Abstract
Over the last number of years, sports analytics has become more popular in supporting personnel decisions, evaluating player and team performances, and predicting game results in various sports. One of the most traditional sports, football is also modernizing its ways based on sports analytics techniques. The purpose of this study is to propose a football match prediction model for Turkish Super League (TSL) using supervised machine learning techniques. To do this, based on the TSL data of last five years (2013 to 2018), game result prediction models were established using classification techniques including logistics regression, linear and quadratic discriminant analyses, K-nearest neighbors, support vector machines, and random forests. An ensemble of 10 models based on seven different techniques is suggested.
Original language | English |
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Title of host publication | Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference |
Editors | Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga |
Publisher | Springer Verlag |
Pages | 273-280 |
Number of pages | 8 |
ISBN (Print) | 9783030237554 |
DOIs | |
Publication status | Published - 2020 |
Event | International Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey Duration: 23 Jul 2019 → 25 Jul 2019 |
Publication series
Name | Advances in Intelligent Systems and Computing |
---|---|
Volume | 1029 |
ISSN (Print) | 2194-5357 |
ISSN (Electronic) | 2194-5365 |
Conference
Conference | International Conference on Intelligent and Fuzzy Systems, INFUS 2019 |
---|---|
Country/Territory | Turkey |
City | Istanbul |
Period | 23/07/19 → 25/07/19 |
Bibliographical note
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Keywords
- Ensemble modeling
- Football analytics
- Machine learning
- Match result prediction
- Supervised learning
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Saricaoğlu, A. E., Aksoy, A. (2020). Prediction of turkish super league match results using supervised machine learning techniques. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference (pp. 273-280). (Advances in Intelligent Systems and Computing; Vol. 1029). Springer Verlag. https://doi.org/10.1007/978-3-030-23756-1_34
Saricaoğlu, Ahmet Emin ; Aksoy, Abidin ; Kaya, Tolga. / Prediction of turkish super league match results using supervised machine learning techniques. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A.Cagri Tolga. Springer Verlag, 2020. pp. 273-280 (Advances in Intelligent Systems and Computing).
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title = "Prediction of turkish super league match results using supervised machine learning techniques",
abstract = "Over the last number of years, sports analytics has become more popular in supporting personnel decisions, evaluating player and team performances, and predicting game results in various sports. One of the most traditional sports, football is also modernizing its ways based on sports analytics techniques. The purpose of this study is to propose a football match prediction model for Turkish Super League (TSL) using supervised machine learning techniques. To do this, based on the TSL data of last five years (2013 to 2018), game result prediction models were established using classification techniques including logistics regression, linear and quadratic discriminant analyses, K-nearest neighbors, support vector machines, and random forests. An ensemble of 10 models based on seven different techniques is suggested.",
keywords = "Ensemble modeling, Football analytics, Machine learning, Match result prediction, Supervised learning",
author = "Saricaoğlu, {Ahmet Emin} and Abidin Aksoy and Tolga Kaya",
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Saricaoğlu, AE, Aksoy, A 2020, Prediction of turkish super league match results using supervised machine learning techniques. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Advances in Intelligent Systems and Computing, vol. 1029, Springer Verlag, pp. 273-280, International Conference on Intelligent and Fuzzy Systems, INFUS 2019, Istanbul, Turkey, 23/07/19. https://doi.org/10.1007/978-3-030-23756-1_34
Prediction of turkish super league match results using supervised machine learning techniques. / Saricaoğlu, Ahmet Emin; Aksoy, Abidin; Kaya, Tolga.
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A.Cagri Tolga. Springer Verlag, 2020. p. 273-280 (Advances in Intelligent Systems and Computing; Vol. 1029).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
TY - GEN
T1 - Prediction of turkish super league match results using supervised machine learning techniques
AU - Saricaoğlu, Ahmet Emin
AU - Aksoy, Abidin
AU - Kaya, Tolga
N1 - Publisher Copyright:© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Over the last number of years, sports analytics has become more popular in supporting personnel decisions, evaluating player and team performances, and predicting game results in various sports. One of the most traditional sports, football is also modernizing its ways based on sports analytics techniques. The purpose of this study is to propose a football match prediction model for Turkish Super League (TSL) using supervised machine learning techniques. To do this, based on the TSL data of last five years (2013 to 2018), game result prediction models were established using classification techniques including logistics regression, linear and quadratic discriminant analyses, K-nearest neighbors, support vector machines, and random forests. An ensemble of 10 models based on seven different techniques is suggested.
AB - Over the last number of years, sports analytics has become more popular in supporting personnel decisions, evaluating player and team performances, and predicting game results in various sports. One of the most traditional sports, football is also modernizing its ways based on sports analytics techniques. The purpose of this study is to propose a football match prediction model for Turkish Super League (TSL) using supervised machine learning techniques. To do this, based on the TSL data of last five years (2013 to 2018), game result prediction models were established using classification techniques including logistics regression, linear and quadratic discriminant analyses, K-nearest neighbors, support vector machines, and random forests. An ensemble of 10 models based on seven different techniques is suggested.
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Saricaoğlu AE, Aksoy A, Kaya T. Prediction of turkish super league match results using supervised machine learning techniques. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Springer Verlag. 2020. p. 273-280. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-23756-1_34