ML-Notebooks/IPL_Win_Probability_Predictor.ipynb

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        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sn\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ]
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        "matches = pd.read_csv('matches.csv')\n",
        "deliveries = pd.read_csv('deliveries.csv')\n",
        "matches.head()"
      ],
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              "   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  "
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              "   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",
              "\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",
              "\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",
              "\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",
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              "    <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",
              "  </tbody>\n",
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              "<p>5 rows × 21 columns</p>\n",
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    },
    {
      "cell_type": "code",
      "source": [
        "deliveries.columns"
      ],
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        "colab": {
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        },
        "id": "j-fXr-sCarEN",
        "outputId": "2efff125-45c9-45ea-efa2-649d648275ca"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'inning', 'batting_team', 'bowling_team', 'over', 'ball',\n",
              "       'batsman', 'non_striker', 'bowler', 'is_super_over', 'wide_runs',\n",
              "       'bye_runs', 'legbye_runs', 'noball_runs', 'penalty_runs',\n",
              "       'batsman_runs', 'extra_runs', 'total_runs', 'player_dismissed',\n",
              "       'dismissal_kind', 'fielder'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
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    {
      "cell_type": "code",
      "source": [
        "# Grouping the 1st inning, 2nd inning score in a particolur matchid\n",
        "# let's say matchs id = 1, so inning 1 score = 207, inning 2 score = 172, in that way \n",
        "totalrun_df = deliveries.groupby(['match_id', 'inning']).sum()['total_runs'].reset_index()\n",
        "totalrun_df"
      ],
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      "execution_count": 6,
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            "text/plain": [
              "      match_id  inning  total_runs\n",
              "0            1       1         207\n",
              "1            1       2         172\n",
              "2            2       1         184\n",
              "3            2       2         187\n",
              "4            3       1         183\n",
              "...        ...     ...         ...\n",
              "1523     11413       2         170\n",
              "1524     11414       1         155\n",
              "1525     11414       2         162\n",
              "1526     11415       1         152\n",
              "1527     11415       2         157\n",
              "\n",
              "[1528 rows x 3 columns]"
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    {
      "cell_type": "code",
      "source": [
        "# Capturing only the first innings, as we will be predicting for seccond innging\n",
        "totalrun_df = totalrun_df[totalrun_df['inning']==1]\n",
        "totalrun_df['total_runs'] = totalrun_df['total_runs'].apply(lambda x:x+1)\n",
        "totalrun_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "id": "g5t8nxDmcY6Q",
        "outputId": "cb4cdb06-95c6-4472-b64f-e7c62b2a98ad"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-7-9059b71b3d92>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  totalrun_df['total_runs'] = totalrun_df['total_runs'].apply(lambda x:x+1)\n"
          ]
        },
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          "data": {
            "text/plain": [
              "      match_id  inning  total_runs\n",
              "0            1       1         208\n",
              "2            2       1         185\n",
              "4            3       1         184\n",
              "6            4       1         164\n",
              "8            5       1         158\n",
              "...        ...     ...         ...\n",
              "1518     11347       1         144\n",
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              "\n",
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              "\n",
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              "  "
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          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "matches.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A6iiGAsLdW31",
        "outputId": "d84302be-70d0-4619-b2c1-c55c701d04aa"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id', 'Season', 'city', 'date', 'team1', 'team2', 'toss_winner',\n",
              "       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',\n",
              "       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',\n",
              "       'umpire3'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "Merging the total first innings score df with the matches df,\n",
        "where left side merging is done on \"id\" of the matches\n",
        "and right side merging is done on \"match_id\" column of the totalrun_df\n",
        "'''\n",
        "\n",
        "match_df = matches.merge(totalrun_df[['match_id', 'total_runs']],\n",
        "                         left_on='id', right_on='match_id')\n",
        "match_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 887
        },
        "id": "R9EHASU3dnTG",
        "outputId": "9a7e5872-7c9f-4e2c-b8a3-6571bdc65cfd"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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         208  \n",
              "1            S Ravi                      NaN         2         185  \n",
              "2         CK Nandan                      NaN         3         184  \n",
              "3     C Shamshuddin                      NaN         4         164  \n",
              "4               NaN                      NaN         5         158  \n",
              "..              ...                      ...       ...         ...  \n",
              "751        O Nandan                   S Ravi     11347         144  \n",
              "752     Nitin Menon                Ian Gould     11412         137  \n",
              "753             NaN                      NaN     11413         172  \n",
              "754  Bruce Oxenford  Chettithody Shamshuddin     11414         156  \n",
              "755       Ian Gould              Nigel Llong     11415         153  \n",
              "\n",
              "[756 rows x 20 columns]"
            ],
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              "\n",
              "  <div id=\"df-3ebb587b-6b84-45df-8ea0-6c29bcf46560\">\n",
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              "      <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",
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              "      <td>Sunrisers Hyderabad</td>\n",
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              "      <td>AY Dandekar</td>\n",
              "      <td>NJ Llong</td>\n",
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              "      <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>185</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>184</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",
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              "      <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>164</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>IPL-2017</td>\n",
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              "      <td>08-04-2017</td>\n",
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              "      <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",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>158</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",
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              "      <td>11347</td>\n",
              "      <td>144</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>137</td>\n",
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              "    <tr>\n",
              "      <th>753</th>\n",
              "      <td>11413</td>\n",
              "      <td>IPL-2019</td>\n",
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              "      <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>172</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>156</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>153</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>756 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3ebb587b-6b84-45df-8ea0-6c29bcf46560')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-3ebb587b-6b84-45df-8ea0-6c29bcf46560 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3ebb587b-6b84-45df-8ea0-6c29bcf46560');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "match_df['team1'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yfLTcIz9f1Z9",
        "outputId": "6a0da866-bdec-43de-d3e8-7e90aa0c8a5c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "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)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "teams = [\n",
        "    'Sunrisers Hyderabad',\n",
        "    'Mumbai Indians',\n",
        "    'Royal Challengers Bangalore',\n",
        "    'Kolkata Knight Riders',\n",
        "    'Kings XI Punjab',\n",
        "    'Chennai Super Kings',\n",
        "    'Rajasthan Royals',\n",
        "    'Delhi Capitals'\n",
        "]"
      ],
      "metadata": {
        "id": "yh3gzGi6gCmM"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# replacing the Delhi Daredevils with Delhi Capitals\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')\n",
        "\n",
        "\n",
        "# replacing the Deccan Chargers with Sunrises Hyderabad\n",
        "\n",
        "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"
      ],
      "metadata": {
        "id": "VxUDiZUYgHnM"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# will consider only frequently occuring teams,\n",
        "# which are mentioned in the teams list\n",
        "\n",
        "match_df = match_df[match_df['team1'].isin(teams)]\n",
        "match_df = match_df[match_df['team2'].isin(teams)]\n",
        "\n",
        "match_df['team1'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s2L-oF8XgKPt",
        "outputId": "c9c6f6ce-64d1-4ec4-a586-6c4e37f96aa6"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Sunrisers Hyderabad', 'Royal Challengers Bangalore',\n",
              "       'Kolkata Knight Riders', 'Kings XI Punjab', 'Delhi Capitals',\n",
              "       'Mumbai Indians', 'Chennai Super Kings', 'Rajasthan Royals'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "match_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f85zR-ZngMMF",
        "outputId": "ace0257e-79ec-4e91-a056-3ffac61c1284"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(641, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "match_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "JkWoOEStgQkE",
        "outputId": "c772409e-d4dd-4b60-a8f4-c56d35097b20"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id    Season       city        date                        team1  \\\n",
              "0   1  IPL-2017  Hyderabad  05-04-2017          Sunrisers Hyderabad   \n",
              "4   5  IPL-2017  Bangalore  08-04-2017  Royal Challengers Bangalore   \n",
              "6   7  IPL-2017     Mumbai  09-04-2017        Kolkata Knight Riders   \n",
