Wordle Entropy Calculator

In Wordle, every guess creates a pattern of green, yellow, and gray tiles. Some guesses create patterns that split the answer list into many useful groups. Other guesses produce patterns where many answers remain clustered together. Entropy is the information-theory measure that rewards the first kind of guess.

A high-entropy word is not necessarily trying to be the answer. Instead, it is trying to ask a good question. The best early guesses ask questions that have many helpful possible responses. If the response is all gray, you eliminate a large set of letters. If one or two letters hit, their positions and colors usually point toward a much smaller candidate group.

Many players choose a first word by instinct: a favorite word, a word with many vowels, or a word that feels likely. Entropy offers a more reliable question: which word is expected to reduce uncertainty the most? This is why words like SLATE, CRANE, ROATE, STARE, TRACE, and RAISE tend to outperform words with repeated letters or rare letters.

Entropy is most powerful early in the puzzle, when the answer pool is large. Later, the best guess may be a direct solve attempt or a word designed to separate a specific family. The value of entropy is that it teaches you to think in candidate groups instead of simply guessing plausible answers one at a time.

Candidate reduction potential estimates how much of the answer list a guess can remove before you know the feedback. A word with five useful unique letters can create many different color patterns. Some patterns will be rare and leave only a few answers. Other patterns will be common, but a good entropy word still keeps those groups smaller than a weak guess would.

This is why all-gray feedback from a strong word can still be good news. If SLATE is all gray, you have removed S, L, A, T, and E from consideration. If ROATE is all gray, you have removed R, O, A, T, and E. Those results do not solve the puzzle, but they reshape the next guess dramatically. Candidate reduction is the bridge between abstract entropy and the practical feeling of having fewer reasonable answers left.

Frequency asks whether a word contains common letters. Entropy asks how well the entire word separates possible answers. A word can contain common letters and still be less effective if those letters do not create diverse feedback patterns. Another word can contain a slightly less common letter but score well because it splits the answer pool more cleanly.

Good Wordle strategy uses both ideas. Frequency makes feedback more likely. Entropy makes feedback more useful. A strong opener usually contains common letters, avoids repeats, and places those letters in positions that reveal meaningful structure. This is why balanced words are usually better than pure vowel words.

Low entropy is not always bad. If only one or two candidates remain, the best move may be the answer itself, even if the word would be a weak opener. Words with repeated letters, rare letters, or very specific patterns can be poor first guesses but perfect final guesses.

Examples include words with duplicate letters such as EERIE or KNOLL, rare-letter words such as JAZZY, and trap family candidates where only one position changes. These words do not ask broad questions. They answer a narrow question. The skill is knowing when the game has shifted from information gathering to direct solving.

Elite and Strong tiers are usually good first or second guesses because they ask broad questions. They cover common letters, avoid unnecessary repeats, and tend to produce feedback that points somewhere useful. Playable words can still be fine, especially if they match your known clues. Low-tier words are often poor openers, but they may be correct endgame guesses when the candidate list is already small.

Treat the tier as context, not a command. If you have no clues, choose a high-entropy opener. If you already know four letters, entropy matters less than solving the exact word. If you are in hard mode, legality can also matter more than raw entropy. The best Wordle decisions come from combining the score with the actual board state.

A standalone entropy estimate is helpful for learning why some words make better openers, but the richest use of entropy comes after a finished game. Once you know the actual sequence of green, yellow, and gray tiles, you can ask whether each guess was the best information play available at that moment. A word with average first-turn entropy might be excellent on turn three if it separates the exact candidates that remain.

Finished-game review also shows the difference between expected information and actual information. Sometimes a high-entropy guess gets unlucky and leaves a large group. Sometimes a lower-entropy answer guess hits perfectly. That does not make the original decision wrong. It means the outcome and the decision quality are different things. Entropy helps you evaluate the decision quality without being fooled by lucky or unlucky tile patterns.

Use this calculator to understand the shape of a word, then use Wordle Analyzer to replay the board and see how entropy, candidate reduction, and guess efficiency changed after each clue.