journal article·2024-07-31Open access

Changes in Defensive Variables Determining Success in the NBA over the Last 10 Years

Hakan Buyukcelebi, Fatma Nese Sahin, Mahmut Acak, Hüseyin Şahin Uysal, Cengizhan Sari, Dilara Erkan, Semra Yatak, Raci Karayigit

Applied Sciences· Volume 14· Issue 15

Abstract

This study aimed to determine changes in defensive strategies over the past decade in the National Basketball Association (NBA) and identify the most crucial factors for winning games. The study analyzed all games where the 30 NBA teams played over 11 seasons (13,530 games) and created outcome statistics based on win–loss records. Five defensive variables (OREB [offensive rebound], DREB [defensive rebound], TREB [total rebound], ST [steal] and BLK [block]) were compared, revealing that OREB (p < 0.03), DREB (p < 0.001), TREB (p < 0.001), ST (p < 0.001) and BLK (p < 0.001) occur significantly in winning teams. Also, it has been observed that the changes over the years in the variables OREB (p < 0.01), DREB (p < 0.01), TREB (p < 0.01) and ST (p < 0.01) are statistically significant. However, there was no significant difference in the BLK variable over the years (p = 0.24). The impact of defensive variables on winning and their factor loadings are as follows: DREB (λ = 0.50), ST (λ = 0.15), TREB (λ = 0.10), BLK (λ = 0.08) and OREB (λ = 0.06). Coaches can use these findings on defensive variables to strategize and counter opponents during games.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Sports Performance and Training · Sports Analytics and Performance · Sports Dynamics and Biomechanics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Coaching Education, Faculty of Sport Sciences, İnönü University, Malatya 44000, Turkey

Department of Coaching Education, Faculty of Sport Sciences, Ankara University, Gölbaşı, Ankara 06830, Turkey

Department of Coaching Education, Faculty of Sport Sciences, Çanakkale Onsekiz Mart University, Çanakkale 17100, Turkey

Department of Physical Education and Sport, Faculty of Sport Sciences, Burdur Mehmet Akif Ersoy University, Burdur 15030, Turkey

Department of Coaching Education, Faculty of Sport Sciences, Mus Alparslan University, Mus 49001, Turkey

Department of Recreation, Faculty of Sport Sciences, Avrasya University, Trabzon 61220, Turkey

References (36)

Show source-provided references
1. Effects of season period, team quality and playing time on basketball players’ game-related statistics10.1080/17461390903311935 ↗
2. Hughes, M., and Franks, I.M. (2004). Notational Analysis of Sport. Systems for Better Coaching and Performance in Sport, Routledge.
3. Differences in game statistics between winning and losing rugby teams in the six nations tournament
4. Paths to expertise in Portuguese national team athletes
5. Hughes, M., and Franks, I.M. (2015). Essentials of Performance Analysis in Sport, Routledge.10.4324/9781315776743 ↗
6. Performance indicators that distinguish winning and losing teams in basketball
7. Sampaio, J., McGarry, T., Calleja-Gonzalez, J., Jimenez Saiz, S., Schelling, I.D.A.X., and Balciunas, M. (2015). Exploring game performance in the national basketball association using player tracking data. PLoS ONE, 10.10.1371/journal.pone.0132894 ↗
8. The use of performance indicators in performance analysis10.1080/026404102320675602 ↗
9. Performance analysis: Can bringing together biomechanics and notational analysis benefit coaches
10. Game related statistics which discriminate between winning and losing under-16 male basketball games
11. An analysis of defensive strategies used by home and away basketball teams10.2466/pms.110.1.159-166 ↗
12. Game related statistics discriminating between starters and nonstarters players in Women’s National Basketball Association League (WNBA)
13. Basketball game-related statistics that discriminate between teams’ season-long success10.1080/17461390802261470 ↗
14. Analysis of fast breaks in basketball
15. Basketball performance indicators during the ACB regular season from 2003 to 2013
16. Performance profiles and opposition interaction during game-play in elite basketball: Evidences from National Basketball Association
17. Factors characterizing a successful performance in basketball
18. Discriminative power of basketball game-related statistics by level of competition and sex10.2466/pms.99.3f.1231-1238 ↗
19. Identifying basketball performance indicators in regular season and playoff games10.2478/hukin-2013-0016 ↗
20. Zhang, S., Lorenzo, A., Gómez, M.-A., Mateus, N., Gonçalves, B., and Sampaio, J. (2018). Performance Profiles of Basketball Players in NBA according to anthropometric attributes and playing experience. Complex Systems in Sport, International Congress Linking Theory and Practice, Frontiers.10.1080/02640414.2018.1466493 ↗
21. Basketball Game-related statistics discriminating ACB league teams according to game location, game outcome and final score differences
22. Causal-comparative research designs10.3233/JVR-2004-00260 ↗
23. Progressive statistics for studies in sports medicine and exercise science10.1249/MSS.0b013e31818cb278 ↗
24. Detecting drivers of basketball successful games: An exploratory study with machine learning algorithms
25. Horvat, T., Havaš, L., and Srpak, D. (2020). The impact of selecting a validation method in machine learning on predicting basketball game outcomes. Symmetry, 12.10.3390/sym12030431 ↗
26. NBA game result prediction using feature analysis and machine learning10.1007/s40745-018-00189-x ↗
27. Game-related statistics that discriminated winning and losing teams from the Spanish men´s professional basketball teams
28. Discriminative game related statistics between basketball starters and nonstarters when related to team quality and game outcome10.2466/pms.103.2.486-494 ↗
29. Effects of consecutive basketball games on the game-related statistics that discriminate winner and losing teams
30. Differences between winning and losing teams in playing efficiency
31. Dynamic Modeling of Performance in Basketball
32. Analysis of influencing factors behind offensive rebounding performance in elite basketball10.1177/1747954117738900 ↗
33. Differences between winning and defeated top quality basketball teams in final of European club championship
34. Efficiency in the National Basketball Association: A stochastic frontier approach with panel data10.1002/mde.1252 ↗
35. Statistical Analysis of Basketball Performance Indicators According to Home/Away Games and Winning and Losing Teams
36. Instrumental vs. bounded rationality: The case of Major League Baseball and the National Basketball Association10.1016/S1053-5357(02)00117-8 ↗