LeBron or Steph? Ovechkin or Crosby? Sale or Scherzer? Daily fantasy sports players rifle through these questions as they ponder how best to set their lineups. Myriad tools exist to inform those decisions—web sites, podcasts, magazines, network shows—but most of them are reliant primarily on the opinion and cursory statistical observation or analysis of their writers and presenters.
Enter Jarvis Nederlof, 28, and Michael Zaneri, 27. They are students at 42 Silicon Valley, a coding academy in Fremont, Calif. that aims to change how young people learn computer science. They are also sitting squarely at a very intriguing junction between science, technology, engineering, arts, and math education (STEAM) and sports. A little more than a year ago their team developed an AI-based solution to predict and optimize DFS lineups. Dubbed “Project Alea,” their subscription-based service offers players in daily fantasy competitions a true edge.
Alea can be used to improve lineups for MLB and NHL contests, and soon also NBA. The neural-network platform uses complex computer science concepts to generate its outputs, but solves for the most basic and primal directive when playing DFS: winning.
“The challenge is that if you do play fantasy, it gets not fun when you start to lose … and professionals have to win,” said Nederlof, who was a DFS player before enrolling as a student at 42. “People who want to play longer term and win are going to need these kinds of tools.”
The implications of Alea are evident according to Nederlof and Zaneri. Players can improve lineup construction immediately by using a service like this, swapping bias and guesswork out for impartial analysis and predictions. This is a clear value proposition, and ties directly to the burgeoning world of daily fantasy and the economy that has sprung up around it. However, the options for technologies like this could extend far beyond the DFS world.
“Approaches like we’re taking to predict fantasy sports could be used in a lot of other areas within traditional sports, for instance to gather and output data for use by teams, said Zaneri. “Techniques like these, the tools we’re building, will have many other applications. We are very excited to look into that in the future too.”
The introduction of Alea is also interesting when viewed through the lens of the Supreme Court’s recent decision to legalize sports gambling. DFS has been mired in legal battles for years and is blocked in some states. In many cases, the legality of DFS pivots on the question of whether it is considered a game of skill or purely of chance. But as the U.S. continues to open up to the idea of people betting on the games they watch, technologies like Alea only stand to become more prevalent.
“DFS is currently written into law in many places as a skill-based game, and it has been for a while,” said Zaneri. “DFS will definitely work its way into the legal sports gambling world soon, though, and our project puts us in a strong place to succeed.”
One specific area for growth that the two have identified is esports, according to Nederlof. “[Wagering on] esports is definitely something that is coming, no doubt,” he said. “And when it does, we feel like we’ll be in a great position to take advantage with the tools we’ve created to serve the DFS world.
Esports also has tremendous power in engaging young people around learning concepts. And as Nederlof and Zaneri now begin to make their way into the burgeoning sports betting industry with Alea, their example might serve to highlight the opportunities available to young learners who pursue computer science. According to the Wisconsin Technology Council, there are more than 550,000 open computer science jobs in the U.S. today, but there were only 50,000 new computer science graduates last year moving in to fill them.
Next week, 49ers EDU and 42 Silicon Valley will be hosting a high school summer coding camp. Students aged 14 to 18 will learn to program in the statistical analysis language R to complete a series of computer science challenges themed around football.