Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1930 - 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)
(64,258)
0 64,258
2 ➡️
(Org: 2)
(40,789)
0.06 40,789
3 ➡️
(Org: 3)
(30,476)
0 30,476
4 📈
(Org: 8)
(20,817)
0.26 20,817
5 📉
(Org: 4)
(20,607)
0.03 20,607
6 📉
(Org: 5)
(18,657)
0.02 18,657
7 📉
(Org: 6)
(18,287)
0 18,287
8 📉
(Org: 7)
(15,751)
- 15,751
9 ➡️
(Org: 9)
(15,736)
0.02 15,736
10 ➡️
(Org: 10)
(14,982)
0 14,982
11 ➡️
(Org: 11)
(14,805)
0 14,805
12 ➡️
(Org: 12)
(13,232)
0 13,232
13 ➡️
(Org: 13)
(12,842)
- 12,842
14 📈
(Org: 35)
(12,704)
0.5 12,704
15 📉
(Org: 14)
(12,263)
0.02 12,263
16 📉
(Org: 15)
(11,222)
0.02 11,222
17 📉
(Org: 16)
(11,124)
0.04 11,124
18 📉
(Org: 17)
(10,233)
0.01 10,233
19 ➡️
(Org: 19)
(9,690)
0.02 9,690
20 📉
(Org: 18)
(9,674)
0 9,674
21 📈
(Org: 22)
(9,526)
0.02 9,526
22 📉
(Org: 20)
(9,525)
0 9,525
23 📉
(Org: 21)
(9,355)
- 9,355
24 📈
(Org: 33)
(9,303)
0.31 9,303
25 📉
(Org: 24)
(9,148)
0.01 9,148
26 📉
(Org: 23)
(9,081)
- 9,081
27 📉
(Org: 25)
(8,573)
0.01 8,573
28 📉
(Org: 26)
(8,466)
0 8,466
29 📉
(Org: 28)
(7,941)
0.02 7,941
30 📉
(Org: 27)
(7,839)
0 7,839
31 📉
(Org: 29)
(7,688)
- 7,688
32 📉
(Org: 30)
(7,613)
0 7,613
33 📉
(Org: 31)
(6,947)
0 6,947
34 📉
(Org: 32)
(6,871)
0.03 6,871
35 📈
(Org: 39)
(6,707)
0.13 6,707
36 📉
(Org: 34)
(6,537)
0.01 6,537
37 ➡️
(Org: 37)
(6,392)
0.06 6,392
38 📉
(Org: 36)
(6,202)
0.03 6,202
39 📉
(Org: 38)
(5,897)
0.01 5,897
40 📈
(Org: 50)
(5,830)
0.18 5,830
41 📉
(Org: 40)
(5,756)
- 5,756
42 📈
(Org: 70)
(5,696)
0.31 5,696
43 ➡️
(Org: 43)
(5,692)
0.04 5,692
44 📉
(Org: 42)
(5,613)
0.03 5,613
45 📈
(Org: 46)
(5,593)
0.08 5,593
46 📉
(Org: 41)
(5,531)
- 5,531
47 📉
(Org: 43)
(5,477)
0.01 5,477
48 📉
(Org: 45)
(5,250)
- 5,250
49 📈
(Org: 54)
(5,169)
0.11 5,169
50 📉
(Org: 48)
(5,131)
0.01 5,131
51 📉
(Org: 47)
(5,093)
- 5,093
52 📉
(Org: 49)
(5,020)
0.01 5,020
53 📈
(Org: 58)
(4,923)
0.1 4,923
54 📉
(Org: 53)
(4,829)
0.05 4,829
55 📈
(Org: 59)
(4,824)
0.1 4,824
56 📉
(Org: 51)
(4,762)
- 4,762
57 📉
(Org: 52)
(4,692)
0.01 4,692
58 📉
(Org: 55)
(4,686)
0.02 4,686
59 📉
(Org: 56)
(4,540)
0 4,540
60 📉
(Org: 57)
(4,513)
- 4,513
61 📉
(Org: 60)
(4,317)
0 4,317
62 📉
(Org: 61)
(4,273)
- 4,273
63 📉
(Org: 62)
(4,266)
0.01 4,266
64 📉
(Org: 63)
(4,260)
0.03 4,260
65 📈
(Org: 74)
(4,251)
0.2 4,251
66 📈
(Org: 67)
(4,232)
0.03 4,232
67 📉
(Org: 64)
(4,124)
- 4,124
68 📉
(Org: 65)
(4,101)
- 4,101
69 📉
(Org: 68)
(4,099)
0.01 4,099
70 📉
(Org: 66)
(4,098)
- 4,098
71 📈
(Org: 80)
(4,090)
0.21 4,090
72 📈
(Org: 82)
(4,083)
0.23 4,083
73 📉
(Org: 69)
(4,030)
0.02 4,030
74 📉
(Org: 71)
(3,951)
0.02 3,951
75 📉
(Org: 72)
(3,764)
0.01 3,764
76 📉
(Org: 73)
(3,581)
0.01 3,581
77 📈
(Org: 79)
(3,579)
0.09 3,579
78 📈
(Org: 106)
(3,421)
0.29 3,421
79 📉
(Org: 76)
(3,408)
0.01 3,408
80 📉
(Org: 75)
(3,406)
- 3,406
81 📉
(Org: 77)
(3,350)
- 3,350
82 📉
(Org: 78)
(3,298)
0.01 3,298
83 📈
(Org: 89)
(3,238)
0.1 3,238
84 ➡️
(Org: 84)
(3,210)
0.04 3,210
85 📈
(Org: 98)
(3,142)
0.19 3,142
86 📉
(Org: 83)
(3,091)
- 3,091
87 📉
(Org: 86)
(3,039)
0.01 3,039
88 📉
(Org: 87)
(3,027)
0 3,027
89 📈
(Org: 91)
(3,016)
0.05 3,016
90 📉
(Org: 88)
(2,993)
0.01 2,993
91 📈
(Org: 111)
(2,933)
0.19 2,933
92 📉
(Org: 90)
(2,880)
- 2,880
93 📈
(Org: 108)
(2,749)
0.13 2,749
94 📉
(Org: 93)
(2,731)
0.01 2,731
95 📉
(Org: 92)
(2,720)
- 2,720
96 📉
(Org: 94)
(2,710)
0.02 2,710
97 📈
(Org: 105)
(2,677)
0.07 2,677
98 📉
(Org: 95)
(2,654)
0.02 2,654
99 📈
(Org: 103)
(2,653)
0.05 2,653
100 📈
(Org: 119)
(2,573)
0.18 2,573