Optimizing decision making for soccer line-up by a quantum annealer

TL;DR

This paper demonstrates how a quantum annealer can optimize soccer team line-ups by maximizing player ratings for different formations, comparing quantum and classical solutions.

Contribution

It introduces a novel application of quantum annealing to sports team selection, formulating the problem as a binary quadratic model and solving it with a hybrid quantum-classical approach.

Findings

Quantum annealer effectively optimizes team line-ups.

Results comparable or superior to classical solvers.

Application showcases potential of quantum computing in sports analytics.

Abstract

In this paper an application of D-Wave Systems quantum annealer for optimizing initial line-up of a soccer team is presented. Players and their playing position are selected to maximize the sum of players ratings for both a 4-3-3 attack formation and a 4-2-3-1 medium defensive formation. The problem is stated as a binary quadratic model (BQM) and it is solved in a D-Wave Leap Hybrid Solver. Results are presented and compared with already published results obtained with a classical solver.