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The Price of Anarchy in Basketball

Author

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  • Skinner Brian

    (University of Minnesota - Twin Cities)

Abstract

Optimizing the performance of a basketball offense may be viewed as a network problem, wherein each play represents a "pathway" through which the ball and players may move from origin (the in-bounds pass) to goal (the basket). Effective field goal percentages from the resulting shot attempts can be used to characterize the efficiency of each pathway. Inspired by recent discussions of the "price of anarchy" in traffic networks, this paper makes a formal analogy between a basketball offense and a simplified traffic network. The analysis suggests that there may be a significant difference between taking the highest-percentage shot each time down the court and playing the most efficient possible game. There may also be an analogue of Braess's Paradox in basketball, such that removing a key player from a team can result in the improvement of the team's offensive efficiency.

Suggested Citation

  • Skinner Brian, 2010. "The Price of Anarchy in Basketball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-18, January.
    • Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:1:n:3
    DOI: 10.2202/1559-0410.1217
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    References listed on IDEAS

    as
    1. Kubatko Justin & Oliver Dean & Pelton Kevin & Rosenbaum Dan T, 2007. "A Starting Point for Analyzing Basketball Statistics," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(3), pages 1-24, July.
    2. Alamar Benjamin C, 2006. "The Passing Premium Puzzle," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(4), pages 1-10, October.
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    Citations

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    Cited by:

    1. Skinner Brian, 2011. "Scoring Strategies for the Underdog: A General, Quantitative Method for Determining Optimal Sports Strategies," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-18, October.
    2. 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.
    3. Knight, Vincent A. & Harper, Paul R., 2013. "Selfish routing in public services," European Journal of Operational Research, Elsevier, vol. 230(1), pages 122-132.
    4. Filippo Radicchi, 2011. "Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    5. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    6. Tal Neiman & Yonatan Loewenstein, 2014. "Spatial Generalization in Operant Learning: Lessons from Professional Basketball," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-8, May.
    7. Mukherjee, Satyam, 2012. "Identifying the greatest team and captain—A complex network approach to cricket matches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6066-6076.
    8. Ruiz Manuel & Martinez Jose A. & López-Hernández Fernando A. & Castellano Almudena, 2014. "The relationship between concentration of scoring and offensive efficiency in the NBA," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(1), pages 27-36, January.
    9. Tal Neiman & Yonatan Loewenstein, 2014. "Spatial Generalization in Operant Learning: Lessons from Professional Basketball," Discussion Paper Series dp665, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    10. Benjamin Schäfer & Thiemo Pesch & Debsankha Manik & Julian Gollenstede & Guosong Lin & Hans-Peter Beck & Dirk Witthaut & Marc Timme, 2022. "Understanding Braess’ Paradox in power grids," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    11. Brian Skinner & Stephen J Guy, 2015. "A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-15, September.

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