Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2017 - 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: 5)
(23,176)
0.36 23,176
2 📉
(Org: 1)
(20,390)
0.03 20,390
3 📉
(Org: 2)
(18,925)
0.01 18,925
4 📉
(Org: 3)
(16,573)
0.03 16,573
5 📉
(Org: 4)
(15,765)
0.03 15,765
6 ➡️
(Org: 6)
(13,983)
0.03 13,983
7 📈
(Org: 28)
(13,046)
0.53 13,046
8 📉
(Org: 7)
(12,965)
- 12,965
9 📉
(Org: 8)
(12,008)
0.01 12,008
10 📉
(Org: 9)
(11,944)
0.1 11,944
11 📈
(Org: 25)
(11,375)
0.44 11,375
12 📉
(Org: 10)
(10,900)
0.02 10,900
13 📉
(Org: 11)
(10,521)
- 10,521
14 📉
(Org: 12)
(10,502)
0.07 10,502
15 📈
(Org: 31)
(10,298)
0.42 10,298
16 📈
(Org: 22)
(9,553)
0.27 9,553
17 📈
(Org: 23)
(9,517)
0.29 9,517
18 📉
(Org: 13)
(9,393)
0.04 9,393
19 📈
(Org: 26)
(9,320)
0.32 9,320
20 📉
(Org: 18)
(9,007)
0.14 9,007
21 📉
(Org: 17)
(8,885)
0.11 8,885
22 📈
(Org: 63)
(8,781)
0.55 8,781
23 📈
(Org: 33)
(8,592)
0.32 8,592
24 📉
(Org: 20)
(8,299)
0.14 8,299
25 📉
(Org: 16)
(8,257)
0.02 8,257
26 📈
(Org: 29)
(8,254)
0.26 8,254
27 📉
(Org: 14)
(8,237)
0 8,237
28 📉
(Org: 27)
(7,627)
0.19 7,627
29 📈
(Org: 67)
(7,470)
0.48 7,470
30 📉
(Org: 19)
(7,416)
0.01 7,416
31 📈
(Org: 40)
(7,315)
0.29 7,315
32 📉
(Org: 21)
(7,121)
0.01 7,121
33 📈
(Org: 116)
(7,080)
0.62 7,080
34 📈
(Org: 35)
(6,818)
0.19 6,818
35 📈
(Org: 39)
(6,728)
0.23 6,728
36 📉
(Org: 24)
(6,683)
0 6,683
37 📈
(Org: 57)
(6,657)
0.37 6,657
38 📈
(Org: 72)
(6,598)
0.44 6,598
39 📉
(Org: 32)
(6,508)
0.09 6,508
40 📈
(Org: 45)
(6,394)
0.22 6,394
41 📈
(Org: 84)
(6,381)
0.46 6,381
42 📉
(Org: 30)
(6,334)
0.06 6,334
43 📉
(Org: 34)
(6,211)
0.09 6,211
44 📈
(Org: 131)
(6,033)
0.62 6,033
45 📈
(Org: 60)
(5,995)
0.33 5,995
46 📈
(Org: 62)
(5,962)
0.32 5,962
47 📉
(Org: 38)
(5,931)
0.11 5,931
48 📈
(Org: 100)
(5,880)
0.5 5,880
49 📉
(Org: 36)
(5,845)
0.05 5,845
50 📈
(Org: 288)
(5,686)
0.8 5,686
51 📈
(Org: 61)
(5,655)
0.29 5,655
52 📉
(Org: 48)
(5,621)
0.16 5,621
53 📈
(Org: 105)
(5,462)
0.48 5,462
54 📉
(Org: 37)
(5,423)
0.01 5,423
55 📈
(Org: 92)
(5,413)
0.41 5,413
56 📉
(Org: 44)
(5,403)
0.07 5,403
57 📉
(Org: 49)
(5,158)
0.09 5,158
58 📈
(Org: 89)
(5,147)
0.37 5,147
59 ➡️
(Org: 59)
(5,139)
0.21 5,139
60 📉
(Org: 46)
(5,138)
0.06 5,138
61 📈
(Org: 65)
(5,114)
0.24 5,114
62 📉
(Org: 42)
(5,093)
0 5,093
63 📉
(Org: 43)
(5,056)
0 5,056
64 📈
(Org: 114)
(5,044)
0.46 5,044
65 📉
(Org: 58)
(4,964)
0.16 4,964
66 📈
(Org: 82)
(4,955)
0.29 4,955
67 📉
(Org: 52)
(4,946)
0.07 4,946
68 📉
(Org: 47)
(4,797)
0.01 4,797
69 📉
(Org: 50)
(4,756)
0.02 4,756
70 📈
(Org: 97)
(4,743)
0.36 4,743
71 📈
(Org: 88)
(4,690)
0.3 4,690
72 📉
(Org: 51)
(4,646)
0.01 4,646
73 📉
(Org: 56)
(4,615)
0.07 4,615
74 📉
(Org: 53)
(4,602)
0.01 4,602
75 📈
(Org: 109)
(4,547)
0.39 4,547
76 📈
(Org: 111)
(4,357)
0.38 4,357
77 📈
(Org: 155)
(4,350)
0.56 4,350
78 📉
(Org: 54)
(4,332)
- 4,332
79 📉
(Org: 55)
(4,319)
0.01 4,319
80 📉
(Org: 77)
(4,218)
0.15 4,218
81 📈
(Org: 83)
(4,188)
0.18 4,188
82 📈
(Org: 90)
(4,180)
0.23 4,180
83 📈
(Org: 125)
(4,057)
0.4 4,057
84 📉
(Org: 68)
(4,026)
0.04 4,026
85 📉
(Org: 69)
(3,982)
0.03 3,982
86 📉
(Org: 66)
(3,977)
0.02 3,977
87 📉
(Org: 76)
(3,952)
0.09 3,952
88 📉
(Org: 64)
(3,937)
- 3,937
89 📉
(Org: 70)
(3,863)
0.01 3,863
90 📉
(Org: 71)
(3,825)
0.03 3,825
91 📈
(Org: 135)
(3,810)
0.43 3,810
92 📉
(Org: 79)
(3,809)
0.06 3,809
93 📉
(Org: 81)
(3,762)
0.05 3,762
94 📉
(Org: 78)
(3,735)
0.04 3,735
95 📉
(Org: 73)
(3,695)
0.01 3,695
96 📉
(Org: 75)
(3,637)
0.01 3,637
97 📉
(Org: 74)
(3,625)
0 3,625
98 📉
(Org: 80)
(3,580)
0 3,580
99 📈
(Org: 218)
(3,544)
0.6 3,544
100 📉
(Org: 85)
(3,509)
0.05 3,509