Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1993 - 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: 1)
(51,163)
0.03 51,163
2 ➡️
(Org: 2)
(40,804)
0.06 40,804
3 ➡️
(Org: 3)
(37,516)
0.05 37,516
4 ➡️
(Org: 4)
(33,780)
0.01 33,780
5 📈
(Org: 8)
(31,572)
0.11 31,572
6 📉
(Org: 5)
(30,472)
0.02 30,472
7 📉
(Org: 6)
(30,067)
0.04 30,067
8 📈
(Org: 15)
(29,499)
0.13 29,499
9 📉
(Org: 7)
(28,910)
0.01 28,910
10 📉
(Org: 9)
(27,560)
0 27,560
11 📉
(Org: 10)
(27,328)
0 27,328
12 ➡️
(Org: 12)
(27,182)
0.01 27,182
13 📉
(Org: 11)
(27,046)
0 27,046
14 📉
(Org: 13)
(26,800)
0 26,800
15 📉
(Org: 14)
(26,318)
0 26,318
16 ➡️
(Org: 16)
(26,188)
0.05 26,188
17 📈
(Org: 22)
(25,121)
0.21 25,121
18 📉
(Org: 17)
(22,447)
- 22,447
19 📉
(Org: 18)
(22,242)
0 22,242
20 ➡️
(Org: 20)
(21,858)
0.01 21,858
21 📈
(Org: 31)
(21,854)
0.38 21,854
22 📉
(Org: 19)
(21,789)
- 21,789
23 📈
(Org: 24)
(21,183)
0.1 21,183
24 📉
(Org: 21)
(20,574)
0 20,574
25 📈
(Org: 29)
(19,605)
0.26 19,605
26 📉
(Org: 23)
(19,497)
0 19,497
27 📉
(Org: 25)
(19,275)
0.01 19,275
28 📈
(Org: 34)
(18,993)
0.34 18,993
29 📉
(Org: 26)
(17,920)
0.02 17,920
30 📈
(Org: 32)
(17,178)
0.26 17,178
31 📈
(Org: 42)
(16,043)
0.37 16,043
32 📉
(Org: 28)
(15,589)
0.05 15,589
33 📈
(Org: 41)
(15,368)
0.34 15,368
34 📉
(Org: 27)
(15,314)
0.03 15,314
35 📉
(Org: 30)
(14,424)
0.04 14,424
36 📉
(Org: 33)
(12,839)
0.01 12,839
37 📉
(Org: 35)
(11,890)
- 11,890
38 📉
(Org: 36)
(11,847)
- 11,847
39 📉
(Org: 37)
(11,836)
0.01 11,836
40 📉
(Org: 38)
(11,654)
0 11,654
41 📉
(Org: 39)
(11,564)
0 11,564
42 📈
(Org: 68)
(10,756)
0.47 10,756
43 📉
(Org: 40)
(10,237)
0 10,237
44 📈
(Org: 53)
(10,058)
0.25 10,058
45 📉
(Org: 43)
(9,948)
0.01 9,948
46 📉
(Org: 44)
(9,856)
- 9,856
47 📈
(Org: 48)
(9,669)
0.15 9,669
48 📈
(Org: 49)
(9,482)
0.15 9,482
49 📈
(Org: 67)
(9,349)
0.38 9,349
50 📈
(Org: 57)
(9,178)
0.3 9,178
51 📉
(Org: 45)
(9,082)
0.05 9,082
52 📉
(Org: 46)
(8,874)
0.03 8,874
53 📉
(Org: 50)
(7,955)
0 7,955
54 📉
(Org: 51)
(7,869)
0.02 7,869
55 📉
(Org: 54)
(7,672)
0.08 7,672
56 📉
(Org: 52)
(7,670)
0 7,670
57 📈
(Org: 66)
(7,011)
0.17 7,011
58 📉
(Org: 55)
(6,904)
0 6,904
59 📉
(Org: 58)
(6,872)
0.07 6,872
60 📈
(Org: 63)
(6,633)
0.09 6,633
61 📉
(Org: 56)
(6,482)
- 6,482
62 📉
(Org: 59)
(6,425)
0.02 6,425
63 📉
(Org: 60)
(6,290)
0 6,290
64 ➡️
(Org: 64)
(6,257)
0.04 6,257
65 📉
(Org: 62)
(6,101)
0 6,101
66 📉
(Org: 65)
(5,889)
0.01 5,889
67 📈
(Org: 69)
(5,642)
0.01 5,642
68 📈
(Org: 71)
(5,570)
0.04 5,570
69 📈
(Org: 70)
(5,547)
0.03 5,547
70 📈
(Org: 79)
(5,485)
0.14 5,485
71 📈
(Org: 73)
(5,405)
0.05 5,405
72 📈
(Org: 117)
(5,384)
0.44 5,384
73 📉
(Org: 72)
(5,352)
- 5,352
74 📈
(Org: 121)
(5,298)
0.45 5,298
75 📉
(Org: 74)
(5,063)
- 5,063
76 📈
(Org: 81)
(4,970)
0.08 4,970
77 📉
(Org: 76)
(4,866)
0 4,866
78 ➡️
(Org: 78)
(4,790)
- 4,790
79 📈
(Org: 84)
(4,782)
0.07 4,782
80 ➡️
(Org: 80)
(4,692)
0 4,692
81 📈
(Org: 85)
(4,607)
0.04 4,607
82 ➡️
(Org: 82)
(4,548)
0 4,548
83 ➡️
(Org: 83)
(4,513)
0 4,513
84 📈
(Org: 95)
(4,455)
0.12 4,455
85 📈
(Org: 86)
(4,438)
0.01 4,438
86 📈
(Org: 87)
(4,428)
0.02 4,428
87 📈
(Org: 88)
(4,400)
0.01 4,400
88 📈
(Org: 89)
(4,340)
0.01 4,340
89 📈
(Org: 91)
(4,207)
- 4,207
90 📈
(Org: 92)
(4,181)
0 4,181
91 📈
(Org: 93)
(4,060)
- 4,060
92 📈
(Org: 96)
(3,992)
0.03 3,992
93 📈
(Org: 102)
(3,950)
0.1 3,950
94 📈
(Org: 97)
(3,792)
- 3,792
95 📈
(Org: 98)
(3,768)
- 3,768
96 📈
(Org: 99)
(3,754)
- 3,754
97 📈
(Org: 100)
(3,753)
0.02 3,753
98 📈
(Org: 112)
(3,722)
0.15 3,722
99 📈
(Org: 110)
(3,602)
0.11 3,602
100 📈
(Org: 101)
(3,572)
0 3,572