Baby Name Rises and Falls in the Available Records
Compare 2024 and 2025 counts for names present in both imported years. Birth-count change and rank change answer different questions.
By Marvin Tang · Content and calculations reviewed October 27, 2026.
National data scope: 65,411 imported name/sex/year records across 1880–2025. This is a selected subset of SSA records, with narrower historical coverage and catalog/rank filters. A missing row does not establish zero use or fewer than five uses. Figures below describe the stated selection. Data coverage and limits.
Names gaining recorded uses
The gain table orders names by added records. The fall table orders names by lost records. Each comparison requires a matching spelling and sex in both years. A positive rank gain means the later rank number is smaller; this can differ from the direction or size of the count change because ranks also depend on other names.
| Name | SSA sex list | 2024 count | 2025 count | Count change | Rank gain |
|---|---|---|---|---|---|
| Eithan | M | 1,593 | 3,636 | +2043 | +130 |
| Cooper | M | 5,699 | 7,472 | +1773 | +23 |
| Eliana | F | 6,423 | 8,191 | +1768 | +8 |
| Theodore | M | 12,011 | 13,355 | +1344 | +0 |
| Elias | M | 7,653 | 8,837 | +1184 | +12 |
| Bennett | M | 5,095 | 6,268 | +1173 | +20 |
| Atlas | M | 3,417 | 4,413 | +996 | +26 |
| Valentina | F | 4,438 | 5,354 | +916 | +12 |
| Ailani | F | 946 | 1,807 | +861 | +157 |
| Charlotte | F | 12,552 | 13,400 | +848 | +2 |
| Weston | M | 4,660 | 5,482 | +822 | +15 |
| Eloise | F | 3,430 | 4,251 | +821 | +15 |
| Lucy | F | 5,396 | 6,176 | +780 | +9 |
| Callum | M | 2,258 | 2,995 | +737 | +41 |
| Colter | M | 1,643 | 2,354 | +711 | +61 |
Names losing recorded uses
| Name | SSA sex list | 2024 count | 2025 count | Count change | Rank gain |
|---|---|---|---|---|---|
| Liam | M | 22,164 | 20,818 | -1346 | +0 |
| Dylan | M | 7,464 | 6,208 | -1256 | -13 |
| Aiden | M | 6,243 | 5,046 | -1197 | -15 |
| Olivia | F | 14,718 | 13,544 | -1174 | +0 |
| Luna | F | 7,135 | 6,076 | -1059 | -14 |
| Mia | F | 12,113 | 11,078 | -1035 | -1 |
| Camila | F | 7,608 | 6,591 | -1017 | -8 |
| Ava | F | 8,662 | 7,732 | -930 | -2 |
| Emma | F | 13,485 | 12,754 | -731 | -1 |
| Maverick | M | 6,615 | 5,894 | -721 | -13 |
| Logan | M | 6,267 | 5,576 | -691 | -7 |
| Asher | M | 8,123 | 7,456 | -667 | -8 |
| Ezra | M | 8,774 | 8,126 | -648 | -7 |
| Ian | M | 4,547 | 3,924 | -623 | -8 |
| Christian | M | 4,247 | 3,641 | -606 | -19 |
Why a missing earlier year is excluded
The national table is filtered by catalog coverage and rank, with narrower coverage in older years. If a spelling lacks an earlier imported row, the site cannot infer its earlier count. Calling the latest count an increase from zero would manufacture a growth rate. Consult a complete, consistently scoped source series before evaluating such a name.
Use a one-year change as a prompt to investigate
A single annual gain does not forecast future popularity. Open the name history, look for several observations, and keep alternate spellings separate. Counts describe the exact spelling in one sex-specific national series; they cannot predict the names in a future classroom.
Sources and interpretation
Popularity counts come from the US Social Security Administration baby-name files. SSA records applications for Social Security cards and separates exact spellings and recorded sex. Its public files apply privacy limits; this site applies additional import limits. National counts do not identify families, religion, ethnicity, gender identity, or the reason a name was chosen. Name origins are separate editorial fields, not SSA findings.
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