figure_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f4dc3271",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "from functools import reduce\n",
    "import itertools\n",
    "import numpy as np\n",
    "import sklearn.preprocessing as preprocessing\n",
    "import sklearn.model_selection as model_selection\n",
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from sklearn import linear_model\n",
    "from joblib import dump, load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "52a48e31",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "067bfc48",
   "metadata": {},
   "source": [
    "# figure 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "381d9b67",
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_goals_scored = pd.read_csv(r'data/predicting_team_goals.csv')[['team', 'pred_goals_scored', 'team_goals']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7828ede0",
   "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>team</th>\n",
       "      <th>pred_goals_scored</th>\n",
       "      <th>team_goals</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Watford</td>\n",
       "      <td>1.213222</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Swansea City</td>\n",
       "      <td>1.545529</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Burnley</td>\n",
       "      <td>1.534140</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Huddersfield</td>\n",
       "      <td>0.882562</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>0.389978</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             team  pred_goals_scored  team_goals\n",
       "0         Watford           1.213222         2.0\n",
       "1    Swansea City           1.545529         1.0\n",
       "2         Burnley           1.534140         0.0\n",
       "3    Huddersfield           0.882562         0.0\n",
       "4  Crystal Palace           0.389978         0.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted_goals_scored.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6d3ac532",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>pred_goals_scored</th>\n",
       "      <th>team_goals</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Arsenal</th>\n",
       "      <td>Arsenal</td>\n",
       "      <td>1.808530</td>\n",
       "      <td>1.971831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bournemouth</th>\n",
       "      <td>Bournemouth</td>\n",
       "      <td>1.236662</td>\n",
       "      <td>1.380282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brighton</th>\n",
       "      <td>Brighton</td>\n",
       "      <td>1.026374</td>\n",
       "      <td>0.915493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burnley</th>\n",
       "      <td>Burnley</td>\n",
       "      <td>1.168252</td>\n",
       "      <td>1.056338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cardiff City</th>\n",
       "      <td>Cardiff City</td>\n",
       "      <td>0.959556</td>\n",
       "      <td>0.894737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chelsea</th>\n",
       "      <td>Chelsea</td>\n",
       "      <td>1.885410</td>\n",
       "      <td>1.647887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crystal Palace</th>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>1.205815</td>\n",
       "      <td>1.352113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Everton</th>\n",
       "      <td>Everton</td>\n",
       "      <td>1.342606</td>\n",
       "      <td>1.352113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fulham</th>\n",
       "      <td>Fulham</td>\n",
       "      <td>0.959531</td>\n",
       "      <td>0.894737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huddersfield</th>\n",
       "      <td>Huddersfield</td>\n",
       "      <td>0.777270</td>\n",
       "      <td>0.633803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leicester City</th>\n",
       "      <td>Leicester City</td>\n",
       "      <td>1.394011</td>\n",
       "      <td>1.408451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Liverpool</th>\n",
       "      <td>Liverpool</td>\n",
       "      <td>2.089827</td>\n",
       "      <td>2.309859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manchester City</th>\n",
       "      <td>Manchester City</td>\n",
       "      <td>2.317150</td>\n",
       "      <td>2.605634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manchester Utd</th>\n",
       "      <td>Manchester Utd</td>\n",
       "      <td>1.888282</td>\n",
       "      <td>1.647887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Newcastle Utd</th>\n",
       "      <td>Newcastle Utd</td>\n",
       "      <td>1.127983</td>\n",
       "      <td>1.056338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southampton</th>\n",
       "      <td>Southampton</td>\n",
       "      <td>1.136790</td>\n",
       "      <td>1.098592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stoke City</th>\n",
       "      <td>Stoke City</td>\n",
       "      <td>1.062157</td>\n",
       "      <td>0.909091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Swansea City</th>\n",
       "      <td>Swansea City</td>\n",
       "      <td>1.004197</td>\n",
       "      <td>0.787879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tottenham</th>\n",
       "      <td>Tottenham</td>\n",
       "      <td>1.995130</td>\n",
       "      <td>1.887324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Watford</th>\n",
       "      <td>Watford</td>\n",
       "      <td>1.203933</td>\n",
       "      <td>1.253521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Brom</th>\n",
       "      <td>West Brom</td>\n",
       "      <td>1.015036</td>\n",
       "      <td>0.818182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Ham</th>\n",
       "      <td>West Ham</td>\n",
       "      <td>1.214085</td>\n",
       "      <td>1.352113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolves</th>\n",
       "      <td>Wolves</td>\n",
       "      <td>1.217523</td>\n",
       "      <td>1.236842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            team  pred_goals_scored  team_goals\n",
       "team                                                           \n",
       "Arsenal                  Arsenal           1.808530    1.971831\n",
       "Bournemouth          Bournemouth           1.236662    1.380282\n",
       "Brighton                Brighton           1.026374    0.915493\n",
       "Burnley                  Burnley           1.168252    1.056338\n",
       "Cardiff City        Cardiff City           0.959556    0.894737\n",
       "Chelsea                  Chelsea           1.885410    1.647887\n",
       "Crystal Palace    Crystal Palace           1.205815    1.352113\n",
       "Everton                  Everton           1.342606    1.352113\n",
       "Fulham                    Fulham           0.959531    0.894737\n",
       "Huddersfield        Huddersfield           0.777270    0.633803\n",
       "Leicester City    Leicester City           1.394011    1.408451\n",
