sportowe_wizualizacja/Through_Ball.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import StatsbombPitch as sb\n",
    "#import squarify\n",
    "from functools import reduce\n",
    "path = \"/home/kirugulige/Documents/Football-Analytics/open-data-master/data/events/\"\n",
    "Xg_req = pd.DataFrame(data=None)\n",
    "filename = '69275.json'    \n",
    "with open(\"%s\" % path + filename,encoding=\"utf8\") 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": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "through_ball = df.query('pass_through_ball == True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n"
     ]
    }
   ],
   "source": [
    "assist = df.query('pass_goal_assist == True')\n",
    "print(len(assist.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>id</th>\n",
       "      <th>period</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>location</th>\n",
       "      <th>pass_end_location</th>\n",
       "      <th>pass_recipient_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>1f6ef40d-cd32-4566-add6-f1558833d0c1</td>\n",
       "      <td>1</td>\n",
       "      <td>00:05:57.827</td>\n",
       "      <td>[81.5, 37.8]</td>\n",
       "      <td>[103.1, 33.4]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>604</th>\n",
       "      <td>4040c0ab-d934-469b-84f5-c595213b851b</td>\n",
       "      <td>1</td>\n",
       "      <td>00:13:56.420</td>\n",
       "      <td>[48.2, 57.4]</td>\n",
       "      <td>[85.5, 38.3]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6</td>\n",
       "      <td>1</td>\n",
       "      <td>00:18:30.829</td>\n",
       "      <td>[66.8, 46.7]</td>\n",
       "      <td>[93.5, 38.5]</td>\n",
       "      <td>Pedro Eliezer Rodríguez Ledesma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840</th>\n",
       "      <td>3a7da0a1-e9c4-40a1-9702-e99c5ace03c2</td>\n",
       "      <td>1</td>\n",
       "      <td>00:20:46.623</td>\n",
       "      <td>[66.0, 56.5]</td>\n",
       "      <td>[105.5, 34.7]</td>\n",
       "      <td>José María Callejón Bueno</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>2bc53e64-664a-4f83-9d0c-6b046d91a7d9</td>\n",
       "      <td>1</td>\n",
       "      <td>00:23:55.494</td>\n",
       "      <td>[81.5, 28.1]</td>\n",
       "      <td>[94.2, 31.7]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       id  period     timestamp      location  \\\n",
       "280  1f6ef40d-cd32-4566-add6-f1558833d0c1       1  00:05:57.827  [81.5, 37.8]   \n",
       "604  4040c0ab-d934-469b-84f5-c595213b851b       1  00:13:56.420  [48.2, 57.4]   \n",
       "794  7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6       1  00:18:30.829  [66.8, 46.7]   \n",
       "840  3a7da0a1-e9c4-40a1-9702-e99c5ace03c2       1  00:20:46.623  [66.0, 56.5]   \n",
       "962  2bc53e64-664a-4f83-9d0c-6b046d91a7d9       1  00:23:55.494  [81.5, 28.1]   \n",
       "\n",
       "    pass_end_location              pass_recipient_name  \n",
       "280     [103.1, 33.4]             Pablo Daniel Osvaldo  \n",
       "604      [85.5, 38.3]             Pablo Daniel Osvaldo  \n",
       "794      [93.5, 38.5]  Pedro Eliezer Rodríguez Ledesma  \n",
       "840     [105.5, 34.7]        José María Callejón Bueno  \n",
       "962      [94.2, 31.7]              David Villa Sánchez  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "through_ball= through_ball[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
    "through_ball.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>id</th>\n",
       "      <th>period</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>location</th>\n",
       "      <th>pass_end_location</th>\n",
       "      <th>pass_recipient_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6</td>\n",
       "      <td>1</td>\n",
       "      <td>00:18:30.829</td>\n",
       "      <td>[66.8, 46.7]</td>\n",
       "      <td>[93.5, 38.5]</td>\n",
       "      <td>Pedro Eliezer Rodríguez Ledesma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2436</th>\n",
