In this paper we bring to light a novel intersection between corpus linguistics and behavioral data that can be employed as an evaluation metric for resources for low-density languages, drawing on well-established psycholinguistic factors. Using the low-density language Maltese as a test case, we highlight the challenges that face researchers developing resources for languages with sparsely available data and identify a key empirical link between corpus and psycholinguistic research as a tool to evaluate corpus resources. Specifically, we compare two robust variables identified in the psycholinguistic literature: word frequency (as measured in a corpus) and word familiarity (as measured in a rating task). We then apply statistical methods to evaluate the extent to which familiarity ratings predict corpus frequency for verbs in the Maltese corpus from three angles: 1) token frequency, 2) frequency distributions and 3) morpho-syntactic type (binyan). This research provides a multidisciplinary approach to corpus development and evaluation, in particular for less-resourced languages that lack a wide access to diverse language data.