EXAMINING THE TURKIYE'S MEN'S BASKETBALL SUPER LEAGUE TEAMS SUCCESS FOR THE 2020-2021 SEASON ACCORDING TO PLAY TYPE STATISTICS
Year 2023,
, 76 - 88, 30.09.2023
Yasin Akıncı
,
Ahmet Yapar
Abstract
The purpose of this study was to examine the game type statistics in the competitions played in the regular season of the 2020-2021 Basketball Super League and difference between playoff teams and out of playoff teams. In regular season, 480 matches played between 16 teams were examined by systematic observation and a total of 5760 statistics were recorded in 12 game types as point posession and points won. Independent samples t-tests were used to compare the game-type statistics of the playoff and non-playoff groups. Discriminant function analysis was used to analyse the game type statistics variables that contributed to distinguishing these two groups. The findings indicated that the means of catch and shoot, Isolation and Transition points possessions of the playoff teams were significantly higher than the teams that did not qualify. It was observed in the findings of the differential function analysis that Isolation and Transition game possessions made more contributions to the playoff teams. It has been observed that playoff teams' mean points gained by Isolation and Pick and Roll Roller game types were statistically significantly different than the teams that did not qualify. The discriminant function analysis findings showed that Isolation and Pick and roll handler game type were the variables that contributed the most to team success. These results show that the Turkish Basketball Super League could be seen as a high-tempo, shooting-weighted league in which the outside players prefer shoot using picks and the center players prefer to play when their backs turned.
References
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Çene, E. (2018). What is the difference between a winning and a losing team: İnsights from Euroleague basketball. International Journal of Performance Analysis in Sport, 18(1), 55-68. doi: 10.1080/24748668.2018.1446234
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- Ergül, B. (2014). Classification of NBA league teams using discriminant and logistic regression analyses. Pamukkale Journal of Sport Sciences, 5(1), 48-60.
- Evangelos, T., Alexandros, K., & Nikolaos, A. (2005). Analysis of fast breaks in basketball. International Journal of Performance Analysis in Sport, 5(2), 17-22. Doi: 10.1080/24748668.2005.11868324
- Franks, A., Miller, A., Bornn, L., & Goldsberry, K. (2015). Characterizing the spatial structure of defensive skill in professional basketball. The Annals of Applied Statistics, 9(1), 94-121. doi: 10.1214/14-AOAS799
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- Karipidis, A., Mavridis, G., Tsamourtzis, E., & Rokka, S. (2010). The effectiveness of control offense, following an outside game in European Championships. Inquiries in Sport & Physical Education, 8(1), 99-106.
- Lamas, L., Barrera, J., Otranto, G., & Ugrinowitsch, C. (2014). Invasion team sports: Strategy and match modeling. International Journal of Performance Analysis in Sport, 14(1), 307-329. doi: 10.1080/24748668.2014.11868723
Lehto, H., Häyrinen, M., Fay, T., Tammivaara, A., & Dettmann, H. (2010). Technical and tactical game analysis of elite basketball in three different levels. KIHU’s publication series, 19, 33.
- Leicht, A. S., Gómez, M. A., & Woods, C. T. (2017). Explaining match outcome during the men’s basketball tournament at the Olympic Games. Journal of sports science & medicine, 16(4), 468.
- Li, B., & Xu, X. (2021). Application of artificial intelligence in basketball sport. Journal of Education, Health and Sport, 11(7), 54-67. doi: 10.12775/JEHS.2021.11.07.005
- Lorenzo, J., Lorenzo, A., Conte, D., & Giménez, M. (2019). Long-term analysis of elite basketball players’ game-related statistics throughout their careers. Frontiers in psychology, 10, 421. doi: 10.3389/fpsyg.2019.00421
- Losada, J. L., & Manolov, R. (2014). The process of basic training, applied training, maintaining the performance of an observer. Quality & Quantity, 49(1), 339-347.
