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Record W2106078770 · doi:10.1080/10413200209339008

Enhancing Competitive Performance of Ice Hockey Goaltenders Using Centering and Self-Talk

2002· article· en· W2106078770 on OpenAlexaff
Lisa J. Rogerson, Dennis Hrycaiko

Bibliographic record

VenueJournal of Applied Sport Psychology · 2002
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyLeagueIce hockeyApplied psychologyMultiple baseline designMental healthSocial skillsConsistency (knowledge bases)AthletesDevelopmental psychologyPhysical medicine and rehabilitationPhysical therapyComputer scienceIntervention (counseling)Psychotherapist

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effectiveness of two mental skills on the performance of ice hockey goaltenders during league games. The mental skills utilized were relaxation, in the form of centering, and self-talk. The participants were five male junior A hockey goaltenders. A single-subject multiple baseline across individuals design was employed to evaluate the use of the mental skills. The results demonstrated that the mental skills training was effective in producing improvements in the save percentage of the goaltenders. The social validation results indicated that the participants enjoyed using the mental skills and were satisfied with the results obtained. Furthermore, the coaches were very satisfied with the results and felt that the mental skills training was an important ingredient for improving performance, in particular performance consistency.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.321
Teacher spread0.224 · 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 designBench or experimental
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

Citations110
Published2002
Admission routes1
Has abstractyes

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