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Metalodon
Method

How the numbers are made

Metalodon turns public tournament results into a meta report that shows how sure it is. Each number comes with its likely range, and anything resting on too few games is faded or hatched instead of ranked. The plain explanations come first; the precise methods are in the technical details at the end.

Data through Nov 9, 2026 · 710 tournaments · 58,732 entries · 4,779 players · 154,309 games since Jun 4 · updated Nov 10, 07:00 UTC

01Where the data comes from

Results, standings, pairings and decklists come from Limitless TCG, which hosts most online Pokémon TCG Pocket tournaments. Unfinished events are re-checked until they settle. By default the site uses:

  • Eventsfinished, 16+ players, with decklists
  • Formatstandard (no custom ban list)
  • Windowthe last 120 days
  • Gamesa win counts 1, a tie ½; byes, forfeits and double losses are not games

Win rates leave out mirror matches. A deck wins exactly half of them, which would pull every popular deck toward 50%; shares still count every entry. The filters pick one of 12 views (window, all games or top cut), each worked out ahead at every data refresh. Every view counts events of 16 or more players, the one event size the site uses. A view with under 10 events or under 2,000 entries says “Small sample”, and its numbers move a lot; in a top-cut view only the entries that made the cut count.

The window can also start at one of the two latest set releases (Since Dual Fusion (C1), out Oct 29, 2026; Since Deluxe Pack: Mega (B4b), out Sep 30, 2026). It then holds only the games from the day that set came out, all games or top cut. In its first 10 days such a window is too short for trends, so they read “Too new for a trend”, and it has no Rising flags (they compare the last 7 days with the last 28).

02Recent results count more

The meta moves every week, so old results fade gradually. Shares and win rates fade at different speeds. A meta share follows the current field, so an entry counts half as much after 7 days. For 14 days after a set comes out, entries from before the release count 0.3× as much again, because decks change fastest in those days. A card’s play rate and a deck’s core, flex and tech cards count lists the same way, so they follow the same field. Win rates and matchups keep a longer memory and rest on more games. A game counts half as much after 28 days.

0½fulltoday30d ago60d ago90d ago120d agohalves every 28devery 7d
win rates and matchups (halves every 28 days) meta share, play rates and trends (halves every 7 days)How much a result counts by its age. Results older than 120 days are not used.

The share’s weights were picked by predicting the next week’s field from the weeks before at 62 past dates, four after each of 11 set releases and 18 away from any release. A share counting half after 28 days was the worst predictor in every group; four days after a release only about 15% of its weight came from games since the release. The current rule did better at 61 of the 62 dates.

How well each share predicted the next week’s field (log loss per entry, lower is better)
WhenHalf after 28 daysCurrent rule
2 days after a release (11 releases)5.4444.719
4 days after (11 releases)4.9004.426
7 days after (11 releases)4.6874.366
10 days after (11 releases)4.5074.262
Weeks away from a release (18 weeks)5.0554.951

The trend arrows compare this week with the last 4 weeks (in a 14-day view, with the whole 14 days). A win rate compares its last 7 days with its last 28. A meta share and a card’s play rate already count the last week most, so their trends compare the number shown with the last 4 weeks. Shares trend in percent of themselves (2% to 3% is +50%); play rates and win rates trend in points (2% to 3% is +1pp). A deck’s Share trend shows its 4-week share with its own range. In the 14 days after a set release the meta share and play rates count older games less, and their trends use those same numbers.

A change is shown only when it is bigger than the noise; otherwise the trend reads Steady, with the measured change in its tooltip. A win rate whose last 7 days are worth under 20 games once older ones are discounted reads Too few recent games, because a deck played mostly weeks ago can swing 30 points on two recent games.

The Overview's “Meta over time” stacks the most played decks' shares day by day over the last 8 weeks, each as its deck page showed it on that day. Every other deck forms one hatched band on top, so each day adds up to 100%. The charts on deck and card pages also have a point per day, each the number the page showed on that day. The data tables of charts longer than a month, and the screen-reader table of “Meta over time”, list one day a week, ending with the latest.

