This covers the PACSS 2021 which approached interdisciplinary collaboration between theoretical computer science and practical performance analysis though an online workshop and conference. Readers find in this book the peer-reviewed and discussed evidences on how computer scientists and performance analysts can and have worked together to solve both applied and research-based problems in elite sport, using the methods of computer science. In this edition, we organize the content according to four major topics: machine learning, text mining, best practice and interdisciplinary collaboration. This is a refined material written by leading experts with up-to-date overview of research in the multidisciplinary field of computer science and elite sport performance analysis.
Tabla de materias
Text mining and performance analysis.- Match Analysis 4.0 with Big Data: From Studies to Experiments.- Using machine learning to assess and compare athletes in team sports.- Kick it to Me, or Maybe Not – How Player Roles Affect AFL Possessions.- Predicting and understanding Australian Rules Football using Markov processes.- Exercise Evaluation using Time-of-Flight Image Data.- Improving springboard diving video classification accuracy through cumulated segment values.- How Sports Scientists Explain Their Choice of Wearable.- Physical and motivational effects of Exer-games in healthy adults: Overview of Reviews.- The Impact of Order of Performance on Peer-to-Peer Learning of a Lacrosse Ball Pick-Up Skill Through Video Analysis with University Students.
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