Cricket Win Prediction using Machine Learning

Abstract

Abstract: Cricket, being one of the most popular sports worldwide, has attracted significant interest in developing accurate win prediction models. With the advent of machine learning techniques, researchers have leveraged the power of data-driven algorithms to predict cricket match outcomes. This research paper aims to improve cricket win prediction model by using XGBoost machine learning algorithm. Feature importance analysis is conducted to identify the most influential factors contributing to match outcomes. The dataset is divided into training and test sets, and the models are evaluated on both datasets to measure their generalization performance. The findings demonstrate the potential of machine learning techniques in accurately forecasting cricket match outcomes, enabling stakeholders to make informed decisions in the dynamic and unpredictable domain of cricket