Key Takeaways
- GSS data (2010-2020): No significant gender difference in recent cohorts (15% both)
- 2023 Gallup poll: 20% men and 20% women report infidelity
- Natsal-3 UK (2010-2012): Lifetime infidelity 21% men vs 20% women
- General Social Survey (1972-2016) data shows 20% of married men vs. 13% of married women reported extramarital sex
- A 2017 YouGov poll found 23% of men vs. 19% of women admitted to cheating in relationships
- Institute for Family Studies analysis indicates men are 2.5 times more likely to have affairs than women (25% vs 10%)
- GSS analysis shows men cheat more among ages 18-29 (28% vs 24%)
- YouGov (2021): Men lead in workplace affairs (32% vs 25% women)
- Superdrug (2020): Men more likely to cheat via apps (45% vs 38%)
- 2021 YouGov UK poll shows 20% women vs 24% men cheated
- Gleeden app data (2022): 42% female users seeking affairs vs male majority but equal intent
- 2019 DrEd survey: Women 57% vs men 52% in Europe confessed cheating
- DrEd/Superdrug (2021): Women more emotional affairs (65% vs 55% men)
- Gleeden (2023): Female users report higher satisfaction in affairs (52% vs 48%)
- 2022 Bumble poll: Women 29% vs 26% men cheated emotionally
Across major surveys, cheating rates are largely equal between genders, with small differences depending on country and group.
Related reading
Equal rates
Equal rates Interpretation
Men cheat more
Men cheat more Interpretation
Men higher young adults
Men higher young adults Interpretation
More related reading
Women cheat more
Women cheat more Interpretation
Women higher contexts
Women higher contexts Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Sophie Moreland. (2026, February 13). Which Gender Cheats More Statistics. Gitnux. https://gitnux.org/which-gender-cheats-more-statistics
Sophie Moreland. "Which Gender Cheats More Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/which-gender-cheats-more-statistics.
Sophie Moreland. 2026. "Which Gender Cheats More Statistics." Gitnux. https://gitnux.org/which-gender-cheats-more-statistics.
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