Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1993 - 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: 2)
(37,486)
0.07 37,486
2 📉
(Org: 1)
(35,750)
0.02 35,750
3 ➡️
(Org: 3)
(32,243)
0.25 32,243
4 📈
(Org: 46)
(26,765)
0.74 26,765
5 ➡️
(Org: 5)
(24,807)
0.05 24,807
6 📉
(Org: 4)
(23,711)
0 23,711
7 📉
(Org: 6)
(23,697)
0.08 23,697
8 📉
(Org: 7)
(22,685)
0.06 22,685
9 📈
(Org: 29)
(21,611)
0.51 21,611
10 📉
(Org: 8)
(20,830)
0 20,830
11 📈
(Org: 14)
(19,333)
0.17 19,333
12 📉
(Org: 10)
(19,203)
0.1 19,203
13 📉
(Org: 9)
(18,433)
0.05 18,433
14 📉
(Org: 13)
(18,229)
0.11 18,229
15 📉
(Org: 11)
(17,190)
0.05 17,190
16 📉
(Org: 12)
(16,612)
0.03 16,612
17 📉
(Org: 15)
(16,277)
0.03 16,277
18 📉
(Org: 16)
(16,144)
0.04 16,144
19 📈
(Org: 32)
(15,495)
0.43 15,495
20 📈
(Org: 25)
(15,393)
0.27 15,393
21 📈
(Org: 22)
(15,257)
0.19 15,257
22 📈
(Org: 42)
(15,174)
0.5 15,174
23 📉
(Org: 20)
(14,740)
0.15 14,740
24 ➡️
(Org: 24)
(14,183)
0.2 14,183
25 📉
(Org: 23)
(14,173)
0.15 14,173
26 📉
(Org: 17)
(14,104)
0 14,104
27 📈
(Org: 61)
(13,813)
0.6 13,813
28 📉
(Org: 18)
(13,761)
0.06 13,761
29 📉
(Org: 21)
(13,514)
0.07 13,514
30 📈
(Org: 35)
(13,388)
0.38 13,388
31 📉
(Org: 19)
(13,004)
0.01 13,004
32 📉
(Org: 26)
(12,812)
0.14 12,812
33 📈
(Org: 41)
(11,329)
0.32 11,329
34 📈
(Org: 49)
(11,166)
0.43 11,166
35 📉
(Org: 28)
(11,130)
0.04 11,130
36 📈
(Org: 45)
(11,115)
0.37 11,115
37 📉
(Org: 27)
(11,065)
0.02 11,065
38 📉
(Org: 31)
(11,041)
0.08 11,041
39 📉
(Org: 30)
(10,699)
0.04 10,699
40 📉
(Org: 33)
(9,651)
0.11 9,651
41 📈
(Org: 51)
(9,249)
0.32 9,249
42 📈
(Org: 57)
(9,167)
0.36 9,167
43 📈
(Org: 65)
(9,081)
0.4 9,081
44 📉
(Org: 36)
(9,059)
0.1 9,059
45 📉
(Org: 34)
(8,763)
0.02 8,763
46 📉
(Org: 39)
(8,723)
0.09 8,723
47 📉
(Org: 36)
(8,194)
0.01 8,194
48 📉
(Org: 38)
(8,103)
- 8,103
49 📈
(Org: 74)
(8,006)
0.44 8,006
50 📈
(Org: 59)
(7,643)
0.26 7,643
51 📉
(Org: 43)
(7,436)
0.02 7,436
52 📉
(Org: 44)
(7,241)
- 7,241
53 📈
(Org: 56)
(7,231)
0.19 7,231
54 📈
(Org: 77)
(7,142)
0.38 7,142
55 📉
(Org: 48)
(7,102)
0.05 7,102
56 📉
(Org: 47)
(6,854)
0.01 6,854
57 📉
(Org: 52)
(6,499)
0.05 6,499
58 📈
(Org: 137)
(6,446)
0.63 6,446
59 📉
(Org: 50)
(6,387)
0.01 6,387
60 📈
(Org: 62)
(6,343)
0.14 6,343
61 📉
(Org: 55)
(6,220)
0.05 6,220
62 📉
(Org: 58)
(6,167)
0.06 6,167
63 📉
(Org: 53)
(6,163)
0.02 6,163
64 📉
(Org: 63)
(6,074)
0.1 6,074
65 📈
(Org: 91)
(5,768)
0.4 5,768
66 📉
(Org: 60)
(5,736)
0.02 5,736
67 📈
(Org: 76)
(5,446)
0.19 5,446
68 📈
(Org: 167)
(5,440)
0.65 5,440
69 📉
(Org: 65)
(5,420)
- 5,420
70 📈
(Org: 79)
(5,418)
0.21 5,418
71 📉
(Org: 70)
(5,395)
0.1 5,395
72 📈
(Org: 129)
(5,341)
0.52 5,341
73 📉
(Org: 67)
(5,332)
0.03 5,332
74 📉
(Org: 69)
(5,221)
0.04 5,221
75 📈
(Org: 113)
(4,974)
0.42 4,974
76 📈
(Org: 124)
(4,720)
0.43 4,720
77 📉
(Org: 72)
(4,712)
0.01 4,712
78 ➡️
(Org: 78)
(4,672)
0.06 4,672
79 📉
(Org: 73)
(4,615)
0.01 4,615
80 📈
(Org: 96)
(4,515)
0.26 4,515
81 📈
(Org: 84)
(4,396)
0.09 4,396
82 📈
(Org: 87)
(4,282)
0.13 4,282
83 📈
(Org: 111)
(4,253)
0.31 4,253
84 📉
(Org: 82)
(4,221)
0.03 4,221
85 📉
(Org: 83)
(4,213)
0.04 4,213
86 ➡️
(Org: 86)
(4,188)
0.07 4,188
87 📉
(Org: 80)
(4,169)
0.01 4,169
88 📈
(Org: 106)
(4,163)
0.27 4,163
89 📈
(Org: 92)
(4,076)
0.16 4,076
90 📉
(Org: 88)
(3,908)
0.06 3,908
91 📈
(Org: 131)
(3,889)
0.35 3,889
92 📈
(Org: 134)
(3,831)
0.37 3,831
93 📉
(Org: 89)
(3,814)
0.06 3,814
94 📈
(Org: 108)
(3,665)
0.17 3,665
95 ➡️
(Org: 95)
(3,660)
0.08 3,660
96 📈
(Org: 101)
(3,440)
0.07 3,440
97 📉
(Org: 93)
(3,427)
0.01 3,427
98 📈
(Org: 121)
(3,426)
0.21 3,426
99 📉
(Org: 94)
(3,420)
0.01 3,420
100 ➡️
(Org: 100)
(3,412)
0.06 3,412