<bold>Introduction</bold>. This essay introduces an innovative high jump technique modeling method that uses a cascaded fuzzy neural network. An interactive system for the prediction of the success of a high jump has been designed based on this method and it allows the creation of an individual model for highly skilled athletes to control the jumper's technical training. <bold>Material and methods</bold>. The research material included a video recording of 92 high jumps and analysis by 48 kinematic characteristics. The result allowed the fine tuning of the cascaded fuzzy neural network model in order to analyse successful and failed jumps. <bold>Results and conclusions</bold>. We have developed the interactive system based on the analysis of kinematic characteristics of the high jump and this allows individual performance models to be tailored for elite athletes. With the help of this instrument, which takes into account the individual biomechanical features of an athlete's jumping style, we can analyze all stages of a jump in detail, improve the technique through the targeted correction of specific motions and achieve the optimal combination of kinematic values for the best possible result.
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