fivethirthyeight--2020-11-11--The Polls Weren’t Great. But That’s Pretty Normal.

I ’ m not a pollster , although I ’ m often misidentified as one on TV .
I wanted to get that out of the way because while , in practice , our lives probably get easier in a year where the polls are spot-on , FiveThirtyEight ’ s mission is really to take the polls as they are — for better or worse — and understand the sources of error and uncertainty behind them .
This is true for both the probabilistic forecasts that we build and the reporting that we do .
We ’ re also interested @ @ @ @ @ @ @ media and the public and how that sometimes conflicts with the way we think polls should be viewed .
From that vantage point , the story of how polls did in 2020 is complicated — more complicated in some ways than in 2016 , which was also complicated .
And since the election was called for Joe Biden on Saturday , I ’ ve had lots of somewhat conflicting thoughts pinging around in my head .
Here are a few of them : • On the one hand , I don ’ t @ @ @ @ @ @ @ year was definitely a little weird , given that the vote share margins were often fairly far off from the polls ( including in some high-profile examples such as Wisconsin and Florida ) .
But at the same time , a high percentage of states ( likely 48 out of 50 ) were “ called ” correctly , as was the overall Electoral College and popular vote winner ( Biden ) .
And that ’ s usually how polls are judged : Did they identify the right winner ?
• On the other @ @ @ @ @ @ @ came to the actual vote share margins is a better way to judge polls , so I ’ m glad that people are doing that .
• And yet , the margins by which the polls missed — underestimating President Trump by what will likely end up being 3 to 4 percentage points in national and swing state polls — is actually pretty normal by historical standards .
• However , there are nevertheless reasons to be concerned about the polls going forward , especially if it ’ s hard to get a @ @ @ @ @ @ @ phone .
• Finally , there ’ s a slightly meta point here : Voters and the media need to recalibrate their expectations around polls — not necessarily because anything ’ s changed , but because those expectations demanded an unrealistic level of precision — while simultaneously resisting the urge to “ throw all the polls out.
” In this story , I ’ m going to tackle a little bit of everything from this list apart from No .
4 .
The question of why the polls were off — and what @ @ @ @ @ @ @ — is a vital one , but it ’ s something that deserves a longer and fuller analysis , which we ’ ll do in the upcoming days and weeks .
I ’ m also going to set aside the question of how probabilistic forecasts like FiveThirtyEight ’ s did .
If you want a quick answer , we think our forecasts did very well .
( Biden was a reasonably heavy favorite in our forecast precisely because he could withstand a normal-sized or slightly larger polling error and still come out narrowly @ @ @ @ @ @ @ much what happened . )
Our forecasts should also do well by the more rigorous methods we use to evaluate them .
But that ’ s a different question than how the polls themselves performed .
First , some good news for the polls : Assuming current results hold , the only states where presidential polling averages got the winners wrong will be Florida , North Carolina and the 2nd Congressional District in Maine .
And because Biden ’ s leads in those states were narrow to begin with , they weren ’ @ @ @ @ @ @ @ also two mild upsets in the Senate , where Maine ’ s Susan Collins and North Carolina ’ s Thom Tillis both won reelection despite narrowly trailing in polls . )
I ’ m starting with this point because “ calling ” the outcome right is usually the way that polls are evaluated , even if it isn ’ t the best way to evaluate their actual performance .
Polls were pilloried for “ missing ” Brexit , for instance , even though the position to remain in the European Union had , @ @ @ @ @ @ @ the polling average , and the position to leave won by a narrow margin ( 52 percent leave , 48 percent remain ) .
So while I ’ m not a pollster , I ’ m going to stick up for them on this point .
If you want to criticize polls when they got the outcomes wrong even though the results were close ( within the margin of error ) — not our preference , but how the rest of the media usually covers polls — then , to be consistent , @ @ @ @ @ @ @ identify the right winners , even if the margins are fairly far off .
The better way to evaluate polls is how close they come on vote margins , and this year , polling margins will be fairly far off in several swing states as well as in national polls .
As of this writing , Biden leads by 3.4 percentage points in the national popular vote .
We expect him to improve on that some , as there are still a number of votes to be counted in blue states such as @ @ @ @ @ @ @ so he ’ ll probably finish with a lead closer to 4 points or possibly even a bit larger ; 5 points wouldn ’ t shock me .
In any event , we should expect a miss of around 4 points from Biden ’ s final margin of 8.4 points in national polls , though as I said at the outset , this is actually pretty normal by historical standards .
What about in the swing states ?
It ’ s actually a pretty similar story , at least among the competitive states @ @ @ @ @ @ @ polling errors in noncompetitive states , especially red states , which I ’ ll touch on more in a moment . )
Between the 18 states and congressional districts that we considered to be competitive this cycle , it looks as though the final FiveThirtyEight polling averages will have underestimated Trump by around 3.7 percentage points , on average .
Although , as you can see in the table below , the error was much bigger in some places than others : Note that this analysis is preliminary .
In the estimates above @ @ @ @ @ @ @ instance , that Biden gains about 2 additional points in Ohio and 1 further point in Pennsylvania based on ballots that remain to be counted in those states .
There may be a point or so to be had for Biden in some other states , too , given that provisional ballots and other late-counted ballots generally help Democrats .
Still , it looks like we ’ ll end up with swing state polls having missed Trump by 3 or 4 points , overall .
The errors were a little weird , though @ @ @ @ @ @ @ more in Wisconsin than in neighboring Minnesota , for instance .
Meanwhile , polls slightly overestimated Trump in Maine ’ s 1st Congressional District , but considerably underestimated him in the more rural , 2nd Congressional District .
But this isn ’ t entirely unexpected .
State polling errors are often correlated with one another , but it can also get really complicated .
Sometimes , there ’ s a “ uniform swing ” that affects nearly all states .
Sometimes , there ’ s a group of states that share geographic and @ @ @ @ @ @ @ out of line .
And sometimes , states behave idiosyncratically .
The 2020 election looks as though it featured some combination of all three types of errors .
Trump clearly outperformed his polls overall , but he did so more in some regions ( say , the Midwest ) than others ( say , the Southwest ) .
Even within these regions , though , there were quirks , like Biden winning Georgia but losing Florida .
The error may be somewhat larger in congressional races , too , as Republicans are running @ @ @ @ @ @ @ lead in the U.S. House popular vote total is 1 or 2 points smaller than Biden ’ s ) .
And in deeply red states with supposedly competitive Senate races such as Montana , Kansas and South Carolina , the polls look to have considerably overestimated how well Democrats would do .
Then again , down-ballot races typically feature more polling error than the presidency .
Next question : Are polls becoming less accurate over time ?
The answer is basically no , although it depends on what cycle you start measuring from @ @ @ @ @ @ @ set .
Polls were quite accurate in the 2004 and 2008 presidential elections , for instance , and this was also a time when polling received increased media attention .
The 2012 election was undoubtedly also good for polling ’ s reputation since polls identified the winner correctly in almost every state , although they did underestimate then-President Barack Obama ’ s margin of victory by a few points .
Polls have had a rougher go in the past , however .
Take what the final FiveThirtyEight national polling average ( calculated retroactively @ @ @ @ @ @ @ election since 1972 : On average , the final national polls were off by 2.3 points .
That ’ s pretty close , but there are also several examples of polling error comparable to this year .
There were 4-point polling misses in 1996 and 2012 ( as mentioned , the national polls weren ’ t so good that year ) , a 5-point error in 2000 and a whopping 8-point miss in 1980 , when Ronald Reagan beat Jimmy Carter by far more than polls predicted .
There were also a lot @ @ @ @ @ @ @ mid-20th century .
There aren ’ t enough polls to calculate a FiveThirtyEight-style average prior to 1972 , but we can look at what Gallup ’ s final poll said dating back to 1936 .
Oftentimes , it wasn ’ t much good : The final Gallup poll missed by 5.6 percentage points on average between 1936 and 1968 .
That includes a somewhat infamous 9-point miss in 1948 , when Thomas Dewey didn ’ t actually defeat Harry Truman .
Gallup also lowballed FDR ’ s margin of victory by 12 points @ @ @ @ @ @ @ , our model estimates that the final national polls will miss by about 3 percentage points in an average year .
( That ’ s why we call a 3-point miss a “ normal-sized polling error.
” ) In other words , a 4-point polling error is somewhat par for the course , although maybe you could call it a bogey .
So if all of this is fairly normal , why has there been so much consternation about the polls this year ?
To put my media critic hat on for a @ @ @ @ @ @ @ here .
One is the “ blue shift ” that occurred in states such as Pennsylvania , where mail-in ballots were counted after in-person ballots .
As predictable as the blue shift was , if you didn ’ t know that Biden was eventually going to win Pennsylvania , Wisconsin , Michigan and Georgia , once these mail-in ballots were factored in , the polls looked much worse than they wound up being .
But narratives about what happened in an election tend to form early on in the evening on election night @ @ @ @ @ @ @ that this election could take weeks and that there was a real possibility that neither Trump nor Biden would reach 270 electoral votes on election night .
These narratives also aren ’ t usually formulated by more data- and empirically-driven reporters , who know to wait until more votes are counted .
Next , there ’ s the fact that the polls have missed in the same direction in the last two presidential cycles .
The conventional wisdom trends to treat whatever happened in the most recent election as a new Iron Law @ @ @ @ @ @ @ two times in a row … oh boy , you ’ re never going to hear the end of it .
But what ’ s important to stress here is even though the polls have now missed in the same direction twice in a row , this isn ’ t necessarily indicative of how polls will behave going forward .
In the long run , while polls can be biased , the bias isn ’ t predictable from cycle to cycle .
Sometimes , they do miss in the same direction for a @ @ @ @ @ @ @ Other times , the bias flips around — in 2012 , polls underestimated Obama and Democrats before underestimating Trump and Republicans in 2016 .
It ’ s probably worth mentioning that polls had a very good and unbiased year in the 2018 midterms before their problems this year , too .
The reason there ’ s no long-running polling bias is because pollsters try to correct for their mistakes .
That means there ’ s always the risk of undercorrecting ( which apparently happened this time ) or overcorrecting ( see the 2017 @ @ @ @ @ @ @ all sorts of dodgy things in an effort to not underestimate Conservatives … and wound up underestimating the Labour Party instead ) .
This sets up an especially big challenge for pollsters moving forward because some of the plausible explanations for the polling miss have to do with the COVID-19 pandemic or other factors specific to 2020 , while some do not .
Imagine that , in an effort to correct for the bias it showed in 2020 , a pollster adopts a new technique that results in shifting its margins toward Republicans @ @ @ @ @ @ @ out that the bias was because of something 2020-specific .
Then , the pollster may wind up with polling that underestimates Democrats in 2022 and 2024 .
But if the pollster chalks the error up to COVID-19 and doesn ’ t change anything when it was something lasting , they may underestimate Republicans once again .
Finally , there ’ s the fact that the election comes at a time of exceptionally high anxiety for the country .
Between the pandemic and the election — and in an era when the media and @ @ @ @ @ @ @ challenged in both constructive and unconstructive ways — there ’ s not a lot to feel certain about .
On that front , I ’ m afraid I have some bad news .
If you want certainty about election outcomes , polls aren ’ t going to give you that — at least , not most of the time .
It ’ s not because the polls are bad .
On the contrary , I ’ m amazed that polls are as good as they are .
Given that response rates to polls @ @ @ @ @ @ @ that there are so many other things that can go wrong , from voters changing their minds after you poll them to guessing wrong about which voters will turn out — plus the unavoidable issue of sampling error — it ’ s astonishing that polls get within a couple of points the large majority of the time .
And yet , if a poll projects the outcome at 53-47 and it winds up being 51-49 ( a 4-point miss ) , it will probably receive a lot of criticism — even , as @ @ @ @ @ @ @ if it “ calls ” the winner right .
It ’ s a fairly thankless task .
Nor is the reason to recalibrate your expectations about polls because polls are getting worse , necessarily .
Empirically , after a somewhat worse than average but still fairly normal year in 2016 , a very good year in 2018 , and a 2020 polling error that will likely be a bit worse than 2016 but is still well within the realm of historical precedent , there ’ s not really a basis for coming to @ @ @ @ @ @ @ there may be reasons to expect polls will be worse going forward , but that depends on identifying the reasons for the 2020 error first .
And remember , everybody is just getting started on that process .
The main reason that polls aren ’ t going to provide you with the certitude you might desire is because polls have always come with a degree of uncertainty .
In a highly polarized era , most elections are going to be close — close enough as to exceed the ability of polls to provide @ @ @ @ @ @ @ the final polling averages miss by a bit more than 3 points on average , as our forecast assumes .
That means the margin of error is closer to 7 or 8 points .
And every presidential election so far this century has fallen within that range .
So if you ’ re coming to the polls for strong probabilistic hints of what is going to happen , they can provide those — and the hints will usually lead you in roughly the right direction , as they did this year .
But @ @ @ @ @ @ @ , you ’ ll have to look elsewhere .

