TechGig_AI_Contest.ipynb

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   "source": [
    "# IPL Match Prediction  \n",
    "\n",
    "## Introduction  \n",
    "\n",
    "The game of cricket is about skill and preparation of individual players, coordination and team work of the whole team, evolving tactics and overall strategy adopted by each team in each match, and of course some luck. It is hard to predict what will happen in the next ball, the next over, the next inning, or in next match. This inability to predict and the uncertainty of the outcome is what makes these games fun.  \n",
    "\n",
    "In this notebook, we have explored whether these games are really completely random or are there any underlying latent patterns in them. We will start by fetching and preprocessing our data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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      "startup": false,
      "wait_interval": 0
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     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 8959,
     "status": "ok",
     "timestamp": 1525861107548,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
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    "id": "8cMMoTfoswOo",
    "outputId": "ac1bab4f-6963-4326-e7d4-6f88b73100a8"
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   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "--2018-05-11 20:19:38--  https://www.techgig.com/files/DataScienceFullData/15085_132022/cg-ai-hackathon-dataset.zip\n",
      "Resolving www.techgig.com (www.techgig.com)... 223.165.25.21\n",
      "Connecting to www.techgig.com (www.techgig.com)|223.165.25.21|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 848745 (829K) [application/zip]\n",
      "Saving to: ‘cg-ai-hackathon-dataset.zip’\n",
      "\n",
      "cg-ai-hackathon-dat 100%[===================>] 828.85K   277KB/s    in 3.0s    \n",
      "\n",
      "2018-05-11 20:19:43 (277 KB/s) - ‘cg-ai-hackathon-dataset.zip’ saved [848745/848745]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Fetching data\n",
    "!wget https://www.techgig.com/files/DataScienceFullData/15085_132022/cg-ai-hackathon-dataset.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 136
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2137,
     "status": "ok",
     "timestamp": 1525861112291,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
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    },
    "id": "ETQg_3vTtmvY",
    "outputId": "084944e8-ef2e-49c6-b313-a5bb4212969b"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  cg-ai-hackathon-dataset.zip\n",
      "   creating: cg-ai-hackathon-dataset/\n",
      "  inflating: cg-ai-hackathon-dataset/submission.csv  \n",
      "  inflating: cg-ai-hackathon-dataset/TestDeliveries.csv  \n",
      "  inflating: cg-ai-hackathon-dataset/Testmatches.csv  \n",
      "  inflating: cg-ai-hackathon-dataset/TrainDeliveries.csv  \n",
      "  inflating: cg-ai-hackathon-dataset/Trainmatches.csv  \n"
     ]
    }
   ],
   "source": [
    "# extracting data\n",
    "!unzip cg-ai-hackathon-dataset.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "hjc4YcCjt0JH"
   },
   "outputs": [],
   "source": [
    "# importing necessary packages\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "RpYZubrNuQRN"
   },
   "outputs": [],
   "source": [
    "# Creating dataframes from data\n",
    "#https://www.techgig.com/codegladiators/question/MUpIY1NqVlF1Ymh0dnF4eFJHam5mb3V2MXY0NEtHMkFkaHhuVlNoK0wyRT0=/1&msg_type=1\n",
    "\n",
    "TestDeliveries = pd.read_csv('cg-ai-hackathon-dataset/TestDeliveries.csv') #Appendix A\n",
    "TestMatches = pd.read_csv('cg-ai-hackathon-dataset/Testmatches.csv') #Appendix C\n",
    "TrainDeliveries = pd.read_csv('cg-ai-hackathon-dataset/TrainDeliveries.csv') #Appendix A\n",
    "TrainMatches = pd.read_csv('cg-ai-hackathon-dataset/Trainmatches.csv') #Appendix B"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preprocessing Data\n",
    "\n",
    "### Checking for null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1033,
     "status": "ok",
     "timestamp": 1525873022534,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
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    },
    "id": "q7rxP5TmvtZ5",
    "outputId": "3b305ab4-0d94-4630-f769-0e0fa41f2a40",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "match_id                 0\n",
      "inning                   0\n",
      "batting_team             0\n",
      "bowling_team             0\n",
      "over                     0\n",
      "ball                     0\n",
      "batsman                  0\n",
      "non_striker              0\n",
      "bowler                   0\n",
      "is_super_over            0\n",
      "wide_runs                0\n",
      "bye_runs                 0\n",
      "legbye_runs              0\n",
      "noball_runs              0\n",
      "penalty_runs             0\n",
      "batsman_runs             0\n",
      "extra_runs               0\n",
      "total_runs               0\n",
      "player_dismissed    112771\n",
      "dismissal_kind      112771\n",
      "fielder             114452\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(TrainDeliveries.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id                 0\n",
      "season             0\n",
      "city               0\n",
      "team1              0\n",
      "team2              0\n",
      "toss_winner        0\n",
      "toss_decision      0\n",
      "result             0\n",
      "dl_applied         0\n",
      "winner             1\n",
      "win_by_runs        0\n",
      "win_by_wickets     0\n",
      "player_of_match    0\n",
      "venue              0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(TrainMatches.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "match_id                0\n",
      "inning                  0\n",
      "batting_team            0\n",
      "bowling_team            0\n",
      "over                    0\n",
      "ball                    0\n",
      "batsman                 0\n",
      "non_striker             0\n",
      "bowler                  0\n",
      "is_super_over           0\n",
      "wide_runs               0\n",
      "bye_runs                0\n",
      "legbye_runs             0\n",
      "noball_runs             0\n",
      "penalty_runs            0\n",
      "batsman_runs            0\n",
      "extra_runs              0\n",
      "total_runs              0\n",
      "player_dismissed    30251\n",
      "dismissal_kind      30251\n",
      "fielder             30639\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(TestDeliveries.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "match_id         0\n",
      "season           0\n",
      "city             0\n",
      "team1            0\n",
      "team2            0\n",
      "toss_winner      0\n",
      "toss_decision    0\n",
      "result           0\n",
      "dl_applied       0\n",
      "venue            0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(TestMatches.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
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     "height": 338
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1599,
     "status": "ok",
     "timestamp": 1525873086174,
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      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
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    "id": "UwrMq4LT0Rnh",
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   "outputs": [
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       "    .dataframe tbody tr th {\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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Team1</td>\n",
       "      <td>Team5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Player 105</td>\n",
       "      <td>Player 354</td>\n",
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       "      <td>1</td>\n",
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       "      <td>Team1</td>\n",
       "      <td>Team5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Player 105</td>\n",
       "      <td>Player 354</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>1</td>\n",
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       "      <td>Team1</td>\n",
       "      <td>Team5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Player 105</td>\n",
       "      <td>Player 354</td>\n",
       "      <td>Player 431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Team1</td>\n",
       "      <td>Team5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Player 105</td>\n",
       "      <td>Player 354</td>\n",
       "      <td>Player 431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Team1</td>\n",
       "      <td>Team5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Player 105</td>\n",
       "      <td>Player 354</td>\n",
       "      <td>Player 431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball     batsman  \\\n",
       "0         1       1        Team1        Team5     1     1  Player 105   \n",
       "1         1       1        Team1        Team5     1     2  Player 105   \n",
