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MoneyBall - Data Mining on Cricket Dataset


Using Big Data Analytics to Cr

Scalable and Secure Big Data I

3D Reconstruction in Canonical
Abstract


Cricket is one of the most popular sports in the whole world, and also one of the most popular sports in India. Cricketing events such as the Indian Premier League (IPL) are thoroughly enjoyed by fans all across the country. Fans of the game love predicting the ongoing match results, and this is something that has ended up being a hobby for several people who follow the game. This is a sport with abundant amount of data and using this data, we can make an evaluation on whether a team can win an ongoing IPL match or not. This prediction is implemented by using machine learning algorithms such as Gaussian Naive Bayes, Support Vector Machine, KNearest Neighbor and Random Forest. The required dataset is obtained by collecting using a website and consolidated. As a result, the output is obtained which lists whether the home team has won the match or not. The accuracies obtained are 75%, 80%, 55%, 75%, 80%, 80%, 75% and 84% for the teams CSK, RR, DD, RCB, MI, SRH, KXIP and KKR respectively

KeyWords
Machine Learning, Data Mining, Moneyball, Cricket Dataset, Indian Premier League (IPL)



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