Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1980 - 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)
(59,494)
0.02 59,494
2 📈
(Org: 5)
(36,969)
0.3 36,969
3 📉
(Org: 2)
(35,842)
0 35,842
4 📉
(Org: 3)
(34,274)
0.01 34,274
5 📉
(Org: 4)
(32,694)
0.03 32,694
6 📈
(Org: 37)
(24,803)
0.69 24,803
7 ➡️
(Org: 7)
(23,717)
0.16 23,717
8 📈
(Org: 15)
(21,866)
0.26 21,866
9 📈
(Org: 10)
(21,753)
0.12 21,753
10 📉
(Org: 9)
(20,360)
0.04 20,360
11 📈
(Org: 13)
(20,107)
0.11 20,107
12 📉
(Org: 6)
(19,988)
0 19,988
13 📉
(Org: 8)
(19,833)
- 19,833
14 📉
(Org: 11)
(19,737)
0.06 19,737
15 📈
(Org: 35)
(18,967)
0.58 18,967
16 📈
(Org: 19)
(18,934)
0.28 18,934
17 📉
(Org: 12)
(18,069)
0.01 18,069
18 📉
(Org: 14)
(17,597)
0.08 17,597
19 📉
(Org: 17)
(17,486)
0.13 17,486
20 📉
(Org: 18)
(17,047)
0.16 17,047
21 📉
(Org: 16)
(15,905)
0.02 15,905
22 📈
(Org: 23)
(14,156)
0.18 14,156
23 📉
(Org: 20)
(13,697)
0.02 13,697
24 📈
(Org: 78)
(13,571)
0.7 13,571
25 📉
(Org: 21)
(13,465)
0.04 13,465
26 📈
(Org: 34)
(13,027)
0.33 13,027
27 📉
(Org: 24)
(12,830)
0.1 12,830
28 📉
(Org: 22)
(12,577)
0 12,577
29 📈
(Org: 42)
(12,228)
0.48 12,228
30 📉
(Org: 25)
(11,608)
0.01 11,608
31 📉
(Org: 26)
(11,473)
- 11,473
32 📈
(Org: 53)
(11,281)
0.55 11,281
33 📉
(Org: 28)
(10,451)
- 10,451
34 📉
(Org: 30)
(9,884)
0.08 9,884
35 📉
(Org: 29)
(9,857)
0.02 9,857
36 📉
(Org: 33)
(9,665)
0.08 9,665
37 📉
(Org: 31)
(9,353)
0.04 9,353
38 📉
(Org: 32)
(9,047)
0.02 9,047
39 📈
(Org: 59)
(8,435)
0.42 8,435
40 📉
(Org: 36)
(8,298)
0.05 8,298
41 📈
(Org: 56)
(8,214)
0.4 8,214
42 📉
(Org: 40)
(7,955)
0.08 7,955
43 📉
(Org: 38)
(7,686)
0.03 7,686
44 📈
(Org: 81)
(7,216)
0.46 7,216
45 📈
(Org: 62)
(7,101)
0.34 7,101
46 ➡️
(Org: 46)
(6,812)
0.15 6,812
47 📉
(Org: 44)
(6,755)
0.09 6,755
48 📉
(Org: 43)
(6,598)
0.05 6,598
49 📉
(Org: 48)
(6,511)
0.14 6,511
50 📉
(Org: 47)
(6,316)
0.09 6,316
51 📉
(Org: 45)
(6,273)
0.04 6,273
52 ➡️
(Org: 52)
(6,237)
0.15 6,237
53 📈
(Org: 94)
(6,214)
0.49 6,214
54 📉
(Org: 49)
(6,143)
0.1 6,143
55 📈
(Org: 76)
(6,039)
0.32 6,039
56 📈
(Org: 61)
(5,756)
0.17 5,756
57 📈
(Org: 99)
(5,439)
0.45 5,439
58 📉
(Org: 57)
(5,356)
0.08 5,356
59 📉
(Org: 51)
(5,350)
0.01 5,350
60 📉
(Org: 54)
(5,197)
0.03 5,197
61 📉
(Org: 55)
(5,059)
0 5,059
62 📉
(Org: 60)
(5,044)
0.04 5,044
63 📉
(Org: 58)
(4,930)
0 4,930
64 📈
(Org: 65)
(4,820)
0.04 4,820
65 📉
(Org: 64)
(4,798)
0.02 4,798
66 📈
(Org: 68)
(4,614)
0.04 4,614
67 📈
(Org: 71)
(4,588)
0.05 4,588
68 📉
(Org: 66)
(4,570)
0 4,570
69 📈
(Org: 75)
(4,567)
0.09 4,567
70 📉
(Org: 69)
(4,533)
0.02 4,533
71 📉
(Org: 67)
(4,511)
0.01 4,511
72 📉
(Org: 70)
(4,472)
0.02 4,472
73 📈
(Org: 109)
(4,413)
0.36 4,413
74 📉
(Org: 72)
(4,323)
0.01 4,323
75 📈
(Org: 84)
(4,315)
0.16 4,315
76 📈
(Org: 79)
(4,154)
0.03 4,154
77 📈
(Org: 91)
(4,153)
0.18 4,153
78 📈
(Org: 82)
(4,135)
0.07 4,135
79 📈
(Org: 80)
(4,075)
0.02 4,075
80 📈
(Org: 117)
(3,975)
0.33 3,975
81 📈
(Org: 90)
(3,907)
0.13 3,907
82 📈
(Org: 127)
(3,902)
0.37 3,902
83 📈
(Org: 121)
(3,827)
0.34 3,827
84 📈
(Org: 96)
(3,687)
0.15 3,687
85 📈
(Org: 135)
(3,651)
0.41 3,651
86 📉
(Org: 85)
(3,628)
0 3,628
87 📉
(Org: 86)
(3,614)
0.02 3,614
88 📈
(Org: 89)
(3,611)
0.05 3,611
89 📈
(Org: 100)
(3,455)
0.13 3,455
90 📉
(Org: 88)
(3,436)
- 3,436
91 📈
(Org: 228)
(3,319)
0.66 3,319
92 ➡️
(Org: 92)
(3,291)
0.03 3,291
93 📈
(Org: 167)
(3,228)
0.47 3,228
94 📉
(Org: 93)
(3,170)
0 3,170
95 ➡️
(Org: 95)
(3,154)
0 3,154
96 📈
(Org: 110)
(3,131)
0.1 3,131
97 📈
(Org: 98)
(3,085)
0.01 3,085
98 📉
(Org: 97)
(3,081)
- 3,081
99 📈
(Org: 119)
(3,001)
0.13 3,001
100 📈
(Org: 103)
(2,937)
0 2,937