  Despite having the potential to provide significant insights into tactical
preparations for future matches, very few studies have considered the spatial
trends of team attacking possessions in rugby league. Those which have
considered these trends have used grid based aggregation methods, which provide
a discrete understanding of rugby league match play but may fail to provide a
complete understanding of the spatial trends of attacking possessions due to
the dynamic nature of the sport. In this study, we use Kernel Density
Estimation (KDE) to provide a continuous understanding of the spatial trends of
attacking possessions in rugby league on a team by team basis. We use the
Wasserstein distance to understand the differences between teams (i.e. using
all of each team's data) and within teams (i.e. using a single team's data
against different opponents). Our results show that KDEs are able to provide
interesting tactical insights at the between team level. Furthermore, at the
within team level, the results are able to show patterns of spatial trends for
attacking teams, which are present against some opponents but not others. The
results could help sports practitioners to understand opposition teams'
previous performances and prepare tactical strategies for matches against them.