+38% clear rise−1.2pp clear fallSteady (+0.9pp, now vs the last 4 weeks, within the noise) within the noiseToo few recent games (measured −37.8pp, 7-day vs 28-day) a win rate, most of its games weeks old

03Ranges and small samples

A win rate from 40 games can easily be 10 points off; from 4,000 games it is rarely more than 2 off. So each number carries its likely range, which holds the true value 9 times out of 10. Fewer games give a wider range, and a result is colored only when its whole range is on one side of 50% (or of zero, for a card’s lift).

Reading a win-rate bar (centered on 50%)
Whole range above 50%: blue
54.3%
4.2k games
Win rate 54.3% · 90% range 53.1–55.5% · 4,210 games
Range includes 50%: gray, too close to call
51.2%
980 games
Win rate 51.2% · 90% range 48.8–53.6% · 980 games
Whole range below 50%: red
46.2%
3.1k games
Win rate 46.2% · 90% range 44.7–47.7% · 3,150 games
Too few games: faded and hatched
58.0%
64 games
Win rate 58.0% · 90% range 47.0–68.0% · 64 games · too few games to call
  • Decksno tier and faded under 300 games, older games counting less
  • Matchupshatched and gray under 20 games, older games counting less
  • Cardsfaded when fewer than 50 decklists run them

Faded and hatched results are there for reference. They are never colored, and sorting by a win rate or an effect puts them after the rest.

04Meta share and win rates

Meta share
A deck’s share of tournament entries, recent weeks counting most and the last week most of all; right after a set comes out, entries from before it count less (see Recent results count more). A deck played mostly in the last few days can therefore rank above one with more entries over the whole window.
Win rate
The share of games a deck won, a tie counting half and mirror matches left out.
Adjusted for skill
A deck can look strong just because strong players pick it. This version compares each game with what the two players’ ratings predicted, so it takes out how much better or worse the deck’s pilots were than the players they faced. When it differs from the plain win rate, the difference comes from the players.
Pilot rating
The average rating of the deck’s players over the games behind its win rate, beside the average rating of the players they faced in those games. “+8 vs their opponents” is the difference between the two, the gap Adjusted for skill takes out.
Vs the meta
A plain win rate depends on who a deck happened to meet. Vs the meta averages the deck’s matchups instead, each counted as often as you would meet that opponent in today’s field (mirrors count as 50%).
Top cuts
How often a deck makes the top cut compared with what its events’ cut sizes predict. 1.0× is as expected; 2.0× is twice as often. Top-cut share is the deck’s share of the entries that made a cut; in a top-cut view it is the meta share itself.

05Tiers and the tier list

Tiers use the range of the win rate vs the meta. A deck is S tier only when even the low end of its range is that good, so a great but uncertain number waits for more games, and a deck with a higher win rate from few games can sit below a steadier one. At the bottom, F marks a deck whose whole range sits under 50%, clearly losing to the field, and D a deck whose low end is too low for C while its range still reaches 50%.

Tier SLow end ≥ 52%Suicune ex BaxcaliburHoopa ex Mega Absol exMagnezone Miraidon ex (B1a/B3a)Mega Altaria ex Espeon (B1/B3a)Vespiquen ex Shuckle ex
Tier ALow end ≥ 50.5%Mega Altaria ex GreninjaMega Sceptile ex GreninjaDedenne ex Indeedee ex
Tier BLow end ≥ 49%Mega Lucario ex Lucario (B3/A2)Mega Manectric ex Heliolisk (B2b/B4)Hydreigon Mega Absol ex
Tier CLow end ≥ 47%Mega Charizard Y ex Entei exGiratina ex DragonairUmbreon Mega Absol exDragonair Mega Rayquaza ex (B4)
Tier DLow end below 47%Umbreon Hydreigon (C1/B1)Mega Mewtwo X ex Mew exLopunny RabootPikachu ex Pawmot (C1)
Tier FTop end below 50%Mega Greninja ex Greninja exMega Greninja ex Suicune ex
No tier (too few games)No tier: worth under 300 games once older games are discounted, shown faded

Avatars: the most-played decks in each tier right now.

