{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#edit only this tab\n",
    "#give the folder path of the match\n",
    "path = \"/home/kirugulige/Documents/Football-Analytics/open-data-master/data/events/\"\n",
    "home_team = 'Espanyol'\n",
    "away_team = 'Barcelona'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import codecs\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Arc, Rectangle, ConnectionPatch\n",
    "from matplotlib.offsetbox import  OffsetImage\n",
    "import StatsbombPitch as sb\n",
    "from functools import reduce\n",
    "\n",
    "Xg_req = pd.DataFrame(data=None)\n",
    "\n",
    "filename = '69275.json' # remove the comment line to work for this match\n",
    "with codecs.open(\"%s\" % path + filename,encoding='utf-8') as data_file:    \n",
    "    data = json.load(data_file)\n",
    "    df = pd.DataFrame(data=None)\n",
    "        \n",
    "    df = pd.json_normalize(data, sep = \"_\")\n",
    "        \n",
    "        #df =  df[(df['type_name'] == \"Shot\")]\n",
    "        #df = df.loc[:,['location','shot_body_part_id','shot_end_location','shot_one_on_one','shot_technique_id','shot_type_id','under_pressure','shot_outcome_id']]\n",
    "        #print(df.shape)\n",
    "Xg_req = Xg_req.append(df,ignore_index=True,sort=False)\n",
    "        #df.drop(df.index, inplace=True)\n",
    "        \n",
    "print(\"done\")\n",
    "df = Xg_req"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#type_id=30 is pass event AND type_id=19 is substitution event\n",
    "\n",
    "pass_m = df.query('type_id == 30')\n",
    "substitution = df.query('type_id == 19')\n",
    "#pass_m = df.query('type_name == pass')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Javier Alejandro Mascherano' 'Seydou Kéita' 'Bojan Krkíc Pérez']\n",
      "['Jesús Alberto Dátolo' 'Jordi Amat Maas' 'David García De La Cruz']\n"
     ]
    }
   ],
   "source": [
    "#this cell is WIP\n",
    "substitution_home = set()\n",
    "substitution_home = substitution[substitution.team_name == home_team]\n",
    "substitution_home = substitution_home['substitution_replacement_name'].unique()\n",
    "substitution_away = set()\n",
    "substitution_away = substitution[substitution.team_name == away_team]\n",
    "substitution_away = substitution_away['substitution_replacement_name'].unique()\n",
    "print(substitution_away)\n",
    "print(substitution_home)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# to get \n",
    "\n",
    "home_player = pass_m[(pass_m.team_name == home_team)] \n",
    "home_team_list = set()\n",
    "home_team_list = home_player['player_name'].unique()\n",
    "#print(substitution_belgium)\n",
    "#belgium_list = [player for player in belgium_list if player not in substitution_belgium]\n",
    "#belgium_list.remove([x for x in substitution_belgium])#belgium_list - substitution_belgium\n",
    "home_player =pass_m['player_name'].isin(home_team_list)\n",
    "pass_home = pass_m[home_player] #contains 11 players of home team\n",
    "\n",
    "away_player = pass_m[(pass_m.team_name == away_team)] \n",
    "away_list = away_player['player_name'].unique()\n",
    "#away_list = away_list - substitution_brazil\n",
    "away_player = pass_m['player_name'].isin(away_list)\n",
    "pass_away = pass_m[away_player]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>id</th>\n",
       "      <th>index</th>\n",
       "      <th>period</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>minute</th>\n",
       "      <th>second</th>\n",
       "      <th>possession</th>\n",
       "      <th>duration</th>\n",
       "      <th>type_id</th>\n",
       "      <th>type_name</th>\n",
       "      <th>...</th>\n",
       "      <th>pass_cut_back</th>\n",
       "      <th>substitution_outcome_id</th>\n",
       "      <th>substitution_outcome_name</th>\n",
       "      <th>substitution_replacement_id</th>\n",
       "      <th>substitution_replacement_name</th>\n",
       "      <th>injury_stoppage_in_chain</th>\n",
       "      <th>foul_committed_offensive</th>\n",
       "      <th>pass_deflected</th>\n",
       "      <th>block_deflection</th>\n",
       "      <th>goalkeeper_punched_out</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d6406089-778b-49e0-a70a-ade4788cf911</td>\n",
       "      <td>5</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.606100</td>\n",
       "      <td>30</td>\n",
       "      <td>Pass</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>73d8e43f-8e84-4b5d-88cc-9423278134d5</td>\n",
       "      <td>9</td>\n",
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       "      <td>00:00:02.511</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.776163</td>\n",
       "      <td>30</td>\n",
       "      <td>Pass</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8e47d35d-ab38-4419-a991-efe7105dec56</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>00:00:09.581</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>1.242900</td>\n",
       "      <td>30</td>\n",
       "      <td>Pass</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>a449bfa2-7bd9-4f94-8e13-595620c9bcee</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>00:00:18.784</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>1.298500</td>\n",
       "      <td>30</td>\n",
       "      <td>Pass</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>77f45a53-2eab-4ee5-bfbd-ad39d20a36cb</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>00:00:20.122</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>0.950262</td>\n",
       "      <td>30</td>\n",
       "      <td>Pass</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 122 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      id  index  period     timestamp  minute  \\\n",
