Scripts/westbrook_2016_17/visualization_Westbrook_triple_double_chase.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "westbrook_stats = pd.read_csv('../../Data/westbrook_2016_17/westbrook_2016_17.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rk</th>\n",
       "      <th>G</th>\n",
       "      <th>Date</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Unnamed: 5</th>\n",
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       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "      <th>GmSc</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-10-26</td>\n",
       "      <td>27-349</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
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       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>32</td>\n",
       "      <td>28.4</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-10-28</td>\n",
       "      <td>27-351</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>45:19</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>51</td>\n",
       "      <td>32.9</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>27-353</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:39</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>32.3</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-02</td>\n",
       "      <td>27-356</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAC</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>32:39</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "      <td>15.9</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2016-11-03</td>\n",
       "      <td>27-357</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-26)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:52</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>13.9</td>\n",
       "      <td>-9</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-05</td>\n",
       "      <td>27-359</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIN</td>\n",
       "      <td>W (+20)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:22</td>\n",
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       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>26.2</td>\n",
       "      <td>22</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>27-361</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "      <td>W (+12)</td>\n",
       "      <td>1</td>\n",
       "      <td>26:39</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>2016-11-09</td>\n",
       "      <td>27-363</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TOR</td>\n",
       "      <td>L (-10)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:46</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>36</td>\n",
       "      <td>21.6</td>\n",
       "      <td>-4</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>2016-11-11</td>\n",
       "      <td>27-365</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAC</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
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       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>20.6</td>\n",
       "      <td>-5</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>28-001</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:38</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>42.7</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>2016-11-14</td>\n",
       "      <td>28-002</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DET</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:34</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "      <td>24.6</td>\n",
       "      <td>-6</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2016-11-16</td>\n",
       "      <td>28-004</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:06</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>2016-11-18</td>\n",
       "      <td>28-006</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+19)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:51</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>31.4</td>\n",
       "      <td>21</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>2016-11-20</td>\n",
       "      <td>28-008</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-4)</td>\n",
       "      <td>1</td>\n",
       "      <td>40:20</td>\n",
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       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>15</td>\n",
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       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>20.2</td>\n",
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       "      <th>14</th>\n",
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       "      <td>15</td>\n",
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       "      <td>28-010</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:31</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>23.3</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>2016-11-23</td>\n",
       "      <td>28-011</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>SAC</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:04</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-7</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>2016-11-25</td>\n",
       "      <td>28-013</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:14</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>36</td>\n",
       "      <td>30.4</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>2016-11-26</td>\n",
       "      <td>28-014</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DET</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:19</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>15.9</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>2016-11-28</td>\n",
       "      <td>28-016</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:22</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>25.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>28-018</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WAS</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:07</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>35</td>\n",
       "      <td>24.6</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>28-022</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:31</td>\n",
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       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>19.2</td>\n",
       "      <td>13</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>2016-12-05</td>\n",
       "      <td>28-023</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ATL</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:52</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>2016-12-09</td>\n",
       "      <td>28-027</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:36</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>16.5</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>2016-12-11</td>\n",
       "      <td>28-029</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>37</td>\n",
       "      <td>25.2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>2016-12-13</td>\n",
       "      <td>28-031</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-19)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:21</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>11.9</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>2016-12-14</td>\n",
       "      <td>28-032</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>UTA</td>\n",
       "      <td>L (-20)</td>\n",
       "      <td>1</td>\n",
       "      <td>30:38</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>11.6</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>2016-12-17</td>\n",
       "      <td>28-035</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+13)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>32.9</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>2016-12-19</td>\n",
       "      <td>28-037</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ATL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:25</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>46</td>\n",
       "      <td>33.7</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>28-039</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:35</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>42</td>\n",
       "      <td>32.3</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-12-23</td>\n",
       "      <td>28-041</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+5)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:50</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>39.9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>2017-02-06</td>\n",
       "      <td>28-086</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:07</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>18</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>21.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>28-089</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLE</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:23</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>21.6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>2017-02-11</td>\n",
       "      <td>28-091</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:09</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>47</td>\n",
       "      <td>30.9</td>\n",
       "      <td>-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>2017-02-13</td>\n",
       "      <td>28-093</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>WAS</td>\n",
       "      <td>L (-22)</td>\n",
       "      <td>1</td>\n",
       "      <td>24:12</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>10.5</td>\n",
       "      <td>-36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>28-095</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:44</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>37.7</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>58</td>\n",
       "      <td>2017-02-24</td>\n",
       "      <td>28-104</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>20.3</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>59</td>\n",
       "      <td>2017-02-26</td>\n",
       "      <td>28-106</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:53</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>28.9</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>2017-02-28</td>\n",
       "      <td>28-108</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:47</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>30.1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>61</td>\n",
       "      <td>61</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>28-110</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:52</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>2017-03-03</td>\n",
       "      <td>28-111</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-7)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:05</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>48</td>\n",
       "      <td>41.4</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>2017-03-05</td>\n",
       "      <td>28-113</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>28-115</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:56</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>58</td>\n",
       "      <td>43.6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>28-117</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>W (+10)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:08</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>23.1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>2017-03-11</td>\n",
       "      <td>28-119</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:18</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>29.5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>2017-03-14</td>\n",
       "      <td>28-122</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:42</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>27.8</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>2017-03-16</td>\n",
       "      <td>28-124</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>TOR</td>\n",
       "      <td>W (+21)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:50</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>27.7</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>69</td>\n",
       "      <td>69</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>28-126</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAC</td>\n",
       "      <td>W (+16)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:59</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>24.4</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>2017-03-20</td>\n",
       "      <td>28-128</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:13</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>7.7</td>\n",
       "      <td>-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>71</td>\n",
       "      <td>71</td>\n",
       "      <td>2017-03-22</td>\n",
       "      <td>28-130</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHI</td>\n",
