 Despite its appeal, there are well-known problems with taking HD as a sufficient account of how evidence supports theories (this is often called “naïve HD”). In particular, the naïve view lacks the resources to draw distinctions among underdetermined rival theories that make the same predictions (see Crupi 2013 [2016]). We take it as given that scientists do draw distinctions among theories that naïve HD would treat as on par, as is reflected in judgments regarding how much a given body of evidence supports a particular theory. Scientists routinely distinguish among, for example, theories that may merely “fit the data” as opposed to those that accurately capture laws governing a particular domain, and evaluate some successful predictions as being far more revealing than others.