Does the format matter? A cross-sectional analysis of suspected injuries and game events across the different versions of field hockey
Bibliographic record
Abstract
Introduction: Field Hockey is a popular global sport played by both men and women in three different formats: 11-a-side outdoor hockey (11s), 6-a-side indoor hockey, and 5-a-side Hockey5s. To date, comparisons across formats for match events and injury rates have not occurred. Methods: Using an established video analysis methodology, this study aimed to compare match events (per 10 min of play) and suspected injury rates across formats and genders. A hockey-specific video coding window was co-created with community partners, before being deployed to capture outcomes of interest in 30 international hockey matches (10 per format, 50% male/female). Results: Twenty-seven suspected injuries were identified. The most common trends in these injuries included; being to the head/neck (26%); contusion in nature (74%); ball-player contact mechanism (44%); 74% to defending player. No evidence of significant differences in injury rates between formats or genders were identified, however a trend towards higher rates in men's vs. women's was identified [Rate ratio (RR) range: 1.14-5.00] as well as in Hockey5s for men and 11s for women. Game events differed significantly across formats for both men and women. Increased outcomes which could be deemed "exciting" (e.g., shots, shooting zone entries) differed between formats, however the success (e.g., shots on target vs. off target) of these increased "exciting" outcomes was often lower in formats with higher rates. Discussion: The findings of this study suggest the need for a more in-depth investigation into differences between formats, which may include mixed methods approaches to capture fan engagement, player perception, and injury risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".