Tennis Player.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Year</th>\n",
       "      <th>FirstServe</th>\n",
       "      <th>FirstServePointsWon</th>\n",
       "      <th>FirstServeReturnPointsWon</th>\n",
       "      <th>SecondServePointsWon</th>\n",
       "      <th>SecondServeReturnPointsWon</th>\n",
       "      <th>Aces</th>\n",
       "      <th>BreakPointsConverted</th>\n",
       "      <th>BreakPointsFaced</th>\n",
       "      <th>...</th>\n",
       "      <th>ReturnGamesWon</th>\n",
       "      <th>ReturnPointsWon</th>\n",
       "      <th>ServiceGamesPlayed</th>\n",
       "      <th>ServiceGamesWon</th>\n",
       "      <th>TotalPointsWon</th>\n",
       "      <th>TotalServicePointsWon</th>\n",
       "      <th>Wins</th>\n",
       "      <th>Losses</th>\n",
       "      <th>Winnings</th>\n",
       "      <th>Ranking</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Pedro Sousa</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0</td>\n",
       "      <td>0.14</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.38</td>\n",
       "      <td>8</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>39820</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Roman Safiullin</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.07</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>9</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>17334</td>\n",
       "      <td>381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Pedro Sousa</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.44</td>\n",
       "      <td>2</td>\n",
       "      <td>0.38</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.34</td>\n",
       "      <td>17</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.59</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>109827</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rogerio Dutra Silva</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.33</td>\n",
       "      <td>2</td>\n",
       "      <td>0.33</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.34</td>\n",
       "      <td>15</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9761</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Daniel Gimeno-Traver</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>32879</td>\n",
       "      <td>272</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Player  Year  FirstServe  FirstServePointsWon  \\\n",
       "0           Pedro Sousa  2016        0.88                 0.50   \n",
       "1       Roman Safiullin  2017        0.84                 0.62   \n",
       "2           Pedro Sousa  2017        0.83                 0.60   \n",
       "3   Rogerio Dutra Silva  2010        0.83                 0.64   \n",
       "4  Daniel Gimeno-Traver  2017        0.81                 0.54   \n",
       "\n",
       "   FirstServeReturnPointsWon  SecondServePointsWon  \\\n",
       "0                       0.38                  0.50   \n",
       "1                       0.26                  0.33   \n",
       "2                       0.28                  0.53   \n",
       "3                       0.34                  0.59   \n",
       "4                       0.00                  0.33   \n",
       "\n",
       "   SecondServeReturnPointsWon  Aces  BreakPointsConverted  BreakPointsFaced  \\\n",
       "0                        0.39     0                  0.14                 7   \n",
       "1                        0.07     7                  0.00                 7   \n",
       "2                        0.44     2                  0.38                10   \n",
       "3                        0.33     2                  0.33                 5   \n",
       "4                        0.33     1                  0.00                 2   \n",
       "\n",
       "   ...  ReturnGamesWon  ReturnPointsWon  ServiceGamesPlayed  ServiceGamesWon  \\\n",
       "0  ...            0.11             0.38                   8             0.50   \n",
       "1  ...            0.00             0.20                   9             0.67   \n",
       "2  ...            0.16             0.34                  17             0.65   \n",
       "3  ...            0.14             0.34                  15             0.80   \n",
       "4  ...            0.00             0.20                   2             0.50   \n",
       "\n",
       "   TotalPointsWon  TotalServicePointsWon  Wins  Losses  Winnings  Ranking  \n",
       "0            0.43                   0.50     1       2     39820      119  \n",
       "1            0.41                   0.57     0       1     17334      381  \n",
       "2            0.45                   0.59     4       1    109827      119  \n",
       "3            0.49                   0.63     0       0      9761      125  \n",
       "4            0.35                   0.50     0       1     32879      272  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('tennis_stats.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>FirstServe</th>\n",
       "      <th>FirstServePointsWon</th>\n",
       "      <th>FirstServeReturnPointsWon</th>\n",
       "      <th>SecondServePointsWon</th>\n",
       "      <th>SecondServeReturnPointsWon</th>\n",
       "      <th>Aces</th>\n",
       "      <th>BreakPointsConverted</th>\n",
       "      <th>BreakPointsFaced</th>\n",
       "      <th>BreakPointsOpportunities</th>\n",
       "      <th>...</th>\n",
       "      <th>ReturnGamesWon</th>\n",
       "      <th>ReturnPointsWon</th>\n",
       "      <th>ServiceGamesPlayed</th>\n",
       "      <th>ServiceGamesWon</th>\n",
       "      <th>TotalPointsWon</th>\n",
       "      <th>TotalServicePointsWon</th>\n",
       "      <th>Wins</th>\n",
       "      <th>Losses</th>\n",
       "      <th>Winnings</th>\n",
       "      <th>Ranking</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1721.000000</td>\n",
       "      <td>1.721000e+03</td>\n",
       "      <td>1721.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2013.646717</td>\n",
       "      <td>0.598053</td>\n",
       "      <td>0.680738</td>\n",
       "      <td>0.261673</td>\n",
       "      <td>0.479733</td>\n",
       "      <td>0.466432</td>\n",
       "      <td>97.105171</td>\n",
       "      <td>0.369407</td>\n",
       "      <td>112.003486</td>\n",
       "      <td>102.918071</td>\n",
       "      <td>...</td>\n",
       "      <td>0.173823</td>\n",
       "      <td>0.342208</td>\n",
       "      <td>197.650203</td>\n",
       "      <td>0.715590</td>\n",
       "      <td>0.473155</td>\n",
       "      <td>0.599245</td>\n",
       "      <td>7.876816</td>\n",
