YUSAG_FCS_Elo_Model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The YUSAG FCS Elo Model\n",
    "    by Matt Robinson, Yale Undergraduate Sports Analytics Group"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start by loading the csv of game data, sorted by date:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "game_df = pd.read_csv('2013-2016_NCAA_football_fcs_elo.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>team</th>\n",
       "      <th>opponent</th>\n",
       "      <th>location</th>\n",
       "      <th>teamscore</th>\n",
       "      <th>oppscore</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Central Ark.</td>\n",
       "      <td>Incarnate Word</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>UT Martin</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Dayton</td>\n",
       "      <td>Youngstown St.</td>\n",
       "      <td>-1</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Delaware</td>\n",
       "      <td>Jacksonville</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Eastern Ky.</td>\n",
       "      <td>Robert Morris</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  month  day          team        opponent  location  teamscore  \\\n",
       "0  2013      8   29  Central Ark.  Incarnate Word         1         58   \n",
       "1  2013      8   29   Chattanooga       UT Martin         1         21   \n",
       "2  2013      8   29        Dayton  Youngstown St.        -1         10   \n",
       "3  2013      8   29      Delaware    Jacksonville         1         51   \n",
       "4  2013      8   29   Eastern Ky.   Robert Morris         1         38   \n",
       "\n",
       "   oppscore  \n",
       "0         7  \n",
       "1        31  \n",
       "2        28  \n",
       "3        35  \n",
       "4         6  "
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "game_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "game_df['scorediff'] = (game_df['teamscore']-game_df['oppscore'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>team</th>\n",
       "      <th>opponent</th>\n",
       "      <th>location</th>\n",
       "      <th>teamscore</th>\n",
       "      <th>oppscore</th>\n",
       "      <th>scorediff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Central Ark.</td>\n",
       "      <td>Incarnate Word</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>7</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>UT Martin</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>31</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Dayton</td>\n",
       "      <td>Youngstown St.</td>\n",
       "      <td>-1</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Delaware</td>\n",
       "      <td>Jacksonville</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>Eastern Ky.</td>\n",
       "      <td>Robert Morris</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "      <td>6</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  month  day          team        opponent  location  teamscore  \\\n",
       "0  2013      8   29  Central Ark.  Incarnate Word         1         58   \n",
       "1  2013      8   29   Chattanooga       UT Martin         1         21   \n",
       "2  2013      8   29        Dayton  Youngstown St.        -1         10   \n",
       "3  2013      8   29      Delaware    Jacksonville         1         51   \n",
       "4  2013      8   29   Eastern Ky.   Robert Morris         1         38   \n",
       "\n",
       "   oppscore  scorediff  \n",
       "0         7         51  \n",
       "1        31        -10  \n",
       "2        28        -18  \n",
       "3        35         16  \n",
