Physical and Technical Demands and Preparatory Strategies in Female Field Collision Sports: A Scoping Review
Bibliographic record
Abstract
Women's participation in field collision sports is growing worldwide. Scoping reviews provide an overview of scientific literature in a developing area to support practitioners, policy, and research priorities. Our aim is to explore published research and synthesise information on the physical and technical demands and preparation strategies of female field collision sports. We searched four databases and identified relevant published studies. Data were extracted to form (1) a numerical analysis and (2) thematic summary. Of 2318 records identified, 43 studies met the inclusion criteria. Physical demands were the most highly investigated (n+=+24), followed by technical demands (n+= 18), tactical considerations (n+=+8) and preparatory strategies (n=1). The key themes embody a holistic model contributing to both performance and injury prevention outcomes in the context of female field collision sports. Findings suggest a gender data gap across all themes and a low evidence base to inform those preparing female athletes for match demands. Given the physical and technical differences in match-demands the review findings do not support the generalisation of male-derived training data to female athletes. To support key stakeholders working within female field collision sports there is a need to increase the visibility of female athletes in the literature.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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 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".