       "      <td>9.278908</td>\n",
       "      <td>2.344928e+05</td>\n",
       "      <td>269.610691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.488018</td>\n",
       "      <td>0.054533</td>\n",
       "      <td>0.070422</td>\n",
       "      <td>0.056639</td>\n",
       "      <td>0.066902</td>\n",
       "      <td>0.068447</td>\n",
       "      <td>137.966077</td>\n",
       "      <td>0.162987</td>\n",
       "      <td>119.247651</td>\n",
       "      <td>122.761670</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080880</td>\n",
       "      <td>0.049369</td>\n",
       "      <td>221.208703</td>\n",
       "      <td>0.123287</td>\n",
       "      <td>0.037139</td>\n",
       "      <td>0.057718</td>\n",
       "      <td>10.183716</td>\n",
       "      <td>8.996450</td>\n",
       "      <td>2.530537e+05</td>\n",
       "      <td>277.341947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2009.000000</td>\n",
       "      <td>0.360000</td>\n",
       "      <td>0.270000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.080000e+02</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>0.570000</td>\n",
       "      <td>0.650000</td>\n",
       "      <td>0.240000</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.440000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.130000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.670000</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.570000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.931100e+04</td>\n",
       "      <td>83.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2014.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.690000</td>\n",
       "      <td>0.270000</td>\n",
       "      <td>0.490000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.380000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.180000</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.610000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.252120e+05</td>\n",
       "      <td>166.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>0.720000</td>\n",
       "      <td>0.290000</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>0.430000</td>\n",
       "      <td>201.000000</td>\n",
       "      <td>172.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>0.370000</td>\n",
       "      <td>348.000000</td>\n",
       "      <td>0.790000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>3.500750e+05</td>\n",
       "      <td>333.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>0.880000</td>\n",
       "      <td>0.890000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>1185.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>507.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.560000</td>\n",
       "      <td>0.510000</td>\n",
       "      <td>916.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.820000</td>\n",
       "      <td>0.820000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>1.074562e+06</td>\n",
       "      <td>1443.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year   FirstServe  FirstServePointsWon  \\\n",
       "count  1721.000000  1721.000000          1721.000000   \n",
       "mean   2013.646717     0.598053             0.680738   \n",
       "std       2.488018     0.054533             0.070422   \n",
       "min    2009.000000     0.360000             0.270000   \n",
       "25%    2012.000000     0.570000             0.650000   \n",
       "50%    2014.000000     0.600000             0.690000   \n",
       "75%    2016.000000     0.630000             0.720000   \n",
       "max    2017.000000     0.880000             0.890000   \n",
       "\n",
       "       FirstServeReturnPointsWon  SecondServePointsWon  \\\n",
       "count                1721.000000           1721.000000   \n",
       "mean                    0.261673              0.479733   \n",
       "std                     0.056639              0.066902   \n",
       "min                     0.000000              0.060000   \n",
       "25%                     0.240000              0.460000   \n",
       "50%                     0.270000              0.490000   \n",
       "75%                     0.290000              0.520000   \n",
       "max                     0.480000              0.920000   \n",
       "\n",
       "       SecondServeReturnPointsWon         Aces  BreakPointsConverted  \\\n",
       "count                 1721.000000  1721.000000           1721.000000   \n",
       "mean                     0.466432    97.105171              0.369407   \n",
       "std                      0.068447   137.966077              0.162987   \n",
       "min                      0.000000     0.000000              0.000000   \n",
       "25%                      0.440000     7.000000              0.320000   \n",
       "50%                      0.480000    34.000000              0.380000   \n",
       "75%                      0.500000   140.000000              0.430000   \n",
       "max                      0.750000  1185.000000              1.000000   \n",
       "\n",
       "       BreakPointsFaced  BreakPointsOpportunities  ...  ReturnGamesWon  \\\n",
       "count       1721.000000               1721.000000  ...     1721.000000   \n",
       "mean         112.003486                102.918071  ...        0.173823   \n",
       "std          119.247651                122.761670  ...        0.080880   \n",
       "min            1.000000                  0.000000  ...        0.000000   \n",
       "25%           15.000000                  9.000000  ...        0.130000   \n",
       "50%           55.000000                 41.000000  ...        0.180000   \n",
       "75%          201.000000                172.000000  ...        0.220000   \n",
       "max          507.000000                573.000000  ...        0.560000   \n",
       "\n",
       "       ReturnPointsWon  ServiceGamesPlayed  ServiceGamesWon  TotalPointsWon  \\\n",
       "count      1721.000000         1721.000000      1721.000000     1721.000000   \n",
       "mean          0.342208          197.650203         0.715590        0.473155   \n",
       "std           0.049369          221.208703         0.123287        0.037139   \n",
       "min           0.000000            0.000000         0.000000        0.220000   \n",
       "25%           0.320000           22.000000         0.670000        0.460000   \n",
       "50%           0.350000           86.000000         0.750000        0.480000   \n",
       "75%           0.370000          348.000000         0.790000        0.500000   \n",
       "max           0.510000          916.000000         1.000000        0.820000   \n",
