What is the relationship between variability models and code? While we've worked on exact approaches to compare constraints, we've also explored using metrics to improve this understanding. In a little position paper (joint work with Jianmai Guo) for the VaMoS'14 workshop, we defined low-level metrics that measure core aspects of models (model shape, feature representation, constraints, and dependencies). Using correlation analysis (Spearman's rank correlation coefficient), we show that we can find insights about inherent design characteristics of models, partly also about their relationship to code. Take a look at the paper, the presentation, and the tool and datasets.