Hybrid learning in football education combines traditional face-to-face instruction with ICT-enhanced online learning, using quadruple quadrants and flip learning. Emerging nations like India need this method due to high transportation costs and time-consuming commuting. Utilizing digital tools improves sports education. The use of game-based learning and ICT-based learning in sports education is crucial for promoting sports mindfulness and achieving high instructional standards. This approach attracts rivals and fosters long-term athlete collaboration. It also challenges traditional learning by offering online resources outside the study hall, allowing flexible application of strategic knowledge without compromising educational benefits. This study focuses on football tactical analysis using semantic mining to identify teams' strengths and weaknesses. Utilizing a sophisticated Bayesian belief network, this innovative approach aims to meticulously analyze and derive attack and defense scenarios from meticulously curated pre-recorded match videos within the realm of football. The systematic methodology involves the classification of various shots and replay scenes, the extraction of vital audiovisual components, and the seamless identification of transitional moments from defense to attack, all achieved through the implementation of advanced heuristic algorithms. This in-depth study seeks to scrutinize and evaluate the effectiveness and significance of these transitional instances within the domain of football education, shedding light on their potential impact and relevance in enhancing tactical understanding and strategic decision-making processes and enhancing the overall-understanding of dynamic gameplay sequences.