Super Predictor of Indian Premier League (IPL) using Various ML techniques with help of IBM Cloud

Abstract—Indian Premier League matches are one in every of the foremost important events India. it's professional cricket league India contested by eight teams representing various cities The paper focuses on performance analysis contesting IPL supported runs team, wickets, decisions usurping winning toss and Duckworth Lewis rule analysis. data from 2008 to 2019 is used for player team performances visualized graphically using analytics render interpretation an exceedingly good manner. visual helps selecting players future provides additional information yet as profiles. Almost team’s Management use Analytics better games. Not only owners, there several betting fantasy platform, which highly rely upon his or her success. can help all them research tries predict machine learning models with variables like match id, inning, batting bowling over, ball, batsman, non-striker, bowler super wide runs, bye leg penalty batsman extra total dismissed, dismissal kind fielder. appear out result it uses different statistical method model, Random Forest. results study shows that game, Teams, Venue, Winning Toss, Venue Match Decision after influencers win a match. Different Machine Learning outcome Right selection Model extend Accuracy Prediction. From Classification Models, Support Vector Machine, Tree Forest best All subsequent gives almost 88% accuracy Level. has been conducted Kaggle. Secondary