 0.401786 0.022321 0.000000 0.022321 0.022321 \n",
"4014 0.014141 0.282828 0.049495 0.025253 0.024242 0.015152 \n",
"\n",
" aerials_won aerials_lost \n",
"0 0.000000 0.000000 \n",
"1 0.018735 0.008197 \n",
"2 0.005848 0.008772 \n",
"3 0.015723 0.012579 \n",
"4 0.048662 0.026764 \n",
"... ... ... \n",
"4010 NaN NaN \n",
"4011 0.005319 0.029255 \n",
"4012 0.010256 0.028205 \n",
"4013 0.178571 0.066964 \n",
"4014 0.039394 0.039394 \n",
"\n",
"[4015 rows x 131 columns]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"db"
]
},
{
"cell_type": "markdown",
"id": "d237f87b",
"metadata": {},
"source": [
"Remove undesired database entries."
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "1db9f77f",
"metadata": {},
"outputs": [],
"source": [
"db = db.drop(db[db.r == 'P'].index) # remove goalkeepers\n",
"db = db.drop(db[db.r != db.r].index) # remove non existing players (by searching NaN values)\n",
"db = db.drop(db[db.xg != db.xg].index)\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "f56df3ca",
"metadata": {},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>matchday</th>\n",
" <th>player</th>\n",
" <th>team</th>\n",
" <th>oppteam</th>\n",
" <th>home</th>\n",
" <th>vote</th>\n",
" <th>goals</th>\n",
" <th>assists</th>\n",
" <th>cards_malus</th>\n",
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" <th>...</th>\n",
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>Toloi</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>7.0</td>\n",
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" <th>2</th>\n",
" <td>1</td>\n",
" <td>Djimsiti</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>1</td>\n",
" <td>Hateboer</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0.012579</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>Okoli</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>5.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>5.0</td>\n",
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" <td>0.001217</td>\n",
" <td>0.278589</td>\n",
" <td>0.013382</td>\n",
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" <td>0.015815</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>1</td>\n",
" <td>Zortea</td>\n",
" <td>Atalanta</td>\n",
" <td>Sampdoria</td>\n",
" <td>0</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
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" <td>0.052910</td>\n",
" <td>0.111111</td>\n",
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" <tr>\n",
" <th>4009</th>\n",
" <td>14</td>\n",
" <td>Terracciano F.</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0.008889</td>\n",
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" <td>0.024444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4011</th>\n",
" <td>14</td>\n",
" <td>Lasagna</td>\n",
" <td>Verona</td>\n",
" <td>Juventus</td>\n",
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" <td>6.0</td>\n",
" <td>0</td>\n",
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" <td>Verona</td>\n",
" <td>Juventus</td>\n",
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" <td>5.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0.028205</td>\n",
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" <td>14</td>\n",
" <td>Djuric</td>\n",
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" <td>6.0</td>\n",
" <td>0</td>\n",
