Sports Analytics

<p>As the analysis of big datasets in sports performance becomes a more entrenched part of the sporting landscape, so the value of sport scientists and analysts with formal training in data analytics grows. <i>Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance </i> provides the most authoritative and comprehensive guide to the use of analytics in sport and its application in sports performance, coaching, talent identification and sports medicine available.</p><p>Employing an approach-based structure and integrating problem-based learning throughout the text, the book clearly defines the difference between analytics and analysis and goes on to explain and illustrate methods including:</p><ul> <p> </p> <li>Interactive visualisation</li> <p> </p> <li>Simulation and modelling</li> <p> </p> <li>Geospatial data analysis</li> <p> </p> <li>Spatiotemporal analysis</li> <p> </p> <li>Machine learning</li> <p> </p> <li>Genomic data analysis</li> <p> </p> <li>Social network analysis</li> </ul><p>Offering a mixed-methods case study chapter, no other book offers the same level of scientific grounding or practical application in sports data analytics. <i>Sports Analytics</i> is essential reading for all students of sports analytics, and useful supplementary reading for students and professionals in talent identification and development, sports performance analysis, sports medicine and applied computer science.</p> <p>1. What is Analytics?</p><p>2. Complex Data and the "Data Age"</p><p>3. Interactive Visualisation</p><p>4. Simulation and Modelling</p><p>5. Geospatial Data Analysis</p><p>6. Spatio-Temporal Analysis</p><p>7. Machine Learning and Sport</p><p>8. Genomics in Sports</p><p>9. Social Network Analysis</p><p>10. Knowledge Discovery in Databases and Data Mining</p><p>11. Data Management and Infrastructure</p><p>12. Sports Analytics Applications in Soccer</p>