Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1989 - 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)
(67,670)
0.03 67,670
2 ➡️
(Org: 2)
(56,455)
0.06 56,455
3 ➡️
(Org: 3)
(47,607)
0.05 47,607
4 ➡️
(Org: 4)
(44,375)
0.01 44,375
5 📈
(Org: 6)
(35,346)
0.01 35,346
6 📉
(Org: 5)
(35,241)
0 35,241
7 ➡️
(Org: 7)
(34,846)
0 34,846
8 ➡️
(Org: 8)
(33,277)
0.01 33,277
9 ➡️
(Org: 9)
(32,816)
0 32,816
10 📈
(Org: 12)
(31,402)
0.05 31,402
11 📈
(Org: 14)
(31,218)
0.1 31,218
12 📈
(Org: 22)
(30,679)
0.38 30,679
13 📉
(Org: 11)
(30,122)
0.01 30,122
14 📉
(Org: 10)
(30,082)
0 30,082
15 📈
(Org: 17)
(29,265)
0.19 29,265
16 📉
(Org: 13)
(28,504)
0 28,504
17 📈
(Org: 24)
(26,319)
0.31 26,319
18 📉
(Org: 15)
(24,732)
0 24,732
19 📉
(Org: 18)
(24,464)
0.05 24,464
20 📉
(Org: 16)
(24,432)
0 24,432
21 ➡️
(Org: 21)
(23,740)
0.2 23,740
22 📉
(Org: 19)
(21,360)
0.01 21,360
23 📉
(Org: 20)
(20,911)
0 20,911
24 📈
(Org: 25)
(20,302)
0.11 20,302
25 📈
(Org: 39)
(18,866)
0.37 18,866
26 📉
(Org: 23)
(18,829)
0.02 18,829
27 📉
(Org: 26)
(17,853)
0 17,853
28 📉
(Org: 27)
(16,949)
0 16,949
29 📉
(Org: 28)
(16,458)
0 16,458
30 📈
(Org: 37)
(15,986)
0.25 15,986
31 ➡️
(Org: 31)
(15,941)
0.04 15,941
32 📉
(Org: 29)
(15,936)
0.01 15,936
33 📈
(Org: 55)
(15,910)
0.5 15,910
34 📉
(Org: 30)
(15,835)
0.02 15,835
35 📈
(Org: 43)
(15,293)
0.29 15,293
36 📉
(Org: 32)
(14,638)
0.01 14,638
37 📉
(Org: 33)
(14,156)
0 14,156
38 📉
(Org: 34)
(13,535)
0.03 13,535
39 📈
(Org: 42)
(13,230)
0.14 13,230
40 📉
(Org: 35)
(13,093)
0.04 13,093
41 📈
(Org: 54)
(12,947)
0.35 12,947
42 📉
(Org: 36)
(12,245)
- 12,245
43 📉
(Org: 38)
(12,081)
0.01 12,081
44 📈
(Org: 45)
(11,887)
0.09 11,887
45 📉
(Org: 41)
(11,539)
0 11,539
46 📉
(Org: 44)
(11,532)
0.06 11,532
47 📉
(Org: 46)
(10,330)
- 10,330
48 📈
(Org: 50)
(10,246)
0.14 10,246
49 📉
(Org: 47)
(10,229)
0.01 10,229
50 📉
(Org: 48)
(9,802)
0.01 9,802
51 📉
(Org: 49)
(9,034)
0 9,034
52 📉
(Org: 51)
(8,944)
0.01 8,944
53 📉
(Org: 52)
(8,871)
0.01 8,871
54 📉
(Org: 53)
(8,562)
0 8,562
55 📈
(Org: 75)
(8,163)
0.42 8,163
56 📈
(Org: 57)
(7,630)
0.08 7,630
57 📈
(Org: 58)
(7,292)
0.04 7,292
58 📈
(Org: 59)
(7,063)
0.03 7,063
59 📈
(Org: 60)
(6,560)
0 6,560
60 📈
(Org: 64)
(5,979)
0.06 5,979
61 📈
(Org: 62)
(5,849)
- 5,849
62 📈
(Org: 63)
(5,780)
- 5,780
63 📈
(Org: 66)
(5,427)
0 5,427
64 📈
(Org: 73)
(5,412)
0.1 5,412
65 📈
(Org: 67)
(5,400)
0 5,400
66 📈
(Org: 71)
(5,163)
0.06 5,163
67 📈
(Org: 68)
(5,074)
0.02 5,074
68 📈
(Org: 81)
(4,973)
0.11 4,973
69 📈
(Org: 70)
(4,946)
0.01 4,946
70 📉
(Org: 69)
(4,931)
0 4,931
71 📈
(Org: 72)
(4,926)
0.01 4,926
72 📈
(Org: 74)
(4,828)
0.02 4,828
73 📈
(Org: 76)
(4,751)
0.01 4,751
74 📈
(Org: 77)
(4,637)
- 4,637
75 📈
(Org: 78)
(4,626)
- 4,626
76 📈
(Org: 79)
(4,604)
0.02 4,604
77 📈
(Org: 80)
(4,556)
0.01 4,556
78 📈
(Org: 91)
(4,456)
0.15 4,456
79 📈
(Org: 90)
(4,440)
0.13 4,440
80 📈
(Org: 83)
(4,357)
0.04 4,357
81 📈
(Org: 82)
(4,323)
- 4,323
82 📈
(Org: 86)
(4,122)
0 4,122
83 📈
(Org: 85)
(4,111)
- 4,111
84 📈
(Org: 87)
(4,079)
0.01 4,079
85 📈
(Org: 88)
(3,959)
0 3,959
86 📈
(Org: 93)
(3,954)
0.08 3,954
87 📈
(Org: 115)
(3,905)
0.27 3,905
87 📈
(Org: 89)
(3,905)
- 3,905
89 📈
(Org: 102)
(3,862)
0.14 3,862
90 📈
(Org: 98)
(3,762)
0.08 3,762
91 📈
(Org: 92)
(3,744)
0.01 3,744
92 📈
(Org: 126)
(3,739)
0.3 3,739
93 📈
(Org: 96)
(3,648)
0.01 3,648
94 📈
(Org: 111)
(3,644)
0.19 3,644
95 📉
(Org: 94)
(3,635)
- 3,635
96 📈
(Org: 97)
(3,523)
- 3,523
97 📈
(Org: 100)
(3,418)
- 3,418
98 📈
(Org: 106)
(3,387)
0.08 3,387
99 📈
(Org: 105)
(3,295)
0.04 3,295
100 📈
(Org: 103)
(3,291)
- 3,291