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Monday, January 05, 2009

The Matthew Effect

The Matthew Effect: Talent ID and sports science application

The first post of 2009 is inspired by a book I read over the break - Outliers by Malcolm Gladwell. One of the very first things I recall learning when I started out my postgraduate studies was a tip from Prof Tim Noakes to read widely, and read outside your field. Sensible advice, and it informs much of what we are about here at The Science of Sport.

And in that light, Malcolm Gladwell's book, Outliers, provides the latest inspiration for a somewhat novel look at sports science and talent ID (it's "somewhat novel" because it's actually a well-established phenomenon, but has not been published in sports science journals, but mainly social science journals). Gladwell is not entirely outside my field, it must be said, because much of it deals with economics, marketing, strategy etc. But, nevertheless, it's a different perspective on sports science, especially when it covers such obvious territory as the topic of today's post.

That territory, for those of you who have read Outliers, is called The Matthew Effect.

The Matthew Effect - lessons from ice-hockey, soccer and rugby

Today's post is really just a summary of what is described in the book, with the addition of an example from South African rugby that I've managed to do so far, and my own interpretations. There is much more to come, however, including more examples (some of which I hope you'll provide), as well as discussion of how different sports might be affected by this phenomenon, what might be done, and what the implications are for sports science and management.

But for now, forgive me for merely summarizing the data provided in the book, and take a look at the following set of pie-charts. What you are looking at are the breakdown of month of birth of junior players in four different high level sports teams. From top left, going clock-wise: A Canadian Junior Champion team from 2007, the Czech Junior Football/Soccer team from 2007, the Czech Junior Ice-Hockey team from 2007, and the 2007 South African Schools Rugby team.

What should jump out is the enormously high percentage of high-level players who are born between January and April. All told, out of the 91 junior players making up the above four teams, 55 of them (60%) were born in the first four months of the year, and only 13% in the last four months.

This is not an isolated finding, and is true across just about any sport at a high-level. It was reportedly first observed in the mid-1980's by a Canadian psychologist named Roger Barnsley. He noticed that a disproportionately high percentage of high-level ice-hockey players were born in the first few months of the year, and almost none towards the end of it. He expanded his study and looked at other sports like football and baseball, and even started to examine the effect of birth-month on things like academic achievement, suicide and self-esteem. You can read some of those studies here.

The reason - relative age, and a confusion of ability with maturity

We know you're pretty sharp, so it will probably come as no great surprise to learn that this finding is the result of the effect of RELATIVE age on sports performance, and the very easy mistake that coaches are lured into making. If you thought that it was the result of their star signs and some astrology, then I'm afraid you were on the wrong track! But, you might enjoy this website a little more...

Back to reality, and the suggestion that the reason so many elite athletes are born in the early months of the year is the result of the very large effect that 10 months difference in age can have on young children's ability to play sport.

An example: Ross and Jonathan

Let's take two 10-year olds, Ross and Jonathan. They are both 10 years old on the first day of January 2009, and so they compete in the Under-11 age group of their sport (soccer, let's say).

However, not all 10-year olds are created equal! Ross is 10 years and 11 months old on the first day of 2009 (his birthday is in February). Jonathan is 10 years and 1 month old (his birthday is in December), and so he is a full 10 months YOUNGER than the people, like Ross, who he is going to compete against.

At the age of 11, when skills and strength, and the other attributes required for sporting success are still developing, 10 months is an eternity. Think back to your own development, or better yet, to the development of your children, if you have them. Backyard games of catch or football or rugby or cricket change dramtically from one year to the next because a child at that age acquires skills and strength so quickly that they improve enormously from one month to the next.

This means that the 10-month advantage that Ross has, by virtue of being born in January or February, will manifest itself as a big performance advantage over Jonathan (obviously, I'm generalising here, you'll find exceptions. But the graphs above suggest that they happen infrequently).

Enter the coach, and the Matthew Effect is born

Now the coach enters the picture. He has a team of energetic, uncontrollable young 10-year olds to look after, and he picks his team, and allocates his time and attention to those who are deemed to have the most potential. However, he is unable to distinguish between capacity for performance and maturity. Maturity determines ability - Ross is older, and may possess more strength, speed, skill and therefore appear the star player in practice. Jonathan is yet to develop these attributes, but may have the talent.

