Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000 to 2017


Autoři: Radivoj Mandić aff001;  Saša Jakovljević aff001;  Frane Erčulj aff002;  Erik Štrumbelj aff003
Působiště autorů: University of Belgrade, Faculty of Sport and Physical Education, Belgrade, Serbia aff001;  Faculty of Sports, University of Ljubljana, Ljubljana, Slovenia aff002;  Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223524

Souhrn

We analyse and compare NBA and Euroleague basketball through box-score statistics in the period from 2000 to 2017. Overall, the quantitative differences between the NBA and Euroleague have decreased and are still decreasing. Differences are even smaller after we adjust for game length and when playoff NBA basketball is considered instead of regular season basketball. The differences in factors that contribute to success are also very small—(Oliver’s) four factors derived from box-score statistics explain most of the variability in team success even if the coefficients are determined for both competitions simultaneously instead of each competition separately. The largest difference is game pace—in the NBA there are more possessions per game. The number of blocks, the defensive rebounding rate and the number of free throws per foul committed are also higher in the NBA, while the number of fouls committed is lower. Most of the differences that persist can be reasonably explained by the contrasts between the better athleticism of NBA players and more emphasis on tactical aspects of basketball in the Euroleague.

Klíčová slova:

Entropy – Europe – Games – Regression analysis – Sports – Statistical data – Statistical models – Team behavior


Zdroje

1. Lorenzo A, Gómez MÁ, Ortega E, Ibáñez SJ, Sampaio J. Game related statistics which discriminate between winning and losing under-16 male basketball games. Journal of sports science & medicine. 2010;9(4):664.

2. Oliver D. Basketball on paper: rules and tools for performance analysis. Potomac Books, Inc.; 2004.

3. Akers MD, Wolff S, Buttross TE. An empirical examination of the factors affecting the success of NCAA Division I College Basketball teams. Journal of Business and Economic Studies. 1992.

4. Csataljay G, O’Donoghue P, Hughes M, Dancs H. Performance indicators that distinguish winning and losing teams in basketball. International Journal of Performance Analysis in Sport. 2009;9(1):60–66. doi: 10.1080/24748668.2009.11868464

5. Gómez MA, Lorenzo A, Barakat R, Ortega E, José M P. Differences in game-related statistics of basketball performance by game location for men’s winning and losing teams. Perceptual and motor skills. 2008;106(1):43–50. doi: 10.2466/pms.106.1.43-50 18459354

6. Hofler RA, Payne JE. Measuring efficiency in the National Basketball Association1. Economics letters. 1997;55(2):293–299. doi: 10.1016/S0165-1765(97)00083-9

7. Ibáñez SJ, Sampaio J, Feu S, Lorenzo A, Gómez MA, Ortega E. Basketball game-related statistics that discriminate between teams’ season-long success. European journal of sport science. 2008;8(6):369–372. doi: 10.1080/17461390802261470

8. Ittenbach RF, Esters IG. Utility of team indices for predicting end of season ranking in two national polls. Journal of Sport Behavior. 1995;18(3):216.

9. Ittenbach RF, Kloos ET, Etheridge JD. Team Performance and National Polls: The 1990–91 Ncaa Division I Basketball Season. Perceptual and Motor Skills. 1992;74(3):707–710. doi: 10.2466/pms.1992.74.3.707

10. Melnick MJ. Relationship between team assists and win-loss record in the National Basketball Association. Perceptual and Motor Skills. 2001;92(2):595–602. doi: 10.2466/pms.2001.92.2.595 11361327

11. Mikolajec K, Maszczyk A, Zajac T. Game indicators determining sports performance in the NBA. Journal of human kinetics. 2013;37(1):145–151. doi: 10.2478/hukin-2013-0035 24146715

12. Ortega E, Cárdenas D, Sainz de Baranda P, Palao J. Differences between winning and losing teams in youth basketball games (14-16 years old). International Journal of Applied Sport Sciences. 2006;18(2):1.

13. Puente C, Coso JD, Salinero JJ, Abián-Vicén J. Basketball performance indicators during the ACB regular season from 2003 to 2013. International Journal of Performance Analysis in Sport. 2015;15(3):935–948. doi: 10.1080/24748668.2015.11868842

14. Trninić S, Dizdar D, Lukšić E. Differences between winning and defeated top quality basketball teams in final tournaments of European club championship. Collegium Antropologicum. 2002;26(2):521–531. 12528276

15. García J, Sáez J, Ibáñez SJ, Parejo I, Cañadas M. Home advantage analysis in ACB league in season 2007-2008. Revista de psicología del deporte. 2009;18(3):331–335.

