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How Jets GM Joe Douglas should replicate the Eagles, Part 2: Investing in analytics

Atlanta Falcons v Philadelphia Eagles Photo by Brett Carlsen/Getty Images

The Jets are not going to turn into carbon copies of the Philadelphia Eagles simply because they hired Joe Douglas. The new general manager has been around the league for a long time and has his own ideas. I am sure there are things his old boss Howie Roseman did in Philadelphia that he disagreed with. He will do those things differently now that he is in charge of his own team.

With that said, the Eagles do a lot of things right so I am sure Douglas will borrow some of the philosophies he liked from his time in Philadelphia.

Over the next few days I will share philosophies the Eagles have that I think Douglas should bring to the Jets.

What follows is the second. You can read the first here.

Investing in analytics

I believe many football fans have great misconceptions when they debate whether their favorite team should commit to using analytics.

There is a vision of a general manager punching numbers into a computer and making all of his team’s decisions based on numbers. Experience and football wisdom accumulated over the course of decades is thrown out the window. The expertise of scouts is disregarded. The team must make a choice whether to strategize by utilizing old school methods or making decisions with a spreadsheet.

This is a false choice, especially in today’s National Football League.

There is no dispute that the use of analytics is much more prevalent in professional baseball than in professional football. Within Major League Baseball there has been a 30 team race to incorporate data better since the book Moneyball was published in 2003. That is quite a head start baseball has over football incorporating analytics even without considering how numbers have always been ingrained in baseball’s culture and how the nature of the sport makes it easier to use data to isolate and quantify performance than it is in football. It probably would be accurate to say that the least analytically inclined MLB team dives far deeper into the numbers than the most analytically inclined NFL team.

Still you can take a look at every team website and media guide in Major League Baseball. Not one team has decided to abolish use of a scouting department. They all still utilize traditional methods. Nobody makes all decisions by using an algorithm. I promise.

With that in mind any fears you might have about the Jets diving into analytics, turning decision-making over to a computer, and eliminating the true football people are not based in reality.

It is not a question of scouting vs. numbers. It is a question of using both or only using one. I don’t know about you, but given the choice I would like to see my team use all available information when considering a major decision instead of half of the available information.

The Eagles have been at the forefront of utilizing analytics to build a competitive advantage in the NFL. Here are some of the results.

The results of the fourth-down bids have been overwhelmingly in favor of the Eagles. According to ESPN Stats & Information, they have scored a touchdown or field goal on 13 of the 18 drives in which they converted a fourth down, totaling 85 points (4.7 points per drive). The times they went for it on fourth down and didn’t convert, the opposing team didn’t score a single point on the subsequent drive.

There is plenty of credit to hand out for those numbers, including to the defense for routinely answering the bell, but a big slice goes to the analytics department -- overseen by vice president of football operations and strategy Alec Halaby -- for understanding situational odds and playing them to their favor.


Analytics are being deployed on the defensive side of the ball as well. Defensive coordinator Jim Schwartz might come off as an old-school football guy, but he studied econometrics -- the application of statistical and mathematical techniques in solving problems -- at Georgetown, and is known to be very much data-driven in his approach to the job.

He passes his statistical findings on to his players, and demands they be able to recall it at a moment’s notice.

”He’ll ask you on the spot,” defensive end Steven Means said. “He might be walking past you right now in the locker room and be like, ‘Hey, what’s the percentages when it’s 11 personnel and [shot]gun?’ And you gotta know, boom, ‘70 percent pass.’ He uses that and it makes us more aware.”

Defensive back Jaylen Watkins cited two-minute situations as the top example of how numbers are used to heighten understanding. Under Schwartz, players are required to know the maximum amount of plays left in the half or game based on time remaining, and the point where the opposition needs to advance the ball to be in field goal range -- a variable that changes week-to-week based on the leg strength of the kicker.

Figuring out ways to utilize data isn’t akin to acquiring a magic wand that make a Lombardi Trophy appear.

The NFL is a league where wins come at the margins. Using the numbers to figure out optimal fourth down strategy might help a team steal four extra points in a game by deciding to go for it instead of kicking a field goal. When approximately half of NFL games are decided by one score, that little piece of value can make all of the difference in the world.

The original Moneyball team, the Oakland Athletics were working at a major disadvantage relative to their competitors. They had to figure out a way to win spending a fraction of the money the opposition had. They used data to figure out which players were both inexpensive on the open market and could help them win games.

In the NFL the challenge is different. The league has made an effort to put all teams on equal financial footing. The goal is to develop an edge on the competition. To do that, you have to be able to figure out ways to evaluate better than that competition.

To provide one very basic example, consider the wide receiver position. The first thing anybody typically looks at are core statistics such as receptions, yards, and touchdowns. Those things aren’t only dependent on receiver quality, though. They are also dependent on quarterback play.

A good quarterback might make a shaky receiver look better than he really is by delivering accurate passes into tight windows. A bad quarterback can destroy a receiver’s production by failing to identify when his guy is open and delivering inaccurate balls.

Through services like NexGen Stats we can now track the average separation a receiver gets. Nobody would argue this should be the only criteria used in an evaluation, but it is a tool available that gives us an opportunity to better evaluate the performance of a receiver by isolating solely what he does.

That is one of the most basic tools now at the disposal of teams. There are numerous ways teams can dive far deeper. They don’t replace the ability to judge whether a receiver is capable of getting a good release or high pointing a ball, but they do help tell the story of his effectiveness. Thus they can contribute to a more complete evaluation.

While the Eagles are at the forefront of analytics in the NFL, Douglas has been viewed as the driving force behind more traditional evaluation methods within the organization.

Considered a scout’s scout, Douglas’ traditional approach to evaluating served as a nice counterweight in an increasingly analytics-driven organization. He values production over measurables and character makeup above perhaps all else. He’s looking for leaders, and he’s looking for players who are football-obsessed.

Does that mean Douglas is totally opposed to utilizing analytics? I’m not sure I’ve seen enough evidence to suggest that is the case.

Take this description of how he operates from Tim McManus of ESPN along with Douglas’ own words.

Douglas is well-liked by his peers and is good for building morale. He is quick to give credit where it is deserved and checks his ego at the door. He has shown an ability to work in conjunction with a very present and powerful analytics arm, even though that world was somewhat foreign to him when he arrived in Philly.

”We’re big believers in how we’ve brought together a staff of different viewpoints and perspectives and all come to the same conclusion,” he said. “We all speak our minds, and we all have strong viewpoints, but at the end of the day, we respect each other’s work and respect each other’s decision.”

Douglas might not have a big background in analytics, but that doesn’t necessarily mean he lacks respect for the role they can play in building a better team. He saw firsthand in Philadelphia how the marriage of top notch traditional methods with modern analytical thinking can produce top results. I would hope this has left an impression with him.

Maybe it isn’t his world. Maybe he will need to hire, delegate, and lean on others to utilize their power. But I hope Joe Douglas will seek a competitive edge by emulating the successful organization which most recently employed him.