Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2010 - 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: 2)
(27,111)
0.24 27,111
2 📉
(Org: 1)
(23,748)
0.03 23,748
3 📈
(Org: 9)
(18,432)
0.36 18,432
4 📉
(Org: 3)
(17,697)
0.02 17,697
5 📉
(Org: 4)
(17,260)
0.01 17,260
6 📉
(Org: 5)
(15,762)
0.02 15,762
7 📉
(Org: 6)
(15,535)
0.08 15,535
8 📉
(Org: 7)
(14,961)
0.05 14,961
9 📉
(Org: 8)
(14,520)
0.09 14,520
10 📈
(Org: 19)
(13,491)
0.48 13,491
11 📈
(Org: 31)
(13,153)
0.52 13,153
12 📈
(Org: 17)
(12,237)
0.35 12,237
13 📉
(Org: 11)
(11,962)
0.14 11,962
14 📈
(Org: 35)
(11,813)
0.48 11,813
15 📉
(Org: 10)
(11,237)
0.05 11,237
16 📉
(Org: 14)
(11,222)
0.22 11,222
17 📉
(Org: 12)
(10,859)
0.05 10,859
18 📈
(Org: 40)
(10,756)
0.48 10,756
19 📈
(Org: 90)
(10,719)
0.69 10,719
20 📉
(Org: 13)
(10,091)
0.02 10,091
21 📈
(Org: 57)
(10,048)
0.54 10,048
22 📈
(Org: 51)
(9,244)
0.46 9,244
23 📈
(Org: 76)
(9,238)
0.61 9,238
24 📈
(Org: 37)
(9,063)
0.35 9,063
25 📈
(Org: 26)
(9,041)
0.3 9,041
26 📈
(Org: 30)
(8,964)
0.3 8,964
27 📉
(Org: 22)
(8,907)
0.22 8,907
28 📈
(Org: 54)
(8,846)
0.45 8,846
29 📈
(Org: 38)
(8,832)
0.34 8,832
30 📉
(Org: 24)
(8,736)
0.25 8,736
31 📈
(Org: 34)
(8,615)
0.29 8,615
32 📉
(Org: 16)
(8,478)
0.02 8,478
33 📈
(Org: 68)
(8,469)
0.54 8,469
34 📉
(Org: 15)
(8,410)
- 8,410
35 📉
(Org: 33)
(8,394)
0.26 8,394
36 📉
(Org: 21)
(8,081)
0.13 8,081
37 📈
(Org: 45)
(7,958)
0.33 7,958
38 📉
(Org: 18)
(7,771)
0.01 7,771
39 📈
(Org: 56)
(7,698)
0.39 7,698
40 📉
(Org: 20)
(7,577)
0.08 7,577
41 📈
(Org: 70)
(7,393)
0.48 7,393
42 📈
(Org: 66)
(7,207)
0.45 7,207
43 📈
(Org: 135)
(6,916)
0.67 6,916
44 📉
(Org: 29)
(6,863)
0.08 6,863
45 📈
(Org: 217)
(6,728)
0.79 6,728
46 📉
(Org: 23)
(6,683)
0 6,683
47 📈
(Org: 65)
(6,672)
0.4 6,672
48 📉
(Org: 44)
(6,644)
0.19 6,644
49 📉
(Org: 39)
(6,616)
0.12 6,616
50 📈
(Org: 86)
(6,589)
0.48 6,589
51 📉
(Org: 25)
(6,448)
0 6,448
52 📉
(Org: 27)
(6,374)
0.01 6,374
53 📉
(Org: 32)
(6,336)
0.02 6,336
54 📉
(Org: 36)
(6,258)
0.06 6,258
55 📉
(Org: 43)
(6,043)
0.11 6,043
56 📈
(Org: 61)
(6,033)
0.29 6,033
57 📈
(Org: 105)
(5,952)
0.51 5,952
58 📈
(Org: 78)
(5,651)
0.36 5,651
59 📉
(Org: 49)
(5,635)
0.1 5,635
60 📉
(Org: 41)
(5,560)
0.02 5,560
61 📉
(Org: 53)
(5,462)
0.1 5,462
62 📉
(Org: 60)
(5,432)
0.2 5,432
63 📉
(Org: 62)
(5,408)
0.23 5,408
64 📉
(Org: 46)
(5,358)
- 5,358
65 📉
(Org: 52)
(5,299)
0.07 5,299
66 📉
(Org: 48)
(5,245)
0.02 5,245
67 📉
(Org: 50)
(5,177)
0.03 5,177
68 📉
(Org: 55)
(4,812)
0.03 4,812
69 📈
(Org: 71)
(4,798)
0.22 4,798
70 📉
(Org: 59)
(4,757)
0.07 4,757
71 📉
(Org: 58)
(4,597)
0.03 4,597
72 📈
(Org: 82)
(4,590)
0.24 4,590
73 📈
(Org: 124)
(4,367)
0.42 4,367
74 📈
(Org: 339)
(4,325)
0.78 4,325
75 📈
(Org: 129)
(4,317)
0.43 4,317
76 📉
(Org: 64)
(4,274)
0.06 4,274
77 📈
(Org: 231)
(4,251)
0.68 4,251
78 📉
(Org: 67)
(4,188)
0.05 4,188
79 📉
(Org: 63)
(4,174)
0.02 4,174
80 📉
(Org: 69)
(4,130)
0.06 4,130
81 📈
(Org: 368)
(4,055)
0.79 4,055
82 📉
(Org: 72)
(3,998)
0.07 3,998
83 📉
(Org: 75)
(3,991)
0.09 3,991
84 📈
(Org: 87)
(3,898)
0.14 3,898
85 📉
(Org: 74)
(3,822)
0.03 3,822
86 📉
(Org: 73)
(3,819)
0.03 3,819
87 📈
(Org: 115)
(3,787)
0.28 3,787
88 📉
(Org: 83)
(3,653)
0.05 3,653
89 ➡️
(Org: 89)
(3,623)
0.09 3,623
90 📈
(Org: 111)
(3,607)
0.21 3,607
91 📈
(Org: 99)
(3,578)
0.16 3,578
92 📉
(Org: 80)
(3,569)
- 3,569
93 📉
(Org: 81)
(3,544)
0.01 3,544
94 📈
(Org: 157)
(3,486)
0.44 3,486
95 📉
(Org: 85)
(3,456)
0 3,456
96 📈
(Org: 104)
(3,434)
0.15 3,434
97 📈
(Org: 134)
(3,432)
0.33 3,432
98 📈
(Org: 165)
(3,422)
0.46 3,422
99 📉
(Org: 98)
(3,388)
0.1 3,388
100 📈
(Org: 212)
(3,381)
0.57 3,381