Pioneer data analysis

Published

August 12, 2025

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1 Acknowledgements

Thanks to Badaro for his data collection work and the archetype parser.
Thanks to Aliquanto for his initial analysis, which served as an inspiration for me.
Thanks to Jiliac for integrating Qonfused data and maintaining Format data.

2 Data include

This book contains data in Pioneer format since 16/12/2024. If the period in question contains ban announcements, decks containing non-legal cards have been excluded, as have the associated matchups. Decks containing more than 30 copies of a single card have also been excluded. For decklist analyses, only decks valid for the format have been included (number of main deck cards > 60 and number of side cards <= 15).

3 Principal chapter

3.1 Metagame

3.1.1 Presence archetype

This chapter shows the representation of differences over time. Leagues are excluded from this analysis.

File in 3 parts :

The first shows the presence curves over time for each archetype or archetype base (weeks are expressed in 2 last digits years.weeks of the year). Archetypes with too low a presence are deactivated by default but can be reactivated by clicking on the desired decks. By default, certain Archetypes are hidden if their number is less than 0.25%.

Leagues are includes in this part

The second part shows the presence barchart of the different archetypes (archetype is define as other if their number is less than the minimum of 50 or 1%) and base archetypes for different time intervals:

  • all data

  • one moth

  • two weeks

  • one week

Additional information is available in tooltip (for Archetype and base archetype):

  • Number of copies of the deck

  • The delta in percent compared to the upper time interval

  • Deck rank and its evolution compared to the previous time interval

  • Win rates and confidence interval

    • The confidence interval graphs show the averages and 95% confidence intervals (calculated using the Agresti-Coull method).

    • The vertical red line represents the mean of the winrates and the dotted blue lines represent the mean of the upper and lower bounds of the confidence interval.

    • Top player 10 (top 10 lower CI winrate bound) average win rate and CI (A player need at least 20 rounds for Archetype and 10 for base archetype) result are show above error barIn particular, the publication of the top32 only for results from MTGO led to an overestimation of the winrates, the winrates were centred.

The last part present :

  • The représentation of each colors combinations in the format

  • Number of target for 2 cmc black removal.

  • The presence of different cards in the format.

Leagues are includes in this part

3.1.2 Matrix WR

This chapter focuses on the data for which we know the result of each match and the Archetype of the opponent.

In order to be included, an archetype must be represented more than 50 times in the dataset.

  • Matrix considers the matches as a whole (for example, a 2-1 score counts as 1 game won).

Part one focus on Archetype (aggragated) and part two on base archetype (parser archetype).

They are built on the following model (additionnal information in tooltip) one tab for all data and one tab for 1 month data:

  • Summary of data.

  • Bar chart shows the presence of each archetype and base archetype, as well as their win rate and some additional information in tooltips.

  • The confidence interval graphs show the averages winrates (without miror matchs) and 95% confidence intervals (calculated using the Agresti-Coull method). The vertical red line represents the mean of the winrates and the dotted blue lines represent the mean of the upper and lower bounds of the confidence interval. - Top player 10 (top 10 lower CI winrate bound) average win rate and CI (A player need at least 20 rounds for Archetype and 10 for base archetype) result are show above error bar

  • A complete matrix with all the information.

  • Multiple table with win rate of cards per matchup (only valid deck and matchup with more than 10 games are presented) : the first concentrates on the aggregated maccro archetypes and the second presents the sub-archetypes. Each part is organised in the same way, repeated 2 times, one for the maindeck and one for the sideboard.

  • Base cards: These are the cards present in decks almost exclusively in a given number of copies (deck numbers without the most common count less than 10).

  • Side/Mainboard cards: Cards present in variable numbers in the decks The third part explores the notion of the best deck according to a given metagame using the winrates obtained using the complete games obtained on the data set and the presence of each archetype over time (weeks are expressed in 2 last digits years.weeks of the year).

In order to determine an expected number of victories 2 criteria are used the average winrate and the lower bounds of the confidence interval.Please note that this part is still under construction as some decks with too few matchups are included.

3.2 Deck winrate

3.2.1 Card win rate table

Presents the win rate of each card in each archetype in the form of multiple tables.

The definition of each column is given in a tooltip accessible by passing the cursor over the column names.

This file is split into 2 parts : the first concentrates on the aggregated maccro archetypes and the second presents the sub-archetypes.

Each part is organised in the same way, repeated 2 times, one for the maindeck and one for the sideboard.

  • Base cards: These are the cards present in decks almost exclusively in a given number of copies (deck numbers without the most common count less than 10).

  • Side/Mainboard cards: Cards present in variable numbers in the decks

3.2.2 Cards WR models

This analysis attempts to use regression to determine the cards with the best performance inside archetype or base archetype.

A binomial regression is initially trained on a set of decks. In order to be included in this analysis the archetype must be present at least 50 times in the dataset.

