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This is particularly true in the presence of dynamics for resource competition models between adversarial teams. While game theory provides a conceptual lens for studying such processes, it often struggles with the scale associated with real-world systems. This paper contributes to resolving this limitation through a parallelised variant of the efficient-but-exact nash dominant game pruning framework, which we employ to study the optimal behaviour under adversarial team dynamics parameterised by the so-called networked Boyd\u2013Kuramoto\u2013Lanchester resource competition model. 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