Associations Between Balance and Muscle Strength, Power Performance in Male Youth Athletes of Different Maturity Status
Why this work is in the frame
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Bibliographic record
Abstract
Balance, strength and power relationships may contain important information at various maturational stages to determine training priorities. PURPOSE: The objective was to examine maturity-specific relationships of static/dynamic balance with strength and power measures in young male athletes. METHODS: Soccer players (N = 130) aged 10-16 were assessed with the Stork and Y balance (YBT) tests. Strength/power measures included back extensor muscle strength, standing long jump (SLJ), countermovement jump (CMJ), and 3-hop jump tests. Associations between balance with strength/power variables were calculated according to peak-height-velocity (PHV). RESULTS: There were significant medium-large sized correlations between all balance measures with back extensor strength (r = .486-.791) and large associations with power (r = .511-.827). These correlation coefficients were significantly different between pre-PHV and circa PHV as well as pre-PHV and post-PHV with larger associations in the more mature groups. Irrespective of maturity-status, SLJ was the best strength/power predictor with the highest proportion of variance (12-47%) for balance (i.e., Stork eyes opened) and the YBT was the best balance predictor with the highest proportion of variance (43-78%) for all strength/power variables. CONCLUSION: The associations between balance and muscle strength/power measures in youth athletes that increase with maturity may imply transfer effects from balance to strength/power training and vice versa in youth athletes.
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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 | 0.001 |
| 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 it