Text Statistics
Get detailed statistics about your text content
Text Statistics measures the structure of a passage as you type: words, characters, lines, paragraphs, unique words, lexical diversity, syllables, reading time, speaking time, and common-word frequency. It is a broad editorial snapshot rather than a single score.
Content reviewed: August 27, 2026
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Actions:
How to Use
- Paste your text into the editor
- View comprehensive text statistics
- Check readability scores and word analysis
- Export the statistics report
Features
- Word and character counts
- Sentence, paragraph, and line counts
- Word frequency and lexical diversity
- Reading and speaking time estimates
- Readability metrics for English prose
Tips for getting Text Statistics right
- Reading time assumes ~200 words per minute — adjust mentally for dense technical material
- Compare character counts with and without spaces when a platform limit counts spaces differently than you assumed
- Paragraph counts depend on blank lines, not indentation
- Use the top-word list to catch filler words and repeated phrases before publishing
What each metric means
| Metric | Definition | Common use |
|---|---|---|
| Words | Whitespace-separated tokens | Essay length limits, freelance billing |
| Characters (with spaces) | Everything including spaces/newlines | Platform limits like SMS or meta tags |
| Sentences | Split on . ! ? terminators | Average sentence length checks |
| Paragraphs | Blocks separated by blank lines | Structural balance in drafts |
| Reading time | Words ÷ ~200 wpm | Blog post time-to-read labels |
Practical uses
- Writers: keep blog intros under ~100 words so readers reach the substance fast
- Students: verify essays hit length ranges without padding the conclusion
- Translators: estimate project scope from source-word counts before quoting
What this tool adds beyond a simple word counter
A basic counter tells you how long the text is. This tool helps explain how that length is distributed: whether the draft is repetitive, how many unique words it uses, how long it takes to read aloud, and which words dominate the passage. That makes it more useful for editing and content review than a single total.
Real-World Use Cases
- Checking whether an article draft hits word-count and reading-time targets
- Comparing two versions of copy for lexical diversity and repetition
- Estimating speaking time for a script, speech, or narrated video
- Spotting overused words before final editing
- Exporting a quick metrics sheet for a writer, editor, or client review
Best Practices
- Use the statistics as a dashboard, then decide which metric actually matters for the publishing goal
- Review unique words and top words together when you are trying to reduce repetition
- Check reading time for web content and speaking time for scripts or presentations
- Look at readability metrics in context rather than optimizing every draft toward one number
- Export the CSV when you need to compare revisions or share editorial observations with someone else
Common Mistakes to Avoid
- Treating lexical diversity as a quality score instead of a signal about repetition
- Running the stats on code or data blobs and expecting meaningful writing insights
- Assuming reading and speaking times are universal rather than rough averages
- Ignoring the most common words list when repetition is the actual editing issue
- Comparing drafts with very different structures and reading too much into one metric
Troubleshooting
- If word counts feel off, inspect pasted URLs, punctuation-heavy strings, or hyphenated phrases
- If reading time seems inflated, confirm that the draft does not contain long pasted lists or code blocks
- If the common-word list looks noisy, remember it reflects raw frequency rather than semantic importance
- If readability numbers seem odd, remove non-prose elements and re-run the analysis
- If you need line-by-line cleanup before analysis, use Whitespace Remover or Line Sorter first
Frequently Asked Questions
What readability metrics are shown?
The tool shows Flesch Reading Ease and Flesch-Kincaid Grade Level alongside broader text statistics.
Can it analyze long texts?
Yes. It works well for long passages in the browser, though very large inputs still depend on your device and tab performance.
Does it detect language?
The tool provides statistics regardless of language, though readability scores are calibrated for English.
Privacy & Security
All statistics are computed locally. Your text stays on your device.
Tips & Best Practices
- Reading time assumes ~200 words per minute — adjust mentally for dense technical material
- Compare character counts with and without spaces when a platform limit counts spaces differently than you assumed
- Paragraph counts depend on blank lines, not indentation
- Use the top-word list to catch filler words and repeated phrases before publishing
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