       "      <td>W (+25)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:51</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>25.3</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>28-134</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:58</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>39</td>\n",
       "      <td>30.8</td>\n",
       "      <td>-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>28-135</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:21</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>28.9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>2017-03-29</td>\n",
       "      <td>28-137</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ORL</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:49</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>57</td>\n",
       "      <td>44.2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>2017-03-31</td>\n",
       "      <td>28-139</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:59</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>24.7</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>28-141</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CHO</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>28.8</td>\n",
       "      <td>-6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>77</td>\n",
       "      <td>77</td>\n",
       "      <td>2017-04-04</td>\n",
       "      <td>28-143</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIL</td>\n",
       "      <td>W (+31)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:05</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>28-144</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>MEM</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:32</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>28-146</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-21)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:24</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>10.2</td>\n",
       "      <td>-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2017-04-09</td>\n",
       "      <td>28-148</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:57</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>16</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>45.6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>81</td>\n",
       "      <td>80</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>28-151</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEN</td>\n",
       "      <td>L (-6)</td>\n",
       "      <td>1</td>\n",
       "      <td>18:19</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>82</td>\n",
       "      <td>81</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>28-151</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEN</td>\n",
       "      <td>L (-6)</td>\n",
       "      <td>1</td>\n",
       "      <td>18:19</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rk   G        Date     Age   Tm Unnamed: 5  Opp Unnamed: 7  GS     MP  \\\n",
       "0    1   1  2016-10-26  27-349  OKC          @  PHI     W (+6)   1  36:23   \n",
       "1    2   2  2016-10-28  27-351  OKC        NaN  PHO     W (+3)   1  45:19   \n",
       "2    3   3  2016-10-30  27-353  OKC        NaN  LAL    W (+17)   1  33:39   \n",
       "3    4   4  2016-11-02  27-356  OKC          @  LAC     W (+2)   1  32:39   \n",
       "4    5   5  2016-11-03  27-357  OKC          @  GSW    L (-26)   1  28:52   \n",
       "5    6   6  2016-11-05  27-359  OKC        NaN  MIN    W (+20)   1  28:22   \n",
       "6    7   7  2016-11-07  27-361  OKC        NaN  MIA    W (+12)   1  26:39   \n",
       "7    8   8  2016-11-09  27-363  OKC        NaN  TOR    L (-10)   1  38:46   \n",
       "8    9   9  2016-11-11  27-365  OKC        NaN  LAC     L (-2)   1  35:16   \n",
       "9   10  10  2016-11-13  28-001  OKC        NaN  ORL     L (-2)   1  37:38   \n",
       "10  11  11  2016-11-14  28-002  OKC          @  DET    L (-16)   1  33:34   \n",
       "11  12  12  2016-11-16  28-004  OKC        NaN  HOU     W (+2)   1  36:06   \n",
       "12  13  13  2016-11-18  28-006  OKC        NaN  BRK    W (+19)   1  33:51   \n",
       "13  14  14  2016-11-20  28-008  OKC        NaN  IND     L (-4)   1  40:20   \n",
       "14  15  15  2016-11-22  28-010  OKC          @  LAL     L (-2)   1  35:31   \n",
       "15  16  16  2016-11-23  28-011  OKC          @  SAC    L (-15)   1  35:04   \n",
       "16  17  17  2016-11-25  28-013  OKC          @  DEN     W (+3)   1  41:14   \n",
       "17  18  18  2016-11-26  28-014  OKC        NaN  DET    W (+18)   1  37:19   \n",
       "18  19  19  2016-11-28  28-016  OKC          @  NYK     W (+9)   1  36:22   \n",
       "19  20  20  2016-11-30  28-018  OKC        NaN  WAS    W (+11)   1  41:07   \n",
       "20  21  21  2016-12-04  28-022  OKC        NaN  NOP     W (+9)   1  37:31   \n",
       "21  22  22  2016-12-05  28-023  OKC          @  ATL     W (+3)   1  33:52   \n",
       "22  23  23  2016-12-09  28-027  OKC        NaN  HOU     L (-3)   1  35:36   \n",
       "23  24  24  2016-12-11  28-029  OKC        NaN  BOS     W (+3)   1  36:12   \n",
       "24  25  25  2016-12-13  28-031  OKC          @  POR    L (-19)   1  27:21   \n",
       "25  26  26  2016-12-14  28-032  OKC          @  UTA    L (-20)   1  30:38   \n",
       "26  27  27  2016-12-17  28-035  OKC        NaN  PHO    W (+13)   1  34:01   \n",
       "27  28  28  2016-12-19  28-037  OKC        NaN  ATL     L (-2)   1  35:25   \n",
       "28  29  29  2016-12-21  28-039  OKC          @  NOP    W (+11)   1  33:35   \n",
       "29  30  30  2016-12-23  28-041  OKC          @  BOS     W (+5)   1  34:50   \n",
       "..  ..  ..         ...     ...  ...        ...  ...        ...  ..    ...   \n",
       "52  53  53  2017-02-06  28-086  OKC          @  IND     L (-3)   1  37:07   \n",
       "53  54  54  2017-02-09  28-089  OKC        NaN  CLE     W (+9)   1  35:23   \n",
       "54  55  55  2017-02-11  28-091  OKC        NaN  GSW    L (-16)   1  37:09   \n",
       "55  56  56  2017-02-13  28-093  OKC          @  WAS    L (-22)   1  24:12   \n",
       "56  57  57  2017-02-15  28-095  OKC        NaN  NYK    W (+11)   1  37:44   \n",
       "57  58  58  2017-02-24  28-104  OKC        NaN  LAL    W (+17)   1  35:16   \n",
       "58  59  59  2017-02-26  28-106  OKC        NaN  NOP     W (+8)   1  36:53   \n",
       "59  60  60  2017-02-28  28-108  OKC        NaN  UTA     W (+3)   1  38:47   \n",
       "60  61  61  2017-03-02  28-110  OKC          @  POR     L (-5)   1  36:52   \n",
       "61  62  62  2017-03-03  28-111  OKC          @  PHO     L (-7)   1  38:05   \n",
       "62  63  63  2017-03-05  28-113  OKC          @  DAL    L (-15)   1  34:01   \n",
       "63  64  64  2017-03-07  28-115  OKC        NaN  POR     L (-5)   1  35:56   \n",
       "64  65  65  2017-03-09  28-117  OKC        NaN  SAS    W (+10)   1  35:08   \n",
       "65  66  66  2017-03-11  28-119  OKC        NaN  UTA     W (+8)   1  36:18   \n",
       "66  67  67  2017-03-14  28-122  OKC          @  BRK    W (+18)   1  34:42   \n",
       "67  68  68  2017-03-16  28-124  OKC          @  TOR    W (+21)   1  27:50   \n",
       "68  69  69  2017-03-18  28-126  OKC        NaN  SAC    W (+16)   1  35:59   \n",
       "69  70  70  2017-03-20  28-128  OKC        NaN  GSW    L (-16)   1  27:13   \n",
       "70  71  71  2017-03-22  28-130  OKC        NaN  PHI    W (+25)   1  27:51   \n",
       "71  72  72  2017-03-26  28-134  OKC          @  HOU    L (-12)   1  38:58   \n",
       "72  73  73  2017-03-27  28-135  OKC          @  DAL     W (+1)   1  36:21   \n",
       "73  74  74  2017-03-29  28-137  OKC          @  ORL     W (+8)   1  41:49   \n",
       "74  75  75  2017-03-31  28-139  OKC        NaN  SAS     L (-5)   1  36:59   \n",
       "75  76  76  2017-04-02  28-141  OKC        NaN  CHO    L (-12)   1  36:12   \n",
       "76  77  77  2017-04-04  28-143  OKC        NaN  MIL    W (+31)   1  27:05   \n",
       "77  78  78  2017-04-05  28-144  OKC          @  MEM     W (+3)   1  37:32   \n",
       "78  79  79  2017-04-07  28-146  OKC          @  PHO    L (-21)   1  36:24   \n",
       "79  80  80  2017-04-09  28-148  OKC          @  DEN     W (+1)   1  36:57   \n",
       "80  81  80  2017-04-12  28-151  OKC        NaN  DEN     L (-6)   1  18:19   \n",
       "81  82  81  2017-04-12  28-151  OKC        NaN  DEN     L (-6)   1  18:19   \n",
       "\n",
       "   ...   DRB  TRB  AST  STL  BLK  TOV  PF  PTS  GmSc  +/-  \n",
       "0  ...    11   12    9    0    0    2   2   32  28.4   10  \n",
       "1  ...    10   13   10    2    0    5   3   51  32.9    7  \n",
       "2  ...     7   11   16    1    1    7   3   33  32.3    9  \n",
       "3  ...     5    6    5    3    0   10   4   35  15.9   12  \n",
       "4  ...     5    6   10    1    2    6   3   20  13.9   -9  \n",
       "5  ...     4    6    8    3    0    2   3   28  26.2   22  \n",
       "6  ...     3    5   11    0    0    5   2   14   9.0   24  \n",
       "7  ...     5    7    7    1    2    8   2   36  21.6   -4  \n",
       "8  ...    13   14    9    1    0    4   5   29  20.6   -5  \n",
       "9  ...    10   12   16    0    0    2   2   41  42.7    9  \n",
       "10 ...    13   15    8    0    0    7   4   33  24.6   -6  \n",
       "11 ...     6    7    9    2    0    6   0   30  24.0   12  \n",
       "12 ...     7   10   13    1    0    3   0   30  31.4   21  \n",
       "13 ...     6   11   15    1    0    7   3   31  20.2  -16  \n",
       "14 ...     5    8   13    2    0    8   3   34  23.3    9  \n",
       "15 ...    10   11    9    2    0    3   1   31  28.6   -7  \n",
       "16 ...    10   11   17    1    1    7   3   36  30.4   10  \n",
       "17 ...    10   13   15    1    1    5   2   17  15.9   14  \n",
       "18 ...    12   17   14    2    0    7   3   27  25.2    5  \n",
       "19 ...    10   14   11    2    0    5   3   35  24.6    4  \n",
       "20 ...    16   17   12    1    0   10   1   28  19.2   13  \n",
       "21 ...    12   13   12    1    1    4   1   32  28.6   -4  \n",
       "22 ...     9   10   10    3    0    8   3   27  16.5   -1  \n",
       "23 ...     9   12    6    2    0    7   3   37  25.2    9  \n",
       "24 ...     4    6    6    0    0    4   1   20  11.9  -10  \n",
       "25 ...     5    6    5    1    0    5   4   27  11.6   -6  \n",
       "26 ...    11   11   22    2    1    5   3   26  32.9   16  \n",
       "27 ...     9   11    7    1    0    4   2   46  33.7   -2  \n",
       "28 ...     9   10    7    1    0    4   2   42  32.3   -4  \n",
       "29 ...    10   11   11    1    0    4   1   45  39.9    9  \n",
       ".. ...   ...  ...  ...  ...  ...  ...  ..  ...   ...  ...  \n",
       "52 ...    16   18    9    1    2    4   3   27  21.4    1  \n",
       "53 ...    11   12   11    4    0    7   4   29  21.6    3  \n",
       "54 ...    10   11    8    1    0   11   5   47  30.9  -13  \n",
       "55 ...     2    4    4    2    0    2   0   17  10.5  -36  \n",
       "56 ...    11   14   12    3    1    6   0   38  37.7   13  \n",
       "57 ...    16   18   17    3    0    6   1   17  20.3   19  \n",
       "58 ...     9   11   11    1    0    9   2   41  28.9    4  \n",
       "59 ...    11   11   10    0    0    8   1   43  30.1   10  \n",
       "60 ...     5    7    4    1    1    4   0   45  28.0   -7  \n",
       "61 ...    16   17    9    3    0    4   4   48  41.4   10  \n",
       "62 ...     6    6    5    2    1    1   4   29  20.0  -14  \n",
       "63 ...     2    3    9    3    1    4   4   58  43.6    7  \n",
       "64 ...    10   13   13    2    0    3   2   23  23.1   12  \n",
       "65 ...    10   11   14    2    2    5   1   33  29.5   12  \n",
       "66 ...    11   12   19    2    1    5   3   25  27.8    7  \n",
       "67 ...    10   10   16    1    0    2   2   24  27.7   26  \n",
       "68 ...     5    8   10    4    0    7   1   28  24.4   13  \n",
       "69 ...     8    8    7    2    0    5   4   15   7.7  -25  \n",
       "70 ...    11   11   14    0    2    5   1   18  25.3   21  \n",
       "71 ...    11   11   13    0    0    5   4   39  30.8  -14  \n",
       "72 ...    13   13   10    2    0    6   0   37  28.9   12  \n",
       "73 ...    10   13   11    3    0    7   3   57  44.2    8  \n",
       "74 ...    13   15   12    0    0    8   1   32  24.7  -10  \n",
       "75 ...    12   13   10    2    0    8   1   40  28.8   -6  \n",
       "76 ...    10   13   13    2    0    3   2   12  17.6   19  \n",
       "77 ...     9    9   10    4    0    7   4   45  37.0    2  \n",
       "78 ...     6   12    8    0    1    8   5   23  10.2  -15  \n",
       "79 ...    14   16   10    1    0    2   1   50  45.6   10  \n",
       "80 ...     5    5    8    0    1    3   2    5   2.8   -5  \n",
       "81 ...     5    5    8    0    1    3   2    5   2.8   -5  \n",
       "\n",
       "[82 rows x 30 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "westbrook_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def truncate_float(number):\n",
    "    return \"%.2f\" % number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pts, rbs, ast = westbrook_stats.PTS, westbrook_stats.TRB, westbrook_stats.AST\n",
    "pts_average, rbs_average, ast_average = [], [], []\n",
    "for i in range(len(pts)):\n",
    "    if i == 0:\n",
