Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1982 - 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)
(70,360)
0.03 70,360
2 ➡️
(Org: 2)
(62,711)
0.06 62,711
3 ➡️
(Org: 3)
(47,816)
0.04 47,816
4 ➡️
(Org: 4)
(41,405)
0.02 41,405
5 ➡️
(Org: 5)
(40,497)
0 40,497
6 ➡️
(Org: 6)
(38,897)
0 38,897
7 ➡️
(Org: 7)
(38,191)
0 38,191
8 ➡️
(Org: 8)
(36,764)
0.06 36,764
9 ➡️
(Org: 9)
(34,420)
0 34,420
10 📈
(Org: 14)
(33,737)
0.23 33,737
11 📉
(Org: 10)
(33,009)
0.01 33,009
12 📉
(Org: 11)
(31,402)
0.01 31,402
13 📉
(Org: 12)
(29,407)
0.01 29,407
14 📈
(Org: 26)
(27,793)
0.38 27,793
15 📈
(Org: 16)
(26,896)
0.14 26,896
16 📉
(Org: 13)
(26,746)
0 26,746
17 📉
(Org: 15)
(25,704)
0 25,704
18 📈
(Org: 20)
(24,414)
0.19 24,414
19 📉
(Org: 17)
(22,853)
0 22,853
20 📈
(Org: 22)
(21,292)
0.08 21,292
21 📈
(Org: 29)
(20,965)
0.24 20,965
22 📉
(Org: 18)
(20,871)
0.03 20,871
23 📉
(Org: 19)
(20,118)
0 20,118
24 📉
(Org: 21)
(19,659)
0 19,659
25 📈
(Org: 44)
(19,456)
0.52 19,456
26 📉
(Org: 23)
(17,895)
0.02 17,895
27 📉
(Org: 24)
(17,571)
0.01 17,571
28 📉
(Org: 25)
(17,477)
0 17,477
29 📉
(Org: 28)
(16,950)
0.03 16,950
30 📉
(Org: 27)
(16,766)
0 16,766
31 📈
(Org: 32)
(15,916)
0.13 15,916
32 📈
(Org: 36)
(15,004)
0.28 15,004
33 📉
(Org: 30)
(14,900)
0.03 14,900
34 📉
(Org: 31)
(14,323)
0 14,323
35 📉
(Org: 33)
(13,993)
0.01 13,993
36 📉
(Org: 34)
(12,342)
0.01 12,342
37 📈
(Org: 50)
(11,579)
0.4 11,579
38 📉
(Org: 35)
(11,310)
- 11,310
39 📈
(Org: 43)
(11,013)
0.14 11,013
40 📉
(Org: 37)
(10,736)
0 10,736
41 📉
(Org: 39)
(10,426)
0 10,426
42 📉
(Org: 40)
(10,251)
0.01 10,251
43 📉
(Org: 41)
(10,066)
0 10,066
44 📉
(Org: 42)
(9,590)
0 9,590
45 ➡️
(Org: 45)
(9,365)
0 9,365
46 ➡️
(Org: 46)
(8,627)
0 8,627
47 📈
(Org: 67)
(8,268)
0.45 8,268
48 📉
(Org: 47)
(8,214)
0 8,214
49 📉
(Org: 48)
(7,995)
0.01 7,995
50 📈
(Org: 74)
(7,889)
0.5 7,889
51 ➡️
(Org: 51)
(7,242)
0.04 7,242
52 📈
(Org: 55)
(6,743)
0.09 6,743
53 📈
(Org: 54)
(6,570)
0.05 6,570
54 📉
(Org: 53)
(6,281)
- 6,281
55 📈
(Org: 56)
(6,088)
0.01 6,088
56 📈
(Org: 57)
(5,794)
0 5,794
57 📈
(Org: 58)
(5,712)
- 5,712
58 📈
(Org: 59)
(5,675)
0.01 5,675
59 📈
(Org: 60)
(5,208)
- 5,208
60 📈
(Org: 72)
(5,124)
0.21 5,124
61 ➡️
(Org: 61)
(5,122)
- 5,122
62 ➡️
(Org: 62)
(5,059)
0.01 5,059
63 ➡️
(Org: 63)
(4,988)
- 4,988
64 ➡️
(Org: 64)
(4,654)
0 4,654
65 📈
(Org: 66)
(4,634)
0.01 4,634
66 📉
(Org: 65)
(4,604)
0 4,604
67 📈
(Org: 68)
(4,554)
0.01 4,554
68 📈
(Org: 69)
(4,446)
- 4,446
69 📈
(Org: 70)
(4,306)
0 4,306
70 📈
(Org: 71)
(4,269)
- 4,269
71 📈
(Org: 73)
(4,146)
0.03 4,146
72 📈
(Org: 90)
(3,918)
0.15 3,918
73 📈
(Org: 76)
(3,914)
0.01 3,914
74 📈
(Org: 104)
(3,811)
0.26 3,811
75 📈
(Org: 86)
(3,765)
0.09 3,765
76 📈
(Org: 77)
(3,729)
0 3,729
77 📈
(Org: 85)
(3,711)
0.05 3,711
78 📈
(Org: 84)
(3,698)
0.04 3,698
79 📈
(Org: 83)
(3,658)
0.02 3,658
80 📈
(Org: 81)
(3,605)
- 3,605
81 📈
(Org: 82)
(3,600)
- 3,600
82 📈
(Org: 87)
(3,478)
0.02 3,478
83 📈
(Org: 88)
(3,380)
0.01 3,380
84 📈
(Org: 95)
(3,379)
0.06 3,379
85 📈
(Org: 101)
(3,358)
0.12 3,358
86 📈
(Org: 91)
(3,336)
0 3,336
87 📈
(Org: 89)
(3,329)
- 3,329
88 📈
(Org: 94)
(3,271)
0.01 3,271
89 📈
(Org: 98)
(3,163)
0.04 3,163
90 📈
(Org: 97)
(3,150)
0.04 3,150
91 📈
(Org: 100)
(3,055)
0.04 3,055
92 📈
(Org: 99)
(3,002)
- 3,002
93 📈
(Org: 106)
(2,935)
0.07 2,935
94 📈
(Org: 103)
(2,917)
0.02 2,917
95 📈
(Org: 102)
(2,907)
- 2,907
96 📈
(Org: 129)
(2,856)
0.26 2,856
97 📈
(Org: 105)
(2,787)
0.01 2,787
98 📈
(Org: 112)
(2,707)
0.04 2,707
99 📈
(Org: 107)
(2,687)
- 2,687
100 📈
(Org: 113)
(2,684)
0.03 2,684