Isometric and dynamic strength and neuromuscular attributes as predictors of vertical jump performance in 11- to 13-year-old male athletes
Bibliographic record
Abstract
In explosive contractions, neural activation is a major factor in determining the rate of torque development, while the latter is an important determinant of jump performance. However, the contribution of neuromuscular activation and rate of torque development to jump performance in children and youth is unclear. The purpose of this study was to examine the relationships between the rate of neuromuscular activation, peak torque, rate of torque development, and jump performance in young male athletes. Forty-one 12.5 ± 0.5-year-old male soccer players completed explosive, unilateral isometric and dynamic (240°/s) knee extensions (Biodex System III), as well as countermovement-, squat-, and drop-jumps. Peak torque (pT), peak rate of torque development (pRTD), and rate of vastus lateralis activation (Q30) during the isometric and dynamic contractions were examined in relation to attained jump heights. Isometric pT and pRTD were strongly correlated (r = 0.71) but not related to jump performance. Dynamic pT and pRTD, normalized to body mass, were significantly related to jump height in all 3 jumps (r = 0.38–0.66, p < 0.05). Dynamic normalized, but not absolute pRTD, was significantly related to Q30 (r = 0.35, p < 0.05). In young soccer players, neuromuscular activation and rate of torque development in dynamic contractions are related to jump performance, while isometric contractions are not. These findings have implications in the choice of training and assessment methods for young athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".