Frequency matching is important because it helps to control confounding, which can obscure the true relationship between an exposure and an outcome. By matching the distribution of confounders between cases and controls, researchers can isolate the effect of the exposure of interest. This leads to more accurate estimates of the association and strengthens the validity of the study findings.
