masterclass_ipl_match_win_probability.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Live match win probability using Machine Learning\n",
    "\n",
    "\n",
    "![](./images/win_prb.jpeg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Problem Statement\n",
    "\n",
    "**`Make a win predictor that displays the probability of the chasing team winning an IPL match after every over.`**\n",
    "\n",
    "`Dataset`: https://www.kaggle.com/datasets/ramjidoolla/ipl-data-set\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "##importing the required libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</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>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",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>05-04-2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>06-04-2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>07-04-2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>08-04-2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>08-04-2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id    Season       city        date                        team1  \\\n",
       "0   1  IPL-2017  Hyderabad  05-04-2017          Sunrisers Hyderabad   \n",
       "1   2  IPL-2017       Pune  06-04-2017               Mumbai Indians   \n",
       "2   3  IPL-2017     Rajkot  07-04-2017                Gujarat Lions   \n",
       "3   4  IPL-2017     Indore  08-04-2017       Rising Pune Supergiant   \n",
       "4   5  IPL-2017  Bangalore  08-04-2017  Royal Challengers Bangalore   \n",
       "\n",
       "                         team2                  toss_winner toss_decision  \\\n",
       "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1       Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3              Kings XI Punjab              Kings XI Punjab         field   \n",
       "4             Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "\n",
       "   result  dl_applied                       winner  win_by_runs  \\\n",
       "0  normal           0          Sunrisers Hyderabad           35   \n",
       "1  normal           0       Rising Pune Supergiant            0   \n",
       "2  normal           0        Kolkata Knight Riders            0   \n",
       "3  normal           0              Kings XI Punjab            0   \n",
       "4  normal           0  Royal Challengers Bangalore           15   \n",
       "\n",
       "   win_by_wickets player_of_match                                      venue  \\\n",
       "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
       "1               7       SPD Smith    Maharashtra Cricket Association Stadium   \n",
       "2              10         CA Lynn     Saurashtra Cricket Association Stadium   \n",
       "3               6      GJ Maxwell                     Holkar Cricket Stadium   \n",
       "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
       "\n",
       "          umpire1        umpire2 umpire3  \n",
       "0     AY Dandekar       NJ Llong     NaN  \n",
       "1  A Nand Kishore         S Ravi     NaN  \n",
       "2     Nitin Menon      CK Nandan     NaN  \n",
       "3    AK Chaudhary  C Shamshuddin     NaN  \n",
       "4             NaN            NaN     NaN  "
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##loading the csv files into dataframes\n",
    "match_df = pd.read_csv(\"./ipl_data/matches.csv\")\n",
    "match_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 756 entries, 0 to 755\n",
      "Data columns (total 18 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               756 non-null    int64 \n",
      " 1   Season           756 non-null    object\n",
      " 2   city             749 non-null    object\n",
      " 3   date             756 non-null    object\n",
      " 4   team1            756 non-null    object\n",
      " 5   team2            756 non-null    object\n",
      " 6   toss_winner      756 non-null    object\n",
      " 7   toss_decision    756 non-null    object\n",
      " 8   result           756 non-null    object\n",
      " 9   dl_applied       756 non-null    int64 \n",
      " 10  winner           752 non-null    object\n",
      " 11  win_by_runs      756 non-null    int64 \n",
      " 12  win_by_wickets   756 non-null    int64 \n",
      " 13  player_of_match  752 non-null    object\n",
      " 14  venue            756 non-null    object\n",
      " 15  umpire1          754 non-null    object\n",
      " 16  umpire2          754 non-null    object\n",
      " 17  umpire3          119 non-null    object\n",
      "dtypes: int64(4), object(14)\n",
      "memory usage: 106.4+ KB\n"
     ]
    }
   ],
   "source": [
    "match_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(756, 18)"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions',\n",
       "       'Rising Pune Supergiant', 'Royal Challengers Bangalore',\n",
       "       'Kolkata Knight Riders', 'Delhi Daredevils', 'Kings XI Punjab',\n",
       "       'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers',\n",
       "       'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants',\n",
       "       'Delhi Capitals'], dtype=object)"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df['team1'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Important things to notice:\n",
    "\n",
    "- There is no score in this file.\n",
    "- No data on current run rate, required run rate.\n",
    "\n",
    "Let's read the second file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</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>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</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>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>TS Mills</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>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>TS Mills</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>TS Mills</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>A Choudhary</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>A Choudhary</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>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>S Dhawan</td>\n",
       "      <td>A Choudhary</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning         batting_team                 bowling_team  over  \\\n",
       "0         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "1         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "2         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "3         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "4         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "5         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "6         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     1   \n",
       "7         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     2   \n",
       "8         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     2   \n",
       "9         1       1  Sunrisers Hyderabad  Royal Challengers Bangalore     2   \n",
       "\n",
       "   ball    batsman non_striker       bowler  is_super_over  ...  bye_runs  \\\n",
       "0     1  DA Warner    S Dhawan     TS Mills              0  ...         0   \n",
       "1     2  DA Warner    S Dhawan     TS Mills              0  ...         0   \n",
       "2     3  DA Warner    S Dhawan     TS Mills              0  ...         0   \n",
       "3     4  DA Warner    S Dhawan     TS Mills              0  ...         0   \n",
       "4     5  DA Warner    S Dhawan     TS Mills              0  ...         0   \n",
       "5     6   S Dhawan   DA Warner     TS Mills              0  ...         0   \n",
       "6     7   S Dhawan   DA Warner     TS Mills              0  ...         0   \n",
       "7     1   S Dhawan   DA Warner  A Choudhary              0  ...         0   \n",
       "8     2  DA Warner    S Dhawan  A Choudhary              0  ...         0   \n",
       "9     3  DA Warner    S Dhawan  A Choudhary              0  ...         0   \n",
       "\n",
       "   legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",
       "0            0            0             0             0           0   \n",
       "1            0            0             0             0           0   \n",
       "2            0            0             0             4           0   \n",
       "3            0            0             0             0           0   \n",
       "4            0            0             0             0           2   \n",
       "5            0            0             0             0           0   \n",
       "6            1            0             0             0           1   \n",
       "7            0            0             0             1           0   \n",
       "8            0            0             0             4           0   \n",
       "9            0            1             0             0           1   \n",
       "\n",
       "   total_runs  player_dismissed dismissal_kind fielder  \n",
       "0           0               NaN            NaN     NaN  \n",
       "1           0               NaN            NaN     NaN  \n",
       "2           4               NaN            NaN     NaN  \n",
       "3           0               NaN            NaN     NaN  \n",
       "4           2               NaN            NaN     NaN  \n",
       "5           0               NaN            NaN     NaN  \n",
       "6           1               NaN            NaN     NaN  \n",
       "7           1               NaN            NaN     NaN  \n",
       "8           4               NaN            NaN     NaN  \n",
       "9           1               NaN            NaN     NaN  \n",
       "\n",
       "[10 rows x 21 columns]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##reading the second file from the dataset\n",
    "dlvr_df = pd.read_csv(\"./ipl_data/deliveries.csv\")\n",
    "dlvr_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 179078 entries, 0 to 179077\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count   Dtype \n",
      "---  ------            --------------   ----- \n",
      " 0   match_id          179078 non-null  int64 \n",
      " 1   inning            179078 non-null  int64 \n",
      " 2   batting_team      179078 non-null  object\n",
      " 3   bowling_team      179078 non-null  object\n",
      " 4   over              179078 non-null  int64 \n",
      " 5   ball              179078 non-null  int64 \n",
      " 6   batsman           179078 non-null  object\n",
      " 7   non_striker       179078 non-null  object\n",
      " 8   bowler            179078 non-null  object\n",
      " 9   is_super_over     179078 non-null  int64 \n",
      " 10  wide_runs         179078 non-null  int64 \n",
      " 11  bye_runs          179078 non-null  int64 \n",
      " 12  legbye_runs       179078 non-null  int64 \n",
      " 13  noball_runs       179078 non-null  int64 \n",
      " 14  penalty_runs      179078 non-null  int64 \n",
      " 15  batsman_runs      179078 non-null  int64 \n",
      " 16  extra_runs        179078 non-null  int64 \n",
      " 17  total_runs        179078 non-null  int64 \n",
      " 18  player_dismissed  8834 non-null    object\n",
      " 19  dismissal_kind    8834 non-null    object\n",
      " 20  fielder           6448 non-null    object\n",
      "dtypes: int64(13), object(8)\n",
      "memory usage: 28.7+ MB\n"
     ]
    }
   ],
   "source": [
    "dlvr_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll have to calculate scores from the deliveries data and then add it to matches data.\n",
    "\n",
    "## Total score in every inning in every match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "match_id  inning\n",
       "1         1         207\n",
       "          2         172\n",
       "2         1         184\n",
       "          2         187\n",
       "3         1         183\n",
       "                   ... \n",
       "11413     2         170\n",
