fivethirthyeight--2020-09-10--Coronavirus Models Were Always About More Than Flattening The Curve

Hey , remember March ?
It was a simpler time .
Everyone had a loaf of fresh sourdough .
“ Animal Crossing ” was all the rage .
And across this great nation , Americans were breathlessly hanging on the latest epidemiological model updates .
But that was then .
Now we don ’ t need complicated math to tell us that 190,000 Americans have died from the novel coronavirus , with no end in the sight .
Where once public debates about the reliability of one model versus another could command front-page headlines , today updated projections barely break @ @ @ @ @ @ @ goes on , the deaths continue to mount , but somehow public concern about predicting what will happen with the case count and death toll seems to have drifted off , like an aerosol droplet on a summer breeze .
But the models are still there , quietly updating .
Most of them agree we ’ ll have more than 200,000 deaths by mid September .
As the fear and restlessness of the early pandemic gives way to the steady ache of constant vigilance — and as we become increasingly resigned to death @ @ @ @ @ @ @ to predict how many people will succumb by a certain date ?
Experts told me “ yes.
” But they also told me “ no.
” And “ sort of , it depends.
” Turns out , it ’ s not only difficult to make a good model of a pandemic , it ’ s also pretty hard to use those models effectively .
What the models are telling us now — what they ’ ve always been telling us — is not , necessarily , the job we asked them to do @ @ @ @ @ @ @ Models are still factoring into officials ’ decision-making , experts told me , especially the models that combine information about how a disease works with demographic and behavioral data .
( These are called “ mechanistic models ” in forecaster lingo . )
These models are especially useful for playing out “ what-if ” scenarios — if we intervene in this way , would the outcome be better or worse than if we intervene in that way ?
The Imperial College model you heard about a bunch back in the spring is a @ @ @ @ @ @ @ The other kind of model is a statistical one , which uses data on things like death counts and hospitalizations over time to forecast how many future deaths are likely under current conditions .
The Institute for Health Metrics and Evaluation ( IHME ) model , once the favored model of the Trump Administration , works this way .
In the spring , attention was largely focused on statistical models and what they could tell us about whether the pandemic would truly be a big deal in our lives .
Now , with @ @ @ @ @ @ @ you very much ) , researchers are primarily using mechanistic models to understand the past ( like , say , what might have been behind various dips and surges in transmission ) and help make decisions about what to do next ( for example , what guidelines should a university follow to safely reopen classes ) .
That there is a difference between the two types of models , and that they do different things , has largely been lost on the general public , said William Hanage , a professor of epidemiology @ @ @ @ @ @ @ the way it feels like models have stopped being important , he said , even though they haven ’ t .
The focus just turned to different goals .
Currently , states are using models to explore potential outcomes of opening certain kinds of businesses , said Carter Price , a senior mathematician at the Rand Corporation .
Universities use them to decide who should be getting tested for COVID-19 and how often .
Models can also help answer questions like “ Who should be at the top of the list for receiving @ @ @ @ @ @ @ .
Statistical death count projections are still being done , though experts told me they ’ re most accurate and useful in the short term — think two to four weeks out .
But the answer to the question of whether models still matter is really yes and no , said John Drake , director of the Center for the Ecology of Infectious Diseases at the University of Georgia and a past FiveThirtyEight contributor .
And that ’ s largely because of political choices .
It ’ s sort of like the “ @ @ @ @ @ @ @ ” question : If a model tells you something bad is likely to happen and politicians ignore it , does the model really matter ?
The way COVID-19 has become politicized — with partisan divides on a broad variety of issues , including mask wearing , stay-at-home orders and whether the pandemic itself is a myth — has meant some governments have made decisions that fly in the face of empiricism rather than being informed by it .
Drake ’ s home state of Georgia , for example , lifted its stay-at-home-order at @ @ @ @ @ @ @ stay closed for another two months .
And then there ’ s the other , less-obvious problem in the clash between models and politics — data collection .
“ The data are appalling , ” Hanage said .
What he means by that is that the United States never established a consistent , sustained , national system to test residents for COVID-19 and trace who was in contact with people who tested positive .
Testing rates go up and down .
The turnaround for results lags and speeds up and lags again .
@ @ @ @ @ @ @ — even in different parts of the same state — and at different times .
And centralized data collection and analysis … just hasn ’ t happened .
As a result , researchers don ’ t have good , reliable data on how the coronavirus spreads — which is fairly important if you ’ re trying to put together a model to show you ways to prevent the spread .
Those are political choices .
Policy makers could have built a robust testing system .
They could have implemented rigorous contact tracing .
@ @ @ @ @ @ @ several experts told me that they believed the country ’ s springtime obsession with statistical modeling was part of why .
“ The early focus on modeling sucked a lot of air out of things that should have been focused on … less sexy things like data-collection issues , ” Engler said .
Without that data , ironically , the models have suffered .
One thing Drake would love to know is how effective lockdowns were .
We know they were effective , he told me .
You can see that observationally just @ @ @ @ @ @ @ numbers when lockdowns were implemented and removed .
But in the midst of lockdown , a lot of other interventions also came into play — face masks , plexiglass screens at the grocery store , contactless deliveries , and more .
How much of the effectiveness of lockdown was thanks to the lockdown and how much was thanks to those other things ?
“ That ’ s an exquisite question for modeling to answer , ” Drake said .
“ But we can ’ t do it because of our inconsistent data collection.
@ @ @ @ @ @ @ flashy promise of models , and then we made those models less useful by not collecting the boring stuff they needed to operate effectively .
Scientists and politicians began this pandemic with almost no data on this coronavirus .
The models were originally based on data from previous outbreaks of its cousin viruses , SARS and MERS , but scientists assumed that politicians would quickly muster the forces of public health to collect detailed , COVID-19-specific data .
Unfortunately , experts said , scientists really weren ’ t ready for their assumptions about @ @ @ @ @ @ @ dead wrong .
And that ’ s a problem that carries over to the models .
All models are based on assumptions , and some of our assumptions about how people would behave during the COVID-19 pandemic weren ’ t correct .
For example , early on , model designs were often based in part on the assumption that the rise and fall of cases in the U.S. would match the curves we ’ d seen in Wuhan , China , and the Lombardy region of Italy .
Scientists assumed that curve was @ @ @ @ @ @ @ it wasn ’ t .
Instead , Hanage said , the neat curve turned out to reflect extreme lockdowns and stringent travel restrictions — things the United States was not prepared to choose for itself .
And so our curves have looked different , and the models were , at first , wrong .
And those wrong assumptions affect more than this one pandemic .
The idea that travel restrictions and population-wide lockdowns don ’ t work was baked into existing epidemiological models before COVID-19 came along , said Alex Siegenfeld , a @ @ @ @ @ @ @ at MIT .
The assumption was that such measures would always be leaky and impossible to maintain — an idea I wrote about myself back in February .
But that has proven to only be correct with some people , some of the time .
None of this is to say that modeling COVID-19 is pointless .
It ’ s just that using a model effectively is sometimes harder than simply doing math .
A model can seem relatively easy to put together , so easy that it ’ s not even much @ @ @ @ @ @ @ turn out to be really , really complicated .
And even seven months later , that ’ s a lesson we ’ re still struggling to learn .

