Quote:
Originally Posted by Michael Corsetto
However, I want to emphasize that, in practice, filtering pick lists based off of pit data can be very helpful. I call it "strategic generalization".
For 2010-2014 era games, 1678 found that making an initial filter based on drivetrain type improved the quality of our 2nd pick. I think this is what Gregor was talking about.
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A better-said version of what I was trying to say. Although it isn't usually helpful for much else, pit scouting data can make a good filter.
Quote:
Originally Posted by gblake
Do you suppose that it's possible that an even more effective and useful filtering or ranking could have been done using accurate observations of how the drivetrains (and drivers) performed on the field, instead of using the results of your pit scouting?
I'll wager a nice dinner that it is more than just possible; and I think that is what EricH was talking about.
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I'm sure it's possible, but it would be highly subjective. I'm not saying that subjective information is bad, but trying to use subjective information to filter quantitative data is unreliable, at best. Say you ranked each team's drivetrain/driving abilities on a scale of 1-5, and only viewed the 4s and 5s. This, of course, raises a few inevitable questions:
-what's the difference between a 4 and a 5? You'll need a list of differences between a 4 and a 5, which will include even more subjective criteria.
-how important is the difference between a 4 and a 5, versus the more objective quantitative data? What if there's a team with a 5 that can't do any scoring, but there's a 4 that could score a few points in auto, and a few in teleop if needed?
It's probably possible, but it's the kind of thing that would get very messy very easily. It's better to do your first-order sort by easily-quantified information, then take into account more subjective information to do more detailed sorting. It makes the entire picklisting process more efficient.