Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2024 - 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: 6)
(20,206)
0.4 20,206
2 📉
(Org: 1)
(14,796)
0.01 14,796
3 📉
(Org: 2)
(14,183)
0.05 14,183
4 📉
(Org: 3)
(12,836)
0.01 12,836
5 📉
(Org: 4)
(12,558)
0 12,558
6 📉
(Org: 5)
(12,388)
0.02 12,388
7 ➡️
(Org: 7)
(11,306)
0.05 11,306
8 📈
(Org: 29)
(10,616)
0.46 10,616
9 📉
(Org: 8)
(10,340)
0.12 10,340
10 📈
(Org: 11)
(10,100)
0.25 10,100
11 📉
(Org: 9)
(8,878)
0.02 8,878
12 📈
(Org: 18)
(8,540)
0.25 8,540
13 📈
(Org: 42)
(8,071)
0.42 8,071
14 📈
(Org: 20)
(7,909)
0.19 7,909
15 📈
(Org: 24)
(7,907)
0.23 7,907
16 📈
(Org: 65)
(7,749)
0.57 7,749
17 📈
(Org: 37)
(7,707)
0.31 7,707
18 📈
(Org: 22)
(7,528)
0.19 7,528
19 📉
(Org: 14)
(7,448)
0.04 7,448
20 📉
(Org: 12)
(7,370)
- 7,370
21 📉
(Org: 13)
(7,213)
0.01 7,213
22 📉
(Org: 17)
(7,182)
0.04 7,182
23 📉
(Org: 15)
(7,067)
0.01 7,067
24 📉
(Org: 16)
(6,928)
0 6,928
25 📈
(Org: 27)
(6,889)
0.14 6,889
26 📈
(Org: 53)
(6,863)
0.42 6,863
27 📉
(Org: 21)
(6,649)
0.05 6,649
28 📉
(Org: 26)
(6,496)
0.09 6,496
29 📉
(Org: 23)
(6,437)
0.05 6,437
30 📉
(Org: 19)
(6,414)
0 6,414
31 📉
(Org: 25)
(6,319)
0.06 6,319
32 📈
(Org: 83)
(5,961)
0.51 5,961
33 📈
(Org: 34)
(5,950)
0.09 5,950
34 📉
(Org: 30)
(5,860)
0.03 5,860
35 📈
(Org: 36)
(5,835)
0.09 5,835
36 📈
(Org: 81)
(5,756)
0.48 5,756
37 📉
(Org: 28)
(5,741)
- 5,741
38 📉
(Org: 33)
(5,700)
0.04 5,700
39 📉
(Org: 35)
(5,661)
0.05 5,661
40 📉
(Org: 31)
(5,632)
- 5,632
41 📉
(Org: 32)
(5,566)
0.01 5,566
42 📈
(Org: 46)
(5,443)
0.16 5,443
43 📉
(Org: 39)
(5,386)
0.06 5,386
44 📈
(Org: 51)
(5,199)
0.19 5,199
45 📉
(Org: 43)
(5,192)
0.11 5,192
46 📉
(Org: 38)
(5,147)
- 5,147
47 📈
(Org: 163)
(5,059)
0.63 5,059
48 📈
(Org: 77)
(5,031)
0.39 5,031
49 📉
(Org: 40)
(5,019)
0 5,019
50 📈
(Org: 54)
(4,973)
0.22 4,973
51 📈
(Org: 69)
(4,907)
0.34 4,907
52 📉
(Org: 45)
(4,718)
0.03 4,718
53 📉
(Org: 44)
(4,705)
0.02 4,705
54 📉
(Org: 41)
(4,676)
0 4,676
55 📉
(Org: 52)
(4,659)
0.13 4,659
56 📈
(Org: 66)
(4,615)
0.27 4,615
57 📈
(Org: 93)
(4,486)
0.4 4,486
58 📉
(Org: 47)
(4,443)
0 4,443
59 📈
(Org: 95)
(4,334)
0.38 4,334
60 📉
(Org: 55)
(4,311)
0.11 4,311
61 📉
(Org: 48)
(4,301)
0.01 4,301
62 📉
(Org: 49)
(4,291)
0.01 4,291
63 📈
(Org: 103)
(4,260)
0.4 4,260
64 📉
(Org: 50)
(4,240)
- 4,240
65 📉
(Org: 61)
(4,214)
0.16 4,214
66 📈
(Org: 80)
(4,151)
0.28 4,151
67 📈
(Org: 140)
(3,982)
0.47 3,982
68 📈
(Org: 73)
(3,975)
0.22 3,975
69 📈
(Org: 100)
(3,882)
0.33 3,882
70 📈
(Org: 74)
(3,861)
0.2 3,861
71 📈
(Org: 148)
(3,857)
0.49 3,857
72 📉
(Org: 63)
(3,802)
0.07 3,802
73 📉
(Org: 57)
(3,797)
0.02 3,797
74 📉
(Org: 60)
(3,780)
0.05 3,780
75 📉
(Org: 56)
(3,751)
0 3,751
76 📈
(Org: 162)
(3,750)
0.5 3,750
77 📉
(Org: 58)
(3,723)
- 3,723
78 📈
(Org: 99)
(3,722)
0.3 3,722
79 📉
(Org: 67)
(3,709)
0.1 3,709
80 📈
(Org: 167)
(3,700)
0.51 3,700
81 📈
(Org: 148)
(3,618)
0.45 3,618
82 📈
(Org: 106)
(3,555)
0.3 3,555
83 📈
(Org: 85)
(3,544)
0.17 3,544
84 📉
(Org: 62)
(3,539)
0.01 3,539
85 📈
(Org: 129)
(3,525)
0.37 3,525
86 📉
(Org: 68)
(3,497)
0.05 3,497
87 📈
(Org: 217)
(3,490)
0.59 3,490
88 📉
(Org: 70)
(3,460)
0.08 3,460
89 📈
(Org: 102)
(3,451)
0.26 3,451
90 📉
(Org: 64)
(3,443)
0 3,443
91 📈
(Org: 130)
(3,407)
0.35 3,407
92 📉
(Org: 89)
(3,339)
0.14 3,339
93 📈
(Org: 122)
(3,313)
0.32 3,313
94 📈
(Org: 175)
(3,261)
0.47 3,261
95 📈
(Org: 294)
(3,255)
0.67 3,255
96 📉
(Org: 76)
(3,239)
0.05 3,239
97 📉
(Org: 71)
(3,235)
0.03 3,235
98 📈
(Org: 108)
(3,190)
0.22 3,190
99 📉
(Org: 78)
(3,168)
0.03 3,168
100 📉
(Org: 75)
(3,133)
0.01 3,133