Hey, remember March? It was a simpler time. Everyone had a loaf of fresh sourdough. “Animal Crossing” was all the rage. And across this great nation, Americans were breathlessly hanging on the latest epidemiological model updates.
But that was then. Now we don’t need complicated math to tell us that 190,000 Americans have died from the novel coronavirus, with no end in the sight.
Where once public debates about the reliability of one model versus another could command front-page headlines, today updated projections barely break into the news cycle. The virus goes on, the deaths continue to mount, but somehow public concern about predicting what will happen with the case count and death toll seems to have drifted off, like an aerosol droplet on a summer breeze. But the models are still there, quietly updating. Most of them agree we’ll have more than 200,000 deaths by mid September.
As the fear and restlessness of the early pandemic gives way to the steady ache of constant vigilance — and as we become increasingly resigned to death — is there still value in efforts to predict how many people will succumb by a certain date?
Experts told me “yes.” But they also told me “no.” And “sort of, it depends.” Turns out, it’s not only difficult to make a good model of a pandemic, it’s also pretty hard to use those models effectively. What the models are telling us now — what they’ve always been telling us — is not, necessarily, the job we asked them to do at the beginning of this pandemic.
Models are still factoring into officials’ decision-making, experts told me, especially the models that combine information about how a disease works with demographic and behavioral data. (These are called “mechanistic models” in forecaster lingo.) These models are especially useful for playing out “what-if” scenarios — if we intervene in this way, would the outcome be better or worse than if we intervene in that way? The Imperial College model you heard about a bunch back in the spring is a good example of a mechanistic model.
The other kind of model is a statistical one, which uses data on things like death counts and hospitalizations over time to forecast how many future deaths are likely under current conditions. The Institute for Health Metrics and Evaluation (IHME) model, once the favored model of the Trump Administration, works this way.
In the spring, attention was largely focused on statistical models and what they could tell us about whether the pandemic would truly be a big deal in our lives. Now, with that question pretty solidly answered (thank you very much), researchers are primarily using mechanistic models to understand the past (like, say, what might have been behind various dips and surges in transmission) and help make decisions about what to do next (for example, what guidelines should a university follow to safely reopen classes).
That there is a difference between the two types of models, and that they do different things, has largely been lost on the general public, said William Hanage, a professor of epidemiology at Harvard. That helps account for the way it feels like models have stopped being important, he said, even though they haven’t. The focus just turned to different goals.
Currently, states are using models to explore potential outcomes of opening certain kinds of businesses, said Carter Price, a senior mathematician at the Rand Corporation. Universities use them to decide who should be getting tested for COVID-19 and how often. Models can also help answer questions like “Who should be at the top of the list for receiving a coronavirus vaccine?” Hanage said. Statistical death count projections are still being done, though experts told me they’re most accurate and useful in the short term — think two to four weeks out.
But the answer to the question of whether models still matter is really yes and no, said John Drake, director of the Center for the Ecology of Infectious Diseases at the University of Georgia and a past FiveThirtyEight contributor. And that’s largely because of political choices.
It’s sort of like the “if a tree falls in the forest” question: If a model tells you something bad is likely to happen and politicians ignore it, does the model really matter?
The way COVID-19 has become politicized — with partisan divides on a broad variety of issues, including mask wearing, stay-at-home orders and whether the pandemic itself is a myth — has meant some governments have made decisions that fly in the face of empiricism rather than being informed by it. Drake’s home state of Georgia, for example, lifted its stay-at-home-order at a time when models suggested it should stay closed for another two months.
And then there’s the other, less-obvious problem in the clash between models and politics — data collection. “The data are appalling,” Hanage said. What he means by that is that the United States never established a consistent, sustained, national system to test residents for COVID-19 and trace who was in contact with people who tested positive. Testing rates go up and down. The turnaround for results lags and speeds up and lags again. Both factors are different in different states — even in different parts of the same state — and at different times. And centralized data collection and analysis … just hasn’t happened. As a result, researchers don’t have good, reliable data on how the coronavirus spreads — which is fairly important if you’re trying to put together a model to show you ways to prevent the spread.
Those are political choices. Policy makers could have built a robust testing system. They could have implemented rigorous contact tracing. But they didn’t. And several experts told me that they believed the country’s springtime obsession with statistical modeling was part of why. “The early focus on modeling sucked a lot of air out of things that should have been focused on … less sexy things like data-collection issues,” said Alex Engler, a Rubenstein fellow specializing in governance studies at The Brookings Institution.
Without that data, ironically, the models have suffered. One thing Drake would love to know is how effective lockdowns were. We know they were effective, he told me. You can see that observationally just by looking at what happened with case numbers when lockdowns were implemented and removed. But in the midst of lockdown, a lot of other interventions also came into play — face masks, plexiglass screens at the grocery store, contactless deliveries, and more. How much of the effectiveness of lockdown was thanks to the lockdown and how much was thanks to those other things? “That’s an exquisite question for modeling to answer,” Drake said. “But we can’t do it because of our inconsistent data collection.”
We got hung up on the flashy promise of models, and then we made those models less useful by not collecting the boring stuff they needed to operate effectively. Scientists and politicians began this pandemic with almost no data on this coronavirus. The models were originally based on data from previous outbreaks of its cousin viruses, SARS and MERS, but scientists assumed that politicians would quickly muster the forces of public health to collect detailed, COVID-19-specific data.
Unfortunately, experts said, scientists really weren’t ready for their assumptions about governments — and people — to be dead wrong. And that’s a problem that carries over to the models.
All models are based on assumptions, and some of our assumptions about how people would behave during the COVID-19 pandemic weren’t correct. For example, early on, model designs were often based in part on the assumption that the rise and fall of cases in the U.S. would match the curves we’d seen in Wuhan, China, and the Lombardy region of Italy. Scientists assumed that curve was something intrinsic to the virus. But it wasn’t. Instead, Hanage said, the neat curve turned out to reflect extreme lockdowns and stringent travel restrictions — things the United States was not prepared to choose for itself. And so our curves have looked different, and the models were, at first, wrong.
And those wrong assumptions affect more than this one pandemic. The idea that travel restrictions and population-wide lockdowns don’t work was baked into existing epidemiological models before COVID-19 came along, said Alex Siegenfeld, a Ph.D. student studying modeling and social behavior at MIT. The assumption was that such measures would always be leaky and impossible to maintain — an idea I wrote about myself back in February. But that has proven to only be correct with some people, some of the time.
None of this is to say that modeling COVID-19 is pointless. It’s just that using a model effectively is sometimes harder than simply doing math. A model can seem relatively easy to put together, so easy that it’s not even much of an intellectual challenge. But people turn out to be really, really complicated. And even seven months later, that’s a lesson we’re still struggling to learn.


fivethirthyeight--2020-09-10--Why Trump Might Be Scaring Off Older Voters

“ Most of the activities you normally have here in adult Disney World are closed down , ” Bryan Casey told me recently by phone from The Villages , Florida , one of the country ’ s largest retirement communities .
COVID-19 has dulled the normally vibrant social lives of Villages residents , who typically spend their days on eternal summer vacation .
The town squares that anchor the sprawling development , usually filled with drinking and dancing and music , have been shut down .
“ Open The Squares ?
Look At What Is Happening At The Colleges , @ @ @ @ @ @ @ letter to the editor at Villages News .
In Sumter County , where The Villages is situated , Donald Trump won 68.3 percent of the vote in 2016 , and no other county in Florida had a higher turnout .
But , Casey — the communications director of the Villages Democratic Club — said , “ I have a couple of friends I know who voted for Trump in 2016 who say that they won ’ t do that this time.
” But few would be willing to admit that publicly .
“ @ @ @ @ @ @ @ to understand that , ” he said .
If that ’ s the case , Casey ’ s friends wouldn ’ t be alone .
The pandemic has killed some 190,000 Americans , and 8 in 10 of the deaths reported have been among those 65 or over .
President Trump ’ s delayed and fractured response to the outbreak appears to have reshaped the political dynamics for older Americans .
Four years ago , he won voters 65 or over by a margin of 13.3 percentage points .
But looking at an @ @ @ @ @ @ @ polls , voters age 65 or over favored Biden to Trump by 49.5 percent to 45.7 percent .
Who are the older voters abandoning Trump ?
A look at the polls from 2016 to 2020 shows movement mostly among white voters .
But why are they increasingly abandoning him ?
There ’ s the pandemic , of course , but I ’ m not sure that explains everything .
An average of six national polls from May — before the beginning of widespread protests against police violence that would come to dominate the @ @ @ @ @ @ @ and Biden tied among voters 65 or over .
Perhaps this other national crisis is driving away older Americans .
Trump ’ s inflammatory rhetoric about race and crime could be alienating them as well .
The Villages is perhaps best known , of late , for a viral video of a pro-Trump golf-cart parade ( these parades are among the primary modes of political expression in The Villages , since golf carts abound and lawn signs are prohibited ) .
In the clip , first retweeted by the president and later deleted @ @ @ @ @ @ @ be heard shouting “ white power ” at a group of counterprotesters .
Despite these provocative pro-Trump images coming out of Florida , the shift toward Biden is evident in the state , a key to winning the Electoral College .
A late August Quinnipiac University poll in Florida showed Biden leading Trump among older voters , by 54 percent to 44 percent and another late August poll of Florida voters , this one by Public Policy Polling , showed Biden in the lead among the same group , by 52 percent to @ @ @ @ @ @ @ to the sentiments of older Florida voters at around this time four years ago .
An early September 2016 CBS News poll found Trump leading Hillary Clinton by 8 points among Florida voters age 65 or over , while a CNN/ORC International poll found him with an even bigger , 15-point , lead .
And sure enough , on Election Day 2016 , exit polls indicated that Trump won this demographic group in Florida by 57 percent to Clinton ’ s 40 percent .
I asked Jerry Prince , the president of the @ @ @ @ @ @ @ of the trend away from Trump among older voters .
“ I think it is false and propaganda by the media and Democrats , ” he wrote in an email .
“ The seniors here have worked hard , retired and remember what Law and Order is and know that what is happening in America today is being denied and pushed by the Democrats .
Again , I think this is false and without some true numbers I will continue to believe it is false.
” A recent Quinnipiac University poll conducted following @ @ @ @ @ @ @ discernible theme that “ violence in the largely Black cities of America makes everyone , including white suburbanites , unsafe ” — showed Biden leading by 10 points overall .
Voters age 65 or over said they supported Biden over Trump by 50 percent to 46 percent , and when asked if Trump made them feel “ more safe ” or “ less safe , ” 46 percent said that Trump made them feel less safe ; 44 percent said the opposite .
In attempting to speak what he thinks is the language @ @ @ @ @ @ @ — racially tinged talk about the destruction of the suburbs , for instance — Trump might actually be shooting himself in the foot .
Even as white Americans ’ support for the Black Lives Matter movement has waned over the course of the summer , this doesn ’ t appear to have had a significant effect on Biden ’ s lead .
Voters seem to separate him from the movement even as Trump has tried to tie it to him .
( My colleague Perry Bacon Jr. took a deeper look at this @ @ @ @ @ @ @ suburbanites , the sort with culturally conservative values who might look askance at the present-day Democratic party , also matured in an America that harshly stigmatized overt racism .
These voters might share Trump ’ s views on race but be turned off by the way he expresses them .
Ronald Reagan , the original Republican disrupter of the political status quo , was good at talking to these voters .
He ’ s famous for popularizing the racist trope of the “ welfare queen , ” for instance , a way to @ @ @ @ @ @ @ the guise of people abusing a government benefit .
His administration ’ s public-health stance of “ just say no ” to drugs was largely geared toward suburban voters , a softer way to talk about substance abuse , while the Anti-Drug Abuse Act of 1986 promoted harsher mandatory minimum sentences for possession of crack , a drug largely associated with Black inner-city populations , compared with the punishments for possession of powder cocaine .
Trump ’ s rhetoric focused on the suburban American idyll might , ironically , be making the people @ @ @ @ @ @ @ these nerve-wracking times .
He might have been better off sticking with the pandemic — cases appear to be flattening out ever so slightly , though thousands of new cases are reported daily — than with the red meat of racial politics .

