  Volleyball is a team sport with unique and specific characteristics. We
introduce a new two level-hierarchical Bayesian model which accounts for theses
volleyball specific characteristics. In the first level, we model the set
outcome with a simple logistic regression model. Conditionally on the winner of
the set, in the second level, we use a truncated negative binomial distribution
for the points earned by the loosing team. An additional Poisson distributed
inflation component is introduced to model the extra points played in the case
that the two teams have point difference less than two points. The number of
points of the winner within each set is deterministically specified by the
winner of the set and the points of the inflation component. The team specific
abilities and the home effect are used as covariates on all layers of the model
(set, point, and extra inflated points). The implementation of the proposed
model on the Italian Superlega 2017/2018 data shows an exceptional
reproducibility of the final league table and a satisfactory predictive
ability.