       "\n",
       "       TotalServicePointsWon         Wins       Losses      Winnings  \\\n",
       "count            1721.000000  1721.000000  1721.000000  1.721000e+03   \n",
       "mean                0.599245     7.876816     9.278908  2.344928e+05   \n",
       "std                 0.057718    10.183716     8.996450  2.530537e+05   \n",
       "min                 0.250000     0.000000     0.000000  1.080000e+02   \n",
       "25%                 0.570000     0.000000     2.000000  4.931100e+04   \n",
       "50%                 0.610000     3.000000     5.000000  1.252120e+05   \n",
       "75%                 0.630000    13.000000    17.000000  3.500750e+05   \n",
       "max                 0.820000    48.000000    36.000000  1.074562e+06   \n",
       "\n",
       "           Ranking  \n",
       "count  1721.000000  \n",
       "mean    269.610691  \n",
       "std     277.341947  \n",
       "min       3.000000  \n",
       "25%      83.000000  \n",
       "50%     166.000000  \n",
       "75%     333.000000  \n",
       "max    1443.000000  \n",
       "\n",
       "[8 rows x 23 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Player', 'Year', 'FirstServe', 'FirstServePointsWon',\n",
       "       'FirstServeReturnPointsWon', 'SecondServePointsWon',\n",
       "       'SecondServeReturnPointsWon', 'Aces', 'BreakPointsConverted',\n",
       "       'BreakPointsFaced', 'BreakPointsOpportunities', 'BreakPointsSaved',\n",
       "       'DoubleFaults', 'ReturnGamesPlayed', 'ReturnGamesWon',\n",
       "       'ReturnPointsWon', 'ServiceGamesPlayed', 'ServiceGamesWon',\n",
       "       'TotalPointsWon', 'TotalServicePointsWon', 'Wins', 'Losses', 'Winnings',\n",
       "       'Ranking'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1721 entries, 0 to 1720\n",
      "Data columns (total 24 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   Player                      1721 non-null   object \n",
      " 1   Year                        1721 non-null   int64  \n",
      " 2   FirstServe                  1721 non-null   float64\n",
      " 3   FirstServePointsWon         1721 non-null   float64\n",
      " 4   FirstServeReturnPointsWon   1721 non-null   float64\n",
      " 5   SecondServePointsWon        1721 non-null   float64\n",
      " 6   SecondServeReturnPointsWon  1721 non-null   float64\n",
      " 7   Aces                        1721 non-null   int64  \n",
      " 8   BreakPointsConverted        1721 non-null   float64\n",
      " 9   BreakPointsFaced            1721 non-null   int64  \n",
      " 10  BreakPointsOpportunities    1721 non-null   int64  \n",
      " 11  BreakPointsSaved            1721 non-null   float64\n",
      " 12  DoubleFaults                1721 non-null   int64  \n",
      " 13  ReturnGamesPlayed           1721 non-null   int64  \n",
      " 14  ReturnGamesWon              1721 non-null   float64\n",
      " 15  ReturnPointsWon             1721 non-null   float64\n",
      " 16  ServiceGamesPlayed          1721 non-null   int64  \n",
      " 17  ServiceGamesWon             1721 non-null   float64\n",
      " 18  TotalPointsWon              1721 non-null   float64\n",
      " 19  TotalServicePointsWon       1721 non-null   float64\n",
      " 20  Wins                        1721 non-null   int64  \n",
      " 21  Losses                      1721 non-null   int64  \n",
      " 22  Winnings                    1721 non-null   int64  \n",
      " 23  Ranking                     1721 non-null   int64  \n",
      "dtypes: float64(12), int64(11), object(1)\n",
      "memory usage: 322.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1721, 24)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                Year  FirstServe  FirstServePointsWon  \\\n",
      "Year                        1.000000    0.051406            -0.016728   \n",
      "FirstServe                  0.051406    1.000000            -0.070659   \n",
      "FirstServePointsWon        -0.016728   -0.070659             1.000000   \n",
      "FirstServeReturnPointsWon  -0.106784    0.025488             0.021729   \n",
      "SecondServePointsWon        0.005300    0.101417             0.320765   \n",
      "SecondServeReturnPointsWon -0.039087   -0.001924            -0.004724   \n",
      "Aces                       -0.108367    0.048149             0.460323   \n",
      "BreakPointsConverted       -0.072404   -0.018877            -0.041538   \n",
      "BreakPointsFaced           -0.101735    0.057709             0.301925   \n",
      "BreakPointsOpportunities   -0.114806    0.062345             0.324853   \n",
      "BreakPointsSaved           -0.006154    0.087945             0.405751   \n",
      "DoubleFaults               -0.071885   -0.005477             0.373321   \n",
      "ReturnGamesPlayed          -0.108405    0.071776             0.375465   \n",
      "ReturnGamesWon             -0.073256   -0.010676            -0.010193   \n",
      "ReturnPointsWon            -0.078229    0.004189            -0.002793   \n",
      "ServiceGamesPlayed         -0.108477    0.071920             0.376460   \n",
      "ServiceGamesWon            -0.008930    0.137473             0.817829   \n",
      "TotalPointsWon             -0.041790    0.148349             0.648753   \n",
      "TotalServicePointsWon      -0.005544    0.180996             0.860033   \n",
      "Wins                       -0.108235    0.064832             0.356702   \n",
      "Losses                     -0.077181    0.053736             0.330581   \n",
      "Winnings                    0.043908    0.057882             0.361121   \n",
      "Ranking                    -0.040483   -0.068759            -0.150004   \n",
      "\n",
      "                            FirstServeReturnPointsWon  SecondServePointsWon  \\\n",
      "Year                                        -0.106784              0.005300   \n",
      "FirstServe                                   0.025488              0.101417   \n",
      "FirstServePointsWon                          0.021729              0.320765   \n",
      "FirstServeReturnPointsWon                    1.000000              0.072707   \n",
      "SecondServePointsWon                         0.072707              1.000000   \n",
      "SecondServeReturnPointsWon                   0.301265              0.103584   \n",
      "Aces                                         0.140165              0.266269   \n",
      "BreakPointsConverted                         0.324057              0.052755   \n",
      "BreakPointsFaced                             0.295724              0.258691   \n",
      "BreakPointsOpportunities                     0.313338              0.277782   \n",
