Analyses of the impact of laterality on performances in the National Hockey League based on players’ position and origin
Bibliographic record
Abstract
This study addresses the question of the lateral preference of the National Hockey League players. The shooting preference, left or right, was analysed as a function of the origin of four groups of players that are from the USA, Canada, Europe, or Russia. The analysis reveals that the players from the USA are more likely to shoot right than players from other countries. Also, compared to defense players from other groups, defense players from the USA have a higher number of shots per game and a higher goal-to-assist ratio. The study also shows that for wingers shooting left, those playing on the right wing have more goals or points per game than those playing on the left wing; and that European forward players have a better differential (+/-) than American and Canadian forward players. The study reveals the influence of the players' origin on the preference in a bimanual asymmetric task and the impact of this preference on ice hockey performances.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".