Welcome back, did you miss me since.. uhh.. yesterday? Get used to it, because with a Legacy Grand Prix coming up, I’m here all week! Today, we’re going to have a look at the Legacy metagame, going into Grand Prix New Jersey, using the methodology I typically use at the end of every quarter (as dictated by the seasons on the SCG tournament circuit). Normally, with something as big as a Grand Prix coming up, I’d look at the last six months or so worth of data and show different models, some using a distance-based decay and some using a time-weighted decay. This year, however, things are different. Unless you’ve been living under a rock, you know that Khans has shaken the format up in a huuuuuuge way. Legacy has been turned so far on its head that it’s almost like we’re dealing with a new format. With that said, I felt that looking at pre-Khans data is just going to give us a distorted view of what we can expect at the Grand Prix, so I’m only using events that have taken place after the release of Khans. In an ideal world, I would even throw away the week one results, since not everyone realized the true power of the new cards, at first, but then we would have very few data points. In fact, I even had to break my own rule and reach beyond just the SCG data that I normally use and bring in the results of Eternal Weekend to add another data point (not that I think this is a big deal, since Legacy Champs had around the typical attendance of an Open, but I figured that I should disclose any deviation from my normal methodology).
As always, feel free to skip the indented copypasta, below, if you’ve read these posts of mine, in the past and you’re familiar with the methodology that I use. (here are links to other articles where I explained this exercise):
“We will assign each archetype two points for finishing 9th-16th, three points for 5th-8th, four points for 3rd-4th, five points for 2nd, and six points for 1st, then average out the data from the events to arrive at what the expected metagame should look like.”
The method described above was developed by Frank Karsten for analyzing the “winner’s circle” metagame. These results are meant to show the likeliness of seeing a given archetype at the top tables. I don’t want to mislead anyone into thinking that they can safely forget about the plethora of decks that exist in this great format and assume that they will be playing against nothing but Delver and Show and Tell decks, because it is not uncommon to see some pretty wacky shit in the first couple of rounds (or the later rounds if you have fallen below x-3).
One change that regular readers might notice is that I’m not doing the % change since my last metagame analysis, because as I said before, it’s pretty much a whole new format, so I don’t think that data would be very meaningful. Anyways, because I’m cranking out five articles and have a busy week, I won’t mince words, and cut right to the numbers:
| Archetype | K-Score | T-Score | T/K | |
| 1 | UR Delver | 15.81% | 16.68% | 1.0556 |
| 2 | Elves | 13.37% | 12.27% | 0.9174 |
| 3 | Miracles | 9.73% | 9.33% | 0.9589 |
| 4 | Dredge | 5.78% | 5.74% | 0.9947 |
| 5 | Sultai Delver | 5.47% | 5.44% | 0.9949 |
| 6 | Reanimator | 5.17% | 4.75% | 0.9196 |
| 7 | Jeskai Delver | 5.17% | 5.28% | 1.0225 |
| 8 | Sneak and Show | 3.65% | 3.56% | 0.9771 |
| 9 | Temur Delver | 3.65% | 3.65% | 1.0014 |
| 10 | Esper Deathblade | 3.04% | 3.09% | 1.0150 |
| 11 | Lands | 2.74% | 2.93% | 1.0694 |
| 12 | Ad Nauseam Tendrils | 2.74% | 3.01% | 1.1019 |
| 13 | Death and Taxes | 2.43% | 2.20% | 0.9042 |
| 14 | Jeskai Stoneblade | 1.82% | 2.13% | 1.1667 |
| 15 | Omni-Tell | 1.82% | 1.77% | 0.9722 |
| 16 | Mono-Red Moggcatcher | 1.52% | 1.70% | 1.1200 |
