Effects of Short-Term In-Season Weightlifting Training on the Muscle Strength, Peak Power, Sprint Performance, and Ball-Throwing Velocity of Male Handball Players
Bibliographic record
Abstract
Hermassi, S, Schwesig, R, Aloui, G, Shephard, RJ, and Chelly, MS. Effects of short-term in-season weightlifting training on the muscle strength, peak power, sprint performance, and ball-throwing velocity of male handball players. J Strength Cond Res 33(12): 3309-3321, 2019-This study analyzed the effects of in-season weightlifting training, conducted biweekly for 12 weeks. Twenty-two male handball players were divided into experimental (age: 20.3 ± 0.5 years, height: 1.85 ± 0.04 m, and body mass: 86.3 ± 9.4 kg) and control (age: 20.1 ± 0.5 years, height: 1.81 ± 0.05 m, and body mass: 83.9 ± 10.3 kg) groups, and performance was assessed before and after the intervention. Peak power was determined by a cycle ergometer force-velocity test, a vertical squat jump, and a countermovement jump. Measures of 1 repetition maximal strength included bench press, back half-squats, snatch, and clean and jerk. Handball-throwing velocity was assessed by standing, running, and jump throws. The change of direction T-half test and sprint times over 5, 15, and 30 m were recorded by paired photocells. The intraclass correlation coefficient of all parameters exceeded 0.75. Significant training effects were seen for all sprint (3/3) and throwing (3/3) measures, but only 7/14 strength parameters and 3/10 jump parameters. The largest increases of performance were for snatch (η = 0.627; d = 2.85) and 15-m sprinting (η = 0.852; d = 2.73). Countermovement jump force showed a negative response (d = -0.62). Three other parameters (V0 power for the upper and lower limbs, countermovement jump power) showed only small effect sizes (d = 0.45, d = 0.31, and d = 0.23, respectively). We conclude that 12 weeks of biweekly in-season weight training improved the peak power, maximal strength, sprinting, and throwing in handball players, but that their jump performance did not increase with this kind of intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".