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There are still those who fear change and prefer an outdated brand of football populated with “real players” and led by coaches who sport a strong jaw and spit when they talk.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 led to first downs. Here are all the series that didn’t lead to first downs. What are the important differences?’ — without hypothesizing before. You’ll just let the AI machine learning look at all that data and say, ‘Here are some interesting differences.’ One of the great things about machine learning is it finds things you didn’t know were there.”
There is no way of knowing if or how much the Browns are currently using AI, but Thomas Dimitroff, a former executive with the Atlanta Falcons and New England Patriots, told The Athletic that around 75 percent of the league’s teams are using some form of AI to prepare each week.
To get an idea of how the Browns could use AI, we asked ChatGPT to list ways that the club can incorporate AI to be more successful. The suggestions included:
Game strategy and play calling to predict opponent tendencies.
Personalized training regimens based on each player’s performance trends and recovery needs.
Evaluating college prospects based on play style, metrics, and long-term projections.
Identifying inefficiencies in execution and suggesting corrections.
Analyzing joint angles, gait, and impact forces during drills and games to spot signs of strain and prevent injuries.
Benchmarking player value against the market using performance analytics and economic modeling during contract negotiations.
That is all pretty basic stuff, but you get the idea. And it is easy to see how a team with the right people in place working on this full-time could find an edge, which in turn could be the difference between an eight-win season and a playoff run.
Dread it. Run from it. But AI is here, and the NFL is embracing it.
And that most likely includes the Cleveland Browns.