About This Book
This paper documents how we executed Omniverse Sports League® (OSL) simulations on IBM Quantum to accelerate three workloads that are central to competitive decision-making in sports and esports: (1) large-scale Monte Carlo what-if analysis for strategy and risk; (2) tournament-bracket and scheduling optimization; and (3) classification tasks for match-up prediction and roster decisions. We deployed Qiskit’s IBM Quantum Runtime primitives (Sampler/Estimator V2) to orchestrate hybrid quantum-classical loops and leveraged algorithms such as Quantum Amplitude Estimation (QAE) for Monte Carlo speedups, Quantum Approximate Optimization Algorithm (QAOA) for discrete scheduling, and quantum kernel methods for predictive modeling. We show simulated results that illustrate where quantum pipelines can shrink wall-clock experimentation from “months to days” today, with asymptotic paths to “years to days” as device scale and error mitigation improvements.
