fourth-downs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading year: 2014\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-22-2d1190c79762>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2014\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2021\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"loading year: {x}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m     \u001b[0mplys\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_parquet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"https://raw.githubusercontent.com/saiemgilani/cfbfastR-data/master/data/parquet/pbp_players_pos_{x}.parquet\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m     \u001b[0mln\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mretrieveCfbDataFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'lines'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"loaded year: {x}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/io/parquet.py\u001b[0m in \u001b[0;36mread_parquet\u001b[0;34m(path, engine, columns, **kwargs)\u001b[0m\n\u001b[1;32m    280\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    281\u001b[0m     \u001b[0mimpl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 282\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mimpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/io/parquet.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, path, columns, **kwargs)\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    124\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 125\u001b[0;31m         \u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshould_close\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_filepath_or_buffer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    127\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'use_pandas_metadata'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_filepath_or_buffer\u001b[0;34m(filepath_or_buffer, encoding, compression, mode)\u001b[0m\n\u001b[1;32m    205\u001b[0m             \u001b[0;31m# Override compression based on Content-Encoding header\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    206\u001b[0m             \u001b[0mcompression\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'gzip'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 207\u001b[0;31m         \u001b[0mreader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    208\u001b[0m         \u001b[0mreq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mreader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompression\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, amt)\u001b[0m\n\u001b[1;32m    468\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    469\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 470\u001b[0;31m                     \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_safe_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlength\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    471\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mIncompleteRead\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    472\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_close_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/http/client.py\u001b[0m in \u001b[0;36m_safe_read\u001b[0;34m(self, amt)\u001b[0m\n\u001b[1;32m    618\u001b[0m         \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    619\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mamt\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 620\u001b[0;31m             \u001b[0mchunk\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mamt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mMAXAMOUNT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    621\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mchunk\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    622\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mIncompleteRead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mb''\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mamt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/socket.py\u001b[0m in \u001b[0;36mreadinto\u001b[0;34m(self, b)\u001b[0m\n\u001b[1;32m    587\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    588\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 589\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    590\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    591\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_timeout_occurred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/ssl.py\u001b[0m in \u001b[0;36mrecv_into\u001b[0;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[1;32m   1069\u001b[0m                   \u001b[0;34m\"non-zero flags not allowed in calls to recv_into() on %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1070\u001b[0m                   self.__class__)\n\u001b[0;32m-> 1071\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1072\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1073\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m    927\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    928\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mbuffer\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 929\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    930\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    931\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# Based on https://github.com/akeaswaran/cfb_fourth_down but in Python\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xgboost as xgb\n",
