Longitudinal Physiological and Fitness Evaluations in Elite Ice Hockey: A Systematic Review
Bibliographic record
Abstract
ABSTRACT: Chiarlitti, NA, Crozier, M, Insogna, JA, Reid, RER, and Delisle-Houde, P. Longitudinal physiological and fitness evaluations in elite ice hockey: A systematic review. J Strength Cond Res 35(10): 2963-2979, 2021-Ice hockey has greatly evolved since the last review article was published more than 25 years ago. Although players still combine anaerobic and aerobic conditioning, the pace of the game has greatly increased. Players are faster, stronger, and more agile than their predecessors; however, an important emphasis is now placed on maximizing player performance for the play-offs. For the coaching staff, strength and conditioning coaches, and players, an emphasis on mitigating fitness and physiologic losses throughout the season would be beneficial, given the intimate relationship they share with on-ice performance. This systematic review of the literature outlines the current knowledge concerning longitudinal changes in relation to fitness, body composition, and physiologic parameters across an elite hockey season. The search of 4 large scientific databases (i.e., Embase, PubMed, SPORTDiscus, and Web of Science) yielded 4,049 items, which, after removing duplicates and applying inclusion and exclusion criteria, resulted in 23 published scientific articles to be included in this review. The wide span of literature (1956-2020) made inferences difficult giving the degree to which the game of ice hockey has changed; however, more recent research points to an aerobic deconditioning pattern and increased fatigue throughout the season in a specific group of elite hockey players (i.e., university athletes) while showing that ice hockey can lead to many possible histological adaptations. Ultimately, tracking, identifying, and developing methods to mitigate potential negative longitudinal changes will be imperative to influencing individual and team performance in the later parts of the season.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".