Thanks for the question, Will! From a practical/application perspective, both a t-test and an ANOVA are generally used to compare means between groups (although there are several types of t-tests). However, a t-test is commonly restricted to only testing between two groups (could be independent or related, depending on the type off t-test), while an ANOVA can accommodate a comparison of three or more groups. In some cases a t-test can even be used to test a single group, to determine if the mean of that group is significantly different from a predetermined value (one sample t-test). There are other statistical differences also, but that is a summary of the differences in application.