ArticleSensors (Basel, Switzerland)2026
Comparative Analysis of Markerless Motion-Capture Models for Assessing Football Kinematics During 30 m Long-Pass Tasks.
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.
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7 authors.
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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.
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