OriginalIdea(old).ipynb

{
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  {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Season</th>\n",
       "      <th>DayNum</th>\n",
       "      <th>WTeamID</th>\n",
       "      <th>WScore</th>\n",
       "      <th>LTeamID</th>\n",
       "      <th>LScore</th>\n",
       "      <th>WLoc</th>\n",
       "      <th>NumOT</th>\n",
       "      <th>WFGM</th>\n",
       "      <th>WFGA</th>\n",
       "      <th>...</th>\n",
       "      <th>LFGA3</th>\n",
       "      <th>LFTM</th>\n",
       "      <th>LFTA</th>\n",
       "      <th>LOR</th>\n",
       "      <th>LDR</th>\n",
       "      <th>LAst</th>\n",
       "      <th>LTO</th>\n",
       "      <th>LStl</th>\n",
       "      <th>LBlk</th>\n",
       "      <th>LPF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2003</td>\n",
       "      <td>10</td>\n",
       "      <td>1104</td>\n",
       "      <td>68</td>\n",
       "      <td>1328</td>\n",
       "      <td>62</td>\n",
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       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "      <td>22</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>10</td>\n",
       "      <td>1272</td>\n",
       "      <td>70</td>\n",
       "      <td>1393</td>\n",
       "      <td>63</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>62</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>16</td>\n",
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       "      <th>2</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1266</td>\n",
       "      <td>73</td>\n",
       "      <td>1437</td>\n",
       "      <td>61</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>26</td>\n",
       "      <td>14</td>\n",
       "      <td>23</td>\n",
       "      <td>31</td>\n",
       "      <td>22</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1296</td>\n",
       "      <td>56</td>\n",
       "      <td>1457</td>\n",
       "      <td>50</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>38</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1400</td>\n",
       "      <td>77</td>\n",
       "      <td>1208</td>\n",
       "      <td>71</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>61</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>27</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1458</td>\n",
       "      <td>81</td>\n",
       "      <td>1186</td>\n",
       "      <td>55</td>\n",
       "      <td>H</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>57</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1161</td>\n",
       "      <td>80</td>\n",
       "      <td>1236</td>\n",
       "      <td>62</td>\n",
       "      <td>H</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>28</td>\n",
       "      <td>9</td>\n",
       "      <td>21</td>\n",
       "      <td>11</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1186</td>\n",
       "      <td>75</td>\n",
       "      <td>1457</td>\n",
       "      <td>61</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>62</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>23</td>\n",
       "      <td>8</td>\n",
       "      <td>25</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1194</td>\n",
       "      <td>71</td>\n",
       "      <td>1156</td>\n",
       "      <td>66</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>13</td>\n",
       "      <td>25</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1458</td>\n",
       "      <td>84</td>\n",
       "      <td>1296</td>\n",
       "      <td>56</td>\n",
       "      <td>H</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>67</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>23</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Season  DayNum  WTeamID  WScore  LTeamID  LScore WLoc  NumOT  WFGM  WFGA  \\\n",
       "0    2003      10     1104      68     1328      62    N      0    27    58   \n",
       "1    2003      10     1272      70     1393      63    N      0    26    62   \n",
       "2    2003      11     1266      73     1437      61    N      0    24    58   \n",
