Advanced analytics played a role in the Eagles drafting Derek Barnett

Albert Breer recently wrote an interesting column about the role of analytics in the NFL. You can read the entire story at The MMQB, but here’s a nugget about the Philadelphia Eagles and their decision to draft Derek Barnett with the No. 14 overall pick in the 2017 NFL Draft.

It’s not an exact science. Advanced analytics, for example, would tell you that an elite pass-rusher needs a 10-yard split on his 40 time in the 1.6s or better. And in 2005, that helped the Eagles, long a leader in football analytics, conclude that University of Cincinnati defensive end Trent Cole (1.67) could carry his college production (19 sacks) into the NFL. A decade later, Cole left Philadelphia behind only Reggie White on the team’s all-time sack list.

This April, those same Eagles took University of Tennessee edge rusher Derek Barnett with the 14th pick, because they believed some of his pedestrian testing numbers weren’t as relevant as his 10 time and short shuttle.

Leading up to the draft, there were few concerns about Barnett’s production. At only 20 years old, the Tennessee pass rusher finished his college career with more sacks than Reggie White. Barnett’s 23 sacks in his last two years at school were more than No. 1 overall pick Myles Garrett had with 21. And 19 of those Barnett sacks came against one of the NCAA’s top conferences, the SEC, while Garrett only had nine.

Rather, the concerns with Barnett were related to his athleticism. He did not post the best testing numbers at the 2017 NFL Combine, as seen in the spider graph below.

Barnett was sick at the Combine, which probably didn’t help him. Still, there are some concerns about pass rushers who are athletically limited.

The Eagles were able to erase some of those concerns by focusing on the numbers that mattered most. In this case, the team clearly felt comfortable with Barnett’s 10-yard split time of 1.69 seconds, which is nearly identical to the aforementioned Cole’s time of 1.67. Barnett’s three-cone time is also very impressive which is apparent when you watch him play because he displays great bend while rushing around the edge.

Numbers clearly aren’t everything. The objective data only goes so far. This much is illustrated in a story about a pass rusher who posted a strong 10-yard split but hasn’t been a good NFL player.

Conversely, in 2014, with ex-Eagles exec Joe Banner in charge, the Browns saw Barkevious Mingo’s off-the-charts 10 time (1.57) and figured he could become an undersized pass-rushing dynamo along the lines of Dwight Freeney. They overlooked the issues with his playing strength and took him sixth overall. Three years later, they were trading him for what amounted to a JUGS machine.

“There are very, very few examples of an NFL player who produced a lot of sacks that wasn’t able to run a 10 time around 1.6,” says Banner, who established an analytics department in Philly in 1995. “Does that tell you who to pick? No. And if you use that solely, you won’t have much success. But if I pick a guy, and I want sacks from him, and I don’t put weight into that, then that’s just not smart.

“Analytics is 95% common sense. Then you have to add sophisticated people who can use it in complex ways.”

The Eagles’ selection of Barnett seems like a good marriage of objective analytics (Howie Roseman objective influence) and tape scouting (Joe Douglas subjective influence). Barnett’s tape was strong. The Eagles used analytics to assuage concerns about how he projects in the NFL.

Barnett obviously hasn’t proven anything in the real games yet so the effectiveness of the Eagles’ strategy remains to be seen. In the meantime, Barnett has been really impressive during practice. I’ve went as far to suggest he could be a Defensive Rookie of the Year candidate. At the very least, he’ll challenge for significant playing time as a rookie.

On a different note, Breer also mentions former Eagles head coach Chip Kelly in this column.

While the success and failure of those analytics-driven decisions play out, the next frontier of data—player tracking—moves forward. And the NFL actually has former Eagles and Niners coach Chip Kelly to thank for pushing it that way.

Kelly’s Oregon teams implemented Catapult technology years ago to monitor player practice workloads. As Kelly’s teams used it, individual profiles were built on players to provide coaches a roadmap for how hard guys were working, how far they could be pushed, and when they were at risk to suffer soft-tissue injuries. From there grew some of Kelly’s outside-the-box ideas, like having more than just a walkthrough on the day before a game, that still live in the NFL today.

Kelly has flamed out of the NFL (and into a media job) recently but there’s no denying he had an influence on the league.