Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1960 - 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)
(52,078)
0.01 52,078
2 ➡️
(Org: 2)
(46,222)
0.15 46,222
3 ➡️
(Org: 3)
(39,492)
0.06 39,492
4 ➡️
(Org: 4)
(36,763)
0.01 36,763
5 ➡️
(Org: 5)
(34,629)
0.01 34,629
6 ➡️
(Org: 6)
(34,327)
0.02 34,327
7 📈
(Org: 20)
(32,556)
0.43 32,556
8 📉
(Org: 7)
(32,116)
0 32,116
9 📈
(Org: 19)
(31,201)
0.4 31,201
10 📈
(Org: 21)
(29,496)
0.37 29,496
11 📉
(Org: 8)
(27,091)
0.01 27,091
12 📉
(Org: 10)
(27,070)
0.07 27,070
13 📉
(Org: 9)
(26,836)
0 26,836
14 📉
(Org: 11)
(24,894)
0.01 24,894
15 📉
(Org: 12)
(24,469)
0 24,469
16 📉
(Org: 13)
(23,970)
0 23,970
17 📈
(Org: 42)
(22,656)
0.58 22,656
18 📉
(Org: 14)
(22,479)
0.02 22,479
19 📉
(Org: 17)
(22,451)
0.15 22,451
20 📉
(Org: 15)
(22,169)
0.01 22,169
21 📉
(Org: 16)
(20,748)
0.02 20,748
22 📉
(Org: 18)
(19,342)
0.02 19,342
23 ➡️
(Org: 23)
(19,300)
0.1 19,300
24 📈
(Org: 26)
(18,811)
0.1 18,811
25 📉
(Org: 24)
(18,423)
0.07 18,423
26 📉
(Org: 24)
(18,302)
0.07 18,302
27 📉
(Org: 22)
(17,909)
- 17,909
28 📉
(Org: 27)
(17,265)
0.07 17,265
29 📈
(Org: 49)
(17,095)
0.49 17,095
30 📈
(Org: 31)
(16,998)
0.16 16,998
31 📉
(Org: 28)
(16,399)
0.02 16,399
32 📉
(Org: 30)
(15,937)
0.06 15,937
33 ➡️
(Org: 33)
(15,738)
0.11 15,738
34 📈
(Org: 39)
(15,698)
0.37 15,698
35 📉
(Org: 29)
(15,125)
0 15,125
36 📉
(Org: 32)
(15,001)
0.05 15,001
37 📈
(Org: 80)
(14,364)
0.59 14,364
38 📈
(Org: 73)
(13,952)
0.56 13,952
39 📈
(Org: 40)
(12,503)
0.21 12,503
40 📉
(Org: 34)
(12,474)
- 12,474
41 📈
(Org: 52)
(11,599)
0.25 11,599
42 📉
(Org: 36)
(11,501)
0.01 11,501
43 📈
(Org: 44)
(10,695)
0.13 10,695
44 📉
(Org: 38)
(10,332)
0.04 10,332
45 📉
(Org: 41)
(9,621)
- 9,621
46 📈
(Org: 64)
(9,608)
0.29 9,608
47 📉
(Org: 43)
(9,548)
0.02 9,548
48 ➡️
(Org: 48)
(9,402)
0.06 9,402
49 📉
(Org: 46)
(9,358)
0.02 9,358
50 📈
(Org: 84)
(9,056)
0.36 9,056
51 📉
(Org: 47)
(9,014)
0.01 9,014
52 📈
(Org: 54)
(8,792)
0.05 8,792
53 📉
(Org: 50)
(8,706)
0 8,706
54 📉
(Org: 51)
(8,683)
0 8,683
55 📉
(Org: 53)
(8,340)
0 8,340
56 📉
(Org: 55)
(8,070)
0 8,070
57 ➡️
(Org: 57)
(7,949)
0.02 7,949
58 📉
(Org: 56)
(7,908)
- 7,908
59 📉
(Org: 58)
(7,775)
0 7,775
60 📉
(Org: 59)
(7,559)
0 7,559
61 📈
(Org: 67)
(7,531)
0.13 7,531
62 📈
(Org: 90)
(7,529)
0.28 7,529
63 📉
(Org: 61)
(7,522)
0.04 7,522
64 📉
(Org: 60)
(7,442)
0.01 7,442
65 📉
(Org: 63)
(7,239)
0.05 7,239
66 📉
(Org: 62)
(7,192)
0.01 7,192
67 📈
(Org: 85)
(7,182)
0.21 7,182
68 ➡️
(Org: 68)
(6,937)
0.06 6,937
69 📉
(Org: 65)
(6,751)
0.01 6,751
70 📉
(Org: 66)
(6,736)
0.01 6,736
71 ➡️
(Org: 71)
(6,630)
0.04 6,630
72 📉
(Org: 69)
(6,586)
0.02 6,586
73 📉
(Org: 70)
(6,416)
0 6,416
74 📈
(Org: 75)
(6,409)
0.05 6,409
75 📉
(Org: 72)
(6,283)
0 6,283
76 📈
(Org: 116)
(6,244)
0.33 6,244
77 📉
(Org: 74)
(6,163)
0 6,163
78 📉
(Org: 76)
(6,066)
0.01 6,066
79 📈
(Org: 110)
(6,029)
0.27 6,029
80 📉
(Org: 77)
(5,973)
- 5,973
81 📉
(Org: 79)
(5,958)
- 5,958
82 📈
(Org: 83)
(5,831)
- 5,831
83 📈
(Org: 130)
(5,816)
0.4 5,816
84 📈
(Org: 179)
(5,726)
0.61 5,726
85 📈
(Org: 86)
(5,707)
0.01 5,707
86 📈
(Org: 145)
(5,657)
0.48 5,657
87 ➡️
(Org: 87)
(5,650)
0 5,650
88 ➡️
(Org: 88)
(5,636)
- 5,636
89 📈
(Org: 91)
(5,593)
0.06 5,593
90 📈
(Org: 92)
(5,534)
0.05 5,534
91 📈
(Org: 96)
(5,216)
0.04 5,216
92 📈
(Org: 93)
(5,207)
- 5,207
93 📈
(Org: 94)
(5,151)
0 5,151
94 📈
(Org: 95)
(5,084)
0 5,084
95 📈
(Org: 103)
(5,069)
0.07 5,069
96 📈
(Org: 107)
(4,965)
0.1 4,965
97 ➡️
(Org: 97)
(4,961)
0 4,961
98 ➡️
(Org: 98)
(4,891)
0 4,891
99 📈
(Org: 102)
(4,812)
0.01 4,812
100 📈
(Org: 104)
(4,659)
- 4,659