Letter Frequency Analyzer Online
Paste any text to see a full A-Z breakdown showing how many times each letter appears and what percentage of the total letter count it represents. Results are sorted by frequency so the most common letters appear first. Useful for cryptography, word puzzles, and linguistic analysis. Nothing is uploaded.
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Paste your content on the left to instantly analyze the alphabet distribution.
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What the results show
The analyzer counts every letter from A to Z in your text, ignores punctuation, numbers, and spaces, treats uppercase and lowercase as the same letter, and displays the results as a ranked table. Each row shows the letter, how many times it appears, and what percentage of the total letter count it represents. Letters with zero occurrences are included in the table so you can see the full alphabet at a glance, not just the letters that appear.
Results are sorted by frequency by default, with the most common letters at the top. The percentage column is more useful than the raw count when comparing texts of different lengths, since it normalises the data and lets you compare the distribution against the known English averages directly.
English letter frequencies
In standard English text, letters are not evenly distributed. The letter E is the most common by a significant margin, appearing in roughly 12.7% of all letters in a typical sample. The classic mnemonic “ETAOIN SHRDLU” lists the twelve most frequent English letters in order and is well known to typographers, printers, and cryptographers.
Here are the standard frequency percentages for all 26 letters in English, derived from large corpus analysis:
E (12.7%), T (9.1%), A (8.2%), O (7.5%), I (7.0%), N (6.7%), S (6.3%), H (6.1%), R (6.0%), D (4.3%), L (4.0%), C (2.8%), U (2.8%), M (2.4%), W (2.4%), F (2.2%), G (2.0%), Y (2.0%), P (1.9%), B (1.5%), V (1.0%), K (0.8%), J (0.15%), X (0.15%), Q (0.10%), Z (0.07%).
These percentages vary between text types. Technical writing and scientific papers have different distributions from fiction and casual conversation. Formal writing tends to use fewer contractions and simpler verb forms, which shifts the relative frequency of certain letters. The analyzer lets you see the exact distribution for your specific text, which you can then compare against these reference figures manually.
Who uses letter frequency analysis
Cryptographers and cipher solvers
Frequency analysis is the oldest technique in cryptanalysis. A monoalphabetic substitution cipher, where each letter is consistently replaced by another letter, preserves the underlying frequency distribution of the plaintext. The most common letter in the ciphertext is likely E. The second most common is likely T. Working through the ranked frequency table and matching it against ETAOIN SHRDLU is the starting point for breaking substitution ciphers and cryptograms by hand. This tool gives you the ranked table for any ciphertext in seconds.
Word game and puzzle players
Scrabble tile distribution is based on English letter frequency. The game has 12 E tiles and only 1 Z tile for exactly this reason. Understanding which letters are common and which are rare helps with game strategy, particularly when deciding which tiles to hold and which to swap. Wordle players sometimes paste their guesses and responses here to track which letters they have and have not tested yet. The five rarest letters in English — Z, Q, X, J, and K — are the ones most worth saving high-point Scrabble tiles for.
Linguists and language researchers
Different languages have distinct letter frequency fingerprints. German has high frequencies of E, N, and I. French shows high E, A, and S. Spanish has high E, A, and O. Running texts from different languages through a frequency analyzer and comparing the distributions is a practical way to identify a language from an unknown text sample, or to study how different writing styles within the same language shift the distribution. Literary analysis sometimes uses letter frequency to explore whether an author’s style produces a distinctive fingerprint compared to the language baseline. For the related analysis of how many vowels versus consonants your text contains, the vowel and consonant counter gives that breakdown directly.
Educators and students
Letter frequency is a core topic in introductory probability, statistics, and information theory. It underpins Claude Shannon’s work on information entropy and is a hands-on demonstration of how natural language has structure that can be measured and compared. Pasting sample texts here and comparing results against the ETAOIN reference is a practical classroom exercise that grounds the abstract concept in observable data.