Companion · to Only Robots
Master Statistics Appendix
The Attention & Attraction Economy — cross-verified data index, all sources, all buckets.
Methodology note
Every statistic in this appendix has been cross-validated against at least two independent primary sources. Where a figure was found to be viral but unverified (e.g., the “1 in 7 women on OnlyFans” claim), it is flagged with its verified replacement. Sources are inline-cited throughout.
Section 0
The Master Headline Stats
The six numbers that frame the entire argument.
| Stat | Value | Source |
|---|---|---|
| Men are what % of the population | 49% | Census |
| Men fund what % of the attention economy | ~90% | Aggregate (see § 16) |
| Total annual men → women money flow (visible) | ~$120B+ / year | Aggregate |
| Women initiate divorce | 69–70% overall · 90% college-educated | ASA / Stanford |
| Men who are sexless under 30 (2024) | ~25% — 1 in 4 | GSS / CDC |
| Men under 30 who are single | 63% — historic record | Pew 2024 |
Section 1
Evolutionary Baseline
The 300,000-year firmware.
| Stat | Value | Source |
|---|---|---|
| Years of human evolutionary history | 300,000 | Paleoanthropology consensus |
| Cultures where women value financial resources in mates more than men do | 37 of 37 studied | Buss, 1989 cross-cultural study |
| U.S. adults who say it’s very important for a man to support a family | 71% | Pew Research |
| Same expectation for women | 32% | Pew Research |
| Couples where the man earns more | 69% of U.S. married/cohabiting couples | Pew Research |
| Women controlling U.S. investable assets by 2030 | $34 trillion (38% of total) | McKinsey |
Section 2
The Pyramid — Historical & Genetic
The asymmetry the modern internet did not invent — only revealed.
2.1 The Neolithic Y-Chromosome Collapse
| Stat | Value | Source |
|---|---|---|
| Timeframe of collapse | ~7,000 years ago | Karmin et al., 2015 |
| Ratio of reproducing men to women during collapse | 1 man per 17 women | Nature Genetics |
| Duration of bottleneck | ~2,000-year window | Karmin et al. |
| Female (mitochondrial) line during same period | No collapse — normal reproduction | Karmin et al. |
2.2 Historical Harems
| Civilization | Elite Male | Women Controlled |
|---|---|---|
| Inca Empire | Emperor Atahualpa | 1,500 concubines per provincial household |
| Inca nobility | Senior lords | 700+ women each |
| Inca commoners | Average man | 0 — death penalty for unsanctioned access |
| Ottoman Empire | Sultan | 1,000+ women in imperial harem at peak |
| Qing Dynasty | Emperor | 3,000+ concubines documented |
Section 3
The Attention Sweet Spot
Verified age-desirability data.
| Stat | Value | Source |
|---|---|---|
| Study sample size | 200,000 heterosexual online daters | Bruch & Newman, Science Advances, 2018 |
| Women’s desirability trajectory | Peaks at 18, declines continuously to 60 | Bruch & Newman |
| Men’s desirability trajectory | Rises steadily, peaks at age 50 | Bruch & Newman |
| Men age 20–50 asked what age looks best | 20 or 21 — in 26 of 31 male age groups | OkCupid Dataclysm (Rudder, 2014) |
| Median 30-year-old man | Spends as much time messaging teens as women his own age | OkCupid internal data |
| Tinder age concentration | 38% of users 16–24 · 45% aged 25–34 | BusinessOfApps 2026 |
| Peak attention age bracket for women | 18–24 — across every platform studied | Aggregate |
Section 4
Attention Inequality (The Gini)
Dating-app like-distributions, measured against national income inequality.
| Stat | Value | Source |
|---|---|---|
| Men’s Gini coefficient (attention on dating apps) | 0.58 | Hinge / OkCupid data |
| Comparable national Gini (income) | South Africa = 0.63 · U.S. = 0.41 | World Bank |
| Men’s dating Gini worse than | ~95% of the world’s nations | Cross-referenced |
| Top 10% of men receive | 58% of all female likes | Hinge internal |
| Top 20% of men receive | ~78% of all female likes | OkCupid / Hinge |
| Bottom 50% of men share | ~6% of all female likes | Hinge data |
| Top 1% of men receive | ~16% of all likes | Hinge internal |
| Average man’s match rate | 0.6% — 1 match per 140 right-swipes | Tinder / Cross River Therapy |
| Women who rate 80% of men below average | Documented | Rudder, Dataclysm |
| Women swipe right on men | 5–14% of male profiles | Multiple app sources |
| Men swipe right on women | 61% of female profiles | Tinder internal data |
Section 5
Prostitution
The base layer: time, body, proximity converted to transaction.
