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Record W4412861570 · doi:10.46634/riics.445

Bridging the Relationship between Anthropometrics, Physical Performance, and Specific Soccer Skills in Young Male Soccer Players

2025· article· en· W4412861570 on OpenAlex
Chanawat Sanpasitt, Atcharat Yongtawee, Thitiwat Noikhammueang, Minjung Woo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista de Investigación e Innovación en Ciencias de la Salud · 2025
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMinistry of Tourism, Sport and the Arts
FundersThailand Science Research and InnovationMinistry of Higher Education, Science, Research and Innovation, Thailand
KeywordsAnthropometryBridging (networking)PsychologyMedicineComputer science

Abstract

fetched live from OpenAlex

Objective. The aim of this study was to investigate the association between anthropometrics, physical performance, and specific soccer skills in young male soccer players. Method. 132 male soccer players aged 13-15 years old were recruited and categorized according to three distinct playing positions: defenders, midfielders, and forwards. Anthropometric profiles, including height, weight, body mass index, body fat, muscle mass, and 2D:4D finger length ratio were evaluated. Furthermore, acceleration ability (10m, 20m, and 30m velocity), countermovement jump (CMJ) test, drop jump (DJ) test; sit and reach test (SRT), and Y-balance test (YBT) were assessed. Soccer-specific performance was measured by the lofted passing accuracy over 35 meters protocol and the modified Illinois change-of-direction test with ball dribbling speed. Results. There was a significant strong positive correlation between the right and left digits’ ratios (r = .644, p < 0.001). However, the 2D:4D ratio of both hands demonstrated no significant differences between playing positions. Notably, body weight and muscle mass showed large positive correlations with long passing accuracy (r = .378, r = .418, respectively), while there was a moderate inverse relationship between dribbling time and both CMJ with arm swing (r = -.396) and drop jump height (r = -.305). Additionally, the YBT on both legs was negatively associated with dribbling time. Conclusion. Our results provide strong evidence that higher muscle mass and weight are associated with greater long passing accuracy, while better performance in countermovement and drop jumps serve as a key predictor of faster dribbling times. This information is useful for talent identification and performance optimization in young male soccer 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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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