Optimizing for Rotisserie Fantasy Basketball

TL;DR

This paper presents a new approximation method for optimizing team construction in rotisserie fantasy basketball, addressing computational intractability and promoting balanced teams through an innovative objective function.

Contribution

It introduces a tractable approximation of the rotisserie objective function, enabling effective optimization and aligning with traditional strategies for balanced team composition.

Findings

The new objective function correlates with balanced team strategies.

Optimization using the approximation performs well in simulated seasons.

The method extends existing head-to-head optimization techniques to rotisserie format.

Abstract

Previous work on fantasy basketball has established methods for optimizing team construction for head-to-head formats. This has been facilitated by the straightforwardness of calculating the objective function for those formats, given that underlying performance distributions are known. Rotisserie has not been optimized in the same way because even with the assumption that performance distributions are known, directly calculating the most natural objective function is intractable. This work introduces a system for making a tractable approximation of that objective function. The resulting simplified objective function aligns well with the traditional wisdom that balanced teams are preferable for the format, because it contains an implicit mechanism that rewards teams for being balanced. Integrating this new objective function into established optimization methods is shown to perform well in the context of simulated seasons.