MétaCan
Menu
Back to cohort
Record W2141298038 · doi:10.1123/tsp.2014-0007

Brazilian Elite Soccer Players: Exploring Attentional Focus in Performance Tasks and Soccer Positions

2014· article· en· W2141298038 on OpenAlexafffund
Rafael Ab Tedesqui, Terry Orlick

Bibliographic record

VenueThe Sport Psychologist · 2014
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsElitePsychologySport psychologyPerspective (graphical)Applied psychologyThematic analysisGoal settingAthletesFocus (optics)Cognitive psychologyFootballSocial psychologyQualitative researchComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this study was to qualitatively explore the attentional focus experienced by elite soccer players in different soccer positions and performance tasks of both closed and open skills. No previous studies have explored elite soccer players’ attentional skills from a naturalistic and qualitative perspective in such detail. Data collection consisted of individual semistructured interviews with eight highly elite Brazilian soccer players from five main soccer positions, namely goalkeeper, defender, wing, midfielder, and forward. Important themes were positive thinking, performing on autopilot, and relying on peripheral vision. For example, thematic analysis indicated that in tasks where there may be an advantage in disguising one’s intentions (e.g., penalty kick), relying on peripheral vision was essential. Early mistakes were among the main sources of distractions; thus, players reported beginning with easy plays as a strategy to prevent distractions. Implications for applied sport psychology were drawn and future studies recommended.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.324
Teacher spread0.273 · 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

Citations16
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueThe Sport PsychologistSame topicSport Psychology and PerformanceFrench-language works237,207