Author(s): MAGOME, T., TANAKA, T, Institution: OSAKA UNIVERSITY GRADUATE SCHOOL OF MEDICINE, Country: JAPAN, Abstract-ID: 1384

INTRODUCTION:
In recent years, the integration of Artificial Intelligence (AI), the Internet of Things (IoT), and sensor technologies has brought about a paradigm shift in sports analytics. In team sports such as soccer, the use of wearable devices equipped with GPS and accelerometers has enabled the precise measurement of performance metrics, including distance covered and movement intensity. The analysis of such tracking data has contributed to multifaceted insights, particularly in injury prevention and prediction. Against this backdrop, the present study utilizes network analysis to visualize the offensive and defensive tactics of Japanese professional soccer team. This approach aims to highlight the characteristics of team strategy while quantitatively elucidating the interactions and individual contributions of the players.
METHODS:
In this study, top-tier Japanese professional soccer league matches were analyzed using wearable accelerometers. A unique algorithm was developed to evaluate player coordination networks by processing acceleration data and deriving relevant random variables. By calculating the entropy of player movements through statistical analysis, we established an index for inter-player synchronization. This metric elucidates the characteristics of team performance in both offensive and defensive phases during a match. Specifically, this research focuses on quantifying three-player coordination, a fundamental unit of tactical teamwork in soccer.
RESULTS:
Analyses of official matches between closely ranked teams revealed that player synchronization, measured via phase difference entropy, was significantly higher in matches where team tactics were effectively executed. Furthermore, a marked difference in the degree of interplay was observed between periods of successful organized attacks compared to less effective periods. Specifically, player synchronization during successful organized attacks was approximately 30% higher than the overall match average (p < .05). Notably, diminished coordination was associated with erratic, high-intensity compensatory movements, indicating that network evaluation could serve as a vital metric for monitoring mechanical stress and managing injury risk within team structures.
CONCLUSION:
This research demonstrates that quantifying inter-player coordination allows for objective performance evaluation, the visualization of tactical quality, and the assessment of injury risks. Integrating these network metrics with individual-level data will facilitate a more holistic understanding of team performance. While detailed analysis of all tactical variations remains a challenge, future research should focus on collaborating with professional teams to identify and visualize key performance indicators (KPIs) in offensive and defensive phases. By optimizing high-quality collective movements through real-time feedback, this approach has the potential to provide transformative value not only to soccer but to the broader field of sports science.