    "        pts_average.append(truncate_float(pts[i]))\n",
    "        rbs_average.append(truncate_float(rbs[i]))\n",
    "        ast_average.append(truncate_float(ast[i]))\n",
    "    elif i == 80:\n",
    "        pts_average.append(truncate_float(pts[:(i-1)].mean()))\n",
    "        rbs_average.append(truncate_float(rbs[:(i-1)].mean()))\n",
    "        ast_average.append(truncate_float(ast[:(i-1)].mean()))\n",
    "    else:\n",
    "        pts_average.append(truncate_float(pts[:i].mean()))\n",
    "        rbs_average.append(truncate_float(rbs[:i].mean()))\n",
    "        ast_average.append(truncate_float(ast[:i].mean()))\n",
    "\n",
    "westbrook_stats.loc[:, \"AvgPTS\"] = pts_average\n",
    "westbrook_stats.loc[:, \"AvgTRB\"] = rbs_average\n",
    "westbrook_stats.loc[:, \"AvgAST\"] = ast_average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rk</th>\n",
       "      <th>G</th>\n",
       "      <th>Date</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Opp</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>GS</th>\n",
       "      <th>MP</th>\n",
       "      <th>...</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "      <th>GmSc</th>\n",
       "      <th>+/-</th>\n",
       "      <th>AvgPTS</th>\n",
       "      <th>AvgTRB</th>\n",
       "      <th>AvgAST</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-10-26</td>\n",
       "      <td>27-349</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHI</td>\n",
       "      <td>W (+6)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:23</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>32</td>\n",
       "      <td>28.4</td>\n",
       "      <td>10</td>\n",
       "      <td>32.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>9.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-10-28</td>\n",
       "      <td>27-351</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>45:19</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>51</td>\n",
       "      <td>32.9</td>\n",
       "      <td>7</td>\n",
       "      <td>32.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>9.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>27-353</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:39</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>32.3</td>\n",
       "      <td>9</td>\n",
       "      <td>41.50</td>\n",
       "      <td>12.50</td>\n",
       "      <td>9.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-02</td>\n",
       "      <td>27-356</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAC</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>32:39</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "      <td>15.9</td>\n",
       "      <td>12</td>\n",
       "      <td>38.67</td>\n",
       "      <td>12.00</td>\n",
       "      <td>11.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2016-11-03</td>\n",
       "      <td>27-357</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-26)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:52</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>13.9</td>\n",
       "      <td>-9</td>\n",
       "      <td>37.75</td>\n",
       "      <td>10.50</td>\n",
       "      <td>10.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-05</td>\n",
       "      <td>27-359</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIN</td>\n",
       "      <td>W (+20)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:22</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>26.2</td>\n",
       "      <td>22</td>\n",
       "      <td>34.20</td>\n",
       "      <td>9.60</td>\n",
       "      <td>10.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>27-361</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "      <td>W (+12)</td>\n",
       "      <td>1</td>\n",
       "      <td>26:39</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>9.0</td>\n",
       "      <td>24</td>\n",
       "      <td>33.17</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>2016-11-09</td>\n",
       "      <td>27-363</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TOR</td>\n",
       "      <td>L (-10)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:46</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>36</td>\n",
       "      <td>21.6</td>\n",
       "      <td>-4</td>\n",
       "      <td>30.43</td>\n",
       "      <td>8.43</td>\n",
       "      <td>9.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>2016-11-11</td>\n",
       "      <td>27-365</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAC</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>20.6</td>\n",
       "      <td>-5</td>\n",
       "      <td>31.12</td>\n",
       "      <td>8.25</td>\n",
       "      <td>9.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>28-001</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:38</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>42.7</td>\n",
       "      <td>9</td>\n",
       "      <td>30.89</td>\n",
       "      <td>8.89</td>\n",
       "      <td>9.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>2016-11-14</td>\n",
       "      <td>28-002</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DET</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:34</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "      <td>24.6</td>\n",
       "      <td>-6</td>\n",
       "      <td>31.90</td>\n",
       "      <td>9.20</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2016-11-16</td>\n",
       "      <td>28-004</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:06</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12</td>\n",
       "      <td>32.00</td>\n",
       "      <td>9.73</td>\n",
       "      <td>9.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>2016-11-18</td>\n",
       "      <td>28-006</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+19)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:51</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>31.4</td>\n",
       "      <td>21</td>\n",
       "      <td>31.83</td>\n",
       "      <td>9.50</td>\n",
       "      <td>9.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>2016-11-20</td>\n",
       "      <td>28-008</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-4)</td>\n",
       "      <td>1</td>\n",
       "      <td>40:20</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>20.2</td>\n",
       "      <td>-16</td>\n",
       "      <td>31.69</td>\n",
       "      <td>9.54</td>\n",
       "      <td>10.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>2016-11-22</td>\n",
       "      <td>28-010</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:31</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>23.3</td>\n",
       "      <td>9</td>\n",
       "      <td>31.64</td>\n",
       "      <td>9.64</td>\n",
       "      <td>10.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>2016-11-23</td>\n",
       "      <td>28-011</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>SAC</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:04</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-7</td>\n",
       "      <td>31.80</td>\n",
       "      <td>9.53</td>\n",
       "      <td>10.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>2016-11-25</td>\n",
       "      <td>28-013</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:14</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>36</td>\n",
       "      <td>30.4</td>\n",
       "      <td>10</td>\n",
       "      <td>31.75</td>\n",
       "      <td>9.62</td>\n",
       "      <td>10.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>2016-11-26</td>\n",
       "      <td>28-014</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DET</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:19</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>15.9</td>\n",
       "      <td>14</td>\n",
       "      <td>32.00</td>\n",
       "      <td>9.71</td>\n",
       "      <td>10.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>2016-11-28</td>\n",
       "      <td>28-016</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:22</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>25.2</td>\n",
       "      <td>5</td>\n",
       "      <td>31.17</td>\n",
       "      <td>9.89</td>\n",
       "      <td>11.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>28-018</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WAS</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:07</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>35</td>\n",
       "      <td>24.6</td>\n",
       "      <td>4</td>\n",
       "      <td>30.95</td>\n",
       "      <td>10.26</td>\n",
       "      <td>11.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>28-022</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:31</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>19.2</td>\n",
       "      <td>13</td>\n",
       "      <td>31.15</td>\n",
       "      <td>10.45</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>2016-12-05</td>\n",
       "      <td>28-023</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ATL</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:52</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-4</td>\n",
       "      <td>31.00</td>\n",
       "      <td>10.76</td>\n",
       "      <td>11.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>2016-12-09</td>\n",
       "      <td>28-027</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:36</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>16.5</td>\n",
       "      <td>-1</td>\n",
       "      <td>31.05</td>\n",
       "      <td>10.86</td>\n",
       "      <td>11.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>2016-12-11</td>\n",
       "      <td>28-029</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>37</td>\n",
       "      <td>25.2</td>\n",
       "      <td>9</td>\n",
       "      <td>30.87</td>\n",
       "      <td>10.83</td>\n",
       "      <td>11.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>2016-12-13</td>\n",
       "      <td>28-031</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-19)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:21</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>11.9</td>\n",
       "      <td>-10</td>\n",
       "      <td>31.12</td>\n",
       "      <td>10.88</td>\n",
       "      <td>11.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>2016-12-14</td>\n",
       "      <td>28-032</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>UTA</td>\n",
       "      <td>L (-20)</td>\n",
       "      <td>1</td>\n",
       "      <td>30:38</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>11.6</td>\n",
       "      <td>-6</td>\n",
       "      <td>30.68</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>2016-12-17</td>\n",
       "      <td>28-035</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+13)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>32.9</td>\n",
       "      <td>16</td>\n",
       "      <td>30.54</td>\n",
       "      <td>10.50</td>\n",
       "      <td>10.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>2016-12-19</td>\n",
       "      <td>28-037</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ATL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:25</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>46</td>\n",
       "      <td>33.7</td>\n",
       "      <td>-2</td>\n",
       "      <td>30.37</td>\n",
       "      <td>10.52</td>\n",
       "      <td>11.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>28-039</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:35</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>42</td>\n",
       "      <td>32.3</td>\n",
       "      <td>-4</td>\n",
       "      <td>30.93</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-12-23</td>\n",
       "      <td>28-041</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+5)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:50</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>39.9</td>\n",
       "      <td>9</td>\n",
       "      <td>31.31</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>2017-02-06</td>\n",
       "      <td>28-086</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:07</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>21.4</td>\n",
       "      <td>1</td>\n",
       "      <td>31.02</td>\n",
       "      <td>10.37</td>\n",
       "      <td>10.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>28-089</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLE</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:23</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>21.6</td>\n",
       "      <td>3</td>\n",
       "      <td>30.94</td>\n",
       "      <td>10.51</td>\n",
       "      <td>10.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>2017-02-11</td>\n",
       "      <td>28-091</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:09</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>47</td>\n",
       "      <td>30.9</td>\n",
       "      <td>-13</td>\n",
       "      <td>30.91</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>2017-02-13</td>\n",
