How to name your child: a scientific approach

As of the time of this writing, by hook or by crook, I am within three weeks of becoming a first-time father.  Yes, yes, it’s all very exciting.  I’m sure my future son will read this post in the year 2030 while drinking a 36-hour energy drink and rolling his eyes, but until then, let me tell you the story of how my wife and I approached naming him.

Estimated reading time: 20 minutes

Initial approach

Honestly, the name was the first material bit of responsibility that confronted me on this journey.  All of the other stuff (impending late nights, biohazardous diapers, pierced eardrums) were mostly theoretical and to a large degree still are before birth.  I’m sure I’ll write a post in the future about all the little things I did to prepare for that day, but none weighed heavier or bothered me more than the name.

I’m sure most people start with their own names, or names of those closest to them.  Michael is a legitimately cool name — for a guy with a weird last name, I was always grateful to my parents for choosing a simple, strong first name and thus avoiding the most obvious transgressions of 1980s naming conventions (all the Codys and the Aarons say whaaaat!).

I first downloaded an app called BabyName on my iPhone. It’s basically like Tinder for naming your baby — you and your partner swipe through a ton of names and those you both ‘swipe right’ on are saved as ‘matches’.  A small smattering of our matches are shown in the image to the left here.

I’m pretty sure I went through every name in their database — I guess I was waiting to be bowled over by that ‘name’ that just jumps out at you as being simultaneously brilliant, and fun, and intelligent, and unique, yet traditional.  That had more or less happened when naming my dogs and I honestly thought this was all a function of going through enough names.

There wasn’t a limit to the lists of names I read.  I waded through Nobel Prize winners.  I read all 5753 members of the  “Persons eligible to succeed to the British Throne as of 1 Jan 2011” list.  I read lists of famous authors, generals, Canadians, actors, humanitarians, and Hockey Hall of Fame members (Hap Day, represent). Nothing really jumped out at me.

Initially I was heavily cheering for a girl simply because I found it much easier to get behind girls’ names.  Whether they’re simply more aesthetic or I’ve just disliked more males to ruin name associations is not entirely clear.  Best laid plans being what they are, of course we found out we were having a boy and I begrudgingly threw away all my Eloises and Adas.  Alright — what now smart guy? I decided to pore over some studies.

12 naming lessons from academic studies

I did some light googling and dug up with the following truths on how to name your child (especially in western English-speaking countries):

  1. Don’t use unusual, invented, or oddly-spelled names
  2. Children with alternative spellings of more common names have been shown to have slowed spelling and reading capabilities. One study showed that men with uncommon names were “more likely to drop out of school and be lonely later in life“. A 1960s investigation into psychiatric records found people given uncommon names were diagnosed as psychotic at a higher rate, while more recent research has shown that “boys with the least popular names are more likely to commit crime“.

  3. Don’t give boys a feminine or androgynous name
  4. While I realize some parents like to challenge societal norms, research has shown that boys who were given more feminine sounding names “tend to misbehave disproportionately upon entry to middle school, as compared to other boys and to their previous (relative) behavior patterns”.  Boys with feminine names are more likely to be taunted starting in middle school, which potentially compels them to act out as a means to prove their masculinity.

  5. Don’t use names that are likely to be given by parents of low socioeconomic status
  6. This one’s a bit messy. While books like Freakonomics brought to a wide audience the topic of race-based name discrimination, more recent research has added the even more important negative influence of low socioeconomic status names in general. The author created a way to rate the ‘status’ of a name on a sliding scale, and found that “the further along this scale he went, the worse the school test scores and the less likely the student was to be recommended for the schools’ programme for “gifted” students. Strikingly, this held true for brothers within a family, and even – although the sample size was small – for twins”. The major hypothesized reason for this is because of lowered perceptions of teachers and authority-figures of students with low status names — essentially a self-fulfilling negative feedback loop.

  7. Stay away from traditional ethnic names (unless you have Asian ancestry)
  8. Related to the above concept, studies have shown implicit bias in the perception of strongly ethnic names. In one famous study, authors created fake resumes using both black- and white-sounding names. The white-sounding applicants received a call-back for every 10 resumes sent, while the black-sounding applicants needed to apply to 15 jobs to receive one callback. Interestingly though, one study found that “an Asian child with a name such as ‘Vivek’ is more likely to be referred to the gifted program, conditional on test scores, and is more likely to have high mathematics test scores than an Asian child with a name such as ‘Alex'”. Again, this could be due to teachers’ enhanced perceptions of the mathematical ability of a child with an Asian-sounding name, which is then reinforced in the child.

  9. Keep in mind that initials and phonetic anchors have powerful effects
  10. This one is mostly silly, but still interesting. One study found that people are subconsciously drawn to live in cities which sound like their name (think Phil moving to Philadelphia), live in cities that have their birth day number in their name (eg people born August 2nd moving to Two Hills), and pursue careers which sound like their names (Dennis the dentist). I read somewhere that people are more likely to pursue professional designations and work at companies that resemble their initials (Michael Parkatti, Member of Parliament?). Related to this is my general belief of avoiding phonetic relationships to negatively perceived words (eg Oscar –> scar).

  11. All things being equal, choose names earlier in the alphabet
  12. Researchers in 2006 found that people with surnames starting with letters earlier in the alphabet were “markedly more likely to work in prestigious university departments and win a Nobel Prize”, along with several other proxies for professional success. These same researchers later conducted a survey of 15,000 people and asked them to self-rate themselves on career, financial, health, and general success measures. There was a clear pattern — “the further down the alphabet your surname came, the less likely you were to be successful“. The hypothesized link here is that children who are arranged earlier on alphabetized lists of names in grade school feel somewhat “special” compared to their peers.

  13. Strong (think royal) names have been rated as likely to be borne by people who are more intelligent and successful
  14. A 2008 study in the UK found that in a survey of 6000 people rating 40 common names, royal-related names came out on top in terms of their perceived intelligence and success. A separate German study found that people with noble-sounding names such as Kaiser were found in management roles in their organization at a higher rate than people with commoner-sounding names like Koch (“cook”).

