Quote:
Originally Posted by MikeE
I think JesseK's expectation is that we would see substantial variation between different schedules, i.e. ranking is more a function of schedule than of OPR "performance".
So yes, while the average would approach OPR, we only play a single schedule which is likely to be helpful to some teams and disadvantage others.
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Correct; given a specific schedule (such as the preliminary one or the one we'll receive Wed/Thurs), the question is more about the point spread across the matches a given team (e.g. 1885) is in and the potential to change the predicted outcome. If a team knows their own potential increase (i.e. we know we can now hit 4 cycles in a match instead of 1-2) due to pre-champ tweaking, then it can be used as motivation team-wide for each student to perform better. Or it can be used to manage expectations if a team hasn't done
anything to improve their bot.
Such simulations can also be used as motivation in the decision making process -- do we keep practicing what we're doing, or do we try a different approach for this match? How would that decision change if we have 3 hours of consecutive pit time prior to that large-spread match vs. if we only have 30 minutes? If the point spread is large, with little predicted chance for us to win, we may take more risks for those matches.
Simulations may be more accurate for prediction than bean-count scouting early on in a schedule. Yet once we've hit everyone's 3rd or 4th match, I'd much rather have the disc-by-disc replay than a regression stat with few data points. Behavioral analysis also helps.