Skip to content
DELIVERY: Please note, the Christmas deadline has now passed and we can no longer guarantee delivery before 25th December 2025.
DELIVERY: Please note, the Christmas deadline has now passed and we can no longer guarantee delivery before 25th December 2025.

Machine Learning in Sports

Keisuke Fujii

Open Approach for Next Play Analytics

Barcode 9789819614448
Paperback

Original price £45.72 - Original price £45.72
Original price
£45.72
£45.72 - £45.72
Current price £45.72

Click here to join our rewards scheme and earn points on this purchase!

Availability:
Low Stock
FREE shipping

Release Date: 11/04/2025

Genre: Sports & Hobbies
Label: Springer Nature Switzerland AG
Series: SpringerBriefs in Computer Science
Language: English
Publisher: Springer Nature Switzerland AG

Open Approach for Next Play Analytics

This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis.


This open access book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis. This book not only covers the essential methodologies of capturing and analyzing real sports data but also pioneers the integration of real-world analytics with digital modeling, advancing the field toward sophisticated digital modeling in sports.

Through a seamless blend of theoretical frameworks and practical applications, the book illustrates how these integrated technologies can be utilized to predict, evaluate, and suggest next plays in sports. By leveraging the power of machine learning, the book presents cutting-edge approaches to sports analytics, where data from actual games is enhanced with predictive simulations for strategic planning and decision-making. The use of digital modeling in sports opens up new dimensions of interaction between the physical play and its digital analysis, offering a comprehensive understanding that was previously unattainable.

This book is an essential read for postgraduates, researchers, and technologists, who are interested in sports analysts. The book consists of five parts: Part I, which comprises a single chapter exploring the fundamentals and scope of learning-based sports analytics; Parts II, III, IV, and V review the various aspects of this field, including data acquisition with computer vision, predictive analysis and play evaluation with machine learning, potential play evaluation with learning-based agent modeling, and future perspectives and ecosystems on the field. This structure provides a comprehensive overview that will engage and inform researchers and practitioners interested in the intersection of analytical research and cutting-edge technology in sports.