Author(s)

Ruihui Dai

Corresponding Author

Ruihui Dai

Abstract

With the rapid development of Artificial Intelligence Generated Content (AIGC), its application has expanded beyond creative industries into fields requiring complex analysis and real-time decision-making. This study explores the integration of AIGC technology into basketball tactics analysis and decision-making. By leveraging multimodal data such as in-game images, trajectory tracking, and statistical indicators, the research constructs an intelligent modeling system capable of automatic tactical script generation, dynamic prediction, and real-time tactical assistance. Utilizing deep learning and natural language generation techniques, the system enhances tactical interpretation, simulates strategic development, and supports personalized decision-making during gameplay. The study aims to shift tactical analysis in basketball from experience-driven to data- and intelligence-driven models. Major innovations include an AIGC-based automated tactical modeling framework, a neural network-driven dynamic evolution simulation mechanism, and a real-time feedback system designed for in-game applications. This research offers a novel paradigm for the intelligent development of sports tactics, contributing theoretical and practical value to the field of AI-empowered competitive sports.

Keywords

AIGC; Basketball tactics; Intelligent decision-making; Deep learning; Tactical modeling; Real-time analysis; Sports technology