Gunning Fog Index

What Is the Gunning Fog Index?

Gunning Fog Index is a readability formula that maps English prose to a U.S. grade level. A Fog score of 12 means a typical high school graduate can read the passage on the first try.

Why it matters: Robert Gunning built FOG for business and newspaper writing — places where “foggy” jargon blocked comprehension even when readers had finished school.

Example: A press release at Fog 14 reads like college-level copy; the same story rewritten at Fog 8 uses shorter sentences and fewer three-syllable words.

Common mistake: Treating Fog as a quality grade. It measures surface complexity, not whether the ideas are worth the harder words.

Robert Gunning and the “fog” metaphor

Robert Gunning founded a readability consultancy in 1944 and published the Fog Index in 1952 in The Technique of Clear Writing. He used “fog” for prose that hides meaning behind unnecessary complexity.

Why it matters: FOG was designed for manual counting — two inputs writers could audit without computers.

Edge case: Fog targets English. Scores on other languages are not comparable to U.S. grade bands.

Reference: Background and grade table: Wikipedia — Gunning fog index (external).

What Your Gunning Fog Score Means

A Fog result is a grade-level number, usually between 6 and 17 for published prose. Lower scores mean easier reading on the FOG scale.

Why it matters: Editors can set concrete targets — “keep customer emails below Fog 10” — instead of debating whether copy “feels simple.”

Example: Fog 8 aligns with conversational U.S. English; many magazines and public websites aim near that band.

Common mistake: Assuming higher Fog always means better writing. Specialist audiences may need Fog 14+ by design.

Score-to-grade bands

Edge case: Scores below 6 or above 20 appear on very short or extreme samples — treat them as directional, not precise.

How the Gunning Fog Formula Works

Fog = 0.4 × (ASL + PHW)

ASL = total words ÷ total sentences. PHW = (complex words ÷ total words) × 100. The 0.4 factor scales the sum onto U.S. grade years.

Why it matters: PHW is already a percentage, so vocabulary swings move the score quickly — replacing five three-syllable words in a 200-word passage can drop Fog by roughly one grade band.

Example: ASL = 18 and PHW = 12 → Fog = 0.4 × (18 + 12) = 12.

Common mistake: Forgetting to multiply complex-word share by 100 before adding to ASL.

ASL — average sentence length

ASL measures how many words appear per sentence on average. Longer sentences raise Fog through the first term in the formula.

Why it matters: Splitting one 40-word sentence into two 20-word sentences cuts ASL and lowers Fog without changing vocabulary.

Edge case: Semicolon and colon splits change ASL — see the sentence-boundary rule in the complex-words section.

The 0.4 scaling factor

The 0.4 multiplier maps the sum of ASL and PHW onto U.S. grade years. Without it, raw totals would sit far above readable grade bands.

Why it matters: The constant was calibrated against reading-comprehension research so that Fog 12 aligns with twelfth-grade comfort, not an arbitrary index number.

Example: ASL + PHW = 30 → Fog = 12. ASL + PHW = 20 → Fog = 8.

PHW — percentage of hard (complex) words

PHW is the share of words with three or more syllables, expressed as a percentage of total words.

Why it matters: Fog penalizes polysyllabic density more aggressively than formulas that average syllables across every word.

Example: One word like “incomprehensible” in a short paragraph can spike PHW even when most other words are monosyllabic.

100-word sample method

Classic FOG instructions use a passage of about 100 words without skipping sentences. For long documents, take several spaced 100-word samples and average the results.

Why it matters: A single dense paragraph in a long file can misrepresent the whole if you score only the introduction.

Common mistake: Scoring navigation menus and boilerplate with body copy — strip chrome before auditing.

Complex Words and Counting Rules

On the canonical Gunning Fog method, a complex word has three or more syllables. Published rules also exclude certain tokens that look long but are familiar.

Why it matters: Two calculators can disagree when one excludes proper nouns and suffix forms and another counts every 3+ syllable token.

Example: “Created” is often excluded when -ed adds a syllable to a shorter root; “beautiful” usually counts as complex despite being common speech.

Common mistake: Assuming every long word is equally hard — Fog counts syllables, not reader familiarity.

Canonical exclusions

• Proper nouns (e.g. city and person names)
• Familiar compound words (e.g. “bookkeeper”)
• Words made three syllables only by -ed or -es (e.g. “created,” “trespasses”)
• Hyphenated compounds — often excluded when both parts are familiar

Why it matters: Legal and medical drafts full of long names can score high on strict counters even when the prose is plain.

UTF-8, Unicode, and syllable edge cases

Unicode defines characters; UTF-8 is how files and browsers store them. Syllable counts run on decoded word tokens, not raw byte length.

Why it matters: Smart quotes, ligatures, or decomposed accents can split tokens and change syllable totals.

Example: Pasting from PDFs often introduces soft hyphens that break one word into two tokens — both may flip from non-complex to complex or vice versa.

Edge case: Numbers and acronyms syllabify differently across engines. Compare scores on the same tool when auditing drafts.

Semicolons, colons, and sentence boundaries

Manual FOG methods often treat a semicolon or colon between independent clauses as a sentence break, counting the passage as two sentences instead of one.

Why it matters: One 40-word sentence with a semicolon may become two 20-word sentences — ASL drops from 40 to 20 and Fog falls sharply.