       "11414     1         155\n",
       "          2         162\n",
       "11415     1         152\n",
       "          2         157\n",
       "Name: total_runs, Length: 1528, dtype: int64"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df.groupby(['match_id', 'inning']).sum()['total_runs']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1518</th>\n",
       "      <td>11347</td>\n",
       "      <td>1</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1520</th>\n",
       "      <td>11412</td>\n",
       "      <td>1</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1522</th>\n",
       "      <td>11413</td>\n",
       "      <td>1</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1524</th>\n",
       "      <td>11414</td>\n",
       "      <td>1</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1526</th>\n",
       "      <td>11415</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      match_id  inning  total_runs\n",
       "0            1       1         207\n",
       "2            2       1         184\n",
       "4            3       1         183\n",
       "6            4       1         163\n",
       "8            5       1         157\n",
       "...        ...     ...         ...\n",
       "1518     11347       1         143\n",
       "1520     11412       1         136\n",
       "1522     11413       1         171\n",
       "1524     11414       1         155\n",
       "1526     11415       1         152\n",
       "\n",
       "[756 rows x 3 columns]"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inn_score = dlvr_df.groupby(['match_id', 'inning']).sum()['total_runs'].reset_index()\n",
    "\n",
    "## we need only 1st innings score from here.\n",
    "inn_score = inn_score[inn_score['inning'] == 1]\n",
    "inn_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge the match_df with inn_scores dataframe on `id`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</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>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",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "      <th>match_id</th>\n",
       "      <th>total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>05-04-2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>Yuvraj Singh</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Pune</td>\n",
       "      <td>06-04-2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>SPD Smith</td>\n",
       "      <td>Maharashtra Cricket Association Stadium</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>07-04-2017</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>CA Lynn</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Indore</td>\n",
       "      <td>08-04-2017</td>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>GJ Maxwell</td>\n",
       "      <td>Holkar Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>08-04-2017</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>KM Jadhav</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>IPL-2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>05-05-2019</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>HH Pandya</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>Nanda Kishore</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>11347</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>IPL-2019</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>07-05-2019</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>AS Yadav</td>\n",
       "      <td>M. A. Chidambaram Stadium</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>11412</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>IPL-2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>08-05-2019</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11413</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>IPL-2019</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>10-05-2019</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>F du Plessis</td>\n",
       "      <td>ACA-VDCA Stadium</td>\n",
       "      <td>Sundaram Ravi</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>Chettithody Shamshuddin</td>\n",
       "      <td>11414</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>IPL-2019</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>12-05-2019</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Rajiv Gandhi Intl. Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>Ian Gould</td>\n",
       "      <td>Nigel Llong</td>\n",
       "      <td>11415</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>756 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id    Season           city        date                        team1  \\\n",
       "0        1  IPL-2017      Hyderabad  05-04-2017          Sunrisers Hyderabad   \n",
       "1        2  IPL-2017           Pune  06-04-2017               Mumbai Indians   \n",
       "2        3  IPL-2017         Rajkot  07-04-2017                Gujarat Lions   \n",
       "3        4  IPL-2017         Indore  08-04-2017       Rising Pune Supergiant   \n",
       "4        5  IPL-2017      Bangalore  08-04-2017  Royal Challengers Bangalore   \n",
       "..     ...       ...            ...         ...                          ...   \n",
       "751  11347  IPL-2019         Mumbai  05-05-2019        Kolkata Knight Riders   \n",
       "752  11412  IPL-2019        Chennai  07-05-2019          Chennai Super Kings   \n",
       "753  11413  IPL-2019  Visakhapatnam  08-05-2019          Sunrisers Hyderabad   \n",
       "754  11414  IPL-2019  Visakhapatnam  10-05-2019               Delhi Capitals   \n",
       "755  11415  IPL-2019      Hyderabad  12-05-2019               Mumbai Indians   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "0    Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "1         Rising Pune Supergiant       Rising Pune Supergiant         field   \n",
       "2          Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "3                Kings XI Punjab              Kings XI Punjab         field   \n",
       "4               Delhi Daredevils  Royal Challengers Bangalore           bat   \n",
       "..                           ...                          ...           ...   \n",
       "751               Mumbai Indians               Mumbai Indians         field   \n",
       "752               Mumbai Indians          Chennai Super Kings           bat   \n",
       "753               Delhi Capitals               Delhi Capitals         field   \n",
       "754          Chennai Super Kings          Chennai Super Kings         field   \n",
       "755          Chennai Super Kings               Mumbai Indians           bat   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "0    normal           0          Sunrisers Hyderabad           35   \n",
       "1    normal           0       Rising Pune Supergiant            0   \n",
       "2    normal           0        Kolkata Knight Riders            0   \n",
       "3    normal           0              Kings XI Punjab            0   \n",
       "4    normal           0  Royal Challengers Bangalore           15   \n",
       "..      ...         ...                          ...          ...   \n",
       "751  normal           0               Mumbai Indians            0   \n",
       "752  normal           0               Mumbai Indians            0   \n",
       "753  normal           0               Delhi Capitals            0   \n",
       "754  normal           0          Chennai Super Kings            0   \n",
       "755  normal           0               Mumbai Indians            1   \n",
       "\n",
       "     win_by_wickets player_of_match  \\\n",
       "0                 0    Yuvraj Singh   \n",
       "1                 7       SPD Smith   \n",
       "2                10         CA Lynn   \n",
       "3                 6      GJ Maxwell   \n",
       "4                 0       KM Jadhav   \n",
       "..              ...             ...   \n",
       "751               9       HH Pandya   \n",
       "752               6        AS Yadav   \n",
       "753               2         RR Pant   \n",
       "754               6    F du Plessis   \n",
       "755               0       JJ Bumrah   \n",
       "\n",
       "                                         venue         umpire1  \\\n",
       "0    Rajiv Gandhi International Stadium, Uppal     AY Dandekar   \n",
       "1      Maharashtra Cricket Association Stadium  A Nand Kishore   \n",
       "2       Saurashtra Cricket Association Stadium     Nitin Menon   \n",
       "3                       Holkar Cricket Stadium    AK Chaudhary   \n",
       "4                        M Chinnaswamy Stadium             NaN   \n",
       "..                                         ...             ...   \n",
       "751                           Wankhede Stadium   Nanda Kishore   \n",
       "752                  M. A. Chidambaram Stadium     Nigel Llong   \n",
       "753                           ACA-VDCA Stadium             NaN   \n",
       "754                           ACA-VDCA Stadium   Sundaram Ravi   \n",
       "755         Rajiv Gandhi Intl. Cricket Stadium     Nitin Menon   \n",
       "\n",
       "            umpire2                  umpire3  match_id  total_runs  \n",
       "0          NJ Llong                      NaN         1         207  \n",
       "1            S Ravi                      NaN         2         184  \n",
       "2         CK Nandan                      NaN         3         183  \n",
       "3     C Shamshuddin                      NaN         4         163  \n",
       "4               NaN                      NaN         5         157  \n",
       "..              ...                      ...       ...         ...  \n",
       "751        O Nandan                   S Ravi     11347         143  \n",
       "752     Nitin Menon                Ian Gould     11412         136  \n",
       "753             NaN                      NaN     11413         171  \n",
       "754  Bruce Oxenford  Chettithody Shamshuddin     11414         155  \n",
       "755       Ian Gould              Nigel Llong     11415         152  \n",
       "\n",
       "[756 rows x 20 columns]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df = match_df.merge(inn_score[['match_id','total_runs']], left_on='id', right_on='match_id')\n",
    "match_df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clean up the dataframe\n",
    "\n",
    "- Remove the duplicate teams."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_df['team1'] = match_df['team1'].str.replace('Deccan Chargers','Sunrisers Hyderabad')\n",
    "match_df['team2'] = match_df['team2'].str.replace('Deccan Chargers','Sunrisers Hyderabad')\n",
    "\n",
    "match_df['team1'] = match_df['team1'].str.replace('Delhi Daredevils','Delhi Capitals')\n",
    "match_df['team2'] = match_df['team2'].str.replace('Delhi Daredevils','Delhi Capitals')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Keeping data for only existing teams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "teams = [\n",
    "    'Chennai Super Kings',\n",
    "    'Delhi Capitals',\n",
    "    'Mumbai Indians',\n",
    "    'Kolkata Knight Riders',\n",
    "    'Kings XI Punjab',\n",
    "    'Rajasthan Royals',\n",
    "    'Royal Challengers Bangalore',\n",
    "    'Sunrisers Hyderabad'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "## using isin method to retain rows that are in the list above\n",
    "match_df = match_df[match_df['team1'].isin(teams)]\n",
    "match_df = match_df[match_df['team2'].isin(teams)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(641, 20)"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting rid of Duckworth-Lewis Matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1])"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df['dl_applied'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>Season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</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>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",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "      <th>match_id</th>\n",
