  In this work, we compare several different modeling approaches for count data
applied to the scores of handball matches with regard to their predictive
performances based on all matches from the four previous IHF World Men's
Handball Championships 2011 - 2017: (underdispersed) Poisson regression models,
Gaussian response models and negative binomial models. All models are based on
the teams' covariate information. Within this comparison, the Gaussian response
model turns out to be the best-performing prediction method on the training
data and is, therefore, chosen as the final model. Based on its estimates, the
IHF World Men's Handball Championship 2019 is simulated repeatedly and winning
probabilities are obtained for all teams. The model clearly favors Denmark
before France. Additionally, we provide survival probabilities for all teams
and at all tournament stages as well as probabilities for all teams to qualify
for the main round.
