  In recent years, many different approaches have been proposed to quantify the
performances of soccer players. Since player performances are challenging to
quantify directly due to the low-scoring nature of soccer, most approaches
estimate the expected impact of the players' on-the-ball actions on the
scoreline. While effective, these approaches are yet to be widely embraced by
soccer practitioners. The soccer analytics community has primarily focused on
improving the accuracy of the models, while the explainability of the produced
metrics is often much more important to practitioners.
  To help bridge the gap between scientists and practitioners, we introduce an
explainable Generalized Additive Model that estimates the expected value for
shots. Unlike existing models, our model leverages features corresponding to
widespread soccer concepts. To this end, we represent the locations of shots by
fuzzily assigning the shots to designated zones on the pitch that practitioners
are familiar with. Our experimental evaluation shows that our model is as
accurate as existing models, while being easier to explain to soccer
practitioners.