I’m not a pollster, although I’m often misidentified as one on TV. I wanted to get that out of the way because while, in practice, our lives probably get easier in a year where the polls are spot-on, FiveThirtyEight’s mission is really to take the polls as they are — for better or worse — and understand the sources of error and uncertainty behind them. This is true for both the probabilistic forecasts that we build and the reporting that we do. We’re also interested in how polls are perceived by the media and the public and how that sometimes conflicts with the way we think polls should be viewed.
Where the rest of the 2020 races stand | FiveThirtyEight Politics Podcast
From that vantage point, the story of how polls did in 2020 is complicated — more complicated in some ways than in 2016, which was also complicated. And since the election was called for Joe Biden on Saturday, I’ve had lots of somewhat conflicting thoughts pinging around in my head.
Here are a few of them:
On the one hand, I don’t entirely understand the polls-were-wrong storyline. This year was definitely a little weird, given that the vote share margins were often fairly far off from the polls (including in some high-profile examples such as Wisconsin and Florida). But at the same time, a high percentage of states (likely 48 out of 50) were “called” correctly, as was the overall Electoral College and popular vote winner (Biden). And that’s usually how polls are judged: Did they identify the right winner? On the other hand, evaluating how close the polls came to the actual vote share margins is a better way to judge polls, so I’m glad that people are doing that. And yet, the margins by which the polls missed — underestimating President Trump by what will likely end up being 3 to 4 percentage points in national and swing state polls — is actually pretty normal by historical standards. However, there are nevertheless reasons to be concerned about the polls going forward, especially if it’s hard to get a truly representative sample of people on the phone. Finally, there’s a slightly meta point here: Voters and the media need to recalibrate their expectations around polls — not necessarily because anything’s changed, but because those expectations demanded an unrealistic level of precision — while simultaneously resisting the urge to “throw all the polls out.”
So, yeah, it’s complicated.
In this story, I’m going to tackle a little bit of everything from this list apart from No. 4. The question of why the polls were off — and what that means for the polls going forward — is a vital one, but it’s something that deserves a longer and fuller analysis, which we’ll do in the upcoming days and weeks. I’m also going to set aside the question of how probabilistic forecasts like FiveThirtyEight’s did. If you want a quick answer, we think our forecasts did very well. (Biden was a reasonably heavy favorite in our forecast precisely because he could withstand a normal-sized or slightly larger polling error and still come out narrowly ahead — and that’s pretty much what happened.) Our forecasts should also do well by the more rigorous methods we use to evaluate them. But that’s a different question than how the polls themselves performed.
First, some good news for the polls: Assuming current results hold, the only states where presidential polling averages got the winners wrong will be Florida, North Carolina and the 2nd Congressional District in Maine. And because Biden’s leads in those states were narrow to begin with, they weren’t huge upsets. (There were also two mild upsets in the Senate, where Maine’s Susan Collins and North Carolina’s Thom Tillis both won reelection despite narrowly trailing in polls.)
[Related: Democrats Aren’t Sure Why They Didn’t Do Better In The House And Senate. It Might Not Be Clear For Weeks.]
I’m starting with this point because “calling” the outcome right is usually the way that polls are evaluated, even if it isn’t the best way to evaluate their actual performance. Polls were pilloried for “missing” Brexit, for instance, even though the position to remain in the European Union had, at best, a tiny advantage in the polling average, and the position to leave won by a narrow margin (52 percent leave, 48 percent remain).
So while I’m not a pollster, I’m going to stick up for them on this point. If you want to criticize polls when they got the outcomes wrong even though the results were close (within the margin of error) — not our preference, but how the rest of the media usually covers polls — then, to be consistent, you ought to praise them if they identify the right winners, even if the margins are fairly far off.
The better way to evaluate polls is how close they come on vote margins, and this year, polling margins will be fairly far off in several swing states as well as in national polls. As of this writing, Biden leads by 3.4 percentage points in the national popular vote. We expect him to improve on that some, as there are still a number of votes to be counted in blue states such as New York, California and Illinois, so he’ll probably finish with a lead closer to 4 points or possibly even a bit larger; 5 points wouldn’t shock me. In any event, we should expect a miss of around 4 points from Biden’s final margin of 8.4 points in national polls, though as I said at the outset, this is actually pretty normal by historical standards.
What about in the swing states? It’s actually a pretty similar story, at least among the competitive states. (There were some fairly bad polling errors in noncompetitive states, especially red states, which I’ll touch on more in a moment.) Between the 18 states and congressional districts that we considered to be competitive this cycle, it looks as though the final FiveThirtyEight polling averages will have underestimated Trump by around 3.7 percentage points, on average. Although, as you can see in the table below, the error was much bigger in some places than others:
There were big misses in some swing states Joe Biden’s final FiveThirtyEight polling average in each battleground race compared to his vote share margin in each race Biden’s lead or deficit Polling Average Actual result Diff ME-2 +3 -8 -11 Wisconsin +8 +1 -7 Iowa -1 -8 -7 Florida +3 -3 -6 Michigan +8 +3 -5 Ohio -1 -6* -5 Texas -1 -6 -5 New Hampshire +11 +7 -4 Maine (statewide) +13 +9 -4 Pennsylvania +5 +2* -3 Arizona +3 +0 -3 North Carolina +2 -1 -3 Virginia +12 +10 -2 Minnesota +9 +7 -2 Nevada +5 +3 -2 Georgia +1 +0 -1 Colorado +13 +14 +1 NE-2 +4 +7 +3 * In Ohio and Pennsylvania, actual results reflects expected changes once all votes are counted. Sources: Polls, ABC News, the Cook Political Report, State Websites
Note that this analysis is preliminary. In the estimates above, I’m guesstimating, for instance, that Biden gains about 2 additional points in Ohio and 1 further point in Pennsylvania based on ballots that remain to be counted in those states. There may be a point or so to be had for Biden in some other states, too, given that provisional ballots and other late-counted ballots generally help Democrats. Still, it looks like we’ll end up with swing state polls having missed Trump by 3 or 4 points, overall.
The errors were a little weird, though. Trump beat his polls by considerably more in Wisconsin than in neighboring Minnesota, for instance. Meanwhile, polls slightly overestimated Trump in Maine’s 1st Congressional District, but considerably underestimated him in the more rural, 2nd Congressional District. But this isn’t entirely unexpected. State polling errors are often correlated with one another, but it can also get really complicated. Sometimes, there’s a “uniform swing” that affects nearly all states. Sometimes, there’s a group of states that share geographic and demographic similarities in which the polls are out of line. And sometimes, states behave idiosyncratically. The 2020 election looks as though it featured some combination of all three types of errors. Trump clearly outperformed his polls overall, but he did so more in some regions (say, the Midwest) than others (say, the Southwest). Even within these regions, though, there were quirks, like Biden winning Georgia but losing Florida.
Biden is set to be president. What comes next? | FiveThirtyEight Politics Podcast
The error may be somewhat larger in congressional races, too, as Republicans are running slightly ahead of Trump (Democrats’ lead in the U.S. House popular vote total is 1 or 2 points smaller than Biden’s). And in deeply red states with supposedly competitive Senate races such as Montana, Kansas and South Carolina, the polls look to have considerably overestimated how well Democrats would do. Then again, down-ballot races typically feature more polling error than the presidency.
Next question: Are polls becoming less accurate over time?
The answer is basically no, although it depends on what cycle you start measuring from and how your expectations around polls are set. Polls were quite accurate in the 2004 and 2008 presidential elections, for instance, and this was also a time when polling received increased media attention. The 2012 election was undoubtedly also good for polling’s reputation since polls identified the winner correctly in almost every state, although they did underestimate then-President Barack Obama’s margin of victory by a few points.
Polls have had a rougher go in the past, however. Take what the final FiveThirtyEight national polling average (calculated retroactively) would have said in each past election since 1972:
The polls aren’t getting more inaccurate Polling error in the FiveThirtyEight national polling average compared to the national popular vote margin, 1972 to 2020 Year Final Average Result Error 1972 R+24 R+23 1 1976 D+1 D+2 1 1980 R+2 R+10 8 1984 R+18 R+18 0 1988 R+10 R+8 2 1992 D+7 D+6 1 1996 D+13 D+9 4 2000 R+4 D+1 5 2004 R+2 R+2 0 2008 D+7 D+7 0 2012 D+0 D+4 4 2016 D+4 D+2 2 2020 D+8 D+4* 4 *The 2020 result reflects Biden’s projected margin once all votes are counted. FiveThirtyEight’s polling averages are calculated retroactively for years prior to 2020.
On average, the final national polls were off by 2.3 points. That’s pretty close, but there are also several examples of polling error comparable to this year. There were 4-point polling misses in 1996 and 2012 (as mentioned, the national polls weren’t so good that year), a 5-point error in 2000 and a whopping 8-point miss in 1980, when Ronald Reagan beat Jimmy Carter by far more than polls predicted.
There were also a lot of fairly wild polling errors in the mid-20th century. There aren’t enough polls to calculate a FiveThirtyEight-style average prior to 1972, but we can look at what Gallup’s final poll said dating back to 1936. Oftentimes, it wasn’t much good:
The Gallup era was no golden era Polling error in the final Gallup presidential poll compared to the national popular vote margin, 1936 to 1968 Year Final Average Result Error 1936 D+12 D+24 12 1940 D+4 D+10 6 1944 D+3 D+7 4 1948 R+5 D+4 9 1952 R+2 R+11 9 1956 R+19 R+15 4 1960 D+2 D+0 2 1964 D+28 D+23 5 1968 R+1 R+1 0 Source: gallup
The final Gallup poll missed by 5.6 percentage points on average between 1936 and 1968. That includes a somewhat infamous 9-point miss in 1948, when Thomas Dewey didn’t actually defeat Harry Truman. Gallup also lowballed FDR’s margin of victory by 12 points in 1936.
Evaluating all this data, our model estimates that the final national polls will miss by about 3 percentage points in an average year. (That’s why we call a 3-point miss a “normal-sized polling error.”) In other words, a 4-point polling error is somewhat par for the course, although maybe you could call it a bogey.
So if all of this is fairly normal, why has there been so much consternation about the polls this year? To put my media critic hat on for a second, I see a few factors here. One is the “blue shift” that occurred in states such as Pennsylvania, where mail-in ballots were counted after in-person ballots. As predictable as the blue shift was, if you didn’t know that Biden was eventually going to win Pennsylvania, Wisconsin, Michigan and Georgia, once these mail-in ballots were factored in, the polls looked much worse than they wound up being.
But narratives about what happened in an election tend to form early on in the evening on election night, even though we knew going in that this election could take weeks and that there was a real possibility that neither Trump nor Biden would reach 270 electoral votes on election night. These narratives also aren’t usually formulated by more data- and empirically-driven reporters, who know to wait until more votes are counted.
Next, there’s the fact that the polls have missed in the same direction in the last two presidential cycles. The conventional wisdom trends to treat whatever happened in the most recent election as a new Iron Law of Politics. So if something happens two times in a row … oh boy, you’re never going to hear the end of it.
[Related: Politics Podcast: Why Polls Were Off In 2020, And Why They Weren’t That Bad]
But what’s important to stress here is even though the polls have now missed in the same direction twice in a row, this isn’t necessarily indicative of how polls will behave going forward. In the long run, while polls can be biased, the bias isn’t predictable from cycle to cycle. Sometimes, they do miss in the same direction for a couple of cycles in a row. Other times, the bias flips around — in 2012, polls underestimated Obama and Democrats before underestimating Trump and Republicans in 2016. It’s probably worth mentioning that polls had a very good and unbiased year in the 2018 midterms before their problems this year, too.
The reason there’s no long-running polling bias is because pollsters try to correct for their mistakes. That means there’s always the risk of undercorrecting (which apparently happened this time) or overcorrecting (see the 2017 U.K. general election, where pollsters did all sorts of dodgy things in an effort to not underestimate Conservatives … and wound up underestimating the Labour Party instead). This sets up an especially big challenge for pollsters moving forward because some of the plausible explanations for the polling miss have to do with the COVID-19 pandemic or other factors specific to 2020, while some do not.
Imagine that, in an effort to correct for the bias it showed in 2020, a pollster adopts a new technique that results in shifting its margins toward Republicans by 3 points — but it turns out that the bias was because of something 2020-specific. Then, the pollster may wind up with polling that underestimates Democrats in 2022 and 2024. But if the pollster chalks the error up to COVID-19 and doesn’t change anything when it was something lasting, they may underestimate Republicans once again.
Finally, there’s the fact that the election comes at a time of exceptionally high anxiety for the country. Between the pandemic and the election — and in an era when the media and other forms of expertise are constantly being challenged in both constructive and unconstructive ways — there’s not a lot to feel certain about.
On that front, I’m afraid I have some bad news. If you want certainty about election outcomes, polls aren’t going to give you that — at least, not most of the time.
It’s not because the polls are bad. On the contrary, I’m amazed that polls are as good as they are. Given that response rates to polls are in the low single digits and that there are so many other things that can go wrong, from voters changing their minds after you poll them to guessing wrong about which voters will turn out — plus the unavoidable issue of sampling error — it’s astonishing that polls get within a couple of points the large majority of the time. And yet, if a poll projects the outcome at 53-47 and it winds up being 51-49 (a 4-point miss), it will probably receive a lot of criticism — even, as we’ve seen this year, if it “calls” the winner right. It’s a fairly thankless task.
Nor is the reason to recalibrate your expectations about polls because polls are getting worse, necessarily. Empirically, after a somewhat worse than average but still fairly normal year in 2016, a very good year in 2018, and a 2020 polling error that will likely be a bit worse than 2016 but is still well within the realm of historical precedent, there’s not really a basis for coming to that conclusion … yet. Theoretically, there may be reasons to expect polls will be worse going forward, but that depends on identifying the reasons for the 2020 error first. And remember, everybody is just getting started on that process.
The main reason that polls aren’t going to provide you with the certitude you might desire is because polls have always come with a degree of uncertainty. In a highly polarized era, most elections are going to be close — close enough as to exceed the ability of polls to provide you with a definitive answer. Say the final polling averages miss by a bit more than 3 points on average, as our forecast assumes. That means the margin of error is closer to 7 or 8 points. And every presidential election so far this century has fallen within that range. So if you’re coming to the polls for strong probabilistic hints of what is going to happen, they can provide those — and the hints will usually lead you in roughly the right direction, as they did this year. But if you’re looking for certainty, you’ll have to look elsewhere.
Polling 101: Should You Trust The Polls In 2020? | FiveThirtyEight


