PREMİER LİG'DE ATLETİK VERİMLİLİĞİN ÖLÇÜLMESİ: BİR STOKASTİK SINIR ANALİZİ YAKLAŞIMI

Öz

Bu çalışma, 2008/2009 ve 2017/2018 sezonları arasında İngiltere Premier Ligi’nde atletik verimliliği dört boyutta: genel, ofansif, defansif ve iç saha verimliliği, stokastik sınır analizi (SSA) yöntemiyle incelemektedir. Bulgular, orta saha ve hücum oyuncularına yapılan yatırımların hem ofansif hem de genel verimliliği önemli ölçüde artırdığını, buna karşılık kaleci piyasa değerinin defansif verimlilik üzerinde istatistiksel olarak anlamlı bir etkisinin olmadığını göstermektedir. Ayrıca, ortalama seyirci sayısının iç saha verimliliğiyle pozitif ilişkisi, taraftarların sportif başarı üzerindeki önemini yeniden teyit etmektedir. Verimsizlik sınır analizi ise sık teknik direktör değişiklikleri ve yüksek kadro sirkülasyonunun teknik verimsizliğin temel belirleyicileri olduğunu; buna karşılık organizasyonel istikrarın ve düşük oyuncu değişiminin performansı artırdığını göstermektedir. Elde edilen bulgulara dayanarak, kaynak tahsisini iyileştirme, istikrar sağlama ve uzun vadeli kapasite yatırımları yapma yoluyla hem kulüp düzeyinde performansın hem de sistem genelinde verimliliğin artırılmasına yönelik politika önerileri sunulmaktadır.

Anahtar Kelimeler

• Stokastik Sınır Analizi
• Verimlilik
• İngiltere Premier Lig

MEASURING ATHLETIC EFFICIENCY IN THE PREMIER LEAGUE: A STOCHASTIC FRONTIER ANALYSIS APPROACH

Öz

This study investigates the determinants of athletic efficiency in the English Premier League with a stochastic frontier analysis (SFA) across four dimensions: overall, offensive, defensive, and home-game efficiency using data from the 2008/2009 to 2017/2018 seasons. The findings reveal that investments in midfielders and attackers significantly enhance both offensive and overall efficiency while goalkeeper market value does not have a statistically significant effect on defensive efficiency. Furthermore, average attendance is positively associated with home-game efficiency, reinforcing the importance of fan engagement in sporting success. The inefficiency frontier analysis identifies frequent managerial turnover and high squad volatility as key drivers of technical inefficiency, while organizational stability and lower player turnover contribute to improved performance. Based on these insights, the study proposes several actionable recommendations for club managers and league organizers aimed at enhancing sporting performance and system-wide efficiency through better resource allocation, strategic stability, and investment in long-term capabilities.

Anahtar Kelimeler

• Stochastic Frontier Analysis
• Efficiency
• English Premier League

Kaynakça

1. Barros, C., & Garcia-del-Barrio, P. (2008). Efficiency measurement of the English football Premier League with a random frontier model. Economic Modelling, 25(5), 994–1002. https://doi.org/10.1016/j.econmod.2008.01.004
2. Barros, C., & Rossi, G. (2014). A Bayesian stochastic frontier of Italian football. Applied Economics, 46(20), 2398–2407. https://doi.org/10.1080/00036846.2014.902023
3. Battese, G., & Coelli, T. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20, 325- 332. https://doi.org/10.1007/BF01205442
4. Boscá, J. E., Liern, V., Martínez, A., & Sala, R. (2009). Increasing offensive or defensive efficiency? An analysis of Italian and Spanish football. Omega, 37(1), 63- 78. https://doi.org/10.1016/j.omega.2006.08.002
5. Castellano, J., Casamichana, D., & Lago, C. (2013). The use of match statistics that discriminate between successful and unsuccessful soccer teams. Journal of Human Kinetics, 31, 139–147. 10.2478/v10078-012-0015-7
6. Carmichael, F., & Thomas, D. (2005). Home-Field Effect and Team Performance: Evidence From English Premiership Football. Journal of Sports Economics, 6(3), 264- 281. https://doi.org/10.1177/1527002504266154
7. Carney, K. (2023). Sales, stats and strategies: how Brighton and Brentford stay one step ahead. Retrieved March 8, 2025, from https://www.theguardian.com/football/2023/jan/20/sales-stats-and-strategies-how-brighton-and-brentford-stay-one-step-ahead
8. Cifuentes-Faura, J. (2021). Efficiency and transparency of Spanish football clubs: A non-parametric approach. Managerial Economics, 43(6), 1850–1860. https://doi.org/10.1002/mde.3492

