Spoiling for Speed

This is a slightly modified deck from the one I just used to face Taskmaster on Heroic difficulty for my YouTube channel. (https://www.youtube.com/watch?v=2eihBG_dmYY)

I don't usually post the decks, but when I looked on Marvelcdb and found 0 decks with Quicksilver using the recent ready cards Spoiling for a Fight or Surprise Move, I thought..."let's change that!"

Any ready ability is inherently stronger with Quicksilver due to the extra resource generated by Friction Resistance and his many ways to buff his stats. Surprise Move already comes at a great rate, albeit with a strict condition to maximize it. Spoiling for a Fight is less good on its own due to the potential negative variability of drawing a minion that's too big to kill with one ready, but it has its uses and adds some consistency to the minion attachment archetype. I especially like the use case of ignoring the minion entirely and rushing the villain at the end of the game, as Spoiling turns 1 ER into 5-8 damage with Maximum Velocity and Jarnbjorn, depending on additional buffs from Combat Training, Symbiote Suit, and Reinforced Sinew.

As for minion attachments, we've got Suppressing Fire and Gatekeeper - solid cards on rate. Suppressing Fire helps with Quicksilver's weakness of hp, and Gatekeeper helps Aggression's weakness of threat removal.

I'll be the first to admit there's a lot going on here. First, I've dedicated lots of deck slots to cards that are simply great with Quicksilver - Deft Focus (with a 2nd copy for consistency), Combat Training, Symbiote Suit, Superpower Training (for Friction Resistance), Endurance, and Jarnbjorn. Then there's the package of minion attachments + Surprise Move. Then there's a small amount of minion payoff cards in Throg and Valkyrie. You could easily substitute some of the staples for greater consistency in the minion attachment archetype, or add more ways to pay off defeating minions like Blood Rage to make Spoiling for a Fight better.

Consider it a work in progress for now, but I think this is a useful skeleton, and I have had success so far in my extremely small sample size.