Effects of Elastic Band Based Plyometric Exercise on Explosive Muscular Performance and Change of Direction Abilities of Male Team Handball Players
Bibliographic record
Abstract
This study examined the effects of incorporating 8 weeks of bi-weekly lower limb elastic band based loaded plyometric training into the in-season regimen of junior handball players. Participants were assigned between control ( n = 15, age: 18.1 ± 0.5 years, body mass: 73.7 ± 13.9 kg, height: 1.82 ± 0.06 m, body fat: 14.4 ± 6.0%) and experimental groups ( n = 14, age: 17.7 ± 0.3 years, body mass: 76.8 ± 10.7 kg, height: 1.83 ± 0.04 m, body fat: 13.4 ± 3.8%). Measures obtained before and after the intervention included a cycle ergometer force-velocity test, squat and countermovement jump characteristics, sprints times, repeated change of direction and change of direction tests (COD), a 1-RM half-back squat, and anthropometric estimates of limb volumes. Gains in the experimental group relative to controls included absolute muscle power (W) (Δ 23.1%; p < 0.05; ES = 0.565), relative muscle power (W.kg –1 ) (Δ 22.1%; p < 0.05; ES = 0.573), sprint times over 5 and 30 m (Δ−8.7%; p < 0.01; ES = 0.921 and Δ−7.2%; p < 0.05; ES = 0.573, respectively), COD times (Δ−9.2%; p < 0.05; ES = 0.561) and all repeated COD parameters except the fatigue index. However, a significant improvement by time interaction was observed in both groups on some anthropometric parameters (leg muscle volume and surface section thigh max), 1-RM half- back squat and vertical jump performance. We conclude that bi-weekly elastic band-loaded plyometric training improves the ability to sprint, COD and repeated COD relative to regular training, and thus it can be recommended to young male team handball players as a new method of plyometric training to improve important elements of their physical 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".