Relationships of Peak Leg Power, 1 Maximal Repetition Half Back Squat, and Leg Muscle Volume to 5-m Sprint Performance of Junior Soccer Players
Bibliographic record
Abstract
Performance over very short distances (1-5 m) is important in soccer. We investigated this in 23 male regional-level soccer players aged 17.2 +/- 0.7 years, filming body markers to determine the average velocity and acceleration over the first step (V(S) and A(S)) and the first 5 m (V(5), A(5)). Data were related to scores on a force-velocity test, squat jump (SJ), countermovement jump (CMJ), and 1 maximal repetition (1 RM) half back squat. Leg and thigh muscle volumes were also assessed anthropometrically. V(5) was positively correlated with leg and thigh muscle volumes (r = 0.61, p < 0.05; r = 0.43, p < 0.05, respectively), SJ power (absolute and relative to body mass, r = 0.45, p < 0.05; r = 0.43, p < 0.05, respectively), absolute force-velocity leg power (r = 0.49, p < 0.05), and 1 RM half back squat (r = 0.66, p < 0.001). The use of dimensional exponents did not change coefficients materially. V(S) was also correlated with leg muscle volume and 1 RM back half squat (r = 0.56, p < 0.01; r = 0.58, p < 0.01, respectively) and more weakly with force-velocity leg power and SJ force (r = 0.49, p < 0.05; r = 0.46, p < 0.5, respectively). However, the CMJ was unrelated to velocity or acceleration. Sprinting ability is correlated with measures of power and force such as the force-velocity test, SJ, and 1 RM half back squat; such measures thus offer useful guidance to soccer coaches who wish to improve the short-distance velocity of their players.
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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 | 0.000 | 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 | 0.000 |
| 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".