I think it's worth talking about the utility of empirical segmentation of a continuum (at least, if anyone's interested in the technical aspect of this.) Binning (categorizing a near continuous or continuous function into several discrete outputs) is a common technique in big data and statistics in general, to the point it's frequently automated. For instance, one could make a parser that would look through morgues and categorize them into 5 automatic bins of melee vs magic. (probably take actions of each type of weapon, normalize based on minimum attack time, and then divide by total conjurations/summoning/Hexes casts, also normalized based roughly on approximate damage per cast.) The definitions going in would be somewhat arbitrary (what exactly qualifies as a conjuration?) and the divisions on the scale of melee/magic would be completely arbitrary.
How is a completely arbitrary binning useful? It lets you make generalizations about the game. Does anyone think the the killer list is going to look the same for the top 19% magic users and the bottom 17% of magic users? No way! And you can fit various correlated variables to those (arbitrary) bins. Maybe oozes tend to kill more melee heros. You can find out by fitting a line to the bins/killer graph. Maybe the middle bins tend to worship Kiku more. Maybe the more magicy ones are more likely to enter a zig.
Given that you can't meaningfully operate on each individual game due to their uniqueness, binning lets you ignore the variability in favor of simply dealing with the statistics. See also
https://en.wikipedia.org/wiki/Data_binningIn this particular case Sandman wants to fit perceived lair branch difficulty to a 2 dimensional binning system. This is useful in spite of the fact that individual games don't fit the bins very well because there are a lot of games. Overall, we'd expect some correlation trends between tools routinely available to a chacter and percieved difficulty. Binning lets us largely ignore the variance and just find what effect this has overall.
(Note that the sample size is really low here, and the initial prompts probably led to inaccurate binning. I wish Lasty hadn't added the option, as it's basically noise and doesn't fit the bins, and had just reset the options with clearer instructions.) Regardless, I think this will be at best marginally significant results. But that complaint hasn't been brought up. Instead people are complaining that binning like this is inherently useless because edge cases are arbitrary. They're wrong, that doesn't keep it from being useful. It's a pretty standard statistical tool.
If you want a none of the above option, it shouldn't be 'well-rounded character'. Hell, no character is well rounded in the Lair! There isn't enough XP! It should be I play a wide variety of characters. This is actually realistic.