Machine Learning Techniques for Result Prediction of One Day International (ODI)Cricket Match

Abstract

Cricket is the most popular sport and most watched now a day. Test matches, One Day Internationals (ODI), and Twenty20 Internationals are the three forms in which it is played. Until the last ball of the last over, no one can predict who would win the match. Machine learning is a new field that uses existing data to predict future results. The goal of this study is to build a model that will predict the winner of a One-Day International Match before it begins. Machine learning techniques will be used on testing and training datasets to predict the winner of ODI match that will be based on the specified features. The data for the model is collected from Kaggle and some of the data are collected from the different cricket websites because the data obtained from Kaggle has only matches up until July 2021. Two algorithms were used for the prediction, K-Nearest and XGBoost, out of these two algorithms prediction accuracy of 91% was obtained by K-Nearest Neighbor Algorithm and prediction accuracy of 89% was obtained by XGBoost Algorithm