Preprint
Jul 2026
Predicting Drafted Deck Strength for"Magic: the Gathering"
An encoder-based model is proposed that produces set-contextualized card embeddings to encode the draft decision sequence, with a consistent improvement over linear baselines on large-scale real-world data, establishing a first learned benchmark for outcome prediction in MTG Draft.
Tomas Rigaux, Hisashi Kashima
· 1 citation