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" <tr>\n",
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" <td>14</td>\n",
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" <td>Verona</td>\n",
" <td>Juventus</td>\n",
" <td>1</td>\n",
" <td>6.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>6.5</td>\n",
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" <td>0.003030</td>\n",
" <td>0.014141</td>\n",
" <td>0.282828</td>\n",
" <td>0.049495</td>\n",
" <td>0.025253</td>\n",
" <td>0.024242</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>3717 rows × 131 columns</p>\n",
"</div>"
],
"text/plain": [
" matchday player team oppteam home vote goals \\\n",
"1 1 Toloi Atalanta Sampdoria 0 7.0 1 \n",
"2 1 Djimsiti Atalanta Sampdoria 0 6.0 0 \n",
"3 1 Hateboer Atalanta Sampdoria 0 6.0 0 \n",
"4 1 Okoli Atalanta Sampdoria 0 5.5 0 \n",
"5 1 Zortea Atalanta Sampdoria 0 6.0 0 \n",
"... ... ... ... ... ... ... ... \n",
"4009 14 Terracciano F. Verona Juventus 1 6.0 0 \n",
"4011 14 Lasagna Verona Juventus 1 6.0 0 \n",
"4012 14 Kallon Verona Juventus 1 5.5 0 \n",
"4013 14 Djuric Verona Juventus 1 6.0 0 \n",
"4014 14 Henry Verona Juventus 1 6.5 0 \n",
"\n",
" assists cards_malus fantavote ... touches_live_ball \\\n",
"1 0 0.0 10.0 ... 0.617096 \n",
"2 0 0.0 6.0 ... 0.736842 \n",
"3 0 0.5 5.5 ... 0.574423 \n",
"4 0 0.5 5.0 ... 0.598540 \n",
"5 0 0.5 5.5 ... 0.634921 \n",
"... ... ... ... ... ... \n",
"4009 0 0.0 6.0 ... 0.477778 \n",
"4011 0 0.0 6.0 ... 0.279255 \n",
"4012 0 0.0 5.5 ... 0.417949 \n",
"4013 0 0.5 5.5 ... 0.473214 \n",
"4014 0 0.0 6.5 ... 0.342424 \n",
"\n",
" dribbles_completed dribbles passes_received miscontrols dispossessed \\\n",
"1 0.001171 0.004684 0.357143 0.007026 0.001171 \n",
"2 0.000000 0.002924 0.511696 0.002924 0.008772 \n",
"3 0.002096 0.005241 0.339623 0.006289 0.005241 \n",
"4 0.000000 0.001217 0.278589 0.013382 0.003650 \n",
"5 0.052910 0.111111 0.328042 0.026455 0.005291 \n",
"... ... ... ... ... ... \n",
"4009 0.000000 0.008889 0.271111 0.015556 0.006667 \n",
"4011 0.006649 0.018617 0.186170 0.038564 0.023936 \n",
"4012 0.007692 0.038462 0.289744 0.038462 0.025641 \n",
"4013 0.000000 0.000000 0.401786 0.022321 0.000000 \n",
"4014 0.003030 0.014141 0.282828 0.049495 0.025253 \n",
"\n",
" fouls fouled aerials_won aerials_lost \n",
"1 0.009368 0.005855 0.018735 0.008197 \n",
"2 0.002924 0.002924 0.005848 0.008772 \n",
"3 0.013627 0.002096 0.015723 0.012579 \n",
"4 0.015815 0.008516 0.048662 0.026764 \n",
"5 0.021164 0.000000 0.026455 0.005291 \n",
"... ... ... ... ... \n",
"4009 0.008889 0.022222 0.020000 0.024444 \n",
"4011 0.021277 0.018617 0.005319 0.029255 \n",
"4012 0.017949 0.023077 0.010256 0.028205 \n",
"4013 0.022321 0.022321 0.178571 0.066964 \n",
"4014 0.024242 0.015152 0.039394 0.039394 \n",
"\n",
"[3717 rows x 131 columns]"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"db"
]
},
{
"cell_type": "markdown",
"id": "ab69d09e",
"metadata": {},
"source": [
"Save outfield players database to file."
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "df26c8e0",
"metadata": {},
"outputs": [],
"source": [
"db.to_excel('mid_outputs/database_entries.xlsx')"
]
},
{
"cell_type": "markdown",
"id": "38b564d2",
"metadata": {},
"source": [
"Do the same process for goalkeepers, generating a different database."