fivethirthyeight--2020-11-11--The 2014-15 Kansas City Royals Were One Of Baseball’s Great Underdog Stories

We love our sports forecasts here at FiveThirtyEight , but one of the things that make the games great is when a team comes along and takes prognosticators by surprise .
So along with our Hall of Pretty Damn Good Players , we want to appreciate these unsung teams that nobody saw coming , in a series we ’ re calling the Little Teams That Could .
Before their magical playoff runs of 2014 and 2015 , the Kansas City Royals had not exactly been a fixture in baseball ’ s postseason .
Although K.C .
had ranked among baseball @ @ @ @ @ @ @ the mid-1980s , the 1990s and 2000s were not kind to the franchise .
Team cornerstones like George Brett , Willie Wilson and Frank White gave way to stars who didn ’ t stay long — Carlos Beltrán , Johnny Damon , Zack Greinke , etc .
— and a host of lesser players who filled in the gaps .
After winning the 1985 World Series , Kansas City missed the playoffs for the next 28 seasons in a row .
And worse than merely being mediocre , Kansas City was almost always @ @ @ @ @ @ @ , the Royals finished better than 20th in our final Elo rankings just three times ( 19th in 2000 , 18th in 2008 and 14th in 2013 ) .
The mid-2010s weren ’ t supposed to change that .
Though an impressive prospect pipeline and a surprising 86-76 finish in 2013 had raised expectations some , Kansas City was not viewed as a serious contender going into 2014 .
FanGraphs gave K.C .
just a 2.7 percent chance of making the World Series , and the Vegas odds implied only a slightly better @ @ @ @ @ @ @ names ( did Alex Gordon , James Shields and Salvador Pérez count ? )
and no recent history of playoff success to call upon , there was little reason to think the Royals would suddenly turn into a powerhouse .
And yet , the Royals started out steady in 2014 and exploded in the second half of the season — going an MLB-best 52-27 from July 22 onward ( including playoffs ) .
K.C .
got an All-Star-level season ( 4.4 wins above replacement ) from the late-blooming Lorenzo Cain in center field @ @ @ @ @ @ @ with manager Ned Yost ’ s core Royals formula : contact hitting , great defense , blazing speed and a lights-out bullpen .
Kansas City made the playoffs for the first time since that 1985 championship and knocked off the A ’ s in an unforgettable wild-card game , then swept the Angels and Orioles to give themselves a perfect 8-0 postseason record en route to the World Series .
Granting that the postseason was expanded by an extra round in 2012 , no team had ever won each of its first eight @ @ @ @ @ @ @ the World Series , nor has it happened since .
( The 1976 Cincinnati Reds won all seven of their postseason contests . )
And they did it mostly out of nowhere .
According to our Weighted Average Loss Total ( WALT ) metric , which looks at a team ’ s average losses per 162 games over the 20 preceding seasons — placing more emphasis on recent seasons — the Royals were the fourth-most-unsung pennant winner since the divisional era launched in 1969 .
And only one team in that span ( @ @ @ @ @ @ @ straight to the World Series on the heels of a longer playoff drought than Kansas City did in 2014 .
Though the Royals lost to the dynasty San Francisco Giants in the Fall Classic , they came about as close as a team can get to winning without hoisting the Commissioner ’ s Trophy — falling in seven games with the tying run stranded 90 feet away in the bottom of the ninth , after Gordon had delivered one of the most iconic near-game-changers in baseball history .
With that unfinished business in @ @ @ @ @ @ @ run in 2015 .
But despite coming off a World Series appearance , they carried only +3300 championship odds at the end of spring training , according to SportsOddsHistory.com — which was tied for just 18th-best in baseball .
( After adjusting for the cut , +3300 odds would translate to a mere 2.2 percent chance of winning the World Series . )
Since 1985 , only two World Series teams were ever disrespected so much by the oddsmakers going into the following season : the fire-sale 1998 Florida Marlins ( +8000 ) @ @ @ @ @ @ @ +5000 ) .
Most of the other teams on that list had good cause to be dismissed .
The Marlins sunk to an abysmal 54-108 record a year after their 1997 championship , and the Padres fell to 74-88 after their 1998 World Series bid .
But the Royals beat their odds yet again — this time , even more convincingly than before .
They improved by six games in the standings , more than tripled their run differential from 2014 and had an MLB-high seven players named to the All-Star Game ( @ @ @ @ @ @ @ shenanigans ) .
Rather than regressing to the mean like most teams do after a meteoric rise , Kansas City just kept getting better .
And the Royals did it their way , playing small ball even as the rest of baseball moved away from that style .
We can measure just how “ Royals-y ” the 2014-15 Royals really were by looking at their percentile rankings in contact rate , speed , and defensive and relief-pitching WAR , and adding them up to create what we ’ re calling an ESCOBAR Rating @ @ @ @ @ @ @ who perhaps most embodied the Royals ’ brand of winning baseball ) .
With an ESCOBAR of 397 ( out of a possible 400 ) , the 2015 Royals were indeed the Royals-iest team in baseball during the expansion era ( since 1961 ) , while the 2014 Royals ’ 393 ESCOBAR ranks second on the list : Armed with more talent than the year before — like starters Johnny Cueto and Edinson Vólquez , and all-purpose icon Ben Zobrist — the Royals thrived again in the 2015 postseason .
They outlasted the @ @ @ @ @ @ @ sprinted past the favored Blue Jays in the ALCS and finally took care of the upstart Mets in a five-game World Series , coming from behind to force extra innings in the deciding game thanks to a heads-up , aggressive base-running gambit by first baseman Eric Hosmer : That play — Hosmer ’ s Mad Dash , as ESPN ’ s Tim Kurkjian later immortalized it in this oral history — represented everything special about Kansas City ’ s playoff runs in 2014 and 2015 .
Nobody saw it coming , and by @ @ @ @ @ @ @ ’ t be stopped .
“ That ’ s what I ’ m most proud of , how aggressive and fearless [ Hosmer ] was , ” Yost said .
“ He was not afraid to make a mistake .
He played to win .
He saw a way to win the game .
That is what we do here — we play to win.
” When the Royals scored five in the top of the 12th inning and shut down the Mets with lights-out closer Wade Davis a half-inning later , Kansas @ @ @ @ @ @ @ oddity to world champions .
“ The way the Royals defied the projections is almost without precedent , ” my colleague Rob Arthur wrote at the time , noting that Kansas City was no fluke , either — its core simply began playing better all at once , maximizing the potential of its playing style ( and , like most champions , excelling during the most important moments ) .
It didn ’ t last beyond 2015 — K.C .
is currently mired in a five-year postseason drought — but for two magical @ @ @ @ @ @ @ the quintessential Little Teams That Could .

