Relationship between ice hockey-specific complex test and maximal strength, aerobic capacity and postural regulation in professional players
Bibliographic record
Abstract
BACKGROUND: We aimed to examine the validity of an ice hockey-specific complex test (IHCT) and nonspecific off-ice tests for sports performance. METHODS: Eighteen professional athletes (27.4±6.0 years) underwent the IHCT, maximal strength squat tests, an endurance cycling test (PWC 170) and posturography during in the first week of the pre-seasonal training. The IHCT included parameters of load (e.g., 10-m and 30-m sprint, transition and weave agility without and with puck, slap and wrist shots before and after the test). The players were closely accompanied during the season of competition (seven months) in order to collect match performance data. Based on these data, we calculated a match performance score (MPS) for each player. RESULTS: Stability indicator (r2=0.39), weave agility with puck (r2=0.39), maximal relative squat (r2=0.37) and frequency band F7-8 (r2=0.35) proved to be the most valid tests. However, with the MPS as dependent variable, 21 of 44 parameters tested (48%) explained 10% or more of variance. CONCLUSIONS: The current findings suggest that postural stability, cerebellar control mechanisms and concentric maximum leg strength are the most important predictors of MPS. Regarding IHCT, actions with the puck under fatigue conditions and the ability to recover quickly are highly relevant for ice hockey players.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".