Effect of cluster set warm-up configurations on sprint performance in collegiate male soccer players
Bibliographic record
Abstract
The purpose of this study was to determine if back squat cluster sets (CS) with varying inter-repetition rest periods would potentiate greater sprint performance compared with a traditional set parallel back squat in collegiate soccer players. Twelve collegiate male soccer players (age, 21.0 ± 2.0 years; height, 180.0 ± 9.0 cm; body mass, 79.0 ± 9.5 kg) performed a 20-m sprint prior to a potentiation complex and at 1, 4, 7, and 10 min postexercise on 3 separate, randomized occasions. On each occasion, the potentiation complex consisted of 1 set of 3 repetitions at 85% 1-repetition maximum (1RM) for the traditional parallel back squat. However, on 1 occasion the 3-repetition set was performed in a traditional manner (i.e., continuously), whereas on the other 2 occasions, 30s (CS 30 ) and 60 s (CS 60 ) of rest were allotted between each repetition. Repeated-measures ANOVA revealed greater (p = 0.022) mean barbell velocity on CS 60 compared with the traditional set. However, faster (p < 0.040) 20-m sprint times were observed for CS 30 (3.15 ± 0.16 s) compared with traditional (3.20 ± 0.17 s) only at 10 min postexercise. No other differences were observed. These data suggest that a single cluster set of 3 repetitions with 30-s inter-repetition rest periods at 85% 1RM acutely improves 20-m sprinting performance. Strength and conditioning professionals and their athletes might consider its inclusion during the specific warm-up to acutely improve athletic performance during the onset (≤10 min) of training or competition.
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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 | 0.000 | 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) | 0.000 | 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".