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Journals / Cumhuriyet Science Journal / 2020 / Cilt: 41 - Sayı: 4

Prediction of UEFA champions league elimination rounds winners using machine learning algorithms

Coşkun KUŞ
İsmail Hakkı KINALIOĞLU
Pages
951–967
Publication Date
2022-10-12
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In the first application, the most successfulmethod is naive bayes classifier (86.66%) and in the second application, the most successfulmethod is random forest (74.81%).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the teams that qualified for the next round as a result of two-legged matchupsare predicted using the data collected from the UEFA (Union of European FootballAssociations) Champions League group stage matches.
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Key Findings & Data:The data are collected from the matches played in the Champions Leagueorganizations held between 2010-2018.
💡
Conclusion & Impact:In the first application, the most successfulmethod is naive bayes classifier (86.66%) and in the second application, the most successfulmethod is random forest (74.81%).
🔬Design:Modeling & Simulation
📍Scope:2010-2018 Verileri
⚙️Variables:Domain Parameters

Abstract

In this study, the teams that qualified for the next round as a result of two-legged matchupsare predicted using the data collected from the UEFA (Union of European FootballAssociations) Champions League group stage matches. The study contributes to the literaturein terms of variety of methods used and content of the dataset compared to other studiesconducted on football data. It is also a pioneering study to predict the outcome of a two-leggedmatchup. The data are collected from the matches played in the Champions Leagueorganizations held between 2010-2018. Classification methods as Artificial Neural Network,K-Nearest Neighbors, Logistic Regression Analysis, Naive Bayes Classifier, Random Forestand Support Vector Machine are used for the prediction. Two applications are carried out totest the successes of the classification models. In the first application, the most successfulmethod is naive bayes classifier (86.66%) and in the second application, the most successfulmethod is random forest (74.81%).

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Cite This Article

KUŞ, C., KINALIOĞLU, İ. H. (2022). Prediction of UEFA champions league elimination rounds winners using machine learning algorithms. Cumhuriyet Science Journal, Cilt: 41 - Sayı: 4, 951–967. https://ajindex.com/articles/477683

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