       "      <th>total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>IPL-2017</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>17-05-2017</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>NM Coulter-Nile</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>IPL-2008</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>17-05-2008</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>DPMD Jayawardene</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>AV Jayaprakash</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>103</td>\n",
       "      <td>IPL-2008</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>18-05-2008</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>M Ntini</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>120</td>\n",
       "      <td>IPL-2009</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>19-04-2009</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>DL Vettori</td>\n",
       "      <td>Newlands</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>SD Ranade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>123</td>\n",
       "      <td>IPL-2009</td>\n",
       "      <td>Durban</td>\n",
       "      <td>21-04-2009</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>Kingsmead</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>SD Ranade</td>\n",
       "      <td>NaN</td>\n",
       "      <td>123</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>149</td>\n",
       "      <td>IPL-2009</td>\n",
       "      <td>Centurion</td>\n",
       "      <td>07-05-2009</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>ML Hayden</td>\n",
       "      <td>SuperSport Park</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>TH Wijewardene</td>\n",
       "      <td>NaN</td>\n",
       "      <td>149</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>281</td>\n",
       "      <td>IPL-2011</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>07-05-2011</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Iqbal Abdulla</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>PR Reiffel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>281</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>291</td>\n",
       "      <td>IPL-2011</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>14-05-2011</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>RB Tiffin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>291</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>489</td>\n",
       "      <td>IPL-2014</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>10-05-2014</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>DW Steyn</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>RM Deshpande</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>NaN</td>\n",
       "      <td>489</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>537</td>\n",
       "      <td>IPL-2015</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>22-04-2015</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...</td>\n",
       "      <td>RK Illingworth</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "      <td>537</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>568</td>\n",
       "      <td>IPL-2015</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>15-05-2015</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>NaN</td>\n",
       "      <td>568</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>625</th>\n",
       "      <td>626</td>\n",
       "      <td>IPL-2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>18-05-2016</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>626</td>\n",
       "      <td>211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>641</th>\n",
       "      <td>7899</td>\n",
       "      <td>IPL-2018</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>11-04-2018</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>SV Samson</td>\n",
       "      <td>Sawai Mansingh Stadium</td>\n",
       "      <td>K Ananthapadmanabhan</td>\n",
       "      <td>Rod Tucker</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>7899</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653</th>\n",
       "      <td>7911</td>\n",
       "      <td>IPL-2018</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>21-04-2018</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>KL Rahul</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>A.D Deshmukh</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>7911</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>667</th>\n",
       "      <td>7925</td>\n",
       "      <td>IPL-2018</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>02-05-2018</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>1</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>RR Pant</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>O Nandan</td>\n",
       "      <td>Virender Kumar Sharma</td>\n",
       "      <td>Bruce Oxenford</td>\n",
       "      <td>7925</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id    Season           city        date                        team1  \\\n",
       "56     57  IPL-2017      Bangalore  17-05-2017          Sunrisers Hyderabad   \n",
       "99    100  IPL-2008          Delhi  17-05-2008               Delhi Capitals   \n",
       "102   103  IPL-2008        Kolkata  18-05-2008        Kolkata Knight Riders   \n",
       "119   120  IPL-2009      Cape Town  19-04-2009              Kings XI Punjab   \n",
       "122   123  IPL-2009         Durban  21-04-2009              Kings XI Punjab   \n",
       "148   149  IPL-2009      Centurion  07-05-2009          Chennai Super Kings   \n",
       "280   281  IPL-2011        Kolkata  07-05-2011          Chennai Super Kings   \n",
       "290   291  IPL-2011      Bangalore  14-05-2011        Kolkata Knight Riders   \n",
       "488   489  IPL-2014          Delhi  10-05-2014               Delhi Capitals   \n",
       "536   537  IPL-2015  Visakhapatnam  22-04-2015          Sunrisers Hyderabad   \n",
       "567   568  IPL-2015      Hyderabad  15-05-2015          Sunrisers Hyderabad   \n",
       "625   626  IPL-2016      Bangalore  18-05-2016  Royal Challengers Bangalore   \n",
       "641  7899  IPL-2018         Jaipur  11-04-2018             Rajasthan Royals   \n",
       "653  7911  IPL-2018        Kolkata  21-04-2018        Kolkata Knight Riders   \n",
       "667  7925  IPL-2018          Delhi  02-05-2018               Delhi Capitals   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "56         Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "99               Kings XI Punjab             Delhi Daredevils           bat   \n",
       "102          Chennai Super Kings        Kolkata Knight Riders           bat   \n",
       "119               Delhi Capitals             Delhi Daredevils         field   \n",
       "122        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "148              Kings XI Punjab          Chennai Super Kings           bat   \n",
       "280        Kolkata Knight Riders          Chennai Super Kings           bat   \n",
       "290  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
       "488          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "536        Kolkata Knight Riders        Kolkata Knight Riders         field   \n",
       "567  Royal Challengers Bangalore          Sunrisers Hyderabad           bat   \n",
       "625              Kings XI Punjab              Kings XI Punjab         field   \n",
       "641               Delhi Capitals             Delhi Daredevils         field   \n",
       "653              Kings XI Punjab              Kings XI Punjab         field   \n",
       "667             Rajasthan Royals             Rajasthan Royals         field   \n",
       "\n",
       "     result  dl_applied                       winner  win_by_runs  \\\n",
       "56   normal           1        Kolkata Knight Riders            0   \n",
       "99   normal           1              Kings XI Punjab            6   \n",
       "102  normal           1          Chennai Super Kings            3   \n",
       "119  normal           1             Delhi Daredevils            0   \n",
       "122  normal           1        Kolkata Knight Riders           11   \n",
       "148  normal           1          Chennai Super Kings           12   \n",
       "280  normal           1        Kolkata Knight Riders           10   \n",
       "290  normal           1  Royal Challengers Bangalore            0   \n",
       "488  normal           1          Sunrisers Hyderabad            0   \n",
       "536  normal           1          Sunrisers Hyderabad           16   \n",
       "567  normal           1  Royal Challengers Bangalore            0   \n",
       "625  normal           1  Royal Challengers Bangalore           82   \n",
       "641  normal           1             Rajasthan Royals           10   \n",
       "653  normal           1              Kings XI Punjab            0   \n",
       "667  normal           1             Delhi Daredevils            4   \n",
       "\n",
       "     win_by_wickets   player_of_match  \\\n",
       "56                7   NM Coulter-Nile   \n",
       "99                0  DPMD Jayawardene   \n",
       "102               0           M Ntini   \n",
       "119              10        DL Vettori   \n",
       "122               0          CH Gayle   \n",
       "148               0         ML Hayden   \n",
       "280               0     Iqbal Abdulla   \n",
       "290               4          CH Gayle   \n",
       "488               8          DW Steyn   \n",
       "536               0         DA Warner   \n",
       "567               6           V Kohli   \n",
       "625               0           V Kohli   \n",
       "641               0         SV Samson   \n",
       "653               9          KL Rahul   \n",
       "667               0           RR Pant   \n",
       "\n",
       "                                                 venue                umpire1  \\\n",
       "56                               M Chinnaswamy Stadium           AK Chaudhary   \n",
       "99                                    Feroz Shah Kotla         AV Jayaprakash   \n",
       "102                                       Eden Gardens              Asad Rauf   \n",
       "119                                           Newlands              MR Benson   \n",
       "122                                          Kingsmead              DJ Harper   \n",
       "148                                    SuperSport Park              DJ Harper   \n",
       "280                                       Eden Gardens              Asad Rauf   \n",
       "290                              M Chinnaswamy Stadium            RE Koertzen   \n",
       "488                                   Feroz Shah Kotla           RM Deshpande   \n",
       "536  Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St...         RK Illingworth   \n",
       "567          Rajiv Gandhi International Stadium, Uppal           AK Chaudhary   \n",
       "625                              M Chinnaswamy Stadium  KN Ananthapadmanabhan   \n",
       "641                             Sawai Mansingh Stadium   K Ananthapadmanabhan   \n",
       "653                                       Eden Gardens          C Shamshuddin   \n",
       "667                                   Feroz Shah Kotla               O Nandan   \n",
       "\n",
       "                   umpire2         umpire3  match_id  total_runs  \n",
       "56             Nitin Menon             NaN        57         128  \n",
       "99             RE Koertzen             NaN       100         118  \n",
       "102            K Hariharan             NaN       103         149  \n",
       "119              SD Ranade             NaN       120         104  \n",
       "122              SD Ranade             NaN       123         158  \n",