The 2014-15 Kansas City Royals Were One Of Baseball’s Great Underdog Stories Clubs that fooled the forecasters — the Little Teams That Could — keep sports fun.
We love our sports forecasts here at FiveThirtyEight, but one of the things that make the games great is when a team comes along and takes prognosticators by surprise. So along with our Hall of Pretty Damn Good Players, we want to appreciate these unsung teams that nobody saw coming, in a series we’re calling the Little Teams That Could.
Before their magical playoff runs of 2014 and 2015, the Kansas City Royals had not exactly been a fixture in baseball’s postseason.
OK, talk about huge understatements …
Although K.C. had ranked among baseball’s best from the mid-1970s to the mid-1980s, the 1990s and 2000s were not kind to the franchise. Team cornerstones like George Brett, Willie Wilson and Frank White gave way to stars who didn’t stay long — Carlos Beltrán, Johnny Damon, Zack Greinke, etc. — and a host of lesser players who filled in the gaps. After winning the 1985 World Series, Kansas City missed the playoffs for the next 28 seasons in a row. And worse than merely being mediocre, Kansas City was almost always straight-up bad. From 1997 through 2013, the Royals finished better than 20th in our final Elo rankings just three times (19th in 2000, 18th in 2008 and 14th in 2013).
The mid-2010s weren’t supposed to change that. Though an impressive prospect pipeline and a surprising 86-76 finish in 2013 had raised expectations some, Kansas City was not viewed as a serious contender going into 2014. FanGraphs gave K.C. just a 2.7 percent chance of making the World Series, and the Vegas odds implied only a slightly better 4.7 percent probability. With few household names (did Alex Gordon, James Shields and Salvador Pérez count?) and no recent history of playoff success to call upon, there was little reason to think the Royals would suddenly turn into a powerhouse.
The 2014-15 Royals were true long shots Chances to make and win the 2014 and 2015 World Series for the Kansas City Royals, according to Las Vegas odds and FanGraphs’ statistical model 2014 Odds to… 2015 Odds to… Projection via Make WS Win WS Make WS Win WS Vegas oddsmakers* 4.7% 2.5% 4.7% 2.2% FanGraphs 2.7 1.2 2.2 0.9 Average 3.7 1.9 3.4 1.6 *Implied probabilities are adjusted for the “cut” that bookmakers take on each bet. Sources: FanGraphs, Sports Odds History
And yet, the Royals started out steady in 2014 and exploded in the second half of the season — going an MLB-best 52-27 from July 22 onward (including playoffs). K.C. got an All-Star-level season (4.4 wins above replacement) from the late-blooming Lorenzo Cain in center field and an improved rotation, to go with manager Ned Yost’s core Royals formula: contact hitting, great defense, blazing speed and a lights-out bullpen. Kansas City made the playoffs for the first time since that 1985 championship and knocked off the A’s in an unforgettable wild-card game, then swept the Angels and Orioles to give themselves a perfect 8-0 postseason record en route to the World Series.
Granting that the postseason was expanded by an extra round in 2012, no team had ever won each of its first eight playoff games until the 2014 Royals visited the World Series, nor has it happened since. (The 1976 Cincinnati Reds won all seven of their postseason contests.) And they did it mostly out of nowhere. According to our Weighted Average Loss Total (WALT) metric, which looks at a team’s average losses per 162 games over the 20 preceding seasons — placing more emphasis on recent seasons — the Royals were the fourth-most-unsung pennant winner since the divisional era launched in 1969. And only one team in that span (the 1995 Cleveland Indians) had gone straight to the World Series on the heels of a longer playoff drought than Kansas City did in 2014.
The 2014 Royals’ World Series came out of nowhere Most recent losses (as measured by our Weighted Average Loss Total metric) and longest playoff droughts for World Series teams, 1969-2020 Most avg. recent losses Longest playoff droughts Year Team WALT* Year Team Prev. App. Drought 1969 Mets 104.5 1995 Indians 1954 40 yrs 2008 Rays 97.4 2014 Royals 1985 28 2006 Tigers 93.8 2006 Tigers 1987 18 2014 Royals 92.0 1987 Twins 1970 16 1984 Padres 91.9 2002 Angels 1986 15 1991 Braves 90.8 1984 Padres — 15 1973 Mets 90.7 1982 Cardinals 1968 13 2015 Royals 90.3 1986 Mets 1973 12 1992 Braves 88.8 2007 Rockies 1995 11 1997 Marlins 88.7 1984 Tigers 1972 11 2003 Marlins 88.1 1976 Yankees 1964 11 *WALT looks at team’s average losses per 162 games over the 20 previous seasons, weighted for recency (i.e., one year ago gets a weight of 20, two years ago gets 19, and so forth until 20 years ago gets a weight of 1). Source: Retrosheet
Though the Royals lost to the dynasty San Francisco Giants in the Fall Classic, they came about as close as a team can get to winning without hoisting the Commissioner’s Trophy — falling in seven games with the tying run stranded 90 feet away in the bottom of the ninth, after Gordon had delivered one of the most iconic near-game-changers in baseball history.
With that unfinished business in mind, Kansas City reloaded for another run in 2015. But despite coming off a World Series appearance, they carried only +3300 championship odds at the end of spring training, according to Sports Odds History — which was tied for just 18th-best in baseball. (After adjusting for the cut, +3300 odds would translate to a mere 2.2 percent chance of winning the World Series.) Since 1985, only two World Series teams were ever disrespected so much by the oddsmakers going into the following season: the fire-sale 1998 Florida Marlins (+8000) and the 1999 San Diego Padres (+5000).
Vegas didn’t believe in the Royals. It didn’t matter. Longest preseason World Series odds for teams that had been to the previous World Series, 1985-2020 Year Team Prev. Season Preseason WS Odds Season Outcome 1998 Florida Marlins Won WS +8000 No playoffs 1999 San Diego Padres Lost WS 5000 No playoffs 2015 Kansas City Royals Lost WS 3300 Won WS 2006 Houston Astros Lost WS 3000 No playoffs 2015 San Francisco Giants Won WS 2500 No playoffs 2004 Florida Marlins Won WS 2500 No playoffs 2008 Colorado Rockies Lost WS 2200 No playoffs 2020 Washington Nationals Won WS 2000 No playoffs 2012 St. Louis Cardinals Won WS 2000 Lost LCS 2011 Texas Rangers Lost WS 2000 Lost WS Source: Sports Odds History
Most of the other teams on that list had good cause to be dismissed. The Marlins sunk to an abysmal 54-108 record a year after their 1997 championship, and the Padres fell to 74-88 after their 1998 World Series bid. But the Royals beat their odds yet again — this time, even more convincingly than before. They improved by six games in the standings, more than tripled their run differential from 2014 and had an MLB-high seven players named to the All-Star Game (thanks in part to some fun balloting shenanigans). Rather than regressing to the mean like most teams do after a meteoric rise, Kansas City just kept getting better.
(We should note that the statistical systems fared no better than Vegas in predicting the 2015 Royals — to the point that we wondered whether they had broken our beloved projection algorithms.)
And the Royals did it their way, playing small ball even as the rest of baseball moved away from that style. We can measure just how “Royals-y” the 2014-15 Royals really were by looking at their percentile rankings in contact rate, speed, and defensive and relief-pitching WAR, and adding them up to create what we’re calling an ESCOBAR Rating, after speedy shortstop Alcides Escobar (who perhaps most embodied the Royals’ brand of winning baseball). With an ESCOBAR of 397 (out of a possible 400), the 2015 Royals were indeed the Royals-iest team in baseball during the expansion era (since 1961), while the 2014 Royals’ 393 ESCOBAR ranks second on the list:
Who is the most Royals-y team of them all? ESCOBAR* Ratings for MLB teams since 1961, based on leaguewide percentile grades in contact rate, speed, defense and bullpen WAR Percentile Rankings Year Team Playoffs? Contact Speed Defense Bullpen ESCOBAR Rating 2015 Royals Won WS 100 97 100 100 397 2014 Royals Lost WS 100 100 93 100 393 2000 Rockies No playoffs 97 100 97 97 390 2013 Royals No playoffs 97 97 100 97 390 2001 Mariners Lost LCS 97 97 100 86 379 2002 Angels Won WS 100 97 100 83 379 1976 Royals Lost LCS 96 96 91 87 370 2013 Rangers No playoffs 97 86 83 100 366 2017 Indians Lost LDS 97 86 86 97 366 1973 Orioles Lost LCS 87 100 100 78 365 2003 Angels No playoffs 100 83 83 97 362 1985 Yankees No playoffs 96 84 80 100 360 1985 Blue Jays Lost LCS 84 92 100 84 360 2005 Angels Lost LCS 97 97 86 79 359 1976 Yankees Lost WS 100 74 100 83 357 1967 White Sox No playoffs 100 58 100 95 353 1969 Orioles Lost WS 96 57 100 100 352 2017 Red Sox Lost LDS 90 72 97 93 352 1964 White Sox No playoffs 95 79 100 74 347 1966 White Sox No playoffs 74 89 100 84 347 *Efficiency Score for Contact rate, glOvework, Bullpen WAR And Running. Ratings are out of a possible 400 (which would mean the team finished 1st in each category). Sources: Fangraphs, Baseball-Reference.com
