Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1948 - 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)
(88,604)
- 88,604
2 ➡️
(Org: 2)
(85,482)
0 85,482
3 ➡️
(Org: 3)
(85,089)
0.03 85,089
4 ➡️
(Org: 4)
(61,997)
0 61,997
5 ➡️
(Org: 5)
(56,624)
- 56,624
6 ➡️
(Org: 6)
(54,451)
0.03 54,451
7 ➡️
(Org: 7)
(50,983)
0 50,983
8 ➡️
(Org: 8)
(43,952)
0 43,952
9 ➡️
(Org: 9)
(38,688)
0 38,688
10 ➡️
(Org: 10)
(33,595)
0 33,595
11 ➡️
(Org: 11)
(33,513)
0 33,513
12 📈
(Org: 20)
(33,044)
0.48 33,044
13 📉
(Org: 12)
(28,475)
0 28,475
14 📉
(Org: 13)
(26,989)
0.01 26,989
15 📉
(Org: 14)
(26,443)
- 26,443
16 📉
(Org: 15)
(23,571)
0 23,571
17 ➡️
(Org: 17)
(22,196)
0.02 22,196
18 📉
(Org: 16)
(21,947)
0 21,947
19 📉
(Org: 18)
(21,260)
0 21,260
20 📉
(Org: 19)
(18,983)
- 18,983
21 ➡️
(Org: 21)
(17,177)
0.02 17,177
22 ➡️
(Org: 22)
(16,643)
0.01 16,643
23 📈
(Org: 24)
(13,481)
0.05 13,481
24 📈
(Org: 25)
(12,698)
- 12,698
25 📈
(Org: 26)
(12,157)
0 12,157
26 📈
(Org: 27)
(11,623)
0 11,623
27 📈
(Org: 29)
(11,521)
0.11 11,521
28 📈
(Org: 54)
(11,211)
0.45 11,211
29 📉
(Org: 28)
(11,065)
- 11,065
30 📈
(Org: 31)
(10,819)
0.1 10,819
31 📉
(Org: 30)
(10,403)
0.05 10,403
32 ➡️
(Org: 32)
(9,755)
0 9,755
33 ➡️
(Org: 33)
(9,589)
0.01 9,589
34 📈
(Org: 50)
(9,315)
0.26 9,315
35 📈
(Org: 42)
(9,065)
0.14 9,065
36 📉
(Org: 34)
(8,687)
0 8,687
37 📉
(Org: 35)
(8,627)
- 8,627
38 📈
(Org: 59)
(8,403)
0.3 8,403
39 ➡️
(Org: 39)
(8,305)
0.04 8,305
40 📉
(Org: 36)
(8,165)
0 8,165
41 📉
(Org: 37)
(8,056)
0 8,056
42 📉
(Org: 38)
(8,043)
- 8,043
43 📉
(Org: 40)
(8,020)
0.01 8,020
44 📉
(Org: 41)
(7,879)
- 7,879
45 📉
(Org: 43)
(7,647)
0 7,647
46 📉
(Org: 44)
(7,621)
0.01 7,621
47 📈
(Org: 58)
(7,496)
0.21 7,496
48 📉
(Org: 45)
(7,452)
0 7,452
49 📉
(Org: 46)
(7,394)
- 7,394
50 📉
(Org: 47)
(7,321)
0 7,321
51 📉
(Org: 48)
(7,225)
0 7,225
52 📉
(Org: 49)
(7,130)
0.01 7,130
53 📉
(Org: 52)
(6,983)
0.02 6,983
54 📉
(Org: 51)
(6,915)
- 6,915
55 📈
(Org: 73)
(6,786)
0.3 6,786
56 📉
(Org: 53)
(6,520)
0.05 6,520
57 📉
(Org: 55)
(6,156)
- 6,156
58 📉
(Org: 56)
(6,118)
0 6,118
59 📉
(Org: 57)
(5,952)
0 5,952
60 📈
(Org: 64)
(5,789)
0.07 5,789
61 📈
(Org: 62)
(5,787)
0.04 5,787
62 📉
(Org: 60)
(5,741)
- 5,741
63 📈
(Org: 75)
(5,669)
0.2 5,669
64 📉
(Org: 61)
(5,622)
0 5,622
65 📉
(Org: 63)
(5,497)
- 5,497
66 📈
(Org: 76)
(5,413)
0.17 5,413
67 📉
(Org: 65)
(5,397)
0 5,397
68 📉
(Org: 66)
(5,376)
- 5,376
69 📉
(Org: 67)
(5,310)
0.04 5,310
70 ➡️
(Org: 70)
(5,053)
0.01 5,053
71 📉
(Org: 68)
(5,045)
- 5,045
72 📉
(Org: 71)
(4,938)
0.03 4,938
73 📉
(Org: 72)
(4,755)
- 4,755
74 ➡️
(Org: 74)
(4,701)
0.01 4,701
75 📈
(Org: 78)
(4,453)
0.05 4,453
76 📈
(Org: 77)
(4,308)
- 4,308
77 📈
(Org: 80)
(4,248)
0.01 4,248
78 📈
(Org: 79)
(4,220)
- 4,220
79 📈
(Org: 83)
(4,137)
0.04 4,137
80 📈
(Org: 81)
(4,134)
0.02 4,134
81 📈
(Org: 82)
(4,029)
0.01 4,029
82 📈
(Org: 95)
(3,968)
0.15 3,968
83 📈
(Org: 84)
(3,926)
- 3,926
84 📈
(Org: 85)
(3,902)
0 3,902
85 📈
(Org: 108)
(3,816)
0.29 3,816
86 ➡️
(Org: 86)
(3,808)
- 3,808
87 ➡️
(Org: 87)
(3,795)
0 3,795
88 📈
(Org: 91)
(3,711)
0.04 3,711
89 📉
(Org: 88)
(3,704)
0 3,704
90 📉
(Org: 89)
(3,686)
0.01 3,686
91 📉
(Org: 90)
(3,625)
- 3,625
92 📈
(Org: 93)
(3,538)
0.03 3,538
93 📈
(Org: 98)
(3,485)
0.09 3,485
94 📉
(Org: 92)
(3,466)
- 3,466
95 📉
(Org: 94)
(3,457)
0.01 3,457
96 ➡️
(Org: 96)
(3,245)
- 3,245
97 ➡️
(Org: 97)
(3,234)
- 3,234
98 📈
(Org: 101)
(3,212)
0.04 3,212
99 📈
(Org: 100)
(3,180)
0.01 3,180
100 📉
(Org: 99)
(3,172)
0.01 3,172