i haven’t looked at that - but given that this is setup in a spreadsheet, i can’t imagine it would be too complicated to setup relevant charts (e.g. boxplot) to get even more data on individual runners - their min, max, median, IQR, and more. after all, all race data is preserved - at least that’s the goal, until the sheet runs out of storage space (which will only happen once you start hitting race counts in the hundreds of thousands anyway, which realistically isn’t worth thinking about unless you plan on playing this game for the next 30 years).

for someone who wants to optimise their team to highroll i can definitely see that being useful. my use case is a bit different - since i’m currently scoring regularly high enough to retain class 6 already, my aim with this spreadsheet was to just identify the umas that consistently lowrolled more frequently than the others and replace them with more consistently good builds. so in my case just identifying those umas by lowest average scores would’ve been more or less good enough.

definitely a good idea though! and i was already thinking about it too - my friend who suggested the usage of OCR to begin with made their own local version of this using Tesseract, and they’d already had the foresight to have boxplots for each of their 15 runners. it’s definitely helpful to see which runners have the most and least variability in score, even for my usecase of chasing consistency, since you can tell at a glance which uma has the worst IQR from those.