  15. Ensure the name is easy to spell and say
  16. A 2012 study out of NYU found that people with easy to pronounce names were a) more likely to receive job promotions, b) more likely to win political races against opponents with harder to pronounce names, and c) attorneys with more pronounceable names rose more quickly to superior positions in their firm hierarchies.

  17. Pick a name with a lower Scrabble score
  18. Because of my love of Scrabble, this one hit home — a study found that one of the major determinants of low socio-economic status names was use of low-frequency consonants. This trait was most easily characterized by segmenting names that had Scrabble scores of 20 or higher.

  19. People with the least unique names are considered more likable
  20. A Marquette study with very simple conclusions found that names considered to be the least unique were considered more likable. To test this theory, researchers found that people with common names were more likely to be hired in a job competition, while those with rare names were the least likely to be hired.

  21. Pick a middle name with a flattering, complementary initial
  22. Another semi-silly entry — a 2014 study found that professional writers that used a middle initial in their published name had a) increased perceptions of their writing performance, b) higher perceptions of career status, and c) higher perceptions of intelligence. Awesomely, they found this effect increased for each middle initial used (David F.P.R. Clark received the highest reviews!).

  23. All things being equal, select a shorter name or a name that is commonly shortened
  24. A 2011 LinkedIn analysis of 100 million profiles found that names most associated with the CEO role are short or shortened names, such as Bob, Jack, and Bill. This has been speculated to be because men in power like to use nicknames to convey a sense of friendliness. I suppose that to accomplish this effect, you’d need to be setup with a non-complex non-unique name that can actually be shortened in a familiar fashion (William -> Bill Gates, Timothy -> Tim Cook).

Exploration into the history of names

The lessons of the previous section seemed pretty clear to me — it’s preferable to select short names that are simple to say, spell, and understand with non-exotic letters.  There’s also a clear incentive to use traditional names with a discernible noble streak in them.  That really sent me thinking — what is traditional in our cultural context?  Is that the Anglo-Saxon tradition?  Where did that come from?

Top 10 male names over a thousand years

RankEng-1120Eng-1260Eng-1415Eng-1570sEng-1620sEng-1825US - 1890sUS-1950s
1WillelmJohnJohnJohnJohnWilliamJohnJames
2RobertWilliamWilliamWilliamThomasJohnWilliamMichael
3RicardRobertThomasThomasWilliamGeorgeJamesRobert
4RadulfRichardRobertRobertRichardJamesGeorgeJohn
5RogerThomasRichardRichardRobertThomasCharlesDavid
6HerbertWalterNicholasGeorgeEdwardHenryJosephWilliam
7HugoHenryHenryRapheJamesCharlesFrankRichard
8JohannesAdamRogerChristopherGeorgeJosephRobertThomas
9AnschetillRogerRaufHenryHenryEdwardEdwardMark
10DrogoStephenWalterEdwardFrancisRobertHenryCharles

The above table shows a nice overview of the evolution of the most predominant English names across various points in the last thousand years.  Many of the first columns were gleaned from this fantastic read which goes into a ton of detail about both male and female names in England, while the last two columns using American names were sourced from here.

You can see the final traces of Anglo-Saxon Old English in the 1120 names — only Robert and Roger would be considered still common today among the proto-modern names (though I’m sure Game of Thrones fans all clapped at the appearance of “Drogo”!).  By 1260, however, you can clearly see a coalescence into names we all know and implicitly identify as ‘traditional’.

More interesting to me than the actual top names is the market share of these top names — what penetration did the, say, top 10 names have in English society throughout history compared to modern day Alberta?

Penetration of top names in different eras

Penetrion of:11201260141515101570s1610182519902015
Top 5 Names22.6%52.0%72.1%62.3%58.8%54.0%56.4%10.3%4.3%
Top 10 Names30.1%68.8%84.0%74.2%74.8%71.8%80.1%18.2%7.8%
Top 25 Names--93.2%-90.8%--33.5%16.6%
Top 100 Names--100.0%-99.6%--64.8%38.5%

What we see here is a clear parabola — the early Anglo-Saxon names were quite diffused among other choices, with the top 10 names accounting for only 30% of all men.  This penetration quickly shoots upwards, with the top 10 accounting for 69% by 1260 and 84% by the Battle of Agincourt in 1415.  If you had to call a peak for near universal first names in England, it seems like it would be around 1350, as many parts of England had over 90% penetration of the top 10 names around that time.

When you have that level of ubiquity, questions of what are and aren’t ‘traditional’ names become moot — you have the same names as everyone else.

So when does this strangle-hold break down?  Look at the last two columns in this chart, which show the 1990 and 2015 boy name penetrations seen in the province of Alberta.  There is an insanely-wide chasm seen between 1825 and 1990 where top 10 penetration drops from 80% and 18%.  I found one particular chart that broaches these two points in England in gory detail:

Obviously, societal attitudes towards names underwent a sea change in English society over this period.  Between the start of the 19th and 20th centuries, the top 10 male names dropped from 85% to 51% of the population — by 1994, this had fallen to 28%.

In 2015 in Alberta, the top 10 names accounted for only 7.8% of boy names given.  Hell, in 1415, 28% of all men were named John — in the current day, you’d need to add up the top 57 names in Alberta to account for a similar percentage!

