T20 Cricket Match Score Dataset

This dataset provides simulated data for predicting the final score of a cricket team in a T20 match based on various match and environmental factors. It is intended for beginner to intermediate machine learning practitioners who want to experiment with regression models in sports analytics. The dataset includes common factors that can influence a cricket match score, such as overs played, wickets lost, run rate, opponent strength, pitch conditions, and weather.

Each row represents a unique T20 match scenario, and the target variable is the predicted total score for the batting team at the end of their innings.

Dataset Structure:

Match ID: Unique identifier for each match.
Overs Played: Overs completed (between 1 and 20, as per T20 format).
Wickets Lost: Number of wickets lost by the batting team.
Run Rate: Runs per over at the current state of the match.
Home/Away: Whether the match is played at the team’s home ground or away.
Opponent Strength: Rating from 1 to 10, indicating the opponent’s bowling strength.
Pitch Condition: Type of pitch – Batting-friendly, Bowling-friendly, or Balanced.
Weather: Weather conditions during the match – Sunny, Cloudy, or Overcast.
Predicted Score: Target variable. Predicted total score for the team based on match conditions.