       "4         6         32  "
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "game_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll create an initial dictionary of elo ratings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "elo_ratings_dict = {}\n",
    "for index, row in game_df.iterrows():\n",
    "    elo_ratings_dict[row['team']] = 1500\n",
    "    # also go through opponent column in case any team only in that column\n",
    "    elo_ratings_dict[row['opponent']] = 1500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Now, let's go through the games and apply the elo algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# function to update elo ratings based on the score\n",
    "def elo_update(winner_elo, loser_elo, mov):\n",
    "    k = 20\n",
    "    mov_multiplier = (2.2 * np.log(mov + 1))/((0.001 * (winner_elo-loser_elo))+2.2)\n",
    "    \n",
    "    u_winner = 1/(1+(10 ** ((winner_elo-loser_elo)/400)))\n",
    "    u_loser = 1/(1+(10 ** ((loser_elo-winner_elo)/400)))\n",
    "    \n",
    "    s1 = 1\n",
    "    s2 = 0\n",
    "    \n",
    "    new_winner_elo = winner_elo + k * mov_multiplier * (s1 - u_winner)\n",
    "    new_loser_elo = loser_elo + k * mov_multiplier * (s2 - u_loser)\n",
    "    \n",
    "    return [new_winner_elo, new_loser_elo]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "current_year = 2013\n",
    "for index, row in game_df.iterrows():\n",
    "    # first check if it is a new year\n",
    "    year = row['year']\n",
    "    if year != current_year:\n",
    "        # if new year, regress all elo ratings to the mean\n",
    "        for key in elo_ratings_dict:\n",
    "            elo_ratings_dict[key] = (0.5*elo_ratings_dict[key]) + (0.5*1500)\n",
    "        # update the year\n",
    "        current_year = year\n",
    "        \n",
    "    # find the margin of victory\n",
    "    score_diff = row['scorediff']\n",
    "    mov = abs(score_diff)\n",
    "        \n",
    "    # check if the game was at home, away, or neutral\n",
    "    if row['location'] == 1.0:\n",
    "        home_team = row['team']\n",
    "        away_team = row['opponent']\n",
    "        \n",
    "        # get corresponding elo ratings\n",
    "        home_elo = elo_ratings_dict[home_team] + 65\n",
    "        away_elo = elo_ratings_dict[away_team]\n",
    "        \n",
    "        # check if home or away team won\n",
    "        if score_diff > 0: \n",
    "            new_home_elo = elo_update(home_elo,away_elo,mov)[0] - 65\n",
    "            new_away_elo = elo_update(home_elo,away_elo,mov)[1]\n",
    "        elif score_diff < 0:\n",
    "            new_away_elo = elo_update(away_elo,home_elo,mov)[0]\n",
    "            new_home_elo = elo_update(away_elo,home_elo,mov)[1] - 65 \n",
    "            \n",
    "        # update the ratings dict\n",
    "        elo_ratings_dict[home_team] = new_home_elo\n",
    "        elo_ratings_dict[away_team] = new_away_elo\n",
    "        \n",
    "    elif row['location'] == -1.0:\n",
    "        home_team = row['opponent']\n",
    "        away_team = row['team']\n",
    "        \n",
    "        # get corresponding elo ratings\n",
    "        home_elo = elo_ratings_dict[home_team] + 65\n",
    "        away_elo = elo_ratings_dict[away_team]\n",
    "        \n",
    "        # check if home or away team won\n",
    "        if score_diff < 0: \n",
    "            new_home_elo = elo_update(home_elo,away_elo,mov)[0] - 65\n",
    "            new_away_elo = elo_update(home_elo,away_elo,mov)[1]\n",
    "        elif score_diff > 0:\n",
    "            new_away_elo = elo_update(away_elo,home_elo,mov)[0]\n",