    "\n",
    "\n",
    "def retrieveCfbDataFile(endpoint, year):\n",
    "    return pd.read_csv(f\"data/{endpoint}/{year}.csv\", encoding='latin-1')\n",
    "\n",
    "pbp = pd.DataFrame()\n",
    "line_data = pd.DataFrame()\n",
    "\n",
    "for x in range(2014, 2021):\n",
    "    print(f\"loading year: {x}\")\n",
    "    plys = pd.read_parquet(f\"https://raw.githubusercontent.com/saiemgilani/cfbfastR-data/master/data/parquet/pbp_players_pos_{x}.parquet\")\n",
    "    ln = retrieveCfbDataFile('lines',x)\n",
    "    print(f\"loaded year: {x}\")\n",
    "    pbp = pbp.append(plys, sort=False)\n",
    "    \n",
    "    ln['year'] = x\n",
    "    line_data = line_data.append(ln, sort=False)\n",
    "\n",
    "print(f\"Total Plays: {len(pbp)}\")\n",
    "print(f\"Spreads imported: {len(line_data)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>year</th>\n",
       "      <th>week</th>\n",
       "      <th>id_play</th>\n",
       "      <th>game_id</th>\n",
       "      <th>game_play_number</th>\n",
       "      <th>half_play_number</th>\n",
       "      <th>drive_play_number</th>\n",
       "      <th>pos_team</th>\n",
       "      <th>def_pos_team</th>\n",
       "      <th>pos_team_score</th>\n",
       "      <th>...</th>\n",
       "      <th>lag_change_of_poss</th>\n",
       "      <th>lag_change_of_pos_team</th>\n",
       "      <th>lag_change_of_pos_team2</th>\n",
       "      <th>lag_kickoff_play</th>\n",
       "      <th>lag_punt</th>\n",
       "      <th>lag_punt2</th>\n",
       "      <th>lag_scoring_play</th>\n",
       "      <th>lag_turnover_vec</th>\n",
       "      <th>lag_downs_turnover</th>\n",
       "      <th>lag_defense_score_play</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>Temple</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>Temple</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 331 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      year  week       id_play    game_id  game_play_number  half_play_number  \\\n",
       "4   2014.0     1  4.005476e+17  400547640               4.0               4.0   \n",
       "7   2014.0     1  4.005476e+17  400547640               7.0               7.0   \n",
       "11  2014.0     1  4.005476e+17  400547640              11.0              11.0   \n",
       "16  2014.0     1  4.005476e+17  400547640              15.0              15.0   \n",
       "21  2014.0     1  4.005476e+17  400547640              19.0              19.0   \n",
       "\n",
       "    drive_play_number    pos_team def_pos_team  pos_team_score  ...  \\\n",
       "4                 4.0      Temple   Vanderbilt               0  ...   \n",
       "7                 7.0      Temple   Vanderbilt               0  ...   \n",
       "11                3.0  Vanderbilt       Temple               0  ...   \n",
       "16                3.0      Temple   Vanderbilt               0  ...   \n",
       "21                3.0  Vanderbilt       Temple               0  ...   \n",
       "\n",
       "    lag_change_of_poss  lag_change_of_pos_team  lag_change_of_pos_team2  \\\n",
       "4                  0.0                     0.0                      0.0   \n",
       "7                  0.0                     0.0                      0.0   \n",
       "11                 0.0                     0.0                      0.0   \n",
       "16                 0.0                     0.0                      0.0   \n",
       "21                 0.0                     0.0                      0.0   \n",
       "\n",
       "    lag_kickoff_play  lag_punt lag_punt2 lag_scoring_play  lag_turnover_vec  \\\n",
       "4                0.0       0.0       0.0              0.0               0.0   \n",
       "7                0.0       0.0       0.0              0.0               0.0   \n",
       "11               0.0       0.0       0.0              0.0               0.0   \n",
       "16               0.0       0.0       0.0              0.0               0.0   \n",
       "21               0.0       0.0       0.0              0.0               0.0   \n",
       "\n",
       "    lag_downs_turnover  lag_defense_score_play  \n",
       "4                  0.0                     0.0  \n",
       "7                  0.0                     0.0  \n",
       "11                 0.0                     0.0  \n",
       "16                 0.0                     0.0  \n",
       "21                 0.0                     0.0  \n",
       "\n",
       "[5 rows x 331 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_vars = pbp[\n",