However, the fateful decision made by the coach is to pick Ross ahead of Jonathan. What happens next determines the distribution you see in the graphs above. By virtue of having been picked based on his "superior" ability, Ross plays against higher quality competition, receives better coaching, more attention, and therefore improves MORE than Jonathan will. Their paths are determined from the outset, based on their selection, and the different journeys they will take are going to mean that one day, Ross is the better athlete or player, thanks to these advantages and opportunities he has received.

At the same time, Jonathan is far less likely to continue to play, because:

  1. He is often smaller than the guys he competes against, and that's not likely to make his life much fun!
  2. He becomes discouraged at the ever-growing gap between himself and the other guys who are being more heavily invested in
What we have then, is a self-fulfilling prophecy, where Ross is picked because he is better, and then ends up being better because he was picked, apparently vindicating the coach's early decision. The issue is this: Was his initial selection the result of his age, or was he genuinely the better sportsman? That is the challenge for talent identification. The figure below summarizes the process.

And why is it called the Matthew Effect, you may be asking? That name was coined by the sociologist Robert Merton, based on the bible verse from Matthew: "For everyone who has will be given more, and he will have an abundance. Whoever does not have, even what he has well be taken from him" (Matt 25:29).

That means that success comes to those that are successful, thanks to their advantage, in this case, from their relative age.

Confounders and debate

There are of course debates and issues around this. The presence of athletes who are born between September and December (albeit a low 13%) suggests that exceptions do exist. What might be very instructive is to examine how those "outliers" (apologies, Malcolm) reach the level they do - they may be early developers, they may have parents who start them out by playing games at a younger age developing their skills "ahead of the normal curve", or they may have older siblings who drag them to a higher level of performance despite their younger relative age. All these options are intriguing and instructive for talent ID purposes, and for understanding how sporting success is determined.

The three elements required: Selection, streaming and differentiated experience

To dig into the effect a little further, the afore-mentioned Roger Barnsley suggested that three things are required for this effect to occur:
  1. Selection - someone (in this case, a coach) must be selecting players based on ability
  2. Streaming - once selected, players are placed into streams. These can be competitions, teams, training squads etc.
  3. Differentiated experiences - very importantly, once in the streams, players receive different levels of coaching, competition and opportunity. This is summarized in the figure above.
Now, all three of these characteristics are found in what is called a meritocracy - wherever performance is rewarded through selection based on ability, and the pyramid of progress exists, you will generate this skewed distribution. Where there is no meritocracy, the effect is diminished, because the emphasis on the selection of the best players (regardless of age) is not as prioritized.

The lack of a meritocracy can be seen in the slightly more balanced distribution of the SA schools rugby team, by the way. In that team, "only" 44% were born in the first three months of the year, much lower than for the other three teams. So what, you ask? Well, that's because the SA school team was selected out of a mix of "traditional" and "non-traditional" rugby schools. Without going into the history and politics of our SA rugby, we have some schools that are very heavily based around performance, and have multiple teams at each age group, right down to junior level. Others are not as focused on age-group performance, and because of the selection policies in SA sport, the team is a mixture of the two. This dilutes the Matthew Effect. You'll find that whenever merit is NOT the primary factor for selection, this will occur.

Implications for sports science

Well, I'm running out of time (and so are you, probably!). This post has run over-time, but there's much more discussion on this topic to come. One area that interests me in particular is that talent ID often does not note this potential confounder of age. It is for this reason that the identification of talent, especially if that result is going to be used to "stratify" young sportspeople into different paths, should occur as late as possible.

What this suggests is that a sports scientist who plans to do some talent ID on a group of unknown sports people might as well make his first selection on the basis of date of birth! OK, that's being too extreme, but the point is, by the time a sports scientist tests a squad of potential athletes aged say 19 years, it's often too late to undo the effect that he measures, and which may have been created 9 years earlier. More to the point, the sport in question might be missing out on some of its best potential talent, which was lost 9 years earlier thanks to a wrong selection! At the senior level, the coach who picks the team may believe he is picking from the whole pool, when in fact, 40% of it has been lost through premature selection, 9 years previously! That should be a significant "flag" for people involved in high performance sport...

