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Record W1974996516 · doi:10.1016/j.jshs.2014.10.001

Women's football: Player characteristics and demands of the game

2014· article· en· W1974996516 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of sport and health science/Journal of Sport and Health Science · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSprintFootballPopularityFootball playersPsychologyEliteDemographyVertical jumpPhysical therapyJumpMedicinePolitical scienceSocial psychologySociologyLaw

Abstract

fetched live from OpenAlex

The number of scientific investigations on women's football specific to the topics of player characteristics and demands of the game has considerably increased in recent years due to the increased popularity of the women's game worldwide, although they are not yet as numerous as in the case of men's football. To date, only two scientific publications have attempted to review the main findings of studies published in this area. However, one of them was published about 20 years ago, when women's football was still in its infancy and there were only a few studies to report on. The other review was more recent. Nonetheless, its main focus was on the game and training demands of senior elite female players. Thus, information on female footballers of lower competitive levels and younger age groups was not included. Consequently, an updated review is needed in this area. The present article therefore aims to provide an overview of a series of studies that have been published so far on the specific characteristics of female football players and the demands of match-play. Mean values reported in the literature for age (12–27 years), body height (155–174 cm), body mass (48–72 kg), percent body fat (13%–29%), maximal oxygen uptake (45.1–55.5 mL/kg/min), Yo-Yo Intermittent Recovery Test Level 1 (780–1379 m), maximum heart rate (189–202 bpm), 30 m sprint times (4.34–4.96 s), and counter-movement jump or vertical jump (28–50 cm) vary mostly according to the players' competitive level and positional role. There are also some special considerations that coaches and other practitioners should be aware of when working with female athletes such as the menstrual cycle, potential pregnancy and lactation, common injury risks (particularly knee and head injuries) and health concerns (e.g., female athlete triad, iron deficiency, and anemia) that may affect players' football performance, health or return to play. Reported mean values for total distance covered (4–13 km), distance covered at high-speed (0.2–1.7 km), average/peak heart rate (74%–87%/94%–99% HRmax), average/peak oxygen uptake (52%–77%/96%–98% VO2max), and blood lactate (2.2–7.3 mmol/L) during women's football match-play vary according to the players' competitive level and positional role. Methodological differences may account for the discrepancy of the reported values as well. Finally, this review also aims to identify literature gaps that require further scientific research in women's football and to derive a few practical recommendations. The information presented in this report provides an objective point of reference about player characteristics and game demands at various levels of women's football, which can help coaches and sport scientists to design more effective training programs and science-based strategies for the further improvement of players' football performance, health, game standards, and positive image of this sport.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.345
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it