Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1931 - 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)
(60,386)
0 60,386
2 ➡️
(Org: 2)
(38,609)
0.06 38,609
3 ➡️
(Org: 3)
(26,570)
0 26,570
4 📈
(Org: 5)
(25,600)
0.25 25,600
5 📉
(Org: 4)
(21,813)
0 21,813
6 ➡️
(Org: 6)
(18,258)
0.03 18,258
7 ➡️
(Org: 7)
(17,614)
0.02 17,614
8 ➡️
(Org: 8)
(16,470)
- 16,470
9 ➡️
(Org: 9)
(14,439)
0 14,439
10 ➡️
(Org: 10)
(13,826)
0.01 13,826
11 ➡️
(Org: 11)
(13,166)
0 13,166
12 ➡️
(Org: 12)
(11,911)
0 11,911
13 📈
(Org: 36)
(11,244)
0.5 11,244
14 📉
(Org: 13)
(11,219)
0.02 11,219
15 📉
(Org: 14)
(10,806)
- 10,806
16 📉
(Org: 15)
(10,592)
0 10,592
17 📉
(Org: 16)
(10,529)
0.02 10,529
18 📉
(Org: 17)
(10,123)
0.01 10,123
19 📉
(Org: 18)
(10,110)
0.04 10,110
20 📉
(Org: 19)
(9,961)
0.03 9,961
21 📉
(Org: 20)
(9,473)
0.01 9,473
22 📉
(Org: 21)
(8,821)
0 8,821
23 📉
(Org: 22)
(8,800)
0 8,800
24 ➡️
(Org: 24)
(8,615)
0.01 8,615
25 📉
(Org: 23)
(8,547)
- 8,547
26 📉
(Org: 25)
(8,436)
0 8,436
27 📈
(Org: 37)
(8,262)
0.32 8,262
28 📉
(Org: 26)
(8,175)
0 8,175
29 📉
(Org: 27)
(7,582)
0 7,582
30 📉
(Org: 28)
(7,489)
0 7,489
31 📉
(Org: 29)
(7,364)
0.02 7,364
32 ➡️
(Org: 32)
(7,028)
0.06 7,028
33 📉
(Org: 30)
(6,881)
- 6,881
34 📉
(Org: 31)
(6,856)
0.01 6,856
35 📉
(Org: 34)
(6,067)
0.03 6,067
36 📈
(Org: 40)
(6,058)
0.13 6,058
37 📉
(Org: 33)
(5,897)
- 5,897
38 📈
(Org: 46)
(5,893)
0.17 5,893
39 📉
(Org: 35)
(5,858)
- 5,858
40 📉
(Org: 38)
(5,630)
0.04 5,630
41 📉
(Org: 39)
(5,524)
0.03 5,524
42 📈
(Org: 71)
(5,349)
0.32 5,349
43 📈
(Org: 45)
(5,261)
0.06 5,261
44 📉
(Org: 42)
(5,241)
0.03 5,241
45 📉
(Org: 41)
(5,090)
- 5,090
46 📉
(Org: 43)
(5,048)
0.01 5,048
47 📈
(Org: 59)
(5,024)
0.2 5,024
48 📉
(Org: 44)
(5,002)
- 5,002
49 ➡️
(Org: 49)
(4,950)
0.07 4,950
50 📉
(Org: 47)
(4,864)
0.01 4,864
51 📉
(Org: 48)
(4,758)
0.03 4,758
52 📉
(Org: 50)
(4,646)
0.02 4,646
53 📉
(Org: 51)
(4,527)
0.01 4,527
54 📉
(Org: 52)
(4,461)
- 4,461
55 📉
(Org: 53)
(4,440)
- 4,440
56 📉
(Org: 55)
(4,415)
0.01 4,415
57 📉
(Org: 54)
(4,406)
0 4,406
58 📈
(Org: 63)
(4,275)
0.11 4,275
59 📈
(Org: 62)
(4,224)
0.09 4,224
60 📉
(Org: 56)
(4,218)
0.01 4,218
61 📉
(Org: 57)
(4,130)
- 4,130
62 📉
(Org: 58)
(4,050)
- 4,050
62 📉
(Org: 60)
(4,050)
0.01 4,050
64 📈
(Org: 78)
(3,937)
0.2 3,937
65 📉
(Org: 64)
(3,925)
0.03 3,925
66 📉
(Org: 61)
(3,907)
0 3,907
67 📉
(Org: 66)
(3,777)
0 3,777
68 📉
(Org: 65)
(3,772)
- 3,772
69 ➡️
(Org: 69)
(3,771)
0.01 3,771
70 📉
(Org: 67)
(3,760)
- 3,760
71 📉
(Org: 70)
(3,738)
0.01 3,738
72 ➡️
(Org: 72)
(3,706)
0.02 3,706
73 📈
(Org: 88)
(3,667)
0.26 3,667
74 📉
(Org: 73)
(3,587)
0.01 3,587
75 📉
(Org: 74)
(3,555)
0.01 3,555
76 📈
(Org: 84)
(3,542)
0.19 3,542
77 📉
(Org: 75)
(3,411)
0 3,411
78 📉
(Org: 76)
(3,336)
0.01 3,336
79 📉
(Org: 77)
(3,316)
0.03 3,316
80 📈
(Org: 105)
(3,208)
0.3 3,208
81 ➡️
(Org: 81)
(3,207)
0.09 3,207
82 📈
(Org: 97)
(3,127)
0.18 3,127
83 📉
(Org: 79)
(3,034)
- 3,034
84 📉
(Org: 82)
(2,984)
0.03 2,984
85 📉
(Org: 80)
(2,979)
- 2,979
86 📈
(Org: 89)
(2,967)
0.1 2,967
87 ➡️
(Org: 87)
(2,913)
0.04 2,913
88 📉
(Org: 83)
(2,869)
- 2,869
89 📉
(Org: 85)
(2,861)
0.01 2,861
90 📉
(Org: 86)
(2,818)
0 2,818
91 📈
(Org: 96)
(2,807)
0.08 2,807
92 📈
(Org: 95)
(2,785)
0.07 2,785
93 📉
(Org: 91)
(2,624)
- 2,624
94 📈
(Org: 112)
(2,607)
0.19 2,607
95 📉
(Org: 94)
(2,599)
0 2,599
96 📉
(Org: 93)
(2,597)
- 2,597
97 📈
(Org: 98)
(2,525)
- 2,525
98 📈
(Org: 99)
(2,476)
0.01 2,476
99 📈
(Org: 100)
(2,469)
0.02 2,469
100 📈
(Org: 113)
(2,450)
0.14 2,450