The Use of Applied Technology in Team Sport describes and assists researchers, academics and professionals with understanding the methodology around applied technology in sport examining; what systems track players performance, who are the manufacturers that provide these systems.
The Use of Applied Technology in Team Sport describes and assists researchers, academics and professionals with understanding the methodology around applied technology in sport examining; what systems track players performance, who are the manufacturers that provide these systems.
José Pino-Ortega is Titular Professor in University of Murcia, Spain, and researcher of the BIOVETMED & SPORTSCI Research Group from the same university. He has a Ph.D. in Sport Sciences-Applied technology to Sport in Faculty of Sport Science from University of Murcia, Spain. Markel Rico-González is a researcher of both University of Basque Country, Spain, and BIOVETMED & SPORTSCI Research Group from University of Murcia, Spain. He has a Ph.D. in Sport Sciences- Team Sports Performance and Applied Technology and Applied Technology in Faculty of Education and Sport from the University of Basque Country.
Inhaltsangabe
Part I: Data Collection Technology 1. Standarization Of Electronic Performance and Tracking Systems 2. Semi-Automatic Multiple Camera Systems 3. Global Navigation Satellite Systems 4. Local Positioning Systems 5. Microelectromechanical Systems 6. Wearables for the Internal Workload Monitoring: Combined Hear Rate and Mechanical Sensors Part II: Data Transmission 7. Data Acquisition and Transmission 8. Real-Time Feedback: An Update Part III: Data Processing: Performance Variables 9. Kinematical Variables 10. Collective Tactical Variables 11. Neuromuscular Variables 12. Physiological Variables - Training Impulse and Heart Rate Variability 13. Multidimensional Variables Part IV: Big Data and Reduction Techniques 14. Big Data Applied to Team Sport Athletes¿ Performance 15. Data Mining in Sports: The Case of Principal Component Analysis Part V: Computer Vision and Machine Learning 16. Computer Vision 17. Machine Learning
Part I: Data Collection Technology 1. Standarization Of Electronic Performance and Tracking Systems 2. Semi-Automatic Multiple Camera Systems 3. Global Navigation Satellite Systems 4. Local Positioning Systems 5. Microelectromechanical Systems 6. Wearables for the Internal Workload Monitoring: Combined Hear Rate and Mechanical Sensors Part II: Data Transmission 7. Data Acquisition and Transmission 8. Real-Time Feedback: An Update Part III: Data Processing: Performance Variables 9. Kinematical Variables 10. Collective Tactical Variables 11. Neuromuscular Variables 12. Physiological Variables - Training Impulse and Heart Rate Variability 13. Multidimensional Variables Part IV: Big Data and Reduction Techniques 14. Big Data Applied to Team Sport Athletes¿ Performance 15. Data Mining in Sports: The Case of Principal Component Analysis Part V: Computer Vision and Machine Learning 16. Computer Vision 17. Machine Learning
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