A stakeholder assessment of basketball player evaluation metrics

Jose Antonio Martinez, Laura Martínez

Abstract

In this research we examined the opinions of basketball stakeholders regarding several questions of special interests to valuate players. Players, coaches, agents, journalists, editors, bloggers, researchers, analysts, fans and chairs participated in this macro-research. After analysing their opinions using the content analysis methodology, we found that current player evaluation systems are insufficient to fulfill the expectations of stakeholders regarding the definition of value, because they fail to rate intangibles. In addition, the importance of qualitative thinking is prominent and should be considered in valuating such intangibles. The current system of valuation used in Euroleague and Spanish ACB League (Ranking) is acknowledged as deficient, but stakeholders think that other advanced metrics do not significantly outperform Ranking. Implications for management, decision making and marketing in basketball are finally discussed.


Keywords

Player evaluation metrics; Basketball; Stakeholders; Decision making

References

Aitchison, J. The statistical analysis of compositional data (with discussion). Journal of the Royal Statistical Society, Series B (Statistical Methodology). 1982; 44(2):139-177.

Ariely, D. Predictably Irrational: The Hidden Forces That Shape Our Decisions. HarperCollins; 2008.

Ballard, C. The art of a beautiful game. Simon & Shuster: New York; 2009.

Barfield, O. Saving the appearances; Study in idolatry (2nd edition). Middletown, CT: Wesleyan University Press; 1988.

Berger, P.L., Luckmann, T. The social construction of reality: A treatise in the sociology of knowledge.Garden City, NY: Doubleday; 1966.

Berri, D.J. Who is 'most valuable'? Measuring the player's production of wins in the National Basketball Association. Managerial and Decision Economics. 1999; 20:411-427. https://doi:10.1002/1099-1468(199912)20:8

Berri, D.J. Measuring performance in the National Basketball Association. Working paper; 2010.

Berri, D.J., Brook, S.L., Schmidt, M.B. Does One Simply Need to Score to Score? International Journal of Sport Finance. 2007; 2(4):190-205.

Berri, D.J., Bradbury, J.C. Working in the land of metricians. Journal of Sports Economics. 2010; 11(1):29-47. https://doi.org/10.1177/1527002509354891

Berri, D.J., Schmidt, M.B. Stumbling on wins: Two economists expose the pitfalls on the road to victory in professional sports. FT Press; 2010.

Berri, D.J., Schmidt, M.B., Brook, S.L. The wages of wins: Taking measure of the many myths in modern sport. Palo Alto,CA: Stanford University Press; 2006.

Colditz, G.A., Atwood, K.A., Emmons, K., Monson, R.R., Willett, W.C., Trichopoulos, D., Hunter, D.J. Harvard Cancer Risk Index. Cancer Causes Control 11. 2000; 477-488. https://doi.org/10.1023/A:1008984432272

Cooper, W.W., Ruiz, J.L., Sirvent, I. Selecting non-zero weights to evaluate effectiveness of basketball players with DEA. European Journal of Operational Research. 2009; 195(2):563-574. https://doi.org/10.1016/j.ejor.2008.02.012

Doolittle, B., Pelton, K. Pro Basketball Prospectus 2009-10. Prospectus Entertainment Ventures LLC; 2009.

Doyle, P. Marketing management and strategy. Fourth edition. Financial Times/ Prentice Hall; 2006.

Esteller-Moré, A., Eres-García, M. A note on consistent players' valuation. Journal of Sports Economics. 2002; 3(4):354-360. https://doi.org/10.1177/152700202237500

Fransella, F., Bell, R., Bannister, R. A manual for repertory grid technique. Second Edition. Wiley; 2004.

Gigerenzer, G., Todd, P.M., & The Abc Research Group. Simple Heuristics That Make. Us Smart. New York: Oxford University Press; 1999.

Grissom, R.J., & Kim, J.J. Effect sizes for research. A broad practical approach. Mahwah, NJ: LEA; 2005.

Hayduk, L.A. LISREL Issues, Debates and Strategies. Ed. Johns Hopkins University Press: Baltimore, MD; 1996.

Hayes, A.F., Krippendorff, K. Answering the call for a standard reliability measure for coding data. Communication Methods and Measures. 2007; 1:77-89. https://doi.org/10.1080/19312450709336664

Hollinger, J. Pro Basketball Forecast. Washington, D.C.: Potomac, Inc; 2005.

Hunter, J.E., Schmidt, F.L. Methods of Meta-Analysis: Correcting Error and Bias in Research. Findings. 2nd Edition. Newbury Park: Sage Publications; 2004. https://doi.org/10.4135/9781412985031

John, D.J., Loken, B., Kim, K.H., Monga, A.B. Brand Concept Maps: a methodology for identifying brand association networks. Journal of Marketing Research. 2006; 43(4):549-563. https://doi.org/10.1509/jmkr.43.4.549

Kelly, S.W., Tian, K. Fanatical consumption. An investigation of the behaviour of sports fans through textual data. In Kahle Riley (Ed), Sports marketing and the psychology of marketing communication. 2004; 27-65.

Krippendorff, K. Content analysis: an introduction to its methodology. 2nd ed. Sage publication. Thousand Oask, California; 2004.

Kubatko, J. Calculating Win Shares. Retrieved from http://www.basketballreference.com/about/ws.html; 2009

Kuksov, D., Villas-Boas, J.M. When more alternatives lead to less choice. Marketing Science. 2010; 29(3):507-524. https://doi.org/10.1287/mksc.1090.0535

Levitt, S.D., Dubner, S.J. Freakonomics: A rogue economist explores the hidden side of everything. New York: William Morrow; 2005.