More to come...



Colin said...

It would be interesting to see what percentage of athletes born at the end of the year went on to become some sort of "superstar". That is, their ability was so great that it overwhelmed any potential Matthew Effect. LeBron James and Tiger Woods, both born in December, come to mind.

Anonymous said...

You might be interested in this post I wrote at the end of last year:

31 December

When you look at the current All Blacks squad it shows the same bias, although there is one true outlier in the group: Richie McCaw, who was born on the 31st December, the worst possible day according to this theory.

Perhaps he is an example of the superstar that Colin refers to above?

Anonymous said...

Great article, thanks.

Coincidentally, I just read another article on the "Relative Age Effect" found in the US National Soccer Team age group pools. One finding, "In the U15 pool, 62% of the players were born in the first quarter of the year." Here the link:


Anonymous said...

Thanks Ross and Happy Hew Year. The most interesting thing about Gladwell's book for me was the 10,000 hours effect: the approximate investment in practice/training it takes to become world-class at anything.

Gladwell's not the only one to pick up on this; it is also covered more readably by Geoff Colvin in his new book "Talent is Overrated - what really separates world-class performers from everybody else". You "must" read this one next!

Colvin makes the point more clearly than Gladwell that it is years of "deliberate", focused, intelligent practice that are required - not just putting the hours in.

This explains the exceptions to the Matthew Effect. There are some youngsters who, despite not getting preferential treatment early on, continue to practise like crazy.

You introduced the word "talent" into the discussion. After reading Gladwell and Colvin, I've become deeply suspicious of the word; they both seem to be suggesting that the "only" real talent is an exceptional capacity to perservere with an extreme long-term effort - to do whatever it takes to succeed.

What do you think?

Ross Tucker and Jonathan Dugas said...

Hi guys

Thanks for your contribution and comments. I'll post again on the topic and discuss it some more, but just to respond briefly:

Colin, good point. I suspect golf will be the sport most likely to buck the trend of skewed birth days, because as far as I know (at least, here in SA this is true), there is no selection and differentiated experience - most of our top players here in SA started out through the intervention of parents, who pay for coaching and ensure that they get the opportunity. It seems to me to be a much more proactive process - Woods seems to have been that way.

In the book, Gladwell argues that basketball escapes the age trend because kids have access to facilities all across the USA - I'm not sure I believe that though, might warrant further investigation. I think these December outliers are a result of factors that no-one has explained yet - more play at school, peer groups, influential parents (who influence more than simply coaching - also mental attitude towards training).


Thanks for that, very interesting. What is McCaw's story? Is he a product of a normal rugby pathway? Did he play age-group rugby and move through the system? I'd be interested to know if he might have had family, a father or brothers, combined with early development - who knows? Be interesting to pull it apart.


Thanks for that - I'll bring it up as another example when I post on it next!


Yeah, that was interesting. I wasn't sold on it, maybe because Gladwell didn't cover it as well as he might. I was stimulated enough to want to read more about it, so I'm definitely going to take you up on your suggestion, and also read some of the original source papers mentioned.

I think talent certainly still exists - I'm not prepared to dispense with it just yet. From a physiology point of view, it's not possible for some people to be great long-distance runners (muscle fibre types etc.) and I believe the same to be true for most sports - there are people who simply could not be great rugby players. I think people probably gravitate to sports they are naturally good at, and then put in the hours of training. Is that talent? Probably not, that's probably not the right word for it, and perhaps I should use a different one next time.

But I believe the combination is crucial, especially when you sift out large groups of people. I certainly agree that within a small group, right at the top level, hard work separates good from great, but as I understand it, a comparison between me and say, Tiger Woods comes down to talent plus hard work. I think that efforts to separate them don't work.

Thanks again, more discussion, hopefully to follow!


Anonymous said...

Maybe introducing a weight/height classification for youth sports would make for a fairer competition? Something similar to boxing where fighters are competing against others who are in their weight category.

mcgrathe said...

