Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1928 - 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)
(67,003)
0 67,003
2 ➡️
(Org: 2)
(38,859)
0.07 38,859
3 ➡️
(Org: 3)
(33,803)
0 33,803
4 ➡️
(Org: 4)
(23,604)
0.03 23,604
5 ➡️
(Org: 5)
(20,651)
0.02 20,651
6 ➡️
(Org: 6)
(17,917)
0 17,917
7 ➡️
(Org: 7)
(16,843)
0.02 16,843
8 ➡️
(Org: 8)
(14,878)
0 14,878
9 ➡️
(Org: 9)
(14,540)
0 14,540
10 ➡️
(Org: 10)
(14,267)
0 14,267
11 📈
(Org: 33)
(13,892)
0.5 13,892
12 📈
(Org: 13)
(12,730)
0.05 12,730
13 📉
(Org: 12)
(12,546)
0.03 12,546
14 📉
(Org: 11)
(12,331)
- 12,331
15 📉
(Org: 14)
(12,039)
0.02 12,039
16 📉
(Org: 15)
(11,652)
- 11,652
17 📈
(Org: 28)
(11,007)
0.3 11,007
18 📉
(Org: 17)
(10,743)
0.02 10,743
19 📉
(Org: 18)
(10,580)
0.01 10,580
19 📉
(Org: 16)
(10,580)
0 10,580
21 📈
(Org: 27)
(10,537)
0.25 10,537
22 📉
(Org: 19)
(10,148)
0 10,148
23 📉
(Org: 20)
(9,614)
- 9,614
24 📉
(Org: 21)
(9,336)
0.01 9,336
25 📉
(Org: 22)
(8,259)
0 8,259
26 📉
(Org: 23)
(8,213)
0.01 8,213
27 📉
(Org: 24)
(8,161)
- 8,161
28 📉
(Org: 25)
(8,126)
0 8,126
29 📉
(Org: 26)
(8,074)
0.02 8,074
30 📉
(Org: 29)
(7,893)
0.03 7,893
31 📈
(Org: 36)
(7,526)
0.13 7,526
32 📉
(Org: 30)
(7,259)
0 7,259
33 📉
(Org: 31)
(7,053)
- 7,053
34 📉
(Org: 32)
(7,000)
0 7,000
35 📉
(Org: 34)
(6,927)
0.03 6,927
36 📉
(Org: 35)
(6,626)
0.01 6,626
37 📈
(Org: 49)
(6,595)
0.19 6,595
38 📈
(Org: 39)
(6,519)
0.08 6,519
39 📉
(Org: 37)
(6,329)
- 6,329
40 📉
(Org: 38)
(6,277)
0.03 6,277
41 📈
(Org: 64)
(6,124)
0.31 6,124
42 📉
(Org: 40)
(5,978)
- 5,978
43 📉
(Org: 41)
(5,878)
0.01 5,878
44 📈
(Org: 51)
(5,744)
0.11 5,744
45 📉
(Org: 42)
(5,690)
0 5,690
46 📉
(Org: 43)
(5,595)
0.01 5,595
47 📉
(Org: 44)
(5,517)
- 5,517
48 📈
(Org: 53)
(5,510)
0.1 5,510
49 📉
(Org: 46)
(5,489)
0.01 5,489
50 📉
(Org: 45)
(5,473)
- 5,473
51 📉
(Org: 47)
(5,441)
0 5,441
52 📉
(Org: 48)
(5,413)
0 5,413
53 📉
(Org: 50)
(5,370)
0.04 5,370
54 📉
(Org: 52)
(5,013)
0 5,013
55 📈
(Org: 57)
(4,946)
0.03 4,946
56 📉
(Org: 54)
(4,932)
- 4,932
57 📉
(Org: 55)
(4,928)
- 4,928
58 📈
(Org: 61)
(4,856)
0.08 4,856
59 📉
(Org: 56)
(4,846)
- 4,846
60 ➡️
(Org: 60)
(4,803)
0.04 4,803
61 📉
(Org: 58)
(4,734)
- 4,734
62 📉
(Org: 59)
(4,731)
0.02 4,731
63 📉
(Org: 62)
(4,518)
0.02 4,518
64 📈
(Org: 71)
(4,359)
0.11 4,359
65 📉
(Org: 63)
(4,335)
0 4,335
66 📉
(Org: 65)
(4,113)
0 4,113
67 📉
(Org: 66)
(4,096)
- 4,096
68 ➡️
(Org: 68)
(4,072)
0.02 4,072
69 📉
(Org: 67)
(4,046)
0.01 4,046
70 📉
(Org: 69)
(3,975)
0.01 3,975
71 📉
(Org: 70)
(3,942)
0 3,942
72 📈
(Org: 88)
(3,885)
0.24 3,885
73 📈
(Org: 77)
(3,707)
0.1 3,707
74 📈
(Org: 76)
(3,494)
0.03 3,494
75 📉
(Org: 72)
(3,480)
0 3,480
76 📉
(Org: 73)
(3,477)
0 3,477
77 📉
(Org: 74)
(3,451)
0 3,451
78 ➡️
(Org: 78)
(3,446)
0.04 3,446
79 📈
(Org: 83)
(3,442)
0.09 3,442
80 📈
(Org: 97)
(3,314)
0.17 3,314
81 📈
(Org: 82)
(3,296)
0.04 3,296
82 📈
(Org: 104)
(3,259)
0.2 3,259
83 📉
(Org: 79)
(3,236)
0.01 3,236
84 📉
(Org: 81)
(3,227)
0.02 3,227
85 📉
(Org: 80)
(3,206)
- 3,206
86 📉
(Org: 84)
(3,158)
0.01 3,158
87 📈
(Org: 96)
(3,084)
0.1 3,084
88 📉
(Org: 87)
(3,057)
0.02 3,057
89 📉
(Org: 85)
(3,044)
0.01 3,044
90 📉
(Org: 86)
(3,023)
0 3,023
91 📈
(Org: 101)
(2,995)
0.11 2,995
92 📈
(Org: 95)
(2,968)
0.06 2,968
93 📉
(Org: 89)
(2,957)
0.01 2,957
94 📈
(Org: 135)
(2,894)
0.4 2,894
95 📉
(Org: 90)
(2,886)
0 2,886
96 📉
(Org: 91)
(2,883)
0.01 2,883
97 📉
(Org: 92)
(2,842)
- 2,842
98 📈
(Org: 126)
(2,833)
0.31 2,833
99 📉
(Org: 93)
(2,824)
- 2,824
100 📉
(Org: 94)
(2,810)
- 2,810