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "4d06576a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 - matchday\n",
"1 - player\n",
"2 - team\n",
"3 - oppteam\n",
"4 - home\n",
"5 - vote\n",
"6 - goals\n",
"7 - assists\n",
"8 - cards_malus\n",
"9 - fantavote\n",
"10 - r\n",
"11 - games\n",
"12 - games_starts\n",
"13 - minutes\n",
"14 - shots_on_target_pct\n",
"15 - goals_per_shot\n",
"16 - goals_per_shot_on_target\n",
"17 - passes_pct\n",
"18 - dribble_tackles_pct\n",
"19 - dribbles_completed_pct\n",
"20 - aerials_won_pct\n",
"21 - team_possession\n",
"22 - team_goals_assists_per90\n",
"23 - team_goals_pens_per90\n",
"24 - team_goals_assists_pens_per90\n",
"25 - team_xg_per90\n",
"26 - team_gk_goals_against_per90\n",
"27 - team_gk_save_pct\n",
"28 - team_gk_clean_sheets_pct\n",
"29 - team_passes_pct\n",
"30 - team_passes_pct_medium\n",
"31 - team_passes_pct_long\n",
"32 - team_sca_per90\n",
"33 - team_gca_per90\n",
"34 - team_dribble_tackles_pct\n",
"35 - team_aerials_won_pct\n",
"36 - vs_team_possession\n",
"37 - vs_team_goals_per90\n",
"38 - vs_team_assists_per90\n",
"39 - vs_team_xg_per90\n",
"40 - vs_team_gk_save_pct\n",
"41 - vs_team_gk_clean_sheets_pct\n",
"42 - vs_team_gk_pct_passes_launched\n",
"43 - vs_team_gk_crosses_stopped_pct\n",
"44 - vs_team_shots_on_target_per90\n",
"45 - vs_team_passes_pct\n",
"46 - vs_team_passes_pct_short\n",
"47 - vs_team_passes_pct_medium\n",
"48 - vs_team_passes_pct_long\n",
"49 - vs_team_sca_per90\n",
"50 - vs_team_gca_per90\n",
"51 - vs_team_dribble_tackles_pct\n",
"52 - vs_team_dribbles_completed_pct\n",
"53 - vs_team_aerials_won_pct\n",
"54 - opp_team_possession\n",
"55 - opp_team_goals_assists_per90\n",
"56 - opp_team_goals_pens_per90\n",
"57 - opp_team_goals_assists_pens_per90\n",
"58 - opp_team_xg_per90\n",
"59 - opp_team_gk_goals_against_per90\n",
"60 - opp_team_gk_save_pct\n",
"61 - opp_team_gk_clean_sheets_pct\n",
"62 - opp_team_passes_pct\n",
"63 - opp_team_passes_pct_medium\n",
"64 - opp_team_passes_pct_long\n",
"65 - opp_team_sca_per90\n",
"66 - opp_team_gca_per90\n",
"67 - opp_team_dribble_tackles_pct\n",
"68 - opp_team_aerials_won_pct\n",
"69 - opp_vs_team_possession\n",
"70 - opp_vs_team_goals_per90\n",
"71 - opp_vs_team_assists_per90\n",
"72 - opp_vs_team_xg_per90\n",
"73 - opp_vs_team_gk_save_pct\n",
"74 - opp_vs_team_gk_clean_sheets_pct\n",
"75 - opp_vs_team_gk_pct_passes_launched\n",
"76 - opp_vs_team_gk_crosses_stopped_pct\n",
"77 - opp_vs_team_shots_on_target_per90\n",
"78 - opp_vs_team_passes_pct\n",
"79 - opp_vs_team_passes_pct_short\n",
"80 - opp_vs_team_passes_pct_medium\n",
"81 - opp_vs_team_passes_pct_long\n",
"82 - opp_vs_team_sca_per90\n",
"83 - opp_vs_team_gca_per90\n",
"84 - opp_vs_team_dribble_tackles_pct\n",
"85 - opp_vs_team_dribbles_completed_pct\n",
"86 - opp_vs_team_aerials_won_pct\n",
"87 - vote_avg\n",
"88 - vote_std\n",
"89 - goals\n",
"90 - assists\n",
"91 - cards_yellow\n",
"92 - cards_red\n",
"93 - xg\n",
"94 - npxg\n",
