Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1947 - 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)
(94,763)
- 94,763
2 ➡️
(Org: 2)
(91,662)
0 91,662
3 ➡️
(Org: 3)
(90,682)
0.03 90,682
4 ➡️
(Org: 4)
(67,031)
0 67,031
5 ➡️
(Org: 5)
(58,541)
0 58,541
6 ➡️
(Org: 6)
(57,814)
0 57,814
7 ➡️
(Org: 7)
(52,221)
0.03 52,221
8 ➡️
(Org: 8)
(45,028)
0 45,028
9 ➡️
(Org: 9)
(40,792)
0 40,792
10 ➡️
(Org: 10)
(35,009)
0 35,009
11 ➡️
(Org: 11)
(34,957)
0 34,957
12 ➡️
(Org: 12)
(30,110)
0 30,110
13 📈
(Org: 21)
(28,857)
0.47 28,857
14 📉
(Org: 13)
(28,260)
- 28,260
15 📉
(Org: 14)
(27,714)
0.01 27,714
16 📉
(Org: 15)
(24,597)
0 24,597
17 ➡️
(Org: 17)
(24,189)
0.02 24,189
18 📉
(Org: 16)
(23,939)
0 23,939
19 📉
(Org: 18)
(22,814)
0 22,814
20 📉
(Org: 19)
(20,539)
- 20,539
21 📉
(Org: 20)
(19,202)
0.02 19,202
22 ➡️
(Org: 22)
(15,322)
0.01 15,322
23 ➡️
(Org: 23)
(14,000)
0 14,000
24 📈
(Org: 25)
(13,406)
0.05 13,406
25 📈
(Org: 26)
(12,756)
0 12,756
26 📈
(Org: 27)
(12,357)
0 12,357
27 📈
(Org: 28)
(11,382)
0.06 11,382
28 📈
(Org: 57)
(11,050)
0.44 11,050
29 📈
(Org: 32)
(10,610)
0.1 10,610
30 📉
(Org: 29)
(10,524)
- 10,524
31 📈
(Org: 44)
(10,502)
0.25 10,502
32 📉
(Org: 30)
(10,174)
0 10,174
33 📉
(Org: 31)
(10,000)
0.01 10,000
34 📉
(Org: 33)
(9,352)
0 9,352
35 📈
(Org: 40)
(9,219)
0.13 9,219
36 📉
(Org: 34)
(9,217)
- 9,217
37 📉
(Org: 35)
(8,921)
0 8,921
38 📈
(Org: 47)
(8,834)
0.12 8,834
39 📈
(Org: 61)
(8,712)
0.3 8,712
40 📉
(Org: 36)
(8,597)
0 8,597
41 📉
(Org: 37)
(8,533)
0 8,533
42 📉
(Org: 39)
(8,371)
0.04 8,371
43 📉
(Org: 38)
(8,313)
0.01 8,313
44 📉
(Org: 42)
(8,027)
0 8,027
45 📉
(Org: 41)
(8,014)
- 8,014
46 📉
(Org: 43)
(7,934)
0 7,934
47 📉
(Org: 46)
(7,848)
0.01 7,848
48 📉
(Org: 45)
(7,823)
- 7,823
49 📉
(Org: 48)
(7,614)
0.01 7,614
50 📉
(Org: 49)
(7,561)
0.02 7,561
51 📉
(Org: 50)
(7,389)
- 7,389
52 📉
(Org: 51)
(7,286)
0.05 7,286
53 📈
(Org: 70)
(7,227)
0.29 7,227
54 📈
(Org: 66)
(7,185)
0.21 7,185
55 📉
(Org: 52)
(6,747)
- 6,747
56 📉
(Org: 53)
(6,662)
0.01 6,662
57 📉
(Org: 54)
(6,523)
0 6,523
58 📉
(Org: 55)
(6,462)
- 6,462
59 📉
(Org: 56)
(6,392)
- 6,392
60 ➡️
(Org: 60)
(6,369)
0.04 6,369
61 📉
(Org: 58)
(6,231)
- 6,231
62 📉
(Org: 59)
(6,198)
0 6,198
63 📈
(Org: 64)
(6,164)
0.06 6,164
64 📉
(Org: 62)
(6,061)
- 6,061
65 📉
(Org: 63)
(5,977)
0.01 5,977
66 📈
(Org: 78)
(5,788)
0.2 5,788
67 📈
(Org: 75)
(5,768)
0.17 5,768
68 📉
(Org: 65)
(5,750)
- 5,750
69 📉
(Org: 68)
(5,524)
0.01 5,524
70 📉
(Org: 67)
(5,521)
0 5,521
71 📉
(Org: 69)
(5,472)
0.04 5,472
72 📉
(Org: 70)
(5,323)
0.03 5,323
73 📉
(Org: 72)
(5,145)
0.01 5,145
74 📉
(Org: 73)
(5,075)
- 5,075
75 📈
(Org: 76)
(4,681)
- 4,681
76 📈
(Org: 80)
(4,680)
0.05 4,680
77 ➡️
(Org: 77)
(4,640)
- 4,640
78 📈
(Org: 79)
(4,609)
0 4,609
79 📈
(Org: 81)
(4,417)
0 4,417
80 📈
(Org: 83)
(4,394)
0.03 4,394
81 📈
(Org: 82)
(4,346)
- 4,346
82 📈
(Org: 85)
(4,268)
0.02 4,268
83 📈
(Org: 84)
(4,264)
0.01 4,264
84 📈
(Org: 86)
(4,152)
0.04 4,152
85 📈
(Org: 95)
(4,101)
0.16 4,101
86 📈
(Org: 87)
(3,950)
0.01 3,950
87 📈
(Org: 88)
(3,920)
- 3,920
88 📈
(Org: 107)
(3,825)
0.28 3,825
89 📈
(Org: 92)
(3,781)
0.03 3,781
90 📉
(Org: 89)
(3,773)
- 3,773
91 📉
(Org: 90)
(3,724)
- 3,724
92 📉
(Org: 91)
(3,712)
0.01 3,712
93 ➡️
(Org: 93)
(3,687)
0.01 3,687
94 ➡️
(Org: 94)
(3,564)
- 3,564
95 📈
(Org: 96)
(3,417)
- 3,417
96 📈
(Org: 97)
(3,406)
0.01 3,406
97 📈
(Org: 98)
(3,347)
- 3,347
98 📈
(Org: 99)
(3,132)
0.03 3,132
99 📈
(Org: 106)
(3,052)
0.09 3,052
99 📈
(Org: 103)
(3,052)
0.05 3,052