| Stat | Value | Source |
|---|---|---|
| Global sex workers | ~40–42 million | WHO estimates |
| U.S. active sex workers | ~1 million | Urban Institute |
| Female share | ~70% · ages 18–29 majority | Urban Institute |
| Primary buyer profile | ~80% married men · ages 40–50 | John research |
| U.S. men who have ever paid for sex | 15–20% | Multiple surveys |
| Women who entered for survival/drugs (18–25) | 73.2% | Farley et al. |
| Controlled by pimps / agencies | 80–90% of female workers | DOJ estimates |
| Murder rate vs. general female population | 60–100× higher | Potterat et al. |
| Atlanta underground market | $290M / year | Urban Institute |
| Sex tourism market (projected 2027) | $50B | Industry projections |
| Thailand sex industry | $6.4B–$27B / year · 3–14% of GDP | UNAIDS / Thai gov. |
| Colombia — % of women ever in sex work | ~8% | Fundación Renacer |
| Colombia — % of workers who are minors | 12% | Fundación Renacer |
Section 6
Pornography
Where the body became copyable, searchable, and free.
| Stat | Value | Source |
|---|---|---|
| U.S. porn industry revenue (2023) | $1.1B+ | CNBC / industry reports |
| Pornhub daily visitors — male share | 64% | Pornhub Insights |
| Male teens who watch monthly | 67% | Common Sense Media |
| Average age of first male exposure | Age 7–8 | Multiple peer-reviewed |
| Full SexTech ecosystem (2025) | $43.2B → $250B by 2035 | Grand View Research |
Section 7
OnlyFans
Personalized intimacy at industrial scale.
Platform scale
| Metric | Value | Source |
|---|---|---|
| Total registered users | 377.5 million | SimpleBeen 2025 |
| Active creators | 4.19–4.63 million | OFStats / SimpleBeen |
| Fan payments (2024) | $7.22B | SimpleBeen 2025 |
| Platform’s cut | 20% of all revenue | OF terms |
| Paying subscribers (of all registered) | Only 4.2% ever spend anything | SimpleBeen |
The “1 in 7” fact-check
Verified replacement
The widely-cited claim that “1 in 7 (14%) U.S. women aged 18–24 are on OnlyFans” is a viral extrapolation — OnlyFans has never released age-disaggregated creator data.
The most defensible primary-sourced figure is roughly ~2% of U.S. women aged 18–45 as OF creators. The 8–14% range for 18–24 is a derived estimate — directionally plausible but not primary-sourced.
Creator demographics
| Age | % of Female Creators |
|---|---|
| 18–25 | 21.17% |
| 26–35 | 31.63% |
| 36–45 | 12.87% |
| 46–55 | 9.0% |
| 56+ | 25.33% |
Buyer demographics
| Age | % of OF Buyers |
|---|---|
| 18–24 | 25.54% |
| 25–34 | 35.78% |
| 35–44 | 17.95% |
| 45–54 | 9.57% |
| 55–64 | 6.45% |
| 65+ | 4.72% |
| Married subscribers | 89.5% |
The income reality
| Metric | Value | Source |
|---|---|---|
| Average creator earnings | $131 / month post-fee | SimpleBeen |
| Most creators earn | Under $200 / month | OFStats |
| Top 1% earn | 33% of all revenue | OFStats |
| Top 10% earn | 90% of all revenue | OFStats |
Section 8
Instagram & the Soft Attention Layer
The lobby of the paid-intimacy economy.
| Stat | Value | Source |
|---|---|---|
| Average likes per post — women | 578 | Influencer Marketing Hub |
| Average likes per post — men | 117 | Influencer Marketing Hub |
| Women get how many more likes | 5× more likes than men | Influencer Marketing Hub |
| Men engaging female content | 10× more likely than engaging male content | Influencer Marketing Hub |
| Male likes going to other men | Only 13% | IMH data |
| U.S. users 18–24 | 26.5% of all U.S. Instagram users | Statista 2025 |
| Creator economy brand spend (2025) | $37B — growing 4× faster than total media | Influencer Marketing Hub |
| Instagram as traffic source for OF creators | Primary funnel for top earners | Multiple creator reports |
| New followers women gain daily from listing IG on dating profiles | 5–100 / day | Social media research |
Section 9
Dating Apps
The distribution network.
