  Goals are results of pin-point shots and it is a pivotal decision in soccer
when, how and where to shoot. The main contribution of this study is two-fold.
At first, after showing that there exists high spatial correlation in the data
of shots across games, we introduce a spatial process in the error structure to
model the probability of conversion from a shot depending on positional and
situational covariates. The model is developed using a full Bayesian framework.
Secondly, based on the proposed model, we define two new measures that can
appropriately quantify the impact of an individual in soccer, by evaluating the
positioning senses and shooting abilities of the players. As a practical
application, the method is implemented on Major League Soccer data from 2016/17
season.
