201 to 300 Most Popular Boy Baby Names by Pronunciation in the US 2020 - Combined Name Rankings

About Distortion Index

The Distortion Index shows how much the ranking might be skewed by alternative spellings of the same pronunciation. A higher index (closer to 1.0) means the main name represents a smaller portion of the total, indicating the ranking could be misleading. A lower index (closer to 0.0) means the main name dominates, making the ranking more accurate.

Low Distortion (0.07): Jayden (1,000) + Zayden (50) + Jaden (30) = Main name dominates
High Distortion (0.91): Jayden (100) + Zayden (800) + Jaden (200) = Alternative spellings dominate
Distortion Index Color Guide:
0.0-0.29 Low Distortion (Green) - Main name dominates
0.3-0.69 Medium Distortion (Orange) - Moderate alternative spellings
0.7-1.0 High Distortion (Red) - Alternative spellings dominate
Rank Adjustment Explanation:

Adjusted Rank: The primary rank shown reflects the combined count of all similar pronunciation names, providing a more accurate representation of the name's true popularity. Original Rank: The rank in parentheses shows the original ranking based on the main name only, before grouping similar pronunciations.

Rank Change Indicators:
📈 Rank improved (moved up)
📉 Rank declined (moved down)
➡️ Rank unchanged

Advanced Pronunciation Algorithm

We've developed a revolutionary pronunciation comparison algorithm that intelligently groups baby names with similar sounds and pronunciations. Our sophisticated system automatically corrects common typos and misspellings, ensuring accurate name grouping based on phonetic similarity rather than just spelling.

This cutting-edge algorithm uses advanced phonetic analysis to identify names that sound alike but may have different spellings, providing you with the most comprehensive and accurate baby name rankings by pronunciation. 💡 Understanding the Distortion Index is crucial for interpreting these results accurately. While our algorithm is highly accurate, if you notice any grouping errors, please let us know and we'll promptly resolve them.

🔍 Intelligent phonetic analysis and grouping
✏️ Automatic typo correction and misspelling detection
🎯 Accurate pronunciation-based name categorization