For completeness sake (and because the Government only publishes full names in PDF format), I will paste the complete list of 1990 and 2015 Alberta boy names below.  You can easily search the list yourself to see how many boys were given your name in those years.  We’ll start with 1990…

1990 Complete List of Alberta Boys Names

NumberNamePercentage
570Michael2.6%
511Matthew2.3%
428Kyle1.9%
427Christopher1.9%
365Ryan1.6%
362Jordan1.6%
361Justin1.6%
344Daniel1.5%
342Joshua1.5%
337Tyler1.5%
322Andrew1.4%
298David1.3%
251Steven1.1%
245Jesse1.1%
245Kevin1.1%
241Cody1.1%
239James1.1%
223Robert1.0%
221Adam1.0%
205Nicholas0.9%
193Alexander0.9%
193Travis0.9%
189Brandon0.8%
179Scott0.8%
172Mark0.8%
168Jason0.8%
163Aaron0.7%
161Eric0.7%
161Sean0.7%
158Jonathan0.7%
155Dustin0.7%
154Brett0.7%
151Thomas0.7%
148Stephen0.7%
147Benjamin0.7%
146Joseph0.7%
144John0.6%
140Taylor0.6%
139Bradley0.6%
139William0.6%
136Jeffrey0.6%
131Dylan0.6%
131Nathan0.6%
127Mitchell0.6%
124Zachary0.6%
123Derek0.6%
122Patrick0.5%
120Richard0.5%
115Evan0.5%
111Joel0.5%
110Anthony0.5%
107Curtis0.5%
105Cameron0.5%
102Peter0.5%
100Jeremy0.4%
97Chad0.4%
90Brian0.4%
88Paul0.4%
87Shane0.4%
85Craig0.4%
84Cory0.4%
83Ian0.4%
83Trevor0.4%
81Colin0.4%
81Jacob0.4%
81Timothy0.4%
76Brendan0.3%
76Logan0.3%
76Samuel0.3%
75Corey0.3%
75Shawn0.3%
74Colton0.3%
73Gregory0.3%
72Jared0.3%
71Spencer0.3%
68Cole0.3%
66Kenneth0.3%
65Luke0.3%
63Devon0.3%
62Tyson0.3%
60Douglas0.3%
60Lucas0.3%
59Ethan0.3%
57Riley0.3%
55Mathew0.2%
54Devin0.2%
52Jamie0.2%
51Micheal0.2%
50Darren0.2%
49Dallas0.2%
49Keith0.2%
48Kristopher0.2%
47Bryce0.2%
45Connor0.2%
45Garrett0.2%
44Graham0.2%
43Brent0.2%
43Chase0.2%
43Clayton0.2%
41Austin0.2%
41Charles0.2%
41Marc0.2%
40Christian0.2%
40Tanner0.2%
39Erik0.2%
39Philip0.2%
38Adrian0.2%
38Calvin0.2%
38George0.2%
37Neil0.2%
37Raymond0.2%
37Vincent0.2%
36Alex0.2%
36Grant0.2%
36Troy0.2%
34Bryan0.2%
34Lee0.2%
34Stuart0.2%
33Johnathan0.1%
33Levi0.1%
33Shaun0.1%
32Darcy0.1%
32Geoffrey0.1%
32Landon0.1%
31Braden0.1%
31Carson0.1%
31Martin0.1%
30Kelly0.1%
29Dennis0.1%
29Drew0.1%
29Jessie0.1%
29Kurtis0.1%
29Owen0.1%
29Russell0.1%
29Sheldon0.1%
29Trent0.1%
28Nathaniel0.1%
28Randy0.1%
28Todd0.1%
28Wesley0.1%
27Dalton0.1%
27Donald0.1%
27Myles0.1%
26Blaine0.1%
26Morgan0.1%
25Brennan0.1%
25Dillon0.1%
25Gordon0.1%
25Julian0.1%
25Mackenzie0.1%
25Simon0.1%
24Caleb0.1%
24Dale0.1%
24Ross0.1%
23Alan0.1%
23Allan0.1%
23Blake0.1%
23Dean0.1%
23Derrick0.1%
23Edward0.1%
23Gary0.1%
23Lance0.1%
23Liam0.1%
23Phillip0.1%
23Tristan0.1%
22Blair0.1%
22Casey0.1%
22Donovan0.1%
22Jonathon0.1%
22Kirk0.1%
22Nolan0.1%
22Stefan0.1%
21Gabriel0.1%
21Jarrett0.1%
21Kurt0.1%
20Baby0.1%
20Jay0.1%
20Ty0.1%
20Warren0.1%
19Brayden0.1%
19Clinton0.1%
19Colby0.1%
19Jake0.1%
19Mason0.1%
19Maxwell0.1%
19Quinn0.1%
18Albert0.1%
18Brady0.1%
18Colten0.1%
18Jordon0.1%
18Wade0.1%
17Ashton0.1%
17Carl0.1%
17Chance0.1%
17Conrad0.1%
17Dakota0.1%
17Jeffery0.1%
17Kent0.1%
17Rory0.1%
17Terry0.1%
16Brenden0.1%
16Brendon0.1%
16Brock0.1%
16Kody0.1%
16Marcus0.1%
16Victor0.1%
15Ali0.1%
15Gerald0.1%
15Isaac0.1%