In order to be considered a card must be included at least 50 times in either the main deck or the sideboards, one or the other being considered separately. In models comparing the number of copies of each card, when a number of copies is less than 50 it is grouped with an adjacent number of copies. For example, a card that is present 32 times in 1 copy 200 times in 2 copies, 15 times in 3 copies and 47 times in 4 copies would lead to the following result 1/2 : 232 and 3/4 : 62. The formulation 2-4 indicates that the numbers of copies 2, 3 and 4 have been grouped together.

Be careful, this part leads to results that I’m not really sure of. The interpretation of the regression coefficients seems really questionable, particularly in relation to the collinearity problem and the very large number of variables with sometimes small sample sizes. I would therefore encourage you to be very careful.

Templates are created separately for the maindeck and the sideboard and maindeck and side board pull together (Total 75) according to the following scheme :

  • Base Cards cards systematically present in decks with an almost fixed number of copies less than 50 decks that do not have the most common number of copies. decks with zero copies are grouped with the majority class) contained in the decks, for which the number of copies varies, quasibinomial regression models are created using the wins and losses of each deck :

    • Comparing for each card presence Most common count vs absence Other

    • Comparing each card count with a sufficient sample size Most common count vs 1 vs 3-4 for example

  • Uncommon Cards, These cards are not always included in decks, quasibinomial regression models are created using the wins and losses of each deck :

    • Comparing for each card presence +1 vs absence 0

    • Comparing each card count with a sufficient sample size 0 vs 1 vs 3-4 for example.

3.3 Best performing deck

3.3.1 Best deck analysis

This analysis attempts to use regression to determine the decks with the best performance inside archetype or base archetype.

A binomial regression is initially trained on a set of decks. In order to be included in this analysis the archetype must be present at least 50 times in the dataset.

In order to be considered a card must be included at least 25 times in either the main deck or the sideboards, one or the other being considered separately. In models comparing the number of copies of each card, when a number of copies is less than 25 it is grouped with an adjacent number of copies. For example, a card that is present 32 times in 1 copy 200 times in 2 copies, 15 times in 3 copies and 47 times in 4 copies would lead to the following result 1/2 : 232 and 3/4 : 62. The formulation 2-4 indicates that the numbers of copies 2, 3 and 4 have been grouped together. Be careful, this part leads to results that I’m not really sure of. The interpretation of the regression coefficients seems really questionable, particularly in relation to the collinearity problem and the very large number of variables with sometimes small sample sizes. I would therefore encourage you to be very careful.

A total of 6 quasibinomial regression models are created using the wins and losses of each deck:.

  • Two models using the deck as a whole (maindeck and sideboard)

    • Comparing for each card presence +1 vs absence 0.

    • Comparing each card count with a sufficient sample size 0 vs 1 vs 3-4 for example

  • Four separate models 2 for maindeck and 2 for sideboard

    • Comparing for each card presence +1 vs absence 0

    • Comparing each card count with a sufficient sample size 0 vs 1 vs 3-4 for example

These different models are then used to determine the 7 complete decks (maindeck and sideboard) with the highest probability of victory for each archetype (weeks are expressed in 2 last digits years.weeks of the year).

As well as the 7 maindecks and 7 sideboards with the highest probability of victory are presented for each archetype.Warning: this second part can lead to inconsistent combinations. It seemed useful if you want explore the maindecks and sides separately.

Table shows the top7 decks:

  • Firstly base cards (present in all decklist).

  • Variables cards are present as card name average number of cards[minimum; maximum number of cards]number of base cards* (if this card is also in base cards)

3.3.2 Top 8 deck

This chapter is divided by week over the last 3 weeks (weeks are expressed in 2 last digits years.weeks of the year). For each week the different tournaments with more than64players.-For each tournament, a bar graph shows the presence of each archetype and base archetype, as well as their win rate and some additional information in tooltips.

  • A table shows the top8 decks, their basic archetype Archetype the player (which is a link to the decklist), and the decklist itself.

3.4 New card

This chapter focuses on the cards that have recently entered the format (the latest 5 months). The aim is to present the number of times they have been included in decks and their winrates. The file is split into 3 parts:

  • A first part aggregating all the cards whether they are maindeck or sideboard and whatever the archetypes.

  • The second part is stratified by archetype and shows the presence and winrate of new cards when they are present in the main deck.

  • The third part is stratified by archetype and shows the presence and winrate of new cards when they are present in the sideboard.

For parts 2 and 3, the win rates of the cards are only described in situations with a number of wins and losses (excluding 5-0 leagues), but the presence of a card also includes 5-0 leagues.

4 Archetype aggregation

For the grouping of decks, the analyses are mainly centred around 2 concepts: archetype and base archetype. Base archetypes are very close to the archetypes returned by the XXX parser. The archetypes are a personal construction to try to solve two problems:

  • giving more flexibility to predict certain decks considered unknown by the parser
  • Group together decks with a small number of players that would be very close to a deck with a larger number of players.

Deck with banned cards or with 40 copies or more of a single card are excluded.

4.1 Predict model

5 models were trained on decks with a defined archetype over the last 6 months, or over the entire period of interest if it was longer than 6 months, with cross-validation on 5 folds. The hyper parameters of each model were chosen from a grid search.

