The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
AI in Sports Analytics
Abstract
The advancement of artificial intelligence has revolutionized the modern sports ecosystem by transforming performance analysis, tactical decision-making, and fan engagement. AI enables real-time monitoring of athletes' physiological conditions through wearable devices and processes the data using edge computing to ensure fast and secure responses. In game strategy, AI is used to analyze team formations, predict match scenarios, and support evidence-based decisions, replacing intuition with data. In the commercial domain, technologies such as NLP and Generative AI allow content personalization, automated highlight generation, and enhanced experiences in smart stadiums. However, the integration of AI also brings ethical challenges, including athlete data privacy, algorithmic bias, and technological inequality. Therefore, the success of AI implementation in sports depends heavily on ethical governance, multidisciplinary collaboration, and an inclusive, adaptive approach to innovation.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|