Correlation of static and dynamic trunk muscle endurance and bat swing velocity in high school aged baseball players
Bibliographic record
Abstract
BACKGROUND: Trunk muscle endurance training is used by most high school baseball or softball coaches. However, evidence demonstrating a relationship between trunk muscle endurance and batting performance is lacking. OBJECTIVE: This study aimed to establish a relationship between trunk muscle endurance and bat swing velocity in a high school baseball team. METHOD: Sixty-one high school (15–18 years old) baseball players, taken from the same team, with 6.5 ± 1.3 years of training experience, participated in the following tests: static trunk flexion/extension endurance tests, dynamic trunk flexion/extension endurance tests and a maximum bat swing velocity test. RESULTS: Bat swing velocity showed significant low-to-moderate negative correlations with static trunk flexor endurance (P=0.001, r=−0.404), dynamic trunk flexor endurance (P=0.016, r= −0.308) and the ratio of static flexor/extensor endurance (P=0.021, r=−0.298). CONCLUSIONS: These findings support the concept that better trunk flexor endurance might not benefit batting performance. Trunk flexor endurance training should not be over-emphasized when the targeted training goal is to enhance bat swing velocity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".