Newton's Football, page 17
The Wonderlic? Not so much. While test scores aren’t made public, the leaked numbers that have been widely reported reveal that a large number of Hall of Fame quarterbacks put up less than stellar Wonderlic scores, including Peyton Manning’s 28 out of 50, Brett Favre’s 22, Terry Bradshaw’s 16, and Dan Marino’s 15.*
For all its flaws, NFL teams continue to use the Wonderlic—and a similar mental aptitude test that supplemented it in 2013. At some level, the football establishment realizes that, to paraphrase Yogi Berra, 90 percent of the game is half mental.
“I wanted to make sure Grandma could cross the street without getting killed,” Jocelyn Faubert admits, but his research at the University of Montreal may enhance the lives not only of senior citizens but of NFL general managers as well.
A neuroscientist, Faubert explains that one of the problems that the elderly encounter as they age is a diminished ability to process information in complex situations. In some cases—walking in a crowded store—this can be annoying. In others—crossing the street at a busy intersection—it can be outright dangerous.
“There’s a lot of information coming in, and older people are detecting the information, but they’re not necessarily interpreting it well,” he explains. “They slow down. They hesitate. It becomes scary. And when that happens people don’t want to leave the apartment.”
It ultimately became apparent to Faubert that the dangers that vex an elderly pedestrian on a busy street corner are not much different from those faced by a quarterback in the pocket. It’s all information processing.
A decade ago, Faubert got funding for a device that would help him study complex information processing in minds both fast and slow. Until that point, most brain researchers were interested in easily controlled, small-scale experiments on desktop screens. In an attempt to replicate real-world conditions more closely, Faubert created immersive environments—known colloquially as “caves”—with 3-D images projected in a room-sized booth.
“I wanted quite a large visual field. And there had to be some speed components, because we’re confronted with fast-moving elements and we have to make rapid decisions,” Faubert explains. “We found that we could train older observers to improve, and there was transfer of that training on socially relevant stimuli. We found that they were tremendously improved in anticipating body movements, so they can avoid collisions.”
In gathering data for the project, Faubert also enlisted younger volunteers, and the results for the athletes in that group surprised him. The researchers assumed that young people with an athletic background would start much higher than the seniors but wouldn’t have much room for improvement. “We found that wasn’t the case,” Faubert explains. “What we found is that athletes not only started off higher, but they also improved faster. There’s something special about how they can process this input and especially how they can learn it.”
Faubert soon realized that Grandma and a rookie quarterback both encounter the same information-processing challenges, just at vastly different levels. And that the same diagnostic tests that can assess Granny’s ability to walk across a four-lane intersection can also predict the fledgling QB’s ability to find an open receiver while avoiding a blitzing safety.
Faubert’s research culminated in a device called Neurotracker. It’s a commercial version of his research device which comes in several sizes, ranging from a room-sized installation to a portable version that runs through a 3D TV. While it’s even been used by hedge fund traders looking to sharpen their ability to make quick decisions, Neurotracker’s most interesting application has been to evaluate and train elite athletes. Among those using the device are Canadian women’s hockey team goalie Shannon Szabados, mogul skiing gold medalist Jennifer Heil, and players on the University of Tennessee and the University of Oregon football teams. At least one elite NFL team uses Neurotracker at the NFL Combine to evaluate its draft prospects.
What’s it like training with the Neurotracker?
In a word, challenging.
The goal is straightforward enough. The test begins with seven stationary yellow balls on a black background on the Panasonic 3D flatscreen. Four of the balls turn red for a moment and then turn back to yellow. The object is to keep track of those four previously red balls among the seven yellow balls. The balls move randomly on the screen, bouncing off the edges of the frame as well as one another, and then stop. At the end of a trial the subject now must identify the four “red” balls.
A trial lasts only eight seconds, but it’s very intense. Faubert’s description of the necessary skill—“hyperconcentration”—is quite apt. The task of finding those four red ones may look easy, but it’s anything but. It’s not terribly difficult to keep track of one or two of the balls, but when the balls are moving rapidly, it can be fiendishly hard to locate all of them.
The program doesn’t test a player’s reactions per se, like a video game such as Call of Duty. Neurotracker only tests the player’s ability to process information. Hand-to-eye coordination isn’t a factor. Neurotracker doesn’t give extra credit for clicking on the appropriate balls quickly. You can even call out the numbers and have a trainer enter them. It’s not about reflexes; it’s about accurate information processing.
Athletes begin with the core game, in which four balls move at a constant speed throughout each trial. The speed of the balls in the next trial is keyed to the player’s performance in the previous trial. So like a good coach, the software keeps upping the ante without approaching the point of overload. Once a player has established a baseline, the program starts throwing out variations. In some games, the balls speed up and slow down randomly. In others, the goal is to mark the balls in order, prioritizing the targets.
Neurotracker is all about progress. A normal person might start out at a baseline of Level 0.7 and in an hour improve by more than 40 percent to Level 1.0. But an elite athlete might start at Level 2.0, where the balls are moving at hyperspeed and bouncing around more dynamically. At those levels, a normal person can have trouble tracking even a single ball for the full eight seconds. If the four balls were actually blitzing linebackers, that failure to process information would result in a trip to the hospital.
