Cover Image

Artificial Intelligence and Machine Learning in Sports Science

This professional book is one of the first book publications providing a comprehensive overview of how artificial intelligence (AI) and machine learning (ML) are used in the context of sports science research and sports practice. In addition to the basics of AI and ML, various applications are descr...

Full description

Saved in:
Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Memmert, Daniel (Editor)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2025.
Edition:1st ed. 2025.
Subjects:
Sports sciences.
Artificial intelligence.
Machine learning.
Computer science.
Recreation > Equipment and supplies.
Sport Science.
Artificial Intelligence.
Machine Learning.
Sport Analytics.
Computer Science.
Sport Technology.
Online Access:https://doi.org/10.1007/978-3-662-70155-3
Tags: Add Tag
No Tags, Be the first to tag this record!
Table of Contents:
  • I Basics
  • AI and ML: Definitions and basics
  • Supervised and Unsupervised Learning
  • Model evaluation in machine learning applications
  • Predictive Bayesian Modeling in Sport Science
  • Computer Vision and Deep Learning for Sports Analytics
  • Human and artificial intelligence integration for decision-making in sports performance
  • Match predictions in soccer: Machine learning vs. Poisson approaches
  • II Metrics in team sports
  • Machine Learning in Soccer
  • Machine Learning in Basketball
  • Machine Learning in Handball
  • Risk, Reward, and Reinforcement Learning in Ice Hockey Analytics
  • III Metrics in individual sports
  • Machine Learning for Contemporary Dance
  • Automatic annotation of movements in dance
  • Profiling of High-Performance Skateboarders from Anthro-fitness Variables: A Random Forest-Based-Machine Learning Analysis
  • IV Applications in sports science
  • Defining player dominant region in soccer: background, data-driven models advances, and scientific challenges
  • Applications of Computer Vision in Sports Sciences
  • Machine learning-based analysis of multi-agent trajectories in basketball
  • Artificial intelligence to promote physical activity
  • Machine Learning for Injury Prediction
  • Event Data Based Action Valuation: Possibilities and Limitations
  • V Outlook
  • Responsible use of Machine Learning in Sports Science
  • Opportunities and challenges of artificial intelligence in sports science.

Similar Items