"95 - shots_on_target\n",
"96 - passes_completed\n",
"97 - passes_into_final_third\n",
"98 - passes_into_penalty_area\n",
"99 - progressive_passes\n",
"100 - passes_live\n",
"101 - passes_dead\n",
"102 - through_balls\n",
"103 - passes_switches\n",
"104 - crosses\n",
"105 - corner_kicks\n",
"106 - dribble_tackles\n",
"107 - dribbles_vs\n",
"108 - dribbled_past\n",
"109 - blocks\n",
"110 - blocked_shots\n",
"111 - blocked_passes\n",
"112 - interceptions\n",
"113 - clearances\n",
"114 - errors\n",
"115 - touches\n",
"116 - touches_def_pen_area\n",
"117 - touches_def_3rd\n",
"118 - touches_mid_3rd\n",
"119 - touches_att_3rd\n",
"120 - touches_att_pen_area\n",
"121 - touches_live_ball\n",
"122 - dribbles_completed\n",
"123 - dribbles\n",
"124 - passes_received\n",
"125 - miscontrols\n",
"126 - dispossessed\n",
"127 - fouls\n",
"128 - fouled\n",
"129 - aerials_won\n",
"130 - aerials_lost\n"
]
}
],
"source": [
"for i in range(db.columns.shape[0]):\n",
" print(str(i) + \" - \" + str(db.columns[i]))"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "01bb7413",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['r',\n",
" 'fb_ID',\n",
" 'gk_games',\n",
" 'gk_games_starts',\n",
" 'gk_minutes',\n",
" 'gk_goals_against_per90',\n",
" 'gk_shots_on_target_against',\n",
" 'gk_saves',\n",
" 'gk_save_pct',\n",
" 'gk_clean_sheets_pct',\n",
" 'gk_free_kick_goals_against',\n",
" 'gk_corner_kick_goals_against',\n",
" 'gk_own_goals_against',\n",
" 'gk_psxg',\n",
" 'gk_psnpxg_per_shot_on_target_against',\n",
" 'gk_psxg_net',\n",
" 'gk_psxg_net_per90',\n",
" 'gk_passes_completed_launched',\n",
" 'gk_passes_launched',\n",
" 'gk_passes_pct_launched',\n",
" 'gk_passes',\n",
" 'gk_passes_throws',\n",
" 'gk_pct_passes_launched',\n",
" 'gk_passes_length_avg',\n",
" 'gk_goal_kicks',\n",
" 'gk_pct_goal_kicks_launched',\n",
" 'gk_goal_kick_length_avg',\n",
" 'gk_crosses',\n",
" 'gk_crosses_stopped',\n",
" 'gk_crosses_stopped_pct',\n",
" 'gk_def_actions_outside_pen_area',\n",
" 'gk_def_actions_outside_pen_area_per90',\n",
" 'gk_avg_distance_def_actions',\n",
" 'team_possession',\n",
" 'team_goals_assists_per90',\n",
" 'team_goals_pens_per90',\n",
" 'team_goals_assists_pens_per90',\n",
" 'team_xg_per90',\n",
" 'team_gk_goals_against_per90',\n",
" 'team_gk_save_pct',\n",
" 'team_gk_clean_sheets_pct',\n",
" 'team_passes_pct',\n",
" 'team_passes_pct_medium',\n",
" 'team_passes_pct_long',\n",
" 'team_sca_per90',\n",
" 'team_gca_per90',\n",
" 'team_dribble_tackles_pct',\n",
" 'team_aerials_won_pct',\n",
" 'vs_team_possession',\n",
" 'vs_team_goals_per90',\n",
" 'vs_team_assists_per90',\n",
" 'vs_team_xg_per90',\n",
" 'vs_team_gk_save_pct',\n",
" 'vs_team_gk_clean_sheets_pct',\n",
" 'vs_team_gk_pct_passes_launched',\n",
" 'vs_team_gk_crosses_stopped_pct',\n",
" 'vs_team_shots_on_target_per90',\n",
" 'vs_team_passes_pct',\n",
" 'vs_team_passes_pct_short',\n",
" 'vs_team_passes_pct_medium',\n",
" 'vs_team_passes_pct_long',\n",
" 'vs_team_sca_per90',\n",
