Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1983 - 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)
(55,479)
0.02 55,479
2 ➡️
(Org: 2)
(45,752)
0.01 45,752
3 📈
(Org: 5)
(37,365)
0.27 37,365
4 ➡️
(Org: 4)
(35,243)
0.06 35,243
5 📉
(Org: 3)
(33,800)
0 33,800
6 📈
(Org: 8)
(26,136)
0.15 26,136
7 ➡️
(Org: 7)
(26,049)
0.14 26,049
8 📈
(Org: 37)
(24,962)
0.65 24,962
9 📉
(Org: 6)
(24,238)
0.03 24,238
10 📈
(Org: 11)
(23,661)
0.24 23,661
11 📈
(Org: 34)
(22,052)
0.56 22,052
12 📈
(Org: 16)
(21,623)
0.29 21,623
13 📉
(Org: 9)
(20,764)
0 20,764
14 📉
(Org: 10)
(20,630)
0.04 20,630
15 📉
(Org: 13)
(18,797)
0.1 18,797
16 📈
(Org: 20)
(17,539)
0.17 17,539
17 📉
(Org: 14)
(17,141)
0.07 17,141
18 📈
(Org: 19)
(17,119)
0.14 17,119
19 📉
(Org: 12)
(17,096)
- 17,096
20 📉
(Org: 15)
(16,337)
0.06 16,337
21 📈
(Org: 26)
(16,063)
0.28 16,063
22 📉
(Org: 18)
(15,122)
0.02 15,122
23 📉
(Org: 21)
(15,115)
0.07 15,115
24 📉
(Org: 17)
(14,918)
0 14,918
25 📈
(Org: 33)
(13,921)
0.3 13,921
26 📉
(Org: 23)
(13,672)
0.03 13,672
27 📉
(Org: 22)
(13,301)
0.01 13,301
28 📉
(Org: 24)
(13,262)
0.02 13,262
29 📉
(Org: 25)
(12,851)
0.04 12,851
30 📉
(Org: 28)
(12,147)
0.09 12,147
31 📉
(Org: 27)
(11,698)
0.02 11,698
32 📈
(Org: 56)
(11,475)
0.55 11,475
33 📉
(Org: 29)
(11,464)
0.07 11,464
34 📉
(Org: 30)
(10,420)
0 10,420
35 ➡️
(Org: 35)
(10,278)
0.16 10,278
36 📈
(Org: 61)
(10,169)
0.54 10,169
37 📈
(Org: 53)
(10,098)
0.46 10,098
38 📉
(Org: 32)
(10,018)
0.01 10,018
39 📉
(Org: 36)
(9,063)
0.05 9,063
40 📈
(Org: 133)
(8,871)
0.75 8,871
41 📉
(Org: 38)
(8,552)
0.01 8,552
42 📉
(Org: 39)
(8,209)
- 8,209
43 📉
(Org: 41)
(7,992)
0.06 7,992
44 📈
(Org: 59)
(7,938)
0.37 7,938
45 📉
(Org: 44)
(7,861)
0.14 7,861
46 📉
(Org: 40)
(7,742)
0 7,742
47 📈
(Org: 48)
(7,455)
0.14 7,455
48 📉
(Org: 45)
(7,423)
0.1 7,423
49 📉
(Org: 43)
(7,208)
0.05 7,208
50 📉
(Org: 46)
(6,751)
0.01 6,751
51 ➡️
(Org: 51)
(6,647)
0.06 6,647
52 📉
(Org: 48)
(6,609)
0.03 6,609
53 📈
(Org: 84)
(6,462)
0.47 6,462
54 📉
(Org: 52)
(6,008)
0.05 6,008
55 📉
(Org: 53)
(5,647)
0.04 5,647
56 📈
(Org: 89)
(5,310)
0.41 5,310
57 📈
(Org: 103)
(5,240)
0.48 5,240
58 📉
(Org: 55)
(5,237)
0 5,237
59 📈
(Org: 65)
(5,101)
0.16 5,101
60 📉
(Org: 58)
(5,061)
0 5,061
61 📈
(Org: 67)
(5,044)
0.16 5,044
62 📈
(Org: 86)
(4,985)
0.33 4,985
63 📉
(Org: 60)
(4,953)
0.01 4,953
64 📈
(Org: 70)
(4,854)
0.17 4,854
65 📉
(Org: 64)
(4,803)
0.09 4,803
66 📉
(Org: 62)
(4,691)
0.03 4,691
67 📈
(Org: 110)
(4,506)
0.43 4,506
68 📈
(Org: 101)
(4,274)
0.36 4,274
69 📈
(Org: 71)
(4,222)
0.06 4,222
70 📈
(Org: 73)
(4,195)
0.06 4,195
71 📉
(Org: 68)
(4,143)
0.02 4,143
72 📉
(Org: 69)
(4,062)
0.01 4,062
73 📉
(Org: 72)
(4,058)
0.03 4,058
74 📈
(Org: 82)
(4,034)
0.14 4,034
75 📈
(Org: 128)
(4,012)
0.41 4,012
76 📉
(Org: 74)
(3,915)
0 3,915
77 📉
(Org: 75)
(3,913)
0.01 3,913
78 📈
(Org: 114)
(3,901)
0.35 3,901
79 📉
(Org: 77)
(3,875)
0.02 3,875
80 📈
(Org: 126)
(3,748)
0.36 3,748
81 📈
(Org: 102)
(3,734)
0.27 3,734
82 📉
(Org: 79)
(3,705)
0.04 3,705
83 📉
(Org: 81)
(3,644)
0.03 3,644
84 📈
(Org: 87)
(3,588)
0.11 3,588
85 📈
(Org: 173)
(3,542)
0.55 3,542
86 📉
(Org: 83)
(3,498)
0.01 3,498
87 📈
(Org: 132)
(3,468)
0.35 3,468
88 📉
(Org: 85)
(3,399)
0.01 3,399
89 📈
(Org: 153)
(3,336)
0.43 3,336
90 📉
(Org: 88)
(3,220)
0.01 3,220
91 📈
(Org: 94)
(3,198)
0.09 3,198
92 📉
(Org: 90)
(3,164)
0 3,164
93 📉
(Org: 91)
(3,070)
0.01 3,070
94 ➡️
(Org: 94)
(3,035)
0.04 3,035
95 📈
(Org: 96)
(3,019)
0.05 3,019
96 📈
(Org: 139)
(3,008)
0.3 3,008
97 📈
(Org: 142)
(2,983)
0.32 2,983
98 📉
(Org: 92)
(2,978)
0.01 2,978
99 📈
(Org: 108)
(2,915)
0.11 2,915
100 📉
(Org: 99)
(2,880)
0.04 2,880