Top 100 Most Popular Girl Baby Names by Pronunciation in the US 2014 - 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)
(28,388)
0.34 28,388
2 📉
(Org: 1)
(21,434)
0.02 21,434
3 📉
(Org: 2)
(20,040)
0.01 20,040
4 ➡️
(Org: 4)
(17,697)
0.03 17,697
5 ➡️
(Org: 5)
(16,147)
0.03 16,147
6 📈
(Org: 22)
(14,962)
0.5 14,962
7 📉
(Org: 6)
(14,142)
0.04 14,142
8 📉
(Org: 7)
(13,704)
0.08 13,704
9 📈
(Org: 21)
(13,273)
0.42 13,273
10 📈
(Org: 18)
(12,749)
0.33 12,749
11 📉
(Org: 8)
(12,475)
0.03 12,475
12 📉
(Org: 9)
(11,478)
0.1 11,478
13 📈
(Org: 37)
(11,336)
0.51 11,336
14 📈
(Org: 27)
(10,446)
0.35 10,446
15 📉
(Org: 13)
(10,122)
0.05 10,122
16 📉
(Org: 10)
(10,120)
- 10,120
17 📈
(Org: 60)
(9,807)
0.56 9,807
18 📉
(Org: 16)
(9,766)
0.1 9,766
19 📈
(Org: 47)
(9,717)
0.51 9,717
20 📉
(Org: 11)
(9,616)
- 9,616
21 📉
(Org: 14)
(9,583)
0 9,583
22 📈
(Org: 29)
(9,491)
0.32 9,491
23 📈
(Org: 26)
(9,076)
0.25 9,076
24 📈
(Org: 52)
(8,935)
0.49 8,935
25 📉
(Org: 15)
(8,899)
0.01 8,899
26 📉
(Org: 23)
(8,845)
0.2 8,845
27 📉
(Org: 17)
(8,749)
0.02 8,749
28 📉
(Org: 25)
(8,747)
0.21 8,747
29 📈
(Org: 51)
(8,685)
0.47 8,685
30 📈
(Org: 69)
(8,565)
0.51 8,565
31 📉
(Org: 19)
(8,131)
0.02 8,131
32 📈
(Org: 73)
(7,951)
0.5 7,951
33 📉
(Org: 24)
(7,874)
0.11 7,874
34 📈
(Org: 39)
(7,798)
0.3 7,798
35 📉
(Org: 20)
(7,711)
0.01 7,711
36 📉
(Org: 35)
(7,664)
0.27 7,664
37 📈
(Org: 45)
(7,615)
0.36 7,615
38 📈
(Org: 41)
(7,400)
0.29 7,400
39 📈
(Org: 202)
(7,361)
0.77 7,361
40 📉
(Org: 30)
(7,274)
0.17 7,274
41 📈
(Org: 56)
(7,259)
0.39 7,259
42 📉
(Org: 28)
(7,241)
0.09 7,241
43 📈
(Org: 82)
(7,144)
0.48 7,144
44 📈
(Org: 141)
(6,827)
0.65 6,827
45 📈
(Org: 49)
(6,758)
0.3 6,758
46 📈
(Org: 50)
(6,740)
0.3 6,740
47 📈
(Org: 160)
(6,651)
0.69 6,651
48 📉
(Org: 42)
(6,601)
0.23 6,601
49 📈
(Org: 74)
(6,539)
0.39 6,539
50 📉
(Org: 31)
(6,433)
0.08 6,433
51 📉
(Org: 38)
(6,361)
0.14 6,361
52 📉
(Org: 48)
(5,963)
0.2 5,963
53 📉
(Org: 36)
(5,947)
0.06 5,947
54 📉
(Org: 33)
(5,740)
0 5,740
55 📉
(Org: 34)
(5,739)
0.01 5,739
56 📉
(Org: 53)
(5,699)
0.21 5,699
57 📈
(Org: 96)
(5,673)
0.46 5,673
58 📉
(Org: 44)
(5,577)
0.1 5,577
59 📉
(Org: 54)
(5,390)
0.17 5,390
60 📉
(Org: 57)
(5,370)
0.19 5,370
61 📈
(Org: 129)
(5,252)
0.52 5,252
62 📈
(Org: 114)
(5,208)
0.47 5,208
63 📉
(Org: 43)
(5,089)
- 5,089
64 📈
(Org: 85)
(5,031)
0.28 5,031
65 📉
(Org: 46)
(5,026)
0.03 5,026
66 📈
(Org: 104)
(5,020)
0.41 5,020
67 📉
(Org: 55)
(4,965)
0.1 4,965
68 📈
(Org: 97)
(4,781)
0.36 4,781
69 📈
(Org: 81)
(4,723)
0.22 4,723
70 📈
(Org: 119)
(4,703)
0.44 4,703
71 📉
(Org: 61)
(4,647)
0.08 4,647
72 📈
(Org: 76)
(4,559)
0.16 4,559
73 📉
(Org: 58)
(4,546)
0.04 4,546
74 📉
(Org: 68)
(4,528)
0.08 4,528
75 📈
(Org: 115)
(4,477)
0.38 4,477
76 📉
(Org: 72)
(4,407)
0.08 4,407
77 📉
(Org: 59)
(4,379)
0.01 4,379
78 📉
(Org: 64)
(4,353)
0.02 4,353
79 📉
(Org: 65)
(4,338)
0.02 4,338
80 📉
(Org: 63)
(4,267)
0 4,267
81 📉
(Org: 67)
(4,243)
0.01 4,243
82 📉
(Org: 66)
(4,228)
0.01 4,228
83 📉
(Org: 70)
(4,206)
0.02 4,206
84 📉
(Org: 75)
(4,165)
0.07 4,165
85 📉
(Org: 71)
(4,094)
0 4,094
86 📉
(Org: 77)
(4,012)
0.05 4,012
87 📉
(Org: 78)
(3,974)
0.06 3,974
88 📈
(Org: 117)
(3,892)
0.3 3,892
89 📉
(Org: 80)
(3,841)
0.03 3,841
90 📉
(Org: 84)
(3,839)
0.05 3,839
91 📉
(Org: 79)
(3,833)
0.02 3,833
92 📉
(Org: 87)
(3,815)
0.07 3,815
93 📈
(Org: 230)
(3,769)
0.62 3,769
94 📉
(Org: 83)
(3,742)
0.01 3,742
95 📉
(Org: 91)
(3,718)
0.09 3,718
95 📈
(Org: 264)
(3,718)
0.67 3,718
97 📉
(Org: 86)
(3,711)
0.03 3,711
98 📈
(Org: 100)
(3,683)
0.18 3,683
99 📉
(Org: 90)
(3,669)
0.07 3,669
99 📈
(Org: 189)
(3,669)
0.52 3,669