“Most of the activities you normally have here in adult Disney World are closed down,” Bryan Casey told me recently by phone from The Villages, Florida, one of the country’s largest retirement communities. COVID-19 has dulled the normally vibrant social lives of Villages residents, who typically spend their days on eternal summer vacation. The town squares that anchor the sprawling development, usually filled with drinking and dancing and music, have been shut down. “Open The Squares? Look At What Is Happening At The Colleges,” read the headline on a recent letter to the editor at Villages News.
In Sumter County, where The Villages is situated, Donald Trump won 68.3 percent of the vote in 2016, and no other county in Florida had a higher turnout. But, Casey — the communications director of the Villages Democratic Club — said, “I have a couple of friends I know who voted for Trump in 2016 who say that they won’t do that this time.” But few would be willing to admit that publicly. “You’ve got to live here to understand that,” he said.
If that’s the case, Casey’s friends wouldn’t be alone. The pandemic has killed some 190,000 Americans, and 8 in 10 of the deaths reported have been among those 65 or over. President Trump’s delayed and fractured response to the outbreak appears to have reshaped the political dynamics for older Americans. Four years ago, he won voters 65 or over by a margin of 13.3 percentage points. But looking at an average of the nine most recent national polls, voters age 65 or over favored Biden to Trump by 49.5 percent to 45.7 percent.
Who are the older voters abandoning Trump? A look at the polls from 2016 to 2020 shows movement mostly among white voters. But why are they increasingly abandoning him? There’s the pandemic, of course, but I’m not sure that explains everything. An average of six national polls from May — before the beginning of widespread protests against police violence that would come to dominate the news over the summer — showed Trump and Biden tied among voters 65 or over. Perhaps this other national crisis is driving away older Americans. Trump’s inflammatory rhetoric about race and crime could be alienating them as well.
The Villages is perhaps best known, of late, for a viral video of a pro-Trump golf-cart parade (these parades are among the primary modes of political expression in The Villages, since golf carts abound and lawn signs are prohibited). In the clip, first retweeted by the president and later deleted by him, a Trump supporter can be heard shouting “white power” at a group of counterprotesters.
Despite these provocative pro-Trump images coming out of Florida, the shift toward Biden is evident in the state, a key to winning the Electoral College. A late August Quinnipiac University poll in Florida showed Biden leading Trump among older voters, by 54 percent to 44 percent and another late August poll of Florida voters, this one by Public Policy Polling, showed Biden in the lead among the same group, by 52 percent to 47 percent. This stands in contrast to the sentiments of older Florida voters at around this time four years ago. An early September 2016 CBS News poll found Trump leading Hillary Clinton by 8 points among Florida voters age 65 or over, while a CNN/ORC International poll found him with an even bigger, 15-point, lead. And sure enough, on Election Day 2016, exit polls indicated that Trump won this demographic group in Florida by 57 percent to Clinton’s 40 percent.
I asked Jerry Prince, the president of the Villages Republican Club, what he made of the trend away from Trump among older voters. “I think it is false and propaganda by the media and Democrats,” he wrote in an email. “The seniors here have worked hard, retired and remember what Law and Order is and know that what is happening in America today is being denied and pushed by the Democrats. Again, I think this is false and without some true numbers I will continue to believe it is false.”
A recent Quinnipiac University poll conducted following the RNC — an event with the discernible theme that “violence in the largely Black cities of America makes everyone, including white suburbanites, unsafe” — showed Biden leading by 10 points overall. Voters age 65 or over said they supported Biden over Trump by 50 percent to 46 percent, and when asked if Trump made them feel “more safe” or “less safe,” 46 percent said that Trump made them feel less safe; 44 percent said the opposite.
In attempting to speak what he thinks is the language of an older generation of white Americans — racially tinged talk about the destruction of the suburbs, for instance — Trump might actually be shooting himself in the foot. Even as white Americans’ support for the Black Lives Matter movement has waned over the course of the summer, this doesn’t appear to have had a significant effect on Biden’s lead. Voters seem to separate him from the movement even as Trump has tried to tie it to him. (My colleague Perry Bacon Jr. took a deeper look at this issue last month.)
Older white suburbanites, the sort with culturally conservative values who might look askance at the present-day Democratic party, also matured in an America that harshly stigmatized overt racism. These voters might share Trump’s views on race but be turned off by the way he expresses them. Ronald Reagan, the original Republican disrupter of the political status quo, was good at talking to these voters. He’s famous for popularizing the racist trope of the “welfare queen,” for instance, a way to talk about Black Americans in cities under the guise of people abusing a government benefit. His administration’s public-health stance of “just say no” to drugs was largely geared toward suburban voters, a softer way to talk about substance abuse, while the Anti-Drug Abuse Act of 1986 promoted harsher mandatory minimum sentences for possession of crack, a drug largely associated with Black inner-city populations, compared with the punishments for possession of powder cocaine.
Trump’s rhetoric focused on the suburban American idyll might, ironically, be making the people living that dream even more nervous in these nerve-wracking times. He might have been better off sticking with the pandemic — cases appear to be flattening out ever so slightly, though thousands of new cases are reported daily — than with the red meat of racial politics.


fivethirthyeight--2020-09-10--Will Liverpool Run Away With The Premier League Again, Or Can Manchester City Take The Title Back?

No one has ever dominated the Premier League like Liverpool and Manchester City have in the past three years .
Each team finished with at least 97 points on two occasions — City with 100 in 2017-18 and 98 in 2018-19 , Liverpool with 97 in 2018-19 and 99 in 2019-20 , the four best seasons in league history — and each won the league in record-breaking fashion .
It ’ s safe to say that City and Liverpool are in a class above the rest of the Premier League — and have been for several seasons now .
The @ @ @ @ @ @ @ a single point — and just 11.7 millimeters .
But like City in 2017-18 , Liverpool last season jumped out to a double-digit lead before the halfway mark .
A 4-0 thrashing of Leicester City at King Power stadium on Boxing Day all but wrapped it up for the Reds , who dropped only 2 points in their first 27 games in 2019-20 .
Although at the start of the season City was favored to complete the three-peat , according to FiveThirtyEight ’ s club soccer prediction model , the Reds were undaunted @ @ @ @ @ @ @ from the previous season in the past and bulldozed the league en route to their first league title in 30 years .
There was no real title race last season , just a seven-month coronation .
There ’ s a case to be made that Liverpool got lucky last season , or at least that scoring patterns went Liverpool ’ s way at key times , as judged by expected goals scored ( xG ) and expected goals against ( xGA ) .
According to an analysis by Grace Robertson for StatsBomb , @ @ @ @ @ @ @ more and conceded fewer goals than expected when games were tied and then played at roughly expected levels offensively while continuing to outperform defensively after they took a lead .
“ Liverpool score more to get ahead , then concede less once they get there , ” Robertson wrote .
“ They ’ re not just beating xG .
They ’ re beating xG at the right moments , in the right ways , to maximise points.
” Liverpool ’ s ability to get leads and hold onto them , especially late in @ @ @ @ @ @ @ a season ago .
The Reds faltered a bit toward the end of the season , but only after the title was sewn up and the season had been paused for several months in the midst of a pandemic .
Who can blame them for taking their foot off the gas a bit ?
City won eight games by four goals or more in 2017-18 and 10 games by four goals or more last season — including an 8-0 win over lowly , since-relegated Watford .
But the Reds rarely annihilated their opponents @ @ @ @ @ @ @ to outperform xG and xGA at the right times allowed it to win a lot of one-goal games last season : 14 to be exact .
A handful of tough results in close games killed Liverpool in 2018-19 ; good results in close games made Liverpool champions of England in 2019-20 .
City , on the other hand , slightly underperformed its expected goals against in 2019-20 .
And while it smashed the xG models yet again — City has paced the league in xG , xGA , xG differential per 90 minutes @ @ @ @ @ @ @ and non-penalty expected goals plus expected assists per 90 minutes in each of the past three seasons — City turned in its worst performance of the Pep Guardiola era by losses and its second-worst by points .
The team often battered opponents when it took the lead and failed to get the job done when things were tight : Five of its nine losses — nine !
— were by one goal .
Much was written about the absence of center back Aymeric Laporte from City ’ s defense last season , as @ @ @ @ @ @ @ replace former captain Vincent Kompany .
A knee injury to Laporte early in the season left the Cityzens thin at the back , and they looked vulnerable as a result .
A revolving central defending unit of Nicolás Otamendi , John Stones , a teenage Eric García and an aging Fernandinho — who famously isn ’ t a center back — wasn ’ t ideal .
As such , a team that scored 102 goals while conceding just 35 lost nine games and finished 18 points behind the champions .
City ’ s @ @ @ @ @ @ @ the acquisition of former Bournemouth center back Nathan Aké .
At first glance , Aké doesn ’ t appear to be any better than Otamendi , Stones , García or Fernandinho .
But comparing a center back from Bournemouth , which possessed the ball just 43.8 percent of the time last season , to center backs from City , which possessed the ball 66.9 percent of the time last season and spent the majority of that time in the middle or attacking third of the pitch , isn ’ t exactly fair .
@ @ @ @ @ @ @ , but the center back City really wants is Napoli ’ s Kalidou Koulibaly .
Koulibaly is considered alongside Liverpool ’ s Virgil van Dijk to be one of the best center backs on the planet , and a partnership with a healthy Laporte could be the best duo in the Premier League , if not all of world soccer .
So far the Koulibaly transfer is merely a rumor , and Napoli is allegedly after a monster fee ( especially for a 29-year-old , and especially during the COVID-19 pandemic ) .
@ @ @ @ @ @ @ the line , it could transform City more significantly than any other transfer in the Guardiola era .
Liverpool has been relatively quiet in the transfer market by comparison .
The Reds signed left back Kostas Tsimikas from Olympiacos for about $ 15 million , which is relatively short money , and the Greek is expected to back up Andy Robertson .
Bayern Munich and Spain midfielder Thiago Alcántara has been linked with a move to Merseyside , while Georginio Wijnaldum has been linked with a move away from Liverpool to Barcelona , @ @ @ @ @ @ @ yet .
Alcántara doesn ’ t fit with Liverpool ’ s recent transfer strategy — he ’ s 29 and injury prone — but he would certainly give the Reds a different look going forward .
Among Liverpool ’ s current set of midfielders , only Naby Keïta approaches Thiago in terms of shot-creating actions , progressive passing , passes made into the attacking third and pass completion percentage .
If they end up hanging onto Wijnaldum , the Reds don ’ t really need another midfielder .
But if they deal the @ @ @ @ @ @ @ replace his minutes somehow — since joining Liverpool in 2016 , Wijnaldum has played in 141 of a possible 152 Premier League games — and they could do far worse than Alcántara .
So , will this season be like 2017-18 and 2019-20 — inevitable and over as quickly as it started — or will Premier League fans be treated to the kind of historic title race we saw in 2018-19 ?
The FiveThirtyEight model likes City from the jump , giving the Mancunians a 57 percent chance of winning their third title @ @ @ @ @ @ @ percent chance of repeating .
Whether the title race is tight or not , one thing is clear : It ’ s still Liverpool and City ’ s league to lose .

