Internal Physiological Load Measured Using Training Impulse in Varsity Men's and Women's Ice Hockey Players Between Game Periods
Bibliographic record
Abstract
ABSTRACT: Bigg, JL, Gamble, ASD, and Spriet, LL. Internal physiological load measured using training impulse in varsity men's and women's ice hockey players between game periods. J Strength Cond Res 35(10): 2824-2832, 2021-This study quantified internal load in male and female ice hockey players throughout a season, with comparisons between game periods and match outcome. Twenty-seven male and 24 female varsity ice hockey players participated in this longitudinal prospective cohort study monitoring internal load, using Banister's training impulse (TRIMP). Data were assessed according to game periods, match outcome (win or loss), and games played in noncongested (1 game/wk) or congested (2 + games/wk) weeks. Statistical significance was considered at p < 0.05. The TRIMP for period 1 for both male (25 ± 16 arbitrary units [AU]) and female (23 ± 19 AU) players was significantly lower than period 3 (males: 30 ± 21 AU; p = 0.001; females: 29 ± 21 AU; p = 0.003) but not period 2 (males: 27 ± 17 AU; p = 0.183; females: 27 ± 19 AU; p = 0.681). There were no differences in TRIMP within any period between games resulting in a win compared with a loss. Overall, there were no differences in TRIMP between male and female players. However, when stratified by position, male forwards experienced greater TRIMP than female forwards (p < 0.001 for all periods), whereas female defense had greater TRIMP than male defense (p ≤ 0.032 for all periods). There were no differences between noncongested and congested week games and no differences in TRIMP between nonback-to-back and back-to-back games, or the first and second games played of a back-to-back series. This study measured physiological demand throughout the periods of ice hockey games in men and women and concluded that internal load was highest in the third period. Understanding the demands throughout a game can provide information to coaches and players that would be useful in managing fatigue and optimizing physical performance.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".