A program like Neurotracker can provide valuable answers to an NFL GM. It can measure a quarterback’s ability to process information in a complex environment. And if the player runs a series of trials, it can assess something equally important: his ability to improve his information-processing skill. All of which could be vital information on Draft Day.
For researchers, the data is rich but remains somewhat difficult to parse.
“Is this a nature-or-nurture problem?” Faubert wonders. “It’s an open question still, and I think both are involved for sure. If you expose the kids very early, they build specialized circuits, and they’re off the blocks faster. But if you do this to two or three or four kids, you’re going to find some of them learn faster, and they’re the ones who get more experience from the same stimulation, and they become experts faster. I don’t think they’re separable, and in the end you need both.”
At least if you want to become an NFL quarterback.
* * *
* The all-time Wonderlic leader is Pat McInally. The Harvard grad–turned–Bengals punter is reportedly the only player to score a perfect 50 on the test. Former Giants GM George Young told McInally that his high score “may have cost you a few rounds in the draft because we don’t like extremes. We don’t want them too dumb, and we sure as hell don’t want them too smart.”
PART FOUR
THE FUTURE
“I have seen the future and it is much like the present … only longer.”
—DAN QUISENBERRY
CHAPTER 14
OF RISK, INNOVATION, AND COACHES WHO BEHAVE LIKE MONKEYS
It was early in the 2008 season, and the Miami Dolphins were already on the ropes.
They had lost their first two games, the second one an especially lopsided defeat to the Arizona Cardinals. Up next? A New England Patriots team that was riding an NFL-record regular-season winning streak of twenty-one games.
The Dolphins? They had been the worst team in football the previous season, with a 1–15 record. Miami had lost eight of their last eleven games against its division rival New England dating back to 2002.
Which is to say, this matchup did not favor the Dolphins.
On the long flight home after that disheartening loss to the Cardinals, Miami coach Tony Sparano pondered his options. He called quarterback coach David Lee up to the front of the plane.
What did they come up with? The idea of using a formation called the Wildcat, which Lee had employed while running the offense at the University of Arkansas. In the Wildcat, Arkansas star running back Darren McFadden would take the snap at center in lieu of the quarterback. The other running back, Felix Jones, would go in motion from left to right. The quarterback, meanwhile, would be lined up at wide receiver.
From this esoteric formation came three simple plays: Steeler, Power, and Counter. In Steeler, McFadden takes the snap, hands it off directly to Jones as he streaks in front of him, trying to outrun the defensive pursuit. In Power, McFadden gets the snap, fakes the handoff to Jones, and then runs straight ahead through a hole on the right side opened up by his blockers. Often McFadden would decide at the last moment whether to keep the ball or hand off, depending on the reaction of the defense. In Counter, McFadden takes the snap again, fakes to Jones, waits for the defense to commit to the right side, and then he runs left. Those three plays, along with a couple of basic passes by McFadden off that formation, made up the Wildcat.
The formation seemed radical, but it was hardly new. It borrowed elements of the single wing formation invented by Pop Warner, who ran it for the legendary Jim Thorpe. In 1907.
Sparano considered the way the Wildcat had made McFadden a star—he finished second in the Heisman Trophy voting twice. He considered that Miami’s two best players were running backs Ronnie Brown and Ricky Williams. And he considered his lack of other options.
“This is something really interesting we could do in a ball game,” Sparano told The Washington Post, “if we had enough nerve to bring it out there and call it.”
For an NFL coach like Tony Sparano, what’s the goal in each game?
To win?
Not so fast.
Sparano, like any other NFL coach, will tell reporters or anyone else who’ll listen that his job is to win the game. But deep down he has a meta-goal that takes precedence over winning: to keep his job so that he can coach the next game. Usually, winning the game at hand is a pretty good way to accomplish that. But not always. Sometimes it might be better to lose while following the conventional wisdom than to win by employing outside-the-box strategies that would encourage fans, the media, and front-office personnel to second-guess him. Going for it on 4th and 2, benching the starting quarterback, using an offense that hasn’t been employed in the league in fifty years—those are all ways for a coach to attract unwanted attention.
Most pro football coaches—who might not admit it—make decisions with this dynamic in mind, playing the game differently when they’re being scrutinized than they would in a vacuum.
Werner Heisenberg would understand. The German physicist won the Nobel Prize in 1932 for the discovery of quantum physics. The pioneer of the Uncertainty Principle, he observed a similar phenomenon in the physical world. Heisenberg argued that the mere process of observing an experiment can and often does change its outcome. For example, dipping a thermometer into a liquid to measure its temperature actually changes the temperature of the liquid slightly. A tire gauge lets out a tiny puff of air as it checks the pressure of your steel-belted radials, lowering the psi a small, but real, amount. “What we observe is not nature itself,” Heisenberg argued, “but nature exposed to our method of questioning.”