The precise rule. A deck’s tier reads the 90% range of its win rate vs the meta, in this order: S, A and B on the low end (S ≥ 52%, A ≥ 50.5%, B ≥ 49%), then F on the top end (F top end below 50%), then C on the low end (C ≥ 47%), and D for every other deck (D below 47%). A deck whose top end is below 50% is F before C or D, since it is clearly losing to the field. Both ends are compared as the site shows them, to one decimal (a low end shown as 49.0% is tier B; a top end shown as 50.0% is never F). The tier comes from Vs the meta, so a deck with a higher plain win rate can sit in a lower tier. Only a deck whose games are worth at least 300 once older games are discounted gets a tier. Within a tier, decks are ordered by the low end, highest first, as in the Decks table’s Tier column and on the tier list. Each meta view (the window, all games or top cuts only) has its own tiers, recomputed with every data refresh.

The tier list shows every deck with a tier, S to F, with its win rate vs the meta and its meta share; decks too new or too rarely played to rank are on the Decks page, faded.

06Matchups

Each matchup is one number, the games the two decks played blended with what their usual decklists predict (a model that reads the cards and types of both lists). The prediction also learns from games at past events with ban lists, NOEX and other formats, and gives each deck a small correction from how it has done. With few games the number leans on the prediction; as games add up it follows the games. The same number appears on the deck page, the “how to beat” page and the matrix, with the record behind it as wins–losses(–ties) in the window, and the two sides add up (if A beats B 60% of the time, B beats A 40%). When no prediction model is available, the prediction is each deck's results against other decks instead.

Most of the 1,446 decks in the data are one-off brews, so most pairs have few games. A matchup worth under 20 games once older games are discounted is hatched and gray; its record can show more games than that.

The Overview's “Top Metagame Matchups” draws the same numbers for the 10 most played decks (8 on phones), each circle sized by its meta share. A solid arrow points from a deck to one it beats when that matchup's whole range is above 50% and the two decks have enough recent games; it is brighter the further the range clears 50% and thicker the bigger the margin. Every deck drawn gets at least 2 arrows. A deck with fewer solid ones gets dashed arrows from its other matchups where one side wins at least 55% and is at least 80% sure to be ahead (the 90% range read as a normal curve), few recent games allowed, the surest first, until it has 2. A deck still short of 2 is left out with its arrows, and the rule runs again on the decks left. No arrow means too close to call or too few games.

07Decks and cards

Decks are the deck types Limitless assigns to each list, with reprints merged, so the same deck built from different printings counts once. Limitless names a deck after two of its Pokémon, so one deck can carry several names; names that cover the same deck are joined. A build around a different version of a Pokémon stays its own deck.

Cards are identified by what they do. Reprints and alternate arts share one page, named after the earliest printing.

  • Copycat B1 225B1 225
  • Copycat B1 270B1 270
  • Copycat B4b 225B4b 225
  • Copycat B4b 391B4b 391
  • Copycat B4b 424B4b 424
5 printings, one card: Copycat.

Two cards with the same name but different attacks or abilities stay separate, like the two Dustox (B1) and Dustox (B4) cards. Card names anywhere on the site show the card on hover or tap.

08What a deck runs

Each deck page sorts a typical list into three groups, Core, Flex and Tech, and flags the staples:

Core
Cards in 9 of every 10 lists of the deck or more. They make it this deck.
Flex
One spot in the deck that different cards of the same name can fill, like two printings of a Basic or the four Furfrou. Lists pick one or mix them, and each option shows its share of the lists.
Tech
Optional cards, in from 1 in 20 to 9 in 10 of the deck’s lists.
Staple
A flag on a card most decks play (Professor’s Research, Poké Ball, Copycat, Cyrus). A staple can also be core.

The shares count recent lists most, the last week most of all, like the meta share. A deck with many lists in the window and few in recent weeks gets a note that its groups are a rough guide, and a version with too few recent lists cannot be told apart from the rest of the deck.

Since one deck can carry several Limitless names, Versions of this deck lists each name with its share of the deck, its win rate adjusted for skill and the cards that set it apart.

