Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1971 - 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)
(57,947)
0.02 57,947
2 ➡️
(Org: 2)
(41,543)
0.2 41,543
3 📈
(Org: 4)
(33,310)
0.08 33,310
4 📉
(Org: 3)
(33,281)
0.01 33,281
5 ➡️
(Org: 5)
(26,237)
- 26,237
6 📈
(Org: 18)
(26,221)
0.48 26,221
7 📉
(Org: 6)
(26,063)
0.01 26,063
8 📉
(Org: 7)
(24,805)
0.04 24,805
9 📈
(Org: 13)
(24,560)
0.42 24,560
10 📈
(Org: 32)
(20,428)
0.55 20,428
11 📉
(Org: 8)
(20,090)
0.12 20,090
12 📈
(Org: 17)
(18,500)
0.25 18,500
13 📈
(Org: 22)
(17,980)
0.3 17,980
14 📈
(Org: 25)
(17,687)
0.33 17,687
15 📉
(Org: 9)
(16,956)
0.01 16,956
16 📉
(Org: 11)
(16,904)
0.1 16,904
17 📉
(Org: 10)
(15,655)
0.02 15,655
18 📉
(Org: 12)
(15,037)
0 15,037
19 📉
(Org: 16)
(14,970)
0.07 14,970
20 📈
(Org: 65)
(14,957)
0.64 14,957
21 📉
(Org: 14)
(14,428)
0.01 14,428
22 📉
(Org: 15)
(14,423)
0.01 14,423
23 📈
(Org: 34)
(14,338)
0.4 14,338
24 📉
(Org: 19)
(14,079)
0.03 14,079
25 📈
(Org: 30)
(13,826)
0.28 13,826
26 📈
(Org: 88)
(13,790)
0.71 13,790
27 📉
(Org: 20)
(13,428)
0.01 13,428
28 📉
(Org: 23)
(12,969)
0.06 12,969
29 📉
(Org: 21)
(12,926)
0.02 12,926
30 📉
(Org: 27)
(12,308)
0.15 12,308
31 📉
(Org: 24)
(12,262)
0.01 12,262
32 📉
(Org: 26)
(11,486)
0 11,486
33 📉
(Org: 29)
(11,085)
0.09 11,085
34 📉
(Org: 28)
(10,335)
0.02 10,335
35 📉
(Org: 31)
(9,923)
0.02 9,923
36 📉
(Org: 33)
(9,078)
0.04 9,078
37 📈
(Org: 58)
(9,055)
0.35 9,055
38 📉
(Org: 35)
(8,488)
0 8,488
39 📉
(Org: 38)
(8,300)
0.03 8,300
40 📉
(Org: 36)
(8,258)
0 8,258
41 📉
(Org: 37)
(8,210)
0.01 8,210
42 ➡️
(Org: 42)
(8,081)
0.09 8,081
43 📈
(Org: 51)
(7,919)
0.22 7,919
44 📈
(Org: 46)
(7,864)
0.15 7,864
45 📉
(Org: 40)
(7,793)
0.03 7,793
46 📈
(Org: 55)
(7,723)
0.23 7,723
47 📈
(Org: 50)
(7,587)
0.17 7,587
48 📈
(Org: 54)
(7,210)
0.15 7,210
49 📉
(Org: 44)
(7,205)
0.04 7,205
50 📉
(Org: 43)
(7,161)
- 7,161
51 📈
(Org: 91)
(6,997)
0.45 6,997
52 📈
(Org: 94)
(6,919)
0.45 6,919
53 📉
(Org: 45)
(6,897)
- 6,897
54 📉
(Org: 53)
(6,840)
0.1 6,840
55 📈
(Org: 108)
(6,693)
0.48 6,693
56 📉
(Org: 48)
(6,629)
0.03 6,629
57 📉
(Org: 47)
(6,464)
0 6,464
58 📉
(Org: 49)
(6,450)
0.02 6,450
59 📉
(Org: 52)
(6,358)
0.02 6,358
60 📈
(Org: 62)
(6,163)
0.12 6,163
61 📉
(Org: 57)
(6,048)
0.02 6,048
62 📈
(Org: 68)
(6,025)
0.15 6,025
63 📈
(Org: 75)
(6,001)
0.2 6,001
64 📉
(Org: 60)
(5,950)
0.07 5,950
65 📉
(Org: 56)
(5,939)
- 5,939
66 📈
(Org: 79)
(5,889)
0.23 5,889
67 📉
(Org: 59)
(5,750)
0 5,750
68 📈
(Org: 119)
(5,682)
0.47 5,682
69 ➡️
(Org: 69)
(5,627)
0.13 5,627
70 📈
(Org: 115)
(5,603)
0.43 5,603
71 📈
(Org: 76)
(5,438)
0.13 5,438
72 📉
(Org: 64)
(5,405)
0.01 5,405
73 📉
(Org: 63)
(5,386)
0 5,386
74 📉
(Org: 70)
(5,342)
0.08 5,342
75 📉
(Org: 66)
(5,339)
0.04 5,339
76 📈
(Org: 145)
(5,258)
0.58 5,258
77 📈
(Org: 107)
(4,973)
0.28 4,973
78 📈
(Org: 151)
(4,967)
0.57 4,967
79 📉
(Org: 72)
(4,865)
0 4,865
80 📉
(Org: 77)
(4,842)
0.03 4,842
81 📉
(Org: 73)
(4,830)
- 4,830
82 📈
(Org: 95)
(4,751)
0.2 4,751
83 📉
(Org: 78)
(4,558)
- 4,558
84 📉
(Org: 80)
(4,553)
0.01 4,553
85 📈
(Org: 103)
(4,467)
0.19 4,467
86 📈
(Org: 109)
(4,402)
0.21 4,402
87 📈
(Org: 156)
(4,372)
0.54 4,372
88 📉
(Org: 81)
(4,333)
- 4,333
89 📈
(Org: 92)
(4,269)
0.1 4,269
90 📉
(Org: 82)
(4,227)
0 4,227
91 📈
(Org: 99)
(4,215)
0.12 4,215
92 📉
(Org: 83)
(4,209)
- 4,209
93 📉
(Org: 85)
(4,153)
0.02 4,153
94 📉
(Org: 84)
(4,130)
- 4,130
95 📈
(Org: 188)
(4,125)
0.6 4,125
96 📉
(Org: 86)
(4,066)
0.02 4,066
97 📈
(Org: 105)
(4,005)
0.1 4,005
98 📉
(Org: 93)
(3,984)
0.03 3,984
99 📈
(Org: 112)
(3,935)
0.14 3,935
100 📈
(Org: 134)
(3,908)
0.38 3,908