  • C5 decision tree
  • Random forest
  • Elastic net regression
  • KNN
  • Xgboost

Then the ‘unknown’ decks or decks with an archetype with low sample size were predicted by each model returns a probability that the deck belongs to each training archetype. The results were aggregated by averaging the probability returned by each model that a deck belonged to one of the training archetypes. For decks with an average probability greater than 0.3, they were integrated into the most likely archetype on average according to the models.

Tabler summarise how the archetypes are aggregated
Custom corresponds to my definition of archetypes, also shown as Base_archetype in the data

Reference corresponds to Badaro definition of archetypes, also shown as Reference_archetype in the data

Parser
Custom
Reference
Custom Reference Percent Archetype Percent Sub Archetype Percent Archetype Percent Sub Archetype
Mono Red Aggro (n :2973) Mono Red Aggro Mono Red Aggro 1621/2973(54.5%) 1621/1621(100%) 1612/2973(54.2%) 1612/1612(100%)
Rakdos Aggro Rakdos Aggro 469/2973(15.8%) 469/469(100%) 469/2973(15.8%) 469/469(100%)
Boros Convoke Boros Convoke 17/2973(0.6%) 17/17(100%) 17/2973(0.6%) 17/17(100%)
Jund Creativity Jund Creativity 13/2973(0.4%) 13/13(100%) 13/2973(0.4%) 13/13(100%)
Gruul Aggro Gruul Aggro 466/2973(15.7%) 466/466(100%) 466/2973(15.7%) 466/466(100%)
Temur Creativity Temur Creativity 2/2973(0.1%) 2/2(100%) 2/2973(0.1%) 2/2(100%)
Mardu Aggro Mardu Aggro 8/2973(0.3%) 8/9(88.9%) 8/2973(0.3%) 8/9(88.9%)
Azorius Metalwork Combo Azorius Metalwork Combo 9/2973(0.3%) 9/11(81.8%) 9/2973(0.3%) 9/11(81.8%)
Opus Opus 7/2973(0.2%) 7/7(100%) 7/2973(0.2%) 7/7(100%)
Boros Goblins Boros Goblins 15/2973(0.5%) 15/15(100%) 15/2973(0.5%) 15/15(100%)
Boros Aggro Boros Aggro 41/2973(1.4%) 41/41(100%) 41/2973(1.4%) 41/41(100%)
Izzet Creativity Izzet Creativity 111/2973(3.7%) 111/111(100%) 111/2973(3.7%) 111/111(100%)
Gruul Creativity Gruul Creativity 3/2973(0.1%) 3/3(100%) 3/2973(0.1%) 3/3(100%)
Grixis Creativity Grixis Creativity 2/2973(0.1%) 2/2(100%) 2/2973(0.1%) 2/2(100%)
Mono Red Aggro Unknown 1621/2973(54.5%) 1621/1621(100%) 9/2973(0.3%) 9/34(26.5%)
5 Color Gyruda 5 Color Gyruda 31/2973(1%) 31/38(81.6%) 31/2973(1%) 31/38(81.6%)
Gruul Goblins Gruul Goblins 4/2973(0.1%) 4/4(100%) 4/2973(0.1%) 4/4(100%)
Quintorius Combo Quintorius Combo 11/2973(0.4%) 11/13(84.6%) 11/2973(0.4%) 11/13(84.6%)
Boros Nalaar Boros Nalaar 5/2973(0.2%) 5/5(100%) 5/2973(0.2%) 5/5(100%)
Rakdos Tree Combo Rakdos Tree Combo 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Rakdos Creativity Rakdos Creativity 2/2973(0.1%) 2/2(100%) 2/2973(0.1%) 2/2(100%)
Gruul Bard Class Gruul Bard Class 20/2973(0.7%) 20/20(100%) 20/2973(0.7%) 20/20(100%)
Boros Cycling Boros Cycling 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Mono Red Goblins Mono Red Goblins 5/2973(0.2%) 5/5(100%) 5/2973(0.2%) 5/5(100%)
Jund Aggro Jund Aggro 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
5 Color Creativity 5 Color Creativity 7/2973(0.2%) 7/7(100%) 7/2973(0.2%) 7/7(100%)
Gruul Stompy Gruul Stompy 4/2973(0.1%) 4/4(100%) 4/2973(0.1%) 4/4(100%)
Mono Red Midrange Mono Red Midrange 3/2973(0.1%) 3/3(100%) 3/2973(0.1%) 3/3(100%)
Boros Creativity Boros Creativity 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Gruul aggro Gruul aggro 4/2973(0.1%) 4/4(100%) 4/2973(0.1%) 4/4(100%)
