Expected Pass Turnovers (xPT) - a model to analyse turnovers from passing events in football.

Expected pass turnovers football metric logistic regression

Journal

Journal of sports sciences
ISSN: 1466-447X
Titre abrégé: J Sports Sci
Pays: England
ID NLM: 8405364

Informations de publication

Date de publication:
22 Jul 2024
Historique:
medline: 22 7 2024
pubmed: 22 7 2024
entrez: 22 7 2024
Statut: aheadofprint

Résumé

The aim of this study was to create a novel metric, Expected Pass Turnovers (xPT), that could evaluate possession retention from player-passing events in football. Event and positional data were analysed from all 380 matches in the 2020/21 English Premier League season, which encompassed 256,433 passes in the final dataset. A logistic mixed-effects model was implemented to attribute the probability of each pass getting turned over. The use of positional data enabled the identification of a) opposition players present in radii surrounding the ball carrier and b) availability of teammates with respect to the ball carrier. The addition of these positional features improved the accuracy (+6.1 AUC Score) of the model. xPT serves as a practitioner Key Performance Indicator, as analysts can identify players that lose possession more often or not than expected, given the situational context of each pass, from game to game. Future work may include modelling the turnover probability of dribble and carry actions, as this would lead to a more comprehensive understanding of turnover events in football.

Identifiants

pubmed: 39036961
doi: 10.1080/02640414.2024.2379697
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-9

Auteurs

Andrew J Peters (AJ)

Faculty of Science & Technology, Middlesex University, London, UK.
Data Analytics Department, Leicester City Football Club, Leicester, UK.

Nimai Parmar (N)

Faculty of Science & Technology, Middlesex University, London, UK.

Michael Davies (M)

Faculty of Science & Technology, Middlesex University, London, UK.
Data Analytics Department, Leicester City Football Club, Leicester, UK.

Matt Reeves (M)

Sports Science & Medical Department, Leicester City Football Club, Leicester, UK.

Mladen Sormaz (M)

Data Analytics Department, Leicester City Football Club, Leicester, UK.

Nic James (N)

Faculty of Science & Technology, Middlesex University, London, UK.

Classifications MeSH