TL;DR

· Belcher is the cleanest story of the week: only 3% of the metagame, but 2 Challenge wins, the best Top32 to Top8 conversion in the field, and a 12% Win/Top32 rate.

· Boros Energy bounced back hard. The deck won 5 Challenges and reached Top8 in 71% of events, even while its metagame share is still moving down.

· Affinity had the highest delta in the entire deck field and appeared in the Top32 of every Challenge, but its below-median conversion keeps it closer to “high presence” than true overperformer.

· Eldrazi Tron was almost everywhere in the results: 93% Top32 presence, but 0 wins and weak conversion. The deck is back, but it is not finishing tournaments yet.

· Prowess had another week without trophy, despite strong Top32 and Top8 presence.

· Control keeps gaining ground. Azorius Control won 2 events, converted well, and continues a climb.

· Graveyard decks are still a major part of the format, but the story is split. Grixis Reanimator is the leader, Living End is falling hard, and Goryo’s Vengeance still converts better than it wins.

· Domain Zoo is down to 2% metagame share, but the Challenge numbers do not say the deck is dead. Its 28% conversion is still above the field median.

Quick definitions

· Top32 presence - in how many Challenges a deck appeared in the Top32.

· Top8 presence - in how many Challenges a deck appeared in the Top8.

· Conversion - how often Top32 appearances become Top8 appearances.

· Win/Top32 - how often a Top32 appearance turns into an actual Challenge win.

· Delta - the difference between metagame share and Challenge-result presence. A high delta means a deck shows up in results much more often than its raw metagame share would suggest.

· Trusted sample - at least 150 matches. That does not make the number final, but it is large enough to treat it as more than pure noise.

What you are actually likely to face

Raw metagame share is useful, but encounter probability is usually more intuitive from a player’s perspective. Boros Energy is still the deck you are most likely to run into, but the next tier is very compressed. Affinity, Grixis Reanimator, Eldrazi Tron, Prowess, Broodscale, Living End, Azorius Control and Goryo’s all sit close enough that preparing only for the top deck would miss a large part of the real field.

Key observations

The 18-week trend: Boros down, the field wider

The longer trend makes the post-ban shift easier to see. Boros Energy is still the most important deck by raw share, but it is no longer sitting in the same dominant position as a few weeks ago. At the same time, decks like Azorius Control, Broodscale Combo, Eldrazi Tron and Grixis Reanimator are taking up more space. This is not a completely new format, but it is clearly less centered around one deck.

Challenge conversion: presence is not the same as closing

This is the chart that best explains the week. Boros Energy converted its presence into actual wins. Belcher did even more impressive work relative to its size. On the other side, Eldrazi Tron and Prowess were everywhere in Top32 and Top8 data, but neither deck managed to win a Challenge. That difference between “showing up” and “closing” is one of the main patterns of this window.

Belcher

Belcher is the clearest overperformer in this window. The deck was only 3% of the metagame, but it reached Top32 in 86% of Challenges, Top8 in 50%, and won 2 of the 14 events. The most important number is the conversion: 41%, the best result in the field. Its Win/Top32 rate was also excellent at 12%. Still I have a problem with Red/Blue versions of the deck I need to fix in my workflow.

The wins came from two different pilots, Savior0117 and GregorV, so this does not look like one player carrying an otherwise fringe deck. The league win rate is 49% (n=223), which would not be exciting on its own, but the Challenge data tells a different story. Belcher is not just entering events. It is finishing them.

My read is simple: sideboards are still not respecting this deck enough. When a 3% deck wins 2 Challenges and posts the best conversion in the field, it stops being a small footnote. Moreover Belcher can win a game on a spot when you have no answer in hand or just tap out in wrong time.

Boros Energy

Boros Energy is still trending down in raw metagame share, but the deck clearly did not go away. It made the Top32 of every Challenge, reached Top8 in 71% of them, and won 5 events. In other words, more than one third of this window still ended with Boros on top.

The conversion is also strong at 35%, comfortably above the field median of 23%. The win rate is 53% (n=744), so this is one of the more reliable samples in the data set.

The most likely story is not that Boros became unpopular because it is bad. It looks more like the casual bandwagon has thinned out, while experienced Boros pilots are still putting up serious results. It won as many Challenges in this window as it did in the previous two weeks combined.

Eldrazi Tron

Eldrazi Tron tells the opposite story. The deck is rising, has about 6% metagame share, and appeared in the Top32 of 13 out of 14 Challenges. That level of presence is impossible to ignore.

The problem is what happens after the first result line. The deck reached Top8 in only 29% of events, did not win a Challenge, and converted at just 18%. Among decks with a real sample, that is one of the weakest conversion profiles of the week. The win rate is also only 48% (n=462).

So yes, Tron is coming back. But for now it is mostly coming back as a deck that shows up everywhere and then struggles to finish. You still need a plan for it, especially because the delta is huge, but I would not call it one of the best-performing decks of the window.

Prowess

Prowess is still in a strange place. It has about 6% metagame share, a stable trend, 93% Top32 presence, and 43% Top8 presence. The win rate is 53% (n=453), so the deck is clearly winning matches.

The issue is the same as before: no trophies. Conversion sits at 23%, basically around the field median, but the deck keeps reaching elimination rounds without turning those runs into first-place finishes.

One trophyless week can easily be variance. Several weeks in a row starts to look like a pattern. Prowess may be very good at getting through Swiss, but something about the Top8 field, sideboarded games, or elimination-round matchups is keeping it from closing.

Graveyard decks as a whole

Graveyard is still one of the macro-archetypes of the format. As a group, it made up 16% of the metagame, appeared in the Top32 of every event, reached Top8 in 79%, and produced 3 total wins. Conversion was 27%.

The important part is that this is no longer one clean graveyard story. Grixis Reanimator looks like the leader. Living End is falling sharply. Goryo’s Vengeance keeps converting at a high rate, but its trophy count still lags behind the numbers.

Azorius Control

Azorius Control looks like one of the clearest signs that the post-ban format is opening up. The deck has about 5% metagame share, reached Top32 in 86% of events, reached Top8 in 36%, won 2 Challenges, and converted at 29%.

The win rate is 51% (n=359), which is solid rather than flashy, but the Challenge results are strong. More importantly, this is part of a longer growth pattern. Even if the short-window trend label is stable, the deck has now been moving up for several weeks.

Control is no longer just a small specialist pocket. It is becoming one of the decks you actually need a real post-board plan for.

Archetype breakdown

Archetype-level conversion

At the archetype level, Combo had the cleanest conversion week, helped heavily by Belcher. Aggro still won the largest share of events, mostly because Boros Energy remains very strong in the hands of experienced pilots. Ramp is the strange case: excellent Top32 presence, reasonable Top8 presence, but no wins. Control is not the biggest part of the field yet, but its conversion is good enough to treat it as a real piece of the format.

Aggro - 28% meta

Aggro is still the largest archetype in the field. It appeared in the Top32 of every event, reached Top8 in 93%, and won 43% of the Challenges. Since 43% of 14 events is 6 wins, Aggro still had the strongest trophy output of the window.

The interesting part is that this is happening while Boros Energy, the main Aggro deck, is still losing raw popularity. Aggro is not as dominant by share as it was before the bans, but the results are still there.

Boros Energy

Boros Energy has about 10% metagame share and a Falling Deck trend, but the Challenge line is excellent: 100% Top32 presence, 71% Top8 presence, 5 wins, and 35% conversion.

This is a deserved Challenge Overperformer label. If people expected Boros to collapse after the bans, this window does not support that reading. The deck is smaller, but it is still winning. It even looks like it performs better then before the bans.

Affinity

Affinity is another deck that should not disappear from the conversation. It has 7% metagame share, a falling trend, and 50% win rate (n=487), so the raw league data does not make it look especially scary at first glance. The Challenge data tells a different story.

The deck appeared in the Top32 of every Challenge in the window and posted the highest delta in the entire deck field. In other words, Affinity is showing up in results much more often than its metagame share would suggest. That does not automatically make it an overperformer, though. Its Top8 conversion was only 19%, below the field median, so this looks more like a deck with excellent presence than a deck that consistently turns that presence into trophies.

The split between larger and smaller Challenges is also interesting. Affinity looked much better in C64 events, where it had 100% Top32 presence, around 42% Top8 presence, and all of its first-place finishes from this window. In C32 events, the deck was much less impressive: lower Top32 presence, only one Top8 appearance, and no wins. That may just be sample noise, but for now the bigger-event data is clearly more favorable.

Prowess

Prowess has about 6% metagame share and looks stable. It reached Top32 in 93% of events and Top8 in 43%, but again finished with 0 wins.

The deck is not weak. The win rate is 53% (n=453), and its result presence is far above what the metagame share alone would predict. The open question is whether it can solve the Top8 closing problem. Also, I had a signal that the player won with the Challenge with the Prowess deck, but it was named differently. Unfortunately, I can’t catch all of those things because I do those analyses by myself in my free time, but thank you a lot for those updates!

Combo - 18% meta

Combo had one of the strongest weeks among the macro-archetypes. It appeared in the Top32 and Top8 of every event, won 29% of Challenges, and had the best archetype-level conversion at 28%.

Belcher is obviously the headline deck, but this is not only a Belcher story. Broodscale Combo is also still rising and still converting well.

Belcher

Belcher had only 3% metagame share, but it posted 86% Top32 presence, 50% Top8 presence, 2 wins, 41% conversion, and a 12% Win/Top32 rate.

This is exactly the kind of deck that punishes lazy sideboarding and lowering the guard. You may not face it every league, but when it shows up in Challenges, it is going deep.

Broodscale Combo

Broodscale Combo has about 5% metagame share, a Rising Deck trend, 93% Top32 presence, 50% Top8 presence, one win, and 32% conversion. The win rate is 52% (n=408).

The deck has been one of the fastest-growing Combo decks for several weeks in a row. At this point, it should be treated as a real part of the format, not as a temporary spike.

Graveyard - 16% meta

Graveyard decks are stable in the metagame share and very visible in Challenge results. The archetype had 100% Top32 presence, 79% Top8 presence, 21% winner-event frequency, and 27% conversion rate.

That is a healthier trophy count than in the previous window, but the story is uneven. Grixis Reanimator is doing most of the work, Living End is moving in the wrong direction, and Goryo’s Vengeance is still stuck in the familiar pattern of good conversion without many wins.

Grixis Reanimator

Grixis Reanimator looks like the best graveyard deck right now. It reached Top32 in 93% of events, Top8 in 50%, won 2 Challenges, and posted a 51% win rate (n=471).

The deck is rising and has clearly moved ahead of Living End in the current Challenge data. If you are choosing which graveyard deck to respect first, this is the one.

Living End

Living End is the weak point of the archetype this week. It has about 5% metagame share, but only 57% Top32 presence, 14% Top8 presence, 0 wins, and 19% conversion.

The league win rate is the biggest warning sign: 40% (n=402), the lowest win rate among trusted decks in the field. That is not a number I would casually wave away. The format looks prepared, and Living End is paying the price.

Goryo’s Vengeance

Goryo’s Vengeance has about 4% metagame share, 93% Top32 presence, 50% Top8 presence, one win, and 39% conversion. That is the second-best conversion number in the field after Belcher.

This is the same pattern we have seen before: the deck reaches elimination rounds at an impressive rate, but the trophy count still trails the conversion profile.

Midrange - 12% meta

Midrange had 100% Top32 presence, 79% Top8 presence, 14% winner-event frequency, and 23% conversion rate. It is not the loudest archetype in the room, but it remains very present.

For Zoo players, the most relevant part of this bucket is still Domain Zoo itself. The deck lost metagame share after the Phlage ban, but the results are not nearly as bad as the raw popularity number suggests.

Domain Zoo

Domain Zoo is only about 2% of the metagame and still has a Falling Deck trend. It reached Top32 in 50% of events, Top8 in 29%, finished with 0 wins, and converted at 28%. The win rate is exactly 50% (n=164), but a sample is pretty low.

