Matching is an intuitively appealing design strategy for ensuring balance on one or more potential confounding variables, usually either among subjects who were exposed or unexposed to a suspected risk factor for disease in a cohort study or between diseased and nondiseased subjects in a case-control study. But does matching always automatically "control" confounding and is it always as good a strategy as it seems? It is the intention of this review to shed light on these questions primarily through illustrative examples of the effects of matching on the validity of point estimates of the odds ratio between exposure and disease status in both types of study designs. It is seen that the results of matching are more or less in line with expectations in cohort studies, but that matching can lead to unexpected results in case-control studies. In a case-control study, confounding is not automatically controlled by matching per se; rather, matching and a statistical analysis that properly accounts for the matching are needed to obtain a valid estimate of effect in a case-control study design.