Boros Midrange Boros Midrange 24/2973(0.8%) 24/29(82.8%) 24/2973(0.8%) 24/29(82.8%)
Boros Heroic Boros Heroic 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
WURG Stompy WURG Stompy 2/2973(0.1%) 2/3(66.7%) 2/2973(0.1%) 2/3(66.7%)
Izzet Prowess Izzet Prowess 2/2973(0.1%) 2/2(100%) 2/2973(0.1%) 2/2(100%)
Fires of Invention Fires of Invention 2/2973(0.1%) 2/4(50%) 2/2973(0.1%) 2/4(50%)
Izzet Aggro Izzet Aggro 19/2973(0.6%) 19/20(95%) 19/2973(0.6%) 19/20(95%)
Rakdos Midrange Rakdos Midrange 2/2973(0.1%) 2/69(2.9%) 2/2973(0.1%) 2/69(2.9%)
Temur Merfolk Temur Merfolk 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Jeskai Creativity Jeskai Creativity 15/2973(0.5%) 15/15(100%) 15/2973(0.5%) 15/15(100%)
Temur Stompy Temur Stompy 1/2973(0%) 1/2(50%) 1/2973(0%) 1/2(50%)
Mono Red Lutri Mono Red Lutri 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Naya Creativity Naya Creativity 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
WURG Creativity WURG Creativity 8/2973(0.3%) 8/8(100%) 8/2973(0.3%) 8/8(100%)
Izzet Control Izzet Control 5/2973(0.2%) 5/32(15.6%) 5/2973(0.2%) 5/32(15.6%)
Mono Red Creativity Mono Red Creativity 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Herald Combo Herald Combo 1/2973(0%) 1/3(33.3%) 1/2973(0%) 1/3(33.3%)
Selesnya Hardened Scales Selesnya Hardened Scales 1/2973(0%) 1/3(33.3%) 1/2973(0%) 1/3(33.3%)
Azorius Soldiers Azorius Soldiers 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
Azorius Artifact Aggro Azorius Artifact Aggro 1/2973(0%) 1/1(100%) 1/2973(0%) 1/1(100%)
B Demon : Demons (n :1702) Rakdos Demons Rakdos Demons 1089/1702(64%) 1089/1089(100%) 1089/1702(64%) 1089/1089(100%)
Black Demons Black Demons 423/1702(24.9%) 423/423(100%) 423/1702(24.9%) 423/423(100%)
Rakdos Transmogrify Rakdos Transmogrify 9/1702(0.5%) 9/10(90%) 9/1702(0.5%) 9/10(90%)
Rakdos Midrange Rakdos Midrange 67/1702(3.9%) 67/69(97.1%) 67/1702(3.9%) 67/69(97.1%)
Waste Not Waste Not 14/1702(0.8%) 14/14(100%) 14/1702(0.8%) 14/14(100%)
Mono Black Midrange Mono Black Midrange 51/1702(3%) 51/51(100%) 51/1702(3%) 51/51(100%)
Dimir Midrange Dimir Midrange 20/1702(1.2%) 20/34(58.8%) 20/1702(1.2%) 20/34(58.8%)
Orzhov Midrange Orzhov Midrange 12/1702(0.7%) 12/32(37.5%) 12/1702(0.7%) 12/32(37.5%)
Golgari Midrange Golgari Midrange 1/1702(0.1%) 1/5(20%) 1/1702(0.1%) 1/5(20%)
Grixis Demons Grixis Demons 1/1702(0.1%) 1/1(100%) 1/1702(0.1%) 1/1(100%)
Esper Midrange Esper Midrange 11/1702(0.6%) 11/17(64.7%) 11/1702(0.6%) 11/17(64.7%)
Herald Combo Herald Combo 2/1702(0.1%) 2/3(66.7%) 2/1702(0.1%) 2/3(66.7%)
WUBR Midrange WUBR Midrange 1/1702(0.1%) 1/1(100%) 1/1702(0.1%) 1/1(100%)
Dimir Control Dimir Control 1/1702(0.1%) 1/28(3.6%) 1/1702(0.1%) 1/28(3.6%)
Phoenix (n :835) Phoenix Phoenix 818/835(98%) 818/818(100%) 817/835(97.8%) 817/817(100%)
Ascendancy Ascendancy 1/835(0.1%) 1/3(33.3%) 1/835(0.1%) 1/3(33.3%)
Phoenix Unknown 818/835(98%) 818/818(100%) 1/835(0.1%) 1/34(2.9%)
Izzet Control Izzet Control 15/835(1.8%) 15/32(46.9%) 15/835(1.8%) 15/32(46.9%)
Izzet Aggro Izzet Aggro 1/835(0.1%) 1/20(5%) 1/835(0.1%) 1/20(5%)
Control (n :389) Azorius Control Azorius Control 371/389(95.4%) 371/371(100%) 371/389(95.4%) 371/371(100%)
Esper Control Esper Control 5/389(1.3%) 5/5(100%) 5/389(1.3%) 5/5(100%)
