Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1972 - 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)
(64,944)
0.02 64,944
2 ➡️
(Org: 2)
(37,006)
0.21 37,006
3 📈
(Org: 4)
(28,457)
0.08 28,457
4 📉
(Org: 3)
(27,866)
0.01 27,866
5 ➡️
(Org: 5)
(25,872)
- 25,872
6 ➡️
(Org: 6)
(23,686)
0.01 23,686
7 ➡️
(Org: 7)
(23,465)
0.04 23,465
8 📈
(Org: 16)
(23,262)
0.48 23,262
9 📈
(Org: 19)
(19,415)
0.41 19,415
10 📉
(Org: 8)
(18,808)
0.1 18,808
11 📉
(Org: 10)
(18,763)
0.16 18,763
12 📈
(Org: 33)
(16,967)
0.55 16,967
13 📉
(Org: 9)
(16,335)
0 16,335
14 📉
(Org: 11)
(16,315)
0.13 16,315
15 📈
(Org: 23)
(15,537)
0.3 15,537
16 📈
(Org: 24)
(14,494)
0.27 14,494
17 📈
(Org: 28)
(14,388)
0.34 14,388
18 📉
(Org: 12)
(14,320)
0.02 14,320
19 📉
(Org: 14)
(14,125)
0.06 14,125
20 📉
(Org: 13)
(13,969)
0.02 13,969
21 📈
(Org: 25)
(13,908)
0.27 13,908
22 📈
(Org: 74)
(13,884)
0.7 13,884
23 📈
(Org: 65)
(13,353)
0.65 13,353
24 📉
(Org: 17)
(12,691)
0.07 12,691
25 📉
(Org: 15)
(12,599)
0.03 12,599
26 📈
(Org: 39)
(12,010)
0.4 12,010
27 📉
(Org: 18)
(11,636)
0.01 11,636
28 📉
(Org: 20)
(11,441)
0.01 11,441
29 📉
(Org: 21)
(11,333)
0.01 11,333
30 📉
(Org: 22)
(11,212)
0.02 11,212
31 📉
(Org: 25)
(10,288)
0.01 10,288
32 📉
(Org: 27)
(9,600)
- 9,600
33 📉
(Org: 29)
(9,397)
0.09 9,397
34 📈
(Org: 49)
(9,300)
0.34 9,300
35 📉
(Org: 31)
(8,063)
0.02 8,063
36 📉
(Org: 30)
(8,021)
- 8,021
37 📉
(Org: 32)
(7,787)
0.01 7,787
38 📈
(Org: 40)
(7,666)
0.16 7,666
39 📉
(Org: 34)
(7,624)
0.02 7,624
40 📉
(Org: 38)
(7,408)
0.02 7,408
41 📉
(Org: 35)
(7,406)
0 7,406
42 📉
(Org: 37)
(7,243)
- 7,243
43 📈
(Org: 55)
(7,065)
0.24 7,065
44 📈
(Org: 53)
(6,994)
0.22 6,994
45 📉
(Org: 43)
(6,562)
0.04 6,562
46 📈
(Org: 87)
(6,519)
0.47 6,519
47 📉
(Org: 45)
(6,516)
0.04 6,516
48 📉
(Org: 42)
(6,514)
0.03 6,514
49 📈
(Org: 59)
(6,443)
0.22 6,443
50 ➡️
(Org: 50)
(6,361)
0.04 6,361
51 📉
(Org: 47)
(6,317)
0.03 6,317
52 📉
(Org: 51)
(6,290)
0.09 6,290
53 📉
(Org: 44)
(6,270)
- 6,270
54 📉
(Org: 46)
(6,265)
0.01 6,265
55 📈
(Org: 56)
(6,158)
0.17 6,158
56 📉
(Org: 48)
(6,120)
- 6,120
57 📈
(Org: 97)
(5,982)
0.46 5,982
58 📈
(Org: 60)
(5,970)
0.16 5,970
59 📉
(Org: 52)
(5,772)
0.03 5,772
60 📉
(Org: 57)
(5,652)
0.1 5,652
61 📈
(Org: 108)
(5,629)
0.46 5,629
62 📉
(Org: 61)
(5,408)
0.1 5,408
63 📉
(Org: 54)
(5,402)
- 5,402
64 📉
(Org: 58)
(5,079)
- 5,079
65 📈
(Org: 115)
(5,008)
0.44 5,008
66 📈
(Org: 71)
(4,997)
0.12 4,997
67 📉
(Org: 63)
(4,926)
0.02 4,926
68 📈
(Org: 148)
(4,921)
0.61 4,921
69 📈
(Org: 75)
(4,851)
0.14 4,851
70 ➡️
(Org: 70)
(4,848)
0.08 4,848
71 📉
(Org: 62)
(4,845)
0 4,845
72 📉
(Org: 64)
(4,841)
0.02 4,841
73 📈
(Org: 79)
(4,800)
0.21 4,800
74 📉
(Org: 66)
(4,769)
0.02 4,769
75 📈
(Org: 140)
(4,739)
0.56 4,739
76 📈
(Org: 78)
(4,714)
0.14 4,714
77 📉
(Org: 73)
(4,712)
0.11 4,712
78 📈
(Org: 147)
(4,535)
0.58 4,535
79 📈
(Org: 124)
(4,523)
0.45 4,523
80 📉
(Org: 72)
(4,265)
0 4,265
81 📈
(Org: 106)
(4,204)
0.27 4,204
82 📈
(Org: 117)
(4,188)
0.34 4,188
83 📉
(Org: 76)
(4,181)
- 4,181
84 📉
(Org: 80)
(4,096)
0.09 4,096
85 📉
(Org: 77)
(4,088)
- 4,088
86 📈
(Org: 94)
(3,995)
0.18 3,995
87 📈
(Org: 119)
(3,952)
0.33 3,952
88 📈
(Org: 107)
(3,864)
0.21 3,864
89 📉
(Org: 81)
(3,749)
0.02 3,749
90 📉
(Org: 82)
(3,598)
0.01 3,598
91 📈
(Org: 177)
(3,596)
0.55 3,596
92 📉
(Org: 84)
(3,568)
0.01 3,568
93 📈
(Org: 96)
(3,566)
0.08 3,566
94 📉
(Org: 83)
(3,564)
0 3,564
95 📉
(Org: 89)
(3,465)
0.02 3,465
96 📉
(Org: 86)
(3,449)
- 3,449
97 📈
(Org: 111)
(3,408)
0.13 3,408
98 📉
(Org: 90)
(3,394)
- 3,394
99 📈
(Org: 248)
(3,389)
0.68 3,389
100 📉
(Org: 93)
(3,384)
0.03 3,384