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.

中文翻译：

---

使用贝叶斯先验预测板球结果

本研究开发了一种统计建模程序来预测未来板球比赛的结果。提出的模型通过将个人球员的表现历史与贝叶斯先验相结合，不仅针对特定的反对派而且针对任何板球比赛国家 - 国际板球理事会 (ICC ）。提供了下一届 2023 年印度 ICC 板球世界杯的案例研究，获得了所有参赛球队相互对抗的预测，并讨论了模拟结果。所提出的统计模型在 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，和其他具有合理准确性的位置。该方法可以预测每个参与团队的获胜概率。这种方法也可以扩展到其他板球比赛。