    "            new_home_elo = elo_update(away_elo,home_elo,mov)[1] - 65 \n",
    "            \n",
    "        # update the ratings dict\n",
    "        elo_ratings_dict[home_team] = new_home_elo\n",
    "        elo_ratings_dict[away_team] = new_away_elo\n",
    "            \n",
    "    elif row['location'] == 0.0:\n",
    "        # since neutral just arbitrarily make home and away, but don't add 65\n",
    "        home_team = row['team']\n",
    "        away_team = row['opponent']\n",
    "        \n",
    "        # get corresponding elo ratings\n",
    "        home_elo = elo_ratings_dict[home_team]\n",
    "        away_elo = elo_ratings_dict[away_team]\n",
    "        \n",
    "        # check if home or away team won\n",
    "        if score_diff > 0: \n",
    "            new_home_elo = elo_update(home_elo,away_elo,mov)[0]\n",
    "            new_away_elo = elo_update(home_elo,away_elo,mov)[1]\n",
    "        elif score_diff < 0:\n",
    "            new_away_elo = elo_update(away_elo,home_elo,mov)[0]\n",
    "            new_home_elo = elo_update(away_elo,home_elo,mov)[1] \n",
    "            \n",
    "        # update the ratings dict\n",
    "        elo_ratings_dict[home_team] = new_home_elo\n",
    "        elo_ratings_dict[away_team] = new_away_elo\n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Abilene Christian': 1371.974938356436,\n",
       " 'Alabama A&M': 1374.3341829364481,\n",
       " 'Alabama St.': 1531.3148770439902,\n",
       " 'Albany (NY)': 1450.2693603080852,\n",
       " 'Alcorn': 1701.8276801582988,\n",
       " 'Ark.-Pine Bluff': 1161.740418109933,\n",
       " 'Austin Peay': 1123.4516182364441,\n",
       " 'Bethune-Cookman': 1648.4534815599309,\n",
       " 'Brown': 1483.962590862064,\n",
       " 'Bryant': 1507.9389540387938,\n",
       " 'Bucknell': 1512.8109647936383,\n",
       " 'Butler': 1419.6600888772978,\n",
       " 'Cal Poly': 1566.1194861884806,\n",
       " 'Campbell': 1450.2633126904798,\n",
       " 'Central Ark.': 1651.5359822068558,\n",
       " 'Central Conn. St.': 1248.925705135111,\n",
       " 'Charleston So.': 1663.2472596991638,\n",
       " 'Charlotte': 1498.2961741013578,\n",
       " 'Chattanooga': 1789.5125575680909,\n",
       " 'Coastal Caro.': 1664.9051818247553,\n",
       " 'Colgate': 1523.1475646331128,\n",
       " 'Columbia': 1248.9326673570238,\n",
       " 'Cornell': 1255.826315531858,\n",
       " 'Dartmouth': 1638.3716743940108,\n",
       " 'Davidson': 1161.991736348733,\n",
       " 'Dayton': 1764.5603427276037,\n",
       " 'Delaware': 1476.5952521239183,\n",
       " 'Delaware St.': 1161.103845779578,\n",
       " 'Drake': 1535.9457766586243,\n",
       " 'Duquesne': 1589.0757560955617,\n",
       " 'ETSU': 1307.7035714020321,\n",
       " 'Eastern Ill.': 1592.6017420523813,\n",
       " 'Eastern Ky.': 1574.0307901436413,\n",
       " 'Eastern Wash.': 1762.8820015346482,\n",
       " 'Elon': 1224.3533603503838,\n",
       " 'Florida A&M': 1336.1859120785418,\n",
       " 'Fordham': 1771.9473721716381,\n",
       " 'Furman': 1374.5163149413702,\n",
       " 'Gardner-Webb': 1402.4316671493505,\n",
       " 'Georgetown': 1306.0999539659297,\n",
       " 'Grambling': 1740.4148814920263,\n",
       " 'Hampton': 1442.7437297829019,\n",
       " 'Harvard': 1781.550447813401,\n",
       " 'Holy Cross': 1409.332327661456,\n",
       " 'Houston Baptist': 1254.9947172161642,\n",
       " 'Howard': 1373.273541160323,\n",
       " 'Idaho St.': 1326.9412271058495,\n",
       " 'Illinois St.': 1659.68107625332,\n",
       " 'Incarnate Word': 1315.2278894323636,\n",
       " 'Indiana St.': 1388.9763457261065,\n",
