Fantasy sports leagues have long been dominated by stats-savvy players who track athletic performance down to the decimal point, closely monitor injury reports, and build rosters with the precision of a professional analyst. For the average fan, keeping up can feel impossible.
But what if anyone could draft competitive lineups without spending hours poring over data?
That’s the question that led Adam Scharf, an MBA student at Dartmouth’s Tuck School of Business, to develop Smart Roster—a fantasy baseball application that uses a combination of predictive analytics, optimization modeling, and natural language technologies to create a more engaging experience for players of all levels.
Daily Fantasy Sports (DFS) platforms give players the chance to draft new lineups every day, competing for points and cash prizes based on how well their chosen athletes perform. Of course, there are specific rules a player’s roster must adhere to, from strict salary caps to position constraints.
With thousands of players to choose from and constantly shifting performance data, building the right lineups is both an art and a science.
Scharf realized that existing fantasy sites failed to integrate sophisticated statistical metrics with engagement, leaving many average users, or “managers,” with consistent losses and a frustrating experience.
By combining predictive models with advanced optimization algorithms and natural language, Scharf designed Smart Roster to instantly generate high-performing lineups that win DFS contests. This allows the personalization and interaction that most users crave, while unlocking the horsepower of Gurobi for everyday users.
“I was introduced to Gurobi by two of my professors at Dartmouth Tuck School of Business, Jim Smith and Raghav Singal. Both had used the tool at a highly advanced level for years, so they were able to guide me in the initial steps very quickly,” says Scharf. “With this as a baseline, I began exploring it more deeply and expanding my use cases. The ease of use and power of the tool is why I decided to go forward with Gurobi as my optimization tool of choice over other options.”
Smart Roster uses predictive analytics—analyzing historical data, matchup statistics, injury reports, and more—to forecast player performance. These forecasts serve as essential inputs for the optimization model, which is then run on Gurobi to construct optimal rosters while increasing variance and avoiding overlap with other DFS players.
Leveraging a variety of techniques pioneered in scholarly articles about inefficiencies in fantasy sports, SmartRoster builds optimized lineups based on salaries, variance optimization techniques, and expected point maximization. Scharf weaves DFS techniques with hard-nosed optimization to statistically improve players’ odds.
What goes into a DFS lineup? Much like an actual MLB game, a roster is constructed with one player at each position (e.g., first baseman, second baseman, shortstop, etc.), plus two pitchers (for a total of 10 players per lineup).
Each player is assigned a salary before the game, and each overall lineup of 10 players has a salary cap. Based on real-world performance (like RBIs or runs scored), each player accrues points for the manager’s “team.”
This tees us up for a classic optimization question: How can a savvy manager best allocate their pre-determined salary budget to create the highest scoring lineup?
What’s more, typical DFS contests reward the top 5% of managers—which is why Scharf used Gurobi constraints to crank up the variance in each lineup, optimizing for points and variance to land users in the money.
Constraints that Scharf uses include:
By combining advanced optimization with user engagement, Scharf hopes to bring advanced Gurobi techniques to everyone.
With Smart Roster, players can:
SmartRoster demonstrates how predictive analytics (all those forecasts and data) can be used as effective inputs for prescriptive analytics (optimization), leading to better, faster results.
Scharf’s Smart Roster is an illustration of just how versatile mathematical optimization is, and the many ways it can be applied. It’s also a reminder that powerful analytics don’t have to be intimidating—and that optimization can unlock smarter decisions, even in the world of fantasy baseball.
Smart Roster is currently available for beta testing. You can find out more or request to join the private beta here.
Senior Data Science Strategist
Senior Data Science Strategist
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies. Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS. Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs. Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies. Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS. Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs. Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.
Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.