Data-Driven Optimization of Carbohydrate Intake for Enhanced Performance and Recovery in Sports Dance

Sports dance demands both high metabolic efficiency and precise nutritional support because of its combination of physical exertion and artistic performance. The author examined energy metabolism patterns in sports dance athletes and proposes a data-driven model to optimize carbohydrate intake on the basis of individual needs. Through experimental tracking and multidimensional analysis, the author evaluated the impact of dynamic dietary adjustments on energy utilization and recovery. The results demonstrated that the optimized carbohydrate intake model significantly enhanced metabolic efficiency, lactate clearance, and perceived performance, outperforming traditional intake strategies. By incorporating real-time feedback and adaptive regulation, this approach transcends static guidelines, better addressing athletes' fluctuating energy demands. The findings provide a scientific foundation for personalized nutrition in sports dance, highlighting the potential of data-informed dietary strategies to enhance both performance and recovery.