IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v6y2010i1n3.html
   My bibliography  Save this article

The Price of Anarchy in Basketball

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1217
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1559-0410.1217?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Knight, Vincent A. & Harper, Paul R., 2013. "Selfish routing in public services," European Journal of Operational Research, Elsevier, vol. 230(1), pages 122-132.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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 & López-Hernández Fernando A. & Martinez Jose 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. 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.
    10. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    11. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joseph Price & Justin Wolfers, 2010. "Racial Discrimination Among NBA Referees," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(4), pages 1859-1887.
    2. Emara, Noha & Owens, David & Smith, John & Wilmer, Lisa, 2017. "Serial correlation in National Football League play calling and its effects on outcomes," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 69(C), pages 125-132.
    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. Jared Quenzel & Paul Shea, 2016. "Predicting the Winner of Tied National Football League Games," Journal of Sports Economics, , vol. 17(7), pages 661-671, October.
    5. Leonardo Lamas & José Vitor Senatore & Gilbert Fellingham, 2020. "Two steps for scoring a point: Creating and converting opportunities in invasion team sports," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-16, October.
    6. Pierpalo D’Urso & Livia Giovanni & Vincenzina Vitale, 2023. "A Bayesian network to analyse basketball players’ performances: a multivariate copula-based approach," Annals of Operations Research, Springer, vol. 325(1), pages 419-440, June.
    7. Letian Zhang, 2019. "Who Loses When a Team Wins? Better Performance Increases Racial Bias," Organization Science, INFORMS, vol. 30(1), pages 40-50, February.
    8. Turner, Chad & Hakes, Jahn Karl, 2007. "The Collective Bargaining Effects of NBA Player Productivity Dynamics," MPRA Paper 5058, University Library of Munich, Germany.
    9. Leonardo Lamas & Felipe Santana & Matthew Heiner & Carlos Ugrinowitsch & Gilbert Fellingham, 2015. "Modeling the Offensive-Defensive Interaction and Resulting Outcomes in Basketball," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-14, December.
    10. Alessandro Chessa & Pierpaolo D’Urso & Livia Giovanni & Vincenzina Vitale & Alfonso Gebbia, 2023. "Complex networks for community detection of basketball players," Annals of Operations Research, Springer, vol. 325(1), pages 363-389, June.
    11. Yurko Ronald & Ventura Samuel & Horowitz Maksim, 2019. "nflWAR: a reproducible method for offensive player evaluation in football," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(3), pages 163-183, September.
    12. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2021. "Spatial Performance Indicators and Graphs in Basketball," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 725-738, August.
    13. Matteo Pazzona, 2022. "Peer interactions and performance in a high‐skilled labour market," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(4), pages 1087-1116, October.
    14. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2023. "Spatial performance analysis in basketball with CART, random forest and extremely randomized trees," Annals of Operations Research, Springer, vol. 325(1), pages 495-519, June.
    15. Fabio Fonti & Massimo Maoret, 2016. "The direct and indirect effects of core and peripheral social capital on organizational performance," Strategic Management Journal, Wiley Blackwell, vol. 37(8), pages 1765-1786, August.
    16. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    17. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.
    18. Sabin R. Paul, 2021. "Estimating player value in American football using plus–minus models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(4), pages 313-364, December.
    19. Štrumbelj, Erik & Vračar, Petar, 2012. "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting, Elsevier, vol. 28(2), pages 532-542.
    20. Miguel Ángel Pérez-Toledano & Francisco J Rodriguez & Javier García-Rubio & Sergio José Ibañez, 2019. "Players’ selection for basketball teams, through Performance Index Rating, using multiobjective evolutionary algorithms," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-20, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:6:y:2010:i:1:n:3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.