09Play rate and lift

Play rate
The share of decklists that run at least one copy, weighted like the meta share. The last week counts most, and for 14 days after a set comes out lists from before it count less. Copies is the average count in those lists. The trend compares the play rate shown with the last 4 weeks.
Win rate with it
The win rate of decks running the card. It mostly reflects which decks play it, so it is never colored. Over all decks it is counted in player-games: a game where both players run the card counts twice.
Lift
How many points a deck’s win rate against the meta changes when its lists run the card versus when they don’t, with its other cards and the players’ skill held equal. A 2nd copy lift compares two copies with one. A card in almost every list, in very few lists, or in a deck with too few games has no lift, and the page says which.
Lift across decks
The card’s lift averaged over the decks that play it, each deck counted by its games with the card. It needs three or more decks.
Cards that win more
The Overview’s cards whose lift across decks stays above zero over its whole range, ranked by the low end of that range, so a big number from few games ranks below a surer one.
On the rise
The Overview’s cards whose play rate grew by more than the noise against the last 4 weeks, biggest gain in points first, each with the deck that plays it most. Both lists leave out cards in fewer than 50 lists.
Reading a lift bar (centered on 0)
Whole range above zero: colored
+4.1pp+4.1pp · 90% range +1.2pp to +7.0pp · 820 games
Range includes zero: gray, could be noise
+1.8pp+1.8pp · 90% range −2.4pp to +6.0pp · 410 games · could be zero

A lift shows how decks with a card did; it does not prove the card caused it. A card that strong players happen to favor can still look a couple of points better than it is.

10Cards against a deck

On the beat-a-deck page, each card’s number says how much running it helps against that deck. Each deck that plays the card into the matchup gives its own number (its lists with the card against its lists without it, other cards and player skill held equal), and the page shows the average over every such deck, counting each deck by its games with the card. Open a card to see each deck’s own number; the head-to-head page shows them for both sides of one matchup.

Cards are ranked by the low end of their range, because a big number from a few games (often a rarely played card) has a wide range and usually shrinks as new games come in. Two tags appear only when the whole range is above zero: Swings a losing matchup (most of its games against the deck come from decks whose matchup is below 50%) and Underused (fewer than one list in four runs it).

11New, Breakout and Rising

A deck carries one tag at a time: Breakout, else Rising, else New. New and Breakout are worked out at every data refresh on the default view’s events and read the same in every view; Rising belongs to the view.

  • New: first seen in the last 14 days, however few players run it
  • Breakout: first seen on or after the latest set’s release (C1, out Oct 29, 2026), with a card of that set in 50%+ of its lists since then and 6%+ of the entries since the release (the share its “Since” view shows), in 2+ events with 5+ different pilots. It shows from 48 hours after the release until 14 days after it, checked again at every refresh

Breakout is experimental. Its rule was picked on a replay of 11 past releases, where a meta deck is one holding 3%+ of the entries 3 to 6 weeks after the release. Tagged 48 hours in, 12 of 16 decks became meta decks (75%, 90% range 50%–94%); tagged 72 hours in, 15 of 18 (83%, range 64%–95%). The tag finds 15 of the 35 meta decks by 72 hours, and 4.7% of all new decks built on a set became one. While a deck is new to the latest set, its page shows its share since the release where Top cuts usually is, and the Decks page’s top tile goes to a Breakout deck for the first 14 days.

What’s moving puts the decks in four groups, then every other deck: a Breakout deck while the latest set is under 14 days old; a Rising deck; a deck worth 300+ games whose meta share is clearly above its share over the last 4 weeks; a New deck with 0.5%+ of the meta. Breakout and New decks rank by meta share, the other two by how fast their share grows. The Overview shows the first 8, the Decks page’s Trends view opens in this order, and the Decks page’s top tile takes its Breakout or Rising deck from it. For 14 days after a release the Overview names the set and its day, and for 28 days the tier list adds a New this set row: decks first seen since the release with 0.5%+ of the entries since then, too new for a tier.

