Maybe the World Cup Wasn’t the Best Example

In our recent New York Times column, we talked about what makes people good at what they do.

As one example, we conjectured (based on some academic work done by others) that people born in the early months of the year would be overrepresented on World Cup rosters. The underlying theory is that in 1997, FIFA made January 1 the cutoff for determining ages in all international soccer competitions. If this rule had an important impact in determining who made the national youth soccer teams, then these early selection rules would play out to more long run success at the highest levels of soccer. The academic evidence is that these national teams are overwhelmingly made up of players born early in the calendar year, even on the age 21 and under teams, where a few months of physical development isn’t likely to make a big difference. A commenter on our blog, Bill Loyd, has done some hard work to gather data and argues that for past World Cups and for a few of the 2006 squads that he found, he doesn’t see the pattern we predict.

Why might this be the case? For the earlier World Cups, it might not be very surprising that no pattern is there because the FIFA rule didn’t come in until 1997. More fundamentally, the FIFA selection rules and the rules that different countries use for play within the county differ.

For instance, as many readers have emailed us, in the U.S., the age cutoffs tend to be in the summer. In Germany, the within country age cutoff is August 1. Thus, in soccer there are two different competitive pressures at work: one pushing towards more players born in the early months and the other towards more players in the later months. Much of the study of birth-date timing focuses on the cutoff rules within countries, virtually all of them finding important effects.

In light of this difference between FIFA and country rules, the example we gave of the World Cup might not have been the best one, even though the age effect is very strong in the national youth squads that feed many World Cup teams.

This shouldn’t distract from the important fact that the evidence in the literature overwhelming supports the basic point — that across many activities, you can identify long-term effects of essentially arbitrary age cutoffs early in life.

Perhaps a better example than the World Cup would have been the N.H.L. Here is one graph that I found on the web of the birth month of NHL hockey players versus Canadians and Americans more generally:

The black-and-white dots are the NHL players, who are much more likely to be born in January and February and much less likely to be born September-December. This is the sort of pattern that appears over and over in these sorts of studies.

Some other readers have offered a clever, very Freakonomics-y alternative explanation for these age patterns: the parents are lying about their child’s birthday. If the parents want the kid to be a star, they take an older kid and change his date of birth to make him eligible to play with younger children. While I don’t think this is actually the primary reason for what people find in these studies, is definitely worth thinking about.

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  1. David Kane says:

    Mr. Dubner,

    Thanks for taking the time to provide that link. No doubt I am an idiot, but after looking at the site for 15 minutes, I could not find a single piece of data that supported the factual claim that — at the adult, elite level (i.e., World Cup soccer, NHL hockey) — there is an month-of-birth effect. (Everyone seems to agree that there is such an effect under age 20 or so.)

    Could you specify the precise location at that site with such data?

    Thanks for your time.

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  2. David Kane says:

    Mr. Dubner,

    Thanks for taking the time to provide that link. No doubt I am an idiot, but after looking at the site for 15 minutes, I could not find a single piece of data that supported the factual claim that — at the adult, elite level (i.e., World Cup soccer, NHL hockey) — there is an month-of-birth effect. (Everyone seems to agree that there is such an effect under age 20 or so.)

    Could you specify the precise location at that site with such data?

    Thanks for your time.

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  3. Bill L. Lloyd says:

    Mr. Levitt,

    Thank you for posting on my World Cup findings.

    I’m afraid I still don’t see any good evidence for your and Mr. Dubner’s thesis.

    Not trusting a graph that you “found on the web,” with no citation, I tallied up a sample of 158 NHL players.

    At random, I chose five awards: the Frank J. Selke Award for Best Defensive Forward; Rookie of the Year; Playoffs MVP; the Lady Byng Trophy; and the Masterton Sportsmanship Award. I figured, if there’s a way to calculate who “elite” hockey players are, award-winners is the most accurate criterion.

    I counted all 158 players who had won one or more of these awards, being sure not to count people who had won two or more of them (or the same one twice), which is easy to do, since my browser highlights the links I’ve visited already.

    Results: of the 158 players, 79 were born in the first six months of the year, 79 were born in the last six months. An exact tie (oddly enough, I also found exact ties in the 1982 and 1986 World Cups).