       "3    2003      11     1296      56     1457      50    N      0    18    38   \n",
       "4    2003      11     1400      77     1208      71    N      0    30    61   \n",
       "5    2003      11     1458      81     1186      55    H      0    26    57   \n",
       "6    2003      12     1161      80     1236      62    H      0    23    55   \n",
       "7    2003      12     1186      75     1457      61    N      0    28    62   \n",
       "8    2003      12     1194      71     1156      66    N      0    28    58   \n",
       "9    2003      12     1458      84     1296      56    H      0    32    67   \n",
       "\n",
       "  ...   LFGA3  LFTM  LFTA  LOR  LDR  LAst  LTO  LStl  LBlk  LPF  \n",
       "0 ...      10    16    22   10   22     8   18     9     2   20  \n",
       "1 ...      24     9    20   20   25     7   12     8     6   16  \n",
       "2 ...      26    14    23   31   22     9   12     2     5   23  \n",
       "3 ...      22     8    15   17   20     9   19     4     3   23  \n",
       "4 ...      16    17    27   21   15    12   10     7     1   14  \n",
       "5 ...      11    12    17    6   22     8   19     4     3   25  \n",
       "6 ...      15    20    28    9   21    11   30    10     4   28  \n",
       "7 ...      17    17    23    8   25    10   15    14     8   18  \n",
       "8 ...      18    12    27   13   26    13   25     8     2   18  \n",
       "9 ...      14     7    12    9   23    10   18     1     3   18  \n",
       "\n",
       "[10 rows x 34 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the data source and prepare a dataframe\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "data = pd.read_csv(\"./Dataset/MarchmadnessDatasetFull.csv\", header=\"infer\")\n",
    "# display(data.head(10))\n",
    "\n",
    "data2 = pd.read_csv(\"./Dataset/RegularSeasonDetailedResults.csv\", header=\"infer\")\n",
    "display(data2.head(10))\n",
    "\n",
    "teams = pd.read_csv(\"./Dataset/Teams.csv\", header=\"infer\")\n",
    "# teams.head(10)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Preprocess Dataset\n",
    "\n",
    "# Drop the Location, Rk and Region info because it's irrelevant\n",
    "#data2 = data2.drop('DayNum', axis=1)#not important for analysis\n",
    "data2 = data2.drop('WLoc', axis=1)#not important for analysis\n",
    "# data2 = data2.drop('WTeamID', axis=1)#not important for analysis\n",
    "# data2 = data2.drop('LTeamID', axis=1)#not important for analysis\n",
    "# data2 = data2.drop('Season', axis=1)#not important for analysis\n",
    "\n",
    "data = data.drop('Rk', axis=1)#not important for analysis\n",
    "data = data.drop('Year', axis=1)#not important for analysis\n",
    "data = data.drop('Date', axis=1)#not important for analysis\n",
    "data = data.drop('Location', axis=1)#not important for analysis\n",
    "data = data.drop('Region', axis=1)#not important for analysis\n",
    "\n",
    "data2 = data2.drop('WPF', axis=1) #Personal Fouls are not significant\n",
    "data2 = data2.drop('LPF', axis=1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "H:\\Tools\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:63: RuntimeWarning: invalid value encountered in longlong_scalars\n",
      "H:\\Tools\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:62: RuntimeWarning: invalid value encountered in longlong_scalars\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Season</th>\n",
       "      <th>DayNum</th>\n",
       "      <th>WTeamID</th>\n",
       "      <th>WScore</th>\n",
       "      <th>LTeamID</th>\n",
       "      <th>LScore</th>\n",
       "      <th>NumOT</th>\n",
       "      <th>WFGM</th>\n",
       "      <th>WFGA</th>\n",
       "      <th>WFGM3</th>\n",
       "      <th>...</th>\n",
       "      <th>LAst</th>\n",
       "      <th>LTO</th>\n",
       "      <th>LStl</th>\n",
       "      <th>LBlk</th>\n",
       "      <th>WFTP</th>\n",
       "      <th>LFTP</th>\n",
       "      <th>WFGP</th>\n",
       "      <th>LFGP</th>\n",
       "      <th>LPoss</th>\n",
       "      <th>WPoss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2003</td>\n",