       "      <td>28-093</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>WAS</td>\n",
       "      <td>L (-22)</td>\n",
       "      <td>1</td>\n",
       "      <td>24:12</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>10.5</td>\n",
       "      <td>-36</td>\n",
       "      <td>31.20</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>28-095</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:44</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>37.7</td>\n",
       "      <td>13</td>\n",
       "      <td>30.95</td>\n",
       "      <td>10.43</td>\n",
       "      <td>10.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>58</td>\n",
       "      <td>2017-02-24</td>\n",
       "      <td>28-104</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>20.3</td>\n",
       "      <td>19</td>\n",
       "      <td>31.07</td>\n",
       "      <td>10.49</td>\n",
       "      <td>10.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>59</td>\n",
       "      <td>2017-02-26</td>\n",
       "      <td>28-106</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:53</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>28.9</td>\n",
       "      <td>4</td>\n",
       "      <td>30.83</td>\n",
       "      <td>10.62</td>\n",
       "      <td>10.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>2017-02-28</td>\n",
       "      <td>28-108</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:47</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>30.1</td>\n",
       "      <td>10</td>\n",
       "      <td>31.00</td>\n",
       "      <td>10.63</td>\n",
       "      <td>10.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>61</td>\n",
       "      <td>61</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>28-110</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:52</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-7</td>\n",
       "      <td>31.20</td>\n",
       "      <td>10.63</td>\n",
       "      <td>10.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>2017-03-03</td>\n",
       "      <td>28-111</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-7)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:05</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>48</td>\n",
       "      <td>41.4</td>\n",
       "      <td>10</td>\n",
       "      <td>31.43</td>\n",
       "      <td>10.57</td>\n",
       "      <td>10.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>2017-03-05</td>\n",
       "      <td>28-113</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-14</td>\n",
       "      <td>31.69</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>28-115</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:56</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>58</td>\n",
       "      <td>43.6</td>\n",
       "      <td>7</td>\n",
       "      <td>31.65</td>\n",
       "      <td>10.60</td>\n",
       "      <td>10.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>28-117</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>W (+10)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:08</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>23.1</td>\n",
       "      <td>12</td>\n",
       "      <td>32.06</td>\n",
       "      <td>10.48</td>\n",
       "      <td>10.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>2017-03-11</td>\n",
       "      <td>28-119</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:18</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>29.5</td>\n",
       "      <td>12</td>\n",
       "      <td>31.92</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>2017-03-14</td>\n",
       "      <td>28-122</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:42</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>27.8</td>\n",
       "      <td>7</td>\n",
       "      <td>31.94</td>\n",
       "      <td>10.53</td>\n",
       "      <td>10.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>2017-03-16</td>\n",
       "      <td>28-124</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>TOR</td>\n",
       "      <td>W (+21)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:50</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>27.7</td>\n",
       "      <td>26</td>\n",
       "      <td>31.84</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>69</td>\n",
       "      <td>69</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>28-126</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAC</td>\n",
       "      <td>W (+16)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:59</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>24.4</td>\n",
       "      <td>13</td>\n",
       "      <td>31.72</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>2017-03-20</td>\n",
       "      <td>28-128</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:13</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>7.7</td>\n",
       "      <td>-25</td>\n",
       "      <td>31.67</td>\n",
       "      <td>10.51</td>\n",
       "      <td>10.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>71</td>\n",
       "      <td>71</td>\n",
       "      <td>2017-03-22</td>\n",
       "      <td>28-130</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHI</td>\n",
       "      <td>W (+25)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:51</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>25.3</td>\n",
       "      <td>21</td>\n",
       "      <td>31.43</td>\n",
       "      <td>10.47</td>\n",
       "      <td>10.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>28-134</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:58</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>39</td>\n",
       "      <td>30.8</td>\n",
       "      <td>-14</td>\n",
       "      <td>31.24</td>\n",
       "      <td>10.48</td>\n",
       "      <td>10.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>28-135</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:21</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>28.9</td>\n",
       "      <td>12</td>\n",
       "      <td>31.35</td>\n",
       "      <td>10.49</td>\n",
       "      <td>10.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>2017-03-29</td>\n",
       "      <td>28-137</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ORL</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:49</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>57</td>\n",
       "      <td>44.2</td>\n",
       "      <td>8</td>\n",
       "      <td>31.42</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>2017-03-31</td>\n",
       "      <td>28-139</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:59</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>24.7</td>\n",
       "      <td>-10</td>\n",
       "      <td>31.77</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>28-141</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CHO</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>28.8</td>\n",
       "      <td>-6</td>\n",
       "      <td>31.77</td>\n",
       "      <td>10.61</td>\n",
       "      <td>10.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>77</td>\n",
       "      <td>77</td>\n",
       "      <td>2017-04-04</td>\n",
       "      <td>28-143</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIL</td>\n",
       "      <td>W (+31)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:05</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19</td>\n",
       "      <td>31.88</td>\n",
       "      <td>10.64</td>\n",
       "      <td>10.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>28-144</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>MEM</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:32</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2</td>\n",
       "      <td>31.62</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>28-146</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-21)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:24</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>10.2</td>\n",
       "      <td>-15</td>\n",
       "      <td>31.79</td>\n",
       "      <td>10.65</td>\n",
       "      <td>10.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2017-04-09</td>\n",
       "      <td>28-148</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:57</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>45.6</td>\n",
       "      <td>10</td>\n",
       "      <td>31.68</td>\n",
       "      <td>10.67</td>\n",
       "      <td>10.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>81</td>\n",
       "      <td>80</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>28-151</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEN</td>\n",
       "      <td>L (-6)</td>\n",
       "      <td>1</td>\n",
       "      <td>18:19</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-5</td>\n",
       "      <td>31.68</td>\n",
       "      <td>10.67</td>\n",
       "      <td>10.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>82</td>\n",
       "      <td>81</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>28-151</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEN</td>\n",
       "      <td>L (-6)</td>\n",
       "      <td>1</td>\n",
       "      <td>18:19</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-5</td>\n",
       "      <td>31.58</td>\n",
       "      <td>10.67</td>\n",
       "      <td>10.37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rk   G        Date     Age   Tm Unnamed: 5  Opp Unnamed: 7  GS     MP  \\\n",
       "0    1   1  2016-10-26  27-349  OKC          @  PHI     W (+6)   1  36:23   \n",
       "1    2   2  2016-10-28  27-351  OKC        NaN  PHO     W (+3)   1  45:19   \n",
       "2    3   3  2016-10-30  27-353  OKC        NaN  LAL    W (+17)   1  33:39   \n",
       "3    4   4  2016-11-02  27-356  OKC          @  LAC     W (+2)   1  32:39   \n",
       "4    5   5  2016-11-03  27-357  OKC          @  GSW    L (-26)   1  28:52   \n",
       "5    6   6  2016-11-05  27-359  OKC        NaN  MIN    W (+20)   1  28:22   \n",
       "6    7   7  2016-11-07  27-361  OKC        NaN  MIA    W (+12)   1  26:39   \n",
       "7    8   8  2016-11-09  27-363  OKC        NaN  TOR    L (-10)   1  38:46   \n",
       "8    9   9  2016-11-11  27-365  OKC        NaN  LAC     L (-2)   1  35:16   \n",
       "9   10  10  2016-11-13  28-001  OKC        NaN  ORL     L (-2)   1  37:38   \n",
       "10  11  11  2016-11-14  28-002  OKC          @  DET    L (-16)   1  33:34   \n",
       "11  12  12  2016-11-16  28-004  OKC        NaN  HOU     W (+2)   1  36:06   \n",
       "12  13  13  2016-11-18  28-006  OKC        NaN  BRK    W (+19)   1  33:51   \n",
       "13  14  14  2016-11-20  28-008  OKC        NaN  IND     L (-4)   1  40:20   \n",
       "14  15  15  2016-11-22  28-010  OKC          @  LAL     L (-2)   1  35:31   \n",
       "15  16  16  2016-11-23  28-011  OKC          @  SAC    L (-15)   1  35:04   \n",
       "16  17  17  2016-11-25  28-013  OKC          @  DEN     W (+3)   1  41:14   \n",
       "17  18  18  2016-11-26  28-014  OKC        NaN  DET    W (+18)   1  37:19   \n",
       "18  19  19  2016-11-28  28-016  OKC          @  NYK     W (+9)   1  36:22   \n",
       "19  20  20  2016-11-30  28-018  OKC        NaN  WAS    W (+11)   1  41:07   \n",
       "20  21  21  2016-12-04  28-022  OKC        NaN  NOP     W (+9)   1  37:31   \n",
       "21  22  22  2016-12-05  28-023  OKC          @  ATL     W (+3)   1  33:52   \n",
       "22  23  23  2016-12-09  28-027  OKC        NaN  HOU     L (-3)   1  35:36   \n",
       "23  24  24  2016-12-11  28-029  OKC        NaN  BOS     W (+3)   1  36:12   \n",
       "24  25  25  2016-12-13  28-031  OKC          @  POR    L (-19)   1  27:21   \n",
       "25  26  26  2016-12-14  28-032  OKC          @  UTA    L (-20)   1  30:38   \n",
       "26  27  27  2016-12-17  28-035  OKC        NaN  PHO    W (+13)   1  34:01   \n",
       "27  28  28  2016-12-19  28-037  OKC        NaN  ATL     L (-2)   1  35:25   \n",
       "28  29  29  2016-12-21  28-039  OKC          @  NOP    W (+11)   1  33:35   \n",
       "29  30  30  2016-12-23  28-041  OKC          @  BOS     W (+5)   1  34:50   \n",
       "..  ..  ..         ...     ...  ...        ...  ...        ...  ..    ...   \n",
       "52  53  53  2017-02-06  28-086  OKC          @  IND     L (-3)   1  37:07   \n",
       "53  54  54  2017-02-09  28-089  OKC        NaN  CLE     W (+9)   1  35:23   \n",
       "54  55  55  2017-02-11  28-091  OKC        NaN  GSW    L (-16)   1  37:09   \n",
       "55  56  56  2017-02-13  28-093  OKC          @  WAS    L (-22)   1  24:12   \n",
       "56  57  57  2017-02-15  28-095  OKC        NaN  NYK    W (+11)   1  37:44   \n",
       "57  58  58  2017-02-24  28-104  OKC        NaN  LAL    W (+17)   1  35:16   \n",
       "58  59  59  2017-02-26  28-106  OKC        NaN  NOP     W (+8)   1  36:53   \n",
       "59  60  60  2017-02-28  28-108  OKC        NaN  UTA     W (+3)   1  38:47   \n",
       "60  61  61  2017-03-02  28-110  OKC          @  POR     L (-5)   1  36:52   \n",
       "61  62  62  2017-03-03  28-111  OKC          @  PHO     L (-7)   1  38:05   \n",
       "62  63  63  2017-03-05  28-113  OKC          @  DAL    L (-15)   1  34:01   \n",
