Analysis of the Competitive Activity Structure of Skilled Female Basketball Players
Keywords:
basketball, structure, technical and tactical activity, principal component analysis
Abstract
The study purpose was to examine, analyze, and generalize the competitive activity structure based on the hierarchy of technical and tactical indicators of skilled female basketball players in won and lost games using principal component analysis.
Materials and methods. The study participants were 96 professional female basketball players, members of national teams of Spain, France, Belgium, Greece, Turkey, Latvia, Italy, and Slovakia, which took the 1st-8th places in the final tournament of the European Basketball Championship 2017. The study analyzed 16 main technical and tactical indicators of skilled female basketball players in 52 official games to examine and interpret the obtained results using principal component analysis. The total number of observations is 52.
Results. The experimental indicators obtained during the study made it possible to examine and analyze the grouping of elements of the competitive activity structure of skilled female basketball players, to interpret the obtained results in order to define informative criteria for optimizing training and improving the competitive activity effectiveness. The study revealed considerable differences in the competitive activity structure in won and lost games: in accordance with the most significant indicators of factor loadings, the percentage of a sample of elements that correlate with one another is: for won games – 67.40%, for lost games – 69.52%.
Conclusions. Principal component analysis is quite effective and informative for studying the competitive activity structure of skilled female basketball players. It was demonstrated that the greatest difficulties in studying the competitive activity structure in basketball using principal component analysis are the selection of indicators that do not duplicate one another and are not calculated, expert interpretation of the obtained results, and algorithmization of special analysis of technical and tactical indicators.
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References
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https://doi.org/10.1080/17461390600676200
Scanlan, А., Dascombe, В., & Reaburn, Р. (2011). A comparison of the activity demands of elite and sub-elite Australian men's basketball competition. Journal of Sports Sciences, 29(11), 1153-1160. https://doi.org/10.1080/02640414.2011.582509
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Sporiš, G., Šango, J., Vučetić, V., & Mašina, T. (2006). The latent structure of standard game efficiency indicators in basketball. International Journal of Performance Analysis in Sport, 6(1), 120-129. https://doi.org/10.1080/24748668.2006.11868360
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Tao Zhang, Gongzhu Hu, & Qi Liao (2013). Analysis of offense tactics of basketball games using link prediction. 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS). https://doi.org/10.1109/ICIS.2013.6607842
Teck, K.К., Wang, C.K.J., & Mallett, C.J. (2012). Discriminating Factors between Successful and Unsuccessful Elite Youth Olympic Female Basketball Teams. International Journal of Performance Analysis in Sport, 12(1), 119-131. https://doi.org/10.1080/24748668.2012.11868588
Tyshchenko, V., Hnatchuk, Y., Pasichnyk, V., Bubela, O., & Semeryak, Z. (2018). Factor analysis of indicators of physical and functional preparation for basketball players. Journal of Physical Education and Sport, 18(4), 1839-1844. https://doi.org/10.7752/jpes.2018.s4269
Villa, G., & Lozano, S. (2018). Dynamic Network DEA approach to basketball games efficiency. Journal of the Operational Research Society, 69(11), 1738-1750. https://doi.org/10.1080/01605682.2017.1409158
Wei Yin (2014). Principal component factor analysis-based NBA player comprehensive ability evaluation research. Journal of Chemical and Pharmaceutical Research, 6(6), 2400-2405. http://www.jocpr.com/articles/principal-component-factor-analysisbased-nba-player-comprehensive-ability-evaluation-research.pdf
Calvo, J.L., García, А.М., & Navandar, А. (2017). Analysis of mismatch after ball screens in Spanish professional basketball. International Journal of Performance Analysis in Sport, 17(4), 555-562. https://doi.org/10.1080/24748668.2017.1367999
