To understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts.
By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches.
Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
1. Empowering Human Intelligence: The Ecological Dynamics Approach to Big Data and Artificial Intelligence in Sport Performance Preparation
2. How is Artificial Intelligence being Used in the Sport Sciences to Analyse and Support Performance of Athletes and Teams?
3. From Reliable Sources of Big Data to Capturing Sport Performance by Ecophysical Variables
4. Computational Metrics to Inspect the Athletic Performance
5. Artificial Intelligence for Pattern Recognition in Sports: Classifying Actions and Performance Signatures
6. From Classification to Prediction
7. Technology, Artificial Intelligence and the Future of Sport and Physical Activity
"A unique synthesis of the very latest theoretical and methodological advances to identify and predict the complex patterns and relationships associated with successful sport performance. An essential read for all involved with enhancing the performance of individuals and teams."
Mike Court, Head of Recruitment Analysis Manchester United FC, UK