       "2         1       1        Team1        Team5     1     3  Player 105   \n",
       "3         1       1        Team1        Team5     1     4  Player 105   \n",
       "4         1       1        Team1        Team5     1     5  Player 105   \n",
       "\n",
       "  non_striker      bowler  is_super_over   ...    bye_runs  legbye_runs  \\\n",
       "0  Player 354  Player 431              0   ...           0            0   \n",
       "1  Player 354  Player 431              0   ...           0            0   \n",
       "2  Player 354  Player 431              0   ...           0            0   \n",
       "3  Player 354  Player 431              0   ...           0            0   \n",
       "4  Player 354  Player 431              0   ...           0            0   \n",
       "\n",
       "   noball_runs  penalty_runs  batsman_runs  extra_runs  total_runs  \\\n",
       "0            0             0             0           0           0   \n",
       "1            0             0             0           0           0   \n",
       "2            0             0             4           0           4   \n",
       "3            0             0             0           0           0   \n",
       "4            0             0             0           2           2   \n",
       "\n",
       "   player_dismissed dismissal_kind fielder  \n",
       "0               NaN            NaN     NaN  \n",
       "1               NaN            NaN     NaN  \n",
       "2               NaN            NaN     NaN  \n",
       "3               NaN            NaN     NaN  \n",
       "4               NaN            NaN     NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TrainDeliveries.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(118666, 21)\n",
      "(500, 14)\n",
      "(31794, 21)\n",
      "(136, 10)\n"
     ]
    }
   ],
   "source": [
    "# Shape of data\n",
    "print(TrainDeliveries.shape)\n",
    "print(TrainMatches.shape)\n",
    "print(TestDeliveries.shape)\n",
    "print(TestMatches.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "jOSwXOjO0UV8"
   },
   "outputs": [],
   "source": [
    "#Clean TrainDeliveries(Appendix A) dataframe for NaN, strings\n",
    "\n",
    "TrainDeliveries['batting_team'] = TrainDeliveries['batting_team'].str[4:]#removed Team from Team1\n",
    "TrainDeliveries['bowling_team'] = TrainDeliveries['bowling_team'].str[4:] #removed Team from Team1\n",
    "TrainDeliveries['batsman'] = TrainDeliveries['batsman'].str[7:] #removed Player from Player 105\n",
    "TrainDeliveries['non_striker'] = TrainDeliveries['non_striker'].str[7:] #removed Player from Player 105\n",
    "TrainDeliveries['bowler'] = TrainDeliveries['bowler'].str[7:] #removed Player from Player 105\n",
    "TrainDeliveries.fillna(0, inplace=True) #replaced NaN values with 0\n",
    "TrainDeliveries.loc[TrainDeliveries.player_dismissed != 0, 'player_dismissed'] = TrainDeliveries[TrainDeliveries.player_dismissed != 0].player_dismissed.str[7:] \n",
    "TrainDeliveries.loc[TrainDeliveries.fielder != 0, 'fielder'] = TrainDeliveries[TrainDeliveries.fielder != 0].fielder.str[7:]\n",
    "\n",
    "mapping = {'caught':1, 'bowled':2, 'run out':3,\n",
    "          'lbw':4, 'caught and bowled':5, 'stumped':6,\n",
    "          'retired hurt':7, 'hit wicket':8, 'obstructing the field':9}\n",
    "TrainDeliveries.replace({'dismissal_kind':mapping}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
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     "height": 253
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1035,
     "status": "ok",
     "timestamp": 1525873208338,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
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    {
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       "      <th>bowling_team</th>\n",
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       "      <th>...</th>\n",
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       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
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       "    </tr>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball batsman non_striker  \\\n",
       "0         1       1            1            5     1     1     105         354   \n",
       "1         1       1            1            5     1     2     105         354   \n",
       "2         1       1            1            5     1     3     105         354   \n",
       "3         1       1            1            5     1     4     105         354   \n",
       "4         1       1            1            5     1     5     105         354   \n",
       "\n",
       "  bowler  is_super_over   ...    bye_runs  legbye_runs  noball_runs  \\\n",
       "0    431              0   ...           0            0            0   \n",
       "1    431              0   ...           0            0            0   \n",
       "2    431              0   ...           0            0            0   \n",
       "3    431              0   ...           0            0            0   \n",
       "4    431              0   ...           0            0            0   \n",
       "\n",
       "   penalty_runs  batsman_runs  extra_runs  total_runs  player_dismissed  \\\n",
       "0             0             0           0           0                 0   \n",
       "1             0             0           0           0                 0   \n",
       "2             0             4           0           4                 0   \n",
       "3             0             0           0           0                 0   \n",
       "4             0             0           2           2                 0   \n",
       "\n",
       "  dismissal_kind fielder  \n",
       "0              0       0  \n",
       "1              0       0  \n",
       "2              0       0  \n",
       "3              0       0  \n",
       "4              0       0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TrainDeliveries.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "qC5ynhxaeWF-"
   },
   "outputs": [],
   "source": [
    "#clean TestDeliveries for NaN, strings\n",
    "TestDeliveries['batting_team'] = TestDeliveries['batting_team'].str[4:] #removed Team from Team1\n",
    "TestDeliveries['bowling_team'] = TestDeliveries['bowling_team'].str[4:] #removed Team from Team1\n",
    "TestDeliveries['batsman'] = TestDeliveries['batsman'].str[7:] #removed Player from Player 105\n",
    "TestDeliveries['non_striker'] = TestDeliveries['non_striker'].str[7:] #removed Player from Player 105\n",
    "TestDeliveries['bowler'] = TestDeliveries['bowler'].str[7:] #removed Player from Player 105\n",
    "TestDeliveries.fillna(0, inplace=True) #replaced NaN values with 0\n",
    "TestDeliveries.loc[TestDeliveries.player_dismissed != 0, 'player_dismissed'] = TestDeliveries[TestDeliveries.player_dismissed != 0].player_dismissed.str[7:] \n",
    "TestDeliveries.loc[TestDeliveries.fielder != 0, 'fielder'] = TestDeliveries[TestDeliveries.fielder != 0].fielder.str[7:]\n",
    "\n",
    "mapping = {'caught':1, 'bowled':2, 'run out':3,\n",
    "          'lbw':4, 'caught and bowled':5, 'stumped':6,'retired hurt':7, 'hit wicket':8, 'obstructing the field':9}\n",
    "TestDeliveries.replace({'dismissal_kind':mapping}, inplace=True)\n",
    "\n",
    "TestDeliveries['bowling_team'] = TestDeliveries['bowling_team'].replace({'4s':'4'})\n",
    "TestDeliveries['batting_team'] = TestDeliveries['batting_team'].replace({'4s':'4'})"
   ]
  },
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    "executionInfo": {
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     "status": "ok",
     "timestamp": 1525862356055,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
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    "id": "M7sDw80Ze6cS",
    "outputId": "0948f3da-e97f-401d-f656-ee90376b297d"
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       "      <th>3</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball batsman non_striker  \\\n",
       "0       501       1            2            9     1     1     260         234   \n",
       "1       501       1            2            9     1     2     234         260   \n",
       "2       501       1            2            9     1     3     234         260   \n",
       "3       501       1            2            9     1     4     234         260   \n",
       "4       501       1            2            9     1     5     234         260   \n",
       "\n",
       "  bowler  is_super_over   ...     bye_runs  legbye_runs  noball_runs  \\\n",
       "0     48              0   ...            0            0            0   \n",
       "1     48              0   ...            0            0            0   \n",
       "2     48              0   ...            0            0            0   \n",
       "3     48              0   ...            0            0            0   \n",
       "4     48              0   ...            0            0            0   \n",
       "\n",
       "   penalty_runs  batsman_runs  extra_runs  total_runs  player_dismissed  \\\n",
       "0             0             1           0           1                 0   \n",