15Keegan0.1%
15Lawrence0.1%
15Marshall0.1%
15Nicolas0.1%
15Tony0.1%
14Danny0.1%
14Elijah0.1%
14Gavin0.1%
14Henry0.1%
14Jackson0.1%
14Mitchel0.1%
14Reid0.1%
14Theodore0.1%
14Tyrell0.1%
14Wyatt0.1%
13Corbin0.1%
13Duncan0.1%
13Johnathon0.1%
13Oliver0.1%
13Randall0.1%
13Ronald0.1%
13Wayne0.1%
12Andre0.1%
12Branden0.1%
12Byron0.1%
12Garett0.1%
12Jack0.1%
12Jimmy0.1%
12Johnny0.1%
12Jonah0.1%
12Kelvin0.1%
12Leonard0.1%
12Max0.1%
12Nigel0.1%
12Rylan0.1%
12Shayne0.1%
12Terence0.1%
11Allen0.0%
11Andy0.0%
11Coleman0.0%
11Damon0.0%
11Daryl0.0%
11Frank0.0%
11Josh0.0%
11Kale0.0%
11Kelsey0.0%
11Louis0.0%
11Lyndon0.0%
11Mohamed0.0%
11Quinton0.0%
11Stephan0.0%
10Ahmed0.0%
10Brennen0.0%
10Damian0.0%
10Damien0.0%
10Dane0.0%
10Darryl0.0%
10Dexter0.0%
10Dwight0.0%
10Glen0.0%
10Graeme0.0%
10Jeremiah0.0%
10Jerry0.0%
10Josiah0.0%
10Lukas0.0%
10Preston0.0%
10Robin0.0%
10Roman0.0%
10Ryley0.0%
10Tyrone0.0%
9Barry0.0%
9Bruce0.0%
9Carter0.0%
9Collin0.0%
9Elliott0.0%
9Everett0.0%
9Gage0.0%
9Hayden0.0%
9Keenan0.0%
9Lane0.0%
9Lorne0.0%
9Malcolm0.0%
9Murray0.0%
9Nikolas0.0%
9Sebastian0.0%
9Seth0.0%
9Stephane0.0%
9Terrance0.0%
9Trenton0.0%
9Tyrel0.0%
8Catlin0.0%
8Chris0.0%
8Clifford0.0%
8Conor0.0%
8Dana0.0%
8Darrell0.0%
8Don0.0%
8Dwayne0.0%
8Elliot0.0%
8Ernest0.0%
8Francis0.0%
8Garret0.0%
8Harrison0.0%
8Ivan0.0%
8Jaden0.0%
8Jayden0.0%
8Jose0.0%
8Karl0.0%
8Kyler0.0%
8Layne0.0%
8Lyle0.0%
8Marco0.0%
8Mario0.0%
8Matt0.0%
8Mohammed0.0%
8Nelson0.0%
8Reece0.0%
8Reuben0.0%
8Ricky0.0%
8Rodney0.0%
8Roger0.0%
8Roy0.0%
8Sam0.0%
8Shelby0.0%
8Skylar0.0%
8Skyler0.0%
8Stanley0.0%
8Stewart0.0%
7Aidan0.0%
7Alec0.0%
7Bobby0.0%
7Braeden0.0%
7Clint0.0%
7Dawson0.0%
7Dayton0.0%
7Elias0.0%
7Fraser0.0%
7Harley0.0%
7Jace0.0%
7Jarvis0.0%
7Kane0.0%
7Kenton0.0%
7Kieran0.0%
7Kirby0.0%
7Kory0.0%
7Kristian0.0%
7Madison0.0%
7Marvin0.0%
7Mathieu0.0%
7Mohamad0.0%
7Nickolas0.0%
7Noah0.0%
7Noel0.0%
7Olivier0.0%
7Omar0.0%
7Parker0.0%
7Randal0.0%
7Reed0.0%
7Steve0.0%
7Tylor0.0%
6Abraham0.0%
6Arthur0.0%
6Beau0.0%
6Ben0.0%
6Brant0.0%
6Bret0.0%
6Brody0.0%
6Carlos0.0%
6Clay0.0%
6Davin0.0%
6Denis0.0%
6Edwin0.0%
6Frederick0.0%
6Guy0.0%
6Jarred0.0%
6Joey0.0%
6Julien0.0%
6Kai0.0%
6Kaleb0.0%
6Kalen0.0%
6Keifer0.0%
6Leighton0.0%
6Leslie0.0%
6Luc0.0%
6Michel0.0%
6Oscar0.0%
6Regan0.0%
6Rene0.0%
6Rick0.0%
6Sebastien0.0%
6Tommy0.0%
6Tory0.0%
6Waylon0.0%
6Wilson0.0%
6Zachery0.0%
5Alain0.0%
5Alvin0.0%
5Amandeep0.0%
5Aubrey0.0%
5Belal0.0%
5Braydon0.0%
5Brodie0.0%
5Cale0.0%
5Carey0.0%
5Coleton0.0%
5Colter0.0%
5Dallin0.0%
5Darin0.0%
5Desmond0.0%
5Eli0.0%
5Erich0.0%
5Glenn0.0%
5Greg0.0%
5Harold0.0%
5Hussein0.0%
5Iain0.0%
5Jarrod0.0%
5Jessy0.0%
5Jorden0.0%
5Jordy0.0%
5Kasey0.0%
5Kenny0.0%
5Kevan0.0%
5Kiefer0.0%
5Kolton0.0%
5Luis0.0%
5Marcel0.0%
5Marlon0.0%
5Melvin0.0%
5Miguel0.0%
5Miles0.0%
5Ricardo0.0%
5Royce0.0%
5Ruben0.0%
5Shea0.0%
5Tate0.0%
5Tomas0.0%
5Walter0.0%
5Zackary0.0%
5Zane0.0%
4Alfred0.0%
4Ammon0.0%
4Antonio0.0%
4Barrett0.0%
4Bevan0.0%
4Bilal0.0%
4Blade0.0%
4Bo0.0%
4Bradly0.0%
4Braedon0.0%
4Brennon0.0%
4Bretton0.0%
4Callum0.0%
4Clarence0.0%
4Codie0.0%
4Cooper0.0%
4Cordell0.0%
