Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1932 - 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)
(59,977)
0 59,977
2 ➡️
(Org: 2)
(36,897)
0.07 36,897
3 📈
(Org: 5)
(27,951)
0.25 27,951
4 📉
(Org: 3)
(26,324)
0 26,324
5 📉
(Org: 4)
(25,027)
0 25,027
6 ➡️
(Org: 6)
(17,995)
0 17,995
7 📈
(Org: 8)
(16,970)
0.04 16,970
8 📉
(Org: 7)
(16,836)
0.02 16,836
9 ➡️
(Org: 9)
(14,505)
0 14,505
10 ➡️
(Org: 10)
(13,124)
0.02 13,124
11 ➡️
(Org: 11)
(12,298)
0 12,298
12 ➡️
(Org: 12)
(11,375)
0 11,375
13 ➡️
(Org: 13)
(11,042)
0.01 11,042
14 📈
(Org: 39)
(11,035)
0.51 11,035
15 📈
(Org: 16)
(10,913)
0.03 10,913
16 📉
(Org: 15)
(10,883)
0.02 10,883
17 📉
(Org: 14)
(10,772)
0 10,772
18 📉
(Org: 17)
(10,178)
0.02 10,178
19 ➡️
(Org: 19)
(9,970)
0.04 9,970
20 ➡️
(Org: 20)
(9,651)
0.01 9,651
21 📉
(Org: 18)
(9,630)
- 9,630
22 📉
(Org: 21)
(8,536)
- 8,536
23 📉
(Org: 22)
(8,448)
0 8,448
24 📉
(Org: 23)
(8,094)
0.02 8,094
25 📈
(Org: 32)
(8,066)
0.19 8,066
26 📉
(Org: 24)
(7,924)
- 7,924
27 📉
(Org: 25)
(7,813)
- 7,813
28 📈
(Org: 29)
(7,802)
0.06 7,802
29 📈
(Org: 43)
(7,710)
0.33 7,710
30 📉
(Org: 26)
(7,643)
- 7,643
31 📉
(Org: 28)
(7,598)
0.01 7,598
32 📉
(Org: 27)
(7,588)
0 7,588
33 📉
(Org: 30)
(7,464)
0.02 7,464
34 📉
(Org: 31)
(6,940)
0 6,940
35 📉
(Org: 33)
(6,476)
- 6,476
36 📉
(Org: 34)
(6,195)
- 6,195
37 📉
(Org: 35)
(6,093)
0.05 6,093
38 📉
(Org: 37)
(5,812)
0.04 5,812
39 📉
(Org: 36)
(5,648)
0 5,648
40 📉
(Org: 38)
(5,645)
0.03 5,645
41 📉
(Org: 40)
(5,607)
0.03 5,607
42 ➡️
(Org: 42)
(5,590)
0.05 5,590
43 📈
(Org: 45)
(5,539)
0.13 5,539
44 📉
(Org: 41)
(5,385)
- 5,385
45 📈
(Org: 67)
(5,362)
0.33 5,362
46 📉
(Org: 44)
(4,844)
- 4,844
47 📈
(Org: 60)
(4,706)
0.19 4,706
48 📉
(Org: 46)
(4,621)
0.01 4,621
49 📉
(Org: 47)
(4,570)
0.01 4,570
50 📈
(Org: 55)
(4,528)
0.08 4,528
51 📉
(Org: 49)
(4,476)
0.03 4,476
52 📉
(Org: 48)
(4,413)
0.01 4,413
53 ➡️
(Org: 53)
(4,405)
0.03 4,405
54 📉
(Org: 52)
(4,283)
0.01 4,283
55 📉
(Org: 50)
(4,279)
- 4,279
56 📉
(Org: 51)
(4,272)
- 4,272
57 📉
(Org: 54)
(4,252)
0.02 4,252
58 📉
(Org: 56)
(4,152)
- 4,152
59 📉
(Org: 57)
(4,117)
0.01 4,117
60 📈
(Org: 63)
(4,027)
0.09 4,027
61 📉
(Org: 58)
(4,012)
- 4,012
62 📈
(Org: 71)
(3,983)
0.11 3,983
63 📉
(Org: 59)
(3,936)
0.01 3,936
64 📉
(Org: 61)
(3,867)
0.03 3,867
65 📈
(Org: 85)
(3,671)
0.22 3,671
66 📉
(Org: 64)
(3,667)
0.01 3,667
67 📈
(Org: 68)
(3,649)
0.02 3,649
68 📉
(Org: 65)
(3,635)
0.01 3,635
69 📉
(Org: 66)
(3,607)
- 3,607
70 📉
(Org: 69)
(3,570)
- 3,570
71 📉
(Org: 70)
(3,569)
0 3,569
72 ➡️
(Org: 72)
(3,563)
0.01 3,563
73 📈
(Org: 86)
(3,520)
0.19 3,520
74 📉
(Org: 73)
(3,507)
0 3,507
75 📈
(Org: 84)
(3,500)
0.17 3,500
76 📈
(Org: 78)
(3,453)
0.07 3,453
77 📉
(Org: 75)
(3,395)
0.02 3,395
78 📈
(Org: 106)
(3,376)
0.32 3,376
79 📉
(Org: 74)
(3,363)
- 3,363
80 📉
(Org: 76)
(3,350)
0.01 3,350
81 📈
(Org: 100)
(3,349)
0.26 3,349
82 📉
(Org: 77)
(3,254)
- 3,254
83 📉
(Org: 80)
(3,220)
0.03 3,220
84 📉
(Org: 83)
(3,085)
0.05 3,085
85 📈
(Org: 88)
(3,045)
0.1 3,045
86 📉
(Org: 81)
(2,969)
- 2,969
87 📈
(Org: 89)
(2,964)
0.07 2,964
88 📉
(Org: 82)
(2,959)
- 2,959
89 📈
(Org: 93)
(2,876)
0.08 2,876
90 📉
(Org: 87)
(2,795)
0 2,795
91 📉
(Org: 90)
(2,753)
0.03 2,753
92 📈
(Org: 111)
(2,708)
0.18 2,708
93 📉
(Org: 90)
(2,675)
0 2,675
94 📉
(Org: 92)
(2,657)
- 2,657
95 📈
(Org: 103)
(2,632)
0.09 2,632
96 📉
(Org: 94)
(2,628)
- 2,628
97 📉
(Org: 96)
(2,583)
0.01 2,583
98 📉
(Org: 97)
(2,560)
0 2,560
99 📉
(Org: 98)
(2,526)
0 2,526
100 📈
(Org: 101)
(2,524)
0.02 2,524