Futbolda Defansif Aksiyonların Göreceli Etkinliğinin Veri Zarflama Analizi ile Belirlenmesi: Türkiye Süper Ligi Örneği

Year 2025, Volume: 9 Issue: 21, 81 - 90, 29.07.2025

Nurullah Ekmekci

https://doi.org/10.58202/joecopol.1719365

Abstract

Bu çalışma, Türkiye Süper Ligi 2023–2024 sezonunda mücadele eden 20 profesyonel futbol takımının defansif performanslarını göreli etkinlik temelinde analiz etmeyi amaçlamaktadır. Modern futbolda savunma performansı, sadece bireysel becerilerle değil, takımın bütüncül stratejik yaklaşımıyla şekillenmektedir. Dolayısıyla bu alanda yapılacak ölçümler, futbol takımlarının sportif başarısı için kritik öneme sahiptir. Bu bağlamda, çalışmada çıktı yönelimli Veri Zarflama Analizi (VZA) yöntemi kullanılarak, takımların savunma aksiyonları (savunma müdahalesi, araya girme, engellenen şut ve uzaklaştırma) ile sezon genelinde elde ettikleri sonuçlar (yenilen gol sayısı ve kaybedilmeyen maç sayısı) arasındaki etkinlik ilişkisi değerlendirilmiştir. Analiz sonucunda Galatasaray, Fenerbahçe, Kasımpaşa, Pendikspor ve İstanbulspor gibi hem üst sıralarda hem de orta-alt sıralarda yer alan bazı takımlar tam etkin bulunurken; diğer takımlar için teknik veya ölçeksel iyileştirme önerileri sunulmuştur. Özellikle düşük puanla sezonu tamamlayan ancak tam etkin bulunan takımların mevcut savunma kaynaklarını etkili kullandıkları; buna karşın başarıya ulaşmak için bu kaynakların yeterli olmadığı tespit edilmiştir. Elde edilen bulgular, teknik ekiplerin savunma stratejilerini geliştirmeleri açısından önemli bir karar desteği sunmaktadır.

Keywords

Veri Zarflama Analizi (VZA) , Göreli Etkinlik , Defansif Performans , Futbol Analitiği , Türkiye Süper Ligi , Çıktı Yönelimli Model , Sportif Performans Değerlendirmesi

Ethical Statement

Çalışma için etik kurul iznine gerek yoktur.

Supporting Institution

Selçuk Üniversitesi BAP Koordinatörlüğü

Project Number

25401064

Thanks

Bu çalışma Selçuk Üniversitesi BAP Koordinatörlüğü tarafından (Proje No: 25401064) desteklenmiştir.

Determining the Relative Efficiency of Defensive Actions in Football Using Data Envelopment Analysis: The Case of Turkish Super League

Abstract

This study aims to analyze the defensive performance of 20 professional football teams competing in the 2023–2024 season of the Turkish Super League based on relative efficiency. In modern football, defensive performance is shaped not only by individual skills but also by the team's holistic strategic approach. Therefore, performance measurement in this area holds critical importance for the sporting success of football teams. In this context, the study employs output-oriented Data Envelopment Analysis (DEA) method to evaluate the efficiency relationship between teams’ defensive actions (tackles, interceptions, shots blocked, and clearances) and their season-long outcomes (number of goals conceded and number of matches not lost). The analysis revealed that some teams—including Galatasaray, Fenerbahçe, Kasımpaşa, Pendikspor, and İstanbulspor—were found to be efficient despite being positioned both at the top and mid-lower sections of the league table. For the remaining teams, technical or scale-related improvement recommendations were provided. Particularly, teams that finished the season with fewer points but achieved full efficiency were identified as utilizing their defensive resources effectively; however, these resources were deemed insufficient to achieve overall success. The findings offer valuable decision support for coaching staff aiming to enhance defensive strategies.

Keywords

Data Envelopment Analysis (DEA) , Relative Efficiency , Defensive Performance , Football Analytics , Turkish Super League , Output-Oriented Model , Sports Performance Evaluation

