The Cleveland Browns have returned to their roots by taking an innovative approach to building a team through the NFL Draft.
The Cleveland Browns are giving a prominent role to analytics in player personnel decisions. This is evident by their philosophical approach to managing their salary cap. But have the Browns done anything to show that analytics is driving personnel decisions?
For all the ink that has been spilled over the Browns non-traditional approach, it should be remembered that the Browns have never been a traditional team. Paul Brown was the greatest innovator in NFL history, making changes from rules to equipment to racial integration. If anything, the Browns spirit of innovation is more traditional than the football traditionalists.
But the question at hand is how this new analytical approach is driving personnel decisions when it comes to the draft. Did the Browns use only analytics? Did they only use traditional scouting methods to make decisions?
Related: Analytics is different from moneyball
The Browns uniquely combined both traditional scouting and analytics when it came to selecting players in the 2016 NFL Draft. There were key performance indicators at play when making draft choices.
At the same time, these analytical cues were filtered through the lenses of offensive and defensive schemes. The Browns selected players that are fits for Ray Horton’s defense and players that fit Hue Jackson’s offense.
In the end, the Browns employed analytics in the service of finding players to fit the schemes the coaches are implementing.
The idea that analytics would serve to find the best players for a given scheme does not fit the national narrative of Harvard computer geeks playing fantasy football with real players. Nevertheless, the Browns use of analytics has demonstrated how it will be used in the NFL, at least initially.
Here are three thoughts on what the Browns have done so far.
Next: Analytics is not about schematic preference
The Browns are not using analytics to find the best offensive scheme. The scheme choice is being left to traditional football people – the coaches.
The national fear is that the Browns will do to football what analytics has done to baseball. In baseball, analytics is employed to determine defensive schemes, hitting approaches, in-game strategic approaches and on and on.
Commentators lament that football is not baseball. Football is not a static game of nine individuals whose play can be analyzed independently of each other. In this respect, the commentators are correct. Football is the ultimate team sport. One cannot analyze the play of individuals because their actions are integrated like a great symphony.
By placing analytics at the service of the scheme, it puts traditional football people at the forefront.
Related: Analytics are not running the Browns
This (as I will explore below) is the great challenge of analytics in football. However, because football is a far more integrated sport than baseball, analytics has yet to be able to break down which overall schemes (west coast, vertical, power run, zone read option) are the absolute best for football. In many ways, that nut is not even worth cracking at this nascent period of football analytics.
Instead, it is better for analytics to serve whatever scheme is being employed. By default, placing analytics at the service of the scheme puts traditional football people at the forefront.
The coach becomes one of, if not the most, important hire in the organization. The coaches need to determine which offensive and defensive schemes are to be employed. It is of utmost importance an organization finds the right head coach to lead.
Once that is key aspect is settled, the first phase of true football analytics can begin – the acquisition and evaluation of player personnel in terms of scheme fit.
Next: Analytics is about finding players
There is an old coach’s truism that players win games. Coaches can scheme, plan, plot and teach all they want. But the game will ultimately be determined by who has the better players. A team can have the best schemes, strategy and innovation in the league; but without players to execute it, it is all worthless.
Every scheme needs players who can play the scheme. With all the “rebuilding” projects the Browns have undergone, they have players drafted to play a 4-3 defense, some to play in a 3-4, corners drafted to play man, while others were drafted to play zone. The result has been a conglomerate mish mash of players who collectively don’t fit any scheme.
The Browns are making the right move by tearing down the roster and starting all over. It allows them to build an entire roster around one specific scheme.
The Browns are now in the unenviable position of having to find players to fit the current scheme. The good news is that Horton’s defensive scheme, roughly speaking, is a “cousin” of former head coach Mike Pettine’s 3-4 scheme. Although they are different, they belong to the same family tree.
Continuity is absolutely necessary for analytics to work. Rome was not built in a day. Nor can an NFL championship team be built in one draft. The Browns are making the right move by tearing down the roster and starting all over. It allows them to build an entire roster around one specific scheme.
The Browns are using analytics as a tool for finding players that fit their scheme. The question of analytics in the NFL is not about its usage. The question and debate is about how influential analytical analysis should be in the evaluation process.
The NFL draft is like playing the stock market. Players’ value rise and fall much like stocks. And much like the stock market, everything involves risk. A stock or player may or may not pan out. The Browns are using analytics in the draft much in the same way stock brokers use analytics – to predict future performance and mitigate against loss.
But unlike the stock market, the commodities bought and sold are players (who are willing active participants in the system). All references to Charles Barkley aside, the players involved must be evaluated for on field performance, scheme fit and personal qualities that might lead to success or failure in the NFL. Analytics cannot determine all these aspects of player personnel.
