The rise of the underdog? The relative age effect reversal among Canadian-born NHL hockey players: A reply to Nolan and Howell
Bibliographic record
Abstract
The relative age effect associated with cut-off dates for hockey eligibility has been an ongoing debate in certain academic circles and in the popular media. The effect is primarily found in Canadian Major Junior Hockey, where a disproportionate share of birthdays fall in the first three months of the year. But when the National Hockey League rosters of Canadian-born players are examined, the pattern is less pronounced. Using publically available data of hockey players from 2000–2009, we find that the relative age effect, as described by Nolan and Howell (2010) and Gladwell (2008), is moderate for the average Canadian National Hockey League player and reverses when examining the most elite professional players (i.e. All-Star and Olympic Team rosters). We also find that the average career duration is longer for players born later in the year. In sum, there is a surprising ‘relative age effect reversal’ that occurs from the junior leagues to the most elite level of hockey play. This supports an ‘underdog’ hypothesis, where the relatively younger players are thought to benefit by more competitive play with their older counterparts.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.012 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".