Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1968 - 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)
(50,015)
0.01 50,015
2 ➡️
(Org: 2)
(44,958)
0.26 44,958
3 ➡️
(Org: 3)
(34,884)
0.09 34,884
4 📈
(Org: 14)
(27,927)
0.41 27,927
5 📉
(Org: 4)
(27,512)
0.02 27,512
6 📈
(Org: 10)
(25,540)
0.24 25,540
7 📈
(Org: 12)
(23,495)
0.27 23,495
8 ➡️
(Org: 8)
(23,047)
0.13 23,047
9 📉
(Org: 5)
(22,593)
0.04 22,593
10 📉
(Org: 6)
(22,014)
0.01 22,014
11 📈
(Org: 25)
(21,827)
0.42 21,827
12 📉
(Org: 7)
(20,779)
0.01 20,779
13 📉
(Org: 11)
(20,300)
0.08 20,300
14 📉
(Org: 9)
(19,838)
0.01 19,838
15 📈
(Org: 22)
(19,780)
0.34 19,780
16 📈
(Org: 30)
(18,632)
0.41 18,632
17 📉
(Org: 13)
(17,092)
- 17,092
18 📉
(Org: 16)
(16,058)
0.02 16,058
19 📉
(Org: 15)
(15,818)
0 15,818
20 📈
(Org: 56)
(15,589)
0.61 15,589
21 📉
(Org: 17)
(15,383)
0.03 15,383
22 📉
(Org: 18)
(14,923)
0.01 14,923
23 📉
(Org: 20)
(14,270)
0.02 14,270
24 📉
(Org: 19)
(14,169)
0.01 14,169
25 📉
(Org: 23)
(14,163)
0.09 14,163
26 📈
(Org: 55)
(13,666)
0.55 13,666
27 📉
(Org: 21)
(13,590)
0.01 13,590
28 📉
(Org: 24)
(13,133)
0.03 13,133
29 📉
(Org: 27)
(12,996)
0.05 12,996
30 📉
(Org: 26)
(12,962)
0.02 12,962
31 📉
(Org: 28)
(12,501)
0.09 12,501
32 📉
(Org: 31)
(11,593)
0.08 11,593
33 📈
(Org: 37)
(11,151)
0.18 11,151
34 📈
(Org: 44)
(10,769)
0.26 10,769
35 📉
(Org: 33)
(10,710)
0.05 10,710
36 📉
(Org: 32)
(10,632)
0.03 10,632
37 📈
(Org: 43)
(9,948)
0.18 9,948
38 📉
(Org: 34)
(9,943)
- 9,943
39 📉
(Org: 35)
(9,925)
0 9,925
40 📈
(Org: 42)
(9,879)
0.16 9,879
41 📉
(Org: 36)
(9,741)
- 9,741
42 📉
(Org: 40)
(9,522)
0.08 9,522
43 📉
(Org: 38)
(9,250)
0.02 9,250
44 📉
(Org: 39)
(9,118)
0.02 9,118
45 📈
(Org: 138)
(8,683)
0.73 8,683
46 📉
(Org: 41)
(8,427)
0 8,427
47 📈
(Org: 50)
(8,293)
0.19 8,293
48 📈
(Org: 76)
(7,795)
0.4 7,795
49 ➡️
(Org: 49)
(7,776)
0.09 7,776
50 📉
(Org: 45)
(7,653)
0 7,653
51 📉
(Org: 46)
(7,554)
0 7,554
52 📈
(Org: 83)
(7,383)
0.42 7,383
53 📉
(Org: 48)
(7,089)
- 7,089
54 📈
(Org: 78)
(6,945)
0.35 6,945
55 📈
(Org: 58)
(6,837)
0.12 6,837
56 📉
(Org: 52)
(6,775)
0.05 6,775
57 📉
(Org: 51)
(6,584)
- 6,584
58 📉
(Org: 53)
(6,572)
0.03 6,572
59 📈
(Org: 114)
(6,513)
0.54 6,513
60 📈
(Org: 97)
(6,446)
0.44 6,446
61 📉
(Org: 54)
(6,177)
- 6,177
62 📉
(Org: 57)
(6,089)
- 6,089
63 📈
(Org: 66)
(5,978)
0.12 5,978
64 📈
(Org: 119)
(5,901)
0.54 5,901
65 📉
(Org: 59)
(5,730)
- 5,730
66 📈
(Org: 154)
(5,702)
0.63 5,702
67 ➡️
(Org: 67)
(5,668)
0.08 5,668
68 📉
(Org: 61)
(5,662)
0.02 5,662
69 📉
(Org: 60)
(5,661)
- 5,661
70 📉
(Org: 63)
(5,523)
0.02 5,523
71 📉
(Org: 62)
(5,506)
0 5,506
72 📈
(Org: 73)
(5,412)
0.11 5,412
73 📉
(Org: 68)
(5,373)
0.03 5,373
74 📉
(Org: 65)
(5,354)
- 5,354
75 📈
(Org: 91)
(5,317)
0.28 5,317
76 📉
(Org: 70)
(5,277)
0.05 5,277
77 📈
(Org: 86)
(5,267)
0.24 5,267
78 📈
(Org: 85)
(5,205)
0.21 5,205
79 📉
(Org: 71)
(5,014)
0 5,014
80 📉
(Org: 74)
(4,775)
0 4,775
81 📉
(Org: 77)
(4,600)
0.01 4,600
82 📈
(Org: 104)
(4,580)
0.25 4,580
83 📈
(Org: 98)
(4,435)
0.19 4,435
84 📈
(Org: 92)
(4,378)
0.15 4,378
85 📉
(Org: 80)
(4,342)
0.01 4,342
86 📉
(Org: 81)
(4,311)
0 4,311
87 📉
(Org: 82)
(4,306)
0 4,306
88 📉
(Org: 87)
(4,042)
0.02 4,042
89 ➡️
(Org: 89)
(3,985)
0.02 3,985
90 📈
(Org: 186)
(3,918)
0.56 3,918
91 📉
(Org: 88)
(3,914)
- 3,914
92 📉
(Org: 90)
(3,896)
0.02 3,896
93 📈
(Org: 101)
(3,890)
0.1 3,890
94 ➡️
(Org: 94)
(3,819)
0.05 3,819
95 📈
(Org: 103)
(3,810)
0.1 3,810
96 📈
(Org: 231)
(3,801)
0.67 3,801
97 📉
(Org: 93)
(3,753)
0.01 3,753
98 📉
(Org: 95)
(3,641)
- 3,641
99 📉
(Org: 96)
(3,622)
- 3,622
100 📉
(Org: 99)
(3,569)
- 3,569