Tiger Woods May Not Get A Better Shot At Another Green Jacket

As the world’s greatest golfers convene in Augusta, Georgia, this week for the Masters, it’s time for every sports fan’s annual rite of spring: wild speculation about whether Tiger Woods can add a fifth green jacket to his closet. Picking Woods used to be a trendy bet; then it began to feel like a totally futile exercise. Well after he last won the event in 2005, there was a period when Woods was in the news constantly for everything except golf success. In fact, it wasn’t too long ago that Woods’s relevance as a winning golfer seemed finished, along with his bid to chase down Jack Nicklaus’s record for all-time majors won.

But that all changed last season, when Woods put everything back together again to finish eighth on the PGA Tour money list and win the season-ending Tour Championship in September. Now Woods is back, in his best position in years to win another Masters. According to VegasInsider, Woods has the third-best odds of any player to win this weekend; he’s also playing even more inspired golf than he did during last year’s comeback campaign. But at age 43, will this be one of Woods’s last chances to win at Augusta before his days of being a viable champion are over?

Certainly, Tiger has been outplaying many of his much younger rivals these past few seasons. Since the end of his lost 2017 campaign, Woods ranks sixth among qualified5 PGA Tour players in total strokes gained per round, trailing only Dustin Johnson, Justin Thomas, Justin Rose, Rory McIlroy and Tommy Fleetwood. He’s mostly regained his old mastery of irons on approach shots and still has some of the game’s best feel for shots around the green. In terms of strokes gained, Woods is picking up 1.67 shots (relative to the average player) per round so far in 2019, an even better mark than the 1.60 he posted last season — which itself was easily his best performance in five years.

One of the most impressive aspects of Woods’s early play this season has been improved accuracy off the tee. According to the PGA Tour, Woods has hit 65.2 percent of possible fairways on his drives this season, which ranks 54th out of 214 qualified players. That might not sound amazing, but by Woods’s standards, it is ultraprecise accuracy. Last year, he hit only 59.4 percent of fairways, which ranked him 127th, and he struggled to break 55 percent over the four injury-plagued seasons before that. (Even during his really great pre-scandal/injury seasons, hitting fairways was an Achilles’ heel. In 2007, when he made the most money playing golf of his career, Woods ranked 152nd in driving accuracy and failed to hit 60 percent of fairways.) When Woods is scuffling, the first indication is often a wayward drive that requires subsequent artistry just to make par.

With the help of that improved accuracy, Woods now ranks 72nd in strokes gained on drives this year — he was 100th last year — and ninth in strokes gained from the tee to the green, picking up 1.48 shots per round before ever setting his spikes on the putting surface. Classic Tiger was always a tee-to-green monster, ranking either first or second in the category every healthy season from 2006 to 2013, so his strong performance in that category this year is another signal that Woods is returning to vintage form.

It’s also a very good sign for his chances at Augusta. That’s because, as Todd Schneider wrote about for FiveThirtyEight a few years ago, the Masters often comes down to a player’s skills with the long clubs — contrary to the tournament’s reputation for being a putting contest.

Great PGA Tour players generally assert themselves most on approach shots and drives anyway, gaining about 4 strokes relative to average from tee to green for every extra shot they pick up on putts. But the recent history of Masters winners also suggests that a great long game is the true prerequisite for winning the green jacket. The average winner since strokes gained was first tracked in 2004 (excluding the 2016 and 2017 winners, Danny Willett and Sergio Garcia, because they lacked enough PGA Tour rounds to qualify for official leaderboards) ranked only about 86th in putting performance per round but 35th in strokes gained off the tee, 32nd in strokes gained on approach shots and 18th in total strokes gained from tee to green.

Masters winners do their best work from tee to green

Strokes gained rankings by category for Masters Tournament winners during the seasons they won, 2004-18

PGA Tour Rank
Year Masters Winner Off Tee Approach Around Green Tee to Green Putting Total
2018 Patrick Reed 104 74 2 29 72 24
2017 Sergio García
2016 Danny Willett
2015 Jordan Spieth 15 11 7 4 9 2
2014 Bubba Watson 2 47 63 7 109 8
2013 Adam Scott 2 16 77 5 108 11
2012 Bubba Watson 1 59 84 3 160 6
2011 Charl Schwartzel 22 45 64 19 96 20
2010 Phil Mickelson 66 5 32 5 133 12
2009 Ángel Cabrera 37 48 169 63 63 51
2008 Trevor Immelman 116 50 11 31 191 113
2007 Zach Johnson 61 30 164 60 5 13
2006 Phil Mickelson 12 4 66 4 40 5
2005 Tiger Woods 4 4 128 4 5 1
2004 Phil Mickelson 7 22 43 5 128 9
Average 34.5 31.9 70.0 18.4 86.1 21.2

Garcia and Willett didn’t play enough rounds to qualify for the PGA Tour’s rankings during their Masters-winning seasons.

Source: PGAtour.com

Strokes gained tee-to-green was the top category (or tied for the top) for 46 percent of the Masters winners over that span,6 and 62 percent of winners ranked among the Top 10 in the statistic — like Woods does this year. (This is consistent with my previous research that driving distance and approach accuracy are the two secret weapons players can possess at Augusta, causing them to play better in the Masters than their overall scoring average would predict.)

I haven’t mentioned Tiger’s putting numbers yet, and with good reason. Woods used to be the greatest putter in the world, but so far this season he ranks just 74th in strokes gained with the flatstick, adding only 0.19 shots above average per round. Last year, he was better — 48th on tour — though he still wasn’t the putting maestro who once showed me and countless others the fundamentals of a great stroke. However, Augusta has frequently seen putters who rank far worse than Woods win during the era of detailed PGA Tour tracking data. (In fact, more than half of qualified Masters winners since 2004 have ranked worse than 78th in putting.) Putting performance is so random from year to year — much less from tournament to tournament or even round to round — that it’s a lot easier for a good tee-to-green player to get hot on the green for a weekend than for a good putter to suddenly have an uncharacteristically amazing weekend off the tee.

Because of all this, it’s not hard to understand why Woods is a strong 12-to-1 bet to win the Masters. But it’s also not hard to imagine that this could be the 43-year-old’s last, best chance to win another green jacket. Using our research on historical major winners from a few years ago, here’s what the aging curve for championship golfers looks like:

That spike in wins for players in their early 40s came from 42-year-olds Ernie Els, Darren Clarke, Payne Stewart, Tom Kite and Gary Player, and it was the last actual uptick on the chart — and Woods is now on the wrong side of it. Jack Nicklaus famously won his final major at age 46, but most great golfers are largely done winning by their early to mid-40s. And the game has only gotten younger in the twilight of Woods’s career; while the average major-winner in our data set above (through 2014) was 31.9, that number is just 29.6 in the years since. With his own early career dominance and popularity, Woods has inspired a younger generation of gifted golfers that he now must do battle with.

