Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1974 - 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)
(70,196)
0.04 70,196
2 ➡️
(Org: 2)
(55,597)
0.02 55,597
3 ➡️
(Org: 3)
(50,911)
0.05 50,911
4 📈
(Org: 8)
(42,153)
0.18 42,153
5 📉
(Org: 4)
(41,817)
0 41,817
6 📉
(Org: 5)
(41,344)
0 41,344
7 📉
(Org: 6)
(40,404)
0.07 40,404
8 📉
(Org: 7)
(37,015)
0 37,015
9 ➡️
(Org: 9)
(28,299)
0.04 28,299
10 📈
(Org: 19)
(27,774)
0.36 27,774
11 📉
(Org: 10)
(27,033)
0 27,033
12 📈
(Org: 15)
(25,279)
0.24 25,279
13 📉
(Org: 11)
(24,151)
0.01 24,151
14 📉
(Org: 13)
(23,810)
0.15 23,810
15 📉
(Org: 12)
(22,089)
0.01 22,089
16 ➡️
(Org: 16)
(22,015)
0.14 22,015
17 📈
(Org: 30)
(20,845)
0.45 20,845
18 📉
(Org: 14)
(19,564)
0.01 19,564
19 📉
(Org: 17)
(18,654)
0 18,654
20 📉
(Org: 18)
(18,355)
0.02 18,355
21 📉
(Org: 20)
(17,541)
0.02 17,541
22 📉
(Org: 21)
(16,397)
0 16,397
23 📉
(Org: 22)
(15,910)
0 15,910
24 📉
(Org: 23)
(15,151)
- 15,151
25 📉
(Org: 24)
(13,677)
0.03 13,677
26 📉
(Org: 25)
(13,195)
0 13,195
27 📉
(Org: 26)
(12,885)
0.01 12,885
28 📉
(Org: 27)
(12,312)
- 12,312
29 📉
(Org: 28)
(11,783)
0 11,783
30 📉
(Org: 29)
(11,667)
0.01 11,667
31 📈
(Org: 33)
(11,568)
0.12 11,568
32 ➡️
(Org: 32)
(10,928)
0.04 10,928
33 📉
(Org: 31)
(10,915)
0.01 10,915
34 ➡️
(Org: 34)
(10,151)
0 10,151
35 📈
(Org: 36)
(8,441)
0 8,441
36 📈
(Org: 38)
(8,152)
0 8,152
37 📈
(Org: 39)
(7,846)
- 7,846
38 📈
(Org: 40)
(7,820)
- 7,820
39 📈
(Org: 41)
(7,759)
- 7,759
40 📈
(Org: 42)
(7,671)
0 7,671
41 📈
(Org: 52)
(7,554)
0.23 7,554
42 📈
(Org: 43)
(7,488)
0.01 7,488
43 📈
(Org: 44)
(7,448)
0.01 7,448
44 📈
(Org: 46)
(7,317)
0.02 7,317
45 📈
(Org: 74)
(7,138)
0.49 7,138
46 📈
(Org: 70)
(6,954)
0.43 6,954
47 ➡️
(Org: 47)
(6,721)
- 6,721
48 ➡️
(Org: 48)
(6,461)
0 6,461
49 ➡️
(Org: 49)
(6,330)
0.01 6,330
50 📈
(Org: 77)
(6,283)
0.46 6,283
51 ➡️
(Org: 51)
(6,039)
0.03 6,039
52 📉
(Org: 50)
(5,952)
0 5,952
53 ➡️
(Org: 53)
(5,921)
0.01 5,921
54 📈
(Org: 56)
(5,907)
0.04 5,907
55 📉
(Org: 54)
(5,709)
0 5,709
56 📉
(Org: 55)
(5,708)
0 5,708
57 ➡️
(Org: 57)
(5,663)
0.02 5,663
58 ➡️
(Org: 58)
(5,334)
0.03 5,334
59 ➡️
(Org: 59)
(5,024)
0.03 5,024
60 📈
(Org: 67)
(4,917)
0.16 4,917
61 ➡️
(Org: 61)
(4,799)
0.03 4,799
62 📉
(Org: 60)
(4,726)
0.01 4,726
63 📈
(Org: 68)
(4,649)
0.12 4,649
64 📉
(Org: 62)
(4,593)
0 4,593
65 📉
(Org: 63)
(4,564)
- 4,564
66 📉
(Org: 64)
(4,428)
- 4,428
67 📉
(Org: 65)
(4,364)
- 4,364
68 📈
(Org: 69)
(4,063)
0.01 4,063
69 📈
(Org: 89)
(3,937)
0.26 3,937
70 📈
(Org: 71)
(3,871)
- 3,871
71 📈
(Org: 72)
(3,856)
0 3,856
72 📈
(Org: 73)
(3,802)
- 3,802
73 📈
(Org: 80)
(3,601)
0.11 3,601
74 📈
(Org: 78)
(3,502)
0.04 3,502
74 📈
(Org: 75)
(3,502)
0 3,502
76 ➡️
(Org: 76)
(3,432)
0.01 3,432
77 📈
(Org: 79)
(3,365)
0.01 3,365
78 📈
(Org: 81)
(3,335)
0.04 3,335
79 📈
(Org: 84)
(3,269)
0.03 3,269
80 📈
(Org: 83)
(3,226)
0.02 3,226
81 📈
(Org: 82)
(3,196)
0.01 3,196
82 📈
(Org: 95)
(3,186)
0.16 3,186
83 📈
(Org: 99)
(3,182)
0.19 3,182
84 📈
(Org: 106)
(3,158)
0.22 3,158
85 📈
(Org: 87)
(2,958)
- 2,958
86 📈
(Org: 93)
(2,926)
0.06 2,926
87 📈
(Org: 91)
(2,925)
0.02 2,925
88 📈
(Org: 92)
(2,893)
0.03 2,893
89 📈
(Org: 141)
(2,892)
0.38 2,892
90 📈
(Org: 98)
(2,844)
0.09 2,844
91 📈
(Org: 100)
(2,780)
0.09 2,780
92 📈
(Org: 116)
(2,741)
0.17 2,741
93 📈
(Org: 135)
(2,726)
0.29 2,726
94 📈
(Org: 129)
(2,676)
0.24 2,676
95 📈
(Org: 108)
(2,675)
0.1 2,675
96 ➡️
(Org: 96)
(2,623)
- 2,623
97 ➡️
(Org: 97)
(2,599)
- 2,599
98 📈
(Org: 101)
(2,540)
0.01 2,540
99 📈
(Org: 105)
(2,499)
0.01 2,499
100 📈
(Org: 103)
(2,490)
- 2,490