A deck’s Rising score adds up four signals, each damped when the sample is small so a handful of results cannot carry it:

  • Gaining: its share is growing (this week against the month), with 5+ different pilots in the last 14 days
  • Strong: its win rate adjusted for skill stays above 50% at the low end of its range once a small sample is damped toward the field, so a deck whose range is just above 50% can still miss it
  • Converting: it makes top cut more often than expected, at the low end once damped the same way
  • New: first seen in the last 14 days

Strength and top cuts count only once a deck is gaining or new, so a strong deck with a flat share is not flagged. A deck scoring 5.75+ while under 3% share gets a Rising badge on Decks. The badge is experimental, a hint of what to watch.

Cards are scored the same way inside each deck, from how fast the card turns up in more of the deck’s lists and how often those lists make top cut. A flagged card is marked Rising on the deck page’s card usage, and the Cards page says how many decks it is rising in. The Decks page’s Trends view shows how fast every deck’s share is moving.

See the share trends →

12The deck builder's suggestions

The builder compares your cards with every recent tournament list and leans on the lists most like yours, the closest and newest counting most. A deck that mixes two decks borrows from both, and a deck that matches no known deck still gets what the lists nearest to it run.

It suggests the core cards those lists almost always run first, then flex choices (which Riolu, which Furfrou) and techs. A second card for a spot your deck already fills is offered only when the lists run both. Cards few of those lists run are offered as cuts. When your deck reads as a known deck, the suggestions also carry that deck’s lifts; a rogue deck gets no win-rate claims, because the nearest deck’s numbers are about another deck. “Analyze as” a deck compares yours with that deck’s lists only.

The card search’s Recommended order reads the same lists, so what they run comes first, each card with a short reason. Its Lift switch marks each card with its Lift in the deck your list reads as and a small bar for its range. The number is colored only where the range clears zero. The large card view shows the same Lift, and a second copy’s Lift when the deck has one.

On two weeks of later tournament lists with one to three cards hidden, a hidden card was among the first five suggestions about 95 times in 100 for lists of known decks and 67 in 100 for rogue or rare decks. For a deck made of halves of two decks, cards of both halves came back among the first five about one time in four.

13Opening-hand odds

The builder’s Insights tab shows each card’s chance to be in your hand at the start, worked out exactly for the deck on screen from one simple rule for the deal. One Basic Pokémon card is picked at random from all the deck’s Basic copies, and 4 more cards come from the other 19. Both players then draw a card at the start of their first turn. Fossils are Items, so they don’t count as Basics here.

Can start with it
A Basic’s chance to be among those 5 cards, either as the Basic picked (as often as its share of your Basic copies) or among the other 4.
Must start with it
A Basic’s chance to be the only Basic in those 5 cards, so it has to be your Active Pokémon. A deck’s only Basic always starts.
Turn-1
Every card’s chance of holding at least one copy at the start of your first turn, after its draw. For a card that isn’t a Basic it is 26.3% with one copy and 46.8% with two, in every deck.

The odds show once the deck is legal: 20 cards and no rule broken. The formulas are in the technical details.

14Players and ratings

Rating
Each player’s skill, from their results against the players they met, with the strength of the decks they played taken out. 1500 is an average player. Its range holds the true rating 9 times out of 10; it is wide with few games and grows with time off.
The leaderboard
Players with at least 10 events, one of them in the last 30 days, ordered by their rating minus twice its uncertainty, so a high rating from few games ranks below a slightly lower one we are surer of. Every rating shows its range.
Win rate
The share of a player’s games won in Standard events over the last 120 days, recent weeks counting most and a tie counting half. Byes, forfeits and double losses never count, so a player page’s records come from the pairings rather than the event’s standings.
Team events
Every member carries the team’s placement and record, so team events are left out of a player’s event count, win rate and most played decks. Their games still count toward the rating and its number of games.

Players are their Limitless usernames; the name shown is the latest one they used, and search finds every name. A player can ask to be left out. Their page and name are then removed, while their games still count in every deck statistic.

15Following and what changed

Signed in, you can follow decks, cards and players. “Since your last visit” lists what changed for them since you last opened that list, going back at most 30 days. Players’ new events come first, then the biggest changes: a rating, meta share, win rate against the meta or play rate that moved by more than its noise (the two ranges barely overlap), a new tier, a deck turning Rising, a card’s lift across decks starting or ceasing to clear zero, and a player entering or leaving the top 100. Each change compares the numbers the site showed then with today’s.