Woods is a special talent and in the conversation for the greatest golfer ever.7 He’s playing as well heading into Augusta as he has in a long time and excelling in exactly the right categories. But between aging effects and his own injury history, he may never have a better shot at winning another Masters than he does right now. Once upon a time, Tiger was legendary for pouncing on every opportunity left in front of him. We’ll just have to see if he can summon that ability yet again.

Willians Astudillo Is A Baseball Enigma

Willians Astudillo was already something of a cult hero before he made this year’s opening day roster of the Minnesota Twins. He earned a video shoutout on MLB.com shortly after his major league debut last year when his first-to-home sprint left him gasping. And ESPN tweeted that he “may have broken every single one of baseball’s unwritten rules” after he kneeled in the batter’s box to watch a winter ball home run. (The kneel was “a natural reaction,” Astudillo told us. “I thought it was going to be foul.”)

But there’s another thing that makes the 27-year-old rookie nicknamed La Tortuga is perhaps the most interesting man in baseball: his bat. No one in pro baseball hits quite like he does.

Among all major league hitters in history to record at least 100 plate appearances, Astudillo ranks first in batting average (.382). While he looks something like Bartolo Colon, he’s hitting like Ty Cobb.

With the Twins and Diamondbacks Triple-A teams in 2018 and 2017, Astudillo posted the lowest strikeout rate each season among all Double-A and Triple-A batters with at least 100 plate appearances. In the farm systems of the Braves and Phillies in 2016 and 2015, he had the lowest K-rates in all of the minors. Across his entire minor league career, he struck out just 81 times in 2,461 plate appearances (3.3 percent). With velocity and strikeouts at record levels across the majors, it’s never been more difficult to make contact with a pitch. But in an age when walks and on-base percentage are prized, Astudillo has shown little interest in watching pitches go by. He walked on just 85 occasions (a 3.5 percent walk rate) across nine seasons in the minors.1

In his brief major league career, he’s striking out at a 2.8 percent rate. Two players have had lower K rates for a season since 1989: Tony Gwynn (1995) and Felix Fermin (1993 and 1995).

Astudillo has always hit. So why did it take him 10 years to make the major leagues? It’s probably that the sport didn’t know what to do with him. No one has looked, or hit, quite like the 5-foot-9, 225-pound catcher/utility man.

The Twins’ scouts were perplexed by Astudillo, said Derek Falvey, the chief baseball officer for Minnesota.

“They weren’t necessarily projecting the power or the on-base skill because of the lack of walks,” Falvey said. “I’d say [the scouts’ grade on his bat] was probably fringe-average, in that range, toward average. It wasn’t anything that stood out.”

He was such an outlier that Minnesota’s own projection system struggled to find comps when the Twins were scouring minor league free agents after the 2017 season.2

“He’s an interesting guy because he’s not someone projection systems would easily pick out,” Falvey said. “It’s a simple reason: Projection systems are based upon history. Take a random player, like Jonathan Schoop. You know what his track record was through the minor leagues. If you have a similar batted-ball profile, strikeout rate, swing-and-miss rate, all those things, there’s a chance you might become someone like him over time. That’s the way projection systems are built. They look at history to then look at the future.

“Willians is kind of his own breed.”

Astudillo is interesting for another reason, too: He’s getting better.

Astudillo’s grandfather and father were obsessed with baseball. His father had played professionally in Venezuela. Astudillo remembers a drill in which his father would kneel a few feet away and flick corn kernels toward him in their backyard in the coastal city of Barcelona, Venezuela. Astudillo’s objective was to hit the knuckling projectiles with a broomstick. He thinks his rare contact ability is part nature and part nurture.

“I think it’s just who I’ve been since the beginning, practicing with my dad and my grandfather. That close nucleus back home, just practicing,” Astudillo told FiveThirtyEight through an interpreter. “It’s something that I have. I don’t know how to explain it exactly.”

But low-strikeout, high-contact hitters are increasingly interesting for another reason beyond their scarcity: They’ve shown a knack for developing power.

The average launch angle has increased every year since Statcast began measuring balls in play in 2015, from 10.1 degrees in 2015 to 11.7 degrees last season and to what would be a record rate of 13.2 degrees as it stands early this season. (Astudillo’s average launch angle was 12.2 degrees last season.) That trend suggests that more hitters are trying to hit balls above infield shifts and out of the ballpark.

Hitters with excellent contact rates but unlikely power-hitting builds — like Jose Ramirez, Jose Altuve, Justin Turner, Mookie Betts and Francisco Lindor — have become sluggers in recent seasons. As more batters are adjusting their swing planes, elite contact hitters have made the greatest offensive gains — measured in one way by isolated power, or slugging percentage minus batting average.

Astudillo has also gained power in recent years without having to sacrifice his contact ability. No projection system or scout saw that coming. Falvey, who had worked in the Cleveland front office before taking the Twins job, noted that Ramirez was also a high-contact hitter before he had an unlikely power breakout.

“Did anyone see Jose Ramirez turning into that kind of power hitter?” he said. “If anyone tells you they believed that at the outset — I worked there — I can tell you that’s not true. We did believe he had some interesting profile traits. Same thing with Willians.”

While Astudillo was limited to 128 Triple-A plate appearances with the Diamondbacks in 2017, his isolated power jumped to a career-best .217, up from .065 the previous year. His previous best ISO mark had been .101. (The MLB average ISO was .161 in 2018.) With the Twins last year, he followed up with a .192 ISO mark in 307 plate appearances in Triple-A and a .161 mark in 97 plate appearances with the major league club.

His power has been present early this season, too. Within his first three major league swings of 2019 on Sunday, he doubled twice. In his second start Wednesday, Astudillo went 3-for-5 with another double.

“I think it’s the experience from playing more often,” Astudillo said of his power surge. “Yes, I made contact (early in my career), but it was mostly weak contact. I was swinging at pitches a little out of the zone. Now I am not swinging at those pitches. I am being more selective.”

Astudillo ranks 35th in the frequency of swinging at pitches out of the zone among major league hitters to have recorded at least 100 plate appearances since last season, and he ranks 17th in swing percentage. But Falvey noted that Astudillo doesn’t dramatically expand his zone and offer at pitches far outside the strike zone.

“It’s not like he’s trying to chase balls over his head or out of the strike zone,” Falvey said. “He just constantly attacks strikes. He has a unique ability that when he attacks a strike, he usually doesn’t miss.”

