Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1949 - 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)
(94,896)
0.04 94,896
2 ➡️
(Org: 2)
(67,369)
0.01 67,369
3 ➡️
(Org: 3)
(46,325)
- 46,325
4 📈
(Org: 5)
(44,543)
0.15 44,543
5 📉
(Org: 4)
(42,614)
0 42,614
6 ➡️
(Org: 6)
(31,291)
0.02 31,291
7 📈
(Org: 8)
(29,847)
0.1 29,847
8 📉
(Org: 7)
(29,555)
0.01 29,555
9 ➡️
(Org: 9)
(27,438)
0.04 27,438
10 ➡️
(Org: 10)
(26,291)
0.02 26,291
11 📈
(Org: 37)
(23,909)
0.62 23,909
12 📉
(Org: 11)
(22,732)
0.01 22,732
13 📉
(Org: 12)
(22,440)
0.02 22,440
14 📉
(Org: 13)
(20,544)
- 20,544
15 📉
(Org: 14)
(19,648)
0.01 19,648
16 📉
(Org: 15)
(19,493)
0.01 19,493
17 📈
(Org: 36)
(18,566)
0.5 18,566
18 📉
(Org: 16)
(17,671)
0 17,671
19 📉
(Org: 17)
(17,654)
0.01 17,654
20 📉
(Org: 18)
(17,317)
0 17,317
21 📉
(Org: 19)
(17,251)
- 17,251
22 ➡️
(Org: 22)
(16,683)
0.1 16,683
23 📉
(Org: 20)
(16,369)
0.02 16,369
24 📉
(Org: 23)
(15,518)
0.04 15,518
25 📉
(Org: 21)
(15,441)
0.02 15,441
26 📉
(Org: 24)
(14,453)
- 14,453
27 📈
(Org: 28)
(14,319)
0.16 14,319
28 📈
(Org: 42)
(14,153)
0.4 14,153
29 📉
(Org: 25)
(13,951)
0.02 13,951
30 ➡️
(Org: 30)
(13,738)
0.14 13,738
31 📉
(Org: 26)
(13,596)
0 13,596
32 📉
(Org: 27)
(12,939)
0 12,939
33 📉
(Org: 29)
(11,883)
0 11,883
34 📉
(Org: 31)
(10,612)
0.01 10,612
35 📉
(Org: 32)
(10,438)
0 10,438
36 📉
(Org: 33)
(10,330)
0.05 10,330
37 📈
(Org: 51)
(10,164)
0.29 10,164
38 📈
(Org: 63)
(10,098)
0.45 10,098
39 📉
(Org: 35)
(9,931)
0.02 9,931
40 📉
(Org: 34)
(9,809)
- 9,809
41 📉
(Org: 38)
(9,395)
0.03 9,395
42 📉
(Org: 41)
(9,353)
0.07 9,353
43 📈
(Org: 70)
(9,141)
0.43 9,141
44 📉
(Org: 40)
(8,922)
0.02 8,922
45 📉
(Org: 39)
(8,915)
0 8,915
46 ➡️
(Org: 46)
(8,288)
0.07 8,288
47 📉
(Org: 43)
(8,272)
0.01 8,272
48 📈
(Org: 58)
(8,001)
0.25 8,001
49 📉
(Org: 45)
(7,902)
0.02 7,902
50 📉
(Org: 44)
(7,870)
- 7,870
51 📉
(Org: 49)
(7,712)
0.04 7,712
52 📉
(Org: 47)
(7,672)
0 7,672
53 📉
(Org: 50)
(7,637)
0.04 7,637
54 📉
(Org: 48)
(7,548)
0 7,548
55 📈
(Org: 74)
(6,960)
0.3 6,960
56 📈
(Org: 95)
(6,923)
0.46 6,923
57 📉
(Org: 54)
(6,790)
0.02 6,790
58 📉
(Org: 53)
(6,660)
- 6,660
59 📉
(Org: 55)
(6,592)
0 6,592
60 📉
(Org: 56)
(6,329)
0 6,329
61 📉
(Org: 57)
(6,316)
0.02 6,316
62 📈
(Org: 84)
(6,266)
0.31 6,266
63 📉
(Org: 60)
(6,019)
0.04 6,019
64 📈
(Org: 65)
(5,783)
0.07 5,783
65 📉
(Org: 64)
(5,528)
0 5,528
66 📈
(Org: 68)
(5,491)
0.04 5,491
67 ➡️
(Org: 67)
(5,486)
0.03 5,486
68 📉
(Org: 66)
(5,371)
- 5,371
69 ➡️
(Org: 69)
(5,367)
0.02 5,367
70 📈
(Org: 77)
(5,332)
0.1 5,332
71 ➡️
(Org: 71)
(5,157)
0 5,157
72 📈
(Org: 85)
(5,152)
0.2 5,152
73 📉
(Org: 72)
(5,148)
0 5,148
74 📈
(Org: 75)
(5,113)
0.06 5,113
75 📉
(Org: 73)
(5,034)
0.02 5,034
76 ➡️
(Org: 76)
(4,774)
- 4,774
77 📈
(Org: 78)
(4,664)
0 4,664
78 📈
(Org: 79)
(4,611)
- 4,611
79 📈
(Org: 80)
(4,610)
0.02 4,610
80 📈
(Org: 98)
(4,572)
0.21 4,572
81 📈
(Org: 115)
(4,366)
0.36 4,366
82 📈
(Org: 83)
(4,327)
- 4,327
83 📈
(Org: 100)
(4,268)
0.17 4,268
84 📈
(Org: 90)
(4,125)
0.05 4,125
85 📈
(Org: 86)
(4,052)
- 4,052
86 📈
(Org: 89)
(4,022)
0.02 4,022
87 ➡️
(Org: 87)
(3,991)
0 3,991
88 ➡️
(Org: 88)
(3,938)
0 3,938
89 📈
(Org: 92)
(3,927)
0.02 3,927
90 📈
(Org: 94)
(3,916)
0.03 3,916
91 ➡️
(Org: 91)
(3,897)
- 3,897
92 📈
(Org: 102)
(3,714)
0.07 3,714
93 📈
(Org: 97)
(3,669)
0 3,669
93 📈
(Org: 96)
(3,669)
- 3,669
95 📈
(Org: 135)
(3,667)
0.35 3,667
96 📈
(Org: 99)
(3,589)
- 3,589
97 📈
(Org: 103)
(3,453)
- 3,453
98 📈
(Org: 129)
(3,435)
0.27 3,435
99 📈
(Org: 105)
(3,432)
0.01 3,432
100 📈
(Org: 104)
(3,431)
0 3,431