Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1960 - 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

Boy Names

Ranking Name Distortion Index Count
1 📈
(Org: 2)
(88,442)
0.05 88,442
2 📉
(Org: 1)
(85,924)
0 85,924
3 📈
(Org: 4)
(80,517)
0.06 80,517
4 📉
(Org: 3)
(76,822)
0 76,822
5 ➡️
(Org: 5)
(72,368)
0 72,368
6 ➡️
(Org: 6)
(61,314)
0.04 61,314
7 📈
(Org: 10)
(50,143)
0.32 50,143
8 📉
(Org: 7)
(49,389)
0 49,389
9 📉
(Org: 8)
(43,567)
0 43,567
10 📉
(Org: 9)
(39,476)
0.01 39,476
11 📈
(Org: 14)
(37,993)
0.24 37,993
12 📉
(Org: 11)
(30,518)
0 30,518
13 📉
(Org: 12)
(30,047)
0.01 30,047
14 📉
(Org: 13)
(29,691)
0 29,691
15 ➡️
(Org: 15)
(28,539)
0.01 28,539
16 ➡️
(Org: 16)
(27,727)
0 27,727
17 📈
(Org: 20)
(27,169)
0.19 27,169
18 📉
(Org: 17)
(26,191)
0.01 26,191
19 📉
(Org: 18)
(25,650)
0 25,650
20 📉
(Org: 19)
(22,734)
- 22,734
21 📈
(Org: 23)
(22,094)
0.02 22,094
22 📉
(Org: 21)
(21,739)
0 21,739
23 📉
(Org: 22)
(21,738)
0 21,738
24 ➡️
(Org: 24)
(20,399)
0 20,399
25 ➡️
(Org: 25)
(19,504)
0 19,504
26 ➡️
(Org: 26)
(16,597)
0 16,597
27 📈
(Org: 28)
(16,050)
0 16,050
28 📈
(Org: 29)
(15,571)
0.01 15,571
29 📈
(Org: 30)
(15,241)
0.01 15,241
30 📈
(Org: 31)
(14,679)
0.03 14,679
31 📈
(Org: 32)
(14,322)
0.01 14,322
32 📈
(Org: 38)
(14,168)
0.22 14,168
33 ➡️
(Org: 33)
(14,105)
0 14,105
34 ➡️
(Org: 34)
(13,991)
0 13,991
35 📈
(Org: 37)
(12,302)
0.04 12,302
36 📉
(Org: 35)
(12,234)
0 12,234
37 📉
(Org: 36)
(12,041)
- 12,041
38 📈
(Org: 66)
(11,608)
0.48 11,608
39 📈
(Org: 44)
(11,179)
0.06 11,179
40 📉
(Org: 39)
(10,966)
- 10,966
41 ➡️
(Org: 41)
(10,916)
0.02 10,916
42 📉
(Org: 40)
(10,757)
0 10,757
43 📉
(Org: 42)
(10,721)
0 10,721
44 📉
(Org: 43)
(10,646)
- 10,646
45 📈
(Org: 53)
(10,474)
0.25 10,474
46 📉
(Org: 45)
(10,372)
0 10,372
47 📉
(Org: 46)
(9,740)
0 9,740
48 📉
(Org: 47)
(9,497)
0.05 9,497
49 📉
(Org: 48)
(8,808)
0.02 8,808
50 📉
(Org: 49)
(8,584)
0.01 8,584
51 📈
(Org: 59)
(8,457)
0.15 8,457
52 📉
(Org: 50)
(8,357)
- 8,357
53 📉
(Org: 52)
(8,216)
0.03 8,216
54 📉
(Org: 51)
(8,202)
- 8,202
55 📈
(Org: 74)
(8,006)
0.3 8,006
56 ➡️
(Org: 56)
(7,701)
0.03 7,701
57 📉
(Org: 54)
(7,690)
0 7,690
58 📉
(Org: 57)
(7,353)
0.01 7,353
59 📈
(Org: 61)
(7,269)
0.05 7,269
60 📉
(Org: 58)
(7,195)
0 7,195
61 📈
(Org: 69)
(7,151)
0.19 7,151
62 📈
(Org: 63)
(7,146)
0.09 7,146
63 📈
(Org: 64)
(7,092)
0.1 7,092
64 📉
(Org: 62)
(6,989)
0.06 6,989
65 📈
(Org: 87)
(6,984)
0.3 6,984
66 📉
(Org: 60)
(6,961)
0 6,961
67 📈
(Org: 83)
(6,820)
0.25 6,820
68 📈
(Org: 96)
(6,339)
0.3 6,339
69 📉
(Org: 65)
(6,309)
0.02 6,309
70 📉
(Org: 67)
(6,217)
0.03 6,217
71 📉
(Org: 68)
(5,875)
0 5,875
72 📈
(Org: 73)
(5,851)
0.03 5,851
73 📉
(Org: 70)
(5,766)
- 5,766
74 📉
(Org: 72)
(5,758)
0 5,758
75 📉
(Org: 71)
(5,750)
- 5,750
76 📈
(Org: 79)
(5,662)
0.05 5,662
77 📉
(Org: 75)
(5,555)
0 5,555
78 📉
(Org: 77)
(5,510)
0 5,510
79 📉
(Org: 78)
(5,401)
0 5,401
80 📈
(Org: 81)
(5,309)
0.01 5,309
81 📉
(Org: 80)
(5,301)
0.01 5,301
82 ➡️
(Org: 82)
(5,229)
0.01 5,229
83 📈
(Org: 84)
(4,998)
0.01 4,998
84 📈
(Org: 85)
(4,966)
0.01 4,966
85 📈
(Org: 86)
(4,914)
0 4,914
86 📈
(Org: 104)
(4,907)
0.15 4,907
87 📈
(Org: 90)
(4,867)
0.03 4,867
88 📈
(Org: 91)
(4,796)
0.02 4,796
89 ➡️
(Org: 89)
(4,780)
0 4,780
90 📈
(Org: 92)
(4,685)
0 4,685
91 📈
(Org: 93)
(4,602)
- 4,602
92 📈
(Org: 94)
(4,543)
0.01 4,543
93 📈
(Org: 114)
(4,506)
0.23 4,506
94 📈
(Org: 95)
(4,500)
- 4,500
95 📈
(Org: 106)
(4,462)
0.08 4,462
96 📈
(Org: 102)
(4,408)
0.05 4,408
97 📈
(Org: 99)
(4,382)
0 4,382
98 ➡️
(Org: 98)
(4,372)
- 4,372
99 📈
(Org: 101)
(4,265)
0.01 4,265
100 ➡️
(Org: 100)
(4,234)
0 4,234