" 'vs_team_gca_per90',\n",
" 'vs_team_dribble_tackles_pct',\n",
" 'vs_team_dribbles_completed_pct',\n",
" 'vs_team_aerials_won_pct']"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rx = pd.read_excel('tmp/playermatchdata_sel_gk.xlsx', index_col = 0, header = None) \n",
"\n",
"out = list()\n",
"\n",
"for i in range(1, rx.shape[1]):\n",
" if(rx[i][2] == \"x\"):\n",
" out.append(rx[i][0])\n",
" \n",
"out"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "02f961d8",
"metadata": {},
"outputs": [],
"source": [
"features_abs_gk = [\n",
" 'gk_games',\n",
" 'gk_games_starts',\n",
" 'gk_minutes',\n",
" 'gk_goals_against_per90', \n",
" 'gk_save_pct',\n",
" 'gk_clean_sheets_pct',\n",
" 'gk_psxg_net_per90',\n",
" 'gk_passes_pct_launched',\n",
" 'gk_pct_passes_launched',\n",
" 'gk_passes_length_avg',\n",
" 'gk_pct_goal_kicks_launched',\n",
" 'gk_goal_kick_length_avg',\n",
" 'gk_crosses_stopped_pct',\n",
" 'gk_def_actions_outside_pen_area_per90',\n",
" 'gk_avg_distance_def_actions',\n",
" \n",
" 'team_possession',\n",
" 'team_goals_assists_per90',\n",
" 'team_goals_pens_per90',\n",
" 'team_goals_assists_pens_per90',\n",
" 'team_xg_per90',\n",
" 'team_gk_goals_against_per90',\n",
" 'team_gk_save_pct',\n",
" 'team_gk_clean_sheets_pct',\n",
" 'team_passes_pct',\n",
" 'team_passes_pct_medium',\n",
" 'team_passes_pct_long',\n",
" 'team_sca_per90',\n",
" 'team_gca_per90',\n",
" 'team_dribble_tackles_pct',\n",
" 'team_aerials_won_pct',\n",
" 'vs_team_possession',\n",
" 'vs_team_goals_per90',\n",
" 'vs_team_assists_per90',\n",
" 'vs_team_xg_per90',\n",
" 'vs_team_gk_save_pct',\n",
" 'vs_team_gk_clean_sheets_pct',\n",
" 'vs_team_gk_pct_passes_launched',\n",
" 'vs_team_gk_crosses_stopped_pct',\n",
" 'vs_team_shots_on_target_per90',\n",
" 'vs_team_passes_pct',\n",
" 'vs_team_passes_pct_short',\n",
" 'vs_team_passes_pct_medium',\n",
" 'vs_team_passes_pct_long',\n",
" 'vs_team_sca_per90',\n",
" 'vs_team_gca_per90',\n",
" 'vs_team_dribble_tackles_pct',\n",
" 'vs_team_dribbles_completed_pct',\n",
" 'vs_team_aerials_won_pct',\n",
" 'opp_team_possession',\n",
" 'opp_team_goals_assists_per90',\n",
" 'opp_team_goals_pens_per90',\n",
" 'opp_team_goals_assists_pens_per90',\n",
" 'opp_team_xg_per90',\n",
" 'opp_team_gk_goals_against_per90',\n",
" 'opp_team_gk_save_pct',\n",
" 'opp_team_gk_clean_sheets_pct',\n",
" 'opp_team_passes_pct',\n",
" 'opp_team_passes_pct_medium',\n",
" 'opp_team_passes_pct_long',\n",
" 'opp_team_sca_per90',\n",
" 'opp_team_gca_per90',\n",
" 'opp_team_dribble_tackles_pct',\n",
" 'opp_team_aerials_won_pct',\n",
" 'opp_vs_team_possession',\n",
" 'opp_vs_team_goals_per90',\n",
" 'opp_vs_team_assists_per90',\n",
" 'opp_vs_team_xg_per90',\n",
" 'opp_vs_team_gk_save_pct',\n",
" 'opp_vs_team_gk_clean_sheets_pct',\n",
" 'opp_vs_team_gk_pct_passes_launched',\n",
" 'opp_vs_team_gk_crosses_stopped_pct',\n",
" 'opp_vs_team_shots_on_target_per90',\n",
" 'opp_vs_team_passes_pct',\n",
" 'opp_vs_team_passes_pct_short',\n",
" 'opp_vs_team_passes_pct_medium',\n",
