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Record W4214568489 · doi:10.3390/jfmk7010025

Association between Concentric and Eccentric Isokinetic Torque and Unilateral Countermovement Jump Variables in Professional Soccer Players

2022· article· en· W4214568489 on OpenAlexaff
Bruno Mazziotti Oliveira Alves, Robson Dias Scoz, Ricardo Lima Burigo, Isabella Christina Ferreira, Ana Paula Silveira Ramos, José João Mendes, Luciano Maia Alves Ferreira, César Ferreira Amorim

Bibliographic record

VenueJournal of Functional Morphology and Kinesiology · 2022
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversité du Québec
FundersFundação para a Ciência e a TecnologiaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsConcentricCountermovementEccentricJumpMathematicsPhysical medicine and rehabilitationVertical jumpImpulse (physics)TorquePhysical therapyLinear regressionMedicineOrthodonticsStatisticsPhysicsEngineeringStructural engineeringGeometry

Abstract

fetched live from OpenAlex

Isokinetic tests have been highly valuable to athletic analysis, but their cost and technical operation turn them inaccessible. The purpose of this study was to verify the correlation between unilateral countermovement jump variables and isokinetic data. Thirty-two male professional soccer players were subjected to the isokinetic testing of both knee extensors and flexors in concentric and eccentric muscle contractions. They also executed unilateral countermovement vertical jumps (UCMJ) to compare maximum height, ground reaction force, and impulse power with isokinetic peak torque. Data analysis was conducted through Pearson correlation and linear regression. A high correlation was found between dominant unilateral extensor concentric peak torque and the UCMJ maximum height of the dominant leg. The non-dominant leg jump showed a moderate correlation. No other variable showed statistical significance. Linear regression allowed the generation of two formulae to estimate the peak torque from UCMJ for dominant and non-dominant legs. Although few studies were found to compare our results, leading to more studies being needed, a better understanding of the unilateral countermovement jump may be used in the future as a substitute to the expensive and technically demanding isokinetic testing when it is unavailable, allowing the assessment of lower limb physical asymmetries in athletic or rehabilitation environments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.248
Teacher spread0.235 · 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 teacher head, 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

Citations6
Published2022
Admission routes1
Has abstractyes

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