Using simple running models, researchers have argued that swing-leg retraction can improve running robot performance. In this paper, we investigate whether this holds for a more realistic simulation model validated against a physical running robot. We find that swing-leg retraction can improve stability and disturbance rejection. Alternatively, swing-leg retraction can simultaneously reduce touchdown forces, slipping likelihood, and impact energy losses. Surprisingly, swing-leg retraction barely affected net energetic efficiency. The retraction rates at which these effects are the greatest are strongly model-dependent, suggesting that robot designers cannot always rely on simplified models to accurately predict such complex behaviors.