Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2015 - 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)
(25,735)
0.52 25,735
2 📉
(Org: 1)
(19,762)
0 19,762
3 📈
(Org: 13)
(18,987)
0.29 18,987
4 📉
(Org: 2)
(18,562)
0.01 18,562
5 📈
(Org: 20)
(17,925)
0.35 17,925
6 📉
(Org: 3)
(17,319)
0.04 17,319
7 📉
(Org: 4)
(16,227)
0.01 16,227
8 📉
(Org: 5)
(15,969)
0 15,969
9 📉
(Org: 6)
(15,147)
0 15,147
10 📉
(Org: 9)
(14,958)
0.03 14,958
11 📉
(Org: 7)
(14,903)
0 14,903
12 📉
(Org: 8)
(14,600)
0 14,600
13 📉
(Org: 11)
(13,921)
0.02 13,921
14 📈
(Org: 16)
(13,863)
0.11 13,863
15 📉
(Org: 10)
(13,793)
0 13,793
16 📉
(Org: 12)
(13,636)
0.01 13,636
17 📉
(Org: 15)
(13,428)
0.05 13,428
18 📈
(Org: 24)
(13,174)
0.18 13,174
19 📉
(Org: 14)
(13,069)
0.01 13,069
20 📈
(Org: 38)
(12,983)
0.34 12,983
21 📈
(Org: 47)
(12,224)
0.35 12,224
22 📉
(Org: 18)
(11,836)
- 11,836
23 📉
(Org: 19)
(11,731)
0.01 11,731
24 📉
(Org: 21)
(11,563)
0 11,563
25 📈
(Org: 37)
(11,419)
0.23 11,419
26 📉
(Org: 22)
(11,061)
0.01 11,061
27 ➡️
(Org: 27)
(11,040)
0.07 11,040
28 📈
(Org: 75)
(11,021)
0.51 11,021
29 📉
(Org: 23)
(10,946)
0 10,946
30 📈
(Org: 95)
(10,864)
0.61 10,864
31 📈
(Org: 32)
(10,821)
0.09 10,821
32 📉
(Org: 26)
(10,782)
0.03 10,782
33 📉
(Org: 31)
(10,765)
0.07 10,765
34 📉
(Org: 25)
(10,660)
- 10,660
35 📉
(Org: 28)
(10,373)
0.01 10,373
36 📉
(Org: 29)
(10,323)
0.01 10,323
37 📉
(Org: 30)
(10,144)
- 10,144
38 📉
(Org: 33)
(9,882)
0 9,882
39 📉
(Org: 34)
(9,704)
0 9,704
40 📉
(Org: 35)
(9,664)
0 9,664
41 📈
(Org: 46)
(9,638)
0.18 9,638
42 📉
(Org: 36)
(9,614)
0 9,614
43 📈
(Org: 55)
(9,296)
0.27 9,296
44 📈
(Org: 48)
(9,103)
0.16 9,103
44 📈
(Org: 62)
(9,103)
0.31 9,103
46 📉
(Org: 40)
(8,841)
0.04 8,841
47 📉
(Org: 39)
(8,608)
0.01 8,608
48 📉
(Org: 42)
(8,400)
0.01 8,400
49 📉
(Org: 41)
(8,361)
- 8,361
50 📈
(Org: 61)
(8,315)
0.24 8,315
51 📈
(Org: 56)
(8,278)
0.18 8,278
52 📉
(Org: 43)
(8,218)
- 8,218
53 📉
(Org: 45)
(8,152)
0.01 8,152
54 📈
(Org: 60)
(7,916)
0.2 7,916
55 📉
(Org: 49)
(7,863)
0.03 7,863
56 📉
(Org: 52)
(7,563)
0.05 7,563
57 📉
(Org: 51)
(7,550)
0.05 7,550
58 📈
(Org: 68)
(7,418)
0.21 7,418
59 📉
(Org: 53)
(7,327)
0.02 7,327
60 📈
(Org: 85)
(7,320)
0.31 7,320
61 📉
(Org: 50)
(7,204)
- 7,204
62 📉
(Org: 54)
(6,826)
- 6,826
63 📉
(Org: 57)
(6,688)
0 6,688
64 📉
(Org: 59)
(6,623)
0.04 6,623
65 📉
(Org: 58)
(6,536)
- 6,536
66 📈
(Org: 86)
(6,336)
0.21 6,336
67 📉
(Org: 63)
(6,132)
- 6,132
68 📉
(Org: 66)
(6,123)
0.02 6,123
69 📉
(Org: 64)
(6,122)
0 6,122
70 📈
(Org: 89)
(6,112)
0.22 6,112
71 📉
(Org: 65)
(6,103)
0.01 6,103
72 📉
(Org: 69)
(5,964)
0.02 5,964
73 📉
(Org: 67)
(5,952)
0.01 5,952
74 ➡️
(Org: 74)
(5,842)
0.08 5,842
75 📉
(Org: 70)
(5,827)
0.01 5,827
76 ➡️
(Org: 76)
(5,752)
0.07 5,752
77 📉
(Org: 71)
(5,750)
0 5,750
78 📉
(Org: 77)
(5,496)
0.04 5,496
79 📈
(Org: 107)
(5,485)
0.32 5,485
80 📈
(Org: 138)
(5,461)
0.44 5,461
81 📉
(Org: 73)
(5,424)
0 5,424
82 📉
(Org: 72)
(5,418)
- 5,418
83 📈
(Org: 88)
(5,410)
0.1 5,410
84 📉
(Org: 83)
(5,358)
0.04 5,358
85 📉
(Org: 78)
(5,264)
0.01 5,264
86 📉
(Org: 79)
(5,261)
0.01 5,261
87 📉
(Org: 81)
(5,242)
0.01 5,242
88 📈
(Org: 166)
(5,229)
0.52 5,229
89 📉
(Org: 82)
(5,210)
0.01 5,210
90 📉
(Org: 80)
(5,176)
- 5,176
91 📈
(Org: 116)
(4,930)
0.29 4,930
92 📈
(Org: 140)
(4,901)
0.38 4,901
93 📉
(Org: 92)
(4,829)
0.1 4,829
94 📉
(Org: 90)
(4,672)
0 4,672
95 📉
(Org: 91)
(4,615)
0 4,615
96 📉
(Org: 93)
(4,433)
0.02 4,433
97 📈
(Org: 98)
(4,308)
0.03 4,308
98 📉
(Org: 94)
(4,271)
- 4,271
99 📉
(Org: 96)
(4,257)
0.01 4,257
100 📈
(Org: 108)
(4,228)
0.12 4,228