       "      <td>10</td>\n",
       "      <td>1104</td>\n",
       "      <td>68</td>\n",
       "      <td>1328</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>58</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>0.379310</td>\n",
       "      <td>0.421053</td>\n",
       "      <td>0.317647</td>\n",
       "      <td>0.293333</td>\n",
       "      <td>72.3456</td>\n",
       "      <td>61.9392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>10</td>\n",
       "      <td>1272</td>\n",
       "      <td>70</td>\n",
       "      <td>1393</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>62</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>0.344828</td>\n",
       "      <td>0.310345</td>\n",
       "      <td>0.295455</td>\n",
       "      <td>0.263736</td>\n",
       "      <td>65.6256</td>\n",
       "      <td>60.0192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1266</td>\n",
       "      <td>73</td>\n",
       "      <td>1437</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>58</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0.369565</td>\n",
       "      <td>0.378378</td>\n",
       "      <td>0.292683</td>\n",
       "      <td>0.231579</td>\n",
       "      <td>56.9856</td>\n",
       "      <td>55.2192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1296</td>\n",
       "      <td>56</td>\n",
       "      <td>1457</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>38</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0.354167</td>\n",
       "      <td>0.347826</td>\n",
       "      <td>0.321429</td>\n",
       "      <td>0.268657</td>\n",
       "      <td>50.2656</td>\n",
       "      <td>52.3392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1400</td>\n",
       "      <td>77</td>\n",
       "      <td>1208</td>\n",
       "      <td>71</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>61</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.458333</td>\n",
       "      <td>0.386364</td>\n",
       "      <td>0.329670</td>\n",
       "      <td>0.279070</td>\n",
       "      <td>63.7056</td>\n",
       "      <td>52.3392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2003</td>\n",
       "      <td>11</td>\n",
       "      <td>1458</td>\n",
       "      <td>81</td>\n",
       "      <td>1186</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>57</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.413793</td>\n",
       "      <td>0.313253</td>\n",
       "      <td>0.303030</td>\n",
       "      <td>59.8656</td>\n",
       "      <td>60.0192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1161</td>\n",
       "      <td>80</td>\n",
       "      <td>1236</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>30</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0.450704</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.294872</td>\n",
       "      <td>0.316667</td>\n",
       "      <td>64.6656</td>\n",
       "      <td>62.8992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1186</td>\n",
       "      <td>75</td>\n",
       "      <td>1457</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>62</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.425000</td>\n",
       "      <td>0.311111</td>\n",
       "      <td>0.253165</td>\n",
       "      <td>73.3056</td>\n",
       "      <td>66.7392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1194</td>\n",
       "      <td>71</td>\n",
       "      <td>1156</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>58</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>25</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0.357143</td>\n",
       "      <td>0.307692</td>\n",
       "      <td>0.325581</td>\n",
       "      <td>0.315789</td>\n",
       "      <td>71.3856</td>\n",
       "      <td>64.8192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2003</td>\n",
       "      <td>12</td>\n",
       "      <td>1458</td>\n",
       "      <td>84</td>\n",
       "      <td>1296</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.441176</td>\n",
