Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286781 
Year of Publication: 
2021
Citation: 
[Journal:] AStA Advances in Statistical Analysis [ISSN:] 1863-818X [Volume:] 107 [Issue:] 1-2 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 177-204
Publisher: 
Springer, Berlin, Heidelberg
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.
Subjects: 
Hierarchical Bayes
Shrinkage
Football
Penalties
JEL: 
C11
C53
Z20
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.