Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2016 - 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: 17)
(24,652)
0.54 24,652
2 📉
(Org: 1)
(19,270)
0 19,270
3 📉
(Org: 2)
(18,436)
0.01 18,436
4 📈
(Org: 16)
(17,255)
0.29 17,255
5 📈
(Org: 27)
(16,032)
0.37 16,032
6 📉
(Org: 4)
(15,903)
0.04 15,903
7 📉
(Org: 3)
(15,819)
0 15,819
8 📉
(Org: 5)
(14,957)
0 14,957
9 📉
(Org: 7)
(14,783)
0.02 14,783
10 📈
(Org: 14)
(14,761)
0.13 14,761
11 📉
(Org: 6)
(14,755)
0 14,755
12 📉
(Org: 8)
(14,562)
0.03 14,562
13 📉
(Org: 9)
(14,162)
0.01 14,162
14 📉
(Org: 10)
(13,917)
0 13,917
15 📈
(Org: 37)
(13,846)
0.37 13,846
16 📉
(Org: 11)
(13,458)
0 13,458
17 📉
(Org: 15)
(13,249)
0.04 13,249
18 📉
(Org: 12)
(13,118)
0 13,118
19 📉
(Org: 13)
(13,076)
0.01 13,076
20 📈
(Org: 26)
(12,379)
0.17 12,379
21 📈
(Org: 43)
(12,043)
0.34 12,043
22 📉
(Org: 18)
(11,397)
0.01 11,397
23 📉
(Org: 19)
(11,153)
0 11,153
24 📉
(Org: 20)
(11,015)
0 11,015
25 📉
(Org: 21)
(10,653)
0 10,653
26 📉
(Org: 22)
(10,496)
0.01 10,496
27 📈
(Org: 32)
(10,456)
0.07 10,456
28 ➡️
(Org: 28)
(10,445)
0.04 10,445
29 📈
(Org: 31)
(10,442)
0.06 10,442
30 📉
(Org: 25)
(10,428)
0.01 10,428
31 📉
(Org: 23)
(10,335)
0 10,335
32 📉
(Org: 24)
(10,312)
0 10,312
33 📈
(Org: 44)
(10,285)
0.22 10,285
34 📉
(Org: 29)
(10,095)
0.01 10,095
35 📈
(Org: 76)
(10,004)
0.48 10,004
36 ➡️
(Org: 36)
(9,913)
0.08 9,913
37 📉
(Org: 30)
(9,899)
- 9,899
38 📈
(Org: 101)
(9,831)
0.59 9,831
39 📈
(Org: 54)
(9,756)
0.28 9,756
40 📉
(Org: 33)
(9,617)
0 9,617
41 📉
(Org: 34)
(9,431)
- 9,431
42 📉
(Org: 35)
(9,287)
0 9,287
43 📈
(Org: 59)
(9,078)
0.28 9,078
44 📉
(Org: 38)
(8,769)
0.04 8,769
45 📈
(Org: 63)
(8,663)
0.33 8,663
46 📉
(Org: 39)
(8,476)
0.01 8,476
47 📈
(Org: 53)
(8,427)
0.16 8,427
48 📉
(Org: 40)
(8,336)
0.01 8,336
49 📈
(Org: 57)
(8,321)
0.18 8,321
50 📈
(Org: 56)
(8,257)
0.15 8,257
51 📉
(Org: 42)
(8,189)
0.01 8,189
52 📉
(Org: 47)
(7,807)
0.03 7,807
53 📉
(Org: 48)
(7,720)
0.05 7,720
54 📉
(Org: 45)
(7,675)
- 7,675
55 📉
(Org: 46)
(7,668)
- 7,668
56 📉
(Org: 49)
(7,542)
0.05 7,542
57 📈
(Org: 64)
(7,367)
0.22 7,367
58 📉
(Org: 50)
(7,291)
0.02 7,291
59 📉
(Org: 51)
(7,247)
0.02 7,247
60 📉
(Org: 52)
(7,125)
- 7,125
61 📉
(Org: 55)
(7,038)
0 7,038
62 📈
(Org: 68)
(6,979)
0.19 6,979
63 📈
(Org: 72)
(6,813)
0.2 6,813
64 📉
(Org: 58)
(6,631)
0 6,631
65 📉
(Org: 60)
(6,336)
- 6,336
66 📉
(Org: 61)
(6,178)
0.01 6,178
67 📈
(Org: 81)
(6,175)
0.2 6,175
68 📈
(Org: 84)
(6,059)
0.19 6,059
69 📉
(Org: 62)
(6,005)
- 6,005
70 📉
(Org: 65)
(5,947)
0.05 5,947
71 📉
(Org: 66)
(5,673)
0.01 5,673
72 📉
(Org: 69)
(5,656)
0.01 5,656
73 📉
(Org: 67)
(5,641)
0 5,641
74 📉
(Org: 71)
(5,602)
0.01 5,602
75 📉
(Org: 70)
(5,561)
- 5,561
76 📈
(Org: 142)
(5,500)
0.47 5,500
77 📉
(Org: 73)
(5,484)
0.02 5,484
78 ➡️
(Org: 78)
(5,467)
0.07 5,467
79 📈
(Org: 105)
(5,442)
0.31 5,442
80 📈
(Org: 94)
(5,317)
0.18 5,317
81 📉
(Org: 74)
(5,309)
0 5,309
82 📈
(Org: 86)
(5,269)
0.08 5,269
83 📉
(Org: 75)
(5,245)
0 5,245
84 📉
(Org: 79)
(5,172)
0.04 5,172
85 📉
(Org: 77)
(5,119)
- 5,119
86 📈
(Org: 89)
(5,054)
0.09 5,054
87 📉
(Org: 85)
(5,004)
0.02 5,004
88 📉
(Org: 80)
(4,955)
0 4,955
89 📉
(Org: 83)
(4,910)
- 4,910
90 📉
(Org: 87)
(4,729)
- 4,729
91 📈
(Org: 123)
(4,655)
0.28 4,655
92 📉
(Org: 90)
(4,653)
0.02 4,653
93 📉
(Org: 88)
(4,646)
0 4,646
94 📉
(Org: 93)
(4,582)
0.02 4,582
95 📈
(Org: 186)
(4,577)
0.53 4,577
96 📈
(Org: 144)
(4,572)
0.37 4,572
96 📉
(Org: 91)
(4,572)
0.01 4,572
98 📈
(Org: 180)
(4,568)
0.51 4,568
99 📈
(Org: 100)
(4,488)
0.09 4,488
100 📉
(Org: 95)
(4,332)
0 4,332