Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1936 - 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)
(54,485)
0 54,485
2 ➡️
(Org: 2)
(35,207)
0 35,207
3 ➡️
(Org: 3)
(31,691)
0 31,691
4 ➡️
(Org: 4)
(28,047)
0.08 28,047
5 📈
(Org: 7)
(25,323)
0.33 25,323
6 📉
(Org: 5)
(23,916)
- 23,916
7 📈
(Org: 10)
(17,986)
0.19 17,986
8 📉
(Org: 6)
(17,714)
0 17,714
9 📉
(Org: 8)
(16,895)
0.01 16,895
10 📉
(Org: 9)
(14,807)
0.01 14,807
11 ➡️
(Org: 11)
(12,778)
0.04 12,778
12 ➡️
(Org: 12)
(12,002)
0 12,002
13 ➡️
(Org: 13)
(11,515)
0.04 11,515
14 📈
(Org: 44)
(9,711)
0.53 9,711
15 📉
(Org: 14)
(9,675)
0 9,675
16 📉
(Org: 15)
(9,351)
0.01 9,351
17 📉
(Org: 16)
(9,246)
0 9,246
18 📈
(Org: 19)
(9,122)
0.04 9,122
19 📉
(Org: 18)
(9,040)
0.02 9,040
20 📉
(Org: 17)
(8,976)
0.01 8,976
21 📉
(Org: 20)
(8,660)
0.01 8,660
22 📉
(Org: 21)
(8,439)
0.04 8,439
23 📉
(Org: 22)
(8,260)
0.04 8,260
24 📉
(Org: 23)
(8,000)
0.01 8,000
25 ➡️
(Org: 25)
(7,550)
0.02 7,550
26 📉
(Org: 24)
(7,391)
- 7,391
27 📉
(Org: 26)
(7,349)
0.02 7,349
28 📉
(Org: 27)
(7,201)
- 7,201
29 ➡️
(Org: 29)
(6,672)
0.01 6,672
30 📉
(Org: 28)
(6,666)
- 6,666
31 📉
(Org: 30)
(6,417)
- 6,417
32 📈
(Org: 57)
(6,411)
0.4 6,411
33 📈
(Org: 35)
(6,250)
0.03 6,250
34 ➡️
(Org: 34)
(6,216)
0.02 6,216
35 📉
(Org: 33)
(6,187)
0.01 6,187
36 📉
(Org: 31)
(6,149)
- 6,149
37 📉
(Org: 32)
(6,140)
- 6,140
38 📉
(Org: 36)
(5,732)
0 5,732
39 📉
(Org: 37)
(5,699)
- 5,699
40 📉
(Org: 38)
(5,696)
0.03 5,696
41 📉
(Org: 39)
(5,666)
0.06 5,666
42 📈
(Org: 62)
(5,343)
0.34 5,343
43 📉
(Org: 41)
(5,100)
0.05 5,100
44 📉
(Org: 40)
(5,052)
- 5,052
45 📈
(Org: 47)
(4,940)
0.12 4,940
46 📉
(Org: 42)
(4,839)
0.02 4,839
47 📉
(Org: 43)
(4,596)
0 4,596
48 📉
(Org: 45)
(4,529)
- 4,529
49 ➡️
(Org: 49)
(4,446)
0.04 4,446
50 📈
(Org: 51)
(4,378)
0.03 4,378
51 📉
(Org: 46)
(4,366)
0 4,366
52 📉
(Org: 50)
(4,318)
0.01 4,318
53 📈
(Org: 66)
(4,304)
0.22 4,304
54 📉
(Org: 52)
(4,196)
- 4,196
55 📈
(Org: 59)
(4,193)
0.13 4,193
55 📉
(Org: 53)
(4,193)
0.01 4,193
57 📉
(Org: 54)
(4,002)
0.03 4,002
58 📉
(Org: 56)
(3,900)
0 3,900
59 📈
(Org: 110)
(3,776)
0.43 3,776
60 📉
(Org: 58)
(3,760)
- 3,760
61 📉
(Org: 60)
(3,722)
0.04 3,722
62 📉
(Org: 61)
(3,564)
0 3,564
63 📈
(Org: 72)
(3,535)
0.07 3,535
64 📈
(Org: 70)
(3,532)
0.06 3,532
65 📈
(Org: 94)
(3,517)
0.27 3,517
66 📉
(Org: 62)
(3,515)
- 3,515
67 📉
(Org: 64)
(3,478)
0 3,478
68 📈
(Org: 88)
(3,477)
0.21 3,477
69 📉
(Org: 67)
(3,471)
0.03 3,471
70 📉
(Org: 69)
(3,454)
0.04 3,454
71 📈
(Org: 111)
(3,448)
0.38 3,448
72 📉
(Org: 68)
(3,435)
0.03 3,435
73 📉
(Org: 65)
(3,423)
0.01 3,423
74 📈
(Org: 76)
(3,390)
0.07 3,390
75 📉
(Org: 71)
(3,305)
- 3,305
76 📈
(Org: 101)
(3,210)
0.27 3,210
77 📉
(Org: 74)
(3,197)
- 3,197
78 📉
(Org: 75)
(3,183)
- 3,183
79 📈
(Org: 83)
(3,162)
0.06 3,162
80 📉
(Org: 77)
(3,155)
0 3,155
81 📉
(Org: 79)
(3,153)
0.01 3,153
82 📉
(Org: 78)
(3,139)
0.01 3,139
83 📉
(Org: 80)
(3,108)
0.01 3,108
84 📉
(Org: 81)
(3,038)
- 3,038
85 📉
(Org: 82)
(2,999)
0.01 2,999
86 📉
(Org: 84)
(2,977)
0.01 2,977
87 📈
(Org: 92)
(2,871)
0.08 2,871
88 📈
(Org: 95)
(2,851)
0.11 2,851
89 📉
(Org: 85)
(2,847)
0.01 2,847
90 📈
(Org: 114)
(2,844)
0.28 2,844
91 📉
(Org: 86)
(2,813)
0.01 2,813
92 📉
(Org: 87)
(2,759)
- 2,759
93 📉
(Org: 89)
(2,756)
- 2,756
94 📉
(Org: 90)
(2,730)
- 2,730
95 📉
(Org: 91)
(2,684)
- 2,684
96 📈
(Org: 97)
(2,655)
0.08 2,655
97 📈
(Org: 98)
(2,608)
0.08 2,608
98 📉
(Org: 93)
(2,594)
0.01 2,594
99 📉
(Org: 96)
(2,551)
0.02 2,551
100 📈
(Org: 106)
(2,523)
0.11 2,523