Epidemiology of Injury in Elite and Amateur Soccer Referees: A Systematic Review and Meta-analysis
Notice bibliographique
Résumé
Abstract Background The epidemiology of injury in soccer has traditionally focused on soccer players, rather than match officials. Although injury data on referees exist, no comprehensive review has summarized injury profiles in this population. Objective To conduct a systematic review and meta-analysis of injury epidemiology in elite and amateur soccer referees, focusing on injury rates, types, locations, severity, and causes. Methods PubMed (Medline), Web of Science, Scopus, CINAHL, and SPORTDiscus, covering their entire history up to 19 April 2025 were searched. This review included prospective and retrospective studies reporting injury incidence or prevalence among football match officials, with a study period of at least one season. Studies needed to specify injury definitions and include data on injury location, type, mechanism, or severity. Both male and female officials were eligible. Systematic reviews, commentaries, and letters were excluded. Study quality and risk of bias were evaluated using the STROBE-SIIS, in addition to the Newcastle–Ottawa Scale and funnel plots. Injury incidence rates were estimated using a random effects Poisson regression, accounting for heterogeneity and moderators. Heterogeneity was assessed with the I 2 statistic. Results A total of 17 studies were included, encompassing 3621 referees. The most frequent injuries were strains and sprains in the knee and ankle. The overall injury incidence was 2.19 injuries per 1000 h of exposure (95% CI 1.30–3.69). On-field referees experienced an incidence rate of 1.46 injuries per 1000 h of exposure (95% CI 0.76–2.81), while assistant referees had a lower rate of 0.84 per 1 h of exposure (95% CI 0.36–1.97). During matches, the injury incidence was 2.24 per 1000 h of exposure (95% CI 1.38–3.64), compared with 0.67 injuries per 1000 h of exposure during training sessions (95% CI 0.36–1.24). However, despite sensitivity analysis, there were still high levels of heterogeneity across included studies. Conclusions Findings noted higher injury incidence during matches compared with training, and on-field referees compared with assistants. The variation in injury profiles highlights the importance of implementing targeted preventive strategies tailored to the unique demands of refereeing. However, there is still a lack of research in this population, especially in female referees. PROSPERO Registration Number CRD42024497970.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,023 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».