Data Analytics in Football provides students, researchers, and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how they can be collected, modeled, analyzed, and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. The book seeks to define the role of positional data in football match analysis by exploring topics such as the following:
Based on data collected from active leagues and fully revised for the new second edition, the text now also examines data collection in relation to other sports, how a data-driven approach in decision-making is achieved by professional teams, the potential of the new methods of data collection, and how they could evolve in the future.
Accessibly written, packed full of examples from elite football, and supplemented with expert interviews, Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher, or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Daniel Memmert is Professor and Executive Head of the Institute of Exercise Training and and Sports Informatics at the German Sport University Cologne, Germany. His scientific work focuses on movement science, sports psychology, and computer science in sports. The institute cooperates with various Bundesliga football teams and DAX companies, and it has organized the first international master's degree course in match analysis and the certificate "Technical Sports Director of Youth Performance Soccer and Amateur Soccer".
Dominik Raabe is Ph.D. student at the German Sport University Cologne, Germany. He holds a Bachelor of Science degree in Cognitive Science from the University of Osnabrück, Germany, and a Master of Science degree in Scientific Computing from the Technical University of Berlin, Germany. He is consulting elite level sports organizations around the globe.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Paperback. Condizione: New. Data Analytics in Football provides students, researchers, and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how they can be collected, modeled, analyzed, and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. The book seeks to define the role of positional data in football match analysis by exploring topics such as the following:What is positional data analysis, and how did it emerge from conventional match analysis?How can positional data be collected, and which technologies can be used?What key performance indicators based on positional data should be used?How can traditional match analysis be complemented by using positional data and advanced KPIs?How can these new methods evolve in the future? Based on data collected from active leagues and fully revised for the new second edition, the text now also examines data collection in relation to other sports, how a data-driven approach in decision-making is achieved by professional teams, the potential of the new methods of data collection, and how they could evolve in the future. Accessibly written, packed full of examples from elite football, and supplemented with expert interviews, Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher, or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally. Codice articolo LU-9781032532479
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