Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1981 - 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)
(58,184)
0.02 58,184
2 ➡️
(Org: 2)
(42,988)
0.01 42,988
3 📈
(Org: 4)
(39,606)
0.29 39,606
4 📉
(Org: 3)
(34,400)
0 34,400
5 ➡️
(Org: 5)
(29,006)
0.03 29,006
6 📈
(Org: 31)
(28,102)
0.65 28,102
7 ➡️
(Org: 7)
(23,792)
0.15 23,792
8 ➡️
(Org: 8)
(22,692)
0.11 22,692
9 ➡️
(Org: 9)
(21,006)
0.04 21,006
10 📉
(Org: 6)
(20,344)
- 20,344
11 ➡️
(Org: 11)
(20,222)
0.12 20,222
12 📈
(Org: 17)
(20,065)
0.28 20,065
13 📈
(Org: 39)
(19,891)
0.58 19,891
14 📈
(Org: 16)
(19,838)
0.2 19,838
15 📉
(Org: 12)
(19,175)
0.13 19,175
16 📉
(Org: 10)
(17,960)
0 17,960
17 📉
(Org: 14)
(17,859)
0.08 17,859
18 📉
(Org: 13)
(17,809)
0.06 17,809
19 📈
(Org: 23)
(16,616)
0.29 16,616
20 📉
(Org: 15)
(16,022)
0.01 16,022
21 📈
(Org: 22)
(15,234)
0.17 15,234
22 📉
(Org: 18)
(14,544)
0.02 14,544
23 📉
(Org: 19)
(14,136)
0.02 14,136
24 📉
(Org: 20)
(13,841)
0 13,841
25 📉
(Org: 21)
(13,803)
0.04 13,803
26 📈
(Org: 41)
(13,522)
0.49 13,522
27 📈
(Org: 36)
(12,745)
0.32 12,745
28 ➡️
(Org: 28)
(12,196)
0.1 12,196
29 📉
(Org: 24)
(11,690)
0 11,690
30 📈
(Org: 94)
(11,500)
0.72 11,500
31 📉
(Org: 25)
(11,411)
0 11,411
32 📉
(Org: 29)
(11,233)
0.04 11,233
33 📉
(Org: 27)
(11,175)
0.01 11,175
34 📉
(Org: 30)
(10,856)
0.08 10,856
35 📈
(Org: 65)
(10,002)
0.55 10,002
36 📉
(Org: 34)
(9,819)
0.1 9,819
37 📉
(Org: 33)
(9,648)
0.07 9,648
38 📉
(Org: 32)
(9,377)
0.02 9,377
39 📉
(Org: 35)
(9,038)
0.02 9,038
40 📉
(Org: 37)
(8,715)
0.02 8,715
41 📈
(Org: 57)
(8,111)
0.4 8,111
42 📉
(Org: 40)
(8,034)
0.04 8,034
43 📈
(Org: 67)
(8,023)
0.46 8,023
44 📉
(Org: 43)
(7,727)
0.14 7,727
45 📉
(Org: 44)
(7,274)
0.09 7,274
46 📉
(Org: 45)
(6,697)
0.05 6,697
47 📈
(Org: 86)
(6,581)
0.44 6,581
48 📈
(Org: 77)
(6,523)
0.41 6,523
49 📉
(Org: 46)
(6,430)
0.09 6,430
50 📈
(Org: 71)
(6,299)
0.33 6,299
51 📈
(Org: 97)
(6,194)
0.5 6,194
52 📉
(Org: 47)
(6,150)
0.05 6,150
53 📈
(Org: 55)
(6,056)
0.16 6,056
54 📉
(Org: 49)
(6,024)
0.04 6,024
55 📈
(Org: 58)
(6,004)
0.19 6,004
56 ➡️
(Org: 56)
(5,868)
0.16 5,868
57 📉
(Org: 52)
(5,698)
0.06 5,698
58 📉
(Org: 51)
(5,536)
0 5,536
59 📈
(Org: 61)
(5,362)
0.1 5,362
60 📈
(Org: 63)
(5,353)
0.15 5,353
61 📉
(Org: 53)
(5,314)
0.01 5,314
62 📈
(Org: 91)
(5,267)
0.34 5,267
63 📉
(Org: 54)
(5,211)
0 5,211
64 📉
(Org: 59)
(5,041)
0.04 5,041
65 📉
(Org: 59)
(4,983)
0.02 4,983
66 📉
(Org: 62)
(4,897)
0.03 4,897
67 📉
(Org: 64)
(4,653)
0.02 4,653
68 📉
(Org: 66)
(4,623)
0.03 4,623
69 📈
(Org: 81)
(4,474)
0.15 4,474
70 📉
(Org: 68)
(4,407)
0.02 4,407
71 📉
(Org: 70)
(4,405)
0.04 4,405
72 📈
(Org: 102)
(4,332)
0.34 4,332
73 📉
(Org: 69)
(4,280)
0 4,280
74 ➡️
(Org: 74)
(4,091)
0.01 4,091
75 📈
(Org: 122)
(4,086)
0.41 4,086
76 📈
(Org: 82)
(4,068)
0.07 4,068
77 📈
(Org: 90)
(4,010)
0.1 4,010
78 📉
(Org: 75)
(4,000)
0.01 4,000
79 📈
(Org: 85)
(3,980)
0.06 3,980
80 ➡️
(Org: 80)
(3,953)
0.03 3,953
81 📉
(Org: 76)
(3,941)
0.01 3,941
82 📈
(Org: 84)
(3,881)
0.04 3,881
83 📉
(Org: 79)
(3,879)
0.01 3,879
84 📉
(Org: 78)
(3,875)
0 3,875
85 📈
(Org: 121)
(3,852)
0.37 3,852
86 📈
(Org: 95)
(3,726)
0.13 3,726
87 📈
(Org: 123)
(3,725)
0.36 3,725
88 📉
(Org: 87)
(3,703)
0 3,703
89 📉
(Org: 88)
(3,679)
0 3,679
90 📉
(Org: 89)
(3,627)
0 3,627
91 📈
(Org: 104)
(3,534)
0.19 3,534
92 ➡️
(Org: 92)
(3,408)
- 3,408
93 📈
(Org: 214)
(3,406)
0.64 3,406
94 📈
(Org: 106)
(3,240)
0.14 3,240
95 📈
(Org: 96)
(3,201)
- 3,201
96 📈
(Org: 244)
(3,155)
0.68 3,155
97 📈
(Org: 111)
(3,069)
0.11 3,069
98 📈
(Org: 117)
(3,055)
0.15 3,055
99 📉
(Org: 98)
(2,997)
- 2,997
100 📈
(Org: 101)
(2,982)
0.02 2,982