Baseball Savant

When Astudillo goes outside the zone, he’s not going that far out of the zone. And when he swings — either in or out of the zone — he doesn’t miss. Astudillo leads baseball in contact rate (91.9 percent) and out-of-zone contact rate (83.3) among batters with at least 100 plate appearances since last season. That’s well above the MLB averages for both last season, with contact rate at 76.9 percent and out-of-zone contact at 60.1 percent.

While Astudillo’s bat is fascinating, it’s not the reason the Twins signed him in November 2017 to a minor league contract with an invite to spring training. They were intrigued by his glove.

During their organizational meetings last spring, Twins officials went through the scouting reports on players in their camp. As they looked at Astudillo, they thought he could play second, third, left field and catcher — important versatility in a sport that increasingly requires roster flexibility. A Twins evaluator in the room then spoke up.

“‘He can play center, too, just ask him,’” Falvey recalled.

The club officials were amused. Center field didn’t seem like a natural fit for the stout player. But Astudillo showed them the proof: video of himself robbing a home run in a 2014 Venezuelan winter league playoff game.

Months later, after several Twins went down with heat exhaustion during a game on a sweltering afternoon last June, Astudillo trotted out to center field in Wrigley Field. He became the first player 5-foot-9 or shorter weighing more than 220 pounds to play center in a major league baseball game, according to Baseball-Reference.com.

But even given his versatility, the Twins thought he was best suited to play catcher, according to Falvey. Astudillo rated as an above-average pitch framer throughout his minor league career, according to Baseball Prospectus defensive metrics — and pitch framing has been a focus of Falvey’s since he took the reins of the Twins after the 2016 season.

While the Twins initially brought in Astudillo for his interesting glove, it’s his bat that will ultimately determine how much he plays and whether he’s a short-lived curiosity or becomes a useful major leaguer.

Even the Twins admit that they didn’t see this player emerging. But as is so often the case with Astudillo, what you expect is not what you get.

Check out our latest MLB predictions.

Significant Digits For Friday, April 5, 2019

You’re reading Significant Digits, a daily digest of the numbers tucked inside the news.

2 open seats

There are two open seats on the seven-seat Federal Reserve board of governors. President Trump has been hoping to fill one of them with Stephen Moore, the author of “Trumponomics” and who the IRS has said owes tens of thousands in back taxes. Now, Trump is hoping to fill the second seat with Herman Cain, the former CEO of Godfather’s Pizza, promoter of the “9-9-9” tax plan, and accused sexual harasser of multiple women. [The Washington Post]

More than 280 people

Immigration and Customs Enforcement agents arrested more than 280 people at a phone equipment repair company in the Dallas suburbs, in what BuzzFeed News reports is the largest such sweep in more than a decade. ICE officials said they’d received a tip that the company, CVE Technology Group, “may have knowingly hired workers with fake documents.” ICE agents made almost 10 times as many immigration arrests at workplaces last fiscal year than the fiscal year before. [BuzzFeed News]


That was the appraised value of the house belonging to Peter Brand, Harvard’s fencing coach. Two years ago, however, the house sold to a wealthy businessman for nearly $1 million. The buyer’s son later matriculated at Harvard and joined the fencing team, and the buyer sold the house, having never lived in it, for a $324,500 loss. [The Boston Globe]

4th richest woman

Following her divorce settlement with Jeff Bezos, MacKenzie Bezos is now the fourth-richest woman in the world. She retains a 4 percent stake in Amazon worth some $36 billion. She is behind a L’Oreal heiress, a member of Walmart’s Walton family, and a member of the Mars family of confectioners. [Bloomberg]

“70 percent”

When we say it, we mean it. My colleagues recently published an exhaustive look at thousands of forecasts that FiveThirtyEight has made in the past, testing them for calibration — do events occur about as often as we say they’re going to occur — and discrimination — can we distinguish relatively more likely events from relatively less likely ones. The results of this self-analysis were good. For one thing, the events we said had a 70 percent chance of happening happened 71 percent of the time. [FiveThirtyEight]

7 agencies

Before yesterday, the spacecrafts of six agencies — the United States, the former Soviet Union, China, Japan, India and the European Space Agency — had orbited the moon. Israel has become the seventh with its Beresheet craft, which will attempt to land on the lunar surface on April 11. If successful, it would become the first privately funded craft to do so. [The New York Times]

From ABC News:
It's Morning, America: Friday, April 5, 2019

Love digits? Find even more in FiveThirtyEight’s book of math and logic puzzles, “The Riddler.”

If you see a significant digit in the wild, please send it to @ollie.

Does Your Gift Card Still Have Free Drinks On It?

Welcome to The Riddler. Every week, I offer up problems related to the things we hold dear around here: math, logic and probability. There are two types: Riddler Express for those of you who want something bite-size and Riddler Classic for those of you in the slow-puzzle movement. Submit a correct answer for either,3 and you may get a shoutout in next week’s column. If you need a hint or have a favorite puzzle collecting dust in your attic, find me on Twitter.

Riddler Express

From Jamie Wilkowski, who suggests that you think outside of the box:

What is the missing letter in the sequence below?

Submit your answer

Riddler Classic

From Michael Branicky, your card has been declined:

Lucky you! You’ve won two gift cards, each loaded with 50 free drinks from your favorite coffee shop, Riddler Caffei-Nation. The cards look identical, and because you’re not one for record-keeping, you randomly pick one of the cards to pay with each time you get a drink. One day, the clerk tells you that he can’t accept the card you presented to him because it doesn’t have any drink credits left on it.

What is the probability that the other card still has free drinks on it? How many free drinks can you expect are still available?

Submit your answer

Solution to last week’s Riddler Express

Congratulations to 👏 Andrea Ceres 👏 of Glen Rock, New Jersey, winner of last week’s Riddler Express!

Last week, you played your first ever game of “Ticket to Ride,” a contest in which players compete to lay down railroad tracks on a map of the country. At the start of the game, you were randomly dealt a set of three Destination Tickets out of a deck of 30 different tickets. (Each revealed two terminals you had to connect with a railroad to receive points.) During the game, you eventually picked up another set of three Destination Tickets, so you saw six of the 30 tickets in the game. Later, because you enjoyed the game so much, you and your friends played again. The ticket cards were all returned and reshuffled. Again, you were dealt a set of three tickets. Which was more likely, that you had seen at least one of the tickets before or that they were all new to you?

Although the chances of each were very similar, it was ever slightly more likely that you had seen one of the tickets before.

