This research introduces and puts into action a system for enhancing the audience experience at sports events through big data technology, with the goal of monitoring audience behavior in real-time and making dynamic adjustments by combining various modules including data collection, processing, analysis, and tailored recommendations. This system collects data on audience behavior at stadiums using sensor networks and social media platforms, then uses machine learning algorithms to analyze the data and anticipate audience interests and behavior. The system has been proven effective in various major sports events, as demonstrated by the application outcomes. By utilizing precise data analysis and personalized recommendation features, the system is able to enhance audience satisfaction, prolong their time at the venue, and lessen congestion during busy periods. The research results verify the significant effect of this system in optimizing the viewing experience, and provide new technical approaches for sports event management and audience experience improvement. The successful application of the system demonstrates the huge potential of big data technology in the sports field and provides an important reference for the organization and management of future sports events.