Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1952 - 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)
(69,957)
0.04 69,957
2 ➡️
(Org: 2)
(66,200)
0.01 66,200
3 ➡️
(Org: 3)
(53,106)
0 53,106
4 ➡️
(Org: 4)
(51,017)
0.02 51,017
5 ➡️
(Org: 5)
(47,361)
0.13 47,361
6 ➡️
(Org: 6)
(39,870)
0 39,870
7 ➡️
(Org: 7)
(32,156)
0.01 32,156
8 ➡️
(Org: 8)
(29,221)
0.01 29,221
9 📈
(Org: 34)
(28,185)
0.61 28,185
10 📉
(Org: 9)
(27,265)
0.02 27,265
11 ➡️
(Org: 11)
(27,007)
0.05 27,007
12 📉
(Org: 10)
(26,550)
0.02 26,550
13 📉
(Org: 12)
(26,044)
0.08 26,044
14 📉
(Org: 13)
(24,136)
0.02 24,136
15 📉
(Org: 14)
(23,811)
0.02 23,811
16 📉
(Org: 15)
(21,439)
- 21,439
17 📈
(Org: 29)
(21,212)
0.42 21,212
18 📉
(Org: 17)
(21,192)
0.01 21,192
19 📉
(Org: 16)
(21,063)
- 21,063
20 ➡️
(Org: 20)
(20,464)
0.14 20,464
21 📉
(Org: 18)
(19,957)
0 19,957
22 📈
(Org: 37)
(19,016)
0.46 19,016
23 📉
(Org: 19)
(18,620)
0.04 18,620
24 📉
(Org: 21)
(17,278)
0.01 17,278
25 📉
(Org: 22)
(16,274)
0.02 16,274
26 📉
(Org: 23)
(14,978)
- 14,978
27 📈
(Org: 31)
(14,739)
0.17 14,739
28 📈
(Org: 61)
(14,523)
0.53 14,523
29 📉
(Org: 24)
(14,492)
0.02 14,492
30 📈
(Org: 52)
(14,346)
0.49 14,346
31 📉
(Org: 25)
(14,107)
0 14,107
32 📉
(Org: 26)
(13,879)
0.02 13,879
33 📉
(Org: 32)
(13,314)
0.09 13,314
34 📈
(Org: 39)
(13,288)
0.27 13,288
35 📉
(Org: 27)
(13,154)
0 13,154
36 📉
(Org: 28)
(12,545)
0 12,545
37 📉
(Org: 30)
(12,487)
0.02 12,487
38 📉
(Org: 33)
(11,711)
0.01 11,711
39 📉
(Org: 35)
(10,623)
0.01 10,623
40 📉
(Org: 36)
(10,458)
- 10,458
41 📉
(Org: 38)
(10,232)
0.04 10,232
42 ➡️
(Org: 42)
(9,884)
0.06 9,884
43 📉
(Org: 40)
(9,703)
0 9,703
44 📉
(Org: 41)
(9,580)
0.02 9,580
45 📈
(Org: 58)
(9,270)
0.25 9,270
46 📉
(Org: 43)
(9,234)
0.03 9,234
47 📉
(Org: 44)
(8,837)
0.01 8,837
48 📉
(Org: 45)
(8,652)
- 8,652
49 📉
(Org: 46)
(8,629)
0 8,629
50 📉
(Org: 47)
(8,577)
0 8,577
51 📈
(Org: 71)
(8,398)
0.31 8,398
52 📉
(Org: 49)
(8,180)
0 8,180
53 ➡️
(Org: 53)
(7,724)
0.07 7,724
54 📉
(Org: 50)
(7,613)
0.01 7,613
55 📉
(Org: 51)
(7,401)
0 7,401
56 📉
(Org: 55)
(7,266)
0.02 7,266
57 📉
(Org: 54)
(7,217)
0.01 7,217
58 📈
(Org: 100)
(7,032)
0.47 7,032
59 📈
(Org: 63)
(7,020)
0.08 7,020
60 📉
(Org: 57)
(6,963)
0 6,963
61 📈
(Org: 62)
(6,553)
- 6,553
62 📈
(Org: 65)
(6,380)
0.04 6,380
63 📈
(Org: 67)
(6,341)
0.04 6,341
64 📈
(Org: 110)
(6,333)
0.46 6,333
65 📈
(Org: 66)
(6,290)
0.02 6,290
66 📈
(Org: 120)
(6,267)
0.52 6,267
67 📉
(Org: 64)
(6,218)
- 6,218
68 ➡️
(Org: 68)
(6,140)
0.03 6,140
69 📈
(Org: 93)
(6,097)
0.34 6,097
70 📉
(Org: 69)
(5,908)
- 5,908
71 📉
(Org: 70)
(5,859)
0 5,859
72 ➡️
(Org: 72)
(5,726)
0.01 5,726
73 ➡️
(Org: 73)
(5,725)
0.01 5,725
74 📈
(Org: 77)
(5,692)
0.05 5,692
75 📉
(Org: 74)
(5,608)
0 5,608
76 📉
(Org: 75)
(5,583)
- 5,583
77 📈
(Org: 81)
(5,551)
0.09 5,551
78 📈
(Org: 79)
(5,257)
- 5,257
79 📈
(Org: 82)
(5,236)
0.05 5,236
80 ➡️
(Org: 80)
(5,226)
0 5,226
81 📈
(Org: 83)
(5,033)
0.02 5,033
82 📈
(Org: 115)
(4,992)
0.34 4,992
83 📈
(Org: 96)
(4,933)
0.21 4,933
84 📈
(Org: 85)
(4,571)
0.02 4,571
85 📈
(Org: 95)
(4,459)
0.11 4,459
86 ➡️
(Org: 86)
(4,454)
0.02 4,454
87 ➡️
(Org: 87)
(4,304)
0.01 4,304
88 📈
(Org: 102)
(4,285)
0.15 4,285
89 📈
(Org: 106)
(4,245)
0.16 4,245
90 📉
(Org: 88)
(4,237)
0 4,237
91 📉
(Org: 90)
(4,219)
0.02 4,219
92 📉
(Org: 89)
(4,211)
0 4,211
93 📉
(Org: 91)
(4,134)
- 4,134
94 ➡️
(Org: 94)
(4,119)
0.02 4,119
95 📉
(Org: 92)
(4,116)
- 4,116
96 📈
(Org: 98)
(3,943)
0.03 3,943
97 📈
(Org: 99)
(3,919)
0.03 3,919
98 📉
(Org: 97)
(3,903)
0.01 3,903
99 📈
(Org: 104)
(3,899)
0.08 3,899
100 📈
(Org: 108)
(3,820)
0.09 3,820