" 'opp_vs_team_passes_pct_long',\n",
" 'opp_vs_team_sca_per90',\n",
" 'opp_vs_team_gca_per90',\n",
" 'opp_vs_team_dribble_tackles_pct',\n",
" 'opp_vs_team_dribbles_completed_pct',\n",
" 'opp_vs_team_aerials_won_pct',\n",
" \n",
" 'vote_avg',\n",
" 'vote_std']\n",
"\n",
"features_rel_gk = [\n",
" 'gk_shots_on_target_against',\n",
" 'gk_saves',\n",
" 'gk_free_kick_goals_against',\n",
" 'gk_corner_kick_goals_against',\n",
" 'gk_own_goals_against',\n",
" 'gk_psxg',\n",
" 'gk_psnpxg_per_shot_on_target_against',\n",
" 'gk_psxg_net',\n",
" 'gk_passes_completed_launched',\n",
" 'gk_passes_launched',\n",
" 'gk_passes',\n",
" 'gk_passes_throws',\n",
" 'gk_goal_kicks',\n",
" 'gk_crosses',\n",
" 'gk_crosses_stopped',\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "5e3694a0",
"metadata": {},
"outputs": [],
"source": [
"def player_match_data_ext_gk(player, pteam, oppteam):\n",
" pdata = player_match_data(player, pteam, oppteam)\n",
" \n",
" if(not isinstance(pdata, pd.DataFrame)):\n",
" return None\n",
" \n",
" if(pdata['gk_games'][0] <= 0):\n",
" return None\n",
" \n",
" out = pd.concat([pdata[features_abs_gk], pdata[features_rel_gk]], axis = 1)\n",
" \n",
" out[features_rel_gk] = out[features_rel_gk] / max(pdata['minutes'][0], 1)\n",
"\n",
" return out\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "9b671646",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>gk_games</th>\n",
" <th>gk_games_starts</th>\n",
" <th>gk_minutes</th>\n",
" <th>gk_goals_against_per90</th>\n",
" <th>gk_save_pct</th>\n",
" <th>gk_clean_sheets_pct</th>\n",
" <th>gk_psxg_net_per90</th>\n",
" <th>gk_passes_pct_launched</th>\n",
" <th>gk_pct_passes_launched</th>\n",
" <th>gk_passes_length_avg</th>\n",
" <th>...</th>\n",
" <th>gk_psxg</th>\n",
" <th>gk_psnpxg_per_shot_on_target_against</th>\n",
" <th>gk_psxg_net</th>\n",
" <th>gk_passes_completed_launched</th>\n",
" <th>gk_passes_launched</th>\n",
" <th>gk_passes</th>\n",
" <th>gk_passes_throws</th>\n",
" <th>gk_goal_kicks</th>\n",
" <th>gk_crosses</th>\n",
" <th>gk_crosses_stopped</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Consigli</th>\n",
" <td>14.0</td>\n",
" <td>14.0</td>\n",
" <td>1260</td>\n",
" <td>1.36</td>\n",
" <td>58.5</td>\n",
" <td>35.7</td>\n",
" <td>-0.17</td>\n",
" <td>41.0</td>\n",
" <td>31.0</td>\n",
" <td>34.7</td>\n",
" <td>...</td>\n",
" <td>16.6</td>\n",
" <td>0.37</td>\n",
" <td>-2.4</td>\n",
" <td>84.0</td>\n",
" <td>205.0</td>\n",
" <td>523.0</td>\n",
" <td>77.0</td>\n",
" <td>134.0</td>\n",
" <td>189.0</td>\n",
" <td>13.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1 rows × 98 columns</p>\n",
"</div>"
],
"text/plain": [
" gk_games gk_games_starts gk_minutes gk_goals_against_per90 \\\n",
"Consigli 14.0 14.0 1260 1.36 \n",
"\n",
" gk_save_pct gk_clean_sheets_pct gk_psxg_net_per90 \\\n",
"Consigli 58.5 35.7 -0.17 \n",
"\n",
" gk_passes_pct_launched gk_pct_passes_launched \\\n",
"Consigli 41.0 31.0 \n",
"\n",
" gk_passes_length_avg ... gk_psxg \\\n",