    "    (pbp.down.isin([3,4]))\n",
    "    & ((pbp[\"rush\"] == 1) | (pbp[\"pass\"] == 1))\n",
    "    & (pbp.offense_play.notna())\n",
    "    & (pbp.yards_to_goal.notna())\n",
    "    & (pbp.score_diff.notna())\n",
    "#     & (pbp.offense_conference.notna())\n",
    "#     & (pbp.defense_conference.notna())\n",
    "]\n",
    "model_vars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>homeTeam</th>\n",
       "      <th>homeScore</th>\n",
       "      <th>awayTeam</th>\n",
       "      <th>awayScore</th>\n",
       "      <th>lineProvider</th>\n",
       "      <th>overUnder</th>\n",
       "      <th>spread</th>\n",
       "      <th>formattedSpread</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>400547640</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>37.0</td>\n",
       "      <td>numberfire</td>\n",
       "      <td>50.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>Vanderbilt -8.5</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>400547641</td>\n",
       "      <td>Connecticut</td>\n",
       "      <td>10.0</td>\n",
       "      <td>BYU</td>\n",
       "      <td>35.0</td>\n",
       "      <td>numberfire</td>\n",
       "      <td>54.0</td>\n",
       "      <td>15.5</td>\n",
       "      <td>BYU -15.5</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>400547642</td>\n",
       "      <td>UCF</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Penn State</td>\n",
       "      <td>26.0</td>\n",
       "      <td>numberfire</td>\n",
       "      <td>44.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>UCF -2</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>400547644</td>\n",
       "      <td>Houston</td>\n",
       "      <td>7.0</td>\n",
       "      <td>UT San Antonio</td>\n",
       "      <td>27.0</td>\n",
       "      <td>numberfire</td>\n",
       "      <td>56.0</td>\n",
       "      <td>-9.5</td>\n",
       "      <td>Houston -9.5</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>400547647</td>\n",
       "      <td>Tulsa</td>\n",
       "      <td>38.0</td>\n",
       "      <td>Tulane</td>\n",
       "      <td>31.0</td>\n",
       "      <td>numberfire</td>\n",
       "      <td>46.5</td>\n",
       "      <td>-4.5</td>\n",
       "      <td>Tulsa -4.5</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id     homeTeam  homeScore        awayTeam  awayScore lineProvider  \\\n",
       "0  400547640   Vanderbilt        7.0          Temple       37.0   numberfire   \n",
       "1  400547641  Connecticut       10.0             BYU       35.0   numberfire   \n",
       "2  400547642          UCF       24.0      Penn State       26.0   numberfire   \n",
       "3  400547644      Houston        7.0  UT San Antonio       27.0   numberfire   \n",
       "4  400547647        Tulsa       38.0          Tulane       31.0   numberfire   \n",
       "\n",
       "   overUnder  spread  formattedSpread  year  \n",
       "0       50.0    -8.5  Vanderbilt -8.5  2014  \n",
       "1       54.0    15.5        BYU -15.5  2014  \n",
       "2       44.0    -2.0           UCF -2  2014  \n",
       "3       56.0    -9.5     Houston -9.5  2014  \n",
       "4       46.5    -4.5       Tulsa -4.5  2014  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# model_line_data = line_data[\n",
    "#     (line_data.lineProvider == \"consensus\")\n",
    "# ]\n",
    "# model_line_data.head()\n",
    "# line_data.head()\n",
    "grouped_lines = line_data.groupby(\"id\")\n",
    "grouped_lines = grouped_lines.apply(lambda x: x[(x.overUnder.notna()) & (x.spread.notna())].head(1))\n",
    "grouped_lines = grouped_lines.reset_index(drop=True)\n",
    "# first_values.head()\n",
    "grouped_lines.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>week</th>\n",
       "      <th>id_play</th>\n",
       "      <th>game_id</th>\n",
       "      <th>game_play_number</th>\n",
       "      <th>half_play_number</th>\n",
       "      <th>drive_play_number</th>\n",
       "      <th>pos_team</th>\n",
       "      <th>def_pos_team</th>\n",
       "      <th>pos_team_score</th>\n",
       "      <th>...</th>\n",
       "      <th>lag_kickoff_play</th>\n",
       "      <th>lag_punt</th>\n",
       "      <th>lag_punt2</th>\n",
       "      <th>lag_scoring_play</th>\n",
       "      <th>lag_turnover_vec</th>\n",
       "      <th>lag_downs_turnover</th>\n",
       "      <th>lag_defense_score_play</th>\n",
       "      <th>id</th>\n",
       "      <th>spread</th>\n",
       "      <th>overUnder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014.0</td>\n",
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       "      <td>400547640</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>Temple</td>\n",
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       "      <td>...</td>\n",
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       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014.0</td>\n",
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       "      <td>400547640</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
