Tag: analytics

As I’ve gotten older, I’ve realized that, in almost any field, from sports to politics to economics to media to parenthood, there are essentially two types of people: people who want new information, and people who don’t. You have people who are trying to learn, and you have people who have decided that what they already think is just fine, thank you. Perhaps not coincidentally, as the years go by, the first group tends to transform inexorably into the second. But — and this is what’s most important — in the end, the second group always loses.

On Sunday, the long-suffering Detroit Lions, trying to reach their first Super Bowl ever, blew a 17-point lead to the San Francisco 49ers in the NFC Championship Game on Sunday. Many, many things went wrong for the Lions during a nightmarish second half, from dropped passes to untimely penalties to a freakish, act-of-God play in which a Lions defender had a pass bounce through his hands and off his helmet and somehow end up with a game-changing 49ers 51-yard play that led to momentum-shifting touchdown:

Of all the things that went wrong for the Lions, though, the takeaway from many old-school NFL observers the morning after was: They used too much math.

The reason? Lions coach Dan Campbell, a hyperaggressive metalhead former linebacker who looks and acts like a professional wrestler and thus no one’s idea of a pencil pusher, uses analytics. Specifically, he, guided by his analytically driven front office, followed statistical probability in his decision making rather than whatever may or may not have been in his gut. Thus, Campbell passed on multiple opportunities to kick field goals (worth three points) and instead go for touchdowns (six points; 6 > 3) in key moments, and, unfortunately for him and his team, the probabilities didn’t pay off for him; the Lions missed on two huge fourth-down plays, which led directly to the 49ers victory.

As someone who has obsessed over baseball for as long as I’ve known baseball exists, it is difficult to overstate the impact analytics had on how I (and so many others) viewed the game, thanks to the analytical baseball writers like Bill James and Rob Neyer who introduced me (and countless others) to this lens. So much of what I thought I knew about the game was wrong. Walks really were as good as a hit; the most important thing a hitter can do is get on base; strikeouts are not that big of a deal; RBIs and batting average are pointless stats; the hit-and-run is counterproductive and sort of dumb. How could I have known so little about something I loved so much? Those writers, along with the crew at Baseball Prospectus (boosted by Michael Lewis’s best seller and subsequent movie Moneyball), didn’t just change the way I thought about baseball; they changed how generations of fans — and, eventually, front offices and players — thought about baseball. The sport quite famously resisted this change for many years, and if you listen to John Smoltz or any other of a number of older, crotchety baseball television broadcasters, you might think that debate remains unsettled. But the war is over. There isn’t a baseball team that isn’t run by the very stat-heads who were once the outcasts, and there isn’t a player who doesn’t know their spin rate or exit velocity. The reason for this is simple: Using analytics — which, at their core, exist simply to determine probabilities of success — gives you a better chance to win. People like to win. That’s why they play sports.

Every sport has been changed by the analytical revolution, from basketball (which now focuses on three-point shooting, thanks to the mind-blowing mathematical formula: 3 > 2) to soccer (which pays almost as much attention to “expected goals” as actual goals) to even boxing (sensor technology can actually quantify how much that face-punch just hurt). If there has been one sport that has been slowest to embrace their revolution, it has undeniably been the NFL. In fact, football seems to be going through the same dumb fights baseball went through 15 years ago. So it comes as no surprise that a whole bunch of John Smoltzes have decided the reason the Lions lost on Sunday night was not the dropped passes or a lack of execution but all that math.

Leading this charge has been Pro Football Talk’s Mike Florio, who in his well-read column on Monday morning voiced what he clearly hopes will become the new conventional wisdom: The math bros are ruining football.
 
“Enter analytics, the effort by mathematicians to infiltrate NFL front offices (and to get NFL paychecks) without possessing traditional football skills,” Florio sniffed. “It worked in baseball, so they decided to move it to football. Even if it doesn’t work nearly as well in football as the mathematicians insist.” Florio wasn’t alone in this complaint, but his practiced Luddite-ism was the most evocative of the same tired argument people made about baseball (and other sports) 20 years ago — before those arguments were rendered so ridiculous that no serious person could possibly make them anymore and still remain a part of their sport.

Coach Campbell’s decisions were not out of character: Going for it on fourth down was his modus operandi all season and was, in fact, a big part of why he and his team were a win away from the Super Bowl. The Lions are considered one of the more analytically driven front offices in the sport, one of the primary reasons they just had their best season in more than 30 years. But rather than recognize the Lions as the Moneyball Oakland A’s (or the NBA’s “Seven Seconds or Less” Phoenix Suns, another canonical analytical vanguard team) — a canary in the coal mine who other teams would end up emulating for years to come — the NFL’s tough guys (wannabe and otherwise) have decided that the very analytics that led the Lions to the NFC Championship Game are the reason they (and Campbell) lost it.

This is not to say that analytics are the be-all and end-all of the NFL any more than they are in any other sport: Even the wonkiest efficiency expert in the most McKinsey-esque MLB front office would tell you analytics are best mixed with on-field scouting and, of course, having big talented humans on your team who can run, throw, jump, and tackle. But the usefulness of analytics is a settled fact in every other sport, and the talking points these detractors use are now decades past their expiration date.

Campbell was simply doing what gave his team the best chance to win, which is what every coach has tried to do forever. One doesn’t need to be a “mathematician” to do so; Campbell certainly isn’t one. He just went for it on fourth down. His strategy didn’t work. But he made it clear after the game that he’d do it again. Because that’s what playing probabilities is. It sure beats trusting your gut. The NFL is a zero-sum game: Everyone’s trying to win. The rest of the NFL saw what the Lions did this year and will copy them. Most teams have already started. In 20 years, we will all see the Florios of the world as figures of mockery, just like we all do with those bygone baseball dinosaurs from 20 years ago. Meanwhile, coaches like Campbell will keep doing the same thing and thriving because of it. Sports are about winning and finding new ways to do it. And math always wins. That’s why it’s math.