Bipedal running gaits may be self-stable if they rely on the intrinsic system dynamics to attenuate deviations. This use of passive dynamics for gait stability has been observed in biological running and applied for running robotics, supported with the results of numerical simulations. It is an important aspect of the development of fast and agile legged robotic locomotion over complex terrain. One part of running stability, trunk stabilization, can be described using a virtual pendulum model. We believe such a metacentric model may be applied in robotic design to achieve passive stabilization of body pitch for fast bipedal running. In this study, we test metacentric models for self-stabilization of body pitch in bipedal running and evaluate the effects of running speed, design parameter variations, and control strategies. We extract data from experiments with the Planar Elliptical Runner and compare these with a planar spring-loaded inverted pendulum model with a trunk (TSLIP). We find passive self-stable gaits in the TSLIP model with the centre of mass below the hip. These gaits demonstrate robustness to disturbances and do not require inertial measurements or high-gain feedback control. At high velocities, foot placement and choice of leg stiffness become less critical for gait stability. Data from experiments with the Planar Elliptical Runner support the findings from the model behaviour as it runs reliably, with passively stable body pitch, and without feedback control. A metacentric model, such as the virtual pendulum model, may explain the observed passive body-pitch stabilization. Evidence from the model ground reaction forces suggests that pitch stability for the Planar Elliptical Runner can also be explained with a metacentric model. Stability in height and velocity can be explained with the compliant leg behaviour in stance. Constructing a metacentre through mechanical design is beneficial to intrinsic body-pitch stability and subsequently facilitates full gait self-stability in fast running robotics. Implicit feedback allows off-loading of high-gain feedback control onto the system mechanical design, thus contributing to developments for fast legged locomotion over rough terrain.