      "BreakPointsSaved                             0.048347              0.340147   \n",
      "DoubleFaults                                 0.244592              0.235941   \n",
      "ReturnGamesPlayed                            0.261871              0.296480   \n",
      "ReturnGamesWon                               0.757435              0.096622   \n",
      "ReturnPointsWon                              0.834267              0.095585   \n",
      "ServiceGamesPlayed                           0.261206              0.296809   \n",
      "ServiceGamesWon                              0.091319              0.650764   \n",
      "TotalPointsWon                               0.496682              0.622673   \n",
      "TotalServicePointsWon                        0.052335              0.713076   \n",
      "Wins                                         0.256029              0.268979   \n",
      "Losses                                       0.243278              0.250918   \n",
      "Winnings                                     0.240808              0.281215   \n",
      "Ranking                                     -0.178664             -0.181013   \n",
      "\n",
      "                            SecondServeReturnPointsWon      Aces  \\\n",
      "Year                                         -0.039087 -0.108367   \n",
      "FirstServe                                   -0.001924  0.048149   \n",
      "FirstServePointsWon                          -0.004724  0.460323   \n",
      "FirstServeReturnPointsWon                     0.301265  0.140165   \n",
      "SecondServePointsWon                          0.103584  0.266269   \n",
      "SecondServeReturnPointsWon                    1.000000  0.095494   \n",
      "Aces                                          0.095494  1.000000   \n",
      "BreakPointsConverted                          0.264413  0.037188   \n",
      "BreakPointsFaced                              0.234212  0.757405   \n",
      "BreakPointsOpportunities                      0.249583  0.784934   \n",
      "BreakPointsSaved                              0.073867  0.282672   \n",
      "DoubleFaults                                  0.193233  0.819031   \n",
      "ReturnGamesPlayed                             0.209937  0.863648   \n",
      "ReturnGamesWon                                0.603755  0.139987   \n",
      "ReturnPointsWon                               0.727338  0.138023   \n",
      "ServiceGamesPlayed                            0.209521  0.866138   \n",
      "ServiceGamesWon                               0.096553  0.440922   \n",
      "TotalPointsWon                                0.408975  0.428679   \n",
      "TotalServicePointsWon                         0.055004  0.472101   \n",
      "Wins                                          0.193093  0.825301   \n",
      "Losses                                        0.185217  0.768628   \n",
      "Winnings                                      0.199401  0.798404   \n",
      "Ranking                                      -0.159592 -0.277811   \n",
      "\n",
      "                            BreakPointsConverted  BreakPointsFaced  \\\n",
      "Year                                   -0.072404         -0.101735   \n",
      "FirstServe                             -0.018877          0.057709   \n",
      "FirstServePointsWon                    -0.041538          0.301925   \n",
      "FirstServeReturnPointsWon               0.324057          0.295724   \n",
      "SecondServePointsWon                    0.052755          0.258691   \n",
      "SecondServeReturnPointsWon              0.264413          0.234212   \n",
      "Aces                                    0.037188          0.757405   \n",
      "BreakPointsConverted                    1.000000          0.096368   \n",
      "BreakPointsFaced                        0.096368          1.000000   \n",
      "BreakPointsOpportunities                0.086502          0.973352   \n",
      "BreakPointsSaved                       -0.015956          0.271783   \n",
      "DoubleFaults                            0.075320          0.917645   \n",
      "ReturnGamesPlayed                       0.083155          0.972449   \n",
      "ReturnGamesWon                          0.561759          0.335205   \n",
      "ReturnPointsWon                         0.387170          0.331043   \n",
      "ServiceGamesPlayed                      0.083182          0.971296   \n",
      "ServiceGamesWon                        -0.025670          0.354012   \n",
      "TotalPointsWon                          0.255050          0.463110   \n",
      "TotalServicePointsWon                  -0.007254          0.354005   \n",
      "Wins                                    0.076989          0.883470   \n",
      "Losses                                  0.062297          0.943309   \n",
      "Winnings                                0.075022          0.876036   \n",
      "Ranking                                -0.051005         -0.322082   \n",
      "\n",
      "                            BreakPointsOpportunities  ...  ReturnGamesWon  \\\n",
      "Year                                       -0.114806  ...       -0.073256   \n",
      "FirstServe                                  0.062345  ...       -0.010676   \n",
      "FirstServePointsWon                         0.324853  ...       -0.010193   \n",
      "FirstServeReturnPointsWon                   0.313338  ...        0.757435   \n",
      "SecondServePointsWon                        0.277782  ...        0.096622   \n",
      "SecondServeReturnPointsWon                  0.249583  ...        0.603755   \n",
      "Aces                                        0.784934  ...        0.139987   \n",
      "BreakPointsConverted                        0.086502  ...        0.561759   \n",
      "BreakPointsFaced                            0.973352  ...        0.335205   \n",
      "BreakPointsOpportunities                    1.000000  ...        0.358483   \n",
      "BreakPointsSaved                            0.247996  ...        0.046127   \n",
      "DoubleFaults                                0.906391  ...        0.274225   \n",
      "ReturnGamesPlayed                           0.978824  ...        0.294470   \n",
      "ReturnGamesWon                              0.358483  ...        1.000000   \n",
      "ReturnPointsWon                             0.352783  ...        0.872216   \n",
      "ServiceGamesPlayed                          0.978278  ...        0.293995   \n",
      "ServiceGamesWon                             0.372271  ...        0.057315   \n",