16Coming with Premium

A paid plan is on its way for tools that plan and compute for you. Everything on the pages you can read today stays free. Pages marked Premium, coming soon describe what a tool will do and never show its results. Custom Meta will take a field you describe (starting from this week’s meta, with any deck’s share changed) and banned cards, and give each deck’s expected win rate against it, your saved decks included. Before it goes live we test it on past tournaments that had bans. Signed in, “Tell me when it’s ready” notes that you want a tool, and its launch then shows under Since your last visit; Undo takes it back, and nobody else sees who asked.

The deck builder’s Advanced tab holds two of these tools, both working on your exact 20 cards. The swaps passed a check on later tournaments. When players made a swap the model marks Confident, the list after it did better about 52 times in 100.

  • Swaps: One card out, one in, ranked by how much the win-rate model expects each to help against the meta.
  • Cards by turn N: Your chance to have the cards you pick in hand or in play by any turn, from a million simulated games.

17Technical details

For statisticians: the precise methods

Weighting and sample size

Every rate is exponentially decay-weighted: weight 2−age/28d for headline win rates and matchups (window 120 days) and 2−age/7d for the fast series. The headline meta share, card play rates (with copies and the role shares) and every field weight (Vs the meta, tiers, a card’s lift across opponents) use 2−age/7d, times 0.3 for an entry dated before the latest main-set release R while the snapshot is under 14 days past R (outside those days it equals the fast weight). Win-rate trends are fast − slow; share and play-rate trends are that headline − slow (shares relative). Counts shown as “games” (or entries, lists) are raw counts; Kish’s effective n = (Σw)²/Σw² sets the intervals and the “few games” cuts (shown as “weighted games” where it appears). A trend is marked when |Δ| exceeds 1.645 standard errors; otherwise it reads “Steady”. A win-rate trend whose fast side carries a weight Σwfast under 20 (a game today counts 1, a week-old one 0.5; capped by that side’s effective n) reads “Too few recent games” whatever its test says. The charts over time recompute the headline number as of the end of each UTC day (rows dated through that day, the same window and weights measured from its end). The last point is the headline, which counts every game up to the latest data; in a “Since <set>” window every point counts only games since the release and starts a day after it.

Intervals

90% Wilson intervals on neff/deff. Pilots repeat decks and lists, so rows are not independent: shares, win rates and card play rates use player-clustered sandwich variances, and deff = max(1, clustered / iid variance). Matchup cells are clustered two-way (player and opponent) so A-vs-B and B-vs-A stay mirror images. Real data: share deff median ≈ 4, win-rate SE about 1.2× the iid one.

Player ratings and skill adjustment

Glicko-2 ratings updated once per tournament from earlier results only (starting RD 60). Each game’s expectation includes a leak-free deck-strength offset (archetype residual from earlier tournaments, 28-day decay, 30 pseudo-games), so ratings are net of deck strength. Adjusted for skill = 0.5 + mean(score − skill-only expected score). A deck’s Pilot rating and its opponents’ are decay-weighted means of the pilots’ and the opponents’ ratings over those same games, and “vs their opponents” is the difference of the two numbers shown; across the well-sampled decks the adjustment is about −0.14 points of win rate per rating point of that gap and crosses zero at a gap of ~0 (the pilots’ distance from 1500 put it at ~1507).

