Circuit reliability under statistical process variation is an area of growing concern. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. Existing techniques perform poorly when tasked to generate both efficient sampling and sound statistics for these rare events. Statistical blockade is a novel Monte Carlo technique that allows us to efficiently filter - to block - unwanted samples insufficiently rare in the tail distributions we seek. The method synthesizes ideas from data mining and extreme value theory, and shows speed-ups of 10times - 100times over standard Monte Carlo