Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1943 - 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)
(66,520)
0.01 66,520
2 ➡️
(Org: 2)
(43,444)
0 43,444
3 📈
(Org: 4)
(40,886)
0.06 40,886
4 📉
(Org: 3)
(39,621)
- 39,621
5 ➡️
(Org: 5)
(38,674)
0.18 38,674
6 ➡️
(Org: 6)
(26,736)
0.03 26,736
7 📈
(Org: 8)
(25,664)
0.04 25,664
8 📉
(Org: 7)
(25,317)
0 25,317
9 ➡️
(Org: 9)
(24,200)
0.01 24,200
10 ➡️
(Org: 10)
(23,924)
0.1 23,924
11 📈
(Org: 21)
(23,056)
0.43 23,056
12 📉
(Org: 11)
(20,660)
0.01 20,660
13 📈
(Org: 18)
(18,988)
0.22 18,988
14 📉
(Org: 13)
(18,209)
0.05 18,209
15 📉
(Org: 12)
(17,840)
0 17,840
16 📉
(Org: 14)
(17,412)
0.01 17,412
17 📉
(Org: 15)
(17,098)
0.02 17,098
18 📉
(Org: 16)
(16,512)
0 16,512
19 📉
(Org: 17)
(15,345)
0.03 15,345
20 📉
(Org: 19)
(14,839)
0 14,839
21 📉
(Org: 20)
(13,786)
0.03 13,786
22 📈
(Org: 48)
(13,670)
0.6 13,670
23 📉
(Org: 22)
(12,498)
0.03 12,498
24 📉
(Org: 23)
(11,842)
0.02 11,842
25 📉
(Org: 24)
(11,326)
- 11,326
26 📉
(Org: 25)
(10,868)
0 10,868
27 ➡️
(Org: 27)
(10,690)
0.05 10,690
28 📉
(Org: 26)
(10,651)
- 10,651
29 📉
(Org: 28)
(10,351)
0.05 10,351
30 📈
(Org: 31)
(9,774)
0.03 9,774
31 📉
(Org: 29)
(9,714)
0 9,714
32 📉
(Org: 30)
(9,689)
0 9,689
33 📉
(Org: 32)
(9,485)
0.01 9,485
34 📉
(Org: 33)
(9,390)
0 9,390
35 📉
(Org: 34)
(9,036)
0.02 9,036
36 📉
(Org: 35)
(8,436)
- 8,436
37 📉
(Org: 36)
(8,268)
0.02 8,268
38 📈
(Org: 39)
(7,846)
0.03 7,846
39 📉
(Org: 37)
(7,829)
- 7,829
40 📈
(Org: 68)
(7,687)
0.47 7,687
41 📉
(Org: 38)
(7,648)
- 7,648
42 📉
(Org: 40)
(7,251)
0.02 7,251
43 📉
(Org: 41)
(6,731)
0.03 6,731
44 📈
(Org: 55)
(6,700)
0.28 6,700
45 📉
(Org: 44)
(6,358)
0.05 6,358
46 📉
(Org: 43)
(6,259)
0.02 6,259
47 📉
(Org: 45)
(6,080)
0.02 6,080
48 📉
(Org: 46)
(6,050)
0.01 6,050
49 📈
(Org: 71)
(6,010)
0.34 6,010
50 📈
(Org: 51)
(5,517)
0.06 5,517
51 📉
(Org: 47)
(5,491)
0 5,491
52 📈
(Org: 65)
(5,470)
0.23 5,470
53 📈
(Org: 57)
(5,228)
0.11 5,228
54 📉
(Org: 50)
(5,207)
- 5,207
55 📉
(Org: 52)
(5,111)
0.02 5,111
56 📉
(Org: 53)
(5,004)
0.02 5,004
57 📉
(Org: 54)
(4,953)
0.02 4,953
58 📉
(Org: 56)
(4,732)
0.01 4,732
59 📉
(Org: 58)
(4,554)
0 4,554
60 📉
(Org: 59)
(4,549)
0.01 4,549
61 📈
(Org: 63)
(4,530)
0.05 4,530
62 📉
(Org: 61)
(4,355)
- 4,355
63 📉
(Org: 62)
(4,344)
0 4,344
64 ➡️
(Org: 64)
(4,231)
- 4,231
65 📈
(Org: 66)
(4,176)
0 4,176
66 📈
(Org: 67)
(4,172)
0 4,172
67 📈
(Org: 100)
(4,167)
0.3 4,167
68 📈
(Org: 97)
(4,139)
0.28 4,139
69 📈
(Org: 73)
(4,106)
0.08 4,106
70 📉
(Org: 69)
(4,070)
- 4,070
71 📉
(Org: 70)
(4,049)
0 4,049
72 📈
(Org: 88)
(4,021)
0.21 4,021
73 📈
(Org: 81)
(4,000)
0.13 4,000
74 📉
(Org: 72)
(3,856)
0 3,856
75 📈
(Org: 79)
(3,734)
0.03 3,734
76 📉
(Org: 74)
(3,698)
- 3,698
77 📈
(Org: 84)
(3,688)
0.1 3,688
78 📉
(Org: 77)
(3,678)
0.01 3,678
79 📈
(Org: 102)
(3,645)
0.21 3,645
80 📉
(Org: 76)
(3,626)
- 3,626
81 📈
(Org: 109)
(3,597)
0.29 3,597
82 ➡️
(Org: 82)
(3,592)
0.03 3,592
83 📉
(Org: 80)
(3,535)
- 3,535
84 📈
(Org: 90)
(3,506)
0.1 3,506
85 📈
(Org: 134)
(3,501)
0.41 3,501
86 📉
(Org: 83)
(3,427)
0.01 3,427
87 📈
(Org: 89)
(3,344)
0.05 3,344
88 📉
(Org: 87)
(3,338)
0.02 3,338
89 📈
(Org: 94)
(3,287)
0.08 3,287
90 📈
(Org: 136)
(3,213)
0.37 3,213
91 📈
(Org: 149)
(3,151)
0.43 3,151
92 📈
(Org: 104)
(3,137)
0.09 3,137
93 📉
(Org: 91)
(3,085)
- 3,085
94 📉
(Org: 92)
(3,063)
- 3,063
95 📈
(Org: 107)
(3,056)
0.11 3,056
96 📉
(Org: 93)
(3,054)
0 3,054
97 📉
(Org: 96)
(2,978)
0 2,978
98 📉
(Org: 95)
(2,973)
- 2,973
99 📉
(Org: 98)
(2,952)
- 2,952
100 📉
(Org: 99)
(2,930)
- 2,930