论文标题
使用贝叶斯先验预测板球的结果
Predicting Cricket Outcomes using Bayesian Priors
论文作者
论文摘要
这项研究开发了一种统计建模程序，以预测未来板球比赛的结果。拟议的模型通过纳入各个参与者的表现历史以及贝叶斯先验，不仅与特定的反对派，而且还与任何板球比赛国家 - 国际板球委员会（ICC）的正式成员，还可以结合各个球员的表现历史以及贝叶斯先验，从而深入了解团队选择模式的应用。提供了印度下一个ICC板球世界杯2023年世界杯的案例研究，对所有参与团队彼此之间的预测进行了预测，并讨论了模拟结果。拟议的统计模型在2020年印度超级联赛（IPL）赛季进行了测试。该模型正确地预测了IPL 2020的前三名，包括锦标赛的获胜者，孟买印第安人和其他职位，并具有合理的准确性。该方法可以预测每个参与团队获胜的概率。此方法也可以扩展到其他板球比赛。
This research has developed a statistical modeling procedure to predict outcomes of future cricket tournaments. Proposed model provides an insight into the application of stratified survey sampling to the team selection pattern by incorporating individual players' performance history coupled with Bayesian priors not only against a particular opposition but also against any cricket playing nation - full member of International Cricket Council (ICC). A case study for the next ICC cricket world cup 2023 in India is provided, predictions are obtained for all participating teams against one another, and simulation results are discussed. The proposed statistical model is tested on 2020 Indian Premier League (IPL) season. The model predicted the top three finishers of IPL 2020 correctly, including the winners of the tournament, Mumbai Indians, and other positions with reasonable accuracy. The method can predict probabilities of winning for each participating team. This method can be extended to other cricket tournaments as well.
