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Pre-post Season Differences In Physical, Fitness, And Performance Characteristics In Elite Female Ice Hockey Players

2009· article· en· W2068074742 on OpenAlexaboutno aff
Christina A. Geithner, Courtney L. K. Haia, Dione H. Fernandez, Michael R. Bracko

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2009
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsDashSprintAnaerobic exerciseVertical jumpIce hockeyWaistAnthropometryPhysical therapyAnimal scienceMedicineJumpPhysical medicine and rehabilitationComputer scienceBiologyBody mass indexInternal medicinePhysics

Abstract

fetched live from OpenAlex

PURPOSE: Only one study has examined the effects of multiple seasons of play in elite female ice hockey players, and on a limited number of variables. Thus, the purpose of this study was to determine if physical characteristics, fitness, and on-ice skating performance vary significantly from pre- to post-season in elite female ice hockey players. METHODS: The subjects of this study were players from the University of Alberta (n=94, age=20.9±2.5 yrs) measured over nine seasons of play (1999-2007). A full anthropometric battery was taken on each player for four pre- and post-seasons (1999-2000, 2004-05, 2005-06, and 2007-08). Off-ice fitness tests included vertical jump (VJ), sit-ups (SU), push-ups (PU), Leger Test (to predict VO2max), and 40-yd dash (DASH). On-ice skating performance tests included a 44.80 m speed (SPEED), 6.10 m acceleration (ACCEL), Cornering S-Turn agility (AGIL), and Modified Repeat Sprint Skate (MRSS) tests. Blood lactates were taken immediately after the MRSS and after 4-6 minutes recovery. Anaerobic power estimates were derived (anaerobic capacity and power from MRSS and SPEED - Watson & Sargeant, 1986) and (peak anaerobic power from VJ - Sayers, 1998). Paired sample t-tests were run using SPSS (Mac Version 11.0) with a significance level set a priori at p<0.01. RESULTS: Significant pre-to-post season differences were found for thigh and waist circumferences and % body fat; DASH; anaerobic capacity; AGIL and MRSS, MRSS drop-off, recovery HR, and post-MRSS lactate clearance. CONCLUSIONS: Anthropometric differences were within measurement error, suggesting that physical characteristics do not change significantly over the course of a season of play. However, differences in fitness and performance measures indicate that players improve selected aspects of both over the course of a season. These changes are likely a result of training, skating skill enhancement, and/or ice time rather than a learning effect over a five-to-six month period.

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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.279
Teacher spread0.263 · 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
Published2009
Admission routes1
Has abstractyes

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