Malcolm Gladwell capitalized on research conducted by Roger Barnsley (et al., 1985) by suggesting in his 2008 book, Outliers, that there is an “Iron Law of Canadian Hockey.” This theory is also known as the relative age effect in psychological research and it suggests that the older a player is when they begin training for a sport, the more likely they are to achieve success in that sport.
In fact, in a talk posted on YouTube, Gladwell goes even further, saying, “In absolutely every system in which hockey is played, a hugely disproportionate number of hockey players are born in the first half of the year.” He says this in the context of a talk about society not taking advantage of opportunities to improve human potential.
“Logic tells us there should be as many great hockey players born in the second half of the year,” suggests Gladwell, “as born in the first half. But what we can see here, there’s almost no one born it the end of the year, everyone’s from the beginning.”
But is this actually true — are more elite hockey players born in the first half versus the second half of the year?
I was listening to this talk and couldn’t help but wonder, “This seems like a really perhaps-too-neat result. Is this actually true? Does the relative age effect impact your likelihood to be a great hockey player?”
So first I went over to Wikipedia and found this list, List of 100 greatest hockey players by The Hockey News from 1998. This is a quick and dirty way of testing the hypothesis at face value — are the hockey greats of the world more likely to have been born in the first half of the year?
Only 39 of the hockey players on the list have Wikipedia entries, so they were the easiest to verify their date of birth. Of those 39 players, 20 were born in the first half of the year, and 19 were born in the second half. Hmmm… that doesn’t really seem to jive with Gladwell’s claims. ((Yes, I realize this isn’t robust research — it’s an arbitrary list and only 39 out of 100 datapoints were examined, but there’s no reason to suspect that those 39 datapoints were not fairly random.))
So finding some support that perhaps the issue isn’t as clear-cut and dried as Gladwell suggests, I turned to PsycINFO, the psychological research database. It didn’t take long to find a study that had the same questions I did — does the relative age effect (RAE) actually predict excellence in sports?
Gibbs, Jarvis & Dufur (2012) suggest that the answer is no. In a far more systematic approach than my quick and dirty review of a top 100 list, the researchers examined the distribution of birth months for the first round draft picks of Canadian players in the NHL for the years 2007-2010. Then they looked at 1,109 players who played on major league rosters from 2000-2009.
Last, they examined All-Star and Olympic hockey rosters from 2002-2010. These are the elite players of hockey — the cream of the crop.
So what did they find?
In our analyses, we found a strong relative age effect that eventually fades, then reverses across levels of hockey play among Canadian-born players.
In our first data, early birth-month advantage is apparent in the Medicine Hat Tigers championship roster of 2007
(56%) and for their opponents the Vancouver Giants (44%), but it is less true of the same teams three years later (33% and 39% respectively). [These were the teams Gladwell highlighted in his book chapter.]The effect is also apparent among Canadian-born first round draft picks, with 40 percent, 41 percent, 47 percent, and 33 percent born in the first quarters of 2007, 2008, 2009, and 2010 respectively.
But for the average player in the NHL, the effect seems to fade. Although the first round draft picks confirm Gladwell’s law (33 — 47 percent across 2007 — 2010) — a reflection of their Major Junior Hockey performance — the percent of all Canadian hockey players in the NHL born in the first three months is a modest 28 percent.
But it gets worse. Among the most elite hockey players, the effect completely reverses — it’s better to be born later in the year if you want to become one of the great hockey players: “The combined average of the All-stars and Olympic rosters [born in the first three months of the year] is 17 percent.” Compare this to the 28 percent noted above and you see that it actually hurts your chances to be born earlier in the year if you want to play in the Olympics or on an All-Star team.
Last, the researchers found one more perhaps-not-so-surprising result — players born earlier in the year have shorter hockey careers — an average of a year less than those born in the last three months of the year (Gibbs, Jarvis & Dufur, 2012).
The incongruous findings come from Gladwell confusing simply playing on a team with being an elite player in that sport. He defined success in hockey as simply making the team — a way most people who play sports probably wouldn’t agree with. The researchers sum it up nicely:
Our findings illustrate how critical it is to define hockey success. When hockey success is defined as playing Major Junior Hockey, the effect is strong, as Gladwell reported in the popular press.
But the effect diminishes when success is defined as making the NHL, and fades when performance and skill are considered.
When hockey success is defined as the most elite levels of play, the relative age effect reverses.
Who Will Tell YouTubers?
Now here’s the real problem — these YouTube talks and videos don’t get updated or removed. Nobody is going to come along and point out that the things Gladwell says in this talk aren’t necessarily true based upon our latest understanding of the research. ((Gladwell’s talk was apparently conducted in 2008, prior to the new research being published.))
Remember his line, “Logic tells us there should be as many great hockey players born in the second half of the year.” Well, actually the data suggests that this is, in fact, true after all.