       "1             0             0           0           0                 0   \n",
       "2             0             0           0           0                 0   \n",
       "3             0             0           0           0                 0   \n",
       "4             0             1           0           1                 0   \n",
       "\n",
       "  dismissal_kind  fielder  \n",
       "0              0        0  \n",
       "1              0        0  \n",
       "2              0        0  \n",
       "3              0        0  \n",
       "4              0        0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TestDeliveries.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "p8gVBkxkmhBK"
   },
   "outputs": [],
   "source": [
    "#clean Trainmatches(Appendix B) dataframe for NaN, strings\n",
    "\n",
    "TrainMatches['city'] = TrainMatches['city'].str[4:]\n",
    "TrainMatches['team1'] = TrainMatches['team1'].str[4:]\n",
    "TrainMatches['team2'] = TrainMatches['team2'].str[4:]\n",
    "TrainMatches['toss_winner'] = TrainMatches['toss_winner'].str[4:]\n",
    "TrainMatches['winner'] = TrainMatches['winner'].str[4:]\n",
    "TrainMatches['player_of_match'] = TrainMatches['player_of_match'].str[7:]\n",
    "TrainMatches['venue'] = TrainMatches['venue'].str[7:]\n",
    "\n",
    "map1 = {'field':1, 'bat':2}\n",
    "TrainMatches.replace({'toss_decision':map1}, inplace=True)\n",
    "\n",
    "map2 = {'normal':1, 'tie':2, 'no result':3}\n",
    "TrainMatches.replace({'result':map2}, inplace=True)\n",
    "\n",
    "TrainMatches.rename(columns={'id':'match_id'}, inplace=True)\n",
    "TrainMatches.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "autoexec": {
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     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1063,
     "status": "ok",
     "timestamp": 1525861701963,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
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    },
    "id": "QKgRodJJr2_k",
    "outputId": "98287d84-34b0-408b-f3a0-ee5bf2a71618"
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   "outputs": [
    {
     "data": {
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       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>405</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>85</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>145</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>209</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  season city team1 team2 toss_winner  toss_decision  result  \\\n",
       "0         1    2017    1     1     5           5              1       1   \n",
       "1         2    2017    2     2     4           4              1       1   \n",
       "2         3    2017    3     3     6           6              1       1   \n",
       "3         4    2017    4     4     8           8              1       1   \n",
       "4         5    2017    5     5     7           5              2       1   \n",
       "\n",
       "   dl_applied winner  win_by_runs  win_by_wickets player_of_match venue  \n",
       "0           0      1           35               0             467     1  \n",
       "1           0      4            0               7             405     2  \n",
       "2           0      6            0              10              85     3  \n",
       "3           0      8            0               6             145     4  \n",
       "4           0      5           15               0             209     5  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TrainMatches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "xHOUSkTGhh1b"
   },
   "outputs": [],
   "source": [
    "# get a list of the columns\n",
    "col_list = list(TrainMatches)\n",
    "# swap the elements\n",
    "col_list[9], col_list[13] = col_list[13], col_list[9]\n",
    "TrainMatches = TrainMatches.loc[TrainMatches.index[:], col_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1006,
     "status": "ok",
     "timestamp": 1525863927408,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "HYO6DG6lhzn7",
    "outputId": "34f4ac3b-1b7d-450a-cc09-3364b5d7859a"
   },
   "outputs": [
    {
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       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>209</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "   match_id  season city team1 team2 toss_winner  toss_decision  result  \\\n",
       "0         1    2017    1     1     5           5              1       1   \n",
       "1         2    2017    2     2     4           4              1       1   \n",
       "2         3    2017    3     3     6           6              1       1   \n",
       "3         4    2017    4     4     8           8              1       1   \n",
       "4         5    2017    5     5     7           5              2       1   \n",
       "\n",
       "   dl_applied venue  win_by_runs  win_by_wickets player_of_match winner  \n",
       "0           0     1           35               0             467      1  \n",
       "1           0     2            0               7             405      4  \n",
       "2           0     3            0              10              85      6  \n",
       "3           0     4            0               6             145      8  \n",
       "4           0     5           15               0             209      5  "
      ]
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     "execution_count": 18,
     "metadata": {},
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    "TrainMatches.head()"
   ]
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  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
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    "executionInfo": {
     "elapsed": 1049,
     "status": "ok",
     "timestamp": 1525862757876,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
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    },
    "id": "wzTAqcQBgc7s",
    "outputId": "01f2307c-3a4c-406b-a3d7-7181b7e2751b"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>city</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
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       "      <th>2</th>\n",
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       "      <td>Team5</td>\n",
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       "      <td>504</td>\n",
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       "      <td>Team10</td>\n",
       "      <td>Team6</td>\n",
       "      <td>Team6</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Stadium7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>505</td>\n",
       "      <td>2014</td>\n",
       "      <td>City10</td>\n",
       "      <td>Team8</td>\n",
       "      <td>Team2</td>\n",
       "      <td>Team2</td>\n",
       "      <td>field</td>\n",
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       "      <td>0</td>\n",
       "      <td>stadium35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  season    city   team1  team2 toss_winner toss_decision  result  \\\n",
       "0       501    2014  City22   Team2  Team9       Team2           bat  normal   \n",
       "1       502    2014   City9   Team7  Team8       Team8         field  normal   \n",
       "2       503    2014   City1   Team5  Team1       Team5           bat  normal   \n",
       "3       504    2014   City8  Team10  Team6       Team6         field  normal   \n",
       "4       505    2014  City10   Team8  Team2       Team2         field  normal   \n",
       "\n",
       "   dl_applied      venue  \n",
       "0           0  Stadium23  \n",
       "1           0   Stadium8  \n",
       "2           0   Stadium1  \n",
       "3           0   Stadium7  \n",
       "4           0  stadium35  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TestMatches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "ngaPxsLbfDrA"
   },
   "outputs": [],
   "source": [
    "#clean TestMatches for NaN, strings\n",
    "\n",
    "TestMatches['city'] = TestMatches['city'].str[4:]\n",
    "TestMatches['team1'] = TestMatches['team1'].str[4:]\n",
    "TestMatches['team2'] = TestMatches['team2'].str[4:]\n",
    "TestMatches['toss_winner'] = TestMatches['toss_winner'].str[4:]\n",
    "TestMatches['venue'] = TestMatches['venue'].str[7:]\n",
    "\n",
    "map1 = {'field':1, 'bat':2}\n",
    "TestMatches.replace({'toss_decision':map1}, inplace=True)\n",
    "\n",
    "map2 = {'normal':1, 'tie':2, 'no result':3}\n",
    "TestMatches.replace({'result':map2}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
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    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1671,
     "status": "ok",
     "timestamp": 1525863913037,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
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    },
    "id": "og3cAy4Rk3Ry",
    "outputId": "74b6db02-6642-416a-c697-931acdfcde5c"
   },
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>505</td>\n",
       "      <td>2014</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  season city team1 team2 toss_winner  toss_decision  result  \\\n",
