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Comment by mtnGoat | Hacker News Reader

I think Yahoo fantasy sports and others in the space are doing amazing work on this idea. I wonder if an LLM is even necessary for this, it’s mostly maths. Analyze past winning decks and made decisions based on performance.

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I think a non-LLM model would be good for learning to draft within a particular set, because it can simply encode each card and learn what cards do well together, comparative strength, etc. without learning the stats/rules text on the card.

For learning to draft in one environment and then applying it to a new set of cards, like done here, it would become far more difficult to do without an LLM. The variations and nuances of cards rules text would have to be encoded as features, which would be extremely cumbersome. The LLM gets you some level of understanding of that for free.

Fair and valid points, it’s been years since I played magic but I agree an LLM would Be very useful in reading the cards and possibly then getting into understanding strategy based on that context.

Some status (mana cost, stats) of MTG cards are numbers, but the most important part, the effect of the card, is defined in English text. So, in my opinion, this seems to be an area where LLM can work well.

MTGA and MO development team do a lot of work to put card effects into if-then rule, but unfortunately their work is not visible to the players :)

17Lands data would definitely help, but humans don't have that data in their head when sitting at a draft table.

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