Expected goals in football: Improving model performance and demonstrating value.

ABSTRACT: Recently, football has seen the creation of various novel, ubiquitous metrics used throughout clubs' analytics departments. These can influence many of their day-to-day operations ranging from financial decisions on player transfers, to evaluation of team performance. At the forefront of this scientific movement is the metric expected goals, a measure which allows analysts to quantify how likely a given shot is to result in a goal however, xG models have not until this point considered using important features, e.g., player/team ability and psychological effects, and is not widely trusted by everyone in the wider football community. This study aims to solve both these issues through the implementation of machine learning techniques by, modelling expected goals values using previously untes

SUBMITTER: Mead J 

PROVIDER: S-EPMC10075453 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature