Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1986 - 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)
(66,249)
0.03 66,249
2 ➡️
(Org: 2)
(60,039)
0.06 60,039
3 ➡️
(Org: 3)
(48,964)
0.04 48,964
4 ➡️
(Org: 4)
(37,814)
0.01 37,814
5 ➡️
(Org: 5)
(37,187)
0 37,187
6 ➡️
(Org: 6)
(36,916)
0.01 36,916
7 ➡️
(Org: 7)
(34,207)
0 34,207
8 ➡️
(Org: 8)
(33,891)
0 33,891
9 📈
(Org: 10)
(31,753)
0.05 31,753
10 📉
(Org: 9)
(31,361)
0 31,361
11 📈
(Org: 20)
(30,041)
0.3 30,041
12 📈
(Org: 25)
(29,990)
0.4 29,990
13 📉
(Org: 11)
(29,588)
0 29,588
14 📉
(Org: 12)
(29,096)
0.01 29,096
15 📈
(Org: 16)
(28,651)
0.16 28,651
16 📉
(Org: 13)
(28,278)
0.04 28,278
17 📉
(Org: 14)
(26,934)
0.01 26,934
18 📉
(Org: 17)
(24,771)
0.08 24,771
19 📉
(Org: 15)
(24,413)
0 24,413
20 📈
(Org: 22)
(23,516)
0.17 23,516
21 📉
(Org: 18)
(22,982)
0.02 22,982
22 📉
(Org: 19)
(21,965)
0 21,965
23 📈
(Org: 37)
(20,958)
0.44 20,958
24 📉
(Org: 21)
(20,043)
0.01 20,043
25 📉
(Org: 23)
(19,338)
0 19,338
26 📉
(Org: 24)
(18,178)
0 18,178
27 📈
(Org: 32)
(17,969)
0.24 17,969
28 📉
(Org: 26)
(17,709)
0.02 17,709
29 📉
(Org: 27)
(16,920)
0 16,920
30 📉
(Org: 28)
(16,828)
0.03 16,828
31 📉
(Org: 29)
(15,055)
0 15,055
32 📈
(Org: 35)
(14,653)
0.14 14,653
33 📈
(Org: 43)
(14,277)
0.3 14,277
34 📉
(Org: 30)
(13,957)
0.01 13,957
35 📉
(Org: 31)
(13,665)
0 13,665
36 📉
(Org: 33)
(13,151)
0.03 13,151
37 📈
(Org: 38)
(13,027)
0.1 13,027
38 📉
(Org: 34)
(12,639)
0 12,639
39 📈
(Org: 62)
(11,635)
0.5 11,635
40 📉
(Org: 39)
(11,476)
0.01 11,476
41 📈
(Org: 57)
(11,109)
0.38 11,109
42 📉
(Org: 40)
(11,045)
0.01 11,045
43 📉
(Org: 41)
(10,641)
0 10,641
44 📉
(Org: 42)
(10,391)
0.01 10,391
45 📉
(Org: 44)
(10,084)
0.01 10,084
46 📈
(Org: 48)
(9,845)
0.13 9,845
47 📉
(Org: 45)
(9,716)
- 9,716
48 📉
(Org: 46)
(9,645)
0.01 9,645
49 ➡️
(Org: 49)
(8,492)
0 8,492
50 📈
(Org: 70)
(8,480)
0.45 8,480
51 📉
(Org: 50)
(8,460)
0 8,460
52 📉
(Org: 51)
(8,385)
0 8,385
53 ➡️
(Org: 53)
(7,727)
0.05 7,727
54 📉
(Org: 52)
(7,660)
0.01 7,660
55 📈
(Org: 56)
(7,477)
0.07 7,477
56 📉
(Org: 54)
(7,332)
0.04 7,332
57 📈
(Org: 58)
(6,570)
0.07 6,570
58 📈
(Org: 59)
(6,097)
0.01 6,097
59 📈
(Org: 60)
(5,815)
0 5,815
60 📈
(Org: 61)
(5,779)
- 5,779
61 📈
(Org: 63)
(5,279)
- 5,279
62 📈
(Org: 69)
(5,240)
0.1 5,240
63 📈
(Org: 67)
(5,172)
0.05 5,172
64 ➡️
(Org: 64)
(5,118)
0 5,118
65 ➡️
(Org: 65)
(5,076)
- 5,076
66 ➡️
(Org: 66)
(5,067)
0.01 5,067
67 📈
(Org: 71)
(4,662)
- 4,662
68 📈
(Org: 79)
(4,608)
0.13 4,608
69 📈
(Org: 72)
(4,518)
0 4,518
70 📈
(Org: 73)
(4,443)
0.01 4,443
71 📈
(Org: 74)
(4,404)
0.01 4,404
72 📈
(Org: 75)
(4,224)
- 4,224
73 📈
(Org: 83)
(4,204)
0.11 4,204
74 📈
(Org: 76)
(4,089)
- 4,089
75 📈
(Org: 80)
(4,078)
0.04 4,078
76 📈
(Org: 77)
(4,064)
0 4,064
77 📈
(Org: 81)
(3,894)
0 3,894
78 📈
(Org: 82)
(3,816)
0.01 3,816
79 📈
(Org: 85)
(3,797)
0.02 3,797
80 📈
(Org: 84)
(3,726)
0 3,726
81 📈
(Org: 100)
(3,496)
0.17 3,496
82 📈
(Org: 114)
(3,389)
0.28 3,389
83 📈
(Org: 88)
(3,293)
- 3,293
84 📈
(Org: 90)
(3,292)
0.03 3,292
85 📈
(Org: 96)
(3,259)
0.07 3,259
86 📈
(Org: 89)
(3,214)
- 3,214
87 📈
(Org: 91)
(3,183)
0 3,183
88 📈
(Org: 93)
(3,142)
0.02 3,142
89 📈
(Org: 98)
(3,095)
0.04 3,095
90 📈
(Org: 95)
(3,084)
0.01 3,084
91 📈
(Org: 94)
(3,070)
0 3,070
92 📈
(Org: 97)
(2,981)
- 2,981
93 📈
(Org: 99)
(2,943)
- 2,943
94 📈
(Org: 105)
(2,911)
0.08 2,911
95 📈
(Org: 117)
(2,874)
0.17 2,874
96 📈
(Org: 104)
(2,822)
0.04 2,822
97 📈
(Org: 101)
(2,789)
- 2,789
98 📈
(Org: 103)
(2,770)
0.02 2,770
99 📈
(Org: 106)
(2,664)
0 2,664
100 📈
(Org: 107)
(2,648)
- 2,648