The important correction is that 28% is not a top-three conversion number in the full field. Belcher, Goryo, Boros, Broodscale, and Azorius all sit higher. But it is still above the median, and for a deck with only 2% share, that matters.

That is the real takeaway: Zoo has a popularity problem, not a death certificate. When the deck reaches Top8, it can still fight. The lack of a win in this sample looks much more like finals variance than proof that the archetype is gone.

Ramp - 10% meta

Ramp appeared in the Top32 of every Challenge, reached Top8 in 57%, and finished with 0 wins. It also had the highest archetype-level delta at about +90 percentage points, mostly because of Eldrazi Tron.

The archetype is present everywhere, but the trophy count is empty. In practical terms, Ramp is something you need to prepare for, but the current data does not show it as a deck family that is actually winning Challenges.

Eldrazi Tron

Eldrazi Tron has about 6% metagame share and a Rising Deck trend. It appeared in the Top32 of 13 out of 14 Challenges, but had only 29% Top8 presence and 0 wins.

This is a clear Needs Attention deck. It may not be closing events yet, but it is too common in results to ignore.

Control - 10% meta

Control is now a real part of the post-ban format. It reached Top32 in 93% of events, Top8 in 50%, has a rising archetype trend, and converted at 24%.

That is a meaningful change from the pre-ban feel of the format. Control is no longer just a choice for specialists. It is starting to shape the field around it.

Azorius Control

Azorius Control is the main reason Control matters this week. It has about 5% metagame share, 86% Top32 presence, 36% Top8 presence, 2 wins, and a 29% conversion rate.

The deck is not exploding in raw win rate, but it is consistent, growing, and finishing tournaments.

On the Radar - Universe B

Below are decks that sit below the safe league encounter threshold, but still show up enough in Challenges to matter.

Jeskai Blink - below threshold

43% Top32 presence, 14% Top8 presence, 0 wins. The archetype is not back to its old position, but it is still showing up often enough to keep on the radar. It is now more into a control then midrange role.

Dimir Midrange - below threshold

43% Top32 presence, 7% Top8 presence, 0 wins. Worth tracking, but not yet a format pillar.

Boros Burn - below threshold

36% Top32 presence, 7% Top8 presence, 0 wins. Burn is not a major deck, but it still appears often enough to punish lists that get too greedy.

WUR - below threshold

29% Top32 presence and 7% Top8 presence. The shell is present, but the data does not show a breakout yet.

Sultai Ritual - below threshold

21% Top32 presence and one win by Ardonas. A win from below the encounter threshold is always worth putting on the radar.

Sam Combo - below threshold

21% Top32 presence and 14% Top8 presence. Not common, but not invisible either.

BRG - below threshold

7% Top32 presence and one win by Aldreen. This could be a pilot spike, but a Challenge win is still a Challenge win.

Best pilots

Several pilots had standout windows. rastaf on Boros Energy finished with 2 wins and 6 Top8s, MayoDominaria also put up 2 wins and 4 Top8s with Boros Energy, Savior0117 did the same with Belcher, and Azja matched that line on Broodscale Combo.

McWinSauce on Esper Blink, Denisevich on Grixis Reanimator, ashame on Azorius Blink, and DFrank on Amulet Titan also finished with 2 wins and 2 Top8s each. These names matter because some of the best deck results this week may be partly pilot-driven.

Conclusion

The post-ban format did not reset into a completely new world. Boros Energy still wins. Amulet and other older pillars are still around. But the space around them is clearly wider than it was before.

The biggest winner of this window is Combo, mostly because Belcher overperformed so hard. Control also looks more real each week, with Azorius Control now posting both growth and trophies. Ramp is back in the results, but not in the winner column. Prowess and graveyard decks keep reaching Top8, although they still have different versions of the same trophy problem.

For Domain Zoo, the message is cautiously positive. The deck lost popularity after the Phlage ban, but the Challenge results do not support the idea that Zoo is dead. The deck needs work, and it probably needs the right build for the new field, but when it reaches elimination rounds, it still has the numbers of a deck that can compete.

By Karol Małota

aka WarLord1986pl / TribalFlamesInYourFace

Idea

Sideboard construction in competitive Magic: The Gathering is conventionally guided by subjective assessments of metagame composition and individual matchup experience. This article presents a quantitative framework grounded in encounter probability, calculated from metagame share data (MTG Decks database) projected onto an assumed event size of N=1000 players, to make sideboard allocation decisions more systematic. By distinguishing between deck-level and archetype-level encounter rates, and applying a hypergeometric model to estimate the probability of encountering a given opponent type across a 5-round event, I try to demonstrate that archetype-level targeting offers substantially better sideboard efficiency than deck-specific targeting. A practical application to Domain Zoo (Thrull variant) is provided as a worked example, grounded in a published sideboard guide for that archetype. I also address the question of scale: when does this framework yield an actionable signal, and when is the event too small for it to be meaningful? Finally, I consider the temporal dimension of metagame tracking and close with a practical rule-of-thumb framework for players preparing for high-stakes events such as RCQ season.

You can find how to use Metagame Analyser Tool in this Video.

1. The Problem with Conventional Sideboard Design

All players who are involved in competitive magic know that sideboard construction typically proceeds from two sources: personal matchup experience and qualitative metagame assessment derived from tournament results and community discussion. Both are susceptible to systematic biases. Tournament coverage overrepresents top-finishing decks and underrepresents the actual distribution a player encounters across a field. Personal experience is subject to recency bias and small sample sizes.

A more tractable approach is to treat the sideboard as a constrained optimisation problem. Given 15 slots and a known (or estimated) probability distribution over opponent archetypes and decks, how should those slots be allocated to maximise expected utility across the event? The prerequisite for this approach is reliable metagame share data and a model that translates that share into a concrete probability of encounter.

2. The Data Model: Metagame Share, Event Size, and Encounter Probability

2.1 Data Source: Metagame Share from Decklists Database

The input data comes from MTG Decks (mtgdecks.net), a database that aggregates MTGO and paper event decklists. For each deck or archetype, the database reports its metagame share: the proportion of submitted decklists playing that deck in the tracked period. For this date in Modern, Boros Energy represented 17.89% of all decklists, meaning roughly 1 in 5.6 decks in the database was Boros Energy.

You have to remember that it is a field composition estimate, not a directly measured per-game encounter rate. It assumes that the distribution of decks in the database is representative of the actual competitive field a player will face. This is a reasonable approximation for MTGO Leagues, where the player pool is large, diverse, and broadly representative of the active competitive metagame. The assumption becomes weaker for local events, which is addressed in Section 4.

2.2 Event Size Assumption: N=1000

From my observations, MTGO Competitive Leagues have approximately 1000 active participants at any given time. The framework uses N=1000 as the assumed event size, which determines how many players are expected to be on each deck. If Boros Energy has a 17.89% metagame share, then approximately 179 of your potential opponents are on Boros Energy.

The choice of N=1000 is not arbitrary: it is a calibrated estimate of the MTGO League player pool. Yes, I’m aware that it’s sometimes 800 and sometimes 1300, depending on the season, but 1000 may be treated as a sweet spot. For other event types (RCQ, PPTQ, local events), N should be adjusted to reflect the actual or expected field size, as this affects the encounter probability calculation described below.

2.3 Encounter Probability Formula

Let’s go into math. Given N=1000 players in the field and k players on a given deck (where k = meta_share% x N / 100), the probability of facing that deck at least once across 5 rounds is calculated using a hypergeometric approximation. Because you cannot face the same opponent twice in Swiss, the probability of not facing deck X in a single round is (N-k)/(N-1), not simply (1-k/N). Over 5 rounds:

P(at least 1 encounter) = 1 - ((N - k) / (N - 1))^5

For Boros Energy: k=179, N=1000, so P = 1 - (821/999)^5 = 1 - 0.372 = 62.8%. This hypergeometric formula is slightly more accurate than the simpler binomial approximation 1-(1-p)^5 when the event population is finite and large but not infinite. For N=1000, the difference between the two formulas is small (typically under 1 percentage point), but the hypergeometric model is the correct one for Swiss tournament pairings.

It is important not to conflate encounter probability with the expected number of rounds until first encounter, which is (N-1)/k. For Boros Energy, that is 999/179 = 5.6 rounds. The fact that first encounter is expected after 5.6 rounds does not mean the probability of encountering Boros in a 5-round event is low. Because the distribution of first-encounter times has a long tail, the median encounter occurs well before the mean, and the probability of at least one encounter in 5 rounds is 62.8%.

3. Deck-Level vs. Archetype-Level Targeting

3.1 Deck-Level Data

At the individual deck level, encounter probabilities in Modern metagame are highly fragmented, with only Boros Energy exceeding 50% metagame share-equivalent pressure. The full picture for decks tracked at or above ~5% encounter probability is below.

A practical threshold emerges from this data. Below approximately 3.5% meta share (encounter probability ~16%), a player is more likely than not to never face that specific deck in a given 5-round event. Devoting a sideboard slot to a narrow answer for such a deck means that slot goes unused in more than half of all events. This does not mean that those decks are irrelevant, but that targeting them individually with specific hate is a poor use of constrained sideboard space.

For a clearer picture, I followed the Modern metagame for three consecutive weeks to see how it changes. From that data, you can see the Trend column: decks currently Rising (Boros Energy, Affinity, Jeskai Blink, Esper Reanimator, Tameshi Belcher, Dimir Frog) should be weighted more heavily than their current meta share alone suggests, while Falling decks may be over-represented in a static snapshot. That is quite relevant before RCQ season, when those deck fluctuations can tell you which deck is tested by players, which is doing fine, and which is naturally pushed out of the meta. It is quite important when you try to guess what to put into your sideboard.

3.2 Archetype-Level Data

Aggregating to the archetype level produces a fundamentally different picture. Individual decks are fragmented across many specific builds, but the underlying strategic vulnerabilities they share cluster into a much smaller number of categories. Remember that you can cluster your archetypes for your purpose. A good idea is to cluster them by game plan and weak spots; this is why I put the Reanimator archetype here and did not put those decks into Combo. The same is true for a Blink. But remember, do not overextend this. I use this clustering and consider the Blink archetype quite important for me; the same is true for Reanimator, but you can have your own archetypes. What is crucial for you is important. The archetype-level encounter probabilities for my data are:

When looking into the archetype level, every category exceeds the 17% encounter threshold, and six of eight exceed 29%. Aggro and Combo are effectively guaranteed encounters in virtually every 5-round event. Even Control and Rogue, which at the deck level were too fragmented to justify dedicated targeting, collectively represent encounter probabilities above 60% per event. A sideboard card that works broadly against Combo will be relevant in more than 99% of events; a card targeting only Ruby Storm specifically will be relevant in roughly 76% of events. That should give you an initial idea of why I am writing this article. Magic is a great example of an optimisation game, and for me, it is more optimal to have a card that works in 3 matchups than in one, especially since we all know how small the SB limit has become.

4. Sample Size and Applicability: When Does This Framework Work?

The framework rests on two inputs: metagame share data and an assumed event size. Both need to be appropriate for the context. Misapplying either produces false precision: numbers that look exact but measure the wrong thing. All this is based on my MTG Metagame Analyzer that you can use freely for your own data, share with others and use in your content.

4.1 The MTGO League Context: Where the Framework Is Calibrated

The framework is calibrated for MTGO Competitive Leagues. The MTG Decks database draws primarily from MTGO (in a smaller portion from paper events), which have large, diverse, and geographically broad player pools. The N=1000 assumption matches the approximate number of active participants in MTGO Modern Leagues. You can use this framework for any other format, just remember to use the proper number. I have no idea if it is useful for Arena, cause I did not find any information on how many people play the events, and they also had this ladder, which I think is not as easy to estimate. But as far as I know, there are some competitive events with known player numbers, so it can be used for sure in that case. In this context, metagame share data is genuinely predictive of the distribution of opponents a player will encounter, and week-to-week data is stable enough to make reliable inferences.