       "148         TH Wijewardene             NaN       149         185  \n",
       "280             PR Reiffel             NaN       281         114  \n",
       "290              RB Tiffin             NaN       291          89  \n",
       "488           BNJ Oxenford             NaN       489         143  \n",
       "536            VA Kulkarni             NaN       537         176  \n",
       "567        HDPK Dharmasena             NaN       568         135  \n",
       "625              M Erasmus             NaN       626         211  \n",
       "641             Rod Tucker     Nitin Menon      7899         156  \n",
       "653           A.D Deshmukh          S Ravi      7911         200  \n",
       "667  Virender Kumar Sharma  Bruce Oxenford      7925         203  "
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## looking at DL matches\n",
    "match_df[match_df['dl_applied'] == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "## filtering all the matches where D/L was not applied\n",
    "match_df = match_df[match_df['dl_applied'] == 0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting rid of redundant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_df = match_df[['match_id','city','winner','total_runs']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Indore</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>11347</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>11412</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>11413</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>11414</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>626 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id           city                       winner  total_runs\n",
       "0           1      Hyderabad          Sunrisers Hyderabad         207\n",
       "4           5      Bangalore  Royal Challengers Bangalore         157\n",
       "6           7         Mumbai               Mumbai Indians         178\n",
       "7           8         Indore              Kings XI Punjab         148\n",
       "9          10         Mumbai               Mumbai Indians         158\n",
       "..        ...            ...                          ...         ...\n",
       "751     11347         Mumbai               Mumbai Indians         143\n",
       "752     11412        Chennai               Mumbai Indians         136\n",
       "753     11413  Visakhapatnam               Delhi Capitals         171\n",
       "754     11414  Visakhapatnam          Chennai Super Kings         155\n",
       "755     11415      Hyderabad               Mumbai Indians         152\n",
       "\n",
       "[626 rows x 4 columns]"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Match status in the 2nd innings\n",
    "\n",
    "- Using this 1st innings data and scores, we'll prepare the 2nd innings data that will be fed to the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</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_y</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>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>DA Warner</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>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>DA Warner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149573</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>RA Jadeja</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149574</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149575</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>run out</td>\n",
       "      <td>KH Pandya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149576</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149577</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>lbw</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>149578 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id       city               winner  total_runs_x  inning  \\\n",
       "0              1  Hyderabad  Sunrisers Hyderabad           207       1   \n",
       "1              1  Hyderabad  Sunrisers Hyderabad           207       1   \n",
       "2              1  Hyderabad  Sunrisers Hyderabad           207       1   \n",
       "3              1  Hyderabad  Sunrisers Hyderabad           207       1   \n",
       "4              1  Hyderabad  Sunrisers Hyderabad           207       1   \n",
       "...          ...        ...                  ...           ...     ...   \n",
       "149573     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149574     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149575     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149576     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149577     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "\n",
       "               batting_team                 bowling_team  over  ball  \\\n",
       "0       Sunrisers Hyderabad  Royal Challengers Bangalore     1     1   \n",
       "1       Sunrisers Hyderabad  Royal Challengers Bangalore     1     2   \n",
       "2       Sunrisers Hyderabad  Royal Challengers Bangalore     1     3   \n",
       "3       Sunrisers Hyderabad  Royal Challengers Bangalore     1     4   \n",
       "4       Sunrisers Hyderabad  Royal Challengers Bangalore     1     5   \n",
       "...                     ...                          ...   ...   ...   \n",
       "149573  Chennai Super Kings               Mumbai Indians    20     2   \n",
       "149574  Chennai Super Kings               Mumbai Indians    20     3   \n",
       "149575  Chennai Super Kings               Mumbai Indians    20     4   \n",
       "149576  Chennai Super Kings               Mumbai Indians    20     5   \n",
       "149577  Chennai Super Kings               Mumbai Indians    20     6   \n",
       "\n",
       "          batsman  ... bye_runs legbye_runs  noball_runs  penalty_runs  \\\n",
       "0       DA Warner  ...        0           0            0             0   \n",
       "1       DA Warner  ...        0           0            0             0   \n",
       "2       DA Warner  ...        0           0            0             0   \n",
       "3       DA Warner  ...        0           0            0             0   \n",
       "4       DA Warner  ...        0           0            0             0   \n",
       "...           ...  ...      ...         ...          ...           ...   \n",
       "149573  RA Jadeja  ...        0           0            0             0   \n",
       "149574  SR Watson  ...        0           0            0             0   \n",
       "149575  SR Watson  ...        0           0            0             0   \n",
       "149576  SN Thakur  ...        0           0            0             0   \n",
       "149577  SN Thakur  ...        0           0            0             0   \n",
       "\n",
       "        batsman_runs  extra_runs  total_runs_y  player_dismissed  \\\n",
       "0                  0           0             0               NaN   \n",
       "1                  0           0             0               NaN   \n",
       "2                  4           0             4               NaN   \n",
       "3                  0           0             0               NaN   \n",
       "4                  0           2             2               NaN   \n",
       "...              ...         ...           ...               ...   \n",
       "149573             1           0             1               NaN   \n",
       "149574             2           0             2               NaN   \n",
       "149575             1           0             1         SR Watson   \n",
       "149576             2           0             2               NaN   \n",
       "149577             0           0             0         SN Thakur   \n",
       "\n",
       "        dismissal_kind    fielder  \n",
       "0                  NaN        NaN  \n",
       "1                  NaN        NaN  \n",
       "2                  NaN        NaN  \n",
       "3                  NaN        NaN  \n",
       "4                  NaN        NaN  \n",
       "...                ...        ...  \n",
       "149573             NaN        NaN  \n",
       "149574             NaN        NaN  \n",
       "149575         run out  KH Pandya  \n",
       "149576             NaN        NaN  \n",
       "149577             lbw        NaN  \n",
       "\n",
       "[149578 rows x 24 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df = match_df.merge(dlvr_df, on=\"match_id\")\n",
    "dlvr_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "## filtering 2nd innings deliveries\n",
    "dlvr_df = dlvr_df[dlvr_df['inning'] == 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</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_y</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>125</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</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>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149573</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>RA Jadeja</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149574</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149575</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>run out</td>\n",
       "      <td>KH Pandya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149576</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149577</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>lbw</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72413 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id       city               winner  total_runs_x  inning  \\\n",
       "125            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "...          ...        ...                  ...           ...     ...   \n",
       "149573     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149574     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149575     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149576     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149577     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "\n",
       "                       batting_team         bowling_team  over  ball  \\\n",
       "125     Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126     Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127     Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128     Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129     Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "...                             ...                  ...   ...   ...   \n",
       "149573          Chennai Super Kings       Mumbai Indians    20     2   \n",
       "149574          Chennai Super Kings       Mumbai Indians    20     3   \n",
       "149575          Chennai Super Kings       Mumbai Indians    20     4   \n",
       "149576          Chennai Super Kings       Mumbai Indians    20     5   \n",
       "149577          Chennai Super Kings       Mumbai Indians    20     6   \n",
       "\n",
       "              batsman  ... bye_runs legbye_runs  noball_runs  penalty_runs  \\\n",
       "125          CH Gayle  ...        0           0            0             0   \n",
       "126     Mandeep Singh  ...        0           0            0             0   \n",
       "127     Mandeep Singh  ...        0           0            0             0   \n",
       "128     Mandeep Singh  ...        0           0            0             0   \n",
       "129     Mandeep Singh  ...        0           0            0             0   \n",
       "...               ...  ...      ...         ...          ...           ...   \n",
       "149573      RA Jadeja  ...        0           0            0             0   \n",
       "149574      SR Watson  ...        0           0            0             0   \n",
       "149575      SR Watson  ...        0           0            0             0   \n",
       "149576      SN Thakur  ...        0           0            0             0   \n",
