101 to 200 Most Popular Boy Baby Names by Pronunciation in the US 1980 - 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
101 📈
(Org: 111)
(2,734)
0.01 2,734
102 📈
(Org: 126)
(2,721)
0.19 2,721
103 📈
(Org: 113)
(2,706)
0.02 2,706
104 📈
(Org: 110)
(2,700)
- 2,700
105 📈
(Org: 112)
(2,671)
- 2,671
106 📈
(Org: 114)
(2,647)
0.01 2,647
107 📈
(Org: 117)
(2,397)
0.03 2,397
108 📈
(Org: 115)
(2,392)
- 2,392
109 📈
(Org: 129)
(2,388)
0.09 2,388
110 📈
(Org: 116)
(2,385)
0.01 2,385
111 📈
(Org: 120)
(2,319)
0.02 2,319
112 📈
(Org: 118)
(2,318)
- 2,318
113 📈
(Org: 173)
(2,286)
0.38 2,286
114 📈
(Org: 161)
(2,282)
0.3 2,282
115 📈
(Org: 125)
(2,279)
0.03 2,279
116 📈
(Org: 121)
(2,266)
- 2,266
117 📈
(Org: 136)
(2,258)
0.1 2,258
118 📈
(Org: 123)
(2,242)
0.01 2,242
119 📈
(Org: 124)
(2,211)
- 2,211
120 📈
(Org: 128)
(2,205)
0.01 2,205
121 📈
(Org: 134)
(2,204)
0.06 2,204
122 📈
(Org: 130)
(2,202)
0.02 2,202
123 📈
(Org: 131)
(2,195)
0.01 2,195
124 📈
(Org: 142)
(2,105)
0.07 2,105
125 📈
(Org: 133)
(2,083)
- 2,083
126 📈
(Org: 135)
(2,070)
- 2,070
127 📈
(Org: 149)
(2,066)
0.13 2,066
128 📈
(Org: 150)
(2,051)
0.12 2,051
129 📈
(Org: 139)
(2,039)
0.02 2,039
130 📈
(Org: 148)
(2,026)
0.1 2,026
131 📈
(Org: 140)
(2,024)
0.02 2,024
132 📈
(Org: 137)
(2,010)
- 2,010
133 📈
(Org: 141)
(1,999)
0.01 1,999
134 📈
(Org: 181)
(1,998)
0.33 1,998
135 📈
(Org: 143)
(1,956)
- 1,956
136 📈
(Org: 151)
(1,949)
0.08 1,949
137 📈
(Org: 182)
(1,929)
0.31 1,929
138 📈
(Org: 144)
(1,903)
- 1,903
139 📈
(Org: 145)
(1,887)
0 1,887
140 📈
(Org: 165)
(1,852)
0.2 1,852
141 📈
(Org: 154)
(1,844)
0.04 1,844
142 📈
(Org: 146)
(1,842)
- 1,842
143 📈
(Org: 147)
(1,833)
0.01 1,833
144 📈
(Org: 152)
(1,812)
0.01 1,812
145 📈
(Org: 155)
(1,794)
0.06 1,794
146 📈
(Org: 153)
(1,792)
0.01 1,792
147 📈
(Org: 162)
(1,752)
0.11 1,752
148 📈
(Org: 216)
(1,742)
0.34 1,742
149 📈
(Org: 167)
(1,740)
0.16 1,740
150 📈
(Org: 160)
(1,721)
0.06 1,721
151 📈
(Org: 163)
(1,715)
0.11 1,715
152 📈
(Org: 158)
(1,704)
0.05 1,704
153 📈
(Org: 156)
(1,680)
- 1,680
154 📈
(Org: 259)
(1,677)
0.49 1,677
155 📈
(Org: 224)
(1,661)
0.36 1,661
156 📈
(Org: 157)
(1,650)
- 1,650
157 📈
(Org: 164)
(1,647)
0.08 1,647
158 📈
(Org: 159)
(1,629)
0 1,629
159 📈
(Org: 180)
(1,620)
0.15 1,620
160 📈
(Org: 190)
(1,610)
0.2 1,610
161 📈
(Org: 204)
(1,586)
0.25 1,586
162 📈
(Org: 209)
(1,580)
0.25 1,580
163 📈
(Org: 192)
(1,560)
0.18 1,560
164 📈
(Org: 213)
(1,516)
0.24 1,516
165 📈
(Org: 177)
(1,492)
0.07 1,492
166 ➡️
(Org: 166)
(1,480)
- 1,480
167 📈
(Org: 203)
(1,471)
0.18 1,471
168 📈
(Org: 170)
(1,468)
0.02 1,468
169 📉
(Org: 167)
(1,462)
- 1,462
170 📉
(Org: 169)
(1,448)
- 1,448
171 📈
(Org: 179)
(1,439)
0.04 1,439
172 ➡️
(Org: 172)
(1,418)
- 1,418
173 📈
(Org: 208)
(1,416)
0.16 1,416
174 📈
(Org: 175)
(1,404)
0.01 1,404
175 ➡️
(Org: 175)
(1,402)
0 1,402
175 📈
(Org: 178)
(1,402)
0.01 1,402
177 📈
(Org: 185)
(1,378)
0.04 1,378
178 📈
(Org: 193)
(1,359)
0.06 1,359
179 📈
(Org: 232)
(1,353)
0.25 1,353
180 📈
(Org: 205)
(1,352)
0.12 1,352
181 📈
(Org: 184)
(1,349)
0.02 1,349
182 📈
(Org: 210)
(1,327)
0.11 1,327
183 📈
(Org: 186)
(1,315)
0.01 1,315
184 📈
(Org: 187)
(1,313)
0.01 1,313
185 📈
(Org: 189)
(1,310)
0.02 1,310
186 📈
(Org: 188)
(1,301)
0 1,301
187 📈
(Org: 195)
(1,299)
0.02 1,299
188 📈
(Org: 194)
(1,288)
0.01 1,288
189 📈
(Org: 190)
(1,287)
- 1,287
190 📈
(Org: 196)
(1,274)
0.01 1,274
191 📈
(Org: 197)
(1,265)
0 1,265
192 📈
(Org: 245)
(1,264)
0.28 1,264
193 📈
(Org: 234)
(1,248)
0.21 1,248
194 📈
(Org: 198)
(1,237)
- 1,237
195 📈
(Org: 214)
(1,225)
0.07 1,225
196 📈
(Org: 199)
(1,224)
- 1,224
197 📈
(Org: 201)
(1,218)
- 1,218
198 📈
(Org: 202)
(1,214)
- 1,214
199 📈
(Org: 206)
(1,207)
0.01 1,207
200 📈
(Org: 211)
(1,201)
0.03 1,201