Simic Control Simic Control 1/389(0.3%) 1/1(100%) 1/389(0.3%) 1/1(100%)
Bant Control Bant Control 4/389(1%) 4/4(100%) 4/389(1%) 4/4(100%)
Jeskai Control Jeskai Control 6/389(1.5%) 6/7(85.7%) 6/389(1.5%) 6/7(85.7%)
Azorius Lotus Control Azorius Lotus Control 1/389(0.3%) 1/1(100%) 1/389(0.3%) 1/1(100%)
Azorius Lutri Azorius Lutri 1/389(0.3%) 1/1(100%) 1/389(0.3%) 1/1(100%)
Greasefang (n :350) Mardu Greasefang Mardu Greasefang 147/350(42%) 147/147(100%) 147/350(42%) 147/147(100%)
Esper Greasefang Esper Greasefang 17/350(4.9%) 17/17(100%) 17/350(4.9%) 17/17(100%)
Abzan Greasefang Abzan Greasefang 68/350(19.4%) 68/68(100%) 68/350(19.4%) 68/68(100%)
WBRG Greasefang WBRG Greasefang 1/350(0.3%) 1/1(100%) 1/350(0.3%) 1/1(100%)
Boros Midrange Boros Midrange 5/350(1.4%) 5/29(17.2%) 5/350(1.4%) 5/29(17.2%)
Orzhov Greasefang Orzhov Greasefang 109/350(31.1%) 109/109(100%) 109/350(31.1%) 109/109(100%)
Greasefang Unknown 1/350(0.3%) 1/1(100%) 1/350(0.3%) 1/34(2.9%)
Abzan Midrange Abzan Midrange 1/350(0.3%) 1/6(16.7%) 1/350(0.3%) 1/6(16.7%)
Orzhov Midrange Orzhov Midrange 1/350(0.3%) 1/32(3.1%) 1/350(0.3%) 1/32(3.1%)
Self Bounce (n :319) Dimir Self Bounce Dimir Self Bounce 233/319(73%) 233/233(100%) 233/319(73%) 233/233(100%)
Esper Self Bounce Esper Self Bounce 71/319(22.3%) 71/71(100%) 71/319(22.3%) 71/71(100%)
Grixis Self Bounce Grixis Self Bounce 4/319(1.3%) 4/4(100%) 4/319(1.3%) 4/4(100%)
Dimir Control Dimir Control 2/319(0.6%) 2/28(7.1%) 2/319(0.6%) 2/28(7.1%)
Orzhov Self Bounce Orzhov Self Bounce 6/319(1.9%) 6/6(100%) 6/319(1.9%) 6/6(100%)
Mono Black Self Bounce Mono Black Self Bounce 1/319(0.3%) 1/1(100%) 1/319(0.3%) 1/1(100%)
Mardu Self Bounce Mardu Self Bounce 1/319(0.3%) 1/1(100%) 1/319(0.3%) 1/1(100%)
Orzhov Aggro Orzhov Aggro 1/319(0.3%) 1/1(100%) 1/319(0.3%) 1/1(100%)
Sacrifice (n :254) Jund Sacrifice Jund Sacrifice 243/254(95.7%) 243/243(100%) 243/254(95.7%) 243/243(100%)
Rakdos Sacrifice Rakdos Sacrifice 11/254(4.3%) 11/11(100%) 11/254(4.3%) 11/11(100%)
Angels (n :246) Selesnya Stompy Selesnya Stompy 3/246(1.2%) 3/28(10.7%) 3/246(1.2%) 3/28(10.7%)
Selesnya Angels Selesnya Angels 241/246(98%) 241/242(99.6%) 241/246(98%) 241/242(99.6%)
WUBG Angels WUBG Angels 1/246(0.4%) 1/1(100%) 1/246(0.4%) 1/1(100%)
Lotus Strings (n :239) Lotus Strings Lotus Strings 239/239(100%) 239/239(100%) 239/239(100%) 239/239(100%)
Mono Green Devotion (n :234) Mono Green Devotion Mono Green Devotion 230/234(98.3%) 230/230(100%) 230/234(98.3%) 230/230(100%)
Mono Green Stompy Mono Green Stompy 3/234(1.3%) 3/4(75%) 3/234(1.3%) 3/4(75%)
Selesnya Big Mana Selesnya Big Mana 1/234(0.4%) 1/1(100%) 1/234(0.4%) 1/1(100%)
Ninjas (n :220) Dimir Ninjas Dimir Ninjas 212/220(96.4%) 212/212(100%) 212/220(96.4%) 212/212(100%)
Dimir Midrange Dimir Midrange 1/220(0.5%) 1/34(2.9%) 1/220(0.5%) 1/34(2.9%)
Esper Midrange Esper Midrange 6/220(2.7%) 6/17(35.3%) 6/220(2.7%) 6/17(35.3%)
Azorius Ninjas Azorius Ninjas 1/220(0.5%) 1/1(100%) 1/220(0.5%) 1/1(100%)
GW Company (n :202) Selesnya Company Selesnya Company 163/202(80.7%) 163/163(100%) 163/202(80.7%) 163/163(100%)
Azorius Midrange Azorius Midrange 1/202(0.5%) 1/1(100%) 1/202(0.5%) 1/1(100%)
Selesnya Stompy Selesnya Stompy 25/202(12.4%) 25/28(89.3%) 25/202(12.4%) 25/28(89.3%)
Selesnya Coco Toolbox Selesnya Coco Toolbox 5/202(2.5%) 5/5(100%) 5/202(2.5%) 5/5(100%)
