An Assessment of the Hopping Strategy and Inter-Limb Asymmetry during the Triple Hop Test: A Test–Retest Pilot Study
Bibliographic record
Abstract
The aims of the present study are to: (1) determine within- and between-session reliability of multiple metrics obtained during the triple hop test; and (2) determine any systematic bias in both the test and inter-limb asymmetry scores for these metrics. Thirteen male young American football athletes performed three trials of a triple hop test on each leg on two separate occasions. In addition to the total distance hopped, manual detection of touch down and toe-off were calculated via video analysis, enabling flight time (for each hop), ground contact time (GCT), reactive strength index (RSI), and leg stiffness (between hops) to be calculated. Results showed all coefficient of variation (CV) values were ≤ 10.67% and intraclass correlation coefficients (ICC) ranged from moderate to excellent (0.53–0.95) in both test sessions. Intrarater reliability showed excellent reliability for all metrics (CV ≤ 3.60%, ICC ≥ 0.97). No systematic bias was evident between test sessions for raw test scores (g = −0.34 to 0.32) or the magnitude of asymmetry (g = −0.19 to 0.43). However, ‘real’ changes in asymmetry (i.e., greater than the CV in session 1) were evident on an individual level for all metrics. For the direction of asymmetry, kappa coefficients revealed poor-to-fair levels of agreement between test sessions for all metrics (K = −0.10 to 0.39), with the exception of the first hop (K = 0.69). These data show that, given the inherent limitations of distance jumped in the triple hop test, practitioners can confidently gather a range of reliable data when computed manually, provided sufficient test familiarization is conducted. In addition, although the magnitude of asymmetry appears to show only small changes between test sessions, limb dominance does appear to fluctuate between test sessions, highlighting the value of also monitoring the direction of the imbalance.
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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 | 0.000 | 0.001 |
| 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".