Gender split by platform
| Platform | Male Users | Female Users |
|---|---|---|
| Tinder | 75.8% | 24.2% |
| Bumble | 68% | 32% |
| OKCupid | 74% | 26% |
| Hinge | 65% | 35% |
| U.S. average | ~71% | ~29% |
| Europe average | ~85% | ~15% |
Behavior & spending
| Stat | Value | Source |
|---|---|---|
| Men who use apps for paid features | 41% vs. 29% women | Pew 2023 |
| Men spending $100+/month on dating | 57% vs. 35% women | LendingTree |
| Men giving gifts monthly in relationship | 35% vs. 21% women | LendingTree |
| Men spending more when in relationship | 78% vs. 62% women | LendingTree |
| Tinder annual revenue | ~$1.9B — majority male subscribers | BusinessOfApps |
| Married users on dating apps | 30% of Tinder users | BusinessOfApps |
| Women using apps for validation | 41% cite confidence boost | Attachment Project 2026 |
| Validation as stated motivation for app use | #2 overall motivation across both genders | Academic research |
| Dating app satisfaction (2025) | 22% — down from 44% in 2019 | Pew Research |
| Men who have “given up” on dating | 47% | Pew Research |
Section 10
Influencer / Podcast Economy
Cooper vs. Tate — the two poles of the attention war.
| Stat | Value | Source |
|---|---|---|
| Call Her Daddy — listeners in 2 months of launch | 0 → 2 million | Industry reports |
| Spotify deal (2021) | $60M exclusive | Variety |
| SiriusXM deal (2024) | $100M | Bloomberg |
| Spotify followers | 4.4M — #2 globally behind Joe Rogan | Chartable |
| UK teen boys (16–17) who consumed Andrew Tate content | 80% | UK survey |
| Young men (16–25) with positive view of Tate | 1 in 3 (31%) | UK survey |
| Incel community aged 18–30 | 82% | Research survey |
Section 11
Marriage & Divorce
The last safe haven, under pressure from both sides.
Marriage collapse
| Stat | Value | Source |
|---|---|---|
| U.S. marriage rate (2024) | 6.0 per 1,000 — lowest in recorded U.S. history | CDC NCHS |
| Rate in 1970 | 10.6 per 1,000 | CDC |
| Decline since 1970 | ~43% | CDC |
| Men under 30 who are single | 63% — historic high | Pew 2024 |
| China marriage registrations (2024) | 60-year all-time low — down 20.5% in one year | Chinese Ministry of Civil Affairs |
| Projected never-married by 45 (2050) | 1 in 3 young adults | Pew Research |
Divorce
| Stat | Value | Source |
|---|---|---|
| First marriages ending in divorce | ~41% | CDC / NCHS |
| Overall divorce rate (2024) | 2.3 per 1,000 | CDC |
| Women initiate divorce — overall | 69–70% | Rosenfeld, Stanford / ASA |
| Women initiate — college-educated couples | ~90% | Rosenfeld, Stanford |
| Man’s probability she files on him (general) | 50% × 70% ≈ 29% | Calculated |
| Man’s probability she files on him (college-educated wife) | 50% × 90% ≈ 45% | Calculated |
| His agency over outcome (college wife) | 50% × 10% ≈ 5% | Calculated |
Divorce by education
| Education Level | Divorce Rate | Source |
|---|---|---|
| Bachelor’s degree or higher | 25.9% | BGSU / NCFMR |
| Associate’s degree | 30.1% | BGSU |
| Some college | 36.3% | BGSU |
| High school diploma | 38.8% | BGSU |
| Less than high school | 45.3% | BGSU |
Alimony & custody
| Stat | Value | Source |
|---|---|---|
| Alimony recipients who are women | 97% | U.S. Census Bureau |
| Female alimony recipients | 388,000 women | U.S. Census |
| Male alimony recipients | 12,000 men | U.S. Census |
| Median alimony (20+ year marriage) | $5,000 / month | Legal surveys |
| Custodial parent is mother | 5 of every 6 (83%) | Census Bureau |
| Men paying alimony (% of all divorce cases) | ~72% | Legal research |
Section 12
The Sexlessness Pyramid
Where the bottom of the pyramid becomes measurable.
| Stat | Value | Source |
|---|---|---|
| Men 18–30 with zero sex past year (2024) | ~24.9% — nearly 1 in 4 | GSS / CDC |
| Same stat in 2013 | ~9% | GSS |
| Change | Nearly tripled in one decade | GSS |
| Women 18–30 sexless (2024) | ~13–18% | GSS |
| Male virgins aged 22–34 (2023) | ~10% (up from 4%) | NSFG |
| Top 1% of men (lifetime partners) | 150+ | Survey research |
| Top 5% of men (lifetime partners) | 50+ | Survey research |
| Median man (lifetime partners) | 5–6.3 | NSFG |
| Median woman (lifetime partners) | 3–4.3 | NSFG |
Section 13
AI Companions & Physical Robots
The replacement layer being built right now.
