文章基本信息

标题：Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball)
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作者：Kozina Zh.L ; Kozina Zh.L ; Cieslicka M 等
期刊名称：Physical Education of Students
电子版ISSN：2308-7250
出版年度：2017
卷号：21
期号：5
页码：225-238
DOI：10.15561/20755279.2017.0505
语种：English
出版社：H.S. Skovoroda Kharkov National Pedagogical University
摘要：to determine main laws of determination of athletes’ fitness structure’s individual characteristics with the help of multidimensional analysis (on example of basketball). Material: in the research elite basketball players (n=54) participated. Pedagogic testing included 12 tests, applied in combined teams of Ukraine and Russia. For every test three attempts were given and the best result was registered. The tests were passed during 2-3 training sessions. Results: we worked out general scheme of ways of athletes’ training individualization. For every athlete we determined the groups of leading and secondary factors in individual structure of fitness. The process of athletes’ training shall contain basic and variable components. Basic component was 70% of means in general system of athletes’ training. Variable component was 30% of means and implies application of individual training means. Percentage of means in individual programs varies depending on the following: leading factors in fitness individual structure; period of individual dynamic of competition efficiency. In every micro-cycle 30% is assigned for athletes’ individual training: athletes received individual tasks; groups on the base of cluster analysis data were formed, if necessary. Conclusions: when working out individual training programs, development of leading factors in individual factorial structure of athletes’ fitness shall be accented. Application of individual programs, combined with universal individualization methods creates preconditions for rising competition activities’ efficiency.
关键词：structure; sports; individual approach; algorithm; basketball; factorial; cluster; analysis