A Recursive IndetermTree Soft Set (RIT-Soft Set) for Dynamic and Uncertain Performance Evaluation in College Competitive Sports

Abstract

This paper introduces the Recursive IndetermTree Soft Set (RIT-Soft Set), a novel 
extension of Soft Set Theory designed for performance evaluation in dynamic and uncertain 
environments. Unlike conventional models, RIT-Soft Set incorporates recursive logic and 
supports hierarchical structures with embedded indeterminacy, allowing flexible representation 
of interdependent and evolving attributes.  The model is particularly useful in domains where 
performance is context-dependent, and data may be incomplete or ambiguous  such as university
level competitive sports. RIT-Soft Set enables recursive feedback within attribute trees, permitting 
deeper insight into athlete performance by allowing low-level data to influence higher-level 
assessments dynamically. 
A case study on a collegiate football team illustrates the practical application of the model, 
demonstrating how it can effectively manage multi-level evaluations involving physical, tactical, 
and psychological dimensions. The results show that the RIT-Soft Set provides greater 
interpretability and adaptability compared to flat or deterministic models. 
This framework opens avenues for developing decision-support systems that reflect real-world 
complexity and uncertainty, with potential for application beyond sports, in areas such as 
behavioral analysis and adaptive learning environments.

DOi: 10.5281/zenodo.15399374