4Dan0.0%
4Davis0.0%
4Devan0.0%
4Diego0.0%
4Dion0.0%
4Drake0.0%
4Duane0.0%
4Dusty0.0%
4Dustyn0.0%
4Grady0.0%
4Graydon0.0%
4Grayson0.0%
4Griffin0.0%
4Harman0.0%
4Hunter0.0%
4Ibrahim0.0%
4Jacky0.0%
4Jade0.0%
4Jamal0.0%
4Jameson0.0%
4Jan0.0%
4Jarret0.0%
4Jean0.0%
4Jermaine0.0%
4Jerome0.0%
4Jonas0.0%
4Jordin0.0%
4Jory0.0%
4Keaton0.0%
4Keilan0.0%
4Kellen0.0%
4Kerry0.0%
4Kodi0.0%
4Korey0.0%
4Kristoffer0.0%
4Landen0.0%
4Larry0.0%
4Lars0.0%
4Layton0.0%
4Lewis0.0%
4Lindsay0.0%
4Lloyd0.0%
4Mandeep0.0%
4Manuel0.0%
4Markus0.0%
4Maximillian0.0%
4Micah0.0%
4Michal0.0%
4Mykel0.0%
4Nathanael0.0%
4Nathanial0.0%
4Norman0.0%
4Perry0.0%
4Philippe0.0%
4Quincy0.0%
4Randolph0.0%
4Reginald0.0%
4Robbie0.0%
4Roberto0.0%
4Rocky0.0%
4Solomon0.0%
4Sumeet0.0%
4Sundeep0.0%
4Tobias0.0%
4Tomasz0.0%
4Vance0.0%
4Vaughn0.0%
4Vernon0.0%
4Vishal0.0%
4Wacey0.0%
4Willie0.0%
4Zachariah0.0%
3Abdulrahman0.0%
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1Ravinder0.0%
1Ravy0.0%
1Ray-Al0.0%
1Rayburn0.0%
1Rayneel0.0%
1Reagan0.0%
1Real0.0%
1Reegan0.0%
1Reehan0.0%
1Reese0.0%
1Reggin0.0%
1Regnil0.0%
1Rehan0.0%
1Rehn0.0%
1Reilly0.0%
1Rein0.0%
1Reinhard0.0%
1Remal0.0%
1Remington0.0%
1Remy0.0%
1Rennie0.0%
1Renny0.0%
1Reon0.0%
1Reynold0.0%
1Reynolds0.0%
1Rhody0.0%
1Riad0.0%
1Riccardo0.0%
1Ricco0.0%
1Rich0.0%
1Richer0.0%
1Richmond0.0%
1Ricki0.0%
1Riendieu0.0%
1Ringo0.0%
1Rion0.0%
1Rishi0.0%
1Ritesh0.0%
1River0.0%
1Riyadh0.0%
1Rob0.0%
1Robbert0.0%
1Robin-Lee0.0%
1Robroy0.0%
1Rock0.0%
1Rockie0.0%
1Rockwell0.0%
1Rodey0.0%
1Rodger0.0%
1Rodman0.0%
1Rodnie0.0%
1Rohit0.0%
1Romeo0.0%
1Rommel0.0%
1Ron0.0%
1Ronan0.0%
1Ronnel0.0%
1Ronnie0.0%
1Rorey0.0%
1Rosh0.0%
1Roshan0.0%
1Roshant0.0%
1Roth0.0%
1Rowley0.0%
1Royle0.0%
1Rueben0.0%
1Rusjot0.0%
1Rustin0.0%
1Ryanjeet0.0%
1Ryann0.0%
1Ryker0.0%
1Ryle0.0%
1Rylund0.0%
1Ryon0.0%
1Saad0.0%
1Saadiq0.0%
1Sabin0.0%
1Sadiq0.0%
1Saed0.0%
1Safron0.0%
1Said0.0%
1Saif0.0%
1Salar0.0%
1Saleem0.0%
1Salman0.0%
1Salwin0.0%
1Sami0.0%
1Sanam0.0%
1Sanang0.0%
1Sandro-Andreas0.0%
1Sansitny0.0%
1Santino0.0%
1Santos0.0%
1Sarkis0.0%
1Satinderpaul0.0%
1Saul0.0%
1Saunder0.0%
1Saunders0.0%
1Saverio0.0%
1Savic0.0%
1Saxon0.0%
1Scotford0.0%
1Seamus0.0%
1Seanan0.0%
1Sebastain0.0%
1Sedique0.0%
1Seiichiro0.0%
1Selim0.0%
1Serawatt0.0%
1Serge0.0%
1Shaan-E-Abbas0.0%
1Shad0.0%
1Shaddy0.0%
1Shadi0.0%
1Shadoe0.0%
1Shadrak0.0%
1Shahbaz0.0%
1Shahil0.0%
1Shaile0.0%
1Shalvin0.0%
1Shameek0.0%
1Shamil0.0%
1Shannon0.0%
1Shant0.0%
1Shanti0.0%
1Sharman0.0%
1Shavinesh0.0%
1Shawki0.0%
1Shawnik0.0%
1Sheffield0.0%
1Shelton0.0%
1Shelvain0.0%
1Shen0.0%
1Sheridan0.0%
1Sherman0.0%
1Shevlin0.0%
1Sheycil0.0%
1Shivanand0.0%
1Shon0.0%
1Shone0.0%
1Shouresh0.0%
1Shue-Ke0.0%
1Shyloh0.0%
1Shyrone0.0%
1Sidney0.0%
1Sikander0.0%
1Sile0.0%
1Silvester0.0%
1Simo0.0%
1Simpson0.0%
1Simranjeet0.0%
1Simranjit0.0%
1Simranjot0.0%
1Siribood0.0%
1Siryun0.0%
1Skylare0.0%
1Skylier0.0%
1Sohel0.0%
1Sohrab0.0%
1Solon0.0%
1Somkaven0.0%
1Sormbatt0.0%
1Soroosh0.0%
1Soshiance0.0%
1Stanislaw0.0%
1Stapana0.0%
1Staven0.0%
1Steele0.0%
1Steen0.0%
1Stefano0.0%
1Stellen0.0%
1Stergios0.0%
1Sterlin0.0%
