Evidence map›Paper›PMID 42356626›Full record

ArticleSensors (Basel, Switzerland)2026

Comparative Analysis of Markerless Motion-Capture Models for Assessing Football Kinematics During 30 m Long-Pass Tasks.

Donghao Wang, Junkai Yu, Shiqin Chen, Jingran Yang, Weichao Jiang, Yikang Gong, Chong Luo

Abstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 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

7 authors.

Donghao WangSchool of Physical Education, Shanghai University of Sport, Shanghai 200438, China.ORCID 0009-0005-1587-7168
Junkai YuSchool of Physical Education, Huzhou University, Huzhou 313000, China.
Shiqin ChenSchool of Athletic Sport, Shanghai University of Sport, Shanghai 200438, China.
Jingran YangSchool of Physical Education and Health, East China Normal University, Shanghai 200241, China.
Weichao JiangSchool of Athletic Sport, Shanghai University of Sport, Shanghai 200438, China.
Yikang GongSchool of Physical Education, Shanghai University of Sport, Shanghai 200438, China.
Chong LuoSchool of Athletic Sport, Shanghai University of Sport, Shanghai 200438, China.ORCID 0000-0003-2403-2632

Funding

Ministry of Education of the People's Republic of China 22YJC890016
6 · The paper itself

Abstract

This study was based on a 30 m inside-foot long-pass scenario and aimed to preliminarily evaluate the agreement between MediaPipe Pose, DWPose, YOLO-Pose, and Xsens, as well as their practical utility under real-field conditions. Twelve elite male football players performed 15 consecutive long-passes, with data collected simultaneously using Xsens and two smartphones positioned at 15° and 35° to the right front of the participants. The Intraclass Correlation Coefficient (ICC (2,1)) and Bland-Altman analysis were used to evaluate discrete kinematic measures. Continuous kinematic agreement was assessed using Root Mean Square Error (RMSE) and the Coefficient of Multiple Determination (CMD), while Statistical Parametric Mapping (SPM) and Statistical non-Parametric Mapping (SnPM) compared differences across the entire analysis interval. Across the three models, CMD ranged from 0.13 ± 0.17 to 0.67 ± 0.25, and RMSE ranged from 9.88 ± 8.20° to 39.92 ± 10.44°. The SPM and SnPM results showed that significant differences were mainly concentrated in the bilateral hip, knee, and ankle joints. The three models cannot yet be used for field-based high-precision kinematic data measurement; however, MediaPipe Pose and DWPose may be selectively used for rapid screening of movement patterns and analysis of movement trends in football-specific technical movements.

Indexed as

FootballMotion CaptureSoccerAdultBiomechanical PhenomenaHumansMale30 m long passDWPosefootballkinematicsmarkerless motion captureMediaPipe Pose

Identifiers

PMID42356626
PMCPMC13306328

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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.