  Data analytics in sports is crucial to evaluate the performance of single
players and the whole team. The literature proposes a number of tools for both
offence and defence scenarios. Data coming from tracking location of players,
in this respect, may be used to enrich the amount of useful information. In
basketball, however, actions are interleaved with inactive periods. This paper
describes a methodological approach to automatically identify active periods
during a game and to classify them as offensive or defensive. The method is
based on the application of thresholds to players kinematic parameters, whose
values undergo a tuning strategy similar to Receiver Operating Characteristic
curves, using a ground truth extracted from the video of the games.
