{"title":"一个贝叶斯框架,用于通过隐藏代码分析体育运动中的作弊行为,应用于桥牌和棒球","authors":"Aafko Boonstra, Ronald Meester","doi":"10.1016/j.serev.2025.100050","DOIUrl":null,"url":null,"abstract":"<div><div>We develop a statistical framework to evaluate evidence of alleged cheating involving illegal signaling in sports from a forensic perspective. We explain why, instead of a frequentist procedure, a Bayesian approach is called for. We apply this framework to cases of alleged cheating in professional bridge and professional baseball. The diversity of these applications illustrates the generality of the method.</div></div>","PeriodicalId":101182,"journal":{"name":"Sports Economics Review","volume":"9 ","pages":"Article 100050"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Bayesian framework for analyzing alleged cheating in sports through hidden codes, with applications to bridge and baseball\",\"authors\":\"Aafko Boonstra, Ronald Meester\",\"doi\":\"10.1016/j.serev.2025.100050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We develop a statistical framework to evaluate evidence of alleged cheating involving illegal signaling in sports from a forensic perspective. We explain why, instead of a frequentist procedure, a Bayesian approach is called for. We apply this framework to cases of alleged cheating in professional bridge and professional baseball. The diversity of these applications illustrates the generality of the method.</div></div>\",\"PeriodicalId\":101182,\"journal\":{\"name\":\"Sports Economics Review\",\"volume\":\"9 \",\"pages\":\"Article 100050\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sports Economics Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2773161825000047\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sports Economics Review","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2773161825000047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Bayesian framework for analyzing alleged cheating in sports through hidden codes, with applications to bridge and baseball
We develop a statistical framework to evaluate evidence of alleged cheating involving illegal signaling in sports from a forensic perspective. We explain why, instead of a frequentist procedure, a Bayesian approach is called for. We apply this framework to cases of alleged cheating in professional bridge and professional baseball. The diversity of these applications illustrates the generality of the method.