Armed with more talent than the year before — like starters Johnny Cueto and Edinson Vólquez, and all-purpose icon Ben Zobrist — the Royals thrived again in the 2015 postseason. They outlasted the Astros in the AL Division Series, sprinted past the favored Blue Jays in the ALCS and finally took care of the upstart Mets in a five-game World Series, coming from behind to force extra innings in the deciding game thanks to a heads-up, aggressive base-running gambit by first baseman Eric Hosmer:
That play — Hosmer’s Mad Dash, as ESPN’s Tim Kurkjian later immortalized it in this oral history — represented everything special about Kansas City’s playoff runs in 2014 and 2015. Nobody saw it coming, and by the time they did, it couldn’t be stopped. “That’s what I’m most proud of, how aggressive and fearless [Hosmer] was,” Yost said. “He was not afraid to make a mistake. He played to win. He saw a way to win the game. That is what we do here — we play to win.”
When the Royals scored five in the top of the 12th inning and shut down the Mets with lights-out closer Wade Davis a half-inning later, Kansas City had gone from an out-of-nowhere playoff oddity to world champions.
“The way the Royals defied the projections is almost without precedent,” my colleague Rob Arthur wrote at the time, noting that Kansas City was no fluke, either — its core simply began playing better all at once, maximizing the potential of its playing style (and, like most champions, excelling during the most important moments). It didn’t last beyond 2015 — K.C. is currently mired in a five-year postseason drought — but for two magical seasons, the Royals were one of the quintessential Little Teams That Could.
Sara Ziegler contributed research.


fivethirthyeight--2020-11-12--Liverpool And Manchester City Look Ordinary. Are They?

Before the 2020-21 Premier League season began , we wrote that the title was Liverpool ’ s and Manchester City ’ s to lose .
The new-ish rivals from the northwest dominated the league during the previous three seasons like no other teams in the history of the English top flight , and they each returned large chunks of their rosters , which are stocked with some of soccer ’ s biggest superstars .
As such , FiveThirtyEight ’ s club soccer prediction model gave City and Liverpool the best and second-best probabilities , respectively , to win the Premier @ @ @ @ @ @ @ City added former Benfica center back Rúben Dias to shore up its flaky defensive line .
Meanwhile , Liverpool acquired Diogo Jota from Wolverhampton Wanderers to provide cover ( and competition ) for its devastating but often overworked front three as well as Thiago Alcântara — one of the world ’ s greatest midfielders — from Bayern Munich to further solidify its already imperious midfield corps .
Which is all to say that the two teams that entered the season with the best squads and the best odds got even better , a @ @ @ @ @ @ @ those hoping to mount a title challenge .
But after Matchweek 8 , neither juggernaut occupies the top spot in the league table .
Our model still thinks City and Liverpool are the respective best and second-best team in the league — and by some margin — but the Premier League table begs to differ .
As things stand , Liverpool sits in third , level with Tottenham Hotspur on points but behind the north Londoners on goal differential , while City occupies the 10th position , behind the likes of Southampton , @ @ @ @ @ @ @ .
So , why are the two best teams in England underperforming expectations ?
In Liverpool ’ s case , the struggles have all been at the back .
Once airtight defensively , the Reds have given up the third-most goals ( 16 ) through Matchweek 8 , one fewer than recently promoted Leeds United and West Bromwich Albion , and one more than recently promoted Fulham .
To put that number in perspective , Liverpool conceded just 22 goals during the entire 2018-19 season .
To be fair , the Reds conceded @ @ @ @ @ @ @ extraordinarily flukey match against Aston Villa .
Still , no one would have expected the best defensive team in England to occupy space on the goals-against table next to three teams that played in the second-tier league earlier this year .
To make matters worse , the Reds lost do-it-all center back Virgil van Dijk after Everton goalkeeper Jordan Pickford — who apparently thought he was involved in a UFC fight , not a soccer match — scissor-kicked the Dutchman ’ s right knee .
Never mind that Liverpool conceded 11 of those @ @ @ @ @ @ @ the lineup — there ’ s no team on the planet that could account for the loss of a player of van Dijk ’ s caliber .
If the Reds were shaky defensively with van Dijk in the lineup , it ’ s hard to imagine they won ’ t be shaky defensively while he rehabilitates his busted knee .
Unfortunately for Jürgen Klopp , van Dijk ’ s isn ’ t the only injury giving the Liverpool manager selection fits at the moment .
Thiago missed time after a positive COVID-19 diagnosis @ @ @ @ @ @ @ against Everton — and remains sidelined ; defensive midfielder Fabinho , who was deployed at center back in van Dijk ’ s absence , injured his hamstring in a Champions League match and remains sidelined as well ; right back Trent Alexander-Arnold , the creative force who makes Liverpool ’ s attack purr , is out for at least a month with a calf injury ; and center back Joe Gomez , who is typically first choice as van Dijk ’ s partner , recently injured his knee while training with the English @ @ @ @ @ @ @ early defensive woes are unexpected , its early offensive prowess is anything but .
The Reds have been one of the most prolific attacking teams in the Premier League since Klopp took the helm in 2015 , and that remains unchanged .
Through Matchweek 8 , Liverpool leads the league in both expected goals ( 2.32 ) and non-penalty expected goals ( 1.95 ) per 90 minutes .
Mohamed Salah continues to deliver the goods — he ’ s the league ’ s joint top scorer — while Jota and Sadio Mané look @ @ @ @ @ @ @ .
In fact , the Reds have been so impenetrable defensively for the past two seasons , it ’ s easy to forget that they have also been as good as any team in the world going forward .
Losing van Dijk ( and Gomez , and Trent Alexander-Arnold ) is a hard pill to swallow , and Liverpool may very well have to rely on its front three — and new addition Jota — if it hopes to remain Premier League champion .
But if it keeps scoring at the rate it @ @ @ @ @ @ @ how to leak fewer goals here and there , that might not be such a bad strategy .
For City , the issue isn ’ t so much its inability to keep other teams from putting the ball in its net but rather its inability to put the ball into the nets of its opponents — or its inability to do so at the same outrageous rate it has grown accustomed to over the past three seasons .
Through seven matches , City ’ s non-penalty expected goals ( xG ) per 90 @ @ @ @ @ @ @ it ’ s tied with Chelsea for seventh-best in the league — but not Pep Guardiola ’ s Man City great , either .
In each of the previous three seasons , City has finished with a non-penalty xG per 90 mark of 1.95 or greater , and it has finished its first seven matches with a non-penalty xG per 90 mark of 2.08 or greater .
The Cityzens ’ underperformance so far this season is stark , but it has a simple explanation : Forwards Sergio Agüero and Gabriel Jesus — who @ @ @ @ @ @ @ ago — have both missed the majority of the young season with muscle injuries .
City ’ s injury crisis may not be as dire or as comprehensive as Liverpool ’ s — though it did just lose center back Nathan Aké to a hamstring injury , which will limit Guardiola ’ s ability to rotate at the back — but you can ’ t win games without scoring goals .
And you can ’ t score goals when your two most prolific players are sitting on the sidelines .
Fortunately for City @ @ @ @ @ @ @ he scored the equalizer in the 1-1 draw against Liverpool last weekend — and Agüero has returned to training .
If City remains solid at the back , and if Agüero and Jesus can find their world-class form from a season ago , it may not be long before City is back at the top of the table .
No teams dominated the English top division like City and Liverpool did between 2017-18 and 2019-20 — City finished with 100 points in the former season , Liverpool with 99 in the latter — @ @ @ @ @ @ @ to finish the current season with more than 81 points .
Since the turn of the millennium , only two teams have lifted the Premier League trophy after accumulating 81 points or fewer .
Could Liverpool ’ s and City ’ s slow starts keep them from winning the top domestic silverware ?
It ’ s too early to start ordaining champions and writing others off , especially during a season as deeply weird and unsettling as this one , beset by a pandemic .
Congested fixture lists mean more injuries , especially @ @ @ @ @ @ @ travel and a greater risk of COVID-19 exposure .
The model still likes City and Liverpool , but the model can ’ t account for injuries and outbreaks , two things City and Liverpool have been unlucky with to differing degrees .
But , in a year of uncertainty , at least one thing seems certain : Neither City nor Liverpool looks destined to run away with the title , and we might have one hell of a title race on our hands .

