u/Careless_Opposite798

IPL Player Career Progression (2008-2025) on #kaggle via @KaggleDatasets

A comprehensive dataset tracking the career progression of every IPL player from 2008 to 2025. This dataset provides season-by-season batting and bowling statistics computed from ball-by-ball match data, enabling rich analysis of player development, peak performance periods, and career trajectories.

Quick Stats

* **Seasons**: 2008-2025 (18 seasons) * **Players**: 771 * **Ball-by-ball deliveries analyzed**: 278,034 * **Batting records**: 2,782 player-season combinations * **Bowling records**: 2,075 player-season combinations

Methodology

All stats computed from ball-by-ball IPL match data sourced from [cricsheet.org](https://cricsheet.org):

* **Batting average** = Runs / (Innings - Not Outs) * **Strike rate** = (Runs / Balls) × 100 * **Economy** = Runs Conceded / (Balls / 6) * **Bowling SR** = Balls / Wickets * Wickets count: caught, bowled, lbw, caught & bowled, stumped, hit wicket * Bowling stats exclude wides, no-balls, and penalty runs

Use Cases

* Player career trajectory analysis * Peak performance identification * Fantasy cricket & auction analytics * Statistical modeling & ML * Data visualization projects

reddit.com
u/Careless_Opposite798 — 5 days ago
▲ 2 r/kaggle

IPL Player Career Progression (2008-2025) on #kaggle via @KaggleDatasets

Overview

A comprehensive dataset tracking the career progression of every IPL player from 2008 to 2025. This dataset provides season-by-season batting and bowling statistics computed from ball-by-ball match data, enabling rich analysis of player development, peak performance periods, and career trajectories.

Data Source: iplrecords.com

Quick Stats

  • Seasons: 2008-2025 (18 seasons)
  • Players: 771
  • Ball-by-ball deliveries analyzed: 278,034
  • Batting records: 2,782 player-season combinations
  • Bowling records: 2,075 player-season combinations

Files

ipl_players_master.csv (771 rows)

Player registry with career totals for every IPL player.

Column Description
player_name Full display name
country Player's country
debut_year First IPL season
last_year Most recent IPL season
seasons_played Number of seasons participated
teams Comma-separated list of teams
career_runs Total career runs
career_balls_faced Total balls faced
career_batting_innings Total batting innings
career_hundreds Centuries (100+ runs)
career_fifties Half-centuries (50-99 runs)
career_highest_score Best individual score
career_fours Total fours
career_sixes Total sixes
career_batting_sr Career strike rate
career_wickets Total wickets
career_bowling_innings Total bowling innings
career_bowling_economy Career economy rate
career_bowling_sr Career bowling strike rate

ipl_batting_career_progression.csv (2,782 rows)

Season-by-season batting stats for each player.

Column Description
player_name Player name
country Player's country
season IPL season year
team Team represented
innings Matches batted
not_outs Times remained not out
runs_scored Runs scored
balls_faced Balls faced
batting_average Runs per dismissal
batting_strike_rate Runs per 100 balls
highest_score Season best score
hundreds Centuries
fifties Half-centuries
fours Fours hit
sixes Sixes hit

ipl_bowling_career_progression.csv (2,075 rows)

Season-by-season bowling stats for each player.

Column Description
player_name Player name
country Player's country
season IPL season year
team Team represented
innings Matches bowled
balls_bowled Balls bowled
total_runs_conceded Runs conceded
total_wickets Wickets taken
economy_rate Runs per over
bowling_average Runs per wicket
bowling_strike_rate Balls per wicket
best_wickets Best match figures
three_wicket_hauls Matches with 3 wickets
four_wicket_hauls Matches with 4 wickets
five_wicket_hauls Matches with 5+ wickets

Methodology

All stats computed from ball-by-ball IPL match data sourced from cricsheet.org:

  • Batting average = Runs / (Innings - Not Outs)
  • Strike rate = (Runs / Balls) × 100
  • Economy = Runs Conceded / (Balls / 6)
  • Bowling SR = Balls / Wickets
  • Wickets count: caught, bowled, lbw, caught & bowled, stumped, hit wicket
  • Bowling stats exclude wides, no-balls, and penalty runs

Use Cases

  • Player career trajectory analysis
  • Peak performance identification
  • Fantasy cricket & auction analytics
  • Statistical modeling & ML
  • Data visualization projects

Attribution

Data sourced from iplrecords.com. For live IPL statistics and records, visit the site.

kaggle.com
u/Careless_Opposite798 — 5 days ago