Could Kamala Harris Win The Presidency In 2024? Here’s What History Tells Us.

The fact that California Sen. Kamala Harris is Joe Biden’s vice presidential nominee is undeniably historic. She is only the third woman to run as vice president on a major-party ticket, and of the two main parties, she is the first Asian American and the first Black woman to run in the general election as president or vice president.

As my colleague Perry Bacon Jr. noted on Tuesday, Biden’s choice could also have ramifications that extend far beyond the 2020 election. If Biden wins in November, his VP pick could go on to become the first woman president. That presents a number of challenges, which we’ll discuss later, but first, let’s look at the track record of VPs making it to the Oval Office.

Since John Adams first held the VP post in 1789, 14 of 47 vice presidents have gone on to become president,<a class="espn-footnote-link" data-footnote-id="1" href="https://fivethirtyeight.com/features/could-kamala-harris-win-the-presidency-in-2024-heres-what-history-tells-us/#fn-1" data-footnote-content="

Not counting Vice President Mike Pence, who is President Trump’s running mate once again in 2020, but could run for the presidency in the future.

“>1 making it the most likely — albeit still far from certain — stepping stone to the White House. The number of vice presidents who have sought the presidency has really skyrocketed in modern times, too. Of the 13 VPs since the end of World War II (excluding Vice President Mike Pence), eight — or more than half — have gone on to become their party’s presidential nominee. However, as you can see in the table below, far fewer — just three — have won a presidential election, and just four have become president at all. Biden, of course, is hoping to become the fifth modern VP to accomplish this feat.

Most vice presidents run for president … but not all win

Vice presidents since 1948 who have run for president, and whether they won their party’s nomination and the subsequent presidential election

Vice President Party Won nomination Won pres. election
Alben Barkley D
Richard Nixon* R
Lyndon Johnson† D
Hubert Humphrey D
Gerald Ford† R
Walter Mondale D
George H.W. Bush R
Dan Quayle R
Al Gore D
Joe Biden D

* Nixon lost the first time he ran for president, in 1960, after serving as vice president, but ran again in 1968 and won.

† Johnson and Ford both became president upon the death or resignation of their predecessors, so they technically ran as incumbents.

Spiro Agnew, Nelson Rockefeller and Dick Cheney didn’t run for president after serving as vice president. This list does not include Vice President Mike Pence, as he could still run for president in the future.

That’s not a great batting average, especially when you consider that both Lyndon Johnson and Gerald Ford first became president because their predecessors could not finish their terms — in Johnson’s case, because John F. Kennedy was assassinated, and, in Ford’s case, because Richard Nixon resigned. At 77, Biden is the oldest major-party nominee in history and, if elected, would be the oldest president to hold the office, so without getting too macabre, there could easily be a scenario in which his VP must finish his term.

Biden’s advanced age has understandably prompted many to assign huge importance to his vice presidential pick and what it might signal for the future of the Democratic Party. Even if Biden wins and serves out his term, it’s not clear that he’d run for a second one. He has portrayed himself as a transitional candidate, describing his campaign as a “bridge” to the next generation of Democratic leaders, so it’s entirely possible that Harris, who is 55, will be thought of as the future of the party no matter what.

Harris is likely eyeing a future White House run, too. For one thing, she campaigned for it in 2020. And, as we mentioned at the outset, it’s pretty common for VPs to run. Just three of the vice presidents since 1948 — Spiro Agnew, Nelson Rockefeller and Dick Cheney — didn’t seek the presidency after serving as VP. But that doesn’t mean if Harris were to run it would be easy. It turns out that running for president after being VP is kind of a mixed bag.

Take someone like Ford. After assuming the presidency in 1974 when Nixon resigned, Ford mounted a run for a full term in 1976, but it was hardly a coronation. Before he won the GOP nomination, he had to fend off a serious primary challenge from Ronald Reagan that went all the way to the national convention. Some elected vice presidents, like Nixon, George H.W. Bush and Al Gore, have had an easier time winning their party nominations against weak opposition, but others, like Alben Barkley and Dan Quayle, didn’t even make it to the general election.

It’s impossible to say which of these comparisons might prove most apt for Harris — we don’t even know if she’ll be vice president — but it’s not hard to imagine her facing a major intraparty challenge in the future. For one, we’ve never had a woman vice president, let alone a woman president — and past elections have shown us just how challenging it can be for a highly qualified woman to win. For his part, Biden has sparked criticism for botching the selection process — the only thing we knew up until Tuesday was that he would pick a woman to be his running mate — making the conversation less about his running mate’s credentials and more about whether she was the “right” kind of woman for the job. It’s also possible that four years from now, the Democratic Party will have moved even further to the left, and Biden and Harris’s more moderate politics will have fallen out of fashion, encouraging a primary challenge.

Nevertheless, if Harris does become vice president, it undoubtedly raises her odds that she might one day occupy the White House and lead the Democratic Party in a presidential election. Even after her underwhelming 2020 bid, one only has to look at Biden’s career arc to see how Harris’s presidential aspirations could benefit from serving as VP. It wasn’t until Barack Obama made Biden his vice president in 2008 that he established a strong enough profile within the party to become its preferred choice in 2020. (His two prior presidential bids were unsuccessful.) It is, of course, too soon to say whether Biden will win in November, but he could become the 15th vice president to reach the White House. And someday Harris could easily become the 16th.

