Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2013 - 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)
(30,599)
0.31 30,599
2 ➡️
(Org: 2)
(21,456)
0.02 21,456
3 ➡️
(Org: 3)
(18,683)
0.01 18,683
4 ➡️
(Org: 4)
(18,320)
0.03 18,320
5 ➡️
(Org: 5)
(15,650)
0.02 15,650
6 📈
(Org: 24)
(14,857)
0.51 14,857
7 ➡️
(Org: 7)
(14,413)
0.09 14,413
8 📈
(Org: 18)
(13,919)
0.43 13,919
9 📉
(Org: 6)
(13,835)
0.05 13,835
10 📈
(Org: 14)
(13,269)
0.34 13,269
11 📉
(Org: 8)
(12,913)
0.04 12,913
12 📉
(Org: 9)
(11,649)
0.09 11,649
13 📈
(Org: 27)
(10,758)
0.35 10,758
14 📈
(Org: 45)
(10,035)
0.51 10,035
15 📉
(Org: 10)
(9,995)
0.05 9,995
16 📈
(Org: 44)
(9,943)
0.5 9,943
17 📈
(Org: 40)
(9,738)
0.47 9,738
18 📈
(Org: 30)
(9,690)
0.33 9,690
19 📈
(Org: 43)
(9,526)
0.47 9,526
20 📈
(Org: 21)
(9,484)
0.21 9,484
21 📉
(Org: 11)
(9,311)
- 9,311
22 📈
(Org: 28)
(9,261)
0.25 9,261
23 📈
(Org: 68)
(9,211)
0.57 9,211
24 📉
(Org: 12)
(9,191)
0 9,191
25 📈
(Org: 26)
(8,965)
0.21 8,965
26 📉
(Org: 19)
(8,780)
0.12 8,780
27 📈
(Org: 61)
(8,624)
0.53 8,624
28 📉
(Org: 15)
(8,616)
0.02 8,616
29 📈
(Org: 62)
(8,572)
0.53 8,572
30 📉
(Org: 20)
(8,469)
0.09 8,469
31 📈
(Org: 37)
(8,302)
0.37 8,302
32 📉
(Org: 16)
(8,284)
- 8,284
33 📉
(Org: 17)
(8,163)
0.01 8,163
34 📉
(Org: 23)
(8,124)
0.1 8,124
35 📉
(Org: 34)
(7,772)
0.3 7,772
36 📈
(Org: 51)
(7,674)
0.4 7,674
37 📉
(Org: 32)
(7,666)
0.27 7,666
38 📈
(Org: 134)
(7,474)
0.68 7,474
39 📉
(Org: 22)
(7,432)
0.01 7,432
40 📉
(Org: 25)
(7,328)
0.02 7,328
41 📉
(Org: 39)
(7,239)
0.29 7,239
42 📈
(Org: 77)
(7,172)
0.48 7,172
43 📈
(Org: 48)
(6,850)
0.31 6,850
44 📉
(Org: 38)
(6,757)
0.23 6,757
45 📈
(Org: 72)
(6,710)
0.43 6,710
46 📉
(Org: 29)
(6,516)
- 6,516
47 📈
(Org: 280)
(6,508)
0.83 6,508
48 📈
(Org: 144)
(6,426)
0.67 6,426
49 📉
(Org: 42)
(6,372)
0.21 6,372
50 📉
(Org: 36)
(6,153)
0.15 6,153
51 📉
(Org: 33)
(5,990)
0.06 5,990
52 📈
(Org: 111)
(5,620)
0.5 5,620
53 📉
(Org: 41)
(5,609)
0.09 5,609
54 📈
(Org: 71)
(5,488)
0.29 5,488
55 📉
(Org: 35)
(5,424)
0.01 5,424
56 📈
(Org: 114)
(5,369)
0.49 5,369
57 📈
(Org: 99)
(5,280)
0.4 5,280
58 📈
(Org: 83)
(5,241)
0.33 5,241
59 📉
(Org: 50)
(5,188)
0.1 5,188
60 📈
(Org: 105)
(5,123)
0.41 5,123
61 📉
(Org: 57)
(4,973)
0.15 4,973
62 📉
(Org: 46)
(4,874)
0.02 4,874
63 📉
(Org: 49)
(4,846)
0.04 4,846
64 📈
(Org: 65)
(4,796)
0.17 4,796
65 📉
(Org: 47)
(4,789)
0 4,789
66 📈
(Org: 73)
(4,765)
0.2 4,765
67 📈
(Org: 124)
(4,742)
0.45 4,742
68 📉
(Org: 55)
(4,707)
0.09 4,707
69 📉
(Org: 52)
(4,654)
0.04 4,654
70 📈
(Org: 81)
(4,458)
0.2 4,458
71 📈
(Org: 84)
(4,430)
0.22 4,430
72 📉
(Org: 59)
(4,366)
0.05 4,366
73 📉
(Org: 56)
(4,299)
0 4,299
74 📉
(Org: 66)
(4,290)
0.08 4,290
75 📉
(Org: 58)
(4,283)
0.02 4,283
76 📈
(Org: 80)
(4,276)
0.16 4,276
77 📉
(Org: 74)
(4,255)
0.12 4,255
78 📉
(Org: 67)
(4,230)
0.07 4,230
79 📉
(Org: 60)
(4,213)
0.03 4,213
80 📈
(Org: 173)
(4,164)
0.56 4,164
81 📈
(Org: 120)
(4,113)
0.36 4,113
82 📉
(Org: 76)
(4,097)
0.08 4,097
83 📉
(Org: 78)
(4,023)
0.09 4,023
84 📉
(Org: 63)
(4,004)
0.01 4,004
85 📉
(Org: 64)
(3,977)
0 3,977
86 📉
(Org: 69)
(3,962)
0.01 3,962
87 📉
(Org: 70)
(3,939)
0.01 3,939
88 📉
(Org: 75)
(3,889)
0.03 3,889
89 📈
(Org: 98)
(3,876)
0.18 3,876
90 📈
(Org: 91)
(3,810)
0.12 3,810
91 📈
(Org: 125)
(3,746)
0.3 3,746
92 📉
(Org: 82)
(3,718)
0.06 3,718
93 📈
(Org: 181)
(3,700)
0.52 3,700
94 📈
(Org: 237)
(3,693)
0.64 3,693
95 📈
(Org: 96)
(3,676)
0.11 3,676
96 📉
(Org: 94)
(3,658)
0.1 3,658
97 📈
(Org: 103)
(3,641)
0.16 3,641
98 📉
(Org: 87)
(3,631)
0.05 3,631
99 📉
(Org: 86)
(3,601)
0.04 3,601
100 📈
(Org: 150)
(3,570)
0.41 3,570