Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2009 - 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)
(23,231)
0.04 23,231
2 📈
(Org: 4)
(22,729)
0.25 22,729
3 📉
(Org: 2)
(18,260)
0.02 18,260
4 📉
(Org: 3)
(17,689)
0.01 17,689
5 📈
(Org: 6)
(16,728)
0.08 16,728
6 📈
(Org: 9)
(16,725)
0.29 16,725
7 ➡️
(Org: 7)
(16,695)
0.09 16,695
8 📉
(Org: 5)
(16,181)
0.02 16,181
9 📉
(Org: 8)
(15,173)
0.05 15,173
10 📈
(Org: 25)
(15,007)
0.51 15,007
11 📈
(Org: 26)
(14,289)
0.49 14,289
12 📈
(Org: 67)
(12,979)
0.68 12,979
13 📈
(Org: 18)
(12,337)
0.34 12,337
14 📈
(Org: 16)
(12,146)
0.22 12,146
15 📉
(Org: 12)
(12,143)
0.12 12,143
16 📉
(Org: 10)
(12,030)
0.05 12,030
17 📉
(Org: 11)
(11,714)
0.06 11,714
18 📈
(Org: 59)
(11,046)
0.59 11,046
19 📈
(Org: 21)
(10,909)
0.29 10,909
20 📈
(Org: 47)
(10,765)
0.52 10,765
21 📈
(Org: 24)
(10,606)
0.31 10,606
22 📈
(Org: 38)
(10,403)
0.46 10,403
23 📉
(Org: 13)
(10,175)
0.02 10,175
24 📈
(Org: 30)
(9,976)
0.34 9,976
25 📉
(Org: 15)
(9,836)
0.02 9,836
26 📈
(Org: 62)
(9,752)
0.55 9,752
27 📈
(Org: 42)
(9,679)
0.45 9,679
28 📉
(Org: 14)
(9,674)
0 9,674
29 📉
(Org: 19)
(9,217)
0.13 9,217
30 📈
(Org: 52)
(9,064)
0.47 9,064
31 📉
(Org: 29)
(8,879)
0.24 8,879
32 📉
(Org: 27)
(8,874)
0.23 8,874
33 ➡️
(Org: 33)
(8,562)
0.28 8,562
34 📉
(Org: 20)
(8,514)
0.08 8,514
35 📈
(Org: 60)
(8,454)
0.48 8,454
36 📉
(Org: 17)
(8,382)
0.01 8,382
37 📈
(Org: 77)
(8,327)
0.53 8,327
38 📉
(Org: 23)
(8,300)
0.09 8,300
39 📈
(Org: 45)
(8,119)
0.36 8,119
40 📈
(Org: 61)
(8,031)
0.45 8,031
41 📉
(Org: 22)
(7,975)
0.05 7,975
42 📉
(Org: 37)
(7,974)
0.29 7,974
43 📈
(Org: 70)
(7,783)
0.47 7,783
44 📉
(Org: 41)
(7,753)
0.3 7,753
45 📈
(Org: 215)
(7,190)
0.79 7,190
46 📈
(Org: 63)
(7,189)
0.39 7,189
47 📉
(Org: 39)
(7,087)
0.21 7,087
48 📉
(Org: 28)
(6,853)
0.01 6,853
49 📈
(Org: 135)
(6,764)
0.65 6,764
50 📈
(Org: 71)
(6,739)
0.39 6,739
51 📈
(Org: 100)
(6,713)
0.51 6,713
52 📉
(Org: 35)
(6,522)
0.1 6,522
53 📉
(Org: 31)
(6,495)
0.02 6,495
54 📉
(Org: 48)
(6,398)
0.21 6,398
55 📉
(Org: 51)
(6,364)
0.23 6,364
56 📉
(Org: 40)
(6,317)
0.12 6,317
57 📉
(Org: 32)
(6,301)
- 6,301
58 📉
(Org: 34)
(6,138)
0 6,138
59 📉
(Org: 56)
(6,028)
0.23 6,028
60 📉
(Org: 44)
(6,005)
0.12 6,005
61 📈
(Org: 85)
(5,699)
0.36 5,699
62 📉
(Org: 43)
(5,468)
0.03 5,468
63 📉
(Org: 46)
(5,368)
0.03 5,368
63 📉
(Org: 53)
(5,368)
0.1 5,368
65 📉
(Org: 49)
(5,342)
0.06 5,342
66 📈
(Org: 80)
(5,270)
0.29 5,270
67 📉
(Org: 50)
(5,129)
0.03 5,129
68 📉
(Org: 54)
(4,937)
0.03 4,937
69 📉
(Org: 55)
(4,798)
0.02 4,798
70 📉
(Org: 57)
(4,737)
0.03 4,737
71 📈
(Org: 331)
(4,717)
0.79 4,717
72 📉
(Org: 58)
(4,624)
0.02 4,624
73 📈
(Org: 125)
(4,594)
0.44 4,594
74 📉
(Org: 65)
(4,588)
0.07 4,588
75 📈
(Org: 94)
(4,559)
0.24 4,559
76 📉
(Org: 66)
(4,502)
0.06 4,502
77 📉
(Org: 69)
(4,443)
0.06 4,443
78 📈
(Org: 187)
(4,442)
0.6 4,442
79 📉
(Org: 74)
(4,361)
0.08 4,361
80 📈
(Org: 120)
(4,335)
0.39 4,335
81 📈
(Org: 89)
(4,235)
0.15 4,235
82 📉
(Org: 68)
(4,191)
- 4,191
83 📈
(Org: 348)
(4,168)
0.77 4,168
84 📉
(Org: 76)
(4,159)
0.05 4,159
85 📉
(Org: 72)
(4,113)
0.01 4,113
86 📉
(Org: 73)
(4,064)
- 4,064
87 📈
(Org: 92)
(4,022)
0.13 4,022
88 📉
(Org: 83)
(4,008)
0.08 4,008
89 📈
(Org: 141)
(3,949)
0.43 3,949
90 📉
(Org: 78)
(3,939)
0.04 3,939
91 📈
(Org: 149)
(3,915)
0.45 3,915
92 📉
(Org: 79)
(3,905)
0.04 3,905
93 📈
(Org: 132)
(3,809)
0.35 3,809
94 📉
(Org: 91)
(3,772)
0.07 3,772
95 📈
(Org: 113)
(3,750)
0.23 3,750
96 📉
(Org: 81)
(3,732)
0 3,732
97 📉
(Org: 96)
(3,708)
0.08 3,708
98 📈
(Org: 115)
(3,706)
0.23 3,706
99 📉
(Org: 93)
(3,683)
0.05 3,683
100 📉
(Org: 87)
(3,643)
0.01 3,643