One effective approach to addressing uncertainties in a parametric manner is soft set theory, which generalizes classical set theory. Building on this foundation, we introduce the concepts of statistical and lacunary statistical convergence for sequences of closed sets within the framework of soft metric spaces. We establish fundamental properties associated with these types of convergence and explore their interrelationships, resulting in several inclusion results. Furthermore, we utilize a generalized version of the natural density function, referred to as the ϕ-weighted density function, to strengthen our findings.