Excellent post guys. It's definitely a phenomenon that I have noticed myself. When competing in Track & Field throughout school, there were two separate sanctioning bodies - one schools body and one club body. The cut off date for the school's age categories was the 1st of July - so with my birthday of June 16th I ended up age 14 not allowed to compete under 15 but forced to compete under 17 (next age group) while somebody 3 weeks younger was in their "proper" age group. However the club date was January 1st so for those competitions I was in my correct age group.
It definitely can have a demoralising effect, but it's hard to know how to fix it. Even across other sports, when in your teens, being big, strong and fast means you can compensate somewhat for any lack of skill and ability. There's a saying here that
"a good big 'un will always beat a good little 'un"
which probably tells you a lot about the mindset of youth coaching.
I would suspect that if you were to take soccer as an example, there may be less bias in certain countries than others. In Northern Europe, the physicality of the game is emphasised from a very young age - to the associated detriment of skill levels, whereas in France and Spain, the underage setup is more geared towards skill - smaller pitches and goals eliminate much of the advantage of height, pace and strength.
Incidentally, are there any similar studies on underage rugby players in New Zealand? One thing that we often notice in the Northern Hemisphere is the earlier physical development of players of Pacific Islands descent - the Baby Blacks as an example always look huge compared to our junior teams, whose players seem to take an extra year or two to fill out. How does the NZ rugby system bring through players that are at a physical disadvantage right up until senior age grades?

Ross Tucker and Jonathan Dugas said...

Hi Adam

Yeah, that's one option. It would work in certain sports only, because some sports actually require skills that are specific to different positions and the development of these skills would be compromised if you eliminate the weight effect. Rugby, for example, requires that some players develop very specific skills because players are smaller and faster, or bigger and heavier. Weight classes would prevent this, so one has to be careful about it. It's been done before - I think they did it in Australia. I suspect ice-hockey requires a similar position-specific skill development.

Then to mcgrathe:

Thanks for the comment. You're right about the structure and competition determining the size of the effect - I think this might hold the answer to the problem. You have to change the emphasis of the competition, and emphasize skills that are independent of size. But then you run the risk of doing what I mentioned above - destroying position-specific skill development. I have to give that some more thought, it is a very, very difficult one to solve.

Just about New Zealand, no study that I know of, but you can check out Rowan's post above (it's the second one) - he's done the senior All Black team. But not juniors. That is an interesting one though, because there, you have a genetic trait that promotes early development. One could argue that this increases the effect of birth month, or that it decreases it. Early development of that specific group of players (Maori-descent, if this is a real physiological effect) might mean that the Pacific Island players are less likely to be born in January, and they don't have to do anything about it - just pick the guys! It would be an interesting analysis to do though.

I am going to look into SA rugby and all our teams, and maybe we have the NZ information as well, I'll find out.


Anonymous said...

Hi Ross and Jonathan !

Thanks for the great post ! Talent ID is, in my opinion, THE crucial point for all nations looking at playing some sort of role in sports at international level. Unfortunately, not many countries have (good) talent ID programs and rely on what comes out of the club system..with all the talents lost due to the Matthew effect its quite a dark perspective.
The next topic I see in this "Talent ID" context is "Nature vs. Nurture" or "Talent vs. Training".
Keep up the good work !

Barrld said...

Great post, as always. I have a very athletic 6 year old son who was born mid June but is very tall for his age (95% ile +) and quite strong. In our soccer league when he was 4 he was far too talented to play in the 3-4 division (he played one half of one game and scored five goals on 5 shots) so I moved him to 5-6 (he was the only 4 year old) where he got to play with kids who were 50% older than he was. Last year at 5 he played in the 5-6 spring league and was league MVP. This spring, even though he's 6 I will move him up to the 7-8 division b/c I don't think it fair to kids just turned 5to play against a very talented 6.5year old. Also I want him to face bigger kids and tougher competition to keep him challenged.

At some point I suspect the age/birthday differential will catch up with him, esp. if he decides to keep on playing soccer at the higher club levels in the coming years. For now at least he is an example (though admittedly only casually empirical) of talent mastering the age spread.