4.2 RCQ Preparation: The Most Practical Use Case

An RCQ season is the strongest practical use case for this framework for players who primarily compete in paper. Modern RCQ events typically draw 30-80 players, which is smaller than N=1000, and the encounter probability numbers should be recalculated with the actual expected field size. For N=64 and Boros Energy at 17.89% meta share, k=11 players: P = 1 - (53/63)^5 = 1 - 0.840^5 = 1 - 0.418 = 58.2%. The relative ranking of decks and archetypes is preserved, and the qualitative conclusions are unchanged, but the absolute encounter probabilities are lower than the N=1000 figures.

The more important point is that MTGO metagame share data is a reasonable proxy for the field composition at a competitive paper RCQ, particularly in the first half of a season before local metagame adaptations diverge significantly from the online metagame. Players preparing for an RCQ season can use this framework to build a sideboard that is robust to the archetype distribution they will actually encounter across multiple events, rather than optimizing for a single predicted opponent list.

4.3 Small Local Events: FNM and Store Leagues

Applying this framework directly to a local FNM with 12-20 players is using an instrument at the wrong scale. At N=16, the expected number of Boros Energy players in the field is 2-3, meaning any single round of pairings in such an event is dominated by sampling noise rather than metagame signal. A single local grinder bringing an unusual brew can shift apparent archetype shares by 10-15 percentage points within a single event. Moreover, in LGS, people know each other, and basically, it looks like everybody knows what somebody will play.

More fundamentally, local FNM metagames are shaped by factors that no aggregate database captures: local player preferences, budget constraints, and the social dynamics of a regular playgroup. Personal knowledge of the local player pool is a substantially better input than MTGO metagame share data at this scale. This is not a failure of the framework, it is the correct domain boundary for it.

4.4 Adjusting N for Non-League Contexts

Ideas from this article can be applied to any event size by substituting the appropriate N. For a 64-player RCQ, use N=64. For a 256-player Regional Championship, use N=256. The metagame share data (the k/N ratio) should remain constant; what changes is N itself, which scales k proportionally and affects the per-round encounter probability. As N increases, the hypergeometric formula converges toward the simpler binomial approximation, so for large events the difference is negligible.

5. Temporal Dynamics: Metagame Drift and Trend Tracking

A single week of metagame share data is a snapshot. Competitive formats (such as Modern, Standard) metagames evolve continuously in response to new card releases, bans, tournament results, community discourse, and the natural predator-prey dynamics between archetypes. A sideboard optimised for Week 3 may be suboptimal for Week 7, and potentially wrong if a structural metagame shift occurs between data collection and the event. But do not overthink that, metagame analysis once a week is perfectly fine, you do not need to check it every day. Basically, a nice method is to do it once a week in one day, let’s say Monday (most of the big events are at the weekend, so Monday is a good day to check what happened).

5.1 Deck Lifecycles and the Trend Signal

Data from a 3-week period already contains directional trend information. Decks classified as Rising (Boros Energy, Affinity, Jeskai Blink, Esper Reanimator, Tameshi Belcher, Dimir Frog) are gaining meta share week-over-week and should be weighted more heavily than their current encounter probability alone suggests. Decks classified as Falling (Dimir Control, Izzet Prowess, Golgari Yawgmoth, Eldrazi Ramp, Grixis Reanimator, Azorius Control) may be over-represented in the snapshot relative to what a player will actually face a week or two later.

Simic Ritual provides a useful historical example. PleBoy sideboard guides describe it as a deck that spiked in popularity when it had a favorable matchup against Amulet Titan, then declined as both Titan’s prevalence fell and the field adapted. At its peak, it warranted dedicated preparation. A player tracking only a single-week snapshot at the wrong point in Simic Ritual’s cycle would either over-prepare (catching it on the way down) or under-prepare (catching it on the way up). Multi-week trend data resolves this ambiguity.

5.2 Rolling Averages vs. Single-Week Snapshots

Single-week metagame share data contains noise from one-off spikes: a prominent streamer playing a deck, a strong tournament result, or a weekend event with unusual field composition. A 4-week (or longer) rolling average of meta share is more robust for sideboard allocation decisions. The raw weekly data is useful for detecting emerging trends early; the rolling average is the appropriate input for stable slot allocation.

A practical heuristic: treat a deck as preparation-relevant when its meta share crosses the relevant threshold (roughly 3.5% for deck-level targeting, or any share at the archetype level) in two consecutive weeks, rather than a single-week observation. This filters out most transient noise without introducing significant lag.

5.3 Pre-Season vs. Mid-Season Calibration

At the start of an RCQ season, the metagame is typically unsettled and high-variance approaches to sideboard design are appropriate: broader archetype coverage, flexible hate cards that address multiple archetypes, and slightly more flex slots. By mid-season, the metagame tends to converge and the archetype distribution stabilizes. This is the point at which encounter probability data is most precise and fine-tuning card selection within archetype slots is the relevant margin. Rebuilding sideboard composition entirely mid-season based on a single week’s data is generally a mistake, absent clear evidence of a structural shift such as a major ban or an unambiguously dominant new deck reaching critical mass.

6. A Framework for Slot Allocation

6.1 Coverage Groups: The Right Unit of Analysis

The practical allocation process should operate on coverage groups rather than pure archetype labels. A coverage group is defined by shared sideboard vulnerability, not strategic category. Graveyard hate addresses Goryo’s Vengeance, Esper Reanimator, Living End, and Storm (via Past in Flames) simultaneously. Fast-mana/multiple spell hate (Damping Sphere) addresses Ramp and portions of Combo. These groups typically have combined encounter rates well above any individual archetype within them.

Grouping by vulnerability rather than archetype captures an important efficiency: a single well-chosen card covering three decks from two different archetypes is more efficient than three deck-specific answers, even if the individual answers are stronger in their respective matchups.

6.2 Adjustments for Maindeck Strength

Encounter probability tells you how often you will need the sideboard card; it does not tell you how badly you need it. A deck with a 30% encounter rate but a 55% pre-sideboard win rate requires fewer dedicated slots than a deck with a 20% encounter rate but a 20% pre-sideboard win rate. Both inputs are necessary: encounter frequency determines how often the investment pays off, conditional win rate determines how much the investment is worth per occurrence.

6.3 Cross-Coverage Card Selection

Within allocated slots, prioritize cards that remain relevant across multiple coverage groups. Nihil Spellbomb/Thraben Charm covers Goryo’s Vengeance, Esper Reanimator, Living End, and Storm simultaneously. Wear // Tear hits Ruby Storm’s key permanents, Affinity’s artifacts, Urza’s Saga, Amulet Titan cards and various enchantment-based hate cards across multiple matchups. Mystical Dispute is effective against Neoform, Uxx Blink Decks, hard-cast Subtely, Kappa Cannoneer, Psychic Frog and Teferi. Cards effective against exactly one specific deck should only occupy slots if that deck’s meta share is high enough to justify the investment, roughly 5%+ for reliable league-level relevance.

7. Worked Example: Domain Zoo (Thrull Variant)

Domain Zoo with the Doorkeeper Thrull (DKT) package is a useful worked example because its maindeck is already well-positioned against many fair strategies, constraining where sideboard slots need to work hardest. The analysis below references The Pleybook (made by great Zoo player known as Pleyboy), a published sideboard guide for the archetype, to ground card selection in tested matchup knowledge.

7.1 Maindeck Baseline

Thrull Zoo’s maindeck includes Leyline Binding and Consign to Memory as primary interaction, Scion of Draco plus Leyline of the Guildpact as the domain combo, Phlage, Titan of Fire’s Fury as a recursive threat, Ragavan, Nimble Pilferer for early pressure and mana advantage, and DKT for ETB denial. The Thrull enables both defensive lines (blanking Solitude, Riddler, Atraxa triggers) and offensive ones (hasty Phlage via Arena of Glory). This maindeck configuration handles fair Aggro and Midrange reasonably well; the sideboard’s primary job is to address combo and graveyard strategies where the maindeck is structurally weak.

7.2 Coverage Groups and Slot Allocation

The Pleybook confirms several of these allocations through direct matchup testing. Against Boros Energy (62.8% encounter probability, the highest-priority matchup by a large margin), Wrath of the Skies is the primary sideboard answer, supplemented by Celestial Purge for Blood Moon and Phlage. Against graveyard combo across multiple decks, Nihil Spellbomb appears consistently as a low-cost, flexible answer. Against the combo matchups broadly, Mystical Dispute handles Neoform, Frog, Riddler, Teferi, Murktide Regent, Subtely, and all blue spells making it one of the highest cross-coverage cards available in the sideboard.

The guide also illustrates where raw encounter probability data is insufficient. Damping Sphere appears in the Eldrazi Tron and Amulet Titan sideboard guides, but is explicitly flagged as a potential trap against E-Ramp (shuts off Arena of Glory lines, which are critical for applying pressure) and against Neobrand (two-mana tax is too slow against their combo speed). These are specific to the deck’s game plan and cannot be detected by encounter probability. The data tells you how many slots to allocate; it does not tell you which cards to put in them.

7.3 Maindeck Strength Adjustments

Against Aggro (Boros Energy, Affinity), Thrull Zoo has meaningful maindeck equity. DKT stops Affinity’s Weapons Manufacturing and Kappa Cannoneer triggers outright. The Scion plus Leyline of the Guildpact combo creates a 4/4 flying blocker with first strike that stabilizes against most Aggro draws. Because of this built-in resilience, the Aggro sideboard allocation can be somewhat lighter than the 86.2% encounter rate alone would suggest. In the guide, only 3 slots address the Boros matchup directly, with the balance allocated toward combo and graveyard strategies where the maindeck has no structural answer.

8. Sideboard Guides: The Right Level of Specificity

Sideboard composition should be designed at the archetype level, using encounter probability data to determine slot allocation. Sideboard guides (explicit in/out instructions) should operate at the individual deck level. These are different decisions made at different times with different information available.

The composition decision happens before the event, under uncertainty about which specific decks will appear. Archetype-level encounter probability is the right input here. The in-game decision happens after game 1, when the opponent’s specific deck is known. At that point, archetype-level guidance is too coarse: the question is not ‘how many anti-Combo cards do I board in’ but specifically whether to keep Mystical Dispute or Nihil Spellbomb against Goryo’s Vengeance given what the opponent revealed in game 1.

Sideboard guides operates correctly at this level: explicit in/out recommendations per deck, play/draw distinctions (e.g., different Ragavan counts OTP vs. OTD against Jeskai Blink, different cuts against Affinity on the play vs. draw), and non-obvious interaction callouts. Writing this level of detail is worthwhile for decks above roughly 3.5% meta share, where encounter probability exceeds 16% and the matchup will arise frequently enough to justify preparation. For decks below that threshold, heuristic archetype-level guidance is sufficient: ‘against graveyard combo broadly, keep Nihil Spellbomb and Leyline of the Void, cut Thrull and LoTG.’

9. Limitations

Several assumptions underlying this framework deserve explicit acknowledgement. The metagame share data from MTG Decks reflects the distribution of submitted decklists, not a directly measured per-game encounter rate. The assumption that these proportions are representative of actual opponent distribution is reasonable for large competitive events but weakens for local events with distinct local metagames. N=1000 is a calibrated approximation for MTGO Leagues; applying it uncritically to a 32-player RCQ overstates encounter probabilities by roughly 40-60% at the deck level.

The hypergeometric model assumes random Swiss pairings from a fixed field. Real Swiss pairings are record-dependent: by rounds 3-5, you are paired predominantly against players with similar records. If certain archetypes perform better at higher records (e.g., Combo decks tend to either win early or lose early), the late-round pairing distribution may differ from the overall field distribution. This effect is difficult to quantify without round-by-round data and is not accounted for in the current model.

