Determining the most important game-related statistics in Euroleague basketball competitions: A five-year follow-up

Year 2023, Volume: 25 Issue: 3, 455 - 461, 31.12.2023

Berk Yılmaz , Özkan Işık , İlkay Doğan

https://doi.org/10.15314/tsed.1369508

Abstract

The purpose of this study was to investigate the game-related statistics in the Play-Off and Final Four rounds of the Euroleague basketball competitions held between 2014 and 2018. In the study, the game-related statistics of 60 teams that participated in the Euroleague Play-Off and Final Four rounds between 2014 and 2018 were evaluated. The independent samples t-test was used to compare the game-related statistics of the two groups. The linear discriminant analysis was used to determine the important game-related statistics between the teams that qualified and those that were eliminated. The results of the study showed that there was a statistically significant difference between the game-related statistics of the two groups in the Play-Off competitions. This difference was seen in the free throw percentage, fouls committed, and performance efficiency scores. As a result of the discriminant analysis, it was found that foul, three-point field-goal percentage, performance efficiency score, turnover, free-throw percentage, and two-point field-goal percentage are important game-related statistics in qualifying the Play-Off round. When the game-related statistics of the two groups in the Final Four were compared, it was seen that only three-point field-goal percentage was an effective variable in becoming the champion. According to the results of the discriminant analysis, turnover, defensive rebound, and total rebound are important game-related statistics to being an Euroleague champion. In conclusion, it is thought that being the Euroleague champion in the Euroleague, it is necessary to have a lower number of turnovers and a defensive game.

Keywords

Basketball, Euroleague, Game-related statistics

References

• 1. Berry DJ, Schmidt MB. Instrumental versus bounded rationality: A comparison of major league Baseball and national basketball association. Journal of Socio-Economics, 2002; 31: 191-214.
• 2. Çene, E. What is the difference between a winning and a losing team: insights from Euroleague basketball. International Journal of Performance Analysis in Sport, 2018; 18(1): 55-68.
• 3. 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.
• 4. Doğan, İ., Işık, O ve Ersöz Y. Examining the Turkish men’s professional basketball team’s success according to game-related statistics with discriminant analysis. International Journal of Performance Analysis in Sport, 2016; 16(3): 829-836.
• 5. Doğan, İ., ve Ersöz, Y. The important game-related statistics for qualifying next rounds in Euroleague. Montenegrin Journal of Sports Science and Medicine, 2019; 8(1): 43-50.
• 6. Ergül, B. Classification of NBA league teams using discriminant and logistic regression analyses. Pamukkale Journal of Sport Sciences, 2014; 5(1): 48-60.
• 7. Gómez, A.M., Lorenzo, A., Sampaio, J., José Ibánez, S., & Ortega, E. Game-related statistics that discriminated winning and losing teams from the Spanish men’s professional basketball teams. Collegium Antropologicum, 2008; 32(2): 451-456.
• 8. http://www.euroleague.net/competition/teams (Accessed 09.05.2021).
• 9. Ibánez, S. J., Sampaio, J., Feu, S., Lorenzo, A., Gómez, M. A., & Ortega, E. Basketball game-related statistics that discriminate between teams’ season-long success. European journal of sport science, 2008; 8(6): 369-372.
• 10. Marmarinos, C., Apostolidis, N., Kostopoulos, N., & Apostolidis, A. Efficacy of the “pick and roll” offense in top-level European basketball teams. Journal of Human Kinetics, 2016; 51(1):121-129.
• 11. Özdamar, K. Paket Programlar ile İstatistiksel Veri Analizi. Eskişehir, TR: Nisan Kitabevi, 2013.
• 12. Ribas, R. L., Navarro, R., Tavares, F., & Gómez, M. A. Analysis of number of players involved in rebound situations in Euroleague basketball games. Open Sports Sciences Journal, 2011; 4: 10-13.
• 13. Sampaio, J., Janeira, M., Ibáñez, S., & Lorenzo, A. Discriminant analysis of game-related statistics between basketball guards, forwards and centres in three professional leagues. European Journal of Sport Science, 2006; 6(3): 173-178.
• 14. Sampaio, J., Drinkwater, E. J., Leite, N. M. Effects of season period, team quality, and playing time on basketball players' game-related statistics. European Journal of Sport Science, 2010; 10(2): 141-149.
• 15. Sampaio, J., Lago, C., & Drinkwater, E. J. Explanations for the United States of America’s dominance in basketball at the Beijing Olympic Games (2008). Journal of Sports Sciences, 2010; 28(2): 147-152.
• 16. Smith, N., Handford, C., & Priestley, N. Sport analysis in coaching. Alsager, UK: The Manchester Metropolitan University, 1997.
• 17. Tabachnick, B. G., & Fidell, L. S. Computer-assisted research design and analysis. Allyn & Bacon, Boston, 2001.