No one has ever dominated the Premier League like Liverpool and Manchester City have in the past three years. Each team finished with at least 97 points on two occasions — City with 100 in 2017-18 and 98 in 2018-19, Liverpool with 97 in 2018-19 and 99 in 2019-20, the four best seasons in league history — and each won the league in record-breaking fashion. It’s safe to say that City and Liverpool are in a class above the rest of the Premier League — and have been for several seasons now.
The title race in 2018-19 was decided by a single point — and just 11.7 millimeters. But like City in 2017-18, Liverpool last season jumped out to a double-digit lead before the halfway mark. A 4-0 thrashing of Leicester City at King Power stadium on Boxing Day all but wrapped it up for the Reds, who dropped only 2 points in their first 27 games in 2019-20. Although at the start of the season City was favored to complete the three-peat, according to FiveThirtyEight’s club soccer prediction model, the Reds were undaunted. They left their devastating near miss from the previous season in the past and bulldozed the league en route to their first league title in 30 years. There was no real title race last season, just a seven-month coronation.
There’s a case to be made that Liverpool got lucky last season, or at least that scoring patterns went Liverpool’s way at key times, as judged by expected goals scored (xG) and expected goals against (xGA). According to an analysis by Grace Robertson for StatsBomb, through early February, the Reds scored more and conceded fewer goals than expected when games were tied and then played at roughly expected levels offensively while continuing to outperform defensively after they took a lead. “Liverpool score more to get ahead, then concede less once they get there,” Robertson wrote. “They’re not just beating xG. They’re beating xG at the right moments, in the right ways, to maximise points.”
Liverpool’s ability to get leads and hold onto them, especially late in proceedings, was among its greatest virtues a season ago. The Reds faltered a bit toward the end of the season, but only after the title was sewn up and the season had been paused for several months in the midst of a pandemic. Who can blame them for taking their foot off the gas a bit?
City won eight games by four goals or more in 2017-18 and 10 games by four goals or more last season — including an 8-0 win over lowly, since-relegated Watford. But the Reds rarely annihilated their opponents. Instead, Liverpool’s ability to outperform xG and xGA at the right times allowed it to win a lot of one-goal games last season: 14 to be exact. A handful of tough results in close games killed Liverpool in 2018-19; good results in close games made Liverpool champions of England in 2019-20.
City, on the other hand, slightly underperformed its expected goals against in 2019-20. And while it smashed the xG models yet again — City has paced the league in xG, xGA, xG differential per 90 minutes, non-penalty expected goals per 90 minutes and non-penalty expected goals plus expected assists per 90 minutes in each of the past three seasons — City turned in its worst performance of the Pep Guardiola era by losses and its second-worst by points. The team often battered opponents when it took the lead and failed to get the job done when things were tight: Five of its nine losses — nine! — were by one goal.
Much was written about the absence of center back Aymeric Laporte from City’s defense last season, as well as City’s inability to replace former captain Vincent Kompany. A knee injury to Laporte early in the season left the Cityzens thin at the back, and they looked vulnerable as a result. A revolving central defending unit of Nicolás Otamendi, John Stones, a teenage Eric García and an aging Fernandinho — who famously isn’t a center back — wasn’t ideal. As such, a team that scored 102 goals while conceding just 35 lost nine games and finished 18 points behind the champions.
City’s need to strengthen at the back inspired the acquisition of former Bournemouth center back Nathan Aké. At first glance, Aké doesn’t appear to be any better than Otamendi, Stones, García or Fernandinho. But comparing a center back from Bournemouth, which possessed the ball just 43.8 percent of the time last season, to center backs from City, which possessed the ball 66.9 percent of the time last season and spent the majority of that time in the middle or attacking third of the pitch, isn’t exactly fair.
Aké should provide solid cover when needed, but the center back City really wants is Napoli’s Kalidou Koulibaly. Koulibaly is considered alongside Liverpool’s Virgil van Dijk to be one of the best center backs on the planet, and a partnership with a healthy Laporte could be the best duo in the Premier League, if not all of world soccer. So far the Koulibaly transfer is merely a rumor, and Napoli is allegedly after a monster fee (especially for a 29-year-old, and especially during the COVID-19 pandemic). But if the deal does get over the line, it could transform City more significantly than any other transfer in the Guardiola era.
Liverpool has been relatively quiet in the transfer market by comparison. The Reds signed left back Kostas Tsimikas from Olympiacos for about $15 million, which is relatively short money, and the Greek is expected to back up Andy Robertson. Bayern Munich and Spain midfielder Thiago Alcántara has been linked with a move to Merseyside, while Georginio Wijnaldum has been linked with a move away from Liverpool to Barcelona, but neither transfer has come to pass yet. Alcántara doesn’t fit with Liverpool’s recent transfer strategy — he’s 29 and injury prone — but he would certainly give the Reds a different look going forward. Among Liverpool’s current set of midfielders, only Naby Keïta approaches Thiago in terms of shot-creating actions, progressive passing, passes made into the attacking third and pass completion percentage. If they end up hanging onto Wijnaldum, the Reds don’t really need another midfielder. But if they deal the Dutchman, they’ll have to replace his minutes somehow — since joining Liverpool in 2016, Wijnaldum has played in 141 of a possible 152 Premier League games — and they could do far worse than Alcántara.
So, will this season be like 2017-18 and 2019-20 — inevitable and over as quickly as it started — or will Premier League fans be treated to the kind of historic title race we saw in 2018-19? The FiveThirtyEight model likes City from the jump, giving the Mancunians a 57 percent chance of winning their third title in four seasons and Liverpool a 24 percent chance of repeating. Whether the title race is tight or not, one thing is clear: It’s still Liverpool and City’s league to lose.


fivethirthyeight--2020-09-10--Economists’ Best- And Worst-Case Scenarios For The Recovery Haven’t Changed Very Much