      "TotalPointsWon                              0.491198  ...        0.549022   \n",
      "TotalServicePointsWon                       0.380716  ...        0.037907   \n",
      "Wins                                        0.923453  ...        0.292920   \n",
      "Losses                                      0.909295  ...        0.263472   \n",
      "Winnings                                    0.900444  ...        0.279645   \n",
      "Ranking                                    -0.334548  ...       -0.191280   \n",
      "\n",
      "                            ReturnPointsWon  ServiceGamesPlayed  \\\n",
      "Year                              -0.078229           -0.108477   \n",
      "FirstServe                         0.004189            0.071920   \n",
      "FirstServePointsWon               -0.002793            0.376460   \n",
      "FirstServeReturnPointsWon          0.834267            0.261206   \n",
      "SecondServePointsWon               0.095585            0.296809   \n",
      "SecondServeReturnPointsWon         0.727338            0.209521   \n",
      "Aces                               0.138023            0.866138   \n",
      "BreakPointsConverted               0.387170            0.083182   \n",
      "BreakPointsFaced                   0.331043            0.971296   \n",
      "BreakPointsOpportunities           0.352783            0.978278   \n",
      "BreakPointsSaved                   0.054317            0.274677   \n",
      "DoubleFaults                       0.271299            0.925879   \n",
      "ReturnGamesPlayed                  0.291782            0.999842   \n",
      "ReturnGamesWon                     0.872216            0.293995   \n",
      "ReturnPointsWon                    1.000000            0.291102   \n",
      "ServiceGamesPlayed                 0.291102            1.000000   \n",
      "ServiceGamesWon                    0.096023            0.418467   \n",
      "TotalPointsWon                     0.565603            0.488998   \n",
      "TotalServicePointsWon              0.047758            0.429605   \n",
      "Wins                               0.280240            0.929153   \n",
      "Losses                             0.265271            0.935182   \n",
      "Winnings                           0.271646            0.912985   \n",
      "Ranking                           -0.202597           -0.331738   \n",
      "\n",
      "                            ServiceGamesWon  TotalPointsWon  \\\n",
      "Year                              -0.008930       -0.041790   \n",
      "FirstServe                         0.137473        0.148349   \n",
      "FirstServePointsWon                0.817829        0.648753   \n",
      "FirstServeReturnPointsWon          0.091319        0.496682   \n",
      "SecondServePointsWon               0.650764        0.622673   \n",
      "SecondServeReturnPointsWon         0.096553        0.408975   \n",
      "Aces                               0.440922        0.428679   \n",
      "BreakPointsConverted              -0.025670        0.255050   \n",
      "BreakPointsFaced                   0.354012        0.463110   \n",
      "BreakPointsOpportunities           0.372271        0.491198   \n",
      "BreakPointsSaved                   0.518091        0.464380   \n",
      "DoubleFaults                       0.378686        0.446670   \n",
      "ReturnGamesPlayed                  0.417825        0.488351   \n",
      "ReturnGamesWon                     0.057315        0.549022   \n",
      "ReturnPointsWon                    0.096023        0.565603   \n",
      "ServiceGamesPlayed                 0.418467        0.488998   \n",
      "ServiceGamesWon                    1.000000        0.727091   \n",
      "TotalPointsWon                     0.727091        1.000000   \n",
      "TotalServicePointsWon              0.934764        0.791356   \n",
      "Wins                               0.385040        0.459368   \n",
      "Losses                             0.367345        0.428543   \n",
      "Winnings                           0.395577        0.461061   \n",
      "Ranking                           -0.198822       -0.272007   \n",
      "\n",
      "                            TotalServicePointsWon      Wins    Losses  \\\n",
      "Year                                    -0.005544 -0.108235 -0.077181   \n",
      "FirstServe                               0.180996  0.064832  0.053736   \n",
      "FirstServePointsWon                      0.860033  0.356702  0.330581   \n",
      "FirstServeReturnPointsWon                0.052335  0.256029  0.243278   \n",
      "SecondServePointsWon                     0.713076  0.268979  0.250918   \n",
      "SecondServeReturnPointsWon               0.055004  0.193093  0.185217   \n",
      "Aces                                     0.472101  0.825301  0.768628   \n",
      "BreakPointsConverted                    -0.007254  0.076989  0.062297   \n",
      "BreakPointsFaced                         0.354005  0.883470  0.943309   \n",
      "BreakPointsOpportunities                 0.380716  0.923453  0.909295   \n",
      "BreakPointsSaved                         0.476143  0.252053  0.246990   \n",
      "DoubleFaults                             0.383379  0.847459  0.881922   \n",
      "ReturnGamesPlayed                        0.428759  0.928408  0.936755   \n",
      "ReturnGamesWon                           0.037907  0.292920  0.263472   \n",
      "ReturnPointsWon                          0.047758  0.280240  0.265271   \n",
      "ServiceGamesPlayed                       0.429605  0.929153  0.935182   \n",
      "ServiceGamesWon                          0.934764  0.385040  0.367345   \n",
      "TotalPointsWon                           0.791356  0.459368  0.428543   \n",
      "TotalServicePointsWon                    1.000000  0.399270  0.371283   \n",
      "Wins                                     0.399270  1.000000  0.878732   \n",
      "Losses                                   0.371283  0.878732  1.000000   \n",
      "Winnings                                 0.407707  0.913297  0.869277   \n",
      "Ranking                                 -0.208355 -0.287018 -0.300614   \n",
      "\n",
      "                            Winnings   Ranking  \n",
      "Year                        0.043908 -0.040483  \n",
      "FirstServe                  0.057882 -0.068759  \n",
      "FirstServePointsWon         0.361121 -0.150004  \n",
      "FirstServeReturnPointsWon   0.240808 -0.178664  \n",
      "SecondServePointsWon        0.281215 -0.181013  \n",
      "SecondServeReturnPointsWon  0.199401 -0.159592  \n",
      "Aces                        0.798404 -0.277811  \n",