And that’s the challenge of disseminating pop-psychology tidbits on video and in books — their conclusions will remain forever etched ((Unless someone goes back and edits these things, which is rarely done.)), while the science and research data continue to march forward.
Finally, it’s a reminder that psychology and sociology data rarely results in neat, clean conclusions. While initial research might draw such conclusions, later more-nuanced, rigorous research often demonstrates the problems with those first studies.
Watch the Gladwell YouTube talk: Malcolm Gladwell Explains Why Human Potential Is Being Squandered
Read Ben Gibbs’ blog entry on his research: Relative Age Effect Reversal Found At Elite Level of Canadian Hockey
References
Barnsley, RH, Thompson AH and Barnsley PE. (1985). Hockey success and birthdate: The relative age effect. Canadian Association of Health, Physical Education and Recreation (CAHPER) Journal 51: 23 — 28.
Gibbs, B.G., Jarvis, J.A., & Dufur, M.J. (2012). The rise of the underdog? The relative age effect reversal among Canadian-born NHL hockey players: A reply to Nolan and Howell. International Review for the Sociology of Sport, 47, 644-649.
Gladwell, M. (2008). Outliers: The Story of Success. New York: Little, Brown.
14 comments
And this article is supposed to be an example of more nuanced, rigorous research? You examined only the most easily accessible information on wikipedia. Your footnote does not excuse the disparity between the conclusion of the article and the actual research done.
Did you actually read the whole article? The Wikipedia back-of-a-napkin review piqued my interest. The actual peer-reviewed research is cited right after that.
Take a look at:
http://en.wikipedia.org/wiki/Relative_age_effect
for a comprehensive list of references circa 100 academic papers
Yes, and many (most?) of those papers look at rosters — not necessarily “success.”
I think it’s a good achievement if someone makes the team. Absolutely.
But I think if you look at who the all-stars in a sport are, the research I cite in this blog entry demonstrates that this relationship is a little bit more complicated than just, “If you’re born earlier in the year, you’re going to be a ‘great’ hockey player.”
I think your article and the cited research is a strong proof of the Relative Age Effect, which is more likely to happen in youth and junior teams. In these teams the players are not fully grown and so the “older” players have a physical advantages over the “younger” players. This explains that the RAE is in the research more obvious on youth stage. I’m not too much into Hockey (more into Soccer) but I would understand that at the time of NHL first round draft picks the players are mostly grown up or have compensated their physical weaknesses with superior skating or technique skills so that it is even again.
Imho the RAE is a problem at youth level where maybe talent can get lost because of physical deficits.
Greetings from Austria
Thank you for this article and the interesting comments. It seems to me that all agree that RAE exists. It is important enough to discuss even if it applies only to junior teams. One cannot tell players in these teams (or their parents):”Forget it, you ain’t successful”. You can’t tell the guys who did not make these teams:”Don’t loose hope, you still have a chance…”.
But my little research on Israel soccer teams (I am no expert, but I, too, read Gladwell’s book) shows clear RAE in junior leagues (especially in recent years)and a reduced effect in professional teams. The reason for that IMHO is twofold:
1. As the professional are older and fewer, the database is smaller and the players were less effected by recent years’ effective machine of measuring and encouraging young soccer players.
2. More important: A November born player, who has made it to a youth league, who “broke the RAE system” is probably more talented than the average January born players. He might be more dedicated, more industrious, more into-it. So in the long run, going into the creme-de-la-creme professional world, he has more chance to survive, compensating for the RAE odds that were against him.
I totally agree that younger (born later or even a bigger problem late in puberty) players are leaving top teams due to only the RAE factor. I have seen this in youth soccer for 15 years. When boys turn 12-13 some starts to develop fast. In elite teams this gets more obvious because early developed players outnumber normal or late players. My approximation is that more than 50% of the talent is wasted, which means they could have developed to be a top player but was not in the right context for 5 years or so.
When boys turn approx 17 the early developed players looses their advantage and quits. then the few late bloomers who were extremely talented becomes better than everybody else. Therefore the effect in the study that among the best players it even is more late bloomers than early. This is obvious. I don’t understand why not everone see this connection. I would bet that EVERY super technical football player who is tall and heavy was late in puberty or born late. Because if they were early they are often playing using the advantage of speed and strength as late bloomers have to develop unique technical skills to master the ball, and when the later on get big they have both advantages. Don’t forget that we already lost most of the talent around 15 years old…/Mats
I love replication studies! However, these findings look a bit weird to me. I took the list that you referred to (List of 100 greatest hockey players by The Hockey News) and ordered the list by birth dates for the TOP 50 players in excel. Only 3 players are not from Canada. From the other 47 players, 19 are born in the first 3 months of the year! That means 40.42% which is a large number considering that the percentage should be around 25%. The players born in the last three months represent 23.40% which is almost expected. Given these results, I am not sure this part of the article is correct: “When hockey success is defined as the most elite levels of play, the relative age effect reverses.”
These are facts for the elite players – the real cream of the crop.!
