Mining the silver lining of the Trump presidency

It’s January 9, 2021. Yesterday, two days after the President (who by the way is Donald Trump, the guy from The Apprentice) ginned his supporters up into storming the Capitol (wtf?) and coming within minutes of possibly lynching the Vice President (okay, maybe this wouldn’t have happened), Twitter finally discovered the justification to shut down Trump’s account. This is all horribly and hilariously and unimaginably absurd.

Let’s get even weirder. For the better part of the last four politically insane years, a community of gamblers wagered stupid amounts of money betting on a simple question: How many times would Donald Trump tweet this week? The game ended for us before it ended for the President, but now that it’s completely over, I feel this tiny corner of Internet weirdness deserves some remembrance. After all, there are very few other people on this planet that understood Trump’s twitter habits – and by extension, Trump himself – more than the people who bet on them.

The Genesis

It starts with PredictIt, which of course readers of this blog are familiar with. In 2016, the run-up to the election featured a suite of recurring weekly markets in which traders bet on who would be leading in the polls, Congress’ approval, the direction of the country, and Obama’s job approval. These were fairly successful for the website in that degenerate bettors loved markets where small bets can hit big (which they did) and savvy bettors enjoyed the game (and gamesmanship) that came with figuring out how polling averages worked, polls were released, and how that information eventually reached the market. In the process, a community formed. In particular, the discussion boards for the Obama approval markets (OA) became a place for happy numerically-inclined (and often left-of-center) traders to hang out. Thursdays, for example were “scotch-and-base” nights when a trader (“baselevel“) and others would drink scotch and answer questions from newer traders who had no clue how polling markets worked.

The OA crowd got tight-knit enough that after the election, an IRL get-together was planned for Chicago (in the middle of the country). The organizers were baselevel and m4ry and it was relatively well-attended, with I think around 20-30 traders showing up in what was the first or one of the first real-life PredictIt trader meet-ups (I didn’t go – at the time my net PredictIt winnings were literally $1200 and I couldn’t justify the cost). John Aristotle, the founder of PredictIt, was so jazzed there was a meetup happening among people who met on his website that he even flew out from DC and came by himself, talking a lot about his big plans for site expansion and so forth (as I understand it).

Anyway, a few weeks after this meetup in the middle of December, John reached out to some of the traders he had met. Polling markets were drying up a bit and he wondered if the polling market crew had any ideas for any new weekly recurring markets. At this point, I was involved in the twitter group chat with a handful of the OA veterans, and we began tossing around ideas. At this time, the mainstream was just getting used to the idea of paying attention to Trump’s tweets. Every tweet was a news story in November and December of 2016. He was threatening GM and Chrysler via tweets and nuking their stock prices (briefly). Quants on Wall Street started building bots that would keyword search his tweets for relevant companies so they could automatically trade in response to a twitter attack (the stock market was the first tweet market). There was this notion that Trump “used” his twitter account strategically (we’ll get there, but any tweet market trader would laugh at this now), and his “grasp” of social media was being talked up and praised. Here was a President-elect who posted his own tweets in a way that was unpredictable and – at that time – seemingly unavoidable.

So in our brainstorming session, at one point I said something like “you know what would be cool – if we had a market on how many times Trump tweeted in a week”. I’d gone and done a PhD at this point and yet this tiny little thought ended up snowballing into the most lucrative idea I’ve ever had in my life (and probably changed the course of my life – which is a deeply strange and weird thing to reflect on now). Others immediately agreed, and we began working on it. Dmp (another trader) wrote up an email proposing a more fleshed-out idea (m4ry and I did some research on possible brackets) that everyone had contributed to at that point. We sent it in to Aristotle, heard back that he loved it, and then heard nothing else. (One note here: we weren’t the only ones thinking of this as a market idea, at least one other OA person, a trader that goes by “klumein” also posted about a week after we sent the email in that a market on Trump’s tweets would be amazing. I’m sure there were others.)

There was a problem in our proposal: we didn’t have a good way to keep track of the count. We suggested just manually counting the tweets, but we knew that the PI resolution people probably wouldn’t want to do that. As December went away, we figured our market idea was dead or otherwise found unworkable by the powers that be. Imagine our delight, then, when early January brought us this:

The very first tweet market. PredictIt had solved the tweet count problem: apparently you could just hover your mouse over the number of tweets on a user’s homepage and even if they had thousands of tweets it would give you the precise number. The game was on, and everyone was stoked:

The first comments of the first tweet market.

The Early Days

The early markets were instant classics. That first market? It did 1.7M in volume. And he barely tweeted back then! Look at these brackets, those of you who only came to discover tweets in 2018 or 2019:

(Amusingly, B45 would win three weeks in a row to start)

People had absolutely *no idea* what they were doing. 50+ opened at 33c then rose to 50c then fell back down then did it again (it hit 50c or higher six out of seven trading days and ultimately lost). Then there were the complex rules. Did retweets count? What did deletions do? We had to figure it out ourselves:

People didn’t know what “the count” was. A tweet would happen and it would take a minute before the market reacted and the comment section had sorted out what the current count was. Every time a tweet was posted, someone would post “BOOM” in the comments, leading to a cottage industry of shitposters spamming “BOOM” every so often just to see if people would react (hi, JonH). When a tweet killed a bracket, it would actually take longer than a second for it to die (no one was using Twitter’s API back then).

[By the time we got a few months in, people started creating websites to track the count publicly – there was (now defunct) and then, most notably, created by PI trader Abe. This fantastic resource made it so everyone knew where the count could. Eventually, we even got to the point where traders like Dave were offering paid services of a twitter bot (pitwets, with free version pi_alerts) that would notify you of each accounts tweet instantly, the count, whether a deletion happened, what the “pace” was and so on. An entire cottage industry built within this little fairy garden of the internet!]

The first market also birthed the first Trump tweet analytics, with m4ry among the first to make a spreadsheet tracking his habits and attempting to model them:

(Using a Poisson distribution to model Trump’s tweets is, it turned out later, really hilariously bad).

And all the OG traders were there. The very first tweet market? RJ took an enormous bath:

Even Domer, who later came to more or less hate tweet markets (well, the non-Trump ones especially) enjoyed himself:

The early markets were pure. Degenerate? Very. But we were living in a world where Trump was about to be President. Weird stuff happens now. So, sure. Why not bet on how many times a madman will tweet?

Switch to POTUS confirmed??

As inauguration loomed, so too did a huge question for tweet traders. Would Trump keep tweeting on @realDonaldTrump, or would he switch to @POTUS? That market (I can’t dig up the link right now) was absolutely insane. The first few posts following his dark inaugural? All went to POTUS. The lowest bracket went north of 70c. Later in the afternoon? Trump tweets himself. Back down to 20c. Then back up. Over 4M was traded, with the final result landing again somewhere in the 40s for the weekly count.

With the uncertainty of an account switch, PI obliged us by creating a second tweet market for the @POTUS account, just in case. But then both markets did very well, and after a while – why not one for @VP as well? By summer 2017 we had four weekly twitter markets: @realDonaldTrump, @POTUS, and two for @VP (one that ended Tuesday and one that ended Friday, which never confused anyone ever causing them to make a trade in the wrong place). At one point in 2019 we had like twelve tweet markets (it was too many).

Tweet markets consume all

Around this point, it became clear that you could actually kind of make money trading tweets. I had started writing guides explaining how the markets work. Traders were getting more sophisticated. We understood what we had to do to win. For Trump’s account, that meant we had to know him. We had to learn when he tweeted and when he didn’t (waking up at 6am on a Wednesday was absolutely required – for years the “bong” of my computer signaling a Trump tweet was my alarm clock). We had to learn why he tweeted what he did (he saw it on Fox news – I bought a YouTube TV subscription at one point so that I could find where he was in his DVR-viewing-sesh and scroll forward to find likely topics). We had to learn how to get the tweets as fast as possible (I had begun learning to code in grad school, but it was PredictIt forcing me to do so for polling and twitter markets that actually taught me). We had to know when there were deletions. We had to learn how the markets reacted to a tweet. In effect, tweet markets taught me how to trade. (There’s honestly probably a prediction market research paper waiting to be written on tweet markets about how just the existence of a novel market type produces smarter prices over time as the participants gather experience.)

