{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mplsoccer.pitch import Pitch\n",
    "from scipy.spatial import Voronoi, voronoi_plot_2d\n",
    "import highlight_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.font_manager\n",
    "from IPython.core.display import HTML\n",
    "\n",
    "def make_html(fontname):\n",
    "    return \"<p>{font}: <span style='font-family:{font}; font-size: 24px;'>{font}</p>\".format(font=fontname)\n",
    "\n",
    "code = \"\\n\".join([make_html(font) for font in sorted(set([f.name for f in matplotlib.font_manager.fontManager.ttflist]))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "barca_x=[93,96,99,102,104,95,86,79,89]\n",
    "barca_y=[9,22,33,44,56,63,52,33,22]\n",
    "barca = list(np.zeros((9,),dtype=int))\n",
    "\n",
    "opp_x=[99,100,102,104,104,102,97,98,94,77]\n",
    "opp_y=[14,22,33,43,46,55,37,27,21,45]\n",
    "opp = list(np.ones((10,),dtype=int))\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'x':barca_x+opp_x,\n",
    "    'y':barca_y+opp_y,\n",
    "    'team':barca+opp\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x24a62a78>"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAHwCAYAAAC4xyi3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAArHUlEQVR4nO3daXRb533n8R9A3AuuIEAKJMVdC7VQIkVZ8hbbqRO7SZzEdtwkbvalTpdM4rietE3bc2Y7J9OZzrTjcZs2aVJnmZk4dhLZae04jdPUdmJ5lWXZtCRTlKiFhEQCokBwxz4vKNGWJT2kxOUS4PfzRgJ0CfwfieIX9wIXcF111TVZAQBwAW6nBwAALG2EAgBgRCgAAEaEAgBgRCgAAEaEAgBglPOhGBjod3qEeZVv65Hyb035th4p/9aUb+uRnF1TzociHM6vb4h8W4+Uf2vKt/VI+bemfFuP5Oyacj4UAICF5VrMM7N37XpeXq93Xm8zmUzJsjzzeptOyrf1SPm3pnxbj5R/a8q39UgLs6Z4PK7t26+ccbtF/Zv0er1qa+tYzLsEAFxAZ+eeWW3HoScAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYzemDi4aGojpypEfZrFRVVa26uvr5mgsAsERc8h5FNpvV4cM92rBhk7Zs2arBwYjGx8fnczYAwBJwyXsUo6MjKiwsVGFhoSSpsjKoaPSUiouLL/g1Dc2Nuue+ey/1LgFgWbv7jrscud9LDkUikZBt29OXbdvW6OjIOdsNDPQrHO6XJJX5yi717gAA8yyZTJ31udlVVTWqrq45Z7s5PUdxLtc511RXv3HHnZ175rWIZ/ZOnKosACyGhToSY1ketbV1zLjdJT9HYdu2EonE9OW37mEAAPLDJYeitLRMk5MTmpycVCaT0eBgRIFAxXzOBgBYAi750JPL5VJz82q9/vre0y+PrTI+kQ0AyE1zeo4iEKhgLwIA8hxnZgMAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjDwzbXDoULei0agsy9KWLVslSalUUt3dXYrH4/J6vWpp2SCPZ8abAgDkoBn3KILBKm3c2HrWdaFQSD6fXx0d2+Tz+RUK9S3YgAAAZ80YCp+vXAUFZ+8tRKODCgarJE2FJBodXJjpAACOu6TjRclkUrZtS5Js21YymbzgtgMD/QqH+09/XepS7g4AsACSyZQ6O/dMX66qqlF1dc052y34EwvV1W/c8ZsHAgA4y7I8amvrmHG7S3rVk2VZSiQSkqREIiHLsi7lZgAAOeCSQhEIVCgSCUuSIpGwAoHKeR0KALB0zHjoqbu7S8PDMaVSKe3e/aLq6xtVW1uv7u4uRSIDsm2v1q1bvxizAgAcMGMoWlrOH4HW1s3zPgwAYOnhzGwAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgBGhAAAYEQoAgJHH6QEA5IZ77rvX6RHgEPYoAABG7FEAuCh333GX0yMsO07vzbFHAQAwIhQAACNCAQAwIhQAACNCAQAwIhQAAKMZXx4bj8d16NABJRJJuVxSVVWNVq6sVSqVVHd3l+LxuLxer1paNsjj4dW2AJBvZvzJ7nK51NS0SiUlpUqnU+rsfEXl5X5FImH5fH7V1dUrFOpTKNSnpqbmRRgZALCYZjz0ZNu2SkpKJUkFBR4VFRUrkUgoGh1UMFglSQoGqxSNDi7spAAAR1zUsaLJyUmNjY2qtLRUyWRStm1LmopJMpk879cMDPQrHO6XJCWTqTmOCwCYL8lkSp2de6YvV1XVqLq65pztZh2KdDqt7u7X1dy8+qKei6iufuOO3zwQAMBZluVRW1vHjNvN6lVPmUxGBw68rhUrgqqoqDx9B5YSiYQkKZFIyLKsS58WALBkzRiKbDarnp6DKioq0sqVddPXBwIVikTCkqRIJKxAoHLhpgQAOGbGY0gjIyM6eTKi4uJivfrqHklSQ0Ojamvr1d3dpUhkQLbt1bp16xd6VgCAA2YMhc/n01VXXXPeP2tt3TzvAwEAlhbOzAYAGHEqNXAe48FWjay+XhmvT+74sMp6nlRxZJ/TYwGOIBTAW4wHWxVbf5NUMHWeUKawfOqyRCywLHHoCXiLkdXXT0diWoE9dT2wDBEK4C0yXt9FXQ/kO0IBvIU7PnxR1wP5jlAAb1HW86SUTpx9ZToxdT2wDPFkNvAWZ56w5lVPwBRCAZxHcWQfYQBO49ATAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjAgFAMCIUAAAjDwzbZDJZLR3b6ey2Yyy2awqKlaooaFRqVRS3d1disfj8nq9amnZII9nxpsDAOSYGX+yu1wutbZuVkFBwXQ0/P6ATp0alM/nV11dvUKhPoVCfWpqal6EkQEAi2lWoSgoKJAkZbNZZbNZSVI0OqjW1jZJUjBYpX37Ouc9FMUlxQpWB+Xzl8tX7pPP71O5v1wlpSXTM0nS7/3h7yuVSmt0ZETDQ8Majg1reCim2NCwwv0Dik/G53UuAMvLPffd6/QIjprVsaJsNqvOzlc0OTmh6uqVKisrUzKZlG3bkiTbtpVMJs/7tQMD/QqH+yVJyWTqgvfhLfSqaVWT6psb1NDcoIamBlUGV8xqERvbWo1/Hu4fUO+RPvUd7VXvkWM6dvjYBecFgOUimUyps3PP9OWqqhpVV9ecs92sQuFyudTe3qFUKqUDB/ZrfHxs1oNUV79xx28eSJL8FQFt2rJJm7ZsVsuGFnmss8dJJBIaOD6goeiQRmLDig3FNBwb1ujIqFLJlH7/7j+QJP3DPd+QZVkq9ZWqfHrvo1z+QLmqV9aoqqZaVTXV2nbVtqnbjSfUta9Le/e8pr2v7tXo8Mis1wNg+br7jrscud+F2qOxLI/a2jpm3O6inn32eDzy+co1NDQky7KUSCRk27YSiYQsy5rVbZSUlujKa6/U1iu3qb6xfvr6TCajoz1HdOzwMfUe7VXfkV4NnBhQJpOZ8TZff23/Bf+soKBAK+tWTu2pNDWocXWT6hvr1ba1TW1b25TJZHTs8FHtenaXdj37IoepAOAtZgxFMpmUy+WSx+NRJpNWLBZTbW2dAoEKRSJh1dXVKxIJKxConPHOKlZU6j/91X+Zjkp8Mq7X976uvXs6te/VfRobnf2eymyl02n1HetT37E+PadnJUnl/nK1btmkzR2b1bJxnZrXrFLzmlW6+UO3aNezL2rnE0/rROjEvM8CALloxlAkEgkdOtQtKatsVqqsrFQgUKHS0jJ1d3cpEhmQbXu1bt36Ge/szJPQ+17dq2eefEZde19XKnXh5y0WSmwopmefekbPPvWMbK+t1vZNetv116hlQ4uuece1uuYd16rnwCH9/J//RQf2H1j0+QBgKZkxFCUlJWpv7zjnesuy1Nq6+aLubDg2rL/4s69q8OTgRX3dQkrEE9rz4sva8+LLqqmt0duuv0aXv+0KrV63Rp//oy+oa2+XfrrjEfUe7XV6VABwxKKeIReLDi2pSLxV//F+PXT/Dj264xFd986364b33qD1m9Zr/ab12vPiy/rpQz/VyXDE6TEBYFFxKvV5JOIJ/fJn/6pnf/WM3nnTDbruhrer4/Kt2tSxWT97+DE9+fgT0+eTAEC+472eDMbHxvXojx/RX/z5V/XizhdkWZZuuf1WfenP7lJVTZXT4wHAoiAUsxCLxnT/t7+vb/7vf9DQqSE1r1mlP/rPf6Lr3/0OuVwup8cDgAVFKC7C/s59+sv/+N/1/NPPybIs3Xr7B/Tpz39Wttd2ejRgQZWUljg9AhxEKC7S5MSEHvjOD/Ste7+pifFxbdm2RV/6sz9UoLLC6dGABdHQ3Kgv/8c/dnoMOIhQXKJ9r+7VPV+9R+H+AdU11Onf/4cva826NU6PBcyr9Zs26It/cqcClQGnR4GDCMUcRAbCuuer92h/5z6VlpXq81/+grZs2+L0WMC82Ly1TZ+783dle209//RzTo8DBxGKOZqcmNC37v2mnnr8SRV4CvSpP/iMLrtym9NjAXNy2ZXb9JnPf1Yey6OnfvGkHvjOD5weCQ7iPIp5kM1m9ZMHH9bk5KTefct79PHPfULZbFYvv7Db6dGAi3b126/Whz55u9xutx5/9Of62cOPOT0SHEYo5tG//NPPlE6n9d7b3qePf+4TSqVS6tz9qtNjAbN2+dsu1+2f/ogk6dEdj+iXj/2rwxNhKeDQ0zz7xaOP6/FHf66CggJ98vc+pYbmRqdHAmZl1dpVuv1TU5H4yQMPEwlMIxQL4GcPP6Znntwpy7L0O1+8Q75yn9MjAUaBygp99gt3yGN59Otf/kpP/eJJp0fCEkIoFshD9+/QoQMH5Q/4p/4DejjKh6XJW+jV5+78XZX5ytS193X95IGHnR4JSwyhWCDpdFrf+btv69TJQTWvadbtn/5tp0cCzuFyufTxz31StQ21GjgxoO9947uz+lRJLC+EYgGNjY7pvr/9R8XjcV3+tiu0/ertTo8EnOXad16ntq1tGhsb0z/+zbc0MT7h9EhYggjFAjved1wPfX+HJOm2j36Q5yuwZFSuqNT7Pvh+SdID376fz1rBBRGKRfDCzue179W9Ki4p1oc/dbvT4wCSpNs/8xF5vV7tfv4lvbbnNafHwRJGKBbJD7/3oCbGx7W5o03bruIQFJx11duv1rqN6zQ6MqqH7t/h9DhY4gjFIokNxfSTB34iSbrtY7+louIiZwfCslUeKNctH75V0tSr88ZGxxyeCEsdoVhEL+x8Xt37D6ikpEQ33HSj0+Ngmbr5Q7eqqLhInS938jYzmBVCscge+fEjkqTrbny7yv3lDk+D5aa2vlbbrtqmVDKlh3/AISfMDqFYZL1HjmnPrpdl27befct7nB4Hy8xNt71XkvTMUzsVHYw6PA1yBaFwwGMPPaZ0Oq0rrr1Sweoqp8fBMlHfWK/NHW2Kx+P6xU9/4fQ4yCGEwgGRgbBe2Pm8CgoKdP27rnd6HCwTN7x36nmxZ596RqPDIw5Pg9m65757z/v7xUQoHPLkz5+QJG27arsKiwodngb5bkVVUO3btiiVSk1/7wGzRSgcEu4Pq3v/AXkLvbr86sudHgd57oprr5Tb7dZLz72k2FDM6XGQYwiFg3Y+8bQk6Zp3XOvwJMhnLpdL266a+njeF3c+7/A0yEWEwkGdezoVG4qpurZGa9evdXoc5KnVLatVUVmhU4On1NPd4/Q4yEGEwkGZdEYvPD31CG/L9g5nh0He2n760OZLz+5SNpt1eBrkIkLhsM6XOyVJmzo2OzwJ8pHH45l+ELLruV3ODoOcRSgc1ne0V7GhmAIVAdU11jk9DvLMxrZWFRUXqffIMYVPDDg9DnIUoXBYNpvV3tNv8bxpC3sVmF9rN0w998XbiGMuCMUSsPeVqf/Emzn8hHm2au1qSVLPgUMOT4JcRiiWgO7Xu5VOp1XXWC/LtpweB3nCW+hVXWOd0qm0jh4+6vQ4yGGEYglIJpIaOD4gt9ut2gaep8D8aF7TLLfbrd6jvUomkk6PgxxGKJaI3qO9kqSGpgaHJ0G+OHPY6fBBzp3A3BCKJaLvdCjqCQXmSfOaVZKkw92HHZ4EuY5QLBHsUWC+VQYrJUn9x/sdngS5jlAsEf2hE5KkyqpKhydBPnC5XPJX+CVJQ1E+oAhzQyiWiPhkXPF4XF6vV95Cr9PjIMeV+crk8Xg0OjLKE9mYM0KxhAwPDUsSn6WNOTuzN8HHnWI+EIolZDg29TkBvnKfw5Mg1wUqApKk6ClCgbkjFEtI7PQehY89CsyR/3QohggF5oFnthtms1l1dr4i27a1YUOrUqmkuru7po+rt7RskMcz65vDeYyPjkmSikuKHZ4Eue7MGf7xeMLhSZAPZr1H0d9/XEVFRdOXQ6GQfD6/Ojq2yefzKxTqW5ABL6Rl47rp39c31S/qfS+UdDotSXK72dHD3BQUFEiSMqe/p3Ld6nVr9F//5r/pq/f+hZrWNDs9zrIzq59I8Xhc0WhUVVXV09dFo4MKBqskScFglaLRwYWZ8AI+8JHbpn//3tvev6j3vVAymYykN/6TA5fqzPdQOk9CccuHb1VxSbFKSkt08wdvdnqcZWdWx4qOHj2sxsbms77pksmkbNuWJNm2rWTy/C/BGxjoVzjcf/prUnOd943bPdGv2vpaSVL/8RPzdrtOcrlckqRMNuPwJMh1Zz7J7sz3VK4bONGv2oZaKcsJhPMpmUyps3PP9OWqqhpVV9ecs92MoYhGT8myLJWWlip2+lU5F6O6+o07fvNAc/WDb9+vrZdfJkl6dMcj83a7TjpzyCmTJhSYmzMP6vJl7/RH/+eHOt53XJl0Rs88tdPpcfKGZXnU1tYx43YzhmJkZFjR6ClFo1Flsxml02kdPHhAlmUpkUjItm0lEglZ1uK+PfabTyLKlx+sZ56ATF1g7wyYrelQePIjFKlUSk89/qTTYyxbM4aisbFZjY3NkqRYLKYTJ0Jau3adjh49rEgkrLq6ekUiYQUCvPXEXPnKp14WOzI84vAkyHWjI6OSpNKyMocnQT645Nez1tbWq7u7S5HIgGzbq3Xr1s/nXMvSmRPtzpxPAVyqM+dPBCoDDk+CfHBRoSgvL1f56Ue9lmWptZWP7pxP5f6pUAxfwnNBwJtFTw1JeuMMbWAueMH+EuF2u1XqK1Mmk+HQE+bszB7Fmfd8AuaCUCwR5YFyud1ujY6M5s2T83BOIp7Q2OjY1CsWy0qdHgc5jlAsEXWNU2eXn+jLj3NC4LwzbwhYsaLC4UmQ6wjFEnHmk+3OfCQqMFdnPgyrobnR4UmQ6wjFEnHms7J7jxxzeBLki57uHknS6pbVDk+CXEcologzexS97FFgnvQcOCRJWt2yxuFJkOsIxRJQGaxUWXmZxkbHdOrkKafHQZ4I94c1Njomf4VfgUqep8ClIxRLwKYtU+ejdO3rcngS5JNsNqvDBzn8hLkjFEvApi2bJEl797zm8CTINz0HpkLRsrHF4UmQywiFwwqLirRm3Vql02m9/tp+p8dBntn36l5JUvtl7XwCJS4ZoXDYxrYNKvAUqKe7R+Nj406PgzwzcGJAfUd7VVRcrNbTe67AxSIUDtt6xTZJ0t5XOOyEhbHr2V2SpO1Xb3d4EuQqQuEgf0VAm7ZsUiqV0kvPveT0OMhTu59/SZlMRhvbWlVcUuz0OMhBhMJBV//G1XK73Xpl1ysa5Y0AsUBGhkfUtbdLHo9HHZdvdXoc5CBC4ZCCggJdfd3bJEk7n3ja4WmQ73Y9+6Ik6Zrrr3V4EuQiQuGQ9m1bVFZepuO9x6df6w4slFde2qOh6JBqG2rV2s6T2rg4hMIBbrdb77r53ZKkp//tVw5Pg+UgnUrrycefkCTd+L7fdHga5BpC4YDtV1+umtoaDUZO6oWdLzg9DpaJZ596RqMjo1q1dpU2bN7g9DiYpbvvuOu8v19MhGKReTwevefWmyRJjz38mNLptMMTYblIxBP6t5/9UpL0vt96v1wul8MTIVcQikV27TuvU6AyoFBvSC+/sNvpcbDMPP3ErxUbiqm+qUFbr7jM6XGQIwjFIirzlenG908dH/7pjkeVzWYdngjLTTKR1M8efkyS9IGP3KaS0hKHJ0IuIBSL6MOful0lJSXa37lf+zv3OT0Olqnnn35O3fsPqMxXpts++kGnx0EOIBSL5LIrt6lta7smJyb1w+894PQ4WOYe/N4DSsQT2nbVtul3LwYuhFAsgjJfmX7rY1OP3H7y4MMaig45OxCWvcHIoH760KOSpA998nYVFhU5PBGWMkKxwFwul3770x9RSWmJXn9tv57/9XNOjwRIkn79y1/p8MHD8gf8+uDHOQSFCyMUC+w9t96kTR2bNT42rge/96DT4wDTstmsHvjuDxSPx7X96st1/bvf4fRIWKIIxQLquHyr3nXzu5XJZPS9b3xXQ6eiTo8EnCV8YkD33/d9SdLNH7qF5ytwXoRigdQ31uujn/2YJOmfHvyJDvB52FiiXn3pFT328E/ldrv1id/7lFbWrXR6JCwxhGIBBCoD+p07Pyfba+v5p5/Tr/71KadHAox+8ejjeum5l1RYWKg77vxdlZaVOj0SlhBCMc/K/eX6/Je/oEBFQD3dPfrR//2h0yMBs/Lgd3+goz1HVRms1B98+d+p1Ffm9EhYIgjFPCr3l+vzf/QFBauD6j1yTN+695tKp3gvJ+SGZDKpb3/tHzVwYkB1DXW68yt3qjxQ7vRYWAIIxTwJVAb0xa98SdUrqxU61qdv/K+va3JiwumxgIsyHBvW1/7ybxTqDamqplp3fuUuVa6odHosOIxQzIPGVU2668/v1oqqFTp2+Jj+/q/+TuNj406PBVyS0ZFR/f3//JqO9hxRZbBSX/zTL6lqZbXTY8FBhGKOtl99ub74lTtV7i9X9/4D+vpfEwnkvvGxcX39r/9eB1/vlj/g15f+1JnPQcDSQCgukdvt1i23f0Af/9wnZFmWfv3LX+kb93xdkxOTTo8GzIv4ZFzfvPcf9NqeTt5ldpnzOD1ALqpYUaGPfPZjatnQonQqrR3f/5Ge/dWzTo8FzLtkIqlvf+0+vevmd09/4BaWH0JxEVwul67+jbfplg/fKm+hVyPDI/ru17+jngOHnB4NWDDZbFY//+d/IRTLGKGYpYoVFfrIZz6qlo3rJEkvv7BbO77/Y42Njjk8GQAsLEIxg6LiIt1w04267sa3y7ZtjQyPaMf/+5FeeekVp0cDgEVBKC7Asi1dd8PbdcNNN6q4pFiStPv5l/TQ/TvYiwCwrCxqKFyupf8iq+KSYl1x7ZX6jd+8Xv6AX5J0YP8BPfrjR9R75JizwwGAAxY1FLUNtfrgxz+knU/uVH/oxGLe9YwaVzXqmndcq61XXCbLsiRJfUd79eiOR9S1l3d+BbB8LWoo3G63rn3ndbr2ndfpcHePXtn9ivbueU0nwycXc4xpNbU12tSxWR3bO1Tf1DB9/f7Ofdr5xNPa9+o+ZbNZR2YDgKViVqHYvXuXCgoK5HK55HJJbW0dSqWS6u7uUjwel9frVUvLBnk85pvrD/Xr6X/7tba/7XKtalmtVS2r9YHfvk39x/u1d89r2t+5T71He5WIJ+ZlcW9VWFSkxlWNam1v1eaOzaoMrpj+s7HRMT3/9HN65smdGowMLsj9A0AumvUeRWvr5ulDMpIUCoXk8/lVV1evUKhPoVCfmpqajbeRTCa04/s/1qM7HlFre6s2bWlTa/tG1dTWqKa2Rje890ZlMhlF+sPqPdqnvqO9Ot53XLHokIZjw7M+67mouEjl/nKVB/yqa6hVfVOD6psaFKwOnrXdyPCI9r26V3v37NXrr+1XMpmc7V8HACwbl3zoKRodVGtrmyQpGKzSvn2dM4bijPhkXC+/8LJefuFluQvcWr12tTZvbdPqljVaWb9S1bU1qq6t0fart5/9dfG4hoeGNToyqnQqNX39F/74i/JYHpX5yuTzl58VtDdLJpM63hvSwdcP6rU9nTrac5RDSwBm7Z777nV6BEfMKhQul7R//165XFJVVY2qq2uUTCZl27YkybbtCz4aHxjoVzjcL0lKJlPn/HkmndHBroM62HVQklTgKVBtXa3qmxvU0NSgqpVV8pWXy+f3yev1KlgdPGfPYO2GlrMuT05MKjYU03BsWAPH+9V7tFd9R3rVf6JfmXRmNksGgLyXTKbU2bln+vKZn+9vNatQbNrUJtv2KplMaP/+vSoqKpr1INXVb9zxmwe6kHQqrd6jveo92qu3vnuSt9Crcn+5SkpLVVDg1hf+5E5J0tf+x98qk05rZHhUw7HYgj3HAWB5uvsOZ989d6H2ZCzLo7a2jhm3m1UobNt7+kZtBQKVGh0dlWVZSiQSsm1biUTigod75lN8Mq5wf1hS+KzrD53eGwEAzL8Zz4BLp9NKp1PTv4/FhlRcXKxAoEKRyNQP7EgkrECAT8ECgHw04x5FMpnUgQP7JU29i+SKFUH5/QGVlJSqu7tLkciAbNurdevWL/iwAIDFN2MoCgsL1d6+9ZzrLctSa+vmBRkKALB0LP03XwIAOIpQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMPLPZKJVKqafnoMbHxyVJa9asVVFRkbq7uxSPx+X1etXSskEez6xuDgCQQ2b1k/3IkR75/X6tW7dBmUxGmUxGoVCffD6/6urqFQr1KRTqU1NT8wKPCwBYbDMeekqlUhoZGVYwWD31BW63PB6PotFBBYNVkqRgsErR6ODCTgoAcMSMexTx+KQ8HkuHDh3U+PiYSkpK1Ny8WslkUrZtS5Js21YymTzv1w8M9Csc7pckJZOpeRwdADAXyWRKnZ17pi9XVdWourrmnO1mDEU2m9XY2Kiam1errKxMR4706PjxvlkPUl39xh2/eSAAgLMsy6O2to4Zt5vx0JNte2XbXpWVlUmSKioqNTY2JsuylEgkJEmJREKWZc1tYgDAkjSLUNjyer2amJh6xVMsFlNRUZECgQpFImFJUiQSViBQubCTAgAcMatXPTU3r9LBgweUzWbl9RZqzZoWZbNZdXd3KRIZkG17tW7d+oWeFQDggFmFoqSk9LzHsVpbN8/3PACAJYYzswEARoQCAGBEKAAARrw5E4CLcs999zo9AhYZexQAACP2KADMyt133OX0CMuW03tx7FEAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIwIBQDAiFAAAIw8M20wMTGu7u4D05fj8UnV1zcqGAyqu7tL8XhcXq9XLS0b5PHMeHMAgBwz40/2oqJitbd3SJKy2ax2735RFRUVCoVC8vn8qqurVyjUp1CoT01NzQs8LgBgsV3UoadYbEheb6G83kJFo4MKBqskScFglaLRwQUZEADgrIs6VjQ4eFIrVgQlSclkUrZtS5Js21YymTzv1wwM9Csc7j/9Nam5zAoAmEfJZEqdnXumL1dV1ai6uuac7WYdikwmo2j0lBoami5qkOrqN+74zQMBAJxlWR61tXXMuN2sDz0NDUVVUlI6vRdhWZYSiYQkKZFIyLKsS5sUALCkzToUg4MnVVm5YvpyIFChSCQsSYpEwgoEKud/OgCA42YVinQ6rVhsSBUVb8SgtrZesdiQ9ux5SbHYkOrq6hZsSACAc2b1HEVBQYG2b7/yrOssy1Jr6+YFGQoAsHRwZjYAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMCAUAwIhQAACMPLPZ6MSJkMLhAUkuFRcXa82aFmUyaXV3dykej8vr9aqlZYM8nlndHAAgh8z4kz2RiKu//4S2bNkqt7tABw68rpMnI5qYmJDP51ddXb1CoT6FQn1qampehJEBAItpVrsA2WxWmUxGLpdbmUxGtm3r+PE+tba2SZKCwSrt29c5Yygamht1z333znnot1qI2wQATJkxFLbt1cqVddq9e5fcbrfKy/3y+wNKJpOybfv0NraSyeR5v35goF/hcL8kqcxXNo+jAwDmIplMqbNzz/TlqqoaVVfXnLPdjKFIpVKKRk9p69btKigoUHd3lyKR8KwHqa5+4447O/fo7jvumvXXAgAWjmV51NbWMeN2M77qKRYbktfrlWVZcrvdqqio1OjoiCzLUiKRkCQlEglZljXnoQEAS8+MobBtr0ZHR5ROp5XNZhWLDamoqEiBQMX0nkUkElYgULngwwIAFt+Mh57KyspUUbFCnZ2vyOVyqaSkRFVVNUqn06cPQw3Itr1at279YswLAFhks3rVU0NDoxoaGs+6zu12q7V184IMBQBYOjgzGwBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEaEAgBgNKvPo5gv8Xj8rA/yng/JZEqWtajLWFD5th4p/9aUb+uR8m9N+bYeaWHWFI/HZ7Xdov5Nbt9+5bzfZmfnnll9OHiuyLf1SPm3pnxbj5R/a8q39UjOrolDTwAAI0IBADDK+VBUVdU4PcK8yrf1SPm3pnxbj5R/a8q39UjOrsl11VXXZB27dwDAkpfzexQAgIVFKAAARjn1QuNUKqWenoMaHx+XJK1Zs1ZFRUXq7u5SPB6X1+tVS8sGeTy5sayJiXF1dx+YvhyPT6q+vlHBYDBn13TiREjh8IAkl4qLi7VmTYsymXTOrkeSTpw4fnpNWVVV1WjlylqlUsmcWtOhQ92KRqOyLEtbtmyVJOMaQqE+hcMDcrmk5ubV8vsDTo5/jvOtZ3DwpPr6jmliYkKbN7ertLRsevulvh7p/Gs6evSwotGo3G6XvN5CrVnT4si/UU7tURw50iO/36+OjsvU3t6hoqJihUIh+Xx+dXRsk8/nVyjU5/SYs1ZUVKz29g61t3eorW2L3G63KioqcnZNiURc/f0n1Na2RVu2bFU2m9XJk5GcXY8kjY+PKRwe0ObN7Wpv36po9JQmJiZybk3BYJU2bmw967oLrWF8fFyDgxFt2bJVGzZs0uHDPcpml9ZTmedbT3Fxsdat26CyMt9Z1+fCeqTzr6m83K8tW7aqvX2rCguLHPs3yplQpFIpjYwMKxisliS53W55PB5Fo4MKBqskTf1FR6ODTo55yWKxIXm9hfJ6C3N6TdlsVplMZvpX27Zzej0TExMqLS1VQUGBXC6XfL5yRaODObcmn69cBQVn7/FcaA3R6ClVVgbldrtVWFiowsJCjY6OLPrMJudbT1FRsYqKis/ZNhfWI51/TX5/QC6XS5JUVlamRGLqTOrFXtPS3Vd+i3h8Uh6PpUOHDmp8fEwlJSVqbl6tZDIp27YlSbZtK5lMOjzppRkcPKkVK4KSlLNrsm2vVq6s0+7du+R2u1Ve7pffH8jZ9UhTj1J7e48qmUzK7XZraCiqkpLSnF7TGRdaQyIRP+uwjW3bSiQSjsw4H/JlPeHwgCorV0ha/DXlTCiy2azGxkbV3LxaZWVlOnKkR8ePL+3d/dnKZDKKRk+poaHJ6VHmJJVKKRo9pa1bt6ugoEDd3V2KRMJOjzUnRUXFqq2t1/79e1VQUKDi4mKdfoAHLJpQqFcul2v6weRiy5lDT7btlW17VVY2VdGKikqNjY3JsqzpkiYSCVmW5eSYl+TMo9Qzj+5ydU1Th8+8sizr9PMtlRodHcnZ9ZxRVVWt9vYObdrUJo/HUmFhUc6vSbrw95lte896dJpIJKa/N3NRrq8nEgkrGo1q7dp104ehFntNORQKW16vVxMTU694isViKioqUiBQMf2oNRIJKxCodHLMSzI4eHJ6l1JSzq7Jtr0aHR1ROp1WNptVLDaUF/9GyeTUf8h4PK5Tpwa1YkUw59ckXfj7LBCo0OBgRJlMRpOTk5qcnDjrMEeuyeX1DA