Our New Metric Shows How Good NFL Receivers Are At Creating Separation

Is Michael Thomas elite? On its face, that seems like an outrageous question. Michael Thomas, the New Orleans wide receiver who led the NFL in receiving yards and set an NFL record for receptions in 2019<a class="espn-footnote-link" data-footnote-id="1" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-1" data-footnote-content="

The second season in a row that he led the NFL in catches.

“>1 on the way to winning Offensive Player of the Year — that Mike Thomas might not be an elite receiver? Yet throughout the offseason, NFL analysts have debated whether Thomas’s production is best explained by his skill and talent, or if instead he’s merely a good receiver who runs a lot of slants and benefits from being in an elite offense.

Playing with Drew Brees — a former Super Bowl MVP who holds the NFL record for highest career completion percentage, most career passing yards and most career passing touchdowns — certainly doesn’t hurt. And running routes in schemes designed by Sean Payton, a coach with a .630 career win percentage (208-131, third among active NFL coaches), probably also has a strong positive effect on his production. But Thomas’s numbers are still eye-popping, and his peers in the NFL recently ranked him first among all wide receivers (and fifth overall) in the NFL 100. So which is it: elite talent, or elite situation?

One way to try to answer the question is to look at how well a receiver creates and maintains separation from a defender. Being quick and fast isn’t enough for NFL success; just ask Yamon Figurs or Darrius Heyward-Bey, both of whom ran a 4.3 40-yard dash at the NFL combine. The elements of savvy route running — footwork, head and body fakes, disguising the intent of the route, changing direction sharply without losing speed — all appear to be more reliable indicators of NFL skill and talent than speed. And the ultimate goal of every route is to create enough separation from a defender to earn a target and make a catch.

To try to capture the results of this game of cat and mouse between receiver and defender, we used NFL Next Gen Stats data that measures the distance between a receiver and the nearest defender at key moments in each play. Perhaps it’s no surprise that in the ultimate team sport, assigning credit for something even as seemingly straightforward as separation is complicated. For instance, short passes are, on average, associated with more separation than deeper passes because a defender’s top priority is to avoid getting beat deep. So we need to account for depth of target and how far the QB had to throw the ball when we apportion credit for the separation a receiver got on a given play. The type of play call matters, too. Play-action passes create more separation than non-play-action passes at nearly every depth of target on average, so we need to contextualize players who are targeted more often on play-action as well.

We also needed to decide when to measure receiver separation. Since the most interesting routes to analyze are those that earned a target, there are two obvious points in a play to focus on: the moment the ball leaves the QB’s hand and the moment the ball arrives at the receiver’s location.

But there again we’re confronted with confounders that make apportioning credit and blame difficult.<a class="espn-footnote-link" data-footnote-id="2" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-2" data-footnote-content="

It also means the entire analysis is conditional on a player actually being targeted. We can’t say anything about the skill of receivers who fail to earn targets.

“>2 For example, some QBs throw with more anticipation than others, releasing the ball before a receiver has made his break and created the separation necessary for a successful completion. Measuring separation at the time of the throw punishes teammates with great chemistry.

So we decided to focus on separation at the moment the ball arrives, on the theory that scheme and QB play have the least influence at this crucial moment in a pass play. Ultimately, our separation model ending up including features that account for quarterback arm strength, the receiver’s separation at the time the QB targeted them, the horizontal and vertical position of the receiver on the field at the time of the throw, where the receiver lined up pre-snap, the distance to the goal line, the amount of break in the receiver’s route during the football’s journey through the air after it was released, the depth of the QB’s drop, the number of other routes that were being run on the play, if the play was a play-action pass or a screen, and the number of deep safeties.<a class="espn-footnote-link" data-footnote-id="3" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-3" data-footnote-content="

The data set includes all regular-season pass attempts from the last three seasons, excluding spikes and passes from punts and field goal formations.


The final model does a decent job of predicting separation at the catch point on a given play.<a class="espn-footnote-link" data-footnote-id="4" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-4" data-footnote-content="

The model is an xgboost trained with fivefold cross validation and tested on out-of-sample data. Root mean squared error 1.52, r-squared 0.61, mean absolute error 1.09.

“>4 We used its predictions as a baseline for performance and compared each receiver’s actual separation on a given play to what the model expected an average player’s separation would have been, given similar circumstances. This result is a context-adjusted “separation over expected” (SOE) metric that we can calculate for each NFL receiver.

Since depth of target is so important in determining separation, we grouped plays into buckets — depending on whether a pass attempt was short, intermediate or deep — and created an SOE leaderboard for each. The resulting lists have reasonably strong face validity — players at the top of the leaderboards tend to be widely regarded as good route runners — suggesting SOE could be useful as a descriptive metric.

