MétaCan
Menu
← Back to cohort

Reactive Strength Index Impact On Skating Speed, Agility And Change Of Direction In Youth Ice Hockey Players

2024· article· en· W4402663609 on OpenAlexaffabout
Philippe Roy, Vincent Lalande, Mathieu Poisson, Francis Létourneau, Alain Steve Comtois

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMontreal Clinical Research InstituteQuebec Labrador FoundationUniversité du Québec à Montréal
Fundersnot available
KeywordsIce hockeySpeed skatingIndex (typography)Physical medicine and rehabilitationComputer scienceSimulationMedicine

Abstract

fetched live from OpenAlex

Reactive Strength Index (RSI) tests are often used in sports to primarily measure the peak force, power and reactive strength of the lower body. Does this variable measure speed and change of direction for ice hockey players ?. PURPOSE: The purpose of the present study was to determine the impact of the RSI on skating speed, agility and change of direction on youth ice hockey players. METHODS: Thirty-two youth male ice hockey players, [age: 14.32 ± 0.72 years; height: 172.88 ± 14.57 cm; weight: 60.04 ± 17.00 kg] performed three trials per test. The off ice test was a Drop Jump (DJ) from 24 inches. The flight time was measured using a force plate (Desmotec, Italy). After a complete rest of 15 minutes (time required to put on full ice hockey equipment), participants had to perform three on ice tests. The on ice tests were best of three trials of a 30 meter sprint measured with a camera and a reflective system (SciencePerfo, Quebec) and of the Pro Agility and a Modified Vierumaki measured with timing gates (Exsurgo, USA). A rest of 120 seconds was taken between each trial. Values are reported as mean ± SD for all variables. Simple regression equations and Pearson correlation analysis were performed using SPSS (Ver. 28). RESULTS: Average RSI was (1.40 ± 0.39 sec/sec), Skating sprint was (5.27 ± 0.45 sec), Modified Vierumaki was (16.44 ± 2.21 sec), ProAgility Left was (5.42 ± 0.67 sec) and ProAgility Right was (5.44 ± 0.66 sec). The coefficient of determination (r2) was 0.20 (r = 0.45, p = 0.01) for Skating Sprint as a function of RSI, r2 = 0.23 (r = 0.48, p = 0.006) for Modified Vierumaki as a function of RSI, r2 = 0.23 (r = 0.48, p = 0.006) for Pro Agility Left as a function of RSI and r2 = 0.196 (r = 0.44, p = 0.011) for Pro Agility Right as a function of RSI. When adding height and weight into regression, the results show a strong regression, r2 = 0.784 (r = 0.885, p < 0.0001) for skating speed. CONCLUSION: The RSI partially explains the players’ skating speed, agility and change of direction and shows that it is a fitness component that cannot be neglected for strength and conditioning coaches in ice hockey. Moreover, further research can be made with a more homogenous group to find better statistical evidence of the impact of RSI on ice hockey 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 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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0030.001

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 head0.035
GPT teacher head0.327
Teacher spread0.293 · 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 routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & Exercise→Same topicSports Performance and Training→French-language works237,207→