Nonverbal Behaviour in Football: A 3D Pose-Based Analysis of Player Expressions and Observer Perceptions
Aki Uehata et al.
What the paper says
Nonverbal behaviour (NVB) is a critical component of human communication, particularly in high-stakes, naturalistic settings such as sport. Despite advances in computational analysis, the extent to which objectively computable NVB features reflect subjective human judgments remains unclear. In this study, we present the inaugural investigation into the correspondence between computable NVB indicators and observer perceptions in the context of elite football. The utilisation of 3D pose data from a FIFA World Cup match enabled the extraction of volumetric, angular and kinematic features from players’ body movements during match events. Parallelly, human participants rated short video segments of these events on multiple NVB dimensions. Statistical analyses revealed significant differences in objective computable NVB indicators across play contexts (scoring, conceding, regular play), with players on the scoring team exhibiting more expansive and dynamic body language. Subjective ratings closely mirrored these differences, and repeated measures correlation analyses demonstrated strong associations between objectively computable NVB features and human judgments. These findings may provide a scientific basis for the use of 3D pose-based metrics for scalable, automated NVB analysis and may highlight their ecological validity in capturing expressive behaviours meaningful to human observers. The study has the potential to contribute to the advancement of methodological approaches for NVB research.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.