       "63  64  64  2017-03-07  28-115  OKC        NaN  POR     L (-5)   1  35:56   \n",
       "64  65  65  2017-03-09  28-117  OKC        NaN  SAS    W (+10)   1  35:08   \n",
       "65  66  66  2017-03-11  28-119  OKC        NaN  UTA     W (+8)   1  36:18   \n",
       "66  67  67  2017-03-14  28-122  OKC          @  BRK    W (+18)   1  34:42   \n",
       "67  68  68  2017-03-16  28-124  OKC          @  TOR    W (+21)   1  27:50   \n",
       "68  69  69  2017-03-18  28-126  OKC        NaN  SAC    W (+16)   1  35:59   \n",
       "69  70  70  2017-03-20  28-128  OKC        NaN  GSW    L (-16)   1  27:13   \n",
       "70  71  71  2017-03-22  28-130  OKC        NaN  PHI    W (+25)   1  27:51   \n",
       "71  72  72  2017-03-26  28-134  OKC          @  HOU    L (-12)   1  38:58   \n",
       "72  73  73  2017-03-27  28-135  OKC          @  DAL     W (+1)   1  36:21   \n",
       "73  74  74  2017-03-29  28-137  OKC          @  ORL     W (+8)   1  41:49   \n",
       "74  75  75  2017-03-31  28-139  OKC        NaN  SAS     L (-5)   1  36:59   \n",
       "75  76  76  2017-04-02  28-141  OKC        NaN  CHO    L (-12)   1  36:12   \n",
       "76  77  77  2017-04-04  28-143  OKC        NaN  MIL    W (+31)   1  27:05   \n",
       "77  78  78  2017-04-05  28-144  OKC          @  MEM     W (+3)   1  37:32   \n",
       "78  79  79  2017-04-07  28-146  OKC          @  PHO    L (-21)   1  36:24   \n",
       "79  80  80  2017-04-09  28-148  OKC          @  DEN     W (+1)   1  36:57   \n",
       "80  81  80  2017-04-12  28-151  OKC        NaN  DEN     L (-6)   1  18:19   \n",
       "81  82  81  2017-04-12  28-151  OKC        NaN  DEN     L (-6)   1  18:19   \n",
       "\n",
       "     ...    STL  BLK  TOV  PF  PTS  GmSc  +/-  AvgPTS  AvgTRB  AvgAST  \n",
       "0    ...      0    0    2   2   32  28.4   10   32.00   12.00    9.00  \n",
       "1    ...      2    0    5   3   51  32.9    7   32.00   12.00    9.00  \n",
       "2    ...      1    1    7   3   33  32.3    9   41.50   12.50    9.50  \n",
       "3    ...      3    0   10   4   35  15.9   12   38.67   12.00   11.67  \n",
       "4    ...      1    2    6   3   20  13.9   -9   37.75   10.50   10.00  \n",
       "5    ...      3    0    2   3   28  26.2   22   34.20    9.60   10.00  \n",
       "6    ...      0    0    5   2   14   9.0   24   33.17    9.00    9.67  \n",
       "7    ...      1    2    8   2   36  21.6   -4   30.43    8.43    9.86  \n",
       "8    ...      1    0    4   5   29  20.6   -5   31.12    8.25    9.50  \n",
       "9    ...      0    0    2   2   41  42.7    9   30.89    8.89    9.44  \n",
       "10   ...      0    0    7   4   33  24.6   -6   31.90    9.20   10.10  \n",
       "11   ...      2    0    6   0   30  24.0   12   32.00    9.73    9.91  \n",
       "12   ...      1    0    3   0   30  31.4   21   31.83    9.50    9.83  \n",
       "13   ...      1    0    7   3   31  20.2  -16   31.69    9.54   10.08  \n",
       "14   ...      2    0    8   3   34  23.3    9   31.64    9.64   10.43  \n",
       "15   ...      2    0    3   1   31  28.6   -7   31.80    9.53   10.60  \n",
       "16   ...      1    1    7   3   36  30.4   10   31.75    9.62   10.50  \n",
       "17   ...      1    1    5   2   17  15.9   14   32.00    9.71   10.88  \n",
       "18   ...      2    0    7   3   27  25.2    5   31.17    9.89   11.11  \n",
       "19   ...      2    0    5   3   35  24.6    4   30.95   10.26   11.26  \n",
       "20   ...      1    0   10   1   28  19.2   13   31.15   10.45   11.25  \n",
       "21   ...      1    1    4   1   32  28.6   -4   31.00   10.76   11.29  \n",
       "22   ...      3    0    8   3   27  16.5   -1   31.05   10.86   11.32  \n",
       "23   ...      2    0    7   3   37  25.2    9   30.87   10.83   11.26  \n",
       "24   ...      0    0    4   1   20  11.9  -10   31.12   10.88   11.04  \n",
       "25   ...      1    0    5   4   27  11.6   -6   30.68   10.68   10.84  \n",
       "26   ...      2    1    5   3   26  32.9   16   30.54   10.50   10.62  \n",
       "27   ...      1    0    4   2   46  33.7   -2   30.37   10.52   11.04  \n",
       "28   ...      1    0    4   2   42  32.3   -4   30.93   10.54   10.89  \n",
       "29   ...      1    0    4   1   45  39.9    9   31.31   10.52   10.76  \n",
       "..   ...    ...  ...  ...  ..  ...   ...  ...     ...     ...     ...  \n",
       "52   ...      1    2    4   3   27  21.4    1   31.02   10.37   10.25  \n",
       "53   ...      4    0    7   4   29  21.6    3   30.94   10.51   10.23  \n",
       "54   ...      1    0   11   5   47  30.9  -13   30.91   10.54   10.24  \n",
       "55   ...      2    0    2   0   17  10.5  -36   31.20   10.55   10.20  \n",
       "56   ...      3    1    6   0   38  37.7   13   30.95   10.43   10.09  \n",
       "57   ...      3    0    6   1   17  20.3   19   31.07   10.49   10.12  \n",
       "58   ...      1    0    9   2   41  28.9    4   30.83   10.62   10.24  \n",
       "59   ...      0    0    8   1   43  30.1   10   31.00   10.63   10.25  \n",
       "60   ...      1    1    4   0   45  28.0   -7   31.20   10.63   10.25  \n",
       "61   ...      3    0    4   4   48  41.4   10   31.43   10.57   10.15  \n",
       "62   ...      2    1    1   4   29  20.0  -14   31.69   10.68   10.13  \n",
       "63   ...      3    1    4   4   58  43.6    7   31.65   10.60   10.05  \n",
       "64   ...      2    0    3   2   23  23.1   12   32.06   10.48   10.03  \n",
       "65   ...      2    2    5   1   33  29.5   12   31.92   10.52   10.08  \n",
       "66   ...      2    1    5   3   25  27.8    7   31.94   10.53   10.14  \n",
       "67   ...      1    0    2   2   24  27.7   26   31.84   10.55   10.27  \n",
       "68   ...      4    0    7   1   28  24.4   13   31.72   10.54   10.35  \n",
       "69   ...      2    0    5   4   15   7.7  -25   31.67   10.51   10.35  \n",
       "70   ...      0    2    5   1   18  25.3   21   31.43   10.47   10.30  \n",
       "71   ...      0    0    5   4   39  30.8  -14   31.24   10.48   10.35  \n",
       "72   ...      2    0    6   0   37  28.9   12   31.35   10.49   10.39  \n",
       "73   ...      3    0    7   3   57  44.2    8   31.42   10.52   10.38  \n",
       "74   ...      0    0    8   1   32  24.7  -10   31.77   10.55   10.39  \n",
       "75   ...      2    0    8   1   40  28.8   -6   31.77   10.61   10.41  \n",
       "76   ...      2    0    3   2   12  17.6   19   31.88   10.64   10.41  \n",
       "77   ...      4    0    7   4   45  37.0    2   31.62   10.68   10.44  \n",
       "78   ...      0    1    8   5   23  10.2  -15   31.79   10.65   10.44  \n",
       "79   ...      1    0    2   1   50  45.6   10   31.68   10.67   10.41  \n",
       "80   ...      0    1    3   2    5   2.8   -5   31.68   10.67   10.41  \n",
       "81   ...      0    1    3   2    5   2.8   -5   31.58   10.67   10.37  \n",
       "\n",
       "[82 rows x 33 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "westbrook_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'seaborn-darkgrid',\n",
       " u'seaborn-notebook',\n",
       " u'classic',\n",
       " u'seaborn-ticks',\n",
       " u'grayscale',\n",
       " u'bmh',\n",
       " u'seaborn-talk',\n",
       " u'dark_background',\n",
       " u'ggplot',\n",
       " u'fivethirtyeight',\n",
       " u'_classic_test',\n",
       " u'seaborn-colorblind',\n",
       " u'seaborn-deep',\n",
       " u'seaborn-whitegrid',\n",
       " u'seaborn-bright',\n",
       " u'seaborn-poster',\n",
       " u'seaborn-muted',\n",
       " u'seaborn-paper',\n",
       " u'seaborn-white',\n",
       " u'seaborn-pastel',\n",
       " u'seaborn-dark',\n",
       " u'seaborn',\n",
       " u'seaborn-dark-palette']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.style.use('seaborn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 84)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n5MihmM1mqlev4RzP5MkfsX//Pmw2G127dqNDh4ed923btpVvvvkKi8XMmTMR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\nHecaeMjnOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f705a5ca510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 12))\n",
    "\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.AvgPTS.astype(float), label=\"Points per game\", color=\"#c5423d\")\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.AvgTRB.astype(float), label=\"Rebounds per game\", color=\"#4341c2\")\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.AvgAST.astype(float), label=\"Assist per game\", color=\"#40c23b\")\n",
    "plt.xlabel(\"Game in season\")\n",
    "plt.ylabel(\"PTS/TRB/AST per game\")\n",
    "\n",
    "plt.title(\"Russell Westbrook's averages during his 2016-17 NBA season\")\n",
    "\n",
    "plt.legend()\n",
    "plt.xlim(0, 84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "westbrook_stats = westbrook_stats.drop(westbrook_stats.index[80]) # dropping duplicate game"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pts_season, trb_season, ast_season = westbrook_stats.PTS.mean(), westbrook_stats.TRB.mean(), westbrook_stats.AST.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "            17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "            34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,\n",
       "            51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,\n",
       "            68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 81],\n",
       "           dtype='int64')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts, rbs, ast = westbrook_stats.AvgPTS, westbrook_stats.AvgTRB, westbrook_stats.AvgAST\n",
    "pts_change, rbs_change, ast_change = [], [], []\n",
    "for i in pts.index.tolist():\n",
    "    pts_change.append(truncate_float(float(pts[i]) - pts_season))\n",
    "    rbs_change.append(truncate_float(float(rbs[i]) - trb_season))\n",
    "    ast_change.append(truncate_float(float(ast[i]) - ast_season))\n",
    "\n",
    "westbrook_stats.loc[:, \"PTSChange\"] = pts_change\n",
    "westbrook_stats.loc[:, \"TRBChange\"] = rbs_change\n",
    "westbrook_stats.loc[:, \"ASTChange\"] = ast_change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rk</th>\n",
       "      <th>G</th>\n",
       "      <th>Date</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Opp</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>GS</th>\n",
       "      <th>MP</th>\n",
       "      <th>...</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "      <th>GmSc</th>\n",
       "      <th>+/-</th>\n",
       "      <th>AvgPTS</th>\n",
       "      <th>AvgTRB</th>\n",
       "      <th>AvgAST</th>\n",
       "      <th>PTSChange</th>\n",
       "      <th>TRBChange</th>\n",
       "      <th>ASTChange</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2016-10-26</td>\n",
       "      <td>27-349</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHI</td>\n",
       "      <td>W (+6)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:23</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>32</td>\n",
       "      <td>28.4</td>\n",
       "      <td>10</td>\n",
       "      <td>32.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.42</td>\n",
       "      <td>1.33</td>\n",
       "      <td>-1.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2016-10-28</td>\n",
       "      <td>27-351</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>45:19</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>51</td>\n",
       "      <td>32.9</td>\n",
       "      <td>7</td>\n",
       "      <td>32.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.42</td>\n",
       "      <td>1.33</td>\n",
       "      <td>-1.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>27-353</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:39</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>32.3</td>\n",
       "      <td>9</td>\n",
       "      <td>41.50</td>\n",
       "      <td>12.50</td>\n",
       "      <td>9.50</td>\n",
       "      <td>9.92</td>\n",
       "      <td>1.83</td>\n",
       "      <td>-0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-02</td>\n",
       "      <td>27-356</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAC</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>32:39</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "      <td>15.9</td>\n",
       "      <td>12</td>\n",
       "      <td>38.67</td>\n",
       "      <td>12.00</td>\n",
       "      <td>11.67</td>\n",
       "      <td>7.09</td>\n",
       "      <td>1.33</td>\n",
       "      <td>1.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2016-11-03</td>\n",
       "      <td>27-357</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-26)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:52</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>13.9</td>\n",
       "      <td>-9</td>\n",
       "      <td>37.75</td>\n",
       "      <td>10.50</td>\n",
       "      <td>10.00</td>\n",
       "      <td>6.17</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>-0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-05</td>\n",
       "      <td>27-359</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIN</td>\n",
       "      <td>W (+20)</td>\n",
       "      <td>1</td>\n",
       "      <td>28:22</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>26.2</td>\n",