1Sterling0.0%
1Stetson0.0%
1Stevahn0.0%
1Stian0.0%
1Stormy0.0%
1Stratton0.0%
1Strephon0.0%
1Subegh0.0%
1Subhan0.0%
1Suhas0.0%
1Suhile0.0%
1Sukhjit0.0%
1Sukhpal0.0%
1Suley0.0%
1Sumit0.0%
1Sunil0.0%
1Sunjeet0.0%
1Sunny0.0%
1Suraj0.0%
1Surjot0.0%
1Surkhveer0.0%
1Sven0.0%
1Swapnil0.0%
1Sydney0.0%
1Sylvester0.0%
1Sylvester-Jozef0.0%
1Taber0.0%
1Tache0.0%
1Tadeus0.0%
1Tadeusz0.0%
1Taheer0.0%
1Tahner0.0%
1Taidhg0.0%
1Taimoore0.0%
1Taisser0.0%
1Taize0.0%
1Tajammal0.0%
1Takahiro0.0%
1Taliesin0.0%
1Talin0.0%
1Talon0.0%
1Talwinder0.0%
1Tamer0.0%
1Tamiz0.0%
1Tan0.0%
1Taranbir0.0%
1Taranveer0.0%
1Tarek0.0%
1Tarek-Zakaria0.0%
1Tareq0.0%
1Tarik0.0%
1Tariq0.0%
1Tarique0.0%
1Tarnvir0.0%
1Tarryl0.0%
1Taryl0.0%
1Tasso0.0%
1Taurean0.0%
1Taurian0.0%
1Tavin0.0%
1Tavis0.0%
1Tavish0.0%
1Taylar0.0%
1Tayte0.0%
1Teddy0.0%
1Teepu0.0%
1Te-Ja0.0%
1Tendayi0.0%
1Tenneil0.0%
1Teo0.0%
1Terance0.0%
1Terell0.0%
1Terho0.0%
1Teri-James0.0%
1Tero0.0%
1Terrace0.0%
1Terrell0.0%
1Terrill0.0%
1Terris0.0%
1Teunis0.0%
1Tevin0.0%
1Texter0.0%
1Thaison0.0%
1Thane0.0%
1Thanh0.0%
1Thayl0.0%
1Thayne0.0%
1Thazhumpal0.0%
1The0.0%
1Theophile0.0%
1Theoren0.0%
1Theran0.0%
1Thereon0.0%
1Therin0.0%
1Theron0.0%
1Thien0.0%
1Thompson0.0%
1Thomson0.0%
1Thorin0.0%
1Thu0.0%
1Thuan0.0%
1Tien0.0%
1Tighe0.0%
1Tiluck0.0%
1Timmothy0.0%
1Tin0.0%
1Titus0.0%
1Tobby0.0%
1Tobiah0.0%
1Tobin0.0%
1Todd-James0.0%
1Tokunbq0.0%
1Tokunn0.0%
1Tom0.0%
1Tomoosee0.0%
1Tori-Lee0.0%
1Torquil0.0%
1Torrey0.0%
1Torrin0.0%
1Torry0.0%
1Trae0.0%
1Traphton0.0%
1Traves0.0%
1Travin0.0%
1Treaver0.0%
1Tremaine0.0%
1Trenten0.0%
1Trestin0.0%
1Treston0.0%
1Trevis0.0%
1Tri0.0%
1Trigger0.0%
1Trinity0.0%
1Tristin0.0%
1Trong0.0%
1Tronspencer0.0%
1Truman0.0%
1Trung0.0%
1Truong0.0%
1Tubby0.0%
1Tuong0.0%
1Tyce0.0%
1Tyee0.0%
1Tylan0.0%
1Tylar0.0%
1Tyler-James0.0%
1Tylin0.0%
1Tyller0.0%
1Tymen0.0%
1Tymon0.0%
1Tynan0.0%
1Tyner0.0%
1Tyree0.0%
1Tyroan0.0%
1Tysei0.0%
1Tysen0.0%
1Tysson0.0%
1Uriah0.0%
1Usmaan0.0%
1Usman0.0%
1Vafa0.0%
1Van0.0%
1Vaughan0.0%
1Veeran0.0%
1Verne0.0%
1Videan0.0%
1Viet0.0%
1Vikas0.0%
1Vikramjeet0.0%
1Vikramjit0.0%
1Vinay0.0%
1Vincenzo0.0%
1Vinesh0.0%
1Vinh0.0%
1Vinson0.0%
1Virgilio0.0%
1Vitale0.0%
1Vittorio0.0%
1Vivek0.0%
1Vlasey0.0%
1Vuthy0.0%
1Wacy0.0%
1Waden0.0%
1Waleed0.0%
1Walid0.0%
1Walied0.0%
1Walker0.0%
1Waqaas0.0%
1Ward0.0%
1Warren-Hudson0.0%
1Wes0.0%
1Wesleigh0.0%
1Wesly0.0%
1Westin0.0%
1Westley0.0%
1Whitespottedfeather0.0%
1Wiley0.0%
1Will0.0%
1Willis0.0%
1Willm0.0%
1Willson0.0%
1Winslow0.0%
1Woodrow0.0%
1Wren0.0%
1Wylee0.0%
1Wynston0.0%
1Xavier0.0%
1Yafet0.0%
1Yale0.0%
1Yardley0.0%
1Yasen0.0%
1Yat-Hang0.0%
1Yazeed0.0%
1Yazir0.0%
1Yeobanny0.0%
1Yihya0.0%
1Yilan0.0%
1Yin0.0%
1Yogesh0.0%
1Yonnase0.0%
1Young0.0%
1Yue-Bon0.0%
1Yuen0.0%
1Yuki0.0%
1Yukiya0.0%
1Yung0.0%
1Yu-Sheng0.0%
1Yuvraj0.0%
1Zaccary0.0%
1Zachari0.0%
1Zacharia0.0%
1Zacharie0.0%
1Zachiary0.0%
1Zachrey0.0%
1Zahid0.0%
1Zainoon0.0%
1Zak0.0%
1Zakary0.0%
1Zakhary0.0%
1Zamir0.0%
1Zan0.0%
1Zander0.0%
1Zandon0.0%
1Zaqir0.0%
1Zarin0.0%
1Zeff0.0%
1Zeth0.0%
1Ziad-H.0.0%
1Zoheb0.0%
1Zsigmond0.0%
1Zulfiqar0.0%
1Zuviel0.0%

