Positional Value in Soccer: Expected League Points Added above Replacement
Year: 2018
Type: preprint
Abstract: Soccer is undeniably the most popular sport world-wide, but at the same time it is one of the least quantified. To date there is not a way to explicitly quantify the contribution of every player on the field to his team chances of winning. Successful sports metrics, such as the (adjusted) +/- that allows for division of credit among a basketball team's players, fail to work in soccer due to severe co-linearities (i.e., the same players being on the field for the majority of the time). In this work, we develop a framework that can estimate the expected contribution of a soccer player to his team's winning chances. In particular, using data from (i) approximately 20,000 games from 11 European leagues over a period of 8 seasons, as well as, (ii) player ratings from FIFA, we estimate through a Skellam regression model the importance of every line in winning a soccer game. We consequently translate the model to expected league points added (per game) above a replacement player eLPAR. This model can be used as a guide for player transfer decisions, as well as, for transfer fees and contract negotiations among other applications. To showcase the applicability of eLPAR we use market value data for approximately 10,000 players and we identify evidence that currently the market under-values defensive line players relative to goalkeepers. Finally, we show how eLPAR can be used to facilitate transfer fee estimations.
Source: arXiv (Cornell University)
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2887215547