Innovative vector of development in sports science (based on materials from the XII international congress ‘Sports, people, health,’ Saint Petersburg, 2025)

Abstract

Objective of the study is to identify key factors associated with improving the effectiveness of athlete training. The objectives of the study include evaluating information resources aimed at accelerating the growth of athletic skills and identifying the most common training problems.

Methods and structure of the study. The methodological design of the research ensures an internal consistent relationship between the recorded parameters and the adjustment of functional states and the growth of athletic achievements. In assessing the operational profitability of R&D, the processes of digital transformation of training implemented with the help of artificial intelligence technologies (P. Bordovsky, E. Kosmina, I. Manzheley, P. Petrov, I. Polikanova, G. Ponomarev, E. Sabaeva, A. Shukaeva, Luo Ran) are indicative.

Results and conclusions. The research is dialectically adequate in terms of achieving maximum values through diversification of resources and technological management. New opportunities are opening up with the use of artificial intelligence (AI) algorithms, big data and cloud computing. It has been shown that the use of generative-competitive methods and deep learning technologies allows analysing the effectiveness of load parameter regulation (speed, pace, power) based on physiological shifts within the ‘control-effect’ limits.