Cieślicka, M., Sobko, I., Ulaeva, L., Ishenko, O., Shepelenko, T., Tamozhanska, G., & Bugayets, N. (2019). Improving the protective technique of 13-14-year-old basketball players using rubber bands and unstable platforms. Journal of Physical Education and Sport, 19(3), 903-911. https://doi.org/10.7752/jpes.2019.s3130
Doroshenko, E., Sushko, R., Koryahin, V., Pityn, M., Tkalich, I., & Blavt, O. (2019). The competitive activity structure of highly skilled basketball players on the basis of factor analysis methods. Human Movement, 20(4), 33-40. https://doi.org/10.5114/hm.2019.85091
Ferreira, A.P., Volossovitch, А., & Sampaio, J. (2014). Towards the game critical moments in basketball: a grounded theory approach. International Journal of Performance Analysis in Sport, 14(2), 428-442. https://doi.org/10.1080/24748668.2014.11868732
Gryko, K., Mikołajec, К., Maszczyk, А., Cao, R., & Adamczyk, J. (2017). Structural analysis of shooting performance in elite basketball players during FIBA EuroBasket 2015. International Journal of Performance Analysis in Sport, 18(2), 380-392. https://doi.org/10.1080/24748668.2018.1479923
Jiang, Н. (2014). Research of Chinese men's basketball team development countermeasures based on the analytic hierarchy process. BioTechnology: An Indian Journal, 10(11), 4994-5003. https://www.tsijournals.com/articles/research-of-chinese-mens-basketball-team-development-countermeasures-based-on-the-analytic-hierarchy-process.pdf
Kawabata, М., & Mallett, C.J. (2012). Interpreting the Dispositional Flow Scale-2 scores: A pilot study of latent class factor analysis. Journal of Sports Sciences, 30(11), 1183-1188. https://doi.org/10.1080/02640414.2012.695083
Kozina, Z., Repko, O., Ionova, O., Boychuk, Y., & Korobeinikov, V. (2016). Mathematical basis for the integral development of strength, speed and endurance in sports with complex manifestation of physical qualities. Journal of Physical Education and Sport, 16(1), 70-76. https://doi.org/10.7752/jpes.2016.01012
Kozina, Z., Jagiello, W., & Jagiello, M. (2015). 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, 19(12), 41-50. https://doi.org/10.15561/18189172.2015.1207
Kozina, Z.L., Bazylyuk, Т.A., & Boyko, A.G. (2017). Analysis of the structure of the integrated preparedness of qualified handballers using multidimensional analysis methods. Health, sport, rehabilitation, 3(2), 15-24. http://dx.doi.org/10.34142/zenodo.1109904
Koryahin, V., Dutchak, M., Iedynak, G., Blavt, O., Galamandjuk, L., & Cherepovska, E. (2018). The technical and physical preparation of basketball players. Human Movement, 19(4), 29-34. https://doi.org/10.5114/hm.2018.77321
Križan, M., & Mikulič, M. (2018). Dependence of the Result on the Effectiveness of Performance in the World Women’s Handball Championship 2016. Theory and Methods of the Physical Education 18(2), 63-68. https://doi.org/10.17309/tmfv.2018.2.02
Kyrychenko, R., & Doroshenko, Е. (2006). Stady of the structure of technical and tactical activities of qualified basketball players by the method of main components. Pedagogics, psychology, medical-biological problems of physical training and sports, (5), 36-41.
Li, Y., Wang, X., Chen, Х., & Dai, В. (2015). Exploratory factor analysis of the functional movement screen in elite athletes. Journal of Sports Sciences, 33(11), 1166-1172. https://doi.org/10.1080/02640414.2014.986505
Liju, G. (2013). Statistical Analysis of Technical Characteristics of Eastern and Western Players in 2013 NBA All-star Game Based on MATLAB. Information Technology Journal, 12(16), 3612-3618. https://doi.org/10.3923/itj.2013.3612.3618
Makuts, T.B., & Vysochina, N.L. (2015). Factorial analysis of tennis players’ psychological and technical-tactic fitness at the stage of specialized basic training. Pedagogics, psychology, medical-biological problems of physical training and sports, 19(9), 45-50. https://doi.org/10.15561/18189172.2015.0907
Pluta, В., & Andrzejewski, М. (2018). Analysis of team sports results based on the European basketball men’s championships. Trends in Sport Sciences, 1(25), 21-27. https://doi.org/10.23829/TSS.2018.25.1-3
Okazaki, V.H.A., Rodacki, A.L.F., & Satern, M.N. (2015). A review on the basketball jump shot. Sports Biomechanics. 14(2), 190-205. https://doi.org/10.1080/14763141.2015.1052541
Sampaio, J., Janeira, М., Ibáñez, S., & Lorenzo, А. (2006). Discriminant analysis of game-related statistics between basketball guards, forwards and centres in three professional leagues. European Journal of Sport Science, 6(3), 173-178.
