Top 100 Most Popular Boy Baby Names by Pronunciation in the US 2014 - 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: 18)
(25,191)
0.51 25,191
2 📈
(Org: 15)
(20,174)
0.36 20,174
3 📈
(Org: 14)
(19,660)
0.32 19,660
4 📉
(Org: 1)
(19,438)
0.01 19,438
5 📉
(Org: 2)
(18,656)
0.01 18,656
6 📉
(Org: 3)
(17,915)
0.04 17,915
7 📉
(Org: 4)
(17,208)
0.02 17,208
8 📉
(Org: 5)
(16,870)
0 16,870
9 📉
(Org: 7)
(15,995)
0.03 15,995
10 📉
(Org: 6)
(15,824)
0 15,824
11 📉
(Org: 8)
(15,465)
0 15,465
12 📉
(Org: 9)
(14,513)
0 14,513
13 📉
(Org: 11)
(14,083)
0.01 14,083
14 📉
(Org: 10)
(14,069)
0.01 14,069
15 📈
(Org: 19)
(13,921)
0.13 13,921
16 📉
(Org: 12)
(13,897)
0.01 13,897
17 📉
(Org: 13)
(13,799)
0.01 13,799
18 📉
(Org: 16)
(13,576)
0.05 13,576
19 📈
(Org: 38)
(13,497)
0.33 13,497
20 📈
(Org: 68)
(13,094)
0.52 13,094
21 📈
(Org: 27)
(12,853)
0.17 12,853
22 📉
(Org: 17)
(12,258)
0 12,258
23 📉
(Org: 20)
(12,214)
0.01 12,214
24 📈
(Org: 35)
(12,072)
0.23 12,072
25 📉
(Org: 21)
(11,611)
- 11,611
26 📈
(Org: 90)
(11,584)
0.59 11,584
27 📈
(Org: 30)
(11,366)
0.09 11,366
28 📈
(Org: 29)
(11,288)
0.08 11,288
29 📉
(Org: 22)
(11,187)
- 11,187
30 📉
(Org: 24)
(11,119)
0.01 11,119
31 📉
(Org: 26)
(11,117)
0.04 11,117
32 📉
(Org: 23)
(11,060)
0 11,060
33 📉
(Org: 25)
(10,984)
0.01 10,984
34 📉
(Org: 31)
(10,806)
0.08 10,806
35 📉
(Org: 28)
(10,608)
0.01 10,608
36 📈
(Org: 63)
(10,255)
0.36 10,255
37 📈
(Org: 43)
(10,181)
0.19 10,181
38 📈
(Org: 52)
(9,883)
0.27 9,883
39 📈
(Org: 57)
(9,707)
0.3 9,707
40 📈
(Org: 44)
(9,642)
0.16 9,642
41 📉
(Org: 33)
(9,545)
0.01 9,545
42 📉
(Org: 32)
(9,473)
0 9,473
43 📉
(Org: 34)
(9,358)
0 9,358
44 📉
(Org: 37)
(9,172)
0.01 9,172
45 📉
(Org: 36)
(9,164)
0 9,164
46 📉
(Org: 41)
(9,083)
0.04 9,083
47 📉
(Org: 39)
(8,954)
0.01 8,954
48 📈
(Org: 62)
(8,896)
0.26 8,896
49 📉
(Org: 40)
(8,838)
- 8,838
50 📉
(Org: 42)
(8,479)
- 8,479
51 📈
(Org: 53)
(8,364)
0.15 8,364
52 📉
(Org: 45)
(8,146)
0.01 8,146
53 📈
(Org: 65)
(8,094)
0.21 8,094
54 📉
(Org: 48)
(7,893)
0.03 7,893
55 📈
(Org: 69)
(7,841)
0.2 7,841
56 📉
(Org: 47)
(7,811)
0.02 7,811
57 📉
(Org: 50)
(7,785)
0.05 7,785
58 📉
(Org: 49)
(7,688)
0.02 7,688
59 📉
(Org: 54)
(7,442)
0.05 7,442
60 📉
(Org: 51)
(7,360)
- 7,360
61 📉
(Org: 55)
(7,240)
0.05 7,240
62 📈
(Org: 75)
(7,098)
0.22 7,098
63 📉
(Org: 56)
(6,895)
- 6,895
64 📉
(Org: 58)
(6,750)
0 6,750
65 📉
(Org: 59)
(6,706)
- 6,706
66 📉
(Org: 60)
(6,660)
- 6,660
67 📉
(Org: 61)
(6,650)
0 6,650
68 📉
(Org: 64)
(6,496)
0 6,496
69 📉
(Org: 66)
(6,459)
0.02 6,459
70 📉
(Org: 67)
(6,318)
0 6,318
71 ➡️
(Org: 71)
(6,122)
0.04 6,122
72 📉
(Org: 70)
(6,019)
0.02 6,019
73 📈
(Org: 77)
(5,921)
0.08 5,921
74 📉
(Org: 72)
(5,916)
0.01 5,916
75 📈
(Org: 82)
(5,889)
0.12 5,889
76 📈
(Org: 122)
(5,832)
0.43 5,832
77 📈
(Org: 149)
(5,828)
0.53 5,828
78 ➡️
(Org: 78)
(5,792)
0.07 5,792
79 📈
(Org: 91)
(5,780)
0.2 5,780
80 📉
(Org: 73)
(5,720)
- 5,720
81 📉
(Org: 76)
(5,485)
- 5,485
82 📈
(Org: 102)
(5,398)
0.28 5,398
83 📉
(Org: 79)
(5,362)
0 5,362
84 📈
(Org: 108)
(5,359)
0.31 5,359
85 📈
(Org: 89)
(5,306)
0.1 5,306
86 📉
(Org: 80)
(5,300)
0.01 5,300
87 📈
(Org: 124)
(5,290)
0.38 5,290
88 📉
(Org: 81)
(5,222)
0 5,222
89 📉
(Org: 86)
(5,050)
0.04 5,050
90 📉
(Org: 83)
(5,033)
0.01 5,033
91 📉
(Org: 84)
(4,978)
0.01 4,978
92 📉
(Org: 87)
(4,898)
0.02 4,898
93 📉
(Org: 88)
(4,811)
0 4,811
94 📉
(Org: 93)
(4,806)
0.1 4,806
95 📈
(Org: 142)
(4,786)
0.4 4,786
96 📈
(Org: 106)
(4,642)
0.19 4,642
97 📈
(Org: 117)
(4,453)
0.23 4,453
98 📉
(Org: 92)
(4,391)
0.01 4,391
99 ➡️
(Org: 99)
(4,367)
0.11 4,367
100 📉
(Org: 95)
(4,277)
0.04 4,277