Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1948 - 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)
(100,440)
0.04 100,440
2 ➡️
(Org: 2)
(69,085)
0.01 69,085
3 ➡️
(Org: 3)
(46,833)
0 46,833
4 ➡️
(Org: 4)
(46,148)
0 46,148
5 ➡️
(Org: 5)
(42,538)
0.15 42,538
6 📈
(Org: 8)
(32,653)
0.11 32,653
7 📉
(Org: 6)
(31,773)
0.02 31,773
8 📉
(Org: 7)
(29,747)
0.01 29,747
9 ➡️
(Org: 9)
(26,807)
0.02 26,807
10 ➡️
(Org: 10)
(24,220)
0.04 24,220
11 ➡️
(Org: 11)
(22,448)
0.02 22,448
12 ➡️
(Org: 12)
(22,313)
0.01 22,313
13 📈
(Org: 41)
(20,948)
0.61 20,948
14 📉
(Org: 13)
(19,102)
0.01 19,102
15 📉
(Org: 14)
(18,879)
0.01 18,879
16 📈
(Org: 37)
(18,676)
0.5 18,676
17 📈
(Org: 18)
(18,487)
0.1 18,487
18 📉
(Org: 16)
(18,304)
0.03 18,304
19 📉
(Org: 15)
(17,868)
0 17,868
20 📉
(Org: 17)
(17,699)
- 17,699
21 📉
(Org: 19)
(16,607)
- 16,607
22 📉
(Org: 20)
(16,149)
0 16,149
23 📈
(Org: 25)
(15,589)
0.15 15,589
24 📉
(Org: 22)
(14,549)
0.02 14,549
25 📉
(Org: 24)
(14,527)
0.04 14,527
26 📉
(Org: 21)
(14,393)
0 14,393
27 📉
(Org: 23)
(14,162)
- 14,162
28 📉
(Org: 26)
(13,432)
0.02 13,432
29 📉
(Org: 27)
(12,283)
0 12,283
30 📉
(Org: 28)
(11,699)
0 11,699
31 📉
(Org: 30)
(11,442)
0.02 11,442
32 📈
(Org: 35)
(11,383)
0.15 11,383
33 📉
(Org: 29)
(11,342)
0 11,342
34 📈
(Org: 55)
(10,946)
0.44 10,946
35 📉
(Org: 31)
(10,872)
0.01 10,872
36 📉
(Org: 33)
(10,409)
0.05 10,409
37 📉
(Org: 32)
(10,011)
- 10,011
38 📉
(Org: 34)
(9,989)
0.02 9,989
39 📈
(Org: 62)
(9,928)
0.44 9,928
40 📉
(Org: 38)
(9,396)
0.03 9,396
41 📉
(Org: 39)
(9,322)
0.06 9,322
42 📈
(Org: 51)
(9,308)
0.29 9,308
43 📉
(Org: 36)
(9,307)
0 9,307
44 📉
(Org: 40)
(8,897)
0.07 8,897
45 📉
(Org: 42)
(8,464)
0.03 8,464
46 ➡️
(Org: 46)
(8,167)
0.04 8,167
47 📉
(Org: 43)
(8,108)
0.01 8,108
48 📉
(Org: 44)
(8,025)
- 8,025
49 📉
(Org: 47)
(7,921)
0.02 7,921
50 📉
(Org: 45)
(7,918)
0 7,918
51 📈
(Org: 58)
(7,749)
0.25 7,749
52 📉
(Org: 48)
(7,726)
0 7,726
53 📈
(Org: 81)
(7,545)
0.42 7,545
54 📈
(Org: 91)
(7,157)
0.46 7,157
55 📉
(Org: 49)
(6,987)
0 6,987
56 📉
(Org: 50)
(6,925)
0.02 6,925
57 📉
(Org: 52)
(6,617)
0 6,617
58 📈
(Org: 80)
(6,546)
0.3 6,546
59 📉
(Org: 53)
(6,512)
0.02 6,512
60 📉
(Org: 56)
(6,189)
0.03 6,189
61 📈
(Org: 85)
(6,179)
0.33 6,179
62 📉
(Org: 60)
(5,964)
0.03 5,964
63 📉
(Org: 59)
(5,962)
0.02 5,962
64 📉
(Org: 57)
(5,957)
0.01 5,957
65 📉
(Org: 61)
(5,896)
0.03 5,896
66 📉
(Org: 64)
(5,648)
0.02 5,648
67 📈
(Org: 72)
(5,587)
0.1 5,587
68 📉
(Org: 62)
(5,556)
- 5,556
69 📉
(Org: 67)
(5,317)
0.01 5,317
70 📈
(Org: 73)
(5,308)
0.08 5,308
71 📉
(Org: 70)
(5,192)
0.02 5,192
72 📉
(Org: 69)
(5,177)
0 5,177
73 📈
(Org: 86)
(5,132)
0.19 5,132
74 📉
(Org: 71)
(5,022)
- 5,022
75 📈
(Org: 77)
(4,983)
0.06 4,983
76 📉
(Org: 74)
(4,917)
0.02 4,917
77 📈
(Org: 90)
(4,916)
0.21 4,916
78 📉
(Org: 75)
(4,841)
0 4,841
79 📉
(Org: 76)
(4,725)
- 4,725
80 📉
(Org: 78)
(4,684)
0 4,684
81 📉
(Org: 79)
(4,656)
0 4,656
82 📈
(Org: 83)
(4,427)
0.05 4,427
83 📈
(Org: 105)
(4,174)
0.16 4,174
84 📈
(Org: 88)
(4,160)
0.02 4,160
85 📈
(Org: 87)
(4,122)
- 4,122
86 📈
(Org: 89)
(4,037)
- 4,037
87 📈
(Org: 96)
(4,030)
0.07 4,030
88 📈
(Org: 92)
(3,850)
0 3,850
89 📈
(Org: 95)
(3,845)
0.01 3,845
90 📈
(Org: 93)
(3,817)
0 3,817
91 📈
(Org: 100)
(3,756)
0.02 3,756
92 📈
(Org: 97)
(3,721)
- 3,721
93 📈
(Org: 98)
(3,714)
- 3,714
94 📈
(Org: 133)
(3,713)
0.39 3,713
95 📈
(Org: 99)
(3,692)
0 3,692
96 📈
(Org: 101)
(3,679)
0 3,679
97 📈
(Org: 102)
(3,615)
- 3,615
98 📈
(Org: 103)
(3,614)
0.01 3,614
99 📈
(Org: 113)
(3,400)
0.13 3,400
100 📈
(Org: 109)
(3,302)
0.08 3,302