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Record W4322769920 · doi:10.3390/sym15030625

Difference Asymmetry between Preferred Dominant and Non-Dominant Legs in Muscular Power and Balance among Sub-Elite Soccer Players in Qatar

2023· article· en· W4322769920 on OpenAlexaff
Monoem Haddad, Zied Abbes, Nidhal Zarrouk, Zlatan Aganović, Albraa Hulweh, Imen Moussa-Chamari, David G. Behm

Bibliographic record

VenueSymmetry · 2023
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsMemorial University of Newfoundland
FundersQatar National Research Fund
KeywordsBalance (ability)Dynamic balanceFootballBalance testFootball playersVertical jumpAbsolute powerJumpLeagueMathematicsLeg musclePhysical therapyPhysical medicine and rehabilitationMedicinePhysicsGeography

Abstract

fetched live from OpenAlex

The objective of this study was to determine and compare leg asymmetry between preferred dominant and non-dominant legs in muscular power and balance among sub-elite soccer (football) players in Qatar. Thirty-two professional local soccer players from the Qatar Stars League (Second Division) participated in the study (23.1 ± 6.1 years). They were classified according to their preferred dominant leg (preferred leg to kick the ball). Twenty-two players had a right dominant leg, and the remaining ten had a left dominant leg. Countermovement jump (CMJ) was used to measure unilateral and bilateral vertical jump performances. The Y-balance test (YBT) was used to assess dynamic balance. No significant differences were found between the dominant and non-dominant leg for CMJ flight height (p > 0.05; asymmetry index (AI) = 1.83 ± 11.46) or the relative and absolute reach distance derived from the YBT (p > 0.05; AI (relative) = −0.45 ± 9.68, AI (absolute) = −0.60 ± 12.3). Bilateral asymmetry in dynamic balance was not significant for any of the anterior, posteromedial, or the posterolateral reaching directions (p > 0.05). The selected football players demonstrated an acceptable level of leg symmetry for power and dynamic balance. These findings may prove helpful for the assessment and evaluation of talents and should help to develop and optimize training regimes.

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 score0.010
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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