In recent years, there have been several exciting applications of methods from nonstandard analysis in the field of statistics. In this talk I will discuss recent joint work with Haosui Duanmu and Daniel M. Roy, in which we give a precise characterization of admissibility in Bayesian terms, solving a long-standing problem in the field of statistical decision theory. This result uses so-called hyperpriors, which can give infinitesimal weight to events, to achieve this characterization, and also has interesting classical consequences (that is, not mentioning hyperpriors or infinitesimals).