    Here are the Wikipedia pages:

    http://en.wikipedia.org/wiki/Bill_Masterton_Memorial_Trophy

    http://en.wikipedia.org/wiki/Calder_Memorial_Trophy

    http://en.wikipedia.org/wiki/Conn_Smythe_Trophy

    http://en.wikipedia.org/wiki/Lady_Byng_Memorial_Trophy

    http://en.wikipedia.org/wiki/Frank_J._Selke_Trophy

    The monthly breakdowns reveal no pattern that I can discern:

    Jan 12
    Feb 12
    Mar 18
    Apr 13
    May 12
    Jun 12
    Jul 19
    Aug 10
    Sept 8
    Oct 15
    Nov 10
    Dec 17

    I find it surprising that a high-level economist relies on “one graph that [he] found on the web” as the keystone of a New York Times article.

    Perhaps badminton, Mr. Levitt? Shall I check?

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  4. Bill L. Lloyd says:

    Mr. Levitt,

    Thank you for posting on my World Cup findings.

    I’m afraid I still don’t see any good evidence for your and Mr. Dubner’s thesis.

    Not trusting a graph that you “found on the web,” with no citation, I tallied up a sample of 158 NHL players.

    At random, I chose five awards: the Frank J. Selke Award for Best Defensive Forward; Rookie of the Year; Playoffs MVP; the Lady Byng Trophy; and the Masterton Sportsmanship Award. I figured, if there’s a way to calculate who “elite” hockey players are, award-winners is the most accurate criterion.

    I counted all 158 players who had won one or more of these awards, being sure not to count people who had won two or more of them (or the same one twice), which is easy to do, since my browser highlights the links I’ve visited already.

    Results: of the 158 players, 79 were born in the first six months of the year, 79 were born in the last six months. An exact tie (oddly enough, I also found exact ties in the 1982 and 1986 World Cups).

    Here are the Wikipedia pages:

    http://en.wikipedia.org/wiki/Bill_Masterton_Memorial_Trophy

    http://en.wikipedia.org/wiki/Calder_Memorial_Trophy

    http://en.wikipedia.org/wiki/Conn_Smythe_Trophy

    http://en.wikipedia.org/wiki/Lady_Byng_Memorial_Trophy

    http://en.wikipedia.org/wiki/Frank_J._Selke_Trophy

    The monthly breakdowns reveal no pattern that I can discern:

    Jan 12
    Feb 12
    Mar 18
    Apr 13
    May 12
    Jun 12
    Jul 19
    Aug 10
    Sept 8
    Oct 15
    Nov 10
    Dec 17

    I find it surprising that a high-level economist relies on “one graph that [he] found on the web” as the keystone of a New York Times article.

    Perhaps badminton, Mr. Levitt? Shall I check?

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  5. David Kane says:

    It appears that Dr. Levitt found his graph here.

    Reliable data? Tough to know. Wonder why Dr. Levitt didn’t follow the universal blogospheric practice of providing the link? You’ll have to ask him. But I certainly wouldn’t put an excessive amount of faith in a webpage that starts with this:

    Do the world’s best hockey players have a common cosmic signature? Does Mercury tend to be in a certain area of the sky when a professional hockey player is born? I am intrigued by that question and many, many others and what follows are the observations I have made during the course of the project. Stay with me, this gets very interesting.

    During the 2001-2002 hockey season the National Hockey League was composed of 30 professional teams located in Canada and the United States of America, averaging 26 players per team (range 22 to 31), a total of 761 individuals. Birth information was gathered for each player including the day, month, year, city and country of birth. The time of each player’s birth was not readily available and so the time for each player was set for noon on the day of birth, halfway through the planetary motions for the day. The birth information was input to Matrix Software’s Win*Star Plus program which accurately produced a heliogram for each player.

    HELIOGRAMS

    A heliogram is a two dimensional arrangement of the planets around the Sun at the time of the birth of any individual. The position in the heliogram of Mercury, Venus, Earth and Mars for each player was transferred into Microsoft’s Access database along with information about the heliogram “type” and the planetary patterns associated with the heliogram. The heliogram is a heliocentric view of our solar system and includes the positions of all the planets which orbit our sun including Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune and Pluto. The heliogram is divided into 12 equal sized sectors each of 30° and labeled sectors 1, 2, 3 etc. in a clockwise direction from the East. Each planet in a heliogram has a planetary address; for example, a planetary address of 1215 means that the planet is in sector 12 at the 15th degree.

    Good to know. Perhaps the next New York Times article will discuss the freakonomics of heliograms. I look forward to it.

