Measuring the Performance of Teams in the Indian Premier League
Author(s)
Sanjeet Singh
ABSTRACT
In this paper, using the Data Envelopment Analysis (DEA), we have measured the technical efficiency of cricket teams in the Indian Premier League. Taking the data for the 2009 season, the input used by the teams is approached by the total expenses which include players’ wage bill and wage of the support staff and other miscellaneous expenses. Output is measured by the points awarded, net run rate, profit and revenues. Efficiency scores are highly correlated with the performance in the league with a few exception, and when decomposing inefficiency into technical inefficiency and scale inefficiency it can be shown that the largest part of inefficiency can be explained by suboptimal scale of production and ineffficient transformation of inputs into outputs.
In this paper, using the Data Envelopment Analysis (DEA), we have measured the technical efficiency of cricket teams in the Indian Premier League. Taking the data for the 2009 season, the input used by the teams is approached by the total expenses which include players’ wage bill and wage of the support staff and other miscellaneous expenses. Output is measured by the points awarded, net run rate, profit and revenues. Efficiency scores are highly correlated with the performance in the league with a few exception, and when decomposing inefficiency into technical inefficiency and scale inefficiency it can be shown that the largest part of inefficiency can be explained by suboptimal scale of production and ineffficient transformation of inputs into outputs.
KEYWORDS
DEA, Linear Programming, Technical Efficiency, Cricket, Indian Premier League, Sports Management
DEA, Linear Programming, Technical Efficiency, Cricket, Indian Premier League, Sports Management
Cite this paper
nullS. Singh, "Measuring the Performance of Teams in the Indian Premier League," American Journal of Operations Research, Vol. 1 No. 3, 2011, pp. 180-184. doi: 10.4236/ajor.2011.13020.
nullS. Singh, "Measuring the Performance of Teams in the Indian Premier League," American Journal of Operations Research, Vol. 1 No. 3, 2011, pp. 180-184. doi: 10.4236/ajor.2011.13020.
References
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[1] http://www.rediff.com/business/slide-show/slide-show-1-ipl-brand-value-crashes/20110408.htm [2] S. Rao, “Indian Premier League,” Edinburgh Middle East Report (EMER), Retrieved 2010-03-25. [3] S. Singh, S. Gupta and V. Gupta, “Dynamic Bidding Strategy for Players Auction in IPL,” International Journal of Sports Science and Engineering, Vol. 5, No. 1, 2011, pp. 3-16. [4] S. Szymanski and R. Smith, “The English Football Industry: Profit, Performance and Industrial Structure,” Inter national Review of Applied Economics, Vol. 11, No. 1, 1997, pp. 135-153. doi:10.1080/02692179700000008 [5] S. Dobson and J. Goddard, “The Economics of Football,” Cambridge University Press, Cambridge, 2001. doi:10.1017/CBO9780511493225 [6] T. Anderson and G. Sharp, “A New Measure of Baseball Batters Using DEA,” Annals of Operations Research, Vol. 73, No. 1, 1997, pp. 141-155. doi:10.1023/A:1018921026476 [7] S. D. Jahangir, H. Mehrzad and H. Sajadi, “Evaluating the Performance of Iranian Football Teams Utilizing Linear Programming,” American Journal of Operations Research, Vol. 1, No. 3, 2011, pp. 65-72. [8] J. L. Fizel and M. D’Itri, “Estimating Managerial Efficiency: The Case of College Basketball Coaches,” Journal of Sport Management, Vol. 10, No. 4, 1996, pp. 435- 445. [9] M. J. Farrell, “The Measurement of Productive Efficiency,” Journal of the Royal Statistical Society, Vol. 120, No. 3, 1957, pp. 253-290. doi:10.2307/2343100 [10] A. Charnes, W. Cooper and E. Rhodes, “Measuring the Efficiency of Decision Making Units,” European Journal of Operational Research, Vol. 2, No. 6, 1978, pp. 429-444. doi:10.1016/0377-2217(78)90138-8 [11] R. S. Barr and T. F. Siems, “Bank Failure Prediction Using DEA to Measure Management Quality,” In: R. S. Barr, R. V. Helgason and J. L. Kennington, Eds., Advances in Metaheuristics, Optimization, and Stochastic Modeling Techniques, Kluwer Academic Publishers, Boston, 1997, pp. 341-365. [12] R. Fare, S. Grosskopf, J. Logan and C. A. K. Lovell, “Measuring Efficiency in Production: With an Application to Electric Utilities,” In: R. Fare, G. Grosskopf and C. A. K. Lovell, Eds., The Measurement of Efficiency of Production, Kluwer-Nijhoff Publishing, Kluwer Acade- mic Publishers, Boston, 1985, pp. 185-214. [13] L. M. Seiford and J. Zhu, “Profitability and Marketability of the Top 55 US Commercial Banks,” Management Science, Vol. 45, No. 9, 199, pp. 1270-1288. [14] K. Wilkens and J. Zhu, “Portfolio Evaluation and Benchmark Selection: A Mathematical Programming Approach,” Journal of Business and Economic Statistics, Vol. 11, No. 3, 2001, pp. 319-323. [15] S. Gattoufi, M. Oral and A. Reisman, “A Taxonomy for Data Envelopment Analysis,” Socio-Economic Planning Sciences, Vol. 38, No. 2-3, 2004, pp. 141-158. doi:10.1016/S0038-0121(03)00022-3 [16] S. Gattoufi, M. Oral, A. Kumar and A. Reisman, “Epistemology of Data Envelopment Analysis and Comparison with Other Fields of OR/MS for Relevance to Applications,” Socio-Economic Planning Sciences, Vol. 38, No. 2-3, 2004, pp. 123-140. doi:10.1016/S0038-0121(03)00021-1 [17] W. W. Cooper, L. M. Seiford and K. Tone, “Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References, and DEA-Solver Software,” Kluwer Academic Publishers, Dordrecht, 2007. [18] http://www.espncricinfo.com/ipl2009/content/current/series/374163.html [19] http://www.iiflcap.com [20] J. Zhu, “Quantitative Models for Performance Evaluation and Benchmarking: DEA with Spreadsheets,” 2nd Edition, Springer, Boston, 2009.