Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1975 - 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)
(59,489)
0.02 59,489
2 ➡️
(Org: 2)
(32,253)
- 32,253
3 📈
(Org: 6)
(27,930)
0.19 27,930
4 ➡️
(Org: 4)
(25,055)
0.04 25,055
5 📉
(Org: 3)
(24,322)
0 24,322
6 📉
(Org: 5)
(23,507)
0.01 23,507
7 ➡️
(Org: 7)
(21,843)
0.07 21,843
8 📈
(Org: 22)
(19,878)
0.54 19,878
9 📉
(Org: 8)
(18,382)
0.01 18,382
10 📉
(Org: 9)
(17,253)
0.09 17,253
11 📉
(Org: 10)
(16,812)
0.15 16,812
11 📈
(Org: 12)
(16,812)
0.23 16,812
13 📈
(Org: 17)
(16,316)
0.32 16,316
14 📈
(Org: 53)
(16,115)
0.68 16,115
15 📈
(Org: 16)
(16,093)
0.27 16,093
16 📈
(Org: 34)
(15,993)
0.55 15,993
17 📉
(Org: 11)
(15,413)
0.1 15,413
18 📈
(Org: 24)
(13,966)
0.39 13,966
19 📉
(Org: 13)
(13,101)
0.01 13,101
20 📉
(Org: 15)
(13,006)
0.04 13,006
21 📈
(Org: 58)
(12,747)
0.62 12,747
22 📉
(Org: 14)
(12,666)
0 12,666
23 📉
(Org: 18)
(11,334)
0.02 11,334
24 📉
(Org: 19)
(11,139)
0.01 11,139
25 📉
(Org: 20)
(10,990)
0.06 10,990
26 📈
(Org: 32)
(10,196)
0.27 10,196
27 📈
(Org: 39)
(10,120)
0.34 10,120
28 📈
(Org: 29)
(10,032)
0.22 10,032
29 📉
(Org: 26)
(9,928)
0.17 9,928
30 📉
(Org: 21)
(9,549)
0.02 9,549
31 📈
(Org: 57)
(9,382)
0.47 9,382
32 📉
(Org: 23)
(8,796)
0.01 8,796
33 📉
(Org: 31)
(8,626)
0.13 8,626
34 📈
(Org: 61)
(8,440)
0.45 8,440
35 📉
(Org: 27)
(8,339)
0.02 8,339
36 📉
(Org: 25)
(8,254)
0 8,254
37 📉
(Org: 33)
(8,123)
0.08 8,123
38 📉
(Org: 28)
(8,052)
0 8,052
39 📈
(Org: 43)
(7,820)
0.2 7,820
40 📉
(Org: 30)
(7,719)
0.02 7,719
41 📉
(Org: 37)
(7,689)
0.1 7,689
42 📈
(Org: 63)
(7,471)
0.39 7,471
43 📉
(Org: 42)
(7,417)
0.14 7,417
44 📉
(Org: 35)
(7,137)
0.01 7,137
45 📉
(Org: 38)
(7,090)
0.03 7,090
46 📉
(Org: 36)
(7,073)
0 7,073
47 📉
(Org: 40)
(6,638)
0.01 6,638
48 📉
(Org: 41)
(6,597)
0.02 6,597
49 📉
(Org: 47)
(6,276)
0.12 6,276
50 📈
(Org: 89)
(6,077)
0.45 6,077
51 📈
(Org: 65)
(6,013)
0.28 6,013
52 📈
(Org: 55)
(5,899)
0.14 5,899
53 📉
(Org: 45)
(5,897)
- 5,897
54 📉
(Org: 48)
(5,790)
0.05 5,790
55 📈
(Org: 94)
(5,771)
0.46 5,771
56 📉
(Org: 46)
(5,744)
0 5,744
57 📉
(Org: 49)
(5,658)
0.03 5,658
58 📉
(Org: 52)
(5,568)
0.04 5,568
59 📉
(Org: 51)
(5,485)
0.02 5,485
60 📉
(Org: 50)
(5,384)
0 5,384
61 📈
(Org: 163)
(5,201)
0.68 5,201
62 📈
(Org: 68)
(4,896)
0.14 4,896
63 📈
(Org: 71)
(4,870)
0.16 4,870
64 📉
(Org: 62)
(4,800)
0.04 4,800
65 📉
(Org: 59)
(4,690)
0 4,690
66 📉
(Org: 64)
(4,479)
0 4,479
67 📉
(Org: 66)
(4,431)
0.03 4,431
68 📈
(Org: 69)
(4,419)
0.05 4,419
69 📈
(Org: 70)
(4,279)
0.02 4,279
70 📉
(Org: 67)
(4,238)
- 4,238
71 📈
(Org: 90)
(4,219)
0.21 4,219
72 ➡️
(Org: 72)
(4,130)
0.02 4,130
73 📈
(Org: 76)
(4,089)
0.09 4,089
74 📈
(Org: 84)
(4,038)
0.15 4,038
75 ➡️
(Org: 75)
(3,916)
0.05 3,916
76 📈
(Org: 80)
(3,886)
0.09 3,886
77 📈
(Org: 81)
(3,867)
0.09 3,867
78 📈
(Org: 93)
(3,786)
0.16 3,786
79 📉
(Org: 77)
(3,688)
0.02 3,688
80 📈
(Org: 106)
(3,655)
0.26 3,655
81 📈
(Org: 118)
(3,635)
0.35 3,635
82 📈
(Org: 86)
(3,615)
0.06 3,615
83 📈
(Org: 85)
(3,600)
0.05 3,600
84 📈
(Org: 97)
(3,589)
0.16 3,589
85 📉
(Org: 79)
(3,583)
0 3,583
86 📉
(Org: 82)
(3,582)
0.02 3,582
87 📈
(Org: 95)
(3,462)
0.12 3,462
88 📉
(Org: 83)
(3,454)
- 3,454
89 📈
(Org: 160)
(3,409)
0.5 3,409
90 📉
(Org: 87)
(3,406)
- 3,406
91 ➡️
(Org: 91)
(3,383)
0.03 3,383
92 📈
(Org: 122)
(3,328)
0.3 3,328
93 📈
(Org: 148)
(3,305)
0.45 3,305
94 📉
(Org: 92)
(3,235)
0 3,235
95 📈
(Org: 102)
(3,139)
0.12 3,139
96 📈
(Org: 129)
(3,106)
0.28 3,106
96 📈
(Org: 214)
(3,106)
0.63 3,106
98 📈
(Org: 135)
(3,094)
0.33 3,094
99 📈
(Org: 113)
(3,018)
0.18 3,018
100 📈
(Org: 165)
(2,987)
0.46 2,987