New set is upon us and we have an impossible task of figuring out which cards are grerat and which are traps without the advantage of having them ever in our hands. Data won't solve that problem but it can definitely help, by looking at the general trends in card power across mana values, colors, etc. Also we can look into the amazing #P0P1 initiative from MTG_DS, where hundreds of people put their bets on the best cards in a set before its release (which mtg_ds kindly shared with me). This let me look at the wisdom of the crowd - what cards were widely liked but turned out to be duds, which cards nobody saw coming. Why some cards fly under the radar, while some lure us into the trap?Here is the example fo P0P1 results from TMD for reference - make sure to give MTG_DS a follow - in the end it stands for Magic Data Science, you should be interested!https://x.com/mtg_ds/status/1920641850546815335 Ping me for coaching. Join the Discord , sign up for Patreon , and use this Linktree for everything else! Watch this episode and see the slides: Episode #154 vid This podcast is sponsored by mtgazone.com - get your reading fix from the best and brightest Magic writers in the business. You can get the BulkBox if you are in the UK. Remember to use SIERKO10 code for a 10% discount!If you are outside of UK, you can find your local distributor on the BulkBox website .