Matchups

A matchup is wr(A, B) = λ·x̄AB + (1 − λ)·p0(A, B), with λ = neff / (neff + 50). The prior p0 starts from a win-rate model fitted on the default games plus the games of NOEX, ban-list, CUSTOM and other-format events (special-rule events out), read for A’s mean list against B’s from its card strengths and type matchups only: its matchup-cell term and its card × opponent-deck terms are left out, because both are fitted on the pair’s own games, which λ already counts. That prediction is then moved by d(A) − d(B), a per-deck offset fitted as a ridge Bradley–Terry model (penalty 300, 120 days, time-weighted, past non-default games at 3 times the weight), with the pair’s own default games taken back out of its offset so they are not counted twice. This is the matchup half of Custom Meta’s method; tried once on the seven weeks from September 5, it lowered matchup log loss on default games (z −3.2) against the earlier prior, the model on default games alone. Every block of the model is antisymmetric, so wr(A, B) = 1 − wr(B, A). A cell’s interval is wr ± z·se with se² = λ²·q(1 − q)·deff/neff + (1 − λ)²·(q(1 − q)/50 + the prior’s bootstrap variance). The prior strength was chosen on validation windows; on later held-out games the earlier model prior cut matchup log loss by 0.012 against the previous shrinkage, most for pairs with few games. Every view uses the model fitted at the snapshot’s date, since it reads lists rather than a window. When no model is fitted, cells shrink toward the row’s pooled rate instead (empirical-Bayes strength) and the shown cell averages the two sides, ½(ŵAB + 1 − ŵBA), so they still add up.

The win rate vs the meta and tiers

The win rate vs the meta is ΣB share(B)·wr(A, B), mirror = 0.5, with share(B) the headline meta share (the weights in “Weighting and sample size”); its variance adds the clustered sampling variance, the prior’s bootstrap variance (scaled ×1.5, calibrated on validation windows) and the field shares’ own player-clustered variance (delta method, the cells held fixed). Tiers, in order: S ≥ 52%, A ≥ 50.5%, B ≥ 49% on the lower 90% bound; F when the upper bound is below 50%; C ≥ 47% on the lower bound; else D. Both bounds as shown (one decimal); no tier under 300 effective games.

Top cuts

Indirectly standardized by event: over events where some but not all entries make the cut, the deck’s cut entries are compared with the sum of its entries’ event cut fractions; ratio = (expected + residual) / expected, with a player-clustered interval.

Card roles

Within a deck, cards with the same name, category, stage and type form one slot (a card that may evolve as if it were X joins X’s). Shares are shares of the deck’s lists on the meta share’s weight (as the play rate) with player-clustered intervals; a deck worth under 20 lists on that weight gets the “rough guide” note. Core: slot in ≥ 90% of lists with one card in it; flex: two or more cards each in ≥ 5% of the slot’s lists; tech: one card, slot in 5–90%. Staple: the slot is in at least half the lists of more than half of all decks with 20+ lists. The cuts sit where the distributions change: slot shares pile up above 90% over a flat spread of optional cards, and the four staples (breadth 0.86–0.99) are far from the next card (0.33).

Card lift

For each deck with about 150+ effective listed games, a penalized logistic model of its games: card presence (≥ 1 copy, and a 2nd copy term where lists vary), card × opponent-archetype interactions, opponent effects, and a skill covariate (each player’s window strength leaving out their games on this deck). A card’s lift is its effect per opponent, plus the rest of the field, averaged by opponent share and converted to points; the interval comes from the fit’s weighted sandwich plus penalty covariance (not player-clustered; a clustered check moved it by under 10%, since the penalty dominates). On synthetic worlds with known answers it beat comparing lists with and without the card (lower RMSE and bias); a no-effect card favored by strong players can still read about +2 to +4 points (the most when players stick to one deck). Lift across decks is the games-weighted mean over three or more decks.

Cards against a deck

Each deck with 30+ effective listed games against the target gets the card-lift model with the target as its own opponent level; the card’s row against the target (≥ 1 copy vs none, as played) needs 10+ effective games with and without it. The beat page pools these per-deck effects with weights = effective games with the card, SE = √(Σw²se²)/Σw (separate fits), I² for heterogeneity, ranked by the lower 90% bound. Chosen over the deck builder model’s shared card × deck terms on synthetic worlds with a planted counter card (coverage 88–100% vs 0–12%; neutral cards cleared zero 4–11% vs 14–16%). On real held-out weeks neither predicted much (pooled points shrink to ~15% of their size), so only the low end ranks and tags.

