There are more possible NBA schedule combinations than there are atoms in the sun. That’s not hyperbole—it’s the mathematical reality facing anyone trying to arrange 1,230 games across 30 teams over six months while satisfying TV networks, player safety rules, arena operators, and competitive fairness requirements all at once. This impossible puzzle is exactly what Fastbreak AI, a 30-person startup out of New York, has built its business around.
Fastbreak’s AI software now powers scheduling for more than 50 professional leagues globally, quietly controlling when billions of dollars in sporting events hit your calendar.
“I’m always amazed when we produce a playable schedule,” Fastbreak cofounder and CEO John Stewart says. “It’s a nearly impossible set of math problems. We’re considering billions upon billions of possibilities.”
Map Anything
Stewart’s path to sports scheduling began with a $250 million exit. His previous company, Map Anything, was acquired by Salesforce in 2019 for its field service optimization technology, which used the same mathematical principles that would later power Fastbreak.
While still running Map Anything, in 2016, Stewart began recruiting two KPMG consultants, Chris Groer and Tim Carnes, who had built the NBA’s scheduling system, with the promise that he’d eventually start a company dedicated to sports scheduling.
When that occurred in June 2022, the timing was fortuitous. The NBA needed help scheduling its new in-season tournament, but the team they had worked with at KPMG was now at Fastbreak, making it easy for Stewart to onboard the league as one of the company’s first major clients.
‘If everyone hates you equally, you’ve done your job’
What the trio of founders discovered with the NBA schedule was a system of staggering complexity. The NBA has 30 teams, and each arena has different constraints.
The San Antonio Spurs, for instance, are the fourth priority in their own building, meaning concerts can be prioritized over games. The Lakers’ venue hosts the Grammys and other marquee events each year, forcing the team to play on the road for certain stretches.
Media partners pay billions for specific matchups to be in prime time and on marquee dates. Player safety rules prevent back-to-back games over 350 miles apart. And on top of that, each team is allowed to make requests. The Miami Heat, for instance, prefer to play at home during Art Basel.
Still, not all requests can be granted.
“It’s the art of managing disappointment equally,” Stewart says. “If everyone hates you equally, you’ve done your job right.”
The challenge isn’t just mathematical—it’s diplomatic. Fastbreak’s platform gives different access to arena managers, media partners, and team executives, who can each enter requests into the system for consideration. When changes happen, the AI is designed to minimize collateral damage while accommodating whoever needs the adjustment.
Schedule repair—the logistics game changer
The traveling salesman problem is a classic mathematical and logistical challenge about finding the most efficient route through multiple cities. Computer scientists can solve that for hundreds of thousands of locations. But even a simplified sports scheduling problem featuring just 10 teams?
“People have written many PhD dissertations on it and still not solved that problem to optimality,” Groer says.
But even after clearing that mathematical hurdle, the job isn’t done. When the LA wildfires and Gulf Coast hurricanes disrupted games this year, forcing the NBA and NHL to reschedule, it triggered what experts call cascading optimization crises. A single venue change can force adjustments to hundreds of other games due to ripple effects across team travel schedules, TV contracts, and competitive balance requirements.
Fastbreak’s “schedule repair” function suggests optimal fixes in minutes using what Stewart calls “warm starting”—beginning from the current state rather than rebuilding from scratch.
Think of it like GPS rerouting when there’s traffic, but infinitely more complex. When one game gets moved, the AI instantly recalculates how that affects every other game and the 500-plus other rules, then suggests the least disruptive solution to minimize collateral damage to uninvolved teams.
The art behind the science
Fastbreak’s breakthrough isn’t just computational power. It’s incorporating machine learning—teaching AI systems to understand the subjective art of what makes a good schedule.
League executives manually rate thousands of past road trips on a 1–10 scale, teaching the system what constitutes quality travel patterns. A trip hitting multiple East Coast cities in logical geographic order might rate an 8 or 9. A chaotic journey ping-ponging across time zones could get a 3.
“You actually have to give business users a user experience where they can train this model and teach it the meaning of ‘good,’” Groer says. “You can never just provide all these trips to an AI model because it would immediately bias to ‘this trip’s been done in the past, therefore it must be acceptable.’”
The result is that the AI has become more consistent than human experts were with each other—when multiple league officials rated the same trips, the AI’s ratings were closer to each expert’s opinion than the experts were to each other.
Fastbreak’s AI uses a sophisticated scoring system to balance competing demands, weighing different violations based on league priorities. A hard constraint—like preventing teams from playing back-to-back games over 350 miles apart—might carry infinite penalty points, essentially making such schedules impossible to generate. Softer preferences, like avoiding Monday home games, carry smaller penalties that can be traded off against other benefits when the AI is trying to optimize the overall schedule.
All told, professional schedules can have more than 500 different “rules,” each with carefully calibrated penalty weights to ensure accurate prioritization, and teams get point allocations for special requests. They might have 2,000 points to distribute across their wish list, creating a market-like system where they must prioritize what matters most.
Beyond the big leagues
Fastbreak now powers scheduling for the NFL, NBA, WNBA, NHL, and Major League Soccer, plus top college conferences like the SEC, ACC, and Big East. But Stewart sees an even bigger opportunity in youth sports—a $40 billion annual market where parents juggle multiple apps and constantly changing schedules.
“I bet on your phone you’ve got nine different apps for those different sports, and I bet you hate them all,” Stewart says, describing a frustratingly common experience for sports parents.
In June, the company launched Fastbreak Compete, which has integrated the same AI scheduling engine it offers professional leagues. As of June, the software is used by 12 youth sports organizations, with commitments from over 40 more for 2026.
Fastbreak’s strategy is to use its professional-grade technology as a hook, then expand into adjacent services. Fastbreak Compete creates schedules, but also serves as a one-stop shop for parents, as it consolidates scheduling, communications, travel booking, and payments into one platform, eliminating the app-juggling nightmare and providing real-time updates when tournaments inevitably change.
Fairness, not perfection
When the NBA season tips off, Stewart and his team will already be preparing to work on next year’s schedule, starting with arena availability collection in November. It’s the first step toward the ultimate goal of building a schedule that is not just operationally efficient, but also fair.
Fastbreak’s algorithms continuously monitor dozens of metrics: total travel miles, home weekend games, back-to-back frequency, rest advantages, and countless other factors that could create competitive imbalances. The extensive fairness metrics help ensure that when schedules are released, every team has roughly equal advantages and disadvantages across multiple dimensions.
“If you’ve done your job right, everyone will find something to complain about,” Stewart says. “But the complaints will be equally distributed.”
As leagues continue evolving—adding tournaments, managing global events, negotiating increasingly complex media deals—the optimization challenges only intensify. For an industry built on competition, perhaps the ultimate victory happens behind the scenes, in algorithms that ensure the playing field remains level, one perfectly balanced constraint at a time.