- Madarame, H. (2017). Game-related statistics which discriminate between winning and losing teams in Asian and European men’s basketball championships. Asian Journal of Sports Medicine, 8(2). doi: 10.5812/asjsm.42727
- Marmarinos, C., Apostolidis, N., Kostopoulos, N., & Apostolidis, A. (2016). Efficacy of the “pick and roll” offense in top level European basketball teams. Journal of human kinetics, 51(1), 121-129. doi: 10.1515/hukin-2015-0176
- Matulaitis, K., & Bietkis, T. (2021). Prediction of offensive possession ends in elite basketball teams. International journal of environmental research and public health, 18(3), 1083. doi: 10.3390/ijerph18031083
- Milanovic, D., Stefan, L., Sporis, G., Vuleta, D., & Selmanovic, A. (2016). Effects of situational efficiency indicators on final outcome among male basketball teams on the Olympic games in London 2012. Acta Kinesiologica, 10(1), 78-84.
- Nikolaidis, Y. (2015). Building a basketball game strategy through statistical analysis of data. Annals of Operations Research, 227(1), 137-159. doi: 10.1007/s10479-013-1309-4
- Ostojic, S. M., Mazic, S., & Dikic, N. (2006). Profiling in basketball: Physical and physiological characteristics of elite players. Journal of strength and Conditioning Research, 20(4), 740. doi: 10.1519/R-15944.1
- Özdamar, K. (2013). Paket programlar ile istatistiksel veri analizi (Cilt ; ss 27-36). Ankara: Nisan Kitapevi.
- Passos, P., Milho, J., Fonseca, S., Borges, J., Araújo, D., & Davids, K. (2011). Interpersonal distance regulates functional grouping tendencies of agents in team sports. Journal of motor behavior, 43(2), 155-163. doi: 10.1080/00222895.2011.552078
- Remmert, H., & Chau, A.-T. (2019). Players’ decisions within ball screens in elite German men’s basketball: Observation of offensive–defensive interactions using a process-orientated state-event model. International Journal of Performance Analysis in Sport, 19(1), 1-13. doi: 10.1080/24748668.2018.1534198
- Sampaio, J., Janeira, M., Ibáñez, S., & Lorenzo, A. (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. doi: 10.1080/17461390600676200
Selmanović, A., Škegro, D., & Milanović, D. (2015). Basic characteristics of offensive modalities in the Euroleague and the NBA. Acta Kinesiol, 9, 83-87.
- Shah, R., & Romijnders, R. (2016). Applying deep learning to basketball trajectories. arXiv preprint arXiv:1608.03793.
- Suárez-Cadenas, E., & Courel-Ibáñez, J. (2017). Shooting strategies and effectiveness after offensive rebound and its impact on game result in Euroleague basketball teams. Cuadernos de Psicología del Deporte, 17(3), 217-222.
- Tabachnick, B. G., & Fidell, L. S. (2000). Computer-assisted research design and analysis. Allyn & Bacon, Inc.
Trninić, S., Dizdar, D., Dežman, B. (2000). Empirical verification of the weighted system of criteria for the elite basketball players quality evaluation. Collegium Antropologicum, 24(2), 443-465.
- Trninić, S., Dizdar, D., & Lukšić, E. (2002). Differences between winning and defeated top quality basketball teams in final tournaments of European club championship. Collegium antropologicum, 26(2), 521-531.
- Vaquera, A., García-Tormo, J. V., Gómez Ruano, M. A., & Morante, J. C. (2016). An exploration of ball screen effectiveness on elite basketball teams. International Journal of Performance Analysis in Sport, 16(2), 475-485. doi: 10.1080/24748668.2016.11868902
- Zhang, S., Lorenzo, A., Zhou, C., Cui, Y., Gonçalves, B., & Angel Gómez, M. (2019). Performance profiles and opposition interaction during game-play in elite basketball: Evidences from National Basketball Association. International Journal of Performance Analysis in Sport, 19(1), 28-48. doi: 10.1080/24748668.2018.1555738
- Zukolo, Z., Dizdar, D., Selmanović, A., & Vidranski, T. (2019a). The role of finishing actions in the final result of the basketball match. J. Sports Sci, 12, 90-95.
- Zukolo, Z., Dizdar, D., Selmanović, A., & Vidranski, T. (2019b). The role of finishing actions in the final result of the basketball match. J. Sports Sci, 12, 90-95.
