2018 Prediction

This Saturday, my grandmother died.  I have decided with a heavy heart to continue to predict this election.  This project has been two years and many hours in the making.,  and I believe that my Grandma would have wanted me to continue. But given that this is a very emotional time,  I will later repeat the model in case I made a mistake.

Map with Tossups

Map with Tossups Decided

Overall I predict that Republicans will hold the Senate.  The polls are very close, and there might be a few surprises.  A part of me is afraid that we will see the same amount of under-capturing the support of Trump voters.  I do think a lot of pollsters have put a lot of work into building better likely voter models and weighting and they should be better, but there could be the same error we saw in 2016 that is making me a little nervous about the polls in the states Trump won with Democratic incumbents.   A lot of these competitive states are hard to poll.

I also want to represent the uncertainty in my model based on my error in the presidential model because that’s the best estimate I have of my success.    I measure my success both in terms of my predicted outcome and the actual outcome and what races I call correctly.  But since there is six toss-up states, I could be wrong about the winner but still do a very good job at predicted the outcome.  This election will come down to turnout and who is more enthusiastic about the election.

Here is the scale of uncertainty:

Safe:  Unlikely (but possible)  for the model to be wrong in predicting the winner (darkest color)

Probably Safe: It is more likely than not that the predicted winner will win. (Medium color)

To close to call: within 2.5 points or within one average error of the presidential model meaning a near statistical tie at about 68% confidence. (light color)

I have no idea:  The error is within or almost within the credible interval in my model with suggests the model is incapable of distinguishing a winner but the leader gets the seat in the final count.  (beige color in the first map, light color in the second)

Competitive Race Highlights

Here are the 11 competitive states and the predicted margins for the pooled and iterative model.  The expected error based on the presidential model data is about 2.5 points.  This doesn’t mean that I will be off by 2.5 points in all of these races. I usually get some states that are spot on with the very small error and then a few outlier states.  Numbers may not add to 100% due to rounding. R, D represent the party, and I represents incumbent.

Missouri- Hawley (R) 50.6, McCaskill (D, I) 49.4,  Margin: 1.2

Verdict:  I honestly have no idea.

The polls are really close.  FiveThirtyEight says that the fundamentals and the bias of the pollsters give McCaskill an advantage and my model doesn’t include that.  Honestly, my goal is not to predict the winner here and just hope that my prediction is close.

Nevada- Rosen (D) 51.2 ,  Heller (R,I) 48.8 , Margin 2.4

Verdict:  To close to call.

In 2012, Heller won a  point, and Clinton did carry Nevada.  I think Rosen has a slight advantage here, but turnout will determine the winner.  Democrats and independents are turning out in early voting,  but you could see an election day surge among Republicans,  and we only know the party the voters were from and not the actual votes.

Florida- Nelson 50.2 (D,I),  Scott 49.9 (R) Margin 0.3

Verdict:  I have no idea who will win.

All I know about this race is that is incredibly close, and Nelson might benefit from the excitement over the Democratic Governor candidate Gillum.

Arizona- Sinema (D) 51.5,  McSally (R,I) 48.5, margin 2

Verdict:  To close to call.

This is another one of these races where it comes down to turnout.

Texas: Cruz 52.8 (R,I), O’Rouke (D)  47.2, Margin: 5.6,

Verdict: Probably safe for Cruz

In my home state of Texas, I predict a Cruz win with a margin of 5.6%.  Based on my historical presidential error this would mean Cruz has about a 95% chance of winning, but my gut suggests that the polls may not have captured the enthusiasm among first time and young voters, so maybe its closer to 66% chance for Cruz.

Tennessee: Blackburn: 51.1 (R),   Bredesen (D) 48.9  Margin: 2.2

Verdict: To close to call with more than 68% certainty

The model thought this was more of a toss-up than I did,  but it wouldn’t be surprising for either candidate to win.  Turnout is probably key here.

North Dakota: Cramer (R) 54.4, Heitkamp (D, I) 45.6, Margin 8.8

Verdict: Relatively safe for Cramer

The North Dakota polling is a little sparse and Heitkamp could surprise us, but I doubt it.

Montana: Tester (D, I) 52.3, Rosendale (R) 47.7, Margin: 4.6

Verdict: Probably Safe

I would not be surprised if polling overly favors Democrats in the heavily red states because Trump still trashes the polls and the media so I completely wouldn’t reject the possibility of a repeat the surprise of 2016 in Michigan, Pennsylvania, and Wisconsin, but I ultimately think Tester should win.

Indiana: Donnelly (D, I) 51, Braun (R) 49, Margin 2

Verdict: To Close to Call

The model thought this race was closer than I thought it would.  There has been a lot of last-minute polling in October where Braun began to edge closer.  I wasn’t expecting this race as competitive as it was until this week. If Braun wins this would be not surprising for me.

West Virginia: Manchin (D,I) 54.4,  Morrisey 45.6, Margin 8.8

Verdict:  Probably Safe for Manchin

This race was a lot less competitive than I expected, but I guess West Virginians like Manchin.  My model always struggled with West Virginia in presidential elections so if Morrisey would it wouldn’t be that surprising.

Details

This election I have five different groups.  To be considered competitive a race must have two polls where the margin is smaller than the margin of error.  The red group contains both Mississippi races, Utah, Wyoming, and Nebraska.  Wyoming has no polls so I will use Utah’s polls.  The blue West group contains Washington, California, New Mexico, Wisconsin, Michigan,  Hawaii, and both Minnesota races. The blue east group contains Maine, Vermont, New York, New Jersey, Ohio, Virginia, Delaware, Maryland, Massachusetts, Connecticut, Pennsylvania.

I split up the races with two or more polls were the leader in the poll was ahead by less than the margin of error.  I then group the states into red-leaning, blue-leaning and toss-up states based on how I viewed the race.  The competitive red-leaners are Texas, Tennessee, North Dakota. The competitive blue-leaners are Montana, Indiana,   West Virginia. The tossups are Missouri, Nevada,  Arizona, and Florida.

And lastly the special cases.  Hawaii and Wyoming have no polls, so my prediction is just the prior average. California has two Democrats, so there I just averaged the polls there.  In Maine and Vermont, I treat the independent senators as Democrats in my model since they caucus with the Democrats and there isn’t a viable Democratic candidate in those states.