Quote:
Originally Posted by Ed Law
Great analysis. I think 72 should be very close to the cutoff like you predicted. Can you redo #2 with data from Week 5 and see what the cutoff is? You should be doing this for Michigan every year from now on.
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Thanks a bunch!
I repeated the analysis on the data. Now, everyone has played one or two events (except one team that I presume will not attend any) and thus we don't need to fudge the number of slots for teams that haven't played. With these projected points, the 102nd slot was the very last team with
72 points. If you account for chairman's winners, which so far there are 5 winners that are below the cutoff. There may be more come week 6, but if you assume 5 auto-qualifiers, then the cutoff is the very last team with
73 points.
This is interesting because it has gone up ever so slightly from last week. But there are other factors at play. There are more teams than usual this year that are playing their second event in week 6 than other weeks (since there were relatively fewer 3rd district slots this year, and a lot of them were are LSSU, for example). This shouldn't bias the data that much, but it reduces the external factor that 3rd district teams tend to do marginally better than teams playing their 2nd district out, because they have more experience in the year. Thus, it implies that the cutoff may be closer to the chairman's fudged cutoff of 73. Either way I think it means that there's room for variance, but it is likely that either all teams with 72 points and some with 71 make it in, or just some teams with 72 make it in (ignoring declines).
On another aside, I dug up
this post from last year that presents an approximation based on past years points and only is dependent on % of teams attending. If we use 102 teams out of 410 teams for this year, and plug it into that equation, we get approximately
71.39 points which I thought was just so cool since that's what my totally different regression method got (see #3 from my post). I do think that this formula gives a bit low of a number since it was a bit low last year, and that's probably because it doesn't account for the change in district points last year. I would try to add last year's data point to that data, but I don't know where to find the data from previous years that he used.