Examination of the Physical and Motoric Characteristics of Elite Soccer Players According to Their Positions
Bibliographic record
Abstract
The purpose of the present study was to examine the physical and motoric characteristics of elite soccer players playing at different positions in U21 team. A total of 64 male soccer players participated in the present study (4 goalkeepers, 16 defense players, 21 midfield players, and 23 strikers). The Body Mass Indices of the players were computed by measuring their height and weights. The Yo-Yo Intermittent Recovery 2 Test and the t-test were applied to the players. The VO2max values of the players were computed according to the formula that was developed by Bangsbo et al. The statistical package programs were employed for data analyses. The “Independent Sampling One-Way Variance Analysis” was applied to compare the physical and motoric characteristics of elite soccer players according to their positions. When differences were detected between the measurements, the “Tukey Analysis” was carried out to determine the direction of these differences. The results were evaluated according to (p<0.05) significance level. It was determined that there was a statistically significant difference between the BMI values of elite soccer players according to their positions (p<0.05). It was also determined that the motoric characteristics of the players did not have any significant differences according to their positions (p>0.05). The lowest values were determined in goalkeepers, strikers, midfield players and defense players according to the BMI values of the elite soccer players. This situation might be associated with the fact that in today’s soccer, players show performance in different areas of the field for attack and defense without considering their positions. According to the BMI values of the elite soccer players, the lowest values were determined in goalkeepers, strikers, midfield players and defense players; and no differences were detected in terms of motoric characteristics.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".