      "BreakPointsConverted        0.075022 -0.051005  \n",
      "BreakPointsFaced            0.876036 -0.322082  \n",
      "BreakPointsOpportunities    0.900444 -0.334548  \n",
      "BreakPointsSaved            0.258271 -0.121220  \n",
      "DoubleFaults                0.854685 -0.305866  \n",
      "ReturnGamesPlayed           0.912613 -0.331478  \n",
      "ReturnGamesWon              0.279645 -0.191280  \n",
      "ReturnPointsWon             0.271646 -0.202597  \n",
      "ServiceGamesPlayed          0.912985 -0.331738  \n",
      "ServiceGamesWon             0.395577 -0.198822  \n",
      "TotalPointsWon              0.461061 -0.272007  \n",
      "TotalServicePointsWon       0.407707 -0.208355  \n",
      "Wins                        0.913297 -0.287018  \n",
      "Losses                      0.869277 -0.300614  \n",
      "Winnings                    1.000000 -0.359835  \n",
      "Ranking                    -0.359835  1.000000  \n",
      "\n",
      "[23 rows x 23 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['FirstServeReturnPointsWon'],df['Winnings'])\n",
    "plt.title('FirstServeReturnPointsWon vs Winnings')\n",
    "plt.xlabel('FirstServeReturnPointsWon')\n",
    "plt.ylabel('Winnings')\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['Year'],df['Aces'])\n",
    "plt.title('Year vs Aces')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Aces')\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['Year'],df['Winnings'])\n",
    "plt.title('Year vs Winnings')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Winnings')\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['Ranking'],df['Wins'])\n",
    "plt.title('Ranking vs Wins')\n",
    "plt.xlabel('Ranking')\n",
    "plt.ylabel('Wins')\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['FirstServeReturnPointsWon'],df['Winnings'])\n",
    "plt.title('FirstServeReturnPointsWon vs Winnings')\n",
    "plt.xlabel('FirstServeReturnPointsWon')\n",
    "plt.ylabel('Winnings')\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.05496237254314872\n",
      "0.06392361682772452\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['FirstServeReturnPointsWon']]\n",
    "winnings = df['Winnings']\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('FirstServeReturnPointsWon vs Winnings')\n",
    "plt.xlabel('Winnings')\n",
    "plt.ylabel('FirstServeReturnPointsWon')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.01083475000817613\n",
      "0.01350307359043601\n"
     ]
    },
    {
     "data": {
      "image/png": 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9Q8NAUEPJF6tMFiq89kX9DqMKmklmKzUyXoL2tEel5jNbqTrvu0h7CWZKVXwf4jHF94OD8Lk5D64smEgPsui+Q50tHh2pOPnKuRFNbV78vEmtLiRi8E/fGyFXDJowk4k4T56c4g0/MuAsJpFw1XIRVIOaShx1/iEOXt7FPY+fouYzf0Csqg0/ILakUqfRqSKX97SyuffcEiO+up/Mt6WvjVsGN7L38DinwtFfr31Rv/NT4/oo2VSCGlCp1YjFhGwqseTM3tW0oTMdzAqvVClVFS8udLak2NDp9si76sON27o5fGaWqfCg5cZt3VTcVqAAIZmM0yIyPwTb9eoDAEfP5DkxWQzm83jBkPUTkxWOnnE3QCWdiDEb/n9iCD5KueKTTridUn/sbIEt3S08eiJHvlSlLZXgpRuyDT8gtqRSp7lmpuyCeQNRaGaCILG4TiKLtSQTbOltJVeqzQ/5zKbixB2359x4ZS/lJ09TrqWo+T7xWIxkPCh3qT8cubdry7mO5lyhQneb66+qMlOqzS//42tw3/UAlcdHpunIeMyWq0wWlGRc6Mh4PD4y7SymTd0t1PxZilWfSpiAOzIemxwP8X/48BkeOzlNaypBb1uSQsXnsZPTJOIx3rHrioa9jvtDjYvM7m09HJ+Y4YEfnOaex0d44AenOT4xw25bAnxJOzd1UvWDoZ/Xrssy0JGh6tPwdtx6vWnnBjpbPCZmS5zKFZmYLdHZ4vGmnRucxrV7Ww+ThQq5cMRcrlBhslBxvn8FQ8DDhrgFndCuh4bPlKrMlCr4GgwT9xVmShVmHMZ147ZeWsI1gGrhkOuWZJwbHX+GR8dnAWW2XONUrsRsOTgoCMobx/Xhz0VpbqighKs3uu50nnN0LM/ew+Pzkx93b+txXnN5084NjOZKTMyUmSpUSCZibO5tdf7jPTwxy+npMtl0gmwqAQKnp8vOV0+OajNmsRasi+b7Qrnmk4zHiMUUx3NFScXjnCmXzptr4ftKV4u7ZVo2dKTJlap4cSEZj6NArlRlg+PWjFKlxnSxSsqL48WFSs2nVKnNJ8BGsaRSp72Hx9nc08pLNp470s4VKuw9PO70iz83+bEz47EubKLbMzTMLYMbnf9I/uIrt0Yu2UV19eSo6m5JcDpXoz3jkYgHnbwzpQrdLW6Xj0nEdL5DfG7NO0SCcke++fQ4PS0eo/ky5YpP0ovR35bkm0+P89YbGtfMVK+UFyfjxShUa+RLQT9ixouRbHBfjyWVOkV1PsjCyY/A/LXrZAfR7OsZmSqwofP8WerZTIKTk24/x6geHNy4rZf7D40Fo/fKPl5c6GhJOm/SIRanp9WjWPEp14I+lbQXg5i7TvGDJycZn6mQTsRpTyao+MpYvoyedLvqxmVtHkfGZuZn91drSq6q7Bho7IGBJZU6RbWjPqrJLqoGOjLkCtXzaiq5QtXp8h4Q3YODm3duYHS6xPhMeX7ARU9rkpsdN2N2tySYmi3NL3vva9CP4bIGNVsOTg1QrvoUfCUeriQx43jyo4qQjAvF6rlFVNMJQRs8EblpHfUisklE7heRgyLyuIi8JyzvFpF7ReSp8LorLL9WRB4UkZKIvG/BdtIi8rCIPBpu53eXeb2fFZExETkQXn6hGe9r97Yejo3P8MCh03z98VM8cOg0x8bdd9RHdfJjVN1y/UaOj+f59tNjfPMHp/n202McH89zy/UbncY1OlWkbdEKzm3phPMZ9Vv62rj9FVt5xVV9/MiGTl5xVR+3v2Kr8xro+o40+VJwXiNBqfk++VLN6dL3qYRQLNeo1nzisWDSY7FcI5VwvIrEdBFflWzGo789RTbj4asyNt3Yc+I0c/RXFXivqm4HdgHvEpEdwPuB+1T1KuC+8D7ABPBu4COLtlMCflxVXwrsBF4nIruWec09qrozvPxVg9/PvOlihWcmZjlyJs8zE7NMF90u7QHRHTUUZTEJd/+5mf7ifjCkHRzUZ7JYpTUZJx6LoQSLJrYm406Xvm9Le7SnPWoanG+mpkp72qMt7bb/qVhV2jIe5WqNs4UK5WqNtoxHcbnVQi9Q075Fqjqiqo+Et6eBg8AG4Gbg7vBpdwNvCp9zWlW/A1QWbUdVdW4mkxdenPXCfenACYbPziICqUSwBP7w2Vm+dOCEq5CAc6OGWsMmr9Z0wnk7/JyjY3k+te84H7nnEJ/ad9z5yskQdNT3tCUZ6MzQl00z0Jmhpy3Jnv3DTuOK6sFBVFfBPpMr05KM05KK05ZK0JKK05KMcyZXdhZTX6sXrv8lpBKCiFCo+PS1uk0qGS9OvlAhmYjT1eKRTAT3MxfjgpIishm4DngI6FfVEQgSj4g871AbEYkD+4ErgY+r6kPLPPXNIvJK4AfAL6vqs0ts63bgdoDLL7+87vfy4OFxpmartKYStCQTVGvK1GyVBw+P88s/WffmGmp4YpaHjowzMlVgoCPD5q6M86RydCzPX/zrESZmypSrPj8YnebxE1P84ivdNp0cOzPDeL7ITNmn6vskYjFakzEKS51cfBVFdUhxVPt6CM9w2t26sG+s7HRJFI0JcVEKVX9+SZtMIoY6Xpuopy3JmekSilCpBSc0a00lGn4K7aYnFRFpA74A3KmqObmATiFVrQE7RaQT+AcRebGqfn/R0/4P8BlVLYnIHQS1oB9fYlt3AXcBDA4O1l3jmZip4MUFL5wRHtwWJmbdNoF969Bp/ugbT9GZ8djQGXRC/9E3ngJwOkT2SwdOcOzMDB0tSTrCqvaxMzN86cAJfvknr3EWV75YZXymTCqRIBmPU/N1/r5rURwtF9WBIFt7W3joyAT5UnV+jTQBfmSDu5OajZwtMlv1iYsQjwfNKrNVn5Gzbv9XGzpayBerzJRr1Go+8XjQVLiho7Ez/ZvaiCwiHkFC+bSqfjEsHhWRgfDxAeD0SrenqpPAA8DrlnhsXFXnepz+Erj+BYS+rK4Wj4qvlGs+SnBd8dX56V737A+GoXa2JIlJjM6WJJ0Zz3lzzoFnJ8m2eGS8OCJCxouTbfE48Oyk07iKlWoweRUNz2oYrDpdrLqdIR5V/R1pnhmfYd/Rcb7+xCn2HR3nmfEZ5309W/ra6GpNEosJ1ZpPLCZ0tSbZ7DApj+WLJATiMQER4jEhIUG5S9euz7K1t5VEXChWfRJxYWtvK9eub2wCbuboLwE+ARxU1Y8ueOgrwK3h7VuBLz/PdvrCGgoikgFeDTy5xPMWLkv6RoI+nIa78coeOjIJFKVQrqIoHZkENzo8KRAE8y5iohw5k+eJkSmOnMkTE/cLXYIgi+qDwX23TQFJL05fe5J4TKj4wQ9AX3uSZARqKlG0uSvDw8fOkputkE0nyM1WePjYWednpBSCSX3drUl629N0tyZJeXGne1el5hOLxfDiMdKJ4DoWi1FxvPT95q4MPzg9Q09Lip2bOulpSfGD040/q2gzv0E3Ae8AHhORA2HZB4APA58VkduAZ4C3AojIOmAIyAK+iNwJ7AAGgLvDfpUY8FlV/cfwbz4IDKnqV4B3i8gbCUadTQA/24w3tXDZkXLVJ5kI2nNdLzuSTSd46nSebDpJxotTrSlPnc5z5WVum1Gu29TBg0cmgk5LL0ap4jNZqPDyrd1O49ra28rhsRk2dKZIxIKVd3PFClt73S76B/C5h49z975nOJMv0duW4tZdlzudiQ3BCrdX97VycHSaI2fydGQ8tve3Oz/lw5l8mURMqNTOHaYkYsJ43l1HfVdrkvHpEuWqTy2cpxIXpavV3TBnOP8zPHomT7ZJn2HTkoqq7mX5w9GfWOL5p4ClJgl8j6CTf6nX+O0Ft38D+I36I61PVJcd2dTVwqGRacq1YMXdcs2nVlM2dbn9kbx55waePp3n6bEZZkoVWlMeV/a1Op80d9tNW/jQ1w4GzZfhCQ1bU3Fuu2mL07g+9/Bx/vDep2hLxulrTzFTrPKH9wZ9Yy4Ty5Mnc4xMl1jf2cLW3hjFqs/IdAnvZM5ZTACThQrtaY9N3a3nymbLnC246+O8blMn9zw+SiwmJOIyPyHzOseLqD55MseR8RmqvpJMxKj6ypHxGTxbpsW9KHakZjNJfnJHP488O3nuPBxb+2nPuD2JEgTj9i/vbpmv2bkerw/B4IXfJOiLOhV2Qt9y/Ubn637dve8Z2pJxsuHnFlyXuXvfM06TylSxQjzsE4NgeGqpUmPK8RytjrTHVKFCoVILTltd9amp0uFwH9vS28a67BQTs5VzrRltabb0uv3NODE1y2iuSHs6SUsyQaWmjOZ+eLLtC2VJ5RLR35GmLZXg7QMd82W5QoXWBu8w9YrqApwQJBbXSWSxM/kSfe3nN5O0phOcyTd21nO9OjMeU7MVipXafDNmLQIDVK5dn6VSrQXnqC9U5pvlGt35XI8z+TK97SlaUsEPtxcXWpJxp01yEJy+IC4y33wkBKcLmC01dhi9+ynEpiGiOmkuqsuORFVvW9DktdBMsUqP4/b4awayDHSkODE1y3efOcuJqVkGOlJcPeDuxxvCzuexGXpaw87n1hQ/GGt853M9JgsV2lIeV/dnedH6Dq7uz9KW8pw2yQFkkgk2dmWIx4VCpUY8LmzsypBp8NL3llQuEVGdUW/LjtTn1l2XM1ms8OzZWU5MzvLs2VkmixVu3VX/RN1GWq2RQ/U6drbADZu7yLZ45IpVsi0eN2zu4tjZgrOYOtIe+VKFQ6M5Hj85yaHRHPlSxWmTHJx/wrztTTxhnjV/XUKi2Neze1sPe4aCuTJt6QT5YpXJQoXXvqjfcWTRNLilh5esz3JwNE+hVCOTirO9v53BLW5rnMfOFrimv5UnRvIcPTNDNuOxY6DN+eiv0alicJKpuWHrGpxl0WVNuK89yWMnfEQFQRAVylWfvna3/ZurdcI8SyqmqaK67EhU7T08zq5tfbzmxevny6LQB3VoJMfJyRIbOjNs7WulVPE5OVkiGXc7+iseg31HJoIVG9LBig37jkzw7xwOWZ+b2a/L3HdltUauWlIxTRfFGlRURXU5lMlChXhMSIejv9JenGKl5ryfYO7HWsI759135Mx0GS8Ro+wH54BHFC8R58y02456WJ3voiUVs2YdHctHbr5RVE8CF8WhuwBVH27c1s3hM7PnhtJv66bicF3QqWLQUb+x6/y5M66HX8Pq7PPWUW/WpKgu5R7VUXzXrs+yvb+dVCJGrlghlYg5H7oLQRJOJRLs2tLDa3asY9eWHlKJhNMk3JnxqPlKsVJDCa6jMPx6tfZ5SypmTVq4lHtMhGzGozPjsffwuNO4ojqKb/e2HmLxGDsGsvzE9n52DGSJxWPOk10Uk/A1A1m2D7ST9GJBh7gXY/tAu/Ph16u1z1tSMWvS6FSRYqXKviPhqrtHxilWqjZ/ZhlRTXZb+tq4aWs33z85xT98d5jvn5zipq3dTuPava2HXLFKsRys/1Ms18gVq84T8GrNGbOkYtakuVFDpapPR9qjFI4aijv+RkS1WQ7OnQTuwSNneOjIOMMTs65D4uhYnm8fmeDF6zv4T9dt5MXrO/j2kQnn/698eMrxw2PTPDMxSz4C/SmrNWfMkopZk6I4agii2yw3dxK4fLHKhs4M+WJwErhvHVrx6ZCaIor/ry8fOMFYvszmnlZedkU3m3taGcuX+bLjU46vVlOhjf66AFEcNWTqE8VRQxDdIcULTwIHzF/v2T/sdP200akiXhz2Hc2RCz/Hbb0t5KfcnWztu89O4cXg5FSBYqVG2ouTTcX57rNTzmKC1ZszZkmlTnPNE50Zj3VhdXLP0HAk2pfNyvWHTUu7FsxUzxUqdLe5/UpEdUjxyFSBDZ3nL8mSzSQ4Oek22SVi8G+HJ+gKT1ddqvj82+EJp+frKZSrnM6VaE0l5s9tNHy2yGVZt+u3werMU7HmrzpFsbo95+hYnk/tO85H7jnEp/Ydd96uHGVRHDUU5bgGOjLkCucf/ecK1R+qVa2282arazRmr7ck49Q0jCC8qqkGy8msAZZU6hTVVXej3MEbRVEezRTFuG65fiOThQqTs2V89ZmcLTNZqHDL9UudV2/11HzYtbX7vPkzu7Z24/LMvRs6W7isPYWvUKjU8BUua0+xodP9WUVX48DTmr/qFNXmiYU1KGD+2kMFF5EAABkuSURBVPWaURDdPqioLh8Txbjm+k327B/m5GTQ73PbTZudn49mvhlz6/nNmC7PI3Tt+iytyTinpktMF4MzU65rT7Gpt/X5/7iJVqvp3pJKnaK66m4UOyzB+qAuRFSTcBRPahbF7+PubT3sOVtgx0D2vJhcN2Gu1oGnNX/VKarNE3MdluWKT0fGoxx2WCYcf8JR7oOKImvGrE8Uv49RjAlWr+neaioXIIrNE1HssIToDpGNqig3Y0ZVFL+PUYxptZruraZyiYhihyXYmR/rNTpVpFStsu9ouHzM0XFKVVs+xrxwNvnR1CWKHZYQzTbvKIvivIuoi2ofVNTY5EdTl6j+eNuZH+sT1WZMiOaPtw0EqY9NfjQrFtXOQVOfmg8DHUkeG57k/kOneWx4koGOpPNmzKgOILCBINFjNZVLSBQ7B+1Isj7ThTL7jk7SnkrQ256iWK6x7+gkr0knncYV1QEENhAkeiypmKbae3gcv+bzxEiOXLFCNpwI5vrHKKqOT8ySiAlePIYoePEYiZhw3PEy81H98Y7qZOS1zJq/TFM9eTLHwdHp885bcnB0midP5lyHFknTpSpXXdZKPC4UKjXiceGqy1rJl9wunxzVUXxRXSttLbOaygWIYodlVE0VK8RFyHjBYnoZL06pUmMqAictiqKBjuBcJVt7z+1Pk7Nl5ws3RnkgyE1bu9mzf5iRqQIDHRluud6aVl2ypFKnKPcRRDHZdWY8pmYrFCs1Ul6MUsWn5itdC5orzDm3XL+RD33tICcmC/Nl8Rj85k3bHUZ1/o/3qbApLAo/3gvP/Lhraw/5YpVvH5lgY3eL89jWKmv+qtPew+P4vs8Tp3J84+AoT5zK4fu+89EmUR2dc81Alu0D7SS9GFOFCkkvxvaBdq4eyDqNK6o2drdwZV8b8ZhQqtSIx4Qr+9rY2O12hduFP95vum5DZE7ba6O/osdqKnU6NJLj+PgsranE/OS0gyPTFMpu27yjOjpnfnG9ddFaXC+q9h4e58UbOrnxyr75slyh4vxzjOr+FdUBBGuZJZU6TRYqxGNCOuwjSHtxipUaZwtu+wii+uWK8uTHKDYXRvVzjGpcNvoreprW/CUim0TkfhE5KCKPi8h7wvJuEblXRJ4Kr7vC8mtF5EERKYnI+xZsJy0iD4vIo+F2fneZ10uJyB4ReVpEHhKRzc14Xx1pj5oqhUoNDa9rqnSk3fYRRHV0DgSJ5R27ruB9r72Gd+y6wvkPN0S3uTCqn2NU47LRX9HTzD6VKvBeVd0O7ALeJSI7gPcD96nqVcB94X2ACeDdwEcWbacE/LiqvhTYCbxORHYt8Xq3AWdV9Urg/wN+v9FvCIIT8Gzvbz9v4cbt/e1cu95tH4F9ueoT1bb4qH6OUY3LVpKInqY1f6nqCDAS3p4WkYPABuBm4FXh0+4GHgB+XVVPA6dF5KcWbUeBucNHL7wstRTSzcD/E97+PPAxEZHw7xsmqifgiXIzUxRFtTknqp9jVOOaiy0KcZjAqvSphE1R1wEPAf1hwkFVR0TkeU8lJyJxYD9wJfBxVX1oiadtAJ4Nt1sVkSmgBzizaFu3A7cDXH755XW/F/tyXRqi3BYf1c8xqnGZaGl6UhGRNuALwJ2qmhORurehqjVgp4h0Av8gIi9W1e8vfqml/nSJbd0F3AUwODh4QbUY+3Jd/KI6mc+Yi11T56mIiEeQUD6tql8Mi0dFZCB8fAA4vdLtqeokQXPZ65Z4eBjYFG43AXQQ9NMY80OsLd6Y5mhaTUWCKskngIOq+tEFD30FuBX4cHj95efZTh9QUdVJEckAr2bpTvi57T4IvAX4l0b3p5hLi9U4jWm8ZjZ/3QS8A3hMRA6EZR8gSCafFZHbgGeAtwKIyDpgCMgCvojcCewABoC7w36VGPBZVf3H8G8+CAyp6lcIEtinRORpghrK25r43iIpivMujGk22++jRdbywfzg4KAODQ25DqMhFq5JtrCPwJp0zKXM9ns3RGS/qg4u9Zit/XWJiOq8C2Oayfb76LGkcokYnSrSlj6/NbMtnWDU1kAylzDb76PHksolIqrLaBjTTLbfR48llUtEVJfRMKaZbL+PHksqlwibd2HWItvvo8eWvr+E2LwLsxbZfh8tllSMMRc1m6cSLdb8ZYy5aEX1vDhrmdVUjIkYO/Jeuaie5jiqVmPfspqKMRFiR971sXkqK7da+5YlFWMixGaI18fmqazcau1b1vx1Aax5wjRLVM9IGVV2XpyVW619y2oqdbLmCdNMduRdH5unsnKrtW9ZTaVOew+P49d8nhjJkStWyKY91rWnrGPQNIQdedfP5qmszGrtW3XVVESkS0Re0tAILjJPnsxxcHSaUtWnI+1RqvocHJ3myZM516GZS4AdeZtmWa1963lrKiLyAPDG8LkHgDER+aaq/kpDI7lITBUrxEXIeHEAMl6cUqXGVLHiODJzqbAjb9Msq7FvraSm0qGqOeD/Av5aVa8nOKXvmtSZ8aj5SrFSQwmua77SFY6PN8aYtWwlfSoJERkAfhr4zSbHE3nXDGRpScY5NV1iqlAhm/G4vLudTT2trkMzlwgbXWguZiupqXwQuAc4rKrfEZGtwFPNDSu6dm/rIRaLsWNdlldv72fHuiyxWMyW2jYNYaMLzcXueZOKqn5OVV+iqr8U3j+iqm9ufmjRZB2pppls8qO52K2ko/5q4M+AflV9cTj6642q+ntNjy6irCPVNItNfjQXu5U0f/0l8BtABUBVvwe8rZlBGbNW2eRHc7FbSVJpUdWHF5VVl3ymMeYFsdPjmovdSpLKGRHZBiiAiLwFGGlqVMasUdZnZy52KxlS/C7gLuBaETkBHAV+pqlRGbOGWZ+duZg9b1JR1SPAq0WkFYip6nTzwzLGGHMxet7mLxH5nyLSqaozqjodrv+1Zkd+GWOMWd5Kmr9er6ofmLujqmdF5A3AbzUvLHMpsRnixqwdK+moj4tIau6OiGSA1HM835h5NkPcmLVlJTWVvwPuE5G/Du//HHB380Iyl5KFM8SB+Ws7/4wxl6aVdNT/gYh8j2BlYgH+Gbii2YGZS4PNEDdmbVnpSbpOAT7wZuAngINNi8hcUmyGuDFry7JJRUSuFpHfFpGDwMeAZwFR1X+vqh9btQjNRc1miBuztjxXTeVJglrJf1TV3ar6p0BtpRsWkU0icr+IHBSRx0XkPWF5t4jcKyJPhdddYfm1IvKgiJRE5H3Pt50lXu9VIjIlIgfCy2+vNFbTPDZD3Ji15bn6VN5MsHDk/SLyz8D/JuhTWakq8F5VfURE2oH9InIv8LPAfar6YRF5P/B+4NeBCeDdwJtWsh1VfWKJ1/yWqv6HOmI0q8BmiBuzdixbU1HVf1DVW4BrgQeAXwb6ReTPROQ1z7dhVR1R1UfC29ME/TAbgJs5N3rsbsIkoqqnVfU7hKshr2A7xhhjImYlJ+maUdVPhzWAjcABgtrFionIZuA64CGC87KMhNseAS67wO0s5eUi8qiIfE1EXrTMNm4XkSERGRobG1vxezDGGPP8Vjr6CwBVnVDVv1DVH1/p34hIG/AF4E5VzdUbYB3beQS4QlVfCvwp8KWltqOqd6nqoKoO9vX1XWg4xhhjllBXUqmXiHgEieDTqvrFsHhURAbCxweA0xe4nfOoak5V8+HtrwKeiPQ24G0YY4xZoaYlFRER4BPAQVX96IKHvgLcGt6+FfjyBW5n8fPWhc9FRG4geG92Ym9jjFlFK1mm5ULdBLwDeExEDoRlHwA+DHxWRG4DngHeCkFSAIaALOCLyJ3ADuAlS21HVb8qIncAqOqfA28BfklEqkABeJuqahPfnzHGmEVkLf/uDg4O6tDQkOswjDHmoiIi+1V1cKnHmtqnYowxZm2xpGKMMaZhLKkYY4xpGEsqxhhjGsaSijHGmIaxpGKMMaZhLKkYY4xpmGZOfjTGmKY7OpZn7+FxRqeK9Hek2b2tx0614JDVVIwxF62jY3n2DA0zU6yyriPNTLHKnqFhjo7lXYe2ZllSMcZctPYeHqcz45HNeMREyGY8OjMeew/bsn+uWFIxxly0RqeKtKXPb8VvSycYnSo6ishYUjHGXLT6O9Lki9XzyvLFKv0daUcRGUsqxpiL1u5tPUwWKuQKFXxVcoUKk4UKu7f1uA5tzbKkYoy5aG3pa+OWwY20phOcmirSmk5wy+BGG/3lkA0pNk1nQz5NM23pa7P9KUKspmKayoZ8GrO2WFIxTWVDPo1ZWyypmKayIZ/GrC2WVExT2ZBPY9YWSyqmqWzIpzFriyUV01Q25NOYtcWGFJumsyGfxqwdVlMxxhjTMJZUjDHGNIwlFWOMMQ1jScUYY0zDWFIxxhjTMJZUjDHGNIwlFWOMMQ1jScUYY0zDWFIxxhjTMJZUjDHGNIwlFWOMMQ1jScUYY0zDNC2piMgmEblfRA6KyOMi8p6wvFtE7hWRp8LrrrD8WhF5UERKIvK+59vOEq8nIvInIvK0iHxPRF7WrPdmjDFmac2sqVSB96rqdmAX8C4R2QG8H7hPVa8C7gvvA0wA7wY+ssLtLPZ64KrwcjvwZw1+P8YYY55H05KKqo6o6iPh7WngILABuBm4O3za3cCbwuecVtXvAJUVbmexm4G/1cA+oFNEBhr/zowxxixnVfpURGQzcB3wENCvqiMQJAzgsgvczmIbgGcX3B9mieQjIreLyJCIDI2Nja30pY0xxqxA05OKiLQBXwDuVNVcE7cjS5TpDxWo3qWqg6o62NfXd6HhGGOMWUJTk4qIeASJ4NOq+sWweHSuWSq8Pn2B21lsGNi04P5G4OSFxm6MMaZ+zRz9JcAngIOq+tEFD30FuDW8fSvw5QvczmJfAd4ZjgLbBUzNNbMZY4xZHc08R/1NwDuAx0TkQFj2AeDDwGdF5DbgGeCtACKyDhgCsoAvIncCO4CXLLUdVf2qiNwBoKp/DnwVeAPwNDAL/FwT35sxxpgliOoPdTusGYODgzo0NOQ6DGOMuaiIyH5VHVzqMZtRb4wxpmEsqRhjjGkYSyrGGGMaxpKKMcaYhrGkYowxpmEsqRhjjGkYSyrGGGMaxpKKMcaYhrGkYowxpmEsqRhjjGmYZq79ZVbZ0bE8ew+PMzpVpL8jze5tPWzpa3MdljFmDbGayiXi6FiePUPDzBSrrOtIM1OssmdomKNjedehGWPWEEsql4i9h8fpzHhkMx4xEbIZj86Mx97D465DM8asIZZULhGjU0Xa0ue3ZralE4xOFR1FZIxZiyypXCL6O9Lki9XzyvLFKv0daUcRGWPWIksql4jd23qYLFTIFSr4quQKFSYLFXZv63EdmjFmDbGkconY0tfGLYMbaU0nODVVpDWd4JbBjTb6yxizqmxI8SVkS1+bJRFjjFNWUzHGGNMwllSMMcY0jCUVY4wxDWNJxRhjTMNYUjHGGNMwllSMMcY0jCUVY4wxDWNJxRhjTMNYUjHGGNMwllSMMcY0jCUVY4wxDWNJxRhjTMNYUjHGGNMwllSMMcY0jCUVY4wxDdO0pCIim0TkfhE5KCKPi8h7wvJuEblXRJ4Kr7vC8mtF5EERKYnI+xZt65MiclpEvv8cr/cqEZkSkQPh5beb9d6MWYuOjuX51L7jfOSeQ3xq33GOjuVdh2QiqJk1lSrwXlXdDuwC3iUiO4D3A/ep6lXAfeF9gAng3cBHltjW3wCvW8FrfktVd4aXD77QN2CMCRwdy7NnaJiZYpV1HWlmilX2DA1bYjE/pGlJRVVHVPWR8PY0cBDYANwM3B0+7W7gTeFzTqvqd4DKEtv6V4KkY4xxYO/hcTozHtmMR0yEbMajM+Ox9/C469BMxKxKn4qIbAauAx4C+lV1BILEA1zWwJd6uYg8KiJfE5EXLRPL7SIyJCJDY2NjDXxpYy5do1NF2tLnn328LZ1gdKroKCITVU1PKiLSBnwBuFNVc018qUeAK1T1pcCfAl9a6kmqepeqDqrqYF9fXxPDMebS0d+RJl+snleWL1bp70g7ishEVVOTioh4BAnl06r6xbB4VEQGwscHgNONeC1VzalqPrz9VcATkd5GbNuYtW73th4mCxVyhQq+KrlChclChd3belyHZiKmmaO/BPgEcFBVP7rgoa8At4a3bwW+3KDXWxe+JiJyA8F7swZfYxpgS18btwxupDWd4NRUkdZ0glsGN7Klr811aCZiEs//lAt2E/AO4DERORCWfQD4MPBZEbkNeAZ4KwRJARgCsoAvIncCO1Q1JyKfAV4F9IrIMPA7qvoJEbkDQFX/HHgL8EsiUgUKwNtUVZv4/oxZU7b0tVkSMc9L1vLv7uDgoA4NDbkOwxhjLioisl9VB5d6zGbUG2OMaRhLKsYYYxrGkooxxpiGsaRijDGmYSypGGOMaZg1PfpLRMaA4y9gE73AmQaF00gWV30srvpYXCsXxZjghcd1haouuSTJmk4qL5SIDC03rM4li6s+Fld9LK6Vi2JM0Ny4rPnLGGNMw1hSMcYY0zCWVF6Yu1wHsAyLqz4WV30srpWLYkzQxLisT8UYY0zDWE3FGGNMw1hSMcYY0zCWVBYQkU0icr+IHBSRx0XkPWF5t4jcKyJPhdddYbmIyJ+IyNMi8j0RedmCbf2+iHw/vNyyynFdKyIPikhJRN63aFuvE5FDYczvj1BcnxSR0yLy/RcSUyPjWm47EYgrLSIPh6fOflxEfjcKcS3YXlxEvisi/xiVuETkmIg8JiIHROQFLU3e4Lg6ReTzIvJkuL2Xu45LRK4J/09zl5wEpyJZGVW1S3gBBoCXhbfbgR8AO4A/AN4flr8f+P3w9huArwEC7AIeCst/CriX4Hw1rYTniVnFuC4DfhT4EPC+BduJA4eBrUASeJTgnDVO4wofeyXwMuD7Dj7H5f5fS24nAnEJ0Bbe9oCHgF2u41qwvV8B/h74xyh8juFjx4DeF7pvNSGuu4FfCG8ngc4oxLVgm3HgFMFkxxXFYTWVBVR1RFUfCW9PAweBDcDNBB8+4fWbwts3A3+rgX1ApwSnSN4BfFNVq6o6Q/Dj/brViktVT6vqd4DKok3dADytqkdUtQz873AbruNCVf8VmLjQWJoR13Nsx3VcquGpswmSigdc8IibRn6OIrKR4KDqry40nmbE1UiNiktEsgQHU58In1dW1UnXcS3yE8BhVV3xyiOWVJYhIpuB6wiOAvtVdQSCD44gw0PwgT274M+Gw7JHgdeLSIuI9AL/Hti0inEtZ7l4XcfVNI2Ka9F2nMcVNjEdAE4D96pqJOIC/hj4NcBvRDwNjEuBr4vIfhG5PSJxbQXGgL8Omwv/SkRaIxDXQm8DPlPPa1tSWYKItAFfAO5U1dxzPXWJMlXVrwNfBf6N4AN5EKiuYlzLbmKJshc8prwBcTVFo+Jq9PtrxPZUtaaqO4GNwA0i8mLXcYnIfwBOq+r+FxpLI+MK3aSqLwNeD7xLRF4ZgbgSBE2+f6aq1wEzBM1TruOa204SeCPwuXr+zpLKIiLiEXwgn1bVL4bFo2GzFuH16bB8mPNrIBuBkwCq+iFV3amqP0nwY/7UKsa1nGXjdRxXwzUqrmW24zyuOWFzyQO8gObVBsZ1E/BGETlG0LT64yLydxGIC1Wd+16eBv6BoCnYdVzDwPCCWubnCZKM67jmvB54RFVH64nBksoCIiIE7ZsHVfWjCx76CnBrePtW4MsLyt8pgV3AlKqOhE0TPeE2XwK8BPj6Ksa1nO8AV4nIlvAo5G3hNlzH1VCNius5tuM6rj4R6QxvZ4BXA0+6jktVf0NVN6rqZoJ9619U9WdcxyUirSLSPncbeA1wwaMMG/j/OgU8KyLXhEU/ATzhOq4F3k6dTV+Ajf5aeAF2EzQHfQ84EF7eAPQA9xHUNu4DusPnC/BxghFVjwGDYXmaYOd4AtgH7FzluNYRHAXlgMnwdjZ87A0Eo0IOA78Zobg+A4wQdBoOA7e5jmu57UQgrpcA3w23833gt6PyOS7Y5qt44aO/GvX/2krQz/ko8HjE9vudBKNDvwd8CeiKSFwtwDjQUW8ctkyLMcaYhrHmL2OMMQ1jScUYY0zDWFIxxhjTMJZUjDHGNIwlFWOMMQ1jScWYVRLOZ9orIq9fUPbTIvLPLuMyppFsSLExqyhcTuVzBOsyxQnmErxOVQ+/gG0mVPUFLwNkTCNYUjFmlYnIHxCs89QKTKvq/xCRW4F3ESx//m/A/62qvojcRbB0RwbYo6ofDLcxDPwFwfIsf6yqda3PZEyzJFwHYMwa9LvAI0AZGAxrL/8JuFFVq2EieRvBOUner6oTIpIA7heRz6vq3FIeM6p6k4s3YMxyLKkYs8pUdUZE9gB5VS2JyKsJTpY0FCzfRIZzpyh4u4jcRvBdXU9wrp65pLJndSM35vlZUjHGDZ9z5xwR4JOq+t8XPkFErgLeA9ygqpPhir/pBU+ZWZVIjamDjf4yxr1vAD8dntANEekRkcsJFkOcBnLhkuWvdRijMStiNRVjHFPVx0Tkd4FviEiMYKXmOwhWr32CYCXiI8C33UVpzMrY6C9jjDENY81fxhhjGsaSijHGmIaxpGKMMaZhLKkYY4xpGEsqxhhjGsaSijHGmIaxpGKMMaZh/n8/pdkLdH7EGQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['Aces']]\n",
    "winnings = df['Year']\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('Aces vs Year')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Aces')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0011388662747043865\n",
      "0.0028942600923529405\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['Winnings']]\n",
    "winnings = df['Year']\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('Winnings vs Year')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Winnings')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.08508768360312569\n",
      "0.06320431057217824\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['Wins']]\n",
    "winnings = df['Ranking']\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('Wins vs Ranking')\n",
    "plt.xlabel('Ranking')\n",
    "plt.ylabel('Wins')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.05496237254314873\n",
      "0.06208008049289182\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['Winnings']]\n",
    "winnings = df[['FirstServeReturnPointsWon']]\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('Winnings vs FirstServeReturnPointsWon')\n",
    "plt.xlabel('FirstServeReturnPointsWon')\n",
    "plt.ylabel('Winnings')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.001232199574082271\n",
      "0.004687014990308547\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['Winnings', 'Ranking']]\n",
    "winnings = df[['Year']]\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('2 Features')\n",
    "plt.xlabel('Actual Winnings')\n",
    "plt.ylabel('Predicted Winnings')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8484449500729737\n",
      "0.8149220333672943\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = df[['FirstServe','FirstServePointsWon','FirstServeReturnPointsWon','SecondServePointsWon','SecondServeReturnPointsWon','Aces','BreakPointsConverted','BreakPointsFaced','BreakPointsOpportunities','BreakPointsSaved','DoubleFaults','ReturnGamesPlayed','ReturnGamesWon','ReturnPointsWon','ServiceGamesPlayed','ServiceGamesWon','TotalPointsWon','TotalServicePointsWon']]\n",
    "winnings = df[['Winnings']]\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, winnings, test_size = 0.2, random_state = 1)\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)\n",
    "print(model.score(X_train, y_train))\n",
    "print(model.score(X_test, y_test))\n",
    "y_predict = model.predict(X_test)\n",
    "plt.scatter(y_test, y_predict, alpha=0.4)\n",
    "plt.title('Multiple Regression')\n",
    "plt.xlabel('Actual Winnings')\n",
    "plt.ylabel('Predicted Winnings')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}