@inproceedings{775efdc958114ac8a5873e23668dcd21,
title = "CricAI: A classification based tool to predict the outcome in ODI cricket",
abstract = "Victory is the ultimate goal in any sport. In this work we address the winning factors in the sport of One Day International (ODI) cricket. Winning an ODI cricket match depends on various factors related to scoring as well as physical strength of the two teams. Some of the factors have been described in the literature but there is scope for further research on analyzing them, especially with reference to predicting victory. Interesting factors include home game advantage, day / night effect, winning the toss and batting first. In this article, we have used artificial intelligence techniques, more specifically Bayesian classifiers in machine learning, to predict how these factors affect the outcome of an ODI cricket match. Based on the emerged results, we have developed a software tool called CricAI. This tool outputs the probability of victory in an ODI cricket match using input factors such as home game advantage available at the beginning of the match. The CricAI tool can be used in real-world applications by teams playing cricket. It can accordingly be helpful in adjusting certain factors in order to maximize the chances of winning the real game.",
keywords = "Ai and automation, Bayes thoerem, Classifiers, Predictive analysis, Probability, Sports applications",
author = "Amal Kaluarachchi and Varde, {Apama S.}",
year = "2010",
doi = "10.1109/ICIAFS.2010.5715668",
language = "English",
isbn = "9781424485512",
series = "Proceedings of the 2010 5th International Conference on Information and Automation for Sustainability, ICIAfS 2010",
pages = "250--255",
booktitle = "Proceedings of the 2010 5th International Conference on Information and Automation for Sustainability, ICIAfS 2010",
note = "2010 5th International Conference on Information and Automation for Sustainability, ICIAfS 2010 ; Conference date: 17-12-2010 Through 19-12-2010",
}