Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1967 - 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)
(52,855)
0.01 52,855
2 📈
(Org: 3)
(41,711)
0.26 41,711
3 📉
(Org: 2)
(36,178)
0.09 36,178
4 📈
(Org: 5)
(28,738)
0.23 28,738
5 📈
(Org: 14)
(26,139)
0.39 26,139
6 📉
(Org: 4)
(25,689)
0.01 25,689
7 📉
(Org: 6)
(21,836)
0.01 21,836
8 ➡️
(Org: 8)
(20,976)
0.11 20,976
9 📈
(Org: 24)
(20,931)
0.35 20,931
10 📈
(Org: 28)
(20,798)
0.41 20,798
11 📈
(Org: 29)
(20,362)
0.41 20,362
12 📉
(Org: 7)
(19,627)
0 19,627
13 📉
(Org: 9)
(19,117)
0.04 19,117
14 📉
(Org: 10)
(18,638)
0.02 18,638
15 📈
(Org: 23)
(18,531)
0.26 18,531
16 📉
(Org: 11)
(17,758)
0 17,758
17 📉
(Org: 15)
(17,245)
0.08 17,245
18 📉
(Org: 13)
(16,661)
0.03 16,661
19 📉
(Org: 12)
(16,123)
- 16,123
20 📉
(Org: 16)
(15,838)
0.02 15,838
21 📈
(Org: 55)
(15,694)
0.6 15,694
22 📉
(Org: 17)
(15,641)
0.02 15,641
23 📉
(Org: 18)
(15,450)
0.01 15,450
24 📉
(Org: 19)
(15,187)
0.03 15,187
25 📉
(Org: 20)
(15,007)
0.02 15,007
26 📉
(Org: 22)
(14,817)
0.05 14,817
27 📉
(Org: 25)
(14,798)
0.1 14,798
28 📉
(Org: 26)
(14,363)
0.08 14,363
29 📉
(Org: 21)
(14,305)
0.01 14,305
30 📉
(Org: 27)
(13,296)
0.01 13,296
31 📈
(Org: 35)
(13,193)
0.18 13,193
32 📉
(Org: 30)
(12,201)
0.02 12,201
33 📉
(Org: 32)
(12,138)
0.08 12,138
34 📉
(Org: 31)
(11,478)
- 11,478
35 📈
(Org: 69)
(11,375)
0.55 11,375
36 📉
(Org: 33)
(11,213)
0 11,213
37 📉
(Org: 34)
(11,136)
0 11,136
38 📈
(Org: 41)
(10,916)
0.17 10,916
39 📉
(Org: 37)
(10,447)
0.02 10,447
40 📉
(Org: 38)
(10,419)
0.02 10,419
41 📉
(Org: 39)
(10,291)
0.05 10,291
42 📉
(Org: 40)
(10,136)
0.09 10,136
43 📈
(Org: 45)
(9,195)
0.16 9,195
44 📈
(Org: 64)
(8,936)
0.39 8,936
45 📉
(Org: 42)
(8,911)
0 8,911
46 📈
(Org: 53)
(8,869)
0.26 8,869
47 📈
(Org: 52)
(8,459)
0.18 8,459
48 📉
(Org: 47)
(8,278)
0.1 8,278
49 📈
(Org: 77)
(7,896)
0.43 7,896
50 📉
(Org: 44)
(7,818)
- 7,818
51 📉
(Org: 46)
(7,699)
0 7,699
52 📉
(Org: 51)
(7,540)
0.05 7,540
53 📉
(Org: 50)
(7,427)
0 7,427
54 📉
(Org: 48)
(7,423)
0 7,423
55 📉
(Org: 49)
(7,407)
- 7,407
56 📉
(Org: 54)
(7,196)
0.12 7,196
57 📈
(Org: 113)
(6,955)
0.57 6,955
58 📈
(Org: 147)
(6,552)
0.64 6,552
59 📈
(Org: 165)
(6,546)
0.69 6,546
60 📈
(Org: 115)
(6,392)
0.54 6,392
61 📈
(Org: 83)
(6,355)
0.35 6,355
62 📉
(Org: 56)
(6,326)
- 6,326
63 📉
(Org: 58)
(6,296)
0.01 6,296
64 📉
(Org: 57)
(6,253)
0 6,253
65 📉
(Org: 59)
(6,238)
0.07 6,238
66 📉
(Org: 61)
(6,228)
0.09 6,228
67 📉
(Org: 66)
(6,051)
0.12 6,051
68 📈
(Org: 103)
(5,934)
0.43 5,934
69 📉
(Org: 60)
(5,839)
0.02 5,839
70 📈
(Org: 82)
(5,831)
0.28 5,831
71 📉
(Org: 62)
(5,565)
- 5,565
72 📈
(Org: 81)
(5,452)
0.23 5,452
73 📉
(Org: 65)
(5,362)
0 5,362
74 📉
(Org: 67)
(5,199)
0 5,199
75 📉
(Org: 71)
(5,168)
0.05 5,168
76 📉
(Org: 68)
(5,164)
- 5,164
77 📉
(Org: 70)
(5,124)
0.03 5,124
78 📉
(Org: 73)
(4,784)
0.01 4,784
79 📉
(Org: 75)
(4,681)
0.02 4,681
80 📈
(Org: 104)
(4,500)
0.26 4,500
81 📉
(Org: 79)
(4,467)
- 4,467
82 📈
(Org: 94)
(4,454)
0.18 4,454
83 📉
(Org: 80)
(4,370)
0 4,370
84 📈
(Org: 107)
(4,183)
0.24 4,183
85 📉
(Org: 84)
(4,103)
- 4,103
86 📉
(Org: 85)
(4,050)
0.01 4,050
87 📉
(Org: 86)
(4,049)
0.01 4,049
88 📈
(Org: 90)
(4,037)
0.07 4,037
89 📈
(Org: 96)
(4,005)
0.1 4,005
90 📉
(Org: 88)
(3,921)
0.01 3,921
91 📉
(Org: 87)
(3,904)
- 3,904
92 📈
(Org: 105)
(3,901)
0.15 3,901
93 📉
(Org: 89)
(3,841)
- 3,841
94 📉
(Org: 91)
(3,727)
- 3,727
95 ➡️
(Org: 95)
(3,717)
0.02 3,717
96 📉
(Org: 93)
(3,670)
0 3,670
97 📈
(Org: 101)
(3,540)
0.03 3,540
98 ➡️
(Org: 98)
(3,523)
0 3,523
99 ➡️
(Org: 99)
(3,514)
- 3,514
100 ➡️
(Org: 100)
(3,513)
0.01 3,513