Evidence map›Paper›PMID 36969960›Full record

ArticleFrontiers in sports and active living2023

A data-driven framing of player and team performance in U.S. Women's soccer.

Sachin Narayanan, N David Pifer

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Article in Frontiers in sports and active living, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

2 authors.

Sachin NarayananDepartment of Sport Management, Florida State University, College of Education, Tallahassee, United States.
N David PiferDepartment of Sport Management, Florida State University, College of Education, Tallahassee, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In establishing historical benchmarks for success on the pitch and striving to achieve parity off it, the United States Women's National Team (USWNT) and the National Women's Soccer League (NWSL) have long served as standard bearers for professional women's soccer around the globe. However, off-field dilemmas and incessant juxtapositions to men's soccer frequently overshadow the elements that make U.S. women's soccer unique; that is, in the quest to expose and rid the women's game of blatant misconduct, discriminatory practices, and negative stereotypes, relatively little attention has been devoted to performance features that separate the U.S. women's soccer product from its competition. Because many of the issues hindering the progress of women's soccer are rooted in media and managerial practices that marginalize or ignore its positive traits, a need exists for analyses that will properly identify its innate characteristics and competitive advantages so that media members, managers, and fans can accurately frame their perceptions of women competing in the sport. Methods: To this end, we collected reliable samples of public event data from 560 professional soccer matches and used ANOVAs and t-tests to identify the characteristics that distinguish U.S. women's soccer from other professional leagues and teams. Results and Discussion: In doing so, we showed that the USWNT tends to shoot from more opportune areas and press opponents at a higher rate, and that the NWSL has recently been matched in quality across certain performance metrics by England's FA Women's Super League.

Indexed as

americacompetitive advantagefootball (soccer)genderperformance analytics

Identifiers

PMID36969960
PMCPMC10031044

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read5
measurements read2
Read underepoch 390

Registered trials

None linked

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.