Bant Stompy Bant Stompy 5/202(2.5%) 5/5(100%) 5/202(2.5%) 5/5(100%)
GW Company Unknown 3/202(1.5%) 3/3(100%) 3/202(1.5%) 3/34(8.8%)
Enigmatic Incarnation (n :200) Zur enchantement Zur enchantement 36/200(18%) 36/37(97.3%) 36/200(18%) 36/37(97.3%)
Enigmatic Incarnation Enigmatic Incarnation 164/200(82%) 164/164(100%) 164/200(82%) 164/164(100%)
Bring To Light : Niv To Light (n :157) Niv To Light Niv To Light 156/157(99.4%) 156/156(100%) 156/157(99.4%) 156/156(100%)
Zur enchantement Zur enchantement 1/157(0.6%) 1/37(2.7%) 1/157(0.6%) 1/37(2.7%)
Spirits (n :153) Spirits Spirits 153/153(100%) 153/153(100%) 153/153(100%) 153/153(100%)
Tokens (n :141) Esper Token Control Esper Token Control 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
Boros Token Control Boros Token Control 5/141(3.5%) 5/5(100%) 5/141(3.5%) 5/5(100%)
Mono White Token Control Mono White Token Control 126/141(89.4%) 126/126(100%) 126/141(89.4%) 126/126(100%)
Mono White Book Midrange Mono White Book Midrange 4/141(2.8%) 4/4(100%) 4/141(2.8%) 4/4(100%)
Mono White Midrange Mono White Midrange 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
Boros Book Midrange Boros Book Midrange 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
Orzhov Token Control Orzhov Token Control 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
WUBR Transmogrify WUBR Transmogrify 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
Mardu Transmogrify Mardu Transmogrify 1/141(0.7%) 1/1(100%) 1/141(0.7%) 1/1(100%)
Humans (n :133) Azorius Humans Azorius Humans 44/133(33.1%) 44/44(100%) 44/133(33.1%) 44/44(100%)
Mono White Humans Mono White Humans 70/133(52.6%) 70/70(100%) 70/133(52.6%) 70/70(100%)
Orzhov Humans Pyre Orzhov Humans Pyre 1/133(0.8%) 1/1(100%) 1/133(0.8%) 1/1(100%)
Selesnya Humans Selesnya Humans 1/133(0.8%) 1/1(100%) 1/133(0.8%) 1/1(100%)
Esper Humans Esper Humans 2/133(1.5%) 2/2(100%) 2/133(1.5%) 2/2(100%)
Bant Humans Bant Humans 3/133(2.3%) 3/3(100%) 3/133(2.3%) 3/3(100%)
Orzhov Humans Orzhov Humans 3/133(2.3%) 3/3(100%) 3/133(2.3%) 3/3(100%)
Mardu Humans Mardu Humans 7/133(5.3%) 7/7(100%) 7/133(5.3%) 7/7(100%)
Boros Humans Boros Humans 1/133(0.8%) 1/1(100%) 1/133(0.8%) 1/1(100%)
Abzan Humans Abzan Humans 1/133(0.8%) 1/1(100%) 1/133(0.8%) 1/1(100%)
Ensoul (n :104) Izzet Ensoul Izzet Ensoul 77/104(74%) 77/77(100%) 77/104(74%) 77/77(100%)
Jeskai Ensoul Jeskai Ensoul 4/104(3.8%) 4/4(100%) 4/104(3.8%) 4/4(100%)
Ensoul Unknown 2/104(1.9%) 2/2(100%) 2/104(1.9%) 2/34(5.9%)
Azorius Ensoul Azorius Ensoul 21/104(20.2%) 21/21(100%) 21/104(20.2%) 21/21(100%)
Food (n :98) Golgari Food Golgari Food 93/98(94.9%) 93/93(100%) 93/98(94.9%) 93/93(100%)
Golgari Midrange Golgari Midrange 4/98(4.1%) 4/5(80%) 4/98(4.1%) 4/5(80%)
Jund Food Jund Food 1/98(1%) 1/1(100%) 1/98(1%) 1/1(100%)
Hammer Time (n :88) Boros Hammer Time Boros Hammer Time 74/88(84.1%) 74/74(100%) 74/88(84.1%) 74/74(100%)
Naya Hammer Time Naya Hammer Time 1/88(1.1%) 1/1(100%) 1/88(1.1%) 1/1(100%)
Boros Artifact Aggro Boros Artifact Aggro 8/88(9.1%) 8/8(100%) 8/88(9.1%) 8/8(100%)
Abzan Hammer Time Abzan Hammer Time 1/88(1.1%) 1/1(100%) 1/88(1.1%) 1/1(100%)
Selesnya Hammer Time Selesnya Hammer Time 2/88(2.3%) 2/2(100%) 2/88(2.3%) 2/2(100%)
Mono White Hammer Time Mono White Hammer Time 2/88(2.3%) 2/2(100%) 2/88(2.3%) 2/2(100%)
