Mathematical programming scheduled the Valley Baseball League in under a minute

The Valley Baseball League, a collegiate summer league in Virginia's Shenandoah Valley, has 11 teams playing 42 games each season — an odd team count that makes scheduling hard.

League management also faced venue-sharing constraints, travel limits, an equitable spread of off-days, and team-specific requests for home/away games and road trips.

Furman University researchers encoded all of it in a mathematical programming model; specialized software on modest hardware outputs the single best revenue-generating schedule in under a minute.

The schedule generated by the model was enthusiastically adopted for the 2020 season and significantly outperformed previous manually produced schedules.

Optimize the schedule, not the pairings

One model respected every league mandate and team request at once.

A minute of compute replaced dozens of hours of staff time.

Revenue maximization mattered to a financially constrained amateur league.

Adoption proved the model worked in practice, not just on paper.

Amateur leagues with scarce money can still afford optimization: a model that respects every constraint and answers in a minute beats weeks of manual scheduling.

The league had already used analytics-assisted schedules from 2018; the mathematical-programming schedule was adopted for 2020 and outperformed manual ones. The work was presented at Furman Engaged and published in INFORMS Journal on Applied Analytics (2022).