[
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.
]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
