Name: Indian Premier League (IPL) Match Data 2008-2023
Creator: Kaggle
License: https://www.apache.org/licenses/

About this Dataset

Indian Premier League (IPL) Match Data 2008-2023

This dataset contains historical match results, batting cards, bowling cards, fall of wickets cards, partnership cards, players info and ball by ball data for all IPL matches since 2008 till date. The dataset is split into multiple files, each containing a different type of data.

Files:

ipl_historical.csv: Contains match results data, such as the date, venue, teams involved, toss winner, toss decision, result, margin of victory, player of the match, etc.
ipl_batting_card.csv: Contains batting card data, such as the player name, team, batting position, runs scored, balls faced, fours, sixes, strike rate, dismissal method, etc.
ipl_bowling_card.csv: Contains bowling card data, such as the player name, team, bowling overs, maidens, runs conceded, wickets taken, economy rate, etc.
ipl_fow_card.csv: Contains fall of wicket data, such as the over number, wicket number, batsman name, dismissal method, etc.
ipl_partnership_card.csv: Contains partnership data, such as the partnership number, batsmen names, runs scored, balls faced, etc.
ipl_players_info.csv: Contains player information data, such as the player name, team, nationality, batting style, bowling style, etc.
ipl_ball_by-ball_data.csv: Contains ball-by-ball data for all IPL matches, such as the batsman name, bowler name, runs scored, extras, wicket ball, etc.

Potential Uses:

This dataset can be used for a variety of purposes, such as:

i.   Analyzing the performance of teams and players over time
ii.  Identifying trends in the game
iii. Developing predictive models for match outcomes
iv. Creating simulations of matches
v.  Creating educational and entertainment content

Licensing:

This dataset is licensed under the Open Database License (ODbL). This means that it is free to use, share, and modify for any purpose. The only requirement is that you must attribute the dataset to its creators.

Tables

Ipl Ball By Ball Data

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_ball_by_ball_data

1.13 MB
243,657 rows
21 columns

CREATE TABLE ipl_ball_by_ball_data (
  "series_id" BIGINT,
  "match_id" BIGINT,
  "innings_no" DOUBLE,
  "batsman_id" DOUBLE,
  "bowler_id" DOUBLE,
  "over_number" DOUBLE,
  "ball_number" DOUBLE,
  "over" DOUBLE,
  "total_runs" DOUBLE,
  "batsman_runs" DOUBLE,
  "isfour" VARCHAR,
  "issix" VARCHAR,
  "iswicket" VARCHAR,
  "byes" DOUBLE,
  "legbyes" DOUBLE,
  "wides" DOUBLE,
  "noballs" DOUBLE,
  "penalties" DOUBLE,
  "out_player_id" DOUBLE,
  "current_innings_runs" DOUBLE,
  "current_innings_wickets" DOUBLE
);

Ipl Batting Card

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_batting_card

228.77 kB
22,497 rows
14 columns

CREATE TABLE ipl_batting_card (
  "match_id" BIGINT,
  "innings" BIGINT,
  "team" VARCHAR,
  "batsman_id" DOUBLE,
  "batsman_position" DOUBLE,
  "runs" DOUBLE,
  "balls" DOUBLE,
  "fours" DOUBLE,
  "sixes" DOUBLE,
  "strikerate" DOUBLE,
  "isout" VARCHAR,
  "wickettype" VARCHAR,
  "fielders" VARCHAR,
  "bowler_id" DOUBLE
);

Ipl Bowling Card

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_bowling_card

124.77 kB
12,123 rows
16 columns

CREATE TABLE ipl_bowling_card (
  "match_id" BIGINT,
  "innings" BIGINT,
  "team" VARCHAR,
  "opposition" VARCHAR,
  "bowler_id" DOUBLE,
  "overs" DOUBLE,
  "balls" DOUBLE,
  "maidens" DOUBLE,
  "conceded" DOUBLE,
  "wickets" DOUBLE,
  "economy" DOUBLE,
  "dots" DOUBLE,
  "fours" DOUBLE,
  "sixes" DOUBLE,
  "wides" DOUBLE,
  "noballs" DOUBLE
);

Ipl Fow Card

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_fow_card

72.31 kB
12,042 rows
7 columns

CREATE TABLE ipl_fow_card (
  "match_id" BIGINT,
  "innings" BIGINT,
  "team" VARCHAR,
  "player_id" DOUBLE,
  "wicket" DOUBLE,
  "overs" DOUBLE,
  "runs" DOUBLE
);

Ipl Historical

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_historical

141.57 kB
1,025 rows
34 columns

CREATE TABLE ipl_historical (
  "season" BIGINT,
  "title" VARCHAR,
  "match_id" BIGINT,
  "match_name" VARCHAR,
  "series_id" BIGINT,
  "series_name" VARCHAR,
  "match_date" TIMESTAMP,
  "match_format" VARCHAR,
  "team1_id" BIGINT,
  "team1_name" VARCHAR,
  "team1_captain" BIGINT,
  "team1_runs_scored" DOUBLE,
  "team1_wickets_fell" DOUBLE,
  "team1_extras_rec" DOUBLE,
  "team2_id" BIGINT,
  "team2_name" VARCHAR,
  "team2_captain" BIGINT,
  "team2_runs_scored" DOUBLE,
  "team2_wickets_fell" DOUBLE,
  "team2_extras_rec" DOUBLE,
  "match_venue_stadium" VARCHAR,
  "match_venue_city" VARCHAR,
  "match_venue_country" VARCHAR,
  "umpire1" VARCHAR,
  "umpire2" VARCHAR,
  "match_referee" VARCHAR,
  "toss_winner" VARCHAR,
  "toss_winner_choice" VARCHAR,
  "match_winner" VARCHAR,
  "match_result_text" VARCHAR,
  "mom_player" DOUBLE,
  "team1_playing11" VARCHAR,
  "team2_playing11" VARCHAR,
  "debut_players" VARCHAR
);

Ipl Partnership Card

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_partnership_card

154.68 kB
13,678 rows
13 columns

CREATE TABLE ipl_partnership_card (
  "match_id" BIGINT,
  "innings" BIGINT,
  "for_wicket" DOUBLE,
  "team" VARCHAR,
  "opposition" VARCHAR,
  "player1_id" DOUBLE,
  "player2_id" DOUBLE,
  "player1_runs" DOUBLE,
  "player2_runs" DOUBLE,
  "player1_balls" DOUBLE,
  "player2_balls" DOUBLE,
  "partnership_runs" DOUBLE,
  "partnership_balls" DOUBLE
);

Ipl Players Info

@kaggle.bhuvaneshprasad_ipl_dataset_2008_2023_only_dataset_you_need.ipl_players_info

96.69 kB
696 rows
11 columns

CREATE TABLE ipl_players_info (
  "player_id" BIGINT,
  "player_object_id" BIGINT,
  "player_name" VARCHAR,
  "dob" TIMESTAMP,
  "dod" TIMESTAMP,
  "gender" VARCHAR,
  "batting_style" VARCHAR,
  "bowling_style" VARCHAR,
  "country_id" BIGINT,
  "image_url" VARCHAR,
  "image_metadata" VARCHAR
);