  Reputation is generally defined as the opinion of a group on an aspect of a
thing. This paper presents a reputation model that follows a probabilistic
modelling of opinions based on three main concepts: (1) the value of an opinion
decays with time, (2) the reputation of the opinion source impacts the
reliability of the opinion, and (3) the certainty of the opinion impacts its
weight with respect to other opinions. Furthermore, the model is flexible with
its opinion sources: it may use explicit opinions or implicit opinions that can
be extracted from agent behavior in domains where explicit opinions are sparse.
We illustrate the latter with an approach to extract opinions from behavioral
information in the sports domain, focusing on football in particular. One of
the uses of a reputation model is predicting behavior. We take up the challenge
of predicting the behavior of football teams in football matches, which we
argue is a very interesting yet difficult approach for evaluating the model.
