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Male Ice Hockey Player Body Composition During A Season And Relationships To On-ice Skating Performance

2024· article· en· W4402663196 on OpenAlexaff
Lawrence L. Spriet, Jessica L. Bigg, John R. M. Renwick, Alexander SD Gamble

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMcMaster UniversityUniversity of Guelph
Fundersnot available
KeywordsIce hockeySpeed skatingComposition (language)MedicineEngineeringPhysical medicine and rehabilitationSimulationArtLiterature

Abstract

fetched live from OpenAlex

Literature supporting a potential association between body composition and performance in sports is limited, and no work has investigated this relationship during ice hockey games using wearable technology-derived skating measures. PURPOSE: To examine male ice hockey player’s body composition changes during three months of a season and evaluate the potential associations between body composition and on-ice skating performance measured during games using player-tracking technology. METHODS: Twenty-five male university ice hockey players (22.1 ± 1.2 y, 87.3 ± 5.2 kg, 181 ± 5 cm) underwent dual energy X-ray absorptiometry (DXA) scans during preseason (PRE) and at the mid-way point (MID) of the season to determine whole body and upper and lower segmental changes in fat mass (FM) and lean mass (LM). Selected on-ice skating speeds (medium, high, and very high zones and maximum speed) were measured via a local positioning system and averaged across 4 games within 30 days of the MID assessment. Dependent sample t-tests were used to compare PRE and MID assessments. Pearson’s correlations were used to examine the association between body composition parameters and LPS-derived measures. RESULTS: Whole body mass was maintained between PRE (87.4 ± 5.2 kg) and MID (87.2 ± 5.1 kg) measurements. Upper body mass and lower body mass were also unchanged between PRE and MID. PRE whole body FM was 17.5% (14.0 ± 3.2 kg) and LM was 79.2% (62.9 ± 3.6 kg) and both were unchanged at the MID time point. Upper and lower LM and FM were also unchanged over the 3 months of the season. There were no significant correlations between upper or lower body LM with any of the skating measures. However, whole body mass and lower body mass were significantly correlated with distance in the very high-speed zone (r = 0.46, p = 0.03; r = 0.45, p = 0.03) and maximum speed (r = 0.44, p = 0.03; r = 0.59, p < 0.01). CONCLUSIONS: This study demonstrated that male university hockey players were able to maintain their body composition parameters during three months of a season. Local positioning system-derived measures of skating speeds during ice hockey games revealed few significant correlations with body composition parameters. PepsiCo and Mitacs

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

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)0.0030.001

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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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