ADAPTIVE MULTICRITERIA MODEL FOR SUPPORTING DECISION-MAKING IN SPORTS SELECTION PROBLEMS - HNATCHUK, Alina; HNATCHUK, Yaroslav (Computer systems and information technologies, 2026)
In the current environment of information technology development, intelligent data analysis, and decision support systems, there is a need to formalize and automate sports selection processes. Existing models of multi-criteria assessment of athletes are usually static in nature and focused only on analyzing the current level of preparedness, which limits their effectiveness in selecting young candidates for whom development potential is important. This paper proposes an adaptive multi-criteria decision support model that integrates the assessment of the current level of candidates’ characteristics with formalized consideration of their development dynamics over time. A mathematical apparatus for forming an integral assessment of prospects has been developed, based on the hierarchical aggregation of normalized indicators and the application of the hierarchy analysis method to determine weight coefficients. For the first time, a generalized characteristic indicator has been introduced, which combines normalized indicator values and the rate of their change, allowing not only current results but also development prospects to be assessed. An experimental study on a sample of 24 candidates showed a heterogeneous structure of the distribution of integral assessments, which confirms the feasibility of using adaptive thresholds to classify candidates according to their level of prospects. The sensitivity of the model to changes in the α parameter, which allows adjusting the balance between current indicators and development dynamics, was analyzed. The results confirmed the stability of the model and the consistency of the overall ranking structure of candidates when changing weight parameters. The proposed model ensures transparency, reproducibility, and interpretability of the assessment, which makes it suitable for use in intelligent decision support systems for the selection of young athletes. The practical benefit of the model is that it allows coaches and sports selection specialists to effectively and objectively identify candidates with high development potential, taking into account both their current level of preparedness and the dynamics of their characteristics. The model can be integrated into intelligent decision support systems for planning the training process and strategically forming teams of young athletes.