MGoPredictions Survey 2015
note: TL;DR at bottom
Yay! I finally have enough MGoPoints to post a new thread! For those of you who have already seen this in one of the "There are..." threads, I apologize. I am sure that there are lots of users who avoid those or who don't read every comment, so this is for you.
A few weeks ago, I was listening to a podcast on NPR (http://www.npr.org/sections/money/2015/08/07/430372183/episode-644-how-much-does-this-cow-weigh) about a phenomena that a crowd trying to guess the value of something will get amazingly close to the actual value when you average out all the answers, even if no individual has any expertise in predicting that value. They asked their listeners to guess the weight of a particular cow they had taken a picture of. When they averaged out all the answers, it was within a few pounds! Fascinating!
It inspired me to create a survey to see how well the MGoCommunity could predict this season's outcome. For each game, I'm asking you to assign a probability of winning. I will then average out the win % for each game and run a Monte Carlo simulation to arrive at a predicted number of wins for the season. After the season is over, we can see how we did. A number of experts have made their predictions for our season (e.g. http://mgoblog.com/mgoboard/det-news-article-predicting-number-michigan-wins-season and http://mgoblog.com/mgoboard/angelique-s-chengelis-predicts-michigans-season) let's see if we can do better!
My survey isn't testing the theory exactly. For one, we aren't guessing a single value. Rather, we are guessing a set of probabilities. If we predicted a 50% win probability for a game, were we right if we win or if we lose? Or, if we predict a 90% win probability and then lose that game, were we wrong? Not necessarily: play that same game another 9 times and maybe we win all 9. There are random chances inherent to football that interfere with the theory above. Also, our pool of respondents is inherently biased. Are we going to overpredict the number of wins?
This season will be especially interesting given how difficult it is to quantify HARBAUGH and how much the disappointment of the last few years will skew us towards pessimism, but I plan to do this every season going forward. I suspect it will be a fun tradition.
I'll leave the survey open up until kickoff of the Utah game and will post the results a few days later.
TL;DR
Let's see how accurately the MGoCommunity can predict the outcome of the season by assigning a win probability to each game. I'll run a simulation with the results to calculate the number of wins we as a community expect. Here is the link to the survey: https://www.quicksurveys.com/s/Cj74PpK Thanks for participating!
August 31st, 2015 at 5:47 PM ^
Why you aren't just polling the blog about the number of wins? That is a single value and would test the theory the same way judging a cows weight by picture would.
August 31st, 2015 at 5:49 PM ^
August 31st, 2015 at 5:51 PM ^
Any inherent biases we have as Michigan fans will still be there in estimating our % chances of victory in individual games.
Perhaps asking for individual game % chance victory along with a number of wins for the season would be interesting to compare.
August 31st, 2015 at 6:08 PM ^
August 31st, 2015 at 6:37 PM ^
I thought the same thing too at first. However, I guess by doing a percentage it helps to see if the team over/under acheived.
There's games on the schedule every year that you are "supposed to win" which would have a higher percentage compared to say OSU/MSU.
August 31st, 2015 at 5:48 PM ^
I personally guaransheed all the W's
August 31st, 2015 at 9:56 PM ^
All of the W's what?
September 1st, 2015 at 6:19 AM ^
August 31st, 2015 at 5:52 PM ^
Didn't we already do this? I think we already did this.
August 31st, 2015 at 6:11 PM ^
August 31st, 2015 at 6:00 PM ^
August 31st, 2015 at 7:55 PM ^
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August 31st, 2015 at 6:17 PM ^
August 31st, 2015 at 6:18 PM ^
I am curious about this - were you going to compare the results to those of established algorithms like Massey Ratings to see how far fan estimates would fall from those? I ask because it would be interesting to see any results you get from this put up against some of the more accepted ways of generating probability estimates for these games.
August 31st, 2015 at 6:50 PM ^
August 31st, 2015 at 6:36 PM ^
August 31st, 2015 at 6:41 PM ^
August 31st, 2015 at 7:16 PM ^
August 31st, 2015 at 6:47 PM ^
August 31st, 2015 at 7:18 PM ^
100% gurantee we beat MSU. Chisel it in stone and notarize that shit.
August 31st, 2015 at 9:32 PM ^
August 31st, 2015 at 6:50 PM ^
You should update the results after a person takes the survey. Unless you are not releasing the results until after the season? I'll stick with 8-4, though I would not be surprised if Harbaugh wins 10 games. I think there will be a lot of close tough games on the schedule. The only Cupcakes may be UNLV and Rutgers!
August 31st, 2015 at 7:07 PM ^
I am going with 12-2. Yes: I think they win the Big Ten Championship with their only losses being to BYU and PSU.
The more I think about it, the more I think my original 10 is a "tweener" number. They will either be good enough to win 12 or only good enough to win 9.
August 31st, 2015 at 7:16 PM ^
I happen to be a patent lawyer who during cs grad curriculum and beyond constructed a number of mc simulations. Later I worked in industry utilizing mc. Currently I represent clients who apply mc. I'd love to see you post a link to your approach. Is this for an undergrad thesis? Grad? Industry? Winning a bar bet? (hah) Curious.
September 1st, 2015 at 8:07 AM ^
Nope, it's not for anything, just to satisfy my own curiosities. My approach is pretty simple. Remove outliers. Average out the win probabilities for each game. Then randomly select an outcome for each game in accordance with the win probabilities. Then sum up the number of wins for the season. Do this a couple thousand times and I'll get a distribution of expected wins.
If you have suggestions to improve my approach, I'd love to hear them.
August 31st, 2015 at 7:39 PM ^
I heard that story as well and think this is a cool idea. I guess to some extent however, there is something characteristically different about judging the size of an animal because it isn't predictive--meaning the value is static. I am not sure if the theory would extend to predictions, since the scenario changes constantly. Should be interesting though.
If you're a Redditor, this could be interesting to post on r/CFB, especially if you just created a survey with a handful of well-known teams and asked, "How many regular season wins?" for each.
August 31st, 2015 at 8:41 PM ^
August 31st, 2015 at 8:06 PM ^
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August 31st, 2015 at 8:28 PM ^
August 31st, 2015 at 9:24 PM ^
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August 31st, 2015 at 9:40 PM ^
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August 31st, 2015 at 10:16 PM ^
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August 31st, 2015 at 11:30 PM ^
August 31st, 2015 at 11:08 PM ^
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August 31st, 2015 at 8:40 PM ^
August 31st, 2015 at 9:26 PM ^
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August 31st, 2015 at 9:51 PM ^
The D will be playing lights out and will get some turnovers, one for a TD. Special teams will score a TD and we may win going away 31-13. This not surprise me since everyone and their dog in the media is picking UT to beat us! I worry more about a let down against BYU at home.
September 1st, 2015 at 8:33 AM ^
9-3 win over MSU OR OSU, not both.