Forecasting number of corner kicks taken in association football using compound Poisson distribution

Stan Yip, Yinghong Zou, Ronald Tsz Hin Hung, Ka Fai Cedric Yiu

Research output: Contribution to journalJournal articlepeer-review

Abstract

This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution are introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed.
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalJournal of the Operational Research Society
DOIs
Publication statusE-pub ahead of print - 2 Feb 2024

Scopus Subject Areas

  • Statistics, Probability and Uncertainty
  • Modelling and Simulation
  • Strategy and Management
  • Management Science and Operations Research

User-Defined Keywords

  • Bayesian hierarchical models
  • compound Poisson distribution
  • corner kick
  • geometric-Poisson distribution
  • football
  • negative binomial distribution

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