Building Tomorrow's Champions: A Vision for Olympic Education at the School Level through Virtual Foresight and Sport-Specific Fitness Profiling - Aidyn Doshybekov; Marfuga Absatova; Kurimbayev Yerzhigit; Baglan Yermakhanov; Kopzhanov Galymzhan; Bekir Car (Retos: Nuevas Tendencias en Educación Física, Deportes y Recreación)
The aim of this study is to determine the sport-specific fitness profile with the virtual prediction method and to contribute to the determination of tomorrow's champions with the Olympic Training Module carried out in primary school. In this context, 97 (53 boys, 44 girls) primary school students aged between 10-11 (years) participated in the study. The participants were tested for reaction time, hand grip strength, standing long jump, 30 m sprint, medicine ball throwing and hitting the target at a distance of 5 meters. After all tests were performed, the test results were classified as good (1), fair (2) and poor (3) according to gender. The accuracy between all classifications and performance tests was analyzed with MATLAB 2022B application. Accordingly, male participants' reaction time was 94.34%, handgrip strength 98.11%, standing long jump 100%, 30 m sprint 98.11%, medicine ball throwing 94.34%, and hitting the target from a distance of 5 meters were classified with 100% accuracy. Reaction time of female participants was 95.45%, handgrip strength 100%, standing long jump 100%, 30 m sprint 97.73%, medicine ball throwing 97.73%, and hitting the target from 5 meters distance with 100% accuracy. In addition, performance parameters were significantly different between the groups (p<.001). As a result, it was determined that performance classification using machine learning modeling was performed with great accuracy. Therefore, the results of our research can be used in talent selection and guidance of individuals of this age to the appropriate sports branch.