I haven’t written much lately, mostly due to me going to the Grand Championship in Utrecht this weekend. Some stress has been getting to me as I am preparing for it.
However, as I have been preparing for it, I found an additional method of collection curation which I’d like to share with you. This is a short article that is an addendum to the Deck Selection: Collection Curation article I posted.
Oh, and if you’re wondering, I’m probably not going to finish the journey I have started with it. It is a lot of work and effort to find winning decks in a collection, and practicing with them, which will not be very fruitful for me as I don’t own them. I also feel that what I wrote so far is the important part of collection curation, and is what people were missing in that process.
Exporting a collection
When searching for decks to buy on decksofkeyforge.com you need to rely on their sorting and filtering in order to get to the decks that interest you. But when you’re sorting your own collection you don’t have to.
If you search for your decks, and change the view at the bottom to a list, you’ll get the above result. Scroll down to the “show more” button and click it until your entire collection is loaded. Then scroll back up and click the download button at the top right.
This will download a .csv file which you can open in Excel, or import into google spreadsheets. I’m using the same collection from the previous article and imported into google spreadsheets which you can view.
I deleted a few columns that I don’t find useful, such as wishlist and funny.
SAS is quick
Decksofkeyforge sort decks by SAS, which has been updated and changed recently, and is actually a very good quick metric of a deck. But I’m not looking for just quick, I’m looking for deep and for that, I much prefer looking at individual AERC scores, which I have used in the past.
One of my issues with totalling AERC is that C (creature control) is scaled linearly in the score, while it does not scale linearly in the value it provides in a game. I do want my decks to have creature control, but a score of 20 is complete overkill, yet it provides 20 SAS. I also feel like creature control, much like artifact control is a more binary situation, you either have it, or you don’t, so quantifying it feels less useful.
Actually, it’s more trinary. None/Soft/Hard. In the case of artifact control, soft would be using opponent’s artifacts, bouncing them, or taking control of them. While hard means destruction.
In the case of creature control, soft would mean things that help deal with creatures like bounce, stun, or damage. While hard would be targeted removal or board clears.
Off to the races
In order to win a game of KeyForge you need to forge those three keys before your opponent does. As I started showing in my article Is Æmber control necessary? there is more than one way of doing so.
The easiest way to get to three keys before your opponent is to simply generate enough aember for three keys before your opponent does so, simply for having high aember generation. This is why racing decks were so common in the early days, you just generate aember and win.
Another way to win is generate aember more slowly, but stall your opponent’s aember generation. Naturally, generating a lot of aember while also stopping your opponent is a fantastic path to victory, which is why stealing and shadows are so powerful.
There are more options such as combo decks, but i’d like to analyze those two right now. From reading those two descriptions, I feel we can formulate some kind of quantified approach to the problem.
If there was no aember control in the game, and there were only different ways to generate aember, then the deck which generates aember faster would be the most likely victor. However, since we do have aember control, then we could say that whoever generates more aember plus removes aember from their opponent will likely win.
So our new perspective is that whoever has the most A+E would have the best chance to win. Of course, it’s not that easy because some A is capture, which in effect turns your opponents C into E as now killing creatures generates aember. Still, it is a very powerful tool for curating a collection.
What about F though? as mentioned a high F can work instead of A, or rather, supplement it. A high F allows you to find the cards you need more often. It allows for a more consistent deck. And of course, it allows to generate aember faster if you simply play more cards.
Let’s add a column then, A+E+F and sort by it.
Looking over the stats, I immediately find the weak point in the low C. Regardless, I feel this deck is worth a test. Which means this method of analysis has produced another candidate, and probably a few more interesting ones further down the list.
Not a racer
There are many more combinations of columns you could look at. Maybe you’re a control player and would be interested in A+D+C for aember and boar control and disruption.
Maybe you’re looking for a deck that would cycle fast and disrupt the opponent while doing so, you could consider D+F.
Or perhaps you like to have a big board with a lot of aember control, then you could try P+A.
I leave it to you to find all the interesting ways to analyse this data.
Contact and afterward
I’m heading to Utrecht this weekend, during which I will have my first exposure to Worlds Collide as I have remained spoiler free aside from one starter I opened and played. I expect to be writing about Worlds Collide after that, and how I felt about remaining spoiler free while the community has been raging about it for over a month due to the target leak.
Two weeks after that I also have a Grand Championship in Belgium, which will include Worlds Collide. Very exciting, but may also drain my brain power again and prevent me from writing, as I plow through a new collection of decks.