Effects of In-Season Low-Volume High-Intensity Plyometric Training on Explosive Actions and Endurance of Young Soccer Players
Bibliographic record
Abstract
Integrating specific training methods to improve explosive actions and endurance in youth soccer is an essential part of players' development. This study investigated the efficiency of short-term vertical plyometric training program within soccer practice to improve both explosive actions and endurance in young soccer players. Seventy-six players were recruited and assigned either to a training group (TG; n = 38; 13.2 ± 1.8 years) or a control group (CG; n = 38; 13.2 ± 1.8 years) group. All players trained twice per week, but the TG followed a 7-week plyometric program implemented within soccer practice, whereas the CG followed regular practice. Twenty-meter sprint time (20-m), Illinois agility test time, countermovement jump (CMJ) height, 20- (RSI20) and 40- (RSI40) cm drop jump reactive strength index, multiple 5 bounds distance (MB5), maximal kicking test for distance (MKD), and 2.4-km time trial were measured before and after the 7-week period. Plyometric training induced significant (p ≤ 0.05) and small to moderate standardized effect (SE) improvement in the CMJ (4.3%; SE = 0.20), RSI20 (22%; SE = 0.57), RSI40 (16%; SE = 0.37), MB5 (4.1%; SE = 0.28), Illinois agility test time (-3.5%, SE = -0.26), MKD (14%; SE = 0.53), 2.4-km time trial (-1.9%; SE = -0.27) performances but had a trivial and nonsignificant effect on 20-m sprint time (-0.4%; SE = -0.03). No significant improvements were found in the CG. An integrated vertical plyometric program within the regular soccer practice can substitute soccer drills to improve most explosive actions and endurance, but horizontal exercises should also be included to enhance sprinting performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".