Let’s work out the chances that each of the three tickets you drew in the second game had previously been unseen by you. There were 24 tickets in the deck of 30 that you hadn’t seen. Therefore, there was a 24/30 chance that you would draw one of them as your first ticket, a 23/29 chance that you would draw one of them as your second ticket assuming that your first ticket was new, and a 22/28 chance that you would draw one of them as your third ticket assuming that your first and second tickets were new. That’s a (24/30)(23/29)(22/28) ≈ 49.85 percent that all three tickets were previously unseen. Therefore, the chance that you had seen one before, in your first game, was 50.15 percent.

And by the way, good luck building that route from Seattle to New York!

Solution to last week’s Riddler Classic

Congratulations to 👏 Nir Jacoby 👏 of New York City, winner of last week’s Riddler Classic!

Last week, you and nine others were competing in a spelling bee. You could each spell words perfectly from a certain portion of the dictionary but would misspell any word not in that portion. Specifically, you had 99 percent of the dictionary down cold, and your opponents had 98 percent, 97 percent, 96 percent and so on down to 90 percent memorized. The bee’s rules were simple: You took turns spelling in some fixed order, and at the end of a round, you started again with the first surviving speller. If you missed a word, you were out. And the last speller standing won. The bee words were chosen randomly from the dictionary.

If the contestants went in decreasing order of knowledge, so that you went first, what were your chances of winning the bee? If the contestants went in increasing order of knowledge, so that you went last, what were your chances of winning?

Not surprisingly given your prodigious word knowledge, you were an odds-on favorite in this field of 10. Somewhat surprisingly, however, the order in which contestants take their turns doesn’t matter much. If you had gone first, your chances of winning were about 52.0 percent. If you had gone last, your chances of winning were about 52.5 percent.

Essentially what we are trying to calculate is the probability that all of your competitors err before you do in the two scenarios. Solver Anthony Mulieri explained how to do this with probability theory:

The probability of your getting N-1 words correct and then getting one wrong is modeled by the geometric distribution (\(.01 \cdot .99^{N-1}\)). Therefore, to win before that happens, we want to calculate the probability that none of the other contestants would have correctly spelled every word they were given by then. This can be modeled with the binomial distribution, where the contestant with \(X\) of the dictionary memorized has a \(1 – X^N\) chance of getting all of those \(N\) words correct. These probabilities can then be multiplied together for \(X\) from 0.90 to 0.98 (all of your competitors) and multiplied again with \((.01 \cdot .99^{N-1})\). Summing this from \(N=0\) to \(N=\infty\) (all the numbers of words you might be posed), we arrive at our answer of about 52.5 percent. Additionally, since this counted on your failing after getting the same number right as the other players, this is the solution for when you come last in the spelling order. To get the solution when you are first in the order, just take the same terms but use \((.01 \cdot .99^N)\) instead of \((.01 \cdot .99^{N-1})\). That gives about 52.0 percent.

You could also tackle this problem with computer spelling simulations, as many solvers did. Bradley Gannon and Josh Nees were kind enough to describe their approaches and share their code. As Josh explained, the slight advantage to going last is related to the “last player standing” rule: “The winning player does not actually have to spell a word in the final round because the game ends when their last competitor misspells a word.”

And finally, Tyler Barron plotted the chances of winning for not just you but each of your fellow spellers under both the best-first and best-last ordering regimes:

The “worst” speller in the bee has less than a 0.5 percent chance of winning, it turns out. So you’re telling me I memorized 90 percent of the dictionary for nothing?!

Want more riddles?

Well, aren’t you lucky? There’s a whole book full of the best puzzles from this column and some never-before-seen head-scratchers. It’s called “The Riddler,” and it’s in stores now!

Want to submit a riddle?

Email me at [email protected]

When We Say 70 Percent, It Really Means 70 Percent

One of FiveThirtyEight’s goals has always been to get people to think more carefully about probability. When we’re forecasting an upcoming election or sporting event, we’ll go to great lengths to analyze and explain the sources of real-world uncertainty and the extent to which events — say, a Senate race in Texas and another one in Florida — are correlated with one another. We’ll spend a lot of time working on how to build robust models that don’t suffer from p-hacking or overfitting and which will perform roughly as well when we’re making new predictions as when we’re backtesting them. There’s a lot of science in this, as well as a lot of art. We really care about the difference between a 60 percent chance and a 70 percent chance.

That’s not always how we’re judged, though. Both our fans and our critics sometimes look at our probabilistic forecasts as binary predictions. Not only might they not care about the difference between a 60 percent chance and a 70 percent chance, they sometimes treat a 55 percent chance the same way as a 95 percent one.

There are also frustrating moments related to the sheer number of forecasts that we put out — for instance, forecasts of hundreds of U.S. House races, or dozens of presidential primaries, or the thousands of NBA games in a typical season. If you want to make us look bad, you’ll have a lot of opportunities to do so because some — many, actually — of these forecasts will inevitably be “wrong.”

Sometimes, there are more sophisticated-seeming criticisms. “Sure, your forecasts are probabilistic,” people who think they’re very clever will say. “But all that means is that you can never be wrong. Even a 1 percent chance happens sometimes, after all. So what’s the point of it all?”

I don’t want to make it sound like we’ve had a rough go of things overall.1 But we do think it’s important that our forecasts are successful on their own terms — that is, in the way that we have always said they should be judged. That’s what our latest project — “How Good Are FiveThirtyEight Forecasts?” — is all about.

That way is principally via calibration. Calibration measures whether, over the long run, events occur about as often as you say they’re going to occur. For instance, of all the events that you forecast as having an 80 percent chance of happening, they should indeed occur about 80 out of 100 times; that’s good calibration. If these events happen only 60 out of 100 times, you have problems — your forecasts aren’t well-calibrated and are overconfident. But it’s just as bad if they occur 98 out of 100 times, in which case your forecasts are underconfident.

Calibration isn’t the only thing that matters when judging a forecast. Skilled forecasting also requires discrimination — that is, distinguishing relatively more likely events from relatively less likely ones. (If at the start of the 68-team NCAA men’s basketball tournament, you assigned each team a 1 in 68 chance of winning, your forecast would be well-calibrated, but it wouldn’t be a skillful forecast.) Personally, I also think it’s important how a forecast lines up relative to reasonable alternatives, e.g., how it compares with other models or the market price or the “conventional wisdom.” If you say there’s a 29 percent chance of event X occurring when everyone else says 10 percent or 2 percent or simply never really entertains X as a possibility, your forecast should probably get credit rather than blame if the event actually happens. But let’s leave that aside for now. (I’m not bitter or anything. OK, maybe I am.)

