The Effect of Mid-Season Coach Turnover on Team Performance: The Case of the National Hockey League (1989–2003)
Bibliographic record
Abstract
This study investigated the effects of 15 mid-season coaching turnovers on team performance in the National Hockey League (NHL) from 1989 to 2003. Team performance was tracked for one full season before the turnover (T1), the season of transition before and after the turnover (T2 and T3 respectively) and one full season following the year of transition (T4). Overall team performance improved from .35 at T2 to .45 at T3 of available points earned. Furthermore, team performance continued to improve to 51 at T4. When coaching experience was considered, results showed that incoming coaches had less experience as an NHL head coach than their replaced counterparts. The current findings suggest that mid-season coach turnover does lead to improved team performance in the short-term and at least the full season following the turnover. Results also show that team performance improved despite the fact that inexperienced coaches replaced experienced coaches.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".