Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2000 - 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)
(27,721)
0.06 27,721
2 📈
(Org: 30)
(27,070)
0.68 27,070
3 📉
(Org: 2)
(24,999)
0.08 24,999
4 📈
(Org: 28)
(24,011)
0.62 24,011
5 ➡️
(Org: 5)
(23,113)
0.23 23,113
6 📉
(Org: 3)
(21,075)
0.05 21,075
7 📉
(Org: 4)
(19,552)
0.08 19,552
8 📈
(Org: 15)
(18,761)
0.31 18,761
9 📉
(Org: 6)
(18,190)
0.03 18,190
10 📉
(Org: 7)
(17,285)
0 17,285
11 📈
(Org: 33)
(16,665)
0.51 16,665
12 📉
(Org: 8)
(16,128)
0.03 16,128
13 📉
(Org: 10)
(16,021)
0.06 16,021
14 📉
(Org: 9)
(15,959)
0.05 15,959
15 📉
(Org: 12)
(15,529)
0.13 15,529
16 📉
(Org: 11)
(14,560)
0.03 14,560
17 📉
(Org: 13)
(14,239)
0.07 14,239
18 📉
(Org: 14)
(13,736)
0.05 13,736
19 📈
(Org: 23)
(13,326)
0.23 13,326
20 📉
(Org: 16)
(12,973)
0.01 12,973
21 📉
(Org: 17)
(12,661)
0.01 12,661
22 📈
(Org: 24)
(12,476)
0.21 12,476
23 📉
(Org: 21)
(12,454)
0.14 12,454
24 📉
(Org: 18)
(11,946)
0.04 11,946
25 📉
(Org: 19)
(11,340)
0 11,340
26 📈
(Org: 27)
(11,328)
0.2 11,328
27 📈
(Org: 43)
(11,167)
0.43 11,167
28 📉
(Org: 20)
(11,048)
0.01 11,048
29 📈
(Org: 41)
(11,014)
0.38 11,014
30 📉
(Org: 22)
(10,673)
0.01 10,673
31 📈
(Org: 72)
(10,273)
0.56 10,273
32 📉
(Org: 26)
(9,990)
0.06 9,990
33 📉
(Org: 25)
(9,713)
0.02 9,713
34 📈
(Org: 39)
(9,665)
0.27 9,665
35 📉
(Org: 31)
(9,497)
0.1 9,497
36 📉
(Org: 34)
(9,446)
0.14 9,446
37 ➡️
(Org: 37)
(9,390)
0.24 9,390
38 📈
(Org: 56)
(9,103)
0.41 9,103
39 📈
(Org: 44)
(9,029)
0.3 9,029
40 📉
(Org: 29)
(8,880)
0.01 8,880
41 📈
(Org: 42)
(8,658)
0.24 8,658
42 📉
(Org: 32)
(8,558)
- 8,558
43 📉
(Org: 40)
(8,080)
0.13 8,080
44 📉
(Org: 36)
(7,871)
0.04 7,871
45 📉
(Org: 38)
(7,690)
0.08 7,690
46 📈
(Org: 53)
(7,675)
0.28 7,675
47 📈
(Org: 64)
(7,232)
0.3 7,232
48 📈
(Org: 169)
(7,185)
0.73 7,185
49 📈
(Org: 68)
(7,061)
0.34 7,061
50 📈
(Org: 104)
(6,946)
0.54 6,946
51 📈
(Org: 73)
(6,895)
0.37 6,895
52 📈
(Org: 102)
(6,587)
0.51 6,587
53 📉
(Org: 45)
(6,556)
0.05 6,556
54 📉
(Org: 48)
(6,521)
0.07 6,521
55 📉
(Org: 49)
(6,389)
0.08 6,389
55 📈
(Org: 59)
(6,389)
0.18 6,389
57 📉
(Org: 46)
(6,301)
0.01 6,301
58 📈
(Org: 98)
(6,253)
0.46 6,253
59 📉
(Org: 47)
(6,199)
0 6,199
60 📉
(Org: 50)
(6,090)
0.05 6,090
61 📈
(Org: 94)
(6,046)
0.43 6,046
62 📈
(Org: 109)
(6,038)
0.48 6,038
63 📉
(Org: 51)
(5,921)
0.05 5,921
64 📉
(Org: 52)
(5,902)
0.06 5,902
65 📈
(Org: 82)
(5,760)
0.34 5,760
66 📉
(Org: 60)
(5,706)
0.09 5,706
67 📉
(Org: 58)
(5,653)
0.07 5,653
68 📈
(Org: 142)
(5,647)
0.58 5,647
69 📉
(Org: 60)
(5,576)
0.07 5,576
70 📉
(Org: 63)
(5,529)
0.09 5,529
71 📉
(Org: 67)
(5,493)
0.1 5,493
72 📉
(Org: 55)
(5,479)
- 5,479
73 📉
(Org: 62)
(5,465)
0.06 5,465
74 📈
(Org: 137)
(5,272)
0.54 5,272
75 📈
(Org: 78)
(5,271)
0.24 5,271
76 📉
(Org: 66)
(5,139)
0.03 5,139
77 📈
(Org: 100)
(5,086)
0.35 5,086
78 📉
(Org: 65)
(5,061)
0.01 5,061
79 📈
(Org: 88)
(5,040)
0.27 5,040
79 📈
(Org: 90)
(5,040)
0.28 5,040
81 📉
(Org: 70)
(5,023)
0.09 5,023
82 📈
(Org: 113)
(4,958)
0.39 4,958
83 📉
(Org: 71)
(4,845)
0.06 4,845
84 📉
(Org: 69)
(4,728)
0.03 4,728
85 📉
(Org: 74)
(4,616)
0.07 4,616
86 📈
(Org: 97)
(4,407)
0.23 4,407
87 📈
(Org: 107)
(4,376)
0.28 4,376
88 📉
(Org: 86)
(4,285)
0.13 4,285
89 📈
(Org: 163)
(4,282)
0.52 4,282
90 📈
(Org: 111)
(4,263)
0.28 4,263
91 📈
(Org: 132)
(4,247)
0.4 4,247
92 📉
(Org: 84)
(4,222)
0.11 4,222
93 📈
(Org: 103)
(4,209)
0.24 4,209
94 📈
(Org: 127)
(4,180)
0.36 4,180
95 📈
(Org: 131)
(4,161)
0.39 4,161
96 📉
(Org: 77)
(4,046)
0 4,046
97 📉
(Org: 80)
(4,015)
0.05 4,015
98 📈
(Org: 135)
(4,012)
0.38 4,012
99 📈
(Org: 124)
(4,004)
0.32 4,004
100 📈
(Org: 122)
(3,970)
0.31 3,970