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       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>19.0</td>\n",
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       "      <td>Temple</td>\n",
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       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 334 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  week       id_play    game_id  game_play_number  half_play_number  \\\n",
       "0  2014.0     1  4.005476e+17  400547640               4.0               4.0   \n",
       "1  2014.0     1  4.005476e+17  400547640               7.0               7.0   \n",
       "2  2014.0     1  4.005476e+17  400547640              11.0              11.0   \n",
       "3  2014.0     1  4.005476e+17  400547640              15.0              15.0   \n",
       "4  2014.0     1  4.005476e+17  400547640              19.0              19.0   \n",
       "\n",
       "   drive_play_number    pos_team def_pos_team  pos_team_score  ...  \\\n",
       "0                4.0      Temple   Vanderbilt               0  ...   \n",
       "1                7.0      Temple   Vanderbilt               0  ...   \n",
       "2                3.0  Vanderbilt       Temple               0  ...   \n",
       "3                3.0      Temple   Vanderbilt               0  ...   \n",
       "4                3.0  Vanderbilt       Temple               0  ...   \n",
       "\n",
       "   lag_kickoff_play  lag_punt  lag_punt2  lag_scoring_play  lag_turnover_vec  \\\n",
       "0               0.0       0.0        0.0               0.0               0.0   \n",
       "1               0.0       0.0        0.0               0.0               0.0   \n",
       "2               0.0       0.0        0.0               0.0               0.0   \n",
       "3               0.0       0.0        0.0               0.0               0.0   \n",
       "4               0.0       0.0        0.0               0.0               0.0   \n",
       "\n",
       "  lag_downs_turnover lag_defense_score_play           id  spread  overUnder  \n",
       "0                0.0                    0.0  400547640.0    -8.5       50.0  \n",
       "1                0.0                    0.0  400547640.0    -8.5       50.0  \n",
       "2                0.0                    0.0  400547640.0    -8.5       50.0  \n",
       "3                0.0                    0.0  400547640.0    -8.5       50.0  \n",
       "4                0.0                    0.0  400547640.0    -8.5       50.0  \n",
       "\n",
       "[5 rows x 334 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_vars = pd.merge(model_vars, grouped_lines[[\"id\",\"spread\",\"overUnder\"]], left_on=\"game_id\", right_on=\"id\", how='left')\n",
    "merged_vars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['year',\n",
       " 'week',\n",
       " 'id_play',\n",
       " 'game_id',\n",
       " 'game_play_number',\n",
       " 'half_play_number',\n",
       " 'drive_play_number',\n",
       " 'pos_team',\n",
       " 'def_pos_team',\n",
       " 'pos_team_score',\n",
       " 'def_pos_team_score',\n",
       " 'half',\n",
       " 'period',\n",
       " 'clock.minutes',\n",
       " 'clock.seconds',\n",
       " 'play_type',\n",
       " 'play_text',\n",
       " 'down',\n",
       " 'distance',\n",
       " 'yards_to_goal',\n",
       " 'yards_gained',\n",
       " 'EPA',\n",
       " 'ep_before',\n",
       " 'ep_after',\n",
       " 'wpa',\n",
       " 'wp_before',\n",
       " 'wp_after',\n",
       " 'def_wp_before',\n",
       " 'def_wp_after',\n",
       " 'penalty_detail',\n",
       " 'yds_penalty',\n",
       " 'penalty_1st_conv',\n",
       " 'new_series',\n",
       " 'firstD_by_kickoff',\n",
       " 'firstD_by_poss',\n",
       " 'firstD_by_penalty',\n",
       " 'firstD_by_yards',\n",
       " 'def_EPA',\n",
       " 'home_EPA',\n",
       " 'away_EPA',\n",
       " 'home_EPA_rush',\n",
       " 'away_EPA_rush',\n",
       " 'home_EPA_pass',\n",
       " 'away_EPA_pass',\n",
       " 'total_home_EPA',\n",
       " 'total_away_EPA',\n",
       " 'total_home_EPA_rush',\n",
       " 'total_away_EPA_rush',\n",
       " 'total_home_EPA_pass',\n",
       " 'total_away_EPA_pass',\n",
       " 'net_home_EPA',\n",
       " 'net_away_EPA',\n",
       " 'net_home_EPA_rush',\n",
       " 'net_away_EPA_rush',\n",
       " 'net_home_EPA_pass',\n",
       " 'net_away_EPA_pass',\n",
       " 'success',\n",
       " 'epa_success',\n",
       " 'rz_play',\n",
       " 'scoring_opp',\n",
       " 'middle_8',\n",
       " 'stuffed_run',\n",
       " 'change_of_pos_team',\n",
       " 'downs_turnover',\n",
       " 'turnover',\n",
       " 'pos_score_diff_start',\n",
       " 'pos_score_pts',\n",
       " 'log_ydstogo',\n",
       " 'ExpScoreDiff',\n",
       " 'ExpScoreDiff_Time_Ratio',\n",
       " 'half_clock.minutes',\n",
       " 'TimeSecsRem',\n",
       " 'adj_TimeSecsRem',\n",
       " 'Goal_To_Go',\n",
       " 'Under_two',\n",
       " 'home',\n",
       " 'away',\n",
       " 'home_wp_before',\n",
