Evaluating athletic mental energy analysis: a novel approach using fuzzy-based Bayesian networks

Area of Science:

• Sports Science
• Performance Psychology
• Health and Fitness

Background:

• Athletes' mental energy is crucial for performance and health.
• Physical and psychological conditions significantly affect mental energy.
• Identifying the root causes of mental fatigue is essential.

Purpose of the Study:

• To evaluate the impact of physical and psychological conditions on athletes' mental energy.
• To identify the primary causes of mental fatigue in athletes.
• To develop a model for assessing these causes.

Main Methods:

• Development of a Fuzzy Bayesian Network (FBN) model.
• Probabilistic analysis of physical and psychological factors influencing mental energy.
• Weighting of causal factors for assessment by coaches and scientists.

Main Results:

• A model was developed to evaluate factors affecting athletic mental energy.
• Physical fitness (10.9%), fatigue (10.4%), and nutrient intake (10.2%) are the top three root causes.
• Factors affecting mental energy are closely linked to both physical and psychological states.

Conclusions:

• The FBN model provides a comprehensive probabilistic analysis of physical and psychological interactions.
• The model serves as a guide for identifying strategies to enhance athletes' mental energy.
• Physical condition variables are critical for improving athletes' mental energy.