A look inside the making of an NFL football schedule

Predicting what fans are going to watch in December, now. What is the NFL up to with AWS and how does it work?

In just three months, National Football League (NFL) schedule makers methodically build an exciting 18 week 272-game schedule spanning 576 possible game windows. How do they do it? We caught up with NFL director of broadcasting, Charlotte Carey, as she and her team built this year’s schedule, to get an inside look at the process and how the league uses Amazon Web Services (AWS) to help it uncover the one. 

The scheduling sweet spot: A season within the season

“When it comes to creating a schedule, there’s definitely a mix of art and science involved,” Carey says. Howard Katz, NFL senior vice president of broadcasting and media operations, has led the art side for the past 15 years. “[He’s] built the schedules for many years, trusting his gut and instincts, and it has worked out very well.” And on the science side? That’s where Carey and Mike North, VP of NFL broadcasting, sit. “We’re on the backend trying to figure out exactly what everyone is saying and how the computers are reacting to everyone’s gut and instincts.”

Now an automated operation, the scheduling process for the NFL season was once performed completely by hand, on a corkboard, in the main office. That’s where schedule makers, like North, hunkered down for weeks on end, manually churning through hundreds of potential NFL schedules, game by game, sometimes producing only a few potential finished schedule options per season.

“I wasn’t here during the corkboard era, but I was here when we only had 100 computers at our disposal. That was really all we had from a schedule creation standpoint,” Carey recalls. “[Back then,] when we set off a search at night, it was very common that we’d come back in the morning with nothing. Or one schedule. To be honest, having thousands of AWS spot instances available each night has completely changed our process.”

Since then, the complexity of assembling the schedule has grown. Carey’s team uses more data than ever have before. 100 computers have grown to 4,000 and with the help of AWS, they are able to produce dozens of schedule options each night. “The hardware at this point is really helping the number of seeds that we can run though. We’re able to travel through a lot more of the solution space every night with each run. We’re getting a lot smarter about how we actually look at and analyze [all of] these schedules thanks to what AWS is able to provide us in terms of firepower.”

Today, the team relies on Amazon Elastic Compute Cloud (Amazon EC2) machines to run thousands of schedule scenarios, with the hope of discovering what Carey calls the mythical, magical, perfect schedule. “We have so much more computing power at our disposal and AWS has been great with telling us which boxes we should use, how we should use them, and which spot instances we should be looking for. Those different pieces have really helped us from a solve perspective. And it’s gotten us to a much better place where we are seeing a lot of high-quality schedules every day.”

Where it all begins

As soon as the Super Bowl ends, the NFL’s small but nimble broadcast planning team head back into the office to run simulations with asports complex algorithm that analyzes millions of potential schedules. “As soon as we finish week 18 of the regular season, we know the standings-based matchups. The final piece of the puzzle comes with who wins the Super Bowl. That’s where we start,” Carey explains. “For instance, this year, Kansas City won the Super Bowl. So, what are the options for the kickoff game? You could look at division games, some interesting NFC North matchups, or you could look at some pretty epic playoff rematches with Cincinnati or Buffalo. And you could certainly consider a Super Bowl rematch with Philly. There’s so many different options.”

The schedule makers begin whittling down the pool by first defining key variables and writing unique rules that must be taken into consideration—things like travel requirements, primetime games, free agency, division rivalries, stadium blocks, health and safety concerns, and many more. “To be honest, we have north of 20,000 rules in the system,” Carey admits. “It’s a crazy, crazy management process to say the least.” Rules are input into the system and each night Amazon EC2 instances run different scenarios—each one talking to one another as they comb through different branches of the search tree, in pursuit of a season schedule that abides by each and every rule. It’s a job that would have taken thousands of people hours without AWS.

The ideal season-long football schedule minimizes competitive inequities while at the same time maximizes for television viewership. Carey admits finding an option that equally satisfies 32 NFL teams, 7 network partners, and millions of NFL die-hard fans is nothing short of challenging. “You could ask all coaches what their least favorite thing about any schedule would be and I think you [would] get all different answers. There are some things that everyone hates—nobody likes three straight road games or a road game after a road Monday game,” explains Carey. “We definitely pay a lot of attention to competitive inequity and try to make sure we balance everything out. There may never be such a thing as that mythical, magical, perfect schedule with no team pain or all the networks getting everything they want,” confesses Carey. “I’m not sure we’re ever going to get to perfect but we’re going to darn well try to get as close as we can.”

Predicting the unpredictable

So, how does the NFL account for variables that it can’t expect, like free agency, trades, or unexpected retirements? The short answer is by staying flexible. One example that comes to mind for Carey was in 2020, when Tom Brady signed with the Tampa Bay Buccaneers. The sudden move caused a massive ripple effect on schedule models.

“In the midst of COVID Tom Brady decided that he was going to become a Buccaneer. [Tampa Bay] is now a team with the G.O.A.T. It’s a completely different calculus. How do you then rethink different brands and franchises and everything else when these players have such a big impact on one team? That’s where we use data to inform decisions.”

The shocking swap greatly affected the landscape of scheduling models—catapulting the Buccaneers to the national window and into primetime television territory. But, with AWS, Carey and her team accounted for the change and adapted quickly—allowing them to freely leverage baseline models and rewrite team weightings in the rules engine.

Big moves are still being made—like Aaron Rodgers’ official trade announcement to the New York Jets. “I think the Jets are going to be fun this year. It should be an interesting team, and the calculus definitely shifts now that Rodgers is their quarterback.” The move is sure to garner network interest and influence the upcoming schedule.

What’s next: Looking to the 2023 season

The 2023 NFL season is fast approaching and schedule makers are in the office running simulations. With technological advancements and more data at their disposal each day, the team plans to further leverage AWS cloud computing and potentially predictive analytics to help them better optimize for things like TV ratings, available television windows, delivery methods, and alternative dates and times.

And with the draft behind them, Carey and her team can now put final touches on and make last-minute schedule updates to an already highly anticipated 2023 football season. “Now that the schedule comes out after draft, it’s great because we can factor in interesting things that happened during the draft—particularly rookie quarterbacks that may actually start at the beginning of the season. Those are great opportunities to get good games on schedule that are interesting early on.” So, what should we expect to see on our televisions this year? That’s something we’ll just have to wait to find out.

Learn more about how the NFL uses AWS to build its season schedule: https://thinkwithwp.com/sports/nfl/schedule/.