       "0       501    2014   22     2     9           2              2       1   \n",
       "1       502    2014    9     7     8           8              1       1   \n",
       "2       503    2014    1     5     1           5              2       1   \n",
       "3       504    2014    8    10     6           6              1       1   \n",
       "4       505    2014   10     8     2           2              1       1   \n",
       "\n",
       "   dl_applied venue  \n",
       "0           0    23  \n",
       "1           0     8  \n",
       "2           0     1  \n",
       "3           0     7  \n",
       "4           0    35  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TestMatches.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Features\n",
    "\n",
    "We will first merge the two datasets(Deliveries and Matches) for both Train and Test.  \n",
    "Since we are predicting the winning team for a game, we have identified four features that don't have any foreseeable bearing on the outcome of the match. These features are:  \n",
    "\n",
    "1. Dismissal Kind:  \n",
    "It explains how a particular player was dismissed viz. caught, bowled, run out, lbw, caught and bowled, stumped, retired hurt, hit wicket and obstructing the field. These natures of dismissal don't affect the chances of which team wins the match. Rather it is the actual player dismissed which affects more. So we can safely drop this feature.  \n",
    "\n",
    "2. Win by Runs: \n",
    "It details by how many runs was a match won. This data gives information after a team has won and so it can be safely disregarded when determining which team will win the match.  \n",
    "\n",
    "3. Win by Wickets:  \n",
    "It details by how many wickets was a match won. Again, this data provides information after a team has won and so it can be safely disregarded when determining which team will the match.  \n",
    "\n",
    "4. Player of Match:  \n",
    "It explains who was the player of the match. This information has no bearing on who will win the match so it can be again disregarded.  \n",
    "\n",
    "This leaves us with the following features in our dataset:  \n",
    "\n",
    "1. Match ID:  \n",
    "It is the ID of each match played.  \n",
    "\n",
    "2. Inning:  \n",
    "It is a division of the cricket match during which one team takes its turn to bat.  \n",
    "\n",
    "3. Batting Team:  \n",
    "It is the ID of the batting team in the match.  \n",
    "\n",
    "4. Bowling Team:  \n",
    "It is the ID of the bowling team in the match.  \n",
    "\n",
    "5. Over:  \n",
    "The over number of the innings.\n",
    "\n",
    "6. Ball:  \n",
    "The ball number for a given over of the innings.\n",
    "7. Batsman:  \n",
    "The Player Id for a given batsman for a given ball.\n",
    "8. Non striker:  \n",
    "The Player Id for non-striker batsman for this ball.\n",
    "9. Bowler:  \n",
    "The player Id of bowler for this ball.\n",
    "10. Is super over:  \n",
    "A binary flag suggesting if this is a super over\n",
    "11. Wide Runs:  \n",
    "Number of wide runs on this ball\n",
    "12. Bye Runs:  \n",
    "Number of bye runs on this ball\n",
    "13. Legbye Runs:  \n",
    "Number of legbye runs on this ball\n",
    "14. Noball Runs:  \n",
    "Number of noball runs on this ball\n",
    "15. Penalty Runs:  \n",
    "Number of penalty runs on this ball\n",
    "16. Batsman Runs:  \n",
    "Number of batsman made runs on this ball\n",
    "17. Extra Runs:  \n",
    "Total number of extra runs on this ball (sum of wide, bye, legbye, noball, and penalty)\n",
    "18. Total Runs:  \n",
    "Total number of runs on this ball (sum of batsman_runs and extra_runs)\n",
    "19. Player Dismissed:\n",
    "Player dismissed on this ball if any (PlayerID)\n",
    "20. Fielder:  \n",
    "Fielder if dismissal_kind requires (PlayerID)\n",
    "21. Season:  \n",
    "Year of the match\n",
    "22. City:  \n",
    "City where match was played (CityID)\n",
    "23. Team1:  \n",
    "ID for team 1\n",
    "24. Team2:  \n",
    "ID for team 2\n",
    "25. Toss Winner:\n",
    "Which team won the toss (TeamID)\n",
    "26. Toss Decision:  \n",
    "What did the team decide to do? (field or bat)\n",
    "27. Result:  \n",
    "What was the result (normal or tie)\n",
    "28. DL Applied:  \n",
    "Was DL applied (binary)\n",
    "29. Venue:  \n",
    "Which stadium the match was played (StadiumID)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "autoexec": {
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     }
    },
    "colab_type": "code",
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    "id": "mK6sHvsGtBpU"
   },
   "outputs": [],
   "source": [
    "# join Appendix A and Appendix B data\n",
    "# Training data\n",
    "data = TrainDeliveries.join(TrainMatches.set_index('match_id'), on='match_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
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      "startup": false,
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     "height": 253
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1251,
     "status": "ok",
     "timestamp": 1525873277280,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
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    "id": "ZqogcMNyg3GA",
    "outputId": "3271f9a5-adb7-41bc-b459-b183ad9fde86"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "\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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>venue</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>winner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>105</td>\n",
       "      <td>354</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>105</td>\n",
       "      <td>354</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>105</td>\n",
       "      <td>354</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>354</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>105</td>\n",
       "      <td>354</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball batsman non_striker  \\\n",
       "0         1       1            1            5     1     1     105         354   \n",
       "1         1       1            1            5     1     2     105         354   \n",
       "2         1       1            1            5     1     3     105         354   \n",
       "3         1       1            1            5     1     4     105         354   \n",
       "4         1       1            1            5     1     5     105         354   \n",
       "\n",
       "  bowler  is_super_over  ...    team2  toss_winner  toss_decision  result  \\\n",
       "0    431              0  ...        5            5              1       1   \n",
       "1    431              0  ...        5            5              1       1   \n",
       "2    431              0  ...        5            5              1       1   \n",
       "3    431              0  ...        5            5              1       1   \n",
       "4    431              0  ...        5            5              1       1   \n",
       "\n",
       "   dl_applied  venue  win_by_runs  win_by_wickets player_of_match winner  \n",
       "0           0      1           35               0             467      1  \n",
       "1           0      1           35               0             467      1  \n",
       "2           0      1           35               0             467      1  \n",
       "3           0      1           35               0             467      1  \n",
       "4           0      1           35               0             467      1  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
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    "executionInfo": {
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     "status": "ok",
     "timestamp": 1525870374816,
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     },
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    },
    "id": "FMkOWrLgGBeR",
    "outputId": "3800f766-24ce-4a61-d4fc-62a1a9130be6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(118666, 34)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 612
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1072,
     "status": "ok",
     "timestamp": 1525873663184,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "w69LQ931Dim-",
    "outputId": "ef24611b-7d85-4194-d399-f6603de7cc70",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "match_id             int64\n",
       "inning               int64\n",
       "batting_team        object\n",
       "bowling_team        object\n",
       "over                 int64\n",
       "ball                 int64\n",
       "batsman             object\n",
       "non_striker         object\n",
       "bowler              object\n",
       "is_super_over        int64\n",
       "wide_runs            int64\n",
       "bye_runs             int64\n",
       "legbye_runs          int64\n",
       "noball_runs          int64\n",
       "penalty_runs         int64\n",
       "batsman_runs         int64\n",
       "extra_runs           int64\n",
       "total_runs           int64\n",
       "player_dismissed    object\n",
