Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2000 - 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)
(34,665)
0.01 34,665
2 ➡️
(Org: 2)
(33,282)
0.04 33,282
3 ➡️
(Org: 3)
(29,945)
0.05 29,945
4 📈
(Org: 6)
(29,407)
0.16 29,407
5 📉
(Org: 4)
(27,730)
0.01 27,730
6 📉
(Org: 5)
(26,919)
0.07 26,919
7 ➡️
(Org: 7)
(23,657)
- 23,657
8 📈
(Org: 15)
(23,063)
0.14 23,063
9 📉
(Org: 8)
(22,982)
0.01 22,982
10 📉
(Org: 9)
(22,500)
0.01 22,500
11 📉
(Org: 10)
(21,979)
0.02 21,979
12 ➡️
(Org: 12)
(21,318)
0.05 21,318
13 📈
(Org: 21)
(21,007)
0.2 21,007
14 ➡️
(Org: 14)
(20,939)
0.04 20,939
15 📉
(Org: 11)
(20,700)
0 20,700
16 📉
(Org: 13)
(20,360)
0 20,360
17 📈
(Org: 30)
(20,291)
0.36 20,291
18 📉
(Org: 16)
(19,792)
0 19,792
19 📉
(Org: 17)
(19,655)
- 19,655
20 📉
(Org: 19)
(18,102)
0.02 18,102
21 📉
(Org: 18)
(18,031)
0 18,031
22 📈
(Org: 24)
(17,861)
0.14 17,861
23 📉
(Org: 20)
(17,313)
0 17,313
24 📉
(Org: 23)
(16,211)
0.02 16,211
25 📉
(Org: 22)
(16,057)
- 16,057
26 📈
(Org: 43)
(15,757)
0.43 15,757
27 📉
(Org: 25)
(15,296)
0 15,296
28 📉
(Org: 26)
(14,982)
0.01 14,982
29 📉
(Org: 27)
(14,354)
0.01 14,354
30 📉
(Org: 28)
(14,294)
0.01 14,294
31 ➡️
(Org: 31)
(14,012)
0.09 14,012
32 📈
(Org: 42)
(13,839)
0.34 13,839
33 📉
(Org: 29)
(13,739)
- 13,739
34 📉
(Org: 33)
(13,153)
0.04 13,153
35 📈
(Org: 36)
(12,990)
0.06 12,990
36 📉
(Org: 32)
(12,946)
0.02 12,946
37 📈
(Org: 38)
(12,635)
0.22 12,635
38 📉
(Org: 34)
(12,585)
- 12,585
39 📉
(Org: 35)
(12,547)
0 12,547
40 📉
(Org: 37)
(12,001)
0 12,001
41 📈
(Org: 54)
(11,505)
0.36 11,505
42 📈
(Org: 57)
(11,010)
0.34 11,010
43 📉
(Org: 39)
(10,674)
0.08 10,674
44 📈
(Org: 50)
(10,415)
0.28 10,415
45 📉
(Org: 41)
(10,036)
0.05 10,036
46 📉
(Org: 40)
(9,767)
0 9,767
47 ➡️
(Org: 47)
(8,905)
0.1 8,905
48 📉
(Org: 44)
(8,813)
0.01 8,813
49 📉
(Org: 46)
(8,352)
0.03 8,352
49 📈
(Org: 60)
(8,352)
0.15 8,352
51 📈
(Org: 53)
(8,304)
0.1 8,304
52 📉
(Org: 45)
(8,159)
0 8,159
53 📉
(Org: 49)
(8,018)
0.04 8,018
54 📈
(Org: 56)
(7,849)
0.07 7,849
55 📉
(Org: 48)
(7,711)
- 7,711
56 📉
(Org: 52)
(7,591)
0.02 7,591
57 📉
(Org: 51)
(7,524)
- 7,524
58 📉
(Org: 55)
(7,353)
0 7,353
59 ➡️
(Org: 59)
(7,286)
0.02 7,286
60 📉
(Org: 58)
(7,277)
0 7,277
61 📈
(Org: 74)
(6,807)
0.14 6,807
62 ➡️
(Org: 62)
(6,773)
0 6,773
63 📈
(Org: 79)
(6,735)
0.22 6,735
63 ➡️
(Org: 63)
(6,735)
0 6,735
65 📉
(Org: 64)
(6,658)
0.02 6,658
66 📈
(Org: 72)
(6,620)
0.11 6,620
67 📈
(Org: 117)
(6,551)
0.5 6,551
68 📈
(Org: 69)
(6,507)
0.05 6,507
69 📉
(Org: 65)
(6,366)
0 6,366
70 📉
(Org: 68)
(6,340)
0.01 6,340
71 📉
(Org: 66)
(6,322)
- 6,322
72 📉
(Org: 67)
(6,306)
- 6,306
73 📉
(Org: 71)
(6,304)
0.06 6,304
74 📉
(Org: 73)
(6,245)
0.06 6,245
75 ➡️
(Org: 75)
(5,967)
0.04 5,967
76 ➡️
(Org: 76)
(5,682)
- 5,682
77 ➡️
(Org: 77)
(5,667)
0.04 5,667
78 📈
(Org: 83)
(5,611)
0.14 5,611
79 📈
(Org: 121)
(5,411)
0.41 5,411
80 📉
(Org: 78)
(5,341)
- 5,341
81 📉
(Org: 80)
(5,176)
0.01 5,176
82 📈
(Org: 90)
(5,174)
0.13 5,174
83 📈
(Org: 154)
(5,120)
0.51 5,120
84 📉
(Org: 81)
(5,077)
0.01 5,077
85 📈
(Org: 106)
(5,039)
0.3 5,039
86 📉
(Org: 82)
(4,930)
0.01 4,930
87 📉
(Org: 84)
(4,858)
0.02 4,858
88 📈
(Org: 104)
(4,803)
0.26 4,803
89 📉
(Org: 86)
(4,721)
0.01 4,721
90 📉
(Org: 85)
(4,719)
0.01 4,719
91 📉
(Org: 88)
(4,707)
0.03 4,707
92 📈
(Org: 149)
(4,700)
0.45 4,700
93 📉
(Org: 92)
(4,684)
0.08 4,684
94 📉
(Org: 87)
(4,678)
0.02 4,678
95 📈
(Org: 118)
(4,634)
0.3 4,634
96 📈
(Org: 199)
(4,627)
0.62 4,627
97 📉
(Org: 91)
(4,546)
0.02 4,546
98 📉
(Org: 89)
(4,527)
0 4,527
99 📈
(Org: 110)
(4,280)
0.2 4,280
100 📉
(Org: 93)
(4,235)
- 4,235