Inhouse vs Outsourced Skill Development in Professional Sports: Analysis of Baseball Careers
Bibliographic record
Abstract
This study analyzes the effects of in-house vs. outsourced skill development on professional athletes’ early careers, by analyzing selection and promotion of prospects (promising young players) by Major League Baseball teams. Drawing on research on worker skill development and labor market transaction costs, I theorize three benefits to having a top-tier professional club control the development process for a set of prospective athletes: (1) development of more club-specific skills; (2) better assessment of unmeasurable skills; and (3) ability to maximize general skill development. Focusing on US baseball players exploits the fact that some prospects enter the minor league system (“inhouse” development) at age 18 while others opt for college (“outsourced” development) and do not enter the professional system until age 22. Using a dataset of 9,785 players drafted into the league from 1987 to 2013, I find some evidence that internal development may generate more club-specific skills that aid prospects’ careers. I find that from age 22, prospects that entered the minor leagues from high school may be less likely to be promoted to the top-tier league than those that developed in college—but among those that are promoted, the minor leaguers are promoted more quickly than the college prospects. Furthermore, I find that promotion rate and probability for minor league infielders than non-infielders, which is consistent with the assumption that infielders are more interdependent and thus benefit more from club-specific skills. I also find evidence that college draftees, relative to high school draftees, are more likely to be drafted below their pre-draft rankings. This is consistent with the idea that clubs are more concerned about the unmeasurable skills of college draftees, who will spend less time in the clubs’ development system, than of high school draftees. These findings raise questions about the lack of in-house development systems in other major professional sports, such as US football and basketball.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| 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) | 0.000 | 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".