In the traditional statistical framework, nonsignificant results leave researchers in a state of suspended disbelief. This study examines, empirically, the treatment and evidential impact of nonsignificant results. Our specific goals were twofold: to explore how psychologists interpret and communicate nonsignificant results, and to assess how much these results constitute evidence in favor of the null-hypothesis. Firstly, we examined all nonsignificant findings mentioned in the abstracts of the 2015 volume of *Psychonomic Bulletin & Review*, *Journal of Experimental Psychology: General*, and *Psychological Science* (*N* = 137). In 76% of cases, nonsignificant results were misinterpreted, in the sense that authors inferred that the effect was absent. Secondly, a Bayes factor reanalysis revealed that fewer than 5% of the nonsignificant findings provided strong evidence (i.e., BF01 > 10) in favor of the null-hypothesis compared to the alternative hypotheses. We recommend that researchers expand their statistical toolkit in order to correctly interpret nonsignificant results and to be able to evaluate the evidence for and against the null-hypothesis.