Gender Differences in Fitness and Fatigue Over a Competitive Season in Varsity Soccer Players
Bibliographic record
Abstract
Effective monitoring of fitness and fatigue identifies athletes' recovery abilities and helps to determine appropriate training for optimal performance. PURPOSE: To compare performance on a relative fatigue test between male and female varsity soccer players over the course of a competitive season. METHODS: Athletes from the male (n=18; 57.2 ± 3.9 ml/kg/min) and female (n=18; 50.1 ± 3.5 ml/kg/min) varsity soccer teams participated in fitness testing pre-post training camp and post-season. A field fatigue test (FFT) was also performed pre-post training camp as well as weekly throughout the season. The FFT was developed as a modified version of the 20m shuttle run aerobic test; it consisted of a 2 min warm-up followed by a run to exhaustion at a stage equal to ~90% of individual VO2max on the test. RESULTS: The male and female teams' time to fatigue averaged 208 ± 61 s and 225 ± 64 s respectively, on the FFT at pre-camp. Significant differences between the male and female teams (main effect; p<0.05) existed in FFT performance over the season. FFT time decreased by 14% (p<0.05) for males post-camp, whereas there was no significant change observed post-camp for females. Pre-post season, females increased FFT performance by a total of 43% (n=11; p<0.05), whereas FFT performance by males was not significantly different (−3%, n=11; p=0.28). Over the season, the proportion of athletes that improved FFT scores from week to week (i.e. improved fitness) declined in the females from 69% post-camp to 15% at post-season (p<0.05), but increased in the males from 10% post-camp to 35% post-season (p<0.05). The proportion of athletes that exhibited fatigue (i.e. >20% decrease in FFT performance by week), was not significantly different (p=0.15) between females (36%) and males (52%), although wide individual variance in fatigue was evident with each team. CONCLUSIONS: The male soccer team exhibited greater fatigue post-training camp that limited adaptations by the end of the season. The female team was less fatigued after training camp which resulted in greater overall improvements in performance by the end of season. The opposite response between male and female teams may indicate differences in training philosophies and highlights the importance of individualizing training loads to the needs of particular athletes in a given sport.
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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 | 0.000 | 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) | 0.003 | 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".