Separation is highest on short passes, but their value is low

Best and worst receiver seasons on short passes as measured by separation over expected (SOE) per play, 2017-19

Top 15 Receivers season targets aDOT epa/play soe/play
Evan Engram 2018 40 1.7 0.07 0.98
Zach Ertz 2019 45 2.3 0.43 0.59
Cole Beasley 2019 43 2.8 0.04 0.57
Diontae Johnson 2019 43 0.7 0.15 0.40
Nelson Agholor 2018 51 0.7 0.14 0.38
James Conner 2018 67 -0.9 0.19 0.36
Chris Carson 2019 43 -1.7 0.21 0.35
T.J. Yeldon 2018 71 0.2 -0.09 0.35
Duke Johnson 2018 48 -0.6 0.16 0.33
Jarvis Landry 2018 46 1.4 -0.10 0.33
Davante Adams 2017 48 2.3 0.31 0.30
Dede Westbrook 2019 52 1.1 -0.21 0.29
DeMarco Murray 2017 41 -0.6 0.00 0.29
Jaylen Samuels 2019 53 -1.5 -0.02 0.28
Keenan Allen 2018 64 2.9 0.14 0.28
Bottom 15 Receivers season targets aDOT epa/play soe/play
Latavius Murray 2019 41 -1.4 0.17 -0.28
Chris Thompson 2017 43 0.2 0.49 -0.30
Chris Thompson 2018 49 0.8 0.03 -0.31
Larry Fitzgerald 2018 42 2.4 -0.08 -0.32
Adam Humphries 2018 54 1.9 0.23 -0.33
Royce Freeman 2019 45 -0.3 -0.11 -0.34
Phillip Lindsay 2019 44 -1.8 -0.01 -0.34
Larry Fitzgerald 2019 59 1.3 -0.02 -0.35
Nick Chubb 2019 45 -1.0 0.02 -0.36
Le’Veon Bell 2019 71 -0.5 0.00 -0.39
Javorius Allen 2017 56 0.4 -0.12 -0.40
Giovani Bernard 2019 41 -0.8 -0.34 -0.42
David Johnson 2018 66 -1.2 -0.26 -0.44
Robert Woods 2019 48 -0.1 -0.08 -0.45
Todd Gurley 2019 45 0.5 -0.07 -0.49

Regular-season passes of 5 air yards or shorter, minimum of 40 targets.

Sources: NFL Next Gen Stats, ESPN Stats & Information Group

Two tight ends — Evan Engram of the New York Giants and Zach Ertz of the Philadelphia Eagles — top the list of receiver seasons with the highest separation over expected on short throws (5 air yards or less).<a class="espn-footnote-link" data-footnote-id="5" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-5" data-footnote-content="

As we’re using air yards — the vertical yards on a pass attempt relative to the line of scrimmage — this bucket includes passes behind the line of scrimmage.

“>5 Ertz’s targets especially were high value. While averaging more than a half-yard over expected in separation, his per-play expected points added (EPA) was worth more than 0.4 points in 2019. As a general rule, however, separation and value are decoupled on short passes. The defense is typically willing to allow an offense to throw to wide-open players short, then rally to make a tackle for a short gain.

Another interesting feature of short-target SOE is that a player’s ability to consistently get open on short throws appears to be mostly nonexistent. Having a high SOE in one season says very little about whether you will have a high SOE in the next.<a class="espn-footnote-link" data-footnote-id="6" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-6" data-footnote-content="

Year-over-year r-squared of 0.02.

“>6 Short targets are also the only leaderboard where running backs make an appearance, owing to the dearth of targets they get deeper downfield.

These short passes, however, are where Michael Thomas frequently shines. Forty-eight percent of Thomas’s 185 targets came on passes 5 yards or less downfield in 2019. In the three seasons for which we have Next Gen data, Thomas has regularly posted high EPA per play values on these short targets and has been above average in creating separation at the catch point in two of the past three seasons.

Short, open targets to Mike Thomas are high value …

Receiving stats on short passes for Michael Thomas, including separation over expected (SOE) and expected points added (EPA) per play

season targets Avg. Depth of Target SOE/PLAY epa/PLAY
2019 88 3.2 0.05 0.25
2018 73 2.9 0.06 0.31
2017 57 2.5 -0.05 0.43

Regular-season passes of 5 air yards or less.

Sources: NFL Next Gen Stats, ESPN Stats & Information Group

Other players appear able to consistently create separation on short targets — Jarvis Landry is one example — but the value of Landry’s targets as measured by EPA are much lower than those directed at Thomas. In fact, on an EPA-per-play basis, throwing short to Landry has a worse point expectation than running the ball. That’s somewhat shocking — and perhaps it explains why the number of Landry’s short targets dropped by nearly half after he moved to the analytics-friendly Cleveland Browns.

… while short, open targets to Jarvis Landry are not

Receiving stats on short passes for Jarvis Landry, including separation over expected (SOE) and expected points added (EPA) per play

season targets Avg. Depth of Target soe/play epa/play
2019 49 1.2 0.23 -0.19
2018 46 1.4 0.33 -0.10
2017 89 1.3 0.23 -0.11

Regular-season passes of 5 air yards or less.

Sources: NFL Next Gen Stats, ESPN Stats & Information Group

Wide receivers make the bulk of their high-value receptions on passes at intermediate depths (between 5 and 15 air yards). The intermediate SOE leaderboard includes seasons from receivers like Davante Adams, Keenan Allen, Danny Amendola, Cooper Kupp and Adam Humphries, all of whom are generally regarded as skilled route runners. Interestingly, among the three target depths, SOE on intermediate passes appears to be the most stable year to year. So while we’d like more data, we should probably expect players who show the ability to separate above expectation on routes at these depths to continue to do so.<a class="espn-footnote-link" data-footnote-id="7" href="https://fivethirtyeight.com/features/our-new-metric-shows-how-good-nfl-receivers-are-at-creating-separation/#fn-7" data-footnote-content="

Sample size caveats here. Perhaps even Simpson’s paradox caveats. Year-over-year r-squared of 0.13, n = 53 player season pairs from 2017-2019.


