Elite Adolescent Ice Hockey Players: Analyzing Associations between Anthropometry, Fitness, and On-Ice Performance
Bibliographic record
Abstract
In the field of ice hockey, body mass and height have always played a role in team selection. This study aims to analyze the associations between anthropometry and multiple dimensions of performance among elite adolescent ice hockey players. METHODS: = 107, 14.96 years) took part in the study, in Camp 1. Off-ice fitness and on-ice skating tests were performed. Camp 2 consists of on-ice tests and match performance with players selected by coaching staff at Camp 1. Camp 2 data came from official matches performance and a combination of skating tests and intrasquad matches. Hockey Quebec's selection process consists of going from an entire pool of athletes to a team of twenty-five players, through several camps spread over two years. Correlation analyses were conducted to verify associations between anthropometric measures and performances. RESULTS: In Camp 1, heavier-taller male athletes displayed better performances in most off-ice fitness tests, while heavier female athletes tended to display poorer performance. Camp 2 showed no significant correlations in on-ice tests and match performance. However, some tendencies were observed: heavier male players were less involved in blocked shots, and taller females were more agile. CONCLUSIONS: Despite off-ice advantages, the taller-heavier prototype does not translate directly to better performance on the ice among elite adolescent players. Coaches should analyze anthropometric characteristics with caution, and place more focus on match-specific abilities to identify talent.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".