       "dismissal_kind      object\n",
       "fielder             object\n",
       "season               int64\n",
       "city                object\n",
       "team1               object\n",
       "team2               object\n",
       "toss_winner         object\n",
       "toss_decision        int64\n",
       "result               int64\n",
       "dl_applied           int64\n",
       "venue               object\n",
       "win_by_runs          int64\n",
       "win_by_wickets       int64\n",
       "player_of_match     object\n",
       "winner              object\n",
       "dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "WSx7C1ZgEiwI"
   },
   "outputs": [],
   "source": [
    "# Converting the datatypes into integer\n",
    "\n",
    "data['batting_team'] = data['batting_team'].astype('int64')\n",
    "data['bowling_team'] = data['bowling_team'].astype('int64')\n",
    "data['batsman'] = data['batsman'].astype('int64')\n",
    "data['non_striker'] = data['non_striker'].astype('int64')\n",
    "data['bowler'] = data['bowler'].astype('int64')\n",
    "data['player_dismissed'] = data['player_dismissed'].astype('int64')\n",
    "data['fielder'] = data['fielder'].astype('int64')\n",
    "data['city'] = data['city'].astype('int64')\n",
    "data['team1'] = data['team1'].astype('int64')\n",
    "data['team2'] = data['team2'].astype('int64')\n",
    "data['toss_winner'] = data['toss_winner'].astype('int64')\n",
    "data['venue'] = data['venue'].astype('int64')\n",
    "data['player_of_match'] = data['player_of_match'].astype('int64')\n",
    "data['winner'] = data['winner'].astype('int64')\n",
    "data.drop(['dismissal_kind'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
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      "wait_interval": 0
     },
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     "height": 595
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1017,
     "status": "ok",
     "timestamp": 1525873949360,
     "user": {
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      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "--K7bTarE-6u",
    "outputId": "a287042f-9531-4efb-ea2a-cfde637ec5a7",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "match_id            int64\n",
       "inning              int64\n",
       "batting_team        int64\n",
       "bowling_team        int64\n",
       "over                int64\n",
       "ball                int64\n",
       "batsman             int64\n",
       "non_striker         int64\n",
       "bowler              int64\n",
       "is_super_over       int64\n",
       "wide_runs           int64\n",
       "bye_runs            int64\n",
       "legbye_runs         int64\n",
       "noball_runs         int64\n",
       "penalty_runs        int64\n",
       "batsman_runs        int64\n",
       "extra_runs          int64\n",
       "total_runs          int64\n",
       "player_dismissed    int64\n",
       "fielder             int64\n",
       "season              int64\n",
       "city                int64\n",
       "team1               int64\n",
       "team2               int64\n",
       "toss_winner         int64\n",
       "toss_decision       int64\n",
       "result              int64\n",
       "dl_applied          int64\n",
       "venue               int64\n",
       "win_by_runs         int64\n",
       "win_by_wickets      int64\n",
       "player_of_match     int64\n",
       "winner              int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "Nj0Jwh5JG4xQ"
   },
   "outputs": [],
   "source": [
    "train = data.as_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
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     },
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1038,
     "status": "ok",
     "timestamp": 1525873508922,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "jp6d03eDBZdI",
    "outputId": "9b5b02b0-96ad-4bf3-dc3b-47095a2faeec"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.int64'>\n"
     ]
    }
   ],
   "source": [
    "# sample type printing\n",
    "print(type(train[20][7]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "4Bo-gSFXHfdM"
   },
   "outputs": [],
   "source": [
    "trainX = train[ : , :-4]\n",
    "trainY = train[ : , -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1098,
     "status": "ok",
     "timestamp": 1525875077142,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "K1w0F1SMN7na",
    "outputId": "bffc373e-e986-4984-f81f-ea989704de3d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(118666, 29)\n",
      "(118666,)\n"
     ]
    }
   ],
   "source": [
    "# Shape calculation\n",
    "print(trainX.shape)\n",
    "print(trainY.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 136
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1052,
     "status": "ok",
     "timestamp": 1525875083562,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "Zy1yloRmrgF5",
    "outputId": "32971b1f-06f5-4c03-9b74-cd1aac601f51"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 1 1 ..., 6 6 6]\n"
     ]
    }
   ],
   "source": [
    "# sample printing\n",
    "print(trainY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1053,
     "status": "ok",
     "timestamp": 1525873522950,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "PPwidf0Rxp8x",
    "outputId": "3805cb2f-0898-43d3-e2e2-f5ef94233b9b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.int64'>\n"
     ]
    }
   ],
   "source": [
    "print(type(trainX[0][2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "eh7PX_9oK5V4"
   },
   "outputs": [],
   "source": [
    "# join Appendix A and Appendix C data\n",
    "# Test data\n",
    "test = TestDeliveries.join(TestMatches.set_index('match_id'), on='match_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 1989
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1465,
     "status": "ok",
     "timestamp": 1525884362803,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "k45hGHoTm8xq",
    "outputId": "732a7897-caea-4054-8f67-cc45d8a0a6bd"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>fielder</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>venue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>234</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball batsman non_striker  \\\n",
       "0       501       1            2            9     1     1     260         234   \n",
       "1       501       1            2            9     1     2     234         260   \n",
       "2       501       1            2            9     1     3     234         260   \n",
       "3       501       1            2            9     1     4     234         260   \n",
       "4       501       1            2            9     1     5     234         260   \n",
       "\n",
       "  bowler  is_super_over  ...    fielder  season  city  team1  team2  \\\n",
       "0     48              0  ...          0    2014    22      2      9   \n",
       "1     48              0  ...          0    2014    22      2      9   \n",
       "2     48              0  ...          0    2014    22      2      9   \n",
       "3     48              0  ...          0    2014    22      2      9   \n",
       "4     48              0  ...          0    2014    22      2      9   \n",
       "\n",
       "   toss_winner  toss_decision  result dl_applied  venue  \n",
       "0            2              2       1          0     23  \n",
       "1            2              2       1          0     23  \n",
       "2            2              2       1          0     23  \n",
       "3            2              2       1          0     23  \n",
       "4            2              2       1          0     23  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 527
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1673,
     "status": "ok",
     "timestamp": 1525884438483,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "xIPdYTHUb7jc",
    "outputId": "bc6461a6-7e7e-4990-f0af-f801d8d95371",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "match_id             int64\n",
       "inning               int64\n",
       "batting_team        object\n",
       "bowling_team        object\n",
       "over                 int64\n",
       "ball                 int64\n",
       "batsman             object\n",
       "non_striker         object\n",
       "bowler              object\n",
       "is_super_over        int64\n",
       "wide_runs            int64\n",
       "bye_runs             int64\n",
       "legbye_runs          int64\n",
       "noball_runs          int64\n",
       "penalty_runs         int64\n",
       "batsman_runs         int64\n",
       "extra_runs           int64\n",
       "total_runs           int64\n",
       "player_dismissed    object\n",
       "dismissal_kind       int64\n",
       "fielder             object\n",
       "season               int64\n",
       "city                object\n",
       "team1               object\n",
       "team2               object\n",
       "toss_winner         object\n",
       "toss_decision        int64\n",
       "result               int64\n",
       "dl_applied           int64\n",
       "venue               object\n",