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  6. David Kane says:

    It appears that Dr. Levitt found his graph here.

    Reliable data? Tough to know. Wonder why Dr. Levitt didn’t follow the universal blogospheric practice of providing the link? You’ll have to ask him. But I certainly wouldn’t put an excessive amount of faith in a webpage that starts with this:

    Do the world’s best hockey players have a common cosmic signature? Does Mercury tend to be in a certain area of the sky when a professional hockey player is born? I am intrigued by that question and many, many others and what follows are the observations I have made during the course of the project. Stay with me, this gets very interesting.

    During the 2001-2002 hockey season the National Hockey League was composed of 30 professional teams located in Canada and the United States of America, averaging 26 players per team (range 22 to 31), a total of 761 individuals. Birth information was gathered for each player including the day, month, year, city and country of birth. The time of each player’s birth was not readily available and so the time for each player was set for noon on the day of birth, halfway through the planetary motions for the day. The birth information was input to Matrix Software’s Win*Star Plus program which accurately produced a heliogram for each player.

    HELIOGRAMS

    A heliogram is a two dimensional arrangement of the planets around the Sun at the time of the birth of any individual. The position in the heliogram of Mercury, Venus, Earth and Mars for each player was transferred into Microsoft’s Access database along with information about the heliogram “type” and the planetary patterns associated with the heliogram. The heliogram is a heliocentric view of our solar system and includes the positions of all the planets which orbit our sun including Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune and Pluto. The heliogram is divided into 12 equal sized sectors each of 30? and labeled sectors 1, 2, 3 etc. in a clockwise direction from the East. Each planet in a heliogram has a planetary address; for example, a planetary address of 1215 means that the planet is in sector 12 at the 15th degree.

    Good to know. Perhaps the next New York Times article will discuss the freakonomics of heliograms. I look forward to it.

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  7. SteveSailer says:

    Dear Dr. Levitt:

    Thanks for looking into this further.

    Congratulations to Bill L. Lloyd for his hard work and insights.

    This kind of information could help answer questions about the relative importance of nature vs. nurture in different sports. For example, I would hypothesize that age cutoffs and birthdates would have little correlation with who makes the NBA (especially at center and forward), since height, which is highly heritable, is so overwhelmingly important and thus most players are drawn from the right edge of the height bell curve. If you are Manute Bol, the 7′-7″ Dinka tribesman from the Sudan, you can enjoy a lengthy (if curious) career in the NBA, and lead the league in blocked shots, even though you didn’t see a basketball in your life until you are 19.

    On the other hand, perhaps a sport like soccer where players mostly are fairly average in size is more driven by nurture than nature than is basketball. It’s hard to imagine the soccer equivalent of Manute Bol or of Nigerian Hall of Fame basketball center Hakeem Olajuwon, a seven foot who switched from being soccer goalie to a basketball player at about 16.

    I don’t pretend to know enough about soccer to make a prediction, but the relatively slow progress of the U.S. in the soccer World Cup, compared to say, Argentina in Olympic basketball, might suggest that culture is a bigger driver of success in soccer than in basketball.

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  8. SteveSailer says:

    Dear Dr. Levitt:

    Thanks for looking into this further.

    Congratulations to Bill L. Lloyd for his hard work and insights.

    This kind of information could help answer questions about the relative importance of nature vs. nurture in different sports. For example, I would hypothesize that age cutoffs and birthdates would have little correlation with who makes the NBA (especially at center and forward), since height, which is highly heritable, is so overwhelmingly important and thus most players are drawn from the right edge of the height bell curve. If you are Manute Bol, the 7′-7″ Dinka tribesman from the Sudan, you can enjoy a lengthy (if curious) career in the NBA, and lead the league in blocked shots, even though you didn’t see a basketball in your life until you are 19.

    On the other hand, perhaps a sport like soccer where players mostly are fairly average in size is more driven by nurture than nature than is basketball. It’s hard to imagine the soccer equivalent of Manute Bol or of Nigerian Hall of Fame basketball center Hakeem Olajuwon, a seven foot who switched from being soccer goalie to a basketball player at about 16.

    I don’t pretend to know enough about soccer to make a prediction, but the relatively slow progress of the U.S. in the soccer World Cup, compared to say, Argentina in Olympic basketball, might suggest that culture is a bigger driver of success in soccer than in basketball.

    Thumb up 0 Thumb down 0