Top 100 Most Popular Girl Baby Names by Pronunciation in the US 1945 - 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)
(59,645)
0.01 59,645
2 ➡️
(Org: 2)
(43,963)
0.06 43,963
3 ➡️
(Org: 3)
(38,280)
0 38,280
4 ➡️
(Org: 4)
(35,853)
0 35,853
5 ➡️
(Org: 5)
(35,622)
0.15 35,622
6 ➡️
(Org: 6)
(25,319)
0.02 25,319
7 📈
(Org: 10)
(23,815)
0.19 23,815
8 📉
(Org: 7)
(21,689)
0.01 21,689
9 📉
(Org: 8)
(21,484)
0.03 21,484
10 📈
(Org: 11)
(20,413)
0.1 20,413
11 📉
(Org: 9)
(20,265)
0 20,265
12 📈
(Org: 25)
(18,558)
0.44 18,558
13 ➡️
(Org: 13)
(17,857)
0.05 17,857
14 📉
(Org: 12)
(17,499)
0.01 17,499
15 📉
(Org: 14)
(16,182)
0 16,182
16 ➡️
(Org: 16)
(15,925)
0.02 15,925
17 📉
(Org: 15)
(15,894)
0.01 15,894
18 📉
(Org: 17)
(15,727)
0.02 15,727
19 ➡️
(Org: 19)
(14,293)
0.03 14,293
20 📉
(Org: 18)
(13,972)
0 13,972
21 📈
(Org: 50)
(13,301)
0.62 13,301
22 📉
(Org: 20)
(12,740)
0.03 12,740
23 📉
(Org: 21)
(12,360)
0 12,360
24 📉
(Org: 22)
(12,223)
- 12,223
25 📉
(Org: 23)
(11,037)
- 11,037
26 📉
(Org: 24)
(10,782)
- 10,782
27 📉
(Org: 26)
(10,539)
0.02 10,539
28 📉
(Org: 27)
(9,968)
0.04 9,968
29 📈
(Org: 32)
(9,461)
0.14 9,461
30 📉
(Org: 28)
(9,266)
0 9,266
31 📉
(Org: 29)
(9,204)
- 9,204
32 📉
(Org: 31)
(8,846)
0.06 8,846
33 📉
(Org: 30)
(8,757)
0 8,757
34 ➡️
(Org: 34)
(8,198)
0.03 8,198
35 📉
(Org: 33)
(8,060)
0 8,060
35 📈
(Org: 36)
(8,060)
0.05 8,060
37 📉
(Org: 35)
(7,871)
0.02 7,871
38 📉
(Org: 37)
(7,687)
0.01 7,687
39 📉
(Org: 38)
(7,581)
0.02 7,581
40 📉
(Org: 39)
(7,038)
- 7,038
41 📈
(Org: 52)
(6,823)
0.29 6,823
42 📈
(Org: 70)
(6,765)
0.46 6,765
43 📉
(Org: 40)
(6,725)
0.03 6,725
44 📉
(Org: 41)
(6,359)
- 6,359
45 📉
(Org: 42)
(6,327)
0.02 6,327
46 📉
(Org: 43)
(6,053)
0 6,053
47 📉
(Org: 45)
(6,038)
0.03 6,038
48 📉
(Org: 44)
(5,997)
0.02 5,997
49 📉
(Org: 46)
(5,890)
0.01 5,890
50 📈
(Org: 76)
(5,396)
0.33 5,396
51 📉
(Org: 47)
(5,378)
0.01 5,378
52 📉
(Org: 48)
(5,292)
0.03 5,292
53 📈
(Org: 63)
(5,286)
0.25 5,286
54 📉
(Org: 49)
(5,184)
0.02 5,184
55 📈
(Org: 56)
(4,721)
0.05 4,721
56 📈
(Org: 62)
(4,585)
0.11 4,585
57 📉
(Org: 54)
(4,557)
- 4,557
58 📉
(Org: 55)
(4,540)
0 4,540
59 📈
(Org: 64)
(4,487)
0.11 4,487
60 📈
(Org: 72)
(4,482)
0.19 4,482
61 📉
(Org: 57)
(4,457)
0.02 4,457
62 📉
(Org: 60)
(4,417)
0.04 4,417
63 📈
(Org: 102)
(4,414)
0.38 4,414
64 📉
(Org: 59)
(4,402)
0.03 4,402
65 📈
(Org: 79)
(4,395)
0.2 4,395
66 📉
(Org: 58)
(4,327)
0.01 4,327
67 📈
(Org: 96)
(4,284)
0.32 4,284
68 📉
(Org: 61)
(4,224)
0.01 4,224
69 📈
(Org: 101)
(4,222)
0.35 4,222
70 📉
(Org: 66)
(3,926)
0 3,926
71 ➡️
(Org: 71)
(3,907)
0.07 3,907
72 📈
(Org: 77)
(3,874)
0.07 3,874
73 📉
(Org: 67)
(3,807)
0 3,807
74 📈
(Org: 117)
(3,746)
0.4 3,746
75 📉
(Org: 69)
(3,739)
- 3,739
76 📉
(Org: 74)
(3,629)
0.01 3,629
77 📉
(Org: 75)
(3,607)
0 3,607
77 📉
(Org: 73)
(3,607)
- 3,607
79 📉
(Org: 78)
(3,532)
0.01 3,532
80 📈
(Org: 91)
(3,531)
0.13 3,531
81 📈
(Org: 87)
(3,496)
0.08 3,496
82 📈
(Org: 83)
(3,433)
0.02 3,433
83 📈
(Org: 85)
(3,414)
0.02 3,414
84 📉
(Org: 81)
(3,407)
- 3,407
85 📉
(Org: 84)
(3,350)
- 3,350
86 ➡️
(Org: 86)
(3,327)
0 3,327
87 📈
(Org: 88)
(3,216)
0 3,216
88 📈
(Org: 89)
(3,178)
- 3,178
89 📈
(Org: 90)
(3,136)
0 3,136
90 📈
(Org: 95)
(3,030)
0.04 3,030
91 📈
(Org: 94)
(3,012)
0.03 3,012
92 ➡️
(Org: 92)
(2,974)
0 2,974
93 📈
(Org: 114)
(2,973)
0.2 2,973
94 📉
(Org: 93)
(2,960)
- 2,960
95 📈
(Org: 99)
(2,950)
0.06 2,950
96 📈
(Org: 98)
(2,885)
0.01 2,885
97 📈
(Org: 122)
(2,849)
0.28 2,849
98 📈
(Org: 107)
(2,838)
0.06 2,838
99 📈
(Org: 104)
(2,833)
0.06 2,833
100 ➡️
(Org: 100)
(2,768)
- 2,768