Document Type : Research Paper
Authors
1 Assistant Professor of Sport Management, University of Guilan, Rasht
2 Assistant Professor of Management, University of Guilan, Rasht
3 Assistant Professor of Sport Management, Sports Sciences Research Institute, Tehran
4 Ph.D. Student in Sport Management, University of Guilan, Rasht
Abstract
The aim of this study is Evaluating Efficiency of the Teams Basketball that Presence in Olympic 2016 Brazil. The study is descriptive-analytical in terms of data collection is attributive and libraries. The statistical population consisted of all teams participating in the Men's Olympic Basketball in Brazil (2016). Because of limitation in amount of population, the sample size was considered equal to the population size (N=12). The data refer to the site of the World Federation of Association basketball (FIBA) and classified in two offensive and defensive phases and for analyzed with using SPSS19 and DEA software. The results showed that two teams in offensive phase include Nigeria and USA has full efficiency were equal to 1. Croatia, France, Lithuania, Argentina and Nigeria also the most efficient teams as well as teams in the tournament were the defensive phase. Also, there was no relationship between ranked teams’ performance and position. As a result, the coaches of the basketball team of Iran and other countries can recognize the opponents' offensive and defensive status by choosing more effective plans and exercises and choosing a more appropriate strategy to confront their rivals and reduce their distance with the titular countries.
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Main Subjects
2. Barros, c.p., Assef, A., & Sa-Erp, F. (2009). Brazilizn football league technical efficiency: a simar and Wilson approach, Journal of sports Economics, 20: 078-1249.
3. Chitnis, A., & Vaidya, O. (2014). Performance assessment of tennis players: Application of DEA. Procedia-Social and Behavioral Sciences, 133, 74-83.
4. Clemente, F. M., Martins, F. M. L., Kalamaras, D., & Mendes, R. S. (2015). Network analysis in basketball: Inspecting the prominent players using centrality metrics. Journal of Physical Education and Sport, 15(2), 212 -217
5. Coloba, G., Estellita, M., & Pereira, L. M. (2006). Performance assessment of the soccer team in Brazil using DEA. Pesquisa Operational, 26(3), 521-36.
6. Colombier, C. (2008). Efficiency in public infrastructure provision: A theoretical note. Journal of Economic Studies, 35(6), 528-43.
7. Cooper, W. W., Ramón, N., Ruiz, J. L., & Sirvent, I. (2011). Avoiding large differences in weights in cross-efficiency evaluations: Application to the ranking of basketball players. Journal of CENTRUM Cathedra: The Business and Economics Research Journal, 4(2), 197-215
8. Csataljay, G., James, N., Hughes, M. D., & Dancs, H. (2012). Performance differences between winning and losing basketball teams during close, balanced and unbalanced quarters. Journal of Human Sport & Exercise, 7 (2), 356-64.
9. Csataljay, G., O'Donoghue, P., Hughes, M., & Dancs, H. (2009). Performance indicators that distinguish winning and losing teams in basketball. International Journal of Performance Analysis in Sport, 9(1), 60-6.
10. Escuer, M. E., & Cebrian, L. I. (2010). Measurement of the efficiency of football teams in the champions league. Journal Managerial and Decision Economics, 31(6), 373-86.
11. Ecuer, E., Cebrian, M. C., & Isabel, L. (2006). Performance in sports teams results and potential in the professional soccer league in Spain. Management Decision, 8, 1020-30.
12. Faraji, R. (2009). Measure the effectiveness of using a combination DEA and Fuzzy TOPSIS (Unpublished master's thesis). University of Shahid Beheshti, Tehran (Persian).
13. Farrel, M. J. (1956). The measurement of Productivity and Efficiency. Journal of the Royal Statistical Society, 120(3), 254-89.
14. García, J., Ibáñez, S. J., Martinez De Santos, R., Leite, N., & Sampaio, J. (2013). Identifying basketball performance indicators in regular season and playoff games. Journal of Human Kinetics, 36(1), 161-8.
15. Goncharuk, A. G. (2009). Improving of the efficiency through benchmarking: A case of Ukrainian breweries, benchmarking: An International Journal, 16(1), 70-87.
16. Haas, D., Kocher, M., & Sutter, M. (2004). Measuring efficiency of German football teams by Data Envelopment Analysis. Central European Journal of Operations Research and Economics, (12), 251-68.
17. Horowitz, I. (2017). An efficiency evaluation of men’s college basketball coaches. The American Economist, 62(1), 77-98.
18. Ibáñez, S. J., Sampaio, J., Sáenz-López, P., Giménez, J., & Janeira, M. A. (2003). Game statistics discriminating the final outcome of junior world basketball championship matches (Portugal 1999). Journal of Human Movement Studies, 45(1), 1-20.
19. Lee, Y. H. (2009). Evaluating management efficiency of Korean professional teams using Data Envelopment Analysis. International Journal of Applied Sports Sciences, 21(2), 93-112.
20. Mendes, L., & Janeira, M. (2001). Basketball performance-multivariate study in Portuguese professional male basketball teams. In Hughes, M. D., & Tavares, F. (Eds.), Notational analysis of sport-IV (103-11). Cardiff: UWIC.
21. Milanović, D., Štefan, L., Sporiš, G., & Dinko, V. (2016). Effects of game-related statistics parameters on final outcome in female basketball teams on the Olympic games in London 2012. International Journal of Current Advanced Research, 5, 1-5.
22. MirKazemi, S.O., JahaniRad, Z., NikNahad, S. (2016). Efficiency Measurement of Iranian Men's Volleyball Teams in the Premier League. Sport Development and Managemen, 5(2): 146- 160. (Persian).
23. Rafieii, f., & Nakhjirkan, S. (2008). Measuring Relative Efficiency of Iran s Airlines Using Data Envelopment Analysis. Thesis of the Ministry of Science, Research and Technology - Tarbiat Modares University. (Persian).
24. Rahimi, Gh. (2005). Performance evaluation and continuous improvement of the organization. Journal of Prudence, 25(17), 8-28. (Persian).
25. Ribeiro, A. S., & Lima, F. (2012). Portuguese football league efficiency and players' wages. Journal of Applied Economics Lettersn, 19(6), 560-99.
26. Sajjaadi, S. J., & Omrani, H. (2008). Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies. Energy Policy, 36(11), 4247-54. (Persian).
27. Sameti M., Rezvani M.A. (2001). Efficiency of Major Universities in Iran (Using Dea Method). Tahghighat-E-Eghtesadi, 10(59): 117-47.
28. Soleimani-Damaneh, J. (2010). Major League Soccer's performance evaluation by using management techniques and the integration with mathematical techniques, physical education and sports science (Unpublished masterˊs thesis). Tehran University, Tehran. (Persian).
29. Soleimani-Damaneh, J., Hamidi, M., & Sajjadi, N. (2014). Performance evaluating of Iranian Football Primer League by merging DEA with AHP. Sport management Studies, 6(22), 105-26. (Persian)
30. Tiedemann T, Francksen T, (2010). Assessing the performance of German Bundesliga football players: a no-parametric Meta frontier approach, (12): 145-71
31. Thanasis, B. P. (2010). Analyzing the operating efficiency of Greek football clubs, enter departmental programmed of postgraduate studies (I.P.P.S.) in Economics (Unpublished masterˊ thesis), Greece, and Thessaloniki.
32. Zak, T. A., Huang, C. J., & Siegfried, J. J. (1979). Production efficiency: The case of professional basketball. Journal of Business, 52, 379-92.
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