       "Liverpool              Liverpool           2.089827    2.309859\n",
       "Manchester City  Manchester City           2.317150    2.605634\n",
       "Manchester Utd    Manchester Utd           1.888282    1.647887\n",
       "Newcastle Utd      Newcastle Utd           1.127983    1.056338\n",
       "Southampton          Southampton           1.136790    1.098592\n",
       "Stoke City            Stoke City           1.062157    0.909091\n",
       "Swansea City        Swansea City           1.004197    0.787879\n",
       "Tottenham              Tottenham           1.995130    1.887324\n",
       "Watford                  Watford           1.203933    1.253521\n",
       "West Brom              West Brom           1.015036    0.818182\n",
       "West Ham                West Ham           1.214085    1.352113\n",
       "Wolves                    Wolves           1.217523    1.236842"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted_goals_scored.groupby('team').agg({'team': 'first', 'pred_goals_scored': 'mean', 'team_goals': 'mean'})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c7e620f",
   "metadata": {},
   "source": [
    "# figure 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0031ae4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_points = pd.read_csv(r'data/season_points_predict.csv')[['player', 'predicted_points_xg']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "195fe723",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>player</th>\n",
       "      <th>predicted_points_xg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mohamed Salah</td>\n",
       "      <td>246.539679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Raheem Sterling</td>\n",
       "      <td>241.660845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paul Pogba</td>\n",
       "      <td>202.922922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sadio Mané</td>\n",
       "      <td>199.313762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eden Hazard</td>\n",
       "      <td>198.999148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            player  predicted_points_xg\n",
       "0    Mohamed Salah           246.539679\n",
       "1  Raheem Sterling           241.660845\n",
       "2       Paul Pogba           202.922922\n",
       "3       Sadio Mané           199.313762\n",
       "4      Eden Hazard           198.999148"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted_points.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0095470e",
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_points['predicted_rank'] = predicted_points['predicted_points_xg'].rank(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "55d882db",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>player</th>\n",
       "      <th>predicted_points_xg</th>\n",
       "      <th>predicted_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mohamed Salah</td>\n",
       "      <td>246.539679</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Raheem Sterling</td>\n",
       "      <td>241.660845</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paul Pogba</td>\n",
       "      <td>202.922922</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sadio Mané</td>\n",
       "      <td>199.313762</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eden Hazard</td>\n",
       "      <td>198.999148</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Pierre-Emerick Aubameyang</td>\n",
       "      <td>176.493474</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Andrew Robertson</td>\n",
       "      <td>176.000874</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Aymeric Laporte</td>\n",
       "      <td>174.659464</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sergio Agüero</td>\n",
       "      <td>172.472494</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Virgil van Dijk</td>\n",
       "      <td>171.028666</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      player  predicted_points_xg  predicted_rank\n",
       "0              Mohamed Salah           246.539679             1.0\n",
       "1            Raheem Sterling           241.660845             2.0\n",
       "2                 Paul Pogba           202.922922             3.0\n",
       "3                 Sadio Mané           199.313762             4.0\n",
       "4                Eden Hazard           198.999148             5.0\n",
       "5  Pierre-Emerick Aubameyang           176.493474             6.0\n",
       "6           Andrew Robertson           176.000874             7.0\n",
       "7            Aymeric Laporte           174.659464             8.0\n",
       "8              Sergio Agüero           172.472494             9.0\n",
       "9            Virgil van Dijk           171.028666            10.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted_points.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b282e4ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "actual_points = pd.read_csv(r'data/player_form.csv').query('season == \"2018-19\"')[['player', 'total_points', 'mins', 'pos']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f80d634b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>player</th>\n",
       "      <th>total_points</th>\n",
       "      <th>mins</th>\n",
       "      <th>pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18072</th>\n",
       "      <td>Harvey Barnes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>MID</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18073</th>\n",
       "      <td>Harry Maguire</td>\n",
       "      <td>1.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>DEF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18074</th>\n",
       "      <td>Çağlar Söyüncü</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DEF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18075</th>\n",
       "      <td>Hamza Choudhury</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>MID</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18076</th>\n",
       "      <td>Danny Simpson</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DEF</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                player  total_points  mins  pos\n",
       "18072    Harvey Barnes           0.0   0.0  MID\n",
       "18073    Harry Maguire           1.0  90.0  DEF\n",
       "18074   Çağlar Söyüncü           0.0   0.0  DEF\n",
       "18075  Hamza Choudhury           0.0   0.0  MID\n",
       "18076    Danny Simpson           0.0   0.0  DEF"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actual_points.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d4209cec",
   "metadata": {},
   "outputs": [],
   "source": [
    "actual_points = actual_points.groupby('player', as_index=False).agg({'player': 'first', 'total_points': 'sum', 'mins': 'sum', 'pos': 'first'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e16fcd36",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Aaron Cresswell</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1589.0</td>\n",
