Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1982 - 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)
(58,263)
0.02 58,263
2 ➡️
(Org: 2)
(45,937)
0.01 45,937
3 📈
(Org: 4)
(39,888)
0.29 39,888
4 📉
(Org: 3)
(34,250)
0 34,250
5 📈
(Org: 33)
(27,618)
0.65 27,618
6 📉
(Org: 5)
(26,707)
0.03 26,707
7 📉
(Org: 6)
(25,385)
0.14 25,385
8 📈
(Org: 9)
(24,729)
0.23 24,729
9 📉
(Org: 7)
(23,936)
0.13 23,936
10 📉
(Org: 8)
(21,391)
0.04 21,391
11 📈
(Org: 36)
(21,318)
0.57 21,318
12 📈
(Org: 19)
(20,359)
0.29 20,359
13 📉
(Org: 11)
(20,170)
0.12 20,170
14 📉
(Org: 10)
(18,800)
- 18,800
15 📉
(Org: 13)
(18,519)
0.07 18,519
16 📉
(Org: 15)
(18,338)
0.14 18,338
17 📉
(Org: 12)
(17,511)
0 17,511
18 📉
(Org: 14)
(17,154)
0.06 17,154
19 📈
(Org: 25)
(17,055)
0.29 17,055
20 📈
(Org: 21)
(16,890)
0.18 16,890
21 📉
(Org: 17)
(16,008)
0.07 16,008
22 📉
(Org: 16)
(15,096)
0.01 15,096
23 📉
(Org: 18)
(14,703)
0 14,703
24 📉
(Org: 20)
(14,625)
0.02 14,625
25 📉
(Org: 22)
(13,802)
0.04 13,802
26 📈
(Org: 35)
(13,599)
0.31 13,599
27 📉
(Org: 24)
(13,028)
0.04 13,028
28 📉
(Org: 23)
(12,856)
0.02 12,856
29 📈
(Org: 50)
(12,663)
0.52 12,663
30 📉
(Org: 29)
(12,254)
0.1 12,254
31 📉
(Org: 26)
(11,830)
0.02 11,830
32 📉
(Org: 27)
(11,374)
- 11,374
33 📉
(Org: 31)
(11,033)
0.08 11,033
34 📉
(Org: 30)
(10,970)
0.01 10,970
35 📈
(Org: 104)
(10,513)
0.73 10,513
36 📉
(Org: 34)
(10,126)
0.06 10,126
37 📉
(Org: 32)
(10,066)
0 10,066
38 📈
(Org: 54)
(9,912)
0.45 9,912
39 📈
(Org: 40)
(9,668)
0.18 9,668
40 📈
(Org: 72)
(9,135)
0.55 9,135
41 📉
(Org: 38)
(8,787)
0.02 8,787
42 📉
(Org: 39)
(8,712)
0.05 8,712
43 📈
(Org: 58)
(8,481)
0.39 8,481
44 📉
(Org: 43)
(8,163)
0.13 8,163
45 📉
(Org: 41)
(7,847)
0.02 7,847
46 📉
(Org: 42)
(7,731)
0.05 7,731
47 📉
(Org: 45)
(7,369)
0.09 7,369
48 📈
(Org: 78)
(6,953)
0.45 6,953
49 📉
(Org: 47)
(6,850)
0.05 6,850
50 📉
(Org: 44)
(6,798)
0 6,798
51 📉
(Org: 49)
(6,339)
0.03 6,339
52 📉
(Org: 51)
(6,183)
0.04 6,183
53 📈
(Org: 57)
(6,148)
0.16 6,148
54 📉
(Org: 53)
(6,112)
0.08 6,112
55 📉
(Org: 52)
(5,951)
0.04 5,951
56 📈
(Org: 60)
(5,894)
0.15 5,894
57 📈
(Org: 76)
(5,848)
0.32 5,848
58 📈
(Org: 102)
(5,746)
0.5 5,746
59 📈
(Org: 88)
(5,675)
0.42 5,675
60 📈
(Org: 62)
(5,605)
0.17 5,605
61 ➡️
(Org: 61)
(5,562)
0.16 5,562
62 📉
(Org: 56)
(5,291)
0 5,291
63 📉
(Org: 59)
(5,220)
0.01 5,220
64 📈
(Org: 98)
(4,697)
0.37 4,697
65 📉
(Org: 64)
(4,550)
0.03 4,550
66 📈
(Org: 74)
(4,531)
0.1 4,531
67 📉
(Org: 63)
(4,460)
0.01 4,460
68 📈
(Org: 137)
(4,450)
0.51 4,450
69 📉
(Org: 65)
(4,414)
0.04 4,414
70 📈
(Org: 71)
(4,413)
0.06 4,413
71 📉
(Org: 67)
(4,368)
0.03 4,368
72 📈
(Org: 79)
(4,350)
0.14 4,350
73 📉
(Org: 65)
(4,271)
0 4,271
74 📉
(Org: 68)
(4,249)
0.02 4,249
74 📈
(Org: 119)
(4,249)
0.42 4,249
76 📈
(Org: 77)
(4,246)
0.07 4,246
77 📉
(Org: 69)
(4,217)
0.02 4,217
78 📈
(Org: 108)
(4,178)
0.34 4,178
79 📈
(Org: 113)
(4,171)
0.36 4,171
80 📉
(Org: 75)
(4,003)
0 4,003
81 📈
(Org: 124)
(3,989)
0.4 3,989
82 📈
(Org: 121)
(3,864)
0.36 3,864
83 📈
(Org: 87)
(3,762)
0.12 3,762
84 📉
(Org: 80)
(3,736)
0.02 3,736
85 📉
(Org: 82)
(3,608)
0.02 3,608
86 📉
(Org: 84)
(3,529)
0.01 3,529
87 📉
(Org: 86)
(3,507)
0.03 3,507
88 📈
(Org: 94)
(3,460)
0.1 3,460
89 📈
(Org: 92)
(3,402)
0.08 3,402
90 ➡️
(Org: 90)
(3,317)
0.03 3,317
91 📉
(Org: 89)
(3,288)
0.01 3,288
92 📉
(Org: 91)
(3,220)
0.01 3,220
93 📈
(Org: 105)
(3,165)
0.11 3,165
94 📉
(Org: 93)
(3,150)
0.01 3,150
94 📈
(Org: 96)
(3,150)
0.03 3,150
96 📈
(Org: 107)
(3,130)
0.11 3,130
97 📈
(Org: 244)
(3,121)
0.67 3,121
98 📉
(Org: 95)
(3,111)
0.01 3,111
99 📈
(Org: 147)
(3,037)
0.34 3,037
100 📉
(Org: 97)
(3,031)
0.01 3,031