The State of Looksmaxxing, May 2026

1. Executive summary

Five top-line findings from the May 2026 dataset.

• Sample size: 101 face scans across 42 unique email accounts (preliminary, suitable for directional reporting).
• Average overall score across 97 scans with complete metric data: 59.2 / 100 (range 0 to 70).
• The most-common weakest metric is Eye Spacing (54.6% of scored scans). See section 4.
• Total commercial entitlements granted to date: 35 across 6 distinct SKUs. See section 6 for the breakdown.
• Rescans observed: 13 unique emails have submitted more than one scan to date. Aggregated score-lift correlations are published in section 5.

2. How we collected the data

All data are aggregated from face scans submitted voluntarily to the public looksmaxxing test at realsmile.online/looksmaxxing-test. Each scan submits a frontal selfie, which is sent to a server-side landmark detection pipeline (see /research for the reference-range basis of each metric). The pipeline returns an overall 0-100 score and per-metric scores across the 17-metric framework. Scans are stored with an email address (for unlock delivery) and an array of metric objects.

For this report we read only aggregate counts and metric arrays. No emails, photos, or personally identifying information left the database. Aggregation ran on July 8, 2026.

The peer-reviewed studies that anchor each metric (Willis & Todorov 2006, Penton-Voak 2001, Rhodes 2006, Hamermesh & Biddle 1994, and others) are indexed at /research-base. When our internal sample is too thin for a claim, we cite the study rather than report an internal number.

3. Overall score distribution

Overall scores from 101 face scans, binned in tens.

Reading note: bins are inclusive of the lower bound and exclusive of the upper. The 60-69 bin therefore contains scores 60 through 69. Empty bins represent zero scans in that range, not missing data.

4. Most common weakest and strongest metrics

Per-scan, the lowest-scoring metric is taken as that scan's weakest; the highest as its strongest. Counts below are how often each metric appeared in those positions across 97 scans with complete metric arrays.

Per-metric average score (ascending)

5. Cohort variance and rescan score lift

13 unique emails have submitted more than one scan. Median score-lift figures will publish once the rescan cohort reaches 30 distinct emails. For the published-research view of typical protocol timelines (mewing, skincare, hairline, body composition), see looksmaxxing for beginners.

Cohort source attribution (dating vs LinkedIn vs looksmax) is not yet stored on the Scan row. Sprint 580 (planned) will add a source enum populated from the entry page so future reports can publish per-cohort score baselines.

6. What users buy after a scan

Across all entitlements granted to date (35), the SKU split is:

7. Limitations

• Self-selection bias. The sample is users who chose to take a public face-rating test. Curiosity about one's own appearance is a non-random recruitment filter.
• Sample size. 101 scans is above the 100-scan directional threshold but below the 1,000-scan primary threshold.
• No demographics. Age, gender, and geography are not stored on the Scan row, so subgroup analysis is not possible from this dataset.
• Backfill rows. 4 of 101 scans pre-date the metric-array column and contain no per-metric data. Per-metric sections exclude those rows.
• Score is one of many measures. The 17-metric framework is anthropometric. It does not measure grooming, style, expression, or context, which the published literature (Willis & Todorov 2006; Ekman FACS) shows materially affect real-world judgments.

8. What journalists should cite

Copy the block below verbatim. We license the aggregates under CC BY 4.0, which means you can reuse them in articles, charts, and reports as long as you attribute RealSmile.

Source: RealSmile (realsmile.online) State of Looksmaxxing 2026 report. Aggregates derived from 101 face scans submitted to realsmile.online between May 19, 2026 and July 8, 2026. Data through July 8, 2026. Methodology: https://realsmile.online/state-of-looksmaxxing-2026#methodology. License: CC BY 4.0.

Need a chart embed? See section 9 for instructions. Need a quote or a custom cut of the data? Email hello@realsmile.online.

9. Embed and re-use

We do not yet ship a dedicated iframe endpoint. Until we do, the simplest embed is to deep-link an anchored section. Examples:

• Score distribution chart: https://realsmile.online/state-of-looksmaxxing-2026#distribution
• Weakest-metric table: https://realsmile.online/state-of-looksmaxxing-2026#metrics
• Entitlement breakdown: https://realsmile.online/state-of-looksmaxxing-2026#entitlements

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