Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1976 - 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)
(69,271)
0.03 69,271
2 ➡️
(Org: 2)
(53,493)
0.02 53,493
3 ➡️
(Org: 3)
(47,691)
0.05 47,691
4 ➡️
(Org: 4)
(39,292)
0 39,292
5 ➡️
(Org: 5)
(38,313)
0 38,313
6 📈
(Org: 8)
(38,257)
0.2 38,257
7 📉
(Org: 6)
(36,341)
0.06 36,341
8 📉
(Org: 7)
(33,799)
0 33,799
9 ➡️
(Org: 9)
(31,142)
0.04 31,142
10 📈
(Org: 20)
(26,384)
0.37 26,384
11 📉
(Org: 10)
(25,064)
0.01 25,064
12 📈
(Org: 13)
(24,875)
0.14 24,875
13 📉
(Org: 11)
(24,487)
0 24,487
14 📉
(Org: 12)
(24,357)
0.01 24,357
15 📈
(Org: 17)
(22,238)
0.23 22,238
16 📉
(Org: 14)
(20,734)
0.03 20,734
17 📉
(Org: 15)
(18,589)
0.01 18,589
18 📈
(Org: 34)
(18,537)
0.45 18,537
19 📈
(Org: 25)
(18,115)
0.14 18,115
20 📉
(Org: 16)
(17,511)
0 17,511
21 📉
(Org: 18)
(16,933)
0.01 16,933
22 📉
(Org: 19)
(16,777)
0 16,777
23 📉
(Org: 21)
(16,639)
0 16,639
24 📉
(Org: 22)
(16,603)
- 16,603
25 📉
(Org: 23)
(16,407)
0.02 16,407
26 📉
(Org: 24)
(15,955)
0.01 15,955
27 📉
(Org: 26)
(13,923)
- 13,923
28 📉
(Org: 27)
(13,303)
- 13,303
29 📈
(Org: 31)
(13,010)
0.13 13,010
30 📉
(Org: 29)
(11,833)
0.01 11,833
31 📉
(Org: 28)
(11,789)
0 11,789
32 📉
(Org: 30)
(11,765)
0.04 11,765
33 📈
(Org: 39)
(10,968)
0.22 10,968
34 📉
(Org: 32)
(10,868)
0.02 10,868
35 📉
(Org: 33)
(10,258)
0.01 10,258
36 📉
(Org: 35)
(10,164)
0.01 10,164
37 📉
(Org: 36)
(9,957)
0 9,957
38 ➡️
(Org: 38)
(9,139)
0 9,139
39 📈
(Org: 64)
(8,282)
0.46 8,282
40 ➡️
(Org: 40)
(7,991)
0.03 7,991
41 ➡️
(Org: 41)
(7,680)
0 7,680
42 📈
(Org: 44)
(7,068)
0 7,068
43 📈
(Org: 45)
(7,048)
- 7,048
44 📈
(Org: 46)
(6,841)
0 6,841
45 📈
(Org: 69)
(6,805)
0.44 6,805
46 📈
(Org: 48)
(6,798)
0.01 6,798
47 ➡️
(Org: 47)
(6,795)
- 6,795
48 📈
(Org: 84)
(6,673)
0.53 6,673
49 ➡️
(Org: 49)
(6,459)
- 6,459
50 ➡️
(Org: 50)
(6,441)
- 6,441
51 📈
(Org: 55)
(6,210)
0.15 6,210
52 📉
(Org: 51)
(6,167)
0.03 6,167
53 📉
(Org: 52)
(5,620)
0 5,620
54 📉
(Org: 53)
(5,610)
0.01 5,610
55 📉
(Org: 54)
(5,456)
0 5,456
56 📈
(Org: 57)
(5,296)
0.04 5,296
57 📈
(Org: 62)
(5,288)
0.13 5,288
58 📉
(Org: 56)
(5,274)
0.01 5,274
59 ➡️
(Org: 59)
(5,093)
0.01 5,093
60 📉
(Org: 58)
(5,053)
- 5,053
61 📉
(Org: 60)
(4,853)
0 4,853
62 📉
(Org: 61)
(4,848)
0.02 4,848
63 ➡️
(Org: 63)
(4,509)
- 4,509
64 📈
(Org: 66)
(4,318)
0.03 4,318
65 ➡️
(Org: 65)
(4,228)
0 4,228
66 📈
(Org: 67)
(4,192)
0.03 4,192
67 📈
(Org: 77)
(3,978)
0.13 3,978
68 ➡️
(Org: 68)
(3,899)
- 3,899
69 📈
(Org: 71)
(3,800)
0.01 3,800
70 ➡️
(Org: 70)
(3,787)
- 3,787
71 📈
(Org: 72)
(3,725)
- 3,725
72 📈
(Org: 73)
(3,722)
0 3,722
73 📈
(Org: 75)
(3,711)
0.01 3,711
74 ➡️
(Org: 74)
(3,680)
- 3,680
75 📈
(Org: 95)
(3,572)
0.25 3,572
76 📈
(Org: 78)
(3,422)
0 3,422
77 📈
(Org: 79)
(3,352)
0.01 3,352
78 📈
(Org: 81)
(3,322)
0.01 3,322
79 📈
(Org: 80)
(3,309)
- 3,309
80 📈
(Org: 85)
(3,268)
0.03 3,268
81 📈
(Org: 82)
(3,237)
0.01 3,237
82 📈
(Org: 86)
(3,172)
0.03 3,172
83 📈
(Org: 87)
(3,097)
0.03 3,097
84 📈
(Org: 90)
(3,092)
0.05 3,092
85 📈
(Org: 110)
(3,068)
0.22 3,068
86 📈
(Org: 101)
(3,051)
0.18 3,051
87 📈
(Org: 88)
(2,984)
- 2,984
88 📈
(Org: 92)
(2,942)
0.02 2,942
89 📈
(Org: 109)
(2,922)
0.17 2,922
90 📈
(Org: 96)
(2,896)
0.09 2,896
91 📈
(Org: 93)
(2,873)
- 2,873
92 📈
(Org: 97)
(2,737)
0.03 2,737
93 📈
(Org: 132)
(2,700)
0.26 2,700
94 📈
(Org: 105)
(2,688)
0.09 2,688
95 📈
(Org: 98)
(2,646)
0.01 2,646
96 📈
(Org: 103)
(2,605)
0.05 2,605
97 📈
(Org: 104)
(2,599)
0.06 2,599
98 📈
(Org: 102)
(2,581)
0.03 2,581
99 📈
(Org: 155)
(2,578)
0.38 2,578
100 ➡️
(Org: 100)
(2,527)
- 2,527