  We propose an approach for the analysis and prediction of a football
championship. It is based on Poisson regression models that include the Elo
points of the teams as covariates and incorporates differences of team-specific
effects. These models for the prediction of the FIFA World Cup 2018 are fitted
on all football games on neutral ground of the participating teams since 2010.
Based on the model estimates for single matches Monte-Carlo simulations are
used to estimate probabilities for reaching the different stages in the FIFA
World Cup 2018 for all teams. We propose two score functions for ordinal random
variables that serve together with the rank probability score for the
validation of our models with the results of the FIFA World Cups 2010 and 2014.
All models favor Germany as the new FIFA World Champion. All possible courses
of the tournament and their probabilities are visualized using a single Sankey
diagram.
