Our Data & Methodology
Transparency matters. Here is exactly how DateAtlas collects, processes, and scores dating data for 30 countries.
Data Sources
We aggregate data from five primary, publicly available sources. Each provides a distinct piece of the dating intelligence picture.
Numbeo
www.numbeo.comThe world's largest crowd-sourced cost of living and quality of life database. Millions of data points from residents and visitors across 10,000+ cities. We use it for safety indices, cost of living, and date cost estimates.
EF EPI (English Proficiency Index)
www.ef.com/epiThe world's largest ranking of countries by English skills, based on test data from 2.2 million adults across 111 countries. Critical for understanding communication ease while dating abroad.
Google Play Store
play.google.com/storeApp store data including download counts, user ratings, and review volumes for dating apps in each country. This gives us ground-truth data on which apps are actually popular.
World Bank Open Data
data.worldbank.orgDemographic and economic indicators for every country, including population statistics, gender ratios, internet penetration, and economic development levels.
ILGA World
ilga.orgThe International Lesbian, Gay, Bisexual, Trans and Intersex Association publishes comprehensive data on LGBTQ+ laws and policies worldwide. We use their State-Sponsored Homophobia report.
How Scores Are Calculated
Dating Score (0–100)
The composite Dating Score is a weighted average of seven normalized factors:
| Factor | Weight | Source |
|---|---|---|
| Safety | 20% | Numbeo Crime Index (inverted) |
| Cost Affordability | 15% | Numbeo Cost of Living Index (inverted) |
| English Proficiency | 15% | EF EPI Score |
| Gender Ratio | 10% | World Bank (proximity to 1.0) |
| LGBTQ+ Acceptance | 15% | ILGA Policy Index + social indicators |
| Cultural Openness | 15% | Composite of tourism, expat, and attitude data |
| App Coverage | 10% | Number and quality of active dating apps |
Each factor is first normalized to a 0–100 scale using min-max normalization across all 30 countries. The weighted sum produces the final Dating Score.
Safety Index (0–10)
Derived from Numbeo's Crime Index. We invert the crime index (lower crime = higher safety) and scale to 0–10. A score of 8+ indicates excellent safety; below 4 suggests caution is needed.
Cost Index (Average Date Cost in USD)
Based on Numbeo's restaurant prices: a mid-range meal for two plus two domestic beers plus two cappuccinos. All prices are converted to USD for comparison. The index reflects a typical "going out" date rather than fine dining.
Data Freshness
| Source | Last Updated | Update Frequency |
|---|---|---|
| Numbeo | Q1 2026 | Quarterly |
| EF EPI | 2025 Edition | Annually |
| Google Play Store | March 2026 | Quarterly |
| World Bank | 2024 Dataset | Annually |
| ILGA World | 2025 Report | Annually |
Limitations
We believe in being honest about what our data can and cannot tell you.
- Crowd-sourced bias. Numbeo data skews toward urban areas and English-speaking respondents. Rural areas and non-tourist cities may not be well represented.
- Estimation gaps. When primary data is missing, we use regional estimates. These are clearly labeled but are inherently less reliable than direct measurements.
- Country-level aggregation. Dating culture and safety can vary enormously within a country (e.g., Bangkok vs. rural Thailand, Berlin vs. rural Germany). Our scores represent national averages.
- App data limitations. We primarily use Google Play Store data. iOS-only apps or apps with limited Play Store presence may be underrepresented.
- Cultural nuance. Quantitative scores cannot fully capture the nuance of dating culture. We supplement with editorial content where possible, but a number cannot replace lived experience.
- Rapid change. Laws, app popularity, and social attitudes can change quickly. Our quarterly update cycle means there may be a lag between real-world changes and our data.
Report Corrections
If you spot incorrect data, outdated information, or have firsthand knowledge that contradicts our scores, please let us know. Community feedback is essential to improving data quality.
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