"Consigli 34.7 ... 16.6 \n",
"\n",
" gk_psnpxg_per_shot_on_target_against gk_psxg_net \\\n",
"Consigli 0.37 -2.4 \n",
"\n",
" gk_passes_completed_launched gk_passes_launched gk_passes \\\n",
"Consigli 84.0 205.0 523.0 \n",
"\n",
" gk_passes_throws gk_goal_kicks gk_crosses gk_crosses_stopped \n",
"Consigli 77.0 134.0 189.0 13.0 \n",
"\n",
"[1 rows x 98 columns]"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test = player_match_data_ext_gk('Consigli', 'Sassuolo', 'Atalanta')\n",
"\n",
"add_columns_gk = test.columns\n",
"\n",
"test"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "33f805a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"100\n",
"200\n",
"300\n",
"400\n",
"500\n",
"600\n",
"700\n",
"800\n",
"900\n",
"1000\n",
"1100\n"
]
}
],
"source": [
"db_gk = votes.copy()\n",
"\n",
"delta = pd.DataFrame(columns = add_columns_gk)\n",
"\n",
"for i in range(db_gk.shape[0]):\n",
" ext_data = player_match_data_ext_gk(db_gk['player'][i], db_gk['team'][i], db_gk['oppteam'][i])\n",
" \n",
" if(i % 100 == 0):\n",
" print(i)\n",
" \n",
" if(not isinstance(ext_data, pd.DataFrame)):\n",
" continue\n",
" \n",
" ext_data = ext_data.rename(index = {db_gk['player'][i] : i})\n",
" \n",
" delta = pd.concat([delta, ext_data], axis = 0)\n",
" \n",
" \n",
" \n",
"db_gk = pd.concat([db_gk, delta], axis = 1)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4d484846",
"metadata": {},
"outputs": [],
"source": [
"db_gk"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "adab3577",
"metadata": {},
"outputs": [],
"source": [
"db_gk = db_gk.drop(db_gk[db_gk.gk_games != db_gk.gk_games].index) # remove non extisting players"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e7ae792d",
"metadata": {},
"outputs": [],
"source": [
"db_gk"
]
},
{
"cell_type": "markdown",
"id": "8dbb7476",
"metadata": {},
"source": [
"Save goalkeepers players database to file."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d8b8b6da",
"metadata": {},
"outputs": [],
"source": [
"db_gk.to_excel('mid_outputs/database_entries_gk.xlsx')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "54519b24",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 - matchday\n",
"1 - player\n",
"2 - team\n",
"3 - oppteam\n",
"4 - home\n",
"5 - vote\n",
"6 - goals\n",
"7 - assists\n",
"8 - cards_malus\n",
"9 - fantavote\n",
"10 - gk_games\n",
"11 - gk_games_starts\n",
"12 - gk_minutes\n",
"13 - gk_goals_against_per90\n",
"14 - gk_save_pct\n",
"15 - gk_clean_sheets_pct\n",
"16 - gk_psxg_net_per90\n",
"17 - gk_passes_pct_launched\n",
"18 - gk_pct_passes_launched\n",
"19 - gk_passes_length_avg\n",
"20 - gk_pct_goal_kicks_launched\n",
"21 - gk_goal_kick_length_avg\n",
"22 - gk_crosses_stopped_pct\n",
"23 - gk_def_actions_outside_pen_area_per90\n",
"24 - gk_avg_distance_def_actions\n",
"25 - team_possession\n",
"26 - team_goals_assists_per90\n",
"27 - team_goals_pens_per90\n",
"28 - team_goals_assists_pens_per90\n",
"29 - team_xg_per90\n",
"30 - team_gk_goals_against_per90\n",
