Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1920 - 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)
(71,150)
0 71,150
2 ➡️
(Org: 2)
(36,732)
0 36,732
3 ➡️
(Org: 3)
(35,952)
0.02 35,952
4 ➡️
(Org: 4)
(28,390)
0.01 28,390
5 ➡️
(Org: 5)
(26,204)
0 26,204
6 📈
(Org: 21)
(19,638)
0.55 19,638
7 📉
(Org: 6)
(18,060)
- 18,060
8 📉
(Org: 7)
(17,363)
0 17,363
9 ➡️
(Org: 9)
(16,569)
0.04 16,569
10 📉
(Org: 8)
(16,276)
0.02 16,276
11 ➡️
(Org: 11)
(15,961)
0.12 15,961
12 📉
(Org: 10)
(14,590)
0 14,590
13 📉
(Org: 12)
(14,108)
0.02 14,108
14 📈
(Org: 17)
(13,424)
0.25 13,424
15 📉
(Org: 13)
(12,806)
0 12,806
16 📉
(Org: 14)
(12,144)
0.02 12,144
17 📉
(Org: 15)
(11,603)
0 11,603
18 📉
(Org: 16)
(10,774)
0 10,774
19 📉
(Org: 18)
(10,212)
0.02 10,212
20 📈
(Org: 25)
(9,922)
0.14 9,922
21 📈
(Org: 29)
(9,403)
0.15 9,403
22 📉
(Org: 19)
(9,203)
0 9,203
23 📉
(Org: 20)
(9,011)
- 9,011
24 ➡️
(Org: 24)
(8,963)
0.03 8,963
25 📉
(Org: 22)
(8,953)
0.01 8,953
26 ➡️
(Org: 26)
(8,721)
0.04 8,721
27 📉
(Org: 23)
(8,719)
0 8,719
28 📉
(Org: 27)
(8,337)
0 8,337
29 📉
(Org: 28)
(8,120)
0 8,120
30 📈
(Org: 33)
(8,044)
0.04 8,044
31 📉
(Org: 30)
(7,868)
- 7,868
32 📉
(Org: 31)
(7,814)
- 7,814
33 📉
(Org: 32)
(7,773)
- 7,773
34 ➡️
(Org: 34)
(7,410)
0.01 7,410
35 📈
(Org: 50)
(7,407)
0.32 7,407
36 📉
(Org: 35)
(7,268)
- 7,268
37 ➡️
(Org: 37)
(7,258)
0.01 7,258
38 📉
(Org: 36)
(7,244)
0.01 7,244
39 📈
(Org: 40)
(6,767)
0.12 6,767
40 📉
(Org: 38)
(6,670)
0.02 6,670
41 📉
(Org: 39)
(6,068)
- 6,068
42 📉
(Org: 41)
(5,816)
0 5,816
43 📉
(Org: 42)
(5,815)
0 5,815
44 📉
(Org: 43)
(5,772)
0 5,772
45 📉
(Org: 44)
(5,477)
0 5,477
46 📈
(Org: 48)
(5,276)
0.04 5,276
47 📉
(Org: 46)
(5,260)
0 5,260
48 📈
(Org: 52)
(5,108)
0.03 5,108
49 📉
(Org: 47)
(5,106)
- 5,106
50 📉
(Org: 49)
(5,041)
- 5,041
51 ➡️
(Org: 51)
(5,012)
0 5,012
52 📈
(Org: 83)
(4,943)
0.32 4,943
53 📈
(Org: 54)
(4,929)
0 4,929
54 📉
(Org: 53)
(4,911)
- 4,911
55 ➡️
(Org: 55)
(4,889)
- 4,889
56 ➡️
(Org: 56)
(4,736)
0 4,736
57 ➡️
(Org: 57)
(4,672)
0.01 4,672
58 📈
(Org: 63)
(4,549)
0.08 4,549
59 📉
(Org: 58)
(4,524)
0.01 4,524
60 📈
(Org: 70)
(4,502)
0.13 4,502
61 📉
(Org: 60)
(4,416)
0.03 4,416
62 📈
(Org: 64)
(4,292)
0.04 4,292
62 📉
(Org: 59)
(4,292)
- 4,292
64 📉
(Org: 62)
(4,289)
0.02 4,289
65 📉
(Org: 61)
(4,238)
- 4,238
66 ➡️
(Org: 66)
(4,135)
0.01 4,135
67 📉
(Org: 65)
(4,114)
- 4,114
68 📈
(Org: 73)
(4,110)
0.06 4,110
69 📈
(Org: 71)
(4,107)
0.05 4,107
70 📉
(Org: 69)
(3,996)
0.01 3,996
71 📈
(Org: 72)
(3,979)
0.03 3,979
72 📉
(Org: 68)
(3,961)
0 3,961
73 📈
(Org: 90)
(3,896)
0.19 3,896
74 ➡️
(Org: 74)
(3,833)
0 3,833
75 ➡️
(Org: 75)
(3,791)
0 3,791
76 ➡️
(Org: 76)
(3,788)
0.01 3,788
77 📈
(Org: 99)
(3,740)
0.27 3,740
78 ➡️
(Org: 78)
(3,723)
0.01 3,723
79 📉
(Org: 77)
(3,694)
- 3,694
80 📉
(Org: 79)
(3,632)
0 3,632
81 📉
(Org: 80)
(3,584)
- 3,584
82 📉
(Org: 81)
(3,556)
0.01 3,556
83 📉
(Org: 82)
(3,498)
0 3,498
84 ➡️
(Org: 84)
(3,386)
0.02 3,386
85 ➡️
(Org: 85)
(3,367)
0.01 3,367
86 📈
(Org: 94)
(3,364)
0.1 3,364
87 📈
(Org: 98)
(3,334)
0.16 3,334
87 📈
(Org: 91)
(3,334)
0.05 3,334
89 📉
(Org: 88)
(3,264)
0.01 3,264
90 📉
(Org: 86)
(3,263)
0 3,263
91 📉
(Org: 87)
(3,250)
0 3,250
92 📈
(Org: 108)
(3,181)
0.24 3,181
93 📉
(Org: 89)
(3,166)
- 3,166
94 📉
(Org: 92)
(3,134)
0.02 3,134
95 📉
(Org: 93)
(3,117)
0.02 3,117
96 📈
(Org: 126)
(3,103)
0.34 3,103
97 ➡️
(Org: 97)
(3,068)
0.08 3,068
98 📉
(Org: 95)
(3,022)
0.01 3,022
99 📉
(Org: 96)
(2,925)
0.01 2,925
100 📈
(Org: 103)
(2,777)
0.04 2,777