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This article presents a Bayesian implementation of a cumulative probit modelto forecast the outcomes of the UEFA Champions League matches. The argument ofthe normal CDF involves a cut-off point, a home vs away playing effect and thedifference in strength of the two competing teams. Team strength is assumed tofollow a Gaussian distribution the expectation of which is expressed as alinear regression on an external rating of the team from eg the UEFA ClubRanking (UEFACR) or the Football Club World Ranking (FCWR). Priors on theseparameters are updated at the beginning of each season from their posteriordistributions obtained at the end of the previous one. This allows makingpredictions of match results for each phase of the competition: group stage andknock-out. An application is presented for the 2013-2014 season. Adjustmentbased on the FCWR performs better than on UEFACR.

A simple Bayesian procedure for forecasting the outcomes of the UEFA Champions League matches