Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1979 - 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)
(57,821)
0.02 57,821
2 ➡️
(Org: 2)
(35,272)
0.03 35,272
3 ➡️
(Org: 3)
(31,948)
0 31,948
4 📈
(Org: 6)
(29,723)
0.29 29,723
5 📉
(Org: 4)
(28,083)
0.01 28,083
6 📈
(Org: 9)
(23,300)
0.16 23,300
7 📈
(Org: 10)
(22,335)
0.14 22,335
8 📈
(Org: 14)
(21,967)
0.25 21,967
9 📉
(Org: 5)
(21,609)
- 21,609
10 📉
(Org: 7)
(20,858)
0 20,858
11 📈
(Org: 16)
(20,487)
0.25 20,487
12 📉
(Org: 8)
(20,385)
0.01 20,385
13 📉
(Org: 12)
(18,877)
0.07 18,877
14 📉
(Org: 11)
(18,793)
0.04 18,793
15 📈
(Org: 35)
(18,731)
0.59 18,731
16 📈
(Org: 36)
(18,046)
0.59 18,046
17 📉
(Org: 15)
(17,750)
0.09 17,750
18 📉
(Org: 13)
(17,559)
0.02 17,559
19 📉
(Org: 17)
(16,555)
0.12 16,555
20 📉
(Org: 18)
(16,348)
0.18 16,348
21 📈
(Org: 56)
(16,153)
0.7 16,153
22 📉
(Org: 19)
(13,437)
0.1 13,437
23 📈
(Org: 43)
(12,518)
0.54 12,518
24 📈
(Org: 27)
(12,495)
0.18 12,495
25 📉
(Org: 20)
(12,494)
0.05 12,494
26 📈
(Org: 39)
(12,448)
0.46 12,448
27 📈
(Org: 32)
(12,271)
0.33 12,271
28 📉
(Org: 21)
(11,517)
0.02 11,517
29 📉
(Org: 22)
(11,096)
0 11,096
30 📉
(Org: 23)
(10,912)
0 10,912
31 📉
(Org: 24)
(10,699)
0.01 10,699
32 📉
(Org: 28)
(10,633)
0.1 10,633
33 📉
(Org: 25)
(10,573)
0.02 10,573
34 📉
(Org: 26)
(10,337)
- 10,337
35 📉
(Org: 29)
(9,418)
0.02 9,418
36 📉
(Org: 31)
(9,154)
0.09 9,154
37 📉
(Org: 33)
(8,849)
0.1 8,849
38 📈
(Org: 49)
(8,772)
0.39 8,772
39 📉
(Org: 34)
(8,281)
0.04 8,281
40 📈
(Org: 70)
(7,903)
0.44 7,903
41 📈
(Org: 51)
(7,793)
0.33 7,793
42 📉
(Org: 37)
(7,658)
0.04 7,658
43 📉
(Org: 41)
(7,627)
0.17 7,627
44 📈
(Org: 80)
(7,579)
0.51 7,579
45 📉
(Org: 38)
(7,084)
0.04 7,084
46 📉
(Org: 40)
(6,810)
0.03 6,810
47 📈
(Org: 69)
(6,721)
0.34 6,721
48 📈
(Org: 87)
(6,611)
0.47 6,611
49 📉
(Org: 48)
(6,484)
0.15 6,484
50 📉
(Org: 42)
(6,427)
0.1 6,427
51 📉
(Org: 47)
(6,234)
0.11 6,234
52 📉
(Org: 45)
(5,792)
0.03 5,792
53 📉
(Org: 46)
(5,760)
0.03 5,760
54 📉
(Org: 44)
(5,683)
0.01 5,683
55 📈
(Org: 65)
(5,476)
0.18 5,476
56 📉
(Org: 53)
(5,223)
0.04 5,223
57 📉
(Org: 52)
(5,215)
0 5,215
58 📉
(Org: 54)
(5,106)
0.03 5,106
59 📈
(Org: 63)
(5,049)
0.11 5,049
60 📉
(Org: 55)
(5,028)
0.02 5,028
61 📈
(Org: 71)
(4,985)
0.13 4,985
62 📈
(Org: 64)
(4,946)
0.09 4,946
63 📈
(Org: 67)
(4,895)
0.09 4,895
64 📉
(Org: 57)
(4,759)
0.01 4,759
65 📈
(Org: 95)
(4,733)
0.32 4,733
66 📉
(Org: 58)
(4,730)
0.01 4,730
67 📉
(Org: 59)
(4,679)
0 4,679
68 ➡️
(Org: 68)
(4,613)
0.04 4,613
69 📉
(Org: 66)
(4,479)
0 4,479
70 📈
(Org: 79)
(4,404)
0.15 4,404
71 📈
(Org: 75)
(4,216)
0.03 4,216
72 📈
(Org: 76)
(4,140)
0.02 4,140
73 📈
(Org: 81)
(4,112)
0.1 4,112
74 📈
(Org: 77)
(4,072)
0.02 4,072
75 📈
(Org: 128)
(3,971)
0.44 3,971
76 📈
(Org: 84)
(3,936)
0.07 3,936
77 📈
(Org: 120)
(3,913)
0.33 3,913
78 📈
(Org: 83)
(3,821)
0.04 3,821
79 📈
(Org: 85)
(3,819)
0.08 3,819
80 📈
(Org: 82)
(3,805)
0.03 3,805
81 📈
(Org: 140)
(3,730)
0.47 3,730
82 📈
(Org: 125)
(3,709)
0.38 3,709
83 📈
(Org: 98)
(3,705)
0.17 3,705
84 📈
(Org: 96)
(3,669)
0.15 3,669
85 📈
(Org: 94)
(3,653)
0.12 3,653
86 📈
(Org: 88)
(3,649)
0.05 3,649
87 📈
(Org: 130)
(3,564)
0.38 3,564
88 📈
(Org: 228)
(3,520)
0.67 3,520
89 📉
(Org: 86)
(3,495)
- 3,495
90 📈
(Org: 113)
(3,477)
0.21 3,477
91 📈
(Org: 99)
(3,469)
0.14 3,469
92 📈
(Org: 116)
(3,464)
0.21 3,464
93 📉
(Org: 90)
(3,419)
0.02 3,419
94 📉
(Org: 89)
(3,418)
0 3,418
95 📈
(Org: 144)
(3,322)
0.41 3,322
96 📉
(Org: 92)
(3,277)
0 3,277
97 📉
(Org: 93)
(3,225)
- 3,225
98 📈
(Org: 223)
(3,096)
0.62 3,096
99 📉
(Org: 97)
(3,086)
- 3,086
100 📈
(Org: 234)
(3,064)
0.64 3,064