Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1976 - 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)
(60,683)
0.02 60,683
2 ➡️
(Org: 2)
(31,339)
- 31,339
3 ➡️
(Org: 3)
(25,996)
0.03 25,996
4 ➡️
(Org: 4)
(24,208)
0 24,208
5 📈
(Org: 6)
(24,162)
0.19 24,162
6 📉
(Org: 5)
(22,173)
0.01 22,173
7 📈
(Org: 15)
(22,048)
0.37 22,048
8 📉
(Org: 7)
(20,332)
0.07 20,332
9 📉
(Org: 8)
(18,606)
0.01 18,606
10 📈
(Org: 14)
(18,178)
0.23 18,178
11 📉
(Org: 9)
(17,587)
0.01 17,587
12 📈
(Org: 26)
(17,414)
0.53 17,414
13 ➡️
(Org: 13)
(17,001)
0.15 17,001
14 📉
(Org: 11)
(16,802)
0.1 16,802
15 📈
(Org: 19)
(16,173)
0.27 16,173
16 📉
(Org: 12)
(16,062)
0.1 16,062
17 📉
(Org: 10)
(15,604)
0 15,604
18 📈
(Org: 60)
(14,817)
0.67 14,817
19 📈
(Org: 38)
(14,590)
0.55 14,590
20 📉
(Org: 18)
(14,244)
0.12 14,244
21 📉
(Org: 16)
(14,084)
0.04 14,084
22 📉
(Org: 17)
(13,611)
0.02 13,611
23 📈
(Org: 57)
(13,038)
0.61 13,038
24 📉
(Org: 20)
(11,917)
0.06 11,917
25 📈
(Org: 37)
(11,347)
0.4 11,347
26 📉
(Org: 21)
(11,002)
0.01 11,002
27 📉
(Org: 22)
(10,471)
0.01 10,471
28 📉
(Org: 23)
(10,235)
0.17 10,235
29 📉
(Org: 28)
(10,044)
0.2 10,044
30 📈
(Org: 55)
(9,797)
0.47 9,797
31 📈
(Org: 40)
(8,983)
0.29 8,983
32 📈
(Org: 47)
(8,860)
0.34 8,860
33 📈
(Org: 36)
(8,722)
0.2 8,722
34 📉
(Org: 24)
(8,586)
0.02 8,586
35 📉
(Org: 33)
(8,396)
0.12 8,396
36 📉
(Org: 25)
(8,352)
- 8,352
37 📉
(Org: 32)
(8,263)
0.09 8,263
38 📈
(Org: 54)
(8,198)
0.36 8,198
39 📉
(Org: 29)
(7,838)
- 7,838
40 📉
(Org: 30)
(7,761)
- 7,761
41 📉
(Org: 31)
(7,664)
0.02 7,664
42 📉
(Org: 34)
(7,560)
0.03 7,560
43 📈
(Org: 66)
(7,396)
0.45 7,396
44 📉
(Org: 41)
(7,244)
0.14 7,244
45 📉
(Org: 35)
(7,093)
0.01 7,093
46 📉
(Org: 39)
(7,056)
0.08 7,056
47 📈
(Org: 67)
(6,797)
0.41 6,797
48 📉
(Org: 46)
(6,624)
0.11 6,624
49 📉
(Org: 42)
(6,204)
0.03 6,204
50 📉
(Org: 45)
(6,196)
0.04 6,196
51 📉
(Org: 44)
(6,107)
0.02 6,107
52 📈
(Org: 56)
(6,097)
0.15 6,097
53 📉
(Org: 43)
(6,026)
0 6,026
54 📉
(Org: 48)
(5,812)
0.01 5,812
55 📉
(Org: 50)
(5,763)
0.04 5,763
56 📉
(Org: 49)
(5,657)
0 5,657
57 📉
(Org: 53)
(5,435)
0.04 5,435
58 📉
(Org: 52)
(5,300)
0 5,300
59 📈
(Org: 75)
(5,177)
0.3 5,177
60 📈
(Org: 102)
(5,154)
0.48 5,154
61 📈
(Org: 65)
(5,118)
0.16 5,118
62 📉
(Org: 59)
(4,966)
0.02 4,966
63 📉
(Org: 58)
(4,965)
- 4,965
64 📉
(Org: 61)
(4,819)
- 4,819
65 📈
(Org: 167)
(4,794)
0.69 4,794
66 📉
(Org: 62)
(4,652)
0.04 4,652
67 📉
(Org: 64)
(4,560)
0.03 4,560
68 📈
(Org: 71)
(4,236)
0.11 4,236
69 📈
(Org: 76)
(4,198)
0.14 4,198
70 📉
(Org: 68)
(4,088)
0.02 4,088
71 📈
(Org: 99)
(4,066)
0.27 4,066
72 📉
(Org: 69)
(4,002)
0 4,002
73 📉
(Org: 70)
(3,996)
0.03 3,996
74 📈
(Org: 100)
(3,792)
0.23 3,792
75 📈
(Org: 82)
(3,685)
0.08 3,685
76 📈
(Org: 80)
(3,655)
0.04 3,655
77 📈
(Org: 81)
(3,641)
0.05 3,641
78 ➡️
(Org: 78)
(3,598)
0 3,598
79 📈
(Org: 109)
(3,597)
0.33 3,597
80 📉
(Org: 77)
(3,587)
- 3,587
81 📈
(Org: 94)
(3,559)
0.15 3,559
82 📈
(Org: 90)
(3,440)
0.09 3,440
83 📈
(Org: 84)
(3,438)
0.02 3,438
84 📉
(Org: 83)
(3,400)
0 3,400
85 ➡️
(Org: 85)
(3,367)
0.01 3,367
86 📈
(Org: 87)
(3,355)
0.02 3,355
87 📉
(Org: 86)
(3,314)
- 3,314
88 📈
(Org: 138)
(3,256)
0.37 3,256
89 📈
(Org: 122)
(3,227)
0.3 3,227
90 📈
(Org: 96)
(3,178)
0.06 3,178
91 📈
(Org: 93)
(3,174)
0.04 3,174
92 📉
(Org: 91)
(3,148)
0.02 3,148
93 📈
(Org: 127)
(3,072)
0.29 3,072
94 📈
(Org: 95)
(3,065)
0.02 3,065
95 📉
(Org: 92)
(3,051)
0 3,051
96 📈
(Org: 107)
(2,985)
0.18 2,985
97 📈
(Org: 98)
(2,968)
- 2,968
98 📈
(Org: 105)
(2,967)
0.16 2,967
99 📈
(Org: 174)
(2,893)
0.49 2,893
100 📈
(Org: 186)
(2,886)
0.52 2,886