Optimization Pathways and Empirical Study of Public Sports Facilities Based on Big Data

With the rise of big data technology and the “Healthy China” strategy, optimizing public sports facility utilization has become key to promoting public health. This study builds a closed-loop model of “data-driven–efficiency improvement–health transformation” through multi-source data collection, demand forecasting, dynamic scheduling, and spatial optimization. Using City A as a case, results show that weekday off-peak utilization increased from 29% to 68%, the variance of spatiotemporal use fell to 0.18, and 15-minute fitness-circle coverage increased by 25 points. Participation among health-vulnerable groups grew by 29 points, while exercise-intensity-based interventions reduced injury rates by 69% and boosted adherence by 37%. Findings show how big data can turn facilities into dynamic health-promotion systems that deliver social and economic gains. However, challenges remain in data representativeness, cost-benefit balance, and health effect attribution.