Effects of supplemental jump and sprint exercise training on sand on athletic performance of male U17 handball players
Bibliographic record
Abstract
This controlled study investigated the effects of 7 weeks pre-season supplemental jump and sprint exercise training on sand (JSETS) on athletic ability in male handball players. Males (n = 40; 16.3 ± 0.4 years) were randomly assigned to a jump and sprint training (JSTG; n = 24) or a control (CG; n = 18) group. The JSETS replaced a part of the regular handball training of players. The tests included jumps (squat, counter-movement, and 5 jump tests), sprint times (5 m, 10 m and 20 m), agility (modified T and modified Illinois tests), repeated sprint T-test, and balance (standing stork and Y balance tests). JSTG showed relative to CG significant decreases in sprint times over all distances (5 m (p = 0.002, d = 0.735 (medium); 10 m (p = 0.012, d = 0.577 (medium) and 20 m (p = 0.012, d = 0.573 (medium)), and gains in both measures of agility (p = 0.001, d = 0.859 (large) and p = 0.004, d = 0.670 (medium) for T-Half and Illinois-tests respectively), and in jumping squat (p < 0.001, d = 0.813 (large)) and countermovement jumping (p = 0.004, d = 0.663 (medium)), but not in the 5-jump test. Three of the four repeated sprint scores (best time (BT), meantime (MT) and total time (TT)) improved significantly (p = 0.012, d = 0.577 (medium); p = 0.042, d = 0.463 (small) and p = 0.043, d = 0.458 (small) respectively), but the decrement (DEC) remained unchanged. The Y balance test showed significant gains in 2 of 3 scores for the right leg and 1 of 3 scores for the left leg, and the stork balance (right leg) was enhanced. In conclusion, compared to regular handball training, supplemental jump and sprint exercise training on sand substantially improved sprinting, agility, jumping, repeated sprinting, and balance in male handball 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 | 0.000 |
| 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) | 0.001 | 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".