This example begins with NBA boxsxore data to build a supervised machine learning model that predicts players fantasy point output for a single days games. Those predictions are then used in an optimization model that will select the optimal team consisting of one player from each of the five main positions.
The second part expands the optimization model to reflect actual fantasy basketball competitions, shows different ways to model constraints, and introduces the slack of a constraint.
You can download the repository containing this and other examples by clicking here.
This notebook can be ran using the "online course" version of Gurobi. If you require a full license you can request an evaluation license as a commercial user, or download a free license as an academic user.
Copyright © 2022 Gurobi Optimization, LLC