Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1989 - 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)
(50,434)
0.06 50,434
2 📉
(Org: 1)
(48,726)
0.02 48,726
3 ➡️
(Org: 3)
(41,150)
0.08 41,150
4 📈
(Org: 5)
(37,585)
0.26 37,585
5 📉
(Org: 4)
(36,888)
0 36,888
6 📈
(Org: 8)
(26,018)
0.12 26,018
7 📉
(Org: 6)
(24,869)
0 24,869
8 📉
(Org: 7)
(24,645)
0.03 24,645
9 📈
(Org: 36)
(24,586)
0.64 24,586
10 📈
(Org: 26)
(24,225)
0.53 24,225
11 📈
(Org: 12)
(21,950)
0.13 21,950
12 📉
(Org: 10)
(21,615)
0.06 21,615
13 📉
(Org: 9)
(21,574)
0.02 21,574
14 📉
(Org: 11)
(20,844)
0.05 20,844
15 📈
(Org: 49)
(20,517)
0.66 20,517
16 📈
(Org: 23)
(20,432)
0.36 20,432
17 📈
(Org: 18)
(18,852)
0.19 18,852
18 📉
(Org: 13)
(18,033)
0.04 18,033
19 📉
(Org: 16)
(16,901)
0.07 16,901
20 📉
(Org: 14)
(16,817)
0 16,817
21 📉
(Org: 17)
(16,402)
0.06 16,402
22 📉
(Org: 15)
(16,248)
- 16,248
23 📉
(Org: 21)
(15,837)
0.15 15,837
24 📉
(Org: 19)
(15,831)
0.04 15,831
25 📉
(Org: 20)
(15,433)
0.03 15,433
26 📈
(Org: 27)
(15,240)
0.26 15,240
27 📉
(Org: 24)
(14,937)
0.17 14,937
28 📉
(Org: 22)
(14,757)
0.09 14,757
29 📈
(Org: 32)
(14,228)
0.36 14,228
30 📈
(Org: 34)
(14,050)
0.36 14,050
31 📈
(Org: 41)
(13,376)
0.41 13,376
32 📈
(Org: 37)
(12,765)
0.31 12,765
33 📉
(Org: 25)
(12,042)
0.02 12,042
34 📉
(Org: 28)
(11,927)
0.07 11,927
35 📉
(Org: 31)
(11,164)
0.17 11,164
36 📉
(Org: 30)
(11,036)
0.13 11,036
37 📈
(Org: 46)
(10,913)
0.33 10,913
38 📉
(Org: 33)
(10,678)
0.15 10,678
39 📈
(Org: 64)
(10,063)
0.46 10,063
40 📉
(Org: 35)
(8,898)
- 8,898
41 📉
(Org: 38)
(8,728)
0.01 8,728
42 📈
(Org: 48)
(8,661)
0.18 8,661
43 📈
(Org: 54)
(8,521)
0.21 8,521
44 📉
(Org: 42)
(8,492)
0.08 8,492
45 📉
(Org: 40)
(8,476)
0.04 8,476
46 📉
(Org: 39)
(8,410)
- 8,410
47 📉
(Org: 43)
(8,375)
0.08 8,375
48 📈
(Org: 52)
(8,247)
0.17 8,247
49 📈
(Org: 53)
(8,145)
0.16 8,145
50 📉
(Org: 45)
(8,081)
0.1 8,081
51 📉
(Org: 44)
(7,677)
0.01 7,677
52 📉
(Org: 50)
(7,280)
0.04 7,280
53 📉
(Org: 47)
(7,237)
0.01 7,237
54 📈
(Org: 77)
(7,187)
0.44 7,187
55 📉
(Org: 51)
(6,932)
0 6,932
56 📉
(Org: 55)
(6,810)
0.03 6,810
57 📉
(Org: 56)
(6,765)
0.06 6,765
58 📉
(Org: 57)
(6,549)
0.04 6,549
59 📈
(Org: 62)
(6,348)
0.11 6,348
60 📈
(Org: 98)
(6,330)
0.49 6,330
61 📈
(Org: 103)
(6,083)
0.49 6,083
62 📈
(Org: 63)
(5,889)
0.06 5,889
63 📉
(Org: 61)
(5,746)
0.01 5,746
64 📈
(Org: 225)
(5,250)
0.77 5,250
65 📈
(Org: 146)
(5,216)
0.61 5,216
66 📈
(Org: 81)
(4,979)
0.24 4,979
67 📈
(Org: 71)
(4,951)
0.12 4,951
68 📈
(Org: 133)
(4,797)
0.53 4,797
69 📉
(Org: 68)
(4,741)
0.05 4,741
70 📉
(Org: 66)
(4,734)
- 4,734
71 📈
(Org: 125)
(4,708)
0.5 4,708
72 📉
(Org: 70)
(4,685)
0.07 4,685
73 📈
(Org: 79)
(4,673)
0.17 4,673
74 📈
(Org: 101)
(4,618)
0.32 4,618
75 📉
(Org: 72)
(4,547)
0.06 4,547
76 📉
(Org: 69)
(4,523)
0.02 4,523
77 📈
(Org: 83)
(4,424)
0.14 4,424
78 📉
(Org: 75)
(4,389)
0.07 4,389
79 📉
(Org: 74)
(4,362)
0.05 4,362
80 📉
(Org: 78)
(4,019)
0.02 4,019
81 📈
(Org: 84)
(4,011)
0.06 4,011
82 📈
(Org: 93)
(3,980)
0.13 3,980
83 📈
(Org: 179)
(3,952)
0.61 3,952
84 📈
(Org: 87)
(3,949)
0.07 3,949
85 📉
(Org: 80)
(3,891)
0.01 3,891
86 📈
(Org: 90)
(3,867)
0.07 3,867
87 📈
(Org: 88)
(3,827)
0.05 3,827
88 📉
(Org: 85)
(3,795)
0.02 3,795
89 📈
(Org: 91)
(3,771)
0.05 3,771
90 📉
(Org: 86)
(3,711)
0.01 3,711
91 📉
(Org: 89)
(3,639)
0.01 3,639
92 📈
(Org: 143)
(3,626)
0.43 3,626
93 📉
(Org: 92)
(3,608)
0.02 3,608
94 ➡️
(Org: 94)
(3,501)
0.03 3,501
95 📈
(Org: 275)
(3,454)
0.71 3,454
96 📈
(Org: 137)
(3,420)
0.35 3,420
97 📉
(Org: 96)
(3,387)
0.01 3,387
98 📈
(Org: 155)
(3,369)
0.45 3,369
99 📈
(Org: 108)
(3,332)
0.14 3,332
100 📈
(Org: 150)
(3,331)
0.42 3,331