Getting to First Base: Developmental Trajectories of Major League Baseball Players
Bibliographic record
Abstract
The pathways to elite-level athletic performance are complex and contain significant variability within and across sport type. The road to professional baseball illustrates the non-linearity of athlete development as players may be drafted from various high school, two-year, or four-year programs and then placed into extensive minor league systems. The purpose of this study was to identify the different pathways to Major League Baseball (MLB) and their influence on career success. Performance and developmental data of 2,291 American-born MLB players who debuted between 1990 and 2010 were collected using baseball-reference.com. Two performance indicators, career games played (GP) and wins above replacement (WAR; player’s total contributions in wins), were coupled with high school, post-secondary, and Minor League Baseball (MiLB) data. When distilled, analyses revealed 17 qualitatively different pathways to MLB. Additionally, 63% of the athletes started their career directly after attending a four-year higher education institution (23% high school, 14% junior college) and 79% did not sign or were not selected as high school draft picks. Position players drafted or signed from high school debuted in MLB younger (M = 23.99) and averaged significantly more MiLB GP (M = 909.13) than those drafted or signed from a two-year (M = 25.67 and 834.41 GP) or four-year institution (M = 25.95 and 752.33 GP). Pitchers signed or drafted from high school also debuted in MLB younger and played more MiLB games, as well as played in more MLB games than players from a two-year or four-year institution, F (8, 3,082) = 31.96, p ≤ .001. No significant differences of WAR were noted in position players or pitchers. With recent research suggesting that the sunk-cost fallacy is prevalent in the decisions of MLB teams, it is conceivable that this is a possible explanation for pitchers that were drafted from high school having the highest average GP. Future research may benefit from the consideration of post-secondary and/or high school statistics in combination with draft selection data, which may have important implications for improving talent identification accuracy.
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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) | 0.001 | 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".