A strategy to predict association football players’ passing skills

Jorge Tovar, Andrés Clavijo () and Julián Cárdenas ()

No 15821, Documentos CEDE from Universidad de los Andes, Facultad de Economía, CEDE

Abstract: Transfers are big business in association football. This paper develops a generalized additive mixed model that aids managers in predicting how a football player is expected to perform in a new team. It does so by using event-level data from the Spanish and the Colombian football leagues. Using passes as a performance proxy, the model exploits the richness of the data to account for the difficulty of each pass attempt performed by each player over an entire season. The model estimates are then used to determine how a player transferred from the Colombian league should perform in the Spanish league, taking into account that teammates and rivals’ abilities are different in the latter.

Keywords: Generalized additive mixed models; football; sports forecasting; passing. (search for similar items in EconPapers)
JEL-codes: C53 Z21 Z22 (search for similar items in EconPapers)
Pages: 23
Date: 2017-11-07
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Persistent link: https://EconPapers.repec.org/RePEc:col:000089:015821

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