              "7   8  IPL-2017     Indore  10-04-2017  Royal Challengers Bangalore   \n",
              "9  10  IPL-2017     Mumbai  12-04-2017          Sunrisers Hyderabad   \n",
              "\n",
              "                         team2                  toss_winner toss_decision  \\\n",
              "0  Royal Challengers Bangalore  Royal Challengers Bangalore         field   \n",
              "4               Delhi Capitals  Royal Challengers Bangalore           bat   \n",
              "6               Mumbai Indians               Mumbai Indians         field   \n",
              "7              Kings XI Punjab  Royal Challengers Bangalore           bat   \n",
              "9               Mumbai Indians               Mumbai Indians         field   \n",
              "\n",
              "   result  dl_applied                       winner  win_by_runs  \\\n",
              "0  normal           0          Sunrisers Hyderabad           35   \n",
              "4  normal           0  Royal Challengers Bangalore           15   \n",
              "6  normal           0               Mumbai Indians            0   \n",
              "7  normal           0              Kings XI Punjab            0   \n",
              "9  normal           0               Mumbai Indians            0   \n",
              "\n",
              "   win_by_wickets player_of_match                                      venue  \\\n",
              "0               0    Yuvraj Singh  Rajiv Gandhi International Stadium, Uppal   \n",
              "4               0       KM Jadhav                      M Chinnaswamy Stadium   \n",
              "6               4          N Rana                           Wankhede Stadium   \n",
              "7               8        AR Patel                     Holkar Cricket Stadium   \n",
              "9               4       JJ Bumrah                           Wankhede Stadium   \n",
              "\n",
              "        umpire1        umpire2 umpire3  match_id  total_runs  \n",
              "0   AY Dandekar       NJ Llong     NaN         1         208  \n",
              "4           NaN            NaN     NaN         5         158  \n",
              "6   Nitin Menon      CK Nandan     NaN         7         179  \n",
              "7  AK Chaudhary  C Shamshuddin     NaN         8         149  \n",
              "9   Nitin Menon      CK Nandan     NaN        10         159  "
            ],
            "text/html": [
              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>IPL-2017</td>\n",
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              "    <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 Capitals</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>158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>IPL-2017</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>09-04-2017</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>4</td>\n",
              "      <td>N Rana</td>\n",
              "      <td>Wankhede Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7</td>\n",
              "      <td>179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>IPL-2017</td>\n",
              "      <td>Indore</td>\n",
              "      <td>10-04-2017</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>bat</td>\n",
              "      <td>normal</td>\n",
              "      <td>0</td>\n",
              "      <td>Kings XI Punjab</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>AR Patel</td>\n",
              "      <td>Holkar Cricket Stadium</td>\n",
              "      <td>AK Chaudhary</td>\n",
              "      <td>C Shamshuddin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>IPL-2017</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>12-04-2017</td>\n",
              "      <td>Sunrisers Hyderabad</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>4</td>\n",
              "      <td>JJ Bumrah</td>\n",
              "      <td>Wankhede Stadium</td>\n",
              "      <td>Nitin Menon</td>\n",
              "      <td>CK Nandan</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10</td>\n",
              "      <td>159</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-df78da13-2279-4825-823b-bbe5ec4e74f0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-df78da13-2279-4825-823b-bbe5ec4e74f0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-df78da13-2279-4825-823b-bbe5ec4e74f0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# checking the matches which resulted in dl method\n",
        "\n",
        "match_df[match_df['dl_applied']==1].style.background_gradient(cmap = 'plasma')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "XDWORxf-gU_M",
        "outputId": "7612bf1b-cdc6-4f61-fda0-0fe5e6c61752"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fb3d161b160>"
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              "<table id=\"T_c63dd_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >id</th>\n",
              "      <th class=\"col_heading level0 col1\" >Season</th>\n",
              "      <th class=\"col_heading level0 col2\" >city</th>\n",
              "      <th class=\"col_heading level0 col3\" >date</th>\n",
              "      <th class=\"col_heading level0 col4\" >team1</th>\n",
              "      <th class=\"col_heading level0 col5\" >team2</th>\n",
              "      <th class=\"col_heading level0 col6\" >toss_winner</th>\n",
              "      <th class=\"col_heading level0 col7\" >toss_decision</th>\n",
              "      <th class=\"col_heading level0 col8\" >result</th>\n",
              "      <th class=\"col_heading level0 col9\" >dl_applied</th>\n",
              "      <th class=\"col_heading level0 col10\" >winner</th>\n",
              "      <th class=\"col_heading level0 col11\" >win_by_runs</th>\n",
              "      <th class=\"col_heading level0 col12\" >win_by_wickets</th>\n",
              "      <th class=\"col_heading level0 col13\" >player_of_match</th>\n",
              "      <th class=\"col_heading level0 col14\" >venue</th>\n",
              "      <th class=\"col_heading level0 col15\" >umpire1</th>\n",
              "      <th class=\"col_heading level0 col16\" >umpire2</th>\n",
              "      <th class=\"col_heading level0 col17\" >umpire3</th>\n",
              "      <th class=\"col_heading level0 col18\" >match_id</th>\n",
              "      <th class=\"col_heading level0 col19\" >total_runs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row0\" class=\"row_heading level0 row0\" >56</th>\n",
              "      <td id=\"T_c63dd_row0_col0\" class=\"data row0 col0\" >57</td>\n",
              "      <td id=\"T_c63dd_row0_col1\" class=\"data row0 col1\" >IPL-2017</td>\n",
              "      <td id=\"T_c63dd_row0_col2\" class=\"data row0 col2\" >Bangalore</td>\n",
              "      <td id=\"T_c63dd_row0_col3\" class=\"data row0 col3\" >17-05-2017</td>\n",
              "      <td id=\"T_c63dd_row0_col4\" class=\"data row0 col4\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row0_col5\" class=\"data row0 col5\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row0_col6\" class=\"data row0 col6\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row0_col7\" class=\"data row0 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row0_col8\" class=\"data row0 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row0_col9\" class=\"data row0 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row0_col10\" class=\"data row0 col10\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row0_col11\" class=\"data row0 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row0_col12\" class=\"data row0 col12\" >7</td>\n",
              "      <td id=\"T_c63dd_row0_col13\" class=\"data row0 col13\" >NM Coulter-Nile</td>\n",
              "      <td id=\"T_c63dd_row0_col14\" class=\"data row0 col14\" >M Chinnaswamy Stadium</td>\n",
              "      <td id=\"T_c63dd_row0_col15\" class=\"data row0 col15\" >AK Chaudhary</td>\n",
              "      <td id=\"T_c63dd_row0_col16\" class=\"data row0 col16\" >Nitin Menon</td>\n",
              "      <td id=\"T_c63dd_row0_col17\" class=\"data row0 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row0_col18\" class=\"data row0 col18\" >57</td>\n",
              "      <td id=\"T_c63dd_row0_col19\" class=\"data row0 col19\" >129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row1\" class=\"row_heading level0 row1\" >99</th>\n",
              "      <td id=\"T_c63dd_row1_col0\" class=\"data row1 col0\" >100</td>\n",
              "      <td id=\"T_c63dd_row1_col1\" class=\"data row1 col1\" >IPL-2008</td>\n",
              "      <td id=\"T_c63dd_row1_col2\" class=\"data row1 col2\" >Delhi</td>\n",
              "      <td id=\"T_c63dd_row1_col3\" class=\"data row1 col3\" >17-05-2008</td>\n",
              "      <td id=\"T_c63dd_row1_col4\" class=\"data row1 col4\" >Delhi Capitals</td>\n",
              "      <td id=\"T_c63dd_row1_col5\" class=\"data row1 col5\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row1_col6\" class=\"data row1 col6\" >Delhi Daredevils</td>\n",
              "      <td id=\"T_c63dd_row1_col7\" class=\"data row1 col7\" >bat</td>\n",
              "      <td id=\"T_c63dd_row1_col8\" class=\"data row1 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row1_col9\" class=\"data row1 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row1_col10\" class=\"data row1 col10\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row1_col11\" class=\"data row1 col11\" >6</td>\n",
              "      <td id=\"T_c63dd_row1_col12\" class=\"data row1 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row1_col13\" class=\"data row1 col13\" >DPMD Jayawardene</td>\n",
              "      <td id=\"T_c63dd_row1_col14\" class=\"data row1 col14\" >Feroz Shah Kotla</td>\n",
              "      <td id=\"T_c63dd_row1_col15\" class=\"data row1 col15\" >AV Jayaprakash</td>\n",
              "      <td id=\"T_c63dd_row1_col16\" class=\"data row1 col16\" >RE Koertzen</td>\n",
              "      <td id=\"T_c63dd_row1_col17\" class=\"data row1 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row1_col18\" class=\"data row1 col18\" >100</td>\n",
              "      <td id=\"T_c63dd_row1_col19\" class=\"data row1 col19\" >119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row2\" class=\"row_heading level0 row2\" >102</th>\n",
              "      <td id=\"T_c63dd_row2_col0\" class=\"data row2 col0\" >103</td>\n",
              "      <td id=\"T_c63dd_row2_col1\" class=\"data row2 col1\" >IPL-2008</td>\n",
              "      <td id=\"T_c63dd_row2_col2\" class=\"data row2 col2\" >Kolkata</td>\n",
              "      <td id=\"T_c63dd_row2_col3\" class=\"data row2 col3\" >18-05-2008</td>\n",
              "      <td id=\"T_c63dd_row2_col4\" class=\"data row2 col4\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row2_col5\" class=\"data row2 col5\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row2_col6\" class=\"data row2 col6\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row2_col7\" class=\"data row2 col7\" >bat</td>\n",
              "      <td id=\"T_c63dd_row2_col8\" class=\"data row2 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row2_col9\" class=\"data row2 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row2_col10\" class=\"data row2 col10\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row2_col11\" class=\"data row2 col11\" >3</td>\n",
              "      <td id=\"T_c63dd_row2_col12\" class=\"data row2 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row2_col13\" class=\"data row2 col13\" >M Ntini</td>\n",
              "      <td id=\"T_c63dd_row2_col14\" class=\"data row2 col14\" >Eden Gardens</td>\n",
              "      <td id=\"T_c63dd_row2_col15\" class=\"data row2 col15\" >Asad Rauf</td>\n",
              "      <td id=\"T_c63dd_row2_col16\" class=\"data row2 col16\" >K Hariharan</td>\n",