Before the 2020-21 Premier League season began, we wrote that the title was Liverpool’s and Manchester City’s to lose. The new-ish rivals from the northwest dominated the league during the previous three seasons like no other teams in the history of the English top flight, and they each returned large chunks of their rosters, which are stocked with some of soccer’s biggest superstars. As such, FiveThirtyEight’s club soccer prediction model gave City and Liverpool the best and second-best probabilities, respectively, to win the Premier League.
[Related: Why Has Premier League Scoring Skyrocketed?]
Since the season began, City added former Benfica center back Rúben Dias to shore up its flaky defensive line. Meanwhile, Liverpool acquired Diogo Jota from Wolverhampton Wanderers to provide cover (and competition) for its devastating but often overworked front three as well as Thiago Alcântara — one of the world’s greatest midfielders — from Bayern Munich to further solidify its already imperious midfield corps. Which is all to say that the two teams that entered the season with the best squads and the best odds got even better, a terrifying prospect for their opponents, especially those hoping to mount a title challenge.
But after Matchweek 8, neither juggernaut occupies the top spot in the league table. Our model still thinks City and Liverpool are the respective best and second-best team in the league — and by some margin — but the Premier League table begs to differ. As things stand, Liverpool sits in third, level with Tottenham Hotspur on points but behind the north Londoners on goal differential, while City occupies the 10th position, behind the likes of Southampton, Aston Villa, Crystal Palace and Wolves. So, why are the two best teams in England underperforming expectations?
In Liverpool’s case, the struggles have all been at the back. Once airtight defensively, the Reds have given up the third-most goals (16) through Matchweek 8, one fewer than recently promoted Leeds United and West Bromwich Albion, and one more than recently promoted Fulham. To put that number in perspective, Liverpool conceded just 22 goals during the entire 2018-19 season. To be fair, the Reds conceded seven of those 16 goals in one extraordinarily flukey match against Aston Villa. Still, no one would have expected the best defensive team in England to occupy space on the goals-against table next to three teams that played in the second-tier league earlier this year.
To make matters worse, the Reds lost do-it-all center back Virgil van Dijk after Everton goalkeeper Jordan Pickford — who apparently thought he was involved in a UFC fight, not a soccer match — scissor-kicked the Dutchman’s right knee. Never mind that Liverpool conceded 11 of those 16 goals with van Dijk still in the lineup — there’s no team on the planet that could account for the loss of a player of van Dijk’s caliber. If the Reds were shaky defensively with van Dijk in the lineup, it’s hard to imagine they won’t be shaky defensively while he rehabilitates his busted knee.
Unfortunately for Jürgen Klopp, van Dijk’s isn’t the only injury giving the Liverpool manager selection fits at the moment. Thiago missed time after a positive COVID-19 diagnosis before later injuring his knee — also against Everton — and remains sidelined; defensive midfielder Fabinho, who was deployed at center back in van Dijk’s absence, injured his hamstring in a Champions League match and remains sidelined as well; right back Trent Alexander-Arnold, the creative force who makes Liverpool’s attack purr, is out for at least a month with a calf injury; and center back Joe Gomez, who is typically first choice as van Dijk’s partner, recently injured his knee while training with the English national team.
If Liverpool’s early defensive woes are unexpected, its early offensive prowess is anything but. The Reds have been one of the most prolific attacking teams in the Premier League since Klopp took the helm in 2015, and that remains unchanged. Through Matchweek 8, Liverpool leads the league in both expected goals (2.32) and non-penalty expected goals (1.95) per 90 minutes. Mohamed Salah continues to deliver the goods — he’s the league’s joint top scorer — while Jota and Sadio Mané look dangerous every time they touch the ball. In fact, the Reds have been so impenetrable defensively for the past two seasons, it’s easy to forget that they have also been as good as any team in the world going forward.
Losing van Dijk (and Gomez, and Trent Alexander-Arnold) is a hard pill to swallow, and Liverpool may very well have to rely on its front three — and new addition Jota — if it hopes to remain Premier League champion. But if it keeps scoring at the rate it’s scoring and can figure out how to leak fewer goals here and there, that might not be such a bad strategy.
For City, the issue isn’t so much its inability to keep other teams from putting the ball in its net but rather its inability to put the ball into the nets of its opponents — or its inability to do so at the same outrageous rate it has grown accustomed to over the past three seasons. Through seven matches, City’s non-penalty expected goals (xG) per 90 mark is 1.21. Not terrible — it’s tied with Chelsea for seventh-best in the league — but not Pep Guardiola’s Man City great, either.
In each of the previous three seasons, City has finished with a non-penalty xG per 90 mark of 1.95 or greater, and it has finished its first seven matches with a non-penalty xG per 90 mark of 2.08 or greater. The Cityzens’ underperformance so far this season is stark, but it has a simple explanation: Forwards Sergio Agüero and Gabriel Jesus — who led City in non-penalty xG a year ago — have both missed the majority of the young season with muscle injuries.
City’s injury crisis may not be as dire or as comprehensive as Liverpool’s — though it did just lose center back Nathan Aké to a hamstring injury, which will limit Guardiola’s ability to rotate at the back — but you can’t win games without scoring goals. And you can’t score goals when your two most prolific players are sitting on the sidelines. Fortunately for City, Jesus is back in action — he scored the equalizer in the 1-1 draw against Liverpool last weekend — and Agüero has returned to training. If City remains solid at the back, and if Agüero and Jesus can find their world-class form from a season ago, it may not be long before City is back at the top of the table.
[Sue Bird And Megan Rapinoe Have Gotten Better Together.]
No teams dominated the English top division like City and Liverpool did between 2017-18 and 2019-20 — City finished with 100 points in the former season, Liverpool with 99 in the latter — and yet neither team is on pace to finish the current season with more than 81 points. Since the turn of the millennium, only two teams have lifted the Premier League trophy after accumulating 81 points or fewer. Could Liverpool’s and City’s slow starts keep them from winning the top domestic silverware?
It’s too early to start ordaining champions and writing others off, especially during a season as deeply weird and unsettling as this one, beset by a pandemic. Congested fixture lists mean more injuries, especially to muscles; international fixtures mean international travel and a greater risk of COVID-19 exposure. The model still likes City and Liverpool, but the model can’t account for injuries and outbreaks, two things City and Liverpool have been unlucky with to differing degrees.
But, in a year of uncertainty, at least one thing seems certain: Neither City nor Liverpool looks destined to run away with the title, and we might have one hell of a title race on our hands.
Check out our latest soccer predictions.


fivethirthyeight--2020-11-12--Republicans’ 2020 Gains In The House Set Them Up Well For 2022

