Our new pollster ratings are up!

They've been updated to reflect the results of the 2020 general election + the GA runoffs.

Also a shiny new interactive. Fivey Fox makes a cameo appearance.

Here's the link. I'll discuss some key findings in this 🧵.

projects.fivethirtyeight.com/pollster-ratin…
Note that we now have pages for individual pollsters. So you can see exactly which polls made it into the rating for each polling firm. Basically this means every poll within 3 weeks of an election since 1998!

projects.fivethirtyeight.com/pollster-ratin…
Or if you want to go even deeper, you can find the entire database on GitHub. We strongly encourage people to use this database for academic research, etc. A LOT of hours of gone into building and maintaining it.

github.com/fivethirtyeigh…
The next key link is to my feature article, "The Death of Polling is Greatly Exaggerated", which argues that the death of polling is greatly exaggerated.

fivethirtyeight.com/features/the-d…
Based on average error, the 2019-20 cycle featured decidedly mediocre polling: an average error of 6.3 points. That's the 3rd worst out of 12 cycles we've tracked. At the same time, as you can see, it's not an outlier exactly, either. It was well within the range of "normal".
The polls actually did pretty well in "calling" races correctly, as 79% of polls identified the right winner, which is the same as the historical average. Polls got 48 of 50 presidential states right, correctly identified that Democrats would win Congress, etc.
Is that the best way to evaluate polls? No. It's better to look at the margins. The D wins came by far closer margins than polls projected. Still, the media tends to judge polls by winners and losers so the 💩 the polls got was a tad inconsistent with how they're often evaluated.
But here's the problem that's much harder to excuse. The polls had a big Democratic bias (bias meant in a statistical sense). Republicans beat their polls by 4.8 points on average! The bias was actually larger in Congressional & gubernatorial races than for Trump (4.2 points).
That's the biggest bias in either direction in the cycles our pollster ratings cover (since 1998). It's likely that some earlier years, certainly 1980 and probably 1994, would have had a bigger bias if you extended back that far. So not unprecedented. But still ... not ... good.
don't think we should necessarily expect that polls will continue to have a anti-Republican bias. Historically, the direction of bias is not very predicable as pollsters adjust, adapt, etc. But I do think we may continue to see systematic polling errors in BOTH directions.
In an environment where politics are highly nationalized and polarized, you don't really have "50 separate contests" for the presidency. For that matter, presidential and downballot outcomes are highly correlated. So if your polls are off in one race, they may be off everywhere.
The other big finding is that we no longer see a clear rationale to give live-caller polls a higher grade by default in our pollster ratings. For one thing, they haven't particularly outperformed other methodologies.
For another thing, it no longer really makes sense to classify entire *polling firms* by their methodology. Lots of polling firms mix-and-match methodologies, change them in midstream, etc. Methodology is a characteristic of a poll, not the pollster.
That doesn't mean that quality doesn't matter. We find that pollsters that participate in professional transparency/data-sharing initiatives continue to get considerably better results. The pollster ratings will continue to reflect this.
Something else worth mentioning—it's common sense but it shows up in the data—is that you should be mildly distrustful of pollsters without a track record. As a rule of thumb, it takes about 20 polls before you can have much confidence that what pollster does is working.
Finally, here's how the most prolific pollsters fared in the general election.

The best-performing pollster was AtlasIntel!

Second was Trafalgar!

Yeah, they incorrectly had Trump winning a few states, but they were close on the margins, and that's the better metric.
And ... one last piece (for now) of pollster-ratings-related content. A podcast! If the view I expressed in the article this morning struck you as a little too optimistic about the future of polling, this is shaded a bit more pessimistically FWIW.