Most critically, encounter probability is a necessary but not sufficient input for slot allocation. The model addresses how often you will face a given archetype; it says nothing about how bad the matchup is without dedicated hate, how flexible each specific hate card is, or whether a given card creates with the deck’s own game plan. These require matchup knowledge and testing that no statistical model replaces.

10. Rule of Thumb: Practical Checklist for Data-Assisted Sideboard Design

The following checklist summarizes the framework. It is a starting structure, not a rigid prescription. The data informs the decision; it does not make it.

Step 1: Verify data source and event size

• Data from MTG Decks or similar large decklists databases is appropriate for competitive preparation.

• Use N = actual expected field size for your event (1000 for MTGO League, 64 for typical RCQ, etc.).

• For FNM or local events below ~30 players: use personal field knowledge instead of aggregate data.

• Encounter probability numbers change with N; recalculate if your event size differs significantly from 1000.

Step 2: Check trend direction before allocating slots

• Rising decks deserve more slots than their current meta share alone suggests.

• Falling decks may be over-represented in a single-week snapshot.

• Prefer 3 or more week rolling averages over single-week data for stable allocation decisions.

• Do not rebuild the entire sideboard around a single anomalous week unless a structural shift is evident.

Step 3: Allocate slots to coverage groups, not individual decks

• Group decks by shared sideboard vulnerability, not archetype label.

• Calculate combined encounter probability per coverage group.

• Deck-level targeting is justified above ~3.5% meta share (>16% encounter probability per event).

• Below that threshold, target the coverage group the deck belongs to, not the deck itself.

Step 4: Adjust for maindeck baseline strength

• Reduce slots for matchups your maindeck already handles adequately.

• Increase slots for matchups where you lose structurally without dedicated hate.

• A bad matchup you face rarely may warrant as many or more slots than a moderate matchup you face often.

Step 5: Prioritize cross-coverage cards within slots

• Prefer cards relevant against 2+ coverage groups over single-deck answers.

• Check for your own deck’s game plan before finalizing card selection.

• Reserve 1-2 flex slots for metagame-specific adjustments between events.

Step 6: Build composition at archetype level, guides at deck level

• Sideboard composition is decided before the event: use archetype-level encounter probability.

• In-game swap decisions are made after game 1: use deck-specific guides.

• Detailed in/out guides are worth writing for decks at or above ~3.5% meta share.

• Below that threshold, general heuristics by coverage group are sufficient.

Above all: encounter probability data is an input to sideboard design, not a replacement for matchup understanding. The data tells you where to allocate resources and how many slots each coverage group deserves. It cannot tell you that Damping Sphere shuts off your own Arena of Glory lines, that DKT is the correct answer to Jeskai Blink’s Solitude package specifically because it also blanks Riddler on the same mana, or that Mystical Dispute is substantially weaker against Eldritch Evolution than against Neoform. Those insights come from playing the matchups and studying the work of experienced players. The analytical framework and the matchup knowledge are complementary: neither is sufficient without the other.

11. Conclusion

Encounter probability derived from metagame share data provides a quantitative basis for sideboard slot allocation that is more reliable than qualitative assessment alone, provided it is applied at the right scale and interpreted correctly. The central finding is that archetype-level targeting is substantially more efficient than deck-level targeting: all eight tracked archetypes exceed the encounter threshold that justifies dedicated preparation, while many individual decks do not. A sideboard built around coverage groups with broadly applicable hate cards will outperform one built around specific predicted deck lists across a full season of events.

The framework has clear domain boundaries. It is calibrated for large competitive events with fields that approximate the MTGO metagame distribution. It degrades gracefully but not infinitely as event size decreases, and it should not be applied to small local events where field composition is driven by local factors the database cannot capture. For RCQ preparation, it is the most appropriate analytical tool available to a competitive player without access to private team data.

The practical workflow is: verify data source and event size, check trend direction, allocate slots to coverage groups using multi-week average encounter probability, adjust for maindeck baseline strength, select cards for maximum cross-group coverage while checking for internal non-bos, and write detailed matchup guides only for decks frequent enough to warrant that investment. Treat the output as a structured starting point that requires matchup experience to execute correctly.

By Karol Małota

aka WarLord1986pl / TribalFlamesInYourFace

I also want to thx Pleyboy and Hasku from Zoo Discord for help with that 😉

Quick definitions

· Top32 presence - in how many Challenges a deck appeared in the Top32.

· Top8 presence - in how many Challenges a deck appeared in the Top8.

· Conversion - how often Top32 appearances become Top8 appearances.

· Win/Top32 - how often a Top32 appearance turns into an actual Challenge win.

· Delta - the difference between metagame share and Challenge-result presence. A high delta suggests that a deck shows up in results more often than its raw metagame share would imply.

· Trusted sample - a sample that can be treated as reasonably meaningful, while still remembering that MTGO results can swing sharply from week to week.

Key observations

Belcher

Belcher is the cleanest story of the week. The deck won 3 Challenges from only 4.2% metagame share, and it did so in the hands of two different pilots. On top of that, it posted a 36.0% Top32 to Top8 conversion rate, one of the best results in the entire data set.

This looks like a deck that is still flying somewhat under the radar of sideboards. For comparison, Boros Energy has 13.2% metagame share and also won 3 events, meaning Belcher reached the same final result with more than three times less representation in the field.

Prowess

Prowess is in a strange place. On one hand, it has solid Top32 and Top8 presence. On the other hand, it has now gone three weeks in a row without a win. With 57.1% Top8 presence and 0 trophies, this is starting to look less like pure bad luck and more like a real problem with closing events.

This is not a deck that looks weak. Quite the opposite: both delta and conversion are above the median. The issue is that good entries into the elimination rounds are not becoming wins.

Eldrazi Tron

Eldrazi Tron had 100% Top32 presence - it appeared in the results of every single one of the 14 Challenges. At the same time, it finished with 0 wins and only 12.5% conversion, one of the weakest numbers among decks with a real sample.

This is the biggest gap of the week between presence and performance. The deck is clearly returning to the format and should be kept in mind, but the results show that, for now, it is more often present everywhere than actually finishing tournaments.

Azorius Control

Azorius Control looks like one of the biggest winners of the current window. It has 7.3% metagame share, a rising trend, 37.0% conversion, 7.4% Win/Top32, and a win rate around 54% at n=555.

This is already the fourth week of growth in a row. If this trend continues for another week or two, the deck will quickly move from “watch this” to “must prepare.” From the Domain Zoo perspective, this is especially important because control may become one of the real reference points for sideboard construction.

Living End

Living End posted a very clear decline. The deck still has 5.0% metagame share, but only 7.1% Top8 presence, 5.0% conversion, and 0 wins. Its win rate fell to around 46% at n=384.

Not long ago, Living End looked like one of the main beneficiaries of the return of cascade. Now the data suggests that the format is adapting. Some of the hate prepared for cascade and graveyard decks may be hitting it directly, while the rise of control also makes life harder.

Graveyard decks as a whole

The Graveyard archetype is still highly present: 100% Top32 presence and 78.6% Top8 presence. The problem is that the entire archetype converted all of that into only one win across 14 events.

This is a pattern that has repeated for several weeks now: graveyard decks regularly reach Top8, but they rarely close the tournament. Grixis Reanimator looks like the best deck in this space, Living End is falling sharply, and Goryo’s Vengeance still shows strong entries without trophies.

Archetype breakdown

Aggro - 32.7% meta

Aggro remains the largest archetype in the format. It appeared in the Top32 and Top8 of every one of the 14 events. As a whole, it has 35.7% winner event frequency and 25.1% Top32 to Top8 conversion.

What is interesting is that the whole archetype is losing popularity. This is not only the result of Boros Energy declining; the other aggro decks are also moving down. One possible reason is pressure from cascade decks and a higher amount of sideboard cards that indirectly make life harder for fast strategies.

Boros Energy

Boros Energy currently has 13.2% metagame share and a downward trend, but the results are still very solid. The deck appeared in 92.9% of Top32s, 85.7% of Top8s, and won 3 events, which equals 21.4% of all Challenges in this window.

Its win rate is around 51% at n=1010, so the sample is already fairly solid. It is possible that after the bans some less experienced pilots left the deck, while the players still posting results are more likely to know the archetype well. The high delta suggests that Boros still appears in results much more often than its raw metagame share would imply.

Affinity

Affinity has 7.5% metagame share and is also declining, which is somewhat surprising. The deck has access to good tools against cascade, is fast, and in theory should be able to fight both control and parts of the ramp field reasonably well.

Despite the lower metagame share, the results are strong: 92.9% Top32, 64.3% Top8, and 2 wins, or 14.3% winner event frequency. The win rate is around 54%, but on a smaller sample than Boros (n=569), so I would not base the entire evaluation only on that number. Delta +85.4pp still shows a deck with a very strong presence in results.

Prowess

Prowess has 5.5% metagame share and is still declining. That does not stop it from appearing regularly in results: 85.7% Top32 and 57.1% Top8. The problem is the lack of wins.

A win rate around 53% at n=421 looks solid, but the sample is not huge. The more important signal is different: once again, Prowess looks like a deck that goes deep into tournaments but cannot turn Top8 appearances into trophies.

Combo - 19.0% meta

Combo is the second largest archetype in the metagame. It appeared in 100% of Top32s and 85.7% of Top8s. More importantly, it won almost 43% of events, more than Aggro despite having a much smaller share of the field.

This is where the most important story of the week lives: Belcher.

Broodscale Combo

Broodscale Combo has 4.9% metagame share and a rising trend. The deck posted 71.4% Top32, 35.7% Top8, and one win, or 7.1% winner event frequency.

Its win rate is around 50% at n=377, so the raw win rate itself is not the most impressive part. The more important pieces are the delta, the Challenge Overperformer flag, and the fact that this is the fastest-growing Combo deck for the third week in a row. This is not a deck I would ignore.

Belcher

Belcher has only 4.2% metagame share, yet it appeared in 78.6% of Top32s, 64.3% of Top8s, and won 3 events. That gives it 21.4% winner event frequency, the same final result as Boros Energy with much lower metagame share.

Its 36.0% conversion and roughly 12.0% Win/Top32 put it near the top of the entire field. The win rate is around 54%, although on a small sample (n=323). Combined with delta +74.3pp, that gives it a deserved Challenge Overperformer flag.

In my view, this is the main story of the week.

Amulet Titan

Amulet Titan has 2.8% metagame share and a downward trend, most likely as an after-effect of the bans. Even so, the deck is still putting up excellent tournament results: 64.3% Top32, 21.4% Top8, and 2 wins, or 14.3% of events.

Conversion is 25.0%, and Win/Top32 is 12.5%, one of the best numbers in the format. The win rate sits around 52%, but on a small sample (n=217). The conclusion is simple: metagame share is going down, but experienced pilots can still win with Amulet without Lotus Field.

Ruby Storm

Ruby Storm has 2.2% metagame share and a downward trend. Even so, the deck appeared in 71.4% of Top32s and 21.4% of Top8s, but finished the period without a win.

Its win rate is only around 45% at n=168, so this needs to be treated carefully, but the signal does not look great. It is possible that hate prepared for cascade is also hitting Storm as splash damage. Many sideboard cards that are good against cascade are also very reasonable against Storm.

Crashing Footfalls

The unban of Violent Outburst brought Crashing Footfalls back into the metagame. The deck currently has 2.4% metagame share and is slowly growing.

The results, however, are mixed: 64.3% Top32, but only 7.1% Top8, 0 wins, and 11.1% conversion. The win rate is around 44% at n=185. The deck’s metagame share is indeed rising, but the Challenge results do not yet confirm its strength. Maybe the format is already well prepared for cascade, or maybe two vanilla 4/4 creatures are less scary in today’s Modern than they used to be.

Graveyard - 13.6% meta

Graveyard as an archetype looks very stable in terms of presence, but weak in terms of winning events. It has 100% Top32, 78.6% Top8, but only 7.1% winner event frequency, which means one win in 14 Challenges.