2020 was not supposed to be a good year for House Republicans .
The polls pointed to a Democratic-leaning electoral environment , Democratic candidates were outraising Republicans in most competitive seats , and the GOP had to defend a host of open seats that Republican incumbents had abandoned .
Yet , contrary to expectations , including their own , Republicans managed to gain seats even as the Democrats held onto their majority .
Votes are still being counted , but based on contests projected by ABC News , Republicans have netted six seats so far , and they may still @ @ @ @ @ @ @ numbers about seats gained and lost can only tell us so much .
Let ’ s look at some of the major takeaways from the 2020 House elections .
Coming into the 2020 election , FiveThirtyEight ’ s forecast only gave Republicans about a 1 in 6 shot of picking up six or more seats , and if the GOP gains more as-yet-uncalled seats in the coming days , the party ’ s haul could become even more unlikely .
It ’ s not just the flipped seats that are impressive , though @ @ @ @ @ @ @ lost in the races where we know the outcomes thus far .
Among the outstanding contests , only California Rep. Mike Garcia , who won a May special election , appears to be in danger of losing .
Open-seat races have also been friendly to Republicans , despite the large number of GOP incumbents who retired or left office ahead of the 2020 election .
The GOP had to defend 35 open seats compared to the Democrats ’ 13 , but of the 33 Republican-held open seats projected so far , only three @ @ @ @ @ @ @ two of those Democratic wins were in North Carolina seats that the GOP had written off after a court-ordered redistricting made the districts heavily Democratic .
While the majority of the Republican caucus will still be men come 2021 , there will be far more Republican women in Congress than there were this year .
So far , it looks like at least 26 GOP women will be in the House next year , surpassing the record of 25 from the 109th Congress .
That ’ s thanks in part to the record @ @ @ @ @ @ @ — who ’ ve won House contests .
And it ’ s also because of how well Republican women did in tight races .
The table below shows the Republican women who ran in Democratic-held House districts that were at least potentially competitive , according to FiveThirtyEight ’ s forecast .
As of this writing , seven of them have won .
It ’ s not all bad news for Democrats While it was unquestionably a good night for Republicans , Democrats still held onto most of the seats they won in 2018 @ @ @ @ @ @ @ party in the House .
That ’ s in part because they retained most of the suburban districts they picked up in 2018 .
Of the 233 seats that Democrats held coming into the election , 186 of them were in districts that were predominantly or partly suburban in nature , according to density categorizations by Bloomberg ’ s CityLab .
( This figure excludes North Carolina because CityLab has not updated its density data to account for North Carolina ’ s court-ordered redistricting in 2019 . )
Thus far , Democrats have @ @ @ @ @ @ @ they captured one GOP-held suburban seat around Atlanta .
And thanks to redistricting , they ’ ve also won two formerly Republican seats around Greensboro and Raleigh in North Carolina , which reflect the party ’ s strength in more populous areas .
( ABC News hasn ’ t projected a winner yet in 11 suburban races — eight Democratic-held districts and three Republican-held districts . )
Because of their relative success in the suburbs , Democrats kept many seats in places President Trump won in 2016 .
Coming into the election , @ @ @ @ @ @ @ carried in 2016 , and they would ’ ve lost their majority if they ’ d lost more than half of them ( assuming they didn ’ t offset the losses by gaining seats elsewhere ) .
But they ’ ve won 18 of them so far and picked up one from the GOP ( Georgia ’ s 7th Congressional District ) .
In fact , more than half of Republicans ’ gains have come in seats representing places that Trump won by a pretty sizable margin in 2016 .
We ’ ll @ @ @ @ @ @ @ can tell us how congressional districts voted in 2020 , but for now it seems many Republican gains were made by picking off the lowest-hanging fruit .
Republicans are well positioned to take the House in 2022 Although we don ’ t yet know the winners of some House races , we can already look ahead to the 2022 midterms and see a fairly straightforward path for the GOP to capture the House .
Midterm elections historically go well for the party that ’ s not in the White House , and the @ @ @ @ @ @ @ well in the House , since every seat is up for election ( the Senate is a more complicated story ) .
Since the end of World War II , the presidential party has lost an average of 27 House seats in midterm elections , as the chart below shows .
No matter how many seats Democrats end up with after 2020 ’ s election — at this point , they will probably end up somewhere in the low 220s — a loss of that magnitude would easily be enough for Republicans to @ @ @ @ @ @ @ of midterms in a Democratic president ’ s first term seems especially promising for the GOP , too .
Following Bill Clinton ’ s election in 1992 , Democrats lost more than 50 seats in 1994 , and after Barack Obama won the presidency in 2008 , Democrats lost more than 60 seats .
If Democrats had added five to 10 seats this year , they could have survived a 20-seat loss in the midterms .
Instead , Republicans will probably need to win fewer than 10 seats to gain a slender majority @ @ @ @ @ @ @ , Republicans could very well benefit from the new district lines that will be drawn ahead of the 2022 midterm elections .
The GOP is set to fully control redistricting for about two-fifths of all House seats , while Democrats will only hold sway over one-tenth of them , with the remaining seats are in states with divided governments or where redistricting is done by a commission system .
The Republican line-drawing advantage should help the party draw favorable maps that could help the GOP win more seats than we might otherwise expect @

2020 was not supposed to be a good year for House Republicans. The polls pointed to a Democratic-leaning electoral environment, Democratic candidates were outraising Republicans in most competitive seats, and the GOP had to defend a host of open seats that Republican incumbents had abandoned.
Yet, contrary to expectations, including their own, Republicans managed to gain seats even as the Democrats held onto their majority. Votes are still being counted, but based on contests projected by ABC News, Republicans have netted six seats so far, and they may still flip a few more.
But top-line numbers about seats gained and lost can only tell us so much. Let’s look at some of the major takeaways from the 2020 House elections.
Where the rest of the 2020 races stand | FiveThirtyEight Politics Podcast
Republicans outperformed expectations
Coming into the 2020 election, FiveThirtyEight’s forecast only gave Republicans about a 1 in 6 shot of picking up six or more seats, and if the GOP gains more as-yet-uncalled seats in the coming days, the party’s haul could become even more unlikely.
It’s not just the flipped seats that are impressive, though. Not a single Republican incumbent has lost in the races where we know the outcomes thus far. Among the outstanding contests, only California Rep. Mike Garcia, who won a May special election, appears to be in danger of losing.
[Related: The Polls Weren’t Great. But That’s Pretty Normal.]
Open-seat races have also been friendly to Republicans, despite the large number of GOP incumbents who retired or left office ahead of the 2020 election. The GOP had to defend 35 open seats compared to the Democrats’ 13, but of the 33 Republican-held open seats projected so far, only three have gone for the Democrats. And two of those Democratic wins were in North Carolina seats that the GOP had written off after a court-ordered redistricting made the districts heavily Democratic.
GOP women made big gains
While the majority of the Republican caucus will still be men come 2021, there will be far more Republican women in Congress than there were this year. So far, it looks like at least 26 GOP women will be in the House next year, surpassing the record of 25 from the 109th Congress. That’s thanks in part to the record number of non-incumbent Republican women — 15 — who’ve won House contests. And it’s also because of how well Republican women did in tight races. The table below shows the Republican women who ran in Democratic-held House districts that were at least potentially competitive, according to FiveThirtyEight’s forecast. As of this writing, seven of them have won.
GOP women have flipped several Democratic seats Republican women running for potentially competitive Democratic-held House seats and the status of their race as of 4:30 p.m Eastern on Nov. 11 District Candidate Current Margin Projected GOP flip MN-07 Michelle Fischbach R+13.2 ✓ ✓ NM-02 Yvette Herrell R+7.8 ✓ ✓ OK-05 Stephanie Bice R+4.1 ✓ ✓ FL-27 Maria Elvira Salazar R+2.7 ✓ ✓ IA-01 Ashley Hinson R+2.6 ✓ ✓ CA-48 Michelle Steel R+2.0 ✓ ✓ SC-01 Nancy Mace R+1.3 ✓ ✓ NY-11 Nicole Malliotakis R+15.8 NY-22 Claudia Tenney R+11.0 CA-39 Young Kim R+1.3 IA-02 Mariannette Miller-Meeks 0 NY-18 Chele Farley D+3.0 TX-15 Monica De La Cruz-Hernandez D+2.9 ✓ AZ-01 Tiffany Shedd D+3.4 ✓ PA-07 Lisa Scheller D+3.7 ✓ IL-17 Esther Joy King D+3.8 ✓ TX-32 Genevieve Collins D+6.0 ✓ FL-13 Anna Paulina Luna D+6.1 ✓ IL-06 Jeanne Ives D+6.6 ✓ OR-05 Amy Ryan Courser D+6.7 ✓ OH-13 Christina Hagan D+7.5 ✓ NC-01 Sandy Smith D+8.3 ✓ GA-06 Karen Handel D+9.2 ✓ KS-03 Amanda Adkins D+9.7 ✓ NJ-11 Rosemary Becchi D+9.8 ✓ CA-03 Tamika Hamilton D+10.9 ✓ PA-04 Kathy Barnette D+18.8 ✓ CA-36 Erin Cruz D+22.1 ✓ Results are unofficial. Races are counted as projected only if the projection comes from ABC News. Excludes races in which the Republican candidate has either a less than 1 in 100 chance or greater than 99 in 100 chance of winning. Source: ABC News
It’s not all bad news for Democrats
While it was unquestionably a good night for Republicans, Democrats still held onto most of the seats they won in 2018 and will continue to be the majority party in the House. That’s in part because they retained most of the suburban districts they picked up in 2018.
Of the 233 seats that Democrats held coming into the election, 186 of them were in districts that were predominantly or partly suburban in nature, according to density categorizations by Bloomberg’s CityLab. (This figure excludes North Carolina because CityLab has not updated its density data to account for North Carolina’s court-ordered redistricting in 2019.) Thus far, Democrats have lost seven of those seats, but they captured one GOP-held suburban seat around Atlanta. And thanks to redistricting, they’ve also won two formerly Republican seats around Greensboro and Raleigh in North Carolina, which reflect the party’s strength in more populous areas. (ABC News hasn’t projected a winner yet in 11 suburban races — eight Democratic-held districts and three Republican-held districts.)
Because of their relative success in the suburbs, Democrats kept many seats in places President Trump won in 2016. Coming into the election, Democrats held 30 seats in districts Trump carried in 2016, and they would’ve lost their majority if they’d lost more than half of them (assuming they didn’t offset the losses by gaining seats elsewhere). But they’ve won 18 of them so far and picked up one from the GOP (Georgia’s 7th Congressional District). In fact, more than half of Republicans’ gains have come in seats representing places that Trump won by a pretty sizable margin in 2016. We’ll have to wait a bit before data can tell us how congressional districts voted in 2020, but for now it seems many Republican gains were made by picking off the lowest-hanging fruit.
Republicans are well positioned to take the House in 2022
Although we don’t yet know the winners of some House races, we can already look ahead to the 2022 midterms and see a fairly straightforward path for the GOP to capture the House. Midterm elections historically go well for the party that’s not in the White House, and the out-of-power party is especially likely to do well in the House, since every seat is up for election (the Senate is a more complicated story).
Since the end of World War II, the presidential party has lost an average of 27 House seats in midterm elections, as the chart below shows. No matter how many seats Democrats end up with after 2020’s election — at this point, they will probably end up somewhere in the low 220s — a loss of that magnitude would easily be enough for Republicans to retake the House.
The recent history of midterms in a Democratic president’s first term seems especially promising for the GOP, too. Following Bill Clinton’s election in 1992, Democrats lost more than 50 seats in 1994, and after Barack Obama won the presidency in 2008, Democrats lost more than 60 seats.
If Democrats had added five to 10 seats this year, they could have survived a 20-seat loss in the midterms. Instead, Republicans will probably need to win fewer than 10 seats to gain a slender majority in 2022.
[Related: Politics Podcast: Why Polls Were Off In 2020, And Why They Weren’t That Bad]
On top of this, Republicans could very well benefit from the new district lines that will be drawn ahead of the 2022 midterm elections. The GOP is set to fully control redistricting for about two-fifths of all House seats, while Democrats will only hold sway over one-tenth of them, with the remaining seats are in states with divided governments or where redistricting is done by a commission system. The Republican line-drawing advantage should help the party draw favorable maps that could help the GOP win more seats than we might otherwise expect.
Biden is set to be president. What comes next? | FiveThirtyEight Politics Podcast
CORRECTION (Feb. 18, 2021, 2:52 p.m.): The chart in this article originally showed Democrats losing four House seats in the 1998 midterms; they actually gained four seats.


