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: Journal article publicationJournal articleAcademic researchpeer-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
JournalJournal of the Operational Research Society
DOIs
Publication statusAccepted/In press - 2024

Keywords

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

ASJC Scopus subject areas

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

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