  This article presents a Bayesian implementation of a cumulative probit model
to forecast the outcomes of the UEFA Champions League matches. The argument of
the normal CDF involves a cut-off point, a home vs away playing effect and the
difference in strength of the two competing teams. Team strength is assumed to
follow a Gaussian distribution the expectation of which is expressed as a
linear regression on an external rating of the team from eg the UEFA Club
Ranking (UEFACR) or the Football Club World Ranking (FCWR). Priors on these
parameters are updated at the beginning of each season from their posterior
distributions obtained at the end of the previous one. This allows making
predictions of match results for each phase of the competition: group stage and
knock-out. An application is presented for the 2013-2014 season. Adjustment
based on the FCWR performs better than on UEFACR.
