Name: IPL Complete Dataset (2008- Till Today)
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

IPL Complete Dataset (2008- Till Today)

About Dataset

Context

Now that this year's IPL is over, let's not curb our cricket love and start analyzing the whole of IPL with this latest and complete Indian Premier League dataset. It contains the match descriptions, results, winners, players of the matches, ball-by-ball dataset, and much more. So, stop thinking and start analyzing.

Content

This dataset consists of two seperate CSV files: match_info and deliveries. These files contain the information of each match summary and ball-by-ball details, respectively.

Acknowledgments

Data Source: Cricsheet

PLEASE UPVOTE 👍 THIS DATASET IF YOU APPRECIATE OUR HARD WORK 🙏
WE WILL CONTINUOUSLY UPDATE THIS DATASET TO GIVE YOU THE BEST AND LATEST DATA TO WORK WITH 💯

Tables

Deliveries

@kaggle.colearninglounge_ipl_dataset_download_python_tableau_analysis.deliveries

1.48 MB
225,954 rows
23 columns

CREATE TABLE deliveries (
  "match_id" BIGINT,
  "season" VARCHAR,
  "innings" BIGINT,
  "ball" DOUBLE,
  "batting_team" VARCHAR,
  "bowling_team" VARCHAR,
  "striker" VARCHAR,
  "non_striker" VARCHAR,
  "bowler" VARCHAR,
  "runs_off_bat" BIGINT,
  "extras" BIGINT,
  "wides" DOUBLE,
  "noballs" DOUBLE,
  "byes" DOUBLE,
  "legbyes" DOUBLE,
  "penalty" DOUBLE,
  "wicket_type" VARCHAR,
  "player_dismissed" VARCHAR,
  "other_wicket_type" VARCHAR,
  "other_player_dismissed" VARCHAR,
  "striker_id" VARCHAR,
  "non_striker_id" VARCHAR,
  "bowler_id" VARCHAR
);

Match Details

@kaggle.colearninglounge_ipl_dataset_download_python_tableau_analysis.match_details

37.99 kB
950 rows
21 columns

CREATE TABLE match_details (
  "balls_per_over" BIGINT,
  "team1" VARCHAR,
  "team2" VARCHAR,
  "gender" VARCHAR,
  "season" VARCHAR,
  "date" TIMESTAMP,
  "event" VARCHAR,
  "match_number" DOUBLE,
  "toss_winner" VARCHAR,
  "toss_decision" VARCHAR,
  "player_of_match" VARCHAR,
  "winner" VARCHAR,
  "win_by" DOUBLE,
  "match_id" BIGINT,
  "winner_type" VARCHAR,
  "outcome" VARCHAR,
  "eliminator" VARCHAR,
  "method" VARCHAR,
  "date1" TIMESTAMP,
  "date2" TIMESTAMP,
  "venueid" VARCHAR
);

Players Info With Keys

@kaggle.colearninglounge_ipl_dataset_download_python_tableau_analysis.players_info_with_keys

51.84 kB
642 rows
10 columns

CREATE TABLE players_info_with_keys (
  "name" VARCHAR,
  "full_name" VARCHAR,
  "birth_info" VARCHAR,
  "batting_style" VARCHAR,
  "bowling_style" VARCHAR,
  "playing_position" VARCHAR,
  "identifier" VARCHAR,
  "key_cricinfo" BIGINT,
  "bowling_type" VARCHAR,
  "bowling_arm" VARCHAR
);

Playing 11

@kaggle.colearninglounge_ipl_dataset_download_python_tableau_analysis.playing_11

232.11 kB
20,900 rows
6 columns

CREATE TABLE playing_11 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "match_id" BIGINT,
  "team" VARCHAR,
  "players" VARCHAR,
  "identifier" VARCHAR,
  "key_cricinfo" DOUBLE
);

Venue

@kaggle.colearninglounge_ipl_dataset_download_python_tableau_analysis.venue

3.78 kB
33 rows
3 columns

CREATE TABLE venue (
  "id" VARCHAR,
  "venue" VARCHAR,
  "city" VARCHAR
);