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fWHR Calculator

The facial width-to-height ratio is the one proportion with a research literature behind it. Symmi measures it the way the papers define it, bizygomatic width over upper-lip-to-upper-eyelid height, and gives you the midface ratio alongside.

Drop a photo, paste one, or choose a file

Straight-on, whole face visible, even light. JPG, PNG or WebP.

Runs in your browser. Your photo never leaves your device.

How it is measured

Cheekbone width over upper-face height.

Width is measured across the widest points of the cheekbones. Height is the vertical distance from the upper lip to the upper eyelid line, which is why fWHR is usually between 1.6 and 2.2. The midface ratio uses the pupil-to-pupil distance against the height from the pupil line to the upper lip, and is the reading the Symmi app scores.

fWHR
Width over height. Population mean is about 1.9. Above 2.0 reads as wide and is the range the dominance studies discuss; below 1.8 reads as long.
Midface ratio
Pupil-to-pupil distance over the height from the pupil line to the upper lip. The app's band is 0.95 to 1.15.

Measure it yourself

How to measure fWHR yourself

You need one photo and a ruler, or any photo editor that shows pixel positions.

  1. 1Take a straight-on photo from at least an arm's length away, head level, neutral face, hair off the cheeks. Close-up phone selfies widen the middle of the face.
  2. 2Width: measure straight across between the widest points of the cheekbones (the bizygomatic width).
  3. 3Height: measure straight down from the upper-eyelid line (a line through the highest points of both upper lids) to the top of the upper lip.
  4. 4Divide width by height. For example 14.2 cm ÷ 7.4 cm = 1.92. Pixels work the same way, since only the ratio counts.
  5. 5Measure twice and average. A 1 mm error in the height moves the result by about 0.03.

Skip the ruler: the free tool above does it from one photo in about 30 seconds ↑

What's normal

What is a normal fWHR?

Most faces fall between 1.6 and 2.2, with a population mean of about 1.9. Men rated attractive in several studies cluster around 1.9 to 2.0; women slightly lower.

Under 1.7
Reads as: Long, narrow face
Note: Common with long and oblong face shapes.
1.7 to 1.8
Reads as: Slightly long
Note: Within the normal spread.
1.8 to 2.0
Reads as: Balanced
Note: Around the population mean of about 1.9.
2.0 to 2.1
Reads as: Wide
Note: The range the dominance studies discuss.
Over 2.1
Reads as: Very wide
Note: Reads broad; often a square or round face shape.

fWHR describes a proportion, not a personality. The links to perceived dominance in studies are small and disputed.

Sources

What this is based on.

The measurement and its reference ranges come from published research. Studies use different methods and populations, so compare your number with the range shown on this page rather than with other tools.

  1. 1.

    Weston EM, Friday AE, Liò P (2007). Biometric evidence that sexual selection has shaped the hominin face. PLoS ONE. PubMed 17684556

    Defines facial width-to-height ratio (cheekbone width over upper-face height) and shows it differs between the sexes.

  2. 2.

    Carré JM, McCormick CM (2008). In your face: facial metrics predict aggressive behaviour in the laboratory and in varsity and professional hockey players. Proceedings of the Royal Society B. PubMed 18713717

    The study that linked higher fWHR to aggressive behaviour in men, which made the measure widely known.

  3. 3.

    Geniole SN, Denson TF, Dixson BJ, Carré JM, McCormick CM (2015). Evidence from meta-analyses of the facial width-to-height ratio as an evolved cue of threat. PLoS ONE. doi:10.1371/journal.pone.0132726

    Meta-analyses: links to perceived threat hold up, while the average sex difference is very small.

  4. 4.

    Kosinski M (2017). Facial width-to-height ratio does not predict self-reported behavioral tendencies. Psychological Science. doi:10.1177/0956797617716929

    In a very large sample, fWHR did not predict self-reported behavioural tendencies.

  5. 5.

    Kartynnik Y, Ablavatski A, Grishchenko I, Grundmann M (2019). Real-time facial surface geometry from monocular video on mobile GPUs. arXiv. arXiv:1907.06724

    The face-mesh model that places the 468 surface landmarks this tool measures from.

  6. 6.

    Ablavatski A, Vakunov A, Grishchenko I, et al. (2020). Real-time pupil tracking from monocular video for digital puppetry. arXiv. arXiv:2006.11341

    The iris model that adds 10 eye landmarks (478 in total), used for pupil-based reference lines.

Our own data: how much each reading moves when the same face is photographed again is published on the methodology page. How we choose sources.

Related tools

FAQ

What does fWHR mean?+

It is a proportion that has been correlated in studies with perceived dominance and, in some samples, with behaviour. The effects are small and disputed. It is worth knowing your number; it is not worth reading your personality from it.

What is the ideal fWHR?+

There is no single ideal value. Men rated attractive in several studies cluster around 1.9 to 2.0; women slightly lower. Faces well outside 1.7 to 2.1 read as noticeably long or wide.

What does an fWHR of 1.6, 1.9 or 2.1 mean?+

1.6 to 1.7 reads as a long, narrow face. 1.8 to 2.0 sits around the population mean of about 1.9 and reads as balanced. 2.1 and above reads as wide and is the range the dominance studies discuss.

Does this also measure the midface ratio?+

It shows the midface ratio as a second reading: pupil-to-pupil distance over the height from the pupil line to the upper lip, with 0.95 to 1.15 as the band the Symmi app uses. For the full breakdown with both distances drawn on your photo, use the Midface Ratio Calculator.

Can fWHR change?+

The bone width cannot. The height reading shifts a little with brow position and lip posture, and the visual width shifts with cheek fullness. The Symmi app tracks the midface ratio across rescans.

Is my photo uploaded?+

No. The calculation runs in your browser.

One reading here.
Nineteen in the app.

A controlled scan, every reading against its ideal band, bone vs trainable, a plan, and a 3D model on Face ID iPhones.