2018, Volume 10, Issue 2

Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming



Wojciech Rejdych1, Aleksandra Filip2, Jakub Karpiński1, Magdalena Krawczyk2, Jakub Jarosz2, Teresa Socha1, Adam Maszczyk2

1Department of Individual Sports, The Jerzy Kukuczka Academy of Physical Education in Katowice
2Department of Statistics and Methodology, The Jerzy Kukuczka Academy of Physical Education in Katowice


Author for correspondence: Magdalena Krawczyk; Department of Statistics and Methodology, The Jerzy Kukuczka Academy of Physical Education in Katowice; email: magda.aneta.krawczyk@gmail.com

DOI: 10.29359/BJHPA.10.2.03

Full text

Abstract

Background. General availability of sports results, such as current world records, world rankings, and results of the Olympic Games, offers opportunities for the analysis variation in many different competitions and sports. Current trends in the progress in sports performance have been analysed based on e.g. freestyle swimming. The focus of this study is on the analysis of variability of sports results in swimming achieved by women and men in 11 Olympic Games in 1972-2012.

Material and Methods. The analysis was based on the results of top eight finalists in all four events. Four 100m sprinting events (men's and women's) included in the program of the Olympic Games (freestyle, backstroke, breaststroke and butterfly swimming) were analysed.

Results. The analyses showed that a statistically significant difference in women's real and model results was found for the most recent Olympics in Rio de Janeiro in 2016 for the 100m breaststroke swimming.

Conclusions. The predicted results suggest that during the next Olympic Games in Tokyo, dynamics of progress in women's results is likely to be faster compared to men in three discussed events: 100m breaststroke, 100m butterfly and 100m backstroke. The above trend may not be observed in these events. Therefore, future research studies should be aimed to verify this tendency and the dynamics of progress in the results in breaststroke, backstroke    and butterfly stroke.     


Key words: swimming, sport performance, Olympic Games, sport prediction, ANN, time series


Cite this article as:

AMA:

Rejdych W, Filip A, Karpiński J et al. Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming. Balt J Health Phys Activ. 2018;10(2):25-33. doi:10.29359/BJHPA.10.2.03

APA:

Rejdych, W., Filip, A., Karpiński, J., Krawczyk, M., Jarosz, J., & Socha, T. et al. (2018). Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming. Balt J Health Phys Activ, 10(2), 25-33. https://doi.org/10.29359/BJHPA.10.2.03

Chicago:

Rejdych, Wojciech, Filip Aleksandra, Karpiński Jakub, Krawczyk Magdalena, Jarosz Jakub, Socha Teresa, and Maszczyk Ad. 2018. "Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming". Balt J Health Phys Activ 10 (2): 25-33. doi:10.29359/BJHPA.10.2.03

Harvard:

Rejdych, W., Filip, A., Karpiński, J., Krawczyk, M., Jarosz, J., Socha, T., and Maszczyk, A. (2018). Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming. Balt J Health Phys Activ, 10(2), pp.25-33. https://doi.org/10.29359/BJHPA.10.2.03

MLA:

Maszczyk, Adam et al. "Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming." Balt J Health Phys Activ, vol. 10, no. 2, 2018, pp. 25-33. doi:10.29359/BJHPA.10.2.03

Vancouver:

Rejdych W, Filip A, Karpiński J et al. Dynamics of variation of sports performance in light of Time Series based on Artificial Neural Networks in swimming. Balt J Health Phys Activ 2018; 10(2): 25-33. Available from: doi:10.29359/BJHPA.10.2.03