Seasonal Changes in Physiological Responses and Body Composition During a Competitive Season in Male and Female Elite Collegiate Ice Hockey Players
Bibliographic record
Abstract
Delisle-Houde, P, Reid, RER, Insogna, JA, Chiarlitti, NA, and Andersen, RE. Seasonal changes in physiological responses and body composition during a competitive season in male and female elite collegiate ice hockey players. J Strength Cond Res 33(8): 2162-2169, 2019-Ice hockey continually overloads athletes with limited time for recovery, which may affect several physiological responses and alter body composition. The purpose of this study was to identify changes in physiological parameters and body composition profiles over the competitive season in elite collegiate ice hockey players. Forty-four players, 24 males (age = 22.7 ± 1.3 years, height = 1.82 ± 0.6 m, and body mass = 86.87 ± 6.44 kg) and 20 females (age = 19.9 ± 1.8 years, height = 1.66 ± 0.7 m, and body mass = 68.76 ± 5.91 kg) participated in 4-minute submaximal exercise tests and body composition assessments at pre-season, mid-season, and end-season. Changes in physiological parameters and body composition were analyzed using repeated-measures analysis of covariance controlling for age. Males' postexercise blood lactate concentration decreased (p ≤ 0.05) from pre- to mid-season (9.3 vs. 6.2 mmol·L) and increased (p ≤ 0.05) from mid- to end-season (6.2 vs. 8.0 mmol·L). Heart rate increased (p ≤ 0.05) after the third and fourth minute of the submaximal test in both sexes from pre- to end-season and from mid- to end-season. Males' body fat percentage decreased (p ≤ 0.05) from mid-season (17.4 vs. 16.1%), whereas increases were observed (p ≤ 0.05) in both sexes from mid- to end-season. This study produced evidence that male and female collegiate hockey athletes' physiological responses and body composition profiles change over the season. Sport scientists working with collegiate hockey teams, may need to revise annual training programs to attenuate reductions in fitness and hopefully prevent injuries.
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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".