       " 'away_wp_before',\n",
       " 'home_wp_after',\n",
       " 'away_wp_after',\n",
       " 'end_of_half',\n",
       " 'pos_team_receives_2H_kickoff',\n",
       " 'lead_pos_team',\n",
       " 'lead_play_type',\n",
       " 'lag_pos_team',\n",
       " 'lag_play_type',\n",
       " 'orig_play_type',\n",
       " 'Under_three',\n",
       " 'down_end',\n",
       " 'distance_end',\n",
       " 'log_ydstogo_end',\n",
       " 'yards_to_goal_end',\n",
       " 'TimeSecsRem_end',\n",
       " 'Goal_To_Go_end',\n",
       " 'Under_two_end',\n",
       " 'offense_score_play',\n",
       " 'defense_score_play',\n",
       " 'ppa',\n",
       " 'yard_line',\n",
       " 'scoring',\n",
       " 'pos_team_timeouts_rem_before',\n",
       " 'def_pos_team_timeouts_rem_before',\n",
       " 'pos_team_timeouts',\n",
       " 'def_pos_team_timeouts',\n",
       " 'pos_score_diff',\n",
       " 'pos_score_diff_start_end',\n",
       " 'offense_play',\n",
       " 'defense_play',\n",
       " 'offense_receives_2H_kickoff',\n",
       " 'change_of_poss',\n",
       " 'score_pts',\n",
       " 'score_diff_start',\n",
       " 'score_diff',\n",
       " 'offense_score',\n",
       " 'defense_score',\n",
       " 'offense_conference',\n",
       " 'defense_conference',\n",
       " 'off_timeout_called',\n",
       " 'def_timeout_called',\n",
       " 'offense_timeouts',\n",
       " 'defense_timeouts',\n",
       " 'off_timeouts_rem_before',\n",
       " 'def_timeouts_rem_before',\n",
       " 'rusher_player_name',\n",
       " 'yds_rushed',\n",
       " 'passer_player_name',\n",
       " 'receiver_player_name',\n",
       " 'yds_receiving',\n",
       " 'yds_sacked',\n",
       " 'sack_players',\n",
       " 'sack_player_name',\n",
       " 'sack_player_name2',\n",
       " 'pass_breakup_player_name',\n",
       " 'interception_player_name',\n",
       " 'yds_int_return',\n",
       " 'fumble_player_name',\n",
       " 'fumble_forced_player_name',\n",
       " 'fumble_recovered_player_name',\n",
       " 'yds_fumble_return',\n",
       " 'punter_player_name',\n",
       " 'yds_punted',\n",
       " 'punt_returner_player_name',\n",
       " 'yds_punt_return',\n",
       " 'yds_punt_gained',\n",
       " 'punt_block_player_name',\n",
       " 'punt_block_return_player_name',\n",
       " 'fg_kicker_player_name',\n",
       " 'yds_fg',\n",
       " 'fg_block_player_name',\n",
       " 'fg_return_player_name',\n",
       " 'kickoff_player_name',\n",
       " 'yds_kickoff',\n",
       " 'kickoff_returner_player_name',\n",
       " 'yds_kickoff_return',\n",
       " 'new_id',\n",
       " 'orig_drive_number',\n",
       " 'drive_number',\n",
       " 'drive_result_detailed',\n",
       " 'new_drive_pts',\n",
       " 'drive_id',\n",
       " 'drive_result',\n",
       " 'drive_start_yards_to_goal',\n",
       " 'drive_end_yards_to_goal',\n",
       " 'drive_yards',\n",
       " 'drive_scoring',\n",
       " 'drive_pts',\n",
       " 'drive_start_period',\n",
       " 'drive_end_period',\n",
       " 'drive_time_minutes_start',\n",
       " 'drive_time_seconds_start',\n",
       " 'drive_time_minutes_end',\n",
       " 'drive_time_seconds_end',\n",
       " 'drive_time_minutes_elapsed',\n",
       " 'drive_time_seconds_elapsed',\n",
       " 'drive_numbers',\n",
       " 'number_of_drives',\n",
       " 'pts_scored',\n",
       " 'drive_result_detailed_flag',\n",
       " 'drive_result2',\n",
       " 'drive_num',\n",
       " 'lag_drive_result_detailed',\n",
       " 'lead_drive_result_detailed',\n",
       " 'lag_new_drive_pts',\n",
       " 'id_drive',\n",
       " 'rush',\n",
       " 'rush_td',\n",
       " 'pass',\n",
       " 'pass_td',\n",
       " 'completion',\n",
       " 'pass_attempt',\n",
       " 'target',\n",
       " 'sack_vec',\n",
       " 'sack',\n",
       " 'int',\n",
       " 'int_td',\n",
       " 'turnover_vec',\n",
       " 'turnover_vec_lag',\n",
       " 'turnover_indicator',\n",
       " 'kickoff_play',\n",
       " 'receives_2H_kickoff',\n",
       " 'missing_yard_flag',\n",
       " 'scoring_play',\n",
       " 'td_play',\n",
       " 'touchdown',\n",
       " 'safety',\n",
       " 'fumble_vec',\n",
       " 'kickoff_tb',\n",
       " 'kickoff_onside',\n",
       " 'kickoff_oob',\n",
       " 'kickoff_fair_catch',\n",
       " 'kickoff_downed',\n",
       " 'kickoff_safety',\n",
       " 'kick_play',\n",
       " 'punt',\n",
       " 'punt_play',\n",
       " 'punt_tb',\n",
       " 'punt_oob',\n",
       " 'punt_fair_catch',\n",
       " 'punt_downed',\n",
       " 'punt_safety',\n",
       " 'punt_blocked',\n",
       " 'penalty_safety',\n",
       " 'fg_inds',\n",
       " 'fg_made',\n",
       " 'fg_make_prob',\n",
       " 'No_Score_before',\n",
       " 'FG_before',\n",
       " 'Opp_FG_before',\n",
       " 'Opp_Safety_before',\n",
       " 'Opp_TD_before',\n",
       " 'Safety_before',\n",
       " 'TD_before',\n",
       " 'No_Score_after',\n",
       " 'FG_after',\n",
       " 'Opp_FG_after',\n",
       " 'Opp_Safety_after',\n",
       " 'Opp_TD_after',\n",