Next: Analytics is about key performance indicators
Instead, the Browns player personnel department has developed an ideal of what a successful NFL player looks like at each position in the scheme. In order to create this “ideal” player, analytics and traditional football analysis are employed in unison. Working together, analytics and traditional football scouting create a plan to build the Browns future player personnel.
The traditional football people put together a scheme. They then work with the scouting department and analytics departments to define the ideal player to fit each role within the scheme.
The analytics department then begins searching for key performance indicators.
A metric is a method for measuring something. In this case, a metric is used to measure if a player can succeed at the NFL level. The “ideal” player for each position is a metric and it is the standard by which players are measured.
A key performance indicator are individual events that can be used to predict future performance. For example, the split-10 of a 40-yard dash is key performance indicator (KPI) of short-yard burst. Another KPI could be a college statistic. For example, Nate Orchard had 18.5 sacks for Utah in 2014. Those sack numbers could be a KPI for future sack numbers in the NFL.
The question for the Browns analytics department is which KPIs translate into future performance. Current NFL Network analyst Charley Casserly raises possibly the most serious objection to the use of analytics in the NFL. He questions the use of statistics as KPIs. His question is whether statistics are accurate representations of on field performance.
For example, a player may sack the quarterback. Great! But was the sack the result of the player’s ability to defeat the blocker, close to the quarterback and finish? Or was it a result of a defensive scheme that gave the player a free run to the quarterback. In the first case, the sack is a valid KPI. In the second place, the sack is not a KPI. How can you tell whether the sack was ability or scheme?
Answer: you cannot. As only coaches have access to the defensive scheme, they are the only ones who know exactly what happens on any particular play. This is especially true for offensive lineman. What is credited to the offensive line as a sack may really have been a missed assignment on the part of a running back.
Analytics departments will always be playing a guessing game when it comes to KPI. But the NFL draft is a guessing game anyway. The use of analytics is to predict future performance and mitigate against loss. No approach is perfect. But an analytical approach, with all its uncertainties, may still be more successful than traditional scouting methods.
The Browns will certainly show us if it can be successful or not. Now that all of this has been laid out, let us look at how the Browns up this all together in the 2016 NFL Draft.
Next: A case study on analytics
The Browns drafted six defensive players in this year’s draft. Of the six, four were drafted as a part of the front seven (linemen and linebackers). Was there a common thread that links these four players together? Was there a common metric or KPI that led the Browns to these players?
The one identifiable statistic that links all of these players together is the quarterback sack. The Browns used the sack as a key performance indicator when choosing players because they are looking to pressure the quarterback. Therefore, it would make sense to draft players who have done it before. Or at least that is what the Browns are banking on.
Between the four interior players drafted there were a combined 53 sacks (using 2014 numbers for Scooby Wright). Emmanuel Ogbah had 13 sacks, Carl Nassib had 15.5, Joe Schobert had 9.5 sacks and Scooby Wright III had 15 sacks in 2014. The sack indicates a high level of performance in an area the Browns were looking to improve.
More from Dawg Pound Daily
- How the Browns could maximize Nick Chubb in 2023
- Can Deshaun Watson get to Patrick Mahomes level for Cleveland Browns?
- 3 Cleveland Browns who should see an expanded role in 2023 and 1 who should not
- Is Marcus Davenport on the Browns radar in 2023?
- 5 Free agents from Super Bowl LVII Cleveland Browns should target
However, even if the KPI indicates the player has a chance to be successful, that does not mean the Browns should draft him. Another part of the Browns metric shines through when the players’ backgrounds are investigated. All four of these players showed an ability to overcome great odds to be successful.
Nassib and Schobert were walk-ons at their schools. Wright was a two-star athlete with only one offer out of high school. Ogbah’s family moved to the United States from Nigeria when he was 9 years old, meaning he had to learn a new way of life at a very young age.
The Browns metric included both sacks as a KPI and emphasized perseverance as a character trait for success in the NFL. The last question was if these players fit the scheme.
The final metric serves to find players that fit the scheme established by Horton. This simple point cannot be overstated as the players drafted fit what the Browns hope to accomplish on defense.
The Browns have utilized a combination of traditional football scouting methods along with analytics to develop their roster through the draft. The traditional role has been to identify scheme and intangibles that lead to on-field success. The analytical role was to identity KPIs that translate into success on the NFL level.
By clearly defining these roles, the Browns have found a way to marry traditional football with cutting edge analytical analysis. The Browns have lived up to the spirit of their namesake by approaching a traditional game in a non-traditional way.
Next: 5 toughest QBs Browns will face in 2016
And doing so has placed the Browns back into the familiar position as one of the leagues leaders in innovation. Somewhere, Paul Brown would be proud.