       "      <td>0.368421</td>\n",
       "      <td>0.323232</td>\n",
       "      <td>0.306667</td>\n",
       "      <td>64.6656</td>\n",
       "      <td>61.9392</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Season  DayNum  WTeamID  WScore  LTeamID  LScore  NumOT  WFGM  WFGA  WFGM3  \\\n",
       "0    2003      10     1104      68     1328      62      0    27    58      3   \n",
       "1    2003      10     1272      70     1393      63      0    26    62      8   \n",
       "2    2003      11     1266      73     1437      61      0    24    58      8   \n",
       "3    2003      11     1296      56     1457      50      0    18    38      3   \n",
       "4    2003      11     1400      77     1208      71      0    30    61      6   \n",
       "5    2003      11     1458      81     1186      55      0    26    57      6   \n",
       "6    2003      12     1161      80     1236      62      0    23    55      2   \n",
       "7    2003      12     1186      75     1457      61      0    28    62      4   \n",
       "8    2003      12     1194      71     1156      66      0    28    58      5   \n",
       "9    2003      12     1458      84     1296      56      0    32    67      5   \n",
       "\n",
       "    ...     LAst  LTO  LStl  LBlk      WFTP      LFTP      WFGP      LFGP  \\\n",
       "0   ...        8   18     9     2  0.379310  0.421053  0.317647  0.293333   \n",
       "1   ...        7   12     8     6  0.344828  0.310345  0.295455  0.263736   \n",
       "2   ...        9   12     2     5  0.369565  0.378378  0.292683  0.231579   \n",
       "3   ...        9   19     4     3  0.354167  0.347826  0.321429  0.268657   \n",
       "4   ...       12   10     7     1  0.458333  0.386364  0.329670  0.279070   \n",
       "5   ...        8   19     4     3  0.460000  0.413793  0.313253  0.303030   \n",
       "6   ...       11   30    10     4  0.450704  0.416667  0.294872  0.316667   \n",
       "7   ...       10   15    14     8  0.416667  0.425000  0.311111  0.253165   \n",
       "8   ...       13   25     8     2  0.357143  0.307692  0.325581  0.315789   \n",
       "9   ...       10   18     1     3  0.441176  0.368421  0.323232  0.306667   \n",
       "\n",
       "     LPoss    WPoss  \n",
       "0  72.3456  61.9392  \n",
       "1  65.6256  60.0192  \n",
       "2  56.9856  55.2192  \n",
       "3  50.2656  52.3392  \n",
       "4  63.7056  52.3392  \n",
       "5  59.8656  60.0192  \n",
       "6  64.6656  62.8992  \n",
       "7  73.3056  66.7392  \n",
       "8  71.3856  64.8192  \n",
       "9  64.6656  61.9392  \n",
       "\n",
       "[10 rows x 37 columns]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data2 = data2.drop('WOR', axis=1)\n",
    "# data2 = data2.drop('WDR', axis=1)\n",
    "# data2 = data2.drop('LOR', axis=1)\n",
    "# data2 = data2.drop('LDR', axis=1)\n",
    "\n",
    "#\n",
    "# Further pre-process by appending columns \n",
    "#\n",
    "WFTP = [] #Winning team Free Throw Percentage\n",
    "WFGP = [] #Winning team Field Goal Percentage\n",
    "LFTP = [] #Losing team Free Throw Percentage\n",
    "LFGP = [] #Losing team Field Goal Percentage\n",
    "\n",
    "# Possession stat formula --  0.96*[(FGA)+(TO)+0.44*(FTA)-(ORB)]\n",
    "LPoss = []\n",
    "WPoss = []\n",
    "\n",
    "# calculate the FG% and FT% and append to dataframe\n",
    "for index, row in data2.iterrows():\n",
    "    WFGMade = row['WFGM']\n",
    "    LFGMade = row['LFGM']\n",
    "    \n",
    "    WTurnOver = row['WTO']\n",
    "    LTurnOver = row['LTO']\n",
    "    \n",
    "    WOffRebound = row['WOR']\n",
    "    LOffRebound = row['LOR']\n",
    "    \n",
    "    WFGAttempt = row['WFGA']\n",
    "    LFGAttempt = row['LFGA']\n",
    "    \n",
    "    # calculate percentages\n",
    "    WFGPercent = (WFGMade/(WFGAttempt+WFGMade))\n",
    "    LFGPercent = (LFGMade/(LFGAttempt+LFGMade))\n",
    "    \n",
    "    \n",
    "    WFGAttempt = float(WFGAttempt)\n",
    "    WTurnOver = float(WTurnOver)\n",
    "    WOffRebound = float(WOffRebound)\n",
    "\n",
    "    LFGAttempt = float(LFGAttempt)\n",