The catch about calibration is that it takes a fairly large sample size to measure it properly. If you have just 10 events that you say have an 80 percent chance of happening, you could pretty easily have them occur five out of 10 times or 10 out of 10 times as the result of chance alone. Once you get up to dozens or hundreds or thousands of events, these anomalies become much less likely.

But the thing is, FiveThirtyEight has made thousands of forecasts. We’ve been issuing forecasts of elections and sporting events for a long time — for more than 11 years, since the first version of the site was launched in March 2008. The interactive lists almost all of the probabilistic sports and election forecasts that we’ve designed and published since then. You can see how all our U.S. House forecasts have done, for example, or our men’s and women’s March Madness predictions. There are NFL games and of course presidential elections. There are a few important notes about the scope of what’s included in the footnotes,2 and for years before FiveThirtyEight was acquired by ESPN/Disney/ABC News (in 2013) — when our record-keeping wasn’t as good — we’ve sometimes had to rely on archived versions of the site if we couldn’t otherwise verify exactly what forecast was published at what time.

What you’ll find, though, is that our calibration has generally been very, very good. For instance, out of the 5,589 events (between sports and politics combined) that we said had a 70 chance of happening (rounded to the nearest 5 percent), they in fact occurred 71 percent of the time. Or of the 55,853 events3 that we said had about a 5 percent chance of occurring, they happened 4 percent of the time.

We did discover a handful of cases where we weren’t entirely satisfied with a model’s performance. For instance, our NBA game forecasts have historically been a bit overconfident in lopsided matchups — e.g., teams that were supposed to win 85 percent of the time in fact won only 79 percent of the time. These aren’t huge discrepancies, but given a large enough sample, some of them are on the threshold of being statistically significant. In the particular case of the NBA, we substantially redesigned our model before this season, so we’ll see how the new version does.4

Our forecasts of elections have actually been a little bit underconfident, historically. For instance, candidates who we said were supposed to win 75 percent of the time have won 83 percent of the time. These differences are generally not statistically significant, given that election outcomes are highly correlated and that we issue dozens of forecasts (one every day, and sometimes using several different versions of a model) for any given race. But we do think underconfidence can be a problem if replicated over a large enough sample, so it’s something we’ll keep an eye out for.

It’s just not true, though, that there have been an especially large number of upsets in politics relative to polls or forecasts (or at least not relative to FiveThirtyEight’s forecasts). In fact, there have been fewer upsets than our forecasts expected.

There’s a lot more to explore in the interactive, including Brier skill scores for each of our forecasts, which do account for discrimination as well as calibration. We’ll continue to update the interactive as elections or sporting events are completed.

None of this ought to mean that FiveThirtyEight or our forecasts — which are a relatively small part of what we do — are immune from criticism or that our models can’t be improved. We’re studying ways to improve all the time.

But we’ve been publishing forecasts for more than a decade now, and although we’ve sometimes tried to do an after-action report following a big election or sporting event, this is the first time we’ve studied all of our forecast models in a comprehensive way. So we were relieved to discover that our forecasts really do what they’re supposed to do. When we say something has a 70 percent chance of occurring, it doesn’t mean that it will always happen, and it isn’t supposed to. But empirically, 70 percent in a FiveThirtyEight forecast really does mean about 70 percent, 30 percent really does mean about 30 percent, 5 percent really does mean about 5 percent, and so forth. Our forecasts haven’t always been right, but they’ve been right just about as often as they’re supposed to be right.

Our Organ Donation System Is Unfair. The Solution Might Be Too.

At any given time, there are about 13,000 people waiting for a liver transplant in the United States. Whether the cause is a virus, alcoholism or a bit of genetic bad luck, they’re all suffering while sick and scarred livers struggle to clean their blood. Over time, their intestines bleed. Fluid builds up in their legs and their chests. Their skin turns sallow. Confusion sets in. The only cure is to swap the old liver for a healthy one. Each year, about 8,000 people will get that chance. The rest will wait, getting sicker.

There are always more people who need a new organ than there are organs available. That’s true all over the country, but not every place has the same number of available organs. Some regions have more registered donors, which means how long you have to wait for a liver is partly determined by where you happen to live.

At the end of the month, that’s set to change. The organization that manages the national organ transplant system is trying to make the wait time for donated livers more equal nationwide. It might be a preview of what’s to come for all organ-donation systems, and it’s proving to be controversial. It’s created factions among transplant surgeons. Senators have gotten involved. At least one state has proposed legislation to keep organs donated by its citizens within state borders. It’s a fight over the definition of fairness, experts say, where a seemingly simple effort to reduce geographic inequity in organ donation could end up exacerbating even bigger inequities in health care access.

Organ donation is good and kind, but it isn’t fair. For a healthy organ to save someone’s life, another family has to have the worst day of their lives. To get a lung or a heart or a liver, somebody has to die — ideally while they are young enough that the donated organ isn’t on its last legs.

One of the best ways to do that is to get more people to agree to become organ donors before something bad happens, said David Fleming, president of Donate Life America, a nonprofit that works to increase organ donation nationwide. That way the decision is already made and not left up to grieving, shocked families. But the rate at which healthy Americans choose to sign up as potential organ donors varies a lot from state to state. In some states, like Montana and Alaska, nearly the entire adult population is registered. Others, like New York and Mississippi, hover at less than 40 percent.

Organ donation registration rates vary dramatically by state
State/territory Share of adults registered as organ donors
Montana 93%
Alaska 92
Washington 89
Oregon 79
Utah 78
Indiana 75
Missouri 73
Alabama 72
Iowa 72
Louisiana 71
Maine 69
Kansas 68
Colorado 66
South Dakota 66
North Dakota 65
Virginia 65
Arkansas 64
District of Columbia 64
Idaho 64
New Hampshire 64
Ohio 64
Minnesota 63
Wisconsin 63
Maryland 62
Massachusetts 62
Michigan 62
New Mexico 62
North Carolina 62
Arizona 61
Georgia 61
Hawaii 61
Illinois 60
Vermont 60
Florida 59
Oklahoma 59
Rhode Island 59
Wyoming 58
Delaware 56
Nebraska 56
Kentucky 54
South Carolina 51
Nevada 49
Texas 49
Connecticut 48
California 47
Pennsylvania 47
Tennessee 43
West Virginia 41
New Jersey 40
Mississippi 37
New York 32
Puerto Rico 22

Source: Donate Life America

That disparity matters because, historically, the national system of determining who gets a donated organ has been deeply regional. There are 58 Organ Procurement Organizations, nonprofits that handle the process of talking to families, coordinating with hospitals and setting up the movement of an organ from one body to another. Each of those organizations has a geographical area it covers. The United Network for Organ Sharing, a private nonprofit that contracts with the federal government to manage the national organ transplant system, traditionally uses those boundaries as part of determining which patients on the waiting list get first crack at an organ. When a donor dies, the sickest patients in the same OPO have first dibs, essentially.

