Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1987 - 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)
(65,767)
0.03 65,767
2 ➡️
(Org: 2)
(57,775)
0.06 57,775
3 ➡️
(Org: 3)
(48,640)
0.04 48,640
4 ➡️
(Org: 4)
(40,270)
0.01 40,270
5 ➡️
(Org: 5)
(36,830)
0 36,830
6 ➡️
(Org: 6)
(36,237)
0 36,237
7 ➡️
(Org: 7)
(36,197)
0.01 36,197
8 ➡️
(Org: 8)
(32,802)
0 32,802
9 ➡️
(Org: 9)
(31,870)
0.01 31,870
10 📈
(Org: 11)
(31,105)
0.05 31,105
11 📉
(Org: 10)
(30,247)
0 30,247
12 📈
(Org: 25)
(29,320)
0.39 29,320
13 📈
(Org: 20)
(29,299)
0.3 29,299
14 📉
(Org: 12)
(28,794)
0.01 28,794
15 📉
(Org: 13)
(28,558)
0 28,558
16 📈
(Org: 18)
(27,888)
0.17 27,888
17 📉
(Org: 14)
(25,891)
0.04 25,891
18 📉
(Org: 16)
(25,316)
0.08 25,316
19 📈
(Org: 21)
(24,401)
0.17 24,401
20 📉
(Org: 15)
(24,289)
0 24,289
21 📉
(Org: 17)
(23,128)
0 23,128
22 📉
(Org: 19)
(20,554)
0.01 20,554
23 ➡️
(Org: 23)
(19,894)
0.03 19,894
24 📉
(Org: 22)
(19,888)
0 19,888
25 📈
(Org: 40)
(19,564)
0.41 19,564
26 📉
(Org: 24)
(18,470)
0.02 18,470
27 📈
(Org: 32)
(17,742)
0.24 17,742
28 📉
(Org: 26)
(17,430)
0 17,430
29 📉
(Org: 27)
(16,953)
0 16,953
30 📉
(Org: 28)
(15,070)
0.01 15,070
31 📉
(Org: 29)
(14,936)
0.03 14,936
32 📈
(Org: 33)
(14,672)
0.1 14,672
33 📉
(Org: 30)
(14,448)
0 14,448
34 📉
(Org: 31)
(14,331)
0 14,331
35 📈
(Org: 45)
(14,195)
0.3 14,195
36 ➡️
(Org: 36)
(13,969)
0.14 13,969
37 📈
(Org: 57)
(13,443)
0.52 13,443
38 📉
(Org: 34)
(13,123)
0.03 13,123
39 📈
(Org: 54)
(12,844)
0.36 12,844
40 📉
(Org: 35)
(12,186)
0 12,186
41 📉
(Org: 37)
(11,876)
0 11,876
42 📉
(Org: 39)
(11,678)
0.01 11,678
43 📉
(Org: 41)
(11,218)
0.01 11,218
44 📉
(Org: 42)
(10,410)
0 10,410
45 📉
(Org: 43)
(10,306)
0.01 10,306
46 📉
(Org: 44)
(10,189)
0.01 10,189
47 📉
(Org: 46)
(9,712)
0 9,712
48 📈
(Org: 49)
(9,396)
0.08 9,396
49 📈
(Org: 55)
(9,356)
0.15 9,356
50 📉
(Org: 47)
(9,240)
0.01 9,240
51 📈
(Org: 52)
(8,859)
0.05 8,859
52 📈
(Org: 68)
(8,751)
0.45 8,751
53 📉
(Org: 48)
(8,748)
0 8,748
54 📉
(Org: 50)
(8,663)
0.01 8,663
55 📉
(Org: 53)
(8,366)
0 8,366
56 ➡️
(Org: 56)
(7,203)
0.04 7,203
57 📈
(Org: 58)
(6,686)
0.07 6,686
58 📈
(Org: 60)
(6,049)
0 6,049
59 📈
(Org: 61)
(5,911)
- 5,911
60 📈
(Org: 63)
(5,703)
0.01 5,703
61 📈
(Org: 65)
(5,581)
0.05 5,581
62 📈
(Org: 64)
(5,573)
0 5,573
63 📈
(Org: 66)
(4,976)
- 4,976
64 📈
(Org: 71)
(4,966)
0.11 4,966
65 📈
(Org: 67)
(4,950)
- 4,950
66 📈
(Org: 69)
(4,816)
0.01 4,816
67 📈
(Org: 70)
(4,501)
- 4,501
68 📈
(Org: 82)
(4,493)
0.13 4,493
69 📈
(Org: 80)
(4,479)
0.12 4,479
70 📈
(Org: 72)
(4,439)
0 4,439
71 📈
(Org: 76)
(4,192)
0.02 4,192
72 📈
(Org: 77)
(4,162)
0.02 4,162
73 ➡️
(Org: 73)
(4,153)
- 4,153
74 📈
(Org: 75)
(4,152)
0 4,152
75 📉
(Org: 74)
(4,148)
- 4,148
76 📈
(Org: 81)
(4,026)
0.03 4,026
77 📈
(Org: 79)
(4,008)
0 4,008
78 📈
(Org: 83)
(3,876)
0 3,876
79 📈
(Org: 85)
(3,846)
0.01 3,846
80 📈
(Org: 100)
(3,563)
0.18 3,563
81 📈
(Org: 92)
(3,530)
0.08 3,530
82 📈
(Org: 88)
(3,522)
0.04 3,522
83 📈
(Org: 87)
(3,499)
0 3,499
84 📈
(Org: 93)
(3,357)
0.04 3,357
85 📈
(Org: 89)
(3,338)
- 3,338
86 📈
(Org: 90)
(3,324)
- 3,324
87 📈
(Org: 96)
(3,319)
0.05 3,319
88 📈
(Org: 91)
(3,307)
- 3,307
89 📈
(Org: 95)
(3,221)
0.01 3,221
90 📈
(Org: 101)
(3,152)
0.09 3,152
91 📈
(Org: 97)
(3,124)
- 3,124
92 📈
(Org: 99)
(3,110)
0.01 3,110
93 📈
(Org: 98)
(3,109)
0.01 3,109
94 📈
(Org: 126)
(3,106)
0.28 3,106
95 📈
(Org: 113)
(3,037)
0.15 3,037
96 📈
(Org: 134)
(2,950)
0.29 2,950
97 📈
(Org: 107)
(2,875)
0.04 2,875
98 📈
(Org: 102)
(2,846)
- 2,846
99 📈
(Org: 103)
(2,843)
0 2,843
100 📈
(Org: 115)
(2,837)
0.12 2,837