       " 'Safety_after',\n",
       " 'TD_after',\n",
       " 'position_reception',\n",
       " 'position_target',\n",
       " 'position_completion',\n",
       " 'position_incompletion',\n",
       " 'position_sack_taken',\n",
       " 'position_sack',\n",
       " 'position_interception_thrown',\n",
       " 'position_interception',\n",
       " 'position_fumble',\n",
       " 'position_fumble_forced',\n",
       " 'position_fumble_recovered',\n",
       " 'position_pass_breakup',\n",
       " 'position_rush',\n",
       " 'position_touchdown',\n",
       " 'season',\n",
       " 'opponent',\n",
       " 'team_score',\n",
       " 'opponent_score',\n",
       " 'rush_player_id',\n",
       " 'rush_player',\n",
       " 'rush_yds',\n",
       " 'reception_player_id',\n",
       " 'reception_player',\n",
       " 'reception_yds',\n",
       " 'completion_player_id',\n",
       " 'completion_player',\n",
       " 'completion_yds',\n",
       " 'interception_player_id',\n",
       " 'interception_player',\n",
       " 'interception_stat',\n",
       " 'interception_thrown_player_id',\n",
       " 'interception_thrown_player',\n",
       " 'interception_thrown_stat',\n",
       " 'touchdown_player_id',\n",
       " 'touchdown_player',\n",
       " 'touchdown_stat',\n",
       " 'incompletion_player_id',\n",
       " 'incompletion_player',\n",
       " 'incompletion_stat',\n",
       " 'target_player_id',\n",
       " 'target_player',\n",
       " 'target_stat',\n",
       " 'fumble_recovered_player_id',\n",
       " 'fumble_recovered_player',\n",
       " 'fumble_recovered_stat',\n",
       " 'fumble_forced_player_id',\n",
       " 'fumble_forced_player',\n",
       " 'fumble_forced_stat',\n",
       " 'fumble_player_id',\n",
       " 'fumble_player',\n",
       " 'fumble_stat',\n",
       " 'sack_player_id',\n",
       " 'sack_player',\n",
       " 'sack_stat',\n",
       " 'sack_taken_player_id',\n",
       " 'sack_taken_player',\n",
       " 'sack_taken_stat',\n",
       " 'pass_breakup_player_id',\n",
       " 'pass_breakup_player',\n",
       " 'pass_breakup_stat',\n",
       " 'play_id',\n",
       " 'penalty_flag',\n",
       " 'penalty_declined',\n",
       " 'penalty_no_play',\n",
       " 'penalty_offset',\n",
       " 'penalty_text',\n",
       " 'penalty_play_text',\n",
       " 'row',\n",
       " 'drive_event_number',\n",
       " 'lag_play_type2',\n",
       " 'lag_play_type3',\n",
       " 'lag_play_text',\n",
       " 'lag_play_text2',\n",
       " 'lead_play_text',\n",
       " 'lag_first_by_penalty',\n",
       " 'lag_first_by_penalty2',\n",
       " 'lag_first_by_yards',\n",
       " 'lag_first_by_yards2',\n",
       " 'first_by_penalty',\n",
       " 'first_by_yards',\n",
       " 'play_after_turnover',\n",
       " 'lag_change_of_poss',\n",
       " 'lag_change_of_pos_team',\n",
       " 'lag_change_of_pos_team2',\n",
       " 'lag_kickoff_play',\n",
       " 'lag_punt',\n",
       " 'lag_punt2',\n",
       " 'lag_scoring_play',\n",
       " 'lag_turnover_vec',\n",
       " 'lag_downs_turnover',\n",
       " 'lag_defense_score_play']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_vars.columns.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>year</th>\n",
       "      <th>week</th>\n",
       "      <th>id_play</th>\n",
       "      <th>game_id</th>\n",
       "      <th>game_play_number</th>\n",
       "      <th>half_play_number</th>\n",
       "      <th>drive_play_number</th>\n",
       "      <th>pos_team</th>\n",
       "      <th>def_pos_team</th>\n",
       "      <th>pos_team_score</th>\n",
       "      <th>...</th>\n",
       "      <th>lag_downs_turnover</th>\n",
       "      <th>lag_defense_score_play</th>\n",
       "      <th>id</th>\n",
       "      <th>spread</th>\n",
       "      <th>overUnder</th>\n",
       "      <th>first_down_penalty</th>\n",
       "      <th>home_total</th>\n",
       "      <th>away_total</th>\n",
       "      <th>posteam_total</th>\n",
       "      <th>posteam_spread</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.75</td>\n",
       "      <td>29.25</td>\n",
       "      <td>29.25</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.75</td>\n",
       "      <td>29.25</td>\n",
       "      <td>29.25</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>Temple</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.75</td>\n",
       "      <td>29.25</td>\n",
       "      <td>20.75</td>\n",
       "      <td>-8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Temple</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.75</td>\n",
       "      <td>29.25</td>\n",
       "      <td>29.25</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.005476e+17</td>\n",
       "      <td>400547640</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Vanderbilt</td>\n",
       "      <td>Temple</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400547640.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.75</td>\n",
       "      <td>29.25</td>\n",
       "      <td>20.75</td>\n",