After an August jobs report that yielded better-than-expected results for American workers , economists have a much sunnier outlook on unemployment through the end of the year .
But that optimism isn ’ t trickling into the rest of their economic forecasts — in part because there ’ s still so much uncertainty about what the rest of the year will bring , and in part because the July 31 expiration of the $ 600-per-week payment for unemployed workers could already be leaving millions of Americans in dire economic straits .
In the latest edition of our economic survey , @ @ @ @ @ @ @ Global Markets at the University of Chicago Booth School of Business , FiveThirtyEight asked 28 quantitative macroeconomic economists about the future of the U.S. GDP and unemployment numbers .
We also asked them about Americans ’ spending and saving habits , which the economists believe changed in August ( and not for the better ) .
Recent jobs reports seem to have made experts a lot more optimistic about how quickly Americans can get back to work .
Just two weeks ago , our survey panel thought that there was only a 29 @ @ @ @ @ @ @ drop below 10 percent in the third quarter of 2020 .
But not only did it cross the 10 percent threshold , it fell to 8.4 percent in the Bureau of Labor Statistics ’ most recent data .
( Yes , there are some extenuating circumstances for that , but they don ’ t take too much away from the fact that jobs are recovering much faster than economists predicted . )
This has caused our panel to revise their estimates for unemployment in both September and December 2020 significantly downward : “ @ @ @ @ @ @ @ ’ s unemployment rate is seen by our survey as not being a temporary blip , but as reflecting a more permanent decline , ” said Allan Timmermann , an economist at the University of California , San Diego who has been consulting with FiveThirtyEight on the survey .
The survey panel ’ s projected unemployment rate for December , for instance , is 2 percentage points lower now than it was when we asked just a month earlier .
And our panel currently thinks there is a 63 percent chance that unemployment @ @ @ @ @ @ @ point between now and the end of the year .
Last week ’ s jobs report wasn ’ t the first one that turned out to be a lot cheerier than most observers had projected .
( Predicting the economic recovery in the middle of a pandemic is difficult , as it turns out . )
Unemployment indicators have been particularly challenging to untangle because they ’ re pointing in a bunch of different directions — for instance , even though the unemployment rate is falling , state-level unemployment claims are still historically @ @ @ @ @ @ @ at Johns Hopkins University who has been consulting with FiveThirtyEight on the survey , said that the survey of households that forms the basis of the unemployment rate may not be telling the whole story .
That survey has a fairly restrictive definition of unemployment — it excludes some people who may be out of a job or have lost income , such as part-time workers or those not actively looking for work due to the pandemic .
“ Broader concepts of underemployment are still painting a rather bad picture , ” Wright @ @ @ @ @ @ @ inequality in unemployment — a big problem in August ’ s jobs report — won ’ t be much better by year ’ s end .
The survey panel predicted a median unemployment rate of 11.9 percent for Black workers in December , with at least a 90 percent chance that the year would end with a double-digit unemployment rate for that group .
While the predicted number for Hispanic workers was slightly better ( 9.3 percent ) , the unemployment rates for both Black and Hispanic workers were predicted to be much @ @ @ @ @ @ @ December .
It ’ s extremely telling that the panel ’ s best case forecast for the unemployment rate of Hispanic workers ( 7.8 percent ) is only marginally rosier than the worst case for white workers ( 7.9 percent ) , which in turn is significantly more promising than the best case for Black workers ( 10.1 percent ) .
It ’ s also noteworthy that the economists ’ optimism about the economy as a whole hasn ’ t really been growing — instead , there remains a huge amount of uncertainty @ @ @ @ @ @ @ over the rest of the year .
The gap between best- and worst-case December real GDP growth in our survey is 12.7 percentage points , essentially unchanged from the estimated uncertainty in early July .
Even while our survey ’ s forecasts for the December unemployment rate were being revised downward , the economists ’ outlook for fourth-quarter real GDP growth ( a much broader measure of the overall recovery ) has hardly budged over the past two weeks .
The panel now thinks real GDP will grow at an annualized rate of @ @ @ @ @ @ @ ’ s end , barely up from 5.8 percent on Aug. 24 .
While that rate is higher than any of our survey ’ s median forecasts since we began asking the question on June 8 , the economists still think there ’ s at least a 10 percent chance of negative real GDP growth in the fourth quarter — and their best-case forecasts have been stuck between 12 and 13 percent growth for a month now .
Another sign of the economists ’ continued pessimism : They don ’ t think the @ @ @ @ @ @ @ be that bullish when they come in .
Despite the fact that more Americans were back on the job in August , the economists collectively thought there was a 31 percent probability that real personal consumption expenditures were substantially lower in August , compared to July , and a 51 percent chance that the personal saving rate was substantially lower in August , compared to July .
Some of the economists seemed to tie their predictions for both indicators to the expiration of the $ 600-per-week payment for unemployed workers , which makes @ @ @ @ @ @ @ allowing many people who were out of a job to spend more than they would normally and even save some money .
And a slowdown in consumer expenditures — or a decrease in the savings rate , which could be a harbinger of future household belt-tightening — isn ’ t good news for the economy , since businesses could find it harder to bring back more workers if their customers suddenly start spending less money .
All of this is to say that now is a pivotal — but confusing — moment for @ @ @ @ @ @ @ t as bad as the economists in our survey thought they would be a few months ago .
But it ’ s all a matter of perspective .
After all , over half the jobs that were lost in March and April still haven ’ t returned .
And with millions of people still out of work and an enormous amount of uncertainty about the trajectory of the virus , it ’ s easy to understand why economists aren ’ t celebrating yet .

After an August jobs report that yielded better-than-expected results for American workers, economists have a much sunnier outlook on unemployment through the end of the year. But that optimism isn’t trickling into the rest of their economic forecasts — in part because there’s still so much uncertainty about what the rest of the year will bring, and in part because the July 31 expiration of the $600-per-week payment for unemployed workers could already be leaving millions of Americans in dire economic straits.
In the latest edition of our economic survey, conducted in partnership with the Initiative on Global Markets at the University of Chicago Booth School of Business, FiveThirtyEight asked 28 quantitative macroeconomic economists about the future of the U.S. GDP and unemployment numbers. We also asked them about Americans’ spending and saving habits, which the economists believe changed in August (and not for the better).
Recent jobs reports seem to have made experts a lot more optimistic about how quickly Americans can get back to work. Just two weeks ago, our survey panel thought that there was only a 29 percent chance that the unemployment rate would drop below 10 percent in the third quarter of 2020. But not only did it cross the 10 percent threshold, it fell to 8.4 percent in the Bureau of Labor Statistics’ most recent data. (Yes, there are some extenuating circumstances for that, but they don’t take too much away from the fact that jobs are recovering much faster than economists predicted.) This has caused our panel to revise their estimates for unemployment in both September and December 2020 significantly downward:
Unemployment is improving faster than expected Predicted unemployment rates for September and December 2020, according to the FiveThirtyEight/IGM Economic Survey September 2020 Forecast from… Category Aug. 10 Sept. 8 Lower bound (10th percentile) 8.4% 7.1% Median (50th percentile) 10.0 8.1 Upper bound (90th percentile) 12.0 9.3 December 2020 Forecast from… Category Aug. 10 Sept. 8 Lower bound (10th percentile) 7.7% 6.2% Median (50th percentile) 9.6 7.6 Upper bound (90th percentile) 12.7 9.6 Separate forecasts were made on Aug. 10 and Sept. 8. Source: FIVETHIRTYEIGHT/IGM COVID-19 ECONOMIC SURVEY
“The surprisingly large drop in last month’s unemployment rate is seen by our survey as not being a temporary blip, but as reflecting a more permanent decline,” said Allan Timmermann, an economist at the University of California, San Diego who has been consulting with FiveThirtyEight on the survey.
The survey panel’s projected unemployment rate for December, for instance, is 2 percentage points lower now than it was when we asked just a month earlier. And our panel currently thinks there is a 63 percent chance that unemployment will drop below 8 percent at some point between now and the end of the year.
Last week’s jobs report wasn’t the first one that turned out to be a lot cheerier than most observers had projected. (Predicting the economic recovery in the middle of a pandemic is difficult, as it turns out.) Unemployment indicators have been particularly challenging to untangle because they’re pointing in a bunch of different directions — for instance, even though the unemployment rate is falling, state-level unemployment claims are still historically high.
Jonathan Wright, an economist at Johns Hopkins University who has been consulting with FiveThirtyEight on the survey, said that the survey of households that forms the basis of the unemployment rate may not be telling the whole story. That survey has a fairly restrictive definition of unemployment — it excludes some people who may be out of a job or have lost income, such as part-time workers or those not actively looking for work due to the pandemic. “Broader concepts of underemployment are still painting a rather bad picture,” Wright said.
The economists also think racial inequality in unemployment — a big problem in August’s jobs report — won’t be much better by year’s end. The survey panel predicted a median unemployment rate of 11.9 percent for Black workers in December, with at least a 90 percent chance that the year would end with a double-digit unemployment rate for that group. While the predicted number for Hispanic workers was slightly better (9.3 percent), the unemployment rates for both Black and Hispanic workers were predicted to be much higher than that of white workers come December. It’s extremely telling that the panel’s best case forecast for the unemployment rate of Hispanic workers (7.8 percent) is only marginally rosier than the worst case for white workers (7.9 percent), which in turn is significantly more promising than the best case for Black workers (10.1 percent).
Racial inequality in unemployment is likely to persist Actual August 2020 and predicted December 2020 unemployment rates for American workers, by race, according to the FiveThirtyEight/IGM Economic Survey Dec. 2020 unemployment* Race of workers Aug. 2020 unemployment Best Case median Worst Case White 7.3% 5.4% 6.4% 7.9% Hispanic 10.5 7.8 9.3 11.3 Black 13.0 10.1 11.9 14.0 *Predicted confidence intervals from survey panel. Best- and worst-case scenarios refer to the panel’s 90th and 10th percentile forecasts, respectively. Source: FIVETHIRTYEIGHT/IGM COVID-19 ECONOMIC SURVEY
It’s also noteworthy that the economists’ optimism about the economy as a whole hasn’t really been growing — instead, there remains a huge amount of uncertainty about what will happen with economic growth over the rest of the year. The gap between best- and worst-case December real GDP growth in our survey is 12.7 percentage points, essentially unchanged from the estimated uncertainty in early July. Even while our survey’s forecasts for the December unemployment rate were being revised downward, the economists’ outlook for fourth-quarter real GDP growth (a much broader measure of the overall recovery) has hardly budged over the past two weeks. The panel now thinks real GDP will grow at an annualized rate of 6.3 percent (quarter-over-quarter) at year’s end, barely up from 5.8 percent on Aug. 24.
While that rate is higher than any of our survey’s median forecasts since we began asking the question on June 8, the economists still think there’s at least a 10 percent chance of negative real GDP growth in the fourth quarter — and their best-case forecasts have been stuck between 12 and 13 percent growth for a month now.
Another sign of the economists’ continued pessimism: They don’t think the spending and saving numbers for August will be that bullish when they come in. Despite the fact that more Americans were back on the job in August, the economists collectively thought there was a 31 percent probability that real personal consumption expenditures were substantially lower in August, compared to July, and a 51 percent chance that the personal saving rate was substantially lower in August, compared to July. Some of the economists seemed to tie their predictions for both indicators to the expiration of the $600-per-week payment for unemployed workers, which makes sense because the payment appeared to be allowing many people who were out of a job to spend more than they would normally and even save some money.
And a slowdown in consumer expenditures — or a decrease in the savings rate, which could be a harbinger of future household belt-tightening — isn’t good news for the economy, since businesses could find it harder to bring back more workers if their customers suddenly start spending less money.
All of this is to say that now is a pivotal — but confusing — moment for the economy. Things certainly aren’t as bad as the economists in our survey thought they would be a few months ago. But it’s all a matter of perspective. After all, over half the jobs that were lost in March and April still haven’t returned. And with millions of people still out of work and an enormous amount of uncertainty about the trajectory of the virus, it’s easy to understand why economists aren’t celebrating yet.


fivethirthyeight--2020-09-11--Trump And Biden Both Got Small Convention Bounces. But Only Biden Got More Popular.