Example: “We met the deadline; the client approved the draft.” may count as two sentences in manual scoring but one in some automated splitters.

Common mistake: Comparing manual FOG homework to a browser tool without matching sentence-split rules.

What Is a Good Gunning Fog Score?

For a general U.S. audience, many editors target Fog 7–8. Plain-language and patient-facing programs often aim below 7. Text aimed at near-universal understanding often stays below 12. Professional news and business copy commonly lands 9–12.

Why it matters: Gunning himself cited eighth grade (Fog ~8) as comfortable for average adult readers — a practical default when no policy states otherwise.

Example: A benefits FAQ at Fog 6.5 is easier than the same policy explained at Fog 13.

Common mistake: Forcing Fog 8 on expert journals where Fog 15+ is appropriate for the audience.

Targets by content type

When to Use Gunning Fog Readability

Choose FOG when sentence length plus polysyllabic vocabulary is the main readability risk — business writing, journalism, policy rewrites, and investor communications.

Why it matters: Gunning designed FOG to cut unnecessary complexity in prose meant for busy readers, not to score poetry or fiction style.

Example: A compliance team rewrites a memo from Fog 16 to Fog 11 before publishing to all staff.

Common mistake: Using Fog alone on healthcare leaflets where SMOG is the cited standard — run both when policy names a formula.

Strong use cases

• Business and internal communications.
• Press releases and executive briefs.
• Plain-language audits of government web copy.
• Research abstracts checked for journal readability policies.
• Spot-checking jargon density vs Flesch–Kincaid on the same paste.
• Short passages where SMOG’s 30-sentence minimum is not met.
• Investor and SEC-style plain-English rewrites where Fog is a cited benchmark.

How to Improve Your Gunning Fog Score

To lower Fog (easier reading), replace three-syllable words first, then shorten sentences to reduce ASL.

Why it matters: PHW is multiplied by 100 inside the formula — vocabulary edits usually move Fog faster than light ASL trims.

Example: “Utilize” → “use,” “facilitate” → “help,” and “demonstrate” → “show” can drop PHW several points in one paragraph.

Common mistake: Chopping sentences while leaving Latinate jargon untouched — ASL helps, but PHW often dominates.

Practical editing tips

• Keep most sentences under 20 words for general audiences.
• Define a technical term once, then use a short form.
• Score a plain-text paste without headers, ads, or legal boilerplate.
• Read aloud — breathless sentences often mean high ASL.
• Re-check after edits; crossing from PHW 21% to 19% still lowers Fog.

Gunning Fog vs Other Readability Formulas

Fog complements syllable-average and vocabulary-list formulas. Use it when polysyllabic percentage matters more than total syllables per word.

Why it matters: A passage with one very long word can Fog higher than it Flesch–Kincaids — Fog counts how many words are polysyllabic, not average syllables.

Example: Ten short words plus one “incomprehensible” spikes PHW; Flesch spreads syllables across the whole average.

Common mistake: Publishing only the lowest grade from whichever tool was opened last.

Quick comparison

Limitations of Gunning Fog

Fog measures syllable length and sentence count. It does not know reader expertise, topic interest, or whether a long word is common (“beautiful,” “interesting”).

Why it matters: Pair Fog with audience testing on high-stakes documents — the index is a guide, not a veto on good style.

Example: Sports fans know “offside”; Fog still counts it as polysyllabic if the syllable engine tags three syllables.

Common mistake: Scoring code, JSON, or bullet lists of SKUs. Fog targets running prose.

Scorer and algorithm limitations

Canonical FOG excludes proper nouns, some compounds, and certain -ed/-es forms. Automated tools vary: some count every word with three or more syllables and do not apply those exclusions. Sentence splitters also differ on semicolons and abbreviations.

On this site: TextTools marks any token with three or more syllables as complex — it does not apply the published proper-noun or suffix exclusions. Scores may run slightly higher than manual FOG on name-heavy text.

Why it matters: Two Fog calculators can disagree by one or more grade bands on the same paste.

Historically, some manual methods counted clauses as sentences until the 1980s — modern automated tools use sentence boundaries instead. Compare like with like when citing scores.

Token and sentence edge cases

“Dr.” and “e.g.” affect sentence counts. Legal citations and numbered lists inflate ASL without adding readable sentences.

Example: A 150-word privacy policy with dense “whereas” clauses may show high ASL even after plain-language rewrites elsewhere.

Worked Example — ASL and PHW to Fog Score

Consider one sentence with 10 words, two of them complex (three or more syllables): “The server experienced a critical failure due to a hardware malfunction.”

Why it matters: A single-sentence sample shows how ASL and PHW combine before the 0.4 multiplier.

Step-by-step

ASL = 10 ÷ 1 = 10

Complex words = 2 (“experienced,” “malfunction”)

PHW = (2 ÷ 10) × 100 = 20

Fog = 0.4 × (10 + 20) = 12 → high school graduate band.

Common mistake: Using total syllables instead of the percentage of complex words — that is Flesch territory, not FOG.

Longer passage sketch

With 200 words, 10 sentences (ASL = 20), and 30 complex words (PHW = 15): Fog = 0.4 × (20 + 15) = 14 → college sophomore level.

Frequently Asked Questions