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Journals / Herkes için Spor ve Rekreasyon Dergisi / 2026 / Volume: 8 Issue: 3

Artificial Intelligence Applications in Sports Refereeing: A Systematic Review and Methodological Comparison

Spor Hakemliğinde Yapay Zekâ Uygulamaları: Sistematik Bir Derleme ve Metodolojik Karşılaştırma

Meltem Tarım Karakuzu(AKDENIZ UNIVERSITY, FACULTY OF SPORTS SCIENCE, DEPARTMENT OF SPORTS MANAGEMENT)0000-0001-7292-7030
Alparslan Erman(AKDENIZ UNIVERSITY, FACULTY OF SPORTS SCIENCE, DEPARTMENT OF SPORTS MANAGEMENT, SPORTS MANAGEMENT PR.)0000-0002-6056-4524
Pages
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Publication Date
2026-09-30
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AI Summary & Key Takeaways

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

Overall, AI has potential to enhance the accuracy of refereeing decisions and operational efficiency; however, performance limitations, data quality issues, and ethical concerns remain sig-nificant challenges.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Artificial Intelligence (AI) technologies are increasingly being used in sports refereeing to support decision-making, object and event tracking, and player- or team-related analysis.
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Key Findings & Data:This systematic review aimed to examine the application areas of AI technol-ogies in sports refereeing across different sports, identify the analytical methods em-ployed, and compare their methodological performance based on reported accuracy rates.
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Conclusion & Impact:Overall, AI has potential to enhance the accuracy of refereeing decisions and operational efficiency; however, performance limitations, data quality issues, and ethical concerns remain sig-nificant challenges.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Artificial Intelligence · Deep Learning · Referee

Abstract

Artificial Intelligence (AI) technologies are increasingly being used in sports refereeing to support decision-making, object and event tracking, and player- or team-related analysis. This systematic review aimed to examine the application areas of AI technol-ogies in sports refereeing across different sports, identify the analytical methods em-ployed, and compare their methodological performance based on reported accuracy rates. The literature search and study selection process were conducted in accordance with PRISMA guidelines. Scopus, Web of Science, IEEE Xplore, EBSCO, and Google Scholar databases were searched using the string “((Artificial Intelligence) OR (machine learning) OR (deep learning)) AND Sport AND referee”. A total of 404 records were initially identified; after duplicate removal, 374 studies remained. Following title and abstract screening, 45 articles were assessed in full text, and 14 studies met the inclusion criteria. The findings showed that AI applications were predominantly implemented in football. The primary application areas were Referee Decision Support Systems (7 stud-ies), Object and Event Tracking (5 studies), and Player and Team Analysis (2 studies). The most frequently used methods included CNN, LSTM, and YOLO-based deep learning models. Image-processing-based models, particularly YOLO-based approaches, gener-ally demonstrated higher accuracy compared to sensor-based systems. Overall, AI has potential to enhance the accuracy of refereeing decisions and operational efficiency; however, performance limitations, data quality issues, and ethical concerns remain sig-nificant challenges.

Özet

Yapay Zekâ (YZ) teknolojileri, karar verme sürecini desteklemek, nesne ve olay takibi yapmak ve oyuncu veya takımlarla ilgili analizler gerçekleştirmek amacıyla spor hakemliğinde giderek daha fazla kullanılmaktadır. Bu sistematik derleme, farklı spor dallarında spor hakemliğinde YZ teknolojilerinin uygulama alanlarını incelemek, kullanılan analitik yöntemleri belirlemek ve bildirilen doğruluk oranlarına dayalı olarak bu yöntemlerin metodolojik performansını karşılaştırmayı amaçlamıştır. Literatür taraması ve çalışma seçimi süreci, PRISMA kılavuzlarına uygun olarak yürütülmüştür. Scopus, Web of Science, IEEE Xplore, EBSCO ve Google Scholar veritabanlarında “((Yapay Zeka) VEYA (makine öğrenimi) VEYA (derin öğrenme)) VE Spor VE hakem” dizesi kullanılarak arama yapılmıştır. Başlangıçta toplam 404 kayıt tespit edildi; yinelenenler çıkarıldıktan sonra 374 çalışma kaldı. Başlık ve özet taramasının ardından 45 makalenin tam metni değerlendirildi ve 14 çalışma dahil edilme kriterlerini karşıladı. Bulgular, yapay zeka uygulamalarının ağırlıklı olarak futbolda uygulandığını gösterdi. Başlıca uygulama alanları Hakem Karar Destek Sistemleri (7 çalışma), Nesne ve Olay Takibi (5 çalışma) ve Oyuncu ve Takım Analizi (2 çalışma) idi. En sık kullanılan yöntemler arasında CNN, LSTM ve YOLO tabanlı derin öğrenme modelleri yer aldı. Görüntü işleme tabanlı modeller, özellikle de YOLO tabanlı yaklaşımlar, sensör tabanlı sistemlere kıyasla genel olarak daha yüksek doğruluk sergiledi. Genel olarak yapay zekâ, hakem kararlarının doğruluğunu ve operasyonel verimliliği artırma potansiyeline sahiptir; ancak performans sınırlılıkları, veri kalitesi sorunları ve etik kaygılar önemli birer zorluk olmaya devam etmektedir.

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Cite This Article

Karakuzu, M. T., Erman, A. (2026). Artificial Intelligence Applications in Sports Refereeing: A Systematic Review and Methodological Comparison. Herkes için Spor ve Rekreasyon Dergisi, Volume: 8 Issue: 3. https://doi.org/10.56639/jsar.1994860

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