Is a propensity-score match necessary if my pre-match covariates are already balanced? I planned to run an analysis starting with a dataset of 22,000 records. From this set, I would conduct a match to obtain two balanced groups then look at my outcomes of interest. I was planning to use an SMD of <0.1 as a measure of achieving balance.
However, if my covariates of interest are already balanced (SMD <0.1) prior to running my match, is it still necessary methodologically to run a a match?

It's not necessary, and in fact potentially harmful to use propensity score to match once balance has been achieved; this is one of the main messages of King and Nielsen (2019). Instead, you should adjust for prognostically important covariates using regression, which will improve precision and remove any slight remaining imbalances. With such a large sample, it should be simple to build a flexible regression model that adjusts for the covariates completely.
