  This article is devoted to the forecast of the FIFA World Cup 2022 via nested
zero-inflated generalized Poisson regression. Our regression model incorporates
the Elo points of the participating teams, the location of the matches and the
of team-specific skills in attack and defense as covariates. The proposed model
allows predictions in terms of probabilities in order to quantify the chances
for each team to reach a certain stage of the tournament. We use Monte Carlo
simulations for estimating the outcome of each single match of the tournament,
from which we are able to simulate the whole tournament itself. The model is
fitted on all football games of the participating teams since 2016 weighted by
date and importance. Validation with previous tournaments and comparison with
other Poisson models are given.
