Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1966 - 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)
(57,430)
0.01 57,430
2 📈
(Org: 4)
(38,327)
0.29 38,327
3 📉
(Org: 2)
(35,320)
0.09 35,320
4 📈
(Org: 6)
(30,397)
0.22 30,397
5 📉
(Org: 3)
(29,206)
0.01 29,206
6 📉
(Org: 5)
(25,788)
0.01 25,788
7 📈
(Org: 20)
(24,895)
0.38 24,895
8 📈
(Org: 21)
(23,079)
0.36 23,079
9 📈
(Org: 29)
(22,131)
0.41 22,131
10 📈
(Org: 31)
(21,830)
0.43 21,830
11 📉
(Org: 8)
(20,600)
0.1 20,600
12 📉
(Org: 7)
(20,128)
0 20,128
13 📉
(Org: 10)
(18,683)
0.03 18,683
14 📉
(Org: 9)
(18,615)
0 18,615
15 📈
(Org: 26)
(17,999)
0.26 17,999
16 📉
(Org: 11)
(17,566)
0.01 17,566
17 📉
(Org: 12)
(17,502)
0.03 17,502
18 📉
(Org: 15)
(17,237)
0.06 17,237
19 ➡️
(Org: 19)
(16,946)
0.08 16,946
20 📉
(Org: 18)
(16,891)
0.08 16,891
21 📉
(Org: 13)
(16,623)
0.02 16,623
22 📈
(Org: 54)
(16,604)
0.58 16,604
23 📉
(Org: 14)
(16,549)
0.02 16,549
24 📉
(Org: 16)
(16,393)
0.03 16,393
25 📉
(Org: 17)
(16,152)
0.02 16,152
26 📉
(Org: 22)
(14,820)
0.04 14,820
27 📈
(Org: 34)
(14,075)
0.17 14,075
28 📉
(Org: 23)
(14,070)
0.01 14,070
29 📉
(Org: 24)
(13,730)
0.01 13,730
30 📉
(Org: 28)
(13,334)
0.02 13,334
31 📉
(Org: 25)
(13,295)
- 13,295
32 📉
(Org: 27)
(13,134)
0 13,134
33 📉
(Org: 30)
(12,998)
- 12,998
34 📉
(Org: 33)
(11,931)
0.02 11,931
35 📉
(Org: 32)
(11,849)
0 11,849
36 📈
(Org: 39)
(11,619)
0.16 11,619
37 ➡️
(Org: 37)
(11,506)
0.09 11,506
38 📉
(Org: 35)
(11,478)
0.02 11,478
39 📈
(Org: 42)
(11,182)
0.16 11,182
40 📉
(Org: 38)
(11,180)
0.09 11,180
41 📈
(Org: 59)
(10,445)
0.4 10,445
42 📉
(Org: 40)
(10,221)
0.04 10,221
43 📉
(Org: 41)
(10,189)
0.07 10,189
44 📈
(Org: 47)
(9,977)
0.16 9,977
45 📈
(Org: 76)
(9,633)
0.52 9,633
46 📉
(Org: 43)
(9,194)
- 9,194
47 📉
(Org: 44)
(9,162)
0 9,162
48 ➡️
(Org: 48)
(9,100)
0.09 9,100
49 📉
(Org: 45)
(8,750)
- 8,750
50 📈
(Org: 72)
(8,494)
0.42 8,494
51 📉
(Org: 49)
(7,903)
0 7,903
52 📉
(Org: 50)
(7,873)
0 7,873
53 📈
(Org: 132)
(7,675)
0.64 7,675
54 📉
(Org: 53)
(7,401)
0.06 7,401
55 📈
(Org: 67)
(7,301)
0.27 7,301
56 ➡️
(Org: 56)
(7,255)
0.06 7,255
57 📉
(Org: 51)
(7,208)
- 7,208
58 ➡️
(Org: 58)
(7,167)
0.11 7,167
59 📉
(Org: 52)
(7,145)
- 7,145
60 📉
(Org: 57)
(7,056)
0.09 7,056
61 📉
(Org: 54)
(7,053)
0.01 7,053
62 📈
(Org: 115)
(6,915)
0.56 6,915
63 📉
(Org: 60)
(6,217)
0.02 6,217
64 📈
(Org: 77)
(6,194)
0.27 6,194
65 📈
(Org: 85)
(6,099)
0.34 6,099
66 📉
(Org: 61)
(5,992)
- 5,992
67 📈
(Org: 134)
(5,873)
0.54 5,873
68 📈
(Org: 71)
(5,815)
0.14 5,815
69 📈
(Org: 81)
(5,657)
0.24 5,657
70 📈
(Org: 185)
(5,623)
0.69 5,623
71 📈
(Org: 118)
(5,576)
0.46 5,576
72 📉
(Org: 68)
(5,528)
0.05 5,528
73 📉
(Org: 64)
(5,525)
0 5,525
74 📉
(Org: 65)
(5,468)
0 5,468
75 📉
(Org: 66)
(5,354)
- 5,354
76 📉
(Org: 73)
(5,212)
0.07 5,212
77 📉
(Org: 70)
(5,193)
0.02 5,193
78 📉
(Org: 75)
(4,881)
0.03 4,881
79 📉
(Org: 74)
(4,840)
0.01 4,840
80 📈
(Org: 89)
(4,623)
0.17 4,623
81 📈
(Org: 105)
(4,606)
0.28 4,606
82 📉
(Org: 79)
(4,481)
0.01 4,481
83 📉
(Org: 80)
(4,345)
- 4,345
84 📉
(Org: 82)
(4,300)
0 4,300
85 📈
(Org: 93)
(4,168)
0.1 4,168
86 📉
(Org: 84)
(4,158)
0.02 4,158
87 📉
(Org: 83)
(4,151)
- 4,151
88 📉
(Org: 87)
(4,047)
0.02 4,047
89 📈
(Org: 90)
(3,996)
0.04 3,996
90 📈
(Org: 94)
(3,978)
0.06 3,978
91 📉
(Org: 88)
(3,877)
0 3,877
92 📈
(Org: 97)
(3,808)
0.08 3,808
93 📉
(Org: 92)
(3,747)
- 3,747
94 📈
(Org: 100)
(3,731)
0.09 3,731
95 ➡️
(Org: 95)
(3,684)
0 3,684
96 📈
(Org: 111)
(3,669)
0.12 3,669
97 📉
(Org: 96)
(3,629)
- 3,629
98 📈
(Org: 168)
(3,567)
0.43 3,567
99 📉
(Org: 98)
(3,514)
0.01 3,514
100 📈
(Org: 102)
(3,453)
0.02 3,453