Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1972 - 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)
(74,154)
0.04 74,154
2 ➡️
(Org: 2)
(53,721)
0.03 53,721
3 ➡️
(Org: 3)
(47,070)
0 47,070
4 📈
(Org: 5)
(46,419)
0.07 46,419
5 📉
(Org: 4)
(46,362)
0 46,362
6 📈
(Org: 8)
(43,863)
0.17 43,863
7 📉
(Org: 6)
(43,015)
- 43,015
8 📉
(Org: 7)
(38,114)
0.02 38,114
9 📈
(Org: 19)
(30,902)
0.36 30,902
10 📉
(Org: 9)
(30,566)
0 30,566
11 📈
(Org: 17)
(28,244)
0.23 28,244
12 📈
(Org: 16)
(26,245)
0.16 26,245
13 📈
(Org: 18)
(24,967)
0.14 24,967
14 📉
(Org: 10)
(23,853)
0.04 23,853
15 📉
(Org: 11)
(23,277)
0.02 23,277
16 📉
(Org: 12)
(22,703)
0.01 22,703
17 📉
(Org: 13)
(22,515)
0.01 22,515
18 📉
(Org: 15)
(22,391)
0.01 22,391
19 📉
(Org: 14)
(22,332)
0 22,332
20 📈
(Org: 28)
(22,037)
0.49 22,037
21 📉
(Org: 20)
(19,815)
0.01 19,815
22 📉
(Org: 21)
(17,629)
0 17,629
23 📉
(Org: 22)
(17,471)
0 17,471
24 📉
(Org: 23)
(16,986)
0 16,986
25 📉
(Org: 24)
(14,561)
- 14,561
26 📉
(Org: 25)
(13,487)
0.01 13,487
27 📉
(Org: 26)
(13,159)
0.01 13,159
28 📉
(Org: 27)
(12,342)
0 12,342
29 📈
(Org: 37)
(10,459)
0.12 10,459
30 ➡️
(Org: 30)
(10,114)
- 10,114
31 ➡️
(Org: 31)
(9,968)
- 9,968
32 ➡️
(Org: 32)
(9,521)
0 9,521
33 📈
(Org: 35)
(9,316)
0 9,316
34 ➡️
(Org: 34)
(9,295)
- 9,295
35 📈
(Org: 36)
(9,261)
- 9,261
36 📈
(Org: 38)
(9,215)
0.01 9,215
37 📈
(Org: 39)
(8,884)
0 8,884
38 📈
(Org: 40)
(8,187)
0.04 8,187
39 📈
(Org: 67)
(7,900)
0.48 7,900
40 📈
(Org: 41)
(7,781)
0 7,781
41 📈
(Org: 42)
(7,652)
0.03 7,652
42 📈
(Org: 43)
(7,486)
0.01 7,486
43 📈
(Org: 44)
(7,212)
0.01 7,212
44 📈
(Org: 46)
(6,922)
0.03 6,922
45 📈
(Org: 47)
(6,628)
0 6,628
46 📈
(Org: 48)
(6,494)
0 6,494
47 📈
(Org: 49)
(6,354)
0 6,354
48 📈
(Org: 76)
(6,351)
0.44 6,351
49 📈
(Org: 50)
(5,940)
0 5,940
50 📈
(Org: 52)
(5,772)
0.03 5,772
51 📈
(Org: 53)
(5,770)
0.03 5,770
52 📉
(Org: 51)
(5,752)
0 5,752
53 📈
(Org: 55)
(5,463)
0.04 5,463
54 ➡️
(Org: 54)
(5,458)
0 5,458
55 📈
(Org: 95)
(5,434)
0.45 5,434
56 ➡️
(Org: 56)
(5,167)
- 5,167
57 ➡️
(Org: 57)
(5,150)
0 5,150
58 📈
(Org: 59)
(5,049)
0 5,049
59 📈
(Org: 60)
(5,018)
0.01 5,018
60 📈
(Org: 61)
(4,998)
0.03 4,998
61 📈
(Org: 62)
(4,812)
0.01 4,812
62 📈
(Org: 79)
(4,778)
0.26 4,778
63 ➡️
(Org: 63)
(4,737)
0.02 4,737
64 📈
(Org: 85)
(4,613)
0.26 4,613
65 📉
(Org: 64)
(4,573)
0.02 4,573
66 📉
(Org: 65)
(4,363)
- 4,363
67 📉
(Org: 66)
(4,270)
0.01 4,270
68 📈
(Org: 72)
(4,227)
0.13 4,227
69 📉
(Org: 68)
(4,147)
0.04 4,147
70 📈
(Org: 80)
(4,131)
0.15 4,131
71 📈
(Org: 88)
(4,020)
0.2 4,020
72 📈
(Org: 81)
(3,941)
0.12 3,941
73 📉
(Org: 69)
(3,896)
0.03 3,896
74 📉
(Org: 70)
(3,767)
0.01 3,767
75 ➡️
(Org: 75)
(3,727)
0.05 3,727
76 📉
(Org: 71)
(3,685)
- 3,685
77 📉
(Org: 73)
(3,681)
0 3,681
78 📈
(Org: 97)
(3,653)
0.2 3,653
79 📉
(Org: 74)
(3,630)
0.02 3,630
80 📈
(Org: 81)
(3,589)
0.03 3,589
81 📉
(Org: 77)
(3,537)
0 3,537
82 📉
(Org: 78)
(3,528)
- 3,528
83 📈
(Org: 116)
(3,482)
0.3 3,482
84 ➡️
(Org: 84)
(3,436)
- 3,436
85 📈
(Org: 87)
(3,397)
0.03 3,397
86 📈
(Org: 92)
(3,348)
0.08 3,348
87 📈
(Org: 133)
(3,296)
0.39 3,296
88 📈
(Org: 90)
(3,285)
0.03 3,285
89 📈
(Org: 99)
(3,198)
0.11 3,198
90 📈
(Org: 134)
(3,133)
0.37 3,133
91 📈
(Org: 102)
(3,124)
0.1 3,124
92 📈
(Org: 101)
(3,099)
0.09 3,099
93 📈
(Org: 124)
(3,078)
0.26 3,078
94 ➡️
(Org: 94)
(3,046)
0.01 3,046
94 📉
(Org: 93)
(3,046)
0.01 3,046
96 📈
(Org: 111)
(3,034)
0.16 3,034
97 📉
(Org: 96)
(2,962)
- 2,962
98 ➡️
(Org: 98)
(2,917)
- 2,917
99 📈
(Org: 127)
(2,903)
0.23 2,903
100 📈
(Org: 106)
(2,892)
0.08 2,892