He called this the Observer Effect.
And on some level it’s clearly at work in the NFL. Which raises a question: What is it that spurs innovation in the NFL? And perhaps even more important, what prevents coaches and teams from innovating?
With nothing to lose, the NFL’s worst team prepared to face the best team, and Sparano’s Dolphins ran the Wildcat in practice. Some of Miami’s veterans were skeptical, noting that the unconventional formation forced players out of their comfort zones.
But on Sunday, against the Patriots, the Wildcat was successful beyond anyone’s wildest dreams. Miami ran six plays out of the formation, and four of them resulted in scores. Brown ran for three TDs and threw for another. Miami won 38–13, and that lopsided score ended the Patriots’ streak.
“They were like, ‘23 quarterback! Go over here! No, go over here!’ ” said Brown, describing the reaction of the normally disciplined Patriots defense. “So I was like, ‘Okay, we got them on this one.’ ”
“We had trouble with their new stuff. We had trouble with their old stuff,” said Patriots coach Bill Belichick after the game. “We didn’t play very well on defense. We didn’t coach very well. We didn’t play very well across the board, and they did a good job, so give them credit.”
“The theory that coaches were purely motivated by job security and didn’t want to go against the conventional wisdom, that didn’t quite satisfy me,” says Brian Burke of Advanced NFL Stats. Week in and week out, Burke analyzed games and saw evidence that NFL coaches were costing their teams yardage, 1st downs, and, ultimately, games because of the questionable decisions they were making. He further noticed that those coaches almost invariably erred on the side of caution. But why?
Burke argued that there’s something bigger going on when a coach punts on 4th down when an objective analysis shows he should have gone for it. Or keeps losing with the same tired passing plays when he should toss out his offense or at least replace his quarterback.
It turns out something bigger has been going on for 35 million years.
——
Daniel Kahneman never took an economics class, but that didn’t stop him from winning the Nobel Prize in economics. Kahneman won the award in 2002 for his work in prospect theory, which helped to create the field of behavioral economics.
Before Kahneman and his longtime partner, the late Amos Tversky, came along, economics was based on one overarching assumption: that everyone in the economy would act “rationally” in an attempt to maximize their wealth. And in those instances when someone didn’t aim for maximum profits, economists assumed that they simply lacked the information. They would aim for a maximum return if they could, but they can’t, so they don’t.
Kahneman didn’t buy it. He observed that human beings consistently acted irrationally when it came to making decisions about money. But what made Kahneman’s work compelling—and useful—is that while these behaviors were irrational, in economic terms, the way in which people deviated from an ideal strategy was predictable.
Prospect theory argues that economic decision-making is, like Einsteinian physics, relative. The main tenet of this school of thought is that humans make economic decisions not in absolute terms, in the way a computer might, but relative to personal reference points, and they make a series of predictable errors because of that. And emotions definitely enter into it. “You want to get someone pissed off? Just tell them that everyone they work with now makes a dollar more than they do,” explains Yale behavioral scientist Laurie Santos. A computer sees a one dollar raise as insignificant. A guy in a cubicle most certainly does not.
One of the main principles of prospect theory is that humans tend to treat losses very differently than gains. Researchers have discovered that humans are consistently about two and a half times more sensitive to losses than gains. For example, if you’ve ever had a day when you found a twenty-dollar bill on the street and smiled about your good fortune, then later found a twenty-dollar parking ticket on your car and were ready to declare World War III because of this disaster, you understand this on a personal level. “Losses seem to hurt more than a win feels good,” explains Keith Chen, a Yale economist who has worked with Santos.
This bias—loss aversion—plays out in any number of different ways in the real world. For example, stock investors repeatedly defy logic by selling the winners in their portfolios when they should instead dump the losers. A near-pathological avoidance of loss as homeowners reacted to falling real estate prices helped fuel the subprime mortgage crisis.
One of the most powerful examples of loss avoidance comes from the world of sports. Professional golfers on the PGA Tour, it turned out, were throwing away strokes—and ultimately money—by treating a putt for par differently than a putt for a birdie. A study by two University of Pennsylvania researchers analyzed 2.5 million putts and revealed that professional golfers are 3.6 percent more likely to make a putt for par—that is, avoid a loss relative to par—than they were to drain an identical putt for birdie—that is, post a gain relative to par. In general, golfers tend to leave those birdie putts short of the hole, playing them less aggressively compared to the attempts at par.
Tiger Woods explained this mindset in a 2007 interview. “Any time you make big par putts, I think it’s more important to make those than birdie putts,” he said. “You don’t ever want to drop a shot. The psychological difference between dropping a shot and making a birdie, I just think it’s bigger to make a par putt.”
But, of course, professional golfers aren’t playing against par. They’re playing against their rivals, and saving a stroke while attempting a birdie is worth exactly the same amount as a stroke saved while scrambling for par. Yet the world’s best golfers playing for huge purses treat those two situations—one for a perceived loss and another for a potential gain—very differently.
This is the way humans approach wins and losses across a wide variety of disciplines. Including professional football.
