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Artificial intelligence

Three ways artificial intelligence can save the NFL

Joe Harpaz  Managing Director, Tax & Accounting Corporate Segment, Thomson Reuters

Joe Harpaz  Managing Director, Tax & Accounting Corporate Segment, Thomson Reuters

Don't let Super Bowl excitement fool you. In the U.S., interest in football is flagging. Can AI improve the game and get fans interested again?

It wasn’t so long ago the National Football League (NFL) was thought to be infallible. It had a lock on the most coveted demographics in the country, and the revenues that poured in were only outdone by the mega-ratings that accompanied them. That it could achieve this as the rest of the world moved away from real-time, “destination TV” viewing made the NFL all the more desirable to advertisers.

Now, that era seems like a distant memory.

Ratings have been in a free fall. Last year’s 7 percent dip seems small in comparison to the 9 percent drop the league saw during the 2017 regular season. What’s more, as we steam toward Super Bowl LII in Minneapolis Feb. 4, consumer satisfaction with the product on the field seems to be at an all-time low.

If you ask viewers, like J.D. Power did in its 2017 Fan Experience Study, you get a variety of answers for why this is happening. They range from national anthem protests, to criminal off-field behavior by the league’s players (such as domestic violence), to excessive penalty flags, to too many commercials.

The trend begs the question: What can the league do to reverse the slide?

Like so many other industries wrestling with the challenges of fickle consumer demand, tighter margins, and the threat of tighter regulation, the answer for the NFL may be in artificial intelligence (AI). There have been hints that the NFL is already exploring this in the on-air promos talking about the league’s Next Gen Stats Program, for which it has partnered with Amazon Web Services (AWS) to use machine learning and data analytics tools to provide real-time player stats.

But statistics are really just the tip of the iceberg. When you think about the real business potential of AI when applied to the NFL, an entirely new world of opportunity becomes clear. Here are three ways the league could benefit from the promise of AI and wearable tech:

Tackling player safety

Concussions are an issue that the NFL isn’t going to solve by wishing them away, but it could certainly move to monitor the situation better with wearable technology. In September, the New York Times reported on a company called Catapult, which has already amassed a large roster of college football clients, and uses GPS to record not only distance traveled but also “explosive plays” and “load” — a term for the physiological toll a movement takes, but also how players recover, tracking their down time and sleep.

It’s been proven time again that players will forego their own safety to re-enter a game, especially when the season is on the line. The league’s protocol is supposed to take this element out of the decision-making process, but there are many skeptics as to how it’s working. With wearables, it could be very simple: Get a shot to the head at a certain impact measurement and you’re out for the game, no questions asked.

Solving the Rule Problem

It feels like every week, NFL fans are told a different story on the catch rules. It’s hard to imagine this isn’t turning off casual fans who live for the excitement, but loathe the technicality.

In theory, by incorporating AI-powered technology, it may be possible to determine possession without using an arbitrary determination like, “control to the ground” or looking to see if the ball moves a millimeter upon impact with the hard turf below (spoiler alert: it probably will). Maybe it’s a “control” touchpoint achieved by a certain grip on the ball that is placed in receiver gloves, with the results immediately sent to the NFL’s Microsoft Surface tablets? If any kind of body sensor can help make the catch rule become about common sense, it could curtail a lot of fan kvetching calls on the game’s biggest plays in the biggest spots.

Revolutionizing play-calling

More successful play-calling would mean more offense, and more offense would likely mean more viewers, because that’s what makes the game exciting. So, how can data and predictive analytics make that happen? What if a receiver were able to learn that every time he made a certain cut on third down, he’d get open? Or if a linebacker had a tendency to shift to a specific side depending on a quarterback’s call at the line of scrimmage?

One company trying to solve that equation is Go Route, which claims to be “elevating scout team execution” with their wearable technology, outfits college teams from conferences that including the ACC, PAC 12, and BIG 12. And one would assume that if IBM Watson can win Jeopardy!, it might be able to solve a 3-4 defense, too.

Will wearables and the corresponding AI ever replace a Bill Belichick, five-day film session binge? That’s hard to say right now. But certainly could make offensive or defensive coordinator’s job of calling plays and schemes far easier. It’s not hard to imagine a scenario where coordinators would be prompted, just like a video game user is when EA Sports’ Madden’s suggested play feature is activated, to call a specific play based on a likelihood of it working.

Learn more

In our 2018 AI Predictions report, our industry experts share their forecasts for how developing technology will shape our future.


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