Davante Adams and Keenan Allen are technicians

Best and worst receiver seasons on intermediate passes as measured by separation over expected (SOE) per play, 2017-19

top 15 Receivers season targets aDOT epa/play soe/play
Davante Adams 2018 67 9.5 0.53 0.65
Keenan Allen 2017 69 10.3 0.58 0.58
Davante Adams 2019 44 9.1 0.29 0.52
John Brown 2018 42 10.6 0.32 0.46
Danny Amendola 2019 47 8.9 0.25 0.43
Cooper Kupp 2019 50 10.7 1.12 0.40
Adam Humphries 2018 43 9.4 0.53 0.40
Courtland Sutton 2019 49 10.2 0.39 0.39
John Brown 2019 54 10.2 0.18 0.32
Jared Cook 2017 41 9.7 0.54 0.30
Keenan Allen 2019 56 10.1 0.65 0.30
Robert Woods 2019 50 10.5 0.40 0.30
Odell Beckham Jr. 2019 44 9.7 0.29 0.29
Adam Thielen 2018 56 10.1 0.44 0.28
Zach Ertz 2018 79 9.7 0.20 0.25
Michael Thomas 2018 54 10.1 0.59 0.25
DeAndre Hopkins 2019 49 9.7 0.12 -0.23
D.J. Chark 2019 47 10.0 0.27 -0.26
DeAndre Hopkins 2018 80 9.9 0.50 -0.27
Alshon Jeffery 2017 52 10.4 0.33 -0.27
Eric Decker 2017 40 9.5 0.54 -0.28
T.Y. Hilton 2018 52 9.0 0.29 -0.30
Julio Jones 2019 58 10.8 0.42 -0.31
Allen Robinson 2018 47 9.2 0.21 -0.31
Kenny Golladay 2018 51 10.9 0.16 -0.31
Allen Robinson 2019 68 9.9 0.10 -0.32
Terry McLaurin 2019 43 9.9 0.57 -0.36
Devin Funchess 2017 47 10.7 0.35 -0.36
Jared Cook 2018 41 8.7 0.67 -0.38
Cameron Brate 2017 41 11.1 0.23 -0.53
Kenny Golladay 2019 42 9.8 0.31 -0.54

Regular-season passes of between 5 and 15 air yards, minimum of 40 targets.

Sources: NFL Next Gen Stats, ESPN Stats & Information Group

Thomas isn’t in the same class as Adams and Allen when it comes to creating separation — Adams has averaged over a half-yard of SOE the past two years on intermediates routes — but despite the tighter windows, the expected value Thomas created on these targets ranks him among the best in the league on a per-play basis. Perhaps because of his success, Thomas has seen a steady increase in the number of targets at those depths. And compared to Atlanta’s Julio Jones — a receiver whose natural talent and skill set are rarely questioned — Thomas comes out ahead on both our separation and value metrics.

Thomas did more on midrange targets than Jones

Receiving stats on intermediate passes for Michael Thomas and Julio Jones, including separation over expected (SOE) and expected points added (EPA) per play

PLAYER season targets Avg. Depth of Target soe/play epa/play
Michael Thomas 2019 71 10.6 0.08 0.72
Michael Thomas 2018 54 10.1 0.25 0.59
Michael Thomas 2017 48 9.4 0.01 0.39
Julio Jones 2019 58 10.8 -0.31 0.42
Julio Jones 2018 65 9.8 -0.07 0.36
Julio Jones 2017 44 10.3 0.03 0.29

Regular-season passes of between 5 and 15 air yards.

Source: NFL Next Gen Stats, ESPN Stats & Information Group

Timo Riske of Pro Football Focus has shown that the best receivers in the league earn their targets all over the field, so it’s no surprise to see familiar names in the deep-target SOE ranks. But we also see deep ball specialists like D.J. Chark and Kenny Stills at the top of the list — the “stretch X” receivers whose job is to take the top off a defense. And at the bottom of the list we find names like Robby Anderson, a free agent this offseason who reportedly drew few offers from teams; an aging Larry Fitzgerald; and the unsigned Kelvin Benjamin. Finally, we see the continued effect of depth of target on separation. Deep targets (at least 15 air yards) are the most valuable in football on a per-play basis, but they’re also the throws with the tightest windows.

