Seasonal Changes in Whole Body and Regional Body Composition Profiles of Elite Collegiate Ice-Hockey Players
Bibliographic record
Abstract
The monitoring of a collegiate hockey player's body composition can reflect fitness characteristics and may help players, coaches, or strength and conditioning specialists optimize physiologic gains during an off-season, whereas simultaneously preventing performance decrements in-season. The purpose of the study was to investigate changes in whole-body and regional-body composition of fat and lean tissue. The body composition profiles of 19 elite Canadian collegiate hockey players were assessed using dual energy X-ray absorptiometry. Players completed end-of-season, preseason, and midseason assessments with questionnaires relating to their off-season and in-season training. Statistically significant changes in body composition profiles were observed between the different time points because players showed various tissue gains and losses depending on the region assessed. Overall, players gained (1.38 kg, p ≤ 0.01) and lost (0.79 kg, p ≤ 0.01) fat tissue during the off-season and in-season, respectively. Players also showed a significant gain of leg lean tissue (0.29 kg, p = 0.02) and loss of arm tissue mass (-0.25 kg, p = 0.02) during the first-half of the competitive season. Several correlations emerged that may provide insight into potential trends that could be more pronounced during longer and more demanding schedules. Collegiate hockey players show changes in body composition during the off-season and in-season. The understanding of body composition profiles, body composition fluctuations, and potential variables that may influence the composition of collegiate hockey players can help coaches and athletic programs tailor their team's training, nutrition, lifestyle, and informative resources to further support their athletes.
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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 | 0.002 | 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 | 0.000 | 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) | 0.000 | 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".