https://doi.org/10.1080/17461390600676200
Scanlan, А., Dascombe, В., & Reaburn, Р. (2011). A comparison of the activity demands of elite and sub-elite Australian men's basketball competition. Journal of Sports Sciences, 29(11), 1153-1160. https://doi.org/10.1080/02640414.2011.582509
Shepelenko, T., Kozina, Z., Cieślicka, M., Prusik, K., Muszkieta, R., Sobko, I., Ryepko, O., Bazilyuk, T., Polishchuk, S., Osiptsov, A., & Kostiukevych, V. (2017). Factor structure of aerobics athletes preparation. Pedagogics, psychology, medical-biological problems of physical training and sports, 21(6), 345-352. https://doi.org/10.15561/18189172.2017.0606
Simović S., Matković B., Mijanović M., Kocić M., & Vojvodić, M. (2012). Structure of efficiency factor at XIII, XIV, XV, and XVI World Championship in basketball. Journal of Human Sport and Exercise, 7(2), 527-543. https://doi.org/10.4100/jhse.2012.72.16
Sporiš, G., Šango, J., Vučetić, V., & Mašina, T. (2006). The latent structure of standard game efficiency indicators in basketball. International Journal of Performance Analysis in Sport, 6(1), 120-129. https://doi.org/10.1080/24748668.2006.11868360
Sushko, R., Vysochina, N., Vorobiova, А., Doroshenko, Е., Pastuhova, V., & Vysochin, F. (2019). Psychological selection in game sports on the basketball example. Journal of Physical Education and Sport, 19(3), Art. 250, 1708-1714. https://doi.org/10.7752/jpes.2019.03250
Tao Zhang, Gongzhu Hu, & Qi Liao (2013). Analysis of offense tactics of basketball games using link prediction. 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS). https://doi.org/10.1109/ICIS.2013.6607842
Teck, K.К., Wang, C.K.J., & Mallett, C.J. (2012). Discriminating Factors between Successful and Unsuccessful Elite Youth Olympic Female Basketball Teams. International Journal of Performance Analysis in Sport, 12(1), 119-131. https://doi.org/10.1080/24748668.2012.11868588
Tyshchenko, V., Hnatchuk, Y., Pasichnyk, V., Bubela, O., & Semeryak, Z. (2018). Factor analysis of indicators of physical and functional preparation for basketball players. Journal of Physical Education and Sport, 18(4), 1839-1844. https://doi.org/10.7752/jpes.2018.s4269
Villa, G., & Lozano, S. (2018). Dynamic Network DEA approach to basketball games efficiency. Journal of the Operational Research Society, 69(11), 1738-1750. https://doi.org/10.1080/01605682.2017.1409158
Wei Yin (2014). Principal component factor analysis-based NBA player comprehensive ability evaluation research. Journal of Chemical and Pharmaceutical Research, 6(6), 2400-2405. http://www.jocpr.com/articles/principal-component-factor-analysisbased-nba-player-comprehensive-ability-evaluation-research.pdf
Published
2020-12-25
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How to Cite
Doroshenko, E., Sushko, R., Shamardin, V., Prykhodko, V., Shapovalova, I., Yelisieieva, D., Demidova, O., & Yakovenko, A. (2020). Analysis of the Competitive Activity Structure of Skilled Female Basketball Players. Teorìâ Ta Metodika Fìzičnogo Vihovannâ, 20(4), 219-227. https://doi.org/10.17309/tmfv.2020.4.04
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