Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1990 - 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
1 ➡️
(Org: 1)
(67,477)
0.03 67,477
2 ➡️
(Org: 2)
(55,469)
0.06 55,469
3 ➡️
(Org: 3)
(47,036)
0.05 47,036
4 ➡️
(Org: 4)
(43,484)
0.01 43,484
5 ➡️
(Org: 5)
(34,110)
0.01 34,110
6 ➡️
(Org: 6)
(33,778)
0 33,778
7 ➡️
(Org: 7)
(33,691)
0 33,691
8 ➡️
(Org: 8)
(32,451)
0 32,451
9 ➡️
(Org: 9)
(31,073)
0.01 31,073
10 📈
(Org: 14)
(31,066)
0.1 31,066
11 📈
(Org: 25)
(30,729)
0.39 30,729
12 ➡️
(Org: 12)
(30,574)
0.05 30,574
13 📉
(Org: 10)
(30,337)
0.01 30,337
14 📈
(Org: 17)
(30,157)
0.2 30,157
15 📉
(Org: 11)
(29,340)
0 29,340
16 📉
(Org: 13)
(28,885)
- 28,885
17 📉
(Org: 15)
(25,087)
- 25,087
18 📉
(Org: 16)
(24,957)
0 24,957
19 📈
(Org: 24)
(24,830)
0.22 24,830
20 📈
(Org: 27)
(24,740)
0.32 24,740
21 📉
(Org: 19)
(23,192)
0.04 23,192
22 ➡️
(Org: 22)
(22,947)
0.11 22,947
23 📉
(Org: 18)
(22,728)
0 22,728
24 📉
(Org: 20)
(22,059)
0 22,059
25 📉
(Org: 21)
(21,021)
0.02 21,021
26 📉
(Org: 23)
(20,560)
0.01 20,560
27 📈
(Org: 37)
(19,204)
0.37 19,204
28 📉
(Org: 26)
(18,649)
0.02 18,649
29 ➡️
(Org: 29)
(17,086)
0.06 17,086
30 📈
(Org: 31)
(16,814)
0.08 16,814
31 📉
(Org: 28)
(16,251)
0 16,251
32 📉
(Org: 30)
(15,708)
0 15,708
33 📈
(Org: 44)
(15,602)
0.3 15,602
34 ➡️
(Org: 34)
(15,107)
0.04 15,107
35 📈
(Org: 56)
(14,898)
0.48 14,898
36 📉
(Org: 33)
(14,809)
0.01 14,809
37 📉
(Org: 32)
(14,728)
0 14,728
38 📈
(Org: 43)
(14,700)
0.25 14,700
39 📉
(Org: 35)
(13,599)
0 13,599
40 📈
(Org: 47)
(12,610)
0.15 12,610
41 📈
(Org: 54)
(12,590)
0.36 12,590
42 📉
(Org: 36)
(12,477)
0.01 12,477
43 📉
(Org: 40)
(12,092)
0.03 12,092
44 📉
(Org: 38)
(11,999)
- 11,999
45 📉
(Org: 41)
(11,518)
- 11,518
46 📉
(Org: 42)
(11,469)
0 11,469
47 📉
(Org: 46)
(11,141)
0.04 11,141
48 📉
(Org: 45)
(11,002)
0.01 11,002
49 📉
(Org: 48)
(10,557)
0.15 10,557
50 📉
(Org: 49)
(8,579)
- 8,579
51 📉
(Org: 50)
(8,558)
0.01 8,558
52 📉
(Org: 51)
(8,517)
0.02 8,517
53 📉
(Org: 52)
(8,275)
0 8,275
54 📉
(Org: 53)
(8,170)
0.01 8,170
55 ➡️
(Org: 55)
(8,123)
0.03 8,123
56 📈
(Org: 81)
(7,706)
0.42 7,706
57 📈
(Org: 63)
(7,207)
0.08 7,207
58 📈
(Org: 62)
(7,139)
0.07 7,139
59 📉
(Org: 58)
(7,014)
0 7,014
60 📉
(Org: 59)
(6,973)
0 6,973
61 📉
(Org: 60)
(6,782)
- 6,782
62 📈
(Org: 65)
(6,769)
0.05 6,769
63 📉
(Org: 61)
(6,743)
- 6,743
64 ➡️
(Org: 64)
(6,697)
0.02 6,697
65 📈
(Org: 66)
(6,374)
0.09 6,374
66 📈
(Org: 83)
(6,144)
0.28 6,144
67 📈
(Org: 68)
(5,746)
- 5,746
68 📈
(Org: 73)
(5,727)
0.08 5,727
69 📈
(Org: 70)
(5,563)
0.02 5,563
70 📈
(Org: 76)
(5,359)
0.04 5,359
71 ➡️
(Org: 71)
(5,321)
0 5,321
72 ➡️
(Org: 72)
(5,308)
0 5,308
73 📈
(Org: 74)
(5,247)
0 5,247
74 📈
(Org: 75)
(5,213)
- 5,213
75 📈
(Org: 88)
(4,989)
0.17 4,989
76 📈
(Org: 84)
(4,944)
0.11 4,944
77 ➡️
(Org: 77)
(4,906)
0.01 4,906
78 ➡️
(Org: 78)
(4,879)
0.02 4,879
79 📈
(Org: 89)
(4,784)
0.14 4,784
80 📉
(Org: 79)
(4,651)
0.02 4,651
81 📉
(Org: 80)
(4,516)
0.01 4,516
82 ➡️
(Org: 82)
(4,445)
- 4,445
83 📈
(Org: 85)
(4,430)
0.02 4,430
84 📈
(Org: 99)
(4,399)
0.15 4,399
85 📈
(Org: 93)
(4,394)
0.08 4,394
86 📈
(Org: 87)
(4,177)
- 4,177
87 📈
(Org: 90)
(4,132)
- 4,132
88 📈
(Org: 91)
(4,108)
0 4,108
89 📈
(Org: 92)
(4,079)
0 4,079
90 📈
(Org: 94)
(4,020)
0 4,020
91 📈
(Org: 122)
(4,009)
0.31 4,009
92 📈
(Org: 94)
(4,000)
- 4,000
93 📈
(Org: 98)
(3,957)
0.02 3,957
94 📈
(Org: 97)
(3,899)
- 3,899
95 📈
(Org: 100)
(3,759)
0.02 3,759
96 📈
(Org: 101)
(3,743)
0.01 3,743
97 📈
(Org: 105)
(3,638)
0.06 3,638
98 📈
(Org: 103)
(3,606)
0.02 3,606
99 📈
(Org: 107)
(3,567)
0.07 3,567
100 📈
(Org: 102)
(3,564)
0 3,564