In modern sports simulation modeling, the integration of human decision-making processes and physiological data has become imperative for capturing the intricacies of athlete performance. This paper proposes a novel approach titled "Deciphering Performance," which aims to bridge the gap between human decision-making and physiological responses within sports simulations. By combining insights from cognitive science, biomechanics, and data analytics, this integrated model offers a comprehensive framework for understanding and predicting athlete behavior and performance outcomes. Through the synthesis of qualitative decision-making factors and quantitative physiological markers, sports simulations can achieve heightened realism and accuracy, empowering coaches, analysts, and athletes with valuable insights for training, strategy development, and performance optimization.