Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2004 - 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)
(27,016)
0.07 27,016
2 ➡️
(Org: 2)
(21,826)
0.01 21,826
3 ➡️
(Org: 3)
(21,560)
0.04 21,560
4 📈
(Org: 24)
(20,560)
0.58 20,560
5 📈
(Org: 33)
(20,226)
0.65 20,226
6 📈
(Org: 12)
(17,345)
0.26 17,345
7 📉
(Org: 5)
(17,044)
0.08 17,044
8 📉
(Org: 4)
(16,285)
0.01 16,285
9 📉
(Org: 6)
(16,223)
0.05 16,223
10 📉
(Org: 7)
(15,865)
0.05 15,865
11 📉
(Org: 8)
(15,715)
0.09 15,715
12 📈
(Org: 15)
(15,409)
0.29 15,409
13 📉
(Org: 10)
(14,368)
0.06 14,368
14 📈
(Org: 17)
(14,355)
0.32 14,355
15 📉
(Org: 11)
(13,885)
0.03 13,885
16 📉
(Org: 14)
(13,853)
0.13 13,853
17 📉
(Org: 9)
(13,803)
0 13,803
18 📈
(Org: 35)
(13,652)
0.51 13,652
19 📉
(Org: 13)
(12,635)
0.01 12,635
20 📈
(Org: 50)
(12,306)
0.56 12,306
21 📉
(Org: 19)
(11,591)
0.16 11,591
22 📈
(Org: 26)
(10,930)
0.22 10,930
23 📈
(Org: 49)
(10,779)
0.48 10,779
24 📉
(Org: 18)
(10,578)
0.08 10,578
25 📈
(Org: 27)
(10,492)
0.2 10,492
26 📉
(Org: 16)
(10,225)
0.02 10,225
27 📈
(Org: 44)
(10,064)
0.43 10,064
28 📉
(Org: 22)
(9,871)
0.06 9,871
29 📉
(Org: 21)
(9,753)
0.03 9,753
30 📉
(Org: 23)
(9,708)
0.1 9,708
31 📉
(Org: 20)
(9,581)
0.01 9,581
32 📈
(Org: 63)
(9,036)
0.47 9,036
33 📈
(Org: 42)
(8,756)
0.34 8,756
34 📈
(Org: 40)
(8,717)
0.33 8,717
35 📉
(Org: 25)
(8,704)
0.01 8,704
36 📈
(Org: 54)
(8,564)
0.37 8,564
37 📈
(Org: 58)
(8,554)
0.42 8,554
38 📉
(Org: 28)
(8,395)
0.01 8,395
39 📉
(Org: 29)
(8,322)
0.01 8,322
40 📉
(Org: 38)
(8,153)
0.2 8,153
41 📈
(Org: 53)
(8,066)
0.33 8,066
42 📈
(Org: 79)
(8,048)
0.5 8,048
43 📉
(Org: 34)
(7,989)
0.13 7,989
44 📉
(Org: 30)
(7,809)
0.05 7,809
45 📉
(Org: 41)
(7,690)
0.24 7,690
46 📉
(Org: 31)
(7,464)
0.02 7,464
47 📈
(Org: 76)
(7,329)
0.42 7,329
48 📉
(Org: 32)
(7,258)
0.02 7,258
49 📈
(Org: 177)
(7,140)
0.73 7,140
50 📈
(Org: 88)
(7,107)
0.49 7,107
51 📉
(Org: 39)
(7,046)
0.07 7,046
52 📉
(Org: 37)
(7,021)
0.06 7,021
53 📉
(Org: 36)
(6,904)
0.03 6,904
54 📈
(Org: 83)
(6,791)
0.45 6,791
55 📈
(Org: 70)
(6,453)
0.31 6,453
56 📉
(Org: 43)
(6,368)
0.1 6,368
57 📈
(Org: 64)
(6,301)
0.25 6,301
58 📉
(Org: 47)
(6,298)
0.1 6,298
59 📉
(Org: 55)
(6,072)
0.15 6,072
60 📉
(Org: 48)
(6,041)
0.07 6,041
61 📈
(Org: 65)
(5,947)
0.2 5,947
62 📉
(Org: 46)
(5,895)
0.03 5,895
63 📈
(Org: 94)
(5,638)
0.38 5,638
64 📈
(Org: 85)
(5,633)
0.34 5,633
65 📉
(Org: 52)
(5,594)
0.03 5,594
66 📉
(Org: 56)
(5,560)
0.07 5,560
67 📉
(Org: 51)
(5,550)
0.02 5,550
68 📈
(Org: 236)
(5,249)
0.74 5,249
69 📉
(Org: 61)
(5,195)
0.07 5,195
70 📈
(Org: 78)
(5,182)
0.23 5,182
71 📉
(Org: 57)
(5,056)
- 5,056
72 📉
(Org: 66)
(5,028)
0.06 5,028
73 📈
(Org: 92)
(4,944)
0.29 4,944
74 📉
(Org: 60)
(4,923)
0 4,923
75 📈
(Org: 100)
(4,912)
0.33 4,912
76 📉
(Org: 62)
(4,903)
0.01 4,903
77 📉
(Org: 73)
(4,838)
0.09 4,838
78 📈
(Org: 134)
(4,731)
0.49 4,731
79 📈
(Org: 93)
(4,703)
0.26 4,703
80 📉
(Org: 67)
(4,691)
- 4,691
81 📉
(Org: 75)
(4,678)
0.07 4,678
82 📉
(Org: 71)
(4,593)
0.03 4,593
83 📈
(Org: 123)
(4,577)
0.4 4,577
84 📉
(Org: 81)
(4,571)
0.15 4,571
85 📉
(Org: 72)
(4,523)
0.02 4,523
86 📈
(Org: 119)
(4,506)
0.37 4,506
87 📉
(Org: 74)
(4,411)
0.01 4,411
88 📈
(Org: 101)
(4,408)
0.26 4,408
89 📈
(Org: 108)
(4,384)
0.3 4,384
90 📉
(Org: 89)
(4,358)
0.18 4,358
91 📉
(Org: 84)
(4,301)
0.13 4,301
92 📉
(Org: 80)
(4,116)
0.05 4,116
93 📉
(Org: 77)
(4,044)
- 4,044
94 📈
(Org: 183)
(4,023)
0.53 4,023
95 📉
(Org: 82)
(3,878)
0 3,878
96 📈
(Org: 99)
(3,859)
0.14 3,859
97 📈
(Org: 118)
(3,855)
0.26 3,855
98 📈
(Org: 131)
(3,849)
0.36 3,849
99 📉
(Org: 91)
(3,845)
0.08 3,845
100 📉
(Org: 97)
(3,766)
0.11 3,766