Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2011 - 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)
(29,341)
0.25 29,341
2 ➡️
(Org: 2)
(20,632)
0.03 20,632
3 ➡️
(Org: 3)
(19,225)
0.02 19,225
4 ➡️
(Org: 4)
(17,574)
0.01 17,574
5 📈
(Org: 10)
(17,064)
0.35 17,064
6 📉
(Org: 5)
(15,833)
0.02 15,833
7 📉
(Org: 6)
(15,468)
0.08 15,468
8 📈
(Org: 28)
(14,392)
0.55 14,392
9 📉
(Org: 7)
(13,860)
0.04 13,860
10 📉
(Org: 8)
(13,581)
0.09 13,581
11 📈
(Org: 32)
(12,445)
0.5 12,445
12 📈
(Org: 15)
(12,353)
0.34 12,353
13 📉
(Org: 9)
(12,193)
0.05 12,193
14 📈
(Org: 20)
(11,694)
0.39 11,694
15 📈
(Org: 36)
(11,640)
0.48 11,640
16 📉
(Org: 14)
(11,011)
0.21 11,011
17 📉
(Org: 13)
(10,805)
0.14 10,805
18 📉
(Org: 11)
(10,677)
0.05 10,677
19 📈
(Org: 47)
(10,082)
0.5 10,082
20 📈
(Org: 21)
(9,848)
0.27 9,848
21 📉
(Org: 12)
(9,781)
0.02 9,781
22 📈
(Org: 57)
(9,708)
0.55 9,708
23 📈
(Org: 100)
(9,558)
0.7 9,558
24 📈
(Org: 79)
(9,096)
0.6 9,096
25 📈
(Org: 35)
(9,059)
0.33 9,059
26 📉
(Org: 22)
(8,887)
0.22 8,887
27 📈
(Org: 68)
(8,720)
0.56 8,720
28 📈
(Org: 52)
(8,622)
0.45 8,622
29 ➡️
(Org: 29)
(8,616)
0.26 8,616
30 📈
(Org: 53)
(8,455)
0.45 8,455
31 📈
(Org: 46)
(8,407)
0.39 8,407
32 📈
(Org: 40)
(8,179)
0.33 8,179
33 📈
(Org: 34)
(8,114)
0.25 8,114
34 📈
(Org: 39)
(8,014)
0.31 8,014
35 📈
(Org: 61)
(7,958)
0.47 7,958
36 📉
(Org: 16)
(7,699)
0.01 7,699
37 📉
(Org: 24)
(7,579)
0.11 7,579
38 📉
(Org: 17)
(7,398)
- 7,398
39 📈
(Org: 45)
(7,350)
0.29 7,350
40 📉
(Org: 18)
(7,344)
- 7,344
41 📉
(Org: 25)
(7,250)
0.09 7,250
42 📈
(Org: 64)
(7,112)
0.43 7,112
43 📉
(Org: 23)
(7,035)
0.02 7,035
44 📈
(Org: 127)
(7,025)
0.66 7,025
45 📉
(Org: 37)
(6,944)
0.13 6,944
46 📈
(Org: 48)
(6,798)
0.27 6,798
47 📉
(Org: 41)
(6,790)
0.2 6,790
48 📉
(Org: 26)
(6,693)
0.02 6,693
49 📈
(Org: 248)
(6,478)
0.8 6,478
50 📉
(Org: 30)
(6,470)
0.01 6,470
51 📉
(Org: 27)
(6,430)
- 6,430
52 📈
(Org: 71)
(6,359)
0.41 6,359
53 📈
(Org: 92)
(6,251)
0.48 6,251
54 📉
(Org: 33)
(6,139)
0 6,139
55 📉
(Org: 42)
(5,879)
0.08 5,879
56 📉
(Org: 38)
(5,714)
0.01 5,714
57 📉
(Org: 43)
(5,598)
0.07 5,598
58 📉
(Org: 50)
(5,468)
0.1 5,468
59 📉
(Org: 44)
(5,456)
0.05 5,456
60 📈
(Org: 114)
(5,409)
0.51 5,409
61 📈
(Org: 88)
(5,271)
0.37 5,271
62 📉
(Org: 51)
(5,131)
0.08 5,131
63 📉
(Org: 56)
(5,025)
0.11 5,025
64 📈
(Org: 65)
(4,987)
0.2 4,987
65 📉
(Org: 59)
(4,849)
0.11 4,849
66 📈
(Org: 80)
(4,847)
0.26 4,847
67 📈
(Org: 72)
(4,701)
0.21 4,701
68 📉
(Org: 54)
(4,676)
- 4,676
69 📉
(Org: 55)
(4,610)
0.02 4,610
70 📈
(Org: 116)
(4,579)
0.42 4,579
71 📈
(Org: 180)
(4,578)
0.62 4,578
72 📉
(Org: 58)
(4,477)
0.03 4,477
73 📉
(Org: 60)
(4,375)
0.02 4,375
74 📉
(Org: 63)
(4,264)
0.05 4,264
75 📉
(Org: 62)
(4,234)
0.03 4,234
76 📈
(Org: 90)
(4,224)
0.23 4,224
77 📈
(Org: 89)
(4,214)
0.22 4,214
78 📈
(Org: 132)
(4,173)
0.44 4,173
79 📉
(Org: 78)
(4,144)
0.13 4,144
80 📈
(Org: 91)
(4,093)
0.21 4,093
81 📉
(Org: 66)
(4,066)
0.05 4,066
82 📉
(Org: 73)
(4,054)
0.09 4,054
83 📉
(Org: 67)
(4,042)
0.06 4,042
84 📈
(Org: 385)
(3,989)
0.79 3,989
85 📈
(Org: 394)
(3,923)
0.8 3,923
86 📉
(Org: 77)
(3,879)
0.07 3,879
87 📉
(Org: 70)
(3,851)
0.03 3,851
88 📉
(Org: 81)
(3,850)
0.09 3,850
89 📉
(Org: 76)
(3,848)
0.06 3,848
90 📉
(Org: 69)
(3,784)
0 3,784
91 📉
(Org: 75)
(3,767)
0.03 3,767
92 📈
(Org: 156)
(3,758)
0.47 3,758
93 📉
(Org: 74)
(3,717)
0.01 3,717
94 📈
(Org: 111)
(3,533)
0.23 3,533
95 📉
(Org: 83)
(3,521)
0.01 3,521
96 📈
(Org: 97)
(3,513)
0.13 3,513
97 📉
(Org: 82)
(3,512)
- 3,512
98 📉
(Org: 86)
(3,496)
0.04 3,496
99 📈
(Org: 137)
(3,466)
0.36 3,466
100 📉
(Org: 87)
(3,394)
0.01 3,394