by Chulwook ParkCoordinative structures, the functional groupings of degrees of freedom that simplify motor control, are well documented yet mechanistically unexplained. How they emerge and why they are hierarchically organized remains unclear. This study proposes scale-free network topology as the missing mechanism. Systematic simulations comparing random, small-world, and scale-free networks show that scale-free organization reproduces the defining features of coordinative structures more completely than the alternatives, namely a hub-periphery hierarchy, ordered hub-first recruitment, an abrupt onset of global coordination, and a balance between stability and flexibility. Four formal correspondences connect these features to established coordination phenomena, and a coupled learning model reproduces the characteristic curve of skill acquisition, with scale-free networks reaching coordination fastest. The model is validated against published data from five independent studies spanning motor learning, bimanual coordination, brain networks, and joint coordination. It yields eleven testable predictions with explicit quantitative thresholds, alongside five criteria that would disconfirm it. Network topology thus offers a principled, empirically grounded, and falsifiable basis for how coordinative structures form through structural constraints and experience.