       "149577      SN Thakur  ...        0           0            0             0   \n",
       "\n",
       "        batsman_runs  extra_runs  total_runs_y  player_dismissed  \\\n",
       "125                1           0             1               NaN   \n",
       "126                0           0             0               NaN   \n",
       "127                0           0             0               NaN   \n",
       "128                2           0             2               NaN   \n",
       "129                4           0             4               NaN   \n",
       "...              ...         ...           ...               ...   \n",
       "149573             1           0             1               NaN   \n",
       "149574             2           0             2               NaN   \n",
       "149575             1           0             1         SR Watson   \n",
       "149576             2           0             2               NaN   \n",
       "149577             0           0             0         SN Thakur   \n",
       "\n",
       "        dismissal_kind    fielder  \n",
       "125                NaN        NaN  \n",
       "126                NaN        NaN  \n",
       "127                NaN        NaN  \n",
       "128                NaN        NaN  \n",
       "129                NaN        NaN  \n",
       "...                ...        ...  \n",
       "149573             NaN        NaN  \n",
       "149574             NaN        NaN  \n",
       "149575         run out  KH Pandya  \n",
       "149576             NaN        NaN  \n",
       "149577             lbw        NaN  \n",
       "\n",
       "[72413 rows x 24 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</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_y</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "      <th>current_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</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",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id       city               winner  total_runs_x  inning  \\\n",
       "125         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "\n",
       "                    batting_team         bowling_team  over  ball  \\\n",
       "125  Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126  Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127  Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128  Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129  Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "\n",
       "           batsman  ... legbye_runs noball_runs  penalty_runs  batsman_runs  \\\n",
       "125       CH Gayle  ...           0           0             0             1   \n",
       "126  Mandeep Singh  ...           0           0             0             0   \n",
       "127  Mandeep Singh  ...           0           0             0             0   \n",
       "128  Mandeep Singh  ...           0           0             0             2   \n",
       "129  Mandeep Singh  ...           0           0             0             4   \n",
       "\n",
       "     extra_runs  total_runs_y  player_dismissed  dismissal_kind  fielder  \\\n",
       "125           0             1               NaN             NaN      NaN   \n",
       "126           0             0               NaN             NaN      NaN   \n",
       "127           0             0               NaN             NaN      NaN   \n",
       "128           0             2               NaN             NaN      NaN   \n",
       "129           0             4               NaN             NaN      NaN   \n",
       "\n",
       "     current_score  \n",
       "125              1  \n",
       "126              1  \n",
       "127              1  \n",
       "128              3  \n",
       "129              7  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## score upto that delivery\n",
    "dlvr_df['current_score'] = dlvr_df.groupby('match_id').cumsum()['total_runs_y']\n",
    "dlvr_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "## runs left to score\n",
    "dlvr_df['runs_left'] = dlvr_df['total_runs_x'] - dlvr_df['current_score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs_y</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "      <th>current_score</th>\n",
       "      <th>runs_left</th>\n",
       "      <th>balls_left</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>204</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</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",
       "      <td>7</td>\n",
       "      <td>200</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id       city               winner  total_runs_x  inning  \\\n",
       "125         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "\n",
       "                    batting_team         bowling_team  over  ball  \\\n",
       "125  Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126  Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127  Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128  Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129  Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "\n",
       "           batsman  ... penalty_runs batsman_runs  extra_runs  total_runs_y  \\\n",
       "125       CH Gayle  ...            0            1           0             1   \n",
       "126  Mandeep Singh  ...            0            0           0             0   \n",
       "127  Mandeep Singh  ...            0            0           0             0   \n",
       "128  Mandeep Singh  ...            0            2           0             2   \n",
       "129  Mandeep Singh  ...            0            4           0             4   \n",
       "\n",
       "     player_dismissed  dismissal_kind  fielder  current_score  runs_left  \\\n",
       "125               NaN             NaN      NaN              1        206   \n",
       "126               NaN             NaN      NaN              1        206   \n",
       "127               NaN             NaN      NaN              1        206   \n",
       "128               NaN             NaN      NaN              3        204   \n",
       "129               NaN             NaN      NaN              7        200   \n",
       "\n",
       "     balls_left  \n",
       "125         119  \n",
       "126         118  \n",
       "127         117  \n",
       "128         116  \n",
       "129         115  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## balls left\n",
    "dlvr_df['balls_left'] = 120 - ((dlvr_df['over']-1)*6 + dlvr_df['ball'])\n",
    "dlvr_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wickets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs_y</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "      <th>current_score</th>\n",
       "      <th>runs_left</th>\n",
       "      <th>balls_left</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CH Gayle</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>119</td>\n",
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       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>Hyderabad</td>\n",
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       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>204</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>200</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id       city               winner  total_runs_x  inning  \\\n",
       "125         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "\n",
       "                    batting_team         bowling_team  over  ball  \\\n",
       "125  Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126  Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127  Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128  Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129  Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "\n",
       "           batsman  ... penalty_runs batsman_runs  extra_runs  total_runs_y  \\\n",
       "125       CH Gayle  ...            0            1           0             1   \n",
       "126  Mandeep Singh  ...            0            0           0             0   \n",
       "127  Mandeep Singh  ...            0            0           0             0   \n",
       "128  Mandeep Singh  ...            0            2           0             2   \n",
       "129  Mandeep Singh  ...            0            4           0             4   \n",
       "\n",
       "     player_dismissed  dismissal_kind  fielder  current_score  runs_left  \\\n",
       "125                 0             NaN      NaN              1        206   \n",
       "126                 0             NaN      NaN              1        206   \n",
       "127                 0             NaN      NaN              1        206   \n",
       "128                 0             NaN      NaN              3        204   \n",
       "129                 0             NaN      NaN              7        200   \n",
       "\n",
       "     balls_left  \n",
       "125         119  \n",
       "126         118  \n",
       "127         117  \n",
       "128         116  \n",
       "129         115  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df['player_dismissed'] = dlvr_df['player_dismissed'].fillna(\"0\")\n",
    "dlvr_df['player_dismissed'] = dlvr_df['player_dismissed'].apply(lambda x:x if x == \"0\" else \"1\")\n",
    "dlvr_df['player_dismissed'] = dlvr_df['player_dismissed'].astype('int')\n",
    "dlvr_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "wkts = dlvr_df.groupby(['match_id']).cumsum()['player_dismissed'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>CH Gayle</td>\n",
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       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
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       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "      <td>10</td>\n",
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       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
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       "      <td>10</td>\n",
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       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>200</td>\n",
       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     match_id       city               winner  total_runs_x  inning  \\\n",
       "125         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129         1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "\n",
       "                    batting_team         bowling_team  over  ball  \\\n",
       "125  Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126  Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127  Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128  Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129  Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "\n",
       "           batsman  ... batsman_runs extra_runs  total_runs_y  \\\n",
       "125       CH Gayle  ...            1          0             1   \n",
       "126  Mandeep Singh  ...            0          0             0   \n",
       "127  Mandeep Singh  ...            0          0             0   \n",
       "128  Mandeep Singh  ...            2          0             2   \n",
       "129  Mandeep Singh  ...            4          0             4   \n",
       "\n",
       "     player_dismissed  dismissal_kind  fielder  current_score  runs_left  \\\n",
       "125                 0             NaN      NaN              1        206   \n",
       "126                 0             NaN      NaN              1        206   \n",
       "127                 0             NaN      NaN              1        206   \n",
       "128                 0             NaN      NaN              3        204   \n",
       "129                 0             NaN      NaN              7        200   \n",
       "\n",
       "     balls_left  wickets  \n",
       "125         119       10  \n",
       "126         118       10  \n",