… and continue with 2015

2015 Complete List of Alberta Boys Names

NumberNamePercentage
301Liam1.0%
256Noah0.9%
233Ethan0.8%
222Benjamin0.8%
218Lucas0.8%
218William0.8%
210Oliver0.7%
203Mason0.7%
197Logan0.7%
194Alexander0.7%
189Carter0.7%
189Owen0.7%
187James0.6%
186Jacob0.6%
182Hunter0.6%
173Samuel0.6%
172Gabriel0.6%
172Jack0.6%
171Lincoln0.6%
162Hudson0.6%
161Nathan0.6%
156Jackson0.5%
150Daniel0.5%
143Luke0.5%
141Adam0.5%
132Wyatt0.5%
127Connor0.4%
122Grayson0.4%
122Parker0.4%
121Aiden0.4%
121Thomas0.4%
120Henry0.4%
118Jaxon0.4%
117Caleb0.4%
116David0.4%
116Michael0.4%
116Ryan0.4%
110Emmett0.4%
108Austin0.4%
108Isaac0.4%
106Asher0.4%
105John0.4%
104Jayden0.4%
104Ryder0.4%
102Matthew0.4%
102Theodore0.4%
97Ryker0.3%
95Gavin0.3%
94Dominic0.3%
93Joshua0.3%
93Zachary0.3%
88Levi0.3%
87Declan0.3%
86Eli0.3%
85Andrew0.3%
85Sawyer0.3%
84Nolan0.3%
83Blake0.3%
82Bennett0.3%
82Cole0.3%
82Elijah0.3%
82Evan0.3%
80Dylan0.3%
80Max0.3%
80Sebastian0.3%
78Brody0.3%
78Hayden0.3%
77Nixon0.3%
75Easton0.3%
74Joseph0.3%
73Muhammad0.3%
72Cooper0.2%
71Anthony0.2%
70Carson0.2%
70Jace0.2%
70Jaxson0.2%
69Marcus0.2%
69Tristan0.2%
68Leo0.2%
67Isaiah0.2%
66Jake0.2%
66Jasper0.2%
65Charles0.2%
64Bentley0.2%
63Nathaniel0.2%
62Maxwell0.2%
60Jordan0.2%
60Nash0.2%
60Weston0.2%
59Nicholas0.2%
59Riley0.2%
58Ezra0.2%
58Kai0.2%
58Tyler0.2%
57Chase0.2%
57Landon0.2%
57Xavier0.2%
56Everett0.2%
55Aaron0.2%
55Cameron0.2%
55Cohen0.2%
55Harrison0.2%
54Maverick0.2%
53Brayden0.2%
53Elias0.2%
52Kayden0.2%
51Christopher0.2%
50Ali0.2%
50Christian0.2%
50Silas0.2%
49Eric0.2%
49Jason0.2%
49Rylan0.2%
48Beckett0.2%
48Griffin0.2%
48Jonathan0.2%
47George0.2%
47Micah0.2%
47Spencer0.2%
46Charlie0.2%
46Colton0.2%
46Xander0.2%
45Roman0.2%
44Finn0.2%
44Luca0.2%
44Wesley0.2%
43Jude0.1%
43Omar0.1%
43Tyson0.1%
42Alex0.1%
42Ashton0.1%
42Dawson0.1%
42Elliot0.1%
42Felix0.1%
42Greyson0.1%
41Emerson0.1%
41Ian0.1%
41Kyle0.1%
41Seth0.1%
40Beau0.1%
40Kaiden0.1%
40Simon0.1%
40Tanner0.1%
39Brady0.1%
38Kaleb0.1%
37Gage0.1%
37Jayce0.1%
37Maddox0.1%
37Robert0.1%
36Archer0.1%
36Kingston0.1%
36Mohamed0.1%
36Theo0.1%
35Jase0.1%
35Jax0.1%
35Lukas0.1%
35Oscar0.1%
34Julian0.1%
34Justin0.1%
34Peter0.1%
33Arthur0.1%
33Dax0.1%
32Adrian0.1%
32Ahmed0.1%
32Brandon0.1%
32Jeremiah0.1%
32Josiah0.1%
32Maximus0.1%
32Myles0.1%
31Daxton0.1%
31Jonah0.1%
31Kade0.1%
31Rowan0.1%
30Avery0.1%
30Ayden0.1%
30Ezekiel0.1%
30Hamza0.1%
30Kevin0.1%
30Malcolm0.1%
30Miles0.1%
30Sean0.1%
30Vincent0.1%
30Walker0.1%
29Finley0.1%
29Ibrahim0.1%
29Mohammed0.1%
29Reid0.1%
29Zander0.1%
28Damian0.1%
28Edward0.1%
28Patrick0.1%
28Paul0.1%
28Rory0.1%
27Cruz0.1%
27Damien0.1%
27Jeremy0.1%
27Jesse0.1%
27Joel0.1%
27Lochlan0.1%
27Quinn0.1%
27Rhett0.1%
26Callum0.1%
26Corbin0.1%
26Grady0.1%
26Jett0.1%
26Kieran0.1%
26Mark0.1%
26Odin0.1%
26Santiago0.1%
26Tucker0.1%
26Zane0.1%
25Aidan0.1%
24Abel0.1%
24Benson0.1%
24Calvin0.1%
24Elliott0.1%
24Ellis0.1%
24Kaden0.1%
24Lachlan0.1%
24Markus0.1%
24Marshall0.1%
24Mateo0.1%
24Ronin0.1%
24Stephen0.1%
24Timothy0.1%
23Arjun0.1%
23Axel0.1%
23Emmanuel0.1%
23Holden0.1%
23Ivan0.1%
23Jaden0.1%
23Kian0.1%
23Kyler0.1%
23Madden0.1%
23Yusuf0.1%
22Braxton0.1%
22Brian0.1%
22Dante0.1%
22Erik0.1%
22Linden0.1%
22Preston0.1%
21Atticus0.1%
21Ayaan0.1%
21Bradley0.1%
21Brock0.1%
21Clark0.1%
21Derek0.1%
21Drew0.1%
21Hendrix0.1%
21Knox0.1%
21Malik0.1%
21Matteo0.1%
21Mohammad0.1%
21Mustafa0.1%
21Richard0.1%
21Ronan0.1%
21Sterling0.1%
20Aarav0.1%
20Ben0.1%
20Cody0.1%
20Deacon0.1%
20Sullivan0.1%
20Zion0.1%
19Ahmad0.1%
19Barrett0.1%
19Bodhi0.1%
19Casey0.1%
19Dallas0.1%
19Hugo0.1%
19Jakob0.1%
19Kash0.1%
19Martin0.1%
19Miguel0.1%
19Milo0.1%
19Nate0.1%