       "      <td>DEF</td>\n",
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       "    <tr>\n",
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       "      <td>1215.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Aaron Mooy</td>\n",
       "      <td>75.0</td>\n",
       "      <td>2330.0</td>\n",
       "      <td>MID</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>1331.0</td>\n",
       "      <td>MID</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aaron Rowe</td>\n",
       "      <td>2.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>FWD</td>\n",
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      "text/plain": [
       "            player  total_points    mins  pos\n",
       "0  Aaron Cresswell          33.0  1589.0  DEF\n",
       "1     Aaron Lennon          41.0  1215.0  MID\n",
       "2       Aaron Mooy          75.0  2330.0  MID\n",
       "3     Aaron Ramsey          88.0  1331.0  MID\n",
       "4       Aaron Rowe           2.0    69.0  FWD"
      ]
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     "execution_count": 13,
     "metadata": {},
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    "actual_points.head()"
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  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f82524a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "actual_points['actual_rank'] = actual_points['total_points'].rank(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "528c6b2d",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
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       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Eden Hazard</td>\n",
       "      <td>253.0</td>\n",
       "      <td>3044.0</td>\n",
       "      <td>MID</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>Mohamed Salah</td>\n",
       "      <td>249.0</td>\n",
       "      <td>3250.0</td>\n",
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       "      <td>2.0</td>\n",
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       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>Raheem Sterling</td>\n",
       "      <td>239.0</td>\n",
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       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Aymeric Laporte</td>\n",
       "      <td>222.0</td>\n",
       "      <td>3597.0</td>\n",
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       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>Sergio Agüero</td>\n",
       "      <td>217.0</td>\n",
       "      <td>2827.0</td>\n",
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       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>Pierre-Emerick Aubameyang</td>\n",
       "      <td>210.0</td>\n",
       "      <td>2816.0</td>\n",
       "      <td>FWD</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Andrew Robertson</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3216.0</td>\n",
       "      <td>DEF</td>\n",
       "      <td>8.0</td>\n",
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       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Ederson</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3960.0</td>\n",
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       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>Virgil van Dijk</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3384.0</td>\n",
       "      <td>DEF</td>\n",
       "      <td>10.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        player  total_points    mins  pos  actual_rank\n",
       "146                Eden Hazard         253.0  3044.0  MID          1.0\n",
       "354              Mohamed Salah         249.0  3250.0  MID          2.0\n",
       "397            Raheem Sterling         239.0  3160.0  MID          3.0\n",
       "57             Aymeric Laporte         222.0  3597.0  DEF          4.0\n",
       "423                 Sadio Mané         220.0  3077.0  MID          5.0\n",
       "436              Sergio Agüero         217.0  2827.0  FWD          6.0\n",
       "394  Pierre-Emerick Aubameyang         210.0  2816.0  FWD          7.0\n",
       "35            Andrew Robertson         203.0  3216.0  DEF          8.0\n",
       "147                    Ederson         196.0  3960.0   GK          9.0\n",
       "479            Virgil van Dijk         193.0  3384.0  DEF         10.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actual_points.sort_values(by='actual_rank').head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2001e734",
   "metadata": {},
   "outputs": [],
   "source": [
    "actual_points.to_csv('figure data/FIGURE 7 -50 TOP PEFORMERS.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "19ebbdb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "player_scorers = pd.merge(predicted_points, actual_points, on='player')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "163b6c74",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Mohamed Salah</td>\n",
       "      <td>246.539679</td>\n",
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       "      <td>249.0</td>\n",
       "      <td>3250.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Raheem Sterling</td>\n",
       "      <td>241.660845</td>\n",
       "      <td>2.0</td>\n",
       "      <td>239.0</td>\n",
       "      <td>3160.0</td>\n",
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       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Paul Pogba</td>\n",
       "      <td>202.922922</td>\n",
       "      <td>3.0</td>\n",
       "      <td>183.0</td>\n",
       "      <td>3366.0</td>\n",
       "      <td>MID</td>\n",
       "      <td>16.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eden Hazard</td>\n",
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       "      <td>253.0</td>\n",
       "      <td>3044.0</td>\n",
       "      <td>MID</td>\n",
       "      <td>1.0</td>\n",
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       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "            player  predicted_points_xg  predicted_rank  total_points    mins   \n",
       "0    Mohamed Salah           246.539679             1.0         249.0  3250.0  \\\n",
       "1  Raheem Sterling           241.660845             2.0         239.0  3160.0   \n",
       "2       Paul Pogba           202.922922             3.0         183.0  3366.0   \n",
       "3       Sadio Mané           199.313762             4.0         220.0  3077.0   \n",
       "4      Eden Hazard           198.999148             5.0         253.0  3044.0   \n",
       "\n",
       "   pos  actual_rank  \n",
       "0  MID          2.0  \n",
       "1  MID          3.0  \n",
       "2  MID         16.0  \n",
       "3  MID          5.0  \n",
       "4  MID          1.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_scorers.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c645d8d7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "player_scorers.to_csv('player_scorers.csv')"
   ]
  }
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