This is an archetype that regularly reaches the elimination rounds, but struggles to finish the job.

Grixis Reanimator

Grixis Reanimator has 5.7% metagame share and a rising trend. The results are very good: 92.9% Top32, 57.1% Top8, and one win.

Conversion is 33.3%, the win rate is around 53% at n=436, and delta +87.1pp gives it a strong Challenge Overperformer flag. Right now, it looks like the strongest graveyard deck in Challenges and beats Living End in almost every important metric.

Living End

Living End has 5.0% metagame share, but its results dropped hard. The deck posted 71.4% Top32, only 7.1% Top8, 0 wins, and just 5.0% conversion.

The win rate fell to around 46% at n=384. This is still not a gigantic sample, but the trend is clear. Not long ago, Living End had very high Top8 presence. Now it has fallen to a level that suggests strong format adaptation. Cascade hate, graveyard hate, and a better position for control may together explain the drop.

Goryo’s Vengeance

Goryo’s Vengeance has 2.6% metagame share and also a downward trend. The deck posted 85.7% Top32, 35.7% Top8, but 0 wins.

Conversion at 31.2% and a win rate around 50% at n=198 show a deck that can still enter the top tables regularly, but does not close events. This is another example of the broader graveyard pattern: strong presence, weak trophy count.

Midrange - 11.2% meta

Midrange as an archetype has 100% Top32, 85.7% Top8, and 14.3% winner event frequency, meaning 2 wins. Conversion is 23.1%.

The whole archetype is clearly gaining. This is interesting because Phlage was a very midrange card, and some builds definitely suffered from its ban. On the other hand, midrange usually has many tools and can adapt more easily to a new field.

Domain Zoo

Domain Zoo currently has 3.0% metagame share. The deck dropped after the Phlage ban, but the new versions look playable and effective. Zoo probably has one of the widest ranges of builds in the format: from more aggressive Nacatl versions, through grindy midrange with Quantum Riddler, to more exotic shells.

The results are better than the metagame share alone would suggest: 71.4% Top32, 42.9% Top8, 0 wins, and a very good 35.3% conversion. That is the third-best conversion result in the field. The win rate is around 51% at n=230.

With conversion that high, the lack of a win looks more like a small-sample and finals-variance issue than proof of a real weakness. In other words: Zoo is not dead. The deck has a metagame-share problem, but when it does break into Top8, the numbers suggest that it can fight close to the end of the event.

Yawgmoth

Yawgmoth has 2.3% metagame share and looks stable. The deck posted 64.3% Top32, 28.6% Top8, but like Zoo, it finished without a win.

Conversion is 23.5%, and the win rate is around 53% at n=177. The sample is small, so I would not draw overly sharp conclusions, but the deck looks solid. The heavy presence of graveyard hate may be somewhat hostile to it right now, but this is still a deck worth watching.

Ramp - 8.9% meta

Ramp appeared in 100% of Top32s across all 14 events. The archetype has 57.1% Top8 presence, 7.1% winner event frequency, and 20.4% conversion. Delta at +91.1pp is the highest among archetypes.

Eldrazi Tron

Eldrazi Tron has 5.8% metagame share and a rising trend. It appeared in 100% of Top32s, but only 28.6% of Top8s, and it did not win an event.

Conversion at 12.5% is very weak for a deck with such regular presence. The win rate is around 50% at n=442, and delta +94.2pp is the highest in the entire field. This deserves a Needs Attention label: the deck is present in every Challenge, but for now it cannot turn that presence into trophies.

The main takeaway: Tron is coming back. Even if it is not winning yet, a Top32 finish in a Challenge is still a meaningful result, and 100% Top32 presence means you cannot ignore this deck when preparing for the format.

Control - 8.7% meta

Control is one of the bigger surprises of this period. The archetype has 85.7% Top32, 42.9% Top8, and 14.3% winner event frequency. Conversion is 33.3%, the second-highest value among archetypes.

The most important point is that Control has a rising trend and looks like a real part of the new metagame, not a one-week spike.

Azorius Control

Azorius Control is the main representative of the archetype and, alongside Dimir Control, looks like one of the most serious control decks in the format. It has 7.3% metagame share and a rising trend.

The results are very strong: 85.7% Top32, 42.9% Top8, 2 wins, 37.0% conversion, and 7.4% Win/Top32. On top of that, it has a win rate around 54% at n=555 and delta +78.4pp.

This is a deserved Challenge Overperformer flag. Four straight weeks of growth, a good sample, and excellent conversion suggest that Azorius Control may be one of the most important decks of the next few weeks.

Blink - 5.8% meta

Blink, recently one of the top archetypes, dropped hard after the bans. Even so, it still has solid results: 92.9% Top32, 50.0% Top8, 7.1% winner event frequency, and 31.0% conversion.

The trend is rising, so I would not write this archetype off. It looks more like a deck that has been heavily rebuilt after the bans and may still return to a larger role.

Esper Blink

Esper Blink has 3.2% metagame share and posted 64.3% Top32, 28.6% Top8, and 0 wins. Conversion is 28.6%.

The win rate looks weaker: around 45% at n=245. The sample is not huge, but for now the win rate does not support the deck’s rising popularity. Still, Blink is an archetype you should respect, especially if the upward trend continues next week.

On the Radar - Universe B

Below are decks that sit below the safe league encounter threshold, but still show up repeatedly on the Challenge-results radar.

Eldrazi Ramp - 0.8% meta

42.9% Top32, 7.1% Top8, 0 wins. For such a low metagame share, the Top32 presence is definitely worth noting.

Sultai Ritual - 1.0% meta

28.6% Top32, 14.3% Top8, and 1 win. A win at around 1% metagame share is a strong signal that the deck may be more than a one-off curiosity.

Jeskai Blink - 0.3% meta

Jeskai Blink, until recently one of the more important decks in the format, has fallen below 1% metagame share. It has 21.4% Top32, 14.3% Top8, and 0 wins. This is one of the clearest examples of a deck that was genuinely weakened by the bans.

BRG - 0.7% meta

21.4% Top32, 7.1% Top8, and 1 win. Aldreen won an event with this build. It may be the result of one very strong pilot, but a win at sub-1% metagame share definitely deserves a place on the radar.

Mono-Black Midrange - 0.8% meta

35.7% Top32, 7.1% Top8, 0 wins.

The win rate is around 44%, but without a clear sample size I would treat this number cautiously.

Domain Zoo perspective

From the Domain Zoo perspective, this week is interesting because the deck formally lost metagame share after the Phlage ban, but it does not look dead. Quite the opposite: 35.3% conversion suggests that when Zoo reaches Top8, it can play very deep into the event.

The biggest things I would watch when preparing Zoo:

· Belcher - low metagame share, but a huge impact on this week’s results. You cannot assume this deck is fringe just because you may not meet it often in leagues.

· Azorius Control - rising and looking increasingly like a real problem. This may force a different approach to sideboarding and post-board game plans.

· Eldrazi Tron - not winning yet, but appearing in the Top32 of every event. You need a plan because the deck is returning to the field.

· Graveyard decks - still very high presence, even if the number of wins is low. Graveyard hate still makes sense, but the exact amount matters.

· Prowess - not winning events, but consistently reaching the top tables. You cannot ignore it just because it has no trophies.

Overall, the post-ban format does not look completely reset. Instead, the emphasis has shifted. Boros and Amulet can still win, Combo had a very strong week thanks to Belcher, Control is coming back, and Zoo - despite the drop in popularity - still has numbers suggesting real potential.

How to Track and Analyze Tournament Meta

In this guide, I want to go deeper into metagame analysis and explain how to approach it efficiently using automation tools. This is aimed at tournament organizers, competitive players, content creators who need to produce regular meta reports, and anyone who loves diving into statistics and meta trends but doesn’t want to spend hours wrestling with Excel every week.

I’ll cover what metagame analysis actually involves, why manual methods are time-consuming, and how to use MTG Metagame Analyzer, a tool I built, to automate most of the work. The goal is to help you produce professional meta reports in minutes, not hours.

What is Metagame Analysis

Most competitive players already understand what the metagame is, but since this guide is also aimed at newer tournament organizers and content creators, let’s start with a clear definition.

The metagame (or “meta”) is the ecosystem of deck choices, strategies, and trends in a given format. Metagame analysis means tracking:

· Which decks are being played and how popular they are (meta share)

· Which decks are actually winning (win rates)

· How the meta changes over time (trends)

· Which decks you’re most likely to face in a tournament (encounter probability)

In practice, doing good meta analysis means you can make better preparation decisions, choose optimal deck choices, and understand format health. For tournament organizers, it means providing valuable content to your community.

The Problem with Manual Analysis

Let’s walk through what typical meta analysis looks like without automation.

You finish a tournament and have the data: deck names, how much of the field played each deck, and win rates. Getting that data isn’t the hard part. What comes next is where things become time-consuming.

Data Entry

You copy tournament results into a spreadsheet. This part is usually fine it takes 5-10 minutes depending on tournament size.

Visualization

Here’s where it gets tedious. Want a pie chart showing meta share? A bar graph for win rates? You’re opening Excel, creating charts, fighting with formatting, adjusting colors, fixing labels, resizing everything, and hoping the result doesn’t look terrible.

Even simple visualizations take 30-60 minutes to make presentable. If you want multiple chart types or professional-looking output, add another 30 minutes.

Historical Tracking

Did Mono-Red actually spike this week, or did it just have one good showing? Without tracking data over multiple weeks, you’re just guessing.

Keeping organized historical records means maintaining multiple spreadsheets, manually comparing data between weeks, and identifying trends yourself. Most people don’t bother with this part, which means missing important patterns.

Statistical Analysis

What’s your actual probability of facing Boros in a 9-round tournament if it’s 15% of the meta? Which deck should you prioritize in testing?

These questions require real math—hypergeometric probability distributions that most players aren’t calculating by hand. Without this, you’re making preparation decisions based on gut feeling rather than actual probabilities.

The Time Investment

For a single tournament’s meta report with decent visualizations and basic analysis: 1.5 to 2 hours of work.

If you run weekly tournaments, that’s 75-100 hours per year just on meta analysis. That’s a significant time investment, which is exactly why many organizers either skip detailed reports or produce basic summaries that don’t tell the full story.

The Automated Approach: MTG Metagame Analyzer

There’s a tool I built called MTG Metagame Analyzer that automates the visualization, statistics, and trend tracking parts of this process.

You still need to manually collect and enter your tournament data. There’s no way around that. But everything that comes after data entry is automated.

How It Works

The workflow is straightforward. You collect your tournament data (deck names, meta percentages, win rates), paste it into a provided Excel template, upload the file to a Google Colab notebook, answer a few configuration prompts (tournament size, number of rounds, etc.), click Run, and download your complete meta report as a ZIP file with all charts and data.

First-time setup takes about 10 minutes. After that, generating weekly reports takes under 5 minutes from start to finish.

Input Data Format

The Excel template requires these columns:

Required Columns

· Deck: Deck name (e.g., “Boros Energy”, “Jeskai Blink”)

· Meta: Metagame percentage as a number (e.g., 15.2 for 15.2%)

· Winrate: Overall win rate as a decimal (e.g., 0.52 for 52%)

Optional Columns

· Archetype: Broader deck category (e.g., “Aggro”, “Control”, “Blink”). If not provided, all decks are labeled as “Rogue”

· My Winrate: Your personal win rate against this deck as a decimal (e.g., 0.58 for 58%). Decks with this data will be marked with an asterisk (*) on encounter probability charts

The “My Winrate” column is useful if you track your own match results and want to see your personal performance alongside the overall metadata. Instead of using win rates from online sources or tournament results, you can add your own tracked win rates to identify which matchups you’re personally struggling with or excelling at.

Configuration Options

When you run the tool, it will prompt you for several configuration options. Here’s what each one does:

Player Count

Default: 1,000 players (typical large tournament)

This affects encounter probability calculations. Adjust based on your tournament format:

· Large events (SCG, GPs, MTGO Leagues): 1,000+ players

· Regional qualifiers: 100-500 players

· Small LGS events: 8-20 players

Lower player counts result in higher encounter probabilities, since you’re sampling from a smaller pool.