TÜRKİYE ERKEK BASKETBOL SÜPER LİG TAKIMLARININ 2020-2021 SEZONU BAŞARILARININ OYUN TİPİ İSTATİSTİKLERİNE GÖRE İNCELENMESİ
Year 2023,
, 76 - 88, 30.09.2023
Yasin Akıncı
,
Ahmet Yapar
Abstract
Bu çalışmanın amacı, 2020-2021 Basketbol Süper Ligi normal sezonunda oynanan müsabakalardaki oyun tipi istatistiklerini ve playoff’a kalan 8 takım ile kalamayan 8 takım arasındaki farklı incelemektir. Normal sezonda 16 takım arasında oynanan 480 müsabaka sistematik gözlem yolu ile incelenmiş ve 12 oyun tipinde sayı girişimi ve kazanılan sayı olarak toplamda 5760 istatistik kaydedilmiştir. Playoff’a kalan ve playoff dışı kalan gruba ait oyunla tipi istatistikleri karşılaştırmak için Bağımsız örnekler t testleri kullanılmıştır. Bu iki grubu ayırt etmeye katkıda bulunan oyun tipi istatistikleri değişkenlerini keşfetmek için ayırıcı fonksiyon analizi kullanılmıştır. Bulgular playoff’a kalan takımların sayı girişimlerinde catch and shoot, isolation ve transition sayı girişimi ortalamalarının kalamayan takımlardan anlamlı olarak daha yüksek olduğunu göstermiştir. Playoff’a kalan takımların en çok sayı girişimi Isolation ve Transition oyun tiplerindenden geldiği ayrıcı fonksiyon analizini bulgularında gözlenmiştir. Playoff’a kalan takımların Isolation ve Pick and Roll Roller oyun tipinden kazandıkları sayı ortalamalarının kalamayan takımlara göre istatiksel olarak anlamlı olduğu gözlenmiştir. Ayrıcı fonksiyon analizi bulguları isolation ve pick and roll handler oyun tipinin takım başarısına en büyük katkıyı yapan değişkenler olduğu göstermiştir. Bu sonuçlar Türkiye Basketbol Süper Ligi’nin yüksek tempoda, şut ağırlıklı, dış oyuncuların pick and roll oyunuyla ve ayrıca pivot oyuncuların sırtı dönük oyunuyla çembere atış yaptığı bir lig olduğunu göstermektedir.
References
- Angel Gomez, M., Lorenzo, A., Sampaio, J., Jose Ibanez, S., & Ortega, E. (2008). Game-related statistics that discriminated winning and losing teams from the Spanish men’s professional basketball teams. Collegium antropologicum, 32(2), 451-456.
- Bazanov, B., Võhandu, P., & Haljand, R. (2006). Trends in offensive team activity in basketball. Baltic Journal of Sport and Health Sciences, 2(61), 5-11 doi: https://doi.org/10.33607/bjshs.v2i61.590
- Bloom, G. A., Crumpton, R., & Anderson, J. E. (1999). A systematic observation study of the teaching behaviors of an expert basketball coach. Sport Psychologist, 13, 157-170. doi:10.1123/tsp.13.2.157
- Chang, Y.-H., Maheswaran, R., Su, J., Kwok, S., Levy, T., Wexler, A., & Squire, K. (2014). Quantifying shot quality in the NBA. Proceedings of the 8th Annual MIT Sloan Sports Analytics Conference. MIT, Boston, MA.
- Christmann, J., Akamphuber, M., Müllenbach, A. L., & Güllich, A. (2018). Crunch time in the NBA–The effectiveness of different play types in the endgame of close matches in professional basketball. International Journal of Sports Science & Coaching, 13(6), 1090-1099. doi:10.1177/1747954118772485
- Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and psychological measurement, 20(1), 37-46.
- Conte, D., Favero, T. G., Niederhausen, M., Capranica, L., & Tessitore, A. (2017). Determinants of the effectiveness of fast break actions in elite and sub-elite Italian men’s basketball games. Biology of sport, 34(2), 177. doi: 10.5114/biolsport.2017.65337
- Courel-Ibáñez, J., McRobert, A. P., Toro, E. O., Vélez, D. C. (2016). Inside pass predicts ball possession effectiveness in NBA basketball. International Journal of Performance Analysis in Sport, 16(2), 711-725. doi: 10.1080/24748668.2016.11868918
Çene, E. (2018). What is the difference between a winning and a losing team: İnsights from Euroleague basketball. International Journal of Performance Analysis in Sport, 18(1), 55-68. doi: 10.1080/24748668.2018.1446234
- Demenius, J. (2020). Offensive modalities and their influence on basketball efficiency between winning and losing teams (Final Master‘s Thesis). Internatıonal Basketball Coachıng and Management Study Programme, Lietuvos sporto universitetas.
