The most practical response to this question is also the most direct: you can solve this by combining modern array functions with a single helper column. The user's instinct to reach for MATCH is correct for single-column lookups, but when the target is an entire range, and the goal is a ranked list of the six most frequent non-blank entries, you need a different approach entirely.
What makes this problem interesting is how it exposes a gap in many spreadsheet users' mental models. Most people learn formulas in isolation: a VLOOKUP here, a COUNTIF there. But finding the top six most common strings across a full range requires thinking in layers. The first layer is flattening the range into a single array, something newer spreadsheet tools handle easily with functions like TOCOL or FLATTEN. The second layer is counting occurrences across that flattened array, then ranking them. The third layer is extracting those top six values without erroring out when ties occur or when fewer than six unique strings exist. This is not a single formula problem; it's a small pipeline of logic.
We believe the clearest path for most users is to combine UNIQUE, COUNTIF, SORT, and INDEX. First, use UNIQUE on the flattened range to get every distinct string. Then use COUNTIF against the original range to get each string's frequency. Sort that paired array by frequency in descending order. Finally, use INDEX to pull the top six results. To filter blanks, simply exclude empty cells from the UNIQUE output or add a condition in COUNTIF. The beauty of this approach is that it works across any number of columns, scales with your data, and produces a clean, repeatable result.
The practical takeaway is straightforward: stop trying to force MATCH into a role it was never designed for. Instead, embrace the fact that modern spreadsheets treat ranges as first-class arrays. The user who asked this question is not alone, many feel constrained by legacy formula habits. But the solution here is not a workaround; it is a more natural way of thinking about data. Build the pipeline once, and you will never have to hand-count or manually sort common strings again. That is the real win: not just an answer to a forum post, but a reusable pattern that transforms how you approach any frequency analysis in a multi-column range.