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Sports Data Analytics : Techniques, Applications, and Innovations / edited by Mehul S. Raval, Tolga Kaya, N. Sertac Artan, Christopher Taber.
Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2026 Available online
View online- Format:
- Book
- Author/Creator:
- Raval, Mehul S.
- Series:
- Studies in Big Data, 2197-6511 ; 184
- Language:
- English
- Subjects (All):
- Computational intelligence.
- Quantitative research.
- Artificial intelligence.
- Computer vision.
- Natural language processing (Computer science).
- Computational Intelligence.
- Data Analysis and Big Data.
- Artificial Intelligence.
- Computer Vision.
- Natural Language Processing (NLP).
- Local Subjects:
- Computational Intelligence.
- Data Analysis and Big Data.
- Artificial Intelligence.
- Computer Vision.
- Natural Language Processing (NLP).
- Physical Description:
- 1 online resource (362 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2026.
- Summary:
- In the rapidly evolving world of sports, data has become an invaluable asset, transforming how athletes train, teams strategise, and fans engage. The book delves into the heart of this transformation, offering a comprehensive guide to the latest techniques, applications, and future directions in sports data analytics. The book begins with the fundamentals, introducing key concepts and methodologies for data collection, management, and preprocessing. It then explores various analytical techniques, from descriptive and predictive analytics to advanced AI applications like computer vision and natural language processing. It presents real-world case studies and applications, showcasing how data analytics can enhance in-game strategy, player performance, injury prevention, and fan engagement. Finally, the book addresses emerging technologies, ethical considerations, and the future landscape of sports data analytics.
- Contents:
- Chapter 1` :Fundamentals of Sports Analytics .-Chapter 2 :Analytical Techniques and Models
- Chapter 3 : Case Studies
- Chapter 4: Future Trends .
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 981-9551-32-3
- 9789819551323
- OCLC:
- 1572116961
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