Analysis and Prediction of Cricket Match Using Machine Learning

Abstract

Machine learning is the most well-known field nowadays for predicting future output and making better decisions based on these predictions. Cricket is a popular sport that is watched and played in over 100 nations across the world. Many of these cricket fans are rooting for their side to succeed and win the match. Teams must focus on their performance and areas of strength in order to ensure that their teams win. Similarly, predicting the winner of a cricket match is dependent on a number of criteria such as the toss, team strengths, venue and weather conditions, and so on. The purpose of this research study is to perform exploratory data analysis on a cricket dataset and to predict the winner of the IPL match. Machine learning models trained on the given features are used to predict the winner of an IPL match. Varied machine learning techniques, like Random Forest, SVM, Linear Regression, Logistic Regression, and Decision Trees, have been utilized and deployed on test and training datasets of various sizes for the goal of model construction. For legal betting applications, match reporting media, and cricket fans, this concept is quite valuable. Exploratory data analysis on cricket dataset will be beneficial for cricket team management or analytics team to assess the team’s strength.