Number of Rounds

Default: 5 rounds (standard for MTGO Leagues)

This represents how many different opponents you’ll face in the tournament. The tool uses this to calculate how likely you are to encounter each deck at least once across all your matches.

Adjust based on your tournament structure:

· MTGO Leagues: 5 rounds

· Small LGS events (Swiss): 3-4 rounds

· Larger tournaments (Swiss): 7-9 rounds

· GPs/Major events: 15+ rounds

More rounds means higher probability of encountering any given deck at least once.

Important note: Changing the number of rounds between weeks will affect Encounter Probability calculations, but will NOT affect trend charts. Trend charts track meta share percentages over time, which are independent of tournament structure. This means you can safely compare trends across tournaments with different round counts.

Minimum Encounter Probability Threshold

Default: 5% (shows only decks with ≥5% encounter probability)

This filters encounter probability charts for readability. If your meta has 30 different decks, showing all of them makes the chart cluttered and hard to read. The threshold lets you focus on decks you’re actually likely to face.

Adjust based on your needs:

· Lower threshold (2-3%): See more fringe decks

· Higher threshold (8-10%): Focus only on the most common matchups

Trend Analysis Window

Default: 4 weeks (if you have historical data)

When generating trend charts, the tool asks how many weeks back you want to analyze. Minimum is 2 weeks (you need at least 2 data points for a trend), maximum is however much history you have.

4 weeks is usually a good balance—enough to spot real trends without being affected by very old data that may no longer be relevant.

What the Tool Generates

When analysis completes, you’ll download a ZIP file containing all output files. Here’s exactly what you get:

Excel Files (Data Tables)

· deck_analysis_W{N}.xlsx: Deck-level metrics with all calculated fields

· deck_analysis_ARCHETYPE_W{N}.xlsx: Archetype-level aggregation (combines similar decks)

· deck_analysis_WITH_TRENDS_W{N}.xlsx: Deck metrics with trend status column (only if historical data available)

CSV History File

· Metagame_History_W{N}.csv: Updated historical database. Upload this file next week to continue tracking trends

Chart Files (300 DPI PNG)

· encounter_prob_Deck_W{N}.png: Bar chart showing probability of facing each deck

· encounter_prob_Archetype_W{N}.png: Bar chart showing probability of facing each archetype

· meta_trend_Deck_W{N}_last{X}w.png: Line chart showing how deck meta shares changed over the last X weeks (requires history)

· meta_trend_Archetype_W{N}_last{X}w.png: Line chart showing how archetype meta shares changed over the last X weeks (requires history)

All charts are publication-quality at 300 DPI resolution. You can use them directly in videos, articles, social media, or presentations without any editing.

How Calculations Work

The tool performs several statistical calculations automatically. You don’t need to understand these to use the tool, but if you’re curious about what’s happening under the hood, here’s a breakdown.

Encounter Probability

Uses hypergeometric distribution to calculate the probability of facing a specific deck in a tournament. This is the mathematical model for sampling without replacement—exactly what happens in Swiss pairings.

The formula accounts for:

· Total number of players in the tournament

· Number of players on each deck (calculated from meta percentage)

· Number of rounds you play (your sample size)

Result: P(encounter deck at least once in N rounds)

For example: If Mono-Red is 18% of a 1,000-player tournament and you play 5 rounds, the tool calculates your exact probability of facing it at least once. This is not a rough estimate—it’s the actual statistical probability.

Importance Score

The tool calculates an “Importance” metric that combines meta prevalence and performance:

Importance = 0.7 × (normalized meta share) + 0.3 × (normalized win rate range)

Breaking this down:

· 70% weight on meta share: How common is this deck?

· 30% weight on win rate range: How well does it perform?

· Both metrics are normalized (scaled 0-1) so they’re comparable

This score is then used to assign Prep Priority quartiles.

Prep Priority Quartiles

Decks are divided into four quartiles based on their Importance score:

· Q4 - Very High Prep Priority: Top 25% of decks by importance. These are must-prepare matchups

· Q3 - High Prep Priority: Next 25%. Strongly recommended to test these matchups

· Q2 - Medium Prep Priority: Middle 50%. Optional preparation

· Q1 - Low Prep Priority: Bottom 25%. Minimal focus needed

This quartile system appears on encounter probability charts the percentage labels are color-coded by prep priority (red = very high, orange = high, blue = medium, green = low).

Performance Labels

Each deck is assigned a performance category based on how its meta share and win rate compare to the median values:

· Underplayed Winner: Meta share below median AND win rate above median. These decks are performing well but not many people are playing them potential hidden gems

· Popular Trap: Meta share above median AND win rate below median. Many people are playing these decks but they’re underperforming be cautious

· Neutral: All other combinations

Performance labels appear as color-coded deck names on encounter charts (green = underplayed winner, orange = popular trap, black = neutral).

Trend Status

If you have historical data (at least 2 weeks), the tool calculates whether each deck is Rising, Falling, or Stable.

The calculation:

· Take the last 4 weeks of data for each deck

· Calculate the average meta share over those weeks

· Compare current week’s meta share to that average

· Apply thresholds:

• Decks: Change > 0.5 percentage points = Rising or Falling

• Archetypes: Change > 0.2 percentage points = Rising or Falling

Archetype thresholds are lower because archetypes aggregate multiple decks and tend to have more stable meta shares. This prevents false positives from normal variance.

Archetype Aggregation

When you provide an Archetype column, the tool performs two levels of analysis simultaneously:

· Deck Level: Individual deck metrics (”Jeskai Blink”, “Esper Blink”)

· Archetype Level: Combined metrics for all decks in an archetype (”Blink”)

For archetype-level calculations:

· Meta share: Sum of all deck meta shares in that archetype

· Win rate: Weighted average of deck win rates (weighted by each deck’s meta share)

· My Winrate: Weighted average of personal win rates (if provided)

You can name archetypes however you want—the tool doesn’t enforce any taxonomy. Common approaches include strategy types (”Aggro”, “Control”), card names (”Blink”, “Energy”), or color combinations (”Boros”, “Esper”).

Who This Is For

Different parts of the Magic community can use this tool in different ways. Here are the most common use cases:

Tournament Organizers

If you run weekly Modern nights, monthly Pioneer events, or regular competitive tournaments, you probably want to share meta reports with your players. This tool lets you generate professional summaries in 5 minutes instead of spending an hour on spreadsheets after each event. Your players get clean visualizations and useful statistics, and you can track format health over time.

Specific applications: weekly meta reports for Discord or social media, monitoring format diversity to identify dominant strategies, and data-driven discussions about format health or potential bans.

Content Creators

Making meta analysis videos or articles requires good visuals. Amateur-looking Excel charts hurt your content quality. The tool generates publication-ready charts at 300 DPI. Download them, drop them into your video editor or article layout, and you’re done.

Some creators are using it for weekly meta update videos, format overview articles at the start of each season, and live meta analysis streams during major events.

Competitive Players

Preparing for a Regional Championship Qualifier, PT event, or other competitive tournament means knowing what you’ll face. The tool tells you exactly which decks you’re most likely to encounter and helps prioritize your testing time.

Example workflow: Collect data from the last month of local tournaments or similar events in your region. Run the analysis to see encounter probabilities. Add your current win rates in the “My Winrate” column. Focus testing on decks with high encounter probability AND low personal win rate. Use trend data to identify “rising” decks that might spike at your event.

Local Playgroups

Even casual groups sometimes track their own meta. Maybe you play regular Commander nights, informal Standard leagues, or kitchen table formats. The tool works just as well for small, informal metas as it does for tournament data.

Data Enthusiasts and Statistics Nerds

Some people just love analyzing data and spotting patterns. If you’re the kind of player who enjoys tracking trends, building spreadsheets, or diving into the numbers behind the game, this tool gives you professional-grade statistical analysis without the manual work.

Common applications: tracking your local meta evolution over an entire season, comparing different formats or regions, building historical databases of meta trends, and testing statistical hypotheses about deck performance.

Why Use This Instead of Manual Methods

You can absolutely do meta analysis manually in Excel or Google Sheets. Here’s what you trade off:

Time Savings

Manual analysis: 1.5-2 hours per tournament. Automated analysis: 5 minutes per tournament.

If you track meta weekly, that’s saving 75-95 hours per year. That’s almost two full work weeks of time you could spend actually playing Magic, testing your deck, or producing other content.

Consistency

When you manually create charts every week, they look slightly different each time. Font sizes change, colors vary, formatting is inconsistent. Automated output means every report has identical formatting and professional quality.

Statistical Accuracy

Most players aren’t calculating hypergeometric probabilities by hand. The math isn’t impossible, but it’s tedious and easy to mess up. Having accurate encounter probabilities automatically calculated means you can make better preparation decisions based on real numbers rather than gut feeling.

Historical Data Management

Maintaining historical data in spreadsheets means carefully organizing multiple files, remembering to update comparison formulas, manually identifying trends, and risking data loss if files get corrupted or deleted. The tool handles all of that automatically.

Cost

The tool is free and open source. You’re not paying for software, subscriptions, or premium features. If you want to modify it for your specific needs, the code is available on GitHub.

Getting Started

If you want to try the tool, here’s exactly what to do:

Collect Tournament Data

You need deck names, meta percentages, and win rates for each deck that appeared in your tournament. Optionally, also collect archetype classifications and your personal win rates against each deck.

Download the Excel Template

Get the template from the GitHub repository: github.com/Warlord1986pl/MTG-Metagame-Analyzer

The template has pre-formatted columns for all required and optional data.

Fill in Your Data

Copy-paste your tournament results into the template. This takes about 5 minutes depending on how many unique decks were played.

Important notes: Meta percentages can be entered as decimals (0.18) or whole numbers (18)—the tool handles both. Win rates must be decimals (0.52 for 52%). Leave “My Winrate” blank for decks you haven’t played against.

Open Google Colab

Go to colab.research.google.com (you’ll need a Google account, but it’s free). Create a new notebook and copy the entire script from the repository file docs/SCRIPT_FULL.txt into the Colab cell.

Run the Analysis

Click Runtime → Run all (or press Ctrl+F9). The tool will prompt you to upload your Excel file, upload your CSV history file (optional—only if you have data from previous weeks), enter configuration values (player count, number of rounds, minimum encounter threshold), and specify trend window (if you have historical data).

Download Results

When analysis completes (usually 30-60 seconds), a ZIP file will automatically download containing all Excel data tables, updated CSV history file (save this for next week), and all PNG chart files at 300 DPI.

Time Investment

First time using the tool: 10-15 minutes to familiarize yourself with the process.

After that: Under 5 minutes per tournament to generate complete meta reports.

Working with Historical Data

Trend analysis is one of the most powerful features, but it requires maintaining historical data. Here’s how it works:

Week 1 (No History)

Upload only your Excel file with current week’s data. Tool generates 2 encounter probability charts (deck + archetype). Tool outputs Metagame_History_W1.csv. Save this CSV file—you’ll need it next week.

Week 2+ (With History)

Upload your current week’s Excel file and the Metagame_History_W{N}.csv from last week. Tool prompts: “How many weeks back for trend chart? (default 4)”. Tool generates 4 charts total: 2 encounter probability charts (same as Week 1) plus 2 trend charts showing meta share evolution over time. Tool outputs updated Metagame_History_W{N+1}.csv. Save the new CSV for next week.

Important Notes

· Always use the most recent CSV file when running new analysis

· The CSV contains both deck-level and archetype-level history

· Deck names must match exactly between weeks for trend tracking to work

· If you rename a deck, the tool will treat it as a new deck with no history

· Trend charts require min. 2 weeks of data they won’t generate on Week 1

Conclusions

This concludes the MTG Metagame Analysis Guide, where I explained the components of meta analysis—data collection, visualization, statistical calculations, and trend tracking—and showed how automation can save significant time while improving output quality.