Breakout score

Share momentum (fast vs slow share, needing 5+ pilots in 14 days), skill-adjusted performance and event-standardized top-cut residuals are empirical-Bayes shrunk z-scores, soft-capped at 2 (then 2 + 2u/(1 + u), never above 4), plus a novelty term; strength terms count only for rising or new decks. The flag threshold is the best F0.5 on a replay of past breakouts with a median lead of at least 3 days. On the replayed history (7 breakouts) that threshold was right on 46% of flag-days (90% range 20%–74%), caught 6 of 7 breakouts, with a median 3.5 days of warning. Card flags have no backtest yet, and within-deck win-rate differences are left out of the card score (no signal beyond noise).

The deck builder's suggestions

Each list of the window is a vector over slots (the card-roles slots), √copies × idf with idf = ln((1 + N)/(1 + lists with the slot)) + 1, normalized; similarity is cosine. The 1,000 most similar lists are weighted sim16 × 2−age/14d, each pilot’s lists sharing one weight, and each deck’s total weight W is compressed to √W when no list is close (the exponent rises to 1 as the best similarity goes from 0.75 to 0.85) so a hybrid’s smaller family keeps a voice; shares are weighted shares with player-clustered Wilson intervals. Fills use the card-role thresholds on that neighborhood (core ≥ 90%, flex options ≥ 5% of the slot’s lists, tech 5–90%; a second card of a filled slot needs ≥ 5% of the lists to run it beside the deck’s card); a deck card under 15% of the neighborhood is a cut unless it is a flex option of a slot the lists run. The number of lists, the exponent, the half-life and the compression were chosen on a validation window (lists of 2026-09-05 to 09-18 against the lists before) and reported on 2026-09-19 to 10-02, each list’s own pilot left out. Top-5 recall was 0.949 vs 0.848 for the old archetype-centroid suggestions (+10.1 points, SE 0.6) on lists of decks with 30+ lists and 0.668 vs 0.577 (+9.1, SE 2.0) on rogue or rare lists; synthetic two-deck hybrids got cards of both halves into the top 5 in 0.258 vs 0.110 of cases; a planted off-plan card was flagged as often (0.955 vs 0.957) with fewer real cards flagged (0.37 vs 0.49 per list).

Opening-hand odds

A Basic with a share r of the deck’s Basic copies (2 of 6: r = 1/3) can start with chance r + (1 − r)·P(a copy among 4 cards drawn from 19), and must start with chance r·P(no other Basic’s copy among those 4); a deck’s only Basic has 1. Turn-1 is r + (1 − r)·P(a copy among 5 of 19) for a Basic and P(a copy among 5 of 19) for any other card, 1 − C(19 − k, 5)/C(19, 5) with k copies (5/19 = 26.3% for one, 80/171 = 46.8% for two). Exact fractions, computed in the browser for the deck on screen.

The matchup model

An antisymmetric Bradley–Terry penalized logistic model fitted on both lists of every training match: card main effects (≥ 1 copy, 2nd copy), an archetype matchup cell, card × opponent-archetype terms, and Pokémon type and weakness terms. Intervals come from a tournament-cluster bootstrap plus the cells’ shrinkage variance, widened ×1.5 per matchup and ×2.25 for the overall (calibrated on validation windows). On three rolling 21-day held-out folds and an interpolation split it beat a plain matchup table (each pair’s results shrunk toward the row deck’s pooled rate) on log loss in every split; the site’s matchup numbers use a second fit of it, on more games and with deck offsets, as their prior (Matchups above).

18Credits

  • Tournament data: Limitless TCG and the organizers and players who report results there.
  • Card data and text: Limitless Pocket card database.
  • Card images: TCGdex where available, otherwise the Limitless card CDN; cached and served from our own server. On high-resolution screens, the large art at the top of deck pages is enlarged with an AI upscaler (Real-ESRGAN), which can smooth or invent fine detail.
  • Metalodon is an unofficial fan project, not affiliated with or endorsed by The Pokémon Company, Nintendo, Creatures, GAME FREAK or DeNA. Pokémon names and card images are © their respective owners.

Example as of Nov 9, 2026: the most played deck, Mega Charizard Y ex Entei ex, holds 8.5% of the field over 995 entries.