19River0.1%
19Shawn0.1%
19Victor0.1%
18Arlo0.1%
18Aryan0.1%
18Camden0.1%
18Colin0.1%
18Dean0.1%
18Huxley0.1%
18Kane0.1%
18Karson0.1%
18Karter0.1%
18Lewis0.1%
18Luka0.1%
18Phoenix0.1%
18Raphael0.1%
18Sam0.1%
18Yahya0.1%
17Angad0.1%
17Ari0.1%
17Colt0.1%
17Keaton0.1%
17Keegan0.1%
17Lennox0.1%
17Leonardo0.1%
17Talon0.1%
17Travis0.1%
17Troy0.1%
16Andre0.1%
16Bryson0.1%
16Damon0.1%
16Ewan0.1%
16Harvey0.1%
16Jonas0.1%
16Louis0.1%
16Oakley0.1%
16Russell0.1%
16Tate0.1%
15Cash0.1%
15Cullen0.1%
15Devon0.1%
15Edwin0.1%
15Finnley0.1%
15Francis0.1%
15Johan0.1%
15Mathias0.1%
15Nicolas0.1%
15Rayan0.1%
15Titus0.1%
15Waylon0.1%
15Winston0.1%
15Zayden0.1%
15Zayn0.1%
14Abdullah0.0%
14Brantley0.0%
14Brooks0.0%
14Colby0.0%
14Dexter0.0%
14Graham0.0%
14Gunnar0.0%
14Gunner0.0%
14Jamie0.0%
14Kohen0.0%
14Marco0.0%
14Matthias0.0%
14Quinton0.0%
14Raiden0.0%
14Reed0.0%
14Syed0.0%
14Zain0.0%
13Amir0.0%
13Anders0.0%
13Bruce0.0%
13Bryce0.0%
13Cade0.0%
13Carlos0.0%
13Dane0.0%
13Darius0.0%
13Desmond0.0%
13Duke0.0%
13Enzo0.0%
13Fateh0.0%
13Fletcher0.0%
13Jared0.0%
13Judah0.0%
13Kayson0.0%
13Keith0.0%
13Lawson0.0%
13Layne0.0%
13Maxim0.0%
13Paxton0.0%
13Raymond0.0%
13Steven0.0%
13Taylor0.0%
13Ty0.0%
12Abdul0.0%
12Angelo0.0%
12Antonio0.0%
12Beckham0.0%
12Boston0.0%
12Bowen0.0%
12Bryan0.0%
12Caden0.0%
12Calder0.0%
12Clayton0.0%
12Conner0.0%
12Crosby0.0%
12Davis0.0%
12Dominick0.0%
12Dominik0.0%
12Frank0.0%
12Garrett0.0%
12Gideon0.0%
12Jethro0.0%
12Kashton0.0%
12Killian0.0%
12Lane0.0%
12Leon0.0%
12Milan0.0%
12Miller0.0%
12Morgan0.0%
12Pierce0.0%
12Rhys0.0%
12Ryland0.0%
12Walter0.0%
11Abraham0.0%
11Ace0.0%
11Arnav0.0%
11Atlas0.0%
11Axton0.0%
11Benny0.0%
11Brett0.0%
11Caiden0.0%
11Coen0.0%
11Darren0.0%
11Franz0.0%
11Heath0.0%
11Imran0.0%
11Jeffrey0.0%
11Johnny0.0%
11Juan0.0%
11Kabir0.0%
11Karl0.0%
11Kellan0.0%
11Kendrick0.0%
11Kenneth0.0%
11Leif0.0%
11Marc0.0%
11Philip0.0%
11Rafael0.0%
11Remington0.0%
11Sahib0.0%
11Sami0.0%
11Scott0.0%
11Shane0.0%
11Tobias0.0%
11Yousef0.0%
10Abdirahman0.0%
10Albert0.0%
10Alistair0.0%
10Andy0.0%
10August0.0%
10Bo0.0%
10Brendan0.0%
10Brodie0.0%
10Caius0.0%
10Curtis0.0%
10Donovan0.0%
10Duncan0.0%
10Grant0.0%
10Hassan0.0%
10Jaxton0.0%
10Joaquin0.0%
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3Yousif0.0%
3Youssef0.0%
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3Yuvan0.0%
3Zach0.0%
3Zaiden0.0%
3Zaki0.0%
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3Zein0.0%
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3Zorawar0.0%
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2Amanuel0.0%
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2Amr0.0%
2Anakin0.0%
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2Ansel0.0%
2Ansh0.0%
2Antoine0.0%
2Arhaan0.0%
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2Aris0.0%
2Arius0.0%
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2Arrow0.0%
2Arsenio0.0%
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2Arth0.0%
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2Ashur0.0%
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2Avondre0.0%
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2Awab0.0%
2Axil0.0%
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2Azrael0.0%
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2Baron0.0%
2Barry0.0%
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2Caeden0.0%
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2Calix0.0%
2Camilo0.0%
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2Carmine0.0%
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2Dallan0.0%
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