Top 100 Most Popular Boy Baby Names by Pronunciation in the US 1957 - 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)
(97,858)
0.05 97,858
2 ➡️
(Org: 2)
(84,353)
0 84,353
3 📈
(Org: 5)
(82,527)
0.04 82,527
4 📉
(Org: 3)
(82,415)
0 82,415
5 📉
(Org: 4)
(81,800)
0 81,800
6 ➡️
(Org: 6)
(56,893)
0 56,893
7 📈
(Org: 10)
(56,582)
0.35 56,582
8 📉
(Org: 7)
(55,330)
0.04 55,330
9 📉
(Org: 8)
(52,476)
0 52,476
10 📉
(Org: 9)
(44,829)
0 44,829
11 ➡️
(Org: 11)
(34,290)
0 34,290
12 📈
(Org: 21)
(32,943)
0.27 32,943
13 📉
(Org: 12)
(32,220)
0.01 32,220
14 📉
(Org: 13)
(29,613)
0 29,613
15 📉
(Org: 14)
(28,082)
0 28,082
16 📉
(Org: 15)
(27,909)
- 27,909
17 📉
(Org: 16)
(27,635)
0.01 27,635
18 📉
(Org: 17)
(27,260)
0 27,260
19 📉
(Org: 18)
(27,018)
0 27,018
20 📉
(Org: 19)
(24,769)
0 24,769
21 📉
(Org: 20)
(24,420)
0.01 24,420
22 ➡️
(Org: 22)
(22,004)
0 22,004
23 ➡️
(Org: 23)
(21,573)
0 21,573
24 📈
(Org: 26)
(21,250)
0.18 21,250
25 ➡️
(Org: 25)
(18,716)
0 18,716
26 📈
(Org: 28)
(17,307)
0.02 17,307
27 ➡️
(Org: 27)
(17,069)
0 17,069
28 📈
(Org: 29)
(16,903)
0 16,903
29 📈
(Org: 30)
(16,856)
0.01 16,856
30 📈
(Org: 31)
(16,574)
0.01 16,574
31 📈
(Org: 32)
(16,206)
0.03 16,206
32 📈
(Org: 33)
(15,676)
0 15,676
33 📈
(Org: 40)
(15,063)
0.3 15,063
34 ➡️
(Org: 34)
(13,882)
- 13,882
35 ➡️
(Org: 35)
(13,831)
0.04 13,831
36 ➡️
(Org: 36)
(12,500)
0.01 12,500
37 ➡️
(Org: 37)
(11,618)
0 11,618
38 📈
(Org: 68)
(11,603)
0.48 11,603
39 📉
(Org: 38)
(11,268)
- 11,268
40 📉
(Org: 39)
(10,828)
0 10,828
41 📈
(Org: 49)
(10,619)
0.23 10,619
42 📉
(Org: 41)
(10,387)
0 10,387
43 📉
(Org: 42)
(10,340)
0.05 10,340
44 📈
(Org: 46)
(9,651)
0.09 9,651
45 📈
(Org: 62)
(9,192)
0.32 9,192
46 📉
(Org: 43)
(9,094)
0.01 9,094
47 📉
(Org: 45)
(9,065)
0.03 9,065
48 📉
(Org: 44)
(8,908)
- 8,908
49 📉
(Org: 47)
(8,702)
0 8,702
50 📈
(Org: 73)
(8,275)
0.3 8,275
51 📉
(Org: 48)
(8,209)
- 8,209
52 📈
(Org: 59)
(8,145)
0.18 8,145
53 📉
(Org: 51)
(8,112)
0.06 8,112
54 📉
(Org: 50)
(7,892)
0 7,892
55 📉
(Org: 54)
(7,423)
0.03 7,423
56 📉
(Org: 53)
(7,247)
- 7,247
57 📉
(Org: 55)
(7,178)
0.02 7,178
58 📈
(Org: 77)
(7,172)
0.21 7,172
59 📈
(Org: 60)
(7,078)
0.06 7,078
60 📉
(Org: 56)
(6,996)
- 6,996
61 📉
(Org: 57)
(6,809)
0.01 6,809
62 📉
(Org: 58)
(6,706)
- 6,706
63 📉
(Org: 61)
(6,607)
0.02 6,607
64 ➡️
(Org: 64)
(6,372)
0.04 6,372
65 📉
(Org: 63)
(6,257)
0.01 6,257
66 ➡️
(Org: 66)
(6,116)
0.01 6,116
67 📉
(Org: 65)
(6,107)
0.01 6,107
68 📉
(Org: 67)
(6,078)
0.01 6,078
69 📈
(Org: 71)
(6,014)
0.03 6,014
70 📉
(Org: 69)
(5,979)
0 5,979
71 📉
(Org: 70)
(5,869)
0 5,869
72 ➡️
(Org: 72)
(5,810)
0 5,810
73 📈
(Org: 78)
(5,791)
0.03 5,791
74 ➡️
(Org: 74)
(5,759)
0 5,759
75 ➡️
(Org: 75)
(5,757)
0 5,757
76 ➡️
(Org: 76)
(5,717)
0 5,717
77 📈
(Org: 80)
(5,623)
0.05 5,623
78 📈
(Org: 83)
(5,493)
0.05 5,493
79 📈
(Org: 90)
(5,340)
0.14 5,340
80 📈
(Org: 82)
(5,307)
0.01 5,307
81 ➡️
(Org: 81)
(5,282)
0 5,282
82 📈
(Org: 99)
(5,232)
0.23 5,232
83 📈
(Org: 86)
(5,045)
0.07 5,045
83 📈
(Org: 84)
(5,045)
- 5,045
85 📈
(Org: 87)
(4,711)
0.01 4,711
86 📈
(Org: 88)
(4,648)
0 4,648
87 📈
(Org: 89)
(4,615)
- 4,615
88 📈
(Org: 127)
(4,518)
0.34 4,518
88 📈
(Org: 94)
(4,518)
0.04 4,518
90 📈
(Org: 93)
(4,426)
0.01 4,426
91 📈
(Org: 101)
(4,418)
0.14 4,418
91 📈
(Org: 92)
(4,418)
0 4,418
93 📉
(Org: 91)
(4,413)
- 4,413
94 📈
(Org: 95)
(4,342)
0.05 4,342
95 📈
(Org: 96)
(4,124)
0.01 4,124
96 📈
(Org: 97)
(4,099)
0 4,099
97 📈
(Org: 98)
(4,081)
- 4,081
98 📈
(Org: 133)
(3,823)
0.28 3,823
99 📈
(Org: 100)
(3,806)
- 3,806
100 📈
(Org: 119)
(3,724)
0.13 3,724