              "      <td id=\"T_c63dd_row2_col17\" class=\"data row2 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row2_col18\" class=\"data row2 col18\" >103</td>\n",
              "      <td id=\"T_c63dd_row2_col19\" class=\"data row2 col19\" >150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row3\" class=\"row_heading level0 row3\" >119</th>\n",
              "      <td id=\"T_c63dd_row3_col0\" class=\"data row3 col0\" >120</td>\n",
              "      <td id=\"T_c63dd_row3_col1\" class=\"data row3 col1\" >IPL-2009</td>\n",
              "      <td id=\"T_c63dd_row3_col2\" class=\"data row3 col2\" >Cape Town</td>\n",
              "      <td id=\"T_c63dd_row3_col3\" class=\"data row3 col3\" >19-04-2009</td>\n",
              "      <td id=\"T_c63dd_row3_col4\" class=\"data row3 col4\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row3_col5\" class=\"data row3 col5\" >Delhi Capitals</td>\n",
              "      <td id=\"T_c63dd_row3_col6\" class=\"data row3 col6\" >Delhi Daredevils</td>\n",
              "      <td id=\"T_c63dd_row3_col7\" class=\"data row3 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row3_col8\" class=\"data row3 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row3_col9\" class=\"data row3 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row3_col10\" class=\"data row3 col10\" >Delhi Daredevils</td>\n",
              "      <td id=\"T_c63dd_row3_col11\" class=\"data row3 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row3_col12\" class=\"data row3 col12\" >10</td>\n",
              "      <td id=\"T_c63dd_row3_col13\" class=\"data row3 col13\" >DL Vettori</td>\n",
              "      <td id=\"T_c63dd_row3_col14\" class=\"data row3 col14\" >Newlands</td>\n",
              "      <td id=\"T_c63dd_row3_col15\" class=\"data row3 col15\" >MR Benson</td>\n",
              "      <td id=\"T_c63dd_row3_col16\" class=\"data row3 col16\" >SD Ranade</td>\n",
              "      <td id=\"T_c63dd_row3_col17\" class=\"data row3 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row3_col18\" class=\"data row3 col18\" >120</td>\n",
              "      <td id=\"T_c63dd_row3_col19\" class=\"data row3 col19\" >105</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row4\" class=\"row_heading level0 row4\" >122</th>\n",
              "      <td id=\"T_c63dd_row4_col0\" class=\"data row4 col0\" >123</td>\n",
              "      <td id=\"T_c63dd_row4_col1\" class=\"data row4 col1\" >IPL-2009</td>\n",
              "      <td id=\"T_c63dd_row4_col2\" class=\"data row4 col2\" >Durban</td>\n",
              "      <td id=\"T_c63dd_row4_col3\" class=\"data row4 col3\" >21-04-2009</td>\n",
              "      <td id=\"T_c63dd_row4_col4\" class=\"data row4 col4\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row4_col5\" class=\"data row4 col5\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row4_col6\" class=\"data row4 col6\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row4_col7\" class=\"data row4 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row4_col8\" class=\"data row4 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row4_col9\" class=\"data row4 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row4_col10\" class=\"data row4 col10\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row4_col11\" class=\"data row4 col11\" >11</td>\n",
              "      <td id=\"T_c63dd_row4_col12\" class=\"data row4 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row4_col13\" class=\"data row4 col13\" >CH Gayle</td>\n",
              "      <td id=\"T_c63dd_row4_col14\" class=\"data row4 col14\" >Kingsmead</td>\n",
              "      <td id=\"T_c63dd_row4_col15\" class=\"data row4 col15\" >DJ Harper</td>\n",
              "      <td id=\"T_c63dd_row4_col16\" class=\"data row4 col16\" >SD Ranade</td>\n",
              "      <td id=\"T_c63dd_row4_col17\" class=\"data row4 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row4_col18\" class=\"data row4 col18\" >123</td>\n",
              "      <td id=\"T_c63dd_row4_col19\" class=\"data row4 col19\" >159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row5\" class=\"row_heading level0 row5\" >148</th>\n",
              "      <td id=\"T_c63dd_row5_col0\" class=\"data row5 col0\" >149</td>\n",
              "      <td id=\"T_c63dd_row5_col1\" class=\"data row5 col1\" >IPL-2009</td>\n",
              "      <td id=\"T_c63dd_row5_col2\" class=\"data row5 col2\" >Centurion</td>\n",
              "      <td id=\"T_c63dd_row5_col3\" class=\"data row5 col3\" >07-05-2009</td>\n",
              "      <td id=\"T_c63dd_row5_col4\" class=\"data row5 col4\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row5_col5\" class=\"data row5 col5\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row5_col6\" class=\"data row5 col6\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row5_col7\" class=\"data row5 col7\" >bat</td>\n",
              "      <td id=\"T_c63dd_row5_col8\" class=\"data row5 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row5_col9\" class=\"data row5 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row5_col10\" class=\"data row5 col10\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row5_col11\" class=\"data row5 col11\" >12</td>\n",
              "      <td id=\"T_c63dd_row5_col12\" class=\"data row5 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row5_col13\" class=\"data row5 col13\" >ML Hayden</td>\n",
              "      <td id=\"T_c63dd_row5_col14\" class=\"data row5 col14\" >SuperSport Park</td>\n",
              "      <td id=\"T_c63dd_row5_col15\" class=\"data row5 col15\" >DJ Harper</td>\n",
              "      <td id=\"T_c63dd_row5_col16\" class=\"data row5 col16\" >TH Wijewardene</td>\n",
              "      <td id=\"T_c63dd_row5_col17\" class=\"data row5 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row5_col18\" class=\"data row5 col18\" >149</td>\n",
              "      <td id=\"T_c63dd_row5_col19\" class=\"data row5 col19\" >186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row6\" class=\"row_heading level0 row6\" >280</th>\n",
              "      <td id=\"T_c63dd_row6_col0\" class=\"data row6 col0\" >281</td>\n",
              "      <td id=\"T_c63dd_row6_col1\" class=\"data row6 col1\" >IPL-2011</td>\n",
              "      <td id=\"T_c63dd_row6_col2\" class=\"data row6 col2\" >Kolkata</td>\n",
              "      <td id=\"T_c63dd_row6_col3\" class=\"data row6 col3\" >07-05-2011</td>\n",
              "      <td id=\"T_c63dd_row6_col4\" class=\"data row6 col4\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row6_col5\" class=\"data row6 col5\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row6_col6\" class=\"data row6 col6\" >Chennai Super Kings</td>\n",
              "      <td id=\"T_c63dd_row6_col7\" class=\"data row6 col7\" >bat</td>\n",
              "      <td id=\"T_c63dd_row6_col8\" class=\"data row6 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row6_col9\" class=\"data row6 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row6_col10\" class=\"data row6 col10\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row6_col11\" class=\"data row6 col11\" >10</td>\n",
              "      <td id=\"T_c63dd_row6_col12\" class=\"data row6 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row6_col13\" class=\"data row6 col13\" >Iqbal Abdulla</td>\n",
              "      <td id=\"T_c63dd_row6_col14\" class=\"data row6 col14\" >Eden Gardens</td>\n",
              "      <td id=\"T_c63dd_row6_col15\" class=\"data row6 col15\" >Asad Rauf</td>\n",
              "      <td id=\"T_c63dd_row6_col16\" class=\"data row6 col16\" >PR Reiffel</td>\n",
              "      <td id=\"T_c63dd_row6_col17\" class=\"data row6 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row6_col18\" class=\"data row6 col18\" >281</td>\n",
              "      <td id=\"T_c63dd_row6_col19\" class=\"data row6 col19\" >115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row7\" class=\"row_heading level0 row7\" >290</th>\n",
              "      <td id=\"T_c63dd_row7_col0\" class=\"data row7 col0\" >291</td>\n",
              "      <td id=\"T_c63dd_row7_col1\" class=\"data row7 col1\" >IPL-2011</td>\n",
              "      <td id=\"T_c63dd_row7_col2\" class=\"data row7 col2\" >Bangalore</td>\n",
              "      <td id=\"T_c63dd_row7_col3\" class=\"data row7 col3\" >14-05-2011</td>\n",
              "      <td id=\"T_c63dd_row7_col4\" class=\"data row7 col4\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row7_col5\" class=\"data row7 col5\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row7_col6\" class=\"data row7 col6\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row7_col7\" class=\"data row7 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row7_col8\" class=\"data row7 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row7_col9\" class=\"data row7 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row7_col10\" class=\"data row7 col10\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row7_col11\" class=\"data row7 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row7_col12\" class=\"data row7 col12\" >4</td>\n",
              "      <td id=\"T_c63dd_row7_col13\" class=\"data row7 col13\" >CH Gayle</td>\n",
              "      <td id=\"T_c63dd_row7_col14\" class=\"data row7 col14\" >M Chinnaswamy Stadium</td>\n",
              "      <td id=\"T_c63dd_row7_col15\" class=\"data row7 col15\" >RE Koertzen</td>\n",
              "      <td id=\"T_c63dd_row7_col16\" class=\"data row7 col16\" >RB Tiffin</td>\n",
              "      <td id=\"T_c63dd_row7_col17\" class=\"data row7 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row7_col18\" class=\"data row7 col18\" >291</td>\n",
              "      <td id=\"T_c63dd_row7_col19\" class=\"data row7 col19\" >90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row8\" class=\"row_heading level0 row8\" >488</th>\n",
              "      <td id=\"T_c63dd_row8_col0\" class=\"data row8 col0\" >489</td>\n",
              "      <td id=\"T_c63dd_row8_col1\" class=\"data row8 col1\" >IPL-2014</td>\n",
              "      <td id=\"T_c63dd_row8_col2\" class=\"data row8 col2\" >Delhi</td>\n",
              "      <td id=\"T_c63dd_row8_col3\" class=\"data row8 col3\" >10-05-2014</td>\n",
              "      <td id=\"T_c63dd_row8_col4\" class=\"data row8 col4\" >Delhi Capitals</td>\n",
              "      <td id=\"T_c63dd_row8_col5\" class=\"data row8 col5\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row8_col6\" class=\"data row8 col6\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row8_col7\" class=\"data row8 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row8_col8\" class=\"data row8 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row8_col9\" class=\"data row8 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row8_col10\" class=\"data row8 col10\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row8_col11\" class=\"data row8 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row8_col12\" class=\"data row8 col12\" >8</td>\n",
              "      <td id=\"T_c63dd_row8_col13\" class=\"data row8 col13\" >DW Steyn</td>\n",
              "      <td id=\"T_c63dd_row8_col14\" class=\"data row8 col14\" >Feroz Shah Kotla</td>\n",
              "      <td id=\"T_c63dd_row8_col15\" class=\"data row8 col15\" >RM Deshpande</td>\n",
              "      <td id=\"T_c63dd_row8_col16\" class=\"data row8 col16\" >BNJ Oxenford</td>\n",
              "      <td id=\"T_c63dd_row8_col17\" class=\"data row8 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row8_col18\" class=\"data row8 col18\" >489</td>\n",
              "      <td id=\"T_c63dd_row8_col19\" class=\"data row8 col19\" >144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row9\" class=\"row_heading level0 row9\" >536</th>\n",
              "      <td id=\"T_c63dd_row9_col0\" class=\"data row9 col0\" >537</td>\n",