Yet for all the time-consuming nature of these markets (one of the things about Trump is that the man could get himself going at literally any time), they remained probably one of the healthiest outlets out there – for me at least – when it came to processing the manifestly insane shit that the President said. When you saw an amazing tweet from him, it wasn’t just some alarming thing that a reporter put into your timeline. Now there was an entire community of traders digesting it right along with you, marveling at how stupid or out of left field the tweet was, its typos (would he delete and repost?) and what it meant about what he cared about. Many times you’d see a Trump voter in the twitter market comment section even remarking how nuts Trump’s latest missive was. Looking back, it’s actually shocking how little political arguing there was among the tweet bettors despite it being full of folks on left and right and centering on Donald Trump. For better or worse, tweet markets took at least some of the craziness of this Presidency and boxed it up into an easy-to-understand game where everyone was more or less on the same playing field.

Trump is predictable

One of the biggest false memes in coverage of Trump and his twitter accounts over the years was how his tweets proved how unpredictable he was. In a sense – sure. He could tweet at random times, but mainly he tweeted while watching TV in the morning and the evening. Yes, sometimes things came out of left field, like when he wished Happy Birthday to Maxine Waters at 10am on a Wednesday morning, completely up-ending a market. But overall, betting on his tweets taught you how he worked. The profit incentive offered by the market forced you to learn how narcissism operates. There is a logic there. You just had to have a lot of money on the line to understand. A few lessons from over the years:

-Big news made him go quiet more often than not. When he doesn’t know what to say, he waits. He was quiet after firing Comey became a huge thing. He was quiet immediately after Charlottesville. He was quiet just now, after the Capitol was stormed. You’d get some tweets, sure. But you wouldn’t get a lot of tweets. He’s more conscious when he knows everyone is definitely paying attention. It’s when he was feeling loose that you’d really get some special tweets, or lots of retweets.

-He rarely if ever used twitter as a strategy. There was never a grand design in his tweets (other than some spam endorsements). He just posted. Mainly, if there was a goal, it was to shape the reality perceived by his supporters into the reality he wanted to live in (or thought that he lived in). For over a year leading up to the 2020 election, he would tweet stuff like “96% support in the Republican party – thank you!” Why? To remind people that he had control over the GOP but also to reaffirm the same to himself. You’d typically see these tweets during times of intra-party friction. The number, of course, was more or less completely made up, having derived from a straw poll of CPAC attendees in 2018 and metamorphosed from there (the original number was 93%, it got up to 97% by the time Trump was done with it).

-He was tweeting to his supporters. To him, if you followed him it was because you liked him. His follower count was one of his most prized possessions – narcissism craves validation above all else. He wasn’t ever really tweeting to the media or to his enemies. He’d tweet at them, sure. But the point of the message was always “hey guys, this is how we think about this, ok?”. His trademark ending of tweets with something like “Sad!” encapsulates the whole thing. He’s literally communicating how he feels and how he thinks you should feel too and he wants to make sure the message is heard loud and clear.

-Anger did not produce tweets, but fear did. Donald Trump is deeply insecure, of course. The thought of people laughing at you behind their backs or being otherwise humiliated is the biggest injury someone could ever do to you, in his mind (hence his use of that comparison in the soon-to-be impeachable phone call to the Georgia SOS). When Joe Biden received a firefighter’s union endorsement in Pennsylvania, Trump erupted with over 60 retweets of various purported firefighters that replied to some other tweet angry about it (there were several other PI traders in the replies hoping to land a retweet themselves so they could delete it later and flip a market at some point). Trump hates losing something he thinks belongs to him – his insecurities can’t stand it, hence the furious retweets signaling that in fact he hasn’t lost anything at all. (He will also have to lash out for losing his twitter account at some point. He needs attention and will find another way to get it).

-Retweets and his growing use of them in the back half of his presidency remains underappreciated. There was a time in 2017 where he barely knew how to use the platform (it seemed). He couldn’t thread his tweets, and would often end a tweet with “….” and start the next with “….” to signify they were connected (the two tweets might come hours apart). By the end of his presidency, he threaded tweets himself and engaged in hour-long retweet sprees, often going for 100+ retweets. He began to use the retweet button as a quick and easy way to amplify messages and people that he wanted his followers to internalize. His habit was to stumble on a good account, click through to the username, and scroll through their posts, retweeting as many as he could until he got bored and found another username to scroll through somewhere in the replies. No one else tweets like this. And no one other than tweet market traders really understood what was going on – by the time this habit formed, the media was more or less bored by his tweets and no one else was paying that much attention (probably not even his followers).

It’s All Gone Now

Of course, it’s over and these lessons learned don’t really matter. The markets died first in June of 2020 – victims of regulators who finally decided they crossed the line (the fact that at one point we had markets for Yang Tweets and someone trading on them threatened Yang’s life if he didn’t stop tweeting, getting the FBI involved, probably didn’t help). I’m pretty sure I legitimately grieved their loss, which is both sad (in the pathetic way) and also kind of amazing (also in the pathetic way). I mean, what a weird fucking hobby! The spreadsheets I maintained… good lord. While the money was cool (around +$120k lifetime in tweet markets), the fact that I have memories and stories about “that time when Trump retweeted 60 firefighters” kind of says it all. Normal people do not have these experiences! And all starting with one random kernel of an idea I had back in December 2016.

And now Trump’s account is poofed! Kind of have the feeling they’ll bring it back, maybe in some archival form in a few years. (Just had a thought: the Trump Presidential Library will probably have some sort of exhibit on his tweets). But what a change. No longer is the “I wonder what he’ll say about this” itch going to get scratched. Will GOP politicians try trashing him more often now that they don’t have to care about him tweeting? Are all those primary threats vacant now that Trump can’t drive headlines? Will we care as much about Trump’s 2024 run prospects without being able to rely on him keeping us informed? Or will he re-emerge elsewhere? (I’d assume so).

Whatever happens, we probably won’t be trading on how many times he Parlers (is that the term?) or whatever. So rest in peace to very weird corner of the internet that tried to make sense of a very weird presidency.

Hindsight is 2020

What did we learn from the 2020 election? The SSG blog invited some contributions from other traders (read it here) and I wasn’t able to come up with much at the time of asking. But now with the benefit of a few more full nights of sleep, I’m ready to tentatively sketch out some lessons to take from 2020:

1. The polls were wrong but not unpredictably wrong

If there is a silver lining in this election for MAGA bettors, it’s that at least they can claim that they were right about the polls underestimating support for Trump. It’s unclear exactly why this happened (I am intrigued by the nonresponse bias hypothesis, perhaps exacerbated by the pandemic polarizing stay-at-home-by-the-phone behavior on partisan lines), and even why the extent to which it happened varied by state. Preliminarily, states with lots of educated white college-aged voters were polled well, while those with high populations of white non-college voters were not (see: MN vs WI). Although, district-level polling of suburban educated districts also showed down-ballot Democrats doing a lot better than they ended up doing! So perhaps not the entire story.

There were some hints of reality in the polling. Biden’s softening support with Hispanic voters? It was there, but did not show up as dramatically as it manifested. And the polls did accurately capture the partisan splits in vote by modality (they nailed vote-by-mail preferences), but probably missed on turnout by subgroup. From a bettor’s perspective, what can we learn to minimize our exposure to polling error in the future?

My takeaway is that you have to always be vigilant in challenging assumptions. Did I consider that Biden’s support among Hispanics was soft and getting softer? Yes. Did I ask “what would happen if the floor really fell out for him in this group?” No. Did I take ABC’s Biden +17 in WI poll seriously? No. Did I ask “what would happen if there’s systematic partisan nonresponse among white noncollege voters?” Also no. Did I even fathom that polls of down-ballot Democrats would be so incredibly bad? No, but I mean, lol.

One final point on polling: the polls “felt” a lot worse than they will end up being, and a lot of that has to do with the order in which votes were counted. At the same time, they told a story (“Dems will have a great night”) that did not come to pass, particularly in the House and Senate. And any time the narrative is up-ended, people are going to be mad at the polls. (Note that in 2018, the polls also got a lot of stuff wrong, but people weren’t mad because the overall narrative was correct: Democrats gained a bunch in the House).

2. The models were both wrong and good

In terms of spitting out a win probability, both 538 and The Economist put out models that did a reasonable job given the inputs they had. The inputs were just kind of shit. Was Biden really 90+ to win? He was not. Polling error was not evenly distributed around the mean; it was always more likely that polls favored Biden than that they favored Trump. This shows up clearly when you look at forecasted margins: the prominent modelers had mediocre performances. (Notably, one modeler, Plural Vote, stands out in the crowd; they also had Joe only at 66% to win overall).