       "127         117       10  \n",
       "128         116       10  \n",
       "129         115       10  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df['wickets'] = 10 - wkts\n",
    "dlvr_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "## calculating current run rate = runs/overs\n",
    "dlvr_df['crr'] = (dlvr_df['current_score']*6) / (120 - dlvr_df['balls_left'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "##required run rate  = runs left / overs left\n",
    "dlvr_df['rrr'] = (dlvr_df['runs_left']*6) / dlvr_df['balls_left']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>wickets</th>\n",
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       "      <th>rrr</th>\n",
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       "      <th>126</th>\n",
       "      <td>1</td>\n",
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       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>3.000000</td>\n",
       "      <td>10.474576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "      <td>10</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.564103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>204</td>\n",
       "      <td>116</td>\n",
       "      <td>10</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>10.551724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>200</td>\n",
       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>10.434783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149573</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>RA Jadeja</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>152</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7.862069</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149574</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>154</td>\n",
       "      <td>-2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7.897436</td>\n",
       "      <td>-4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149575</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>run out</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>155</td>\n",
       "      <td>-3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>7.881356</td>\n",
       "      <td>-9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149576</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>157</td>\n",
       "      <td>-5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7.915966</td>\n",
       "      <td>-30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149577</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>lbw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>157</td>\n",
       "      <td>-5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72413 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id       city               winner  total_runs_x  inning  \\\n",
       "125            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "...          ...        ...                  ...           ...     ...   \n",
       "149573     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149574     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149575     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149576     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149577     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "\n",
       "                       batting_team         bowling_team  over  ball  \\\n",
       "125     Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126     Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127     Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128     Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129     Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "...                             ...                  ...   ...   ...   \n",
       "149573          Chennai Super Kings       Mumbai Indians    20     2   \n",
       "149574          Chennai Super Kings       Mumbai Indians    20     3   \n",
       "149575          Chennai Super Kings       Mumbai Indians    20     4   \n",
       "149576          Chennai Super Kings       Mumbai Indians    20     5   \n",
       "149577          Chennai Super Kings       Mumbai Indians    20     6   \n",
       "\n",
       "              batsman  ... total_runs_y player_dismissed  dismissal_kind  \\\n",
       "125          CH Gayle  ...            1                0             NaN   \n",
       "126     Mandeep Singh  ...            0                0             NaN   \n",
       "127     Mandeep Singh  ...            0                0             NaN   \n",
       "128     Mandeep Singh  ...            2                0             NaN   \n",
       "129     Mandeep Singh  ...            4                0             NaN   \n",
       "...               ...  ...          ...              ...             ...   \n",
       "149573      RA Jadeja  ...            1                0             NaN   \n",
       "149574      SR Watson  ...            2                0             NaN   \n",
       "149575      SR Watson  ...            1                1         run out   \n",
       "149576      SN Thakur  ...            2                0             NaN   \n",
       "149577      SN Thakur  ...            0                1             lbw   \n",
       "\n",
       "          fielder  current_score  runs_left  balls_left  wickets       crr  \\\n",
       "125           NaN              1        206         119       10  6.000000   \n",
       "126           NaN              1        206         118       10  3.000000   \n",
       "127           NaN              1        206         117       10  2.000000   \n",
       "128           NaN              3        204         116       10  4.500000   \n",
       "129           NaN              7        200         115       10  8.400000   \n",
       "...           ...            ...        ...         ...      ...       ...   \n",
       "149573        NaN            152          0           4        5  7.862069   \n",
       "149574        NaN            154         -2           3        5  7.897436   \n",
       "149575  KH Pandya            155         -3           2        4  7.881356   \n",
       "149576        NaN            157         -5           1        4  7.915966   \n",
       "149577        NaN            157         -5           0        3  7.850000   \n",
       "\n",
       "              rrr  \n",
       "125     10.386555  \n",
       "126     10.474576  \n",
       "127     10.564103  \n",
       "128     10.551724  \n",
       "129     10.434783  \n",
       "...           ...  \n",
       "149573   0.000000  \n",
       "149574  -4.000000  \n",
       "149575  -9.000000  \n",
       "149576 -30.000000  \n",
       "149577       -inf  \n",
       "\n",
       "[72413 rows x 30 columns]"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Did the team batting in the 2nd innings win or not?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "def match_result(row):\n",
    "    return 1 if row['batting_team'] == row['winner'] else 0\n",
    "\n",
    "\n",
    "## adding chasing team results in the result column ==> 0 -> loss, 1 -> win\n",
    "dlvr_df['result'] = dlvr_df.apply(match_result ,axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>city</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs_x</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>...</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "      <th>current_score</th>\n",
       "      <th>runs_left</th>\n",
       "      <th>balls_left</th>\n",
       "      <th>wickets</th>\n",
       "      <th>crr</th>\n",
       "      <th>rrr</th>\n",
       "      <th>result</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>125</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
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       "      <td>2</td>\n",
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       "      <td>CH Gayle</td>\n",
       "      <td>...</td>\n",
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       "      <td>10</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>118</td>\n",
       "      <td>10</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>10.474576</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
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       "      <td>3</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "      <td>10</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.564103</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>204</td>\n",
       "      <td>116</td>\n",
       "      <td>10</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>10.551724</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>207</td>\n",
       "      <td>2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mandeep Singh</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
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       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>10.434783</td>\n",
       "      <td>0</td>\n",
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       "      <th>149573</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
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       "      <td>152</td>\n",
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       "    <tr>\n",
       "      <th>149574</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>154</td>\n",
       "      <td>-2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7.897436</td>\n",
       "      <td>-4.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149575</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>SR Watson</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>run out</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>155</td>\n",
       "      <td>-3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>7.881356</td>\n",
       "      <td>-9.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149576</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>157</td>\n",
       "      <td>-5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7.915966</td>\n",
       "      <td>-30.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149577</th>\n",
       "      <td>11415</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>152</td>\n",
       "      <td>2</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>SN Thakur</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>lbw</td>\n",
       "      <td>NaN</td>\n",
       "      <td>157</td>\n",
       "      <td>-5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>-inf</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72413 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        match_id       city               winner  total_runs_x  inning  \\\n",
       "125            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "126            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "127            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "128            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "129            1  Hyderabad  Sunrisers Hyderabad           207       2   \n",
       "...          ...        ...                  ...           ...     ...   \n",
       "149573     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149574     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149575     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149576     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "149577     11415  Hyderabad       Mumbai Indians           152       2   \n",
       "\n",
       "                       batting_team         bowling_team  over  ball  \\\n",
       "125     Royal Challengers Bangalore  Sunrisers Hyderabad     1     1   \n",
       "126     Royal Challengers Bangalore  Sunrisers Hyderabad     1     2   \n",
       "127     Royal Challengers Bangalore  Sunrisers Hyderabad     1     3   \n",
       "128     Royal Challengers Bangalore  Sunrisers Hyderabad     1     4   \n",
       "129     Royal Challengers Bangalore  Sunrisers Hyderabad     1     5   \n",