D.J. Chark was open deep a lot in 2019

Best and worst receiver seasons on deep passes as measured by separation over expected (SOE) per play, 2017-19

TOP 15 Receivers season targets aDOT epa/play soe/play
D.J. Chark 2019 30 27.1 0.96 0.41
Kenny Stills 2017 36 25.4 0.46 0.40
Amari Cooper 2019 37 23.3 0.90 0.39
Odell Beckham Jr. 2018 33 24.7 0.72 0.36
Adam Thielen 2017 38 22.0 0.78 0.34
Travis Kelce 2017 31 22.2 1.08 0.33
Jaron Brown 2017 30 24.0 0.52 0.29
Robert Woods 2018 32 23.4 0.29 0.25
Tyreek Hill 2018 48 31.4 0.78 0.25
Curtis Samuel 2019 41 25.7 -0.26 0.24
Brandin Cooks 2017 41 29.2 0.65 0.23
Calvin Ridley 2019 30 25.2 0.68 0.22
Jarvis Landry 2018 39 23.2 0.05 0.19
JuJu Smith-Schuster 2018 33 23.8 0.68 0.17
Brandin Cooks 2018 37 26.9 0.65 0.17
Chris Godwin 2019 30 21.9 1.29 0.13
Odell Beckham Jr. 2019 42 26.6 0.09 -0.18
Dez Bryant 2017 37 23.7 -0.26 -0.20
Marquise Goodwin 2017 35 28.1 0.41 -0.20
Doug Baldwin 2017 36 27.2 0.85 -0.24
DeVante Parker 2019 38 25.2 1.10 -0.25
Alshon Jeffery 2017 41 24.3 0.06 -0.26
Mike Evans 2017 44 23.7 0.20 -0.29
Kelvin Benjamin 2018 30 24.7 -0.47 -0.31
Robby Anderson 2019 42 24.9 0.18 -0.32
Tyler Lockett 2019 31 27.1 0.69 -0.34
Larry Fitzgerald 2017 32 20.1 0.41 -0.34
Marvin Jones 2019 30 23.7 0.48 -0.35
Jarvis Landry 2019 33 22.1 0.89 -0.36
Allen Robinson 2019 37 23.1 0.63 -0.36
Robby Anderson 2018 31 30.7 0.04 -0.42

Regular-season passes greater than 15 air yards, minimum of 30 targets.

Sources: NFL Next Gen Stats, ESPN Stats & Information Group

Again it seems instructive to compare Thomas to Jones. Jones was targeted deep more frequently, suggesting that his skillset is better suited to the demands of beating fast humans in a footrace, but he’s also not as successful at creating separation from defenders as Thomas is. And Julio’s targets have, on average, been worth less than Thomas’s in the previous three years. (Again, no one doubts Jones’s talent or skills, and both he and Thomas are consistently in the conversation for best receiver in the league.)

When we account for the most impactful context that affects a receiver’s most important job — getting open — Thomas is routinely above average in creating that separation. And targets to him are among the most valuable plays in football across all depths. There isn’t much evidence to support the idea that Mike Thomas is anything but an elite football talent.

Yes, Unemployment Fell. But The Recovery Seems To Be Slowing Down.

After three straight months of declining unemployment, we have only just returned to levels of unemployment that rival the depths of the Great Recession. Friday’s jobs report revealed that the unemployment rate dropped from 11.1 percent in June to 10.2 percent in July, and 1.8 million more people were employed in July than in June.

So the economic recovery is continuing — but it’s moving very slowly, and we aren’t close to being out of the woods. Still, this report could have been much worse. After all, weekly unemployment claims rose a bit in July after falling for 15 straight weeks since late March. And across the country, phased reopenings have been rolled back over the past month as the number of COVID-19 infections spiked, preventing more workers from coming back to their jobs.

But the unemployment rate isn’t exactly dropping at the rate you’d expect for an economy that’s roaring back to life: The improvement from June to July was less than half as large as the one from May to June. And if the economy’s momentum is slowing, that means the recovery could be long and painful — particularly if Congress, which is currently deadlocked over the next round of coronavirus relief, cuts back on the aid it’s been pouring into the economy since March.

The economy has now regained about 9 million jobs since April, at which point more than 21 million jobs were lost. The unemployment rate has also fallen substantially from an official peak of 14.7 percent in April — which in reality was likely closer to 20 percent, thanks to a misclassification error on one of the surveys used to produce the jobs report that the Bureau of Labor Statistics now seems to have mostly under control.

One clear message of this month’s jobs report is that the recent uptick in nationwide COVID-19 infections doesn’t seem to be reversing the economic recovery. That runs somewhat contrary to the mixed economic signals we’ve been getting over the past few weeks: In addition to rising weekly unemployment claims, GDP growth was historically dismal for the second quarter of the year — down an annualized rate of 32.9 percent. That, combined with a report from the payroll processing company ADP which showed a substantial slowdown in hiring in July, was enough to spur speculation that the economy might already be backsliding, as gains in consumer spending stalled and businesses across the country were forced to scale back operations only a few weeks after states’ phased reopenings went into effect.

And according to the U.S. Census Bureau’s weekly pulse survey, the share of people who expected someone in their household to lose employment income rose from under 32 percent in early June to 35 percent in early July, after having dropped each week from the beginning of May. That seemed like it might be a leading indicator for unemployment, since it’s measuring anxiety in the workforce before actual job losses occur.

But although those trends might seem at odds with the data in today’s report, they’re a much more imperfect gauge of the state of the economy. Though they come out much more frequently than the monthly jobs report, weekly claims aren’t necessarily reflective of job losses as they’re happening. It’s possible that some of the fluctuations in weekly claims aren’t that meaningful at this point, since the numbers are so huge.