       "      <td>9810ac65-15b8-4736-a09e-08f7faaff01d</td>\n",
       "      <td>2</td>\n",
       "      <td>00:17:04.830</td>\n",
       "      <td>[52.7, 63.4]</td>\n",
       "      <td>[84.2, 57.1]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935</th>\n",
       "      <td>7269b3a6-43d7-45bc-8823-bcfd1542ad45</td>\n",
       "      <td>2</td>\n",
       "      <td>00:30:03.492</td>\n",
       "      <td>[64.4, 33.8]</td>\n",
       "      <td>[79.4, 25.5]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3344</th>\n",
       "      <td>dc1b453d-6e7e-49b1-ad88-79525e8223f9</td>\n",
       "      <td>2</td>\n",
       "      <td>00:38:47.689</td>\n",
       "      <td>[70.1, 30.6]</td>\n",
       "      <td>[98.0, 23.3]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        id  period     timestamp  \\\n",
       "794   7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6       1  00:18:30.829   \n",
       "2436  9810ac65-15b8-4736-a09e-08f7faaff01d       2  00:17:04.830   \n",
       "2935  7269b3a6-43d7-45bc-8823-bcfd1542ad45       2  00:30:03.492   \n",
       "3344  dc1b453d-6e7e-49b1-ad88-79525e8223f9       2  00:38:47.689   \n",
       "\n",
       "          location pass_end_location              pass_recipient_name  \n",
       "794   [66.8, 46.7]      [93.5, 38.5]  Pedro Eliezer Rodríguez Ledesma  \n",
       "2436  [52.7, 63.4]      [84.2, 57.1]             Pablo Daniel Osvaldo  \n",
       "2935  [64.4, 33.8]      [79.4, 25.5]              David Villa Sánchez  \n",
       "3344  [70.1, 30.6]      [98.0, 23.3]              David Villa Sánchez  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assist= assist[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
    "assist.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 748.8x489.6 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.sb_pitch(\"#195905\",\"#faf0e6\",\"horizontal\",\"full\")\n",
    "plt.gca().invert_yaxis() #overlay our different objects on the pitch\n",
    "#plt.ylim(-2, 82)\n",
    "#plt.xlim(-2, 122)\n",
    "#plt.plot(x_axis,y_axis,'ro')\n",
    "#plt.plot(x,y,'bo')\n",
    "plt.axis('off')\n",
    "for i in range(len(through_ball)):\n",
    "    x = through_ball.iloc[i]['pass_end_location'][0]\n",
    "    y = through_ball.iloc[i]['pass_end_location'][1]\n",
    "    xe = through_ball.iloc[i]['location'][0]\n",
    "    ye = through_ball.iloc[i]['location'][0]\n",
    "    plt.scatter(x,y,color=\"red\",edgecolors=\"black\",zorder=10,alpha=1)\n",
    "    plt.plot([x,xe],[y,ye],zorder=11,alpha=1,color=\"black\")\n",
    "\n",
    "\"\"\"\n",
    "for i in range(len(assist)):\n",
    "    # annotate draw an arrow from a current position to pass_end_location\n",
    "    ax.annotate(\"\", xy = (assist.iloc[i]['pass_end_location'][0], assist.iloc[i]['pass_end_location'][1]), xycoords = 'data',\n",
    "               xytext = (assist.iloc[i]['location'][0], assist.iloc[i]['location'][1]), textcoords = 'data',\n",
    "               arrowprops=dict(arrowstyle=\"->\",connectionstyle=\"arc3\", color = \"red\"),)\n",
    "\"\"\"\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 748.8x489.6 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.sb_pitch(\"#195905\",\"#faf0e6\",\"horizontal\",\"full\")\n",
    "plt.gca().invert_yaxis() #overlay our different objects on the pitch\n",
    "#plt.ylim(-2, 82)\n",
    "#plt.xlim(-2, 122)\n",
    "#plt.plot(x_axis,y_axis,'ro')\n",
    "#plt.plot(x,y,'bo')\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "for i in range(len(assist)):\n",
    "    x = assist.iloc[i]['pass_end_location'][0]\n",
    "    y = assist.iloc[i]['pass_end_location'][1]\n",
    "    xe = assist.iloc[i]['location'][0]\n",
    "    ye = assist.iloc[i]['location'][0]\n",
    "    plt.scatter(x,y,color=\"red\",edgecolors=\"black\",zorder=10,alpha=1)\n",
    "    plt.plot([x,xe],[y,ye],zorder=11,alpha=1,color=\"black\")\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}