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Selecting non-zero weights to evaluate effectiveness of basketball players with DEA

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  1. Chih-Hai Yang & Hsuan-Yu Lin & Chiang-Ping Chen, 2014. "Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA," Annals of Operations Research, Springer, vol. 217(1), pages 565-589, June.
  2. Fusco, Elisa, 2015. "Enhancing non-compensatory composite indicators: A directional proposal," European Journal of Operational Research, Elsevier, vol. 242(2), pages 620-630.
  3. Thomas Sexton & Herbert Lewis, 2012. "Measuring efficiency in the presence of head-to-head competition," Journal of Productivity Analysis, Springer, vol. 38(2), pages 183-197, October.
  4. Li, Yongjun & Wang, Lizheng & Li, Feng, 2021. "A data-driven prediction approach for sports team performance and its application to National Basketball Association," Omega, Elsevier, vol. 98(C).
  5. Marco Sandri & Paola Zuccolotto & Marica Manisera, 2020. "Markov switching modelling of shooting performance variability and teammate interactions in basketball," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1337-1356, November.
  6. Pelloneová Natalie, 2023. "Evaluating Hockey Players Using Andersen and Petersen's Super-Efficiency Model: Who is the Best Czech Hockey Player in the NHL?," Polish Journal of Sport and Tourism, Sciendo, vol. 30(3), pages 23-28, September.
  7. Alireza Amirteimoori & Simin Masrouri & Feng Yang & Sohrab Kordrostami, 2017. "Context-based competition strategy and performance analysis with fixed-sum outputs: an application to banking sector," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1461-1469, November.
  8. Song, Kai & Gao, Yiran & Shi, Jian, 2020. "Making real-time predictions for NBA basketball games by combining the historical data and bookmaker’s betting line," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
  9. Rodolfo Metulini & Giorgio Gnecco, 2023. "Measuring players’ importance in basketball using the generalized Shapley value," Annals of Operations Research, Springer, vol. 325(1), pages 441-465, June.
  10. Qing Zhu & Renxian Zuo & Yuze Li & Shan Liu, 2021. "A system evaluation of NBA rookie contract execution efficiency with stacked Autoencoder and hybrid DEA," Operational Research, Springer, vol. 21(4), pages 2771-2807, December.
  11. Guohua Feng & Todd Jewell, 2021. "Productivity and efficiency at english football clubs: a random coefficient approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 571-604, November.
  12. Zhang Li Li, 2011. "Group Identification Method for Features of Human Capital Inner Quality Structure," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 2(3), pages 102-105, September.
  13. Isidoro Guzmán-Raja & Manuela Guzmán-Raja, 2021. "Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football," SAGE Open, , vol. 11(1), pages 21582440219, February.
  14. Nikolaos, Chatzistamoulou & Theodoros, Antonakis & Konstantinos, Kounetas, 2020. "Salary cap and National Basketball Association teams' productive performance. A two stage Data Envelopment Analysis approach under a metatechnology framework," MPRA Paper 98811, University Library of Munich, Germany.
  15. Anthony Glass & Karligash Kenjegalieva & Jason Taylor, 2015. "Game, set and match: evaluating the efficiency of male professional tennis players," Journal of Productivity Analysis, Springer, vol. 43(2), pages 119-131, April.
  16. Nikos Chatzistamoulou & Kounetas Kostas & Antonakis Theodor, 2022. "Salary Cap, Organizational Gap, and Catch-up in the Performance of NBA Teams: A Two-Stage DEA Model Under Heterogeneity," Journal of Sports Economics, , vol. 23(2), pages 123-155, February.
  17. Ahn, Heinz & Neumann, Ludmila & Vazquez Novoa, Nadia, 2012. "Measuring the relative balance of DMUs," European Journal of Operational Research, Elsevier, vol. 221(2), pages 417-423.
  18. José L. Ruiz & Diego Pastor & Jesús T. Pastor, 2013. "Assessing Professional Tennis Players Using Data Envelopment Analysis (DEA)," Journal of Sports Economics, , vol. 14(3), pages 276-302, June.
  19. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
  20. Víctor Blanco & Román Salmerón & Samuel Gómez-Haro, 2018. "A Multicriteria Selection System Based on Player Performance: Case Study—The Spanish ACB Basketball League," Group Decision and Negotiation, Springer, vol. 27(6), pages 1029-1046, December.
  21. Akber Aman Shah & Desheng Wu & Vladmir Korotkov, 2019. "Are Sustainable Banks Efficient and Productive? A Data Envelopment Analysis and the Malmquist Productivity Index Analysis," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
  22. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 571-587, December.
  23. An‐Pang Wang & Che‐Wei Chang & Juin‐Ming Tsai & Shiu‐Wan Hung, 2021. "A performance evaluation of Major League Baseball teams: An integrated social network and data envelopment analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1421-1434, September.
  24. M B Wright, 2009. "50 years of OR in sport," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 161-168, May.
  25. Woodruff, Christopher J., 2010. "Multivariate optimisation for procurement of emergency services equipment - Teams of the best or the best of teams?," European Journal of Operational Research, Elsevier, vol. 205(1), pages 186-194, August.
  26. Lewis, Herbert F. & Lock, Kathleen A. & Sexton, Thomas R., 2009. "Organizational capability, efficiency, and effectiveness in Major League Baseball: 1901-2002," European Journal of Operational Research, Elsevier, vol. 197(2), pages 731-740, September.
  27. Zbranek, Peter, 2013. "Data Envelopment Analysis as a Tool for Evaluation of Employees’ Performance," Acta Oeconomica et Informatica, Faculty of Economics and Management, Slovak Agricultural University in Nitra (FEM SPU), vol. 16(1), pages 1-10, February.
  28. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
  29. Josef Jablonsky, 2022. "Individual and team efficiency: a case of the National Hockey League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 479-494, June.
  30. Yanzhi Bi, 2021. "Analyzing the performance of the Major League Baseball Teams by using the Data Envelopment Analysis," Business & Entrepreneurship Journal, SCIENPRESS Ltd, vol. 10(1), pages 1-1.
  31. Song, Kai & Shi, Jian, 2020. "A gamma process based in-play prediction model for National Basketball Association games," European Journal of Operational Research, Elsevier, vol. 283(2), pages 706-713.
  32. Arnab Adhikari & Adrija Majumdar & Gaurav Gupta & Arnab Bisi, 2020. "An innovative super-efficiency data envelopment analysis, semi-variance, and Shannon-entropy-based methodology for player selection: evidence from cricket," Annals of Operations Research, Springer, vol. 284(1), pages 1-32, January.
  33. Villa, G. & Lozano, S., 2016. "Assessing the scoring efficiency of a football match," European Journal of Operational Research, Elsevier, vol. 255(2), pages 559-569.
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