Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques

Serhan Berke Erden; Ünal Berke Kaymak; Tolga Kaya

doi:10.1007/978-3-031-39777-6_32

Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques

Serhan Berke Erden^*, Ünal Berke Kaymak, Tolga Kaya

^*Bu çalışma için yazışmadan sorumlu yazar

İşletme Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

It is a matter of controversy whether the transfers made in the football industry are efficient or not. The aim of the study is to explore the efficiency of transfers made in the football industry using machine learning techniques. In this context, a methodology to model the success of transfers based on Turkish Super League data is suggested. In the modelling processes, the data of the transfers taken from the Tranfermarkt website were used. The target variable is created as binary and the classification problem is the consideration. Accordingly, the data of 16 teams and 2261 players in total were analysed using advanced machine learning methods. Results reveal that transfers of young and homegrown players are relatively more efficient compare to those of the others.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Editörler	Cengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	262-268
Sayfa sayısı	7
ISBN (Basılı)	9783031397769
DOI'lar	https://doi.org/10.1007/978-3-031-39777-6_32
Yayın durumu	Yayınlandı - 2023
Etkinlik	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey Süre: 22 Ağu 2023 → 24 Ağu 2023

Yayın serisi

Adı	Lecture Notes in Networks and Systems
Hacim	759 LNNS
ISSN (Basılı)	2367-3370
ISSN (Elektronik)	2367-3389

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	22/08/23 → 24/08/23

Bibliyografik not

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Belgeye Erişim

10.1007/978-3-031-39777-6_32

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Erden, S. B., Kaymak, Ü. B., & Kaya, T. (2023). Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques. In C. Kahraman, I. U. Sari, B. Oztaysi, S. Cevik Onar, S. Cebi, & A. Ç. Tolga (Eds.), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference (pp. 262-268). (Lecture Notes in Networks and Systems; Hac. 759 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-39777-6_32

Erden, Serhan Berke ; Kaymak, Ünal Berke ; Kaya, Tolga. / Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques. Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. editör / Cengiz Kahraman ; Irem Ucal Sari ; Basar Oztaysi ; Sezi Cevik Onar ; Selcuk Cebi ; A. Çağrı Tolga. Springer Science and Business Media Deutschland GmbH, 2023. pp. 262-268 (Lecture Notes in Networks and Systems).

@inproceedings{5a244c2e08c042dcb8bc9bd75196beee,

title = "Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques",

abstract = "It is a matter of controversy whether the transfers made in the football industry are efficient or not. The aim of the study is to explore the efficiency of transfers made in the football industry using machine learning techniques. In this context, a methodology to model the success of transfers based on Turkish Super League data is suggested. In the modelling processes, the data of the transfers taken from the Tranfermarkt website were used. The target variable is created as binary and the classification problem is the consideration. Accordingly, the data of 16 teams and 2261 players in total were analysed using advanced machine learning methods. Results reveal that transfers of young and homegrown players are relatively more efficient compare to those of the others.",

keywords = "Classification, Football, Machine Learning, Transfer Efficiency, Turkish Super League",

author = "Erden, {Serhan Berke} and Kaymak, {{\"U}nal Berke} and Tolga Kaya",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference ; Conference date: 22-08-2023 Through 24-08-2023",

year = "2023",

doi = "10.1007/978-3-031-39777-6_32",

language = "English",

isbn = "9783031397769",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "262--268",

editor = "Cengiz Kahraman and Sari, {Irem Ucal} and Basar Oztaysi and {Cevik Onar}, Sezi and Selcuk Cebi and Tolga, {A. {\c C}ağrı}",

booktitle = "Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference",

address = "Germany",

}

Erden, SB, Kaymak, ÜB & Kaya, T 2023, Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques. in C Kahraman, IU Sari, B Oztaysi, S Cevik Onar, S Cebi & AÇ Tolga (eds), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Lecture Notes in Networks and Systems, hac. 759 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 262-268, Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, Istanbul, Turkey, 22/08/23. https://doi.org/10.1007/978-3-031-39777-6_32

Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques. / Erden, Serhan Berke; Kaymak, Ünal Berke; Kaya, Tolga.
Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. ed. / Cengiz Kahraman; Irem Ucal Sari; Basar Oztaysi; Sezi Cevik Onar; Selcuk Cebi; A. Çağrı Tolga. Springer Science and Business Media Deutschland GmbH, 2023. p. 262-268 (Lecture Notes in Networks and Systems; Hac. 759 LNNS).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques

AU - Erden, Serhan Berke

AU - Kaymak, Ünal Berke

AU - Kaya, Tolga

PY - 2023

Y1 - 2023

N2 - It is a matter of controversy whether the transfers made in the football industry are efficient or not. The aim of the study is to explore the efficiency of transfers made in the football industry using machine learning techniques. In this context, a methodology to model the success of transfers based on Turkish Super League data is suggested. In the modelling processes, the data of the transfers taken from the Tranfermarkt website were used. The target variable is created as binary and the classification problem is the consideration. Accordingly, the data of 16 teams and 2261 players in total were analysed using advanced machine learning methods. Results reveal that transfers of young and homegrown players are relatively more efficient compare to those of the others.

AB - It is a matter of controversy whether the transfers made in the football industry are efficient or not. The aim of the study is to explore the efficiency of transfers made in the football industry using machine learning techniques. In this context, a methodology to model the success of transfers based on Turkish Super League data is suggested. In the modelling processes, the data of the transfers taken from the Tranfermarkt website were used. The target variable is created as binary and the classification problem is the consideration. Accordingly, the data of 16 teams and 2261 players in total were analysed using advanced machine learning methods. Results reveal that transfers of young and homegrown players are relatively more efficient compare to those of the others.

KW - Classification

KW - Football

KW - Machine Learning

KW - Transfer Efficiency

KW - Turkish Super League

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DO - 10.1007/978-3-031-39777-6_32

M3 - Conference contribution

AN - SCOPUS:85172732220

SN - 9783031397769

T3 - Lecture Notes in Networks and Systems

SP - 262

EP - 268

BT - Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

A2 - Kahraman, Cengiz

A2 - Sari, Irem Ucal

A2 - Oztaysi, Basar

A2 - Cevik Onar, Sezi

A2 - Cebi, Selcuk

A2 - Tolga, A. Çağrı

PB - Springer Science and Business Media Deutschland GmbH

T2 - Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

Y2 - 22 August 2023 through 24 August 2023

ER -

Erden SB, Kaymak ÜB, Kaya T. Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques. In Kahraman C, Sari IU, Oztaysi B, Cevik Onar S, Cebi S, Tolga AÇ, editörler, Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Springer Science and Business Media Deutschland GmbH. 2023. p. 262-268. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-39777-6_32

Classifying the Success of Transfers Made by Turkish Super-League Teams Using Advanced Machine Learning Techniques

Özet

Yayın serisi

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Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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