State Shares of Recorded Baby Names
Compare one state’s count for a spelling with the national count for the same spelling, sex, and year. The examples are restricted to names covered by both imports.
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.
One example per state in 2025
Each example has at least 200 national records and 10 state records. These editorial cutoffs reduce tiny-denominator comparisons. Among eligible records for each state, the table selects the largest state/national share. It does not search names missing from the national import and therefore cannot identify the most distinctive name among all names used in a state.
| State | Example name | SSA sex list | State count | National count | State share of that name |
|---|---|---|---|---|---|
| AK | Augustus | M | 12 | 783 | 1.53% |
| AL | Judson | M | 22 | 252 | 8.73% |
| AR | Honey | F | 20 | 322 | 6.21% |
| AZ | Mariel | F | 24 | 298 | 8.05% |
| CA | Ernesto | M | 86 | 272 | 31.62% |
| CO | Beck | M | 16 | 259 | 6.18% |
| CT | Salvatore | M | 15 | 249 | 6.02% |
| DC | Khalil | M | 10 | 826 | 1.21% |
| DE | Nyla | F | 14 | 1,315 | 1.06% |
| FL | Milan | M | 267 | 1,418 | 18.83% |
| GA | Ivey | F | 31 | 282 | 10.99% |
| HI | Aila | F | 11 | 329 | 3.34% |
| IA | Drake | M | 18 | 299 | 6.02% |
| ID | Quincy | F | 17 | 335 | 5.07% |
| IL | Khalid | M | 27 | 250 | 10.80% |
| IN | Colten | M | 15 | 238 | 6.30% |
| KS | Laken | F | 11 | 256 | 4.30% |
| KY | Kolton | M | 32 | 489 | 6.54% |
| LA | Landry | F | 24 | 279 | 8.60% |
| MA | Conor | M | 26 | 292 | 8.90% |
| MD | Clare | F | 15 | 283 | 5.30% |
| ME | Alden | M | 13 | 479 | 2.71% |
| MI | Ali | M | 157 | 1,116 | 14.07% |
| MN | Imran | M | 36 | 237 | 15.19% |
| MO | Whitley | F | 33 | 420 | 7.86% |
| MS | Jamir | M | 31 | 495 | 6.26% |
| MT | Quincy | F | 11 | 335 | 3.28% |
| NC | Ivey | F | 28 | 282 | 9.93% |
| ND | Riggs | M | 10 | 329 | 3.04% |
| NE | Merritt | F | 24 | 401 | 5.99% |
| NH | Finnegan | M | 15 | 569 | 2.64% |
| NJ | Yehuda | M | 154 | 351 | 43.87% |
| NM | Amaris | F | 13 | 360 | 3.61% |
| NV | Kiana | F | 12 | 366 | 3.28% |
| NY | Shimon | M | 173 | 241 | 71.78% |
| OH | Cade | M | 119 | 1,392 | 8.55% |
| OK | Whitley | F | 26 | 420 | 6.19% |
| OR | Tilly | F | 13 | 302 | 4.30% |
| PA | Martha | F | 52 | 393 | 13.23% |
| RI | Francesca | F | 11 | 984 | 1.12% |
| SC | Marleigh | F | 17 | 261 | 6.51% |
| SD | Huxley | M | 11 | 357 | 3.08% |
| TN | Merritt | F | 40 | 401 | 9.98% |
| TX | Mariel | F | 101 | 298 | 33.89% |
| UT | Quincy | F | 42 | 335 | 12.54% |
| VA | Virginia | F | 56 | 572 | 9.79% |
| VT | Sullivan | M | 10 | 1,083 | 0.92% |
| WA | Agastya | M | 26 | 253 | 10.28% |
| WI | Loretta | F | 41 | 485 | 8.45% |
| WV | Briar | M | 15 | 397 | 3.78% |
| WY | Tate | M | 11 | 1,862 | 0.59% |
Read the percentage with the right denominator
A share of 20% means the state accounts for one fifth of the national records for that exact spelling and sex in the comparison year. It does not mean one fifth of babies in the state received that name. It also is not a per-capita popularity score: assessing whether a name is unusually common locally requires the state’s relevant total as another denominator.
A state’s recorded count should not exceed the corresponding national count when year, sex, spelling, and source coverage align. Privacy suppression does not justify reversing that relationship. Such a result needs investigation of the imported files or aggregation, and is withheld here.
Use local information without inferring identity
State counts can give context when local repetition matters to a family. They cannot identify parents’ ethnicity, religion, or reasons for choosing a name. Smaller counts are also more sensitive to annual changes. Inspect the state history and exact spelling before using one year as a long-term expectation.
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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