       "      <td>22</td>\n",
       "      <td>34.20</td>\n",
       "      <td>9.60</td>\n",
       "      <td>10.00</td>\n",
       "      <td>2.62</td>\n",
       "      <td>-1.07</td>\n",
       "      <td>-0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-07</td>\n",
       "      <td>27-361</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIA</td>\n",
       "      <td>W (+12)</td>\n",
       "      <td>1</td>\n",
       "      <td>26:39</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>9.0</td>\n",
       "      <td>24</td>\n",
       "      <td>33.17</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.67</td>\n",
       "      <td>1.59</td>\n",
       "      <td>-1.67</td>\n",
       "      <td>-0.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>2016-11-09</td>\n",
       "      <td>27-363</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TOR</td>\n",
       "      <td>L (-10)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:46</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>36</td>\n",
       "      <td>21.6</td>\n",
       "      <td>-4</td>\n",
       "      <td>30.43</td>\n",
       "      <td>8.43</td>\n",
       "      <td>9.86</td>\n",
       "      <td>-1.15</td>\n",
       "      <td>-2.24</td>\n",
       "      <td>-0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>2016-11-11</td>\n",
       "      <td>27-365</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAC</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>20.6</td>\n",
       "      <td>-5</td>\n",
       "      <td>31.12</td>\n",
       "      <td>8.25</td>\n",
       "      <td>9.50</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>-2.42</td>\n",
       "      <td>-0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>28-001</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ORL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:38</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>42.7</td>\n",
       "      <td>9</td>\n",
       "      <td>30.89</td>\n",
       "      <td>8.89</td>\n",
       "      <td>9.44</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>-1.78</td>\n",
       "      <td>-0.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>2016-11-14</td>\n",
       "      <td>28-002</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DET</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:34</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "      <td>24.6</td>\n",
       "      <td>-6</td>\n",
       "      <td>31.90</td>\n",
       "      <td>9.20</td>\n",
       "      <td>10.10</td>\n",
       "      <td>0.32</td>\n",
       "      <td>-1.47</td>\n",
       "      <td>-0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>2016-11-16</td>\n",
       "      <td>28-004</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>W (+2)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:06</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12</td>\n",
       "      <td>32.00</td>\n",
       "      <td>9.73</td>\n",
       "      <td>9.91</td>\n",
       "      <td>0.42</td>\n",
       "      <td>-0.94</td>\n",
       "      <td>-0.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>2016-11-18</td>\n",
       "      <td>28-006</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+19)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:51</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>31.4</td>\n",
       "      <td>21</td>\n",
       "      <td>31.83</td>\n",
       "      <td>9.50</td>\n",
       "      <td>9.83</td>\n",
       "      <td>0.25</td>\n",
       "      <td>-1.17</td>\n",
       "      <td>-0.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>2016-11-20</td>\n",
       "      <td>28-008</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-4)</td>\n",
       "      <td>1</td>\n",
       "      <td>40:20</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>20.2</td>\n",
       "      <td>-16</td>\n",
       "      <td>31.69</td>\n",
       "      <td>9.54</td>\n",
       "      <td>10.08</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-1.13</td>\n",
       "      <td>-0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>2016-11-22</td>\n",
       "      <td>28-010</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>LAL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:31</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>23.3</td>\n",
       "      <td>9</td>\n",
       "      <td>31.64</td>\n",
       "      <td>9.64</td>\n",
       "      <td>10.43</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-1.03</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>2016-11-23</td>\n",
       "      <td>28-011</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>SAC</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:04</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-7</td>\n",
       "      <td>31.80</td>\n",
       "      <td>9.53</td>\n",
       "      <td>10.60</td>\n",
       "      <td>0.22</td>\n",
       "      <td>-1.14</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>2016-11-25</td>\n",
       "      <td>28-013</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:14</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>36</td>\n",
       "      <td>30.4</td>\n",
       "      <td>10</td>\n",
       "      <td>31.75</td>\n",
       "      <td>9.62</td>\n",
       "      <td>10.50</td>\n",
       "      <td>0.17</td>\n",
       "      <td>-1.05</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>2016-11-26</td>\n",
       "      <td>28-014</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DET</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:19</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>15.9</td>\n",
       "      <td>14</td>\n",
       "      <td>32.00</td>\n",
       "      <td>9.71</td>\n",
       "      <td>10.88</td>\n",
       "      <td>0.42</td>\n",
       "      <td>-0.96</td>\n",
       "      <td>0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>2016-11-28</td>\n",
       "      <td>28-016</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:22</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>25.2</td>\n",
       "      <td>5</td>\n",
       "      <td>31.17</td>\n",
       "      <td>9.89</td>\n",
       "      <td>11.11</td>\n",
       "      <td>-0.41</td>\n",
       "      <td>-0.78</td>\n",
       "      <td>0.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>28-018</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WAS</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:07</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>35</td>\n",
       "      <td>24.6</td>\n",
       "      <td>4</td>\n",
       "      <td>30.95</td>\n",
       "      <td>10.26</td>\n",
       "      <td>11.26</td>\n",
       "      <td>-0.63</td>\n",
       "      <td>-0.41</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>28-022</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:31</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>19.2</td>\n",
       "      <td>13</td>\n",
       "      <td>31.15</td>\n",
       "      <td>10.45</td>\n",
       "      <td>11.25</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>0.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>2016-12-05</td>\n",
       "      <td>28-023</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ATL</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:52</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>28.6</td>\n",
       "      <td>-4</td>\n",
       "      <td>31.00</td>\n",
       "      <td>10.76</td>\n",
       "      <td>11.29</td>\n",
       "      <td>-0.58</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>2016-12-09</td>\n",
       "      <td>28-027</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:36</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>16.5</td>\n",
       "      <td>-1</td>\n",
       "      <td>31.05</td>\n",
       "      <td>10.86</td>\n",
       "      <td>11.32</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>2016-12-11</td>\n",
       "      <td>28-029</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>37</td>\n",
       "      <td>25.2</td>\n",
       "      <td>9</td>\n",
       "      <td>30.87</td>\n",
       "      <td>10.83</td>\n",
       "      <td>11.26</td>\n",
       "      <td>-0.71</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>2016-12-13</td>\n",
       "      <td>28-031</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-19)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:21</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>11.9</td>\n",
       "      <td>-10</td>\n",
       "      <td>31.12</td>\n",
       "      <td>10.88</td>\n",
       "      <td>11.04</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>2016-12-14</td>\n",
       "      <td>28-032</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>UTA</td>\n",
       "      <td>L (-20)</td>\n",
       "      <td>1</td>\n",
       "      <td>30:38</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>11.6</td>\n",
       "      <td>-6</td>\n",
       "      <td>30.68</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.84</td>\n",
       "      <td>-0.90</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>2016-12-17</td>\n",
       "      <td>28-035</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHO</td>\n",
       "      <td>W (+13)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>32.9</td>\n",
       "      <td>16</td>\n",
       "      <td>30.54</td>\n",
       "      <td>10.50</td>\n",
       "      <td>10.62</td>\n",
       "      <td>-1.04</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>2016-12-19</td>\n",
       "      <td>28-037</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ATL</td>\n",
       "      <td>L (-2)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:25</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>46</td>\n",
       "      <td>33.7</td>\n",
       "      <td>-2</td>\n",
       "      <td>30.37</td>\n",
       "      <td>10.52</td>\n",
       "      <td>11.04</td>\n",
       "      <td>-1.21</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>28-039</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>33:35</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>42</td>\n",
       "      <td>32.3</td>\n",
       "      <td>-4</td>\n",
       "      <td>30.93</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.89</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>2016-12-23</td>\n",
       "      <td>28-041</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BOS</td>\n",
       "      <td>W (+5)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:50</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>39.9</td>\n",
       "      <td>9</td>\n",
       "      <td>31.31</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.76</td>\n",
       "      <td>-0.27</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>52</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>28-085</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POR</td>\n",
       "      <td>W (+6)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:10</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>42</td>\n",
       "      <td>25.8</td>\n",
       "      <td>7</td>\n",
       "      <td>30.80</td>\n",
       "      <td>10.49</td>\n",
       "      <td>10.29</td>\n",
       "      <td>-0.78</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>-0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>2017-02-06</td>\n",
       "      <td>28-086</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>IND</td>\n",
       "      <td>L (-3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:07</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>21.4</td>\n",
       "      <td>1</td>\n",
       "      <td>31.02</td>\n",
       "      <td>10.37</td>\n",
       "      <td>10.25</td>\n",
       "      <td>-0.56</td>\n",
       "      <td>-0.30</td>\n",
       "      <td>-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>28-089</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLE</td>\n",
       "      <td>W (+9)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:23</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>21.6</td>\n",
       "      <td>3</td>\n",
       "      <td>30.94</td>\n",
       "      <td>10.51</td>\n",
       "      <td>10.23</td>\n",
       "      <td>-0.64</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>2017-02-11</td>\n",
       "      <td>28-091</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:09</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>47</td>\n",
       "      <td>30.9</td>\n",
       "      <td>-13</td>\n",
       "      <td>30.91</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.24</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>56</td>\n",
       "      <td>56</td>\n",
       "      <td>2017-02-13</td>\n",
       "      <td>28-093</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>WAS</td>\n",
       "      <td>L (-22)</td>\n",
       "      <td>1</td>\n",
       "      <td>24:12</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>10.5</td>\n",
       "      <td>-36</td>\n",
       "      <td>31.20</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.20</td>\n",