              "      <td id=\"T_c63dd_row9_col1\" class=\"data row9 col1\" >IPL-2015</td>\n",
              "      <td id=\"T_c63dd_row9_col2\" class=\"data row9 col2\" >Visakhapatnam</td>\n",
              "      <td id=\"T_c63dd_row9_col3\" class=\"data row9 col3\" >22-04-2015</td>\n",
              "      <td id=\"T_c63dd_row9_col4\" class=\"data row9 col4\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row9_col5\" class=\"data row9 col5\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row9_col6\" class=\"data row9 col6\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row9_col7\" class=\"data row9 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row9_col8\" class=\"data row9 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row9_col9\" class=\"data row9 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row9_col10\" class=\"data row9 col10\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row9_col11\" class=\"data row9 col11\" >16</td>\n",
              "      <td id=\"T_c63dd_row9_col12\" class=\"data row9 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row9_col13\" class=\"data row9 col13\" >DA Warner</td>\n",
              "      <td id=\"T_c63dd_row9_col14\" class=\"data row9 col14\" >Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium</td>\n",
              "      <td id=\"T_c63dd_row9_col15\" class=\"data row9 col15\" >RK Illingworth</td>\n",
              "      <td id=\"T_c63dd_row9_col16\" class=\"data row9 col16\" >VA Kulkarni</td>\n",
              "      <td id=\"T_c63dd_row9_col17\" class=\"data row9 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row9_col18\" class=\"data row9 col18\" >537</td>\n",
              "      <td id=\"T_c63dd_row9_col19\" class=\"data row9 col19\" >177</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row10\" class=\"row_heading level0 row10\" >567</th>\n",
              "      <td id=\"T_c63dd_row10_col0\" class=\"data row10 col0\" >568</td>\n",
              "      <td id=\"T_c63dd_row10_col1\" class=\"data row10 col1\" >IPL-2015</td>\n",
              "      <td id=\"T_c63dd_row10_col2\" class=\"data row10 col2\" >Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row10_col3\" class=\"data row10 col3\" >15-05-2015</td>\n",
              "      <td id=\"T_c63dd_row10_col4\" class=\"data row10 col4\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row10_col5\" class=\"data row10 col5\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row10_col6\" class=\"data row10 col6\" >Sunrisers Hyderabad</td>\n",
              "      <td id=\"T_c63dd_row10_col7\" class=\"data row10 col7\" >bat</td>\n",
              "      <td id=\"T_c63dd_row10_col8\" class=\"data row10 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row10_col9\" class=\"data row10 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row10_col10\" class=\"data row10 col10\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row10_col11\" class=\"data row10 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row10_col12\" class=\"data row10 col12\" >6</td>\n",
              "      <td id=\"T_c63dd_row10_col13\" class=\"data row10 col13\" >V Kohli</td>\n",
              "      <td id=\"T_c63dd_row10_col14\" class=\"data row10 col14\" >Rajiv Gandhi International Stadium, Uppal</td>\n",
              "      <td id=\"T_c63dd_row10_col15\" class=\"data row10 col15\" >AK Chaudhary</td>\n",
              "      <td id=\"T_c63dd_row10_col16\" class=\"data row10 col16\" >HDPK Dharmasena</td>\n",
              "      <td id=\"T_c63dd_row10_col17\" class=\"data row10 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row10_col18\" class=\"data row10 col18\" >568</td>\n",
              "      <td id=\"T_c63dd_row10_col19\" class=\"data row10 col19\" >136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row11\" class=\"row_heading level0 row11\" >625</th>\n",
              "      <td id=\"T_c63dd_row11_col0\" class=\"data row11 col0\" >626</td>\n",
              "      <td id=\"T_c63dd_row11_col1\" class=\"data row11 col1\" >IPL-2016</td>\n",
              "      <td id=\"T_c63dd_row11_col2\" class=\"data row11 col2\" >Bangalore</td>\n",
              "      <td id=\"T_c63dd_row11_col3\" class=\"data row11 col3\" >18-05-2016</td>\n",
              "      <td id=\"T_c63dd_row11_col4\" class=\"data row11 col4\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row11_col5\" class=\"data row11 col5\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row11_col6\" class=\"data row11 col6\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row11_col7\" class=\"data row11 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row11_col8\" class=\"data row11 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row11_col9\" class=\"data row11 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row11_col10\" class=\"data row11 col10\" >Royal Challengers Bangalore</td>\n",
              "      <td id=\"T_c63dd_row11_col11\" class=\"data row11 col11\" >82</td>\n",
              "      <td id=\"T_c63dd_row11_col12\" class=\"data row11 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row11_col13\" class=\"data row11 col13\" >V Kohli</td>\n",
              "      <td id=\"T_c63dd_row11_col14\" class=\"data row11 col14\" >M Chinnaswamy Stadium</td>\n",
              "      <td id=\"T_c63dd_row11_col15\" class=\"data row11 col15\" >KN Ananthapadmanabhan</td>\n",
              "      <td id=\"T_c63dd_row11_col16\" class=\"data row11 col16\" >M Erasmus</td>\n",
              "      <td id=\"T_c63dd_row11_col17\" class=\"data row11 col17\" >nan</td>\n",
              "      <td id=\"T_c63dd_row11_col18\" class=\"data row11 col18\" >626</td>\n",
              "      <td id=\"T_c63dd_row11_col19\" class=\"data row11 col19\" >212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row12\" class=\"row_heading level0 row12\" >641</th>\n",
              "      <td id=\"T_c63dd_row12_col0\" class=\"data row12 col0\" >7899</td>\n",
              "      <td id=\"T_c63dd_row12_col1\" class=\"data row12 col1\" >IPL-2018</td>\n",
              "      <td id=\"T_c63dd_row12_col2\" class=\"data row12 col2\" >Jaipur</td>\n",
              "      <td id=\"T_c63dd_row12_col3\" class=\"data row12 col3\" >11-04-2018</td>\n",
              "      <td id=\"T_c63dd_row12_col4\" class=\"data row12 col4\" >Rajasthan Royals</td>\n",
              "      <td id=\"T_c63dd_row12_col5\" class=\"data row12 col5\" >Delhi Capitals</td>\n",
              "      <td id=\"T_c63dd_row12_col6\" class=\"data row12 col6\" >Delhi Daredevils</td>\n",
              "      <td id=\"T_c63dd_row12_col7\" class=\"data row12 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row12_col8\" class=\"data row12 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row12_col9\" class=\"data row12 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row12_col10\" class=\"data row12 col10\" >Rajasthan Royals</td>\n",
              "      <td id=\"T_c63dd_row12_col11\" class=\"data row12 col11\" >10</td>\n",
              "      <td id=\"T_c63dd_row12_col12\" class=\"data row12 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row12_col13\" class=\"data row12 col13\" >SV Samson</td>\n",
              "      <td id=\"T_c63dd_row12_col14\" class=\"data row12 col14\" >Sawai Mansingh Stadium</td>\n",
              "      <td id=\"T_c63dd_row12_col15\" class=\"data row12 col15\" >K Ananthapadmanabhan</td>\n",
              "      <td id=\"T_c63dd_row12_col16\" class=\"data row12 col16\" >Rod Tucker</td>\n",
              "      <td id=\"T_c63dd_row12_col17\" class=\"data row12 col17\" >Nitin Menon</td>\n",
              "      <td id=\"T_c63dd_row12_col18\" class=\"data row12 col18\" >7899</td>\n",
              "      <td id=\"T_c63dd_row12_col19\" class=\"data row12 col19\" >157</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row13\" class=\"row_heading level0 row13\" >653</th>\n",
              "      <td id=\"T_c63dd_row13_col0\" class=\"data row13 col0\" >7911</td>\n",
              "      <td id=\"T_c63dd_row13_col1\" class=\"data row13 col1\" >IPL-2018</td>\n",
              "      <td id=\"T_c63dd_row13_col2\" class=\"data row13 col2\" >Kolkata</td>\n",
              "      <td id=\"T_c63dd_row13_col3\" class=\"data row13 col3\" >21-04-2018</td>\n",
              "      <td id=\"T_c63dd_row13_col4\" class=\"data row13 col4\" >Kolkata Knight Riders</td>\n",
              "      <td id=\"T_c63dd_row13_col5\" class=\"data row13 col5\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row13_col6\" class=\"data row13 col6\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row13_col7\" class=\"data row13 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row13_col8\" class=\"data row13 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row13_col9\" class=\"data row13 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row13_col10\" class=\"data row13 col10\" >Kings XI Punjab</td>\n",
              "      <td id=\"T_c63dd_row13_col11\" class=\"data row13 col11\" >0</td>\n",
              "      <td id=\"T_c63dd_row13_col12\" class=\"data row13 col12\" >9</td>\n",
              "      <td id=\"T_c63dd_row13_col13\" class=\"data row13 col13\" >KL Rahul</td>\n",
              "      <td id=\"T_c63dd_row13_col14\" class=\"data row13 col14\" >Eden Gardens</td>\n",
              "      <td id=\"T_c63dd_row13_col15\" class=\"data row13 col15\" >C Shamshuddin</td>\n",
              "      <td id=\"T_c63dd_row13_col16\" class=\"data row13 col16\" >A.D Deshmukh</td>\n",
              "      <td id=\"T_c63dd_row13_col17\" class=\"data row13 col17\" >S Ravi</td>\n",
              "      <td id=\"T_c63dd_row13_col18\" class=\"data row13 col18\" >7911</td>\n",
              "      <td id=\"T_c63dd_row13_col19\" class=\"data row13 col19\" >201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c63dd_level0_row14\" class=\"row_heading level0 row14\" >667</th>\n",
              "      <td id=\"T_c63dd_row14_col0\" class=\"data row14 col0\" >7925</td>\n",
              "      <td id=\"T_c63dd_row14_col1\" class=\"data row14 col1\" >IPL-2018</td>\n",
              "      <td id=\"T_c63dd_row14_col2\" class=\"data row14 col2\" >Delhi</td>\n",
              "      <td id=\"T_c63dd_row14_col3\" class=\"data row14 col3\" >02-05-2018</td>\n",
              "      <td id=\"T_c63dd_row14_col4\" class=\"data row14 col4\" >Delhi Capitals</td>\n",
              "      <td id=\"T_c63dd_row14_col5\" class=\"data row14 col5\" >Rajasthan Royals</td>\n",
              "      <td id=\"T_c63dd_row14_col6\" class=\"data row14 col6\" >Rajasthan Royals</td>\n",
              "      <td id=\"T_c63dd_row14_col7\" class=\"data row14 col7\" >field</td>\n",
              "      <td id=\"T_c63dd_row14_col8\" class=\"data row14 col8\" >normal</td>\n",
              "      <td id=\"T_c63dd_row14_col9\" class=\"data row14 col9\" >1</td>\n",
              "      <td id=\"T_c63dd_row14_col10\" class=\"data row14 col10\" >Delhi Daredevils</td>\n",
              "      <td id=\"T_c63dd_row14_col11\" class=\"data row14 col11\" >4</td>\n",
              "      <td id=\"T_c63dd_row14_col12\" class=\"data row14 col12\" >0</td>\n",
              "      <td id=\"T_c63dd_row14_col13\" class=\"data row14 col13\" >RR Pant</td>\n",
              "      <td id=\"T_c63dd_row14_col14\" class=\"data row14 col14\" >Feroz Shah Kotla</td>\n",
              "      <td id=\"T_c63dd_row14_col15\" class=\"data row14 col15\" >O Nandan</td>\n",
              "      <td id=\"T_c63dd_row14_col16\" class=\"data row14 col16\" >Virender Kumar Sharma</td>\n",
              "      <td id=\"T_c63dd_row14_col17\" class=\"data row14 col17\" >Bruce Oxenford</td>\n",
              "      <td id=\"T_c63dd_row14_col18\" class=\"data row14 col18\" >7925</td>\n",
              "      <td id=\"T_c63dd_row14_col19\" class=\"data row14 col19\" >204</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ignoring the rows which were DL method\n",
        "\n",
        "match_df = match_df[match_df['dl_applied']==0]\n",
        "\n",
