Examining the influence of physical size among major league pitchers
Bibliographic record
Abstract
BACKGROUND: Among professional pitchers, anthropometric changes and their effect on statistics are relatively unknown. Bivariate analyses and repeated one-way ANOVA evaluated the impact of physical size on baseball pitching statistics and attributes within an elite talent sample of Major League pitching leaders. METHODS: Body Mass Index (BMI) was calculated from publicly available players' heights and weights to form a statistical database of 1028 pitching leaders from 1950-2010. Repeated measures ANOVAs examined differences in anthropometrics and baseball statistics between decades 1950-2010. Bivariate correlation evaluated BMI as an independent variable of influence on statistics, where all tests applied an a-priori significance level (P<0.05). RESULTS: BMI increased throughout the sixty year period with weight growth greater than height (P<0.001). Increased BMI reported earlier signing age, and age of debut (P<0.05), where larger pitchers showed small positive correlation seen among saves (P<0.001) concurrent to negative correlation with innings pitched and complete games (P≤0.001), as well as shutouts (P<0.05). A contrast between saves and complete games pitched was found where saves increased over time (P<0.001) while complete games pitched declined (P<0.001). CONCLUSIONS: Over time, throwing workloads showed better management for larger starting pitchers with less innings pitched and complete games thrown added to an extra rest day in the pitching rotation. In contrast, paralleled increases in physical size with recorded saves at present requires greater medical and training attention to protecting the throwing arm of the larger relief pitchers, as increased body size can increase force properties and ball velocity owing to greater injury risks.
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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) | 0.001 | 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".