Relationships to Skating Performance in Competitive Hockey Players
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Bibliographic record
Abstract
The purpose of this study was to identify off-ice variables that would correlate to on-ice skating sprint performance and cornering ability. Previous literature has not reported any off-ice testing variables that strongly correlate to on-ice cornering ability in ice hockey players. Thirty-six male hockey players aged 15-22 years (mean +/- SD: 16.3 +/- 1.7 years; weight = 70.8 +/- 10.4 kg; height = 175.6 +/- 4.1 cm) with an average of 10.3 +/- 3.0 years hockey playing experience (most at AA and AAA levels) participated in the study. The on-ice tests included a 35-m sprint and the cornering S test. The off-ice tests included the following: 30-m sprint, vertical jump, broad jump, 3 hop jump, Edgren side shuffle, Hexagon agility, side support, push-ups, and 15-second modified Wingate. The on-ice sprint test and cornering S test were strongly correlated (r = 0.70; p < 0.001). While many off-ice tests correlated with on-ice skating, measures of horizontal leg power (off-ice sprint and 3 hop jump) were the best predictors of on-ice skating performance, once weight and playing level were accounted for. These 4 variables accounted for a total of 78% (p < 0.0001) of the variance in on-ice sprint performance. No off-ice test accounted for unique variance in S-cornering performance beyond weight, playing level, and skating sprint performance. These data indicate that coaches should include horizontal power tests of off-ice sprint and 3 hop jump to adequately assess skating ability. To improve on-ice skating performance and cornering ability, coaches should also focus on the development of horizontal power through specific off-ice training, although future research will determine whether off-ice improvements in horizontal power directly transfer to improvements in on-ice skating.
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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 | 0.004 | 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 | 0.000 |
| 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 it