Identify patterns of individual dynamics of competitive performance of athletes as a basis for predicting results (qualified basketball players for example)

Z.L. Kozina, S.A. Gushchin, D.V. Safronov, S.B. Khrapov, Yu.K. Vasilyev

Abstract


The aim of the work wos to develop an algorithm and determine the patterns of the individual dynamics of the competitive performance of qualified basketball players.

Material and methods. The study involved the players of the main composition of the men's basketball team of Ukraine. It was analyzed 12 games of the national team of Ukraine in games with equal rivals - teams of other countries. The research was conducted from June 2018 to September 2018. Technical logging of games, which was carried out using a modified formula of Yu.M. Portnov. Mathematical modeling was used to describe the patterns of individual dynamics of competitive performance using sinusoidal regression models.

Results. The process of changing competitive performance should be considered in terms of oscillatory processes. The most acceptable function to describe this pattern is the sinusoidal function. The regression model of the individual dynamics of the effectiveness of competitive activity of the players of the Ukrainian basketball national team obeys a sinusoidal relationship, which is described by the sinusoidal regression equation.

Conclusions. The data obtained may be useful for predicting the individual game performance of athletes, determining the individual characteristics of players and adjusting training programs

Keywords


basketball; dynamics; game; effectiveness; function; sinewave; individualization

Full Text:

PDF

References


Aphorisms, quotes and popular words. Access mode: http://aphorism-list.com/autors.php?page=belinskiy&tkautors=belinskiy. In Russian

Bondarenko AV. Refinement of the sales forecasting algorithm. [Electronic resource]. Access mode: http://www.cfin.ru/finanalysis/math/add_to_kosh.shtml. In Russian

Zaginaylo IV. Periodic trend lines in forecasting sales [Electronic resource]. Access mode: http://www.cfin.ru/finanalysis/math/add_to_kosh-bond.shtml. In Russian

Koshechkin SA. Algorithm for forecasting sales in MS Excel. [Electronic resource]. Access mode: http://www.cfin.ru/finanalysis/sales_forecast.shtml. In Russian

Matveyev LP, Hasanova FOR Testing a single hypothesis and commenting on it in the aspect of the theory and practice of sports. Theory and Practice nat. culture. 2001; 5: 2-11. In Russian

Kozina Z. Factor models of the physical preparedness of volleyball players of a high class of various game role. Pedagogy, Psychology and medical and biological problems of physical education and sport, 2007;9: 80-85.

Kozina ZL, Cieslicka M, Prusik K, Muszkieta R, Sobko IN, Ryepko OA, Bazilyuk TA, Polishchuk SB, Osiptsov AV, Korol SA. Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball). Physical education of students. 2017;21(5):225-238http://dx.doi.org/10.15561/20755279.2017.0505

Platonov VN. The general theory of training athletes in the Olympic sport. K .: Olympic literature, 1997: 584. In Russian

Platonov VN. Periodization of sports training. General theory and its practical applications. K.: Olympic literature, 2013: 624 p. In Russian

Dykyi BV, Ilko AV. Having infused young-sonic rhythms to the human health camp. Science Bulletin of Uzhgorod University. Ser .: Medicine, 2001;16:107-112. In Ukrainian

Kozina ZhL, Voskoboinik AС, Grin LV. Application of methods of multidimensional and nonlinear regression analysis to reveal the laws of individual dynamics of competitive performance in basketball. Health, sport, rehabilitation. 2015;1:40-42. In Russian

Kozina ZL, Jagiello Wladyslaw, Jagiello Marina. Determination of sportsmen’s individual characteristics with the help of mathematical simulation and methods of multi-dimensional analysis. Pedagogics, psychology, medical-biological problems of physical training and sports, 2015;12:41–50. http://dx.doi.org/10.15561/18189172.2015.120

Kozina Zh.L., Prokopenko I.F., Cretu M., Chebanu O.I., Ryepko O.A., Osiptsov A.V., Razumenko T.O. Individual chronobiological regularity in track-and-field sprint. Pedagogics Psychology Medical-Biological Problems of Physical Training and Sports. 2018, 22(3). https://sportpedagogy.org.ua/index.php/PPS/pages/view/next

U-Journal: Time and life as a form of oscillatory process. [Internet site]. Access Mode: http://www.u-journal.com/sections/time/1(7)/10/. In Russian

Kozina ZhL, Zaschuk SG, Grin LV, Conformities to law individual dynamics of playing effectiveness of basketball-players of collapsible command of Ukraine. Physical Education of Students. 2010;1:52 - 56.

Kozina Zh.L., Ol’khovyj O.M., Temchenko V.A. Influence of information technologies on technical fitness of students in sport-oriented physical education. Physical education of students, 2016;1:21–28. http://dx.doi.org/10.15561/20755279.2016.0103

Ali G. Loads of Training Geared to the Pattern of Daily BioRhythm on Some Vital Functions and Development of 800-meter Runners. World Journal of Sport Sciences. 2010; 3 (S): 1250–1254.

Araujo LG. Waterhouse J., Edwards B. Henrique E., Santos R., Tufik S., Túlio de Mello M. Twenty-four-hour rhythms of muscle strength with a consideration of some methodological problems. Biological Rhythm Research. 2011; 42(6): 473–490.

Bardis K, Atkinson G. Effects of time of day on power output and thermoregulation responses during cycling. Biology of exercise. 2008; 4:17–28.

Hines TM. Comprehensive review of biorhythm theory. Psychology Department, Pace University, Pleasantville, NY. Psychol Rep. 1998 Aug;83(1):19–64

Shaffer JW., Schmidt CW., Zlotowitz HI., Fisher RS. Biorhythms and Highway Crashes. Are They Related? Arch Gen Psychiatry. 1978;35(1):41-46.

Bessot N, Moussay S, Clarys JP, Gauthier A, Sesboüé B, Davenne D. The influence of circadian rhythm on muscle activity and efficient force production during cycling at different pedal rates. J. Electromyogr. Kinesiol. 2007; 17: 176–183.

Chaâri N, Frikha M, Mezghanni N. Time-of-day and warm-up durations effects on thermoregulation and anaerobic performance in moderate conditions. Biological Rhythm Research. 2013; 10: 46-49.

Sokolova VS, Dvornikov PA. Biorithms and their influence on the effectiveness of the training process and the results of competitions of the competition-biathlonists // Modern problems of science and education. 2015; 4:36-42.

Shafiee S, Rahim R, Hakime A, Vahid R. The relationship between biorhythm (physical cycle) and sports performance in women’s basketball. Physical education of students, 2016;3:58–64. doi:10.15561/20755279.2016.030

Pandey A, Gulati S, Gupta A, Tripathi Y. Variation in andrographolide content among different accessions of Andrographis paniculata. The Pharma Innovation Journal, 2019;8(4):140-144.

Tripathi P, Tripathi Y. Physicochemical and Nutritional Evaluation of Rhus pariviflora Fruits - A Relish Wild Edible of Uttarakhand. 2019. 10.13140/RG.2.2.19454.64328.




DOI: http://dx.doi.org/10.34142/HSR.2019.05.02.04

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Health, sport, rehabilitation

License Creative Commons BY