MoneyBall - Data Mining on Cricket Dataset

2019 International Conference on Computational Intelligence in Data Science (ICCIDS) Pub Date : 2019-02-01 DOI:10.1109/ICCIDS.2019.8862065

D. Thenmozhi, P. Mirunalini, S. M. Jaisakthi, Srivatsan Vasudevan, V. Veeramani Kannan, S. Sagubar Sadiq

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引用次数: 10

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, K-Nearest 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.

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MoneyBall -对板球数据集的数据挖掘

板球是世界上最受欢迎的运动之一，也是印度最受欢迎的运动之一。印度板球超级联赛(IPL)等板球赛事深受全国各地球迷的喜爱。这款游戏的粉丝喜欢预测正在进行的比赛结果，这最终成为一些关注这款游戏的人的爱好。这是一项拥有大量数据的运动，使用这些数据，我们可以对一支球队是否能够赢得正在进行的IPL比赛进行评估。这种预测是通过使用机器学习算法，如高斯朴素贝叶斯，支持向量机，k近邻和随机森林来实现的。需要的数据集是通过网站收集和整合得到的。结果，输出将列出主队是否赢得了比赛。CSK、RR、DD、RCB、MI、SRH、KXIP和KKR的准确率分别为75%、80%、55%、75%、80%、80%、75%和84%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 International Conference on Computational Intelligence in Data Science (ICCIDS)

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