Unknown said...

Colin, it seems that individual sports would be exempt from this as the relative age differences decrease even when there is talent identification; take a look at the amount of Division II college runners who go on to the professional ranks. As for basketball the availability of courts and people to play helps to develop players that might not have been selected for teams - and may have actually helped them (Michael Jordan comes to mind).

Anonymous said...

Hi Ross

Greeting from Joburg!

Having been born on 2 April I definitely noticed a huge advantage when it came to both rugby and athletics. At the time, standards (grades)for school ran from July to June. So, I was young for my standard but old for my age group. So while I had an advantage in sport I was at a disadvantage academically. I remember struggling in the first few years of school. Luckily, I was very good at maths and by Std. 2 (grade 4) I was in the top 5 - 10%.

Getting back to the sporting advantage, all the guys in the A rugby team with me were also from the same standard. So, born in the first 6 months of the year. There were of course, some exceptions.

Regarding Ritchie McCaw, as far as I'm aware, in NZ, at younger ages they actually compete according to weight and not age. So someone who's big for their age will compete against older and perhaps more skillfull kids. Something to investigate a bit further and perhaps adopt in SA.

Cheers Sean

Anonymous said...

Intriguing post. I believe there are also studies that show football players are likely to be Librans or Scorpios and medical men are either practical Taureans or mischievous, playful Geminis. It apparently occurs more often than chance would otherwise suggest and it even seems to make some kind of sense!

Now I do not believe astrology is the cause of the observed correlation and likewise I would caution that talent getting weeded out early on may not be the cause of the observed Matthew Effect. It is one of many possible theories. Other theories could include the following. Birth weights vary by season and that could have a big impact on size and strength. Diet varies by season which could be another impact on early size and development. Heck, there tend to be more illegitimate births in September which is thought to result from more merrymaking the previous Christmas season. Perhaps those kids born in that period just have less devoted and responsible parents than kids born earlier in the year. Okay that last point is a stretch and may get many readers angry, but it too is an observed phenomena. The point is that there could be many theories to explain the observed correlation ranging from easily believable to unbelievable. If I believe this one "easy to buy" theory without more evidence I may also have to have faith in astrology and I am not sure I am ready for that.

Ross Tucker and Jonathan Dugas said...

Hi Chuck

You raise some interesting points. There is one very good argument for the explanation I've given, which is not the "easy to buy" argument, as you suggest.

In Europe, football used to have its cut-off date as August 31st, which meant that anyone burn in August competed as a much younger player. The result was that up to about 1980, the majority of players were born in September, October and November (despite the fact that they may have had less devoted parents). It was exactly the same situation as for ice hockey, but moved to September.

Then, in the mid-1980's, the date was changed. All of a sudden, the date became January 1st, and within a few years, the age of players had shifted, so that they were born in Jan, Feb and March.

Therefore, this is an intervention study, entirely by accident, which strongly suggests the argument, and negates all your theories.

I'm pretty satisfied that the explanation for the Matthew effect is accurate, not "easy to buy" and well established. Numerous papers have been published, and it doesn't always apply to Jan, Feb and March.


Anonymous said...


Thanks for the follow up. That is a very interesting bit of additional evidence. I did not mean to sound too cavalier about characterizing the Matthew Effect as "easy to buy". It does seem the most reasonable explanation and the observation you highlight is a telling test of the theory against other possibilities. I am a believer! That is actually why I enjoy reading your material. You cast a more critical eye on the subject. You guys are the Sherlock Holmes and Watson of Sports Science!


morgann said...

hi, i'm working on a project in my high school biology class on the matthew effect, and may possibley be incorporating practice and playing time into my study. i read the bit in Outliers about the matthew effect, and i also read your article, which was very interesting and informative, by the way. it will definitely help with my project a lot. this may seem like kind of a redundant request, but i was wondering if you had any specific information, or any at all, that you think may be good to include in my investigation, you could let me know? that would be great if you could, thanks. :)

oh, my name is morgan and my email is justmemorgiiex33@gmail.com . hope to hear from you.