       "...                             ...                  ...   ...   ...   \n",
       "149573          Chennai Super Kings       Mumbai Indians    20     2   \n",
       "149574          Chennai Super Kings       Mumbai Indians    20     3   \n",
       "149575          Chennai Super Kings       Mumbai Indians    20     4   \n",
       "149576          Chennai Super Kings       Mumbai Indians    20     5   \n",
       "149577          Chennai Super Kings       Mumbai Indians    20     6   \n",
       "\n",
       "              batsman  ... player_dismissed dismissal_kind    fielder  \\\n",
       "125          CH Gayle  ...                0            NaN        NaN   \n",
       "126     Mandeep Singh  ...                0            NaN        NaN   \n",
       "127     Mandeep Singh  ...                0            NaN        NaN   \n",
       "128     Mandeep Singh  ...                0            NaN        NaN   \n",
       "129     Mandeep Singh  ...                0            NaN        NaN   \n",
       "...               ...  ...              ...            ...        ...   \n",
       "149573      RA Jadeja  ...                0            NaN        NaN   \n",
       "149574      SR Watson  ...                0            NaN        NaN   \n",
       "149575      SR Watson  ...                1        run out  KH Pandya   \n",
       "149576      SN Thakur  ...                0            NaN        NaN   \n",
       "149577      SN Thakur  ...                1            lbw        NaN   \n",
       "\n",
       "        current_score  runs_left  balls_left  wickets       crr        rrr  \\\n",
       "125                 1        206         119       10  6.000000  10.386555   \n",
       "126                 1        206         118       10  3.000000  10.474576   \n",
       "127                 1        206         117       10  2.000000  10.564103   \n",
       "128                 3        204         116       10  4.500000  10.551724   \n",
       "129                 7        200         115       10  8.400000  10.434783   \n",
       "...               ...        ...         ...      ...       ...        ...   \n",
       "149573            152          0           4        5  7.862069   0.000000   \n",
       "149574            154         -2           3        5  7.897436  -4.000000   \n",
       "149575            155         -3           2        4  7.881356  -9.000000   \n",
       "149576            157         -5           1        4  7.915966 -30.000000   \n",
       "149577            157         -5           0        3  7.850000       -inf   \n",
       "\n",
       "        result  \n",
       "125          0  \n",
       "126          0  \n",
       "127          0  \n",
       "128          0  \n",
       "129          0  \n",
       "...        ...  \n",
       "149573       0  \n",
       "149574       0  \n",
       "149575       0  \n",
       "149576       0  \n",
       "149577       0  \n",
       "\n",
       "[72413 rows x 31 columns]"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dlvr_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning the final dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = dlvr_df[['batting_team','bowling_team','city','runs_left',\\\n",
    "                    'balls_left','wickets','total_runs_x','crr','rrr','result']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>city</th>\n",
       "      <th>runs_left</th>\n",
       "      <th>balls_left</th>\n",
       "      <th>wickets</th>\n",
       "      <th>total_runs_x</th>\n",
       "      <th>crr</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>206</td>\n",
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       "      <td>6.000000</td>\n",
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       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>206</td>\n",
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       "      <td>10</td>\n",
       "      <td>207</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>10.474576</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>206</td>\n",
       "      <td>117</td>\n",
       "      <td>10</td>\n",
       "      <td>207</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>10.564103</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>204</td>\n",
       "      <td>116</td>\n",
       "      <td>10</td>\n",
       "      <td>207</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>10.551724</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>200</td>\n",
       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "      <td>207</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>10.434783</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149573</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>152</td>\n",
       "      <td>7.862069</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>149574</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>-2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>152</td>\n",
       "      <td>7.897436</td>\n",
       "      <td>-4.000000</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>149575</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>-3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>152</td>\n",
       "      <td>7.881356</td>\n",
       "      <td>-9.000000</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>149576</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>-5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>152</td>\n",
       "      <td>7.915966</td>\n",
       "      <td>-30.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149577</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>-5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>152</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>-inf</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72413 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       batting_team         bowling_team       city  \\\n",
       "125     Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad   \n",
       "126     Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad   \n",
       "127     Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad   \n",
       "128     Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad   \n",
       "129     Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad   \n",
       "...                             ...                  ...        ...   \n",
       "149573          Chennai Super Kings       Mumbai Indians  Hyderabad   \n",
       "149574          Chennai Super Kings       Mumbai Indians  Hyderabad   \n",
       "149575          Chennai Super Kings       Mumbai Indians  Hyderabad   \n",
       "149576          Chennai Super Kings       Mumbai Indians  Hyderabad   \n",
       "149577          Chennai Super Kings       Mumbai Indians  Hyderabad   \n",
       "\n",
       "        runs_left  balls_left  wickets  total_runs_x       crr        rrr  \\\n",
       "125           206         119       10           207  6.000000  10.386555   \n",
       "126           206         118       10           207  3.000000  10.474576   \n",
       "127           206         117       10           207  2.000000  10.564103   \n",
       "128           204         116       10           207  4.500000  10.551724   \n",
       "129           200         115       10           207  8.400000  10.434783   \n",
       "...           ...         ...      ...           ...       ...        ...   \n",
       "149573          0           4        5           152  7.862069   0.000000   \n",
       "149574         -2           3        5           152  7.897436  -4.000000   \n",
       "149575         -3           2        4           152  7.881356  -9.000000   \n",
       "149576         -5           1        4           152  7.915966 -30.000000   \n",
       "149577         -5           0        3           152  7.850000       -inf   \n",
       "\n",
       "        result  \n",
       "125          0  \n",
       "126          0  \n",
       "127          0  \n",
       "128          0  \n",
       "129          0  \n",
       "...        ...  \n",
       "149573       0  \n",
       "149574       0  \n",
       "149575       0  \n",
       "149576       0  \n",
       "149577       0  \n",
       "\n",
       "[72413 rows x 10 columns]"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = final_df[final_df['balls_left'] != 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Segregating the features from the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = final_df.iloc[:,:-1]\n",
    "y = final_df.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Splitting the dataset into training and testing with 20% data reserved for testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>city</th>\n",
       "      <th>runs_left</th>\n",
       "      <th>balls_left</th>\n",
       "      <th>wickets</th>\n",
       "      <th>total_runs_x</th>\n",
       "      <th>crr</th>\n",
       "      <th>rrr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22755</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>131</td>\n",
       "      <td>110</td>\n",
       "      <td>9</td>\n",
       "      <td>139</td>\n",
       "      <td>4.800000</td>\n",
       "      <td>7.145455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149502</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>91</td>\n",
       "      <td>73</td>\n",
       "      <td>9</td>\n",
       "      <td>152</td>\n",
       "      <td>7.787234</td>\n",
       "      <td>7.479452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4619</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>92</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>162</td>\n",
       "      <td>7.777778</td>\n",
       "      <td>8.363636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90058</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>93</td>\n",
       "      <td>65</td>\n",
       "      <td>7</td>\n",
       "      <td>132</td>\n",
       "      <td>4.254545</td>\n",
       "      <td>8.584615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135658</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>101</td>\n",
       "      <td>48</td>\n",
       "      <td>8</td>\n",
       "      <td>189</td>\n",
       "      <td>7.333333</td>\n",
       "      <td>12.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103573</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Visakhapatnam</td>\n",
       "      <td>116</td>\n",
       "      <td>108</td>\n",
       "      <td>10</td>\n",
       "      <td>127</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>6.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43015</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>89</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>184</td>\n",
       "      <td>8.142857</td>\n",
       "      <td>10.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44720</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>86</td>\n",
       "      <td>43</td>\n",
       "      <td>4</td>\n",
       "      <td>183</td>\n",
       "      <td>7.558442</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105544</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>145</td>\n",
       "      <td>89</td>\n",
       "      <td>8</td>\n",
       "      <td>181</td>\n",
       "      <td>6.967742</td>\n",
       "      <td>9.775281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11032</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>58</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>191</td>\n",
       "      <td>8.966292</td>\n",
       "      <td>11.225806</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>57073 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       batting_team                 bowling_team  \\\n",
       "22755              Rajasthan Royals              Kings XI Punjab   \n",
       "149502          Chennai Super Kings               Mumbai Indians   \n",
