Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1987 - 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: 2)
(57,711)
0.05 57,711
2 📉
(Org: 1)
(56,882)
0.02 56,882
3 ➡️
(Org: 3)
(41,840)
0 41,840
4 📈
(Org: 5)
(38,072)
0.27 38,072
5 📉
(Org: 4)
(33,489)
0.02 33,489
6 ➡️
(Org: 6)
(25,264)
0.11 25,264
7 ➡️
(Org: 7)
(24,396)
0.09 24,396
8 ➡️
(Org: 8)
(23,561)
0.14 23,561
9 📈
(Org: 28)
(22,452)
0.54 22,452
10 📈
(Org: 42)
(22,193)
0.67 22,193
11 📈
(Org: 20)
(21,197)
0.35 21,197
12 📉
(Org: 10)
(19,421)
0.04 19,421
13 📈
(Org: 17)
(19,141)
0.18 19,141
14 📉
(Org: 9)
(18,995)
0 18,995
15 📉
(Org: 12)
(18,872)
0.06 18,872
16 📉
(Org: 13)
(18,323)
0.04 18,323
17 📉
(Org: 14)
(18,283)
0.07 18,283
18 📉
(Org: 11)
(18,031)
0 18,031
19 📉
(Org: 16)
(17,037)
0.02 17,037
20 📈
(Org: 26)
(16,923)
0.35 16,923
21 📉
(Org: 15)
(16,783)
0 16,783
22 📉
(Org: 18)
(15,826)
0.07 15,826
23 📉
(Org: 19)
(15,299)
0.04 15,299
24 📈
(Org: 30)
(14,722)
0.33 14,722
25 📉
(Org: 21)
(14,443)
0.1 14,443
26 📈
(Org: 31)
(14,073)
0.34 14,073
27 📉
(Org: 23)
(13,921)
0.06 13,921
28 📉
(Org: 25)
(13,836)
0.16 13,836
29 📉
(Org: 22)
(13,387)
0.03 13,387
30 📈
(Org: 63)
(12,211)
0.59 12,211
31 📉
(Org: 24)
(11,787)
- 11,787
32 📈
(Org: 44)
(11,101)
0.34 11,101
33 📉
(Org: 27)
(10,961)
0.03 10,961
34 📈
(Org: 54)
(10,546)
0.47 10,546
35 📉
(Org: 33)
(10,515)
0.15 10,515
36 📈
(Org: 39)
(9,513)
0.17 9,513
37 📈
(Org: 47)
(9,258)
0.28 9,258
38 📉
(Org: 32)
(9,208)
0.03 9,208
39 📉
(Org: 34)
(9,143)
0.03 9,143
40 📈
(Org: 41)
(9,101)
0.18 9,101
41 📉
(Org: 38)
(9,076)
0.1 9,076
42 📉
(Org: 35)
(8,638)
0.01 8,638
43 📉
(Org: 36)
(8,496)
- 8,496
44 📉
(Org: 37)
(8,490)
0.01 8,490
45 📈
(Org: 61)
(8,344)
0.39 8,344
46 ➡️
(Org: 46)
(7,831)
0.13 7,831
47 📉
(Org: 40)
(7,802)
0.03 7,802
48 📉
(Org: 43)
(7,650)
0.04 7,650
49 📉
(Org: 45)
(7,065)
0.01 7,065
50 📈
(Org: 101)
(6,966)
0.61 6,966
51 📈
(Org: 88)
(6,952)
0.53 6,952
52 📉
(Org: 49)
(6,920)
0.06 6,920
53 📈
(Org: 60)
(6,523)
0.21 6,523
54 📈
(Org: 81)
(6,476)
0.45 6,476
55 📈
(Org: 181)
(6,309)
0.76 6,309
56 📉
(Org: 50)
(6,300)
0.01 6,300
57 📉
(Org: 52)
(6,208)
0.01 6,208
58 📉
(Org: 53)
(6,128)
0.07 6,128
59 📉
(Org: 57)
(6,000)
0.12 6,000
60 📉
(Org: 56)
(5,844)
0.09 5,844
61 📈
(Org: 68)
(5,602)
0.19 5,602
62 📉
(Org: 59)
(5,534)
0.06 5,534
63 📈
(Org: 67)
(5,487)
0.17 5,487
64 📉
(Org: 58)
(5,295)
- 5,295
65 📉
(Org: 64)
(5,091)
0.06 5,091
66 📈
(Org: 71)
(5,027)
0.15 5,027
67 📉
(Org: 66)
(4,970)
0.08 4,970
68 📈
(Org: 120)
(4,955)
0.53 4,955
69 📉
(Org: 65)
(4,826)
0.02 4,826
70 📉
(Org: 69)
(4,751)
0.06 4,751
71 📈
(Org: 79)
(4,718)
0.21 4,718
72 📈
(Org: 73)
(4,462)
0.07 4,462
73 📉
(Org: 72)
(4,428)
0.06 4,428
74 📈
(Org: 122)
(4,130)
0.45 4,130
75 📈
(Org: 104)
(4,127)
0.35 4,127
76 📈
(Org: 108)
(4,071)
0.37 4,071
77 📈
(Org: 82)
(4,040)
0.15 4,040
78 📈
(Org: 117)
(4,021)
0.4 4,021
79 📈
(Org: 139)
(3,970)
0.5 3,970
80 📉
(Org: 76)
(3,955)
0.01 3,955
81 📉
(Org: 77)
(3,854)
0 3,854
82 📈
(Org: 91)
(3,820)
0.18 3,820
83 📉
(Org: 78)
(3,811)
0.01 3,811
84 📈
(Org: 89)
(3,738)
0.15 3,738
85 📉
(Org: 80)
(3,685)
0.02 3,685
86 📈
(Org: 109)
(3,629)
0.3 3,629
87 📈
(Org: 154)
(3,599)
0.51 3,599
88 📉
(Org: 83)
(3,575)
0.04 3,575
89 📉
(Org: 84)
(3,541)
0.04 3,541
90 📈
(Org: 155)
(3,455)
0.49 3,455
91 📉
(Org: 87)
(3,439)
0.04 3,439
91 📈
(Org: 178)
(3,439)
0.55 3,439
93 📉
(Org: 85)
(3,377)
0.01 3,377
94 📈
(Org: 97)
(3,351)
0.14 3,351
95 📉
(Org: 86)
(3,346)
0 3,346
96 📈
(Org: 125)
(3,327)
0.32 3,327
97 📉
(Org: 90)
(3,182)
0.01 3,182
98 📈
(Org: 196)
(3,141)
0.55 3,141
99 📉
(Org: 96)
(3,132)
0.07 3,132
100 📉
(Org: 94)
(3,112)
0.05 3,112