       "dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "h_oNo_FycGcT"
   },
   "outputs": [],
   "source": [
    "test['batting_team'] = test['batting_team'].astype(str).astype(int)\n",
    "test['bowling_team'] = test['bowling_team'].astype(str).astype('int64')\n",
    "test['batsman'] = test['batsman'].astype('int64')\n",
    "test['non_striker'] = test['non_striker'].astype('int64')\n",
    "test['bowler'] = test['bowler'].astype('int64')\n",
    "test['player_dismissed'] = test['player_dismissed'].astype('int64')\n",
    "test['fielder'] = test['fielder'].astype('int64')\n",
    "test['city'] = test['city'].astype('int64')\n",
    "test['team1'] = test['team1'].astype('int64')\n",
    "test['team2'] = test['team2'].astype('int64')\n",
    "test['toss_winner'] = test['toss_winner'].astype('int64')\n",
    "test['venue'] = test['venue'].astype('int64')\n",
    "test.drop(['dismissal_kind'], axis=1, inplace=True)         #dropping attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "v5LIj3DWm-ok"
   },
   "outputs": [],
   "source": [
    "test = test.as_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1199,
     "status": "ok",
     "timestamp": 1525883994667,
     "user": {
      "displayName": "Rajorshi Chaudhuri",
      "photoUrl": "//lh4.googleusercontent.com/-Hlr9hm2DtMQ/AAAAAAAAAAI/AAAAAAAABe0/FScKSLteKTQ/s50-c-k-no/photo.jpg",
      "userId": "116835544570119913049"
     },
     "user_tz": -330
    },
    "id": "OCm702UEnG3Q",
    "outputId": "8b1720db-1631-4d3c-f795-fa87e507cae0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31794, 29)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using GridCV to find best hyperparameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "params_grid = {\n",
    "    'criterion' :['entropy','gini'],\n",
    "    'max_features': ['auto', 'sqrt', 'log2'],\n",
    "    'max_depth':[5,8,12,15],\n",
    "    'min_samples_leaf':[5,8,12,15]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# training and validation set creation\n",
    "from sklearn.model_selection import train_test_split\n",
    "train_x, validation_x, train_y, validation_y = train_test_split(trainX, trainY, test_size=0.66, random_state = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'criterion': 'entropy', 'max_depth': 15, 'max_features': 'sqrt', 'min_samples_leaf': 5}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.99915730337078656"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using RandomForest model for GridCV\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "ranfor = RandomForestClassifier(n_jobs=-1)\n",
    "ranfor_GCV = GridSearchCV(estimator=ranfor, param_grid=params_grid, cv=5)\n",
    "ranfor_GCV.fit(train_x, train_y)\n",
    "print(ranfor_GCV.best_params_)\n",
    "ranfor_GCV.score(validation_x, validation_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make model using best parameters\n",
    "clf = RandomForestClassifier(criterion = 'entropy',\n",
    "                             max_features = 'sqrt',\n",
    "                             max_leaf_nodes = 15, \n",
    "                             n_estimators = 10, \n",
    "                             max_depth = 15,\n",
    "                             min_samples_leaf = 5,\n",
    "                             n_jobs =- 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy',\n",
       "            max_depth=15, max_features='sqrt', max_leaf_nodes=15,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=5, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=-1,\n",
       "            oob_score=False, random_state=None, verbose=0,\n",
       "            warm_start=False)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train model\n",
    "clf.fit(train_x, train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "FKWmcT4kQWIo"
   },
   "outputs": [],
   "source": [
    "# make predicitons on test dataset\n",
    "test_data_predictions = clf.predict(test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Here, we are making predictions for probable winner on each delivery of the match. The model looks at the inputs at each over for each ball and predicts a winner for each delivery. In order to get final winner, we look at the last occurrence of the match_id to get the final predicted winner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31794,)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data_predictions.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_test = TestDeliveries.join(TestMatches.set_index('match_id'), on='match_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "    }\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>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>...</th>\n",
       "      <th>fielder</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>venue</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
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       "      <td>22</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>23</td>\n",
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       "      <th>5</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
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       "      <td>6</td>\n",
       "      <td>260</td>\n",
       "      <td>234</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
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       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>501</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>234</td>\n",
       "      <td>260</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning batting_team bowling_team  over  ball batsman non_striker  \\\n",
       "0       501       1            2            9     1     1     260         234   \n",
       "1       501       1            2            9     1     2     234         260   \n",
       "2       501       1            2            9     1     3     234         260   \n",
       "3       501       1            2            9     1     4     234         260   \n",
       "4       501       1            2            9     1     5     234         260   \n",
       "5       501       1            2            9     1     6     260         234   \n",
       "6       501       1            2            9     2     1     234         260   \n",
       "7       501       1            2            9     2     2     234         260   \n",
       "8       501       1            2            9     2     3     234         260   \n",
       "9       501       1            2            9     2     4     234         260   \n",
       "\n",
       "  bowler  is_super_over  ...    fielder  season  city  team1  team2  \\\n",
       "0     48              0  ...          0    2014    22      2      9   \n",
       "1     48              0  ...          0    2014    22      2      9   \n",
       "2     48              0  ...          0    2014    22      2      9   \n",
       "3     48              0  ...          0    2014    22      2      9   \n",
       "4     48              0  ...          0    2014    22      2      9   \n",
       "5     48              0  ...          0    2014    22      2      9   \n",
       "6    136              0  ...          0    2014    22      2      9   \n",
       "7    136              0  ...          0    2014    22      2      9   \n",
       "8    136              0  ...          0    2014    22      2      9   \n",
       "9    136              0  ...          0    2014    22      2      9   \n",
       "\n",
       "   toss_winner  toss_decision  result dl_applied  venue  \n",
       "0            2              2       1          0     23  \n",
       "1            2              2       1          0     23  \n",
       "2            2              2       1          0     23  \n",
       "3            2              2       1          0     23  \n",
       "4            2              2       1          0     23  \n",
       "5            2              2       1          0     23  \n",
       "6            2              2       1          0     23  \n",
       "7            2              2       1          0     23  \n",
       "8            2              2       1          0     23  \n",
       "9            2              2       1          0     23  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_test.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# creating dataframe for each instance of delivery\n",
    "output = pd.DataFrame(new_test['match_id'])\n",
    "output['winner'] = test_data_predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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      ],
      "text/plain": [
       "      match_id  winner\n",
       "249        501       9\n",
       "502        502       8\n",
       "746        503       5\n",
       "978        504       6\n",
       "1221       505       2\n",
       "1468       506       5\n",
       "1710       507       1\n",
       "1953       508       2\n",
       "2200       509       9\n",
       "2431       510      10"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# selecting last instance to find final winner\n",
    "testing_df = output.copy(deep=True)\n",
    "testing_df.drop_duplicates(subset='match_id', keep='last', inplace=True)\n",
