Relationship Between Physiologic Tests, Body Composition Changes, and On-Ice Playing Time in Canadian Collegiate Hockey Players
Bibliographic record
Abstract
Delisle-Houde, P, Chiarlitti, NA, Reid, RER, and Andersen, RE. Relationship between physiologic tests, body composition changes, and on-ice playing time in canadian collegiate hockey players. J Strength Cond Res 32(5): 1297-1302, 2018-Hockey player's body composition and physical fitness are suggested to influence coaching decisions regarding on-ice playing time. The purpose of this study was to explore the relationship between seasonal body composition changes, off-ice preseason testing, and on-ice metrics. Twenty-one Canadian collegiate hockey players (22.70 ± 1.30 years old, 181.0 ± 5.92 cm, 86.52 ± 6.41 kg) underwent off-ice physical testing at the beginning of their season and had one total body dual energy x-ray absorptiometry scan at the beginning and end of the season. The team's statistician tracked all on-ice metrics. Pearson correlations were used to explore relationships between off-ice tests (long jump, vertical jump, beep test, and Wingate test), change in body composition (body fat percentage, visceral adiposity, and total lean tissue mass), and on-ice performance (average time on ice, average shift length, power play time, penalty kill time, and shot differential). Long jump was correlated with shot differential (r = -0.532, p ≤ 0.05) and average shift length (r = -0.491, p ≤ 0.05) while fatigue index was correlated with average ice time (r = -0.476, p ≤ 0.05). Hockey performance is a complex interaction of player's body compositions and skeletal fitness that interact to affect on-ice playing metrics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".