Overtime! Rules and Incentives in the National Hockey League
Why this work is in the frame
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Bibliographic record
Abstract
We construct a simple 2-period game model to determine the effects of recent National Hockey League rule changes on team incentives to win. The effects differ depending on the relative quality of the contestants and whether the contestants compete in the same conference. The model predicts that the average number of points during a season will rise, yet the average point differential among clubs within the same conference will fall. The model also predicts that the expected value of points per contest will be higher when playing nonconference opponents but lower when playing conference opponents. Because only a small percentage of contests are nonconference, we predict that more effort will be devoted to conference contests, particularly by lesser-talented clubs. The result is more competitive and exciting conference games requiring fewer overtime periods and potential ties. Empirical data support these hypotheses.
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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) | 0.000 | 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