Here, “Presidential Battlegrounds” refers to a set of competitive states which I included in my election prediction contest. View the spreadsheet here.

3. The markets were right for the wrong reasons

Guess what! I think the market’s price for Joe’s odds of winning was closer to reality than what the models had. Fair value? Joe was worth 60-65c, well less than the 95+ that I had him at going into the election. The tipping point state margin was 0.6 points – and at the end of the day that’s just a close election. Certainly not a 90/10 election or a 95/5 election.

Do I think the market arrived at that price by carefully integrating information available to it? No. It got lucky that the combination of “smart” money and stupid money ended up putting things about where they should be. And if you’re of the mind that this proves markets work, please do go and look at prices right now. Yesterday (a week after the election! with most of the votes counted!) people were paying 10c that Trump would win the popular vote, when none of the lawsuits he’s filed makes that remotely possible. You can literally get paid for predicting what has already happened.

It’s also worth asking what the market’s price would have been if polls had zero polling error whatsoever. I think any universe where Trump is polling within a point in the tipping point states, +3 in Florida, etc, is a universe where the market prices him a 65c-70c favorite to win re-election. In other words, the market’s belief was that the polls *always* are wrong by some fixed amount, not that the market knew what the exact margins in each state would be (indeed, pricing in various states suggests the markets were not aware of the true odds).

4. Don’t rely on PredictIt

Those that follow this blog or me on twitter know that PI has a long history of crashing when many traders are trying to trade at the same time. I expected it. I just didn’t think it would crash so soon (nor last so long!) – and as a result I ate a lot of losses that I shouldn’t have had I been able to cancel orders when Miami-Dade nuked everything. My fault, really, and of course I was able to trade my way out of the hole relatively easily.

But the experience has led me to another (blindingly obvious) conclusion, maybe only relevant to people like me that are trading semi-professionally: I really need to learn how to use offshore sportsbooks and crypto exchanges. I would have absolutely crushed 10c Biden-in-Michigan lines had I been able to. There’s no excuse for this, and I think it only makes sense that to be a true professional at political betting (there are very few people that can claim to be) you simply have to know how and where to get your money down.

5. Which electoral shifts persist and which reverse in the coming cycles?

There are a lot of very interesting questions left over from this election, none of which I have any great answers to:

Is the lurch right among Hispanics reversible? Is it Trump-related? An artifact of the COVID economy? Concentrated among men but not latinas? Bigger in rural areas than urban? Are Hispanics becoming white, the same way that whiteness swallowed up immigrant ethnic enclaves in the past? How big a factor was disinformation?

What about white non-college voters, particularly in the north? If they are now culturally polarized, how much more margin can they give up? What about their turnout – can any Republican nominee other than Trump get that level of turnout in this group?

Will white suburban college-educated voters keep shifting left? Or does their higher rate of ticket-splitting suggest that they’ll be comfortable coming home to the Republican party – with a not-too-crazy nominee?

Will future Republicans continue to make up ground with Black men? Or was this, again, a function of Trump?

A lot to chew on and think about as we approach the next round of special elections, midterms, and 2024. See you all then.

The Final Stretch

Hello, it’s October 17 which means there are 17 days until voting ends and Joe Biden very likely wins the election.

The weeks ahead

But enough for now about who is going to win (it’s Biden). Let’s talk about the next two weeks and election day. How are prices going to move between now and Biden 99c? When looking at the returns in Florida on election day, how quickly will you be able to determine that Biden wins by 6 or just 2?

Substantial price movement unlikely until Thursday’s final debate

For all the drama we’ve had since the first debate (remember when Trump might have literally died from COVID?), the overall picture has remained stable, with Biden consolidating gains from Trump’s poor first debate.

More striking than Joe’s consistent (and wide!) national lead is that it comes as fewer voters are undecided or opting for third parties relative to last cycle:

The models, as a result, have Biden at 90%. The markets, by contrast, plod ahead obliviously:

Why? Stupidity. An un-ending stream of MAGA lemmings chasing the high of the 2016 comeback, unaware of or unwilling to comprehend the change in dynamics in this cycle, and lumbering excitedly toward the cliff’s edge as a result. (Volume in the USPREZ market spiked on the first debate on PredictIt from 200k a day to 400k a day and has stayed high until yesterday when the trader limit was reached – now they’re having to venture out to other markets).

And why should this abate? There’s enough stuff floating around (“FiveThirtyEight had Clinton at 87% at this time in 2016 too”, “Hunter’s emails!”,”Biden will get the virus!”,”TargetSmart says Trump is winning the MI early vote!”) to keep MAGA hope alive. The only major scheduled event left is the second and final debate. I expect Trump’s price to remain absurd (and perhaps increase) in anticipation of a “good” debate performance or perhaps simply a “not disastrous” one. Should he deliver, the market reaction could take him near 50c. Should he lose (more likely), I expect rationality will finally start to overtop the levees and Biden’s price will head towards the mid-70s and keep rising until election day.

Election day

The scene: It’s Tuesday, November 3rd. Possibly more than 100 million votes (at minimum 60% of the final nationwide turnout) will have been cast already, and Biden will be leading among these substantially. Knowing the partisan make-up and with some educated guesswork on past vote history and county demographics, we’ll be able to model his lead in many states (see Dave Trotter’s work in FL for one simple such model).

The only thing left is the Final MAGA Hope: big Trump election day turnout. And he’s probably going to get it! I am expecting that if there’s one last dead cat bounce left in Trump’s price, it will be from folks excitedly citing anecdata from Trump county election day turnout.

Morning to 5pm: FL Turnout Watch

This will be particularly true in the one state that matters most of all for early election night: Florida. Unlike many states, Florida provides every-10-minutes updates to its turnout on a county-by-county basis (with a couple exceptions). This is a treasure trove of data (quite useful if you’re playing the ballot market there) for election day.

By the time the 5pm exits roll around, we’ll have a great idea of exactly what turnout in FL is looking like, whether Trump counties are coming in big or just so-so, and (most importantly) what kind of range of margins Trump needs to hit in those counties (among election-day voters) in order to win.

5pm Exits

We won’t know the toplines (well, maybe someone will know someone who knows, but I won’t). But which of the questions they choose to cover in the news and their general tenor (surprised or not surprised?) will be semi-useful tea leaves. After all the whole point of the early exits is to shape news coverage and prime the audience for what’s to come. If they’re talking a lot about how the top priority identified by voters was COVID and so on, it’s good for Biden.

6pm eastern KY and IN

We’ll already have results in Dixville Notch (Biden will win Dixville Notch) from way earlier, but this is when the first real results start to arrive. I’m curious if exits will be released at 6pm (if there are exits in these states) or whether the networks wait until 7pm (parts of both states are in the central time zone). Nonetheless, we’ll get a trickle of results from 6 to 7 from the eastern portions of both, some of which may be interesting. (Note that KY has much more VBM this year and thus initial results may be more D-biased than you’re used to seeing from KY.) I would warn against extrapolating too wildly from anything in appalachia, but if you see some Jefferson/Fayette/Kenton/Boone/Campbell in KY before 7pm they’re probably worth raising an eyebrow at.

7pm KY/IN/VT called, FL/GA/SC/VA close

The action begins. If PredictIt is still operational, we’re in business. KY, IN, and VT are all called. If there’s any hesitation on calling IN, Trump is in big shit and it’s time to eject on your MO/KS Dem NO bets if you want to be cautious. I don’t expect calls in SC or VA, though anything immediate in either is good for Trump (SC) or Biden (VA).

There will however be exits in at least FL/GA* and presumably some of the others, so expect some initial reaction in the markets to those (particularly in the margin markets since that’s where the sharps will have more of their powder kept dry). The exits will be off, of course, but any big signal in them (like if they have Joe winning GA by 4 points or something) will cause tremors everywhere.

*one edit here: we actually might not have FL exits because of the panhandle; those presumably wait until they don’t matter at 8pm.