       "4   d6406089-778b-49e0-a70a-ade4788cf911      5       1  00:00:00.738       0   \n",
       "8   73d8e43f-8e84-4b5d-88cc-9423278134d5      9       1  00:00:02.511       0   \n",
       "16  8e47d35d-ab38-4419-a991-efe7105dec56     17       1  00:00:09.581       0   \n",
       "20  a449bfa2-7bd9-4f94-8e13-595620c9bcee     21       1  00:00:18.784       0   \n",
       "24  77f45a53-2eab-4ee5-bfbd-ad39d20a36cb     25       1  00:00:20.122       0   \n",
       "\n",
       "    second  possession  duration  type_id type_name  ...  pass_cut_back  \\\n",
       "4        0           2  0.606100       30      Pass  ...            NaN   \n",
       "8        2           2  1.776163       30      Pass  ...            NaN   \n",
       "16       9           2  1.242900       30      Pass  ...            NaN   \n",
       "20      18           3  1.298500       30      Pass  ...            NaN   \n",
       "24      20           3  0.950262       30      Pass  ...            NaN   \n",
       "\n",
       "   substitution_outcome_id  substitution_outcome_name  \\\n",
       "4                      NaN                        NaN   \n",
       "8                      NaN                        NaN   \n",
       "16                     NaN                        NaN   \n",
       "20                     NaN                        NaN   \n",
       "24                     NaN                        NaN   \n",
       "\n",
       "   substitution_replacement_id  substitution_replacement_name  \\\n",
       "4                          NaN                            NaN   \n",
       "8                          NaN                            NaN   \n",
       "16                         NaN                            NaN   \n",
       "20                         NaN                            NaN   \n",
       "24                         NaN                            NaN   \n",
       "\n",
       "   injury_stoppage_in_chain  foul_committed_offensive pass_deflected  \\\n",
       "4                       NaN                       NaN            NaN   \n",
       "8                       NaN                       NaN            NaN   \n",
       "16                      NaN                       NaN            NaN   \n",
       "20                      NaN                       NaN            NaN   \n",
       "24                      NaN                       NaN            NaN   \n",
       "\n",
       "   block_deflection goalkeeper_punched_out  \n",
       "4               NaN                    NaN  \n",
       "8               NaN                    NaN  \n",
       "16              NaN                    NaN  \n",
       "20              NaN                    NaN  \n",
       "24              NaN                    NaN  \n",
       "\n",
       "[5 rows x 122 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pass_home.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 748.8x489.6 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "players = home_team_list\n",
    "#fig=plt.figure() #set up the figures\n",
    "sb.sb_pitch(\"#195905\",\"#faf0e6\",\"horizontal\",\"full\")\n",
    "plt.axis('on')\n",
    "plt.gca().invert_yaxis()\n",
    "for player in players:\n",
    "    x_avg = 0\n",
    "    y_avg = 0\n",
    "    touches = 0\n",
    "    if player not in substitution_home: \n",
    "        play_temp = pass_home[(pass_home.player_name == player)]\n",
    "    #print(play_temp.location, players[player])\n",
    "        for i in range(len(play_temp)):\n",
    "            touches+=1\n",
    "            \n",
    "            #https://math.stackexchange.com/questions/1013230/how-to-find-coordinates-of-reflected-point\n",
    "            x_avg = x_avg + play_temp.iloc[i]['location'][0]\n",
    "            y_avg = y_avg + play_temp.iloc[i]['location'][1]\n",
    "        x_avg = x_avg/len(play_temp)\n",
    "        y_avg = y_avg/len(play_temp)\n",
    "    #print(x_avg,y_avg,players[player])\n",
    "        plt.scatter(x_avg, y_avg, s= (3 *touches ),color=\"red\",edgecolors=\"black\",zorder = 15)  \n",
    "        plt.annotate(player, (x_avg, y_avg),zorder = 20,color = 'white')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 748.8x489.6 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "players = away_list #['Alisson Ramsés Becker','Fágner Conserva Lemos','Fernando Luiz Rosa','Gabriel Fernando de Jesus','João Miranda de Souza Filho','José Paulo Bezzera Maciel Júnior','Marcelo Vieira da Silva Júnior','Neymar da Silva Santos Junior','Philippe Coutinho Correia','Thiago Emiliano da Silva','Willian Borges da Silva']\n",
    "sb.sb_pitch(\"#195905\",\"#faf0e6\",\"horizontal\",\"full\")\n",
    "plt.axis('on')\n",
    "for player in players:\n",
    "    x_avg = 0\n",
    "    y_avg = 0\n",
    "    touches = 0\n",
    "    if player not in substitution_away:\n",
    "    #print(players[player])\n",
    "        play_temp = pass_away[(pass_away.player_name == player)]\n",
    "    #print(play_temp.location, players[player])\n",
    "        for i in range(len(play_temp)):\n",
    "            touches+=1\n",
    "            x_avg = x_avg + play_temp.iloc[i]['location'][0]\n",
    "            y_avg = y_avg + play_temp.iloc[i]['location'][1]\n",
    "        x_avg = x_avg/len(play_temp)\n",
    "        y_avg = y_avg/len(play_temp)\n",
    "    #print(x_avg,y_avg,players[player])\n",
    "        plt.scatter(x_avg, y_avg, s= (3 *touches ),color=\"red\",edgecolors=\"black\",zorder = 15)  \n",
    "        plt.annotate(player, (x_avg, y_avg),zorder = 20,color = 'white')\n",
    "plt.show()"
   ]
  }
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