Accesso libero

Principal Component Analysis in the Study of the Structure of Decathlon at Different Stages of Sports Career

INFORMAZIONI SU QUESTO ARTICOLO

Cita

1. Quercetani R. (2000). Athletics: a history of modern track and field athletics: men and women (1860-2000). Mediolan: SEP Editrice. Search in Google Scholar

2. Shuravetzky E. (2008). Decathlon: An outline of the Australian coaching program. Modern Athlete and Coach 46(4), 25-28. Search in Google Scholar

3. Tidow G. (2000). Challenge Decathlon – Barriers on the way to becoming the ‘King of Athletes’. New Studies in Athletics 15(2), 43-52. Search in Google Scholar

4. Edouard P., Mori J.B., Samozino P. (2013). Maximal lower extremity power output changes during a decathlon. New Studies in Athletics 28(3/4), 19-37. Search in Google Scholar

5. Schrader A. (2011). One discipline after another. Leichtathletiktraining 2, 46-53. [in German] Search in Google Scholar

6. Vana Z. (2003). The training of the best decathletes. New Studies in Athletics 18(4), 15-30. Search in Google Scholar

7. Hymans R., Matrahazi I. (2015). Progression of world best performances and IAAF approved world records. International Amateur Athletic Federation. Search in Google Scholar

8. Poliszczuk W.D. (2001). Decathlon. Naukowyj Swit. [in Russian] Search in Google Scholar

9. Bilić M., Balić A. (2015). Types of discipline decathlon functional dependences in relation to age and level of score achievements of the world most successful decathlons. Sport Science 8, 52-56. Search in Google Scholar

10. Bilić M., Smajlovic N., Balić A. (2015). Contribution to discipline decathlon total score results in relation to decathlon age and result level. Acta Kinesiologica 9(1), 66-69. Search in Google Scholar

11. Kabitsis C., Harahousou Y., Kioumourtzoglou E. (1992). A study on the best junior decathletes performances. Physical Education Review 15(2), 157-162. Search in Google Scholar

12. Wimmer V., Fenske N., Pyrka P., Fahrmeir L. (2011). Exploring competition performance in decathlon using semi-parametric latent variable models. Journal of Quantitative Analysis in Sports 7(4), 1-19.10.2202/1559-0410.1307 Search in Google Scholar

13. Stemmler M., Baumler G. (2005). The detection of types among decathletes using Configural Frequency Analysis (CFA). Psychology Science 47(3/4), 447-466. Search in Google Scholar

14. Pavlović R., Idrizović K. (2017). Factor analysis of world record holders in athletic decathlon. Sport Science 10(1), 109-116. Search in Google Scholar

15. Bilić M. (2015). Determination of taxonomic type structures of top decathlon athletes. Acta Kinesiologica 9(Suppl. 1), 20-23. Search in Google Scholar

16. Ertel S. (2011). Exploratory factor analysis revealing complex structure. Personality and Individual Differences 50, 196-200. DOI: 10.1016/j.paid.2010.09.026 Open DOISearch in Google Scholar

17. Woolf A., Ansley L., Bidgood P. (2007). Grouping of decathlon disciplines. Journal of Quantitative Analysis in Sports 3(4). DOI: 10.2202/1559-0410.1057 Open DOISearch in Google Scholar

18. Heazlewood T., Gahreman D., Lee J. (2014). The factor structure of the decathlon and heptathlon: implications for training strength, power, speed and endurance. Journal of Australian Strength and Conditioning 22(5), 161-166. Search in Google Scholar

19. Park J., Zatsiorsky V.M. (2011). Multivariate statistical analysis of decathlon performance results in Olympic athletes (1988-2008). International Journal of Sport and Health Sciences 5(5), 779-782. Search in Google Scholar

20. Chen C., Zhan B. (2017). Development trend of world men decathlon scores BP neural network analysis. 2016 National Convention on Sports Science of China, 01040. DOI: 10.1051/ncssc/201701040 Open DOISearch in Google Scholar

21. World Athletics (2020). Stats zone. Retrieved 1 November, 2020 from: https://www.worldathletics.org/stats-zone. Search in Google Scholar

22. Salmistu J. (2019). World decathlon rankings 1965-2018. Retrieved 9 November, 2020 from: http://www.decathlon2000.com. Search in Google Scholar

23. Matthews P. (2013). Athletics 2013: The international track and field annual. York: SportsBooks. Search in Google Scholar

