Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1946 - 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)
(87,436)
- 87,436
2 ➡️
(Org: 2)
(84,145)
0 84,145
3 ➡️
(Org: 3)
(81,466)
0.03 81,466
4 ➡️
(Org: 4)
(60,064)
0 60,064
5 ➡️
(Org: 5)
(58,885)
0 58,885
6 ➡️
(Org: 6)
(46,449)
0 46,449
7 ➡️
(Org: 7)
(42,498)
0.03 42,498
8 ➡️
(Org: 8)
(39,049)
0 39,049
9 ➡️
(Org: 9)
(38,224)
0 38,224
10 ➡️
(Org: 10)
(31,913)
0 31,913
11 ➡️
(Org: 11)
(28,539)
0 28,539
12 ➡️
(Org: 12)
(26,978)
0 26,978
13 ➡️
(Org: 13)
(26,271)
- 26,271
14 ➡️
(Org: 14)
(24,427)
0.01 24,427
15 ➡️
(Org: 15)
(22,052)
0 22,052
16 📈
(Org: 17)
(21,894)
0.02 21,894
17 📉
(Org: 16)
(21,610)
0 21,610
18 ➡️
(Org: 18)
(21,077)
0 21,077
19 📈
(Org: 24)
(20,711)
0.43 20,711
20 📉
(Org: 19)
(18,585)
- 18,585
21 📉
(Org: 20)
(17,930)
0.02 17,930
22 📈
(Org: 23)
(13,056)
0.05 13,056
23 📉
(Org: 21)
(12,968)
0.01 12,968
24 📉
(Org: 22)
(12,667)
- 12,667
25 ➡️
(Org: 25)
(11,303)
0 11,303
26 ➡️
(Org: 26)
(10,692)
0 10,692
27 ➡️
(Org: 27)
(10,619)
0.06 10,619
28 📈
(Org: 42)
(9,729)
0.27 9,729
29 📈
(Org: 31)
(9,476)
0.1 9,476
30 📈
(Org: 61)
(8,885)
0.43 8,885
31 📉
(Org: 29)
(8,824)
0 8,824
32 📉
(Org: 30)
(8,668)
- 8,668
33 📉
(Org: 32)
(8,459)
- 8,459
34 ➡️
(Org: 34)
(8,425)
0.01 8,425
35 📈
(Org: 39)
(8,405)
0.12 8,405
36 📉
(Org: 33)
(8,397)
0 8,397
37 📈
(Org: 54)
(7,921)
0.28 7,921
38 📉
(Org: 35)
(7,851)
0.01 7,851
39 📉
(Org: 36)
(7,598)
0.01 7,598
40 📉
(Org: 37)
(7,553)
0 7,553
41 📉
(Org: 38)
(7,489)
0 7,489
42 📉
(Org: 40)
(7,371)
0 7,371
43 📉
(Org: 41)
(7,347)
0 7,347
44 📈
(Org: 45)
(7,076)
0.05 7,076
45 📉
(Org: 43)
(6,982)
0.01 6,982
46 ➡️
(Org: 46)
(6,930)
0.04 6,930
47 📉
(Org: 44)
(6,771)
- 6,771
48 📉
(Org: 47)
(6,734)
0.02 6,734
49 📉
(Org: 48)
(6,586)
- 6,586
50 📉
(Org: 49)
(6,490)
- 6,490
51 📈
(Org: 58)
(6,121)
0.13 6,121
52 📉
(Org: 50)
(6,042)
0 6,042
53 ➡️
(Org: 53)
(6,017)
0.04 6,017
54 📉
(Org: 51)
(6,012)
- 6,012
55 📉
(Org: 52)
(6,006)
- 6,006
56 📉
(Org: 55)
(5,694)
- 5,694
57 📉
(Org: 56)
(5,688)
0 5,688
58 📉
(Org: 57)
(5,684)
0 5,684
59 📈
(Org: 81)
(5,569)
0.3 5,569
60 📉
(Org: 59)
(5,352)
0.01 5,352
61 📈
(Org: 75)
(5,293)
0.2 5,293
62 📈
(Org: 78)
(5,289)
0.22 5,289
63 ➡️
(Org: 63)
(5,285)
0.07 5,285
64 📈
(Org: 71)
(5,245)
0.16 5,245
65 📉
(Org: 60)
(5,152)
- 5,152
66 📉
(Org: 62)
(5,055)
0.01 5,055
67 📉
(Org: 66)
(4,924)
0.04 4,924
68 📉
(Org: 64)
(4,854)
- 4,854
69 📉
(Org: 67)
(4,852)
0.03 4,852
70 📉
(Org: 65)
(4,780)
0 4,780
71 📉
(Org: 68)
(4,685)
0.01 4,685
72 📉
(Org: 70)
(4,569)
0.01 4,569
73 📉
(Org: 69)
(4,568)
- 4,568
74 📉
(Org: 72)
(4,354)
- 4,354
75 📉
(Org: 73)
(4,337)
- 4,337
76 📉
(Org: 74)
(4,294)
- 4,294
77 📈
(Org: 79)
(4,255)
0.03 4,255
78 📉
(Org: 76)
(4,161)
- 4,161
79 📉
(Org: 77)
(4,157)
0 4,157
80 ➡️
(Org: 80)
(4,037)
0.01 4,037
81 📈
(Org: 82)
(3,972)
0.04 3,972
82 📈
(Org: 85)
(3,944)
0.05 3,944
83 📈
(Org: 86)
(3,819)
0.02 3,819
84 ➡️
(Org: 84)
(3,757)
- 3,757
85 📈
(Org: 87)
(3,649)
0.01 3,649
86 📈
(Org: 88)
(3,600)
- 3,600
87 📈
(Org: 89)
(3,568)
- 3,568
88 📈
(Org: 109)
(3,496)
0.29 3,496
89 📈
(Org: 90)
(3,471)
- 3,471
90 📈
(Org: 91)
(3,431)
0.02 3,431
91 📈
(Org: 92)
(3,338)
0 3,338
92 📈
(Org: 93)
(3,304)
- 3,304
93 📈
(Org: 94)
(3,238)
- 3,238
94 📈
(Org: 95)
(3,211)
0.01 3,211
95 📈
(Org: 103)
(3,083)
0.16 3,083
96 📈
(Org: 98)
(2,910)
0.05 2,910
97 📉
(Org: 96)
(2,888)
0.01 2,888
98 📈
(Org: 106)
(2,835)
0.12 2,835
99 📉
(Org: 97)
(2,832)
0 2,832
100 📉
(Org: 99)
(2,821)
0.03 2,821