Abstract
Quantum computing (QC) is a computational science that provides efficient results for solving optimization problems. Quantum annealing (QA) is a form of QC and leverages superposition and quantum tunneling, which are phenomena of quantum mechanics. QA is used to solve real-life problems thanks to its superior properties. Therefore, studying QA with a specific focus on fantasy sports based on realistic scenarios offers a relatively under-explored, but promising approach, which represents the primary motivation of this study. Thus, this study presents a mathematical model for the Euroleague Fantasy Challenge (EFC) by Euroleague based on binary integer programming (BIP) to build the ideal team by selecting 10 players and one head coach among 288 players and 18 head coaches, in such a way that some team-building criteria set by the EFC are met and the PTM (Avg points) is maximized. To achieve it, this study uses the open-source Python library PyQUBO to express this model in the quadratic unconstrained binary optimization (QUBO) form and solves this model in the QUBO form through the D-Wave’s Leap Hybrid (quantum-classical) Solver to identify the ideal basketball team and head coach. Accordingly, a mathematical model based on BIP is presented to find the team formation with the highest PTM (Avg points) value, considering various potential team formations for the chosen team. It then converts this model into the QUBO form in the PyQUBO library and solves it on both the D-Wave’s Advantage 4.1 and Hybrid Solver. Both solvers suggest the same line-up (1 guard, 3 forwards, 1 center) as the ideal line-up. This study will hopefully contribute to the relevant field by encouraging further studies to leverage QC to guide complex decision-making processes in all team sports.
| Keywords: | Quantum Annealing Fantasy Basketball Euroleague Fantasy Challenge Quantum Optimization QUBO Pyqubo D-Wave’s |