Impact of Toss on the Result of IPL Matches Using Machine Learning

Cricket is by far the most popular sport in India and is played virtually everywhere. The Indian Premier League (IPL) is a professional men's Twenty20 cricket tournament contested by 10 clubs based in 10 distinct Indian cities. In 2007, the Board of Control for Cricket in India (BCCI) founded the division. Cricket match results are largely influenced by a number of key variables, including the toss, home field advantage, previous results, the location, the team's current form, and the players. However, we focused on the most important factor because it has the greatest impact on all other factors. The primary objective of this paper is to determine whether a team's decision to win the coin toss affects its odds of winning the game. If so, by what percentage does it change? We have conducted a thorough research on the winning percentage of the team that won the toss using a variety of algorithms. The supervised machine learning techniques k-nearest neighbors (KNN), Naive Bayes, Decision trees, support vector machines (SVM), and random forests have all been implemented. We found that KNN had the best accuracy, at 76%, while Naive Bayes had the lowest accuracy, at 60%. According to the findings of this study, the team that wins the coin toss has about 80% of the odds of winning the game since they get to choose the criteria based on their strengths and side advantages. Additionally, other cricket formats include the One-Day International (ODI), Champion League and many more tournaments.