Yes, this is my observation as well. Put another way, statistics is primarily concerned with understanding the mechanisms behind something. Predictive power can

Yes, this is my observation as well. Put another way, statistics is primarily concerned with understanding the mechanisms behind something. Predictive power can and will often be sacrificed if it aids explanatory power or conceptual elegance. By contrast, machine learning is primarily concerned with making the best prediction possible, even if that means sacrificing an understanding of the underlying mechanisms. The Venn diagram of methods can have a fair degree of overlap. Neither disposition is right or wrong, but they tend to have natural places where each makes more sense. If you’re trying to predict whether a picture is of a cat or a dog, you probably don’t care much about the constituent contribution of factors to one pictures dogness or catness. On the other hand, if you’re trying to predict traffic collisions based on characteristics of a roadway, you’re probably less concerned with the predicted number of crashes and more concerned with the relative contribution of a handful of independent variables.