    "    LTurnOver = float(LTurnOver)\n",
    "    LOffRebound = float(LOffRebound)\n",
    "    \n",
    "    ##Very important statistic\n",
    "    WinPoss = (0.96*((WFGAttempt)+(WTurnOver)+0.44*(WFTAttempt)-(WOffRebound)))\n",
    "    LosPoss = (0.96*((LFGAttempt)+(LTurnOver)+0.44*(LFTAttempt)-(LOffRebound)))\n",
    "    \n",
    "    \n",
    "    # append to list\n",
    "    WFGP.append(WFGPercent)\n",
    "    LFGP.append(LFGPercent)\n",
    "    \n",
    "    LPoss.append(LosPoss)\n",
    "    WPoss.append(WinPoss)\n",
    "    \n",
    "for index, row in data2.iterrows():\n",
    "    WFTMade = row['WFTM']\n",
    "    LFTMade = row['LFTM']\n",
    "    WFTAttempt = row['WFTA']\n",
    "    LFTAttempt = row['LFTA']\n",
    "    WFTPercent = (WFTMade/(WFTAttempt+WFTMade))\n",
    "    LFTPercent = (LFTMade/(LFTAttempt+LFTMade))\n",
    "    WFTP.append(WFTPercent)\n",
    "    LFTP.append(LFTPercent)\n",
    "    \n",
    "# Make each list a pandas series \n",
    "LfreethrowPercent = pd.Series(LFTP)\n",
    "WfreethrowPercent = pd.Series(WFTP)\n",
    "\n",
    "LfieldGoalPercent = pd.Series(LFGP)\n",
    "WfieldGoalPercent = pd.Series(WFGP)\n",
    "\n",
    "WinPossession = pd.Series(LPoss)\n",
    "LosPossession = pd.Series(WPoss)\n",
    "\n",
    "# append to dataframe as column\n",
    "data2['WFTP'] = WfreethrowPercent\n",
    "data2['LFTP'] = LfreethrowPercent\n",
    "data2['WFGP'] = WfieldGoalPercent\n",
    "data2['LFGP'] = LfieldGoalPercent\n",
    "\n",
    "data2['LPoss'] = LosPossession\n",
    "data2['WPoss'] = WinPossession\n",
    "\n",
    "data2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "56.9856\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "print(WinPoss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"#df = df[~df['date'].isin(a)]\\nteams = teams[teams['TeamName'].isin(real_teams)]\\n# print((teams))\\nprint(type(teams))\\n#Now we have current season teams\\nprint(len(data2))\\nteam_dict = dict()\\nfor index, team in teams.iterrows():\\n    #print(team.TeamID)\\n    team_dict_list = []\\n    team_ft_list = []\\n    team_fgp_list = []\\n    for index, row2 in data2.iterrows():\\n        if(row2.WTeamID == team.TeamID):\\n            #print(row2.WScore)\\n            team_dict_list.append(row2.WScore - row2.LScore)\\n            \\n            team_ft_list.append('%.3f' % round(row2.WFTP,3))\\n            team_fgp_list.append('%.3f' % round(row2.WFGP,3))\\n        elif(row2.LTeamID == team.TeamID):\\n            team_dict_list.append(row2.LScore - row2.WScore)\\n            team_ft_list.append('%.3f' % round(row2.LFTP,3))\\n            team_fgp_list.append('%.3f' % round(row2.LFGP,3))\\n            #print(row2.WScore)\\n    team_dict[team.TeamName] = {}\\n    team_dict[team.TeamName]['team_points'] = team_dict_list\\n    team_dict[team.TeamName]['team_ft_list'] = team_ft_list\\n    team_dict[team.TeamName]['team_fgp_list'] = team_fgp_list\\n\""
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Remove teams that weren't in LastD1Season as they aren't in the tourney\n",
    "\n",
    "real_teams = ['Alabama', 'Arizona','Arizona St', 'Arkansas', 'Auburn','Bucknell','Buffalo','Butler','CS Fullerton',\n",
    "'Charleston','Cincinnati', 'Clemson','Creighton', 'Davidson','Duke','Florida','Florida St','Georgia St', 'Gonzaga',\n",
    "'Houston','Iona','Kansas', 'Kansas State', 'Kentucky','Lipscomb', 'Long Island', 'Loyola-Chicago', 'Marshall',\n",
    "'Miami FL','Michigan','Michigan St', 'Missouri','Montana','Murray St', \n",
    "'Nevada','New Mexico St','NC Central', 'NC State','North Carolina','Ohio St','Oklahoma',\n",
    "'Penn','Providence', 'Purdue','Radford', 'Rhode Island', 'San Diego St', 'Seton Hall','S Dakota St','St Bonaventure',\n",
    "'SF Austin','Syracuse','TCU','Tennessee','Texas','Texas A&M', 'TX Southern','Texas Tech','UCLA','UMBC', \n",
    "'UNC Greensboro', 'Villanova','Virginia','Virginia Tech', 'West Virginia','Wichita St' ,'Wright St','Xavier'] \n",
    "\n",
    "\n",
    "\"\"\"#df = df[~df['date'].isin(a)]\n",
    "teams = teams[teams['TeamName'].isin(real_teams)]\n",
    "# print((teams))\n",
