Artikel
Hierarchical Bayes modelling of penalty conversion rates of Bundesliga players
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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: AStA Advances in Statistical Analysis ; ISSN: 1863-818X ; Volume: 107 ; Year: 2021 ; Issue: 1-2 ; Pages: 177-204 ; Berlin, Heidelberg: Springer
- Klassifikation
-
Mathematik
Bayesian Analysis: General
Forecasting Models; Simulation Methods
Sports Economics: General
- Thema
-
Hierarchical Bayes
Shrinkage
Football
Penalties
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hanck, Christoph
Arnold, Martin C.
- Ereignis
-
Veröffentlichung
- (wer)
-
Springer
- (wo)
-
Berlin, Heidelberg
- (wann)
-
2021
- DOI
-
doi:10.1007/s10182-021-00420-w
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Hanck, Christoph
- Arnold, Martin C.
- Springer
Entstanden
- 2021
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