"31 - team_gk_save_pct\n",
"32 - team_gk_clean_sheets_pct\n",
"33 - team_passes_pct\n",
"34 - team_passes_pct_medium\n",
"35 - team_passes_pct_long\n",
"36 - team_sca_per90\n",
"37 - team_gca_per90\n",
"38 - team_dribble_tackles_pct\n",
"39 - team_aerials_won_pct\n",
"40 - vs_team_possession\n",
"41 - vs_team_goals_per90\n",
"42 - vs_team_assists_per90\n",
"43 - vs_team_xg_per90\n",
"44 - vs_team_gk_save_pct\n",
"45 - vs_team_gk_clean_sheets_pct\n",
"46 - vs_team_gk_pct_passes_launched\n",
"47 - vs_team_gk_crosses_stopped_pct\n",
"48 - vs_team_shots_on_target_per90\n",
"49 - vs_team_passes_pct\n",
"50 - vs_team_passes_pct_short\n",
"51 - vs_team_passes_pct_medium\n",
"52 - vs_team_passes_pct_long\n",
"53 - vs_team_sca_per90\n",
"54 - vs_team_gca_per90\n",
"55 - vs_team_dribble_tackles_pct\n",
"56 - vs_team_dribbles_completed_pct\n",
"57 - vs_team_aerials_won_pct\n",
"58 - opp_team_possession\n",
"59 - opp_team_goals_assists_per90\n",
"60 - opp_team_goals_pens_per90\n",
"61 - opp_team_goals_assists_pens_per90\n",
"62 - opp_team_xg_per90\n",
"63 - opp_team_gk_goals_against_per90\n",
"64 - opp_team_gk_save_pct\n",
"65 - opp_team_gk_clean_sheets_pct\n",
"66 - opp_team_passes_pct\n",
"67 - opp_team_passes_pct_medium\n",
"68 - opp_team_passes_pct_long\n",
"69 - opp_team_sca_per90\n",
"70 - opp_team_gca_per90\n",
"71 - opp_team_dribble_tackles_pct\n",
"72 - opp_team_aerials_won_pct\n",
"73 - opp_vs_team_possession\n",
"74 - opp_vs_team_goals_per90\n",
"75 - opp_vs_team_assists_per90\n",
"76 - opp_vs_team_xg_per90\n",
"77 - opp_vs_team_gk_save_pct\n",
"78 - opp_vs_team_gk_clean_sheets_pct\n",
"79 - opp_vs_team_gk_pct_passes_launched\n",
"80 - opp_vs_team_gk_crosses_stopped_pct\n",
"81 - opp_vs_team_shots_on_target_per90\n",
"82 - opp_vs_team_passes_pct\n",
"83 - opp_vs_team_passes_pct_short\n",
"84 - opp_vs_team_passes_pct_medium\n",
"85 - opp_vs_team_passes_pct_long\n",
"86 - opp_vs_team_sca_per90\n",
"87 - opp_vs_team_gca_per90\n",
"88 - opp_vs_team_dribble_tackles_pct\n",
"89 - opp_vs_team_dribbles_completed_pct\n",
"90 - opp_vs_team_aerials_won_pct\n",
"91 - vote_avg\n",
"92 - vote_std\n",
"93 - gk_shots_on_target_against\n",
"94 - gk_saves\n",
"95 - gk_free_kick_goals_against\n",
"96 - gk_corner_kick_goals_against\n",
"97 - gk_own_goals_against\n",
"98 - gk_psxg\n",
"99 - gk_psnpxg_per_shot_on_target_against\n",
"100 - gk_psxg_net\n",
"101 - gk_passes_completed_launched\n",
"102 - gk_passes_launched\n",
"103 - gk_passes\n",
"104 - gk_passes_throws\n",
"105 - gk_goal_kicks\n",
"106 - gk_crosses\n",
"107 - gk_crosses_stopped\n"
]
}
],
"source": [
"for i in range(db_gk.columns.shape[0]):\n",
" print(str(i) + \" - \" + str(db_gk.columns[i]))"
]
},
{
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"id": "b0209868",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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"language": "python",
"name": "python3"
},
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