Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1937 - 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)
(55,807)
0 55,807
2 ➡️
(Org: 2)
(34,925)
0 34,925
3 📈
(Org: 5)
(27,432)
0.08 27,432
4 ➡️
(Org: 4)
(26,847)
0 26,847
5 📉
(Org: 3)
(26,838)
- 26,838
6 📈
(Org: 9)
(23,638)
0.35 23,638
7 📉
(Org: 6)
(21,860)
0.21 21,860
8 📉
(Org: 7)
(17,220)
0.01 17,220
9 📉
(Org: 8)
(16,606)
0 16,606
10 ➡️
(Org: 10)
(15,368)
0.01 15,368
11 📈
(Org: 12)
(12,029)
0.05 12,029
12 📉
(Org: 11)
(11,827)
0 11,827
13 ➡️
(Org: 13)
(10,179)
0.04 10,179
14 📈
(Org: 47)
(9,936)
0.55 9,936
15 📈
(Org: 18)
(9,753)
0.04 9,753
16 📉
(Org: 14)
(9,690)
0.01 9,690
17 📉
(Org: 15)
(9,623)
0 9,623
18 📉
(Org: 17)
(9,589)
0.02 9,589
19 📉
(Org: 16)
(9,539)
0 9,539
20 📉
(Org: 19)
(9,384)
0.03 9,384
21 ➡️
(Org: 21)
(9,183)
0.03 9,183
22 📉
(Org: 20)
(9,070)
0.01 9,070
23 📉
(Org: 22)
(9,025)
0.02 9,025
24 📉
(Org: 23)
(8,521)
0.02 8,521
25 📉
(Org: 24)
(7,961)
0 7,961
26 📉
(Org: 25)
(7,768)
- 7,768
27 📉
(Org: 26)
(7,726)
0.03 7,726
28 📉
(Org: 27)
(7,424)
0.02 7,424
29 📉
(Org: 28)
(7,120)
- 7,120
30 📉
(Org: 29)
(7,026)
0.01 7,026
31 📉
(Org: 30)
(6,713)
- 6,713
32 📉
(Org: 31)
(6,571)
0.03 6,571
33 📉
(Org: 32)
(6,334)
- 6,334
34 📈
(Org: 62)
(6,271)
0.41 6,271
35 📉
(Org: 33)
(6,261)
0 6,261
36 📉
(Org: 34)
(6,172)
0 6,172
37 📉
(Org: 35)
(6,122)
0.01 6,122
38 📉
(Org: 36)
(5,873)
0.02 5,873
39 📉
(Org: 37)
(5,568)
- 5,568
40 📈
(Org: 65)
(5,499)
0.35 5,499
41 📉
(Org: 38)
(5,455)
0 5,455
42 📉
(Org: 38)
(5,450)
- 5,450
43 📉
(Org: 40)
(5,355)
0.06 5,355
44 📉
(Org: 41)
(4,904)
0.04 4,904
45 📉
(Org: 42)
(4,836)
0.03 4,836
46 📈
(Org: 53)
(4,793)
0.11 4,793
47 📉
(Org: 44)
(4,778)
0.05 4,778
48 📈
(Org: 49)
(4,684)
0.07 4,684
49 📉
(Org: 43)
(4,645)
- 4,645
50 📉
(Org: 45)
(4,588)
0.01 4,588
51 📈
(Org: 97)
(4,518)
0.42 4,518
52 📉
(Org: 46)
(4,479)
- 4,479
53 📈
(Org: 59)
(4,446)
0.12 4,446
54 📉
(Org: 52)
(4,445)
0.04 4,445
55 📉
(Org: 48)
(4,408)
0.01 4,408
56 📉
(Org: 50)
(4,404)
0.01 4,404
57 📈
(Org: 70)
(4,372)
0.22 4,372
58 📉
(Org: 54)
(4,243)
- 4,243
59 📉
(Org: 57)
(4,224)
0.03 4,224
60 📉
(Org: 55)
(4,220)
0 4,220
61 📉
(Org: 60)
(3,911)
0.03 3,911
62 📈
(Org: 63)
(3,873)
0.05 3,873
62 📉
(Org: 61)
(3,873)
0.03 3,873
64 📈
(Org: 90)
(3,753)
0.27 3,753
65 📉
(Org: 64)
(3,631)
0.01 3,631
66 ➡️
(Org: 66)
(3,573)
0 3,573
67 📈
(Org: 69)
(3,547)
0.04 3,547
68 📈
(Org: 99)
(3,537)
0.26 3,537
68 📉
(Org: 67)
(3,537)
- 3,537
70 📉
(Org: 68)
(3,529)
- 3,529
71 📈
(Org: 110)
(3,487)
0.34 3,487
72 ➡️
(Org: 72)
(3,483)
0.06 3,483
73 ➡️
(Org: 73)
(3,452)
0.07 3,452
74 📈
(Org: 95)
(3,401)
0.21 3,401
75 📉
(Org: 71)
(3,378)
- 3,378
76 📈
(Org: 79)
(3,272)
0.08 3,272
77 📉
(Org: 74)
(3,223)
- 3,223
78 📉
(Org: 75)
(3,179)
- 3,179
79 📉
(Org: 76)
(3,175)
- 3,175
80 📉
(Org: 77)
(3,171)
- 3,171
81 📈
(Org: 83)
(3,157)
0.07 3,157
82 📉
(Org: 78)
(3,062)
- 3,062
83 📉
(Org: 80)
(3,004)
0.01 3,004
84 📈
(Org: 85)
(2,983)
0.03 2,983
85 📉
(Org: 81)
(2,982)
0.01 2,982
86 📉
(Org: 82)
(2,958)
0.01 2,958
87 📉
(Org: 84)
(2,923)
0.01 2,923
88 📉
(Org: 86)
(2,892)
0.01 2,892
89 📈
(Org: 98)
(2,874)
0.08 2,874
90 ➡️
(Org: 90)
(2,859)
0.04 2,859
91 📉
(Org: 87)
(2,837)
0.01 2,837
92 📉
(Org: 88)
(2,764)
- 2,764
93 📉
(Org: 89)
(2,763)
0 2,763
94 ➡️
(Org: 94)
(2,746)
0.01 2,746
95 📉
(Org: 92)
(2,725)
- 2,725
96 📉
(Org: 93)
(2,714)
- 2,714
97 📈
(Org: 129)
(2,655)
0.28 2,655
98 📉
(Org: 96)
(2,647)
- 2,647
99 📈
(Org: 105)
(2,645)
0.11 2,645
99 📈
(Org: 104)
(2,645)
0.1 2,645