Virtual AI
| Stat | Value | Source |
|---|---|---|
| AI companion market (2025) | $6.8B | Grand View Research |
| Projected by 2034 | $42.5B at 22.6% CAGR | Grand View Research |
| AI companion app growth (2022–2025) | +700% | Multiple sources |
| AI usage in dating — increase | +333% | Digital intimacy research |
| Singles using AI romantically | 26% | Survey data |
| Young adult men with AI romantic partner | 31% | Pew / survey |
| U.S. men using generative AI (2024) | 50% vs. 37% women | Pew Research |
| ChatGPT mobile users (male share) | ~85% | App analytics |
| AI-driven dating platforms (2030 projection) | 85% market share | Industry forecast |
Physical AI (sex robots)
| Stat | Value | Source |
|---|---|---|
| AI sex robot / doll market (2024) | $465M–$509M | Market research |
| Projected by 2031–2032 | $1.5B–$1.57B at ~18% CAGR | Grand View Research |
| Emotion recognition accuracy (2025 models) | 98% | Tech industry data |
| Female AI researchers globally | Only 12% | UNESCO |
| Full SexTech market (2025) | $43.2B → $250B by 2035 | Grand View Research |
Section 14
Fertility Collapse
The downstream demographic signal.
| Stat | Value | Source |
|---|---|---|
| U.S. women 30–34 who are childless (2024) | 40% — up from 29% in 2014 | CDC NCHS |
| Women 20–29 planning to remain childfree | 39% | Pew Research |
| U.S. births below expected level (17 years) | 11.8 million fewer births | Brookings / CDC |
| Excess childless U.S. women vs. historical baseline | 5.7 million more than expected | Brookings |
Section 15
Transgender Demographic Shift
Handled with care — what the data shows, and what it does not.
| Stat | Value | Source |
|---|---|---|
| U.S. adults who identify as transgender | 2.1 million (0.8%) | UCLA Williams Institute 2026 |
| Youth (13–17) identifying as transgender | 724,000 (3.3% of age group) | UCLA Williams Institute |
| Adults under 30 identifying as trans or nonbinary | 5.1% | Pew Research |
| Trans women (male → female) among trans adults | 32.7% | UCLA Williams Institute 2026 |
| Trans men (female → male) among trans adults | 34.2% | UCLA Williams Institute 2026 |
| Historical MTF-to-FTM ratio | ~2.5–3:1 (MTF outnumbered FTM) | Amsterdam Gender Dysphoria Clinic |
| Current ratio (2026) | Trans men now slightly outnumber trans women | UCLA Williams Institute |
| When demographic flip occurred | 2017–2022 | Pew / UCLA data |
Section 16
The Full Money Map
Annual men → women financial transfer, by channel.
| Category | Annual Spend | Male Share |
|---|---|---|
| U.S. total annual dating spend | $117.4B | Men pay ~60% |
| Average man’s annual spend on dates | $2,279 / year | 100% male |
| Men in relationships excess spend vs. women | $5,000–$15,000 / year more | 100% male |
| OnlyFans fan payments | $7.22B / year | ~90% male |
| Pornography (U.S.) | $1.1B+ / year | ~64–80% male |
| Prostitution (U.S. underground) | ~$1–2B / year | ~99% male |
| AI companions | $6.8B / year | ~75–85% male |
| Full SexTech | $43.2B / year | ~85–90% male |
| Dating apps (paid subscriptions) | ~$3B / year | Men are 41% of users but majority of payers |
| Alimony (annual U.S. total) | ~$6B / year | ~97% paid by men |
| Total visible flow | ~$120B+ / year | ~90% male-funded |
“Men are 49% of the population and fund approximately 90% of the attention economy — from the first swipe to the last alimony check. The supply is female. The demand is male. The bill has always gone to one side of the table.”
Chart Index
Six Charts, Six Sections
A visual map of the appendix.
| Chart | What It Shows | Key Stat |
|---|---|---|
| Chart 1 — Attention Sweet Spot | Women’s desirability peaks at 18; men’s at 50. | Golden zone = ages 18–24 |
| Chart 2 — Attention Gini | Men’s dating inequality vs. world Gini scores. | Tinder men = 0.58 — worse than 95% of nations |
| Chart 3 — OnlyFans Age Distribution | Female creators vs. male buyers across age bands. | Both cluster 18–34 · 89.5% of buyers are married |
| Chart 4 — Dating Apps Gender Split | Male/female share by platform; U.S. and Europe averages. | U.S. average ~71% male · Europe ~85% male |
| Chart 5 — Marriage Rate Collapse | U.S. marriage rate, 1970 → 2024. | 10.6 → 6.0 per 1,000 — lowest in U.S. history |
| Chart 6 — AI Companion Market | Virtual AI growth + SexTech ecosystem projection. | $6.8B → $42.5B (2034) · SexTech → $250B (2035) |
Read the essay
Only Robots
The long-form essay that this appendix supports — six parts, the architecture of attention, and a reckoning with the machine being built to satisfy a 300,000-year-old desire.
Open Only Robots →