This repository contains a machine learning project aimed at predicting the first innings score in an Indian Premier League (IPL) cricket match. The goal is to use historical match data and various features to accurately forecast the total score that a team will achieve in their first innings. This can be useful for analysts, fans, and sports bettors who are interested in understanding potential match outcomes.
- Historical Match Data: Utilizes data from past IPL matches, including scores, player performances, and match conditions.
- Feature Engineering: Includes derived features such as batting and bowling averages, venue statistics, weather conditions, and more.
- Data Preprocessing: Handles missing values, encodes categorical variables, and normalizes numerical features.
- Modeling: Implements various machine learning models including linear regression, decision trees, random forests, and gradient boosting.
- Evaluation: Provides comprehensive evaluation metrics and visualizations to compare model performance.
- Prediction: Generates score predictions based on trained models and new input data.