Project Number

25401064

References

• Aldamak, A., & Zolfaghari, S. (2017). Review of efficiency ranking methods in data envelopment analysis. Measurement, 106, 161–172. doi:10.1016/j.measurement.2017.04.028
• Ayyıldız, E., & Murat, M. (2018). Türkiye süper ligi’nin veri zarflama analizi ile değerlendirilmesi. CBÜ Beden Eğitimi ve Spor Bilimleri Dergisi, 13(1), 73–86.
• Barros, C. P., & Garcia-del-Barrio, P. (2008). Efficiency measurement of the English football Premier League with a random frontier model. Economic Modelling, 25(5), 994–1002. doi:10.1016/j.econmod.2008.01.004
• Barros, C. P., & Leach, S. (2006). Performance evaluation of the English Premier Football League with data envelopment analysis. Applied Economics, 38(12), 1449–1458. doi:10.1080/00036840500396574
• Carrillo, M., & Jorge, J. M. (2016). A multiobjective DEA approach to ranking alternatives. Expert Systems with Applications, 50, 130–139. doi:10.1016/j.eswa.2015.12.022
• Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429–444.
• Deloitte. (2023). Annual review of football finance 2023. https://www.deloitte.com/global/en/Industries/tmt/research/gx-annual-review-of-football-finance.html adresinden alındı
• Espitia-Escuer, M., & García-Cebrián, L. I. (2006). Performance in sports teams: Results and potential in the professional soccer league in Spain. Management Decision, 44(8), 1020–1030. doi:10.1108/00251740610690595
• García-Cebrián, L. I., Zambom-Ferraresi, F., & Lera-López, F. (2018). Efficiency in European football teams using WindowDEA: Analysis and evolution. International Journal of Productivity and Performance Management, 67(9), 2126–2148. doi:10.1108/IJPPM-02-2018-0053
• González-Gómez, F., & Picazo-Tadeo, A. J. (2009). Can we be satisfied with our football team? Evidence from Spanish professional football. Journal of Sports Economics, 11(4), 418–442. doi:10.1177/1527002509341020
• Gökgöz, F., & Yalçın, E. (2022). A slack-based DEA analysis for the world cup teams. Team Performance Management, 28(1/2), 1–20. doi:10.1108/TPM-07-2021-0050
• Gökgöz, F., & Yalçın, E. (2023). Analyzing the champions league teams via decision models. Team Performance Management, 29(1/2), 15–44. doi:10.1108/TPM-05-2022-0041
• 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), 1-13. doi:10.1177/2158244021989257
• Halkos, G., & Petrou, K. N. (2019). Treating undesirable outputs in DEA: A critical review. Economic Analysis and Policy, 62, 97-104. doi:10.1016/j.eap.2019.01.005
• Hoye, R., Smith, A., Nicholson, M., & Stewart, B. (2015). Sport Management: Principles and Applications. New York: Routledge.
• Kern, A., Schwarzmann, M., & Wiedenegger, A. (2013). Measuring the efficiency of English Premier League football: A two‐stage data envelopment analysis approach. Sport, Business and Management, 2(3), 177–195. doi:10.1108/20426781211261502
• Keskin, H. İ., & Öndes, H. (2020). Seçilmiş Avrupa futbol kulüplerinin etkinliğinin ölçülmesi: VZA ve panel tobit modeli. Sosyoekonomi, 28(43), 153–174. doi:10.17233/sosyoekonomi.2020.01.09
• Kritikos, M. N. (2017). A full ranking methodology in data envelopment analysis based on a set of dummy decision making units. Expert Systems with Applications, 77, 211–225. doi:10.1016/j.eswa.2017.01.042
• Miragaia, D. A., Ferreira, J. J., Carvalho, A., & Ratten, V. (2019). Interactions between financial efficiency and sports performance: Data for a sustainable entrepreneurial approach of European professional football clubs. Journal of Entrepreneurship and Public Policy, 8(1), 84–102. doi:10.1108/JEPP-D-18-00060
• Pyatunin, A. V., V. A., Sherstneva, N. L., Mironova, S. P., Dneprov, S. A., & Grabozdin, Y. P. (2016). The economic efficiency of European football clubs – Data envelopment analysis (DEA) approach. International Journal of Environmental and Science Education, 11(15), 7515–7534.
• Ribeiro, A. S., & Lima, F. (2011). Portuguese football league efficiency and players’ wages. Applied Economics Letters, 19(6), 599–602. doi:10.1080/13504851.2011.591719
• Roboredo, M. C., Aizemberg, L., & Meza, L. A. (2015). The DEA game cross efficiency model applied to the Brazilian football championship. Procedia Computer Science, 55, 758–763. doi:10.1016/j.procs.2015.07.161
• Román-Gallego, J.-Á., Pérez-Delgado, M.-L., Cofiño-Gavito, F.-J., Conde, M. Á., & Rodríguez-Rodrigo, R. (2023). Analysis and parameterization of sports Performance: A case study of soccer. Applied Sciences, 13(23). doi:10.3390/app132312767
• Rubem, A. P., & Brandão, L. C. (2015). Multiple criteria data envelopment analysis – An application to UEFA EURO 2012. Procedia Computer Science, 55, 186–195. doi:10.1016/j.procs.2015.07.031
• Samut, P., & Cafri, R. (2015). Measuring efficiency of public hospitals with a non-parametric method: Malmquist and DEA analysis. International Journal of Health Planning and Management, 30(1), 1-15. doi:10.1002/hpm.2249
• Santin, D. (2024). Measuring the technical efficiency of football legends: Who were Real Madrid’s all-time most efficient players? International Transactions in Operational Research, 21(3), 439–452. doi:10.1111/itor.12082
• Villa, G., & Lozano, S. (2016). Assessing the scoring efficiency of a football match. European Journal of Operational Research, 255(2), 559–569. doi:10.1016/j.ejor.2016.05.024
• Villa, G., & Lozano, S. (2019). Assessing offensive/defensive strategies in a football match using DEA. International Journal of Sport Finance, 14, 131–146. doi:10.32731/ijsf/143.082019.01
• WhoScored.com. (2025). Türkiye Süper Ligi 2023/2024 sezonu takım istatistikleri. https://www.whoscored.com adresinden alındı
• Yılmaz, M., Aksezer, Ç., & Atan, T. (2019). Dynamic frontier estimation for monitoring team performances: A case on Turkish first division football league. Team Performance Management, 25(3/4), 212–228. doi:10.1108/TPM-11-2017-0076
• Zambom-Ferraresi, F., García-Cebrián, L. I., Lera-López, F., & Iráizoz, B. (2017). Performance Eevaluation in the UEFA champions league. Journal of Sports Economics, 18(5), 448-470.
• Zambom-Ferraresi, F., Rios, V., & Lera-Lopez, F. (2018). Determinants of sport performance in European football: What can we learn from the data? Decision Support Systems, 114, 18-28. doi:10.1016/j.dss.2018.08.006
• Zelenkov, Y., & Solntsev, I. (2017). Measuring the efficiency of Russian football premier league clubs. Electronic Journal of Applied Statistical Analysis, 10(3), 773–789. doi:10.1285/i20705948v10n3p773