Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2019 - 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: 4)
(21,260)
0.35 21,260
2 📉
(Org: 1)
(18,695)
0.01 18,695
3 📉
(Org: 2)
(17,881)
0.04 17,881
4 📉
(Org: 3)
(15,022)
0.03 15,022
5 ➡️
(Org: 5)
(13,919)
0.04 13,919
6 ➡️
(Org: 6)
(13,236)
- 13,236
7 ➡️
(Org: 7)
(13,089)
0.01 13,089
8 ➡️
(Org: 8)
(12,882)
0.03 12,882
9 📈
(Org: 31)
(12,471)
0.54 12,471
10 ➡️
(Org: 10)
(11,692)
0.11 11,692
11 📈
(Org: 15)
(11,127)
0.29 11,127
12 📈
(Org: 30)
(10,845)
0.47 10,845
13 📉
(Org: 9)
(10,494)
- 10,494
14 📉
(Org: 11)
(9,358)
0.02 9,358
15 📈
(Org: 23)
(9,246)
0.3 9,246
16 📉
(Org: 12)
(8,850)
0.07 8,850
17 📈
(Org: 24)
(8,761)
0.27 8,761
18 📈
(Org: 42)
(8,607)
0.44 8,607
19 📈
(Org: 21)
(8,389)
0.16 8,389
20 📈
(Org: 72)
(8,326)
0.57 8,326
21 📉
(Org: 13)
(8,324)
0.02 8,324
22 📉
(Org: 14)
(8,247)
0.04 8,247
23 📉
(Org: 20)
(8,093)
0.12 8,093
24 📈
(Org: 29)
(7,932)
0.25 7,932
25 📉
(Org: 16)
(7,884)
0.01 7,884
26 📈
(Org: 34)
(7,760)
0.3 7,760
27 📈
(Org: 46)
(7,712)
0.4 7,712
28 📉
(Org: 19)
(7,655)
0.04 7,655
29 📉
(Org: 18)
(7,349)
- 7,349
30 📉
(Org: 26)
(7,143)
0.12 7,143
31 📈
(Org: 42)
(7,136)
0.33 7,136
32 📉
(Org: 22)
(6,743)
0 6,743
33 📉
(Org: 27)
(6,497)
0.05 6,497
34 📉
(Org: 25)
(6,464)
0.01 6,464
35 📈
(Org: 69)
(6,416)
0.43 6,416
36 📈
(Org: 37)
(6,413)
0.2 6,413
37 📉
(Org: 32)
(6,210)
0.09 6,210
38 📉
(Org: 28)
(6,131)
0 6,131
39 📈
(Org: 41)
(5,901)
0.19 5,901
40 📈
(Org: 62)
(5,898)
0.34 5,898
41 📈
(Org: 70)
(5,858)
0.37 5,858
42 📈
(Org: 121)
(5,848)
0.58 5,848
43 📉
(Org: 35)
(5,824)
0.07 5,824
44 📈
(Org: 76)
(5,779)
0.4 5,779
45 📈
(Org: 123)
(5,689)
0.59 5,689
46 📈
(Org: 52)
(5,664)
0.24 5,664
47 📉
(Org: 44)
(5,535)
0.14 5,535
48 📈
(Org: 53)
(5,529)
0.23 5,529
49 📉
(Org: 36)
(5,496)
0.01 5,496
50 📉
(Org: 33)
(5,471)
0 5,471
51 📈
(Org: 242)
(5,388)
0.76 5,388
52 📈
(Org: 64)
(5,380)
0.29 5,380
53 📈
(Org: 81)
(5,113)
0.35 5,113
54 📈
(Org: 92)
(5,033)
0.39 5,033
55 📉
(Org: 39)
(5,026)
0 5,026
56 📉
(Org: 40)
(5,019)
0 5,019
57 📈
(Org: 110)
(5,010)
0.48 5,010
58 📈
(Org: 114)
(4,884)
0.48 4,884
59 📉
(Org: 48)
(4,862)
0.08 4,862
60 📉
(Org: 47)
(4,836)
0.07 4,836
61 📉
(Org: 56)
(4,811)
0.16 4,811
62 📈
(Org: 77)
(4,777)
0.28 4,777
63 📉
(Org: 54)
(4,775)
0.12 4,775
64 📈
(Org: 117)
(4,726)
0.47 4,726
65 📈
(Org: 120)
(4,679)
0.48 4,679
66 📉
(Org: 49)
(4,674)
0.05 4,674
67 📉
(Org: 51)
(4,639)
0.07 4,639
68 📉
(Org: 45)
(4,616)
0 4,616
69 📉
(Org: 55)
(4,603)
0.1 4,603
70 📈
(Org: 132)
(4,540)
0.54 4,540
71 ➡️
(Org: 71)
(4,497)
0.2 4,497
72 📈
(Org: 97)
(4,495)
0.36 4,495
73 📉
(Org: 50)
(4,493)
0.02 4,493
74 ➡️
(Org: 74)
(4,485)
0.22 4,485
75 ➡️
(Org: 75)
(4,478)
0.22 4,478
76 📉
(Org: 58)
(4,444)
0.09 4,444
77 📈
(Org: 96)
(4,414)
0.34 4,414
78 📉
(Org: 67)
(4,378)
0.16 4,378
79 📉
(Org: 57)
(4,242)
0.05 4,242
80 📈
(Org: 109)
(4,103)
0.37 4,103
81 📉
(Org: 60)
(4,070)
0.03 4,070
82 📉
(Org: 59)
(4,046)
0.02 4,046
83 📉
(Org: 66)
(3,977)
0.06 3,977
84 📉
(Org: 68)
(3,963)
0.07 3,963
85 📈
(Org: 203)
(3,939)
0.62 3,939
86 📉
(Org: 61)
(3,938)
0 3,938
87 📈
(Org: 106)
(3,922)
0.31 3,922
88 📈
(Org: 125)
(3,887)
0.42 3,887
89 📉
(Org: 63)
(3,867)
0.01 3,867
90 📉
(Org: 65)
(3,810)
0 3,810
91 📉
(Org: 79)
(3,621)
0.05 3,621
92 📉
(Org: 83)
(3,584)
0.1 3,584
93 📉
(Org: 78)
(3,581)
0.04 3,581
94 📉
(Org: 73)
(3,577)
0.01 3,577
95 📈
(Org: 107)
(3,544)
0.24 3,544
96 📈
(Org: 110)
(3,482)
0.26 3,482
97 📈
(Org: 187)
(3,439)
0.54 3,439
98 📉
(Org: 93)
(3,426)
0.12 3,426
99 📉
(Org: 85)
(3,374)
0.06 3,374
100 📉
(Org: 80)
(3,369)
- 3,369