       " 'Jackson St.': 1399.5377687451864,\n",
       " 'Jacksonville': 1602.3130425778581,\n",
       " 'Jacksonville St.': 1830.8210672861949,\n",
       " 'James Madison': 1877.6496120704533,\n",
       " 'Kennesaw St.': 1512.3851352153467,\n",
       " 'Lafayette': 1225.7862597985782,\n",
       " 'Lamar University': 1469.7267782321642,\n",
       " 'Lehigh': 1577.5402804903997,\n",
       " 'Liberty': 1638.2801760815009,\n",
       " 'Maine': 1508.2892890324547,\n",
       " 'Marist': 1499.1283209249179,\n",
       " 'McNeese': 1666.394154474875,\n",
       " 'Mercer': 1582.6334399827565,\n",
       " 'Mississippi Val.': 1120.7456318041661,\n",
       " 'Missouri St.': 1271.3286128919408,\n",
       " 'Monmouth': 1487.7738203071199,\n",
       " 'Montana': 1655.4004491540488,\n",
       " 'Montana St.': 1505.645480695307,\n",
       " 'Morehead St.': 1368.4731555550688,\n",
       " 'Morgan St.': 1459.9290867456732,\n",
       " 'Murray St.': 1390.3932348952067,\n",
       " 'N.C. A&T': 1762.467074636234,\n",
       " 'N.C. Central': 1667.9180156901984,\n",
       " 'New Hampshire': 1729.1976840992556,\n",
       " 'Nicholls St.': 1380.5054180118505,\n",
       " 'Norfolk St.': 1335.5960932238554,\n",
       " 'North Dakota': 1556.9208223178582,\n",
       " 'North Dakota St.': 1971.8391491523405,\n",
       " 'Northern Ariz.': 1573.0770667355118,\n",
       " 'Northern Colo.': 1395.6889645207484,\n",
       " 'Northwestern St.': 1352.9472171222219,\n",
       " 'Penn': 1505.6293240739337,\n",
       " 'Portland St.': 1458.2785759203844,\n",
       " 'Prairie View': 1681.8456898733066,\n",
       " 'Presbyterian': 1340.6955021094373,\n",
       " 'Princeton': 1721.5801144483294,\n",
       " 'Rhode Island': 1183.0922877079715,\n",
       " 'Richmond': 1699.0196821240979,\n",
       " 'Robert Morris': 1230.1658296357386,\n",
       " 'SFA': 1456.2393028740357,\n",
       " 'Sacramento St.': 1359.795392818661,\n",
       " 'Sacred Heart': 1665.0990727291128,\n",
       " 'Saint Francis (PA)': 1501.6955857198404,\n",
       " 'Sam Houston St.': 1891.9377626394703,\n",
       " 'Samford': 1584.7959189742542,\n",
       " 'San Diego': 1753.599557264653,\n",
       " 'Savannah St.': 1303.8456160769413,\n",
       " 'South Carolina St.': 1691.8626286570347,\n",
       " 'South Dakota': 1341.9550154484314,\n",
       " 'South Dakota St.': 1671.4037879298478,\n",
       " 'Southeast Mo. St.': 1406.9514788477322,\n",
       " 'Southeastern La.': 1691.0945261408065,\n",
       " 'Southern Ill.': 1483.4171192520344,\n",
       " 'Southern U.': 1712.3737337009629,\n",
       " 'Southern Utah': 1563.0889305746578,\n",
       " 'Stetson': 1282.2444050780637,\n",
       " 'Stony Brook': 1488.8390029388254,\n",
       " 'Tennessee St.': 1573.1172839277206,\n",
       " 'Tennessee Tech': 1363.1006908548645,\n",
       " 'Texas Southern': 1354.2498919863374,\n",
       " 'The Citadel': 1641.5005983084552,\n",
       " 'Towson': 1506.4014848109241,\n",
       " 'UC Davis': 1331.6904265171165,\n",
       " 'UNI': 1647.3203704427046,\n",
       " 'UT Martin': 1617.9748829377463,\n",
       " 'VMI': 1286.0494729874811,\n",
       " 'Valparaiso': 1216.1522264565097,\n",
       " 'Villanova': 1737.8845096192995,\n",
       " 'Wagner': 1479.0013448191139,\n",
       " 'Weber St.': 1425.4716563663665,\n",
       " 'Western Caro.': 1439.4792433323755,\n",
       " 'Western Ill.': 1421.4380067456705,\n",
       " 'William & Mary': 1622.7275130195248,\n",
       " 'Wofford': 1617.0563487090626,\n",
       " 'Yale': 1461.7473543971141,\n",
       " 'Youngstown St.': 1688.773931952247}"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elo_ratings_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# See it in sorted form\n",
