Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1964 - 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)
(54,827)
0.01 54,827
2 ➡️
(Org: 2)
(41,501)
0.01 41,501
3 ➡️
(Org: 3)
(39,074)
0.19 39,074
4 ➡️
(Org: 4)
(30,608)
0.01 30,608
5 📈
(Org: 15)
(29,905)
0.38 29,905
6 📈
(Org: 21)
(27,476)
0.4 27,476
7 📉
(Org: 6)
(26,657)
0.09 26,657
8 📉
(Org: 5)
(26,105)
0 26,105
9 📉
(Org: 8)
(25,649)
0.08 25,649
10 📈
(Org: 23)
(24,324)
0.33 24,324
11 📉
(Org: 7)
(24,313)
0.02 24,313
12 📉
(Org: 10)
(22,832)
0.12 22,832
13 📈
(Org: 14)
(20,591)
0.08 20,591
14 📉
(Org: 9)
(20,456)
0.01 20,456
15 📉
(Org: 12)
(20,436)
0.06 20,436
16 📉
(Org: 11)
(20,164)
0.02 20,164
17 📈
(Org: 28)
(19,994)
0.29 19,994
18 📉
(Org: 13)
(19,575)
0.02 19,575
19 📈
(Org: 54)
(19,451)
0.58 19,451
20 📉
(Org: 16)
(17,817)
0.03 17,817
21 📉
(Org: 17)
(17,619)
0.02 17,619
22 📈
(Org: 35)
(17,251)
0.28 17,251
23 📈
(Org: 29)
(17,242)
0.18 17,242
24 📉
(Org: 18)
(17,105)
- 17,105
25 📈
(Org: 39)
(16,965)
0.39 16,965
26 📈
(Org: 40)
(16,877)
0.4 16,877
27 ➡️
(Org: 27)
(16,735)
0.14 16,735
28 📉
(Org: 20)
(16,715)
0.02 16,715
29 📉
(Org: 19)
(16,499)
0 16,499
30 📉
(Org: 22)
(16,344)
0.01 16,344
31 📉
(Org: 24)
(15,591)
0.02 15,591
32 📉
(Org: 26)
(14,931)
0.02 14,931
33 📉
(Org: 25)
(14,789)
0 14,789
34 📉
(Org: 30)
(14,448)
0.08 14,448
35 📈
(Org: 37)
(14,087)
0.15 14,087
36 ➡️
(Org: 36)
(13,396)
0.09 13,396
37 📉
(Org: 31)
(13,360)
0.03 13,360
38 📉
(Org: 32)
(12,866)
- 12,866
39 📉
(Org: 34)
(12,765)
0.02 12,765
40 📉
(Org: 33)
(12,758)
0.01 12,758
41 📈
(Org: 62)
(12,590)
0.43 12,590
42 📈
(Org: 43)
(11,499)
0.16 11,499
43 📈
(Org: 99)
(10,625)
0.61 10,625
44 📉
(Org: 41)
(10,185)
0 10,185
45 📉
(Org: 42)
(9,980)
- 9,980
46 📈
(Org: 48)
(9,979)
0.07 9,979
47 ➡️
(Org: 47)
(9,957)
0.06 9,957
48 📉
(Org: 46)
(9,855)
0.04 9,855
49 📉
(Org: 44)
(9,575)
- 9,575
50 📉
(Org: 45)
(9,513)
0 9,513
51 📉
(Org: 49)
(9,215)
0.01 9,215
52 ➡️
(Org: 52)
(9,042)
0.07 9,042
53 📈
(Org: 112)
(9,024)
0.59 9,024
54 📉
(Org: 50)
(8,958)
0.05 8,958
55 📉
(Org: 53)
(8,682)
0.04 8,682
56 📉
(Org: 55)
(8,596)
0.06 8,596
57 ➡️
(Org: 57)
(8,588)
0.08 8,588
58 📉
(Org: 51)
(8,473)
- 8,473
59 📉
(Org: 56)
(8,199)
0.02 8,199
60 📈
(Org: 123)
(7,919)
0.56 7,919
61 📈
(Org: 72)
(7,819)
0.27 7,819
62 📉
(Org: 60)
(7,758)
- 7,758
63 📈
(Org: 78)
(7,438)
0.28 7,438
64 📉
(Org: 61)
(7,273)
0 7,273
65 📉
(Org: 64)
(7,178)
0.02 7,178
66 📉
(Org: 63)
(7,086)
0 7,086
67 📈
(Org: 92)
(6,940)
0.34 6,940
68 📉
(Org: 65)
(6,705)
0 6,705
69 📈
(Org: 79)
(6,704)
0.22 6,704
70 📉
(Org: 66)
(6,651)
0.01 6,651
71 📉
(Org: 70)
(6,384)
0.05 6,384
72 📉
(Org: 68)
(6,242)
0.01 6,242
73 📈
(Org: 138)
(6,170)
0.53 6,170
74 📉
(Org: 69)
(6,162)
- 6,162
75 📈
(Org: 88)
(6,115)
0.23 6,115
76 📉
(Org: 73)
(6,043)
0.07 6,043
77 📉
(Org: 71)
(6,011)
- 6,011
78 📉
(Org: 74)
(5,939)
0.07 5,939
79 📈
(Org: 209)
(5,544)
0.7 5,544
80 ➡️
(Org: 80)
(5,466)
0.05 5,466
81 📉
(Org: 76)
(5,412)
- 5,412
82 📉
(Org: 77)
(5,387)
- 5,387
83 📉
(Org: 81)
(5,212)
0.01 5,212
84 📈
(Org: 145)
(5,207)
0.46 5,207
85 📈
(Org: 93)
(5,204)
0.12 5,204
86 📈
(Org: 115)
(5,058)
0.29 5,058
87 📈
(Org: 94)
(5,038)
0.1 5,038
88 📉
(Org: 83)
(5,005)
0 5,005
89 📈
(Org: 101)
(4,947)
0.18 4,947
90 📉
(Org: 85)
(4,914)
0 4,914
91 📉
(Org: 86)
(4,872)
- 4,872
92 📉
(Org: 89)
(4,871)
0.04 4,871
93 📈
(Org: 125)
(4,861)
0.29 4,861
93 📉
(Org: 87)
(4,861)
- 4,861
95 📉
(Org: 90)
(4,772)
0.02 4,772
96 ➡️
(Org: 96)
(4,643)
0.05 4,643
97 📉
(Org: 91)
(4,635)
0.01 4,635
98 📈
(Org: 153)
(4,543)
0.43 4,543
99 📉
(Org: 95)
(4,450)
- 4,450
100 📈
(Org: 102)
(4,343)
0.06 4,343