Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1951 - 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)
(77,093)
0.04 77,093
2 ➡️
(Org: 2)
(66,174)
0.01 66,174
3 ➡️
(Org: 3)
(56,461)
0 56,461
4 📈
(Org: 6)
(46,133)
0.13 46,133
5 📉
(Org: 4)
(42,972)
0.02 42,972
6 📉
(Org: 5)
(40,634)
0 40,634
7 ➡️
(Org: 7)
(30,709)
0.01 30,709
8 ➡️
(Org: 8)
(28,286)
0.01 28,286
9 ➡️
(Org: 9)
(28,141)
0.02 28,141
10 ➡️
(Org: 10)
(27,873)
0.04 27,873
11 📈
(Org: 34)
(27,705)
0.62 27,705
12 📉
(Org: 11)
(26,974)
0.08 26,974
13 📉
(Org: 12)
(24,559)
0.02 24,559
14 📉
(Org: 13)
(24,361)
0.02 24,361
15 📉
(Org: 14)
(21,717)
- 21,717
16 📉
(Org: 15)
(19,841)
- 19,841
17 📉
(Org: 16)
(18,833)
0.01 18,833
18 📈
(Org: 39)
(18,277)
0.49 18,277
19 📉
(Org: 17)
(17,881)
0.01 17,881
20 📈
(Org: 35)
(17,843)
0.42 17,843
21 📉
(Org: 19)
(17,709)
0.04 17,709
22 📈
(Org: 24)
(17,704)
0.15 17,704
23 📉
(Org: 18)
(17,426)
0.02 17,426
24 📉
(Org: 20)
(16,338)
0 16,338
25 📉
(Org: 21)
(15,959)
- 15,959
26 📉
(Org: 22)
(15,402)
0.01 15,402
27 📉
(Org: 23)
(15,355)
0.02 15,355
28 📉
(Org: 25)
(14,975)
0 14,975
29 📉
(Org: 26)
(14,301)
0.02 14,301
30 📉
(Org: 29)
(14,288)
0.1 14,288
31 📉
(Org: 30)
(14,272)
0.16 14,272
32 📉
(Org: 27)
(13,947)
0 13,947
33 📈
(Org: 36)
(13,589)
0.27 13,589
34 📉
(Org: 28)
(13,490)
0 13,490
35 📈
(Org: 58)
(12,815)
0.48 12,815
36 📈
(Org: 63)
(12,576)
0.51 12,576
37 📉
(Org: 32)
(11,173)
0.02 11,173
38 📉
(Org: 31)
(10,961)
0 10,961
39 📉
(Org: 33)
(10,911)
0 10,911
40 📉
(Org: 37)
(9,965)
0.03 9,965
41 📉
(Org: 38)
(9,610)
0 9,610
42 📉
(Org: 41)
(9,564)
0.04 9,564
43 ➡️
(Org: 43)
(9,513)
0.06 9,513
44 📈
(Org: 56)
(9,455)
0.27 9,455
45 📉
(Org: 40)
(9,453)
0.03 9,453
46 📉
(Org: 42)
(9,110)
0 9,110
47 📉
(Org: 44)
(8,801)
0.01 8,801
48 📉
(Org: 46)
(8,429)
0 8,429
49 📉
(Org: 47)
(8,189)
0 8,189
50 📉
(Org: 48)
(8,151)
0 8,151
51 📈
(Org: 72)
(8,117)
0.31 8,117
52 📉
(Org: 49)
(7,759)
0.02 7,759
53 📈
(Org: 54)
(7,521)
0.08 7,521
54 📈
(Org: 95)
(7,517)
0.49 7,517
55 📉
(Org: 50)
(7,408)
0 7,408
56 📉
(Org: 51)
(7,312)
0 7,312
57 📉
(Org: 52)
(7,272)
0.01 7,272
58 📉
(Org: 53)
(7,090)
0 7,090
59 📉
(Org: 57)
(7,051)
0.04 7,051
60 ➡️
(Org: 60)
(6,924)
0.07 6,924
61 📉
(Org: 59)
(6,830)
0.04 6,830
62 📉
(Org: 61)
(6,531)
0.02 6,531
63 📉
(Org: 62)
(6,315)
- 6,315
64 📈
(Org: 67)
(6,197)
0.03 6,197
65 ➡️
(Org: 65)
(6,185)
- 6,185
66 ➡️
(Org: 66)
(6,140)
0.01 6,140
67 📈
(Org: 91)
(6,107)
0.34 6,107
68 📈
(Org: 70)
(6,081)
0.03 6,081
69 📉
(Org: 68)
(5,970)
0 5,970
70 📉
(Org: 69)
(5,897)
- 5,897
71 📈
(Org: 77)
(5,679)
0.1 5,679
72 📈
(Org: 115)
(5,451)
0.44 5,451
73 📈
(Org: 74)
(5,319)
0 5,319
74 📈
(Org: 79)
(5,313)
0.05 5,313
75 📈
(Org: 78)
(5,282)
0.04 5,282
76 📉
(Org: 75)
(5,256)
0 5,256
77 📉
(Org: 76)
(5,194)
0 5,194
78 📈
(Org: 90)
(5,147)
0.22 5,147
79 📈
(Org: 80)
(5,123)
0.02 5,123
80 📈
(Org: 125)
(4,978)
0.44 4,978
81 ➡️
(Org: 81)
(4,919)
0 4,919
82 ➡️
(Org: 82)
(4,873)
- 4,873
83 📈
(Org: 84)
(4,654)
0 4,654
84 📈
(Org: 85)
(4,639)
0.02 4,639
85 📈
(Org: 86)
(4,367)
- 4,367
86 📈
(Org: 88)
(4,300)
0.02 4,300
87 📈
(Org: 109)
(4,214)
0.21 4,214
88 📈
(Org: 103)
(4,176)
0.18 4,176
89 ➡️
(Org: 89)
(4,160)
0.01 4,160
90 📈
(Org: 92)
(3,989)
0 3,989
91 📈
(Org: 93)
(3,955)
0.02 3,955
92 📈
(Org: 97)
(3,904)
0.03 3,904
93 📈
(Org: 98)
(3,877)
0.03 3,877
94 ➡️
(Org: 94)
(3,870)
- 3,870
95 📈
(Org: 96)
(3,785)
- 3,785
96 📈
(Org: 102)
(3,762)
0.07 3,762
97 📈
(Org: 99)
(3,748)
0.02 3,748
98 📈
(Org: 111)
(3,636)
0.12 3,636
99 📈
(Org: 100)
(3,588)
0.01 3,588
100 📈
(Org: 101)
(3,554)
0 3,554