       "      <td>-8.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 339 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  week       id_play    game_id  game_play_number  half_play_number  \\\n",
       "0  2014.0     1  4.005476e+17  400547640               4.0               4.0   \n",
       "1  2014.0     1  4.005476e+17  400547640               7.0               7.0   \n",
       "2  2014.0     1  4.005476e+17  400547640              11.0              11.0   \n",
       "3  2014.0     1  4.005476e+17  400547640              15.0              15.0   \n",
       "4  2014.0     1  4.005476e+17  400547640              19.0              19.0   \n",
       "\n",
       "   drive_play_number    pos_team def_pos_team  pos_team_score  ...  \\\n",
       "0                4.0      Temple   Vanderbilt               0  ...   \n",
       "1                7.0      Temple   Vanderbilt               0  ...   \n",
       "2                3.0  Vanderbilt       Temple               0  ...   \n",
       "3                3.0      Temple   Vanderbilt               0  ...   \n",
       "4                3.0  Vanderbilt       Temple               0  ...   \n",
       "\n",
       "   lag_downs_turnover  lag_defense_score_play           id  spread  overUnder  \\\n",
       "0                 0.0                     0.0  400547640.0    -8.5       50.0   \n",
       "1                 0.0                     0.0  400547640.0    -8.5       50.0   \n",
       "2                 0.0                     0.0  400547640.0    -8.5       50.0   \n",
       "3                 0.0                     0.0  400547640.0    -8.5       50.0   \n",
       "4                 0.0                     0.0  400547640.0    -8.5       50.0   \n",
       "\n",
       "  first_down_penalty home_total  away_total  posteam_total  posteam_spread  \n",
       "0                0.0      20.75       29.25          29.25             8.5  \n",
       "1                0.0      20.75       29.25          29.25             8.5  \n",
       "2                0.0      20.75       29.25          20.75            -8.5  \n",
       "3                0.0      20.75       29.25          29.25             8.5  \n",
       "4                0.0      20.75       29.25          20.75            -8.5  \n",
       "\n",
       "[5 rows x 339 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_vars[\"first_down_penalty\"] = merged_vars[\"firstD_by_penalty\"]\n",
    "\n",
    "merged_vars.yards_gained = merged_vars.yards_gained.clip(-10, 65)\n",
    "merged_vars[\"home_total\"] = (merged_vars.spread + merged_vars.overUnder) / 2\n",
    "merged_vars[\"away_total\"] = (merged_vars.overUnder - merged_vars.spread) / 2\n",
    "merged_vars[\"posteam_total\"] = np.where(merged_vars.offense_play == merged_vars.home, merged_vars.home_total, merged_vars.away_total)\n",
    "merged_vars[\"posteam_spread\"] = np.where(merged_vars.offense_play == merged_vars.home, merged_vars.spread, -1 * merged_vars.spread)\n",
    "\n",
    "merged_vars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/akeaswaran/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "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>down</th>\n",
       "      <th>distance</th>\n",
       "      <th>yards_to_goal</th>\n",
       "      <th>posteam_total</th>\n",
       "      <th>posteam_spread</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>21.25</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21061</th>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26.50</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32675</th>\n",
       "      <td>3.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>16.75</td>\n",
       "      <td>-32.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41662</th>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69430</th>\n",
       "      <td>3.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.50</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       down  distance  yards_to_goal  posteam_total  posteam_spread  label\n",
       "1300    3.0      10.0            4.0          21.25            -7.5     14\n",
       "21061   3.0      10.0            9.0          26.50            -4.0     19\n",
       "32675   3.0      18.0           17.0          16.75           -32.0     10\n",
       "41662   3.0      10.0            1.0          25.00           -10.0     11\n",
       "69430   3.0      13.0            9.0          12.50           -18.0     19"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_vars = merged_vars[\n",
    "    (((merged_vars[\"rush\"] + merged_vars[\"pass\"]) == 1) | (merged_vars.first_down_penalty == 1))\n",
    "    & (merged_vars.distance > 0)\n",
    "    & (merged_vars.yards_to_goal > 0)\n",
    "    & (merged_vars.distance > merged_vars.yards_to_goal)\n",
    "    & (merged_vars.posteam_total.notna())\n",
    "    & (merged_vars.posteam_spread.notna())\n",
    "]\n",
    "filtered_vars[\"label\"] = (filtered_vars.yards_gained.astype(float) + 10).astype(int)\n",
