Bibliographic record
Abstract
This paper investigates the relationship between puck possession and team success in the NHL, focusing on the games played during the 2023-2024 regular season (up to the All-Star break). The analysis first reveals a moderate correlation (r = 0.56) between average team possession percentage and Average Goal Differential (Avg. GoalDiff). Next, we introduce Average Offensive Zone Possession Time Differential (Avg. OZPTD) as a key metric, defined as the difference between a team’s offensive zone possession time and that of their opponents. We find a strong correlation (r = 0.77) between Avg. OZPTD and Avg. GoalDiff, thereby highlighting its relevance in assessing team performance. Our analysis confirms OZPTD’s stability, discriminatory power, and independence from existing metrics like Shot Attempt Percentage (SAT%), also known as Corsi. Additionally, we detail a comprehensive methodology for processing and cleaning possession data sourced from the NHL. This methodology underpins our findings and facilitates future research involving player and team possession data.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".