- Dogan, I., & Ersoz, Y. (2019). The important game-related statistics for qualifying next rounds in Euroleague. Montenegrin Journal of Sports Science and Medicine, 8(1), 43. doi:10.26773/mjssm.190307
- Ergül, B. (2014). Classification of NBA league teams using discriminant and logistic regression analyses. Pamukkale Journal of Sport Sciences, 5(1), 48-60.
- Evangelos, T., Alexandros, K., & Nikolaos, A. (2005). Analysis of fast breaks in basketball. International Journal of Performance Analysis in Sport, 5(2), 17-22. Doi: 10.1080/24748668.2005.11868324
- Franks, A., Miller, A., Bornn, L., & Goldsberry, K. (2015). Characterizing the spatial structure of defensive skill in professional basketball. The Annals of Applied Statistics, 9(1), 94-121. doi: 10.1214/14-AOAS799
- García, J., Ibáñez, S. J., De Santos, R. M., Leite, N., & Sampaio, J. (2013). Identifying basketball performance indicators in regular season and playoff games. Journal of human kinetics, 36, 161. doi: doi: 10.2478/hukin-2013-0016
- Gerrard, B., & Alamar, B. C. (2014). Sports analytics: A Guide for coaches, managers and other decision makers. Sport Management Review, 17(2), 240-241. doi: 10.1016/j.smr.2013.06.005
- Goldman, M., & Rao, J. M. (2013). Live by the Three, Die by the Three? The Price of Risk in the NBA. Submission to the MIT sloan sports analytics conference, p155. MIT Boston
- Gomez, M. A., Gasperi, L., & Lupo, C. (2016). Performance analysis of game dynamics during the 4th game quarter of NBA close games. International Journal of Performance Analysis in Sport, 16(1), 249-263. doi: 10.1080/24748668.2016.11868884
- Gudmundsson, J., & Horton, M. (2017). Spatio-temporal analysis of team sports. ACM Computing Surveys (CSUR), 50(2), 1-34. doi: 10.1145/3054132
- Hughes, M. (2003). Notational analysis. Science and soccer (ss. 253-272). Routledge.
- Ibáñez, S. J., Sampaio, J., Feu, S., Lorenzo, A., Gómez, M. A., & Ortega, E. (2008). Basketball game-related statistics that discriminate between teams’ season-long success. European journal of sport science, 8(6), 369-372. doi: 10.1080/17461390802261470
- Karipidis, A., Mavridis, G., Tsamourtzis, E., & Rokka, S. (2010). The effectiveness of control offense, following an outside game in European Championships. Inquiries in Sport & Physical Education, 8(1), 99-106.
- Lamas, L., Barrera, J., Otranto, G., & Ugrinowitsch, C. (2014). Invasion team sports: Strategy and match modeling. International Journal of Performance Analysis in Sport, 14(1), 307-329. doi: 10.1080/24748668.2014.11868723
Lehto, H., Häyrinen, M., Fay, T., Tammivaara, A., & Dettmann, H. (2010). Technical and tactical game analysis of elite basketball in three different levels. KIHU’s publication series, 19, 33.
- Leicht, A. S., Gómez, M. A., & Woods, C. T. (2017). Explaining match outcome during the men’s basketball tournament at the Olympic Games. Journal of sports science & medicine, 16(4), 468.
- Li, B., & Xu, X. (2021). Application of artificial intelligence in basketball sport. Journal of Education, Health and Sport, 11(7), 54-67. doi: 10.12775/JEHS.2021.11.07.005
- Lorenzo, J., Lorenzo, A., Conte, D., & Giménez, M. (2019). Long-term analysis of elite basketball players’ game-related statistics throughout their careers. Frontiers in psychology, 10, 421. doi: 10.3389/fpsyg.2019.00421
- Losada, J. L., & Manolov, R. (2014). The process of basic training, applied training, maintaining the performance of an observer. Quality & Quantity, 49(1), 339-347.