        "# considering the match_id,city,winner and total runs\n",
        "\n",
        "match_df = match_df[['match_id','city','winner','total_runs']]\n",
        "\n",
        "match_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Sf--2huIgYvX",
        "outputId": "abeead96-2b67-4a78-93f0-1aa0a4b4ed91"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id           city                       winner  total_runs\n",
              "0           1      Hyderabad          Sunrisers Hyderabad         208\n",
              "4           5      Bangalore  Royal Challengers Bangalore         158\n",
              "6           7         Mumbai               Mumbai Indians         179\n",
              "7           8         Indore              Kings XI Punjab         149\n",
              "9          10         Mumbai               Mumbai Indians         159\n",
              "..        ...            ...                          ...         ...\n",
              "751     11347         Mumbai               Mumbai Indians         144\n",
              "752     11412        Chennai               Mumbai Indians         137\n",
              "753     11413  Visakhapatnam               Delhi Capitals         172\n",
              "754     11414  Visakhapatnam          Chennai Super Kings         156\n",
              "755     11415      Hyderabad               Mumbai Indians         153\n",
              "\n",
              "[626 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2f51204d-1b62-4bd0-ac44-5822d1d83a90\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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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              "<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>208</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>158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>179</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>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>Mumbai</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>159</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>144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>752</th>\n",
              "      <td>11412</td>\n",
              "      <td>Chennai</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>753</th>\n",
              "      <td>11413</td>\n",
              "      <td>Visakhapatnam</td>\n",
              "      <td>Delhi Capitals</td>\n",
              "      <td>172</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>156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>755</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>626 rows × 4 columns</p>\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2f51204d-1b62-4bd0-ac44-5822d1d83a90');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
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    },
    {
      "cell_type": "code",
      "source": [
        "deliveries.head(3)"
      ],
      "metadata": {
        "colab": {
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          "height": 341
        },
        "id": "kKhqjvGMgbyj",
        "outputId": "1ff24b5a-a40d-4164-f403-756566233b7c"
      },
      "execution_count": 19,
      "outputs": [
        {
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            "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",
              "\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",
              "\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",
              "\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",
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    {
      "cell_type": "code",
      "source": [
        "# merging matchdf with delevieries on match_id\n",
        "\n",
        "delivery_df = match_df.merge(deliveries,on='match_id')\n",
        "\n",
        "delivery_df.head(5)"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "SrxySOemghYD",
        "outputId": "5750d8e1-deed-4e27-cdb5-8494d14c781c"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   match_id       city               winner  total_runs_x  inning  \\\n",
              "0         1  Hyderabad  Sunrisers Hyderabad           208       1   \n",
              "1         1  Hyderabad  Sunrisers Hyderabad           208       1   \n",
              "2         1  Hyderabad  Sunrisers Hyderabad           208       1   \n",
              "3         1  Hyderabad  Sunrisers Hyderabad           208       1   \n",
              "4         1  Hyderabad  Sunrisers Hyderabad           208       1   \n",
              "\n",
              "          batting_team                 bowling_team  over  ball    batsman  \\\n",
              "0  Sunrisers Hyderabad  Royal Challengers Bangalore     1     1  DA Warner   \n",
              "1  Sunrisers Hyderabad  Royal Challengers Bangalore     1     2  DA Warner   \n",
              "2  Sunrisers Hyderabad  Royal Challengers Bangalore     1     3  DA Warner   \n",
              "3  Sunrisers Hyderabad  Royal Challengers Bangalore     1     4  DA Warner   \n",
              "4  Sunrisers Hyderabad  Royal Challengers Bangalore     1     5  DA Warner   \n",
              "\n",
              "   ... bye_runs legbye_runs  noball_runs  penalty_runs  batsman_runs  \\\n",
              "0  ...        0           0            0             0             0   \n",
              "1  ...        0           0            0             0             0   \n",
              "2  ...        0           0            0             0             4   \n",
              "3  ...        0           0            0             0             0   \n",
              "4  ...        0           0            0             0             0   \n",
              "\n",
              "   extra_runs  total_runs_y  player_dismissed  dismissal_kind  fielder  \n",
              "0           0             0               NaN             NaN      NaN  \n",
              "1           0             0               NaN             NaN      NaN  \n",
              "2           0             4               NaN             NaN      NaN  \n",
              "3           0             0               NaN             NaN      NaN  \n",
              "4           2             2               NaN             NaN      NaN  \n",
              "\n",
              "[5 rows x 24 columns]"
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              "      <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>208</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>208</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>208</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>208</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>208</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",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 24 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cce53b42-d27e-4869-af40-ec33cf8780f2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-cce53b42-d27e-4869-af40-ec33cf8780f2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cce53b42-d27e-4869-af40-ec33cf8780f2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "delivery_df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "07tleP5Hgk_q",
        "outputId": "3f902590-4cbd-4d0a-82fb-8c279632bae5"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['match_id', 'city', 'winner', 'total_runs_x', 'inning', 'batting_team',\n",
              "       'bowling_team', 'over', 'ball', 'batsman', 'non_striker', 'bowler',\n",
              "       'is_super_over', 'wide_runs', 'bye_runs', 'legbye_runs', 'noball_runs',\n",
              "       'penalty_runs', 'batsman_runs', 'extra_runs', 'total_runs_y',\n",
              "       'player_dismissed', 'dismissal_kind', 'fielder'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "delivery_df = delivery_df[delivery_df['inning'] == 2]\n",
        "delivery_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "BbE6LtQfgsST",
        "outputId": "8e8d7276-bb45-46ac-b23e-a1f157bf1d62"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id       city               winner  total_runs_x  inning  \\\n",
              "125         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129         1  Hyderabad  Sunrisers Hyderabad           208       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  ... 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",
              "     batsman_runs  extra_runs  total_runs_y  player_dismissed  dismissal_kind  \\\n",
              "125             1           0             1               NaN             NaN   \n",
              "126             0           0             0               NaN             NaN   \n",
              "127             0           0             0               NaN             NaN   \n",
              "128             2           0             2               NaN             NaN   \n",
              "129             4           0             4               NaN             NaN   \n",
              "\n",
              "     fielder  \n",
              "125      NaN  \n",
              "126      NaN  \n",
              "127      NaN  \n",
              "128      NaN  \n",
              "129      NaN  \n",
              "\n",
              "[5 rows x 24 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1c3ac0a9-c413-48b7-83b4-ee20bf4b584e\">\n",
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              "      <div>\n",
              "<style scoped>\n",
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              "      <th>batsman</th>\n",
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              "      <th>legbye_runs</th>\n",
              "      <th>noball_runs</th>\n",
              "      <th>penalty_runs</th>\n",
              "      <th>batsman_runs</th>\n",
              "      <th>extra_runs</th>\n",
              "      <th>total_runs_y</th>\n",
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              "      <th>fielder</th>\n",
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              "      <th>125</th>\n",
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              "      <td>CH Gayle</td>\n",
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              "      <td>Mandeep Singh</td>\n",
              "      <td>...</td>\n",
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              "      <th>127</th>\n",
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              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
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              "      <td>208</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",
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              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 24 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1c3ac0a9-c413-48b7-83b4-ee20bf4b584e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "delivery_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jlf47zfhg_GM",
        "outputId": "9e499f19-50bf-4abb-d4d4-bb7b16200ea0"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(72413, 24)"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "So by observation we can observe that in the matchdf we had taken\n",
        "firstinnings total runs,right and in the second case,that is in the \n",
        "delivery dataframe we considered second inning runs,as our main aim\n",
        "is to find the probability of either teams to win or loose,we need \n",
        "current runs and runrate,so for current runs,we can apply groupby\n",
        "on matchid and take the cummulative sum wrt total_runs_y,now,basically\n",
        "totalruns was present in matchdf as well as deliveries_df,but as we merged\n",
        "both the dataframes,it resulted in total_runs_x,and total_runs_y,\n",
        "so total_runs_x is the first innings runs and total_runs_y are the second\n",
        "innings runs,ball by ball,by applying cummulative sum,this becomes \n",
