The generation of attack graphs alongside cyber range infrastructures provides a structured representation of potential attack paths; however, their integration with execution-time observations remains limited. This paper investigates how design-time attack graphs can be extended with structured data collected during cyber exercises, enabling a closer connection between modeling and empirical evaluation. We interpret design-time attack graphs as representations of the feasible adversarial state space of a cyber range environment. By aligning execution traces and defensive actions with graph elements, the model can be extended to reflect changes in transition feasibility and reachability during exercise execution. The integration is not yet realized as a fully automated system, existing components, such as the incorporation of intrusion detection alerts into graph representations, demonstrate the feasibility of this approach. The paper outlines a framework in which enriched attack graphs serve as a conceptual bridge between cyber range engineering and data-driven security analysis. This perspective enables structured dataset creation, explainable analysis of security events, and graph-based evaluation of defensive actions, while providing a foundation for future adaptive, self-evolvig cyber range environments.