Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2005 - 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)
(25,898)
0.08 25,898
2 ➡️
(Org: 2)
(20,610)
0.01 20,610
3 ➡️
(Org: 3)
(20,579)
0.05 20,579
4 📈
(Org: 26)
(20,026)
0.57 20,026
5 📈
(Org: 34)
(18,880)
0.65 18,880
6 📈
(Org: 12)
(17,891)
0.29 17,891
7 📉
(Org: 4)
(16,585)
0.05 16,585
8 📉
(Org: 7)
(16,196)
0.08 16,196
9 📈
(Org: 15)
(15,915)
0.27 15,915
10 📉
(Org: 5)
(15,886)
0.01 15,886
11 📉
(Org: 6)
(15,873)
0.04 15,873
12 📉
(Org: 10)
(14,518)
0.09 14,518
13 📉
(Org: 9)
(13,712)
0.01 13,712
14 📉
(Org: 8)
(13,653)
0 13,653
15 📉
(Org: 11)
(13,525)
0.06 13,525
16 📈
(Org: 20)
(13,473)
0.3 13,473
17 📈
(Org: 18)
(13,165)
0.18 13,165
18 📈
(Org: 36)
(12,886)
0.5 12,886
19 📈
(Org: 40)
(12,809)
0.54 12,809
20 📉
(Org: 16)
(12,507)
0.13 12,507
21 📉
(Org: 13)
(12,341)
0.03 12,341
22 📉
(Org: 14)
(11,952)
0.01 11,952
23 📉
(Org: 17)
(11,415)
0.05 11,415
24 📉
(Org: 19)
(10,792)
0.11 10,792
25 📈
(Org: 29)
(10,275)
0.23 10,275
26 📈
(Org: 57)
(9,944)
0.5 9,944
27 📈
(Org: 51)
(9,504)
0.45 9,504
28 📉
(Org: 21)
(9,483)
0.02 9,483
29 📈
(Org: 46)
(9,465)
0.41 9,465
30 📉
(Org: 25)
(9,420)
0.08 9,420
31 📉
(Org: 30)
(9,393)
0.21 9,393
32 📉
(Org: 24)
(9,209)
0.06 9,209
33 📉
(Org: 23)
(9,193)
0.01 9,193
34 📈
(Org: 39)
(9,176)
0.34 9,176
35 📉
(Org: 22)
(9,164)
0.01 9,164
36 📈
(Org: 54)
(9,030)
0.43 9,030
37 📈
(Org: 70)
(8,872)
0.49 8,872
38 📈
(Org: 58)
(8,839)
0.44 8,839
39 📉
(Org: 32)
(8,558)
0.19 8,558
40 📉
(Org: 35)
(8,481)
0.24 8,481
41 📉
(Org: 27)
(8,365)
0.03 8,365
42 📈
(Org: 45)
(8,191)
0.31 8,191
43 📉
(Org: 28)
(8,080)
0.01 8,080
44 📈
(Org: 82)
(8,048)
0.51 8,048
45 📈
(Org: 73)
(7,832)
0.43 7,832
46 📈
(Org: 61)
(7,769)
0.38 7,769
47 📉
(Org: 38)
(7,266)
0.14 7,266
48 📈
(Org: 89)
(7,251)
0.5 7,251
49 📉
(Org: 31)
(7,233)
0.02 7,233
50 📈
(Org: 199)
(7,162)
0.76 7,162
51 📉
(Org: 33)
(6,914)
0.02 6,914
52 📉
(Org: 37)
(6,673)
0.05 6,673
53 📉
(Org: 50)
(6,600)
0.21 6,600
54 📉
(Org: 44)
(6,506)
0.12 6,506
55 📈
(Org: 68)
(6,323)
0.27 6,323
56 📉
(Org: 42)
(6,316)
0.08 6,316
57 📉
(Org: 41)
(6,062)
0.03 6,062
58 📈
(Org: 81)
(5,831)
0.31 5,831
59 📉
(Org: 43)
(5,819)
0 5,819
60 📉
(Org: 48)
(5,811)
0.06 5,811
61 📉
(Org: 47)
(5,756)
0.03 5,756
62 📈
(Org: 87)
(5,742)
0.36 5,742
63 📈
(Org: 64)
(5,635)
0.17 5,635
64 📈
(Org: 93)
(5,611)
0.38 5,611
65 📈
(Org: 78)
(5,599)
0.26 5,599
66 📉
(Org: 56)
(5,555)
0.1 5,555
67 📈
(Org: 224)
(5,540)
0.73 5,540
68 📉
(Org: 49)
(5,409)
0.03 5,409
69 📉
(Org: 55)
(5,379)
0.07 5,379
70 📉
(Org: 62)
(5,169)
0.07 5,169
71 ➡️
(Org: 71)
(5,145)
0.13 5,145
72 📉
(Org: 63)
(5,096)
0.07 5,096
73 📉
(Org: 60)
(5,016)
0.02 5,016
74 📈
(Org: 76)
(5,003)
0.15 5,003
75 📈
(Org: 131)
(4,975)
0.51 4,975
76 📉
(Org: 66)
(4,776)
0.02 4,776
77 📉
(Org: 65)
(4,671)
- 4,671
78 📉
(Org: 67)
(4,654)
- 4,654
79 📉
(Org: 74)
(4,574)
0.06 4,574
80 📈
(Org: 91)
(4,573)
0.21 4,573
81 📉
(Org: 69)
(4,560)
- 4,560
82 📉
(Org: 72)
(4,533)
0.01 4,533
83 📈
(Org: 121)
(4,531)
0.4 4,531
84 📈
(Org: 108)
(4,525)
0.34 4,525
85 📉
(Org: 80)
(4,408)
0.07 4,408
86 📉
(Org: 77)
(4,370)
0.05 4,370
87 📈
(Org: 92)
(4,344)
0.2 4,344
88 📈
(Org: 103)
(4,312)
0.28 4,312
89 📈
(Org: 105)
(4,303)
0.29 4,303
90 📈
(Org: 144)
(4,213)
0.43 4,213
91 📈
(Org: 116)
(4,172)
0.32 4,172
92 📈
(Org: 134)
(4,137)
0.41 4,137
93 📉
(Org: 79)
(4,097)
- 4,097
94 📉
(Org: 83)
(4,005)
0.01 4,005
95 📉
(Org: 84)
(3,960)
0.01 3,960
96 📉
(Org: 94)
(3,910)
0.14 3,910
97 📈
(Org: 127)
(3,898)
0.35 3,898
98 📉
(Org: 86)
(3,854)
0.04 3,854
99 📈
(Org: 186)
(3,807)
0.51 3,807
100 📉
(Org: 95)
(3,805)
0.13 3,805