        "current score\n",
        "\n",
        "\n",
        "total_runs_y gives the run scored after each ball,so in the second innings,\n",
        "we want to get the total second innings runs,so we will groupby match id\n",
        "and will apply the cummulative sum\n",
        "\n",
        "\n",
        "'''\n",
        "\n",
        "# current score of particular match\n",
        "\n",
        "delivery_df['current_score'] = delivery_df.groupby('match_id').cumsum()['total_runs_y']\n",
        "\n",
        "delivery_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
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        "id": "kMl6zWhEhC0R",
        "outputId": "9101c6ba-5205-43fa-9479-e9e045ece876"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id       city               winner  total_runs_x  inning  \\\n",
              "125         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129         1  Hyderabad  Sunrisers Hyderabad           208       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]"
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              "<p>5 rows × 25 columns</p>\n",
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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    {
      "cell_type": "code",
      "source": [
        "# runs left \n",
        "\n",
        "delivery_df['runs_left'] = delivery_df['total_runs_x']-delivery_df['current_score']\n",
        "\n",
        "delivery_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "aLEzms0ehHoC",
        "outputId": "719104f8-72cb-48a8-a2ef-e79bcf36be0d"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id       city               winner  total_runs_x  inning  \\\n",
              "125         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129         1  Hyderabad  Sunrisers Hyderabad           208       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  ... noball_runs penalty_runs  batsman_runs  extra_runs  \\\n",
              "125       CH Gayle  ...           0            0             1           0   \n",
              "126  Mandeep Singh  ...           0            0             0           0   \n",
              "127  Mandeep Singh  ...           0            0             0           0   \n",
              "128  Mandeep Singh  ...           0            0             2           0   \n",
              "129  Mandeep Singh  ...           0            0             4           0   \n",
              "\n",
              "     total_runs_y  player_dismissed  dismissal_kind  fielder  current_score  \\\n",
              "125             1               NaN             NaN      NaN              1   \n",
              "126             0               NaN             NaN      NaN              1   \n",
              "127             0               NaN             NaN      NaN              1   \n",
              "128             2               NaN             NaN      NaN              3   \n",
              "129             4               NaN             NaN      NaN              7   \n",
              "\n",
              "     runs_left  \n",
              "125        207  \n",
              "126        207  \n",
              "127        207  \n",
              "128        205  \n",
              "129        201  \n",
              "\n",
              "[5 rows x 26 columns]"
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              "      <td>CH Gayle</td>\n",
              "      <td>...</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",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>126</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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>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>205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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>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>201</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 26 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-33d2e93f-64e1-473f-bc01-f1cc1d7ab6a7')\"\n",
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          "metadata": {},
          "execution_count": 25
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "if one ball is played,then balls left = 120-1 = 119........(1)\n",
        "if two balls are played,then balls left = 120-2 = 118\n",
        "\n",
        "so similarly if over=1,over has 6 balls right,so 1*6 = 6\n",
        "now,ball = 1,so 6+1 = 7,now 126-7 = 119,which is same as (1)\n",
        "\n",
        "so we'll use balls_left = 126-(over*6+current_ball)\n",
        "\n",
        "'''\n",
        "\n",
        "# balls left\n",
        "\n",
        "\n",
        "delivery_df['balls_left'] = 126-(delivery_df['over']*6+delivery_df['ball'])\n",
        "\n",
        "delivery_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 748
        },
        "id": "lV9VVR_OhKUR",
        "outputId": "3f5083be-b057-4dcd-b18b-9936dd8b3b45"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        match_id       city               winner  total_runs_x  inning  \\\n",
              "125            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "...          ...        ...                  ...           ...     ...   \n",
              "149573     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149574     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149575     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149576     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149577     11415  Hyderabad       Mumbai Indians           153       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  ... penalty_runs batsman_runs  extra_runs  \\\n",
              "125          CH Gayle  ...            0            1           0   \n",
              "126     Mandeep Singh  ...            0            0           0   \n",
              "127     Mandeep Singh  ...            0            0           0   \n",
              "128     Mandeep Singh  ...            0            2           0   \n",
              "129     Mandeep Singh  ...            0            4           0   \n",
              "...               ...  ...          ...          ...         ...   \n",
              "149573      RA Jadeja  ...            0            1           0   \n",
              "149574      SR Watson  ...            0            2           0   \n",
              "149575      SR Watson  ...            0            1           0   \n",
              "149576      SN Thakur  ...            0            2           0   \n",
              "149577      SN Thakur  ...            0            0           0   \n",
              "\n",
              "        total_runs_y  player_dismissed  dismissal_kind    fielder  \\\n",
              "125                1               NaN             NaN        NaN   \n",
              "126                0               NaN             NaN        NaN   \n",
              "127                0               NaN             NaN        NaN   \n",
              "128                2               NaN             NaN        NaN   \n",
              "129                4               NaN             NaN        NaN   \n",
              "...              ...               ...             ...        ...   \n",
              "149573             1               NaN             NaN        NaN   \n",
              "149574             2               NaN             NaN        NaN   \n",
              "149575             1         SR Watson         run out  KH Pandya   \n",
              "149576             2               NaN             NaN        NaN   \n",
              "149577             0         SN Thakur             lbw        NaN   \n",
              "\n",
              "        current_score  runs_left  balls_left  \n",
              "125                 1        207         119  \n",
              "126                 1        207         118  \n",
              "127                 1        207         117  \n",
              "128                 3        205         116  \n",
              "129                 7        201         115  \n",
              "...               ...        ...         ...  \n",
              "149573            152          1           4  \n",
              "149574            154         -1           3  \n",
              "149575            155         -2           2  \n",
              "149576            157         -4           1  \n",
              "149577            157         -4           0  \n",
              "\n",
              "[72413 rows x 27 columns]"
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              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
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              "      <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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>154</td>\n",
              "      <td>-1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149575</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>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",
              "      <td>155</td>\n",
              "      <td>-2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149576</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>157</td>\n",
              "      <td>-4</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149577</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>SN Thakur</td>\n",
              "      <td>lbw</td>\n",
              "      <td>NaN</td>\n",
              "      <td>157</td>\n",
              "      <td>-4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>72413 rows × 27 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a1694287-13cd-4e91-b024-7459682d737d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
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              "          document.querySelector('#df-a1694287-13cd-4e91-b024-7459682d737d button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a1694287-13cd-4e91-b024-7459682d737d');\n",
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              "                                                     [key], {});\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list(delivery_df['player_dismissed'].unique())[:2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S4XdpF0nhOXZ",
        "outputId": "a3996558-dfeb-4de9-c58a-eb7d8599c9ff"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[nan, 'Mandeep Singh']"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# filling nan values with \"0\"\n",
        "\n",
        "delivery_df['player_dismissed'] = delivery_df['player_dismissed'].fillna(\"0\")\n",
        "\n",
        "# now we will convert this player_dismissed col into a boolean col\n",
        "# if the player is not dismissed then it's 0 else its 1\n",
        "\n",
        "delivery_df['player_dismissed'] = delivery_df['player_dismissed'].apply(lambda x:x if x==\"0\" else \"1\")\n",
        "\n",
        "# converting string to int\n",
        "\n",
        "delivery_df['player_dismissed'] = delivery_df['player_dismissed'].astype('int')\n",
        "\n",
        "\n",
        "delivery_df['player_dismissed'].unique()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jnMJaWnxhY_5",
        "outputId": "308bb28f-9812-47cd-9bb0-e4bb782e9dfd"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1])"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# wickets fallen \n",
        "\n",
        "wickets = delivery_df.groupby('match_id').cumsum()['player_dismissed'].values\n",
        "\n",
        "delivery_df['wickets'] = 10-wickets\n",
        "\n",
        "delivery_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 748
        },
        "id": "oC5e6o-nhjEw",
        "outputId": "d95be8cd-fbdd-48ca-a980-cf574658354e"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        match_id       city               winner  total_runs_x  inning  \\\n",
