Friday, March 25, 2016

Friday: Good Friday

What makes it good?

French toast, I guess.
This wasn't the best french toast ever.  It seemed a bit overcooked, and was a bit gummy inside.  Not their best, but they were also crazy busy at 4pm, so I'm guessing the kitchen was just overwhelmed.

But seriously, the best part of today is having a day off.  Originally when I was looking at the calendar, I was unhappy because it looked like today was being used both as the Good Friday holiday and the Prince Kuhio Day (which is tomorrow) holiday.  However, when I looked into it, they've added a "floating holiday" that can be taken anytime to account for the double-vacation weekend.  That's nice, because I can use it to pad out a vacation at some point.

And since it's the weekend, it's sports = statistics time.  First up, my picks for this round of things:
One that I was doomed to get wrong.

And the other doomed one.  But a new mistake!

Texas A&M:
29.687500       14.062500       3.125000                3       6       3       Texas A&M
28.125000       18.750000       21.875000               3       8       2       Oklahoma

First up, I think my analysis notes have been wrong on the previous posts.  The file I'm pulling these numbers from is in 2016/2015/2014/group/game/rank/name format, not 2014/2015/2016 format.  This changes the analysis for some of my previous mistakes, but I'm too lazy to go correct those.  In any case, using this new, correct information, it looks like I thought (from the 2016 ratings) that Texas A&M should be slightly better than Oklahoma.  Folding in previous years could have potentially altered that choice.

I was thinking a bit about adding some score-based information in as well.  The idea being that each team scores a given median number of points across all their games, and have a given median number of points scored against them.  By comparing how well a given score ranks in all their games, and against their opponent's, it should be possible to construct offense and defense ratings.  This might be useful to say, "Team X is generally better, but they only are a +1 in offense, and they're playing a +4 defense, so they might not win."  The other benefit would be to add two new metrics, which could then be used across the full multi-year dual-gender score set to determine which relative weights each should be assigned to a more complete prediction model.

I think the first step that I should do, though, is to dump all of that data into a database, instead of using horrible fixed-width formatted files to manage things.  That's largely a consequence of not really caring a lot about the project.


In any case, here's the comparison table for round three:

#BracketN_R1PP_R1Nwrong_R1P_R1S_R1N_R2PP_R2Nwrong_R1P_R2S_R2
Mine321626.995162450.998
Heart-of-the-cards3211022.656162838.320
Julie3211022.656162642.738
BHO321923.823162643.820
538321824.928162742.738
Rank3211319.129162639.424
#BracketN_R3PP_R3Nwrong_R3P_R3S_R3N_R4PP_R4Nwrong_R4P_R4S_R4
Mine84370.99890348
Heart-of-the-cards84646.04448
Julie84458.61048
BHO84459.67448
53884266.95548
Rank84263.87548

This now has the added columns of S_RX.   These are my simulated CDF values based on the Yahoo selection pick fractions given for each team.  This is another piece of kind-of garbage code that I threw together earlier in the week.  I think it's doing everything correctly, but I don't see any simulated results that get a total score above 83, and yahoo does list some in their leader list.  Maybe 1e6 simulations isn't sufficient to fully probe things?  Maybe I'm truncating or rounding something odd?  The main idea behind this calculation is to see how well a given set of picks should rank.

Plots for individual rounds and the total after three.  In general, the mean drops (because past mistakes have continuing consequences) and the variance increases (because there's the 2^N point scaling thing and because the number of individual games is falling as well).

Links.


  • Even though I've thrown out like five of your flyers, and get annoyed at your TV commercials, I still think you're ok, Bernie Sanders.  I guess birbs agree.
  • Star Wars.
  • This is why I love everything bagels.
  • And even though everyone has already seen it, Bi Lions.
  • Dog.
  • I wish there were more Mordawwa.









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