  A new approach in team sports analysis consists in studying positioning and
movements of players during the game in relation to team performance. State of
the art tracking systems produce spatio-temporal traces of players that have
facilitated a variety of research aimed to extract insights from trajectories.
Several methods borrowed from machine learning, network and complex systems,
geographic information system, computer vision and statistics have been
proposed. After having reviewed the state of the art in those niches of
literature aiming to extract useful information to analysts and experts in
terms of relation between players' trajectories and team performance, this
paper presents preliminary results from analysing trajectories data and sheds
light on potential future research in this field of study. In particular, using
convex hulls, we find interesting regularities in players' movement patterns.
