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Record W2999845123

The role of relative age, playing position, and height and weight in Canadian Hockey League draft selection

2013· article· en· W2999845123 on OpenAlexaffabout
Nick Wattie, Joseph Baker

Bibliographic record

VenueJournal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository) · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsYork UniversityOntario Tech University
Fundersnot available
KeywordsLeagueDemographyElitePsychologyMedicinePolitical scienceSociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Relative age effects describe the over-representation of those born earlier in their youth-sport selection year (i.e., the relatively older) on elite sports teams. However, in the long-term relatively younger players may be more sought after (Baker & Logan, 2007). This study extends prior research by exploring talent identification processes prior to professional sport. The Ontario, Western and Quebec Major Junior Hockey Leagues (i.e., OHL, WHL and QMJHL) are developmental leagues for professional hockey, drafting eligible players who are 15 years of age. Canadian players’ relative age, playing position, weight, height, and draft round were collected for each entry draft within the leagues (OHL: 1999-2012, N = 3537; WHL: 2011-2012, N = 415; QMJHL: 2003-2012, N = 2275). The overall sample of each league reflected significant relative age effects [OHL: χ2 = 873.7, p < 001, w = .49; WHL: χ2 = 126.3, p < 001, w = .55; QMJHL: χ2 = 186.8, p < 001, w = .28). There were also small, positive correlations between relative age and draft round found in each league (r < .12). With the exception of the QMJHL, athletes’ weight (r = -.09 to - .20, p < .05) and height (r = - .11 to - .17, p < .01) were also associated with earlier draft round selection. Further, centres were drafted earlier than other positions. These results showed a small advantage for relatively older youth in the CHL drafts, although height, weight and position were stronger predictors of draft round.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.193
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes2
Has abstractyes

Explore more

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