Cleveland Browns: Embracing Analytics

The night the Cleveland Browns fired both general manager Ray Farmer and head coach Mike Pettine, they announced the promotion of Sashi Brown as Executive Vice President of Football Operations.

Today, the Cleveland Browns have announced the hiring of Paul DePodesta as Chief Strategy Officer. Both believe heavily in using analytics, so understanding how analytics can be used in football is critical.

From analyzing player performance to dealing with probabilities both on the field and the NFL Draft, analytics can be used as a tool to provide context and help improve the chances of success.

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Pro Football Focus has become an extremely popular website for teams, fans and media trying to quantify and explain player performance. While not a perfect system (nothing is), it helps to boil down players down to a number to grade performance in a game or over the course of a season.

At some point, someone has deal with a person that has tried to use a player’s PFF grade as a blunt instrument to win an argument. If not, they are the person doing it. That is analytics.

It is not a perfect system as there is a human element as the person grading may vary in how they perceive a given play or performance. Beyond that, they do not necessarily know what a player was instructed to do on a given play. Nevertheless, NFL teams subscribe to it as much as everyone else does and it keeps growing, expanding into the collegiate game.

Analytics can be used as a measure of team performance and analysis as well. Football Outsiders does this with DVOA (Defense-adjusted Value Over Average) as a way to try to provide a more universal way of measuring team performance on a more even playing field.

For teams though, this is more about analyzing and predicting opponents’ tendencies as well as their own. This is sometimes referred to as Game Theory.

It is 1^st and 10 with the ball on the opponents’ 45 yard line. Analytics can provide some insight into what the opponent might do defensively.

How often do they blitz on 1^st down? How many, which players and which gap?

How do they matchup to this particular formation?

When a particularly dangerous player is here, how do they defend against him?

Analytics do not give a team the answer but that data in addition to their general film work could give them a slight edge. As much as teams might want to be unpredictable, teams tend to have a footprint. They have certain characteristics that make them successful or are simply ways they like to operate.

Teams can also use this as a way to audit themselves. Figuring out where they are most efficient and what plays might be best in a particular situation. Not only figuring out what they do well but if they are too predictable for their own good.

This data, used in the right hands, could be useful in gaining an advantage and exploiting an opportunity. This is the other side of this equation. As much as some would like people to believe that analytics take the human element out of football (or any sport), it only does as much as they allow.

Analytics cannot predict human behavior, account for human instinct or simply thinking on the fly. In the right hands, they are a powerful tool that makes a smart decision maker smarter. In the wrong ones, they are useless numbers that do not have a meaningful impact. The numbers do not ultimately make decisions. People do.

This particular part of the equation is important when it comes to using analytics in the NFL Draft. Analytics can be effective in reducing the margin of error.

Players are more likely to succeed with these particular athletic or physical traits. For example, quarterbacks below a particular height or hand size are far more likely to fail than others that meet this threshold. But wait, Russell Wilson and Drew Brees are shorter than that, so doesn’t that mean the metric is useless?

Of course not. And while both Wilson and Brees are likely going to end up in the Hall of Fame and have been extraordinarily successful, the overwhelming amount of data suggests that their chances of success are lower than taller ones. Lower does not mean zero.

This type of athletic data can also take data like age and athletic traits like agility and explosiveness to get an idea for where a player is now and where they might be able to reach. For example, using quarterbacks again, quarterbacks 24 and older have a miniscule success rate (Hello, Brandon Weeden) compared to those 23 and younger.

Obviously, analytics cannot account for character, both on the field and off of it. They are not going to tell a person if a person is likely to break the law, have issues with drugs or alcohol, or if they have the passion necessary to succeed in the NFL. Again, the human element is critical here.

Nov 30, 2015; Cleveland, OH, USA; Cleveland Browns fans including Pumpkinhead during the second quarter at FirstEnergy Stadium. Mandatory Credit: Ken Blaze-USA TODAY Sports /

Analytics are a tool that provides information. And information has a large amount of value. The more data, the better, assuming they have the right people there to interpret and put them to good use.

What the Browns are doing is not revolutionary, even in football. Teams from high school to the NFL use analytics – some without even realizing it. The Browns might be able to take it to another level, conceivably, but that remains to be seen.

The Browns have gone down this past before and simply did not trust it. In 2014, they famously spent $100,000 on an analytics report that told them to take Teddy Bridgewater in the draft. The owner decided he wanted Johnny Manziel instead. Perhaps learning his lesson or at least one of many he needs to learn, he is trying to take himself out of the process.

This could be a fruitful approach for the Browns organization. They key now is taking what they are doing with Brown and DePodesta and balance it out with the right football people. Both the head coach and general manager are still critical hires.

Analytics are great, but good old fashioned scouting is still a critical part of the process. For a team that has noted a deficiency in talent and how they acquire it, they cannot ignore the scouting part of the process and go solely off analytics. It is a balance that has to be struck for this to work.

The head coach needs to be able to rally the troops, put players in the right positions and help them succeed, using analytics as one way to help him gain an edge. Analytics will not make up for the necessary people skills a head coach has to have in order to be successful. Time management, expertise, charisma, and being able to hire a staff matter a great deal.

This also puts a highlight on the general manager position. As much as it is seemingly being deemphasized by the structure of the Browns on the outside, it is as critical as it would be in any setup. The scope of the job may be smaller in that they do not have control of the 53 man roster and are not balancing out the salary cap, but their focus is entirely on finding the best talent possible and providing that human element to balance out the football side of the front office. That is no small task.

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Analytics is a broad term for any number of ways to use numbers to explain data. It is not going to replace the human element of this sport or any other, but it can aid them in strategy and decision making. If the Browns can find the right people to use that data and bolster their efforts, it could help them become one of the better organizations in the NFL. The problem and challenge for the Browns, which has dogged them since 1999, is finding those right people.

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