       "      <td>-0.38</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>28-095</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NYK</td>\n",
       "      <td>W (+11)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:44</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>37.7</td>\n",
       "      <td>13</td>\n",
       "      <td>30.95</td>\n",
       "      <td>10.43</td>\n",
       "      <td>10.09</td>\n",
       "      <td>-0.63</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>58</td>\n",
       "      <td>58</td>\n",
       "      <td>2017-02-24</td>\n",
       "      <td>28-104</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LAL</td>\n",
       "      <td>W (+17)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:16</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>20.3</td>\n",
       "      <td>19</td>\n",
       "      <td>31.07</td>\n",
       "      <td>10.49</td>\n",
       "      <td>10.12</td>\n",
       "      <td>-0.51</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>-0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>59</td>\n",
       "      <td>59</td>\n",
       "      <td>2017-02-26</td>\n",
       "      <td>28-106</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NOP</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:53</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>28.9</td>\n",
       "      <td>4</td>\n",
       "      <td>30.83</td>\n",
       "      <td>10.62</td>\n",
       "      <td>10.24</td>\n",
       "      <td>-0.75</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>2017-02-28</td>\n",
       "      <td>28-108</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:47</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>30.1</td>\n",
       "      <td>10</td>\n",
       "      <td>31.00</td>\n",
       "      <td>10.63</td>\n",
       "      <td>10.25</td>\n",
       "      <td>-0.58</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>61</td>\n",
       "      <td>61</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>28-110</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:52</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-7</td>\n",
       "      <td>31.20</td>\n",
       "      <td>10.63</td>\n",
       "      <td>10.25</td>\n",
       "      <td>-0.38</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>62</td>\n",
       "      <td>62</td>\n",
       "      <td>2017-03-03</td>\n",
       "      <td>28-111</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-7)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:05</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>48</td>\n",
       "      <td>41.4</td>\n",
       "      <td>10</td>\n",
       "      <td>31.43</td>\n",
       "      <td>10.57</td>\n",
       "      <td>10.15</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>-0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>63</td>\n",
       "      <td>63</td>\n",
       "      <td>2017-03-05</td>\n",
       "      <td>28-113</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>L (-15)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:01</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>29</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-14</td>\n",
       "      <td>31.69</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.13</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>28-115</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POR</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:56</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>58</td>\n",
       "      <td>43.6</td>\n",
       "      <td>7</td>\n",
       "      <td>31.65</td>\n",
       "      <td>10.60</td>\n",
       "      <td>10.05</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>-0.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>28-117</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>W (+10)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:08</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>23.1</td>\n",
       "      <td>12</td>\n",
       "      <td>32.06</td>\n",
       "      <td>10.48</td>\n",
       "      <td>10.03</td>\n",
       "      <td>0.48</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>-0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>66</td>\n",
       "      <td>66</td>\n",
       "      <td>2017-03-11</td>\n",
       "      <td>28-119</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UTA</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:18</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>29.5</td>\n",
       "      <td>12</td>\n",
       "      <td>31.92</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.08</td>\n",
       "      <td>0.34</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>67</td>\n",
       "      <td>2017-03-14</td>\n",
       "      <td>28-122</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>BRK</td>\n",
       "      <td>W (+18)</td>\n",
       "      <td>1</td>\n",
       "      <td>34:42</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>27.8</td>\n",
       "      <td>7</td>\n",
       "      <td>31.94</td>\n",
       "      <td>10.53</td>\n",
       "      <td>10.14</td>\n",
       "      <td>0.36</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>-0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>68</td>\n",
       "      <td>68</td>\n",
       "      <td>2017-03-16</td>\n",
       "      <td>28-124</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>TOR</td>\n",
       "      <td>W (+21)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:50</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>27.7</td>\n",
       "      <td>26</td>\n",
       "      <td>31.84</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.27</td>\n",
       "      <td>0.26</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>69</td>\n",
       "      <td>69</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>28-126</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAC</td>\n",
       "      <td>W (+16)</td>\n",
       "      <td>1</td>\n",
       "      <td>35:59</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>24.4</td>\n",
       "      <td>13</td>\n",
       "      <td>31.72</td>\n",
       "      <td>10.54</td>\n",
       "      <td>10.35</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>-0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>2017-03-20</td>\n",
       "      <td>28-128</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GSW</td>\n",
       "      <td>L (-16)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:13</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>7.7</td>\n",
       "      <td>-25</td>\n",
       "      <td>31.67</td>\n",
       "      <td>10.51</td>\n",
       "      <td>10.35</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>71</td>\n",
       "      <td>71</td>\n",
       "      <td>2017-03-22</td>\n",
       "      <td>28-130</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHI</td>\n",
       "      <td>W (+25)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:51</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>25.3</td>\n",
       "      <td>21</td>\n",
       "      <td>31.43</td>\n",
       "      <td>10.47</td>\n",
       "      <td>10.30</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.20</td>\n",
       "      <td>-0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>28-134</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>HOU</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>38:58</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>39</td>\n",
       "      <td>30.8</td>\n",
       "      <td>-14</td>\n",
       "      <td>31.24</td>\n",
       "      <td>10.48</td>\n",
       "      <td>10.35</td>\n",
       "      <td>-0.34</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>-0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>28-135</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DAL</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:21</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>28.9</td>\n",
       "      <td>12</td>\n",
       "      <td>31.35</td>\n",
       "      <td>10.49</td>\n",
       "      <td>10.39</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>2017-03-29</td>\n",
       "      <td>28-137</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>ORL</td>\n",
       "      <td>W (+8)</td>\n",
       "      <td>1</td>\n",
       "      <td>41:49</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>57</td>\n",
       "      <td>44.2</td>\n",
       "      <td>8</td>\n",
       "      <td>31.42</td>\n",
       "      <td>10.52</td>\n",
       "      <td>10.38</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>2017-03-31</td>\n",
       "      <td>28-139</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAS</td>\n",
       "      <td>L (-5)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:59</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>24.7</td>\n",
       "      <td>-10</td>\n",
       "      <td>31.77</td>\n",
       "      <td>10.55</td>\n",
       "      <td>10.39</td>\n",
       "      <td>0.19</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>28-141</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CHO</td>\n",
       "      <td>L (-12)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:12</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>28.8</td>\n",
       "      <td>-6</td>\n",
       "      <td>31.77</td>\n",
       "      <td>10.61</td>\n",
       "      <td>10.41</td>\n",
       "      <td>0.19</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>77</td>\n",
       "      <td>77</td>\n",
       "      <td>2017-04-04</td>\n",
       "      <td>28-143</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MIL</td>\n",
       "      <td>W (+31)</td>\n",
       "      <td>1</td>\n",
       "      <td>27:05</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19</td>\n",
       "      <td>31.88</td>\n",
       "      <td>10.64</td>\n",
       "      <td>10.41</td>\n",
       "      <td>0.30</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>28-144</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>MEM</td>\n",
       "      <td>W (+3)</td>\n",
       "      <td>1</td>\n",
       "      <td>37:32</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2</td>\n",
       "      <td>31.62</td>\n",
       "      <td>10.68</td>\n",
       "      <td>10.44</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>79</td>\n",
       "      <td>79</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>28-146</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>PHO</td>\n",
       "      <td>L (-21)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:24</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>10.2</td>\n",
       "      <td>-15</td>\n",
       "      <td>31.79</td>\n",
       "      <td>10.65</td>\n",
       "      <td>10.44</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2017-04-09</td>\n",
       "      <td>28-148</td>\n",
       "      <td>OKC</td>\n",
       "      <td>@</td>\n",
       "      <td>DEN</td>\n",
       "      <td>W (+1)</td>\n",
       "      <td>1</td>\n",
       "      <td>36:57</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>45.6</td>\n",
       "      <td>10</td>\n",
       "      <td>31.68</td>\n",
       "      <td>10.67</td>\n",
       "      <td>10.41</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>82</td>\n",
       "      <td>81</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>28-151</td>\n",
       "      <td>OKC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEN</td>\n",
       "      <td>L (-6)</td>\n",
       "      <td>1</td>\n",
       "      <td>18:19</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-5</td>\n",
       "      <td>31.58</td>\n",
       "      <td>10.67</td>\n",
       "      <td>10.37</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Rk   G        Date     Age   Tm Unnamed: 5  Opp Unnamed: 7  GS     MP  \\\n",
       "0    1   1  2016-10-26  27-349  OKC          @  PHI     W (+6)   1  36:23   \n",
       "1    2   2  2016-10-28  27-351  OKC        NaN  PHO     W (+3)   1  45:19   \n",
       "2    3   3  2016-10-30  27-353  OKC        NaN  LAL    W (+17)   1  33:39   \n",
       "3    4   4  2016-11-02  27-356  OKC          @  LAC     W (+2)   1  32:39   \n",
       "4    5   5  2016-11-03  27-357  OKC          @  GSW    L (-26)   1  28:52   \n",
       "5    6   6  2016-11-05  27-359  OKC        NaN  MIN    W (+20)   1  28:22   \n",
       "6    7   7  2016-11-07  27-361  OKC        NaN  MIA    W (+12)   1  26:39   \n",
       "7    8   8  2016-11-09  27-363  OKC        NaN  TOR    L (-10)   1  38:46   \n",
       "8    9   9  2016-11-11  27-365  OKC        NaN  LAC     L (-2)   1  35:16   \n",
       "9   10  10  2016-11-13  28-001  OKC        NaN  ORL     L (-2)   1  37:38   \n",
       "10  11  11  2016-11-14  28-002  OKC          @  DET    L (-16)   1  33:34   \n",
       "11  12  12  2016-11-16  28-004  OKC        NaN  HOU     W (+2)   1  36:06   \n",
       "12  13  13  2016-11-18  28-006  OKC        NaN  BRK    W (+19)   1  33:51   \n",
       "13  14  14  2016-11-20  28-008  OKC        NaN  IND     L (-4)   1  40:20   \n",