Welcome to Pollapalooza , our weekly polling roundup .
More so than Joe Biden , President Trump got a small boost in head-to-head polls coming out of the party conventions ( although it appears to have been short-lived ) .
But Biden got a convention bounce of sorts , too : The share of voters with a favorable opinion of him has ticked up .
Several pollsters have asked Americans whether they have a favorable or unfavorable view of both Trump and Biden since the Republican National Convention ended on Aug. 27 .
On average , these polls gave Biden @ @ @ @ @ @ @ 46 percent unfavorable rating — or a net favorability rating of +3 percentage points .
That ’ s a slight , 4-point increase from his net favorability rating in the same polls before the conventions .
To be more minute about it , his net favorability rating actually went from -2 points in polls conducted entirely or mostly before the conventions , to +3 points in polls conducted entirely or mostly between the two conventions ( after the Democratic National Convention spent four days talking him up ) , to +3 points in @ @ @ @ @ @ @ , this uptick was within the polls ’ margins of error , but the overall upward trend was still pretty clear .
Trump , on the other hand , went into the convention period with lower favorables than Biden and does not appear to have emerged from it any better liked .
Before the conventions , his average net favorability ( according to these same pollsters ) was -13 percentage points .
After the DNC started , but before the RNC , his net favorability rating ticked down to -15 points .
And @ @ @ @ @ @ @ to boost his standing .
In the most recent round of surveys from these pollsters , Trump has an average favorable rating of 41 percent and an average unfavorable rating of 55 percent .
In other words , his net favorability rating is now -14 points .
I don ’ t want to overstate the bump Biden got relative to Trump , though : The increase in Biden ’ s favorables , much like Trump ’ s improvement in head-to-head polls , was small by historical standards .
As former FiveThirtyEight writer Harry @ @ @ @ @ @ @ Jimmy Carter in 1980 to Bill Clinton in 1992 to Al Gore in 2000 to George W. Bush in 2004 saw double-digit surges in their net favorability rating after the conventions , as measured by CBS News polling .
That definitely didn ’ t happen this year .
In addition , Enten found that favorable ratings can also fluctuate a lot after this point in the election cycle .
The average candidate between 1980 and 2012 experienced a 6.4-point change in his net favorability between CBS News ’ s post-convention poll and its @ @ @ @ @ @ @ there ’ s plenty of time for Biden to sink , or Trump to rise — or Biden to rise , or Trump to sink — in popularity .
On the other hand , the conventions ’ failure to budge the candidates ’ favorable ratings more than a few points could suggest that opinions of both Trump and Biden are already baked in , thanks to intense political polarization .
Speaking of polarization , a handful of the post-convention polls also asked respondents how strongly favorable or unfavorable they felt toward the two @ @ @ @ @ @ @ “ very favorable ” and “ very unfavorable ” ratings , both candidates are underwater ; that is , they are both more hated than they are loved .
But Biden still has the advantage in the polls that have asked about this .
On average in these polls , since the conventions ended , 26 percent of Americans have said they view Biden very favorably , and 36 percent have said they view him very unfavorably ( that ’ s -10 points on net ) .
By contrast , Trump has an @ @ @ @ @ @ @ 29 percent and an average “ very unfavorable ” rating of 47 percent ( -18 points on net ) .
That ’ s a much narrower gap than FiveThirtyEight contributor Michael Tesler found in late June , when Biden was at -3 points and Trump was at -23 points in that measure .
But it still suggests that voters ’ motivations to vote against Trump are higher than their motivations to vote against Biden .
As Tesler argued earlier this summer , this could mean that Biden , not Trump , is the @ @ @ @ @ @ @ election .
• Late last week , The Atlantic reported that Trump called fallen American troops “ losers ” and “ suckers ” during a 2018 trip to France .
Trump and a number of other administration officials vigorously denied the report .
This week , YouGov found that 50 percent of Americans believed the report , while 31 percent thought it was false .
Nineteen percent didn ’ t know .
• Despite Trump ’ s claims that a coronavirus vaccine could be available before Election Day , the American public is @ @ @ @ @ @ @ found that 81 percent of Americans didn ’ t think a vaccine will be ready by then .
And if a free coronavirus vaccine is developed and approved by the Food and Drug Administration before the election , just 42 percent of Americans said they would want to get it .
Why ?
Sixty-two percent of respondents said they worried that political pressure would lead the FDA to rush to approve the vaccine before it is proven to be safe and effective .
• A new Pew Research Center survey of thousands of @ @ @ @ @ @ @ voted in 2016 and 2018 — found that Democrats ’ gains in the 2018 midterms came from several sources : More Hillary Clinton voters turned out to vote in the midterms than Trump voters did , more Trump voters defected to Democrats than Clinton voters to Republicans , and those who voted for a third-party candidate or didn ’ t vote at all in 2016 broke for Democrats in 2018 .
• Voters in Portland , Oregon , will vote on a ballot measure this November that would set up an new system @ @ @ @ @ @ @ the community .
This week , a group campaigning for the measure released an internal poll that found 70 percent of Portland voters in favor of it .
The poll also gave Mayor Ted Wheeler , who is up for reelection , a 26 percent favorable rating and 63 percent unfavorable rating .
• A SurveyUSA poll of California ’ s 50th Congressional District , conducted for KGTV-TV and the San Diego Union-Tribune , puts Republican Darrell Issa at 46 percent and Democrat Ammar Campa-Najjar at 45 percent — a surprising result , @ @ @ @ @ @ @ by 15 points in 2016 .
According to FiveThirtyEight ’ s presidential approval tracker , 42.7 percent of Americans approve of the job Trump is doing as president , while 53.1 percent disapprove ( a net approval rating of -10.4 points ) .
At this time last week , 43.4 percent approved and 52.3 percent disapproved ( a net approval rating of -8.9 points ) .
One month ago , Trump had an approval rating of 41.4 percent and a disapproval rating of 54.8 percent , for a net approval rating of -13.4 @ @ @ @ @ @ @ of the generic congressional ballot , Democrats currently lead by 6.6 percentage points ( 48.5 percent to 42.0 percent ) .
A week ago , Democrats led Republicans by 7.4 points ( 48.7 percent to 41.3 percent ) .
At this time last month , voters preferred Democrats by 7.6 points ( 48.5 percent to 40.9 percent ) .
Check out all the polls we ’ ve been collecting ahead of the 2020 elections .

