Since the U.S. Supreme Court’s Davis v. Bandemer ruling in 1986, partisan gerrymandering for statewide electoral advantage has been held to be justiciable. The existing Supreme Court standard, culminating in Vieth v. Jubelirer and LULAC v. Perry, holds that a test for gerrymandering should demonstrate both intents and effects and that partisan gerrymandering may be recognizable by its asymmetry: for a given distribution of popular votes, if the parties switch places in popular vote, the numbers of seats will change in an unequal fashion. However, the asymmetry standard is only a broad statement of principle, and no analytical method for assessing asymmetry has yet been held by the Supreme Court to be manageable. This Article proposes three statistical tests to reliably assess asymmetry in state-level districting schemes: (1) an unrepresentative distortion in the number of seats won based on expectations from nationwide district characteristics; (2) a discrepancy in winning vote margins between the two parties; and (3) the construction of reliable wins for the party in charge of redistricting, as measured by either the difference between mean and median vote share, or an unusually even distribution of votes across districts. The first test relies on computer simulation to estimate appropriate levels of representation for a given level of popular vote and provides a way to measure the effects of a gerrymander. The second and third tests, which can be used to help evaluate redistricting intent, rely on well-established statistical principles and can be carried out using a hand calculator without examination of maps or redistricting procedures. I apply these standards to a variety of districting schemes, starting from the original “Gerry-mander” of 1812, up to modern cases. In post-2010 congressional elections, partisan gerrymandering in a handful of states generated effects that are larger than the total nationwide effect of population clustering. By applying these standards in two recent cases, I show that Arizona legislative districts (Harris v. Arizona Independent Redistricting Commission) fail to qualify as a partisan gerrymander, but Maryland’s congressional districts (Shapiro v. McManus) do. I propose that an intents-and-effects standard based on these tests is robust enough to mitigate the need to demonstrate predominant partisan intent. The three statistical standards offered here add to the judge’s toolkit for rapidly and rigorously identifying the partisan consequences of redistricting.