       "14  15  15  2016-11-22  28-010  OKC          @  LAL     L (-2)   1  35:31   \n",
       "15  16  16  2016-11-23  28-011  OKC          @  SAC    L (-15)   1  35:04   \n",
       "16  17  17  2016-11-25  28-013  OKC          @  DEN     W (+3)   1  41:14   \n",
       "17  18  18  2016-11-26  28-014  OKC        NaN  DET    W (+18)   1  37:19   \n",
       "18  19  19  2016-11-28  28-016  OKC          @  NYK     W (+9)   1  36:22   \n",
       "19  20  20  2016-11-30  28-018  OKC        NaN  WAS    W (+11)   1  41:07   \n",
       "20  21  21  2016-12-04  28-022  OKC        NaN  NOP     W (+9)   1  37:31   \n",
       "21  22  22  2016-12-05  28-023  OKC          @  ATL     W (+3)   1  33:52   \n",
       "22  23  23  2016-12-09  28-027  OKC        NaN  HOU     L (-3)   1  35:36   \n",
       "23  24  24  2016-12-11  28-029  OKC        NaN  BOS     W (+3)   1  36:12   \n",
       "24  25  25  2016-12-13  28-031  OKC          @  POR    L (-19)   1  27:21   \n",
       "25  26  26  2016-12-14  28-032  OKC          @  UTA    L (-20)   1  30:38   \n",
       "26  27  27  2016-12-17  28-035  OKC        NaN  PHO    W (+13)   1  34:01   \n",
       "27  28  28  2016-12-19  28-037  OKC        NaN  ATL     L (-2)   1  35:25   \n",
       "28  29  29  2016-12-21  28-039  OKC          @  NOP    W (+11)   1  33:35   \n",
       "29  30  30  2016-12-23  28-041  OKC          @  BOS     W (+5)   1  34:50   \n",
       "..  ..  ..         ...     ...  ...        ...  ...        ...  ..    ...   \n",
       "51  52  52  2017-02-05  28-085  OKC        NaN  POR     W (+6)   1  35:10   \n",
       "52  53  53  2017-02-06  28-086  OKC          @  IND     L (-3)   1  37:07   \n",
       "53  54  54  2017-02-09  28-089  OKC        NaN  CLE     W (+9)   1  35:23   \n",
       "54  55  55  2017-02-11  28-091  OKC        NaN  GSW    L (-16)   1  37:09   \n",
       "55  56  56  2017-02-13  28-093  OKC          @  WAS    L (-22)   1  24:12   \n",
       "56  57  57  2017-02-15  28-095  OKC        NaN  NYK    W (+11)   1  37:44   \n",
       "57  58  58  2017-02-24  28-104  OKC        NaN  LAL    W (+17)   1  35:16   \n",
       "58  59  59  2017-02-26  28-106  OKC        NaN  NOP     W (+8)   1  36:53   \n",
       "59  60  60  2017-02-28  28-108  OKC        NaN  UTA     W (+3)   1  38:47   \n",
       "60  61  61  2017-03-02  28-110  OKC          @  POR     L (-5)   1  36:52   \n",
       "61  62  62  2017-03-03  28-111  OKC          @  PHO     L (-7)   1  38:05   \n",
       "62  63  63  2017-03-05  28-113  OKC          @  DAL    L (-15)   1  34:01   \n",
       "63  64  64  2017-03-07  28-115  OKC        NaN  POR     L (-5)   1  35:56   \n",
       "64  65  65  2017-03-09  28-117  OKC        NaN  SAS    W (+10)   1  35:08   \n",
       "65  66  66  2017-03-11  28-119  OKC        NaN  UTA     W (+8)   1  36:18   \n",
       "66  67  67  2017-03-14  28-122  OKC          @  BRK    W (+18)   1  34:42   \n",
       "67  68  68  2017-03-16  28-124  OKC          @  TOR    W (+21)   1  27:50   \n",
       "68  69  69  2017-03-18  28-126  OKC        NaN  SAC    W (+16)   1  35:59   \n",
       "69  70  70  2017-03-20  28-128  OKC        NaN  GSW    L (-16)   1  27:13   \n",
       "70  71  71  2017-03-22  28-130  OKC        NaN  PHI    W (+25)   1  27:51   \n",
       "71  72  72  2017-03-26  28-134  OKC          @  HOU    L (-12)   1  38:58   \n",
       "72  73  73  2017-03-27  28-135  OKC          @  DAL     W (+1)   1  36:21   \n",
       "73  74  74  2017-03-29  28-137  OKC          @  ORL     W (+8)   1  41:49   \n",
       "74  75  75  2017-03-31  28-139  OKC        NaN  SAS     L (-5)   1  36:59   \n",
       "75  76  76  2017-04-02  28-141  OKC        NaN  CHO    L (-12)   1  36:12   \n",
       "76  77  77  2017-04-04  28-143  OKC        NaN  MIL    W (+31)   1  27:05   \n",
       "77  78  78  2017-04-05  28-144  OKC          @  MEM     W (+3)   1  37:32   \n",
       "78  79  79  2017-04-07  28-146  OKC          @  PHO    L (-21)   1  36:24   \n",
       "79  80  80  2017-04-09  28-148  OKC          @  DEN     W (+1)   1  36:57   \n",
       "81  82  81  2017-04-12  28-151  OKC        NaN  DEN     L (-6)   1  18:19   \n",
       "\n",
       "      ...      PF  PTS  GmSc  +/-  AvgPTS  AvgTRB  AvgAST  PTSChange  \\\n",
       "0     ...       2   32  28.4   10   32.00   12.00    9.00       0.42   \n",
       "1     ...       3   51  32.9    7   32.00   12.00    9.00       0.42   \n",
       "2     ...       3   33  32.3    9   41.50   12.50    9.50       9.92   \n",
       "3     ...       4   35  15.9   12   38.67   12.00   11.67       7.09   \n",
       "4     ...       3   20  13.9   -9   37.75   10.50   10.00       6.17   \n",
       "5     ...       3   28  26.2   22   34.20    9.60   10.00       2.62   \n",
       "6     ...       2   14   9.0   24   33.17    9.00    9.67       1.59   \n",
       "7     ...       2   36  21.6   -4   30.43    8.43    9.86      -1.15   \n",
       "8     ...       5   29  20.6   -5   31.12    8.25    9.50      -0.46   \n",
       "9     ...       2   41  42.7    9   30.89    8.89    9.44      -0.69   \n",
       "10    ...       4   33  24.6   -6   31.90    9.20   10.10       0.32   \n",
       "11    ...       0   30  24.0   12   32.00    9.73    9.91       0.42   \n",
       "12    ...       0   30  31.4   21   31.83    9.50    9.83       0.25   \n",
       "13    ...       3   31  20.2  -16   31.69    9.54   10.08       0.11   \n",
       "14    ...       3   34  23.3    9   31.64    9.64   10.43       0.06   \n",
       "15    ...       1   31  28.6   -7   31.80    9.53   10.60       0.22   \n",
       "16    ...       3   36  30.4   10   31.75    9.62   10.50       0.17   \n",
       "17    ...       2   17  15.9   14   32.00    9.71   10.88       0.42   \n",
       "18    ...       3   27  25.2    5   31.17    9.89   11.11      -0.41   \n",
       "19    ...       3   35  24.6    4   30.95   10.26   11.26      -0.63   \n",
       "20    ...       1   28  19.2   13   31.15   10.45   11.25      -0.43   \n",
       "21    ...       1   32  28.6   -4   31.00   10.76   11.29      -0.58   \n",
       "22    ...       3   27  16.5   -1   31.05   10.86   11.32      -0.53   \n",
       "23    ...       3   37  25.2    9   30.87   10.83   11.26      -0.71   \n",
       "24    ...       1   20  11.9  -10   31.12   10.88   11.04      -0.46   \n",
       "25    ...       4   27  11.6   -6   30.68   10.68   10.84      -0.90   \n",
       "26    ...       3   26  32.9   16   30.54   10.50   10.62      -1.04   \n",
       "27    ...       2   46  33.7   -2   30.37   10.52   11.04      -1.21   \n",
       "28    ...       2   42  32.3   -4   30.93   10.54   10.89      -0.65   \n",
       "29    ...       1   45  39.9    9   31.31   10.52   10.76      -0.27   \n",
       "..    ...      ..  ...   ...  ...     ...     ...     ...        ...   \n",
       "51    ...       3   42  25.8    7   30.80   10.49   10.29      -0.78   \n",
       "52    ...       3   27  21.4    1   31.02   10.37   10.25      -0.56   \n",
       "53    ...       4   29  21.6    3   30.94   10.51   10.23      -0.64   \n",
       "54    ...       5   47  30.9  -13   30.91   10.54   10.24      -0.67   \n",
       "55    ...       0   17  10.5  -36   31.20   10.55   10.20      -0.38   \n",
       "56    ...       0   38  37.7   13   30.95   10.43   10.09      -0.63   \n",
       "57    ...       1   17  20.3   19   31.07   10.49   10.12      -0.51   \n",
       "58    ...       2   41  28.9    4   30.83   10.62   10.24      -0.75   \n",
       "59    ...       1   43  30.1   10   31.00   10.63   10.25      -0.58   \n",
       "60    ...       0   45  28.0   -7   31.20   10.63   10.25      -0.38   \n",
       "61    ...       4   48  41.4   10   31.43   10.57   10.15      -0.15   \n",
       "62    ...       4   29  20.0  -14   31.69   10.68   10.13       0.11   \n",
       "63    ...       4   58  43.6    7   31.65   10.60   10.05       0.07   \n",
       "64    ...       2   23  23.1   12   32.06   10.48   10.03       0.48   \n",
       "65    ...       1   33  29.5   12   31.92   10.52   10.08       0.34   \n",
       "66    ...       3   25  27.8    7   31.94   10.53   10.14       0.36   \n",
       "67    ...       2   24  27.7   26   31.84   10.55   10.27       0.26   \n",
       "68    ...       1   28  24.4   13   31.72   10.54   10.35       0.14   \n",
       "69    ...       4   15   7.7  -25   31.67   10.51   10.35       0.09   \n",
       "70    ...       1   18  25.3   21   31.43   10.47   10.30      -0.15   \n",
       "71    ...       4   39  30.8  -14   31.24   10.48   10.35      -0.34   \n",
       "72    ...       0   37  28.9   12   31.35   10.49   10.39      -0.23   \n",
       "73    ...       3   57  44.2    8   31.42   10.52   10.38      -0.16   \n",
       "74    ...       1   32  24.7  -10   31.77   10.55   10.39       0.19   \n",
       "75    ...       1   40  28.8   -6   31.77   10.61   10.41       0.19   \n",
       "76    ...       2   12  17.6   19   31.88   10.64   10.41       0.30   \n",
       "77    ...       4   45  37.0    2   31.62   10.68   10.44       0.04   \n",
       "78    ...       5   23  10.2  -15   31.79   10.65   10.44       0.21   \n",
       "79    ...       1   50  45.6   10   31.68   10.67   10.41       0.10   \n",
       "81    ...       2    5   2.8   -5   31.58   10.67   10.37      -0.00   \n",
       "\n",
       "    TRBChange  ASTChange  \n",
       "0        1.33      -1.37  \n",
       "1        1.33      -1.37  \n",
       "2        1.83      -0.87  \n",
       "3        1.33       1.30  \n",
       "4       -0.17      -0.37  \n",
       "5       -1.07      -0.37  \n",
       "6       -1.67      -0.70  \n",
       "7       -2.24      -0.51  \n",
       "8       -2.42      -0.87  \n",
       "9       -1.78      -0.93  \n",
       "10      -1.47      -0.27  \n",
       "11      -0.94      -0.46  \n",
       "12      -1.17      -0.54  \n",
       "13      -1.13      -0.29  \n",
       "14      -1.03       0.06  \n",
       "15      -1.14       0.23  \n",
       "16      -1.05       0.13  \n",
       "17      -0.96       0.51  \n",
       "18      -0.78       0.74  \n",
       "19      -0.41       0.89  \n",
       "20      -0.22       0.88  \n",
       "21       0.09       0.92  \n",
       "22       0.19       0.95  \n",
       "23       0.16       0.89  \n",
       "24       0.21       0.67  \n",
       "25       0.01       0.47  \n",
       "26      -0.17       0.25  \n",
       "27      -0.15       0.67  \n",
       "28      -0.13       0.52  \n",
       "29      -0.15       0.39  \n",
       "..        ...        ...  \n",
       "51      -0.18      -0.08  \n",
       "52      -0.30      -0.12  \n",
       "53      -0.16      -0.14  \n",
       "54      -0.13      -0.13  \n",
       "55      -0.12      -0.17  \n",
       "56      -0.24      -0.28  \n",
       "57      -0.18      -0.25  \n",
       "58      -0.05      -0.13  \n",
       "59      -0.04      -0.12  \n",
       "60      -0.04      -0.12  \n",
       "61      -0.10      -0.22  \n",
       "62       0.01      -0.24  \n",
       "63      -0.07      -0.32  \n",
       "64      -0.19      -0.34  \n",
       "65      -0.15      -0.29  \n",
       "66      -0.14      -0.23  \n",
       "67      -0.12      -0.10  \n",
       "68      -0.13      -0.02  \n",
       "69      -0.16      -0.02  \n",
       "70      -0.20      -0.07  \n",
       "71      -0.19      -0.02  \n",
       "72      -0.18       0.02  \n",
       "73      -0.15       0.01  \n",
       "74      -0.12       0.02  \n",
       "75      -0.06       0.04  \n",
       "76      -0.03       0.04  \n",
       "77       0.01       0.07  \n",
       "78      -0.02       0.07  \n",
       "79       0.00       0.04  \n",
       "81       0.00      -0.00  \n",
       "\n",
       "[81 rows x 36 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "westbrook_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7053bbb390>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BA3HlypVc6+NDY8eOFW5ubiI2NlZERUWJfv36qX0/59RvZpbxyJEjRXx8vFCpVGrtyNfX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VB7gwqNGrf/DgQTZu3IhO11BfBQH+TYm71Hmt22tQ1utVW8KJE9XXlZwrEk0wHnPDCTaVtcmJ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7053bbb1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 14))\n",
    "\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.PTSChange.astype(float), label=\"Difference between points' average through n-th game and season average of \" + truncate_float(pts_season), color=\"#c5423d\")\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.TRBChange.astype(float), label=\"Difference between rebounds' average through n-th game and season average of \" + truncate_float(trb_season), color=\"#4341c2\")\n",
    "plt.plot(westbrook_stats.Rk.astype(int), westbrook_stats.ASTChange.astype(float), label=\"Difference between assists' average through n-th game and season average of\" + truncate_float(ast_season), color=\"#40c23b\")\n",
    "\n",
    "plt.xlabel(\"Game in season\", size=14)\n",
    "plt.ylabel(\"Change in average PTS/TRB/AST through that game in relation to whole season\", size=14)\n",
    "\n",
    "plt.title(\"Russell Westbrook's averages through x-th game in relation to whole season averages during his 2016-17 NBA season\", size=14)\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}