Comparing Workload Between Halves And Its Association To Anthropometry And Cardiorespiratory Performance In Female Collegiate Soccer Players
Bibliographic record
Abstract
The majority of goals scored in competitive soccer occur in the second half. This outcome coincides with alterations in on-field workload. Playing position has shown to influence first and second half workload, where an increase or decrease can occur. Identifying physiological indices associated with workload can allow coaches to focus on training techniques to mitigate or improve second half workloads to influence the outcome of competition. PURPOSE: To examine alterations in workload during the first and second half of six competitive soccer games and its association with cardiorespiratory performance and anthropometry in female collegiate soccer players. METHODS: Ten healthy female collegiate soccer players with an age of (mean ± SD) 18.8 ± 0.79 yr, a weight of 54.2 ± 6.4 kg, a height of 163.7 ± 6.4 cm and a body fat % of 23.2 ± 7.4 volunteered as participants during a six-game period. Indices of workload from each half were recorded using the Polar Team Pro® system and included total distance (TD) covered (km), number of sprints (SPRZ), average heart rate (HRavg) and Polar training load (TL) (AU). Participants completed a YoYo IRT-1 prior to beginning the study period for establishing cardiorespiratory performance. A two-tailed paired sample t-test as well as standardized mean differences to reveal the effect size (ES) were performed to examine alterations in first half and second half workload. Linear regression (R2) was utilized to examine the association between workload and both cardiorespiratory performance and anthropometry. A secondary analysis compared playing positions. This study was approved by and followed the recommendation of the Research Ethics Review board at Langara College. RESULTS: Significant reductions were observed in second half TL (-7.1%, ES = -0.49, p < 0.001), TD (-6.6%, ES = -0.70, p < 0.001), SPRZ (-9.2%, ES = -0.58, p < 0.001) and HRavg (-3.6%, ES = -0.75, p < 0.001). Significant associations were observed between anthropometry and both TL (R2 = 0.33, p < 0.01) and HRavg (R2 = 0.37, p < 0.01), and were similar when comparing playing positions. CONCLUSION: Anthropometry is associated with reductions in second half workloads in mid-field and defence players. This investigation was funded by the Langara College ARC-1 Grant.
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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 | 0.000 |
| 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) | 0.001 | 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".