Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1942 - 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

Girl Names

Ranking Name Distortion Index Count
1 ➡️
(Org: 1)
(63,558)
0 63,558
2 ➡️
(Org: 2)
(44,747)
0 44,747
3 ➡️
(Org: 3)
(39,464)
- 39,464
4 📈
(Org: 5)
(39,084)
0.23 39,084
5 📉
(Org: 4)
(33,751)
0.06 33,751
6 ➡️
(Org: 6)
(25,798)
0.03 25,798
7 ➡️
(Org: 7)
(24,898)
0 24,898
8 📈
(Org: 18)
(24,459)
0.41 24,459
9 ➡️
(Org: 9)
(23,984)
0.1 23,984
10 📉
(Org: 8)
(23,522)
0.01 23,522
11 ➡️
(Org: 11)
(20,356)
0.03 20,356
12 📉
(Org: 10)
(20,305)
0.02 20,305
13 📉
(Org: 12)
(17,781)
0 17,781
14 ➡️
(Org: 14)
(16,799)
0.01 16,799
15 📉
(Org: 13)
(16,757)
0 16,757
16 📉
(Org: 15)
(16,412)
0.05 16,412
17 📉
(Org: 16)
(15,793)
0.03 15,793
18 📈
(Org: 21)
(15,372)
0.22 15,372
19 📉
(Org: 17)
(15,079)
0 15,079
20 📉
(Org: 19)
(13,535)
0.03 13,535
21 📉
(Org: 20)
(13,384)
0.03 13,384
22 📈
(Org: 49)
(12,897)
0.59 12,897
23 📉
(Org: 22)
(11,382)
0.02 11,382
24 ➡️
(Org: 24)
(10,990)
0.03 10,990
25 📉
(Org: 23)
(10,817)
0 10,817
26 ➡️
(Org: 26)
(10,641)
0.06 10,641
27 ➡️
(Org: 27)
(10,432)
0.05 10,432
28 📉
(Org: 25)
(10,286)
- 10,286
29 📈
(Org: 30)
(9,775)
0.03 9,775
30 📉
(Org: 28)
(9,550)
- 9,550
31 📉
(Org: 29)
(9,520)
0 9,520
32 ➡️
(Org: 32)
(9,493)
0.01 9,493
33 📉
(Org: 31)
(9,450)
- 9,450
34 📉
(Org: 33)
(9,330)
0 9,330
35 📉
(Org: 34)
(8,951)
0.01 8,951
36 ➡️
(Org: 36)
(8,443)
0.02 8,443
37 ➡️
(Org: 37)
(8,024)
0.03 8,024
38 ➡️
(Org: 38)
(7,666)
- 7,666
39 ➡️
(Org: 39)
(7,390)
0 7,390
40 📈
(Org: 41)
(7,274)
0.01 7,274
41 📉
(Org: 40)
(7,241)
- 7,241
42 ➡️
(Org: 42)
(6,810)
0.03 6,810
43 📈
(Org: 80)
(6,720)
0.5 6,720
44 📉
(Org: 43)
(6,637)
0.01 6,637
45 📉
(Org: 44)
(6,546)
0.02 6,546
46 📈
(Org: 67)
(6,291)
0.35 6,291
47 📉
(Org: 45)
(6,063)
0.01 6,063
48 📈
(Org: 60)
(6,034)
0.26 6,034
49 📉
(Org: 46)
(5,995)
0.05 5,995
50 📉
(Org: 47)
(5,796)
0.06 5,796
51 📈
(Org: 56)
(5,254)
0.11 5,254
52 📉
(Org: 50)
(5,253)
- 5,253
53 ➡️
(Org: 53)
(5,044)
0.02 5,044
54 📉
(Org: 51)
(5,029)
0 5,029
55 📈
(Org: 69)
(5,010)
0.24 5,010
56 📉
(Org: 52)
(4,990)
0 4,990
57 📉
(Org: 54)
(4,814)
0 4,814
58 📉
(Org: 55)
(4,793)
0.02 4,793
59 📉
(Org: 57)
(4,559)
- 4,559
60 📉
(Org: 59)
(4,488)
- 4,488
61 📈
(Org: 65)
(4,411)
0.05 4,411
62 📉
(Org: 61)
(4,358)
0 4,358
63 📉
(Org: 62)
(4,294)
- 4,294
64 📉
(Org: 63)
(4,267)
- 4,267
65 📈
(Org: 92)
(4,244)
0.29 4,244
66 📉
(Org: 64)
(4,229)
0.01 4,229
67 📉
(Org: 66)
(4,116)
0 4,116
68 📈
(Org: 75)
(4,040)
0.1 4,040
69 📉
(Org: 68)
(3,857)
- 3,857
70 ➡️
(Org: 70)
(3,847)
0.01 3,847
71 📈
(Org: 98)
(3,840)
0.27 3,840
72 📉
(Org: 71)
(3,807)
- 3,807
73 📈
(Org: 78)
(3,796)
0.07 3,796
74 📉
(Org: 72)
(3,793)
0.02 3,793
75 📉
(Org: 74)
(3,756)
0.03 3,756
76 📈
(Org: 104)
(3,749)
0.28 3,749
77 ➡️
(Org: 77)
(3,640)
0.03 3,640
78 📉
(Org: 73)
(3,639)
0 3,639
79 📈
(Org: 83)
(3,636)
0.08 3,636
80 📉
(Org: 79)
(3,611)
0.06 3,611
81 📈
(Org: 87)
(3,580)
0.12 3,580
82 📉
(Org: 76)
(3,525)
- 3,525
83 📈
(Org: 84)
(3,521)
0.08 3,521
84 📈
(Org: 109)
(3,343)
0.24 3,343
85 ➡️
(Org: 85)
(3,316)
0.02 3,316
86 📈
(Org: 91)
(3,304)
0.09 3,304
87 📈
(Org: 141)
(3,233)
0.43 3,233
88 📈
(Org: 96)
(3,212)
0.1 3,212
89 📉
(Org: 86)
(3,170)
- 3,170
90 📉
(Org: 89)
(3,101)
0 3,101
91 📈
(Org: 149)
(3,085)
0.43 3,085
92 📉
(Org: 90)
(3,074)
- 3,074
93 ➡️
(Org: 93)
(2,998)
- 2,998
94 ➡️
(Org: 94)
(2,973)
- 2,973
95 ➡️
(Org: 95)
(2,905)
- 2,905
96 📈
(Org: 97)
(2,836)
0.01 2,836
97 📈
(Org: 102)
(2,821)
0.04 2,821
98 📈
(Org: 117)
(2,787)
0.17 2,787
99 ➡️
(Org: 99)
(2,763)
- 2,763
100 ➡️
(Org: 100)
(2,760)
0 2,760