Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1963 - 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)
(56,642)
0.01 56,642
2 ➡️
(Org: 2)
(42,073)
0.01 42,073
3 ➡️
(Org: 3)
(41,880)
0.19 41,880
4 📈
(Org: 8)
(37,042)
0.35 37,042
5 📉
(Org: 4)
(32,864)
0.01 32,864
6 📈
(Org: 18)
(29,474)
0.39 29,474
7 📉
(Org: 5)
(29,356)
0.06 29,356
8 📉
(Org: 6)
(25,859)
0.02 25,859
9 📉
(Org: 7)
(25,381)
0 25,381
10 📈
(Org: 12)
(24,186)
0.12 24,186
11 ➡️
(Org: 11)
(23,471)
0.1 23,471
12 📈
(Org: 13)
(22,371)
0.06 22,371
13 📈
(Org: 26)
(22,179)
0.35 22,179
14 📉
(Org: 9)
(21,994)
0.02 21,994
15 📉
(Org: 10)
(21,698)
0.01 21,698
16 📉
(Org: 14)
(20,935)
0.02 20,935
17 📉
(Org: 16)
(20,154)
0.08 20,154
18 📈
(Org: 34)
(19,756)
0.38 19,756
19 📉
(Org: 15)
(19,608)
- 19,608
20 📈
(Org: 53)
(19,449)
0.57 19,449
21 📈
(Org: 24)
(18,411)
0.18 18,411
22 📉
(Org: 17)
(18,315)
0 18,315
23 📉
(Org: 20)
(18,135)
0.03 18,135
24 📉
(Org: 19)
(18,106)
0.02 18,106
25 📈
(Org: 29)
(18,059)
0.26 18,059
26 📉
(Org: 21)
(17,593)
0.01 17,593
27 📈
(Org: 32)
(16,806)
0.25 16,806
28 📉
(Org: 25)
(16,647)
0.13 16,647
29 📉
(Org: 22)
(16,642)
0.02 16,642
30 📉
(Org: 23)
(16,480)
0.01 16,480
31 📈
(Org: 48)
(15,267)
0.41 15,267
32 📉
(Org: 28)
(14,586)
0.07 14,586
33 📉
(Org: 27)
(14,156)
0 14,156
34 📈
(Org: 58)
(14,126)
0.45 14,126
35 📉
(Org: 33)
(13,761)
0.09 13,761
36 📉
(Org: 30)
(13,329)
0 13,329
37 📉
(Org: 31)
(13,195)
- 13,195
38 📉
(Org: 35)
(12,363)
0.02 12,363
39 📉
(Org: 36)
(12,143)
0.03 12,143
40 📉
(Org: 37)
(11,795)
0.06 11,795
41 📉
(Org: 40)
(11,360)
0.06 11,360
42 📈
(Org: 95)
(11,257)
0.59 11,257
43 📉
(Org: 41)
(11,247)
0.07 11,247
44 📈
(Org: 45)
(11,070)
0.15 11,070
45 📉
(Org: 39)
(10,681)
- 10,681
46 📈
(Org: 51)
(10,331)
0.17 10,331
47 📈
(Org: 100)
(10,315)
0.58 10,315
48 📉
(Org: 42)
(10,170)
0 10,170
49 📉
(Org: 43)
(9,874)
0 9,874
50 📉
(Org: 44)
(9,745)
0.04 9,745
51 📉
(Org: 49)
(9,463)
0.04 9,463
52 📉
(Org: 46)
(9,409)
0.01 9,409
53 📉
(Org: 50)
(8,706)
- 8,706
54 📉
(Org: 52)
(8,524)
0.01 8,524
55 ➡️
(Org: 55)
(8,324)
0.02 8,324
56 📈
(Org: 73)
(8,278)
0.3 8,278
57 📉
(Org: 56)
(8,250)
0.02 8,250
58 📉
(Org: 54)
(8,228)
- 8,228
59 📉
(Org: 57)
(7,975)
- 7,975
60 ➡️
(Org: 60)
(7,738)
0.05 7,738
61 ➡️
(Org: 61)
(7,656)
0.04 7,656
62 📈
(Org: 127)
(7,520)
0.56 7,520
63 📈
(Org: 64)
(7,331)
0.07 7,331
64 📉
(Org: 62)
(7,319)
0 7,319
65 📈
(Org: 82)
(7,272)
0.28 7,272
66 📉
(Org: 63)
(7,072)
- 7,072
67 📈
(Org: 94)
(7,057)
0.35 7,057
68 📈
(Org: 136)
(6,763)
0.54 6,763
69 📈
(Org: 79)
(6,723)
0.21 6,723
70 📉
(Org: 66)
(6,709)
0 6,709
71 📉
(Org: 70)
(6,571)
0.07 6,571
72 📈
(Org: 75)
(6,546)
0.12 6,546
73 📉
(Org: 68)
(6,335)
0.01 6,335
74 📉
(Org: 72)
(6,268)
0.07 6,268
75 📉
(Org: 69)
(6,210)
0.01 6,210
76 📉
(Org: 71)
(6,098)
0.01 6,098
77 📉
(Org: 74)
(5,776)
- 5,776
78 📉
(Org: 76)
(5,649)
0.01 5,649
79 📈
(Org: 106)
(5,565)
0.26 5,565
80 📉
(Org: 77)
(5,477)
0 5,477
81 📉
(Org: 78)
(5,457)
- 5,457
82 📈
(Org: 85)
(5,436)
0.05 5,436
83 ➡️
(Org: 83)
(5,427)
0.04 5,427
84 📈
(Org: 86)
(5,353)
0.04 5,353
85 📉
(Org: 80)
(5,329)
- 5,329
86 📉
(Org: 81)
(5,323)
0.01 5,323
87 📈
(Org: 88)
(5,287)
0.05 5,287
88 📉
(Org: 84)
(5,221)
- 5,221
89 📈
(Org: 107)
(5,099)
0.21 5,099
90 📉
(Org: 89)
(5,017)
0 5,017
91 📈
(Org: 232)
(4,987)
0.72 4,987
92 📈
(Org: 141)
(4,967)
0.41 4,967
93 📈
(Org: 98)
(4,966)
0.1 4,966
94 📉
(Org: 90)
(4,886)
- 4,886
95 📉
(Org: 91)
(4,743)
- 4,743
96 📉
(Org: 92)
(4,717)
0 4,717
97 📈
(Org: 133)
(4,676)
0.33 4,676
98 📈
(Org: 117)
(4,550)
0.17 4,550
99 📉
(Org: 96)
(4,536)
- 4,536
100 📉
(Org: 97)
(4,527)
0.01 4,527