7-7:15pm initial FL results

The first few counties in FL will report their early vote + VBM, and I expect Trump to be leading off the bat (likely the first few counties will be smaller Trump counties). I don’t expect a tremendous market reaction though it is possible. These are nonetheless important results: probably at least half the votes in these counties (likely higher and perhaps substantially higher) and we should have a good idea of what the vote split there should be based on partisanship and past vote history of those counties. If the numbers are outside my expectations, I’ll certainly be adjusting my positions accordingly.

7:15-7:30pm first big blue FL counties

This is when we start seeing how truly big the early numbers are from places like Hillsborough/Duval/Palm Beach/Dade. Some might not make it in by 7:30 (many may not come until 7:45), but this is about when Biden should take the lead overall in FL. The market may start to call it. (I have no idea where we’ll be in GA by the way, I presume just rurals based on my past GA election experience of waiting until like 9pm to see anything substantial out of Fulton/DeKalb/Cobb/Gwinnett).

7:30-8pm FL/GA and more

OH/NC close (exits to follow) and WV called for Trump.

We’ll have plenty from all over at this point, including most of FL’s early vote (with the always-important exception of the panhandle). Biden could easily be up by 10-15 points or more in FL at this stage which will be a really big gulp for MAGA money. We’ll also have just started to see the first few election-day precincts start to come in, which I’ll be closely watching and which may be definitive (Sumter, for instance, reported 95% of its vote in 2018 in one fell swoop at 7:45pm, at least as recorded by the NYT). GA should also be in full swing, and KY by this point could be nearly half reported with some counties nearing completion which means shifts in counties there will start to become meaningful analytically.

In 2016, Clinton hit 95c shortly after 8pm on her lead in FL and lead in early OH votes. The markets will of course remember that (to some extent) and that over-exuberance occurred in an environment in which she was expected to win (sentiment is more mixed now), but I still struggle to see the markets containing themselves when they’re staring at blue in three and possibly four key swing states (FL, OH, NC, GA). Whether I’m selling this peak, holding through it, or buying the dip back the other way depends on the numbers and whether it seems like PredictIt is about to crash or not.

8pm onwards

I’ll leave the rest of the night and the days and weeks to come as an exercise for the reader.

What if I’m just wrong and Trump wins

I really hope there are some readers of this blog that are rooting for Trump with the giddy anticipation of not just seeing their guy win, but also seeing know-it-all betting types like myself get served another stinging dose of comeuppance. What would it take? A fairly big polling miss (or for The Tightening to finally show up and stick). Huge election-day turnout. Softer than expected early vote margins. Maybe Joe gets the virus in the next couple weeks (anything can happen). It’s conceivable but it’s just not all that likely folks.

Good luck out there, and I hope to see you all enter my final contest when it launches in a week 🙂

To bounce or not to bounce

Whether ’tis nobler to hold and suffer
the ups and downs of September’s surprises,
or dump one’s shares to try again later,
and while awaiting miss out? To buy? To sell?

…that is the question facing Biden longs as we near the conclusion of the RNC and the beginning of the Fall campaign season. (My apologies to the Bard).

First things first

Enter my contest, nerds. It’s free, there’s a $500 prize pool for this one (bigger than last time! prizes for second and third now!) and you can always copy your favorite sharp’s notes by looking at the predictions from the August 1 contest. As of this writing, only about 16 people have entered so far (entries close September 1 at 11:59pm Eastern), so your odds are good! Of course, perhaps many of you are waiting to see what that first round of post-RNC polling shows and whether we finally see The Tightening.

So is this race going to move?

One of the hallmarks of the 2020 cycle so far is that the polling margin between Biden and Trump doesn’t move that much. Of course it does drift! And has drifted towards Joe, especially in the wake of George Floyd and the south/southwest coronavirus wave. But there are no swings like the 2016 roller coaster:

Part of the reason it hasn’t moved? More people have made up their minds; fewer are undecided or considering third parties:

(y-axis is two-party share of the polling average)

Of recent cycles, 2004 and 2012 stand out for relatively similar patterns. Both high in two-party share early on. Both with relatively little turmoil in summer polling. Both occurred in the more polarized modern era, and both featured incumbent presidents on whom the election (at least in part) was a referendum.

And both cycles, as you can see above, featured late August / early September conventions that produced a sizeable polling bump for the incumbent. (Later, this bump eroded after Obama and Bush both lost their first debates, yet of course both would win in the end! One notable difference is that both had higher approvals than Trump going into the campaign season, which might explain why the races hovered around a margin of zero rather than the margin Joe has).

So here we are in August 2020, similar polling dynamics, similar incumbent convention timing, and therefore a similar bounce incoming?

Well, I don’t know. (Sorry). But I do feel like the race moving five points towards Trump in September is far more likely than it moving five points further away from him. It’s just that both tails of the outcome distribution seem far less likely than it moving say just one to three points towards Trump.

To bounce

Why might we see a small shift towards Trump? Well there’s the convention, though I honestly don’t see it doing *too* much in that regard, though partisan nonresponse might kick in for some of the live caller polls. There’s also just the time of year (perhaps the “tuning it out til now” crowd are Trumpier to begin with). Maybe coronavirus is fading and there’s a segment of the undecided electorate that have goldfish memories and/or have never really been that bothered by the deaths and have been more upset at way-of-life changes. Maybe there’s a big chunk of undecideds who really don’t care about BLM except superficially and hate protesters and unrest in general more (especially with sports gone). Maybe Joe gaffes, or maybe the media starts harping on him for getting out-hustled on the campaign trail by Trump (which does seem likely, for safety reasons if anything) in the absence of anything else to complain about.

Not to bounce

And why might the race hold steady? Because an object at rest tends to stay at rest. Because if Biden didn’t get much of a bump (except in his favorability, slightly), why would Trump, especially with a less-watched convention? Because unrest rooted in racial injustice might serve to reinforce the suburban disgust with Trump (you would be amazed, driving around lily white wealthy Boston exurbs how many have BLM yard signs – yes this is a yard sign pump). Because, yes, the low turnout non-college-educated white men do exist but if they’re not already showing up in the polls as likely to vote that isn’t going to change in September (late October, though?). Because the race is, has been, and always will be about Trump and Trump (have you noticed?) is rather unpopular.

Betting on it

So what’s the play? Well I’ve decided I actually I favor a small Trump bounce over no Trump bounce.

I’m going into September owning Trump in the bigger markets though I still hold Biden in many others (some underwater) and I still think Biden is a strong favorite to win in the end. But my playstyle is too impatient to do nothing between now and election day and if I think there’s value in a Trump shift I’m going to try collecting it. I am expecting the margin to be Biden +7 within two weeks or something, and I’ll boldly say that I would not be surprised if Trump surpassed 50c at some point in September.

And if I’m wrong? Then I’ll sell and go the other way of course 🙂

Which Model is the Fairest of Them All?

The tl;dr:

-Models output predictions for each state

-Models also forecast median margins of victory; it is better to use these to compare one model to another

-When looking at national forecasts, the relationship between popular vote MoV and win probability is distorted by the electoral college

Probabilistic forecasts only get to live in one reality

Yesterday, pollster Patrick Ruffini posted a facially reasonable take on the state of election forecasting:

This is a subtweet of the epic Nate Silver – G. Elliott Morris debates on model uncertainty (they were going at it hard last night); Morris’ model has Biden at 90%, Silver’s model isn’t out yet but is expected to be much lower, perhaps near 70%. Ruffini is effectively saying “Chill guys. If Joe wins we’ll never know which of your models was the best because reality only gets to play out once.”

So is there no way to differentiate the skill of a 90% forecast from a 70% forecast?

It’s absolutely true that election modelers are predicting a singular event. The forecast is made, the election happens, and that’s that. We don’t have the luxury of peering into multiple parallel universes to see what happens in 100 of them to see whether Biden really did win 90% of the time or if it was only 70% of the time.

Yet hope is not lost. Whatever future timeline we end up in, we should nonetheless be able to say something about which forecast was better. If a forecast implies Biden is extremely likely to win and he only barely wins, that forecast was worse than the one that said it would be close. Consider 2016: several models had Clinton at 98% or better, Nate Silver’s had her only in the high 60s and low 70s. Suppose that instead of Trump, Clinton had barely held on in MI/WI/PA and won. Were the 98% forecasts better? They’d have a better Brier score! But no, they would have still sucked. Why?

