Effect of optimal cycling repeated-sprint combined with classical training on peak leg power in female soccer players
Bibliographic record
Abstract
BACKGROUND: Muscle power is one of the most important factors influencing sport performance. Despite the variety of training methods used in the literature, more individualised, varied and enjoyable methods are needed to enhance muscle peak power in soccer. OBJECTIVE: To assess the effect of short-sprint cycle ergometer training on peak power output and field performance of female soccer players. METHODS: 7 female soccer players (age: 20.2 ± 1.5 (years); body mass: 55.1 ± 6.1 (kg); height: 1.61 ± 0.06 (m)) served as an experimental group, and seven female soccer players (age: 19.4 ± 1.5(years); body mass: 65.2 ± 6.1 kg; height: 1.69 ± 0.08 m) as a control group. Peak power output (� peak) during a cycle ergometer force-velocity test and field performance (5-jump test and speeds over 10, 20 and 30 m) were assessed both before and after training (3 months duration, with 3 sessions per week). Each training session comprised 2 series of 15 sprints, separated by a 15 min recovery interval. Individual sprints were of 5 sec duration, at the optimal pedalling velocity for the subject (100–110 rpm) and against the optimal frictional loading equal of the subject(7.5%–8.5% of body mass); a recovery period of 55 sec was allowed between sprints. RESULTS: The training regimen induced gains of peak power (p< 0.05), whether expressed in �, �/kg, or relative to leg muscle volume (�/l). There were also gains in 5-jump (p< 0.01), and 20 and 30 m sprint velocities (p< 0.01). Findings in the control participants remained unchanged. CONCLUSION: When combined with traditional soccer training, repeated short sprints on a cycle ergometer offer an effective strategy for enhancing leg power in female Tunisian soccer players.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".