Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1974 - 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)
(64,461)
0.02 64,461
2 📈
(Org: 3)
(31,678)
0.18 31,678
3 📉
(Org: 2)
(29,564)
- 29,564
4 📈
(Org: 6)
(24,208)
0.07 24,208
5 📉
(Org: 4)
(23,200)
0 23,200
6 📈
(Org: 7)
(23,116)
0.04 23,116
7 📉
(Org: 5)
(22,919)
0.01 22,919
8 📈
(Org: 19)
(22,817)
0.57 22,817
9 📉
(Org: 8)
(20,003)
0.01 20,003
10 📉
(Org: 9)
(18,816)
0.1 18,816
11 📉
(Org: 10)
(16,566)
0.08 16,566
12 📈
(Org: 57)
(16,397)
0.69 16,397
13 📈
(Org: 23)
(15,663)
0.41 15,663
14 📉
(Org: 11)
(15,573)
0.16 15,573
15 📈
(Org: 38)
(15,332)
0.56 15,332
16 📉
(Org: 15)
(14,971)
0.28 14,971
17 📉
(Org: 16)
(14,658)
0.26 14,658
18 📈
(Org: 20)
(14,453)
0.32 14,453
19 📉
(Org: 12)
(12,762)
0.04 12,762
20 📈
(Org: 62)
(12,666)
0.64 12,666
21 📉
(Org: 13)
(11,912)
0.01 11,912
22 📈
(Org: 30)
(11,875)
0.33 11,875
23 📈
(Org: 27)
(11,647)
0.27 11,647
24 📉
(Org: 14)
(11,564)
0.02 11,564
25 📉
(Org: 18)
(10,784)
0.02 10,784
26 📉
(Org: 17)
(10,771)
0.01 10,771
27 📉
(Org: 24)
(10,645)
0.13 10,645
28 📉
(Org: 21)
(10,430)
0.07 10,430
29 📉
(Org: 22)
(9,489)
0.01 9,489
30 📈
(Org: 52)
(9,477)
0.43 9,477
31 📈
(Org: 36)
(8,919)
0.17 8,919
32 📉
(Org: 26)
(8,879)
0.03 8,879
33 📉
(Org: 25)
(8,781)
0.01 8,781
34 📉
(Org: 28)
(8,454)
- 8,454
35 📉
(Org: 32)
(8,334)
0.09 8,334
36 📈
(Org: 42)
(8,289)
0.22 8,289
37 📉
(Org: 29)
(8,059)
0 8,059
38 📉
(Org: 31)
(7,936)
0.02 7,936
39 📈
(Org: 80)
(7,728)
0.5 7,728
40 📉
(Org: 33)
(7,659)
0.01 7,659
41 📉
(Org: 40)
(7,626)
0.13 7,626
42 📉
(Org: 34)
(7,478)
0 7,478
43 📉
(Org: 35)
(7,471)
- 7,471
44 📉
(Org: 41)
(7,228)
0.1 7,228
45 📈
(Org: 49)
(7,159)
0.21 7,159
46 📈
(Org: 74)
(7,093)
0.42 7,093
47 📉
(Org: 37)
(6,877)
- 6,877
48 📉
(Org: 39)
(6,777)
0.02 6,777
49 📉
(Org: 43)
(6,461)
0.03 6,461
50 📉
(Org: 44)
(6,400)
0.02 6,400
51 📈
(Org: 63)
(6,321)
0.28 6,321
52 📈
(Org: 91)
(6,208)
0.47 6,208
53 📉
(Org: 47)
(6,029)
0.03 6,029
53 📈
(Org: 56)
(6,029)
0.15 6,029
55 📉
(Org: 46)
(5,996)
- 5,996
56 📉
(Org: 51)
(5,655)
0.03 5,655
57 📈
(Org: 99)
(5,498)
0.46 5,498
58 📉
(Org: 53)
(5,409)
0 5,409
59 📉
(Org: 54)
(5,382)
0.02 5,382
60 📉
(Org: 55)
(5,340)
0.03 5,340
61 📈
(Org: 65)
(5,288)
0.16 5,288
62 📈
(Org: 66)
(5,079)
0.13 5,079
63 📉
(Org: 58)
(5,069)
0 5,069
64 📈
(Org: 158)
(4,913)
0.65 4,913
65 📉
(Org: 59)
(4,829)
- 4,829
66 📉
(Org: 60)
(4,810)
0.03 4,810
67 📉
(Org: 63)
(4,577)
0.01 4,577
68 ➡️
(Org: 68)
(4,559)
0.05 4,559
69 📉
(Org: 67)
(4,545)
0.04 4,545
70 📈
(Org: 83)
(4,523)
0.21 4,523
71 📉
(Org: 69)
(4,503)
0.04 4,503
72 📉
(Org: 70)
(4,469)
0.04 4,469
73 📈
(Org: 75)
(4,446)
0.08 4,446
74 📈
(Org: 76)
(4,369)
0.1 4,369
75 📉
(Org: 71)
(4,284)
0.01 4,284
76 📈
(Org: 88)
(4,223)
0.17 4,223
77 📈
(Org: 86)
(4,174)
0.16 4,174
78 📈
(Org: 84)
(4,109)
0.13 4,109
79 📉
(Org: 78)
(3,969)
0.02 3,969
80 📉
(Org: 77)
(3,912)
0 3,912
81 📈
(Org: 89)
(3,844)
0.11 3,844
82 📉
(Org: 81)
(3,831)
0.02 3,831
83 📈
(Org: 146)
(3,820)
0.5 3,820
84 📈
(Org: 90)
(3,804)
0.1 3,804
85 📈
(Org: 114)
(3,636)
0.29 3,636
86 📉
(Org: 82)
(3,626)
0 3,626
87 ➡️
(Org: 87)
(3,533)
0.01 3,533
88 📉
(Org: 85)
(3,528)
- 3,528
89 📈
(Org: 97)
(3,486)
0.13 3,486
90 📈
(Org: 125)
(3,457)
0.33 3,457
91 📈
(Org: 184)
(3,439)
0.58 3,439
92 📈
(Org: 107)
(3,356)
0.17 3,356
93 📈
(Org: 151)
(3,335)
0.45 3,335
94 📈
(Org: 109)
(3,309)
0.17 3,309
95 📉
(Org: 92)
(3,278)
0 3,278
96 📈
(Org: 115)
(3,196)
0.2 3,196
97 📉
(Org: 94)
(3,191)
0.02 3,191
97 📉
(Org: 93)
(3,191)
0 3,191
99 📈
(Org: 131)
(3,164)
0.33 3,164
100 📈
(Org: 134)
(3,150)
0.34 3,150