I have a Twitter robot that produces a probabilistic prediction for senate races of every day at 4:42 MT.
My prediction is derived directly from the prediction market PredictIt which has markets for 13 of the 35 senate races this fall where the ones there aren’t markets for are pretty unlikely to be interesting. I perform a small adjustment to debias the market prices for favorite-longshot bias that I can go into more detail on should anyone request it.
Note: the Alaska race is between an incumbent Republican (Sullivan) and a Democratic Party independent (Al Gross). For the purposes of this contest I’m considering Gross a Democrat, which I’m sure would bother him to no end.
The goal is for each race to assign a value, D, between 0 and 1 that represents the probability that a Democrat wins the seat, and value, R = 1 - D, that represents that a Republican wins the seat.
A sample entry looks like this:
Race D R Alabama 2.8% 97.2% Alaska 5.7% 94.3% Arizona (special) 83.4% 16.6% Colorado 95.6% 4.4% Georgia 24.2% 75.8% Georgia (special) 32.4% 67.6% Iowa 27.1% 72.9% Kansas 22.6% 77.4% Kentucky 8.6% 91.4% Maine 72.3% 27.7% Michigan 84.2% 15.8% Montana 49.3% 50.7% North Carolina 69.4% 30.6%
Entries will be submitted by posting in this thread. The most recent post by a user with a timestamp on or before May 31 will be that user’s entry (i.e. you can change your entry until the end of May). I plan to post mine by on May 31, but the above sample will be my entry if I don’t post an update.
After the election results are known, I will compute the Brier score for each entry. Lowest Brier score wins.
Can you, using polls, pundits, or pig entrails, outperform PredictIt this far out from an election?
Let’s find out.