              "125            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129            1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "...          ...        ...                  ...           ...     ...   \n",
              "149573     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149574     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149575     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149576     11415  Hyderabad       Mumbai Indians           153       2   \n",
              "149577     11415  Hyderabad       Mumbai Indians           153       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  ... 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",
              "149573      RA Jadeja  ...            1          0             1   \n",
              "149574      SR Watson  ...            2          0             2   \n",
              "149575      SR Watson  ...            1          0             1   \n",
              "149576      SN Thakur  ...            2          0             2   \n",
              "149577      SN Thakur  ...            0          0             0   \n",
              "\n",
              "        player_dismissed  dismissal_kind    fielder  current_score  runs_left  \\\n",
              "125                    0             NaN        NaN              1        207   \n",
              "126                    0             NaN        NaN              1        207   \n",
              "127                    0             NaN        NaN              1        207   \n",
              "128                    0             NaN        NaN              3        205   \n",
              "129                    0             NaN        NaN              7        201   \n",
              "...                  ...             ...        ...            ...        ...   \n",
              "149573                 0             NaN        NaN            152          1   \n",
              "149574                 0             NaN        NaN            154         -1   \n",
              "149575                 1         run out  KH Pandya            155         -2   \n",
              "149576                 0             NaN        NaN            157         -4   \n",
              "149577                 1             lbw        NaN            157         -4   \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",
              "149573           4        5  \n",
              "149574           3        5  \n",
              "149575           2        4  \n",
              "149576           1        4  \n",
              "149577           0        3  \n",
              "\n",
              "[72413 rows x 28 columns]"
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              "\n",
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              "      <th></th>\n",
              "      <th>match_id</th>\n",
              "      <th>city</th>\n",
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              "      <th>batting_team</th>\n",
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              "      <th>batsman</th>\n",
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              "      <th>batsman_runs</th>\n",
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              "      <th>total_runs_y</th>\n",
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              "      <th>fielder</th>\n",
              "      <th>current_score</th>\n",
              "      <th>runs_left</th>\n",
              "      <th>balls_left</th>\n",
              "      <th>wickets</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
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              "      <td>Sunrisers Hyderabad</td>\n",
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              "      <th>126</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
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              "      <td>Sunrisers Hyderabad</td>\n",
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              "      <td>Mandeep Singh</td>\n",
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              "      <td>208</td>\n",
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              "      <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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>10</td>\n",
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              "      <th>128</th>\n",
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              "      <td>Hyderabad</td>\n",
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              "      <td>208</td>\n",
              "      <td>2</td>\n",
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              "      <td>Mandeep Singh</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</td>\n",
              "      <td>2</td>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
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              "      <td>Mandeep Singh</td>\n",
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              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>152</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149574</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>154</td>\n",
              "      <td>-1</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149575</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>0</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>-2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149576</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>157</td>\n",
              "      <td>-4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149577</th>\n",
              "      <td>11415</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Mumbai Indians</td>\n",
              "      <td>153</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>1</td>\n",
              "      <td>lbw</td>\n",
              "      <td>NaN</td>\n",
              "      <td>157</td>\n",
              "      <td>-4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>72413 rows × 28 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c0a723de-da06-4f36-9876-a63c2f16ea09')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c0a723de-da06-4f36-9876-a63c2f16ea09 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c0a723de-da06-4f36-9876-a63c2f16ea09');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# current run rate\n",
        "\n",
        "delivery_df['cur_run_rate'] = (delivery_df['current_score']*6)/(120-delivery_df['balls_left'])\n",
        "\n",
        "# required run rate\n",
        "\n",
        "delivery_df['req_run_rate'] = (delivery_df['runs_left']*6)/(delivery_df['balls_left'])\n",
        "\n",
        "\n",
        "delivery_df.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 341
        },
        "id": "k4F5iOZyhmBw",
        "outputId": "cc08f930-cece-47d0-99e5-495c0561a250"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id       city               winner  total_runs_x  inning  \\\n",
              "125         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127         1  Hyderabad  Sunrisers Hyderabad           208       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",
              "\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",
              "\n",
              "     fielder  current_score  runs_left  balls_left  wickets  cur_run_rate  \\\n",
              "125      NaN              1        207         119       10           6.0   \n",
              "126      NaN              1        207         118       10           3.0   \n",
              "127      NaN              1        207         117       10           2.0   \n",
              "\n",
              "     req_run_rate  \n",
              "125     10.436975  \n",
              "126     10.525424  \n",
              "127     10.615385  \n",
              "\n",
              "[3 rows x 30 columns]"
            ],
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <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>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",
              "      <th>wickets</th>\n",
              "      <th>cur_run_rate</th>\n",
              "      <th>req_run_rate</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>208</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>10</td>\n",
              "      <td>6.0</td>\n",
              "      <td>10.436975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>126</th>\n",
              "      <td>1</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>208</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>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>207</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>208</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>207</td>\n",
              "      <td>117</td>\n",
              "      <td>10</td>\n",
              "      <td>2.0</td>\n",
              "      <td>10.615385</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 30 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fe5e1b10-15e3-4019-94bf-cdb9e0293f84')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fe5e1b10-15e3-4019-94bf-cdb9e0293f84 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fe5e1b10-15e3-4019-94bf-cdb9e0293f84');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def resultfun(row):\n",
        "    \n",
        "    return 1 if row['batting_team'] == row['winner'] else 0"
      ],
      "metadata": {
        "id": "IdSB-yB3hoTS"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "delivery_df['result'] = delivery_df.apply(resultfun,axis=1)\n",
        "delivery_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "8A4xBUEihsr5",
        "outputId": "8a070d06-c6b2-4783-83fa-f29524adeb1e"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     match_id       city               winner  total_runs_x  inning  \\\n",
              "125         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "126         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "127         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "128         1  Hyderabad  Sunrisers Hyderabad           208       2   \n",
              "129         1  Hyderabad  Sunrisers Hyderabad           208       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  ... 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",
              "     current_score  runs_left  balls_left  wickets  cur_run_rate  \\\n",
              "125              1        207         119       10           6.0   \n",
              "126              1        207         118       10           3.0   \n",
              "127              1        207         117       10           2.0   \n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sn.countplot(delivery_df['result'])"
      ],
      "metadata": {
        "colab": {
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          "height": 351
        },
        "id": "eBUU4SYShvYQ",
        "outputId": "d38fc0e9-f305-404d-f287-e842c8df286a"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb3d137adc0>"
            ]
          },
          "metadata": {},
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df = delivery_df[['batting_team','bowling_team','city','runs_left',\n",
        "                        'balls_left','wickets','total_runs_x','cur_run_rate',\n",
        "                        'req_run_rate','result']]\n",
        "\n",
        "final_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "oiIA6wfgh4Sg",
        "outputId": "fb7e0e2b-31ec-4b2e-b48f-79cecef03819"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    batting_team         bowling_team       city  runs_left  \\\n",
              "125  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "126  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "127  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "128  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        205   \n",
