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Effect of a change in selection year on success in male soccer players

2000· article· en· W2050614302 on OpenAlexaff
Werner Helsen, Janet L. Starkes, Jan Van Winckel

Bibliographic record

VenueAmerican Journal of Human Biology · 2000
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHumDemographyLeagueCoachingSelection (genetic algorithm)Football playersFootballMedicinePsychologyGeographyHistory

Abstract

fetched live from OpenAlex

Since 1997 and following the guidelines of the International Football Association, the Belgian Soccer Federation has used January 1st as the start of the selection year. Previously, August 1 was the start. This shift prompted an investigation of changes in birth-date distributions throughout youth categories for 1996-1997 compared to the 1997-1998 competitive years. Birth dates were considered for national youth league players, ages 10-12, 12-14, 14-16, and 16-18 years. Kolmogorov Smirnov tests assessed differences between observed and expected birth-date distributions. Regression analyses examined the relationship between month of birth and number of participants both before and after the August to January shift. Results indicated that from 1996 to 1997, youth players born from January to March (the early part of the new selection year) were more likely to be identified as "talented" and to be exposed to higher levels of coaching. In comparison, players born late in the new selection year (August to October) were assessed as "talented" in significantly lower proportions. Specific suggestions are presented to reduce the relative age effect. Am. J. Hum. Biol. 12:729-735, 2000. Copyright 2000 Wiley-Liss, Inc.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.351
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), 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

Citations139
Published2000
Admission routes1
Has abstractyes

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