    "print(type(teams))\n",
    "#Now we have current season teams\n",
    "print(len(data2))\n",
    "team_dict = dict()\n",
    "for index, team in teams.iterrows():\n",
    "    #print(team.TeamID)\n",
    "    team_dict_list = []\n",
    "    team_ft_list = []\n",
    "    team_fgp_list = []\n",
    "    for index, row2 in data2.iterrows():\n",
    "        if(row2.WTeamID == team.TeamID):\n",
    "            #print(row2.WScore)\n",
    "            team_dict_list.append(row2.WScore - row2.LScore)\n",
    "            \n",
    "            team_ft_list.append('%.3f' % round(row2.WFTP,3))\n",
    "            team_fgp_list.append('%.3f' % round(row2.WFGP,3))\n",
    "        elif(row2.LTeamID == team.TeamID):\n",
    "            team_dict_list.append(row2.LScore - row2.WScore)\n",
    "            team_ft_list.append('%.3f' % round(row2.LFTP,3))\n",
    "            team_fgp_list.append('%.3f' % round(row2.LFGP,3))\n",
    "            #print(row2.WScore)\n",
    "    team_dict[team.TeamName] = {}\n",
    "    team_dict[team.TeamName]['team_points'] = team_dict_list\n",
    "    team_dict[team.TeamName]['team_ft_list'] = team_ft_list\n",
    "    team_dict[team.TeamName]['team_fgp_list'] = team_fgp_list\n",
    "\"\"\"    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33\n",
      "34\n"
     ]
    },
    {
     "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>diff_FTP</th>\n",
       "      <th>diff_FGP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Season</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>-0.076225</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.059220</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>-0.024212</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.110507</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.073636</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.036911</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>-0.067857</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.133484</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.040670</td>\n",
       "      <td>-0.010694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        diff_FTP  diff_FGP\n",
       "Season                    \n",
       "2003   -0.076225 -0.010694\n",
       "2003    0.059220 -0.010694\n",
       "2003   -0.024212 -0.010694\n",
       "2003    0.110507 -0.010694\n",
       "2003    0.073636 -0.010694\n",
       "2003    0.036911 -0.010694\n",
       "2003    0.000000 -0.010694\n",
       "2003   -0.067857 -0.010694\n",
       "2003    0.133484 -0.010694\n",
       "2003    0.040670 -0.010694"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#display(data2.head(10))\n",
    "data2.shape\n",
    "\n",
    "winThrow = (data2['WFTP'])\n",
    "loseThrow = (data2['LFTP'])\n",
    "\n",
    "print(data2.columns.get_loc(\"WFGP\"))\n",
    "print(data2.columns.get_loc(\"LFGP\"))\n",
    "\n",
    "\n",
    "\n",
    "diff = pd.DataFrame((data2.iloc[1:,31].values-data2.iloc[:76635,32].values), \n",
    "                            columns=['diff_FTP'], index=data2.iloc[1:,0])\n",
    "\n",
    "diff['diff_FGP'] = pd.DataFrame((data2.iloc[1:,33].values-data2.iloc[:76635,34].values))\n",
    "\n",
    "\n",
    "display(diff.head(10))\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Season\n",
       "2003   -0.076225\n",
       "2003    0.059220\n",
       "2003   -0.024212\n",
       "2003    0.110507\n",
       "2003    0.073636\n",
       "2003    0.036911\n",
       "2003    0.000000\n",
       "2003   -0.067857\n",
       "2003    0.133484\n",
       "2003    0.040670\n",
       "Name: diff_FTP, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAN UH OH\n",
      "count 76762\n",
      "NAN UH OH\n",
      "count 81846\n",
      "NAN UH OH\n",
      "count 85287\n",
      "NAN UH OH\n",
      "count 86196\n",
      "NAN UH OH\n",
      "count 89282\n",
      "NAN UH OH\n",
      "count 90690\n",
      "NAN UH OH\n",
      "count 92272\n",
      "NAN UH OH\n",
      "count 94510\n",
      "NAN UH OH\n",
      "count 94934\n",
      "NAN UH OH\n",
      "count 101577\n",
      "NAN UH OH\n",