Meanwhile, not all of the real-time economic data we’ve seen recently has been bad. For instance, data from job-search websites such as Indeed shows that job postings have steadily trended upwards since dropping massively in April. At the beginning of May, job postings were down nearly 40 percent relative to the same week in 2019, but are now down just 18 percent compared with last year. We’d expect that improvement to be associated with a decrease in unemployment rate since May — particularly since the gains in postings have been almost uniformly steady.

As you dive deeper into this month’s report, some surprising trends emerge. Since it’s Friday, we’ll start with the good news first: permanent layoffs didn’t grow substantially and more people who lost their jobs temporarily seem to be finding work. In July, 76 percent of jobless workers were on temporary layoff while 24 percent had lost their jobs permanently. That’s slightly higher than in June, when 21 percent of layoffs were permanent, and much higher than the 10 percent share in April. But on the whole, permanent unemployment didn’t increase — a promising sign, since it’s much harder for workers to get back into the labor force if their former employer has cut ties with them completely.

In terms of industries, all of the major economic sectors we’ve been tracking throughout the recovery continued to gain jobs in July:

Jobs still haven’t caught up to pre-crisis levels yet

Net change in total employment over various time frames, by sector

Net Change In Employment Over Last…
Industry sector 1 Month 3 Months 6 Months
Construction +20,000 +639,000 -398,000
Education and health services +215,000 +1,170,000 -1,559,000
Leisure and hospitality +592,000 +3,978,000 -4,281,000
Professional and business services +170,000 +648,000 -1,621,000
Retail trade +258,300 +1,471,100 -910,300
Transportation and warehousing +37,900 +99,800 -470,300

Source: Bureau of Labor Statistics

These are encouraging numbers for some of the areas hit hardest by coronavirus-related shutdowns in the spring, though we should remember that none of them are close to regaining their pre-crisis employment levels. Leisure and hospitality, for instance, is still down 4.3 million total jobs over the past six months, despite the huge recent gains. And as infections remain at dangerously high levels across the country, it could be increasingly difficult for bars, restaurants, hotels and other businesses in this category to continue their rapid employment gains.

And while state and local governments gained nearly 300,000 jobs last month as well, it could be mostly a mirage. Almost all of those gains were in education, and that’s where we may run into problems with the way the BLS’s seasonal adjustments — which follow the ebb and flow of employment under normal circumstances — account for monthly changes. The issue this month is that many teachers were laid off earlier than usual this summer, which may have artificially inflated July’s jobs numbers.

Women — who have been hit harder than men during this recession — did see some substantial gains this month. Their unemployment rate fell from 11.7 percent in June to 10.6 percent in July. The unemployment rate for Hispanic or Latino workers, which hit a peak of nearly 19 percent in April, was at 12.9 percent this month, too — which is a big improvement.

But while nearly every demographic group saw its economic prospects improve in July, some of the most vulnerable workers are still being left behind. There was barely any improvement (less than a percentage point) in the unemployment rate for Black workers, which is still the highest of any racial and ethnic group, at 14.6 percent. Black or African American women have experienced a particularly slow drop in unemployment; July saw their unemployment rate fall by only 0.6 percentage points.

And all of these gains were made possible — at least in part — by the enormous amount of money the federal government has pumped into the economy since March, some of which is already starting to expire. For instance, people kept spending money, despite high levels of unemployment, because the federal government was keeping jobless workers afloat with an additional $600 per week in benefits. No one is getting that $600 payment right now, though, since it expired at the end of July and Congress is still deadlocked over whether to extend it. And without more stimulus money to buoy consumer spending — not to mention additional funds from a federal program that’s helped small businesses keep or bring workers back onto their payrolls — businesses could struggle in the future to keep workers on the job.

Meanwhile, Nick Bunker, the director of economic research for North America at the Indeed Hiring Lab, a research institute connected to the job-search site Indeed, pointed out that so far, we’re not seeing anything close to a v-shaped recovery, which some of President Trump’s advisers have continued to confidently predict.

“It’s important to remember that this is where we are after several months of bounce back and an unprecedented amount of fiscal stimulus,” Bunker said. But further gains will be more and more difficult, especially if an increasing number of temporary layoffs become permanent.

If anything, he said, the falling unemployment rate is a sign that the government’s investment in the economy is working — not that it’s time to turn off the money tap. “No one should be thinking ‘mission accomplished’ right now,” Bunker said.

Lab-Grown Antibodies Might Protect Essential Workers

This week on Podcast-19, we talk about lab-grown antibodies, called monoclonal antibodies, that could temporarily protect people from COVID-19. How soon might they be available for the public?

We also explore the long history of a COVID drug touted as a lifesaver, and learn about an inhalable treatment that might keep coronavirus patients off ventilators.

Don’t want to miss an episode of PODCAST-19, FiveThirtyEight’s weekly look at what we know — and what we know we don’t know — about COVID-19? Subscribe on your favorite podcasting app! For example, here’s where to do it on Apple Podcasts and Spotify.

How The NHL’s New Format Changed The Stanley Cup Race

On Saturday, the NHL joins the ranks of sports returning to action, with 24 teams plotting out one of the strangest paths to the Stanley Cup in hockey history.