There’s a relationship between win probability and margin of victory

This is intuitively obvious but worth exploring. Let’s take a Georgia. If Georgia is a true toss-up, then we shouldn’t be expecting either Joe or Trump to win by 5 points. Maybe sometimes that happens, but more often than not the margin of victory is under 1.5 points either way. Maybe Trump is slightly favored there (not sure I agree, but let’s say he is), but there’s enough uncertainty we can’t say for sure that he’ll win. Maybe he’s worth 60c. Here’s a quick and dirty MSPaint diagram of what’s going on with margin of victory in a 60/40 race, as an example:

We have some sort of median forecast margin of victory (Republican by 1.5 points), but we’re uncertain! Polls have margin of error, so do polling averages, and so does our forecast. The most likely outcome is R+1.5 but it’s not the only outcome. The full probability distribution is shown with the example bell curve above (note that I have no idea how accurate this distribution is). We get the win probability from how much of this probability distribution lies on the R side of the spectrum and how much lies on the D side. Here, at -1.5 points, about 60% of the area under the curve belongs to the R candidate while 40% belongs to the D candidate.

Models are in the business of generating these probability distributions and as a result they all tend to output both win probabilities and margins of victory (others go further and suggest turnout numbers, vote shares, and so on), which allows us to compare the two measures systematically:

In this plot, each point is a particular state forecast (these span all states included in my 8/1 Contest). On the x-axis is the forecast margin of victory (from losing by 30 points to winning by 30 points) while the y-axis shows the win probability. There are two data types shown here: modelers are shown in dark orange, and individual contest entrants (humans) are shown as grey points.

Let’s take just the modelers for a moment. You can see that if they think the margin of victory is near zero, they think that the race is a toss-up (near 50% win probability). And once the margin gets out to +4.5 points or so, the race is already 75%. Note that I’m including all modelers here in dark orange and yet there’s comparatively little spread overall (perhaps at a later date I’ll break them down individually to see what if any differences there are). And while 538’s model isn’t included here (it hasn’t been released yet), the overall curve very closely tracks what their 2018 midterm model showed:

The X-axis range is wider here; but the overall curve is very close to what’s shown above.

Margins > win probabilities for scoring an election forecast

Since it so happens that all modelers agree on the general relationship between win probability and margin of victory (more specifically: so far no modeler has a substantially steeper or flatter curve than any other), it’s fairly straightforward to simply compare them on median forecast margin. Whoever gets closest did the best! (And this is why margins are the dominant scoring factor for my contest). This is wonderfully intuitive: if your forecast is calling for a close race, then the race ought to be close. If it’s a blowout, your forecast probably sucked.

What about national forecasts?

How does margin relate to the overall chances to win the presidency? Thanks to the electoral college, this is not as straightforward. Voters of different parties are not evenly distributed in all the states and as 2016 illustrated one party can thus lose the popular vote while winning the electoral college. A 1.5 point loss in the popular vote for Trump is probably an 80% win chance for him.

Further, this electoral college edge moves from election to election (as individual states drift one way or the other). We can’t know that Joe by 2.1 is the 50/50 line like it was in 2016: the line may well have drifted up to Joe by 3 (as suggested below). Dave Wasserman has argued in the past that it’s even conceivable that Trump can win some elections where he loses the popular vote by 4-5 points.

Where are we now? Based on all contest entrants and modelers, the 50/50 line is somewhere around 3.1 points (where the linear fit to the data below crosses the y-axis; despite this curve being almost entirely generated by human contest entrants, G. Elliott Morris’ model has 3.2 as the 50/50 line):

Translating this into win probabilities across the whole range is a bit trickier – I’d love to see a modeler put out a simple chart of pop vote margin vs win probability (perhaps Nate Silver will give us these data). But roughly speaking: +3 points is probably around 50/50, +4-5 is 60-70, +6-7 is 75-85%, +8-9 is high 80s low 90s, and +10 and up gets to be academic.

To sum up

Yes, we’ll be able to tell 70% and 90% forecasts apart. A 90% national forecast is going to have a much closer TX/GA/IA/OH margins than a 70% national forecast. A 90% national forecast implies a much higher popular vote margin than a 70% forecast, and so on. So fear not, we will know whether Nate Silver’s model is the champion this year or whether The Economist’s can dethrone it (or if any other modeler beats them both). And if you’d like your shot at beating them all, start thinking about your entry into my next contest (entries will open August 25th and close September 1)!

The Predictions Are In

For the first round of my 2020 Prediction Contest, we had an amazing 98-entry turnout (93 of whom revealed themselves publicly and are prize-eligible). Thank you to all who entered, and best of luck! You can view everyone’s entries here (some typo correction was required to fix where people left off a minus sign or other mistake here and there; raw entries are here).

Contest Entrants Think Trump is Going to Lose

Of the 98 entries, only six said that the Democratic candidate was under 50c to win the presidency. In fact, the median predicted probability for the Democratic candidate (hereafter Biden, for brevity) among contest entrants was 87%; notably, the median probability given by the models out there is also 87% (though Nate Silver has yet to release his and based on his fights with G. Elliott Morris it’s probably not going to come in very high).

This confidence in Biden (he is “Likely” to win the presidency, in the parlance of verbal handicappers) isn’t shared by the markets. Both BetFair and PredictIt price Joe in the low 60s, suggesting that the presidency “Leans” Biden (the price ranges on PI depending on the market you’re looking at). Even Silver thinks that’s too low: “I don’t think people realize how dumb and sometimes even irrational the prices are at political betting markets as compared to almost every other type of market (which is not to say other markets are always rational, either).” and “Too low on Biden.”

He’s right! And he’s right to note in that thread that often the highest-profile markets are the most mispriced. Let’s talk about it.

The Markets Are Wrong in Two Ways

  1. Joe Biden is underpriced (by at least 10-15c).
  2. The markets are inconsistent, often wildly.

And it’s this second error that’s the most interesting to me. We know, for instance, that one of the reasons Trump trades higher in the main USPREZ market is that that’s the first place casuals go to plunk their money down on their man (and there are more Trump bettors than there are Joe bettors).

Yet the markets also have Biden comfortably ahead in MI (75), WI (70), and PA (73) which Trump needs to win to have any chance. These numbers are all still underpriced according to the models we have, but they nonetheless imply a higher win probability for Joe than do the main markets. Other markets have even more striking discrepancies: the electoral college market has Biden winning the EC 75% of the time! The popular vote market has Biden getting more than 4.5% (enough to win 95% of the time) at 71c!

In the latter two cases, some of that is internal overpricing (the markets add up to way over 100c) caused by long-shot bias, dart-throwing, and market making overwhelming the neg-riskers. Still, it’s notable that people are willing to pay something like 9c that Biden wins Alabama (lol) while others are willing to pay 7c that Trump wins California (looool). Even aside from the long-shot biased states, Biden is worth well over 60c overall based on his price in MI/WI/PA/FL/NC/AZ. So what happens next?

Something to watch over the coming weeks, particularly with the back-to-back conventions, is whether Biden’s overall win odds increase or whether the state markets simply get Trumpier. My intuition is the latter (already, the price in places like FL/IA/GA has moved about 4c to Trump this week despite moving only 1-2 points his way in the models) as dumb money begins venturing out from the main attraction. Anyone who saw 85c Clinton in California in 2016 knows that things can always get stupider…

Contest Entrants Were More Comfortable with the Main States

When you look at the range of predictions for MoVs for a given state, a tighter range indicates that most of the entrants have a good idea what a particular state will be. Georgia, for example, has a reasonably tight spread. People know that Georgia is going to be close.

Georgia’s MoV with modelers (orange), handicappers (yellow), current polling averages (blue), PredictIt (teal), and contest entrants (black: mean/median; white: individual entries).

Sure you have one person firing a +10 for Joe in GA (@StockJabber, who made Blue Tsunami picks), but by and large everyone knows that GA is going to be within 5 points of a dead heat either way. Contrast that with ME-02:

ME-02’s MoV with modelers (orange), handicappers (yellow), current polling averages (blue), PredictIt (teal), and contest entrants (black: mean/median; white: individual entries).

Most of the points are clustered again from -5 to 5; yet there are quite a few that now extend further out. Overall, the district is still priced as a toss-up by contest entrants (as do the modelers, the markets, and the handicappers), but the spread suggests, to me, that a lot of entrants were simply guessing. ME-02 isn’t talked about as much as places like GA or TX or FL, it’s not something everyone knows the 2016 margin in off the top of their heads.

