Economic-mathematical modeling and instrumental methods for improving efficiency of sports reserve training

The article addresses issues of increasing the economic efficiency for the sports reserve training. Young athletes are viewed as valuable assets, and the training process as an optimizing investment project. Aim. The objective is to develop an economic and mathematical model increasing the human capital return on investment (HCROI) through personalizing training management. Materials and methods. Cluster analysis is used as an investigation method. Results. The K-means clustering algorithm has effectively grouped 103 athletes, who met 15 objective parameters, into two homogeneous groups. Analysis of variance (ANOVA) confirmed significant differences between the groups, allowing them to be interpreted as two types of assets with different potential and risks. For each cluster are developed differentiated management strategies (training programs) aimed at maximizing their "value" (athletic potential) and minimizing risks (injuries, dropout). Conclusion. The study shows that mathematical models facilitate the transition from intuitive to scientific management of sports assets, thereby improving the overall performance of sports organizations.