| 17 | Tezzerator | 1.52% | 1.60% | 1.0500 |
| 18 | Grixis Delver | 1.52% | 1.58% | 1.0383 |
| 19 | Slivers | 1.22% | 1.28% | 1.0500 |
| 20 | Maverick | 0.91% | 0.74% | 0.8167 |
| 21 | UR Painter | 0.91% | 0.96% | 1.0500 |
| 22 | Punishing Maverick | 0.91% | 0.96% | 1.0500 |
| 23 | Abzan Depths | 0.91% | 0.74% | 0.8167 |
| 24 | Goblins | 0.91% | 1.01% | 1.1083 |
| 25 | Imperial Painter | 0.61% | 0.64% | 1.0500 |
| 26 | Jund Pox | 0.61% | 0.64% | 1.0500 |
| 27 | Mono-Black Pox | 0.61% | 0.71% | 1.1667 |
| 28 | UW Counterbalance (not Miracles) | 0.61% | 0.64% | 1.0500 |
| 29 | Shardless Sultai | 0.61% | 0.64% | 1.0500 |
| 30 | Jund | 0.61% | 0.50% | 0.8167 |
| 31 | UW Stoneblade | 0.61% | 0.71% | 1.1667 |
| 32 | Esper Stoneblade | 0.61% | 0.50% | 0.8167 |
| 33 | Burn | 0.61% | 0.60% | 0.9917 |
| 34 | 12-post | 0.61% | 0.67% | 1.1083 |
| 35 | Bant | 0.61% | 0.67% | 1.1083 |
| 36 | Tin Fins | 0.61% | 0.67% | 1.1083 |
While it appears to be a three-horse race, led by UR Delver, followed by Elves and Miracles, looks can be deceiving. Why? Elves took the entire top four of the week one open in Indianapolis, where the top eight featured two copies of Dig Through Time as the only Khans cards. The results of this Open were almost like a pre-Khans open. In fact, I deleted the Indy Open results and ran the pivot table again, just to satisfy my curiosity, and UR Delver actually made up a larger portion of the “winner’s circle” metagame than Miracles and Elves, combined. The big takeaway from that, is that the path to the top eight, in New Jersey, will require you to navigate through a sea of Insectile Aberrations and Elemental tokens (that means UR Delver, in case I wasn’t being clear).
I still wouldn’t completely look at this as the be-all, end-all to what the meta will be like; I cannot stress enough that everything is different, now, and because of that, I think these numbers will be in much more rapid flux than normal, as the metagame adapts and develops around the new/revamped decks. As new decks get stronger, the decks that are their natural predators also get stronger, and as decks that may have once been strong find themselves unable to compete, the other decks that were held back might rise again. It’s all very complicated! Jeskai Stoneblade only had one showing in our data, but I suspect it to be a very-well represented deck in New Jersey. Still, I think this is a reasonable snapshot of what you can expect.
Let’s move onto macro-archetypes, before we conclude for today:
| r | Archetype | K-Score | T-Score | T/K |
| 1 | Delver | 31.61% | 34.70% | 1.0978 |
| 2 | Elves | 13.37% | 10.06% | 0.7523 |
| 3 | Graveyard Combo | 11.55% | 10.41% | 0.9013 |
| 4 | Control | 10.33% | 9.22% | 0.8926 |
| 5 | Stoneblade | 6.69% | 7.90% | 1.1818 |
| 6 | Show and Tell Combo | 5.47% | 5.07% | 0.9264 |
| 7 | Other | 4.86% | 4.53% | 0.9313 |
| 8 | Aether Vial Aggro | 4.56% | 4.34% | 0.9517 |
| 9 | Lands | 2.74% | 3.31% | 1.2083 |
| 10 | Storm | 2.74% | 3.57% | 1.3056 |
| 11 | Maverick | 1.82% | 1.46% | 0.8000 |
| 12 | Painter | 1.52% | 1.75% | 1.1500 |
| 13 | Prison Stompy | 1.52% | 2.07% | 1.3600 |
| 14 | Pox | 1.22% | 1.61% | 1.3250 |
No surprise to see that Delver is making up nearly one third of the meta. This hasn’t changed much, as Delver has always been around that level. The difference is the breakdown of the Delver decks, with UR taking all of the market share. One noteworthy takeaway, here, is that Grafdigger’s Cage is a fine card against two of the top three macro archetypes, so I guess you shouldn’t leave home without those.. well.. unless you’re Elves or graveyard-based combo.
We’ll be back tomorrow with the next part in the “cheat sheet” series!