Large Language Models (LLMs) are increasingly deployed across linguistically and culturally diverse societies, yet evaluations of value alignment remain largely grounded in synthetic benchmarks and normative assumptions. We introduce a population-grounded framework for evaluating multilingual LLM alignment using the European Values Survey (EVS), a large-scale longitudinal study of societal values across Europe. Treating LLMs as survey respondents, we prompt them with EVS questions in multiple European languages and compare model and human response distributions. We analyze correspondence at both country and language-family levels and construct a human value space from EVS responses. Our results show that language families capture a meaningful component of human cross-cultural value variation and provide an informative level of aggregation for multilingual evaluation. The studied LLMs exhibit substantial diversity within this space, occupying distinct regions of the European value landscape rather than converging toward a single value profile. By grounding alignment in observed population responses rather than normative prescriptions, we provide a transparent and reproducible framework for analyzing value-related behavior in multilingual LLMs.