16. García J, Ibáñez SJ, De Santos RM, Leite N, Sampaio J. Identifying basketball performance indicators in regular season and playoff games. Journal of human kinetics. 2013;36(1):161–168. doi: 10.2478/hukin-2013-0016 23717365

17. Jones MB. Home advantage in the NBA as a game-long process. Journal of Quantitative Analysis in Sports. 2007;3(4). doi: 10.2202/1559-0410.1081

18. Pojskic H, Separovic V, Uzicanin E. Modelling home advantage in basketball at different levels of competition. Acta Kinesiologica. 2011;5(1):25–30.

19. Pollard R, Gómez M. Home advantage analysis in different basketball leagues according to team ability. In: Iberian congress on basketball research. vol. 4; 2007. p. 61–64.

20. Pollard R, Gómez MÁ. Variations in home advantage in the national basketball leagues of Europe. Revista de Psicología del Deporte. 2013;22(1).

21. Štrumbelj E, Vračar P, Robnik-Šikonja M, Dežman B, Erčulj F. A decade of Euroleague basketball: An analysis of trends and recent rule change effects. Journal of human kinetics. 2013;38:183–189. doi: 10.2478/hukin-2013-0058 24235993

22. Selmanović A, Škegro D, Milanović D. Basic characteristics of offensive modalities in the Euroleague. Acta Kinesiologica. 2015;2:83–87.

23. George M, Evangelos T, Alexandros K, Athanasios L. The inside game in World Basketball. Comparison between European and NBA teams. International Journal of Performance Analysis in Sport. 2009;9(2):157–164. doi: 10.1080/24748668.2009.11868473

24. Erčulj F, Štrumbelj E. Basketball shot types and shot success in different levels of competitive basketball. PloS one. 2015;10(6):e0128885. doi: 10.1371/journal.pone.0128885 26038836

25. R Core Team. R: A Language and Environment for Statistical Computing; 2018. Available from: https://www.R-project.org/.

26. Kubatko J, Oliver D, Pelton K, Rosenbaum DT. A starting point for analyzing basketball statistics. Journal of Quantitative Analysis in Sports. 2007;3(3). doi: 10.2202/1559-0410.1070

27. Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York; 2016. Available from: http://ggplot2.org.

28. Wickham H. Reshaping Data with the reshape Package. Journal of Statistical Software. 2007;21(12):1–20. doi: 10.18637/jss.v021.i12

29. Carpenter B., Gelman A., Hoffman M. D., Lee D., Goodrich B., Betancourt M., Brubaker M., Guo J., Li P., Riddell A. Stan: A probabilistic programming language. Journal of statistical software. 2017; 76(1): 1–32. doi: 10.18637/jss.v076.i01

30. Stan Development Team. RStan: the R interface to Stan. R package version 2.19.2. 2019; http://mc-stan.org/.

31. Filippi A. Basketball on paper: rules and tools for performance analysis. Adam Filippi; 1st edition.; 2016.

32. Štrumbelj E, Vračar P. Simulating a basketball match with a homogeneous Markov model and forecasting the outcome. International Journal of Forecasting. 2012;28(2):532–542. doi: 10.1016/j.ijforecast.2011.01.004


Článek vyšel v časopise

PLOS One


2019 Číslo 10

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Léčba bolesti v ordinaci praktického lékaře
nový kurz
Autoři: MUDr. PhDr. Zdeňka Nováková, Ph.D.

Revmatoidní artritida: včas a k cíli
Autoři: MUDr. Heřman Mann

Jistoty a nástrahy antikoagulační léčby aneb kardiolog - neurolog - farmakolog - nefrolog - právník diskutují
Autoři: doc. MUDr. Štěpán Havránek, Ph.D., prof. MUDr. Roman Herzig, Ph.D., doc. MUDr. Karel Urbánek, Ph.D., prim. MUDr. Jan Vachek, MUDr. et Mgr. Jolana Těšínová, Ph.D.

Léčba akutní pooperační bolesti
Autoři: doc. MUDr. Jiří Málek, CSc.

Nové antipsychotikum kariprazin v léčbě schizofrenie
Autoři: prof. MUDr. Cyril Höschl, DrSc., FRCPsych.

Všechny kurzy
Kurzy Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se