Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1970 - 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)
(47,201)
0.02 47,201
2 📈
(Org: 4)
(44,612)
0.24 44,612
3 📉
(Org: 2)
(39,325)
0.01 39,325
4 📉
(Org: 3)
(37,093)
0.08 37,093
5 📈
(Org: 10)
(31,072)
0.41 31,072
6 📈
(Org: 14)
(30,593)
0.47 30,593
7 📉
(Org: 5)
(25,213)
- 25,213
8 📉
(Org: 6)
(25,088)
0.01 25,088
9 📉
(Org: 7)
(24,619)
0.04 24,619
10 📉
(Org: 8)
(22,376)
0.12 22,376
11 📈
(Org: 20)
(21,892)
0.33 21,892
12 📈
(Org: 15)
(20,985)
0.25 20,985
13 📈
(Org: 23)
(20,163)
0.33 20,163
14 📉
(Org: 9)
(19,531)
0.02 19,531
15 📈
(Org: 42)
(18,182)
0.57 18,182
16 📉
(Org: 13)
(17,720)
0.07 17,720
17 📉
(Org: 11)
(17,574)
0.02 17,574
18 📉
(Org: 17)
(17,352)
0.11 17,352
19 📉
(Org: 12)
(16,958)
0.02 16,958
20 📈
(Org: 59)
(16,455)
0.64 16,455
21 📈
(Org: 34)
(16,404)
0.41 16,404
22 📉
(Org: 16)
(15,835)
0.01 15,835
23 📉
(Org: 18)
(15,615)
0.03 15,615
24 📉
(Org: 19)
(14,690)
0 14,690
25 📉
(Org: 21)
(13,982)
0.01 13,982
26 📉
(Org: 22)
(13,844)
0.02 13,844
27 📉
(Org: 24)
(13,428)
0 13,428
28 📈
(Org: 35)
(13,405)
0.28 13,405
29 📉
(Org: 26)
(13,140)
0.02 13,140
30 📉
(Org: 25)
(13,045)
0.01 13,045
31 📈
(Org: 105)
(13,012)
0.71 13,012
32 📉
(Org: 30)
(12,532)
0.15 12,532
33 📉
(Org: 28)
(12,150)
0.09 12,150
34 📉
(Org: 27)
(11,502)
0.02 11,502
35 📉
(Org: 29)
(11,472)
0.05 11,472
36 📉
(Org: 33)
(10,351)
0.05 10,351
37 📉
(Org: 32)
(10,315)
0.03 10,315
38 ➡️
(Org: 38)
(9,596)
0.09 9,596
39 📉
(Org: 37)
(9,517)
0.04 9,517
40 📉
(Org: 36)
(9,367)
0 9,367
41 📈
(Org: 44)
(9,014)
0.17 9,014
42 📈
(Org: 51)
(8,837)
0.21 8,837
43 📈
(Org: 46)
(8,781)
0.16 8,781
44 📉
(Org: 39)
(8,744)
0.01 8,744
45 📈
(Org: 65)
(8,674)
0.35 8,674
46 📈
(Org: 77)
(8,342)
0.42 8,342
47 📉
(Org: 40)
(8,336)
- 8,336
48 📉
(Org: 45)
(8,175)
0.09 8,175
49 📉
(Org: 41)
(8,035)
0 8,035
50 📉
(Org: 43)
(7,708)
- 7,708
51 📈
(Org: 95)
(7,523)
0.44 7,523
52 📉
(Org: 47)
(7,338)
0.02 7,338
53 📉
(Org: 50)
(7,215)
0.02 7,215
54 📈
(Org: 58)
(7,158)
0.16 7,158
55 📉
(Org: 49)
(7,140)
- 7,140
56 📈
(Org: 66)
(6,983)
0.2 6,983
57 📉
(Org: 52)
(6,839)
0 6,839
58 📉
(Org: 54)
(6,654)
0.04 6,654
59 📈
(Org: 61)
(6,634)
0.11 6,634
60 📈
(Org: 64)
(6,426)
0.13 6,426
61 📈
(Org: 73)
(6,409)
0.22 6,409
62 📉
(Org: 56)
(6,348)
0.03 6,348
63 📉
(Org: 60)
(6,305)
0.06 6,305
64 📉
(Org: 57)
(6,067)
0 6,067
65 📈
(Org: 113)
(6,011)
0.43 6,011
66 📈
(Org: 94)
(5,848)
0.28 5,848
67 📉
(Org: 62)
(5,740)
- 5,740
68 📈
(Org: 74)
(5,615)
0.12 5,615
69 📈
(Org: 71)
(5,572)
0.09 5,572
70 📈
(Org: 140)
(5,556)
0.57 5,556
71 📈
(Org: 72)
(5,490)
0.08 5,490
72 📈
(Org: 134)
(5,467)
0.52 5,467
73 📉
(Org: 69)
(5,423)
0.02 5,423
74 📈
(Org: 129)
(5,421)
0.49 5,421
75 📈
(Org: 90)
(5,401)
0.2 5,401
76 📉
(Org: 68)
(5,373)
- 5,373
77 📉
(Org: 70)
(5,186)
- 5,186
78 📈
(Org: 207)
(5,166)
0.7 5,166
79 📉
(Org: 75)
(4,937)
- 4,937
80 📈
(Org: 101)
(4,905)
0.22 4,905
81 📈
(Org: 170)
(4,889)
0.6 4,889
82 📉
(Org: 76)
(4,862)
- 4,862
83 📉
(Org: 80)
(4,778)
0.02 4,778
84 📉
(Org: 79)
(4,769)
0.01 4,769
85 📈
(Org: 133)
(4,754)
0.45 4,754
86 📉
(Org: 81)
(4,743)
0.02 4,743
87 📉
(Org: 78)
(4,729)
- 4,729
88 📈
(Org: 96)
(4,694)
0.11 4,694
89 📉
(Org: 84)
(4,630)
0.02 4,630
90 📉
(Org: 82)
(4,602)
- 4,602
91 📈
(Org: 103)
(4,566)
0.18 4,566
92 📉
(Org: 91)
(4,503)
0.04 4,503
93 📉
(Org: 85)
(4,489)
0.01 4,489
94 📈
(Org: 99)
(4,488)
0.11 4,488
95 📉
(Org: 86)
(4,450)
0 4,450
96 📈
(Org: 176)
(4,440)
0.59 4,440
97 📉
(Org: 89)
(4,396)
0.01 4,396
98 📉
(Org: 93)
(4,323)
0.02 4,323
99 📉
(Org: 92)
(4,266)
0 4,266
100 📉
(Org: 97)
(4,160)
0.01 4,160