  We investigate the potential occurrence of change points - commonly referred
to as "momentum shifts" - in the dynamics of football matches. For that
purpose, we model minute-by-minute in-game statistics of Bundesliga matches
using hidden Markov models (HMMs). To allow for within-state correlation of the
variables considered, we formulate multivariate state-dependent distributions
using copulas. For the Bundesliga data considered, we find that the fitted HMMs
comprise states which can be interpreted as a team showing different levels of
control over a match. Our modelling framework enables inference related to
causes of momentum shifts and team tactics, which is of much interest to
managers, bookmakers, and sports fans.
