DraftFM: A FoundationModel for Day-Zero Drafting in Magic: The Gathering

DraftFM, a 1.6-million-parameter discrete-choice policy trained on 149 million human picks from 29 Magic: The Gathering expansions, predicts held-out picks in three withheld expansions with 50.8%, 60.4%, and 56.7% top-1 agreement, versus about 7% uniform chance. The model, which scores cards using only public card records and text embeddings, also produced a card ranking for the unreleased set The Hobbit, published 36 hours before its MTG Arena debut, with the ranking matching expert reviewers as closely as they match each other.

arXiv:2608.19568v1 Announce Type: new Abstract: Drafting a new Magic: The Gathering expansion begins before any pick from it has been observed: the complete card list is public, but the draft logs that supervised pick models train on do not yet exist. We study this day-zero regime directly. DraftFM is a discrete-choice policy that scores exactly the cards available in the current pack, conditioned on the drafted pool and the state of the draft. Every card enters as a frozen 775-dimensional function of its public card record, structured features and a fixed text embedding, with no card identities, set identities, or usage statistics anywhere in the model, so an unseen card is scored by the same machinery as a familiar one. A 1.6-million-parameter network fitted on 149 million human picks from 29 expansions predicts held-out picks in three expansions withheld in their entirety, reaching 50.8%, 60.4%, and 56.7% top-1 agreement, where uniform chance at the opening pick is about 7%. Refitted on all 32 observed expansions, the same architecture produced a card ranking for the then-unreleased set The Hobbit, sealed with its complete cryptographic provenance and published roughly 36 hours before the set became draftable on MTG Arena. The sealed ranking agrees with six independent expert reviewers roughly as much as those reviewers agree with one another. Evaluation against realized outcomes is committed to a follow-on note, whatever it shows.