Scapeshift (n :84) Golgari Scapeshift Golgari Scapeshift 1/84(1.2%) 1/1(100%) 1/84(1.2%) 1/1(100%)
Land Combo Land Combo 13/84(15.5%) 13/14(92.9%) 13/84(15.5%) 13/14(92.9%)
Sultai Scapeshift Sultai Scapeshift 18/84(21.4%) 18/18(100%) 18/84(21.4%) 18/18(100%)
Simic Scapeshift Simic Scapeshift 44/84(52.4%) 44/44(100%) 44/84(52.4%) 44/44(100%)
Scapeshift Unknown 8/84(9.5%) 8/8(100%) 8/84(9.5%) 8/34(23.5%)
Rona (n :65) Jeskai Rona Ascendancy Jeskai Rona Ascendancy 1/65(1.5%) 1/1(100%) 1/65(1.5%) 1/1(100%)
Sultai Rona Combo Sultai Rona Combo 4/65(6.2%) 4/4(100%) 4/65(6.2%) 4/4(100%)
Mono Blue Rona Combo Mono Blue Rona Combo 47/65(72.3%) 47/47(100%) 47/65(72.3%) 47/47(100%)
Simic Rona Combo Simic Rona Combo 1/65(1.5%) 1/1(100%) 1/65(1.5%) 1/1(100%)
Izzet Rona Combo Izzet Rona Combo 12/65(18.5%) 12/12(100%) 12/65(18.5%) 12/12(100%)
Auras (n :51) Selesnya Auras Selesnya Auras 21/51(41.2%) 21/21(100%) 21/51(41.2%) 21/21(100%)
Bant Auras Bant Auras 29/51(56.9%) 29/29(100%) 29/51(56.9%) 29/29(100%)
Esper Auras Esper Auras 1/51(2%) 1/1(100%) 1/51(2%) 1/1(100%)
Dimir Control (n :38) Dimir Control Dimir Control 25/38(65.8%) 25/28(89.3%) 25/38(65.8%) 25/28(89.3%)
Dimir Midrange Dimir Midrange 13/38(34.2%) 13/34(38.2%) 13/38(34.2%) 13/34(38.2%)
Neoform Combo (n :32) Simic Neoform Combo Simic Neoform Combo 28/32(87.5%) 28/28(100%) 28/32(87.5%) 28/28(100%)
Bant Neoform Combo Bant Neoform Combo 1/32(3.1%) 1/1(100%) 1/32(3.1%) 1/1(100%)
Sultai Neoform Combo Sultai Neoform Combo 3/32(9.4%) 3/3(100%) 3/32(9.4%) 3/3(100%)
Orzhov Midrange (n :26) Orzhov Midrange Orzhov Midrange 18/26(69.2%) 18/32(56.2%) 18/26(69.2%) 18/32(56.2%)
Abzan Midrange Abzan Midrange 5/26(19.2%) 5/6(83.3%) 5/26(19.2%) 5/6(83.3%)
Mono Black Aggro Mono Black Aggro 1/26(3.8%) 1/1(100%) 1/26(3.8%) 1/1(100%)
Mardu Aggro Mardu Aggro 1/26(3.8%) 1/9(11.1%) 1/26(3.8%) 1/9(11.1%)
Merfolk (n :20) Simic Merfolk Simic Merfolk 20/20(100%) 20/20(100%) 20/20(100%) 20/20(100%)
Roots (n :18) Golgari Roots Golgari Roots 18/18(100%) 18/18(100%) 18/18(100%) 18/18(100%)
Izzet Control (n :12) Izzet Control Izzet Control 12/12(100%) 12/32(37.5%) 12/12(100%) 12/32(37.5%)
Unknown (n :10) Unknown Unknown 10/10(100%) 10/10(100%) 10/10(100%) 10/34(29.4%)
Gyruda (n :8) 5 Color Gyruda 5 Color Gyruda 7/8(87.5%) 7/38(18.4%) 7/8(87.5%) 7/38(18.4%)
WUBR Gyruda WUBR Gyruda 1/8(12.5%) 1/1(100%) 1/8(12.5%) 1/1(100%)
Rona : Acererak Combo (n :6) Acererak Combo Acererak Combo 6/6(100%) 6/6(100%) 6/6(100%) 6/6(100%)
Soulflayer (n :6) Sultai Soulflayer Sultai Soulflayer 4/6(66.7%) 4/4(100%) 4/6(66.7%) 4/4(100%)
Golgari Soulflayer Golgari Soulflayer 1/6(16.7%) 1/1(100%) 1/6(16.7%) 1/1(100%)
WUBG Soulflayer WUBG Soulflayer 1/6(16.7%) 1/1(100%) 1/6(16.7%) 1/1(100%)
Rogues (n :5) Dimir Rogues Dimir Rogues 5/5(100%) 5/5(100%) 5/5(100%) 5/5(100%)
Simic Big Mana (n :3) Simic Big Mana Simic Big Mana 3/3(100%) 3/3(100%) 3/3(100%) 3/3(100%)
Esper Midrange (n :3) Esper Aggro Esper Aggro 3/3(100%) 3/3(100%) 3/3(100%) 3/3(100%)
Sultai Midrange (n :3) Sultai Midrange Sultai Midrange 3/3(100%) 3/3(100%) 3/3(100%) 3/3(100%)
Ascendancy (n :2) Ascendancy Ascendancy 2/2(100%) 2/3(66.7%) 2/2(100%) 2/3(66.7%)
Fires Of Invention (n :2) Fires of Invention Fires of Invention 2/2(100%) 2/4(50%) 2/2(100%) 2/4(50%)
Lutri (n :2) Sultai Lutri Sultai Lutri 2/2(100%) 2/2(100%) 2/2(100%) 2/2(100%)
