Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students' athletic performance and health management. However, existing literature primarily focuses on the technological implementation of intelligent physical education systems and lacks sufficient discussion on the behavioural motivations behind students' adoption of these systems. To address this study gap, this study designs a survey questionnaire based on the Technology Acceptance Model (TAM) and its six extended external variables: self-efficacy (SE), subjective norms (SN), technological complexity (TC), facilitating conditions (FC), knowledge acquisition (KA), and knowledge sharing (KS). This study aims to investigate the key factors that influence undergraduates' use of intelligent physical education systems, particularly in the context of rapid advancements in physical technology. The results indicate that ATU, PU, SE, and KS have direct effects on university students' BI to use intelligent physical education systems. Additionally, PEU, SN, KA, TC, and FC exert indirect effects on students' BI to engage with these systems. This study not only provides deep insights into the adoption factors of intelligent physical education systems for the academic community but also offers robust theoretical and practical support for the implementation of intelligent physical education systems in higher education institutions. Furthermore, the results will serve as a crucial reference for policymakers and educational technology developers, aiding them in better understanding and promoting the application and widespread adoption of intelligent physical education systems in higher education.