Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2003 - 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)
(27,720)
0.07 27,720
2 📈
(Org: 26)
(23,498)
0.63 23,498
3 📉
(Org: 2)
(22,899)
0.01 22,899
4 📈
(Org: 32)
(21,281)
0.65 21,281
5 📉
(Org: 3)
(21,126)
0.04 21,126
6 📉
(Org: 4)
(19,187)
0.08 19,187
7 📈
(Org: 11)
(18,646)
0.26 18,646
8 📉
(Org: 6)
(16,757)
0.05 16,757
9 📉
(Org: 5)
(16,329)
0.01 16,329
10 📉
(Org: 8)
(15,990)
0.09 15,990
11 📈
(Org: 17)
(15,586)
0.32 15,586
12 📉
(Org: 7)
(15,337)
0.03 15,337
13 📉
(Org: 9)
(14,930)
0.05 14,930
14 ➡️
(Org: 14)
(14,596)
0.13 14,596
15 📉
(Org: 12)
(14,541)
0.05 14,541
16 📈
(Org: 35)
(14,334)
0.5 14,334
17 📉
(Org: 10)
(13,887)
0 13,887
18 📈
(Org: 20)
(13,200)
0.27 13,200
19 📉
(Org: 13)
(12,895)
0.01 12,895
20 📈
(Org: 53)
(11,960)
0.54 11,960
21 📉
(Org: 16)
(11,791)
0.07 11,791
22 📈
(Org: 25)
(11,343)
0.21 11,343
23 📉
(Org: 15)
(11,332)
0.02 11,332
24 📉
(Org: 23)
(10,940)
0.16 10,940
25 📉
(Org: 19)
(10,925)
0.06 10,925
26 📉
(Org: 18)
(10,719)
0.02 10,719
27 📈
(Org: 52)
(10,673)
0.48 10,673
28 📉
(Org: 27)
(10,329)
0.22 10,329
29 📈
(Org: 45)
(10,282)
0.43 10,282
30 📉
(Org: 24)
(10,047)
0.1 10,047
31 📉
(Org: 21)
(9,515)
0.01 9,515
32 📉
(Org: 22)
(9,388)
0.01 9,388
33 📉
(Org: 28)
(9,240)
0.13 9,240
34 📈
(Org: 61)
(9,198)
0.46 9,198
35 📈
(Org: 42)
(9,179)
0.34 9,179
36 📈
(Org: 37)
(8,632)
0.19 8,632
37 📈
(Org: 46)
(8,594)
0.32 8,594
38 📈
(Org: 41)
(8,225)
0.25 8,225
39 📉
(Org: 31)
(8,129)
0.07 8,129
40 📉
(Org: 29)
(8,111)
0.02 8,111
41 📉
(Org: 30)
(8,079)
0.03 8,079
42 📈
(Org: 57)
(8,043)
0.37 8,043
43 📈
(Org: 85)
(7,959)
0.52 7,959
44 📉
(Org: 33)
(7,537)
0.01 7,537
45 📉
(Org: 36)
(7,505)
0.06 7,505
46 📈
(Org: 77)
(7,446)
0.46 7,446
47 📈
(Org: 83)
(7,333)
0.47 7,333
48 📈
(Org: 72)
(7,303)
0.42 7,303
49 📈
(Org: 63)
(7,043)
0.31 7,043
50 📈
(Org: 84)
(6,959)
0.45 6,959
51 📉
(Org: 40)
(6,868)
0.09 6,868
52 📉
(Org: 38)
(6,865)
0.05 6,865
53 📈
(Org: 183)
(6,605)
0.73 6,605
54 📈
(Org: 69)
(6,583)
0.33 6,583
55 📉
(Org: 49)
(6,571)
0.15 6,571
56 📉
(Org: 39)
(6,311)
0 6,311
57 📉
(Org: 51)
(6,218)
0.1 6,218
58 📉
(Org: 43)
(6,214)
0.04 6,214
59 📉
(Org: 44)
(5,972)
0.01 5,972
60 📉
(Org: 47)
(5,883)
0.02 5,883
61 📉
(Org: 48)
(5,877)
0.04 5,877
62 📈
(Org: 73)
(5,835)
0.27 5,835
63 📉
(Org: 55)
(5,764)
0.07 5,764
64 📉
(Org: 50)
(5,754)
0.03 5,754
65 📈
(Org: 90)
(5,609)
0.35 5,609
66 📉
(Org: 56)
(5,476)
0.06 5,476
67 📈
(Org: 87)
(5,456)
0.32 5,456
68 📈
(Org: 226)
(5,397)
0.73 5,397
69 📉
(Org: 54)
(5,354)
- 5,354
70 📈
(Org: 81)
(5,277)
0.26 5,277
71 📉
(Org: 62)
(5,196)
0.06 5,196
72 📈
(Org: 98)
(5,189)
0.33 5,189
73 📈
(Org: 109)
(5,165)
0.4 5,165
74 📉
(Org: 64)
(5,158)
0.06 5,158
75 📉
(Org: 59)
(5,082)
0.01 5,082
76 ➡️
(Org: 76)
(5,080)
0.21 5,080
77 📉
(Org: 60)
(4,982)
- 4,982
78 📈
(Org: 100)
(4,963)
0.31 4,963
79 📈
(Org: 91)
(4,936)
0.26 4,936
80 📉
(Org: 66)
(4,930)
0.07 4,930
81 📉
(Org: 70)
(4,704)
0.07 4,704
82 📉
(Org: 67)
(4,691)
0.02 4,691
83 📈
(Org: 95)
(4,643)
0.24 4,643
84 📉
(Org: 79)
(4,619)
0.14 4,619
85 📉
(Org: 68)
(4,615)
0.01 4,615
86 📈
(Org: 121)
(4,441)
0.36 4,441
87 📈
(Org: 159)
(4,393)
0.52 4,393
88 📈
(Org: 93)
(4,339)
0.18 4,339
89 📉
(Org: 71)
(4,277)
0 4,277
90 📉
(Org: 80)
(4,261)
0.08 4,261
91 📉
(Org: 88)
(4,233)
0.13 4,233
92 📉
(Org: 78)
(4,216)
0.05 4,216
93 📉
(Org: 82)
(4,165)
0.07 4,165
94 📉
(Org: 74)
(4,130)
0 4,130
95 📈
(Org: 103)
(4,096)
0.18 4,096
96 📈
(Org: 112)
(4,091)
0.25 4,091
97 📉
(Org: 92)
(4,084)
0.13 4,084
98 📉
(Org: 75)
(4,071)
0 4,071
99 📈
(Org: 140)
(3,967)
0.41 3,967
100 📉
(Org: 99)
(3,913)
0.13 3,913