Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1938 - 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)
(56,386)
0 56,386
2 ➡️
(Org: 2)
(39,289)
0 39,289
3 📈
(Org: 4)
(27,861)
0.08 27,861
4 📉
(Org: 3)
(27,558)
- 27,558
5 📈
(Org: 6)
(24,386)
0.2 24,386
6 📉
(Org: 5)
(23,800)
0 23,800
7 📈
(Org: 10)
(22,330)
0.36 22,330
8 📉
(Org: 7)
(19,093)
0.01 19,093
9 📉
(Org: 8)
(16,397)
0 16,397
10 📉
(Org: 9)
(15,550)
0.01 15,550
11 ➡️
(Org: 11)
(12,721)
0 12,721
12 📈
(Org: 13)
(11,392)
0.05 11,392
13 📈
(Org: 14)
(11,147)
0.03 11,147
14 📉
(Org: 12)
(10,924)
0 10,924
15 ➡️
(Org: 15)
(10,751)
0.02 10,751
16 ➡️
(Org: 16)
(10,271)
0.04 10,271
17 📈
(Org: 19)
(10,201)
0.04 10,201
18 📈
(Org: 48)
(10,068)
0.55 10,068
19 📈
(Org: 20)
(10,005)
0.03 10,005
20 📉
(Org: 17)
(9,975)
0.02 9,975
21 📉
(Org: 18)
(9,840)
0.01 9,840
22 📉
(Org: 21)
(9,326)
0 9,326
23 📉
(Org: 22)
(9,290)
0 9,290
24 📉
(Org: 23)
(9,242)
0.03 9,242
25 ➡️
(Org: 25)
(8,739)
0.02 8,739
26 📉
(Org: 24)
(8,711)
- 8,711
27 📉
(Org: 26)
(8,585)
0 8,585
28 📉
(Org: 27)
(7,895)
0.02 7,895
29 📉
(Org: 28)
(7,817)
0.02 7,817
30 📈
(Org: 31)
(7,603)
0.07 7,603
31 📉
(Org: 30)
(7,556)
0.04 7,556
32 📉
(Org: 29)
(7,489)
- 7,489
33 📉
(Org: 32)
(6,990)
- 6,990
34 📉
(Org: 33)
(6,645)
0.02 6,645
35 ➡️
(Org: 35)
(6,541)
0.03 6,541
36 📉
(Org: 34)
(6,397)
0 6,397
37 📉
(Org: 36)
(6,297)
- 6,297
38 📈
(Org: 71)
(6,088)
0.42 6,088
39 📉
(Org: 37)
(6,004)
0.01 6,004
40 📉
(Org: 38)
(5,801)
0.02 5,801
41 📈
(Org: 67)
(5,706)
0.34 5,706
42 📈
(Org: 71)
(5,677)
0.37 5,677
43 📉
(Org: 39)
(5,292)
- 5,292
44 📉
(Org: 41)
(5,199)
0.04 5,199
45 📉
(Org: 40)
(5,144)
- 5,144
46 📉
(Org: 44)
(4,969)
0.04 4,969
47 📈
(Org: 54)
(4,907)
0.13 4,907
48 📉
(Org: 45)
(4,899)
0.05 4,899
49 📉
(Org: 42)
(4,885)
0.01 4,885
50 📉
(Org: 43)
(4,809)
- 4,809
51 ➡️
(Org: 51)
(4,760)
0.06 4,760
52 📈
(Org: 69)
(4,598)
0.21 4,598
53 📉
(Org: 47)
(4,562)
- 4,562
54 📈
(Org: 60)
(4,547)
0.11 4,547
55 📉
(Org: 50)
(4,545)
0.01 4,545
56 📉
(Org: 49)
(4,527)
0 4,527
57 📉
(Org: 53)
(4,474)
0.03 4,474
58 📉
(Org: 52)
(4,440)
- 4,440
59 📉
(Org: 58)
(4,363)
0.03 4,363
60 📉
(Org: 56)
(4,304)
0.01 4,304
61 📉
(Org: 55)
(4,261)
- 4,261
62 📈
(Org: 63)
(4,217)
0.08 4,217
63 📈
(Org: 77)
(4,205)
0.24 4,205
64 📉
(Org: 62)
(4,126)
0.05 4,126
65 📉
(Org: 61)
(4,115)
0.04 4,115
66 📉
(Org: 59)
(4,087)
0 4,087
67 📉
(Org: 66)
(4,047)
0.07 4,047
68 📈
(Org: 91)
(3,846)
0.27 3,846
69 📈
(Org: 95)
(3,831)
0.3 3,831
70 📉
(Org: 64)
(3,827)
- 3,827
71 📉
(Org: 65)
(3,814)
0.01 3,814
72 📉
(Org: 70)
(3,633)
0 3,633
73 📈
(Org: 76)
(3,570)
0.07 3,570
74 📉
(Org: 73)
(3,555)
0 3,555
75 📈
(Org: 92)
(3,494)
0.21 3,494
76 📉
(Org: 74)
(3,473)
0.03 3,473
77 📈
(Org: 78)
(3,411)
0.07 3,411
78 📈
(Org: 81)
(3,399)
0.08 3,399
79 📉
(Org: 75)
(3,322)
- 3,322
80 📉
(Org: 79)
(3,141)
- 3,141
81 📉
(Org: 80)
(3,129)
- 3,129
82 ➡️
(Org: 82)
(3,080)
- 3,080
83 ➡️
(Org: 83)
(2,995)
0.01 2,995
84 📈
(Org: 87)
(2,946)
0.03 2,946
85 📈
(Org: 93)
(2,944)
0.07 2,944
86 📉
(Org: 85)
(2,894)
0.01 2,894
87 📉
(Org: 84)
(2,887)
- 2,887
88 📉
(Org: 86)
(2,866)
- 2,866
89 📉
(Org: 88)
(2,846)
0.01 2,846
90 📉
(Org: 89)
(2,830)
0.01 2,830
91 📉
(Org: 89)
(2,824)
0.01 2,824
92 📈
(Org: 108)
(2,762)
0.12 2,762
93 📈
(Org: 94)
(2,725)
- 2,725
94 📈
(Org: 128)
(2,710)
0.31 2,710
95 📈
(Org: 96)
(2,691)
0.01 2,691
96 📈
(Org: 97)
(2,690)
0.01 2,690
97 📈
(Org: 106)
(2,677)
0.07 2,677
98 ➡️
(Org: 98)
(2,662)
- 2,662
99 ➡️
(Org: 99)
(2,636)
- 2,636
100 ➡️
(Org: 100)
(2,633)
0.01 2,633