We show that extending Matsui's Algorithm 1 to using multiple linear approximations leads to a statistical goodness-of-fit problem. We examine common statistical goodness-of-fit tests, propose a new one based on LLR, estimate their performance, and experiment on key recovery with key ranking using these tests.