- Madarame, H. (2017). Game-related statistics which discriminate between winning and losing teams in Asian and European men’s basketball championships. Asian Journal of Sports Medicine, 8(2). doi: 10.5812/asjsm.42727
- Marmarinos, C., Apostolidis, N., Kostopoulos, N., & Apostolidis, A. (2016). Efficacy of the “pick and roll” offense in top level European basketball teams. Journal of human kinetics, 51(1), 121-129. doi: 10.1515/hukin-2015-0176
- Matulaitis, K., & Bietkis, T. (2021). Prediction of offensive possession ends in elite basketball teams. International journal of environmental research and public health, 18(3), 1083. doi: 10.3390/ijerph18031083
- Milanovic, D., Stefan, L., Sporis, G., Vuleta, D., & Selmanovic, A. (2016). Effects of situational efficiency indicators on final outcome among male basketball teams on the Olympic games in London 2012. Acta Kinesiologica, 10(1), 78-84.
- Nikolaidis, Y. (2015). Building a basketball game strategy through statistical analysis of data. Annals of Operations Research, 227(1), 137-159. doi: 10.1007/s10479-013-1309-4
- Ostojic, S. M., Mazic, S., & Dikic, N. (2006). Profiling in basketball: Physical and physiological characteristics of elite players. Journal of strength and Conditioning Research, 20(4), 740. doi: 10.1519/R-15944.1
- Özdamar, K. (2013). Paket programlar ile istatistiksel veri analizi (Cilt ; ss 27-36). Ankara: Nisan Kitapevi.
- Passos, P., Milho, J., Fonseca, S., Borges, J., Araújo, D., & Davids, K. (2011). Interpersonal distance regulates functional grouping tendencies of agents in team sports. Journal of motor behavior, 43(2), 155-163. doi: 10.1080/00222895.2011.552078
- Remmert, H., & Chau, A.-T. (2019). Players’ decisions within ball screens in elite German men’s basketball: Observation of offensive–defensive interactions using a process-orientated state-event model. International Journal of Performance Analysis in Sport, 19(1), 1-13. doi: 10.1080/24748668.2018.1534198
- Sampaio, J., Janeira, M., Ibáñez, S., & Lorenzo, A. (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. doi: 10.1080/17461390600676200
Selmanović, A., Škegro, D., & Milanović, D. (2015). Basic characteristics of offensive modalities in the Euroleague and the NBA. Acta Kinesiol, 9, 83-87.
- Shah, R., & Romijnders, R. (2016). Applying deep learning to basketball trajectories. arXiv preprint arXiv:1608.03793.
- Suárez-Cadenas, E., & Courel-Ibáñez, J. (2017). Shooting strategies and effectiveness after offensive rebound and its impact on game result in Euroleague basketball teams. Cuadernos de Psicología del Deporte, 17(3), 217-222.
- Tabachnick, B. G., & Fidell, L. S. (2000). Computer-assisted research design and analysis. Allyn & Bacon, Inc.
Trninić, S., Dizdar, D., Dežman, B. (2000). Empirical verification of the weighted system of criteria for the elite basketball players quality evaluation. Collegium Antropologicum, 24(2), 443-465.
- Trninić, S., Dizdar, D., & Lukšić, E. (2002). Differences between winning and defeated top quality basketball teams in final tournaments of European club championship. Collegium antropologicum, 26(2), 521-531.
- Vaquera, A., García-Tormo, J. V., Gómez Ruano, M. A., & Morante, J. C. (2016). An exploration of ball screen effectiveness on elite basketball teams. International Journal of Performance Analysis in Sport, 16(2), 475-485. doi: 10.1080/24748668.2016.11868902
- Zhang, S., Lorenzo, A., Zhou, C., Cui, Y., Gonçalves, B., & Angel Gómez, M. (2019). Performance profiles and opposition interaction during game-play in elite basketball: Evidences from National Basketball Association. International Journal of Performance Analysis in Sport, 19(1), 28-48. doi: 10.1080/24748668.2018.1555738
- Zukolo, Z., Dizdar, D., Selmanović, A., & Vidranski, T. (2019a). The role of finishing actions in the final result of the basketball match. J. Sports Sci, 12, 90-95.
- Zukolo, Z., Dizdar, D., Selmanović, A., & Vidranski, T. (2019b). The role of finishing actions in the final result of the basketball match. J. Sports Sci, 12, 90-95.