You can also see this if you compare forecasted national MoV and a given state’s MoV. In better known places, there’s a clear tight linear relationship between what someone said the national MoV would be and what they said the state MoV is. In the lesser known states, things are noisier.

What do I take away from this? Well, if the contest entrants (who are sharper in aggregate than the markets overall based on their pricing) are this uncorrelated for places like ME-02 and MT, then that’s where I’d expect to see softer pricing and nice opportunities in the next few months (and perhaps and especially on election night as well). Something to keep in mind…

More TK

There’s a lot more to say about the contest (including the winprob-MoV curves and how I’m imputing winprobs from verbal handicappers and so on) but this blog is already long enough so I’ll save some for later. In the meantime, check out this thread, and hope to see you all in the second contest in one month!

2020 Election Prediction Contest

Please come win my money!

No purchase necessary! Fill out the form above with your predictions on the presidential election in 2020 and whoever has the best predictions will win $125 from me 🙂

***UPDATE: Due to a generous contribution from anoland, the prize is now $250 per contest at minimum! (He did not receive any special insight into anything for his contribution and remains prize-eligible; I’m the only one who can see entries while they’re being submitted and am thus prize-ineligible)***

First contest: Entries dues 11:59:59 pm eastern time, August 1.

What is this?

This is a public contest to see who can best predict the outcome of the 2020 presidential election overall and in 23 key states. To participate, you must provide a win probability and margin of victory/defeat for the Democratic candidate in each of 23 states plus overall national win probability and electoral college/popular vote margins of victory.

Whoever makes the best predictions wins my $125 (or, if I win, whoever the runner-up is gets my $125).

Wait, why are you doing this?

For 2018, I maintained a spreadsheet that showed a simple comparison between predictions for various modeling organizations, betting markets, and expert handicappers (like Cook Political). I want to do something similar this year, but this time also incorporate individual predictions from all you sharps that follow me and read this blog, plus anyone else in election twitter that happens upon this contest. And I figure in order to get people to do it, I ought to offer a prize! In addition,


Yep, for bragging rights you’ll get to see your entry next to all the modelers and everyone else’s that participates (all predictions will be revealed after entries close). If you’d like to be eligible for the prize, you’ll need to give me your twitter @handle, otherwise your entry will be anonymous. Once the final results are in (I will be waiting until the official FEC report comes out in early 2021 to resolve and pay out the contest), you’ll get to find out if you beat the markets, the handicappers, the average of your peers, or everyone!

When are entries due?

There will be four contests, this post is appearing ahead of the first. Entries for the first contest are due by 11:59:59 pm Eastern time, August 1. Subsequent contests will launch at later times and will be due on September 1, October 1, and November 1. Each contest is separate, so you can enter all four and theoretically win $125 from each. (And by running multiple time points, I’ll hopefully get some fun data for how all of you are or aren’t changing your predictions over time).

How do you determine who wins?

The best predictor wins. In this case, that means the entrant who earns the most points wins. How do you earn points? Because entrants will be making two kinds of predictions (win probability [winprob] and margin of victory [MoV]), each will be scored separately, then combined at the end with four times the weight given to MoV points. (Click here for the scoring rules with an example). Here are the formulae:

  • Winprob predictions: if Dem candidate wins, points = predicted probability; if Dem candidate loses, points = -predicted probability.
    • EXAMPLE: You predict the Dem candidate at 85% to win the presidency and 40% to win Texas. The Dem does win the presidency, but loses Texas. You are awarded 85 points for the first prediction and lose 40 points for the second prediction.
    • Your goal therefore is to maximize winnings and minimize losses, and if you want you can try assigning 99s and 1s to everything where you think the Dem wins or loses – but if you’re wrong you’ll be wrong bad. In theory simply offering an honest probability is the best strategy.
    • All winprop prediction points are summed, giving you the Winprob Subtotal.
  • MoV predictions: points = 10 * (5 – a*(abs(actual-prediction))
    • a = an adjustment factor. For all % point MoVs (all but one of them), a = 1. For the Electoral College MoV, a = 0.18 (this is roughly 100/538 in order to normalize things).
    • abs() is the absolute value function.
    • The formula says that you get more points the closer you are to the actual margin of victory, with a maximum score per prediction of 50 points [10*(5-0)]
    • It also says that if you’re more than five points off the actual margin of victory (or 28 electoral votes for the EC MoV) you will lose points for that prediction (the further you’re off, the more points you’ll lose).
    • All MoV prediction points are summed, giving you the MoV Subtotal
  • Final points = 4*MoV Subtotal + Winprob Subtotal
    • Yes, the overall score is weighted more heavily to MoV predictions. This is deliberate to avoid people trying to win the contest by spamming 99s and 1s for winprob predictions and hoping to get lucky.
    • Whoever has the most points wins.


To be eligible for the prize, you must submit all predictions as well as your twitter @handle via this form (same as above). One entry per contest per entrant. Your twitter account will need to have been created prior to July 1, 2020. If I receive multiple entries from the same entrant, I will reach out to that entrant to find out which entry is theirs; otherwise the first entry made by an entrant will be the one that counts. If you find an entry on the list in your name and did not make an entry, please contact me and I will remove your name from that entry.

There is no fee for entry and you can enter anonymously (your prediction will still appear, but with no name attached). Anonymous entries will not be prize-eligible.

State of the General Election: June 2020

Where things are

Joe Biden holds a commanding lead. It’s not inconceivable that it will fade nor is it impossible that Trump can win. But if the election were held tomorrow Joe Biden would win in an utter rout with Trump defeats in IA, TX, and GA quite plausible if not probable. Joe winning with 400 electoral votes would be a real possibility. Hell, there was a (completely trash) poll out of Arkansas today with Joe trailing Trump by only two points with a 45% share of the electorate (the AR market hit 13c for Dems at one point today, lol).

RCP has Joe up by over 8 points, and with an impressive 49.8% of the national electorate (Clinton was up by 5-6 at this point in 2016 with a 44% share – she would peak post-primary in RCP at 7.9% and 47% share in mid-August; her highest share would be 49% shortly after Access Hollywood). While we wait for Nate Silver to release 538’s official average (soon, apparently), I’ve constructed a simple polling average of all unique polls from the past two weeks from their expertly-maintained database: Joe is up by 8.4 with a 49.4% share while Trump’s share which was in the 43s pre-corona is now mired in the 40s and 41s and sliding further recently.

Trump’s share of the electorate slipped during the peak of corona, it has further eroded during protests. Biden’s share has waxed and waned and is currently dangerously close to exceeding the 50% line.

Where things are going – short term

Despite Joe’s commanding lead and most modelers having him 70-80% to win in November (I price Joe at 71c), the big markets are reluctant to go that far. We’ve drifted from 50/50 to 57/43 before running into some more Trump demand or reluctance to push further. There are a couple reasons for this: there is a widespread perception that “the polls” were wrong in 2016 (they were, on the whole, very good with the notable exception of those that didn’t weight be education in the upper midwest); and there’s the sense that the recent slate of big Joe polls are only so big because of the events they’ve coincided with. Once nationwide protests fade, or the virus does, or the news cycle changes as it has in the past, so too should Joe’s lead shrink. So why buy in now if he might be cheaper later?

I don’t entirely disagree with this line of thinking; in general you make more money walking with the herd of brain-dead zombies than fighting them and sitting on underwater shares for months. But there are big problems here nonetheless worth mentioning:

(1) Joe is worth more than 58c right now even if he were leading by “only” 6 points – he’s probably not worth less until his lead falls below 4 points;

(2) There won’t be that many polls in the back half of June because so many pollsters went hard in early June and early July will also likely be dry with the holiday so people hoping for a quick Trump flip might be waiting for a bit;

(3) If we’re coming into August and convention season with Joe +6.5, he will likely be in the 60s even after factoring in MAGA zombie stupidity;

(4) There are other places where you might want to make this short term play like IA, OH, and TX where the bettors are much more aggressive for Biden than they are in the overall market – after all, Joe is probably losing these states if he’s +5-6 nationally and even the diehards know it.

Even with mean reversion in the polls, Trump faces an uphill struggle

His success in 2016 was rooted in many things ranging from the late October Comey revelations to macro trends in manufacturing to an ability to exploit racism to Hillary Clinton being an utterly reviled figure on the right (and not particularly loved by the left). So while it certainly came as a shock that he did win, it’s worth noting that he only eked it out.