Like the NBA, the NHL season will restart in a “bubble,” with early games split between two “hub” sites: Toronto (for the Eastern Conference) and Edmonton (for the West). Also like its basketball-playing cousins, hockey will have a bit of a convoluted format upon its return. Each conference’s top four teams<a class="espn-footnote-link" data-footnote-id="1" href="https://fivethirtyeight.com/features/how-the-nhls-new-format-changed-the-stanley-cup-race/#fn-1" data-footnote-content="

By regular-season points percentage.

“>1 will play a round-robin tournament (under regular-season rules) for playoff seeding, while the other eight teams from each conference have a best-of-five series (under playoff rules) to determine who reaches the Round of 16.

[Related: A Home Playoff Game Is A Big Advantage — Unless You Play Hockey]

From there, though, the playoffs will look roughly the same as usual, aside from reseeding after every round and a lack of crowds or home-ice advantage — which isn’t worth much in hockey anyway — for anyone except the Maple Leafs and Oilers.<a class="espn-footnote-link" data-footnote-id="2" href="https://fivethirtyeight.com/features/how-the-nhls-new-format-changed-the-stanley-cup-race/#fn-2" data-footnote-content="

Edmonton will be the lone host city for the conference finals and Stanley Cup Final.

“>2 So with the playoffs set to begin, I wanted to see how much the Stanley Cup picture has changed since the last time players took the ice, on March 11. Using Hockey-Reference.com’s Simple Rating System (SRS) for each team — and a set of logistic regressions relating SRS to win probabilities for games under rules for both the regular season and the postseason<a class="espn-footnote-link" data-footnote-id="3" href="https://fivethirtyeight.com/features/how-the-nhls-new-format-changed-the-stanley-cup-race/#fn-3" data-footnote-content="

Using data from the past decade of NHL games.

“>3 — I programmed 10,000 simulations for the rest of the season and playoffs under two scenarios: if the season had played out as planned back in March and under the current expanded format.<a class="espn-footnote-link" data-footnote-id="4" href="https://fivethirtyeight.com/features/how-the-nhls-new-format-changed-the-stanley-cup-race/#fn-4" data-footnote-content="

Toronto and Edmonton were assigned home-ice advantage for games played at their home rinks, but it was reduced by 60 percent (in keeping with our model for soccer).


Before the break, the Stanley Cup favorites (according to SRS) were the Boston Bruins (13 percent), Colorado Avalanche (12 percent), Tampa Bay Lightning (11 percent), St. Louis Blues (9 percent), Philadelphia Flyers (8 percent), Washington Capitals (7 percent) and Vegas Golden Knights (6 percent). Under the new system, those seven are still the front-runners, with essentially the same odds — except Boston dropped to 12 percent and Tampa Bay moved up to 12 percent. So in that sense, the big picture of the playoffs hasn’t changed much.

Cup favorites, then and now

Most likely 2019-20 NHL champions under original* and new playoff systems

Original System New System
Rk Team Prob. Rk Team Prob.
1 Boston Bruins 12.6% 1 Boston Bruins 12.2%
2 Colorado Avalanche 12.0 2 Tampa Bay Lightning 12.1
3 Tampa Bay Lightning 11.2 3 Colorado Avalanche 12.0
4 St. Louis Blues 8.8 4 St. Louis Blues 8.7
5 Philadelphia Flyers 7.8 5 Philadelphia Flyers 8.2
6 Washington Capitals 6.8 6 Washington Capitals 6.9
7 Vegas Golden Knights 5.8 7 Vegas Golden Knights 5.5
8 Pittsburgh Penguins 5.7 8 Dallas Stars 4.3
9 Carolina Hurricanes 5.0 9 Pittsburgh Penguins 3.4
10 Vancouver Canucks 3.6 10 Carolina Hurricanes 3.3
11 Edmonton Oilers 3.6 11 Edmonton Oilers 3.2
12 Dallas Stars 3.4 12 Winnipeg Jets 2.4

*These playoff probabilities use simulations of the original schedule from March 12 onward, with a standard playoff system. (Essentially, these are what the odds would have been without the COVID-19 pandemic.)

Based on 10,000 simulations of both normal and current playoff systems.

Source: Hockey-Reference.com

However, some teams have seen their title probabilities nudged up or down by a percentage point or two. The Arizona Coyotes (whose Cup chances rose by 1.3 percentage points) and New York Rangers (up 0.8 points) saw their odds increase because both are reasonably good teams by SRS — each ranks in the league’s top half — that had relatively long playoff odds beforehand, but now can potentially do damage in the expanded bracket. Others, such as the Montreal Canadiens and Chicago Blackhawks, watched their Cup odds go up mainly because they had next to no shot at making the playoffs under the standard system; now, the qualifying series gives each a fighting chance. And the Dallas Stars’ probability went up because they are the fourth seed in the West — meaning they can avoid the qualifying round entirely and skip straight to the Round of 16, despite ranking among the league’s bottom half in SRS.

How did Cup odds shift under the new playoff format?

