We propose a data-based approximation of the effects of trade sanctions that can readily be computed on the basis of international input-output data. Approximated effects are very close to the exact responses obtained from a canonical multi-country multi-sector model, without having to make difficult calibration choices. We illustrate the approximation with trade sanctions against Russia and obtain estimates well within the existing range. Russia is much more affected by trade sanctions than the EU, even though the importance of EU markets for Russia has been falling, especially since 2014 with China picking up the slack. Within the EU the consequences are largest in ex-“satellite” countries of the Soviet Union: These countries do not typically have access to substitute markets and in fact have historically been highly dependent on Russia. This extreme and persistent dependence is at least partly explained by the existence of specific energy transporting infrastructure (pipelines) that appears to constrain tightly the production of electricity. Our proposed approximation is practical and can be implemented in a variety of contexts: We have developed a web-based dashboard, accessible at exposure.trade that can be used to approximate the costs of trade sanctions for any combinations of sanctioning and sanctioned countries or sectors.