Evidence map›Paper›PMID 36935923›Full record

ArticlePeerJ2023

Methods of performance analysis in women's Australian football: a scoping review.

Braedan R van der Vegt, Adrian Gepp, Justin W L Keogh, Jessica B Farley

Full text readScoping Review
In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Braedan R van der VegtCentre for Data Analytics, Bond Business School, Bond University, Gold Coast, Queensland, Australia.
Adrian GeppCentre for Data Analytics, Bond Business School, Bond University, Gold Coast, Queensland, Australia.
Justin W L KeoghFaculty of Health Sciences & Medicine, Bond University, Gold Coast, Queensland, Australia.
Jessica B FarleyFaculty of Health Sciences & Medicine, Bond University, Gold Coast, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The first women's Australian football (AF) professional competition was established in 2017, resulting in advancement in performance analysis capabilities within the sport. Given the specific constraints of women's AF, it is currently unclear what match-play performance analysis methods and techniques are implemented. Therefore, the aim of this scoping review was to describe and critically appraise physical, technical, and tactical performance analysis methods that have been employed in women's and girls' AF match-play. Methodology: A systematic search was conducted on the 27th of June 2022 through five databases. Eligibility criteria were derived from the PCC framework with the population (P) of women and girls AF players, of any level of play; concepts (C) of interest which were measures, data, and methods related to the sport's physical, technical, and tactical performance; and the context (C) of methods that analysed any match-play performance. A narrative synthesis was conducted using extracted study characteristic data such as sample size, population, time period, collection standards, evaluation metrics for results, and application of thematic categorisations of previous sports performance reviews. Critical appraisal of eligible studies' methodologies was conducted to investigate research quality and identify methodological issues. Results: From 183 studies screened, twelve eligible studies were included, which examined match-play through physical (9/12, 75%), technical (4/12, 33%), and tactical analysis (2/12, 17%). Running demands and game actions analysis were the most researched in senior women's AF. Research into junior girls' AF match-play performance has not been investigated. No research has been conducted on non-running physical demands, contact demands, acceleration, and tactical aspects of women's AF. All studies utilised either inferential statistics or basic predictive models. Critical appraisal deemed most studies as low risk of bias (11/12, 92%), with the remaining study having satisfactory risk. Conclusions: Future research utilising increased longitudinal and greater contextual data is needed to combat the prominent issue of data representativeness to better characterise performance within women's and girls' AF. Additionally, research involving junior and sub-elite AF players across the talent pathways is important to conduct, as it provides greater context and insight regarding development to support the evolving elite women's AF competition. Women's AF has been constrained by its resource environment. As such, suggestions are provided for better utilisation of existing data, as well as for the creation of new data for appropriate future research. Greater data generation enables the use of detailed machine learning predictions, neural networks, and network analysis to better represent the intertwined nature of match-play performance from technical, physical, and tactical data.

Indexed as

Athletic PerformanceTeam SportsAccelerationAustraliaFemaleHumansAFLWAustralian FootballData analysisFemale athleteGame actionsPerformance analysisRunning demands

Identifiers

PMID36935923
PMCPMC10019326

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LicenceCC BY
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reference markers read56
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.