Diagram of the Siamese CNN matching phase. During matching, the trained Siamese CNN compares each observed XMM-Newton velocity map to the full library of simulated velocity maps. Both the observed map and each simulated cluster are passed through the shared-weight CNN encoder to generate corresponding embedding vectors. Similarity between the observation and a given simulated cluster is quantified by the distance between their embeddings in the learned latent space. Simulated clusters with the smallest embedding distance are identified as the closest kinematic matches, enabling a quantitative, model-driven comparison between observed cluster dynamics and the cosmological simulations.