Instances of the well-studied Stable Roommates problem need not admit stable matchings. A long-standing open question posed by Gusfield and Irving (1989) asks about the behaviour of the function Pn, which measures the likelihood that a random instance with n agents is solvable (i.e., admits at least one stable matching). While very recently resolved in the limit for the case where n is even and preferences are sampled uniformly at random, this paper provides a comprehensive analysis of the landscape surrounding this question, combining structural, probabilistic, and experimental perspectives. We estimate Pn for instances with preferences sampled from diverse statistical distributions, for even and odd numbers of agents, examining problem sizes up to 5,001 agents, and considering important substructures. Our results reveal that while Pn tends to be low for most distributions, the number and lengths of "unstable" structures remain limited, suggesting that random instances are "close" to being solvable. Additionally, we present the first empirical study of the number of stable matchings and partitions that random instances admit. Our findings show that the solution sets are typically small, which suggests that many NP-hard problems related to computing optimal stable matchings and partitions become tractable in practice.

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