IPL 2022 Complete Dataset

About this Dataset

Tata IPL is among the most famous cricket league with players coming from worldwide. What makes this series more competitive this year is the auction resulting in all players changing their squad and two new teams added to the league. With IPL starting on 26th March 2022 this year, this dataset is a complete dataset showing match information and also data for each delivery. This dataset will be updated daily with data of the matches coming every day.

The file IPL_Matches_2022.csv contains all details of the match: Venue of the match, Toss Decision, Match Winer, Man of the Match, Squads, etc.
The file IPL_Ball_by_Ball_2022.csv contains ball by ball data of each and every match: Batsman on strike, Bowler, Extras, Runs, Wicket Ball, etc.

Dataset will be updated after every matchday.

Other IPL Database

Interesting Task Ideas

What is the percentage of wins of each team?
Which venue results in a win for Batting first team and vice versa?
Who is the most consistent batsman and bowler in each team and also in the entire league?
Who wins the most player of the matches in the tournament?
Predict the winning team with the consistency of wins and ball deliveries?
Who is the most valuable player after every match day?

Check my other datasets

Acknowledgements

Datasource: Cricsheet
Image Credits

Tables

Ipl Ball By Ball 2022

@kaggle.vora1011_ipl_2022_match_dataset.ipl_ball_by_ball_2022

87.19 KB
17912 rows
17 columns


CREATE TABLE ipl_ball_by_ball_2022 (
  "id" BIGINT,
  "innings" BIGINT,
  "overs" BIGINT,
  "ballnumber" BIGINT,
  "batter" VARCHAR,
  "bowler" VARCHAR,
  "non_striker" VARCHAR,
  "extra_type" VARCHAR,
  "batsman_run" BIGINT,
  "extras_run" BIGINT,
  "total_run" BIGINT,
  "non_boundary" BIGINT,
  "iswicketdelivery" BIGINT,
  "player_out" VARCHAR,
  "kind" VARCHAR,
  "fielders_involved" VARCHAR,
  "battingteam" VARCHAR
);

Ipl Matches 2022

@kaggle.vora1011_ipl_2022_match_dataset.ipl_matches_2022

25.25 KB
74 rows
20 columns


CREATE TABLE ipl_matches_2022 (
  "id" BIGINT,
  "city" VARCHAR,
  "date" TIMESTAMP,
  "season" BIGINT,
  "matchnumber" VARCHAR,
  "team1" VARCHAR,
  "team2" VARCHAR,
  "venue" VARCHAR,
  "tosswinner" VARCHAR,
  "tossdecision" VARCHAR,
  "superover" VARCHAR,
  "winningteam" VARCHAR,
  "wonby" VARCHAR,
  "margin" BIGINT,
  "method" VARCHAR,
  "player_of_match" VARCHAR,
  "team1players" VARCHAR,
  "team2players" VARCHAR,
  "umpire1" VARCHAR,
  "umpire2" VARCHAR
);