Dawgs By Nature
Cleveland has embraced the analytics movement. Now, the next step could be using artificial intelligence to find an edge.
The Cleveland Browns fully embraced the analytics movement when they hired Sashi Brown as general manager in 2013.
Never mind that the team had been using a form of analytics, even if it was not called that, as far back as head coach Paul Brown, who used intelligence tests, film study, the 40-yard dash, and other methods to help give his team an edge. Or that the Dallas Cowboys were using computers to help build their rosters in the 1970s. Or that the New England Patriots were stacking Super Bowl titles while doing deep dives into analytics.
As far as some fans and media members were concerned, the Browns were performing voodoo.
That narrative was built off a media-created image of Paul DePodesta, the team’s chief strategy officer, studying Excel spreadsheets (can you imagine!) deep in a bunker in Southern California as he called all the shots for the team.
Things did not work out for Brown, due in large part to being saddled with the worst head coach in NFL history, and the team took a two-year detour with dinosaur “football guy” John Dorsey running the show.
Analytics may have taken a backseat during Dorsey’s tenure, but the idea of using data-based evaluations as a tool to make better decisions resurfaced under general manager Andrew Berry and head coach Kevin Stefanski. Since then, the Browns have made two playoff appearances, and their analytics department has a league-high 10 members.
There are still those who fear change and prefer an outdated brand of football populated with “real players” and led by coaches who sport a strong jaw and spit when they talk.
But that is not the modern NFL, and a new tool is coming to the league in the form of artificial intelligence.
In March, the Las Vegas Raiders hired Ryan Paganetti as a head coach research specialist, which in plain English means Paganetti will be the team’s AI coordinator. One example of how AI can help teams, according to a paywalled article in The Athletic, is by reviewing game film from two teams and then creating a game plan complete with call sheets for offensive and defensive coordinators.
That was the idea behind this year’s winning team at the NFL’s annual Big Data Bowl. Vishakh Sandwar and Smit Bajaj developed an algorithm to identify coverages based on the computer’s analysis of the defenders. It can adjust in real-time as defensive players move, can spot which ones are giving away the coverage, and is accurate 89 percent of the time, according to the developers
And that is only the beginning of what could be coming in the next few years, as John Guttag, the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT, told The Athletic:
“Over time, it will get better and better. And what you’ll do is say, ‘Here are all the series that...
