Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2016 - 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: 4)
(25,452)
0.36 25,452
2 📉
(Org: 1)
(20,062)
0.03 20,062
3 📉
(Org: 2)
(19,565)
0.01 19,565
4 📉
(Org: 3)
(16,795)
0.03 16,795
5 ➡️
(Org: 5)
(15,358)
0.03 15,358
6 ➡️
(Org: 6)
(15,058)
0.04 15,058
7 📈
(Org: 26)
(14,074)
0.54 14,074
8 📉
(Org: 7)
(13,117)
- 13,117
9 📈
(Org: 22)
(12,423)
0.42 12,423
10 📉
(Org: 8)
(12,101)
0.03 12,101
11 📉
(Org: 9)
(11,846)
0.07 11,846
12 ➡️
(Org: 12)
(11,247)
0.1 11,247
13 📈
(Org: 25)
(11,198)
0.41 11,198
14 📉
(Org: 10)
(10,927)
0.01 10,927
15 📉
(Org: 11)
(10,802)
- 10,802
16 📈
(Org: 20)
(10,546)
0.29 10,546
17 📉
(Org: 15)
(10,155)
0.11 10,155
18 📉
(Org: 13)
(10,065)
0.05 10,065
19 📈
(Org: 24)
(9,685)
0.32 9,685
20 📈
(Org: 62)
(9,430)
0.55 9,430
21 📈
(Org: 30)
(9,287)
0.32 9,287
22 📉
(Org: 18)
(9,186)
0.16 9,186
23 📈
(Org: 54)
(8,899)
0.48 8,899
24 📉
(Org: 16)
(8,781)
0 8,781
25 📈
(Org: 32)
(8,529)
0.29 8,529
26 📉
(Org: 23)
(8,128)
0.15 8,128
27 📉
(Org: 17)
(8,099)
0.02 8,099
28 ➡️
(Org: 28)
(8,023)
0.2 8,023
29 📈
(Org: 34)
(7,754)
0.23 7,754
30 📈
(Org: 31)
(7,726)
0.2 7,726
31 📈
(Org: 37)
(7,708)
0.3 7,708
32 📉
(Org: 19)
(7,654)
0 7,654
33 📈
(Org: 36)
(7,639)
0.27 7,639
34 📉
(Org: 21)
(7,445)
0.02 7,445
35 📈
(Org: 53)
(7,311)
0.36 7,311
36 📈
(Org: 72)
(7,286)
0.47 7,286
37 📈
(Org: 124)
(7,251)
0.64 7,251
38 📉
(Org: 29)
(7,018)
0.1 7,018
39 📈
(Org: 68)
(7,011)
0.44 7,011
40 📈
(Org: 85)
(6,946)
0.51 6,946
41 📈
(Org: 50)
(6,696)
0.29 6,696
42 📉
(Org: 33)
(6,621)
0.09 6,621
43 📈
(Org: 57)
(6,531)
0.32 6,531
44 📉
(Org: 27)
(6,407)
0 6,407
45 📈
(Org: 46)
(6,281)
0.22 6,281
46 📈
(Org: 138)
(6,229)
0.64 6,229
47 📈
(Org: 83)
(6,206)
0.45 6,206
48 📈
(Org: 64)
(6,205)
0.34 6,205
49 📉
(Org: 42)
(6,149)
0.17 6,149
50 📉
(Org: 38)
(6,146)
0.12 6,146
51 📈
(Org: 264)
(6,130)
0.8 6,130
52 📈
(Org: 91)
(6,096)
0.46 6,096
53 📉
(Org: 40)
(5,767)
0.1 5,767
54 📉
(Org: 39)
(5,695)
0.06 5,695
55 📈
(Org: 81)
(5,645)
0.38 5,645
56 📈
(Org: 61)
(5,574)
0.24 5,574
57 📉
(Org: 43)
(5,513)
0.08 5,513
58 📉
(Org: 41)
(5,429)
0.05 5,429
59 📈
(Org: 102)
(5,359)
0.43 5,359
60 📉
(Org: 59)
(5,249)
0.17 5,249
61 📉
(Org: 48)
(5,131)
0.06 5,131
62 📉
(Org: 55)
(4,976)
0.07 4,976
63 📉
(Org: 45)
(4,962)
0.01 4,962
64 📉
(Org: 44)
(4,960)
0 4,960
65 📉
(Org: 47)
(4,948)
0.01 4,948
66 📉
(Org: 51)
(4,883)
0.02 4,883
67 📈
(Org: 95)
(4,844)
0.35 4,844
68 📉
(Org: 49)
(4,839)
0.01 4,839
69 📈
(Org: 113)
(4,773)
0.41 4,773
70 📉
(Org: 58)
(4,708)
0.08 4,708
71 📉
(Org: 52)
(4,698)
0 4,698
72 📈
(Org: 93)
(4,512)
0.29 4,512
73 📈
(Org: 123)
(4,461)
0.41 4,461
74 📉
(Org: 56)
(4,460)
0.01 4,460
75 📉
(Org: 60)
(4,396)
0.02 4,396
76 📈
(Org: 116)
(4,357)
0.38 4,357
77 📈
(Org: 82)
(4,353)
0.2 4,353
78 📈
(Org: 86)
(4,334)
0.22 4,334
79 📈
(Org: 97)
(4,197)
0.26 4,197
80 📉
(Org: 67)
(4,178)
0.05 4,178
81 📉
(Org: 63)
(4,119)
- 4,119
82 📉
(Org: 71)
(4,093)
0.06 4,093
83 📉
(Org: 65)
(4,060)
0 4,060
84 📈
(Org: 185)
(4,058)
0.56 4,058
85 📉
(Org: 70)
(4,040)
0.04 4,040
86 📉
(Org: 66)
(4,025)
0 4,025
87 ➡️
(Org: 87)
(4,004)
0.16 4,004
88 📈
(Org: 107)
(3,918)
0.26 3,918
89 📉
(Org: 79)
(3,914)
0.07 3,914
90 📉
(Org: 75)
(3,902)
0.02 3,902
91 📉
(Org: 74)
(3,861)
0.01 3,861
92 📉
(Org: 73)
(3,823)
- 3,823
93 📉
(Org: 80)
(3,810)
0.05 3,810
94 📉
(Org: 78)
(3,769)
0.02 3,769
95 📉
(Org: 77)
(3,764)
0.02 3,764
96 📉
(Org: 76)
(3,732)
0.01 3,732
97 📈
(Org: 108)
(3,648)
0.21 3,648
98 📈
(Org: 103)
(3,625)
0.16 3,625
99 📈
(Org: 184)
(3,565)
0.5 3,565
100 📈
(Org: 104)
(3,526)
0.15 3,526