Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2015 - 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: 3)
(27,271)
0.36 27,271
2 📉
(Org: 1)
(21,009)
0.02 21,009
3 📉
(Org: 2)
(19,917)
0.01 19,917
4 ➡️
(Org: 4)
(16,885)
0.03 16,885
5 ➡️
(Org: 5)
(16,201)
0.03 16,201
6 ➡️
(Org: 6)
(15,561)
0.04 15,561
7 📈
(Org: 23)
(14,614)
0.52 14,614
8 ➡️
(Org: 8)
(12,800)
0.08 12,800
9 📉
(Org: 7)
(12,784)
0.03 12,784
10 📈
(Org: 21)
(12,306)
0.4 12,306
11 📈
(Org: 17)
(11,514)
0.31 11,514
12 📉
(Org: 9)
(11,415)
- 11,415
13 📉
(Org: 11)
(11,299)
0.11 11,299
14 📈
(Org: 35)
(10,465)
0.45 10,465
15 ➡️
(Org: 15)
(10,328)
0.09 10,328
16 📉
(Org: 10)
(10,310)
- 10,310
17 📉
(Org: 13)
(10,219)
0.04 10,219
18 📈
(Org: 46)
(10,001)
0.5 10,001
19 📉
(Org: 12)
(9,991)
0.01 9,991
20 📈
(Org: 25)
(9,934)
0.33 9,934
21 📈
(Org: 59)
(9,847)
0.54 9,847
22 📉
(Org: 16)
(9,360)
0 9,360
23 📈
(Org: 30)
(9,163)
0.31 9,163
24 📉
(Org: 22)
(8,541)
0.16 8,541
25 📈
(Org: 31)
(8,391)
0.25 8,391
26 ➡️
(Org: 26)
(8,341)
0.21 8,341
27 📈
(Org: 61)
(8,162)
0.46 8,162
28 📉
(Org: 18)
(8,115)
0.02 8,115
29 📉
(Org: 27)
(8,075)
0.19 8,075
30 📈
(Org: 64)
(7,910)
0.46 7,910
31 📈
(Org: 73)
(7,861)
0.51 7,861
32 📈
(Org: 36)
(7,795)
0.28 7,795
33 📉
(Org: 20)
(7,761)
0.02 7,761
34 📉
(Org: 19)
(7,733)
0.01 7,733
35 📈
(Org: 66)
(7,672)
0.46 7,672
36 📈
(Org: 43)
(7,635)
0.31 7,635
37 📈
(Org: 47)
(7,508)
0.35 7,508
38 📉
(Org: 24)
(7,446)
0.1 7,446
39 ➡️
(Org: 39)
(7,418)
0.28 7,418
40 📈
(Org: 41)
(7,382)
0.28 7,382
41 📉
(Org: 29)
(7,120)
0.1 7,120
42 📉
(Org: 28)
(7,029)
0.08 7,029
43 📈
(Org: 232)
(6,968)
0.79 6,968
44 📈
(Org: 84)
(6,674)
0.48 6,674
45 📈
(Org: 68)
(6,594)
0.37 6,594
46 📈
(Org: 57)
(6,565)
0.31 6,565
47 📈
(Org: 124)
(6,524)
0.6 6,524
48 📉
(Org: 42)
(6,518)
0.19 6,518
49 📉
(Org: 45)
(6,432)
0.21 6,432
50 📈
(Org: 72)
(6,362)
0.39 6,362
51 📈
(Org: 141)
(6,319)
0.64 6,319
52 📉
(Org: 38)
(6,302)
0.13 6,302
53 📉
(Org: 32)
(6,158)
0.02 6,158
54 📉
(Org: 34)
(5,958)
0 5,958
55 📉
(Org: 54)
(5,954)
0.22 5,954
56 📉
(Org: 37)
(5,952)
0.06 5,952
57 📈
(Org: 94)
(5,651)
0.43 5,651
58 ➡️
(Org: 58)
(5,492)
0.18 5,492
59 📉
(Org: 49)
(5,368)
0.1 5,368
60 📉
(Org: 40)
(5,352)
0 5,352
61 📉
(Org: 48)
(5,308)
0.08 5,308
62 📉
(Org: 44)
(5,187)
0.01 5,187
63 📈
(Org: 197)
(5,148)
0.68 5,148
64 📈
(Org: 95)
(5,095)
0.37 5,095
65 📉
(Org: 53)
(5,088)
0.07 5,088
66 📈
(Org: 109)
(4,975)
0.43 4,975
67 📉
(Org: 55)
(4,934)
0.08 4,934
68 📉
(Org: 52)
(4,898)
0.03 4,898
69 📉
(Org: 50)
(4,881)
0.01 4,881
70 📉
(Org: 51)
(4,829)
0.01 4,829
71 📈
(Org: 82)
(4,761)
0.27 4,761
72 📈
(Org: 107)
(4,746)
0.4 4,746
73 📉
(Org: 60)
(4,721)
0.06 4,721
74 📈
(Org: 127)
(4,534)
0.43 4,534
75 📉
(Org: 65)
(4,520)
0.08 4,520
76 📈
(Org: 81)
(4,442)
0.21 4,442
77 📉
(Org: 67)
(4,395)
0.06 4,395
78 📉
(Org: 62)
(4,363)
0.01 4,363
79 📉
(Org: 63)
(4,315)
0 4,315
80 📉
(Org: 71)
(4,195)
0.05 4,195
81 📉
(Org: 69)
(4,146)
0.01 4,146
82 📈
(Org: 88)
(4,131)
0.18 4,131
83 📈
(Org: 102)
(4,100)
0.27 4,100
84 📉
(Org: 70)
(4,033)
0 4,033
85 📈
(Org: 133)
(4,011)
0.39 4,011
86 📈
(Org: 207)
(4,008)
0.61 4,008
87 📉
(Org: 77)
(3,949)
0.05 3,949
88 📈
(Org: 92)
(3,907)
0.16 3,907
89 📈
(Org: 93)
(3,900)
0.17 3,900
90 📉
(Org: 74)
(3,897)
0.02 3,897
91 📉
(Org: 75)
(3,891)
0.03 3,891
92 📉
(Org: 76)
(3,829)
0.02 3,829
93 📉
(Org: 83)
(3,714)
0.07 3,714
94 📉
(Org: 80)
(3,706)
0.05 3,706
95 📈
(Org: 113)
(3,694)
0.25 3,694
96 📉
(Org: 86)
(3,690)
0.07 3,690
97 📈
(Org: 176)
(3,676)
0.5 3,676
98 📉
(Org: 78)
(3,663)
0 3,663
99 📈
(Org: 103)
(3,644)
0.18 3,644
100 📉
(Org: 85)
(3,493)
0.02 3,493