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Master’s Guide-Mural MtG Art from The Lost Caverns of Ixalan by Racrufi

Finding Plans in a Draft Format Using Data

The success of your deck in drafting depends on whether it can achieve its intended game plan! Make sure your decks reach its full potential with this Limited strategy guide.

One of the important skills in Limited is realizing what a given color pair wants to be doing and then figuring out if it is good in doing it. Some color pairs want to be more aggressive, some are more midrange and some do better in a control setup. Most of the time realizing it is intuitive in broad strokes – we know that Izzet (UR) deck in The Lost Caverns of Ixalan (LCI) tends to be on the aggressive side. But broad strokes will miss some subtleties that diving deeper into data can answer.

Let’s look at the LCI format more in detail and based on 17Lands.com data, try to see which decks do better when they are aggressive, which decks prefer to play a long game and – probably most importantly – check if they can successfully play the long game.

Speed Impacts Plans

Speed of the format is a term that is used frequently but from my experience, it is often thrown around in a way that is not very meaningful. Just saying that the format is fast or slow may seem like informative, but it can be more detrimental to the understanding of the game than helpful. There are many reasons why games in a format last only a few turns. One, perhaps the most obvious one, is that the cards are statted to be aggressive, thus leading to early start of the game, racing and shorter games.

But aggressively statted creatures if they all trade early can also lead to slow games, where both players lose all their resources early and spend mid to late game topdecking 2/2s and taking ages to win the game. What makes formats fast is a snowball nature of board states. A situation where once ahead, opponent is on the backfoot and has to trade inefficiently just to stay alive, meaning they can never get good value from their cards, while the advantaged player – does.

This is best seen in graphs that show the impact of spending more mana than the opponent. In the one below you can see the win rates of 1000s of games in LTR format, where I looked at how much more/less mana did the player who was on the play spend until a given turn than the player on the draw did:

If the player spent the same amount of mana until the end of the full turn cycle (so both players finished their Xth turn), in the early game, till turn 7, the player on the play has a small advantage in those games (they win 1-2% points more than on average). After turn 7, that advantage disappears. The advantage of being on the play is covered with abundance by the fact that the player on the draw had access to one extra card.

But the interesting part of this analysis is looking at the win rate differences when one of the players outspent the other. Even as early as turn 2, if the player on the play spent 1 mana more, they have 4.1%p higher win rate than if they were in parity. And conversely, if they spent 1 mana less, their win rate is 4.9%p lower than the average. Those numbers are specific for LTR, but the trends are true for every other format I analysed with this method. And same trend as for mana is seen for life and cards drawn.

However, the datasets I analysed were all contemporary sets. And the longer I look at those results, the more I think that they are a symptom of the modern set design. Cards do a lot for their mana cost. 2-drops are relevant threats. 1-drops are best they ever have been. Every creature has some additional effect or is an absolute stat monster. This means that felling behind early is hard to overcome and leads to the snowball effect I was describing.

This is my hypothesis, so treat it with appropriate caution, but I also think that this causes control decks to be less viable in the recent sets. Snowbally nature of cards, multiple effects cards have on ETB, all those factors cause removal to be less efficient in controlling the board state completely – it is very hard to survive the early onslaught of your opponent and survive till the late game in a good enough shape to take over the game. And because so many cards are value generating machines, playing a slower game is not necessarily the best plan for those cards leading to conflicts between individual card power and deck’s meta-strategy.

To put it simply – we moved from times where aggressive creatures were weak and missing one step meant aggressive deck was far behind to the times where aggressive creatures are very strong and this means that now control can’t cope if they have a stumble. But the most important take home message here is that speed is not linked to aggression of the format but to the value accumulation through playing modern design cards.

The game durations and their distributions are essential to figure out what does a given archetype want to achieve. In this table you can see the win rate of each LCI color pair by the turn on which the game ends.

Fast Decks

As you can see there are some decks that do well only if they end the game very early. The most extreme example is Izzet (UR). In games ending on turns 4-6 it has a ~70% win rate, but the longer the game lasts, the lower the win rate. 63.8% if the game ends on turn 7 is still good, even on turn 8 it has a credible 58% win rate but on turns 11-16 it only wins 40-45% of its games, showing that Izzet decks don’t have a late game in this format. And this is a key information to you as a player.

Given a choice of a very aggressive creature and a mid range one, you should lean aggressive while drafting Izzet decks. Because doing so taps into the decks natural power – being very fast and very good at being fast. Of course, once in a blue moon you will manage to draft some sort of Izzet control but vast majority of the time, you should try to maximise the power of the color pair to the full extent.

Izzet being aggressive should be no surprise to those who drafted LCI, but WR might be. People try to draft WR as an aggressive leaning mid-range deck, but numbers show that this might be a bad strategy. WR decks that can close the game early are wildly powerful, with a ~68% win rate on turns 4-6, very similar to Izzet. And further, Boros decks have an almost identical win rate progression as the UR decks. This shows you should do all you can to slant your Boros deck as aggressively as you can.

But a careful observer will see one more thing. If the UR and WR win rates over time look almost identical – why does UR have a much better win rate than WR? They should be the same, no? Here we come to a key point – “wanting” to play fast games is not the same as “being able” to play fast games. It all breaks down on the capability of a color pair to finish games early. If a deck wind 70% of its games that end on turn 5, but only 2% of its games end that early, and 80% of its games end on turn 10 or later – this is not a good sign for its generic win rate.