There are, obviously, problems with this system, said Brian Shepard, CEO of UNOS. Not only does it put patients in states with higher donor-registration rates at an advantage, it’s also drawn up in a pretty arbitrary way. For example, Iowa and Nebraska each have their own OPOs, but both states have a county or two covered by the other’s OPO. Another OPO covers all of Kansas and an odd chunk of western Missouri that’s roughly shaped like a pair of pants with a lot of thigh gap. “Texas has OPOs that have non-contiguous pieces,” Shepard said.

It’s the kind of seemingly random inequality that ends in a lawsuit. Last July, six patients on the liver transplant waiting list sued UNOS and the federal Organ Procurement and Transplantation Network, calling the policy illegal and inequitable. Those patients were from New York, California and Massachusetts. New York and California both have comparatively low rates of donor registration, and both are in regions that have longer wait times than parts of the Midwest and South.1 For instance, a patient with Type B blood who was added to the registry between 2003 and 2006 waited a median of 1,223 days for a new liver in the New York region and a median of 303 days in the region that includes Kansas. If you’re a New Yorker, that doesn’t seem very fair.

The lawsuit is still active, but it has already pushed UNOS toward changes it had long been considering, said Keren Ladin, who is a professor of public health and community medicine at Tufts University and has published research on geographic disparities in liver distribution. Potential organ donors — people who have signed up to be on the registries — aren’t evenly distributed, but maybe organs could be.

To do that, UNOS came up with a new system that will be put into action on April 30. Under the new rules, patients get first priority for newly donated livers if they are in danger of imminent death and live within a 500-mile radius of the deceased donor — OPO borders be damned. If there aren’t any patients within 500 miles who are that sick, then the livers will be offered to the next-sickest patients within a 150-mile radius. Then those in a 250-mile radius. Then 500. That could mean a patient in New York would suddenly have access to a liver from Philadelphia, which under the OPO system would be off-limits to the New Yorker but could go to a patient from West Virginia.

But just like some New Yorkers and Californians thought the old system was unfair, people from states like Missouri and Iowa see unfairness in the new system. In January, 22 senators signed an open letter to the Department of Health and Human Services demanding answers about how the new policy would affect rural communities. In February, the Kansas state legislature introduced a bill that would allow organ donors to specify that they want their body parts to go only to in-state recipients. It has the backing of doctors at the University of Kansas Medical Center’s liver transplant center.

And that, Ladin said, also makes sense because the new plan really could be unfair. Kansas’s health care infrastructure is already inferior to New York’s. Taking its organs out of the state would only exacerbate the Kansas system’s failings.

And those inequities in health care begin with the organs themselves. Donor registration matters, but donor registration isn’t really the thing that creates donors. Deaths do. “Donors get created because of poor access to care: strokes, heart attacks, bad roads,” said Richard Gilroy, who is medical director of liver transplantation at Intermountain Healthcare in Salt Lake City and was on the UNOS liver committee that ultimately voted for the new rules, although he opposes the rule change.

Look at it this way: Kansans may be generous with their organs — 68 percent of them are registered donors. But Kansas also has a higher rate of stroke deaths than New York does, and New York has a lower rate of accidental deaths than Kansas. New Yorkers have a longer wait time for organs partly because they’re less likely to die of the kind of misfortunes that turn registrants into donors.

Moreover, residents of states with better health care systems — like New York — have a greater likelihood of being diagnosed and listed as needing an organ donor to begin with, Gilroy said. And New York has more comprehensive Medicaid coverage than Kansas does, which also means that there are people who can afford to get a liver transplant in New York but couldn’t in Kansas. “Part of the workup is a wallet biopsy,” Ladin said. Patients have to prove that they can afford the drugs needed after the operation. “So already a disparity exists in states with a weaker safety net,” she said. Ultimately, despite the shorter transplant waiting list, Kansans are more likely to die from liver disease than New Yorkers are. To Gilroy, that makes the change look less like a leveling of wait times and more like redistributing health care from people who already have less to people who already have more.

And this is what complicates the fight over liver distribution: There’s more than one thing that’s unfair about the system. That frustrates both Ladin and Fleming, who told me that they see good arguments on both sides of a gaping divide that’s only likely to get bigger because other organ transplant systems are on track for similar changes. Regardless of who is correct here, the bigger problem is that the changes are just shuffling organs around — altering which patients get a liver, not increasing the number of patients who get one. Without that, they said, there’s always going to be someone who waits, and dies.

Abolishing The Electoral College Used To Be A Bipartisan Position. Not Anymore.

Twice in the past five presidential elections, a Republican has won the presidency despite losing the popular vote. Now Democratic Sen. Brian Schatz of Hawaii has introduced a constitutional amendment to abolish the Electoral College and use the national popular vote to decide who becomes president. His proposal is among the latest efforts by Democrats and those on the left to push for structural changes to the American political system.

But Schatz’s amendment is sure to meet defeat in the Republican-controlled Senate. Today, attitudes toward the Electoral College are polarized by party, with Democrats far more likely to support a change and Republicans much more likely to defend the current system — but it wasn’t always like that.

While the controversial 2000 election was still being decided, Gallup found that 61 percent of Americans — including 73 percent of Democrats and 46 percent of Republicans5 — preferred amending the Constitution to elect the popular vote winner. Only 35 percent of respondents preferred the current system. The partisan gap widened even further after the 2016 election: A few weeks after President Trump won the presidency while losing the popular vote, Gallup found that 49 percent of Americans preferred changing to a popular vote system, compared to 47 percent who wanted to keep the Electoral College, with 81 percent of Democrats supporting a change compared to just 19 percent of Republicans.6 Even given some space after that heated election, there remains a major partisan gap in opinion over how to elect a president — Pew Research found in March 2018 that 75 percent of Democrats supported moving to a popular-vote system versus only 32 percent of Republicans.

But 50 years ago, moving on from the Electoral College had bipartisan support. In May 1968, 66 percent of American approved of the idea of amending the constitution to replace the Electoral College with a popular vote system, according to Gallup. And there was no partisan divide: 66 percent of Republicans and 64 percent of Democrats approved. Six months later, Republican Richard Nixon defeated Democrat Hubert Humphrey while only winning the popular vote by less than 1 percentage point, and a post-election Gallup survey found 80 percent of Americans approved of changing the electoral system. The bipartisan support among voters and the fact that the 1968 election nearly produced a split between the popular vote and the Electoral College7 explain why there was bipartisan support in Congress in 1969 for a constitutional amendment to elect presidents based on the popular vote. The House passed it 339 to 70, with more than 80 percent of each party’s voting members lending their support. But small-state senators from both parties filibustered the amendment and it never got an up-or-down vote in the upper chamber.

