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A Two-Stage Bayesian Model for Predicting Winners in Major League Baseball
並列摘要
The probability of winning a game in major league baseball depends on various factors relating to team strength including the past performance of the two teams, the batting ability of the two teams and the starting pitchers. These three factors change over time. We combine these factors by adopting contribution parameters, and include a home field advantage variable in forming a two-stage Bayesian model. A Markov chain Monte Carlo algorithm is used to carry out Bayesian inference and to simulate outcomes of future games. We apply the approach to data obtained from the 2001 regular season in major league baseball.
被引用紀錄
陳昱先（2013）。應用模糊知識本體發展賽事預測系統〔碩士論文，中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201301005
莊聖儀（2007）。台灣初級淡水魚分布與棲地環境因子之關聯性〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2007.01088
呂中堯（2010）。運用Copula-based Regression Model預測中華職棒賽事結果〔碩士論文，國立臺北大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0023-1901201021482400
延伸閱讀
- 周正宸（2013）。Revisit the Relationship Between Team Performance and the Salary Structure in Major League Baseball〔碩士論文，國立清華大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0016-2211201316592169
- 楊意婷（2011）。The Study on The Predictability of Probit and Logistic Regression Models: Case Study of The United States Major League Baseball〔碩士論文，健行科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0022-2507201112123000
- 李俞麟、施致平、黃蕙娟（2011）。An Analysis of Team Performance in Major League Baseball。臺灣體育運動管理學報，11(4)，317-335。https://doi.org/10.6547/tassm.2011.0015
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