◆ Database statistics
Two thousand years of recorded lives
119,194 figures from year 1 to 2039, drawn from the public Historical Popularity Index plus curated additions. Here's how they distribute.
Total entries
119,194
+127 hand-curated
Year range
1 — 2039
2,038 years
Categories
10
Politics to business
Eager-loaded
7,640
HPI ≥ 70 (~1 MB)
Tier breakdown
Sliced by Historical Popularity Index
The HPI score (0-100) measures how globally recognized a figure is, based on Wikipedia coverage and engagement. The eager-loaded tiers cover everyone the average user will recognize; the deeper tiers (HPI < 70) hold the long tail and only load on demand.
1.1k
6.5k
24.8k
37.9k
48.9k
Tier 1 (HPI ≥ 80) eager
Tier 2 (70-80) eager
Tier 3-5 lazy
Era density
Distribution across centuries
Pre-1500 in century buckets, 1500-onward in decade buckets. The dataset's age-threshold for inclusion is why 2000s drops sharply — recent births haven't yet accumulated the fame to register.
Category distribution
Where the famous come from
Sports has the largest share — globally tracked athletes have well-documented birthdates. Politicians and entertainers follow. The smaller "business" category reflects how recent a phenomenon "famous business person" is in historical terms.
Sports45,324
Politics17,640
Entertainment16,388
History9,261
Music9,094
Science7,843
Writing7,039
Arts2,909
Religion2,272
Business1,424
Type distribution
Dominant types across the eager-load sample
Computed live from the 7,640 highest-fame figures. Each percentage shows what share of these entries have that type as their dominant. Loading…
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Lifespan by type
Average age at death, by dominant
Lives that ended (so still-living figures are excluded) grouped by their dominant type. Reflects who happened to die early vs late among the famous figures we have data for — not a claim about which type tends to live longer.
Computing averages…
Type co-occurrence
Which secondaries follow which dominants
For each dominant type (rows), the heatmap shows how often each secondary type (columns) appears in position 2 of the sequence. Darker cells = more common pairing. The diagonal is empty because a type can't be its own secondary.
Building heatmap…
Find your matches in the data
Enter your birthdate and see which historical figures share your sequence — top type, secondary, and the way the rest stack up.