RIGGEDROYALE
AnalyzePlayersDecksCardsData LabMethodologyPro

This material is unofficial and is not endorsed by Supercell. For more information see Supercell's Fan Content Policy. Despite our name, Clash Royale is not actually rigged: Supercell itself explains that matchmaking is based on Trophies and King Level, not on your cards or your wallet. "Rigged" here is satire — we just measure how unlucky you got.

Public methodology·Public player board·Deck Lab and top decks·Card explorer·Public correlations·Rigged Royale Pro·Reddit community·Fan content under the Supercell Fan Content Policy.

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AI DECK LAB

LET THE MODEL UPGRADE YOUR DECK

A machine-learning win-chance model scores your full 8-card list against the live meta, then searches automatic swaps that raise that win rate.

ML model on 47M real 1v1 games scores your full 8-card deck vs the live meta in your bracket, then only surfaces upgrades that raise the rebuilt deck's win rate — not a stats tracker. Read the full methodology

  • Deck improvements3 of 3 left today

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1 · Build the deck

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Cards
0/8
Avg elixir
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Special
0/3
Evo
0/2
Hero
0/2

Tap a card's EVO or HERO pill for a special form — 1 Evo, 1 Hero, plus 1 Wild slot either can take (3 max). Champions take a Hero or Wild slot too, so they count toward the same limit. The model scores evolutions; hero forms are shown for the build.

Card library

122 cards

2 · Score it

Choose a meta segment, then measure or optimize your deck.

Experimental

Objective: Improve

120

Change up to 2 cards. Lock cards on the deck to keep them.

24 · faster500 · max

Time

~1m 43s est.

Actual coverage

42.3%

More decks increase meta coverage and runtime. Coverage comes from current live deck frequencies; times remain rough estimates.

COMMON QUESTIONS

What this tool measures, and what it doesn't

Is this a stats database like RoyaleAPI?

No. Sites like that rank cards or decks from aggregate historical win rates. Rigged Royale is a machine-learning model trained on millions of real 1v1 games: it reads both full 8-card decks at once (plus levels, towers, and your trophy or league bracket) and outputs a win probability for that exact pairing. Public Supercell API data is only the training and battle-log source — the scores come from the model, not from live win-rate tables.

Does the site automatically suggest deck upgrades?

Yes. The Deck Lab has four search modes — improve up to N cards, complete a partial deck, replace a chosen group of 2–4 cards, or sweep single-card swaps. Every candidate is rebuilt as a full 8-card list and re-scored against the same live meta panel; a change only appears when the complete deck's projected win rate rises. You do not have to deduce swaps by hand from matchup charts.

Does this analyze my whole deck or individual cards?

The whole deck. All 16 cards — your 8 and the opponent's 8 — go into the model in a single pass, together with tower troops, both sides' average card levels and the trophy or league bracket. No card is ever scored on its own.

Are my card levels taken into account?

Yes — levels are not assumed equal. Both sides' average card levels are inputs to the win-probability model, so a level gap moves every prediction. Link your player tag and the card-levels panel below also reads your real collection: it lists the decks your levels can already field and names which deck each pending upgrade is holding back.

Does a suggested swap respect synergy and the elixir curve?

Yes, by construction. Every candidate swap is evaluated as a rebuilt 8-card deck scored against the same meta panel, so a card that raises your curve, duplicates a role or leaves your win condition unsupported produces a lower full-deck win rate and is discarded before you ever see it.

ANALYST NOTESHow to read this data
  • The model board scores each popular deck against the frequency-weighted meta panel. It reads matchups, not piloting difficulty.
  • The deck lab and the experimental ML upgrade run on the same model and the same meta panel, and are also exposed as commercial API endpoints under /api/v1.
  • Descriptive data. Small samples, mode mix, patches, card levels, and selection bias can all move a deck before the wider player base confirms it.

Scoring the meta with the win-chance model — first build can take a minute…

THE MODEL'S OWN RANKING

TOP DECKS ACCORDING TO THE WIN-CHANCE MODEL

RankedLadder

Best Ultimate Champion DecksAll leagues and arenas

Scoring the meta with the win-chance model — first build can take a minute…

Does the rating change with my trophies or league?

Yes. The model is segmented across six Trophy Road ranges and three ranked tiers — leagues 1–2, 3–5 and 6–7 — and each bracket is scored against the decks actually played in it. Your own league still reaches the model; the tiers decide which opponents you are measured against, and are grouped so every tier holds enough real games to stand on its own. There is no global rating: a deck can beat the meta in one bracket and lose to it in another, which is why every number on this page names its segment.

YOUR CARD LEVELS

WHAT YOUR COLLECTION CAN ACTUALLY FIELD

Card levels decide which decks you can pilot at full strength, not just which cards you own. This reads your collection, shows the real meta decks your levels are ready for today, and ranks the upgrades that would change that.

Pro
  • ·A read on your whole collection — cards unlocked, cards maxed, and the average level a single deck can reach.
  • ·The real meta decks your own card levels are ready to field today, with the cards holding each one back.
  • ·The next upgrade worth buying, and what it changes for the decks you actually play.
  • ·And the part that changes the lab itself: set your collection as the upgrade reference with a minimum card level, and the deck searches only try cards you own at that level or higher — no suggestion you would have to build first.

Included with Pro — sign in to get started. See what Pro includes.

1206 popular decks screened; 10 distinct picks each scored against 164 frequency-weighted meta decks / Leagues 6–7 / model v5-e2aa7bfc0c76 / built Aug 06, 01:24 PM

01

0.0% of scored meta playbest 81%worst 25%volatility 27

61.8%

model WR vs meta

02

0.0% of scored meta playbest 85%worst 20%volatility 32

59.6%

model WR vs meta

03

0.1% of scored meta playbest 80%worst 21%volatility 30

58.4%

model WR vs meta

04

0.0% of scored meta playbest 87%worst 25%volatility 25

58.1%

model WR vs meta

05

0.0% of scored meta playbest 82%worst 26%volatility 29

57.6%

model WR vs meta

06

0.0% of scored meta playbest 80%worst 20%volatility 26

57.4%

model WR vs meta

07

0.0% of scored meta playbest 81%worst 19%volatility 25

57.4%

model WR vs meta

08

0.0% of scored meta playbest 84%worst 21%volatility 29

57.3%

model WR vs meta

09

0.0% of scored meta playbest 76%worst 30%volatility 22

57.0%

model WR vs meta

10

0.1% of scored meta playbest 85%worst 17%volatility 32

56.7%

model WR vs meta