Hardened Scales (n :2) Selesnya Hardened Scales Selesnya Hardened Scales 2/2(100%) 2/3(66.7%) 2/2(100%) 2/3(66.7%)
Metalwork (n :2) Azorius Metalwork Combo Azorius Metalwork Combo 2/2(100%) 2/11(18.2%) 2/2(100%) 2/11(18.2%)
Discover combo : Quintorius Combo (n :2) Quintorius Combo Quintorius Combo 2/2(100%) 2/13(15.4%) 2/2(100%) 2/13(15.4%)
Sultai Stompy (n :1) Sultai Stompy Sultai Stompy 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Transmogrify (n :1) Rakdos Transmogrify Rakdos Transmogrify 1/1(100%) 1/10(10%) 1/1(100%) 1/10(10%)
Golgari Midrange (n :1) Golgari Stompy Golgari Stompy 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Dwarves (n :1) Boros Dwarves Boros Dwarves 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Jeskai Control (n :1) Jeskai Control Jeskai Control 1/1(100%) 1/7(14.3%) 1/1(100%) 1/7(14.3%)
B Demon (n :1) Orzhov Control Orzhov Control 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Mardu Midrange (n :1) Mardu Midrange Mardu Midrange 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Jund Midrange (n :1) Jund Midrange Jund Midrange 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
WURG Big Mana (n :1) WURG Big Mana WURG Big Mana 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Bant Stompy (n :1) WURG Stompy WURG Stompy 1/1(100%) 1/3(33.3%) 1/1(100%) 1/3(33.3%)
Temur Stompy (n :1) Temur Stompy Temur Stompy 1/1(100%) 1/2(50%) 1/1(100%) 1/2(50%)
Toxic (n :1) Selesnya Toxic Selesnya Toxic 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Rally (n :1) Abzan Rally Abzan Rally 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Mono Green Stompy (n :1) Mono Green Stompy Mono Green Stompy 1/1(100%) 1/4(25%) 1/1(100%) 1/4(25%)
Land Combo (n :1) Land Combo Land Combo 1/1(100%) 1/14(7.1%) 1/1(100%) 1/14(7.1%)
Abzan Stompy (n :1) Abzan Stompy Abzan Stompy 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Multiverse combo (n :1) Multiverse combo Multiverse combo 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Izzet Midrange (n :1) Izzet Midrange Izzet Midrange 1/1(100%) 1/1(100%) 1/1(100%) 1/1(100%)
Invalid deck (< 60 cards) Tabler summarise how the archetypes are aggregated
Parser
Custom
Reference
Custom Reference Percent Archetype Percent Sub Archetype Percent Archetype Percent Sub Archetype
Angels (n :246) Selesnya Angels Selesnya Angels 1/246(0.4%) 1/242(0.4%) 1/246(0.4%) 1/242(0.4%)
Orzhov Midrange (n :26) Orzhov Midrange Orzhov Midrange 1/26(3.8%) 1/32(3.1%) 1/26(3.8%) 1/32(3.1%)

4.2 Proximity aggregation

If the median jaccard distance between 2 archetypes is smaller than the 3 quartiles of the internal distance within the archetype, these 2 archetypes will be grouped together. The table below shows the grouped archetypes:

Proximity aggregation
Total archetype name Base archetype name group
B Demon Orzhov Control
B Demon : Demons B Demon
B Demon : Demons Rakdos Midrange
Bant Stompy WURG Stompy
Dimir Control Dimir Midrange
Esper Midrange Esper Aggro
Food Golgari Midrange
GW Company Bant Stompy
GW Company Selesnya Stompy
Golgari Midrange Golgari Stompy
Mono Red Aggro Bard Class
Mono Red Aggro Creativity
Mono Red Aggro Gruul Aggro
Mono Red Aggro Gruul Stompy
Mono Red Aggro Rakdos Aggro
Ninjas Esper Midrange
Orzhov Midrange Abzan Midrange
Orzhov Midrange Bx Aggro
Tokens Book Combo