       "4619                 Mumbai Indians  Royal Challengers Bangalore   \n",
       "90058         Kolkata Knight Riders              Kings XI Punjab   \n",
       "135658        Kolkata Knight Riders          Sunrisers Hyderabad   \n",
       "...                             ...                          ...   \n",
       "103573             Rajasthan Royals          Sunrisers Hyderabad   \n",
       "43015               Deccan Chargers  Royal Challengers Bangalore   \n",
       "44720              Delhi Daredevils               Mumbai Indians   \n",
       "105544  Royal Challengers Bangalore          Chennai Super Kings   \n",
       "11032   Royal Challengers Bangalore             Delhi Daredevils   \n",
       "\n",
       "                 city  runs_left  balls_left  wickets  total_runs_x       crr  \\\n",
       "22755       Cape Town        131         110        9           139  4.800000   \n",
       "149502      Hyderabad         91          73        9           152  7.787234   \n",
       "4619           Mumbai         92          66        8           162  7.777778   \n",
       "90058       Abu Dhabi         93          65        7           132  4.254545   \n",
       "135658        Kolkata        101          48        8           189  7.333333   \n",
       "...               ...        ...         ...      ...           ...       ...   \n",
       "103573  Visakhapatnam        116         108       10           127  5.500000   \n",
       "43015       Bangalore         89          50        7           184  8.142857   \n",
       "44720          Mumbai         86          43        4           183  7.558442   \n",
       "105544      Bangalore        145          89        8           181  6.967742   \n",
       "11032           Delhi         58          31        7           191  8.966292   \n",
       "\n",
       "              rrr  \n",
       "22755    7.145455  \n",
       "149502   7.479452  \n",
       "4619     8.363636  \n",
       "90058    8.584615  \n",
       "135658  12.625000  \n",
       "...           ...  \n",
       "103573   6.444444  \n",
       "43015   10.680000  \n",
       "44720   12.000000  \n",
       "105544   9.775281  \n",
       "11032   11.225806  \n",
       "\n",
       "[57073 rows x 9 columns]"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Can a machine understand what Rajasthan Royal or Cape Town is?\n",
    "\n",
    "#### Need to take care of the categorical variables - types of categorical variables.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation for model training\n",
    "\n",
    "- Transform columns\n",
    "- One hot encode the categorical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "col_trf = ColumnTransformer([\n",
    "    ('col_trf',OneHotEncoder(sparse=False,drop='first'), ['batting_team','bowling_team','city'])\n",
    "]\n",
    ",remainder='passthrough')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Which model to use?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_pipe = Pipeline(steps=[\n",
    "    ('step1',col_trf),\n",
    "    ('step2',LogisticRegression(solver='liblinear'))\n",
    "])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('step1',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('col_trf',\n",
       "                                                  OneHotEncoder(drop='first',\n",
       "                                                                sparse=False),\n",
       "                                                  ['batting_team',\n",
       "                                                   'bowling_team', 'city'])])),\n",
       "                ('step2', LogisticRegression(solver='liblinear'))])"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_pipe.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model_pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the accuracy of the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8067839372065316"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## But we need probabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.54473037, 0.45526963])"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_pipe.predict_proba(X_test)[10]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "def win_prob_calc(match_data, match_id, model):\n",
    "    \"\"\"\n",
    "    At every delivery, the model will calculate the probability\n",
    "    for the chasing team.\n",
    "    \"\"\"\n",
    "    \n",
    "    match = match_data[match_data['match_id'] == match_id]\n",
    "    \n",
    "    ## Match between teams\n",
    "    print(f\"Match: {match['batting_team'].iloc[0]} vs {match['bowling_team'].iloc[0]}\")\n",
    "    \n",
    "    # converting ball by ball data to over by over data\n",
    "    match = match[(match['ball'] == 6)]\n",
    "    \n",
    "    # get all the required columns in a copy dataframe\n",
    "    copy_df = match[['batting_team','bowling_team','city','runs_left',\\\n",
    "                     'balls_left','wickets','total_runs_x','crr','rrr']].dropna()\n",
    "    \n",
    "    # get rows where balls left are not zero - avoiding division by zero error\n",
    "    copy_df = copy_df[copy_df['balls_left'] != 0]\n",
    "    \n",
    "    # calculate probability using the model\n",
    "    result = model.predict_proba(copy_df)\n",
    "    \n",
    "    ## calculating percentage chance(prob multiplied by 100) for each team\n",
    "    copy_df['lose'] = np.round(result.T[0]*100,1)\n",
    "    copy_df['win'] = np.round(result.T[1]*100,1)\n",
    "    \n",
    "    # end of over \n",
    "    copy_df['end_of_over'] = range(1, copy_df.shape[0]+1)\n",
    "    \n",
    "    \n",
    "    target = copy_df['total_runs_x'].values[0]\n",
    "    print(\"Target:\", target)\n",
    "    \n",
    "    # calculate runs left\n",
    "    runs = list(copy_df['runs_left'].values)\n",
    "    new_runs = runs[:]\n",
    "    runs.insert(0, target)\n",
    "    \n",
    "    copy_df['runs_in_over'] = np.array(runs)[:-1] - np.array(new_runs)\n",
    "    \n",
    "    wickets = list(copy_df['wickets'].values)\n",
    "    \n",
    "    new_wickets = wickets[:]\n",
    "    new_wickets.insert(0,10)\n",
    "    wickets.append(0)\n",
    "    \n",
    "    # \n",
    "    w = np.array(wickets)\n",
    "    nw = np.array(new_wickets)\n",
    "    \n",
    "    copy_df['wickets_in_over'] = (nw - w)[0:copy_df.shape[0]]\n",
    "    \n",
    "    copy_df = copy_df[['end_of_over','runs_in_over','wickets_in_over','lose','win']]\n",
    "    \n",
    "    # chasing team win probability\n",
    "    print(f\"Win probability for {match['batting_team'].iloc[0]}\")\n",
    "    \n",
    "    return copy_df, target\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Match: Royal Challengers Bangalore vs Deccan Chargers\n",
      "Target: 165\n",
      "Win probability for Royal Challengers Bangalore\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>end_of_over</th>\n",
       "      <th>runs_in_over</th>\n",
       "      <th>wickets_in_over</th>\n",
       "      <th>lose</th>\n",
       "      <th>win</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11927</th>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>27.8</td>\n",
       "      <td>72.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11933</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>27.8</td>\n",
       "      <td>72.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11939</th>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>62.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11945</th>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>36.8</td>\n",
       "      <td>63.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11951</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>35.7</td>\n",
       "      <td>64.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11957</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>33.1</td>\n",
       "      <td>66.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11963</th>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>51.8</td>\n",
       "      <td>48.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11969</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>48.9</td>\n",
       "      <td>51.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11975</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>49.2</td>\n",
       "      <td>50.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11981</th>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>52.8</td>\n",
       "      <td>47.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11987</th>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>66.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11993</th>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>50.5</td>\n",
       "      <td>49.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11999</th>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>51.1</td>\n",
       "      <td>48.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12005</th>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12011</th>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>39.9</td>\n",
       "      <td>60.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12017</th>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>37.1</td>\n",
       "      <td>62.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12023</th>\n",
       "      <td>17</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12029</th>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>26.9</td>\n",
       "      <td>73.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12035</th>\n",
       "      <td>19</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>8.4</td>\n",
       "      <td>91.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       end_of_over  runs_in_over  wickets_in_over  lose   win\n",
       "11927            1            10                0  27.8  72.2\n",
       "11933            2             6                0  27.8  72.2\n",
       "11939            3             8                1  37.8  62.2\n",
       "11945            4             6                0  36.8  63.2\n",
       "11951            5             6                0  35.7  64.3\n",
       "11957            6             7                0  33.1  66.9\n",
       "11963            7             3                1  51.8  48.2\n",
       "11969            8             7                0  48.9  51.1\n",
       "11975            9             5                0  49.2  50.8\n",
       "11981           10             3                0  52.8  47.2\n",
       "11987           11            18                0  33.2  66.8\n",
       "11993           12             4                1  50.5  49.5\n",
       "11999           13             5                0  51.1  48.9\n",
       "12005           14            15                0  36.0  64.0\n",
       "12011           15             3                0  39.9  60.1\n",
       "12017           16            17                1  37.1  62.9\n",
       "12023           17            14                0  25.0  75.0\n",
       "12029           18            13                1  26.9  73.1\n",
       "12035           19            21                0   8.4  91.6"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_df, target = win_prob_calc(dlvr_df, 80, model_pipe)\n",
    "out_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the probabilities with runs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Target-165')"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "\n",
    "## plot win probabilities\n",
    "plt.plot(temp_df['end_of_over'],temp_df['win'],color='blue',linewidth=4)\n",
    "\n",
    "## plot losing probabilities\n",
    "plt.plot(temp_df['end_of_over'],temp_df['lose'],color='red',linewidth=4)\n",
    "\n",
    "# plt.bar(temp_df['end_of_over'],temp_df['runs_in_over'])\n",
    "plt.title('Target-' + str(target))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}