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Record W3088974412 · doi:10.1177/1747954120966886

Are relative age and biological ages associated with coaches’ evaluations of match performance in male academy soccer players?

2020· article· en· W3088974412 on OpenAlexaff
Megan Hill, Sam Scott, Darragh McGee, Sean P. Cumming

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2020
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologyMaturity (psychological)Age groupsBiological ageLikert scalePerceptionDemographySocial psychologyDevelopmental psychologyGerontologyMedicine

Abstract

fetched live from OpenAlex

Talent identification and selection in soccer has been shown to be confounded by individual differences in relative age and biological maturation. Limited research has however, investigated whether these effects are reflected in coaches’ evaluations of performance. This study investigated relative and biological age associated differences in coach perceptions of performance in a professional soccer academy across four seasons. The performances of 279 male players were evaluated on a 4-point Likert-scale. Multi-level modelling was used to examine predictive relationships between biological age, chronological age, result and opposition of game, on match grades. Result of the games was a statistically significant predictor of players perceived performance in every age-group; category of opposition was only significant in the under 13 and 14 age-groups. Biological age significantly predicted players perceived performance grades in the under 10, 14 and 15 age-groups, whereby advanced maturity predicted a higher grade. Across all age-groups, a relative age effect was observed, however age half was not a significant predictor of perceived performance grade in any age-group. Coaches evaluations of match performance appear to vary in accordance with maturity, opposition, and result of game. Academy staff should recognise and account for individual differences in biological maturation when retaining and releasing players.

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 score0.002
Threshold uncertainty score0.282

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 head0.092
GPT teacher head0.353
Teacher spread0.261 · 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

Citations54
Published2020
Admission routes1
Has abstractyes

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