No Effect of Muscle Stretching within a Full, Dynamic Warm-up on Athletic Performance
Bibliographic record
Abstract
PURPOSE: This study aimed to examine the effects of static and dynamic stretching routines performed as part of a comprehensive warm-up on flexibility and sprint running, jumping, and change of direction tests in team sport athletes. METHODS: A randomized, controlled, crossover study design with experimenter blinding was conducted. On separate days, 20 male team sport athletes completed a comprehensive warm-up routine. After a low-intensity warm-up, a 5-s static stretch (5S), a 30-s static stretch (30S; 3 × 10-s stretches), a 5-repetition (per muscle group) dynamic stretch (DYN), or a no-stretch (NS) protocol was completed; stretches were done on seven lower body and two upper body regions. This was followed by test-specific practice progressing to maximum intensity. A comprehensive test battery assessing intervention effect expectations as well as flexibility, vertical jump, sprint running, and change of direction outcomes was then completed in a random order. RESULTS: There were no effects of stretch condition on test performances. Before the study, 18/20 participants nominated DYN as the most likely to improve performance and 15/20 nominated NS as least likely. Immediately before testing, NS was rated less "effective" (4.0 ± 2.2 on a 10-point scale) than 5S, 30S, and DYN (5.3-6.4). Nonetheless, these ratings were not related to test performances. CONCLUSION: Participants felt they were more likely to perform well when stretching was performed as part of the warm-up, irrespective of stretch type. However, no effect of muscle stretching was observed on flexibility and physical function compared with no stretching. On the basis of the current evidence, the inclusion of short durations of either static or dynamic stretching is unlikely to affect sprint running, jumping, or change of direction performance when performed as part of a comprehensive physical preparation routine.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 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".