Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2002 - 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)
(30,751)
0.01 30,751
2 ➡️
(Org: 2)
(29,327)
0.04 29,327
3 📈
(Org: 4)
(26,298)
0.04 26,298
4 📉
(Org: 3)
(26,160)
0.01 26,160
5 📈
(Org: 9)
(25,918)
0.17 25,918
6 📈
(Org: 8)
(23,446)
0.07 23,446
7 📉
(Org: 5)
(22,202)
0 22,202
8 📉
(Org: 7)
(22,046)
0.01 22,046
9 📉
(Org: 6)
(22,036)
- 22,036
10 ➡️
(Org: 10)
(21,501)
0.01 21,501
11 📈
(Org: 28)
(20,449)
0.35 20,449
12 📉
(Org: 11)
(20,161)
0 20,161
13 📉
(Org: 12)
(19,595)
0 19,595
14 📈
(Org: 19)
(19,371)
0.14 19,371
15 📈
(Org: 21)
(19,078)
0.19 19,078
16 📉
(Org: 13)
(18,704)
- 18,704
17 📉
(Org: 14)
(18,575)
0.02 18,575
18 📉
(Org: 17)
(18,273)
0.04 18,273
19 📉
(Org: 15)
(17,750)
0 17,750
20 📉
(Org: 16)
(17,745)
0 17,745
21 📉
(Org: 20)
(17,114)
0.05 17,114
22 📉
(Org: 18)
(17,008)
0 17,008
23 ➡️
(Org: 23)
(16,876)
0.12 16,876
24 📈
(Org: 51)
(15,646)
0.48 15,646
25 📉
(Org: 22)
(15,223)
0.02 15,223
26 📈
(Org: 35)
(15,156)
0.23 15,156
27 📉
(Org: 26)
(14,759)
0.01 14,759
28 📉
(Org: 25)
(14,716)
0.01 14,716
29 📉
(Org: 24)
(14,596)
- 14,596
30 📉
(Org: 27)
(13,634)
0.01 13,634
31 📉
(Org: 29)
(13,019)
0 13,019
32 📉
(Org: 30)
(12,868)
- 12,868
33 📈
(Org: 52)
(12,502)
0.37 12,502
34 📉
(Org: 33)
(12,300)
0.02 12,300
35 📉
(Org: 32)
(12,221)
0.01 12,221
36 📉
(Org: 31)
(12,130)
0 12,130
37 📉
(Org: 34)
(12,031)
- 12,031
38 📉
(Org: 37)
(11,871)
0.06 11,871
39 📉
(Org: 36)
(11,831)
0.05 11,831
40 📉
(Org: 39)
(11,594)
0.11 11,594
41 📈
(Org: 47)
(11,340)
0.26 11,340
42 📉
(Org: 38)
(11,085)
- 11,085
43 📉
(Org: 42)
(10,999)
0.09 10,999
44 📈
(Org: 59)
(10,342)
0.32 10,342
45 📉
(Org: 41)
(10,219)
0.02 10,219
46 📉
(Org: 40)
(10,095)
0 10,095
47 📈
(Org: 87)
(9,998)
0.53 9,998
48 📉
(Org: 45)
(9,802)
0.09 9,802
49 📈
(Org: 68)
(9,571)
0.35 9,571
50 ➡️
(Org: 50)
(9,515)
0.14 9,515
51 📉
(Org: 43)
(9,442)
0.05 9,442
52 📉
(Org: 48)
(9,380)
0.11 9,380
53 📉
(Org: 44)
(9,255)
0.03 9,255
54 📉
(Org: 46)
(8,864)
0.02 8,864
55 📉
(Org: 49)
(8,199)
0 8,199
56 📉
(Org: 53)
(8,066)
0.02 8,066
57 📉
(Org: 54)
(7,819)
- 7,819
58 📉
(Org: 55)
(7,778)
0 7,778
59 📉
(Org: 57)
(7,731)
0.05 7,731
60 📉
(Org: 56)
(7,405)
0 7,405
61 📉
(Org: 58)
(7,208)
- 7,208
62 📉
(Org: 61)
(6,985)
0 6,985
63 📉
(Org: 60)
(6,954)
- 6,954
63 📈
(Org: 71)
(6,954)
0.15 6,954
65 📉
(Org: 63)
(6,845)
0.01 6,845
66 📈
(Org: 83)
(6,815)
0.29 6,815
67 ➡️
(Org: 67)
(6,774)
0.06 6,774
68 📈
(Org: 138)
(6,664)
0.58 6,664
69 📉
(Org: 65)
(6,592)
- 6,592
70 📉
(Org: 69)
(6,501)
0.07 6,501
71 📉
(Org: 66)
(6,370)
- 6,370
72 📈
(Org: 75)
(6,321)
0.15 6,321
73 📈
(Org: 116)
(6,224)
0.47 6,224
74 📈
(Org: 153)
(6,043)
0.57 6,043
75 📉
(Org: 70)
(6,032)
0 6,032
76 📉
(Org: 72)
(5,753)
0 5,753
77 📉
(Org: 74)
(5,740)
0.05 5,740
78 📉
(Org: 73)
(5,684)
- 5,684
79 📉
(Org: 76)
(5,388)
0.01 5,388
80 📉
(Org: 78)
(5,352)
0.02 5,352
81 📉
(Org: 77)
(5,322)
- 5,322
81 📈
(Org: 93)
(5,322)
0.21 5,322
83 📉
(Org: 81)
(5,260)
0.04 5,260
84 📈
(Org: 90)
(5,247)
0.16 5,247
85 📉
(Org: 80)
(5,192)
0.01 5,192
86 📉
(Org: 79)
(5,189)
0.01 5,189
87 📉
(Org: 84)
(5,126)
0.06 5,126
88 📉
(Org: 82)
(5,084)
0.04 5,084
89 📈
(Org: 91)
(5,068)
0.14 5,068
90 📉
(Org: 85)
(4,767)
0.01 4,767
91 📈
(Org: 139)
(4,763)
0.41 4,763
92 📉
(Org: 86)
(4,720)
- 4,720
93 📉
(Org: 89)
(4,682)
0.01 4,682
94 📉
(Org: 88)
(4,653)
0 4,653
95 📈
(Org: 96)
(4,534)
0.09 4,534
96 📈
(Org: 97)
(4,410)
0.08 4,410
97 📉
(Org: 92)
(4,368)
0 4,368
98 📈
(Org: 99)
(4,306)
0.08 4,306
99 📈
(Org: 145)
(4,298)
0.38 4,298
100 📉
(Org: 95)
(4,295)
0.03 4,295