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The Poisson model limits in NBA basketball: Complexity in team sports

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  • Martín-González, Juan Manuel
  • de Saá Guerra, Yves
  • García-Manso, Juan Manuel
  • Arriaza, Enrique
  • Valverde-Estévez, Teresa

Abstract

Team sports are frequently studied by researchers. There is presumption that scoring in basketball is a random process and that can be described using the Poisson Model. Basketball is a collaboration-opposition sport, where the non-linear local interactions among players are reflected in the evolution of the score that ultimately determines the winner. In the NBA, the outcomes of close games are often decided in the last minute, where fouls play a main role. We examined 6130 NBA games in order to analyze the time intervals between baskets and scoring dynamics. Most numbers of baskets (n) over a time interval (ΔT) follow a Poisson distribution, but some (e.g., ΔT=10 s, n>3) behave as a Power Law. The Poisson distribution includes most baskets in any game, in most game situations, but in close games in the last minute, the numbers of events are distributed following a Power Law. The number of events can be adjusted by a mixture of two distributions. In close games, both teams try to maintain their advantage solely in order to reach the last minute: a completely different game. For this reason, we propose to use the Poisson model as a reference. The complex dynamics will emerge from the limits of this model.

Suggested Citation

  • Martín-González, Juan Manuel & de Saá Guerra, Yves & García-Manso, Juan Manuel & Arriaza, Enrique & Valverde-Estévez, Teresa, 2016. "The Poisson model limits in NBA basketball: Complexity in team sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 182-190.
    • Handle: RePEc:eee:phsmap:v:464:y:2016:i:c:p:182-190
    DOI: 10.1016/j.physa.2016.07.028
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    References listed on IDEAS

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    1. Pierpaolo Andriani & Bill McKelvey, 2007. "Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 38(7), pages 1212-1230, December.
    2. de Saá Guerra, Y. & Martín González, J.M. & Sarmiento Montesdeoca, S. & Rodríguez Ruiz, D. & García-Rodríguez, A. & García-Manso, J.M., 2012. "A model for competitiveness level analysis in sports competitions: Application to basketball," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(10), pages 2997-3004.
    3. Gabel Alan & Redner Sidney, 2012. "Random Walk Picture of Basketball Scoring," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-20, March.
    4. Greenhough, J & Birch, P.C & Chapman, S.C & Rowlands, G, 2002. "Football goal distributions and extremal statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 615-624.
    5. Skinner Brian, 2010. "The Price of Anarchy in Basketball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-18, January.
    6. Mustafa Yilmaz & Sangit Chatterjee, 2000. "Patterns of NBA team performance from 1950 to 1998," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 555-566.
    7. Picoli, S. & Mendes, R.S. & Malacarne, L.C., 2003. "q-exponential, Weibull, and q-Weibull distributions: an empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(3), pages 678-688.
    8. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
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    Cited by:

    1. Song, Kai & Gao, Yiran & Shi, Jian, 2020. "Making real-time predictions for NBA basketball games by combining the historical data and bookmaker’s betting line," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    2. Singh, Aaditya & Scarf, Phil & Baker, Rose, 2023. "A unified theory for bivariate scores in possessive ball-sports: The case of handball," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1099-1112.
    3. Jeon, Gyuhyeon & Park, Juyong, 2021. "Characterizing patterns of scoring and ties in competitive sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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