Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2007 - 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: 6)
(23,154)
0.26 23,154
2 📉
(Org: 1)
(20,989)
0.08 20,989
3 📉
(Org: 2)
(20,011)
0.04 20,011
4 📈
(Org: 5)
(19,169)
0.06 19,169
5 📈
(Org: 23)
(18,733)
0.55 18,733
6 📉
(Org: 3)
(18,726)
0.02 18,726
7 📉
(Org: 4)
(18,300)
0.01 18,300
8 📉
(Org: 7)
(16,800)
0.01 16,800
9 📈
(Org: 44)
(16,452)
0.66 16,452
10 📉
(Org: 8)
(16,306)
0.05 16,306
11 📉
(Org: 9)
(14,358)
0.07 14,358
12 📈
(Org: 18)
(14,124)
0.29 14,124
13 📉
(Org: 10)
(13,779)
0.05 13,779
14 📉
(Org: 11)
(13,344)
0.1 13,344
15 📈
(Org: 22)
(13,316)
0.34 13,316
16 📈
(Org: 17)
(13,016)
0.2 13,016
17 📉
(Org: 14)
(12,982)
0.13 12,982
18 📈
(Org: 35)
(12,701)
0.52 12,701
19 📉
(Org: 13)
(12,384)
0.08 12,384
20 📉
(Org: 16)
(12,307)
0.13 12,307
21 📉
(Org: 12)
(11,894)
0 11,894
22 📉
(Org: 15)
(11,486)
0.05 11,486
23 📈
(Org: 39)
(11,251)
0.48 11,251
24 📈
(Org: 27)
(11,181)
0.33 11,181
25 📉
(Org: 19)
(10,232)
0.03 10,232
26 📈
(Org: 63)
(9,919)
0.53 9,919
27 📉
(Org: 20)
(9,850)
0.01 9,850
28 📉
(Org: 21)
(9,692)
0.01 9,692
29 📈
(Org: 61)
(9,670)
0.51 9,670
30 📈
(Org: 56)
(9,591)
0.49 9,591
31 📈
(Org: 52)
(9,486)
0.45 9,486
32 📈
(Org: 65)
(9,339)
0.5 9,339
33 📈
(Org: 70)
(9,328)
0.52 9,328
34 📉
(Org: 30)
(9,121)
0.23 9,121
35 📉
(Org: 32)
(8,977)
0.24 8,977
36 📈
(Org: 53)
(8,876)
0.42 8,876
37 📈
(Org: 38)
(8,816)
0.34 8,816
38 📈
(Org: 50)
(8,726)
0.39 8,726
39 📈
(Org: 79)
(8,438)
0.51 8,438
40 📉
(Org: 24)
(8,414)
0.05 8,414
41 📉
(Org: 33)
(8,373)
0.22 8,373
42 📉
(Org: 26)
(8,291)
0.09 8,291
43 📈
(Org: 62)
(8,219)
0.43 8,219
44 📉
(Org: 25)
(7,951)
0.01 7,951
45 📈
(Org: 46)
(7,943)
0.31 7,943
46 📉
(Org: 28)
(7,652)
0.03 7,652
47 📉
(Org: 37)
(7,617)
0.21 7,617
48 📉
(Org: 29)
(7,574)
0.02 7,574
49 📈
(Org: 261)
(7,449)
0.82 7,449
50 📉
(Org: 41)
(7,218)
0.2 7,218
51 📈
(Org: 57)
(6,984)
0.3 6,984
52 📉
(Org: 31)
(6,828)
0 6,828
53 📈
(Org: 69)
(6,551)
0.31 6,551
54 📈
(Org: 85)
(6,504)
0.4 6,504
55 📈
(Org: 67)
(6,304)
0.28 6,304
56 📈
(Org: 83)
(6,289)
0.37 6,289
57 📉
(Org: 34)
(6,286)
0.02 6,286
58 📈
(Org: 84)
(6,218)
0.37 6,218
59 📉
(Org: 47)
(6,192)
0.12 6,192
60 📉
(Org: 40)
(5,935)
0.03 5,935
61 📉
(Org: 59)
(5,885)
0.18 5,885
61 📈
(Org: 172)
(5,885)
0.65 5,885
63 📉
(Org: 42)
(5,878)
0.03 5,878
64 📉
(Org: 55)
(5,806)
0.13 5,806
65 📉
(Org: 43)
(5,804)
0.02 5,804
66 📉
(Org: 45)
(5,721)
0.04 5,721
67 📉
(Org: 49)
(5,684)
0.06 5,684
68 📉
(Org: 51)
(5,575)
0.06 5,575
69 📉
(Org: 54)
(5,425)
0.06 5,425
70 📈
(Org: 123)
(5,416)
0.49 5,416
71 📉
(Org: 48)
(5,386)
- 5,386
72 📉
(Org: 66)
(5,251)
0.12 5,251
73 📈
(Org: 81)
(5,156)
0.22 5,156
74 📈
(Org: 115)
(5,096)
0.43 5,096
75 📉
(Org: 64)
(5,068)
0.08 5,068
76 📉
(Org: 68)
(4,889)
0.07 4,889
77 📉
(Org: 58)
(4,866)
0 4,866
78 📈
(Org: 105)
(4,799)
0.33 4,799
79 📉
(Org: 60)
(4,798)
- 4,798
80 📉
(Org: 71)
(4,785)
0.07 4,785
81 📈
(Org: 148)
(4,781)
0.51 4,781
82 📉
(Org: 72)
(4,745)
0.08 4,745
83 📈
(Org: 88)
(4,684)
0.19 4,684
84 📈
(Org: 128)
(4,632)
0.42 4,632
85 📉
(Org: 74)
(4,429)
0.03 4,429
86 📈
(Org: 95)
(4,406)
0.19 4,406
87 📉
(Org: 86)
(4,339)
0.11 4,339
88 📈
(Org: 108)
(4,316)
0.29 4,316
89 📈
(Org: 338)
(4,305)
0.77 4,305
90 📉
(Org: 82)
(4,278)
0.07 4,278
91 📉
(Org: 78)
(4,277)
0.04 4,277
92 📉
(Org: 77)
(4,255)
0.01 4,255
93 📈
(Org: 96)
(3,991)
0.13 3,991
94 📉
(Org: 91)
(3,926)
0.05 3,926
95 📉
(Org: 89)
(3,890)
0.02 3,890
96 📈
(Org: 97)
(3,887)
0.12 3,887
97 📈
(Org: 133)
(3,866)
0.32 3,866
98 📈
(Org: 185)
(3,865)
0.53 3,865
99 📈
(Org: 360)
(3,843)
0.76 3,843
100 📈
(Org: 127)
(3,829)
0.3 3,829