It is one thing to understand what the plan is and the other to be able to implement it successfully. Izzet decks win better because they are capable to end games early more often. As simple as that. If you see at the distributions of the game lengths of both color pairs, you will see that on each of the early turns, Izzet decks end a couple percent more games than Boros and on longer games, the situation is reversed. And it is those small differences that eventually contribute to a much higher win rate of Izzet decks. Izzet decks managed to end 42.2% of their games by turn 8 and Boros managed only 37%.

Another deck that does very well in its fast version is RG Dinosaurs. I thought it is a classic mid range deck but the data suggests that RG does much better in its more aggressively slanted version. And this is something to keep in consideration. Through all the talk of Jeskai color pairs being the best thing to do in the format, it has escaped many people that RG has been the most winning deck for a couple of weeks running already.

RG is not as spectacular in the early games as WR and UR, but it has a slightly better staying power. And I could gamble a guess that the lower win rate in the early turns is caused by bad builds that are light on early drops and cheap interaction being overrun by other aggro decks. This makes me think that in order to win more with Dinos, you need to prioritise those. 2 drops, cheap removal are key so you don’t end up on the back foot – and keep in mind that your late game is most likely not as good as you think it is.

Midrange and Control

The other deck that does reasonably well in shorter games is WU (Azorius), but this archetype has a twist. Or even two. Firstly, it is not very good at finishing games early. Only 27% of games end before turn 8, comparing with 42% in UR. But that issue is mitigated by the fact, Azorius is actually good in the later game with win rates in 54-56% range on turns 10-14, when Izzet decks at the same time are below 45% win rate.

This staying power suggests to me that there are two types of Azorius decks – a small fraction of them will be good aggressive decks. And if you end up drafting one of those – your plan is very aggressive in the air. But those decks were most likely only available reliably in the early format. As it progressed, Azorius looks more like an aggro control – capable of wins but not through sheer aggression but by combining some early aggressive threats with control cards that let them last long and use their not-as-aggressive threats as the ones UR has, finish the job.

This can be seen in the comparison with UR:

The distribution of Azorius game length is much flatter. You can also see big differences in the number of games that end very early, and the significant % of games that end past turn 10 compared to Izzet. This means to me that drafting Azorius you should probably default to a slower build, as the very aggressive ones don’t seem to come together very often. This can make great use of the fact that white and WU double-sided uncommons, which are very control-slanted are more frequent than the regular uncommons in the set. Cards like Clay-Fired Kilns, Spring-Loaded Sawblades and Master's Guide-Mural are the reasons for that staying power and why despite having a high win rate in short games, Azorius looks like the best mid-range deck in the format.

There are 2 color pairs in the format that do much better in the late game Dimir (UB) and Golgari (BG). They both have low win rates in the early game – in the 40% range on turns 4-7. This means they need to focus their early turns on stemming the bleeding. Making sure they can survive till the late game when they excel. They both don’t have the tools to win early and you should not focus on that plan, rather than that, think how to make sure you manage to get the game past turn 10 in a good shape, which will put you as a clear favourite.

The distribution of the both decks’ game lengths is very similar.

They both manage to make the games longer – only 22% of the games end before turn 8 – this is exactly what they want to achieve. But it is still not enough. They would need to prolong the games by a whole turn to become tier one candidates. But keep in mind – we are looking at the data from average 17Lands.com user, who, while still above average a player, is not at the expert level. So my guess will be that a part of it is related to non-optimal deck building. The best of the best will be able to make the games last longer and – as a result – win more.

Of the two decks, BG has slightly better win rate stats. Why? The main difference is – it is slightly better early. Especially that small win rate difference in favor of BG on turns 8-10 is essential, since over 40% of the games for those decks end in that timeframe. What is worth noting, while still good into a very late game, BG drops off past turn 14, while UB stays pretty good even after that, making me think BG is a bit more midrange on the deck spectrum than UB, which is almost purely a control strategy.

Conclusions

I hope that the article prepares you to look at the format speed data and how to look at it in the context of game plans, but it also should be helpful if you are struggling with LCI. I know that thinking about those results I came to several useful conclusions of the formats and found several spots where my drafting style was misaligned with the color pair plans.

There is also a large scale observation from those data. Modern design is aimed at making formats fast. Games last shorter and controlling archetypes have problems in dealing with that. Threats are too good to be able to reliably extend the games long enough for controls to gain an edge, and I think in the long run this may lead to a certain tiredness with how different limited formats play out. As I am writing this piece, Khans of Tarkir is on Arena and even if it is not my favourite format and card power level is not to my liking, some design features from KTK would be interesting to apply from time to time. Once in a while we can have a set with 1- and 2-drops that are slightly weaker. Or fewer. Streets of New Capenna had a chance to be a format like that but it failed to deliver – mainly because the mono-color spells and powerful 2-drops were so much better than what 3-color cards had to offer, that it removed some incentives to explore the full solution space in the format.

Once in a while a set with a stacked 3-drop slot and bombs that start at 5 mana, with tools that enable longer games and give control decks a fighting chance, would be a breath of fresh air. And I hope that the brief revival of KTK and the generally positive response to it from the players will give a hint to the design team. And if not – make sure to point them to my merry rumblings. Maybe some data will be an eye-opener.

You can see the full seminar of the topic plus much more LCI draft data here:

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Sierkovitz
Sierkovitz

I am a limited player, who mainly skips playing in order to analyse the limited data using 17Lands.com. I run a podcast: Magic Numbers, where I try to use data to let you improve your limited game play, find out which heuristics work out and which common ideas are not well supported by data.

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