Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1999 - 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)
(28,262)
0.06 28,262
2 📈
(Org: 33)
(25,455)
0.68 25,455
3 📈
(Org: 4)
(24,850)
0.23 24,850
4 📉
(Org: 2)
(23,557)
0.08 23,557
5 📉
(Org: 3)
(19,822)
0.03 19,822
6 ➡️
(Org: 6)
(19,678)
0.08 19,678
7 📈
(Org: 31)
(19,408)
0.58 19,408
8 📉
(Org: 5)
(19,061)
0 19,061
9 📉
(Org: 7)
(19,022)
0.05 19,022
10 📈
(Org: 14)
(18,531)
0.33 18,531
11 📉
(Org: 8)
(17,996)
0.06 17,996
12 📉
(Org: 9)
(16,772)
0.03 16,772
13 📉
(Org: 10)
(16,154)
0.05 16,154
14 📈
(Org: 36)
(15,938)
0.5 15,938
15 📉
(Org: 11)
(15,912)
0.12 15,912
16 📉
(Org: 12)
(14,309)
0.03 14,309
17 📉
(Org: 13)
(14,302)
0.07 14,302
18 📈
(Org: 19)
(13,695)
0.15 13,695
19 📉
(Org: 15)
(12,757)
0.04 12,757
20 📈
(Org: 23)
(12,603)
0.23 12,603
21 📉
(Org: 18)
(12,274)
0.05 12,274
22 📉
(Org: 16)
(11,985)
0.01 11,985
23 📈
(Org: 28)
(11,849)
0.23 11,849
24 📉
(Org: 17)
(11,835)
0.01 11,835
25 📈
(Org: 39)
(11,712)
0.4 11,712
26 ➡️
(Org: 26)
(11,504)
0.19 11,504
27 📉
(Org: 20)
(11,351)
0.01 11,351
28 📉
(Org: 21)
(11,253)
0.06 11,253
29 📉
(Org: 25)
(10,512)
0.09 10,512
30 📈
(Org: 69)
(10,358)
0.56 10,358
31 📈
(Org: 38)
(10,148)
0.27 10,148
32 📈
(Org: 40)
(10,063)
0.3 10,063
33 📉
(Org: 24)
(9,847)
0.02 9,847
34 📉
(Org: 22)
(9,749)
- 9,749
35 📈
(Org: 52)
(9,723)
0.44 9,723
36 📉
(Org: 34)
(9,319)
0.13 9,319
37 📉
(Org: 27)
(9,227)
0 9,227
38 📉
(Org: 29)
(9,167)
0.01 9,167
39 📈
(Org: 42)
(8,939)
0.24 8,939
40 📉
(Org: 30)
(8,862)
0.01 8,862
41 📉
(Org: 37)
(8,820)
0.13 8,820
42 📉
(Org: 35)
(8,727)
0.09 8,727
43 📉
(Org: 32)
(8,551)
0.05 8,551
44 📈
(Org: 49)
(8,038)
0.29 8,038
45 📉
(Org: 44)
(7,827)
0.16 7,827
46 📈
(Org: 70)
(7,221)
0.37 7,221
47 📉
(Org: 43)
(7,176)
0.06 7,176
48 📈
(Org: 172)
(7,152)
0.74 7,152
49 📈
(Org: 65)
(7,117)
0.32 7,117
50 📈
(Org: 53)
(7,027)
0.23 7,027
51 📉
(Org: 41)
(6,860)
0 6,860
52 📈
(Org: 75)
(6,817)
0.37 6,817
53 📉
(Org: 46)
(6,635)
0.08 6,635
54 📉
(Org: 45)
(6,454)
0.01 6,454
55 📈
(Org: 109)
(6,427)
0.53 6,427
56 📉
(Org: 47)
(6,350)
0.04 6,350
57 📈
(Org: 114)
(6,296)
0.55 6,296
58 📈
(Org: 106)
(6,150)
0.49 6,150
59 📉
(Org: 48)
(5,975)
0.04 5,975
60 📉
(Org: 51)
(5,941)
0.08 5,941
61 📈
(Org: 79)
(5,914)
0.34 5,914
62 📈
(Org: 107)
(5,904)
0.47 5,904
63 📈
(Org: 72)
(5,888)
0.25 5,888
64 📈
(Org: 73)
(5,719)
0.23 5,719
65 📉
(Org: 56)
(5,664)
0.06 5,664
66 📉
(Org: 61)
(5,651)
0.11 5,651
67 📉
(Org: 57)
(5,649)
0.06 5,649
68 📈
(Org: 87)
(5,618)
0.34 5,618
69 📈
(Org: 97)
(5,615)
0.39 5,615
70 📉
(Org: 58)
(5,596)
0.07 5,596
71 📉
(Org: 62)
(5,567)
0.1 5,567
72 📉
(Org: 60)
(5,355)
0.06 5,355
73 📉
(Org: 66)
(5,319)
0.1 5,319
74 📉
(Org: 63)
(5,306)
0.06 5,306
75 📉
(Org: 64)
(5,129)
0.06 5,129
76 📉
(Org: 59)
(5,070)
- 5,070
77 📈
(Org: 78)
(5,021)
0.2 5,021
78 📈
(Org: 104)
(4,969)
0.35 4,969
79 📉
(Org: 67)
(4,846)
0.03 4,846
80 📈
(Org: 113)
(4,819)
0.41 4,819
81 📈
(Org: 95)
(4,792)
0.29 4,792
82 📈
(Org: 130)
(4,768)
0.47 4,768
83 📈
(Org: 100)
(4,712)
0.29 4,712
83 📈
(Org: 128)
(4,712)
0.46 4,712
85 📈
(Org: 99)
(4,530)
0.25 4,530
86 📉
(Org: 74)
(4,525)
0.04 4,525
87 📉
(Org: 71)
(4,515)
0.01 4,515
88 📈
(Org: 119)
(4,445)
0.38 4,445
89 📈
(Org: 96)
(4,420)
0.23 4,420
90 📉
(Org: 76)
(4,354)
0.03 4,354
91 📉
(Org: 86)
(4,333)
0.14 4,333
92 📉
(Org: 80)
(4,322)
0.1 4,322
93 📈
(Org: 125)
(4,239)
0.37 4,239
94 📉
(Org: 85)
(4,174)
0.11 4,174
95 📈
(Org: 103)
(4,151)
0.21 4,151
96 📉
(Org: 77)
(4,147)
0 4,147
97 📈
(Org: 175)
(4,109)
0.56 4,109
98 📉
(Org: 84)
(4,020)
0.06 4,020
99 📉
(Org: 81)
(3,991)
0.03 3,991
100 📉
(Org: 92)
(3,961)
0.1 3,961