ABSTRACT Disrupting drug operations requires a measured approach to identifying critical actors playing instrumental roles in support of illicit drug market activity. We use a quadratic assignment procedure (QAP) nodal regression routine to explore the explanatory relevance of human capital in accounting for an actor’s structural position within two methamphetamine trafficking communities—one originating from land-based smuggling and the other involving sea-based smuggling. We operationalise human capital with three dichotomous variables (occupying leadership roles, being involved in money laundering, or facilitating international smuggling) and capture positional importance with normalised degree and betweenness centrality scores. The results support arguments in favour of integrating centrality metrics with nodal attributes to improve targeted efforts to disrupt market activity. Additionally, network mapping must be sensitive to the local conditions surrounding specific types of drug trafficking operations—the structure of land-based and sea-based drug distribution chains supplying methamphetamine to Indonesian markets differ substantively. Limitations are discussed.