Inversiones financieras y resultados deportivos en las grandes ligas de fútbol: un análisis comparativo entre el valor de mercado, el salario base y los resultados en las conferencias
Bibliographic record
Abstract
This study examines the link between financial investments and sports performance in Major League Soccer (MLS) during 2023. It finds that higher investments do not ensure superior outcomes. In the Eastern Conference, Cincinnati excelled with modest financial figures ($11.46M base salary, $13.20M Guaranteed Compensation, and €29.25M market value), while higher-spending teams like Inter Miami and Toronto lagged behind. Similarly, in the Western Conference, St. Louis City led with 56 points, despite a lower budget ($9.49M base salary, $10.51M Guaranteed Compensation, €23.03M market value), outperforming higher spenders like Seattle Sounders and LAFC. Correlation analysis revealed negative associations between points and base salary (-0.52) and Guaranteed Compensation (-0.61) in the Eastern Conference, while points in the Western Conference showed weak correlations with financial variables. The study underscores the critical role of financial efficiency over mere expenditure for success in MLS.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".