fivethirthyeight--2020-11-12--Where We Saw Red And Blue Mirages On Election Night

Election night 2020 was an election night like no other — and not just because the “ night ” ended up lasting four days .
This election was also unique because of how Americans voted — a record number voted early , either in person or by mail .
Because many states report absentee and Election Day ballots at different times , and absentee voters are disproportionately likely to be Democrats while Election Day voters are disproportionately likely to be Republicans , that made it tricky to follow the vote in real time .
The candidate who led a given @ @ @ @ @ @ @ always the one who eventually won it , leading many real-time observers to conclude the presidential race was closer than it actually was .
In some states like North Carolina and Ohio , that meant the initial vote totals included a disproportionate number of Biden votes relative to the final results ; in others , like Michigan and Virginia , the initial totals included a disproportionate number of Trump votes .
And in still others , Trump began to look stronger as more votes were counted on election night , but it became @ @ @ @ @ @ @ the last few mail-in ballots were counted in the ensuing days .
You can see this in the map below , which shows you where the reported vote totals stood for each candidate 90 minutes , 12 hours and 72 hours after the last polls were scheduled to close in each state .
Let ’ s take a closer look at the states where Trump gained ground as more votes were counted — a phenomenon sometimes referred to as a “ red shift.
” For example , 90 minutes after polls closed in @ @ @ @ @ @ @ Biden looked competitive in these three states — he even led in North Carolina and Ohio .
But that changed as officials reported more results , and Trump wound up carrying all three states .
It wasn ’ t just battleground states where this happened either .
Deeply Republican states like Kentucky experienced this same “ red shift ” in their vote margins because of the order in which votes happened to be reported — it just didn ’ t affect who won them because they were already so Republican-leaning .
In other @ @ @ @ @ @ @ opposite direction — the appearance of an early lead for Trump was eventually erased as more votes for Biden were counted .
Sometimes this happened because the state was not allowed to process its absentee ballots before the week of the election and therefore couldn ’ t get a head start on its massive volume of absentee ballots ( see Michigan ) .
In other instances , the state only required absentee ballots to be postmarked , not received , by Election Day and was still accepting and counting ballots for a few @ @ @ @ @ @ @ And sometimes , the state was just slow to finish counting all its absentee ballots ( see Georgia ) .
Either way , this “ blue shift ” in the vote count often took several days , making it hard to see who was really ahead if you weren ’ t familiar with the ins and outs of vote-counting .
And finally , in some states , it was more of a mix .
The topline results zigged toward Republicans , then zagged toward Democrats as more votes were counted .
For example @ @ @ @ @ @ @ good for Biden , but most of the votes counted over the next several hours were for Trump , and by Wednesday morning , Trump was ahead .
However , the state spent the next several days counting absentee ballots , which were favorable for Biden .
As it turned out , there were enough absentee ballots outstanding for the Democrat to eventually take the lead at 9 a.m. on Friday morning .
And Pennsylvania was , of course , the key state that eventually handed Biden the presidency .
In sum , @ @ @ @ @ @ @ each state and when made for a roller coaster of an election week , and even produced accusations of fraud .
But there was nothing fishy going on ; no additional ballots were being cast after Election Day to influence the result .
It was just the slow wheels of democracy turning .
Indeed , given how the coronavirus pandemic threw our elections into turmoil with only eight months to prepare for the general election , it ’ s actually quite impressive that , the timing of the results notwithstanding , the election @ @ @ @ @ @ @

Election night 2020 was an election night like no other — and not just because the “night” ended up lasting four days. This election was also unique because of how Americans voted — a record number voted early, either in person or by mail. Because many states report absentee and Election Day ballots at different times, and absentee voters are disproportionately likely to be Democrats while Election Day voters are disproportionately likely to be Republicans, that made it tricky to follow the vote in real time. The candidate who led a given state on Tuesday night wasn’t always the one who eventually won it, leading many real-time observers to conclude the presidential race was closer than it actually was.
How Joe Biden and Kamala Harris won a historic election | FiveThirtyEight
In some states like North Carolina and Ohio, that meant the initial vote totals included a disproportionate number of Biden votes relative to the final results; in others, like Michigan and Virginia, the initial totals included a disproportionate number of Trump votes. And in still others, Trump began to look stronger as more votes were counted on election night, but it became clear that Biden received more votes as the last few mail-in ballots were counted in the ensuing days.
You can see this in the map below, which shows you where the reported vote totals stood for each candidate 90 minutes, 12 hours and 72 hours after the last polls were scheduled to close in each state.
Let’s take a closer look at the states where Trump gained ground as more votes were counted — a phenomenon sometimes referred to as a “red shift.” For example, 90 minutes after polls closed in Iowa, North Carolina and Ohio, Biden looked competitive in these three states — he even led in North Carolina and Ohio. But that changed as officials reported more results, and Trump wound up carrying all three states. It wasn’t just battleground states where this happened either. Deeply Republican states like Kentucky experienced this same “red shift” in their vote margins because of the order in which votes happened to be reported — it just didn’t affect who won them because they were already so Republican-leaning.
In other states, the margins moved in the opposite direction — the appearance of an early lead for Trump was eventually erased as more votes for Biden were counted. Sometimes this happened because the state was not allowed to process its absentee ballots before the week of the election and therefore couldn’t get a head start on its massive volume of absentee ballots (see Michigan). In other instances, the state only required absentee ballots to be postmarked, not received, by Election Day and was still accepting and counting ballots for a few days after (see Virginia). And sometimes, the state was just slow to finish counting all its absentee ballots (see Georgia). Either way, this “blue shift” in the vote count often took several days, making it hard to see who was really ahead if you weren’t familiar with the ins and outs of vote-counting.
And finally, in some states, it was more of a mix. The topline results zigged toward Republicans, then zagged toward Democrats as more votes were counted. For example, Pennsylvania started off election night looking good for Biden, but most of the votes counted over the next several hours were for Trump, and by Wednesday morning, Trump was ahead. However, the state spent the next several days counting absentee ballots, which were favorable for Biden.
As it turned out, there were enough absentee ballots outstanding for the Democrat to eventually take the lead at 9 a.m. on Friday morning. And Pennsylvania was, of course, the key state that eventually handed Biden the presidency.
In sum, the changes in who was leading in each state and when made for a roller coaster of an election week, and even produced accusations of fraud. But there was nothing fishy going on; no additional ballots were being cast after Election Day to influence the result. It was just the slow wheels of democracy turning. Indeed, given how the coronavirus pandemic threw our elections into turmoil with only eight months to prepare for the general election, it’s actually quite impressive that, the timing of the results notwithstanding, the election largely went off without a hitch.
Where the rest of the 2020 races stand | FiveThirtyEight Politics Podcast


fivethirthyeight--2020-11-12--How The Pandemic Might Have Affected The Polls In 2020

In this installment of Model Talk on the FiveThirtyEight Politics podcast , editor-in-chief Nate Silver and Galen Druke discuss the @ @ @ @ @ election and why it may have occurred .

How The Pandemic Might Have Affected The Polls In 2020
In this installment of Model Talk on the FiveThirtyEight Politics podcast, editor-in-chief Nate Silver and Galen Druke discuss the polling error in the 2020 election and why it may have occurred.
Related: What Blue And Red ‘Shifts’ Looked Like In Every State


fivethirthyeight--2020-11-12--Politics Podcast: Why Polls Were Off In 2020, And Why They Weren’t That Bad

The presidential polls were off by somewhere in the range of 4 percentage points , which is notably larger than @ @ @ @ @ 2.3 points .
In this installment of Model Talk on the FiveThirtyEight Politics podcast , @ @ @ @ @ Druke explain why a polling error of even 4 points isn ’ t that unexpected @ @ @ @ @ error occurred , and discuss the usefulness of polling and modeling going forward .

The presidential polls were off by somewhere in the range of 4 percentage points, which is notably larger than the recent average error of 2.3 points. In this installment of Model Talk on the FiveThirtyEight Politics podcast, editor-in-chief Nate Silver and Galen Druke explain why a polling error of even 4 points isn’t that unexpected, offer reasons why the error occurred, and discuss the usefulness of polling and modeling going forward.
Related: The Polls Weren’t Great. But That’s Pretty Normal.