What factors could play to his advantage now?

“Trump has barely gone negative on Joe, the polls will move as his campaign spends money nuking Joe over China.” Joe is not Hillary, nor will any attempt to “define” him make him Hillary. Trump will try, but will not succeed to the degree he did in 2016.

“Maybe the economy will rebound sharply, and voters will be sensitive to the first derivative.” Or maybe it won’t? Or maybe they won’t? Or maybe this whole line of reasoning is desperately speculative what-iffery until we actually see how the polls move?

“Polling error still exists; many polls are still not weighting by education and its probable the national popular vote – electoral college gap has grown. Trump need only be within 3-4 points to be win. He could even win down 5.” This is somewhat true. He certainly is at least 50/50 for any election where he’s only down two points, for instance. But he has to get to that point, which means he’s gotta start polling around 45-47% share and he’s not shown the ability to stay at that range yet. It’s also worth pointing out here that Clinton’s pop vote advantage owed in significant part to the distribution of hispanic voters in CA/TX/etc and that Joe is not doing as well as she did with these voters, despite being up 8 nationally.

“White people voted for Trump at least in part because of a fear of replacement by brown and Black communities and a perceived loss of status associated therewith. This hasn’t changed.” Yes. I agree that this is probably Trump’s best and only play down the stretch. It’ll be back to “caravans” and “thugs” and “The Snake” and other such simple plays to racism. It’s his most potent weapon and it’s where his mind goes naturally anyway.

The virus isn’t going away either

I wrote in early April:

The United States will fail to develop a testing/tracing program needed to contain the virus by the end of May.  The curve will bend, but new cases will continue throughout the summer.  Because the virus spread so readily and from asymptomatic or minimally symptomatic people, our testing regime will only catch cases that make it to the doctor’s office.  Even if we implemented extremely widespread testing, it won’t stop the virus.

And this isn’t too far off the mark. Our testing is quite a bit better now, but tracing lags far behind in most places. And there is no national strategy past “idk, everyone figure it out for yourself”.

Despite the persistence of the virus, quarantine fatigue has set in, coinciding with reopenings, mass protests, and a cultural reticence among places that were relatively spared initially to adopt practices like mask-wearing. As a result, hospitalizations and cases are rising throughout the South and West (increased deaths will follow in a few weeks). If any of these states start seeing big numbers (>10k cases per day, >250 deaths per day), Trump is due for another poor spell of virus news. (Someone will get the virus at one of his rallies at some point too; the media is absolutely champing at the bit to trample him on this story).

So this is going to be a boring blowout election then?

Yeah, probably. Stuff can and will happen. I’d be mildly surprised if we didn’t have at least one period of panic over Joe trailing Trump in polls or something (I’m penciling in early September, immediately post-RNC, for one likely time point. There will probably be a bit of hand-wringing before the first debate as well). Joe could get the virus (he’s not having people he meets with tested), in which case there will be utter pandemonium in the markets. So could Trump, if someone’s cough at one of his indoor rallies finds the perfect air circulation pattern. Maybe someone will figure out why Trump was spirited away to Walter Reed last fall, or maybe Joe will suffer a health scare like Hillary’s pneumonia. Given major shifts to vote-by-mail in the fall and the virus, perhaps the entire election itself will become a legal clusterfuck.

But given what we know about the race right now, our strong Bayesian prior has to be that despite the coming ups and downs, Joe is a favorite to beat Trump, and that a Joe blowout is just as if not more likely than a Trump win.

Preparing for the General Election

Somewhere out there amidst the slow-motion quasipocalypse around us exists the beginnings of a general election campaign between (as yet presumptive) Democratic nominee Joe Biden and the “I’m not a doctor” incumbent President Trump.  What’s going to happen?  Who knows!  But as I’ve said before (most recently on a panel at a political prediction conference that Flip Pidot put together), I tend to trade these things by reacting to the present and making plans for how possible future events could influence market prices.  For example, in the short term, I’m wondering if the next set of Trump v Biden polls will continue to push Joe higher in the various state markets (and the winner market).

But for now let’s set all the intervening drama between now and November 3 aside and skip ahead to the fun part: election night.

The Motivation

I kind of suck at elections.  There, I said it.  Not to say that I lose money on them, just that I frequently don’t make as much as I should, and it’s easily the softest part of my game.  I have a good overall sense of political geography, but not the fine-grained understanding where I know basically what every county in a given state is doing.  And on election nights, it REALLY helps to know that stuff.  If you’re playing a turnout or margin of victory market (or even a winner market when it’s close), you’ve got to be able to estimate quickly and reliably how much vote is remaining and how that vote might fall.  This requires work, and often for big multi-contest elections I never do enough of it and end up just sort of clicking buttons.  This post is hopefully the first in a short series detailing what steps I’m taking to shore up my play in this arena.

The Goal

Wouldn’t it be great to be able to read the results coming in from 7:30 – 8:30 on election night and be able to predict how states that report later will break?  Is it possible to take extremely early results from, say, random counties in Kentucky/Vermont/West Virginia/Indiana that report first and extrapolate something useful from them?  Basically, can I build a better, faster, and more profitable version of The Needle?

The Hypothesis

There’s a lot that goes into live-forecasting an election.  For one, you need to be able to treat absentee/early vote different from election day vote.  You also need to know how homogeneous the precincts are in each county.  You need a sound method for modeling uncertainty around your prediction.  You need to have scrapers working for all the various results providers (NYT/AP, DDHQ, and CNN/Edison) and a way to select the freshest results among them.  But after all that, a basic level you need some way to model how one county’s reported results influence what another county might report.  Is this possible?  In order for it work, my hypothesis is that counties that are similar to each other demographically, by size, and in terms of past electoral history ought to continue behave like each other in elections going forward.

Exploring the data

So far, I’ve not systematically approached this idea – my goal in the early going is to build a rough spreadsheet that I can use to check my ideas before more rigorously testing them.  (And if it doesn’t work at all, at least I learn some more political geography on the way).  What I’ve done is to gather data on each county in the country (demographic and political), then simply do some linear regression on a bunch of variables to see if I can’t find, for any given county, the most similar counties to it in the nation.  This is what that looks like:

Juneau County Wisconsin part one.png

Juneau County Wisconsin part two.png

The top row of the spreadsheet shows where I’ve typed in a target county: Juneau County, Wisconsin.  The rest of the spreadsheet then does some vlookup() magic to pull out all the counties that are closest to Juneau County across several dimensions.  Here, these are shifts in margin and turnout from 2012-2008, 2008-2004, 2004-2000; total dem share and total turnout in 2012, 2008, 2003, and 2000 (I use log(turnout)); and racial demographics (fraction white/black/native american/asian/other/latino).  In this example, I am NOT using any information about 2016 – yet you can see that the average of the ten closest counties to Juneau County end up doing a pretty good job predicting the swing in Juneau from 2012 to 2016.  (Note I’m also not doing any weighting on physical distance of counties, yet this emerges naturally from the data – so far turning off distance as a factor doesn’t seem to make a huge difference but I’ll have to explore it further).

Here are some other sensible groupings it makes:

Hamilton County Ohio.png
Hamilton County, Ohio is home to Cincinnati. The spreadsheet finds Jefferson County, KY as its closest relative (home to Louisville, about 100 miles from Cincinnati) along with a lot of other midwestern/southern cities, interesting as Cinci is sort of half-midwestern and half-southern.


Buffalo County SD.png
Buffalo County, SD, is a Native American majority county, and the spreadsheet correctly pulls out a bunch of other Native American counties as a result (one thing I didn’t know about 2016 was how much worse Hillary did in these counties compared to Obama).

Cobb County Ga.png
Without consideration of 2016, the spreadsheet struggles to find the closest counties to this growing suburban Atlanta county.  Still, not terrible.

Pasco County FL.png
The 2016 shift in Pasco, FL isn’t entirely predicted by the 2016 shift in its nearest neighbors determined by data from 2012 and earlier. (a red county that went hard red in 2016 – I’ll always remember it because Steve Schale tweeted something about how poorly things were going there and it was the first time I realized I was going to lose a lot of money on Hillary Clinton).

Sometimes it doesn’t work

As you can see with Cobb (GA) and Pasco (FL), the most similar counties based on info from 2012 and earlier don’t necessarily shift to the same extent as the target county.  This is particularly true for bigger Obama-Trump counties in the upper midwest (smaller ones, like Juneau (WI) are predicted well as shown above).  Here, for instance, is Macomb County, MI.  First are shown the most similar counties excluding all 2016 information, and next what the most similar counties are with 2016 included.

Macomb County MI 2012.png

Macomb County MI 2016.png
Obviously if you include 2016 numbers you get a much better neighborhood of similar counties.

So what’s next

Well, it’s cool that it sort of kind of works.  But it also fails to pick up on the magnitude of some of the 2012-2016 swing for both Obama-Trump midwestern counties and, to some extent, for suburban counties everywhere.  I can try adding additional weighting schemes, or maybe simply adding midterm data (though if I’m doing national correlations I’d rather not have different inputs in different states).  Perhaps there’s some additional category I can consider weighting on (education comes to mind – maybe I can find some measure of urban/suburban/exurban/rural?).

Finally, finding the closest counties is just a test of the overall approach.  In principle, counties that are quite distant from a given county on any of these metrics could still provide useful input.  We shall see!

Corona Predictions

First, some disclaimers:

I’m definitely not an epidemiologist.  In fact, I’m in that dangerous category where I know just enough about a subject to get me in trouble (if you’d like to read an actual epidemiologist’s take, here’s Lipsitch et al on the topic of what comes next).  I’m also partial to doomerism even in the good times, and the three weeks (years?) of social distancing certainly haven’t ameliorated that tendency.  While I’m in the business of making predictions (literally) that doesn’t necessarily mean that I’m good at it or that the skill in one domain (politics) transfers to others.  But, you know, screw it.  Here are some bleak predictions and let’s hope I’m wrong:

The outbreak in general:

1. The United States will fail to develop a testing/tracing program needed to contain the virus by the end of May.  The curve will bend, but new cases will continue throughout the summer.  Because the virus spread so readily and from asymptomatic or minimally symptomatic people, our testing regime will only catch cases that make it to the doctor’s office.  Even if we implemented extremely widespread testing, it won’t stop the virus. Look at South Korea with their top-line testing program – the outbreak is still trickling along.  Look at Singapore, where the government just announced another lockdown because despite their best-in-the-world contract tracing program they were unable to identify the source of half their new infections.  Look at Hong Kong, with their efficient use of centralized quarantine that will, if ever, only be haphazardly implemented here and would probably raise constitutional issues.  Look at China, where extremely severe measures were needed to contain an outbreak on the scale of New York (that New York is not taking) and where still life has not returned to normal as dozens of cases continue to sporadically emerge (both imported and community spread).  You want to tell me America is going to do better?  Nope.

2. Some cities that are spared in the initial wave in the United States will become hot-spots later.  Rural and small-town communities will see periodic outbreaks that may briefly overwhelm local hospitals (as happened in Albany GA).  Look at the incredibly diffuse spread of the virus in the United States.  It is not going away until half of us have been infected or a vaccine emerges a year from now.

3. By the end of August, there will be estimates based on serological surveys that up to 30 million Americans have been infected.  This is not nearly enough to confer herd immunity and we will still be quite vulnerable to a second wave.

4. There will be a second wave in which peak deaths/day nationwide exceeds 250 or more. It may not be as severe as the first as metro areas institute lockdowns and closures earlier.  Though it’s worth noting the second wave in 1918 hit much harder than the first.

5. In fact, some cities may see multiple waves.

6. The timing of the second wave will depend on the seasonality of the virus and how much restrictions are relaxed and how much better we get at contract tracing, but if it’s anything like 1918, the peak hits literally on election day.  This will cause chaos.

7. Alternatively, it could be barely beginning in late October/November.  Everyone will go to the polls nonetheless, which will accelerate its spread, leading effectively to a nation on lockdown again and a canceled Thanksgiving and Christmas.

8. You will continue to see examples of people violating social distancing norms in various places.  People will begin to turn on each other over this.  Others will get tired of the distancing.  Regardless, our uneven compliance will only be enough to slow the spread but never enough to stop it.  Remember too that many people still need to work and are still using mass transit every day, etc.  The poorest neighborhoods in NYC are the hardest hit so far.  Continued iterations of lockdown and relaxation will persist throughout the year.

9. Sports ain’t happening.  Sorry, sports bettors.  No NBA.  No MLB.  And yes, the NFL is going to see a much shortened season due to the fall wave.  Quite possible there will not be an NFL season at all.

10. People will not want to fly any time soon.  Airlines will require another bailout (and sooner rather than later).  This will be controversial and will collide with the political season.  A major US carrier may go bankrupt.

11. Greenhouse gas emissions will decline.

12. The iterative stop-and-start of social distancing will deepen the severity of the global recession (and prolong it).  Additional stimulus will be required.  At least one more package will be passed.  It too will be inadequate.  Suffering, in the United States, will be far greater than it needs to be as a result.

13. By the end of the pandemic in the second half of 2021, nearly all Americans will know of a friend, co-worker, or family member who was infected, and at least half will know someone who died.


14. In the short term, Trump will continue to agitate between desperately wanting this to be over quickly and sullenly yielding to the medical professionals who tell him that it will not be.  Expect more of “it would have been a lot worse if I weren’t so amazing” mixed with “we can’t let the cure be worse than the disease” + “hydroxychloroquine will be the miracle drug that saves us all”.  Trump of course will not take action to open things up prematurely – he will instead pass that off to the governors (why take responsibility, ever?).

15. By the end of May, preliminary results from randomized control trials of hydroxychloroquine will show no improvement over standard of care on most measures. Nonetheless, a conservative blog will misleadingly write up this study by saying something like “70% of patients taking hydroxychloroquine showed improvement!” (not mentioning the equal success of standard of care alone).  Trump will happily retweet this.  For him, hydroxychloroquine is a win/neutral play.  Either something comes out of it that he can spin into a giant “I told you so and the media was wrong” or nothing comes out of it and he ignores it and Fox News pretends it never happened.

16. Trump will float the idea of having a big Fourth of July parade / party / celebration (of him) again this year.  It won’t end up happening.

17. The CDC will not relax its guidance saying that gatherings of large crowds are to be avoided by the end of August.  The political conventions, if they take place, will lack all energy and will look very different (normal people will not care).

18. If the conventions happen, expect them to prominently feature doctors, nurses, and EMTs.  I actually think the Trump campaign could be very effective here.

19. There will be no rallies, town halls, or normal campaigning.  What’s happening in the primary race right now (and for campaigns across the country) will not stop because the virus will not stop.

20. Trump and Biden will not shake hands at the debates.

21. Trump will be very upset that the virus is depriving him of that which he’s been looking forward to most as president: Running for re-election and speaking before large crowds.  Don’t think this will be to his detriment however.  His narcissism will not let him avoid the spotlight.  He will call into every TV show every day if he has to get his fix.  He will be better at this than Joe.

22. Don’t make the mistake of assuming that Trump will be blamed for the poor economy – he won’t be.  If he takes on water, it will be because people discover how poorly his administration handled the initial outbreak – or future missteps.

23. It’s possible (but not yet probable) that a member of Congress or candidate for Congressional office dies of COVID.

24. Coronavirus will have both an enormous and a small political impact.  It’s all everyone will talk about during the campaign but at the end of the day it will only act to bring into relief all the pre-existing macro political trends.  City-dwellers rich and poor will hate Trump for messing up the initial response.  Suburban voters will find it another example of why they don’t like Trump.  Rural voters will wonder whether it had to be as big of a deal as it was.  White non-college voters who lose their jobs are an interesting group though I suspect they’ll continue trending Trumpward regardless.

25. Coronavirus will definitely, however, make the race more a referendum on Trump than a contrast election (though it was always going to be that way).  In fact, the small impact it does have in moving the electorate (juicing suburban swing?) could be enough that Joe simply wins a landslide.

How all of this is wrong

The bullish case almost certainly involves the emergence of a truly effective treatment that shortens hospitalizations and dramatically reduces the death rate.  Rapid testing could be deployed such that all health care workers and visitors to nursing homes / prisons / hospitals are tested before entry in order to protect the vulnerable even if the virus continues to spread slowly elsewhere.  There are others that have written big plans about re-opening the economy pre-vaccine and so forth that we can look to, and they all rely on the technological or pharmacological dei ex machina that could certainly happen.  But they haven’t happened yet.