Exploring Incentives to Lose in Professional Team Sports: Do Conference Games Matter?
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
Many sports leagues use unbalanced schedules where teams do not play each opponent an equal number of times each season. In many leagues, teams that do not make the playoffs have the opportunity to improve by drafting highly skilled amateur players in the next entry draft, but the opportunity to pick first in the draft provides teams with an incentive to intentionally lose games. This has been a concern in the National Basketball Association (NBA), where the draft format has been altered three times since the 1980s. This research examines the strategic behavior of eliminated teams against conference and nonconference opponents under four NBA amateur draft formats. The results show that different draft formats present different incentives for eliminated teams to lose in conference games. Leagues need to recognize the unintended consequences of changes in league draft policies. Mitigating these consequences is difficult, but important in order to attain the goal of joint profit maximization.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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