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.

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.