Also, you said that from the 100 players in the list “Only 39 of the hockey players on the list have Wikipedia entries”. This is not true at all. As a researcher you need to make an effort and find the entries typing the names directly in Wikipedia. I found the top 50 names and I am sure I would find the other 50 in Wikipedia, if I make an effort.
Hi Alex, I’m not sure of the justification of only picking the top 50 hockey players… Why stop at 50? How about 500? What if we go in the other direction… Would the statistic change if we only chose 10 or the top 20?
If the answer is “yes,” then the statistic isn’t reliable. It’s dependent upon the variables you define ahead of time, meaning you can massage those variables to give you the best dataset possible that fits your hypothesis.
Researchers play this game all the time in the design of their studies. They find the ideal parameters that fit their hypothesis, then define the study accordingly. Tada! The data support the hypothesis.
This article is nearly a year old. When it was written, there were only 39 hockey players (out of 100) on the list who had a Wikipedia entry at that time (that we could find, yes, by typing their name into Wikipedia).
Hi John,
I like very much this part from your comment because I feel the same way: “…you can massage those variables to give you the best dataset possible that fits your hypothesis.
Researchers play this game all the time in the design of their studies. They find the ideal parameters that fit their hypothesis, then define the study accordingly. Tada! The data support the hypothesis.”
It is unfortunate but at the end it looks like there is not much to trust out there. When we read all papers, we are kind of blindly trusting what they say, because unfortunately we do not have much time to replicate all the studies we read. This is an interesting article I came across some time ago: http://www.nature.com/news/replication-studies-bad-copy-1.10634
Hi John,
I am no sports psychologist or statistician, but my understanding of Gladwell’s argument in terms of the RAE is that sports administrators are missing out on the full potential of who is out there by excluding some of the best far too early, to the mutual disadvantage of potential sports stars and the clubs themselves. I would say that the evidence you present absolutely supports this argument. It is not until competitors have been playing at the absolute highest level for some time, with fully developed bodies and techniques, that the best players in the subset of those to have made it that far rise to the top. And surprise, surprise, it is an equal spread. Just as the RAE proponents would predict. What this demonstrates is that there is a large pool of potential talent born from May-December who have been excluded too early. The ones who do make it through, eventually prove their worth to be equal to the early-monthers.
This is a subtle part aspect of the “self-fulfilling prophecy” which actually strengthens the case for the existence of the RAE, but you seem to have misread it as counter-evidence, because you have forgotten about the subset of people who have never had the opportunity to prove their abilities at the highest level and are using the ones drafted into the competition as the entire set of potential champions.
Or have I miss something? You are the psychologist so I defer to you – please show me how I am incorrect.
regards,
Chris
Hi John,
My counterpoint would be that the guys who were born in the second half of the year had to be incredibly talented players to be selected into the elite arena. In other words, coaches pick ‘bigger kids’ initially, but the few that are born in the second half of the year that do get picked, had to be outstanding to get noticed. For this reason, this is why I believe there may be an over-representation of the elite of the elite born in the second half of the year that you describe.
As pointed out its the fixation with youth coaches with winning that is the problem with RAE. It encourages the prioritization of the bigger kids in always being given the ball and therefor the chance to develop. As a rugby youth coach you see it continually. The problem arises the “big” kids can use his relative bulk to win the tackle so actually does not develop a complete skill set and the smaller kid does not get the ball as coach knows he has less chance of scoring than the big kid. The issue then compounds because the RAE levels out and the big kid is unable to use his strength to win – the rest have caught up in bulk. So you have a “superstar” who is no longer a superstar and more liable to walk away from the sport because he’s not used to being on the subs bench. The small kid well normally he has given up years ago because he is tired of being the “make weight” continually. The net result is a downward trend in the abilities in the players within the sport some kids do hand around and will contribute to the game but the reality is all sports are hemorrhaging talent in the pursuit of short term wins.
Good morning,
Just a general opinion on the results:
This looks like anything regarding survival mode in society.
In an early stage, the kids born in the first 3 months have a physical advantage, thus gaining attention and credentials to have success in the junior hockey entrey level.
However, the younger, smaller kids who tend to survive and make the cut, are the ones that have adapted and survived to play with their physicial disadvantage.
Later in life, when the age gap evens out, the smaller kids are adapted to playing aginst adversity, therefore always pushing the ceilings of their game, while the kids who hd it easier in an early stage are not used to leaving their way of playing which has always worked and do not hve the adjustment mentality.
I can’t find an ideal example but I’ll use the following:
In high school, the popular kids are ruling the school society and social approval, along with many things, comes easy. The “not so popular” kids” have it a little harder in school and have to put in the work to become someone in life.
Later on in life, the kids that worked harder are more successful, in a general way, socially, financially, family-weise, while the kids that have everything easy, just were’t able to adapt to the challenges that life has to offer and are not as successful in the aspects mentioned above.
Just a general opinion and comparison,
Thank you,
Dennis