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    Technique characteristics of athletes aged 13–15 years specialized in race walking at the stage of preliminary basic preparation
    (Sport Science Spectrum, 2024) Bobrovnyk V. I.; Sovenko S. P.
    The analysis of the technique of performing a competitive exercise by athletes aged 13–15 years, who specialize in race walking at the stage of preliminary basic training is the basis for further optimization of technical training, both at this and the following stages of long-term improvement.The objective of the study was to determine the main kinematic characteristics of the technique of athletes specialized in race walking at the stage of preliminary basic training. Methods. The kinematic characteristics of the technique of 31 athletes (age – 14,68 years; S = 0,65) at a distance of 3 km at the championships of Ukraine in race walking 2016–2021, as well as the individual dynamics of these indices in two athletes at the stage of specialized basic preparation at a 10 km distance were analyzed. Results. To achieve the level of results at a distance of 3 km – 14:11 (S = 0:22), the average speed at the distance constitutes 3,53 m·s-1 (S = 0,09), stride length – 1,13 m (S = 0,05), stride frequency – 3,13 stride·s-1 (S = 0,12), the duration of the support phase – 0,289 s (S = 0,016), and that of flight – 0,032 s (S = 0,010). The knee joint angle during foot placement on support constituted 179,70º (S = 1,59), the angle of foot placement on support – 69.99º (S = 1,48), and the take-off angle – 60,78º (S = 1–34). Conclusions.The values of technique biomechanical characteristics of athletes aged 13–15 years at the stage of preliminary basic preparation reach high indices and approach those of junior and adult athletes of high national level at distances of 10 and 20 km, respectively. The age of 13–15 years for athletes who specialize in race walking is important for the formation of the basic elements of technique, namely the stride length and frequency and the main kinematic characteristics that affect their values, and should be taken into account when designing their process of technical preparation and long-term improvement strategy in general.
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    Characteristics of the technical action model for athletes specializing in race walking within the long-term development system
    (Journal of Physical Education and Sport, 2025) Sovenko S. P.; Vynohradov V. E.; Edeliev O. S.; Popov S. Y.
    At the current stage of sports development, technical training within the long-term improvement system for race walking athletes should involve clearly defined model characteristics of their technical actions. The integration of advanced modeling technologies, such as artificial neural networks, allows for the creation of effective and high-quality models that represent athletes' technical actions. Objective: To improve the technical preparation of track-and-field athletes specializing in race walking by identifying model characteristics of technical actions within a long-term preparation framework. Materials and Methods: Neural network modeling of the technical actions of athletes specializing in race walking was performed based on data from biomechanical analyses of competitive exercise techniques. This data was collected via video recordings during the 2014–2021 Ukrainian Race Walking Championships, as well as at the Association of Balkan Athletic Federations Championships and the international "Evening Ivano-Frankivsk" Cup, organized in conjunction with Ukraine’s national championships. The studies included male athletes from various age groups competing at distances of 3 km, 10 km, and 20 km. In total, 98 analyses were conducted: 31 at 3 km, 36 at 10 km, and 31 at 20 km. Results. A total of 26 biomechanical indices of athletes' techniques were analyzed. Correlation analysis identified 14 key biomechanical characteristics that significantly influence performance outcomes within the long-term development system. Using these characteristics, along with indices of body length and mass, neural network models were developed to simulate and predict athletic performance. Conclusions. Artificial neural networks enabled the creation of models for race-walking technical actions that support high-level performance in young athletes aged 13–15 years (3 km distance), boys aged 16–19 years (10 km distance), and elite athletes aged 20 years and older (20 km distance).