Cricket Analysis
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About
This dataset contains detailed ball-by-ball information from various cricket matches. It provides an in-depth view of match events, such as player performance, wickets, and scoring patterns, enabling analysis of team strategies, individual contributions, and overall match outcomes.
Dataset Features:
- Match ID: A unique identifier for each match.
- Date: The date on which the match was played.
- Venue: The stadium or location where the match took place.
- Bat First: The team that batted first in the match.
- Bat Second: The team that batted second in the match.
- Innings: The innings number (1 or 2) during the match.
- Over: The over in which the ball was bowled.
- Ball: The specific ball in the over.
- Batter: The player on strike facing the delivery.
- Non-Striker: The player at the non-striker's end.
- Bowler: The bowler delivers the ball.
- Batter Runs: The runs scored by the batter from a specific ball.
- Extra Runs: Additional runs awarded due to extras (integer value.).
- Runs From Ball: Total runs scored off the delivery, including extras.
- Ball Rebowled: Indicates whether the ball was re-bowled (Yes - 1/No - 0).
- Wicket: Indicates whether a wicket was taken (Yes - 1/No - 0).
- Method: Describes how the batter got out (e.g., bowled, caught, LBW).
- Player Out: The name of the player dismissed.
- Innings Runs: Total runs scored in the respective innings.
- Innings Wickets: Total wickets lost in the innings.
- Target Score: The score the batting team is chasing (if applicable).
- Runs to Get: Runs needed to win at that point in the match.
- Balls Remaining: Number of balls left in the innings.
- Winner: The team that won the match.
- Chased Successfully: Indicates whether the target was successfully chased (1 for Yes, 0 for No).
Usage:
This dataset is ideal for cricket analytics and machine learning tasks, including:
- Analysing player and team performance trends.
- Training predictive models for match outcomes.
- Developing simulation tools for cricket strategy optimisation.
- Identifying key moments and contributors in matches.
Coverage:
The dataset encompasses critical match and ball-level details, capturing the intricacies of cricket gameplay. It is suitable for exploring various analytical dimensions, such as player efficiency, bowling performance, and team tactics.
License:
CC0 (Public Domain)
Who can use it:
This dataset is designed for data scientists, sports analysts, machine learning practitioners, and cricket enthusiasts interested in leveraging data for sports analytics.
How to use it:
- Build predictive models for match outcomes and player performances.
- Analyse player contributions in different match contexts.
- Conduct exploratory data analysis on cricket match events.
- Simulate match scenarios to evaluate team strategies.