As long as one side feels disadvantaged by the Electoral College, it will be far more likely to push for a popular-vote system. Right now, that’s the Democrats. Reforming how the country elects presidents falls into the broad effort on the left to reform aspects of our electoral system, including voting access and how campaign finance works. But some who want reform believe abolishing the Electoral College should be a secondary goal. “There’s a bunch of stuff to do without amending the constitution that would have the end result of making institutions and elections more fair,” said David Faris, a political scientist at Roosevelt University, who recently argued in his book “It’s Time To Fight Dirty” that Democrats should be challenging the structural and legal boundaries of the American political system to better gain and hold power. Nonetheless, Faris sees discussion over the electoral system as a good thing in that it could soften up public opinion and make people more willing to consider alternatives to the status quo.

But we may not see a true shift in public opinion unless a Republican loses in the Electoral College while winning the popular vote. As FiveThirtyEight has argued in the past, the system is not inherently biased against either party, with one side’s seeming advantage lasting for just an election or two before it flips to the other party. But as the 1969-1970 example shows, it seems likely that only serious bipartisan support for abolishing the Electoral College system could ever change how we elect a president. Although states may figure out a way around the Electoral College with the National Popular Vote interstate compact, it would not seem as permanent as a constitutional amendment, given that only one amendment has ever been repealed. And as Faris argues, using the interstate compact method might precipitate a crisis because an outcome might be seen as illegitimate and be subject to legal challenges if it delivers a result that contravenes what the Electoral College would otherwise do.

Schatz’s proposal is unlikely to pass the Senate, but it may be a symbolic effort to influence the conversation about what we want our electoral system to look like. Nonetheless, without broader agreement, a constitutional amendment to abolish the Electoral College will pass when pigs fly.

From ABC News:
Sen. Elizabeth Warren wants to get rid of the Electoral College

The Royals Are MLB’s Fastest Team In Years

With a blazing average of 4.07 seconds to first base — that’s 15.1 miles per hour — Kansas City Royals shortstop Adalberto Mondesi was one of the fastest players in Major League Baseball last season. But this year, he’s not even the fastest player on his own team. That honor belongs to new center fielder Billy Hamilton, who runs to first in an astonishing 3.94 seconds. Fourth outfielder Terrance Gore might not be much slower, either, and none of those guys is even the reigning MLB leader in stolen bases — which K.C. right fielder Whit Merrifield happens to be. These are the 2019 Royals: The fastest baseball team assembled in years.

It was clear from the start that this team’s identity would be all about running as fast as possible: “We want to be a motion team,” general manager Dayton Moore told MLB.com in February. “We have to be elite at some aspects of the game, and defense and speed is something we can be elite at.” And Kansas City has already put that speed to good use in its season-opening games against the Chicago White Sox, with Merrifield and Chris Owings swiping three combined bases and Mondesi hitting two triples in a 2-1 series victory.

If the 2014 and 2015 Royals were an experiment in whether a talented small-ball team could win a championship in the modern game (it worked), this year’s version will be more about how much pure speed can make up for a lack of talent in other areas. The Royals might not be “good” per se — but in an era when just about every team is constructed according to the blueprint of advanced analytics, they will be different, and that might have value in itself.

Certainly last season’s Royals could not have been described as anything other than abysmal. K.C. went 58-104, the team’s worst record in 13 years, and had only five regulars1 in common with the 2015 championship club: Alex Gordon, Salvador Perez, Alcides Escobar, Danny Duffy and Mike Moustakas. (Moustakas was then traded to Milwaukee in July; Escobar signed with the White Sox over the offseason.) The Royals were sixth-to-last in scoring and fourth-worst in runs allowed, with a defense tied as the fourth-least efficient in baseball. This was far removed from the team that celebrated the franchise’s second world title just three years earlier.

This year’s team is projected to be better yet still far from first place. The preseason FiveThirtyEight forecast called for Kansas City to improve all the way to 70 wins, though most of that change could be attributed to regression toward the mean rather than any specific additions. (In fact, K.C.’s most notable roster development since last fall was the news that Perez, a six-time All-Star, would miss the whole 2019 season with an elbow injury.) The projections were also low on both the 2014 and 2015 Royals, getting blindsided entirely by their World Series runs, but at least those teams had established, scout-approved talent with some sort of a track record and upside. The 2019 Royals don’t pass the eye test any more than they impress the computers.

The projected speed in this lineup, however, is the genuine article. According to FanGraphs’ preseason depth chart projections, Royal hitters were forecast to swipe 168 bases this year, which represented 6.2 percent of the total steals predicted for all of MLB.2 If Kansas City hits that benchmark, it would become only the sixth team since 1996 to claim at least 6.2 percent of leaguewide stolen bases. The 2016 Brewers did it recently, but mostly that rate was a hallmark of teams from the 1960s, ’70s and ’80s, when gaudy steal totals were the norm and not every team had settled into similar offensive philosophies guided by sabermetrics.

The speed of these Royals emerges in other metrics as well. I filtered down every opening day lineup since 1950 for those that contained at least eight players who had logged 200 or more plate appearances during the previous year. Then, for each lineup, I averaged two numbers from its players in the season before: Speed Score — a Bill James invention that estimates raw speed by combining stolen bases (both attempts and successes), triples and runs scored as a percentage of times on base — and FanGraphs’ Base Running (BsR) statistic, which quantifies the run value of every base-running action (including steals and advancement on other events). The 2019 Royals’ average Speed Score is tied for 24th since 1950, and its average BsR per 600 plate appearances ranks 71st; only 12 opening day lineups were faster by both measures, and half of those played during the nine-season span from 1978 to 1986, a heyday for running teams.

So this is basically an ’80s-style team of burners, in the mold of the Whitey Herzog St. Louis Cardinals,3 dropped down into the modern major leagues. And Kansas City’s speedsters are off to a blazing start already, easily leading baseball in Speed Score through the first weekend of the season with an eye-popping 8.5 mark. (The MLB average is about 4.4 in recent seasons, with the leader topping out around 5.4 most years.)

The Royals’ next step, though, is turning all that speed into more tangible results. Perhaps most surprising in Kansas City’s portfolio of badness last year is that the team was somehow MLB’s fifth-worst at base running (according to BsR) despite the steals-leading presence of Merrifield atop the lineup for most of the year. The Royals’ speed was above average — if not quite as impressive as this season — but they didn’t use it well, particularly between bases in advancement scenarios. According to FanGraphs, K.C. lost 12 runs (more than an entire win) relative to the average team in base-running situations that didn’t involve steals. One of the ways K.C. can improve this year is to deploy its running game in a smarter way, using it to take advantage when opponents inevitably offer up chances to take extra bases.

