Current Volume 8
Personalization of Sports Content with Artificial Intelligence: Enhancing Fan Engagement through Intelligent Recommendations
Abstract
The increasing digitization of the sports industry has transformed how fans consume content, shifting from traditional broadcasting to highly interactive and personalized digital experiences. In this context, artificial intelligence (AI) emerges as a powerful enabler for tailoring content to individual preferences, thereby enhancing user engagement and satisfaction. This article explores how AI technologies — particularly recommendation systems, machine learning algorithms, and natural language processing — are used to personalize sports content across various platforms, including streaming services, sports apps, and social media. By analyzing user behavior, interests, location, and historical interactions, AI systems can suggest customized content such as videos, real-time highlights, articles, interviews, and news. This personalization extends beyond preferences for teams or athletes and includes content formats, preferred languages, and even emotional engagement patterns. The application of AI-driven personalization is already prominent in platforms such as ESPN, DAZN, and OneFootball, which continuously adapt their content strategies to maintain user attention and maximize retention. This article adopts a qualitative methodology through a literature review and case study analysis of real-world implementations. It critically examines the benefits and challenges of using AI in sports content personalization, including ethical concerns regarding data privacy, algorithmic bias, and content filter bubbles. Additionally, the article discusses how these technologies impact fan loyalty, monetization strategies, and the broader digital transformation of sports media. By synthesizing current academic research and industry practices, this paper aims to contribute to the ongoing discourse on AI in the sports domain. It highlights the need for responsible and inclusive design of AI systems to ensure that content personalization not only enhances the fan experience but also aligns with values of fairness, transparency, and data protection. The findings underscore AI’s role as a transformative force in shaping the future of fan engagement in the sports industry.
Keywords
Artificial Intelligence, Sports Content Personalization, Recommendation Systems, Fan Engagement, User Behavior Analytics.
Citations
IRE Journals:
Eduardo Texeira Leite
"Personalization of Sports Content with Artificial Intelligence: Enhancing Fan Engagement through Intelligent Recommendations" Iconic Research And Engineering Journals Volume 4 Issue 7 2021 Page 199-205
IEEE:
Eduardo Texeira Leite
"Personalization of Sports Content with Artificial Intelligence: Enhancing Fan Engagement through Intelligent Recommendations" Iconic Research And Engineering Journals, 4(7)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
Important Links
For Authors
Volume 7:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 6:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 5:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 4:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 3:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12