Mechanical Characteristics and Skating Performance of Trained Youth Ice Hockey Players at Different Maturation Stages
Bibliographic record
Abstract
Objectives: This study aimed to investigate the skating force–velocity (F–V) mechanical characteristics of trained youth ice hockey players at different stages of their maturational development. Methods: A total of 52 male trained ice hockey players (14.6 ± 1.4 years) from U13, U15, U17, and U18 competitive teams of the same hockey program were classified into three maturation groups—Pre-, Mid-, and Post-peak height velocity (PHV). Participants performed two 40 m maximal skating efforts while velocity data were collected using a radar device to derive F–V parameters (e.g., theoretical maximal force (F0), velocity (V0), power (Pmax), and related metrics). The maturation offset was computed using the following formula: Maturity offset = −8.128741 + (0.0070346 · (Chronological age · Sitting height)). Results: Results revealed significant effects of puberty on most performance variables (F(2,49) = [5.58, 31.72]; p ≤ 0.07; η2 = [0.19, 0.56]). Differences in acceleration (0–10 m time) and F0 improved markedly between Mid- and Post-PHV stages (|d| = [1.38, 1.92]), while V0 and maximal sprint velocity (30–40 m time) improved constantly across maturation stages (|d| = [1.03, 1.99]). Conclusions: This is the first study to provide reference skating F–V profile values across puberty in trained youth male ice hockey players. Coaches and practitioners are encouraged to prioritize acceleration and skating technique early during puberty to maximize velocity development and emphasize strength development after reaching peak height velocity. Conclusions should be considered with care as the Pre-PHV group was small (n = 5) and the used F–V method remains to be validated on ice.
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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 | 0.000 | 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 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".