    "filtered_vars = filtered_vars[[\"down\",\"distance\",\"yards_to_goal\",\"posteam_total\",\"posteam_spread\",\"label\"]]\n",
    "filtered_vars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xgboost.core.Booster at 0x7fc58346f3d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nrounds = 157\n",
    "params = {\n",
    "    \"booster\": \"gbtree\",\n",
    "    \"objective\": \"multi:softprob\",\n",
    "    \"eval_metric\": \"mlogloss\",\n",
    "    \"num_class\": 76,\n",
    "    \"eta\": .07,\n",
    "    \"gamma\": 4.325037e-09,\n",
    "    \"subsample\": 0.5385424,\n",
    "    \"colsample_bytree\": 0.6666667,\n",
    "    'max_depth': 4,\n",
    "    \"min_child_weight\": 7\n",
    "}\n",
    "full_train = xgb.DMatrix(filtered_vars[[\"down\",\"distance\",\"yards_to_goal\",\"posteam_total\",\"posteam_spread\"]], label = filtered_vars.label)\n",
    "fd_model = xgb.train(params, full_train, nrounds)\n",
    "fd_model\n",
    "# full_train = xgboost::xgb.DMatrix(model.matrix(~.+0, data = model_vars %>% dplyr::select(-label)), label = as.integer(model_vars$label))\n",
    "# fd_model <- xgboost::xgboost(params = params, data = full_train, nrounds = nrounds, verbose = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "fd_model.save_model(\"fd_model.model\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "input {\n",
       "  name: \"down\"\n",
       "  shortDescription: \"The current down.\"\n",
       "  type {\n",
       "    doubleType {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "input {\n",
       "  name: \"distance\"\n",
       "  shortDescription: \"The number of yards to gain a first down.\"\n",
       "  type {\n",
       "    doubleType {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "input {\n",
       "  name: \"yards_to_goal\"\n",
       "  shortDescription: \"The yards left to gain towards the end zone.\"\n",
       "  type {\n",
       "    doubleType {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "input {\n",
       "  name: \"posteam_total\"\n",
       "  shortDescription: \"The over/under for the game from the current offense\\'s perspective.\"\n",
       "  type {\n",
       "    doubleType {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "input {\n",
       "  name: \"posteam_spread\"\n",
       "  shortDescription: \"The spread for the game from the current offense\\'s perspective. Note that a home favorite will have a negative spread value.\"\n",
       "  type {\n",
       "    doubleType {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "output {\n",
       "  name: \"target\"\n",
       "  type {\n",
       "    int64Type {\n",
       "    }\n",
       "  }\n",
       "}\n",
       "output {\n",
       "  name: \"classProbability\"\n",
       "  type {\n",
       "    dictionaryType {\n",
       "      int64KeyType {\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "}\n",
       "predictedFeatureName: \"target\"\n",
       "predictedProbabilitiesName: \"classProbability\"\n",
       "metadata {\n",
       "  shortDescription: \"Projects number of yards gained on a fourth-down play.\"\n",
       "  author: \"Jason Lee for original R code; Akshay Easwaran for Python and CoreML conversion.\"\n",
       "  license: \"MIT\"\n",
       "  userDefined {\n",
       "    key: \"com.github.apple.coremltools.source\"\n",
       "    value: \"xgboost==1.2.0\"\n",
       "  }\n",
       "  userDefined {\n",
       "    key: \"com.github.apple.coremltools.version\"\n",
       "    value: \"4.0\"\n",
       "  }\n",
       "}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import coremltools as cml\n",
    "cml_model = cml.converters.xgboost.convert(fd_model, force_32bit_float=False, mode=\"classifier\", feature_names=[\n",
    "    \"down\",\"distance\",\"yards_to_goal\",\"posteam_total\",\"posteam_spread\"\n",
    "], n_classes=76)\n",
    "cml_model.author = 'Jason Lee for original R code; Akshay Easwaran for Python and CoreML conversion.'\n",
    "cml_model.license = 'MIT'\n",
    "cml_model.short_description = 'Projects number of yards gained on a fourth-down play.'\n",
    "cml_model\n",
    "\n",
    "# # Set feature descriptions manually\n",
    "cml_model.input_description['posteam_spread'] = 'The spread for the game from the current offense\\'s perspective. Note that a home favorite will have a negative spread value.'\n",
    "cml_model.input_description['posteam_total'] = 'The over/under for the game from the current offense\\'s perspective.'\n",
    "cml_model.input_description['yards_to_goal'] = 'The yards left to gain towards the end zone.'\n",
    "cml_model.input_description['distance'] = 'The number of yards to gain a first down.'\n",
    "cml_model.input_description['down'] = 'The current down.'\n",
    "\n",
    "# cml_model.output_description['target'] = \"The projected number of yards gained on this fourth-down play.\"\n",
    "\n",
    "# # # Save the model\n",
    "cml_model.save('FourthDownYards.mlmodel')\n",
    "cml_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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