We evaluate here the ability of statistical models, namely Hidden Markov Models (HMMs) and Dynamic Bayesian Networks (DBNs), in capturing the interplay and coordination between multimodal behaviors of two individuals involved in a face-to-face interaction. We structure the intricate sensory-motor coupling of the joint multimodal scores by segmenting the whole interaction into so-called interaction units (IU). We show that the proposed statistical models are able to capture the natural dynamics of the interaction and that DBNs are particularly suitable for reproducing original distributions of so-called coordination histograms.