Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2001 - 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)
(32,766)
0.01 32,766
2 ➡️
(Org: 2)
(30,829)
0.04 30,829
3 ➡️
(Org: 3)
(28,097)
0.05 28,097
4 📈
(Org: 6)
(27,478)
0.17 27,478
5 📉
(Org: 4)
(26,184)
0.01 26,184
6 📉
(Org: 5)
(24,899)
0.07 24,899
7 ➡️
(Org: 7)
(22,427)
0 22,427
8 ➡️
(Org: 8)
(22,171)
0.01 22,171
9 📈
(Org: 16)
(21,163)
0.14 21,163
10 📉
(Org: 9)
(21,144)
0.01 21,144
11 📉
(Org: 10)
(20,141)
0 20,141
12 📈
(Org: 23)
(19,949)
0.19 19,949
13 📉
(Org: 11)
(19,744)
0 19,744
14 📈
(Org: 31)
(19,705)
0.36 19,705
15 📉
(Org: 14)
(19,692)
0.04 19,692
16 📉
(Org: 13)
(19,652)
0.02 19,652
17 📉
(Org: 12)
(19,362)
- 19,362
18 ➡️
(Org: 18)
(18,851)
0.05 18,851
19 📈
(Org: 21)
(18,849)
0.12 18,849
20 📉
(Org: 15)
(18,371)
0 18,371
21 📉
(Org: 17)
(18,045)
0 18,045
22 📉
(Org: 19)
(17,112)
0 17,112
23 📉
(Org: 20)
(16,757)
0 16,757
24 📉
(Org: 22)
(16,542)
0.02 16,542
25 📉
(Org: 24)
(15,457)
- 15,457
26 📉
(Org: 25)
(15,180)
0.01 15,180
27 📈
(Org: 46)
(15,134)
0.45 15,134
28 📉
(Org: 26)
(14,951)
0.01 14,951
29 📈
(Org: 37)
(14,549)
0.23 14,549
30 📉
(Org: 27)
(14,483)
0.01 14,483
31 📉
(Org: 28)
(13,544)
0 13,544
32 📈
(Org: 44)
(13,138)
0.35 13,138
33 📉
(Org: 32)
(12,860)
0.02 12,860
34 📈
(Org: 35)
(12,832)
0.1 12,832
35 📉
(Org: 29)
(12,759)
0 12,759
36 📉
(Org: 30)
(12,665)
- 12,665
37 📉
(Org: 33)
(12,658)
0.04 12,658
38 📉
(Org: 34)
(12,142)
- 12,142
39 ➡️
(Org: 39)
(11,571)
0.07 11,571
40 📉
(Org: 36)
(11,345)
0 11,345
41 ➡️
(Org: 41)
(11,098)
0.08 11,098
42 📉
(Org: 38)
(11,086)
0.02 11,086
43 📈
(Org: 49)
(10,904)
0.26 10,904
44 📉
(Org: 40)
(10,607)
0 10,607
45 📈
(Org: 57)
(10,563)
0.32 10,563
46 📈
(Org: 63)
(10,327)
0.36 10,327
47 📉
(Org: 42)
(10,008)
0.05 10,008
48 📉
(Org: 43)
(9,494)
0.1 9,494
49 📉
(Org: 47)
(9,259)
0.11 9,259
50 📉
(Org: 45)
(8,471)
0.02 8,471
51 📉
(Org: 48)
(8,375)
0.03 8,375
52 📉
(Org: 50)
(8,155)
0.02 8,155
53 📉
(Org: 52)
(7,828)
0.04 7,828
54 📈
(Org: 60)
(7,777)
0.12 7,777
55 📉
(Org: 51)
(7,772)
0 7,772
56 📈
(Org: 64)
(7,637)
0.14 7,637
57 📉
(Org: 53)
(7,627)
0.02 7,627
58 📉
(Org: 53)
(7,447)
- 7,447
59 📈
(Org: 114)
(7,311)
0.54 7,311
60 📉
(Org: 55)
(7,283)
- 7,283
61 📉
(Org: 56)
(7,280)
0 7,280
62 📉
(Org: 58)
(6,986)
0 6,986
63 📉
(Org: 59)
(6,842)
- 6,842
64 📈
(Org: 65)
(6,835)
0.06 6,835
65 📉
(Org: 62)
(6,646)
0 6,646
66 📈
(Org: 70)
(6,438)
0.05 6,438
67 ➡️
(Org: 67)
(6,434)
0 6,434
68 📉
(Org: 66)
(6,425)
- 6,425
69 📈
(Org: 71)
(6,390)
0.05 6,390
70 📈
(Org: 125)
(6,321)
0.5 6,321
71 📉
(Org: 68)
(6,233)
0 6,233
72 📈
(Org: 74)
(6,143)
0.07 6,143
73 📈
(Org: 84)
(6,033)
0.21 6,033
74 📈
(Org: 80)
(5,872)
0.14 5,872
75 📉
(Org: 72)
(5,822)
0.01 5,822
76 📉
(Org: 73)
(5,776)
0 5,776
77 📈
(Org: 83)
(5,775)
0.15 5,775
78 📉
(Org: 76)
(5,585)
0.03 5,585
79 📉
(Org: 75)
(5,424)
- 5,424
80 📉
(Org: 79)
(5,412)
0.04 5,412
81 📉
(Org: 77)
(5,386)
0.01 5,386
82 📈
(Org: 176)
(5,290)
0.6 5,290
83 📉
(Org: 78)
(5,286)
0 5,286
84 📉
(Org: 82)
(5,044)
0.02 5,044
85 📉
(Org: 81)
(5,032)
0.01 5,032
86 📈
(Org: 132)
(5,009)
0.4 5,009
87 📈
(Org: 106)
(4,992)
0.27 4,992
88 📈
(Org: 90)
(4,961)
0.15 4,961
89 📈
(Org: 99)
(4,835)
0.2 4,835
90 📉
(Org: 85)
(4,760)
0.01 4,760
91 📉
(Org: 86)
(4,632)
- 4,632
92 📉
(Org: 87)
(4,599)
0.01 4,599
93 📉
(Org: 88)
(4,576)
0 4,576
94 📈
(Org: 127)
(4,553)
0.31 4,553
95 📉
(Org: 92)
(4,518)
0.08 4,518
96 📉
(Org: 89)
(4,416)
0.03 4,416
97 📈
(Org: 119)
(4,354)
0.26 4,354
98 📉
(Org: 90)
(4,222)
- 4,222
99 📉
(Org: 95)
(4,209)
0.06 4,209
100 📈
(Org: 195)
(4,134)
0.55 4,134