Kinematics of Hitting in Youth Baseball: Implications for Skill Development
Bibliographic record
Abstract
This study compared lower extremity, trunk, and upper extremity kinematics between tee and front toss hitting in youth baseball athletes. Twenty youth baseball athletes (14.3±2.9 yrs) performed three maximal effort swings off front toss and tee. Kinematic data were collected during the preparatory and acceleration phases. Lower extremity, trunk, and upper extremity kinematics were compared between tee and front toss hitting using 1-dimensional statistical parametric mapping (SPM). There was a significant difference in trunk kinematics between tee and front toss during the preparatory phase (p=.001); the trunk rotated more toward the back side when hitting off a tee compared to front toss (p<0.001). There was also a significant difference in trunk kinematics between tee and front toss for 67% of the acceleration phase; the trunk rotated more towards the back side from 0 to 67% when hitting off the tee (p<0.001). Significant differences were found in trunk kinematics between tee and front toss hitting in youth baseball players, where the trunk is less rotated toward the pitcher in the tee than in the front toss. Coaches utilize various training modalities to enhance hitting performance; however, differences in trunk kinematics should be considered between modalities when developing fundamental hitting techiques in youth baseball athletes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".