Two-phased DEA-MLA approach for predicting efficiency of NBA players
DOI:
https://doi.org/10.2298/YJOR140430030RKeywords:
data envelopment analysis, efficiency analysis, predictive analytics, machine learningAbstract
In sports, a calculation of efficiency is considered to be one of the most challenging tasks. In this paper, DEA is used to evaluate an efficiency of the NBA players, based on multiple inputs and multiple outputs. The efficiency is evaluated for 26 NBA players at the guard position based on existing data. However, if we want to generate the efficiency for a new player, we would have to re-conduct the DEA analysis. Therefore, to predict the efficiency of a new player, machine learning algorithms are applied. The DEA results are incorporated as an input for the learning algorithms, defining thereby an efficiency frontier function form with high reliability. In this paper, linear regression, neural network, and support vector machines are used to predict an efficiency frontier. The results have shown that neural networks can predict the efficiency with an error less than 1%, and the linear regression with an error less than 2%.References
Aizemberg, L., Roboredo, M. C., Ramos, T. G., de Mello, J. C. C. S., Meza, L. A., Alves, A. M., "Measuring the NBA Teams’ Cross-Efficiency by DEA Game", American Journal of Operations Research, 4 (03) (2014) 101. DOI=http://dx.doi.org/10.4236/ajor.2014.43010.
Andersen, P., Petersen, N. C., "A Procedure for Ranking Efficient Units in Data Envelopment Analysis", Management Science, 39 (10) (1993) 1261-1264.
Charnes, A., "Measuring the Efficiency of Decision Making Units", European Journal of Operational Research, 2 (6) (1978) 429-444.
Drucker, H., Burges, C. J., Kaufman, L., Smola, A., Vapnik, V., "Support Vector Regression Machines", Advances in Neural Information Processing Systems, 9 (1997) 155-161.
ESPN, "ESPN", 2013, Retrieved from http://espn.go.com/nba/salaries.
Fernandez, R. C., Gomez Nunez, T., Garrido, R. S., "Analysis of the Efficiency of Spanish Soccer League Players (2009/10) Using the Metafrontier Approach", Estudios de economíaaplicada, 30(2) (2012) 565-578.
Hill, J., Jolly, N., "Salary Distribution and Collective Bargaining Agreements: A Case Study of the NBA", Industrial Relations: A Journal of Economy and Society, 51 (2) (2012) 342-363.
Hong K.H., Ha S.H., Shin C.K., Park S.C., "Evaluating the Efficiency of System Integration Projects Using Data Envelopment Analyses (DEA) and Machine Learning", Expert Systems with Application, 16 (1999) 283-296.
Jane, W.J., "Overpayment and Reservation Salary in the Nippon Professional Baseball League: A Stochastic Frontier Analysis", Journal of Sports Economics, (2012) 579-598.
Jayaraman, A. R., Srinivasan, M. R., Jeremic, V., "Empirical Analysis of Banks in India using DBA and DEA" Management, 18 (69) (2013) 25-35.
Jeremic, V., Radojicic, Z., "A New Approach in the Evaluation of Team Chess Championships Rankings", Journal of Quantitative Analysis in Sports, 6 (3) (2010) 1-11.
Jiang, B., Chen, W., Zhang, H., Pan, W., "Supplier’s Efficiency and Performance Evaluation using DEA-SVM Approach", Journal of Software, North America, 8 (1) (2013) 25-30.
Kao H-Y, Chang T-K, Chang Y-C, "Classification of Hospital Web Security Efficiency Using Data Envelopment Analysis and Support Vector Machine," Mathematical Problems in Engineering, (2013) Article ID 542314, 8 pages, 2013. doi:10.1155/2013/542314.
Lee, B. L., Worthington, A. C., "A Note on the ‘Linsanity’ of Measuring the Relative Efficiency of National Basketball Association Guards", Applied Economics, 45 (29) (2013) 4193-4202.
Lovell, C., Rouse, A., "Equivalent standard DEA models to provide super-efficiency scores", Journal of the Operational Research Society, 54 (2003) 101-108.
Mierswa, I., Wurst, M., Klinkenberg, R., Scholz, M., Euler, T., "Yale: Rapid Prototyping for Complex Data Mining Tasks", in: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, (2006) 935-940, ACM.
Mitchell T., "Machine Learning", McGraw Hill, 1997.
Moreno, P., Lozano, S., "A Network DEA Assessment of Team Efficiency in the NBA", Annals of Operations Research, 214 (1) (2014) 99-124.
National Basketball Association, "National Basketball Association", 2013, Retrieved from http://www.nba.com/.
Poiter K., "True Efficient Frontiers in Production Performance Assessment Using Machine Learning and Data Envelopment Analysis", PhD Thesis, (2010) Retrieved from http://scholarlyrepository.miami.edu/cgi/viewcontent.cgi?article=1934&context=oa_dissertations.
Radovanović, S., Radojičić, M., Jeremić, V., Savić, G., "A Novel Approach in Evaluating Efficiency of Basketball Players", Management, 67 (2013) 37-45.
Ray, S., "Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research", United Kingdom, Cambridge, Press Syndicate of the University of Cambridge, 2004.
Regan, C. S., "The Price of Efficiency: Examining the Effects of Payroll Efficiency on Major League Baseball Attendance", Applied Economics Letters, 19(11) (2012) 1007-1015.
Ribeiro, A., and Lima, F., "Portuguese Football League Efficiency and Players' Wages", Applied Economics Letters, 19 (6) (2012) 599-602.
Savic, G., Makajic-Nikolic, D., Suknovic, M., "AHP-DEA Measure for Study Program Selection", SymOrg 2012, Zlatibor, University of Belgrade, Faculty of Organizational Sciences, 1217-1223.
Savic, G., Radosavljevic, M., Ilijevski, D., "DEA Window Analysis Approach for Measuring the Efficiency of Serbian Banks Based on Panel Data", Management, 65 (2013) 5-14.
Scheel, H., "EMS: Efficiency Measurement System User’s Manual", Operations Research and Witshaftinsformetik, University of Dortmund, Germany, 2000.
Schumaker, R., Solieman, O., Chen, H., "Sports Data Mining", New York, Springer, 2010.
Scully, G. W., "Pay and Performance in Major League Baseball", The American Economic Review, 64 (6) (1974) 915-930.
Sueyoshi, T., Mika, G., "Returns to Scale vs. Damages to Scale in Data Envelopment Analysis: An Impact of U.S. Clean Air Act on Coal-Fired Power Plants", Omega, 41 (2) (2013) 164-175.
Tsang, S.S., Chen, Y.F., "Facilitating Benchmarking with Strategic Grouping and Data Envelopment Analysis: The Case of International Tourist Hotels in Taiwan", Asia Pacific Journal of Tourism Research, 18 (5) (2012) 1-16.
Yeh C.C., Dhi D.J., Hsu M.F., "A Hybrid Approach of DEA, Rough Set and Support Vector Machine for Business Failure Prediction", Expert Systems with Application, 37 (2010) 1535-1541.
Zak, T., Huang, C., Siegfried, J., "Production Efficiency: The Case of Professional Basketball", The Journal of Business, 52 (3) (1979) 379-392.
Zhang W, Tang S.Y., Zhu Y.F., Wang W.P., "Comparative Studies of Support Vector Regression between Reproducing Kernel and Gaussian Kernel", World Academy of Science, Engineering and Technology, 65 (2010) 933-941.
Downloads
Published
Issue
Section
License
Copyright (c) 2014 YUJOR
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