    "import operator\n",
    "sorted_elo_rankings = sorted(elo_ratings_dict.items(), key=operator.itemgetter(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Mississippi Val.', 1120.7456318041661),\n",
       " ('Austin Peay', 1123.4516182364441),\n",
       " ('Delaware St.', 1161.103845779578),\n",
       " ('Ark.-Pine Bluff', 1161.740418109933),\n",
       " ('Davidson', 1161.991736348733),\n",
       " ('Rhode Island', 1183.0922877079715),\n",
       " ('Valparaiso', 1216.1522264565097),\n",
       " ('Elon', 1224.3533603503838),\n",
       " ('Lafayette', 1225.7862597985782),\n",
       " ('Robert Morris', 1230.1658296357386),\n",
       " ('Central Conn. St.', 1248.925705135111),\n",
       " ('Columbia', 1248.9326673570238),\n",
       " ('Houston Baptist', 1254.9947172161642),\n",
       " ('Cornell', 1255.826315531858),\n",
       " ('Missouri St.', 1271.3286128919408),\n",
       " ('Stetson', 1282.2444050780637),\n",
       " ('VMI', 1286.0494729874811),\n",
       " ('Savannah St.', 1303.8456160769413),\n",
       " ('Georgetown', 1306.0999539659297),\n",
       " ('ETSU', 1307.7035714020321),\n",
       " ('Incarnate Word', 1315.2278894323636),\n",
       " ('Idaho St.', 1326.9412271058495),\n",
       " ('UC Davis', 1331.6904265171165),\n",
       " ('Norfolk St.', 1335.5960932238554),\n",
       " ('Florida A&M', 1336.1859120785418),\n",
       " ('Presbyterian', 1340.6955021094373),\n",
       " ('South Dakota', 1341.9550154484314),\n",
       " ('Northwestern St.', 1352.9472171222219),\n",
       " ('Texas Southern', 1354.2498919863374),\n",
       " ('Sacramento St.', 1359.795392818661),\n",
       " ('Tennessee Tech', 1363.1006908548645),\n",
       " ('Morehead St.', 1368.4731555550688),\n",
       " ('Abilene Christian', 1371.974938356436),\n",
       " ('Howard', 1373.273541160323),\n",
       " ('Alabama A&M', 1374.3341829364481),\n",
       " ('Furman', 1374.5163149413702),\n",
       " ('Nicholls St.', 1380.5054180118505),\n",
       " ('Indiana St.', 1388.9763457261065),\n",
       " ('Murray St.', 1390.3932348952067),\n",
       " ('Northern Colo.', 1395.6889645207484),\n",
       " ('Jackson St.', 1399.5377687451864),\n",
       " ('Gardner-Webb', 1402.4316671493505),\n",
       " ('Southeast Mo. St.', 1406.9514788477322),\n",
       " ('Holy Cross', 1409.332327661456),\n",
       " ('Butler', 1419.6600888772978),\n",
       " ('Western Ill.', 1421.4380067456705),\n",
       " ('Weber St.', 1425.4716563663665),\n",
       " ('Western Caro.', 1439.4792433323755),\n",
       " ('Hampton', 1442.7437297829019),\n",
       " ('Campbell', 1450.2633126904798),\n",
       " ('Albany (NY)', 1450.2693603080852),\n",
       " ('SFA', 1456.2393028740357),\n",
       " ('Portland St.', 1458.2785759203844),\n",
       " ('Morgan St.', 1459.9290867456732),\n",
       " ('Yale', 1461.7473543971141),\n",
       " ('Lamar University', 1469.7267782321642),\n",
       " ('Delaware', 1476.5952521239183),\n",
       " ('Wagner', 1479.0013448191139),\n",
       " ('Southern Ill.', 1483.4171192520344),\n",
       " ('Brown', 1483.962590862064),\n",
       " ('Monmouth', 1487.7738203071199),\n",
       " ('Stony Brook', 1488.8390029388254),\n",
       " ('Charlotte', 1498.2961741013578),\n",
       " ('Marist', 1499.1283209249179),\n",
       " ('Saint Francis (PA)', 1501.6955857198404),\n",
       " ('Penn', 1505.6293240739337),\n",
       " ('Montana St.', 1505.645480695307),\n",
       " ('Towson', 1506.4014848109241),\n",
       " ('Bryant', 1507.9389540387938),\n",
       " ('Maine', 1508.2892890324547),\n",