    "testing_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(136, 2)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making team 1 win flag as per the required output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testing_df['team1'] = TestMatches['team1'].values\n",
    "testing_df['team2'] = TestMatches['team2'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>509</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2431</th>\n",
       "      <td>510</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      match_id  winner team1 team2\n",
       "249        501       9     2     9\n",
       "502        502       8     7     8\n",
       "746        503       5     5     1\n",
       "978        504       6    10     6\n",
       "1221       505       2     8     2\n",
       "1468       506       5     6     5\n",
       "1710       507       1    10     1\n",
       "1953       508       2     2     7\n",
       "2200       509       9     8     9\n",
       "2431       510      10     5    10"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "testing_df['team1'] = testing_df['team1'].astype('int64')\n",
    "testing_df['team2'] = testing_df['team2'].astype('int64')\n",
    "testing_df['team_1_win_flag'] = np.where(testing_df['winner'] == testing_df['team1'],1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>winner</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>team_1_win_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>501</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>502</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>503</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>504</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1221</th>\n",
       "      <td>505</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>506</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1710</th>\n",
       "      <td>507</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1953</th>\n",
       "      <td>508</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>509</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2431</th>\n",
       "      <td>510</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2645</th>\n",
       "      <td>511</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2845</th>\n",
       "      <td>512</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3060</th>\n",
       "      <td>513</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3305</th>\n",
       "      <td>514</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3543</th>\n",
       "      <td>515</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>516</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4045</th>\n",
       "      <td>517</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4280</th>\n",
       "      <td>518</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4528</th>\n",
       "      <td>519</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4783</th>\n",
       "      <td>520</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5035</th>\n",
       "      <td>521</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5273</th>\n",
       "      <td>522</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5525</th>\n",
       "      <td>523</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5773</th>\n",
       "      <td>524</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6010</th>\n",
       "      <td>525</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6250</th>\n",
       "      <td>526</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6496</th>\n",
       "      <td>527</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6749</th>\n",
       "      <td>528</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6998</th>\n",
       "      <td>529</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7233</th>\n",
       "      <td>530</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25022</th>\n",
       "      <td>607</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25269</th>\n",
       "      <td>608</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25517</th>\n",
       "      <td>609</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25759</th>\n",
       "      <td>610</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26003</th>\n",
       "      <td>611</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26248</th>\n",
       "      <td>612</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26474</th>\n",
       "      <td>613</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26706</th>\n",
       "      <td>614</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26952</th>\n",
       "      <td>615</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27196</th>\n",
       "      <td>616</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27440</th>\n",
       "      <td>617</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27677</th>\n",
       "      <td>618</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27905</th>\n",
       "      <td>619</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28147</th>\n",
       "      <td>620</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28289</th>\n",
       "      <td>621</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28532</th>\n",
       "      <td>622</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28769</th>\n",
       "      <td>623</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29008</th>\n",
       "      <td>624</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29201</th>\n",
       "      <td>625</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29387</th>\n",
       "      <td>626</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29601</th>\n",
       "      <td>627</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29848</th>\n",
       "      <td>628</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30098</th>\n",
       "      <td>629</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30334</th>\n",
       "      <td>630</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30581</th>\n",
       "      <td>631</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30817</th>\n",
       "      <td>632</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31057</th>\n",
       "      <td>633</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31301</th>\n",
       "      <td>634</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31543</th>\n",
       "      <td>635</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31793</th>\n",
       "      <td>636</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       match_id  winner  team1  team2  team_1_win_flag\n",
       "249         501       9      2      9                0\n",
       "502         502       8      7      8                0\n",
       "746         503       5      5      1                1\n",
       "978         504       6     10      6                0\n",
       "1221        505       2      8      2                0\n",
       "1468        506       5      6      5                0\n",
       "1710        507       1     10      1                0\n",
       "1953        508       2      2      7                1\n",
       "2200        509       9      8      9                0\n",
       "2431        510      10      5     10                0\n",
       "2645        511       2      1      6                0\n",
       "2845        512       8      7      8                0\n",
       "3060        513       2      9      2                0\n",
       "3305        514       8      6      8                0\n",
       "3543        515      10      2     10                0\n",
       "3800        516      10      8     10                0\n",
       "4045        517       6      8      6                0\n",
       "4280        518       2      2      6                1\n",
       "4528        519      10     10      7                1\n",
       "4783        520       8      9      8                0\n",
       "5035        521      10     10      1                1\n",
       "5273        522       5      6      5                0\n",
       "5525        523       9      7      9                0\n",
       "5773        524       2      8      2                0\n",
       "6010        525       5      5      1                1\n",
       "6250        526       9      2      9                0\n",
       "6496        527       6     10      6                0\n",
       "6749        528       6      8      7                0\n",
       "6998        529       9      1      9                0\n",
       "7233        530       2      2     10                1\n",
       "...         ...     ...    ...    ...              ...\n",
       "25022       607       2      3      7                0\n",
       "25269       608       8      6      8                0\n",
       "25517       609       7      7      4                1\n",
       "25759       610       1      3      1                0\n",
       "26003       611       2      4      5                0\n",
       "26248       612       7      8      7                0\n",
