Worried about irrational exuberance? Have recurring nightmares about the mythical Red Wave of 2022? Want a way to take the jinx off of all the optimism bubbling up on the Right?

Nate Silver has just the take for you -- and while it's not quite doom and gloom, it certainly puts a different perspective on the data we've been seeing at the end. (Well, it's a little doom and gloom.) In his last data analysis of the election season, Silver concludes that he has no conclusion. However, he gives a slight edge to Kamala Harris in the end, based on 80,000 simulations:

🕒 Last and final update: 12:30 a.m., Tuesday, November 5. Happy Election Day! At exactly midnight on Tuesday, we ran our simulation model for the final time in this election cycle. Out of 80,000 simulations, Kamala Harris won in 40,012 (50.015%) cases. She did not win in 39,988 simulations (49.985%). Of those, 39,718 were outright wins for Donald Trump and the remainder (270 simulations) were exact 269-269 Electoral College ties: these ties are likely to eventually result in Trump wins in the U.S. House of Representatives.

How accurate are the simulations? Silver himself can't be sure. He lays it all out in his final Election Day bulletin, arguing that this election cycle has been such a black-swan event that predictions and simulations may not be crafted well enough to cover it:

This is my fifth presidential election — and my ninth general election overall, counting midterms — and there has never been anything like this. In 2008, 2012, and 2020, Democratic candidates were clear Electoral College favorites in our model, and I spent a lot of time arguing with people who claimed they weren’t. Hillary Clinton was a slightly less clear favorite in 2016, and our model was bullish on Donald Trump relative to betting odds and other forecasts — but a favorite she was. I suppose I’ll never get over that one.

In 2010, we correctly had Democrats favored to keep the Senate (where they started with a huge majority) but lose the House. 2014 was a boring and predictable Republican hold. 2018 was the inverse of 2010, with Democrats as heavy favorites in the House but big underdogs in the Senate. In 2022, our final Senate forecast was close1 — though not quite so close as this one — but the House wasn’t particularly so.

Even this year, the model definitively showed Joe Biden as an underdog, and the post I wrote introducing in June it emphasized that point: Democrats were trying to convince themselves the race was a toss-up when it wasn’t. But Democrats did the smart thing and shoved Biden aside. And now they’re rewarded by being able to determine the future of the country by means of … a coin flip?

That may very well be. And this does serve as a reminder that much of our optimism is based on probabilities rather than solid evidence. Polls are just probabilities, influenced by bias -- unconscious and conscious -- and colored by adjustments from previous experience that may not apply in the current environment. 

In other words, be careful about assumptions and aspirations playing too large a role in analysis, in either direction. This data could go either way, at least as it stands, as Nate Silver just proved about 80,000 times. It is just as possible to have missed a swing toward Kamala Harris as to have missed a swing toward Donald Trump in this cycle or as happened in the previous two cycles. 

But how likely is it? For that, we have other data. One measure that isn't probability-based is early voting; we actually have solid numbers for that, and they don't look particularly good for Democrats. America First PAC exec Marc Lotter explained that on CNN last night, although the panel wasn't convinced:

"The math doesn't work. The Democrats are down 1.7 million early votes in the battleground states in urban areas."

"They are down 1.4 million votes in the battleground states among women voters."

"Rural voters have overperformed early by 300,000."

"Democrats have to win their… pic.twitter.com/zarBQ7RY7o

— Kyle Becker (@kylenabecker) November 5, 2024

"Democrats have to win their races early. Republicans generally win them on election day."

"The margins don't add up right now for the Democrats in any of these battleground states," @marc_lotter said.

Take Pennsylvania as n example. In 2020, Democrats went into Election Day with a million-vote EV lead, and ended up winning the state by 82,000 votes. Today, their EV lead is only 410,000. I'd rather have a 410K vote lead than a 410K vote deficit, but the data strongly suggests that Democrats are not turning out the vote and the GOP has been picking up steam in the state -- and that Democrats are coming up short by several hundred thousand votes in a state they barely won the last time.

The other key data does rely on probability, but it also potentially contradicts the probability baseline for the data on which Silver ran his projections. For the first time since Gallup began measuring party identification in 1992, Republicans now have an R+3 average advantage in Gallup polling nationwide -- a shift of eight points from the 2020 general election environment. I've mentioned it before, and Alex Castellanos sent up a warning yesterday as to what that means for the polling data we are considering:

'I think the pollsters are getting this wrong. They are all missing something because they're giving us the same poll over and over again', [Alex Castellanos] said.

'What I think they are missing is a massive shift in voter registration underneath all of this. 

'31 states have voter registration by party, 30 of them in the past four years have seen movement towards Republicans.

'Yet we are getting these surveys that are off base. I'm not going to call it a wave but I think there's a "wavelet" out there of Republican enthusiasm in registration.'  

An eight-point shift in Gallup's party-ID measure in a single cycle from D+5 to R+3 is almost unprecedented, and it almost certainly reflects an enthusiasm shift in this election. If pollsters didn't adjust their models for this shift, then they will likely underestimate voter intent in all of their results. That would infect Silver's simulation models to the extent that the underlying data is inaccurate, and it would miss the enthusiasm gap in likely-voter models especially.

However. As much as we hope that the analyses indicating a big night for Republicans prove accurate, we have to keep in mind that all of these are interpretations. Only the early-voting reports are actual solid data, and even those are being seen through interpretive prisms. That's what we do, but it still behooves us to approach that task with some humility -- or at least professional detachment.

In the end, I'd still rather be Trump than Harris with this data. But let's not get ahead of ourselves in popping champagne corks. Watch, wait ... and vote vote vote.