Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1985 - 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)
(66,986)
0.03 66,986
2 ➡️
(Org: 2)
(63,043)
0.05 63,043
3 ➡️
(Org: 3)
(49,020)
0.04 49,020
4 ➡️
(Org: 4)
(42,524)
0.01 42,524
5 ➡️
(Org: 5)
(38,923)
0.01 38,923
6 ➡️
(Org: 6)
(38,562)
0 38,562
7 ➡️
(Org: 7)
(35,983)
0 35,983
8 📈
(Org: 9)
(33,348)
0.06 33,348
9 📈
(Org: 18)
(32,230)
0.28 32,230
10 📉
(Org: 8)
(32,104)
0 32,104
11 📈
(Org: 24)
(30,954)
0.39 30,954
12 📉
(Org: 10)
(30,518)
0.01 30,518
13 ➡️
(Org: 13)
(30,258)
0.03 30,258
14 📉
(Org: 11)
(30,218)
0 30,218
15 📉
(Org: 12)
(29,976)
0 29,976
16 📈
(Org: 17)
(28,676)
0.16 28,676
17 📉
(Org: 14)
(26,658)
0.02 26,658
18 📉
(Org: 15)
(25,833)
0.01 25,833
19 📈
(Org: 21)
(25,083)
0.17 25,083
20 📉
(Org: 16)
(24,715)
0 24,715
21 📉
(Org: 19)
(24,276)
0.08 24,276
22 📉
(Org: 20)
(22,109)
0 22,109
23 📈
(Org: 38)
(20,877)
0.45 20,877
24 📉
(Org: 22)
(20,195)
0 20,195
25 📈
(Org: 29)
(19,086)
0.24 19,086
26 📉
(Org: 23)
(18,921)
0.01 18,921
27 📉
(Org: 25)
(17,946)
0.02 17,946
28 📉
(Org: 26)
(17,171)
0 17,171
29 📉
(Org: 27)
(16,520)
- 16,520
30 📉
(Org: 28)
(15,373)
0 15,373
31 📈
(Org: 32)
(15,358)
0.14 15,358
32 📈
(Org: 40)
(14,929)
0.29 14,929
33 📉
(Org: 30)
(13,896)
0.03 13,896
34 📉
(Org: 33)
(13,622)
0.04 13,622
35 📉
(Org: 31)
(13,599)
0.01 13,599
36 📉
(Org: 34)
(12,918)
0 12,918
37 📈
(Org: 39)
(12,642)
0.1 12,642
38 📉
(Org: 35)
(12,294)
0 12,294
39 📉
(Org: 37)
(11,676)
0 11,676
40 📈
(Org: 56)
(11,360)
0.41 11,360
41 ➡️
(Org: 41)
(10,506)
0.01 10,506
42 📈
(Org: 43)
(10,330)
0.01 10,330
43 📉
(Org: 42)
(10,315)
- 10,315
44 ➡️
(Org: 44)
(10,248)
0.01 10,248
45 📈
(Org: 63)
(10,053)
0.48 10,053
46 📉
(Org: 45)
(9,870)
0.01 9,870
47 📈
(Org: 51)
(9,522)
0.14 9,522
48 📉
(Org: 46)
(9,109)
0 9,109
49 📉
(Org: 47)
(9,001)
0 9,001
50 📉
(Org: 49)
(8,417)
0 8,417
51 📈
(Org: 69)
(8,331)
0.46 8,331
52 📉
(Org: 50)
(8,321)
0 8,321
53 📉
(Org: 52)
(7,546)
0.06 7,546
54 📉
(Org: 53)
(7,280)
0.04 7,280
55 📉
(Org: 54)
(7,093)
0.01 7,093
56 📈
(Org: 57)
(6,560)
0.01 6,560
57 📈
(Org: 58)
(6,331)
0.07 6,331
58 📈
(Org: 59)
(5,874)
0 5,874
59 📈
(Org: 62)
(5,773)
0.05 5,773
60 ➡️
(Org: 60)
(5,684)
0 5,684
61 ➡️
(Org: 61)
(5,591)
0 5,591
62 📈
(Org: 64)
(5,262)
0.01 5,262
63 📈
(Org: 65)
(4,852)
- 4,852
64 📈
(Org: 70)
(4,830)
0.1 4,830
65 📈
(Org: 68)
(4,752)
0.04 4,752
66 ➡️
(Org: 66)
(4,750)
- 4,750
67 ➡️
(Org: 67)
(4,640)
0 4,640
68 📈
(Org: 72)
(4,357)
0.02 4,357
69 📈
(Org: 71)
(4,299)
- 4,299
70 📈
(Org: 85)
(4,264)
0.13 4,264
71 📈
(Org: 73)
(4,164)
0 4,164
72 📈
(Org: 79)
(4,100)
0.04 4,100
73 📈
(Org: 75)
(4,092)
0 4,092
74 ➡️
(Org: 74)
(4,089)
- 4,089
75 📈
(Org: 78)
(4,085)
0.02 4,085
76 ➡️
(Org: 76)
(4,072)
0.01 4,072
77 📈
(Org: 80)
(3,912)
0 3,912
77 📈
(Org: 86)
(3,912)
0.11 3,912
79 📈
(Org: 82)
(3,821)
0 3,821
80 📈
(Org: 112)
(3,532)
0.28 3,532
81 📈
(Org: 98)
(3,489)
0.16 3,489
82 📈
(Org: 88)
(3,342)
- 3,342
83 📈
(Org: 89)
(3,337)
0 3,337
84 📈
(Org: 90)
(3,303)
- 3,303
85 📈
(Org: 92)
(3,264)
0.02 3,264
86 📈
(Org: 91)
(3,225)
0 3,225
87 📈
(Org: 94)
(3,188)
0.05 3,188
88 📈
(Org: 93)
(3,132)
- 3,132
89 📈
(Org: 95)
(3,080)
0.01 3,080
90 📈
(Org: 97)
(2,953)
0 2,953
91 📈
(Org: 103)
(2,952)
0.04 2,952
92 📈
(Org: 99)
(2,939)
- 2,939
93 📈
(Org: 104)
(2,922)
0.03 2,922
93 📈
(Org: 100)
(2,922)
- 2,922
95 📈
(Org: 101)
(2,914)
- 2,914
96 📈
(Org: 102)
(2,908)
0.01 2,908
97 📈
(Org: 105)
(2,821)
- 2,821
98 📈
(Org: 107)
(2,808)
0.03 2,808
99 📈
(Org: 106)
(2,751)
0 2,751
100 📈
(Org: 108)
(2,686)
- 2,686