Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1995 - 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)
(42,800)
0.03 42,800
2 📈
(Org: 3)
(34,766)
0.06 34,766
3 📉
(Org: 2)
(34,509)
0.05 34,509
4 📈
(Org: 6)
(32,802)
0.11 32,802
5 📉
(Org: 4)
(31,211)
0 31,211
6 📉
(Org: 5)
(30,900)
0.01 30,900
7 ➡️
(Org: 7)
(29,823)
0.02 29,823
8 ➡️
(Org: 8)
(28,043)
0.04 28,043
9 ➡️
(Org: 9)
(26,900)
0.01 26,900
10 📈
(Org: 14)
(26,675)
0.13 26,675
11 📉
(Org: 10)
(26,456)
0.02 26,456
12 📉
(Org: 11)
(25,858)
- 25,858
13 📉
(Org: 12)
(25,503)
0.01 25,503
14 📉
(Org: 13)
(24,297)
0.04 24,297
15 ➡️
(Org: 15)
(23,172)
0 23,172
16 ➡️
(Org: 16)
(23,051)
0 23,051
17 ➡️
(Org: 17)
(22,795)
0 22,795
18 📈
(Org: 23)
(22,716)
0.2 22,716
19 📉
(Org: 18)
(21,945)
0.02 21,945
20 📉
(Org: 19)
(20,482)
- 20,482
21 📉
(Org: 20)
(20,187)
0 20,187
22 📉
(Org: 21)
(19,491)
0 19,491
23 📉
(Org: 22)
(18,592)
0 18,592
24 📈
(Org: 32)
(17,585)
0.29 17,585
25 📈
(Org: 26)
(17,390)
0.1 17,390
26 📈
(Org: 37)
(17,234)
0.38 17,234
27 📉
(Org: 24)
(16,784)
0 16,784
28 📈
(Org: 36)
(16,776)
0.34 16,776
29 📉
(Org: 25)
(16,045)
0.01 16,045
30 📈
(Org: 39)
(15,892)
0.35 15,892
31 📈
(Org: 34)
(15,279)
0.21 15,279
32 📉
(Org: 27)
(14,656)
0.03 14,656
33 📉
(Org: 29)
(14,384)
0.06 14,384
34 📉
(Org: 30)
(13,875)
0.04 13,875
35 📉
(Org: 28)
(13,812)
- 13,812
36 📉
(Org: 31)
(12,852)
0.01 12,852
37 📈
(Org: 45)
(12,777)
0.36 12,777
38 📉
(Org: 33)
(12,558)
0.01 12,558
39 📉
(Org: 35)
(11,780)
- 11,780
40 📉
(Org: 38)
(10,511)
0 10,511
41 📉
(Org: 40)
(9,807)
0 9,807
42 📉
(Org: 41)
(9,544)
0.06 9,544
43 📈
(Org: 55)
(9,127)
0.27 9,127
44 📈
(Org: 74)
(8,900)
0.44 8,900
45 📉
(Org: 42)
(8,784)
- 8,784
46 📉
(Org: 43)
(8,742)
0.01 8,742
47 📉
(Org: 46)
(8,678)
0.14 8,678
48 📉
(Org: 44)
(8,478)
- 8,478
49 📈
(Org: 52)
(8,247)
0.16 8,247
50 📈
(Org: 54)
(8,105)
0.18 8,105
51 📈
(Org: 64)
(7,730)
0.26 7,730
52 📉
(Org: 49)
(7,675)
0.08 7,675
53 📉
(Org: 47)
(7,456)
0 7,456
54 📈
(Org: 83)
(7,414)
0.4 7,414
55 📉
(Org: 48)
(7,300)
0.03 7,300
56 📉
(Org: 50)
(6,982)
- 6,982
57 📉
(Org: 51)
(6,965)
0 6,965
58 📉
(Org: 56)
(6,833)
0.04 6,833
59 📉
(Org: 53)
(6,715)
- 6,715
60 📉
(Org: 59)
(6,552)
0.06 6,552
61 📉
(Org: 58)
(6,483)
0.04 6,483
62 📈
(Org: 63)
(6,383)
0.08 6,383
63 📉
(Org: 61)
(6,256)
0.04 6,256
64 📉
(Org: 60)
(6,098)
0 6,098
65 📉
(Org: 62)
(6,044)
0.02 6,044
66 📉
(Org: 65)
(5,809)
0.02 5,809
67 ➡️
(Org: 67)
(5,765)
0.03 5,765
68 📈
(Org: 69)
(5,718)
0.03 5,718
69 📉
(Org: 66)
(5,602)
- 5,602
70 📉
(Org: 68)
(5,545)
- 5,545
71 📈
(Org: 80)
(5,458)
0.14 5,458
72 📉
(Org: 71)
(5,418)
0 5,418
73 📉
(Org: 72)
(5,242)
0 5,242
74 📈
(Org: 134)
(5,238)
0.5 5,238
75 📈
(Org: 79)
(5,118)
0.07 5,118
76 📈
(Org: 78)
(5,042)
0.06 5,042
77 📉
(Org: 75)
(4,948)
0 4,948
78 📉
(Org: 76)
(4,908)
- 4,908
79 📉
(Org: 77)
(4,842)
0 4,842
80 📈
(Org: 82)
(4,713)
0.02 4,713
81 📈
(Org: 91)
(4,683)
0.13 4,683
82 📉
(Org: 81)
(4,648)
- 4,648
83 📈
(Org: 84)
(4,526)
0.02 4,526
84 📈
(Org: 85)
(4,362)
0.01 4,362
85 📈
(Org: 137)
(4,348)
0.42 4,348
86 📈
(Org: 98)
(4,340)
0.11 4,340
87 📈
(Org: 105)
(4,328)
0.17 4,328
88 📉
(Org: 87)
(4,323)
0.03 4,323
89 📉
(Org: 86)
(4,320)
- 4,320
90 📉
(Org: 88)
(4,143)
- 4,143
91 📈
(Org: 92)
(4,130)
0.01 4,130
92 📉
(Org: 89)
(4,124)
0 4,124
93 📉
(Org: 90)
(4,096)
- 4,096
94 📈
(Org: 95)
(4,088)
0.04 4,088
95 📉
(Org: 93)
(4,034)
0.01 4,034
96 📈
(Org: 109)
(3,994)
0.13 3,994
97 📉
(Org: 94)
(3,993)
0.01 3,993
98 📈
(Org: 106)
(3,955)
0.1 3,955
99 📈
(Org: 103)
(3,928)
0.08 3,928
100 📉
(Org: 96)
(3,911)
- 3,911