              "129  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        201   \n",
              "\n",
              "     balls_left  wickets  total_runs_x  cur_run_rate  req_run_rate  result  \n",
              "125         119       10           208           6.0     10.436975       0  \n",
              "126         118       10           208           3.0     10.525424       0  \n",
              "127         117       10           208           2.0     10.615385       0  \n",
              "128         116       10           208           4.5     10.603448       0  \n",
              "129         115       10           208           8.4     10.486957       0  "
            ],
            "text/html": [
              "\n",
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              "    <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>cur_run_rate</th>\n",
              "      <th>req_run_rate</th>\n",
              "      <th>result</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
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              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Hyderabad</td>\n",
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              "    <tr>\n",
              "      <th>128</th>\n",
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              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>205</td>\n",
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              "      <td>4.5</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>201</td>\n",
              "      <td>115</td>\n",
              "      <td>10</td>\n",
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              "      <td>8.4</td>\n",
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              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fe22c27a-20a3-49be-a352-8d5324a7ef13 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fe22c27a-20a3-49be-a352-8d5324a7ef13');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2lVT5Vgvj4hG",
        "outputId": "f1cc35f8-13ad-4f9d-c092-f0808def46c4"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(72413, 10)"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QteH0Fu7j_7Z",
        "outputId": "e7e9bfbb-9534-4d3e-e53e-e8f1e959c229"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "batting_team      0\n",
              "bowling_team      0\n",
              "city            832\n",
              "runs_left         0\n",
              "balls_left        0\n",
              "wickets           0\n",
              "total_runs_x      0\n",
              "cur_run_rate      0\n",
              "req_run_rate      5\n",
              "result            0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df = final_df.dropna()\n",
        "final_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wkxHY2ZPkFnI",
        "outputId": "6d023b4a-33a1-4e7c-a12d-2b4a017c4cdb"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "batting_team    0\n",
              "bowling_team    0\n",
              "city            0\n",
              "runs_left       0\n",
              "balls_left      0\n",
              "wickets         0\n",
              "total_runs_x    0\n",
              "cur_run_rate    0\n",
              "req_run_rate    0\n",
              "result          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df = final_df[final_df['balls_left'] != 0]"
      ],
      "metadata": {
        "id": "a74U1guFkaIA"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = final_df.copy()\n",
        "test = data['result']\n",
        "train = data.drop(['result'], axis = 1)\n",
        "train.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "8m982QZMknvI",
        "outputId": "ae8982a5-d1be-49fd-ee43-1d748bc67cd6"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    batting_team         bowling_team       city  runs_left  \\\n",
              "125  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "126  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "127  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        207   \n",
              "128  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        205   \n",
              "129  Royal Challengers Bangalore  Sunrisers Hyderabad  Hyderabad        201   \n",
              "\n",
              "     balls_left  wickets  total_runs_x  cur_run_rate  req_run_rate  \n",
              "125         119       10           208           6.0     10.436975  \n",
              "126         118       10           208           3.0     10.525424  \n",
              "127         117       10           208           2.0     10.615385  \n",
              "128         116       10           208           4.5     10.603448  \n",
              "129         115       10           208           8.4     10.486957  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-050b53d1-5ca2-4943-962b-5adffb128e42\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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",
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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>cur_run_rate</th>\n",
              "      <th>req_run_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>207</td>\n",
              "      <td>119</td>\n",
              "      <td>10</td>\n",
              "      <td>208</td>\n",
              "      <td>6.0</td>\n",
              "      <td>10.436975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>126</th>\n",
              "      <td>Royal Challengers Bangalore</td>\n",
              "      <td>Sunrisers Hyderabad</td>\n",
              "      <td>Hyderabad</td>\n",
              "      <td>207</td>\n",
              "      <td>118</td>\n",
              "      <td>10</td>\n",
              "      <td>208</td>\n",
              "      <td>3.0</td>\n",
              "      <td>10.525424</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>207</td>\n",
              "      <td>117</td>\n",
              "      <td>10</td>\n",
              "      <td>208</td>\n",
              "      <td>2.0</td>\n",
              "      <td>10.615385</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>205</td>\n",
              "      <td>116</td>\n",
              "      <td>10</td>\n",
              "      <td>208</td>\n",
              "      <td>4.5</td>\n",
              "      <td>10.603448</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>201</td>\n",
              "      <td>115</td>\n",
              "      <td>10</td>\n",
              "      <td>208</td>\n",
              "      <td>8.4</td>\n",
              "      <td>10.486957</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-050b53d1-5ca2-4943-962b-5adffb128e42')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-050b53d1-5ca2-4943-962b-5adffb128e42 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-050b53d1-5ca2-4943-962b-5adffb128e42');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train,X_test,y_train,y_test = train_test_split(train,test,test_size=0.2,random_state=1)\n",
        "\n",
        "X_train.shape,X_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "64t6EkOVlAOs",
        "outputId": "b3305c55-d7bf-47bb-9a9e-6a06226871ce"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((57073, 9), (14269, 9))"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BDoMx2N7lWIo",
        "outputId": "840704aa-ba61-4476-9830-8938ff424305"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['batting_team', 'bowling_team', 'city', 'runs_left', 'balls_left',\n",
              "       'wickets', 'total_runs_x', 'cur_run_rate', 'req_run_rate'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn import metrics"
      ],
      "metadata": {
        "id": "PvMNvuuLlZlN"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# batting team,bowling team and city are categorical columns\n",
        "# they will be converted to numeric using onehot encoder\n",
        "\n",
        "cf = ColumnTransformer([\n",
        "    ('trf',OneHotEncoder(sparse=False,drop='first'),['batting_team','bowling_team','city'])\n",
        "],remainder='passthrough')\n"
      ],
      "metadata": {
        "id": "IuUB7Lpwlctd"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# creating the pipeline\n",
        "\n",
        "\n",
        "pipe = Pipeline(steps=[\n",
        "    ('step1',cf),\n",
        "    ('step2',LogisticRegression(solver='liblinear'))\n",
        "])\n",
        "\n",
        "# fitting the training data\n",
        "\n",
        "pipe.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mr8EhYpZleFk",
        "outputId": "d139f918-b379-4aa7-c5cc-4ee3aa845bf7"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(steps=[('step1',\n",
              "                 ColumnTransformer(remainder='passthrough',\n",
              "                                   transformers=[('trf',\n",
              "                                                  OneHotEncoder(drop='first',\n",
              "                                                                sparse=False),\n",
              "                                                  ['batting_team',\n",
              "                                                   'bowling_team', 'city'])])),\n",
              "                ('step2', LogisticRegression(solver='liblinear'))])"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = pipe.predict(X_test)\n",
        "print(metrics.accuracy_score(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Md72iTnFlgqc",
        "outputId": "2616dbd4-d860-4538-dde6-af6cf1c1e294"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.8063634452309202\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pipe.predict_proba(X_test)[10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n_Ji8fQZllQc",
        "outputId": "82a302a4-cfc2-4fae-99a0-e2cd71a69474"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.54510747, 0.45489253])"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Selecting Random Forest Classifier\n",
        "\n",
        "pipe2 = Pipeline(steps=[\n",
        "    ('step1',cf),\n",
        "    ('step2',RandomForestClassifier())\n",
        "])\n",
        "\n",
        "pipe2.fit(X_train,y_train)\n",
        "print(metrics.accuracy_score(y_test,pipe2.predict(X_test)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2ADddERomAlV",
        "outputId": "584dd355-2fe9-4016-cb24-c4da0d784f7d"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.9990889340528418\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# oth index is loose prob and 1st index is win prob\n",
        "\n",
        "pipe2.predict_proba(X_test)[10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aLi6x1_5mDUN",
        "outputId": "2d109be7-3baf-4c97-8340-7cc2fc39f657"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.1, 0.9])"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "I will go with Logistic Regression because i need to \n",
        "showcase the probability right,even though Random Forest is \n",
        "giving much accurate result,but RandomForest is being baised\n",
        "at one side,as you can observe the prob of winning for 10th sample\n",
        "is shown as 98% and 2% loose prob,this is kind of tooo strong or may\n",
        "be sometimes unrealistic,so its better to use a model which gives equal \n",
        "justice towards both side,as we also don't know which team will outperform \n",
        "and win the game!\n",
        "'''\n",
        "# saving the logistic regression model\n",
        "\n",
        "import pickle\n",
        "pickle.dump(pipe,open('pipe.pkl','wb'))"
      ],
      "metadata": {
        "id": "-4YjFsPKmFjd"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "MidjfQ46mH9L"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}