We apply techniques from the event probability forecasting literature to the analysis of spillover scenarios in economic and financial networks. A simple spillover scenario is expressed as an inequality constraint with respect to a single spillover measure. More complex spillover scenarios can be defined as combinations of simple scenarios. The scenario probabilities are evaluated using a non-parametric bootstrap. We use our technique to study credit risk transmission among a group of 18 countries over the 2006â€“2010 period. We show that abrupt changes in the probabilities of â€œcrisis scenariosâ€ accurately map on to key events during the Global Financial Crisis.