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Psychological Modelling and Action Recognition for Boxing Performance

Authors:
Vishal Ravishankar
Itish Shukla
Nishat Afroz
Anirudh Bhatta
Surbhi Choudhary

Keywords: Sports psychology; Action recognition; Boxing behavior; Convolution neural network.

Abstract:
Psychological dynamics in boxing remain largely unaddressed during real-time performance evaluation, despite their significant impact on decision-making and reaction time. Traditional analysis tools focus predominantly on physical performance, overlooking the internal cognitive states of athletes. This gap limits coaches’ and psychologists’ ability to intervene strategically during or after a match. The Boxing Psychological State Tracking System is a novel framework designed to analyze a boxer’s psychological state throughout a fight by correlating physical performance indicators with inferred cognitive conditions. By leveraging action recognition and explainable Artificial Intelligence (AI), the system evaluates events such as knockdowns, strike patterns, and defensive behavior to infer mental states like fatigue, disengagement, and stress. Previous approaches to action recognition in sports have either ignored psychological interpretation or lacked transparency in decision making, which this work addresses. Our solution involves a lightweight, vision-based system combining You Only Look Once, version 8 - nano variant (YOLOv8n) and SHapley Additive exPlanations (SHAP) to map strike behavior to inferred cognitive states. The system integrates these insights with a visual analytics interface, enabling coaches, sports psychologists, and athletes to understand and improve performance through a deeper awareness of psychological dynamics. Evaluation of the system demonstrates its potential to reveal meaningful psychological patterns using just two high frequency strikes, providing a practical and explainable method for mental state assessment in combat sports.

Pages: 1 to 8

Copyright: Copyright (c) IARIA, 2025

Publication date: May 18, 2025

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-68558-268-5

Location: Nice, France

Dates: from May 18, 2025 to May 22, 2025