Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players

Christoph Hanck () and Martin C. Arnold ()
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Christoph Hanck: University of Duisburg-Essen
Martin C. Arnold: University of Duisburg-Essen

AStA Advances in Statistical Analysis, 2023, vol. 107, issue 1, No 9, 177-204

Abstract: Abstract Judging by its significant potential to affect the outcome of a game in one single action, the penalty kick is arguably the most important set piece in football. Scientific studies on how the ability to convert a penalty kick is distributed among professional football players are scarce. In this paper, we consider how to rank penalty takers in the German Bundesliga based on historical data from 1963 to 2021. We use Bayesian models that improve inference on ability measures of individual players by imposing structural assumptions on an associated high-dimensional parameter space. These methods prove useful for our application, coping with the inherent difficulty that many players only take few penalties, making purely frequentist inference rather unreliable.

Keywords: Hierarchical Bayes; Shrinkage; Football; Penalties (search for similar items in EconPapers)
JEL-codes: C11 C53 Z20 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10182-021-00420-w

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