9. Dawson, P., Dobson, S., & Gerrard, B. (2000). Stochastic Frontiers and the Temporal Structure of Managerial Efficiency in English Soccer. Journal of Sports Economics, 1(4), 341–362. https://doi.org/10.1177/152700250000100402
10. Deloitte. (2024, June). Annual Review of Football Finance. Retrieved March 1, 2025, from https://www.deloitte.com/content/dam/assets-zone2/uk/en/docs/services/financial-advisory/2024/deloitte-uk-annual-review-of-football-finance.pdf
11. Franck, E., & Nüesch, S. (2012). Talent and/or popularity: What does it take to be a superstar? Economic Inquiry, 50(1), 202–216. https://doi.org/10.1111/j.1465-7295.2010.00360.x
12. García-Sánchez, I. M. (2007). Efficiency and effectiveness of Spanish football teams: A three-stage DEA approach. Central European Journal of Operations Research, 15, 21–45. https://doi.org/10.1007/s10100-006-0017-4
13. Goumas, C. (2013). Modelling home advantage in sport: A new approach. International Journal of Performance Analysis in Sport, 13(2), 428–439. https://doi.org/10.1080/24748668.2013.11868659
14. Guzmán, I., & Morrow, S. (2007). Measuring efficiency and productivity in professional football teams: evidence from the English Premier League. Central European Journal of Operations Research, 15, 309–208. https://doi.org/10.1007/s10100-007-0034-y
15. Guzmán-Raja, I., & Guzmán-Raja, M. (2021). Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence from Spanish Professional Football. SAGE Open, 11(1), https://doi.org/10.1177/2158244021989257
16. Haas, D. (2003). Productive efficiency of English football teams—a data envelopment analysis approach. Managerial and Decision Economics, 24(5), 403–410. https://doi.org/10.1002/mde.1105
17. Hepburn, D., Ritchie, C., & Altimas, C. (2025). Every Premier Club Ranked by Their Wage Bill. Retrieved March 12, 2025, from https://www.givemesport.com/premier-league-wage-bill/
18. Kern, A., Schwarzmann, M., & Wiedenegger, A. (2012). Measuring the efficiency of English Premier League football: A two‐stage data envelopment analysis approach. Sport, Business and Management, 2(3), 177–195. https://doi.org/10.1108/20426781211261502
19. Kim JH. (2019). Multicollinearity and misleading statistical results. Korean Journal of Anesthesiology, 72(6), 558-569. https://doi.org/10.4097/kja.19087
20. Liu, H., Gómez, M.-Á., Lago-Peñas, C., & Sampaio, J. (2016). Match statistics related to winning in the group stage of the 2014 Brazil FIFA World Cup. Journal of Sports Sciences, 33(12), 1205–1213. https://doi.org/10.1080/02640414.2015.1022578
21. Müller, O., Simons, A., & Weinmann, M. (2017). Beyond crowd judgments: Data-driven estimation of market value in association football. European Journal of Operational Research, 263(2), 611–624. https://doi.org/10.1016/j.ejor.2017.05.005
22. Nevill, A. M., & Holder, R. L. (1999). Home advantage in sport: An overview of studies on the advantage of playing at home. Sports Medicine, 28(4), 221–236. https://doi.org/10.2165/00007256-199928040-00001
23. Pérez-González, A., de Carlos, P., & Alén, E. (2022). An analysis of the efficiency of football clubs in the Spanish First Division through a two-stage relational network DEA model: a simulation study. Operational Research, 22, 3089–3112. https://doi.org/10.1007/s12351-021-00650-5
24. Ribeiro, A., & Lima, F. (2012). Portuguese Football League efficiency and players' wages. Applied Economics Letters, 19(6), 599–602. https://doi.org/10.1080/13504851.2011.591719
25. Rohde, M., & Breuer, C. (2018). Competing by investments or efficiency? Exploring financial and sporting efficiency of club ownership structures in European football. Sport Management Review, 21(5), 563–581. https://doi.org/10.1016/j.smr.2018.01.001
26. Simar, L., & Wilson, P. W. (2007). Estimation and inference in two‐stage, semi‐parametric models of production processes. Journal of Econometrics, 136(1), 31–64. https://doi.org/10.1016/j.jeconom.2005.07.009
27. Thakkar, P., & Shah, M. (2021). An Assessment of Football Through the Lens of Data Science. Annals of Data Science, 8, 823–836. https://doi.org/10.1007/s40745-021-00323-2
28. Transfermarkt. (2008–2018). Premier League. Retrieved May 01, 2025, from https://www.transfermarkt.com.tr/premier-league/startseite/wettbewerb/GB1
29. Vamplew, W. (2022). Sports Economics for Non-Economists. Routledge.
30. Villa, G., & Lozano, S. (2019). Assessing Offensive/Defensive Strategies in a Football Match Using DEA. International Journal of Sport Finance, 14(3), 131-146. https://doi.org/10.32731/IJSF.143.082019.01
31. Villa, G., & Lozano, S. (2024). A payroll efficiency analysis of Europe’s top football leagues. IMA Journal of Management Mathematics, dpae014. https://doi.org/10.1093/imaman/dpae014
32. Yenilmez, İ. (2024). Productivity, efficiency and entrepreneurial–innovative university index: An analysis for universities in Türkiye. Estuscience–Se, 25(3), 415–426. https://doi.org/10.18038/estubtda.1455818
33. Yenilmez, İ. (2025). Efficiency analysis of Turkish container ports: SFA or DEA? Verimlilik Dergisi (Productivity for Logistics Issue), 105–118. https://doi.org/10.51551/verimlilik.1522007
34. Zambom-Ferraresi, F., Iráizoz, B., & Lera-López, F. (2019). Are football managers as efficient as coaches? Performance analysis with ex ante and ex post inputs in the Premier League. Applied Economics, 51(3), 303–314. https://doi.org/10.1080/00036846.2018.1495821
35. Zelenkov, Y., & Solntsev, I. (2017). Measuring the efficiency of Russian Football Premier League clubs. Electronic Journal of Applied Statistical Analysis, 10(3), 773–789. https://core.ac.uk/download/pdf/231329218.pdf