Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1988 - 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: 2)
(52,794)
0.05 52,794
2 📉
(Org: 1)
(52,406)
0.02 52,406
3 ➡️
(Org: 3)
(39,520)
0 39,520
4 ➡️
(Org: 4)
(38,476)
0.26 38,476
5 📈
(Org: 6)
(29,342)
0.09 29,342
6 📉
(Org: 5)
(28,606)
0.02 28,606
7 ➡️
(Org: 7)
(25,691)
0.11 25,691
8 📈
(Org: 36)
(24,003)
0.65 24,003
9 📈
(Org: 27)
(23,804)
0.53 23,804
10 📉
(Org: 9)
(23,530)
0.14 23,530
11 📉
(Org: 10)
(20,836)
0.04 20,836
12 📉
(Org: 8)
(20,790)
0 20,790
13 📉
(Org: 11)
(20,052)
0.02 20,052
14 📈
(Org: 22)
(19,700)
0.34 19,700
15 📉
(Org: 13)
(19,655)
0.07 19,655
16 📉
(Org: 12)
(19,587)
0.05 19,587
17 📈
(Org: 19)
(18,860)
0.19 18,860
18 📈
(Org: 44)
(18,795)
0.61 18,795
19 📉
(Org: 14)
(18,053)
0 18,053
20 📉
(Org: 17)
(17,448)
0.07 17,448
21 📉
(Org: 16)
(17,258)
0.04 17,258
22 📉
(Org: 15)
(16,711)
0 16,711
23 📉
(Org: 18)
(16,527)
0.04 16,527
24 📈
(Org: 28)
(15,484)
0.35 15,484
25 📉
(Org: 21)
(14,740)
0.1 14,740
26 📈
(Org: 31)
(14,319)
0.33 14,319
27 📉
(Org: 24)
(14,253)
0.16 14,253
28 📉
(Org: 26)
(14,163)
0.16 14,163
29 📉
(Org: 20)
(13,878)
0.03 13,878
30 📈
(Org: 32)
(13,330)
0.33 13,330
31 📉
(Org: 25)
(12,790)
0.07 12,790
32 📉
(Org: 23)
(12,442)
0.03 12,442
33 ➡️
(Org: 33)
(12,251)
0.28 12,251
34 📈
(Org: 52)
(10,986)
0.4 10,986
35 📈
(Org: 46)
(10,718)
0.33 10,718
36 📈
(Org: 62)
(10,563)
0.48 10,563
37 📉
(Org: 29)
(10,034)
- 10,034
38 📈
(Org: 48)
(8,663)
0.19 8,663
39 📈
(Org: 45)
(8,644)
0.17 8,644
40 📉
(Org: 34)
(8,610)
0.01 8,610
41 📉
(Org: 40)
(8,595)
0.1 8,595
42 📉
(Org: 37)
(8,594)
0.04 8,594
43 📈
(Org: 47)
(8,572)
0.17 8,572
44 📉
(Org: 35)
(8,391)
- 8,391
45 📉
(Org: 39)
(8,121)
0.03 8,121
46 📉
(Org: 38)
(7,966)
0.01 7,966
47 📈
(Org: 50)
(7,879)
0.15 7,879
48 📉
(Org: 41)
(7,815)
0.04 7,815
49 📈
(Org: 53)
(7,624)
0.15 7,624
50 📉
(Org: 43)
(7,492)
0.03 7,492
51 📉
(Org: 49)
(7,429)
0.06 7,429
52 📉
(Org: 42)
(7,321)
0.01 7,321
53 📈
(Org: 59)
(7,133)
0.2 7,133
54 📈
(Org: 64)
(6,606)
0.17 6,606
55 📈
(Org: 91)
(6,536)
0.52 6,536
56 📉
(Org: 54)
(6,484)
0.01 6,484
57 ➡️
(Org: 57)
(6,393)
0.06 6,393
58 📉
(Org: 56)
(6,322)
0.01 6,322
59 📈
(Org: 119)
(6,194)
0.62 6,194
60 ➡️
(Org: 60)
(6,158)
0.07 6,158
61 📈
(Org: 63)
(6,142)
0.11 6,142
62 📈
(Org: 92)
(5,977)
0.47 5,977
63 📉
(Org: 61)
(5,976)
0.07 5,976
64 📈
(Org: 205)
(5,686)
0.77 5,686
65 📈
(Org: 96)
(5,303)
0.44 5,303
66 ➡️
(Org: 66)
(5,237)
0.12 5,237
67 📈
(Org: 72)
(5,018)
0.16 5,018
68 📈
(Org: 117)
(4,953)
0.51 4,953
69 📉
(Org: 67)
(4,941)
0.07 4,941
70 📉
(Org: 65)
(4,839)
- 4,839
71 📉
(Org: 70)
(4,743)
0.06 4,743
72 📉
(Org: 71)
(4,553)
0.02 4,553
73 📈
(Org: 95)
(4,519)
0.33 4,519
74 📉
(Org: 73)
(4,328)
0.07 4,328
75 ➡️
(Org: 75)
(4,208)
0.07 4,208
76 📈
(Org: 82)
(4,201)
0.15 4,201
77 📈
(Org: 143)
(4,109)
0.51 4,109
78 📈
(Org: 112)
(4,055)
0.37 4,055
79 📈
(Org: 101)
(4,002)
0.3 4,002
80 📉
(Org: 79)
(3,992)
0.05 3,992
81 📈
(Org: 86)
(3,941)
0.12 3,941
82 📉
(Org: 78)
(3,889)
0.02 3,889
83 📉
(Org: 77)
(3,832)
0.01 3,832
84 📈
(Org: 129)
(3,780)
0.41 3,780
85 📉
(Org: 80)
(3,774)
0 3,774
86 📉
(Org: 81)
(3,643)
0.01 3,643
87 📈
(Org: 94)
(3,623)
0.15 3,623
88 📉
(Org: 87)
(3,611)
0.05 3,611
89 📉
(Org: 83)
(3,603)
0.02 3,603
90 📈
(Org: 175)
(3,578)
0.55 3,578
91 📉
(Org: 85)
(3,509)
0.01 3,509
92 📉
(Org: 89)
(3,403)
0.04 3,403
93 📉
(Org: 88)
(3,392)
0.01 3,392
94 📈
(Org: 171)
(3,370)
0.51 3,370
95 📉
(Org: 90)
(3,356)
0.05 3,356
96 📈
(Org: 173)
(3,279)
0.5 3,279
97 📈
(Org: 176)
(3,190)
0.5 3,190
98 📉
(Org: 93)
(3,169)
0.01 3,169
99 📈
(Org: 131)
(3,129)
0.29 3,129
100 📈
(Org: 140)
(3,097)
0.33 3,097