Age-related Effects of Speed and Power on Agility Performance of Young Soccer Players
Bibliographic record
Abstract
The purpose of this study is to determine the age-related effects of power and running speed on agility ability of young soccer players. A total of eighty-one soccer players, who do not have professional contracts with any professional club but play for various local and school teams on a regular basis, have participated (mean age: 17.7±1.16, range 16–19) in this study. Tests consist of anthropometric variables, power and speed measurements, and the agility test (T-Agility). At the completion of the warm-up protocol, players completed assessments of countermovement jump (CMJ), squat jump (SJ), speed (10-, and 30-m sprints, respectively), and the agility test (Agility T-Test). An analysis of variance (ANOVA) analysis was used to compare the parameters between each group and Pearson correlation analyses were applied to determine the relationships between agility test, speed, and power. When evaluated by age, only U16 players displayed moderate correlation between Agility T-Test and S10m and S30m (P<0.05). The only significantly weak correlation was found between the Agility T-Test and S30m for U19 players (P<0.05). Similarly, the only significantly weak correlation was found between the Agility T-Test and CMJ and SJ for U19 players (P<0.05). In conclusion, the results showed that speed and lower extremity power should not be considered as important predictors of agility performance in young athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".