Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2008 - 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: 7)
(22,156)
0.27 22,156
2 ➡️
(Org: 2)
(19,449)
0.04 19,449
3 📉
(Org: 1)
(19,187)
0.02 19,187
4 📉
(Org: 3)
(18,854)
0.07 18,854
5 📈
(Org: 6)
(18,356)
0.07 18,356
6 📉
(Org: 4)
(17,344)
0.01 17,344
7 📉
(Org: 5)
(17,339)
0.02 17,339
8 📈
(Org: 25)
(16,568)
0.52 16,568
9 📉
(Org: 8)
(15,846)
0.05 15,846
10 📈
(Org: 53)
(15,217)
0.66 15,217
11 📉
(Org: 10)
(14,827)
0.2 14,827
12 📈
(Org: 31)
(12,982)
0.51 12,982
13 ➡️
(Org: 13)
(12,917)
0.21 12,917
14 📈
(Org: 20)
(12,718)
0.29 12,718
15 📉
(Org: 9)
(12,699)
0.05 12,699
16 📈
(Org: 24)
(12,209)
0.33 12,209
17 📉
(Org: 12)
(12,207)
0.12 12,207
18 📈
(Org: 23)
(11,997)
0.31 11,997
19 📈
(Org: 56)
(11,639)
0.59 11,639
20 📉
(Org: 11)
(11,204)
0 11,204
21 📉
(Org: 16)
(11,003)
0.12 11,003
22 📈
(Org: 51)
(10,950)
0.53 10,950
23 📉
(Org: 14)
(10,711)
0.05 10,711
24 📈
(Org: 39)
(10,544)
0.45 10,544
25 📉
(Org: 17)
(10,467)
0.09 10,467
26 📉
(Org: 18)
(10,197)
0.08 10,197
27 📈
(Org: 45)
(10,165)
0.47 10,165
28 📉
(Org: 15)
(10,032)
0.03 10,032
29 📈
(Org: 58)
(9,784)
0.51 9,784
30 📈
(Org: 32)
(9,664)
0.35 9,664
31 📉
(Org: 19)
(9,509)
0.02 9,509
32 📈
(Org: 65)
(9,397)
0.52 9,397
33 📉
(Org: 21)
(9,131)
0.01 9,131
34 📈
(Org: 60)
(9,013)
0.47 9,013
35 📈
(Org: 66)
(8,852)
0.5 8,852
36 📉
(Org: 35)
(8,790)
0.31 8,790
37 📉
(Org: 22)
(8,777)
0.05 8,777
38 📉
(Org: 29)
(8,699)
0.22 8,699
39 📈
(Org: 63)
(8,670)
0.47 8,670
40 📈
(Org: 42)
(7,981)
0.3 7,981
41 📈
(Org: 71)
(7,824)
0.45 7,824
42 📉
(Org: 33)
(7,815)
0.22 7,815
43 📈
(Org: 55)
(7,792)
0.37 7,792
44 📈
(Org: 197)
(7,756)
0.78 7,756
45 📉
(Org: 40)
(7,614)
0.26 7,614
46 📉
(Org: 28)
(7,523)
0.09 7,523
47 📈
(Org: 93)
(7,507)
0.52 7,507
48 📉
(Org: 43)
(7,474)
0.26 7,474
49 📉
(Org: 48)
(7,470)
0.29 7,470
50 📉
(Org: 26)
(7,325)
0.01 7,325
51 📉
(Org: 27)
(7,273)
0.02 7,273
52 📈
(Org: 67)
(7,149)
0.39 7,149
53 📉
(Org: 47)
(6,882)
0.23 6,882
54 📉
(Org: 37)
(6,754)
0.12 6,754
55 📉
(Org: 49)
(6,691)
0.21 6,691
56 📉
(Org: 30)
(6,652)
0.03 6,652
57 📈
(Org: 76)
(6,583)
0.39 6,583
58 📉
(Org: 34)
(6,130)
0 6,130
59 📈
(Org: 82)
(6,020)
0.35 6,020
60 📈
(Org: 140)
(5,996)
0.6 5,996
61 📉
(Org: 38)
(5,829)
- 5,829
62 📉
(Org: 54)
(5,821)
0.12 5,821
63 📉
(Org: 44)
(5,776)
0.06 5,776
64 📉
(Org: 41)
(5,759)
0.02 5,759
65 📉
(Org: 46)
(5,480)
0.03 5,480
66 📉
(Org: 52)
(5,354)
0.03 5,354
67 📉
(Org: 50)
(5,351)
0.02 5,351
68 📈
(Org: 83)
(5,197)
0.26 5,197
68 📉
(Org: 62)
(5,197)
0.11 5,197
70 📉
(Org: 57)
(5,137)
0.06 5,137
71 📈
(Org: 176)
(4,975)
0.62 4,975
72 📉
(Org: 61)
(4,938)
0.07 4,938
73 📈
(Org: 74)
(4,932)
0.17 4,932
74 📉
(Org: 59)
(4,889)
0.03 4,889
75 📈
(Org: 85)
(4,831)
0.23 4,831
76 📈
(Org: 123)
(4,794)
0.43 4,794
77 📈
(Org: 124)
(4,721)
0.42 4,721
78 📉
(Org: 70)
(4,615)
0.07 4,615
79 📉
(Org: 68)
(4,437)
0.02 4,437
80 📈
(Org: 351)
(4,413)
0.78 4,413
81 📉
(Org: 75)
(4,395)
0.08 4,395
82 📉
(Org: 78)
(4,364)
0.08 4,364
83 📉
(Org: 79)
(4,349)
0.07 4,349
84 📈
(Org: 128)
(4,342)
0.39 4,342
85 📉
(Org: 69)
(4,299)
- 4,299
86 📈
(Org: 118)
(4,295)
0.32 4,295
87 📉
(Org: 72)
(4,263)
- 4,263
88 📈
(Org: 145)
(4,252)
0.45 4,252
89 📉
(Org: 73)
(4,240)
0.01 4,240
90 📈
(Org: 332)
(4,238)
0.76 4,238
91 📉
(Org: 84)
(4,160)
0.09 4,160
92 📈
(Org: 105)
(4,053)
0.18 4,053
93 📈
(Org: 110)
(4,008)
0.21 4,008
94 📈
(Org: 121)
(3,952)
0.29 3,952
95 📈
(Org: 99)
(3,912)
0.12 3,912
96 📉
(Org: 87)
(3,871)
0.05 3,871
97 📈
(Org: 104)
(3,834)
0.13 3,834
98 📉
(Org: 95)
(3,825)
0.08 3,825
99 📈
(Org: 150)
(3,803)
0.4 3,803
100 📈
(Org: 106)
(3,748)
0.12 3,748