1Fdfx4n9av36iCgoLp6xd7TTl1ZvbY2Kh6eg4qm81Ov1Qsm82qu7tLiURctu3VunXr5fHkzqO7dDqtl1/epY6ObdMve0smkzm7pt7eYxocPCmXy6WSkhKtXr1W6XQ6Z9cjSXv3diqVSsrlcqmpaZXKy/0592/U3d2l4eGYUqmULMtSfX2jAoGKC64hFOpVOByWyyU1Na1WILC0Xk56vvV4PB4dOdKjZDIpj8ej4uISbdy4SdLSX490/jWFQn3KZjPT/y6lpaVavXqtpMVdU06FAgCw+HLm0BMAwBmEAgBgRCgAAEaEAgBgRCgAAEaEAgBgRCgAAEb/H+sMZwdVVPgjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 936x612 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(13,8.5))\n",
    "fig.set_facecolor('#38383b')\n",
    "ax.patch.set_facecolor('#38383b')\n",
    "\n",
    "#The statsbomb pitch from mplsoccer\n",
    "pitch = Pitch(pitch_type='statsbomb', orientation='horizontal',\n",
    "              pitch_color='#38383b', line_color='#c7d5cc', figsize=(13, 8),\n",
    "              constrained_layout=False, tight_layout=True, view='half',axis=True,label=True,tick=True)\n",
    "\n",
    "pitch.draw(ax=ax)\n",
    "\n",
    "pitch.scatter(89,22,ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>96</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>99</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>102</td>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>104</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>95</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>86</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>79</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>89</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>99</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>100</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>102</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>104</td>\n",
       "      <td>43</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>104</td>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>102</td>\n",
       "      <td>55</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>97</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>98</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>94</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>77</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      x   y  team\n",
       "0    93   9     0\n",
       "1    96  22     0\n",
       "2    99  33     0\n",
       "3   102  44     0\n",
       "4   104  56     0\n",
       "5    95  63     0\n",
       "6    86  52     0\n",
       "7    79  33     0\n",
       "8    89  22     0\n",
