Again, three of my four mistakes this time around were caused by my winning choice being eliminated in the previous round. For the last one:
Xavier:
12.500000 42.187500 29.687500 2 7 7 Wisconsin
34.375000 12.500000 14.062500 2 8 2 Xavier
What does the scoring comparison look like?
#Bracket | N_R1 | PP_R1 | Nwrong_R1 | P_R1 | N_R2 | PP_R2 | Nwrong_R1 | P_R2 |
Mine | 32 | 1 | 6 | 26 | 16 | 2 | 4 | 50 |
Heart-of-the-cards | 32 | 1 | 10 | 22 | 16 | 2 | 8 | 38 |
Julie | 32 | 1 | 10 | 22 | 16 | 2 | 6 | 42 |
BHO | 32 | 1 | 9 | 23 | 16 | 2 | 6 | 43 |
538 | 32 | 1 | 8 | 24 | 16 | 2 | 7 | 42 |
Rank | 32 | 1 | 13 | 19 | 16 | 2 | 6 | 39 |
Again the "rank" method is garbage, and shouldn't be used. Nate Silver had a tweet earlier about how this is apparently because it's based on RPI too much. Looking at wikipedia, it looks like RPI is an incomplete version of my LAM method. ¯\_(ツ)_/¯ This also shows the point where HotC totally falls apart, becoming the worst method. Everyone else is pretty well clumped together. I'm a bit surprised that 538 isn't doing better, given the "we included scores, and at-home values, and distances to the games, and the number of cats each player owns, and the SAT scores of each player."
This also makes me think I should have actually entered my selections into some pool. Maybe I should hone the method a bit more, and see how it works over a few more years. Or, alternatively, I could do the reasonably easy thing and apply the method to the historical data, and see if this consistently matches reality. Maybe next weekend, since I think it's a long one. This will also make me fix my master Makefile to put things into logical directories, and not just dump the outputs into a common directory.
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