Comparisons and associations among anthropometric indices of first and second division and assistant soccer referees
Bibliographic record
Abstract
Introduction Body composition is an important predictor of performance and a key component of health and physical fitness. Therefore, the purposes of this study were to compare soccer referees of the first and second divisions and field assistant referees from Iran and to analyze associations of a body shape index (ABSI), body adiposity index (BAI), abdominal volume index (AVI), body roundness index (BRI), conicity index (ConI), and body mass index (BMI) with body fat percentage (%BF). Methods A total of 270 male soccer referees from the first ( n = 124) and second ( n = 72) divisions and assistant referees ( n = 74) participated in this study. Skinfold thickness (measured at the chest, biceps, triceps, subscapular, abdominal, iliac crest, and front thigh), height, weight, hip circumference, and waist circumference were assessed to evaluate waist-to-height ratio (WHtR), %BF, and also ABSI, BRI, BAI, ConI, and AVI according to the ISAK protocol. Results The main results indicated differences in WHR, WHtR, ABSI, BRI, AVI, ConI, and BF% with the assistant referees presenting higher values ( p < 0.05). When considering the backward selection model, there were some associations with %BF in each group, specifically BMI, BAI, and ABSI in the first division; BMI, WHR, and ABSI in the second division; and BMI in the assistant referee group (all p < 0.05). Discussion The present study did not confirm the hypothesis that the first-division referees presented better body composition-related variables than the second division or assistant referees. Instead, it showed that the assistant referees that participated in both divisions showed a tendency to higher values which suggests that the level of division is not a major factor when analyzing body composition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".