       "9    99  14     1\n",
       "10  100  22     1\n",
       "11  102  33     1\n",
       "12  104  43     1\n",
       "13  104  46     1\n",
       "14  102  55     1\n",
       "15   97  37     1\n",
       "16   98  27     1\n",
       "17   94  21     1\n",
       "18   77  45     1"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "points=np.column_stack((df.x,df.y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(0.32, 0.9092156862745098, 'Cadiz'),\n",
       "  Text(0.398258547008547, 0.9092156862745098, ' Low Block vs '),\n",
       "  Text(0.5793482905982907, 0.9092156862745098, 'Barcelona')]]"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x612 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(13,8.5))\n",
    "fig.set_facecolor('#38383b')\n",
    "ax.patch.set_facecolor('#38383b')\n",
    "\n",
    "#The statsbomb pitch from mplsoccer\n",
    "pitch = Pitch(pitch_type='statsbomb', orientation='vertical',\n",
    "              pitch_color='#38383b', line_color='#c7d5cc', figsize=(13, 8),\n",
    "              constrained_layout=False, tight_layout=True, view='half')\n",
    "\n",
    "pitch.draw(ax=ax)\n",
    "\n",
    "x=df.x\n",
    "y=df.y\n",
    "team1,team2 = pitch.voronoi(x,y,df.team)\n",
    "\n",
    "t1 = pitch.polygon(team1, ax=ax, fc='#c34c45', ec='white', lw=3, alpha=0.4)\n",
    "t2 = pitch.polygon(team2, ax=ax, fc='#6f63c5', ec='white', lw=3, alpha=0.4)\n",
    "\n",
    "# Plot players\n",
    "for i in range(len(df['x'])):\n",
    "    if df['team'][i]==0:\n",
    "        pitch.scatter(df['x'][i],df['y'][i],ax=ax,color='blue')\n",
    "    if df['team'][i]==1:\n",
    "        pitch.scatter(df['x'][i],df['y'][i],ax=ax,color='red')\n",
    "        \n",
    "#plt.title('Messi Goal vs Real Betis',fontfamily='Andale Mono',c='white',fontsize=24,ha='center',va='center')\n",
    "\n",
    "fig.text(x=.22,y=.1,s='@mckayjohns / twitter',fontstyle='italic',fontsize=9,fontfamily='Andale Mono',color='white')\n",
    "\n",
    "s='<Cadiz> Low Block vs <Barcelona>'\n",
    "highlight_text.fig_text(s=s,x=.32, y=.87, \n",
    "                        fontfamily='Andale Mono', highlight_weights=['bold'], fontsize=24, color='white', \n",
    "                        highlight_colors=['#c34c45','#6f63c5'])\n",
    "\n",
    "\n",
    "#plt.savefig('voronoi.png',dpi=500,bbox_inches = 'tight',facecolor='#38383b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}