Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1997 - 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)
(27,312)
0.06 27,312
2 📈
(Org: 4)
(26,981)
0.23 26,981
3 📈
(Org: 41)
(24,570)
0.71 24,570
4 📉
(Org: 3)
(22,763)
0.08 22,763
5 ➡️
(Org: 5)
(22,295)
0.08 22,295
6 📉
(Org: 2)
(21,622)
0.03 21,622
7 ➡️
(Org: 7)
(20,685)
0.06 20,685
8 📉
(Org: 6)
(20,181)
0 20,181
9 📈
(Org: 17)
(18,714)
0.36 18,714
10 📈
(Org: 31)
(18,293)
0.53 18,293
11 📉
(Org: 8)
(17,698)
0.03 17,698
12 📈
(Org: 32)
(17,164)
0.5 17,164
13 📉
(Org: 9)
(16,383)
0.06 16,383
14 📉
(Org: 13)
(16,248)
0.15 16,248
15 📉
(Org: 10)
(16,008)
0.05 16,008
16 📉
(Org: 11)
(14,873)
0.04 14,873
17 📉
(Org: 12)
(14,727)
0.06 14,727
18 📉
(Org: 15)
(14,625)
0.14 14,625
19 📉
(Org: 14)
(13,639)
0.03 13,639
20 ➡️
(Org: 20)
(12,574)
0.08 12,574
21 📉
(Org: 18)
(12,437)
0.05 12,437
22 📈
(Org: 25)
(12,415)
0.22 12,415
23 📉
(Org: 16)
(12,250)
0 12,250
24 📈
(Org: 38)
(12,162)
0.4 12,162
25 📉
(Org: 21)
(11,926)
0.1 11,926
26 📉
(Org: 19)
(11,866)
0.01 11,866
27 📉
(Org: 24)
(11,811)
0.18 11,811
28 📉
(Org: 23)
(11,037)
0.11 11,037
29 📉
(Org: 28)
(10,723)
0.16 10,723
30 📉
(Org: 22)
(10,590)
0.02 10,590
31 📈
(Org: 35)
(10,476)
0.23 10,476
32 📈
(Org: 39)
(10,401)
0.3 10,401
33 📉
(Org: 26)
(10,035)
0.04 10,035
34 📉
(Org: 27)
(9,547)
0.01 9,547
35 📉
(Org: 30)
(9,094)
0.04 9,094
36 📈
(Org: 42)
(9,060)
0.26 9,060
37 📉
(Org: 29)
(8,952)
0 8,952
38 📈
(Org: 82)
(8,814)
0.54 8,814
39 📉
(Org: 34)
(8,553)
0.06 8,553
40 📈
(Org: 47)
(8,516)
0.23 8,516
41 📉
(Org: 33)
(8,391)
0.01 8,391
42 📈
(Org: 62)
(8,238)
0.37 8,238
43 📈
(Org: 56)
(8,169)
0.3 8,169
44 📈
(Org: 71)
(8,031)
0.44 8,031
45 📉
(Org: 36)
(7,800)
0.01 7,800
46 📈
(Org: 84)
(7,742)
0.48 7,742
47 📈
(Org: 57)
(7,606)
0.27 7,606
48 📈
(Org: 65)
(7,536)
0.33 7,536
49 📉
(Org: 48)
(7,535)
0.13 7,535
50 📈
(Org: 107)
(7,520)
0.59 7,520
51 📉
(Org: 40)
(7,518)
0.05 7,518
52 📉
(Org: 37)
(7,418)
0.01 7,418
53 📉
(Org: 43)
(7,396)
0.09 7,396
54 📈
(Org: 137)
(7,370)
0.68 7,370
55 📉
(Org: 44)
(7,059)
0.05 7,059
56 📈
(Org: 60)
(7,033)
0.25 7,033
57 📈
(Org: 59)
(6,962)
0.24 6,962
58 📉
(Org: 45)
(6,958)
0.04 6,958
59 📉
(Org: 49)
(6,721)
0.08 6,721
60 📉
(Org: 46)
(6,703)
0.01 6,703
61 📈
(Org: 77)
(6,587)
0.35 6,587
62 📉
(Org: 51)
(6,430)
0.08 6,430
63 📈
(Org: 73)
(6,371)
0.3 6,371
64 📉
(Org: 52)
(6,335)
0.06 6,335
65 📈
(Org: 81)
(6,318)
0.35 6,318
66 📉
(Org: 54)
(6,200)
0.07 6,200
67 📉
(Org: 55)
(6,088)
0.06 6,088
68 📉
(Org: 53)
(5,933)
0.02 5,933
69 📉
(Org: 61)
(5,924)
0.12 5,924
70 📈
(Org: 83)
(5,740)
0.29 5,740
71 📈
(Org: 99)
(5,539)
0.38 5,539
72 📈
(Org: 100)
(5,406)
0.37 5,406
73 📉
(Org: 58)
(5,405)
- 5,405
74 📈
(Org: 116)
(5,321)
0.48 5,321
75 📈
(Org: 120)
(5,276)
0.5 5,276
76 ➡️
(Org: 76)
(5,188)
0.15 5,188
77 📉
(Org: 64)
(5,186)
0.03 5,186
78 📉
(Org: 68)
(5,008)
0.05 5,008
79 📉
(Org: 66)
(4,987)
0.03 4,987
80 📉
(Org: 70)
(4,911)
0.07 4,911
81 📈
(Org: 94)
(4,823)
0.25 4,823
82 📈
(Org: 89)
(4,800)
0.21 4,800
83 📈
(Org: 95)
(4,701)
0.23 4,701
84 📉
(Org: 69)
(4,652)
0 4,652
85 📉
(Org: 74)
(4,646)
0.04 4,646
86 📈
(Org: 125)
(4,616)
0.45 4,616
87 📈
(Org: 146)
(4,553)
0.52 4,553
88 📉
(Org: 79)
(4,496)
0.06 4,496
89 📉
(Org: 75)
(4,461)
0 4,461
90 📉
(Org: 78)
(4,392)
0.04 4,392
91 📉
(Org: 87)
(4,322)
0.11 4,322
92 📈
(Org: 138)
(4,165)
0.44 4,165
93 📈
(Org: 105)
(4,067)
0.23 4,067
94 📈
(Org: 103)
(3,992)
0.19 3,992
95 📈
(Org: 98)
(3,973)
0.13 3,973
96 📉
(Org: 85)
(3,971)
0.01 3,971
97 📈
(Org: 104)
(3,956)
0.19 3,956
98 📈
(Org: 115)
(3,880)
0.27 3,880
99 📈
(Org: 130)
(3,873)
0.36 3,873
100 📈
(Org: 122)
(3,824)
0.31 3,824