An approach for enhancing physical education analytics for college sports using AHP based MCDM algorithm integrated...

Area of Science:

• Sports Science
• Data Analytics
• Decision Science

Background:

• Physical education analytics are vital for assessing player growth, managing resources, and tracking performance.
• Traditional methods often neglect crucial factors like motor skills, teamwork, and mental toughness.
• Integrating data into decision-making frameworks is essential for optimizing athlete performance and resources.

Purpose of the Study:

• To introduce a novel multi-criteria decision-making (MCDM) framework for enhancing physical education analytics.
• To integrate the analytical hierarchy process (AHP) and MEREC methods within a spherical fuzzy (SF) context.
• To provide a robust system for informed decision-making in sports management and athlete development.

Main Methods:

• The study proposes a framework combining the analytical hierarchy process (AHP) and the Method on the Removal Effect of Criteria (MEREC).
• Spherical fuzzy sets (SFS) are utilized to handle uncertainty and imprecision in decision-making criteria.
• Pairwise comparisons of factors are evaluated to determine their relative importance within the decision framework.

Main Results:

• The proposed MCDM framework offers a robust and efficient method for evaluating factors in physical education analytics.
• The spherical fuzzy set (SFS) provides flexibility in representing human opinions through satisfaction, abstinence, and dissatisfaction levels.
• The framework facilitates more informed and comprehensive decision-making for coaches, managers, and instructors.

Conclusions:

• The integrated AHP and MEREC approach within the SF context enhances the reliability and efficiency of physical education analytics.
• Colleges can leverage this framework to make better decisions, leading to improved athletic performances and sustainable development.
• This research addresses the need for advanced data integration in sports science for optimized outcomes.