That’s an area in which Kansas City might take a cue from its 2014-15 teams, which were legendary for their opportunism on the base paths. Take the famous ninth-inning play that extended Game 5 of the 2015 World Series: Eric Hosmer’s heads-up sprint from third base to home on a weak groundout, a daring piece of aggressive base running that forced an errant throw by Mets first baseman Lucas Duda and tied the ballgame. The Royals would eventually score five 12th-inning runs off New York’s beleaguered bullpen to secure the championship.

Hosmer (career Speed Score: 4.0) wasn’t even fast, so imagine how much more damage Hamilton, Mondesi, Merrifield and friends could do if they pick their base-running spots correctly. Along the same lines, Kansas City is also hoping this speedy roster can emulate the 2015 Royals’ defense, which according to FanGraphs was the best in baseball in terms of runs saved relative to average.

Larger issues, such as the team’s dismal .305 on-base percentage last season, might place hard limits on how much value Kansas City can get out of its speed this year. (Even Sunday, the team was being no-hit by Chicago’s Lucas Giolito — owner of a career 5.48 earned run average going into the game — into the seventh inning.) But no matter what, it should at least be more worthwhile to watch the fleet Royals this season, both for the entertainment of all those steals and as an experiment in against-the-grain team-building.

Check out our latest MLB predictions.

11 Senators Want To Know Why The CDC’s Gun Injury Estimates Are Unreliable

Eleven senators have sent a letter to the head of the Department of Health and Human Services, demanding answers to a series of questions about the Centers for Disease Control and Prevention’s nonfatal firearm injury estimates. The inquiry relies on the findings of an investigation by The Trace, a nonprofit news organization covering gun violence in America,1 and FiveThirtyEight, and is led by Democratic Sen. Bob Menendez of New Jersey.

The Trace and FiveThirtyEight first reported last year that the CDC’s 2016 gun injury estimate was so uncertain the agency classified it as “unstable and potentially unreliable.” Since then, the agency’s data, which in 2017 was derived from a sample of just 60 hospitals, has become even more unreliable. The CDC’s gun violence estimates are widely cited in academic articles.

“Given that the CDC is not currently conducting gun violence research,” the letter reads, “the very least the agency can do is to ensure that its gun injury numbers are accurate.”

The letter asks HHS Secretary Alex Azar to explain the CDC’s methods for tracking nonfatal firearm injuries, the cause of its increasingly unreliable estimates, and whether the agency has undertaken any actions to improve the quality of its data. The senators also ask whether the Dickey Amendment — a piece of 1996 legislation that bars the CDC from using its funding to “advocate or promote gun control” — has played any role in the agency’s continued reliance on a data source that’s ill-suited for producing firearm injury estimates.

“We as lawmakers, as every American citizen, should be able to follow and understand the latest trends on firearms injuries without the concern of coming across ‘unstable and potentially unreliable’ data,” Menendez told The Trace in an email.

The CDC has previously acknowledged its estimates have a high degree of uncertainty. “CDC continues to look into various ways to strengthen the estimates for nonfatal firearm injuries,” said spokesperson Courtney Lenard in an email.

Researchers interviewed by The Trace and FiveThirtyEight believe the CDC’s estimates are too flawed to use. Guohua Li, editor-in-chief of the medical journal Injury Epidemiology and director of Columbia University’s Center for Injury Epidemiology and Prevention, said the estimates could be improved by drawing upon a larger and more reliable source of data, such as another database administered by HHS.

Menendez makes reference to this proposed solution in the letter, writing, “There appears to be no rational reason that the CDC and HHS use different databases.”

The letter was also signed by Democratic Sens. Cory Booker, Kirsten Gillibrand, Mazie Hirono, Richard Blumenthal, Amy Klobuchar, Kamala Harris, Tina Smith, Chris Murphy and Chris Van Hollen and independent Angus King. The letter asks Azar to respond by April 20.

Significant Digits For Friday, March 29, 2019

You’re reading Significant Digits, a daily digest of the numbers tucked inside the news.

More than 300 pages

The full report of special counsel Robert Mueller is more than 300 pages long, according to the Justice Department. However, all that has been made public is Attorney General William Barr’s summary, which is four pages long. In the context of government reports, Mueller’s isn’t an outlier — the Starr report ran 445 pages, the 9/11 commission report 567 pages, and a report on how the FBI handled an investigation into Hillary Clinton’s use of a private email server was 568 pages. [The New York Times]

More than 1,000 passengers

Wow Air, a budget carrier out of Iceland, ceased operations on Thursday, stranding travelers on multiple continents and affecting more than 1,000 passengers. I’ve heard of canceled flights, but never a canceled airline. “I’m disappointed not to honor our commitments,” the Wow CEO said — those commitments being, like, getting people back across the Atlantic Ocean. [CNN]

6,227 pedestrians

More than 6,000 pedestrians died in traffic accidents in 2018, according to the Governors Highway Safety Association, the highest number in three decades. Experts, according to NPR, attribute the rise to “drivers and pedestrians distracted by their phones” along with an increase in large vehicles. [NPR]

More than $1 trillion

Amy Klobuchar — Democratic candidate for president, senator from Minnesota, and reported eater of salad with comb — wants to “break the partisan logjam” and professes to be able to do so with a $1 trillion infrastructure plan to improve America’s roads and bridges, public schools, and broadband internet. She reportedly plans to make infrastructure, the betterment of which has bipartisan support, a centerpiece of her campaign. [The Wall Street Journal]

5-point window

Despite the seemingly constant clangor from the White House and Washington, D.C., President Trump’s approval ratings remain incredibly steady. Half of his approval polls have fallen with a band of 5 points, between 39 percent and 44 percent. Only President Barack Obama rivaled that narrow range, while every other president back to Harry Truman saw wider ranges, and in many cases much wider. “As Democrats and Republicans move farther apart politically,” my colleague Geoffrey Skelley writes, “the specifics of a president’s job performance may become secondary considerations for voters in forming an opinion of how he’s doing.” [FiveThirtyEight]

184 of the 270 votes

The governor of Delaware signed a law pledging that that state’s Electoral College votes will go to the winner of the national popular vote in the presidential election, regardless of who actually wins the state itself. Delaware is the 13th state to commit to such a pledge, and those states now represent 184 of the 270 Electoral College votes needed to elect a president. [Associated Press]

From ABC News:
It's Morning, America: Friday, March 29, 2019

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