      "count 101670\n",
      "NAN UH OH\n",
      "count 103876\n",
      "NAN UH OH\n",
      "count 104070\n",
      "NAN UH OH\n",
      "count 104620\n",
      "NAN UH OH\n",
      "count 104715\n",
      "NAN UH OH\n",
      "count 106629\n",
      "NAN UH OH\n",
      "count 109672\n",
      "NAN UH OH\n",
      "count 110868\n",
      "NAN UH OH\n",
      "count 116631\n",
      "NAN UH OH\n",
      "count 122113\n",
      "NAN UH OH\n",
      "count 126374\n",
      "NAN UH OH\n",
      "count 127796\n",
      "NAN UH OH\n",
      "count 129764\n",
      "NAN UH OH\n",
      "count 132062\n",
      "NAN UH OH\n",
      "count 132153\n",
      "NAN UH OH\n",
      "count 135135\n",
      "NAN UH OH\n",
      "count 141288\n",
      "NAN UH OH\n",
      "count 142321\n",
      "NAN UH OH\n",
      "count 146590\n",
      "NAN UH OH\n",
      "count 149063\n",
      "NAN UH OH\n",
      "count 152958\n",
      "NAN UH OH\n",
      "count 153003\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "Z = diff['diff_FTP']\n",
    "count = 0\n",
    "display(Z.head(10))\n",
    "for a in Z:\n",
    "    count += 1\n",
    "    if(a != a):\n",
    "        a = float(1)\n",
    "        #print(\"NAN UH OH\")\n",
    "        #print(\"count\", count)\n",
    "for a in Z:\n",
    "    count += 1\n",
    "    if(a != a):\n",
    "        #a = float(1)\n",
    "        #print(\"NAN UH OH\")\n",
    "        #print(\"count\", count)    \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(76630, 5)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(153260, 1)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "Z = Z.fillna(0)\n",
    "\n",
    "from numpy.linalg import inv\n",
    "    \n",
    "Z2 = diff['diff_FGP']\n",
    "for nan in Z:\n",
    "    if(nan == 'NaN'):\n",
    "        nan = 0\n",
    "\n",
    "columnNames = ['lag5','lag4','lag3','lag2','lag1']\n",
    "X = pd.DataFrame(np.column_stack((Z[:-5],Z[1:-4],Z[2:-3],Z[3:-2],Z[4:-1])\n",
    "                                ),columns = columnNames)\n",
    "iX = pd.DataFrame(np.column_stack((Z[:-5],Z[1:-4],Z[2:-3],Z[3:-2],Z[4:-1])\n",
    "                                ),columns = columnNames)\n",
    "\n",
    "print(X.shape)\n",
    "\n",
    "### We're going to make the win out comes list\n",
    "### To test for the negative cases we are inversing the data and denoting the losses with a zero for our model\n",
    "win_count = 0\n",
    "win_list = []\n",
    "lose_list = []\n",
    "while win_count < 76630:\n",
    "    win_list.append(1)\n",
    "    lose_list.append(0)\n",
    "    win_count+=1\n",
    "\n",
    "#print(win_count)\n",
    "#print(win_list)\n",
    "\n",
    "\n",
    "wins = pd.DataFrame(win_list, columns = ['Win'])\n",
    "loss =  pd.DataFrame(lose_list, columns = ['Win'])\n",
    "\n",
    "\n",
    "\n",
    "for index, row in iX.iterrows():\n",
    "    iX.set_value(index,'lag5',-row[0])\n",
    "\n",
    "#All training data along with inverse Vector differences for losing game scenarios\n",
    "trainGames = X.append(iX)\n",
    "results = wins.append(loss)\n",
    "display(results.shape)\n",
    "\n",
    "X = trainGames\n",
    "y = results\n",
    "\n",
    "\n",
    "#display(trainGames.shape)\n",
    "    \n",
    "\n",
    "#display(wins.head(5))\n",
    "#print(wins.shape)\n",
    "#display(X.head(5))\n",
    "#display(iX.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "np.random.seed(1)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.333333)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Root mean squared error = 0.4885\n",
      "R-squared = 0.0455\n"
     ]
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Fit regression model to the training set\n",
    "regr.fit(X_train, y_train)\n",
    "\n",
    "# Apply model to the test set\n",
    "y_pred = regr.predict(X_test)\n",
    "\n",
    "# Model evaluation\n",
    "print(\"Root mean squared error = %.4f\" % np.sqrt(mean_squared_error(y_test, y_pred)))\n",
    "print('R-squared = %.4f' % r2_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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