       " ('Kennesaw St.', 1512.3851352153467),\n",
       " ('Bucknell', 1512.8109647936383),\n",
       " ('Colgate', 1523.1475646331128),\n",
       " ('Alabama St.', 1531.3148770439902),\n",
       " ('Drake', 1535.9457766586243),\n",
       " ('North Dakota', 1556.9208223178582),\n",
       " ('Southern Utah', 1563.0889305746578),\n",
       " ('Cal Poly', 1566.1194861884806),\n",
       " ('Northern Ariz.', 1573.0770667355118),\n",
       " ('Tennessee St.', 1573.1172839277206),\n",
       " ('Eastern Ky.', 1574.0307901436413),\n",
       " ('Lehigh', 1577.5402804903997),\n",
       " ('Mercer', 1582.6334399827565),\n",
       " ('Samford', 1584.7959189742542),\n",
       " ('Duquesne', 1589.0757560955617),\n",
       " ('Eastern Ill.', 1592.6017420523813),\n",
       " ('Jacksonville', 1602.3130425778581),\n",
       " ('Wofford', 1617.0563487090626),\n",
       " ('UT Martin', 1617.9748829377463),\n",
       " ('William & Mary', 1622.7275130195248),\n",
       " ('Liberty', 1638.2801760815009),\n",
       " ('Dartmouth', 1638.3716743940108),\n",
       " ('The Citadel', 1641.5005983084552),\n",
       " ('UNI', 1647.3203704427046),\n",
       " ('Bethune-Cookman', 1648.4534815599309),\n",
       " ('Central Ark.', 1651.5359822068558),\n",
       " ('Montana', 1655.4004491540488),\n",
       " ('Illinois St.', 1659.68107625332),\n",
       " ('Charleston So.', 1663.2472596991638),\n",
       " ('Coastal Caro.', 1664.9051818247553),\n",
       " ('Sacred Heart', 1665.0990727291128),\n",
       " ('McNeese', 1666.394154474875),\n",
       " ('N.C. Central', 1667.9180156901984),\n",
       " ('South Dakota St.', 1671.4037879298478),\n",
       " ('Prairie View', 1681.8456898733066),\n",
       " ('Youngstown St.', 1688.773931952247),\n",
       " ('Southeastern La.', 1691.0945261408065),\n",
       " ('South Carolina St.', 1691.8626286570347),\n",
       " ('Richmond', 1699.0196821240979),\n",
       " ('Alcorn', 1701.8276801582988),\n",
       " ('Southern U.', 1712.3737337009629),\n",
       " ('Princeton', 1721.5801144483294),\n",
       " ('New Hampshire', 1729.1976840992556),\n",
       " ('Villanova', 1737.8845096192995),\n",
       " ('Grambling', 1740.4148814920263),\n",
       " ('San Diego', 1753.599557264653),\n",
       " ('N.C. A&T', 1762.467074636234),\n",
       " ('Eastern Wash.', 1762.8820015346482),\n",
       " ('Dayton', 1764.5603427276037),\n",
       " ('Fordham', 1771.9473721716381),\n",
       " ('Harvard', 1781.550447813401),\n",
       " ('Chattanooga', 1789.5125575680909),\n",
       " ('Jacksonville St.', 1830.8210672861949),\n",
       " ('James Madison', 1877.6496120704533),\n",
       " ('Sam Houston St.', 1891.9377626394703),\n",
       " ('North Dakota St.', 1971.8391491523405)]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_elo_rankings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ivy_team_names = ['Yale','Harvard','Princeton','Cornell','Brown','Columbia','Dartmouth','Penn']\n",
    "ivy_elo_ratings_dict = {}\n",
    "for tpl in sorted_elo_rankings[::-1]:\n",
    "    if tpl[0] in ivy_team_names:\n",
    "        ivy_elo_ratings_dict[tpl[0]] = tpl[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Brown': 1483.962590862064,\n",
       " 'Columbia': 1248.9326673570238,\n",
       " 'Cornell': 1255.826315531858,\n",
       " 'Dartmouth': 1638.3716743940108,\n",
       " 'Harvard': 1781.550447813401,\n",
       " 'Penn': 1505.6293240739337,\n",
       " 'Princeton': 1721.5801144483294,\n",
       " 'Yale': 1461.7473543971141}"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ivy_elo_ratings_dict"
   ]
  }
 ],
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