Sprint profile of professional female soccer players during competitive matches: Female Athletes in Motion (FAiM) study
Bibliographic record
Abstract
The aim of this study was to determine sprint profiles of professional female soccer players and evaluate how various speed thresholds impact those outcomes. Seventy-one professional players competing in full matches were assessed repeatedly during 12 regular season matches using a Global Positioning System (GPS). Locomotion ≥18 km · h⁻¹ was defined as sprinting and each event was classified into: Zone 1: 18.0-20.9 km· h⁻¹; Zone 2: 21.0-22.9 km · h⁻¹; Zone 3: 23.0-24.9 km · h⁻¹ and Zone 4: >25 km · h⁻¹. Outcomes included: duration (s), distance (m), maximum speed (km · h⁻¹), duration since previous sprint (min) and proportion of total sprint distance. In total 5,019 events were analysed from 139 player-matches. Mean sprint duration, distance, maximum speed and time between sprints were 2.3 ± 1.5 s, 15.1 ± 9.4 m, 21.8 ± 2.3 km· h⁻¹, and 2.5 ± 2.5 min, respectively. Mean sprint distances were 657 ± 157, 447 ± 185, and 545 ± 217 m for forwards, midfielders and defenders, respectively (P ≤ 0.046). Midfielders had shorter sprint duration (P = 0.023), distance (P ≤ 0.003) and maximum speed (P < 0.001), whereas forwards performed more sprints per match (43 ± 10) than midfielders (31 ± 11) and defenders (36 ± 12) (P ≤ 0.016). Forty-five percent, 29%, 15%, and 11% of sprints occurred in sprint Zones 1, 2, 3 and 4, respectively. This group of professional female soccer players covered 5.3 ± 2.0% of total distance ≥18 km · h⁻¹ with positional differences and percent decrements distinct from other previously identified elite players. These data should guide the development of high intensity and sprint thresholds for elite-standard female soccer players.
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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) | 0.002 | 0.001 |
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".