24. Van Kuijen H. (1998). 1997 Annual Combined Events. Helmond. Search in Google Scholar

25. Constantin C. (2014). Principal component analysis – A powerful tool in computing marketing information. Bulletin of the Transilvania University of Brasov. Series V: Economic Sciences 7(56), 25-30. Search in Google Scholar

26. Hadi N.U., Abdullah N., Sentosa I. (2016). An easy approach to exploratory factor analysis: Marketing perspective. Journal of Educational and Social Research 6(1), 215-215. DOI: 10.5901/jesr.2016.v6n1p215 Open DOISearch in Google Scholar

27. Abdi H., Williams L.J. (2010). Principal component analysis. WIREs Computational Statistics 2(4), 433-459. DOI: 10.1002/wics.101 Open DOISearch in Google Scholar

28. Bishop C.M. (2006). Pattern recognition and machine learning. New York: Springer. Search in Google Scholar

29. Härdle W.K., Simar, L. (2015). Applied multivariate statistical analysis. New York: Springer.10.1007/978-3-662-45171-7 Search in Google Scholar

30. James G., Witten D., Hastie T., Tibshirani R. (2013). An introduction to statistical learning. New York: Springer.10.1007/978-1-4614-7138-7 Search in Google Scholar

31. Kassambara A. (2017). Practical guide to principal component methods in R: PCA, M (CA), FAMD, MFA, HCPC, facto-extra. STHDA. Search in Google Scholar

32. R Core Team. (2020). R: A language and environment for statistical computing. Technical report, R Foundation for Statistical Computing, Vienna, Austria. Search in Google Scholar

33. Dziadek B., Iskra J., Przednowek K. (2016). The development of the sports careers of the best decathletes in the world and in Poland in the years 1985-2015. Polish Journal of Sport and Tourism 23(1), 7-13. DOI: 10.1515/pjst-2016-0002 Open DOISearch in Google Scholar

34. Edelmann-Nusser J., Hohmann A., Henneberg B. (2002). Modeling and prediction of competitive performance in swimming upon neural networks. European Journal of Sport Science 2(2), 1-10. DOI: 10.1080/17461390200072201 Open DOISearch in Google Scholar

35. O’Donoghue P. (2008). Principal components analysis in the selection of key performance indicators in sport. International Journal of Performance Analysis in Sport 8(3), 145-155. 10.1080/24748668.2008.1186845610.1080/24748668.2008.11868456 Search in Google Scholar

36. Lago-Ballesteros J., Lago-Peñas C. (2010). Performance in team sports: Identifying the keys to success in soccer. Journal of Human Kinetics 25, 85-91.10.2478/v10078-010-0035-0 Search in Google Scholar

37. Parma N., James N., Hearne G., Jones B. (2018). Using principal component analysis to develop performance indicators in professional rugby league. International Journal of Performance Analysis in Sport 18(6), 938-949. DOI: 10.1080/24748668.2018.1528525 Open DOISearch in Google Scholar

38. TIBCO Software Inc. (2020). Data Science Textbook. Retrieved 11 November 2020, from: https://docs.tibco.com/data--science/textbook. Search in Google Scholar

39. Jackson D.A. (1993). Stopping rules in principal components analysis: a comparison of heuristical and statistical approaches. Ecology 74(8), 2204-2214. DOI: 10.2307/1939574 Open DOISearch in Google Scholar

40. Makaruk H., Porter M., Starzak M., Szymczak E. (2016). An examination of approach run kinematics in track and field jumping events. Polish Journal of Sport and Tourism 23(2), 82-87. DOI: 10.1515/pjst-2016-0009 Open DOISearch in Google Scholar

41. Petrov V. (2004). Pole vault-the state of the art. New Studies in Athletics 19(3), 23-32. Search in Google Scholar

42. Gudelj I., Zagorac N., Babić V. (2013). Influence of kinematic parameters on pole vault results in top juniors. Collegium Antropologicum 37(Suppl. 2), 25-30. Search in Google Scholar

43. Dapena J. (2000). The high jump. In V.M. Zatsiorsky (ed.), Biomechanics in Sport. Oxford: Blackwell Science Ltd. Search in Google Scholar

44. Isolehto J., Virmavirta M., Kyrolainen H., Komi P. (2007). Biomechanical analysis of the high jump at the 2005 IAAF World Championships in Athletics. New Studies in Athletics 22(2), 17-27. Search in Google Scholar

45. Čoh M., Iskra J. (2012). Biomechanical studies of 110 m hurdle clearance technique. Sport Science 5(1), 10-14. Search in Google Scholar

eISSN:
2082-8799
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Medicine, Clinical Medicine, Public Health, Sports and Recreation, other