We’ve seen this movie before: simply executing Kolmogorov-Smirnov tests does not guarantee that the interpretation of results is concrete proof of statistical similarity, especially if underlying conditions are ignored. Historically, caution is warranted; these tests are just tools. If reference distributions are poorly chosen, for example by not considering the heavy tails of venture capital returns, the test may show a 'similarity' that is actually an illusion. The traditional game manual tells us that data interpretation is as crucial as the method itself, especially when Japanese markets value a thorough risk and context analysis. A test is not a substitute for informed judgment: ignoring extreme events in venture portfolio analysis can lead to erroneous conclusions.