Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2020 - 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: 5)
(20,118)
0.35 20,118
2 📉
(Org: 1)
(17,799)
0.01 17,799
3 📉
(Org: 2)
(16,315)
0.04 16,315
4 📉
(Org: 3)
(13,675)
0.03 13,675
5 📉
(Org: 4)
(13,105)
0 13,105
6 ➡️
(Org: 6)
(12,932)
0.01 12,932
7 ➡️
(Org: 7)
(12,666)
0.04 12,666
8 📈
(Org: 32)
(11,729)
0.54 11,729
9 📉
(Org: 8)
(11,547)
0.02 11,547
10 📈
(Org: 11)
(11,453)
0.29 11,453
11 📉
(Org: 9)
(10,660)
0.11 10,660
12 📈
(Org: 33)
(10,047)
0.47 10,047
13 📈
(Org: 24)
(9,069)
0.31 9,069
14 📉
(Org: 10)
(8,848)
- 8,848
15 📈
(Org: 43)
(8,678)
0.47 8,678
16 📉
(Org: 13)
(8,333)
0.05 8,333
17 📈
(Org: 26)
(8,204)
0.25 8,204
18 📈
(Org: 66)
(8,098)
0.56 8,098
19 📉
(Org: 12)
(8,070)
0.02 8,070
20 📉
(Org: 14)
(7,946)
0.01 7,946
21 ➡️
(Org: 21)
(7,713)
0.15 7,713
22 📉
(Org: 16)
(7,593)
0.04 7,593
23 📉
(Org: 15)
(7,558)
0.03 7,558
24 📉
(Org: 18)
(7,426)
0.07 7,426
25 📈
(Org: 30)
(7,408)
0.25 7,408
26 📈
(Org: 36)
(7,182)
0.27 7,182
27 ➡️
(Org: 27)
(7,007)
0.12 7,007
28 📉
(Org: 23)
(7,000)
0.11 7,000
29 📉
(Org: 20)
(6,958)
0.05 6,958
30 📉
(Org: 19)
(6,744)
- 6,744
31 📈
(Org: 45)
(6,697)
0.32 6,697
32 📉
(Org: 22)
(6,669)
0.04 6,669
33 📈
(Org: 56)
(6,354)
0.38 6,354
34 📉
(Org: 25)
(6,156)
0 6,156
35 📈
(Org: 53)
(6,148)
0.34 6,148
36 📉
(Org: 29)
(5,986)
0.06 5,986
37 📈
(Org: 116)
(5,778)
0.6 5,778
38 📈
(Org: 46)
(5,671)
0.2 5,671
39 📉
(Org: 28)
(5,652)
0.01 5,652
40 📈
(Org: 65)
(5,602)
0.36 5,602
41 📈
(Org: 79)
(5,572)
0.43 5,572
42 📉
(Org: 38)
(5,562)
0.1 5,562
43 📈
(Org: 49)
(5,560)
0.21 5,560
44 📉
(Org: 39)
(5,537)
0.1 5,537
45 📉
(Org: 31)
(5,527)
0 5,527
46 📉
(Org: 41)
(5,511)
0.13 5,511
47 📈
(Org: 118)
(5,496)
0.58 5,496
48 📉
(Org: 34)
(5,372)
0.01 5,372
49 📈
(Org: 51)
(5,334)
0.2 5,334
50 📉
(Org: 35)
(5,263)
0 5,263
51 📈
(Org: 54)
(5,254)
0.23 5,254
52 📉
(Org: 37)
(5,199)
0.01 5,199
53 📈
(Org: 81)
(5,132)
0.39 5,132
54 📈
(Org: 61)
(5,116)
0.27 5,116
55 📈
(Org: 253)
(4,939)
0.76 4,939
56 📉
(Org: 44)
(4,844)
0.05 4,844
57 📉
(Org: 47)
(4,834)
0.07 4,834
58 📈
(Org: 122)
(4,811)
0.53 4,811
59 📉
(Org: 50)
(4,805)
0.09 4,805
60 📉
(Org: 59)
(4,710)
0.2 4,710
61 📉
(Org: 42)
(4,694)
0.01 4,694
62 📈
(Org: 86)
(4,673)
0.34 4,673
63 📈
(Org: 117)
(4,625)
0.49 4,625
64 📈
(Org: 119)
(4,420)
0.48 4,420
65 📉
(Org: 48)
(4,415)
0 4,415
66 📈
(Org: 80)
(4,404)
0.28 4,404
67 📉
(Org: 64)
(4,342)
0.16 4,342
68 📉
(Org: 58)
(4,279)
0.1 4,279
69 📈
(Org: 77)
(4,234)
0.23 4,234
70 📉
(Org: 52)
(4,228)
0.03 4,228
71 📈
(Org: 101)
(4,227)
0.36 4,227
72 📈
(Org: 98)
(4,196)
0.35 4,196
73 📈
(Org: 121)
(4,191)
0.46 4,191
73 📈
(Org: 113)
(4,191)
0.43 4,191
75 📉
(Org: 57)
(4,132)
0.07 4,132
76 📉
(Org: 67)
(4,106)
0.14 4,106
77 📉
(Org: 62)
(4,052)
0.09 4,052
78 📉
(Org: 55)
(4,048)
0.03 4,048
79 📈
(Org: 92)
(4,017)
0.28 4,017
80 📉
(Org: 72)
(4,002)
0.16 4,002
81 📉
(Org: 60)
(3,969)
0.05 3,969
82 📈
(Org: 136)
(3,918)
0.49 3,918
83 📈
(Org: 88)
(3,910)
0.22 3,910
84 📈
(Org: 110)
(3,799)
0.35 3,799
85 📉
(Org: 63)
(3,729)
0.02 3,729
86 📈
(Org: 204)
(3,619)
0.6 3,619
87 📉
(Org: 74)
(3,584)
0.07 3,584
88 📉
(Org: 69)
(3,582)
0.04 3,582
89 📈
(Org: 109)
(3,578)
0.3 3,578
90 📉
(Org: 75)
(3,539)
0.06 3,539
91 📉
(Org: 68)
(3,523)
0 3,523
92 📈
(Org: 132)
(3,515)
0.42 3,515
93 📈
(Org: 191)
(3,425)
0.56 3,425
94 📉
(Org: 70)
(3,420)
- 3,420
95 📉
(Org: 84)
(3,409)
0.1 3,409
96 📈
(Org: 105)
(3,378)
0.25 3,378
97 📉
(Org: 71)
(3,376)
0 3,376
98 📉
(Org: 73)
(3,357)
0 3,357
99 📉
(Org: 85)
(3,354)
0.08 3,354
100 📉
(Org: 76)
(3,326)
0.01 3,326