Evidence map›Paper›PMID 41766804›Full record

ArticleJournal of human kinetics2026

Match Performance Analysis of Women's Épée in the 2017-2019 World Fencing Championships.

Jo-Ting Hsu, Yin-Hua Chen

Abstract read
In one paragraph

Article in Journal of human kinetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

2 authors.

Jo-Ting HsuGraduate Institute of Athletics and Coaching Science, National Taiwan Sport University, Taoyuan, Taiwan.
Yin-Hua ChenGraduate Institute of Athletics and Coaching Science, National Taiwan Sport University, Taoyuan, Taiwan.ORCID https://orcid.org/0000-0003-2481-1054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Épée preserves the original dueling nature of fencing and is the only discipline that allows double hits. However, there is still limited understanding of how specific techniques are used in different contexts, such as bout rounds, piste areas, and score statuses (leading, tied, or trailing). To address this gap, this study analyzed the performance of elite female épée fencers during the top 16 to final bouts of the 2017-2019 world championships using notational analysis of videos from the International Fencing Federation's official YouTube channel. This dataset included 1,840 scoring events across 45 matches, involving 38 fencers. Three- or two-way mixed-design ANOVAs, as well as two-way repeated measures ANOVAs were conducted to investigate the effects of these factors and their interactions for both winners and losers. Results highlighted the second round as a crucial scoring phase. Winners strategically focused on achieving more single hits (than double hits), attacking in the first two rounds and counterattacking in the third. When leading, winners often lured their opponent toward their side of the piste to maintain control, while becoming more aggressive-advancing into the central or even the middle area of the opponent's side to score with attacks-when temporarily tied or trailing. In contrast, losers frequently scored in the central and middle areas of both sides. When temporarily leading, they displayed no clear preference for specific techniques or areas of the piste. These findings provide valuable insights for coaches to design more effective training sessions and offer targeted feedback during competitions to enhance fencers' performance.

Indexed as

attackcounterattacknotational analysispistescores

Identifiers

PMID41766804
PMCPMC12946867

What OpenQuestion holds

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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.