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More from @NateSilver538

24 Mar
NYC's COVID data has been screwed up lately so here's what the state's data shows for NYC:

Cases (7-day average)
Current: 3921
1 week ago: 3854
2 weeks ago: 3797
3 weeks ago: 3999

Positive test rate (7-day avg)
Current: 4.3%
1 week ago: 4.3%
2 weeks ago: 3.9%
3 weeks ago: 4.2%
On the one hand, I'm pretty sure that sites showing a decline in NYC (the NYT shows this, for example) are wrong. They're filling in missing city data with state data for the city. But that state data isn't apples-to-apples; it doesn't include probably cases, for instance.
On the other hand, I'm seeing a lot of loose talk about a "spike" in NYC when, no, that isn't really justified either. For better or worse, the numbers have settled into a plateau, which is also the case throughout the Northeast. beta.healthdata.gov/Health/COVID-1…
Read 8 tweets
1 Mar
I, too, wish states kept restrictions in place for another few weeks until we're more caught up on vaccinations etc. But I think it's worth thinking about why states (recently including lots of blue states/cities) are opening up despite the CDC and others encouraging them not to.
Two obvious points. First, governors don't think of public health officials as having balanced all equities and considered all costs/benefits. They think of them as one side of "the argument", advocating for a position, with business owners, "citizens", etc. on the other side.
Second, they probably think of public health officials as *always* wanting to keep *everything* closed without clear timelines. Now, the rationale is about new variants. I (Nate) think that + timing of vaccines is a good rationale! But governors may see this as moving goalposts.
Read 4 tweets
8 Feb
Don't think there's been any point in the pandemic at which there's been such a confusing mix of good *and* bad COVID news. I actually think the good > bad, but there's plenty of both, and it's worth thinking about how people react to the uncertainty and confusion that creates.
I guess what I'm getting at is that uncertainty demands nuance, but ironically, people aren't looking for nuance at times of greater uncertainty! They're tired of the uncertainty and want simplicity and even dogmatism.
One obvious example is you've seen an uptick in people scolding images depicting both behaviors that are quite dangerous (that supermarket in Florida where no one's wearing a mask!😬) and others showing e.g. relatively safe outdoor activities. We've lost some of the nuance there.
Read 4 tweets
5 Jan
There's this lazy critique that "the mainstream media isn't taking the 'coup' seriously". Really? Have you actually read the articles that e.g. the NYT and WaPo are writing? This is the first article I found on NYT.com today. nytimes.com/2021/01/04/us/…
I criticized the NYT and other outlets a ton from mid-2015 through mid-2017 for how they covered Trump, including this sort of "news analysis" piece that was prone toward tired tropes and false equivalencies. These stories have changed a LOT since then, in my view for the better.
And, yes, sometimes you have to analyze the political incentives of the relevant actors, which may seem banal. And sometimes you have to assess the likelihood of success (exceedingly low). That is part of the story, and moreover, part of taking the story *seriously*.
Read 4 tweets
1 Jan
While this might sound like posturing by de Blasio, New York indeed has a fairly complicated set of categories and subcategories for who is in which tier and it's plausible to think that's slowing things down.

nytimes.com/2021/01/01/nyr…

And you know what'll probably be worse? Having hard-to-define categories like essential workers or pre-existing conditions. There are lots of borderline cases (and some people who will try to cheat the system). Who's going to verify who qualifies? Big administrative burden.
Rigorous verification will take time and slow things down. Lax verification will make things a free-for-all. I don't think these plans are well thought out. If you're going to have subcategories, make them narrow, specific and easy to verify (e.g. "public school teachers").
Read 4 tweets
18 Dec 20
At least with essential workers—if you can define the scope narrowly—there's an argument to be had about reaching herd immunity sooner. What will literally kill people is treating a broad set of preexisting conditions as being as important as age.
If you look at the research, virtually all of people at highest risk of dying from COVID are aged 70+. There are almost no preexisting conditions that matter remotely as much as age.

nature.com/articles/s4159…
But ACIP defines *more than 100m people* as having "high-risk medical conditions" that put them in the same priority tier as people age 65+ for vaccination. This is NOT following the science. States that want to save lives must give age higher priority. cdc.gov/vaccines/acip/…
Read 4 tweets

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