Competitive Balance and Attendance in Major League Baseball: An Empirical Test of the Uncertainty of Outcome Hypothesis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Competitive balance research partitions into two areas: analyzing sports policy and its effect on competitive balance and the uncertainty of outcome hypothesis. This paper examines the latter section. No formal analysis of the relationship between competitive balance and regular season average attendance in Major League Baseball (MLB) using the actual to idealized standard deviation ratio exits. This paper examines the effect that competitive balance has on MLB attendance between the seasons 1920 and 2006. Additionally, this paper incorporates a games-behind variable to examine if fans are sensitive to team performance. The empirical model in this paper is a fixed-effects OLS model that corrects for heteroscedasticity. The results show a significant inverse relationship between the ratio, games behind, and regular season average attendance. This confirms the uncertainty of outcome hypothesis and shows that fans are sensitive to both league and team performance.
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.
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) | 0.000 | 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 it