Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1953 - 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)
(64,981)
0.01 64,981
2 ➡️
(Org: 2)
(63,638)
0.04 63,638
3 ➡️
(Org: 3)
(53,516)
0.02 53,516
4 ➡️
(Org: 4)
(51,026)
0 51,026
5 ➡️
(Org: 5)
(51,015)
0.13 51,015
6 ➡️
(Org: 6)
(38,483)
0 38,483
7 ➡️
(Org: 7)
(37,398)
0.01 37,398
8 ➡️
(Org: 8)
(31,072)
0.01 31,072
9 ➡️
(Org: 9)
(30,219)
0.01 30,219
10 📈
(Org: 35)
(27,406)
0.6 27,406
11 📉
(Org: 10)
(26,155)
0.02 26,155
12 📉
(Org: 11)
(25,872)
0.01 25,872
13 📉
(Org: 12)
(25,211)
0 25,211
14 ➡️
(Org: 14)
(24,911)
0.05 24,911
15 📉
(Org: 13)
(24,693)
0.02 24,693
16 ➡️
(Org: 16)
(24,110)
0.08 24,110
17 📉
(Org: 15)
(23,439)
0.02 23,439
18 📈
(Org: 23)
(22,715)
0.41 22,715
19 📉
(Org: 17)
(21,350)
- 21,350
20 📉
(Org: 18)
(20,123)
- 20,123
21 📈
(Org: 37)
(18,985)
0.49 18,985
22 📉
(Org: 19)
(18,617)
0.05 18,617
23 📈
(Org: 42)
(16,929)
0.47 16,929
24 📉
(Org: 21)
(16,366)
0.02 16,366
25 📉
(Org: 20)
(16,349)
0.01 16,349
26 📈
(Org: 28)
(15,018)
0.18 15,018
27 📉
(Org: 22)
(14,627)
- 14,627
28 📈
(Org: 61)
(14,464)
0.53 14,464
29 📈
(Org: 32)
(14,002)
0.16 14,002
30 📈
(Org: 39)
(13,252)
0.28 13,252
30 📉
(Org: 24)
(13,252)
0.02 13,252
32 📉
(Org: 25)
(13,077)
0.01 13,077
33 📉
(Org: 27)
(12,978)
0.02 12,978
34 📉
(Org: 26)
(12,817)
0 12,817
35 📉
(Org: 33)
(12,494)
0.09 12,494
36 📉
(Org: 29)
(12,159)
0 12,159
37 📉
(Org: 31)
(12,016)
0.01 12,016
38 📉
(Org: 30)
(11,992)
0 11,992
39 📉
(Org: 34)
(11,333)
0.01 11,333
40 📉
(Org: 36)
(11,129)
0.03 11,129
41 📉
(Org: 38)
(9,686)
0 9,686
42 📉
(Org: 40)
(9,571)
0 9,571
43 📈
(Org: 58)
(9,552)
0.25 9,552
44 📉
(Org: 43)
(9,511)
0.06 9,511
45 📉
(Org: 41)
(9,263)
- 9,263
46 📉
(Org: 44)
(8,988)
0.03 8,988
47 📉
(Org: 45)
(8,817)
0.02 8,817
48 📉
(Org: 47)
(8,668)
0.01 8,668
49 📉
(Org: 46)
(8,579)
- 8,579
50 📈
(Org: 67)
(8,361)
0.28 8,361
51 📉
(Org: 49)
(8,179)
0 8,179
52 📉
(Org: 51)
(8,149)
0.06 8,149
53 📈
(Org: 54)
(7,704)
0.02 7,704
54 📉
(Org: 52)
(7,687)
0.02 7,687
55 📉
(Org: 53)
(7,568)
0 7,568
56 📉
(Org: 55)
(7,447)
0 7,447
57 📈
(Org: 117)
(7,418)
0.55 7,418
58 📈
(Org: 102)
(7,411)
0.5 7,411
59 📉
(Org: 57)
(7,249)
0.01 7,249
60 📉
(Org: 59)
(7,009)
0 7,009
61 📉
(Org: 60)
(6,964)
- 6,964
62 📈
(Org: 66)
(6,952)
0.13 6,952
63 📈
(Org: 108)
(6,721)
0.46 6,721
64 📈
(Org: 65)
(6,635)
0.08 6,635
65 📉
(Org: 62)
(6,599)
0 6,599
66 📈
(Org: 103)
(6,460)
0.43 6,460
67 📉
(Org: 64)
(6,438)
0.02 6,438
68 📈
(Org: 69)
(6,192)
0.04 6,192
69 📈
(Org: 70)
(6,180)
0.04 6,180
70 📈
(Org: 93)
(6,163)
0.34 6,163
71 📉
(Org: 68)
(6,010)
0 6,010
72 ➡️
(Org: 72)
(6,009)
0.04 6,009
73 📈
(Org: 75)
(5,859)
0.05 5,859
74 ➡️
(Org: 74)
(5,776)
0.02 5,776
75 📉
(Org: 73)
(5,740)
- 5,740
76 📈
(Org: 81)
(5,675)
0.09 5,675
77 ➡️
(Org: 77)
(5,564)
0.01 5,564
78 📈
(Org: 85)
(5,563)
0.1 5,563
79 📉
(Org: 76)
(5,558)
0 5,558
80 📈
(Org: 86)
(5,279)
0.06 5,279
81 📉
(Org: 80)
(5,256)
- 5,256
82 ➡️
(Org: 82)
(5,172)
0 5,172
83 ➡️
(Org: 83)
(5,132)
- 5,132
84 ➡️
(Org: 84)
(5,085)
0 5,085
85 📈
(Org: 87)
(4,978)
0.02 4,978
86 📈
(Org: 109)
(4,702)
0.23 4,702
87 📈
(Org: 88)
(4,622)
0.01 4,622
88 📈
(Org: 89)
(4,413)
0 4,413
89 📈
(Org: 91)
(4,337)
0.03 4,337
90 ➡️
(Org: 90)
(4,311)
0 4,311
91 📈
(Org: 113)
(4,246)
0.17 4,246
92 📈
(Org: 96)
(4,220)
0.07 4,220
93 📉
(Org: 92)
(4,181)
0.02 4,181
94 📈
(Org: 99)
(4,127)
0.07 4,127
95 📉
(Org: 94)
(4,121)
0.01 4,121
96 📉
(Org: 95)
(4,030)
- 4,030
97 ➡️
(Org: 97)
(3,982)
0.03 3,982
98 📈
(Org: 101)
(3,959)
0.04 3,959
99 📈
(Org: 111)
(3,848)
0.06 3,848
100 📉
(Org: 98)
(3,837)
- 3,837