Generation of threat: crediting football players for creating dangerous actions in an unbiased way

Abstract We introduce an innovative methodology to identify football players at the origin of threatening actions in a team. In our framework, a threat is defined as entering the opposing team’s danger area . We investigate the timing of threat events and ball touches of players, and capture their correlation using Hawkes processes. Our model-based approach allows us to evaluate a player’s ability to create danger both directly and through interactions with teammates. We define a new index, called Generation of Threat (GoT), that measures in an unbiased way the contribution of a player to threat generation. For illustration, we present a detailed analysis of Chelsea’s 2016–2017 season, with a standout performance from Eden Hazard. We are able to credit each player for his involvement in danger creation and determine the main circuits leading to threat. In the same spirit, we investigate the danger generation process of Stade Rennais in the 2021–2022 season. Furthermore, we establish a comprehensive ranking of Ligue 1 players based on their generated threat in the 2021–2022 season. Our analysis reveals surprising results, with players such as Jason Berthomier, Moses Simon and Frederic Guilbert among the top performers in the GoT rankings.

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Publication Details

Journal
Journal of Quantitative Analysis in Sports
Published
2025-09-23
DOI
https://doi.org/10.1515/jqas-2024-0107
Primary Topic
Education, Psychology, and Social Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Generation of threat: crediting football players for creating dangerous actions in an unbiased way

Journal of Quantitative Analysis in Sports
Education, Psychology, and Social Research
article

Generation of threat: crediting football players for creating dangerous actions in an unbiased way

article en

Abstract

Abstract We introduce an innovative methodology to identify football players at the origin of threatening actions in a team. In our framework, a threat is defined as entering the opposing team’s danger area . We investigate the timing of threat events and ball touches of players, and capture their correlation using Hawkes processes. Our model-based approach allows us to evaluate a player’s ability to create danger both directly and through interactions with teammates. We define a new index, called Generation of Threat (GoT), that measures in an unbiased way the contribution of a player to threat generation. For illustration, we present a detailed analysis of Chelsea’s 2016–2017 season, with a standout performance from Eden Hazard. We are able to credit each player for his involvement in danger creation and determine the main circuits leading to threat. In the same spirit, we investigate the danger generation process of Stade Rennais in the 2021–2022 season. Furthermore, we establish a comprehensive ranking of Ligue 1 players based on their generated threat in the 2021–2022 season. Our analysis reveals surprising results, with players such as Jason Berthomier, Moses Simon and Frederic Guilbert among the top performers in the GoT rankings.

Journal of Quantitative Analysis in Sports
University of Parma (IT), Centre National de la Recherche Scientifique (FR), École Polytechnique (FR), Centre de Mathématiques Appliquées de l'École polytechnique (FR), Université d'Évry Val-d'Essonne (FR)
Openalex Percentile: Top 36%
Education, Psychology, and Social Research
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Generation of threat: crediting football players for creating dangerous actions in an unbiased way · Journal of Quantitative Analysis in Sports (2025) | TGRS Research Map | TGRS