Proper metagame analysis is a valuable skill for tournament organizers, competitive players, and content creators. The challenge has always been the time investment required. MTG Metagame Analyzer solves that problem by automating everything except data entry.

The tool is free, open source, and designed to be straightforward. If you’re tracking meta data but wishing the analysis part was automated, this might be useful.

The tool is available on GitHub at: github.com/Warlord1986pl/MTG-Metagame-Analyzer

If you find it useful, consider sharing it with your local Magic community or tournament organizers in your region.

By Karol Małota
aka WarLord1986pl / TribalFlamesInYourFace

Getting Domain

In Part Two of this mana-focused series, I want to go deeper into land sequencing and explain how to approach it in different game scenarios to play as optimally as possible.

In Part One, I focused on what lands we play in Domain Zoo and why. Now it’s time to talk about how to actually use that manabase correctly—how to get Domain efficiently and how to sequence lands depending on the matchup, your hand, and your opponent’s game plan.

Getting Domain

Most of you are already Zoo players and know what Domain is, but since this article is also aimed at newer players, let’s start with a clear definition. According to the MTG Wiki:

*Domain is an ability word used on cards that care about and count the number of different basic land types (zero to five) a player controls.*

In practice, playing a Domain deck means that you care about land types, not the number of lands. The more different basic land types you control, the stronger your Domain cards become.

There are two very important rules to remember here:

1. Domain does not care whether a land is basic or nonbasic—it only cares about basic land types.

2. Domain does not care how many lands you control, only how many different land types you have.

This distinction matters a lot in real games and explains why Domain Zoo works the way it does.

For example:

• A Triome immediately gives you three different land types.

• Leyline of the Guildpact (LOTG) can give you all five land types from a single land.

That’s exactly why Domain Zoo is possible at all—we can reach full Domain extremely early, sometimes as soon as turn one. Because of that, correct land sequencing is one of the most important skills when playing the deck.

Broadly speaking, there are three ways to achieve full Domain:

• on Turn 1

• on Turn 2

• on Turn 3

Each of these has clear advantages and drawbacks, and understanding when to use which plan is a big part of mastering the deck.

T1: Leyline of the Guildpact (LOTG)

This is the only way to achieve full Domain on turn one.

If Leyline of the Guildpact is in your opening hand, you may start the game with it on the battlefield. From that moment on, all lands you control have all basic land types.

This is, of course, the core combo with Scion of Draco, but for now let’s focus strictly on mana and sequencing.

With LOTG on the battlefield:

• Every land you control (including fetch lands) has all five land types.

• You no longer need to fetch for specific colors.

• Fetch lands can tap for any color of mana.

• You can cast Leyline Binding on turn one, which is extremely important in mirror matches to answer an opposing LOTG immediately.

LOTG vs Blood Moon and Harbinger of the Seas

One very common misconception is that LOTG protects you from Blood Moon or Harbinger of the Seas. It does not.

As explained in a Reddit answer by user Kaymico:

Leyline does Not Grant the Supertype “Basic” to your lands. Just the Basic Land types Like Forest, Island, mountain etc. The Basic Land Type is considered for Domain and Grant the ability to Tap for colored Mana.

But blood moon does Not Care about Lands having a Basic Land Type it Cares about the Supertype Basic Land.

Therefore Both cards are alternating the sub Type of your lands (one giving additional ones the other setting it to one) and therefore being handled in the Same layer.

When to Things Happen in the Same layer we use timestamps. So leyline effects Happen, then blood Moon or Harbinger effect

This leads to a very important gameplay implication:

If all your lands are nonbasic and your fetches are already tapped, you can completely lose Domain.

Because of this, a strong and often correct strategy when LOTG is in play is to fetch at least one basic land. LOTG gives basic lands all five land types, so a single basic land is enough to maintain full Domain.

From that point:

• Blood Moon can be answered with Leyline Binding

• Harbinger of the Seas can usually be removed with Lightning Bolt

Interaction with Arena of Glory

Another important interaction involves Arena of Glory (AoG).

AoG enters the battlefield untapped only if you control a Mountain. With LOTG:

• If AoG is your first land, it still enters tapped.

• If you already control another land, AoG will enter untapped.

• AoG gains all basic land types and can tap for any color of mana.

This matters for sequencing when LOTG is in your opening hand and AoG is part of your mana plan.

Should you fetch with LOTG in play?

This is one of the most nuanced decisions with LOTG, and the answer depends heavily on the matchup.

Against Blood Moon / Harbinger decks, the answer is clear:

you should prioritize fetching basic lands.

Against other decks, the situation is more flexible.

When you have the LOTG + Scion of Draco combo online, life total is usually less important because your creatures gain lifelink. In those cases, you can fetch more aggressively. However, you should still avoid being completely tapped out with only one land on the battlefield.

The reason is simple:

your opponent may have a way to bounce or destroy LOTG. Even if you don’t have a hard counterspell in hand, keeping mana open gives you flexibility and protects you from losing your entire mana setup.

When you don’t have the combo, the decision becomes more complicated.

Against aggressive decks like Boros or Prowess, protecting your life total matters much more. In those matchups:

• Fetching tapped shocks or surveil lands at end of turn is often correct.

• The goal is often not deck thinning, but putting cards into the graveyard to enable Phlage later.

Fetching additional lands while LOTG is on the battlefield can also make sense if you expect your opponent to answer LOTG. In those cases, building a backup configuration—such as a Triome + shock setup that still gives full Domain—is reasonable.

That said, this is where greed becomes dangerous. Against aggressive decks especially, fetching too aggressively can easily lose you the game.

One final detail: sometimes it is correct not to fetch a Triome early and instead go for three shock lands. Drawing a Triome later gives you the option to cycle it, which can be very relevant. This decision depends heavily on your opening hand and manabase configuration—especially because the deck has very limited green sources, and losing LOTG can make casting multiple Kavus in one turn difficult.

These are small details, but they are exactly the kind of things you learn through practice with the deck.

T2: Triome + Shock Land

This is the second way to achieve full Domain.

The most common line is:

• Turn 1: fetch for a Triome (for example, Indatha Triome)

• Turn 2: play or fetch a shock land such as Steam Vents

This gives you all five basic land types by turn two.

The main drawback of this approach is that, in most cases, you have no interaction on turn one, because Triomes always enter the battlefield tapped.

Timing the Triome

One small but important detail is when you fetch the Triome.

Fetching the Triome on your opponent’s end step can be a strong line. It:

• Conceals information about what deck you are playing

• May lead your opponent to assume you are holding interaction

• Can influence their decisions in suboptimal ways

At the same time, this line keeps open the option to fetch a shock land on turn two if you need to answer something immediately.

This becomes especially important:

• When you are on the draw

• Against aggressive decks like Prowess, Boros, or Affinity

In these situations, you are already behind on tempo. Playing a tapped land into two open mana from your opponent can be very dangerous.

Interaction considerations

Even when going for a T2 Domain, you must constantly ask yourself whether you actually need Domain on turn two.

There are many games where the correct line is to:

• Fetch a Triome

• Pass

• And only commit to full Domain if your opponent presents a threat that must be answered immediately

Having access to Steam Vents on turn two allows you to:

• Kill or counter a key threat (for example Ragavan or Tamiyo)

• Still transition into full Domain without losing too much tempo

This decision is especially relevant against aggressive decks like Prowess, Boros, or Affinity, where one unanswered creature can snowball the game very quickly.

Alternative Ragavan lines

There is also an important alternative line when your opening hand contains Ragavan, Steam Vents, and either a fetch land or a Triome.

In this case, you can:

• Play Steam Vents untapped on turn one

• Cast Ragavan

• If Ragavan connects, play a Triome on turn two and use the Treasure token to cast Scion of Draco or Territorial Kavu

This line is particularly strong against Tron. It allows you to apply early pressure while still holding up blue mana to counter cards like Karn, the Great Creator, Kozilek’s Command, or other Eldrazi spells.

Planning ahead: the third land

When you go for a turn-two Domain, it is very important to think one turn ahead.

Just like in LOTG scenarios, you need to consider:

• Blood Moon

• Harbinger of the Seas

This means that choosing the correct third land is often more important than simply completing Domain as fast as possible.

You should also plan ahead for Phlage. Not all fetch lands in the deck can produce both red and white mana, and escaping Phlage requires WWRR. Failing to plan your fetches can easily leave you unable to escape it when it matters most.

T3: Steam Vents + Temple Garden + Godless Shrine

T3: Steam Vents + Temple Garden + Godless Shrine

This is the third way to achieve full Domain, and also the slowest and most life-intensive one. Because of that, this line requires the most careful planning and matchup awareness.

You usually choose this approach in games where early interaction on turn one and turn two is crucial, especially when you are on the draw. Typical examples include:

• Blink decks, where you want to kill Phelia, counter Teferi, or have Leyline Binding available on turn two

• Frog decks, where early Binding or interaction is often mandatory

• Prowess decks, where you want to Bolt Monastery Swiftspear on T1 and bind Slickshot Show-Off or Cori-Steel Cutter on T2

• Situations where you want to play Ragavan on T1 and still keep mana open for interaction if it connects

Another common line is playing Ragavan on turn one and having it die immediately. In many matchups, this is actually a fine exchange—it drains your opponent’s removal and opens the door for Temple Garden on T2 to deploy a Territorial Kavu. These are just a few examples; there are many small sequencing decisions where delaying full Domain until turn three is simply the correct play.

Because this method can cost up to 9 life, nearly half of your starting life total, it is extremely important to evaluate the matchup correctly. Against aggressive decks, this line is inherently risky. While it can be correct against Prowess in some scenarios, you must always be aware of how much pressure you are allowing yourself to take.

A common way to mitigate the life loss is to:

• Play a fetch land and pass

• Fetch a tapped shock or even a surveil land at the opponent’s end step

However, this is not always possible. If you need to deploy a creature on turn two, you will often be forced to fetch an untapped shock, and that decision must be weighed carefully.

Optimal sequencing

For proper land sequencing, the most common and efficient line is:

Steam Vents → Temple Garden → black source (Godless Shrine or equivalent)

This sequencing allows you to:

• Deploy a 4/4 Territorial Kavu on turn two

• Attack for 5 damage on turn three

• Maintain access to early blue interaction

Alternative lines include Ragavan on T1, followed by another creature or Teferi on T2, depending on the matchup and hand texture.

Vulnerability to Blood Moon and Harbinger of the Seas

The biggest downside of this method is how exposed it makes you to Blood Moon and Harbinger of the Seas.

• On the draw (OTD):
  Your opponent can resolve Moon or Harbinger when you only have two lands on the battlefield, often locking you out of proper colors entirely.

• On the play (OTP):
  You may end up with three nonbasic lands in play before the opponent’s third turn, which is still very risky.

Because of this, it is crucial to plan your fetches carefully in these matchups.

A common and often correct line on the play is:

• Play your third land as a fetch

• Attack with a 4/4 Kavu

• Hold the fetch uncracked instead of greedily going for full Domain

This allows you to respond to Blood Moon or Harbinger by fetching the appropriate basic land.

The situation is even more complicated on the draw. In those games, it is often correct to:

• Leave your second fetch uncracked

• Hold up Stubborn Denial / Strix Serenade to counter Moon or Harbinger

• Or keep Lightning Bolt available to answer Harbinger immediately

Summary of T3 Domain

Overall, you should think about the T3 Domain line as:

• The most flexible way to achieve Domain

• But also the most punishing if sequenced incorrectly

It rewards good matchup knowledge, disciplined fetching, and a clear understanding of what your opponent is trying to do. When played well, it gives you maximum interaction and adaptability; when played poorly, it can easily lose you the game on the spot.

Conclusions

This concludes Part Two of the Domain Zoo manabase series, where we discussed the three most common ways to achieve Domain.

