Changes in collegiate ice hockey player anthropometrics and aerobic fitness over 3 decades
Bibliographic record
Abstract
Over the past several decades, an increased emphasis on fitness training has emerged among collegiate ice hockey teams, with the objective of improving on-ice performance. However, it is unknown if this increase in training has translated over time into changes in the anthropometric and fitness profiles of collegiate ice hockey players. The purposes of this study were to describe anthropometric (height, weight, body mass index (BMI), percent body fat (%fat)) and aerobic fitness (peak oxygen consumption) characteristics of collegiate ice hockey players over a period of 36 years and to evaluate whether these characteristics differ among player positions. Anthropometric and physiologic data were obtained through preseason fitness testing of players (N = 279) from a National Collegiate Athletic Association Division I men’s ice hockey team from the years 1980 through 2015. Changes over time in the anthropometric and physiologic variables were evaluated via regression analysis using linear and polynomial models, and differences among player positions were compared via ANOVA (p < 0.05). Regression analysis revealed that a cubic model best predicted changes in mean height (R2 = 0.65), weight (R2 = 0.77), and BMI (R2 = 0.57), whereas a quadratic model best fit change in %fat by year (R2 = 0.30). Little change was observed over time in the anthropometric characteristics. Defensemen were significantly taller than forwards (184.7 ± 12.1 vs. 181.3 ± 5.9 cm) (p = 0.007), and forwards had a higher relative peak oxygen consumption compared with defensemen (58.7 ± 4.7 vs. 57.2 ± 4.4 mL·kg−1·min−1) (p = 0.032). No significant differences were observed in %fat or weight by position. Although average player heights and weights fluctuated over time, increased emphasis on fitness training did not affect the athletes’ relative aerobic fitness. Differences in height and aerobic fitness levels were observed among player positions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".