Dataset: IPL Ball-by-Ball Dataset

About this Dataset

IPL Ball-by-Ball Dataset

IPL is one of the most-attended cricket league. We have collected data of almost every match from 2008 to 2019. The collected data is well processed and cleaned using Python tool. With the help of this dataset we can analyze the status of each team whether it is going to win or lose. We can apply various machine learning and deep learning algorithms to predict the probability of win. We have chosen very real features which are used for predicting the probability of win based on current score, balls left, current run rate, wickets left etc.

👉 Feature Name👈	👉 Meaning👈
batting team	(current) team for batting in 2nd inning
bowling team	(previous) team for bowling in 2nd inning
runs left	for every ball (out of ~120 balls) runs left for win
balls left	balls left (out of ~120)
wicktes	wickets left
target runs	target runs (score by 1st team which is bowling team now)
cur run rate	represent current run rate of batting team
req run rate	represent required run rate fot batting team to win the match
result	1 if team 2 (currently batting team) won otherwise 0

Tables

Ipl B2b Dataset

@kaggle.karandej_ipl_ball_by_ball_score_dataset.ipl_b2b_dataset

887.91 KB
72413 rows
11 columns


CREATE TABLE ipl_b2b_dataset (
  "index" BIGINT,
  "batting_team" VARCHAR,
  "bowling_team" VARCHAR,
  "city" VARCHAR,
  "runs_left" BIGINT,
  "balls_left" BIGINT,
  "wickets" BIGINT,
  "target_runs" BIGINT,
  "cur_run_rate" DOUBLE,
  "req_run_rate" VARCHAR,
  "result" BIGINT
);