Multi-Planar Jump Performance in Speed Skating Athletes: Investigating Interlimb Differences in an Asymmetrical Sport
Bibliographic record
Abstract
Elite speed skaters are exposed to asymmetric lower limb loading consequent to the unidirectional turns inherent to the sport. This presents a unique model to study the effects of sport-specific loading on interlimb differences in mechanical muscle function. This study, therefore, examined baseline interlimb asymmetries in multi-directional jump tests in elite speed skaters using a cross-sectional design. Thereafter, participants were monitored longitudinally using the bilateral countermovement jump (CMJ) to quantify interlimb differences in mechanical muscle function throughout a competitive season. Pre-season baseline testing included a single leg lateral jump (JumpLat) and a single leg forward horizontal jump (JumpHorz) attached to a robotic linear position encoder, along with a bilateral CMJ on a dual force plate system. From baseline, CMJ monitoring was conducted throughout the 24-week competitive season. Within-limb changes in right vs left CMJ concentric impulse (CMJCon) and eccentric deceleration impulse (CMJEcc) were assessed using a linear mixed effects model. No systematic interlimb differences were found at baseline (p = 0.33–0.98) and the between-test agreement in limb dominance was poor (Kappa = −0.17–0.33). Furthermore, there were no time effects observed for interlimb differences in CMJCon (fixed effect = 0.01 N*s) and a small decrease in CMJEcc (fixed effects = −0.35 N*s, p = 0.01). These data suggest that even in a sport with asymmetrical loading, interlimb differences in mechanical output remain stable at the group level. However, changes occurring at the individual athlete level may be occurring that are meaningful for performance and injury.
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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 | 0.001 | 0.002 |
| 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".