The Association of Countermovement Jump, Isometric Mid-Thigh Pull, and On-Ice Sprint Performance in University Level Female and Male Ice Hockey Athletes
Bibliographic record
Abstract
On-ice skating sprint performance is a significant predictor and requirement for playing at the highest levels of hockey. The purpose of this study was to determine the relationship between maximum and dynamic strength measures and on-ice sprint performance in university level ice hockey athletes. Both male (n=18) and female (n=13) hockey players participated in this study. The off-ice measures included two assessment procedures utilizing a force plate; an isometric mid-thigh pull (IMTP) to assess maximum strength and a countermovement jump (CMJ) to assess dynamic strength. Both off-ice measures were analyzed from both a relative (CMJr and IMTPr) and absolute (CMJa and IMTPa) perspective. The on-ice measures were 7.71m and 15.42m sprint times. Pearson product moment correlations were used to quantify the relationships between variables. CMJa (r = -0.56 to -0.61), IMTPa (r = -0.65 to -0.67) and IMTPr (r = -0.55) were significantly correlated (p < 0.05) with on-ice sprint performance. When analyzed by sex, no significant relationships (p > 0.05) were observed between CMJ measures and on-ice sprint times. No significant relationships (p > 0.05) were observed between IMTP measures and on-ice sprint times when individually analyzing male participants, while significant relationships (p < 0.05) were observed in females between IMTPa (r = -0.70 to -0.71) and IMTPr (r = -0.68 to -0.71) and on-ice sprint times. It is concluded that both maximum and dynamic strength are important factors in on-ice sprint performance in hockey players. Furthermore, maximum strength seems to be an important characteristic in on-ice sprint ability in females.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".