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This book provides an account of the use of computational tactical
metrics in improving sports analysis, in particular the use of
Global Positioning System (GPS) data in soccer. As well as offering
a practical perspective on collective behavioural analysis, it
introduces the computational metrics available in the literature
that allow readers to identify collective behaviour and patterns of
play in team sports. These metrics only require the bio-dimensional
geo-referencing information from GPS or video-tracking systems to
provide qualitative and quantitative information about the tactical
behaviour of players and the inter-relationships between teammates
and their opponents. Exercises, experimental cases and algorithms
enable readers to fully comprehend how to compute these metrics, as
well as introducing them to the ultimate performance analysis tool,
which is the basis to run them on. The script to compute the
metrics is presented in Python. The book is a valuable resource for
professional analysts as well students and researchers in the field
of sports analysis wanting to optimise the use of GPS trackers in
soccer.
This book introduces the ultimate performance analysis tool (uPATO)
as a new software to compute social network metrics in the scope of
team sports analysis. The reader will identify the algorithms to
test the general properties of the team, the co-dependencies and
the centrality levels of players, i.e. to evaluate the individual,
sub-group, and team performance analysis. As uPATO tool implements
the metrics for all options, namely for unweighted graphs, weighted
graphs, unweighted digraphs and weighted digraphs, it is also
useful for network analysis into other areas beyond team sports.
The book assists the reader to compute the metrics and to use it in
different scenarios.
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