Indian Premier League Cricket Match Winner Predictor 2025 : A Sports Analytics Study

In this paper, we present a comprehensive study on predicting the outcome of Indian Premier League (IPL) cricket matches using machine learning techniques. We utilized a dataset comprising match details and team information, processed to ensure consistency and integrity. Various classification algorithms, including Gradient Boosting, Decision Tree Classifier, Random Forest, and Light Gradient Boosting Machine, were employed and optimized using hyperparameter tuning to enhance predictive accuracy. Our findings indicate that the Light Gradient Boosting Machine model achieved the highest performance, demonstrating the effectiveness of machine learning in sports analytics. The study also highlights the importance of features such as player performance, team strength, and match conditions in predicting match outcomes. These insights not only advance the application of predictive modeling in sports but also provide valuable tools for analysts and enthusiasts to understand and anticipate game results.