For playoff-bound NHL teams, biggest change in 2019-20 championship odds since play ceased on March 11

Stanley Cup Odds
Team Normal System Current System Change
Arizona Coyotes 0.7% 2.0% +1.3
Chicago Blackhawks <0.1 1.3 1.3
Tampa Bay Lightning 11.2 12.1 0.9
Dallas Stars 3.4 4.3 0.9
New York Rangers 0.5 1.4 0.8
Montreal Canadiens <0.1 0.7 0.7
Columbus Blue Jackets 0.3 0.9 0.6
Philadelphia Flyers 7.8 8.2 0.4
Minnesota Wild 1.2 1.6 0.4
Nashville Predators 1.3 1.6 0.4
Florida Panthers 1.2 1.3 0.1
Washington Capitals 6.8 6.9 0.1
New York Islanders 1.3 1.4 0.1
Toronto Maple Leafs 2.3 2.3 0.0
Colorado Avalanche 12.0 12.0 0.0
St. Louis Blues 8.8 8.7 0.0
Vegas Golden Knights 5.8 5.5 -0.3
Edmonton Oilers 3.6 3.2 -0.4
Boston Bruins 12.6 12.2 -0.4
Winnipeg Jets 2.8 2.4 -0.5
Calgary Flames 1.8 1.2 -0.6
Vancouver Canucks 3.6 2.0 -1.6
Carolina Hurricanes 5.0 3.3 -1.7
Pittsburgh Penguins 5.7 3.4 -2.3

Based on 10,000 simulations of both normal and current playoff systems.

Source: Hockey-Reference.com

That somewhat arbitrary cutoff between the top four seeds and the rest of the conference could prove consequential for several teams. As an example, the Pittsburgh Penguins rank eighth in SRS and possess plenty of star powerwhen healthy — but also finished 3 points behind the rival Flyers for the fourth-best record in the East. That means Pittsburgh must play an extra series — with just a 59 percent chance of winning it — to even make it into the Round of 16, despite having a 98 percent chance to get that far before the pause. Even though the Pens will play the Canadiens, who are tied with the Columbus Blue Jackets for the lowest SRS of any team in the restart field, Pittsburgh is a clear victim of the NHL’s modified playoff system.

Whose playoff odds improved under the new format?

For restart-bound NHL teams, biggest change in odds of making the Round of 16 since play ceased on March 11

Odds to Make Round of 16
Team Normal System Current System Change
Chicago Blackhawks 2.4% 44.8% +42.5
Montreal Canadiens <0.1 41.0 +40.9
Arizona Coyotes 19.4 52.1 +32.7
New York Rangers 17.9 44.4 +26.5
Columbus Blue Jackets 17.6 42.7 +25.1
Florida Panthers 41.5 50.8 +9.3
Minnesota Wild 42.8 48.0 +5.2
Dallas Stars 96.7 +3.3
Vegas Golden Knights 99.4 +0.6
Philadelphia Flyers >99.9 +0.0
Washington Capitals >99.9 +0.0
Boston Bruins >99.9 +0.0
Colorado Avalanche >99.9 +0.0
Tampa Bay Lightning >99.9 +0.0
St. Louis Blues >99.9 +0.0
Nashville Predators 48.1 47.9 -0.2
Winnipeg Jets 63.3 54.7 -8.6
New York Islanders 58.2 49.2 -9.1
Calgary Flames 58.9 45.3 -13.6
Toronto Maple Leafs 76.7 57.3 -19.4
Vancouver Canucks 75.1 52.0 -23.1
Carolina Hurricanes 90.0 55.6 -34.4
Edmonton Oilers 93.9 55.2 -38.7
Pittsburgh Penguins 98.1 59.0 -39.0

Based on 10,000 simulations of both normal and current playoff systems.

Source: Hockey-Reference.com

The same goes for the Oilers, Hurricanes and a number of other teams that had high postseason odds under the old system, but now — by virtue of missing out on the top four seeds in the conference — will need to win a best-of-five series just to get into the usual playoff bracket. (The good news? All three of those teams — Edmonton, Carolina and Pittsburgh — would see their Cup odds double if they do survive the qualifying round.)

[Related: Apparently The Regular Season Is Irrelevant In The NHL]

This effect could also hurt Canadian teams’ chances of winning the Stanley Cup for the first time since 1993. Although Montreal was among the biggest beneficiaries of the amended format, Canada’s other postseason entries all saw their odds of mounting a deep playoff run drop, some significantly. (This despite Canada hosting the entire restart, with two of its teams — Toronto and Edmonton — having at least some extra familiarity by playing in their home facilities.) Overall, the six Canadian teams in the restart — sorry, Ottawa — are, on average, 10 percentage points less likely to make the Round of 16, 5 percentage points less likely to make the conference semifinals, 3 percentage points less likely to make the conference finals and 1 percentage point less likely to make the Cup Final now than if the season had been allowed to play out normally.<a class="espn-footnote-link" data-footnote-id="5" href="https://fivethirtyeight.com/features/how-the-nhls-new-format-changed-the-stanley-cup-race/#fn-5" data-footnote-content="

The average Canadian team’s championship odds are basically steady since none of them was especially likely to win either before the pause or after.


If you’re not a fan of one of the teams hurt by the change in format, though, these playoffs should be as exciting and compelling as ever. Can the defending-champion Blues keep beating the odds? Can the Bruins avenge last year’s Game 7 defeat? Can the Lightning find redemption after their historic 2019 collapse? Or will one of the nonfavorites crash the party, because it’s hockey? All of those storylines are why, despite months of waiting and a byzantine new playoff format (as per the NHL’s typical style), the battle for the 2020 Cup still promises to be a good one.

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