Countermovement Jump Performance and Team Membership of Youth Female and Male Ice Hockey Players
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Bibliographic record
Abstract
This study compared the CMJ performance of two teams of young male ice hockey players and two teams of female ice hockey players of different levels of competition and examined whether a specific CMJ variable could predict Prep or Varsity team membership and thus be used as part of the talent identification process for ice hockey. A retrospective analysis of six CMJ variables collected via force platforms was conducted. Independent samples t-tests were used to compare the means of the six CMJ variables between the male teams and female teams and a logistic regression analysis was performed to compare team membership to Prep or Varsity teams with the specific CMJ variables. Significant differences (p < 0.05) were found between Prep and Varsity male players in four CMJ variables, all in favor of the Varsity group: mRSI (p = 0.016, ES = -0.860), peak propulsive power (p = 0.022, ES = -0.811), time to take-off (p = 0.005, ES = 1.008), and braking rate of force development (p = 0.005, ES = -1.025). For the female players, only countermovement depth was significantly different (p = 0.030, ES = 0.841) between Prep and Varsity teams, in favor of the Varsity group. Following the logistic regression analysis, only countermovement depth (Wald's p-value = 0.011) could predict team membership to the Prep or Varsity group for the girls while no CMJ variables could significantly predict team membership to the Prep or Varsity teams for the boys. Results from this study suggest that other CMJ kinetic variables should be used when comparing CMJ performance between athletes rather than only using jump height. In addition, countermovement depth can be used by coaches of female ice hockey players to predict team membership.
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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 | 0.000 | 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 | 0.000 |
| 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 it