Welcome to Pollapalooza, our weekly polling roundup.
Poll(s) of the week
More so than Joe Biden, President Trump got a small boost in head-to-head polls coming out of the party conventions (although it appears to have been short-lived). But Biden got a convention bounce of sorts, too: The share of voters with a favorable opinion of him has ticked up.
Several pollsters have asked Americans whether they have a favorable or unfavorable view of both Trump and Biden since the Republican National Convention ended on Aug. 27. On average, these polls gave Biden a 48 percent favorable rating and a 46 percent unfavorable rating — or a net favorability rating of +3 percentage points. That’s a slight, 4-point increase from his net favorability rating in the same polls before the conventions. To be more minute about it, his net favorability rating actually went from -2 points in polls conducted entirely or mostly before the conventions, to +3 points in polls conducted entirely or mostly between the two conventions (after the Democratic National Convention spent four days talking him up), to +3 points in the post-convention period. In some cases, this uptick was within the polls’ margins of error, but the overall upward trend was still pretty clear.
Biden left the conventions a bit more popular Polls of Joe Biden’s net favorability (favorable rating minus unfavorable rating) before, between and after the conventions Net Favorability Pollster Pop.* Pre-DNC Between Conventions Post-RNC Change SSRS/CNN RV -1 — +9 +10 Ipsos/ABC News A -3 +5 +6 +9 Monmouth University RV -5 — +3 +8 Global Strategy Group/GBAO/Navigator Research RV -1 +9 +5 +6 Morning Consult/Politico RV -2 — +4 +6 Harris/Harvard RV +1 — +6 +5 YouGov/The Economist RV +1 -1 +5 +4 Morning Consult LV 0 +6 +4 +4 SurveyMonkey/Axios A -7 -1 -6 +1 Change Research/CNBC LV -5 -2 -6 -1 YouGov/Yahoo News RV +2 +6 -2 -4 Average -2 +3 +3 +4 *Population surveyed: Adults (A), registered voters (RV), or likely voters (LV). Includes only pollsters that conducted surveys of the same type of respondent (e.g., registered voters) of Biden’s favorability both shortly before and after the conventions. Polls that were fielded during one of the conventions are grouped by whether they were fielded mostly before or mostly after the first night of the convention. The Morning Consult inter-convention, Morning Consult post-RNC, and YouGov/The Economist post-RNC numbers are averages of two polls each. Source: Polls
Trump, on the other hand, went into the convention period with lower favorables than Biden and does not appear to have emerged from it any better liked. Before the conventions, his average net favorability (according to these same pollsters) was -13 percentage points. After the DNC started, but before the RNC, his net favorability rating ticked down to -15 points. And the RNC didn’t do much to boost his standing. In the most recent round of surveys from these pollsters, Trump has an average favorable rating of 41 percent and an average unfavorable rating of 55 percent. In other words, his net favorability rating is now -14 points.
The RNC didn’t give Trump a favorability boost Polls of President Trump’s net favorability (favorable rating minus unfavorable rating) before, between and after the conventions Net Favorability Pollster Pop.* Pre-DNC Between Conventions Post-RNC Change Morning Consult/Politico RV -18 — -13 +5 YouGov/Yahoo News RV -14 -17 -13 +1 Monmouth University RV -14 — -13 +1 Morning Consult LV -12 -12 -12 0 SurveyMonkey/Axios A -10 -10 -11 -1 YouGov/The Economist RV -13 -11 -14 -1 Harris/Harvard RV -12 — -13 -1 Global Strategy Group/GBAO/Navigator Research RV -9 -16 -11 -2 SSRS/CNN RV -12 — -14 -2 Change Research/CNBC LV -10 -13 -14 -4 Ipsos/ABC News A -23 -28 -28 -5 Average -13 -15 -14 -1 *Population surveyed: Adults (A), registered voters (RV), or likely voters (LV). Includes only pollsters that conducted surveys of the same type of respondent (e.g., registered voters) of Trump’s favorability both shortly before and after the conventions. Polls that were fielded during one of the conventions are grouped by whether they were fielded mostly before or mostly after the first night of the convention. The Morning Consult and YouGov/The Economist post-RNC numbers are averages of two polls each. Source: Polls
I don’t want to overstate the bump Biden got relative to Trump, though: The increase in Biden’s favorables, much like Trump’s improvement in head-to-head polls, was small by historical standards. As former FiveThirtyEight writer Harry Enten found in 2016, candidates from Jimmy Carter in 1980 to Bill Clinton in 1992 to Al Gore in 2000 to George W. Bush in 2004 saw double-digit surges in their net favorability rating after the conventions, as measured by CBS News polling. That definitely didn’t happen this year.
In addition, Enten found that favorable ratings can also fluctuate a lot after this point in the election cycle. The average candidate between 1980 and 2012 experienced a 6.4-point change in his net favorability between CBS News’s post-convention poll and its final poll of the election. So there’s plenty of time for Biden to sink, or Trump to rise — or Biden to rise, or Trump to sink — in popularity. On the other hand, the conventions’ failure to budge the candidates’ favorable ratings more than a few points could suggest that opinions of both Trump and Biden are already baked in, thanks to intense political polarization.
Speaking of polarization, a handful of the post-convention polls also asked respondents how strongly favorable or unfavorable they felt toward the two nominees. And going just by their “very favorable” and “very unfavorable” ratings, both candidates are underwater; that is, they are both more hated than they are loved.
But Biden still has the advantage in the polls that have asked about this. On average in these polls, since the conventions ended, 26 percent of Americans have said they view Biden very favorably, and 36 percent have said they view him very unfavorably (that’s -10 points on net). By contrast, Trump has an average “very favorable” rating of 29 percent and an average “very unfavorable” rating of 47 percent (-18 points on net).
That’s a much narrower gap than FiveThirtyEight contributor Michael Tesler found in late June, when Biden was at -3 points and Trump was at -23 points in that measure. But it still suggests that voters’ motivations to vote against Trump are higher than their motivations to vote against Biden. As Tesler argued earlier this summer, this could mean that Biden, not Trump, is the candidate with the enthusiasm edge in this election.
Other polling bites
Late last week, The Atlantic reported that Trump called fallen American troops “losers” and “suckers” during a 2018 trip to France. Trump and a number of other administration officials vigorously denied the report. This week, YouGov found that 50 percent of Americans believed the report, while 31 percent thought it was false. Nineteen percent didn’t know.
Despite Trump’s claims that a coronavirus vaccine could be available before Election Day, the American public is skeptical. A Kaiser Family Foundation poll found that 81 percent of Americans didn’t think a vaccine will be ready by then. And if a free coronavirus vaccine is developed and approved by the Food and Drug Administration before the election, just 42 percent of Americans said they would want to get it. Why? Sixty-two percent of respondents said they worried that political pressure would lead the FDA to rush to approve the vaccine before it is proven to be safe and effective.
A new Pew Research Center survey of thousands of verified voters — who Pew independently confirmed voted in 2016 and 2018 — found that Democrats’ gains in the 2018 midterms came from several sources: More Hillary Clinton voters turned out to vote in the midterms than Trump voters did, more Trump voters defected to Democrats than Clinton voters to Republicans, and those who voted for a third-party candidate or didn’t vote at all in 2016 broke for Democrats in 2018.
Voters in Portland, Oregon, will vote on a ballot measure this November that would set up an new system for police oversight with more input from the community. This week, a group campaigning for the measure released an internal poll that found 70 percent of Portland voters in favor of it. The poll also gave Mayor Ted Wheeler, who is up for reelection, a 26 percent favorable rating and 63 percent unfavorable rating.
A SurveyUSA poll of California’s 50th Congressional District, conducted for KGTV-TV and the San Diego Union-Tribune, puts Republican Darrell Issa at 46 percent and Democrat Ammar Campa-Najjar at 45 percent — a surprising result, given that this district voted for Trump by 15 points in 2016.
Trump approval
According to FiveThirtyEight’s presidential approval tracker, 42.7 percent of Americans approve of the job Trump is doing as president, while 53.1 percent disapprove (a net approval rating of -10.4 points). At this time last week, 43.4 percent approved and 52.3 percent disapproved (a net approval rating of -8.9 points). One month ago, Trump had an approval rating of 41.4 percent and a disapproval rating of 54.8 percent, for a net approval rating of -13.4 points.
Generic ballot
In our average of polls of the generic congressional ballot, Democrats currently lead by 6.6 percentage points (48.5 percent to 42.0 percent). A week ago, Democrats led Republicans by 7.4 points (48.7 percent to 41.3 percent). At this time last month, voters preferred Democrats by 7.6 points (48.5 percent to 40.9 percent).
Check out all the polls we’ve been collecting ahead of the 2020 elections.


fivethirthyeight--2020-09-11--The Challenges Of Holding An Election During A Pandemic

In this episode of the FiveThirtyEight Politics podcast , Galen Druke speaks with Ohio Secretary of State Frank LaRose about @ @ @ @ @ help prepare the state for the upcoming election .

In this episode of the FiveThirtyEight Politics podcast, Galen Druke speaks with Ohio Secretary of State Frank LaRose about what LaRose is doing to help prepare the state for the upcoming election.


fivethirthyeight--2020-09-11--Politics Podcast: How Ohio Is Preparing For The Pandemic Election

Election Day is just over 50 days away and elections officials around the country are preparing for an unprecedented election @ @ @ @ @ In this installment of the FiveThirtyEight Politics podcast , Ohio Secretary of State Frank LaRose @ @ @ @ @ the challenges of the 2020 election .
You can listen to the episode by clicking @ @ @ @ @ in the audio player above or by downloading it in iTunes , the ESPN App @ @ @ @ @ .
If you are new to podcasts , learn how to listen .
The FiveThirtyEight @ @ @ @ @ and Thursdays .
Help new listeners discover the show by leaving us a rating and @ @ @ @ @ a comment , question or suggestion for “ good polling vs. bad polling ” ?
@ @ @ @ @ , on Twitter or in the comments .

Election Day is just over 50 days away and elections officials around the country are preparing for an unprecedented election amid the coronavirus pandemic. In this installment of the FiveThirtyEight Politics podcast, Ohio Secretary of State Frank LaRose discusses how he is addressing the challenges of the 2020 election.
You can listen to the episode by clicking the “play” button in the audio player above or by downloading it in iTunes, the ESPN App or your favorite podcast platform. If you are new to podcasts, learn how to listen.
The FiveThirtyEight Politics podcast is recorded Mondays and Thursdays. Help new listeners discover the show by leaving us a rating and review on iTunes. Have a comment, question or suggestion for “good polling vs. bad polling”? Get in touch by email, on Twitter or in the comments.


fivethirthyeight--2020-09-11--Which Players Have A Shot At Becoming WNBA Rookie Of The Year?

