Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1965 - 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)
(60,792)
0.01 60,792
2 ➡️
(Org: 2)
(34,673)
0.01 34,673
3 ➡️
(Org: 3)
(33,210)
0.01 33,210
4 📈
(Org: 5)
(33,187)
0.21 33,187
5 📉
(Org: 4)
(31,694)
0.09 31,694
6 📈
(Org: 19)
(25,223)
0.38 25,223
7 📈
(Org: 18)
(25,180)
0.36 25,180
8 📈
(Org: 24)
(24,697)
0.41 24,697
9 📉
(Org: 6)
(23,571)
0 23,571
10 📈
(Org: 21)
(23,392)
0.35 23,392
11 📉
(Org: 8)
(20,971)
0.08 20,971
12 📉
(Org: 11)
(20,372)
0.12 20,372
13 📉
(Org: 7)
(20,130)
0.02 20,130
14 📉
(Org: 9)
(19,371)
0.01 19,371
15 📉
(Org: 10)
(18,834)
0 18,834
16 📈
(Org: 36)
(18,771)
0.4 18,771
17 📉
(Org: 13)
(18,125)
0.06 18,125
18 📉
(Org: 12)
(17,720)
0.01 17,720
19 📉
(Org: 17)
(17,647)
0.08 17,647
20 📉
(Org: 14)
(17,316)
0.02 17,316
21 📈
(Org: 57)
(17,240)
0.58 17,240
22 📈
(Org: 30)
(17,198)
0.26 17,198
23 📉
(Org: 16)
(16,864)
0.03 16,864
24 📉
(Org: 15)
(16,653)
0.02 16,653
25 📉
(Org: 20)
(15,650)
0.03 15,650
26 📉
(Org: 22)
(15,405)
0.02 15,405
27 📈
(Org: 31)
(15,260)
0.18 15,260
28 📉
(Org: 23)
(15,057)
- 15,057
29 📉
(Org: 25)
(14,033)
0 14,033
30 📈
(Org: 33)
(13,808)
0.13 13,808
31 📉
(Org: 26)
(13,499)
0.01 13,499
32 📉
(Org: 27)
(13,347)
0.02 13,347
33 📉
(Org: 28)
(13,095)
0 13,095
34 📉
(Org: 29)
(13,032)
0.02 13,032
35 📈
(Org: 37)
(12,932)
0.15 12,932
36 📉
(Org: 34)
(12,845)
0.08 12,845
37 📈
(Org: 54)
(12,825)
0.39 12,825
38 📉
(Org: 32)
(12,453)
0.02 12,453
39 📉
(Org: 35)
(11,530)
- 11,530
40 📈
(Org: 47)
(11,189)
0.16 11,189
41 📈
(Org: 42)
(11,096)
0.09 11,096
42 📉
(Org: 39)
(11,082)
0.05 11,082
43 📉
(Org: 38)
(11,066)
0.05 11,066
44 📉
(Org: 41)
(10,628)
0.04 10,628
45 📉
(Org: 44)
(10,517)
0.07 10,517
46 📉
(Org: 40)
(10,364)
- 10,364
47 📉
(Org: 43)
(10,084)
- 10,084
48 📉
(Org: 46)
(9,515)
0 9,515
49 📈
(Org: 69)
(9,488)
0.43 9,488
50 📈
(Org: 116)
(8,965)
0.63 8,965
51 📈
(Org: 84)
(8,646)
0.51 8,646
52 📈
(Org: 53)
(8,334)
0.07 8,334
53 📈
(Org: 55)
(8,274)
0.07 8,274
54 📉
(Org: 49)
(7,929)
0 7,929
55 📉
(Org: 50)
(7,902)
- 7,902
56 📉
(Org: 52)
(7,894)
0.01 7,894
57 📈
(Org: 114)
(7,864)
0.58 7,864
58 📉
(Org: 51)
(7,843)
0 7,843
59 📉
(Org: 56)
(7,767)
0.05 7,767
60 📉
(Org: 58)
(7,110)
0.02 7,110
61 📉
(Org: 59)
(6,782)
- 6,782
62 📈
(Org: 74)
(6,749)
0.26 6,749
63 📈
(Org: 76)
(6,585)
0.27 6,585
64 📉
(Org: 62)
(6,582)
0.08 6,582
65 📈
(Org: 80)
(6,369)
0.27 6,369
66 📉
(Org: 61)
(6,257)
0.02 6,257
67 📈
(Org: 70)
(6,129)
0.14 6,129
68 📉
(Org: 63)
(6,081)
- 6,081
69 📈
(Org: 92)
(6,034)
0.33 6,034
70 📉
(Org: 64)
(5,942)
0 5,942
71 📉
(Org: 66)
(5,798)
0 5,798
72 📉
(Org: 67)
(5,679)
0.01 5,679
73 📈
(Org: 75)
(5,672)
0.14 5,672
74 📈
(Org: 141)
(5,600)
0.53 5,600
75 📉
(Org: 68)
(5,497)
- 5,497
76 📈
(Org: 127)
(5,368)
0.43 5,368
77 📉
(Org: 71)
(5,323)
0.01 5,323
78 📉
(Org: 72)
(5,239)
0.02 5,239
79 📉
(Org: 73)
(5,031)
- 5,031
80 📈
(Org: 206)
(5,020)
0.68 5,020
81 📉
(Org: 78)
(4,964)
0.05 4,964
82 📈
(Org: 128)
(4,958)
0.39 4,958
83 📈
(Org: 110)
(4,750)
0.28 4,750
84 📉
(Org: 77)
(4,725)
- 4,725
85 📉
(Org: 81)
(4,719)
0.01 4,719
86 📈
(Org: 98)
(4,641)
0.17 4,641
87 📉
(Org: 83)
(4,599)
0.05 4,599
88 📉
(Org: 86)
(4,590)
0.08 4,590
89 📉
(Org: 82)
(4,555)
0 4,555
90 📈
(Org: 93)
(4,467)
0.1 4,467
91 📈
(Org: 95)
(4,455)
0.12 4,455
92 📉
(Org: 89)
(4,267)
0.03 4,267
93 📈
(Org: 157)
(4,260)
0.43 4,260
94 📉
(Org: 90)
(4,128)
- 4,128
95 📈
(Org: 97)
(4,106)
0.05 4,106
96 📈
(Org: 134)
(4,073)
0.3 4,073
97 📉
(Org: 91)
(4,064)
- 4,064
98 📉
(Org: 94)
(4,017)
- 4,017
99 📉
(Org: 96)
(3,920)
- 3,920
100 ➡️
(Org: 100)
(3,851)
0.01 3,851