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A mixed effects model for identifying goal scoring ability of footballers
Author(s) -
McHale Ian G.,
Szczepański Łukasz
Publication year - 2014
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12015
Subject(s) - statistic , computer science , constant (computer programming) , process (computing) , statistics , artificial intelligence , football , machine learning , mathematics , econometrics , political science , law , programming language , operating system
Summary The paper presents a model that can be used to identify the goal scoring ability of footballers. By decomposing the scoring process into the generation of shots and the conversion of shots to goals, abilities can be estimated from two mixed effects models. We compare several versions of our model as a tool for predicting the number of goals that a player will score in the following season with that of a naive method whereby a player's goals‐per‐minute ratio is assumed to be constant from one season to the next. We find that our model outperforms the naive model and that this outperformance can be attributed, in some part, to the model's disaggregating a player's ability and chance that may have influenced his goal scoring statistic in the previous season.