Boy Names

Ranking Name Distortion Index Count
201 📉
(Org: 197)
(1,935)
0.01 1,935
202 📈
(Org: 239)
(1,930)
0.22 1,930
203 📈
(Org: 287)
(1,912)
0.38 1,912
204 📉
(Org: 199)
(1,911)
- 1,911
205 📈
(Org: 214)
(1,910)
0.08 1,910
206 📈
(Org: 207)
(1,904)
0.03 1,904
206 📉
(Org: 200)
(1,904)
- 1,904
208 📈
(Org: 221)
(1,888)
0.11 1,888
209 📈
(Org: 363)
(1,884)
0.54 1,884
210 📉
(Org: 205)
(1,863)
- 1,863
211 📉
(Org: 206)
(1,861)
- 1,861
212 📈
(Org: 442)
(1,841)
0.63 1,841
213 📉
(Org: 210)
(1,836)
0.01 1,836
214 📉
(Org: 209)
(1,829)
0.01 1,829
215 📉
(Org: 208)
(1,826)
- 1,826
216 📈
(Org: 334)
(1,822)
0.46 1,822
217 ➡️
(Org: 217)
(1,821)
0.04 1,821
218 📈
(Org: 309)
(1,795)
0.41 1,795
219 📉
(Org: 211)
(1,794)
- 1,794
220 📈
(Org: 295)
(1,793)
0.36 1,793
221 📉
(Org: 212)
(1,792)
- 1,792
222 📉
(Org: 213)
(1,771)
- 1,771
223 📉
(Org: 215)
(1,770)
0 1,770
224 📈
(Org: 236)
(1,739)
0.12 1,739
225 📈
(Org: 235)
(1,738)
0.11 1,738
226 📈
(Org: 233)
(1,725)
0.08 1,725
227 📈
(Org: 337)
(1,720)
0.44 1,720
228 📈
(Org: 232)
(1,710)
0.06 1,710
229 📈
(Org: 316)
(1,709)
0.39 1,709
230 📈
(Org: 237)
(1,707)
0.1 1,707
231 📉
(Org: 220)
(1,706)
0 1,706
232 📉
(Org: 219)
(1,705)
- 1,705
233 📈
(Org: 260)
(1,698)
0.21 1,698
234 📉
(Org: 223)
(1,695)
0.01 1,695
235 📈
(Org: 246)
(1,686)
0.16 1,686
236 📈
(Org: 244)
(1,684)
0.13 1,684
237 📉
(Org: 225)
(1,681)
0.01 1,681
238 📉
(Org: 226)
(1,659)
- 1,659
239 📉
(Org: 229)
(1,657)
0.02 1,657
240 📉
(Org: 234)
(1,656)
0.05 1,656
241 📉
(Org: 227)
(1,653)
0 1,653
242 📉
(Org: 228)
(1,646)
- 1,646
243 📉
(Org: 230)
(1,633)
0.01 1,633
244 📈
(Org: 308)
(1,613)
0.34 1,613
245 📈
(Org: 319)
(1,611)
0.36 1,611
246 📉
(Org: 245)
(1,609)
0.1 1,609
247 📉
(Org: 238)
(1,601)
0.04 1,601
248 📈
(Org: 286)
(1,600)
0.26 1,600
249 📉
(Org: 241)
(1,599)
0.07 1,599
250 📈
(Org: 305)
(1,596)
0.32 1,596
251 📈
(Org: 257)
(1,555)
0.12 1,555
252 📈
(Org: 418)
(1,546)
0.54 1,546
253 📈
(Org: 297)
(1,538)
0.26 1,538
254 📈
(Org: 352)
(1,513)
0.41 1,513
255 📉
(Org: 240)
(1,500)
- 1,500
256 📉
(Org: 243)
(1,490)
0.01 1,490
257 📈
(Org: 274)
(1,488)
0.17 1,488
258 📉
(Org: 248)
(1,457)
0.03 1,457
259 📈
(Org: 332)
(1,445)
0.32 1,445
260 📈
(Org: 454)
(1,436)
0.55 1,436
261 📉
(Org: 249)
(1,420)
0.01 1,420
262 📉
(Org: 250)
(1,407)
- 1,407
263 📉
(Org: 252)
(1,406)
0 1,406
263 📉
(Org: 251)
(1,406)
- 1,406
265 📈
(Org: 303)
(1,387)
0.21 1,387
266 📉
(Org: 254)
(1,386)
- 1,386
267 📈
(Org: 278)
(1,350)
0.1 1,350
268 📈
(Org: 292)
(1,339)
0.13 1,339
269 📉
(Org: 261)
(1,328)
- 1,328
270 📉
(Org: 264)
(1,327)
0.03 1,327
271 📈
(Org: 556)
(1,323)
0.62 1,323
272 📈
(Org: 451)
(1,309)
0.5 1,309
273 📉
(Org: 262)
(1,301)
- 1,301
273 ➡️
(Org: 273)
(1,301)
0.05 1,301
275 📈
(Org: 283)
(1,300)
0.08 1,300
276 📈
(Org: 346)
(1,297)
0.29 1,297
277 📉
(Org: 263)
(1,292)
- 1,292
278 📉
(Org: 268)
(1,286)
0.01 1,286
279 📉
(Org: 270)
(1,269)
0.01 1,269
280 📉
(Org: 269)
(1,266)
- 1,266
280 📈
(Org: 403)
(1,266)
0.41 1,266
282 📈
(Org: 302)
(1,264)
0.13 1,264
283 📈
(Org: 289)
(1,257)
0.07 1,257
284 📈
(Org: 451)
(1,252)
0.47 1,252
285 📈
(Org: 290)
(1,251)
0.06 1,251
286 📉
(Org: 272)
(1,240)
- 1,240
287 📉
(Org: 274)
(1,236)
0 1,236
288 📉
(Org: 276)
(1,229)
- 1,229
289 📉
(Org: 279)
(1,217)
0.01 1,217
290 📈
(Org: 356)
(1,196)
0.27 1,196
290 📈
(Org: 293)
(1,196)
0.02 1,196
292 📉
(Org: 282)
(1,192)
- 1,192
293 📉
(Org: 288)
(1,187)
0.01 1,187
294 📈
(Org: 309)
(1,166)
0.09 1,166
295 📈
(Org: 296)
(1,155)
0.01 1,155
296 📈
(Org: 312)
(1,148)
0.08 1,148
297 📈
(Org: 351)
(1,131)
0.2 1,131
298 📈
(Org: 299)
(1,119)
- 1,119
299 📈
(Org: 315)
(1,110)
0.05 1,110
299 📈
(Org: 301)
(1,110)
- 1,110