Of all the WNBA awards , Rookie of the Year may have the most amorphous definition .
Most Valuable Player tends to favor how well a player does at lifting her team , a nexus of individual accomplishment and team record .
Most Improved Player is about measuring the distance from last year to this year .
Sixth Woman is like MVP , but for the players who don ’ t start .
( Also , it ’ s Dearica Hamby in a walk , but I digress . )
But how you measure Rookie of the Year leads to @ @ @ @ @ @ @ vote , especially in 2020 .
Is it about current performance or promise of future play ?
Is how her team performs relevant , or is it purely based on individual numbers ?
Does a rookie get extra credit for outperforming her draft position , thus providing her team with added value ?
The truth is , even I don ’ t know for sure how I ’ m going to vote when I turn in my ballot Monday morning .
The battle is absolutely in flux .
Last year , it was @ @ @ @ @ @ @ rookies : Napheesa Collier , Teaira McCowan and Arike Ogunbowale .
This year ?
You can reasonably make cases for seven rookies , and the arguments for each differ pretty dramatically .
Let ’ s break down the case for each of the seven , in the order of win shares .
Dangerfield has been the primary point guard for her playoff-bound Lynx , who could still finish among the top four teams .
Despite falling to 16th overall in the 2020 draft , Dangerfield has seamlessly translated her game from the University @ @ @ @ @ @ @ her threes , getting to the rim regularly despite her 5-foot-5 size and bringing stability to the position that longtime Lynx Lindsay Whalen left when she retired after the 2018 season .
The only knocks against Dangerfield are a relatively low 21.3 assist percentage and less per-minute production , 17.2 , than some of the other newcomers .
The case for Magbegor is a combination of impact and team success .
The 12th overall pick in the 2019 draft didn ’ t join the Storm until this year , but her size and @ @ @ @ @ @ @ have been terrorizing opposing second teams .
She leads all rookies in block percentage , she ’ s third in effective field-goal percentage , and she ’ s playing meaningful minutes for a Seattle team that leads the WNBA .
Magbegor is second in the league in win shares among rookies yet has played the fewest minutes of anyone in the top 10 .
That ’ s either a positive or a negative , depending on how you weigh the evidence .
But in win shares per 40 minutes , Magbegor laps the @ @ @ @ @ @ @ vital criteria , Sabally is your pick .
She ’ s second only to former Oregon teammate Ruthy Hebard in rebound percentage among rookies , and is north of 15 percent in assist percentage as well .
Wings coach Brian Agler played her a good amount at the wing position , but thanks to a combination of her skill set and Dallas ’ s needs , she ’ s been a primary center of late as well and is thriving in that role , scoring 25 points against the Storm on Wednesday night @ @ @ @ @ @ @ so far this year : she is shooting just 36.8 percent from the field and 19.7 percent from three .
But she ’ s excelled in as many different areas as any rookie .
If what you value is a player capable of performing within herself , well , you probably already enjoyed Hebard with the Oregon Ducks — and even more now in her time as a classic five with the playoff-bound Sky .
Among all players ( not just rookies ) , Hebard is second in offensive points per possession among @ @ @ @ @ @ @ ’ s the leading rookie in total rebounding percentage and the league leader in true shooting percentage , using her vintage around-the-rim moves and strength , a Bri Jones-type player with a few extra inches of height .
But she is only averaging 13.7 minutes per game .
Allemand ’ s case is a combination of volume and efficiency .
The volume refers to how much Indiana has used her — she ’ s third in the league in minutes played among all players , ahead of workhorses like Courtney Vandersloot and Skylar @ @ @ @ @ @ @ Allemand as the primary point guard this season after Erica Wheeler tested positive for COVID-19 and wasn ’ t able to join the team in the bubble .
While in the lineup , all Allemand has done is hit 47.1 percent of her threes , sit second in the league among rookies in assist percentage and run a WNBA offense full time in her first exposure to the league .
If you value team record or defensive numbers , though , Allemand ’ s probably not your pick .
Charles did not play @ @ @ @ @ @ @ her 23rd in the 2020 draft .
But once the Sun started 0-5 , Charles worked her way into the lineup , deploying a previously unseen 3-point shot ( 39.3 percent for the season ) with an athleticism that allows her to get to the rim regularly at a strong 6-foot-1 .
Charles is fourth in win shares on the Sun , a team that has more than recovered from its slow start to reach the playoffs .
Her total numbers probably don ’ t support winning the award , but other than @ @ @ @ @ @ @ point to a rookie who has had a greater impact on a playoff-bound team .
The raw numbers are just astonishing .
She put up 35 points in a game early on , she ’ s led the late charge by the Atlanta Dream in pursuit of a playoff berth , and she ’ s been everything head coach Nicki Collen could have hoped when the team drafted Carter fourth and handed her the offense .
She ’ s averaging 16.5 points per game , she ’ s hitting 37.9 percent of her @ @ @ @ @ @ @ arc , she ’ s unguardable , and she changes the tilt of the floor when she ’ s on it .
She also missed six games — nearly 30 percent of the season — and purely evaluating her campaign means figuring out whether 70 percent of Carter ’ s production is better than 100 percent of any other rookie .
It might well be .

Of all the WNBA awards, Rookie of the Year may have the most amorphous definition.
Most Valuable Player tends to favor how well a player does at lifting her team, a nexus of individual accomplishment and team record. Most Improved Player is about measuring the distance from last year to this year. Sixth Woman is like MVP, but for the players who don’t start. (Also, it’s Dearica Hamby in a walk, but I digress.)
But how you measure Rookie of the Year leads to dramatically different outcomes in who gets your vote, especially in 2020. Is it about current performance or promise of future play? Is how her team performs relevant, or is it purely based on individual numbers? Does a rookie get extra credit for outperforming her draft position, thus providing her team with added value?
The truth is, even I don’t know for sure how I’m going to vote when I turn in my ballot Monday morning. The battle is absolutely in flux. Last year, it was possible to make credible cases for three rookies: Napheesa Collier, Teaira McCowan and Arike Ogunbowale. This year? You can reasonably make cases for seven rookies, and the arguments for each differ pretty dramatically.
Let’s break down the case for each of the seven, in the order of win shares.
Crystal Dangerfield, Minnesota Lynx
Dangerfield has been the primary point guard for her playoff-bound Lynx, who could still finish among the top four teams. Despite falling to 16th overall in the 2020 draft, Dangerfield has seamlessly translated her game from the University of Connecticut, hitting 33.3 percent of her threes, getting to the rim regularly despite her 5-foot-5 size and bringing stability to the position that longtime Lynx Lindsay Whalen left when she retired after the 2018 season. The only knocks against Dangerfield are a relatively low 21.3 assist percentage and less per-minute production, 17.2, than some of the other newcomers.
Ezi Magbegor, Seattle Storm
The case for Magbegor is a combination of impact and team success. The 12th overall pick in the 2019 draft didn’t join the Storm until this year, but her size and skill at both ends of the floor have been terrorizing opposing second teams. She leads all rookies in block percentage, she’s third in effective field-goal percentage, and she’s playing meaningful minutes for a Seattle team that leads the WNBA. Magbegor is second in the league in win shares among rookies yet has played the fewest minutes of anyone in the top 10. That’s either a positive or a negative, depending on how you weigh the evidence. But in win shares per 40 minutes, Magbegor laps the field.
Satou Sabally, Dallas Wings
If versatility is your most vital criteria, Sabally is your pick. She’s second only to former Oregon teammate Ruthy Hebard in rebound percentage among rookies, and is north of 15 percent in assist percentage as well. Wings coach Brian Agler played her a good amount at the wing position, but thanks to a combination of her skill set and Dallas’s needs, she’s been a primary center of late as well and is thriving in that role, scoring 25 points against the Storm on Wednesday night. Her efficiency has been her limitation so far this year: she is shooting just 36.8 percent from the field and 19.7 percent from three. But she’s excelled in as many different areas as any rookie.
Ruthy Hebard, Chicago Sky
If what you value is a player capable of performing within herself, well, you probably already enjoyed Hebard with the Oregon Ducks — and even more now in her time as a classic five with the playoff-bound Sky. Among all players (not just rookies), Hebard is second in offensive points per possession among 101 qualifiers, per Synergy. She’s the leading rookie in total rebounding percentage and the league leader in true shooting percentage, using her vintage around-the-rim moves and strength, a Bri Jones-type player with a few extra inches of height. But she is only averaging 13.7 minutes per game.
Julie Allemand, Indiana Fever
Allemand’s case is a combination of volume and efficiency. The volume refers to how much Indiana has used her — she’s third in the league in minutes played among all players, ahead of workhorses like Courtney Vandersloot and Skylar Diggins-Smith. The Fever have turned to Allemand as the primary point guard this season after Erica Wheeler tested positive for COVID-19 and wasn’t able to join the team in the bubble. While in the lineup, all Allemand has done is hit 47.1 percent of her threes, sit second in the league among rookies in assist percentage and run a WNBA offense full time in her first exposure to the league. If you value team record or defensive numbers, though, Allemand’s probably not your pick.
Kaila Charles, Connecticut Sun
Charles did not play much early on after the Sun selected her 23rd in the 2020 draft. But once the Sun started 0-5, Charles worked her way into the lineup, deploying a previously unseen 3-point shot (39.3 percent for the season) with an athleticism that allows her to get to the rim regularly at a strong 6-foot-1. Charles is fourth in win shares on the Sun, a team that has more than recovered from its slow start to reach the playoffs. Her total numbers probably don’t support winning the award, but other than Dangerfield, it’s hard to point to a rookie who has had a greater impact on a playoff-bound team.
Chennedy Carter, Atlanta Dream
The raw numbers are just astonishing. She put up 35 points in a game early on, she’s led the late charge by the Atlanta Dream in pursuit of a playoff berth, and she’s been everything head coach Nicki Collen could have hoped when the team drafted Carter fourth and handed her the offense. She’s averaging 16.5 points per game, she’s hitting 37.9 percent of her threes and 46.4 percent from inside the arc, she’s unguardable, and she changes the tilt of the floor when she’s on it. She also missed six games — nearly 30 percent of the season — and purely evaluating her campaign means figuring out whether 70 percent of Carter’s production is better than 100 percent of any other rookie. It might well be.