Abstract
Abstract Scoring in a basketball game is a highly dynamic, non-linear process. NBA teams try to be more and more competitive each season. For instance, they incorporate into their rosters the best players in the world. This and other mechanisms concur to make the scoring process in NBA games exciting and rarely predictable. This paper is to study the behavior of timing and scoring in basketball games. The authors analyze all the games in five NBA regular seasons (2005–06, 2006–07, 2007–08, 2008–09, 2009–10), for a total of 6150 games. Scoring does not behave uniformly; therefore, the authors also analyze the distributions of the differences in points in the basketball games. To further analyze the behavior of the tail of the distribution, the authors also carry out a semilog-plot and a log-log plot to verify whether this trend approaches a Poisson distribution or a PL. This paper reveals different areas of behavior related to the score, with specific instances of time that could be considered tipping points of the game. The presence of these critical points suggests that there are phase transitions where the dynamic scoring of the games varies significantly.
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References
Yilmaz M R and Chatterjee S, Patterns of NBA team performance from 1950 to 1998, Journal of Applied Statistics, 2000, 27(5): 555–566.
De Saa Guerra Y, Martin-Gonzalez J M, Arjonilla Lopez N, Sarmiento Montesdeoca S, Rodriguez Ruiz D, and Garcia-Manso J M, Competitiveness analysis in the NBA regular seasons, Education, Physical Training, Sport, 2011, 1(80): 17–21.
Bar-Yam Y, Introducing complex systems, International Conference on Complex Systems, Nashua, NH, 2001.
Chatterjee S and Yilmaz M R, The NBA as an evolving multivariate system, The American Statistician, 1999, 53(3): 257–262.
Vaz de Melo P O S, Almeida V A F, and Loureiro A A F, Can complex network metrics predict the behavior of NBA teams? Proceedings of the 14 th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining [Internet], New York, NY, USA: ACM, 2008.
Amaral L A N and Ottino J M, Complex networks, The European Physical Journal B — Condensed Matter, 2004, 38(2): 147–162.
Goodwin B, How the Leopard Changed Its Spots: The Evolution of Complexity, Princenton University Press, 2001.
Sole R and Goodwin B, Signs of Life: How Complexity Pervades Biology, Basic Books, 2002.
Robson A J, Complex evolutionary systems and the red queen, The Economic Journal, 2005, 115(504): 211–224.
Malacarne L and Mendes R, Regularities in football goal distributions, Physica A: Statistical Mechanics and Its Applications, 2000, 286(1–2): 391–395.
Greenhough J, Birch P C, Chapman S C, and Rowlands G, Football goal distributions and extremal statistics, Physica A: Statistical Mechanics and Its Applications, 2002, 316(1–4): 615–624.
Mendes R S, Malacarne L C, and Anteneodo C, Statistics of football dynamics, IEEE Transactions on Automatic Control, 2007, 363(3): 357–363.
Bittner E, Nußaumer A, Janke W, and Weigel M, Football fever: Goal distributions and non-Gaussian statistics, The European Physical Journal B — Condensed Matter and Complex Systems, 2009, 67(3): 459–471.
Heuer A, Mueller C, and Rubner O, Soccer: Is scoring goals a predictable Poissonian process? Europhys. Lett., 2010, 89(3): 38007.
Mc Garry T, Anderson D I, Wallace S A, Hughes M D, and Franks I M, Sport competition as a dynamical self-organizing system, Journal of Sports Sciences, 2002, 20(10): 771–781.
Bourbousson J, Sève C, and Mc Garry T, Space-time coordination dynamics in basketball, Part 2: The interaction between the two teams, Journal of Sports Sciences, 2010, 28(3): 349–358.
Barabasi A L and Albert R, Emergence of scaling in random networks, Science, 1999, 286(5439): 509–512.
Savaglio S and Carbone V, Human performance: Scaling in athletic world records, Nature, 2000, 404(6775): 244.
Garcia Manso J M, Martin-Gonzalez J M, Da Silva-Grigoletto M E, Vaamonde D, Benito P, and Calderon J, Male powerlifting performance described from the viewpoint of complex systems, Journal of Theoretical Biology, 2008, 251(3): 498–508.
Scheffer M, Bascompte J, Brock W A, Brovkin V, Carpenter S R, Dakos V, Held H, Van Nes E H, Rietkerk M, and Sugihara G, Early-warning signals for critical transitions, Nature, 2009, 461(7260): 53–59.
Van Valen L, A new evolutionary law, Evolutionary Theory, 1973, 1: 1–30.
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This paper was recommended for publication by Editors FENG Dexing and HAN Jing.
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De Saá Guerra, Y., Martín Gonzalez, J.M., Sarmiento Montesdeoca, S. et al. Basketball scoring in NBA games: An example of complexity. J Syst Sci Complex 26, 94–103 (2013). https://doi.org/10.1007/s11424-013-2282-3
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DOI: https://doi.org/10.1007/s11424-013-2282-3