Lewin, D., Rosenbaum, D.T. The pot calling the kettle black. Are NBA statistical models more irrational than "irrational" decision-makers? New England Symposium on Statistics in Sports. Harvard University Science Center; 2007.

Lewis, M.M. Moneyball: The art of winning an unfair game. W.W. Norton & Company Inc; 2003.

Lewis, M.M. The no-stats all stars. Downloaded from http://www.nytimes.com/2009/02/15/magazine/15Battier-t.html; 2009.

Martínez, J.A. Una revisión de los sistemas de valoración de jugadores de baloncesto (I). Descripción de los métodos existentes. Revista Internacional de Derecho y Gestión del Deporte. 2010a; 10:37-77.

Martínez, J.A. Una revisión de los sistemas de valoración de jugadores de baloncesto (II). Competiciones oficiales y ligas de fantasía. Revista Internacional de Derecho y Gestión del Deporte. 2010b; 11:48-68.

Martínez, J.A. Una revisión de los sistemas de valoración de jugadores de baloncesto (III). Discusión general. Revista Internacional de Derecho y Gestión del Deporte. 2010c; 12:44-79.

Martínez, J.A., Martínez, L. Un método probabilístico para las clasificaciones estadísticas de jugadores en baloncesto. Revista Internacional de Ciencias del Deporte. 2010d; 18(6):13-36. https://doi.org/10.5232/ricyde2010.01802

Martínez, M., Choi, T., Martínez, J.A., Martínez, A.R. ISO 9000/1994, ISO 9001/2000 and TQM: The performance debate revisited. Journal of Operations Management. 2009; 27(6):495-511. https://doi.org/10.1016/j.jom.2009.04.002

Mayo, D.G., Cox, D.R. Frequentists statistics as a theory of inductive inference. In Rojo, J. (ed.), 2nd Lehmann Symposium- Optimally. IMS Lecture Notes-Monographs Series. 2006; 1-28. https://doi.org/10.1214/074921706000000400

Neuendorf, K.A. The content analysis guidebook. Sage Publications. Thousand Oaks, London; 2002.

Nichols, J. Explanation of Composite Score. Retrieved from http://basketballstatistics.com/aboutcs.html; 2009

O'donoghue, P.G., Williams, J. An evaluation of human and computer-based predictions of the 2003 rugby union world cup. International Journal of Computer Science in Sport. 2004; 3(1):5-22.

Oliver, D. Basketball on paper. Rules and tools for performance analysis. Washington, D. C.: Brassey's, INC; 2004.

Pawlowsky-Glahn, V., Egozcue, J.J. Geometric approach to statistical analysis on the simplex. Stochastic Environmental Research and Risk Assessment (SERRA). 2001; 15(5):384-398. https://doi.org/10.1007/s004770100077

Pearl, J. Causality: Models of Reasoning and Inference. Cambridge University Press; 2000.

Piette, J., Anand, S., Zhang, K. Scoring and shooting abilities of NBA players. Journal of Quantitative Analysis in Sports. 2010; 6(1) Article 1. https://doi.org/10.2202/1559-0410.1194

Ree, M.J., Carreta, T.H. The role of measurement error in familiar statistics. Organizational Research Methods. 2006; 9(1):99-112. https://doi.org/10.1177/1094428105283192

Riffe, D., Lacy, S., Fico, F. Analyzing media messages. Using quantitative content analysis in research. Taylor & Francis Group. New York; 2008.

Rothman, K.J. No adjustments are needed for multiple comparisons. Epidemiology. 1990; 1(1):43-46. https://doi.org/10.1097/00001648-199001000-00010

Rothman, K.J., Greenland, S., Lash, T.L. Modern Epidemiology. Third edition. Philadelphia: Luppincott, Williams & Wilkins; 2008.

Saaty, T.L. Relative Measurement and Its Generalization in Decision Making Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors The Analytic Hierarchy/Network Process. Review of the Royal Spanish Academy of Sciences. 2008; 102(2):251-318. https://doi.org/10.1007/BF03191825

Savitz, D.A., Olshan, A.F. Decribing data requires o adjustment for multiple comparisons: a reply form Savitz and Olshan. American Journal of Epidemiology. 1998; 147:813-814. https://doi.org/10.1093/oxfordjournals.aje.a009532

Schmidt, F.L., Hunter, J.E. Measurement error in psychological research: Lessons from 26 research scenarios. Psychological Methods. 1996; 1(2):199-223. https://doi.org/10.1037/1082-989X.1.2.199

Skinner, B. The Price of Anarchy in Basketball. Journal of Quantitative Analysis in Sports. 2010; 6(1) Article 3. https://doi.org/10.2202/1559-0410.1217

Thompson, C.J. Eureka! and other tests of signifcance: A new look at evaluating interpretive research, in Advances in Consumer Research Volume 17, eds. Marvin E. Goldberg and Gerald Gorn and Richard W. Pollay, Provo, UT : Association for Consumer Research. 1990; (25-30).

Thompson, C.J. Interpreting Consumers: A Hermeneutical Framework for Deriving Marketing Insights from the Texts of Consumers Consumption Stories, Journal of Marketing Research. 1997; 34(Nov.):438-55. https://doi.org/10.2307/3151963

Treutlein, J. APER: Player Efficiency Ranking adjusted for Assisted Field Goals. Retrieved from http://www.hoopdata.com/recent.aspx?aid=39; 2009.

Winston, W.L. Mathletics. New Jersey: Princeton University Press; 2009.

Zaltman, G. How Customers Think: Essential Insights into the Mind of the Markets. Boston: Harvard Business School Press; 2003.




DOI: https://doi.org/10.4100/jhse.2011.61.17