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A Bayesian inference approach for determining player abilities in football
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Whitaker, Gavin, Silva, Ricardo, Edwards, Daniel and Kosmidis, Ioannis (2021) A Bayesian inference approach for determining player abilities in football. Journal of the Royal Statistical Society: Series C (Applied Statistics), 70 (1). pp. 174-201. doi:10.1111/rssc.12454 ISSN 0035-9254.
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WRAP-Bayesian-approach-determining-player-abilities-football-Kosmidis-2020.pdf - Accepted Version - Requires a PDF viewer. Download (1460Kb) | Preview |
Official URL: https://doi.org/10.1111/rssc.12454
Abstract
We consider the task of determining a football player's ability for a given event type, for example, scoring a goal. We propose an interpretable Bayesian model which is fit using variational inference methods. We implement a Poisson model to capture occurrences of event types, from which we infer player abilities. Our approach also allows the visualisation of differences between players, for a specific ability, through the marginal posterior variational densities. We then use these inferred player abilities to extend the Bayesian hierarchical model of Baio and Blangiardo (2010) which captures a team's scoring rate (the rate at which they score goals). We apply the resulting scheme to the English Premier League, capturing player abilities over the 2013/2014 season, before using output from the hierarchical model to predict whether over or under 2.5 goals will be scored in a given game in the 2014/2015 season. This validates our model as a way of providing insights into team formation and the individual success of sports teams.
Item Type: | Journal Article | ||||||||||||
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Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||
Library of Congress Subject Headings (LCSH): | Bayesian statistical decision theory, Soccer -- Ability testing , Soccer -- Ability testing -- Statistical methods, Variational principles | ||||||||||||
Journal or Publication Title: | Journal of the Royal Statistical Society: Series C (Applied Statistics) | ||||||||||||
Publisher: | Wiley-Blackwell Publishing Ltd. | ||||||||||||
ISSN: | 0035-9254 | ||||||||||||
Official Date: | January 2021 | ||||||||||||
Dates: |
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Volume: | 70 | ||||||||||||
Number: | 1 | ||||||||||||
Page Range: | pp. 174-201 | ||||||||||||
DOI: | 10.1111/rssc.12454 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Reuse Statement (publisher, data, author rights): | "This is the peer reviewed version of the following article: Whitaker, G.A., Silva, R., Edwards, D. and Kosmidis, I. (2020), A Bayesian approach for determining player abilities in football. J R Stat Soc Series C, which has been published in final form at https://doi.org/10.1111/rssc.12454. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions." | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 2 December 2020 | ||||||||||||
Date of first compliant Open Access: | 25 November 2021 | ||||||||||||
RIOXX Funder/Project Grant: |
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Open Access Version: |
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