Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1959 - 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)
(55,154)
0.01 55,154
2 ➡️
(Org: 2)
(47,881)
0.13 47,881
3 ➡️
(Org: 3)
(42,487)
0.05 42,487
4 ➡️
(Org: 4)
(37,174)
0.01 37,174
5 ➡️
(Org: 5)
(36,980)
0.01 36,980
6 ➡️
(Org: 6)
(35,236)
0 35,236
7 📈
(Org: 15)
(34,226)
0.36 34,226
8 📉
(Org: 7)
(31,826)
0.01 31,826
9 ➡️
(Org: 9)
(31,804)
0.07 31,804
10 📉
(Org: 8)
(30,337)
0.01 30,337
11 📈
(Org: 24)
(29,493)
0.41 29,493
12 📉
(Org: 10)
(26,259)
0.02 26,259
13 📈
(Org: 27)
(25,492)
0.41 25,492
14 📉
(Org: 11)
(25,369)
0 25,369
15 📉
(Org: 12)
(25,151)
0.02 25,151
16 📈
(Org: 18)
(24,787)
0.15 24,787
17 📈
(Org: 40)
(24,471)
0.59 24,471
18 📉
(Org: 13)
(23,708)
0.01 23,708
19 📉
(Org: 14)
(23,352)
0.01 23,352
20 📉
(Org: 17)
(21,611)
0.01 21,611
21 📉
(Org: 16)
(21,423)
- 21,423
22 📉
(Org: 20)
(21,214)
0.08 21,214
23 📉
(Org: 19)
(19,972)
- 19,972
24 📉
(Org: 22)
(19,695)
0.08 19,695
25 📉
(Org: 23)
(18,922)
0.07 18,922
26 📉
(Org: 21)
(18,815)
0.02 18,815
27 📉
(Org: 25)
(18,048)
0.06 18,048
28 📈
(Org: 46)
(17,276)
0.49 17,276
29 📉
(Org: 26)
(16,542)
0.02 16,542
30 📈
(Org: 31)
(16,181)
0.15 16,181
31 📉
(Org: 28)
(15,644)
0.04 15,644
32 📉
(Org: 30)
(15,449)
0.06 15,449
33 📈
(Org: 76)
(15,380)
0.59 15,380
34 📈
(Org: 73)
(14,926)
0.57 14,926
35 📉
(Org: 29)
(14,719)
0 14,719
36 📉
(Org: 32)
(14,714)
0.13 14,714
37 📈
(Org: 47)
(14,393)
0.39 14,393
38 📉
(Org: 33)
(14,362)
0.11 14,362
39 📈
(Org: 43)
(11,934)
0.21 11,934
40 📉
(Org: 36)
(11,721)
0.01 11,721
41 📉
(Org: 35)
(11,596)
- 11,596
42 📉
(Org: 38)
(10,827)
0.03 10,827
43 📉
(Org: 37)
(10,489)
- 10,489
44 📉
(Org: 41)
(10,406)
0.05 10,406
45 ➡️
(Org: 45)
(10,026)
0.12 10,026
46 📉
(Org: 42)
(9,876)
0.02 9,876
47 📈
(Org: 63)
(9,572)
0.26 9,572
48 📈
(Org: 75)
(9,062)
0.3 9,062
49 📉
(Org: 44)
(8,927)
0 8,927
50 📉
(Org: 48)
(8,786)
0.01 8,786
51 📈
(Org: 74)
(8,706)
0.27 8,706
52 📉
(Org: 49)
(8,653)
0 8,653
53 📉
(Org: 50)
(8,539)
0 8,539
54 📉
(Org: 53)
(8,173)
0.03 8,173
55 📉
(Org: 51)
(8,071)
0 8,071
56 📈
(Org: 58)
(8,037)
0.09 8,037
56 📈
(Org: 67)
(8,037)
0.15 8,037
58 📉
(Org: 54)
(8,019)
0.01 8,019
59 📉
(Org: 52)
(7,985)
- 7,985
60 📉
(Org: 59)
(7,886)
0.07 7,886
61 📉
(Org: 55)
(7,851)
0.01 7,851
62 📉
(Org: 57)
(7,596)
0.02 7,596
63 📉
(Org: 60)
(7,337)
0 7,337
64 📉
(Org: 61)
(7,290)
0 7,290
65 📉
(Org: 62)
(7,274)
0 7,274
66 ➡️
(Org: 66)
(7,218)
0.05 7,218
67 📉
(Org: 65)
(6,974)
0.01 6,974
68 📉
(Org: 64)
(6,963)
0.01 6,963
69 📉
(Org: 68)
(6,791)
0 6,791
70 📈
(Org: 71)
(6,749)
0.04 6,749
71 📉
(Org: 70)
(6,588)
0 6,588
72 📈
(Org: 78)
(6,489)
0.04 6,489
73 📉
(Org: 72)
(6,444)
0 6,444
74 📈
(Org: 77)
(6,316)
0.01 6,316
75 📈
(Org: 140)
(6,169)
0.5 6,169
76 📈
(Org: 80)
(6,099)
0.01 6,099
77 📈
(Org: 84)
(6,007)
0.06 6,007
78 📈
(Org: 126)
(6,003)
0.4 6,003
79 📈
(Org: 83)
(5,947)
0.04 5,947
80 📈
(Org: 81)
(5,921)
- 5,921
81 📈
(Org: 119)
(5,901)
0.34 5,901
82 📈
(Org: 111)
(5,751)
0.25 5,751
83 📉
(Org: 82)
(5,745)
- 5,745
84 📈
(Org: 131)
(5,638)
0.4 5,638
85 📈
(Org: 86)
(5,598)
0.01 5,598
86 📉
(Org: 85)
(5,580)
- 5,580
87 📈
(Org: 118)
(5,570)
0.29 5,570
88 📉
(Org: 87)
(5,483)
0 5,483
89 📉
(Org: 88)
(5,453)
0 5,453
90 📈
(Org: 91)
(5,414)
0 5,414
91 📈
(Org: 192)
(5,339)
0.65 5,339
92 📈
(Org: 93)
(5,271)
0 5,271
93 📈
(Org: 94)
(5,231)
- 5,231
94 📈
(Org: 98)
(5,115)
0.03 5,115
95 📈
(Org: 101)
(5,090)
0.05 5,090
96 📈
(Org: 97)
(5,061)
0 5,061
97 📈
(Org: 103)
(5,051)
0.07 5,051
98 📈
(Org: 102)
(5,040)
0.06 5,040
99 ➡️
(Org: 99)
(4,883)
0 4,883
100 📈
(Org: 104)
(4,873)
0.04 4,873