Epidemiology of Injury in Elite and Amateur Soccer Referees: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.023 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".