Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1986 - 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)
(53,367)
0.01 53,367
2 ➡️
(Org: 2)
(52,400)
0.05 52,400
3 ➡️
(Org: 3)
(40,576)
0 40,576
4 📈
(Org: 5)
(39,288)
0.28 39,288
5 📉
(Org: 4)
(36,995)
0.02 36,995
6 ➡️
(Org: 6)
(25,321)
0.11 25,321
7 ➡️
(Org: 7)
(24,625)
0.14 24,625
8 📈
(Org: 41)
(23,511)
0.67 23,511
9 📈
(Org: 28)
(22,995)
0.54 22,995
10 📉
(Org: 8)
(22,279)
0.09 22,279
11 📈
(Org: 19)
(21,529)
0.33 21,529
12 📉
(Org: 10)
(19,898)
0.04 19,898
13 📉
(Org: 9)
(19,812)
0 19,812
14 📉
(Org: 11)
(19,811)
0.06 19,811
15 📈
(Org: 25)
(19,423)
0.35 19,423
16 📉
(Org: 15)
(18,795)
0.18 18,795
17 📉
(Org: 12)
(18,312)
0.04 18,312
18 📉
(Org: 14)
(17,074)
0.02 17,074
19 📉
(Org: 13)
(16,995)
0 16,995
20 📉
(Org: 16)
(16,051)
0.07 16,051
21 📉
(Org: 17)
(15,640)
0.07 15,640
22 📉
(Org: 18)
(15,326)
0.06 15,326
23 ➡️
(Org: 23)
(14,844)
0.1 14,844
24 📈
(Org: 29)
(14,824)
0.3 14,824
25 📉
(Org: 20)
(14,537)
0.03 14,537
26 📈
(Org: 31)
(14,328)
0.3 14,328
27 📉
(Org: 21)
(14,156)
0 14,156
28 📉
(Org: 26)
(14,100)
0.16 14,100
29 📉
(Org: 24)
(13,700)
0.03 13,700
30 📉
(Org: 22)
(13,451)
- 13,451
31 📈
(Org: 42)
(11,386)
0.33 11,386
32 📈
(Org: 35)
(10,691)
0.15 10,691
33 📈
(Org: 34)
(10,680)
0.14 10,680
34 📉
(Org: 30)
(10,369)
0.03 10,369
35 📉
(Org: 32)
(9,844)
0.03 9,844
36 📈
(Org: 39)
(9,659)
0.17 9,659
37 📈
(Org: 69)
(9,617)
0.6 9,617
38 📉
(Org: 33)
(9,325)
0.01 9,325
39 📈
(Org: 57)
(9,282)
0.46 9,282
40 📉
(Org: 38)
(9,194)
0.09 9,194
41 📉
(Org: 36)
(8,640)
- 8,640
42 📉
(Org: 37)
(8,606)
0.01 8,606
43 📉
(Org: 40)
(8,141)
0.03 8,141
44 📈
(Org: 45)
(7,811)
0.1 7,811
45 📈
(Org: 87)
(7,760)
0.59 7,760
46 📉
(Org: 43)
(7,737)
0.03 7,737
47 📈
(Org: 65)
(7,516)
0.39 7,516
48 📉
(Org: 44)
(7,484)
0.01 7,484
49 📈
(Org: 79)
(7,464)
0.54 7,464
50 📈
(Org: 158)
(7,425)
0.76 7,425
51 📉
(Org: 46)
(7,340)
0.05 7,340
52 📉
(Org: 49)
(6,428)
0.04 6,428
53 📉
(Org: 52)
(6,206)
0.08 6,206
54 📈
(Org: 55)
(6,143)
0.12 6,143
55 📈
(Org: 60)
(6,073)
0.18 6,073
56 📈
(Org: 80)
(6,021)
0.43 6,021
57 📉
(Org: 51)
(5,931)
0 5,931
58 📉
(Org: 54)
(5,693)
0 5,693
59 📉
(Org: 53)
(5,682)
0 5,682
60 📈
(Org: 62)
(5,659)
0.14 5,659
61 📉
(Org: 56)
(5,387)
0.06 5,387
62 📈
(Org: 108)
(5,348)
0.52 5,348
63 📉
(Org: 59)
(5,275)
0.05 5,275
64 📈
(Org: 73)
(5,238)
0.28 5,238
65 📈
(Org: 93)
(5,129)
0.4 5,129
66 📉
(Org: 58)
(5,118)
0.02 5,118
67 📉
(Org: 64)
(4,863)
0.04 4,863
68 📈
(Org: 85)
(4,635)
0.3 4,635
69 📈
(Org: 117)
(4,489)
0.46 4,489
70 📉
(Org: 68)
(4,423)
0.07 4,423
71 📉
(Org: 66)
(4,274)
0.01 4,274
72 📈
(Org: 102)
(4,247)
0.36 4,247
73 📉
(Org: 70)
(4,211)
0.08 4,211
74 📉
(Org: 72)
(4,092)
0.07 4,092
75 📈
(Org: 139)
(4,066)
0.51 4,066
76 📈
(Org: 78)
(4,011)
0.14 4,011
77 📉
(Org: 71)
(3,915)
0.01 3,915
78 📈
(Org: 83)
(3,913)
0.15 3,913
79 📈
(Org: 121)
(3,852)
0.41 3,852
80 📈
(Org: 95)
(3,831)
0.22 3,831
81 📈
(Org: 85)
(3,798)
0.15 3,798
82 📉
(Org: 75)
(3,688)
0.01 3,688
83 📉
(Org: 82)
(3,669)
0.08 3,669
84 📉
(Org: 77)
(3,656)
0.02 3,656
85 📉
(Org: 76)
(3,635)
0 3,635
86 📈
(Org: 121)
(3,622)
0.37 3,622
87 📈
(Org: 115)
(3,587)
0.32 3,587
88 📈
(Org: 156)
(3,579)
0.5 3,579
89 📈
(Org: 118)
(3,557)
0.33 3,557
90 📉
(Org: 81)
(3,545)
0.03 3,545
91 📉
(Org: 90)
(3,320)
0.07 3,320
92 📈
(Org: 98)
(3,266)
0.1 3,266
93 📈
(Org: 154)
(3,246)
0.44 3,246
94 📉
(Org: 92)
(3,205)
0.04 3,205
95 📈
(Org: 126)
(3,193)
0.3 3,193
96 📉
(Org: 91)
(3,179)
0.03 3,179
97 📈
(Org: 99)
(3,159)
0.1 3,159
98 📉
(Org: 88)
(3,121)
0 3,121
98 📉
(Org: 89)
(3,121)
0.01 3,121
100 📈
(Org: 108)
(3,102)
0.17 3,102