Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1958 - 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)
(95,413)
0.05 95,413
2 ➡️
(Org: 2)
(82,689)
0 82,689
3 📈
(Org: 5)
(79,521)
0.04 79,521
4 📉
(Org: 3)
(78,779)
0 78,779
5 📉
(Org: 4)
(77,365)
0 77,365
6 📈
(Org: 7)
(55,100)
0.04 55,100
7 📉
(Org: 6)
(54,318)
0 54,318
8 📈
(Org: 10)
(50,938)
0.35 50,938
9 📉
(Org: 8)
(50,039)
0 50,039
10 📉
(Org: 9)
(42,299)
0.01 42,299
11 📈
(Org: 21)
(32,562)
0.26 32,562
12 📉
(Org: 11)
(32,262)
0 32,262
13 📉
(Org: 12)
(30,433)
0.01 30,433
14 📉
(Org: 13)
(28,826)
0 28,826
15 📉
(Org: 14)
(26,707)
0 26,707
16 📉
(Org: 15)
(26,265)
0 26,265
17 📉
(Org: 16)
(25,867)
0.01 25,867
18 📉
(Org: 17)
(25,347)
0 25,347
19 📉
(Org: 18)
(25,015)
- 25,015
20 📉
(Org: 19)
(24,890)
0 24,890
21 📉
(Org: 20)
(24,807)
0.01 24,807
22 📈
(Org: 24)
(23,761)
0.19 23,761
23 📉
(Org: 22)
(20,158)
0 20,158
24 📉
(Org: 23)
(19,916)
0.01 19,916
25 ➡️
(Org: 25)
(19,740)
0.03 19,740
26 📈
(Org: 34)
(18,075)
0.26 18,075
27 ➡️
(Org: 27)
(17,434)
0 17,434
28 ➡️
(Org: 28)
(17,375)
- 17,375
29 ➡️
(Org: 29)
(16,831)
0.02 16,831
30 ➡️
(Org: 30)
(15,911)
0.01 15,911
31 ➡️
(Org: 31)
(15,672)
0 15,672
32 ➡️
(Org: 32)
(15,286)
0.01 15,286
33 ➡️
(Org: 33)
(15,062)
0 15,062
34 📈
(Org: 35)
(13,480)
0.04 13,480
35 📈
(Org: 36)
(12,475)
- 12,475
36 📈
(Org: 37)
(11,957)
0 11,957
37 📈
(Org: 38)
(11,326)
- 11,326
38 📈
(Org: 39)
(11,231)
0.01 11,231
39 📈
(Org: 67)
(11,152)
0.48 11,152
40 ➡️
(Org: 40)
(10,779)
- 10,779
41 ➡️
(Org: 41)
(10,775)
0 10,775
42 ➡️
(Org: 42)
(10,274)
0 10,274
43 ➡️
(Org: 43)
(10,227)
0 10,227
44 📈
(Org: 51)
(10,151)
0.24 10,151
45 📉
(Org: 44)
(10,082)
- 10,082
46 📉
(Org: 45)
(9,176)
0.03 9,176
47 ➡️
(Org: 47)
(8,823)
0.05 8,823
48 📈
(Org: 50)
(8,687)
0.06 8,687
49 📉
(Org: 46)
(8,542)
0 8,542
50 📉
(Org: 48)
(8,345)
0 8,345
51 📈
(Org: 52)
(8,320)
0.09 8,320
52 📈
(Org: 77)
(8,258)
0.34 8,258
53 📉
(Org: 49)
(8,226)
- 8,226
54 📈
(Org: 66)
(8,128)
0.28 8,128
55 📈
(Org: 62)
(7,808)
0.19 7,808
56 📉
(Org: 53)
(7,415)
0.02 7,415
57 📈
(Org: 58)
(7,365)
0.07 7,365
58 📉
(Org: 54)
(7,333)
0.02 7,333
59 📉
(Org: 57)
(7,162)
0.03 7,162
60 📉
(Org: 55)
(7,115)
- 7,115
61 📉
(Org: 56)
(7,087)
0 7,087
62 📈
(Org: 73)
(6,966)
0.19 6,966
63 📉
(Org: 60)
(6,735)
0.05 6,735
64 📉
(Org: 61)
(6,436)
0.02 6,436
65 📉
(Org: 64)
(6,345)
0.03 6,345
66 📉
(Org: 63)
(6,313)
- 6,313
67 📈
(Org: 69)
(5,895)
0.03 5,895
68 ➡️
(Org: 68)
(5,872)
0.01 5,872
69 📉
(Org: 65)
(5,865)
- 5,865
70 ➡️
(Org: 70)
(5,743)
0.01 5,743
71 📈
(Org: 72)
(5,704)
0.01 5,704
72 📉
(Org: 71)
(5,681)
0 5,681
73 📈
(Org: 75)
(5,575)
0.01 5,575
74 ➡️
(Org: 74)
(5,561)
0 5,561
75 📈
(Org: 76)
(5,545)
0.01 5,545
76 📈
(Org: 82)
(5,535)
0.05 5,535
77 📈
(Org: 90)
(5,515)
0.14 5,515
78 ➡️
(Org: 78)
(5,462)
0 5,462
79 📈
(Org: 80)
(5,359)
0.01 5,359
80 📉
(Org: 79)
(5,348)
0 5,348
81 📈
(Org: 105)
(5,267)
0.28 5,267
82 📈
(Org: 83)
(5,177)
0 5,177
83 📈
(Org: 84)
(5,155)
0 5,155
84 📈
(Org: 85)
(5,114)
0.01 5,114
85 📈
(Org: 86)
(5,047)
0 5,047
86 📈
(Org: 93)
(5,027)
0.11 5,027
87 📈
(Org: 88)
(4,925)
0 4,925
88 📉
(Org: 87)
(4,922)
- 4,922
89 📈
(Org: 94)
(4,838)
0.08 4,838
90 📉
(Org: 89)
(4,810)
- 4,810
91 📈
(Org: 110)
(4,761)
0.24 4,761
92 ➡️
(Org: 92)
(4,525)
- 4,525
93 📈
(Org: 96)
(4,387)
0.01 4,387
94 📈
(Org: 95)
(4,364)
- 4,364
95 📈
(Org: 100)
(4,359)
0.05 4,359
96 📈
(Org: 97)
(4,347)
0.01 4,347
97 📈
(Org: 98)
(4,293)
0.01 4,293
98 📈
(Org: 99)
(4,220)
- 4,220
99 📈
(Org: 102)
(4,178)
0.04 4,178
100 📈
(Org: 113)
(4,150)
0.15 4,150