A Comparison of Different Modes of Morning Priming Exercise on Evening Jump, Lower Body Strength and On-Ice Sprint Performance in Sub-Elite Female Hockey Players
Bibliographic record
Abstract
The use of a low-intensity pre-game skate to positively influence physical and psychological readiness for evening competition is a common practice at the sub-elite to elite level in ice hockey.Despite its wide-spread use, there is little evidence to support its efficacy.A growing body of research indicates that resistance priming, defined as low volume, high intensity resistance exercise, can lead to increased neuromuscular potentiation and improved performance at time periods of 6-48 hours post stimulus.The objective of this study was to compare the effects of morning on-ice sprinting (skating), and power-based resistance priming, versus a control condition of no morning activity, on measures of off-ice and on-ice performance.This study used a repeated measure, counterbalanced design, with all the subjects completing both experimental (morning on-ice and resistance priming session) and control (no morning activity) trials.Post hoc statistical analysis of combined morning treatments (resistance priming and on-ice sprints) showed significant improvements in measures of lower body power and strength, however significant decreases in on-ice speed were observed when compared to no morning training.While these results demonstrate the efficacy of a morning training stimulus in impacting key performance variables in female hockey players, it is recommended that coaches and practitioners quantify the inter-individual variation of their athlete population when choosing how to apply morning training interventions with the hope of improving competition readiness and 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) | 0.001 | 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) | 0.002 | 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".