Proper fetching and land sequencing are critical skills when playing Domain Zoo. The deck is extremely flexible and adaptable, but that flexibility comes at the cost of complexity. Experience, matchup knowledge, and planning ahead matter a lot.

The key skill is anticipation—not only planning your own land drops and spells, but also understanding what your opponent is likely to do and sequencing your mana accordingly.

In Part Three, I will focus on mulligan decisions based on opening mana, as well as other problematic mana situations that can come up during games.

By Karol Małota
aka WarLord1986pl / TribalFlamesInYourFace

Zoo is a deck where a proper mana base is more crucial than in most other decks. You play all five colours and want access to at least four of them as early as turn two. Modern is a very fast and unforgiving format, so any mistakes with your mana will often cost you the game something I learned the hard way over the last four months.

This article is the first in a series about the Zoo manabase. It will be followed by others where I’ll discuss different land sequencing patterns and, later on, keep-or-mulligan decisions.

Stock DKT Zoo List

Throughout this article, I’ll refer to a stock Zoo list that, in my opinion, represents the most common version right now: Doorkeeper Thrull (DKT) Zoo. The list looks roughly like this:

Stock DKT Zoo List:

Creatures

• 4 Phlage, Titan of Fire’s Fury

• 4 Doorkeeper Thrull (DKT)

• 4 Scion of Draco

• 4 Territorial Kavu

• 4 Ragavan, Nimble Pilferer

Spells

• 1 Winternight Stories

• 2 Consign to Memory

• 4 Leyline of the Guildpact (LOTG)

• 4 Leyline Binding

• 1 Teferi, Time Raveler

• 4 Lightning Bolt

• 2 Stubborn Denial

Lands

• 1 Plains

• 2 Arena of Glory

• 1 Thundering Falls

• 1 Mountain

• 1 Godless Shrine

• 2 Steam Vents

• 4 Arid Mesa

• 1 Temple Garden

• 4 Flooded Strand

• 4 Wooded Foothill,

Please note that there are multiple versions of this deck. Some spell or creature counts may vary, but the core idea of the manabase remainsbasically the same.

Stock Manabase Overview

Zoo Typically plays 22 lands, consisting of:

• 12 fetch lands

• 1 triome

• 2 basic lands

• 2 copies of Arena of Glory

• 1 suareeil land

• The rest as shock lands

A stock Zoo manabase looks like this:

Triome

• 1 Indatha Triome

Basics

• 1 Plains

• 1 Mountain

Surveil Land

• 1 Thundering Falls

Shock Lands

• 1 Temple Garden

• 1 Godless Shrine

• 2 Steam Vents

Fetch Lands

• 4 Arid Mesa

• 4 Flooded Strand

• 4 Wooded Foothills

Misc

• 2 Arena of Glory

Indatha Triome

We start with the triome. You have several triome options, and the one you choose will define the rest of your manabase, because all of your fetch lands must be able to find it.

Currently, Indatha Trprovidesis the most popular choice. It gives access to:

• Green, needed to cast Territorial Kavu

• White, needed for Leyline Binding and Doorkeeper Thrulthe l

• Black, which in this list is used only to complete the Domain

Remember that the triome enters the battlefield tapped, so it’s best played on turn one, or later in the game if needed. Also, keep in mind that it can be cycled for three mana, so even if you draw it late, you can exchange it for something more useful.

Shock Lands

As discussed above, the triome gives you three colours, but to achieve a full Domain, you still need two more. That’s where shock lands come in:

• 1 Temple Garden

• 1 Godless Shrine

• 2 Steam Vents

A typical turn sequence is Indatha Triome on turn one, followed by Steam Vents on turn two. This gives you untapped Domain and allows you to play a 5/5 Territorial Kavu or Scion of Draco on turn two. It also enables a one-mana Leyline Binding if needed.

Importantly, these shock lands also give you four colours as early as turn two, and the whole Domain by turns three or four. You don’t always need five colours on turn two—and sometimes you actively don’t want to. This will be discussed in more detail in a future article.

Shock Land Choices

The Steam Vents + Temple Garden combination is the most important pair. Together, they give you four colours on turn two and allow you to cast your best creature in the deck: Territorial Kavu. I can’t imagine playing Zoo without these two lands.

Godless Shrine is more of a flex slot. It’s used only to provide black for Domain and could be replaced with Blood Crypt. The same applies to the number of Steam Vents. This list plays two because having access to blue mana is often crucial. For example, fetching Triome → Steam Vents → Steam Vents allows you cast crature while keeping blue mana open to protect it.

In the past, people played Sacred Foundry, but it was often the worst land to draw because it doesn’t help get Domain efficiently. I don’t recommend playing it.

You can replace one Steam Vents with another surveil land, but remember that surveil lands enter tapped, which will slow you down. There is flexibility here depending on your sideboard and colour needs. However, if you’re a beginner (like I am), I strongly recommend sticking to this shock land configuration. It’s the most universal setup and works well across many Zoo variants.

Surveil Land

The only surveil land in this list is Thundering Falls. Zoo can technically function without surveil lands, so this is a flexible slot. You can replace it with another surveil land (WB, UW, or WG), but I don’t recommend any color combination that fewer than eight of your fetch lands can find.

Surveil lands help filter draws, which is especially important in the late game. They also help fill your graveyard for Phlage, which is another reason I like having at least one surveil land.

In my opinion, a third blue source is very important, and Thundering Falls fits well. That said, this is a slot you can change fairly freely without heavily risking your manabase.

Fetch Lands

Fetch lands are just as important as triomes and shock lands. Zoo plays 12 fetch lands, and this configuration guarantees that every fetch can find both Indatha Triome and Steam Vents, which is absolutely crucial for the deck.

However, not every fetch can find every shock land, so you need to be careful when sequencing them. This is such an important topic that I’ll cover it separately in the next article, with concrete examples.

Another key point: Zoo mana can be very painful. Fetching and shocking repeatedly can easily cost you 9 life just to achieve full Domain. This is especially important against decks like Prowess, Energy, or other aggressive and burn-heavy strategies. Shock lands do not always need to enter untapped.

Fetch lands also help fill your graveyard, which enables Phlage. Even when Leyline of the Guildpact is on the battlefield, it can be correct to crack a fetch just to put a card into the graveyard and turn on Phlage.

Basic Lands

Zoo plays two basic lands: Plains and Mountain. There are three main reasons for this.

1) Blood Moon

Blood Moon is a three-mana enchantment that turns all nonbasic lands into Mountains. This effectively locks Zoo out of most of its colors. Boros Energy, one of the most popular decks in the format, plays Blood Moon in the main deck and often additional copies in the sideboard.

For this reason, we play Plains. White gives access to the best enchantment removal in Magic, and remember that Leyline Binding can also remove Blood Moon. If you expect Blood Moon, fetching Plains early is extremely important.

2) Harbinger of the Seas

Harbinger of the Seas is a three-mana creature that turns all nonbasic lands into Islands. Functionally, this is similar to Blood Moon, but since it’s a creature, it can be killed—usually with Lightning Bolt. To do that, you need red mana, which is why you fetch Mountain instead of Plains in this matchup.

Harbinger is most common in Merfolk but also appears in other blue decks, including UB strategies, Affinity, and even some combo decks like Belcher.

3) Land Destruction

This is a more marginal case, but some decks attack your manabase with cards like Ghost Quarter. Zoo is extremely vulnerable to land destruction because it relies so heavily on its lands.

Most land destruction effects allow the controller to search for a basic land, so having two basics gives you some protection and can buy enough time to close the game. These matchups are rare, but very difficult.

Arena of Glory

Finally, Arena of Glory. This is the only non-fetch land in the deck without a basic land type, and we play two copies. You should think of Arena more like a spell than a land—it gives your creatures haste, which is incredibly powerful.

Hasting Phlage from the graveyard deals 12 damage immediately if the opponent has no blockers, which is often enough to end the game. Even with blockers, you can kill one large creature or two smaller ones and still hit for six. Arena also gives haste to Ragavan, Kavu, and Scion, and it often decides games on its own.

However, Arena does not contribute to Domain and enters the battlefield tapped unless you control a Mountain. Even with Leyline of the Guildpact in play, Arena will still enter tapped if you don’t already control a Mountain.

Because of this, you generally don’t want Arena early in the game—it can be clunky. You also rarely need two copies, and if you draw a second one, you can discard it to Territorial Kavu to find something more useful.

Conclusion

This concludes Part One of the Zoo manabase series, where we covered land choices and their roles in the deck. The topic is quite large, and what I originally thought would be a single article will likely turn into two or even three parts to properly cover everything.

Remember: the best way to learn Zoo is simply to play it. Guides like this help give you a framework, but Zoo is a deck that rewards experience. You will make mistakes—mis-sequencing lands, misplaying spells—but that’s part of the learning process.

See you in the next article—and remember to play some Zoo 😉

By Karol Małota
aka WarLord1986pl / TribalFlamesInYourFace

Introduction

The Yawgmoth matchup is one of the most nuanced and punishing pairings for Domain Zoo players. While Zoo is fundamentally a proactive, pressure-based deck, Yawgmoth forces you to slow down, sequence your plays carefully, and respect multiple overlapping combo lines. Small mistakes — casting a spell too early, overextending into -1/-1 counters, or ignoring graveyard interactions — can easily cost you the game.

This guide is written primarily from the perspective of a Domain Zoo player, but I’ve intentionally kept the advice as general and principle-based as possible. Even if you’re piloting a different aggressive or midrange strategy, many of the concepts here — identifying key engine pieces, managing graveyard pressure, and choosing the right moment to commit resources — should still be applicable.

The focus of this article is not on a fixed play pattern, but on understanding what actually matters in the matchup: which threats must be answered, which cards can be safely ignored, and how to position yourself to close the game before Yawgmoth’s engines take over. Below you’ll find general gameplay tips followed by a practical sideboard guide tailored to Domain Zoo, but adaptable to similar decks.

General Tips

Consign of Memory can counter Agatha, Soul Cauldron, and trigger form creatures with undying.

Opponents can play Force of Vigor, so don’t rely too much on Leyline of the Guildpact.

Do not cast Phlage too early, as they can easily exile it from your graveyard. The best situation is when they tap Cauldron and you attack with Territorial Kavu, discard, and then play it.

Doorkeeper Thrull is strong in this matchup because it stops Bagdermole Cub animating lands.

Be vigilant: the combination of Young Wolf, Walking Ballista under Cauldron, and Dreader’s Insight can gain them a lot of life, and it can also kill you if they have Blood Artist on the battlefield.

Be aware of Yawgmoth, Thran Physician’s -1/-1 ability – it can wipe out your entire board. But it’s also an opportunity: keep Phlage and burn spells in hand as long as possible; they can win you the game if the opponent gets too greedy.

Top things to do:

• Counter Agatha, Soul Cauldron whenever possible.

• Exile creatures from their graveyard whenever possible.

• Keep burn spells (including Phlage, Titan of Fire’s Fury) to close the game.

• Don’t rely too much on Leyline of the Guildpact or Leyline Binding; they have Force of Vigor, so never play Territorial Kavu into two fetchlands.

• Ragavan, Nimble Pilferer is weak in this matchup, as they have many ways to block or kill it.

Sideboard Guide:

OUT:

• 4 Ragavan, Nimble Pilferer

• 1 Teferi, Time Raveler

• 2 Stubborn Denial

IN:

• All graveyard hate cards you have (Surgical Extraction is excellent in this deck). Exiling Agatha, Soul Cauldron in responding to Dreader’s Insight can make life much easier.

• Wear/ Tear (WT)

• Clarion Conqueror if applicable

• Celestial Purge – exiles Yawgmoth and Grist, the Hunger Tide

• Pyroclasm / Rough Tumble – they often go wide

• Consign to Memory – counters Agatha, Soul Cauldron and Undying triggers

• Wrath of the Sky if available – kills their creatures but also Agatha, Soul Cauldron and Dreader’s Insight