Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2006 - 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)
(23,237)
0.08 23,237
2 📈
(Org: 3)
(19,757)
0.06 19,757
3 📉
(Org: 2)
(19,379)
0.01 19,379
4 ➡️
(Org: 4)
(19,090)
0.04 19,090
5 📈
(Org: 9)
(18,642)
0.28 18,642
6 📈
(Org: 25)
(18,595)
0.55 18,595
7 📈
(Org: 41)
(18,116)
0.66 18,116
8 📉
(Org: 5)
(17,126)
0.01 17,126
9 📉
(Org: 6)
(16,513)
0.05 16,513
10 📉
(Org: 8)
(15,780)
0.08 15,780
11 📉
(Org: 7)
(15,741)
0.01 15,741
12 📈
(Org: 15)
(15,657)
0.29 15,657
13 📈
(Org: 20)
(13,813)
0.32 13,813
14 📈
(Org: 17)
(13,681)
0.2 13,681
15 📉
(Org: 12)
(13,360)
0.08 13,360
16 📉
(Org: 11)
(13,146)
0.05 13,146
17 📈
(Org: 42)
(12,754)
0.53 12,754
18 📉
(Org: 13)
(12,625)
0.05 12,625
19 📉
(Org: 10)
(12,487)
0 12,487
20 📈
(Org: 37)
(12,411)
0.49 12,411
21 📉
(Org: 18)
(11,729)
0.11 11,729
22 📉
(Org: 19)
(11,705)
0.13 11,705
23 📉
(Org: 14)
(11,626)
0.03 11,626
24 📉
(Org: 16)
(11,072)
0.01 11,072
25 📈
(Org: 33)
(10,305)
0.34 10,305
26 📈
(Org: 29)
(10,004)
0.25 10,004
27 📈
(Org: 66)
(9,942)
0.53 9,942
28 📈
(Org: 46)
(9,723)
0.42 9,723
29 📈
(Org: 53)
(9,694)
0.46 9,694
30 📈
(Org: 54)
(9,621)
0.46 9,621
31 📉
(Org: 30)
(9,376)
0.24 9,376
32 📉
(Org: 21)
(9,323)
0.01 9,323
33 📉
(Org: 23)
(9,114)
0.06 9,114
34 📈
(Org: 56)
(9,104)
0.44 9,104
35 📉
(Org: 26)
(8,984)
0.08 8,984
36 📈
(Org: 76)
(8,973)
0.52 8,973
37 📈
(Org: 71)
(8,857)
0.49 8,857
38 📉
(Org: 24)
(8,726)
0.03 8,726
39 📉
(Org: 22)
(8,670)
0.01 8,670
40 📈
(Org: 57)
(8,600)
0.41 8,600
41 📈
(Org: 84)
(8,541)
0.53 8,541
42 📉
(Org: 28)
(8,505)
0.1 8,505
43 📈
(Org: 50)
(8,491)
0.37 8,491
44 📉
(Org: 34)
(8,300)
0.21 8,300
45 📈
(Org: 47)
(8,113)
0.31 8,113
46 📉
(Org: 36)
(7,888)
0.2 7,888
47 📉
(Org: 38)
(7,878)
0.21 7,878
48 📉
(Org: 27)
(7,775)
0.02 7,775
49 📉
(Org: 32)
(7,031)
0.03 7,031
50 📉
(Org: 31)
(7,021)
0.02 7,021
51 📈
(Org: 73)
(6,909)
0.37 6,909
52 📉
(Org: 35)
(6,659)
0.02 6,659
53 📈
(Org: 252)
(6,643)
0.8 6,643
54 📉
(Org: 48)
(6,594)
0.16 6,594
55 📈
(Org: 66)
(6,511)
0.28 6,511
56 📉
(Org: 40)
(6,501)
0.06 6,501
57 📈
(Org: 68)
(6,427)
0.28 6,427
58 📉
(Org: 45)
(6,416)
0.12 6,416
59 📉
(Org: 39)
(6,246)
0.02 6,246
60 📉
(Org: 43)
(5,961)
0 5,961
61 📉
(Org: 44)
(5,942)
0.03 5,942
62 📈
(Org: 90)
(5,919)
0.37 5,919
63 📉
(Org: 51)
(5,716)
0.08 5,716
64 📈
(Org: 203)
(5,557)
0.7 5,557
65 📉
(Org: 49)
(5,526)
- 5,526
66 📉
(Org: 65)
(5,481)
0.13 5,481
67 📈
(Org: 100)
(5,463)
0.38 5,463
68 📈
(Org: 70)
(5,367)
0.16 5,367
69 📉
(Org: 58)
(5,341)
0.06 5,341
70 📈
(Org: 96)
(5,325)
0.33 5,325
71 📉
(Org: 52)
(5,254)
- 5,254
72 📉
(Org: 63)
(5,184)
0.07 5,184
73 📈
(Org: 93)
(5,153)
0.29 5,153
74 📈
(Org: 107)
(5,143)
0.4 5,143
75 📉
(Org: 64)
(5,137)
0.06 5,137
76 📈
(Org: 85)
(5,116)
0.21 5,116
77 📉
(Org: 60)
(5,106)
0.03 5,106
78 📈
(Org: 110)
(5,091)
0.41 5,091
79 📈
(Org: 138)
(5,023)
0.49 5,023
80 📉
(Org: 62)
(5,012)
0.03 5,012
81 📉
(Org: 59)
(5,006)
- 5,006
82 📉
(Org: 69)
(4,901)
0.05 4,901
83 📉
(Org: 74)
(4,831)
0.11 4,831
84 📈
(Org: 112)
(4,655)
0.36 4,655
85 📈
(Org: 86)
(4,557)
0.12 4,557
86 📉
(Org: 79)
(4,499)
0.07 4,499
87 📈
(Org: 92)
(4,441)
0.17 4,441
88 📈
(Org: 155)
(4,402)
0.49 4,402
89 📉
(Org: 77)
(4,378)
0.03 4,378
90 📉
(Org: 81)
(4,374)
0.06 4,374
91 📉
(Org: 88)
(4,315)
0.09 4,315
92 📈
(Org: 108)
(4,179)
0.27 4,179
93 📉
(Org: 80)
(4,158)
0.01 4,158
94 📉
(Org: 83)
(4,149)
0.02 4,149
95 📈
(Org: 118)
(4,127)
0.31 4,127
96 📈
(Org: 370)
(4,064)
0.78 4,064
97 📉
(Org: 94)
(3,985)
0.1 3,985
98 📈
(Org: 104)
(3,966)
0.2 3,966
99 ➡️
(Org: 99)
(3,902)
0.13 3,902
100 📈
(Org: 141)
(3,846)
0.36 3,846