       "26474       613       2      1      2                0\n",
       "26706       614       2      6      3                0\n",
       "26952       615       8      5      8                0\n",
       "27196       616       1      1      4                1\n",
       "27440       617       2      5      2                0\n",
       "27677       618       2      1      7                0\n",
       "27905       619       8      2      8                0\n",
       "28147       620       5      5      3                1\n",
       "28289       621       2      4      6                0\n",
       "28532       622       2      8      1                0\n",
       "28769       623       7      2      7                0\n",
       "29008       624       5      6      5                0\n",
       "29201       625       7      7      4                1\n",
       "29387       626       8      5      8                0\n",
       "29601       627       7      6      3                0\n",
       "29848       628       7      1      7                0\n",
       "30098       629       8      8      4                1\n",
       "30334       630       5      2      3                0\n",
       "30581       631       2      6      1                0\n",
       "30817       632       5      7      5                0\n",
       "31057       633       2      3      5                0\n",
       "31301       634       7      1      6                0\n",
       "31543       635       1      3      1                0\n",
       "31793       636       2      1      5                0\n",
       "\n",
       "[136 rows x 5 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "FinalSubmission_DF = pd.DataFrame({'match_id': testing_df['match_id'], 'team_1_win_flag': testing_df['team_1_win_flag']})\n",
    "FinalSubmission_DF.to_csv('FinalSubmission.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>team_1_win_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>501</td>\n",
       "      <td>0</td>\n",
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       "      <th>502</th>\n",
       "      <td>502</td>\n",
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       "    <tr>\n",
       "      <th>746</th>\n",
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       "      <td>509</td>\n",
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       "      <td>510</td>\n",
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       "      <th>5035</th>\n",
       "      <td>521</td>\n",
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       "    <tr>\n",
       "      <th>5273</th>\n",
       "      <td>522</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5525</th>\n",
       "      <td>523</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>524</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6010</th>\n",
       "      <td>525</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>6250</th>\n",
       "      <td>526</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6496</th>\n",
       "      <td>527</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6749</th>\n",
       "      <td>528</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6998</th>\n",
       "      <td>529</td>\n",
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       "      <th>7233</th>\n",
       "      <td>530</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>25022</th>\n",
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       "      <th>25517</th>\n",
       "      <td>609</td>\n",
       "      <td>1</td>\n",
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       "      <th>25759</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>26003</th>\n",
       "      <td>611</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>26248</th>\n",
       "      <td>612</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>26474</th>\n",
       "      <td>613</td>\n",
       "      <td>0</td>\n",
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       "      <td>614</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>26952</th>\n",
       "      <td>615</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>27196</th>\n",
       "      <td>616</td>\n",
       "      <td>1</td>\n",
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       "      <td>617</td>\n",
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       "    <tr>\n",
       "      <th>27677</th>\n",
       "      <td>618</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27905</th>\n",
       "      <td>619</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28147</th>\n",
       "      <td>620</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28289</th>\n",
       "      <td>621</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28532</th>\n",
       "      <td>622</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28769</th>\n",
       "      <td>623</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29008</th>\n",
       "      <td>624</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29201</th>\n",
       "      <td>625</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29387</th>\n",
       "      <td>626</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29601</th>\n",
       "      <td>627</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29848</th>\n",
       "      <td>628</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30098</th>\n",
       "      <td>629</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30334</th>\n",
       "      <td>630</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30581</th>\n",
       "      <td>631</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30817</th>\n",
       "      <td>632</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31057</th>\n",
       "      <td>633</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31301</th>\n",
       "      <td>634</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31543</th>\n",
       "      <td>635</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31793</th>\n",
       "      <td>636</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       match_id  team_1_win_flag\n",
       "249         501                0\n",
       "502         502                0\n",
       "746         503                1\n",
       "978         504                0\n",
       "1221        505                0\n",
       "1468        506                0\n",
       "1710        507                0\n",
       "1953        508                1\n",
       "2200        509                0\n",
       "2431        510                0\n",
       "2645        511                0\n",
       "2845        512                0\n",
       "3060        513                0\n",
       "3305        514                0\n",
       "3543        515                0\n",
       "3800        516                0\n",
       "4045        517                0\n",
       "4280        518                1\n",
       "4528        519                1\n",
       "4783        520                0\n",
       "5035        521                1\n",
       "5273        522                0\n",
       "5525        523                0\n",
       "5773        524                0\n",
       "6010        525                1\n",
       "6250        526                0\n",
       "6496        527                0\n",
       "6749        528                0\n",
       "6998        529                0\n",
       "7233        530                1\n",
       "...         ...              ...\n",
       "25022       607                0\n",
       "25269       608                0\n",
       "25517       609                1\n",
       "25759       610                0\n",
       "26003       611                0\n",
       "26248       612                0\n",
       "26474       613                0\n",
       "26706       614                0\n",
       "26952       615                0\n",
       "27196       616                1\n",
       "27440       617                0\n",
       "27677       618                0\n",
       "27905       619                0\n",
       "28147       620                1\n",
       "28289       621                0\n",
       "28532       622                0\n",
       "28769       623                0\n",
       "29008       624                0\n",
       "29201       625                1\n",
       "29387       626                0\n",
       "29601       627                0\n",
       "29848       628                0\n",
       "30098       629                1\n",
       "30334       630                0\n",
       "30581       631                0\n",
       "30817       632                0\n",
       "31057       633                0\n",
       "31301       634                0\n",
       "31543       635                0\n",
       "31793       636                0\n",
       "\n",
       "[136 rows x 2 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# submitting previous run CSV file, rerun generated new file\n",
    "FinalSubmission_DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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