Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1977 - 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)
(60,185)
0.02 60,185
2 ➡️
(Org: 2)
(27,866)
0.04 27,866
3 📈
(Org: 11)
(26,864)
0.33 26,864
4 📉
(Org: 3)
(26,730)
- 26,730
5 📉
(Org: 4)
(25,174)
0.01 25,174
6 📈
(Org: 10)
(24,127)
0.24 24,127
7 📉
(Org: 5)
(23,799)
0 23,799
8 📉
(Org: 7)
(23,434)
0.17 23,434
9 📉
(Org: 6)
(21,147)
0.01 21,147
10 📉
(Org: 8)
(19,539)
0.06 19,539
11 📈
(Org: 16)
(19,258)
0.25 19,258
12 📉
(Org: 9)
(18,291)
0 18,291
13 📈
(Org: 15)
(18,089)
0.16 18,089
14 📈
(Org: 30)
(17,587)
0.55 17,587
15 📉
(Org: 14)
(17,251)
0.11 17,251
16 📉
(Org: 12)
(17,246)
0.01 17,246
17 📉
(Org: 13)
(17,096)
0.04 17,096
18 📈
(Org: 59)
(16,447)
0.72 16,447
19 📉
(Org: 17)
(15,932)
0.11 15,932
20 📈
(Org: 44)
(14,965)
0.6 14,965
21 📉
(Org: 18)
(14,465)
0.11 14,465
22 📈
(Org: 42)
(13,752)
0.55 13,752
23 📉
(Org: 19)
(12,754)
0.02 12,754
24 📈
(Org: 25)
(12,007)
0.19 12,007
25 📉
(Org: 20)
(11,990)
0.06 11,990
26 📉
(Org: 21)
(10,810)
0.01 10,810
27 📉
(Org: 26)
(10,809)
0.17 10,809
28 ➡️
(Org: 28)
(10,577)
0.18 10,577
29 📉
(Org: 23)
(10,472)
0.03 10,472
30 📈
(Org: 51)
(10,388)
0.47 10,388
31 📉
(Org: 22)
(10,354)
0.01 10,354
32 📈
(Org: 38)
(10,152)
0.35 10,152
33 📉
(Org: 24)
(9,783)
- 9,783
34 📈
(Org: 50)
(9,346)
0.38 9,346
35 📈
(Org: 45)
(8,742)
0.32 8,742
36 📉
(Org: 31)
(8,568)
0.11 8,568
37 📉
(Org: 29)
(8,073)
0 8,073
38 📉
(Org: 34)
(8,048)
0.1 8,048
39 📈
(Org: 57)
(7,718)
0.34 7,718
40 📉
(Org: 32)
(7,613)
0.02 7,613
41 📉
(Org: 35)
(7,550)
0.05 7,550
42 📉
(Org: 36)
(7,416)
0.04 7,416
43 📉
(Org: 33)
(7,219)
0 7,219
44 📈
(Org: 66)
(7,147)
0.41 7,147
45 📉
(Org: 37)
(7,125)
0.03 7,125
46 📉
(Org: 40)
(7,022)
0.1 7,022
47 📈
(Org: 79)
(6,710)
0.46 6,710
48 📉
(Org: 39)
(6,587)
0.03 6,587
49 📈
(Org: 52)
(6,436)
0.15 6,436
50 📉
(Org: 49)
(6,308)
0.09 6,308
51 📉
(Org: 41)
(6,265)
0 6,265
52 📈
(Org: 92)
(6,262)
0.5 6,262
53 📉
(Org: 43)
(6,138)
0.01 6,138
54 📈
(Org: 55)
(6,105)
0.13 6,105
55 📉
(Org: 47)
(5,924)
0 5,924
56 📉
(Org: 46)
(5,906)
- 5,906
57 📉
(Org: 48)
(5,887)
0.02 5,887
58 📉
(Org: 54)
(5,645)
0.06 5,645
59 📉
(Org: 53)
(5,556)
0.03 5,556
60 📈
(Org: 65)
(5,145)
0.17 5,145
61 📈
(Org: 105)
(5,143)
0.47 5,143
62 📈
(Org: 84)
(5,076)
0.32 5,076
63 📉
(Org: 58)
(5,005)
0.01 5,005
64 📉
(Org: 60)
(4,924)
0.11 4,924
65 📈
(Org: 187)
(4,517)
0.67 4,517
66 📉
(Org: 62)
(4,470)
0.03 4,470
67 📉
(Org: 61)
(4,451)
0.02 4,451
68 📈
(Org: 76)
(4,365)
0.13 4,365
69 📉
(Org: 63)
(4,313)
0 4,313
70 📉
(Org: 64)
(4,264)
- 4,264
71 📉
(Org: 69)
(4,204)
0.04 4,204
72 📈
(Org: 120)
(4,098)
0.41 4,098
73 📉
(Org: 67)
(4,085)
- 4,085
74 📈
(Org: 94)
(4,015)
0.23 4,015
75 📈
(Org: 80)
(4,008)
0.09 4,008
76 📈
(Org: 108)
(3,952)
0.32 3,952
77 📉
(Org: 73)
(3,941)
0.02 3,941
78 📉
(Org: 73)
(3,861)
0 3,861
79 📈
(Org: 88)
(3,803)
0.15 3,803
80 📈
(Org: 81)
(3,786)
0.04 3,786
81 📉
(Org: 78)
(3,689)
0 3,689
82 📈
(Org: 90)
(3,330)
0.04 3,330
83 📈
(Org: 85)
(3,311)
0.01 3,311
84 📈
(Org: 89)
(3,293)
0.02 3,293
85 📈
(Org: 86)
(3,279)
0 3,279
86 📈
(Org: 87)
(3,259)
- 3,259
87 📈
(Org: 95)
(3,245)
0.05 3,245
88 📈
(Org: 99)
(3,210)
0.09 3,210
89 📈
(Org: 93)
(3,194)
0.02 3,194
90 📈
(Org: 167)
(3,180)
0.49 3,180
91 ➡️
(Org: 91)
(3,151)
- 3,151
92 📈
(Org: 112)
(3,148)
0.18 3,148
93 📈
(Org: 96)
(3,124)
0.03 3,124
94 📈
(Org: 137)
(3,099)
0.32 3,099
95 📈
(Org: 190)
(3,029)
0.54 3,029
96 📈
(Org: 106)
(3,014)
0.1 3,014
97 ➡️
(Org: 97)
(2,994)
0.01 2,994
98 📈
(Org: 130)
(2,974)
0.27 2,974
99 📈
(Org: 162)
(2,926)
0.43 2,926
100 📈
(Org: 102)
(2,881)
0.02 2,881