Can An Economic Model Predict The Olympics?
March 3rd, 2010
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Economics professor Daniel K.N. Johnson thinks that the world is much more predictable than you would expect. It’s no surprise that he can use economic models to predict unemployment rates. But one day, he decided to see if he could predict Olympic medal counts the same way.
He didn’t expect it to work, but it did. From the 2000 through 2008 Olympic games, he predicted total medal counts by country with 94% accuracy, and gold medal counts by country with 87% accuracy.
It’s amazing how little information he need to give the computer, and in fact, he doesn’t look at individual athletes at all. He only considers five factors: per capita income, population, climate, political structure, and home court advantage. His track record speaks for itself:
| Event | Accuracy rate of predictions Total medals (Gold medals) |
| 2008 Beijing Summer Games | 93% (92%) |
| 2006 Torino Winter Games | 93% (89%) |
| 2004 Athens Summer Games | 94% (86%) |
| 2002 Salt Lake City Winter Games | 94% (85%) |
| 2000 Sydney Summer Games | 95% (84%) |
In Beijing, he predicted 103 medals for the U.S., with 33 gold. The actual count: 110 and 36. In Athens, he predicted 103 medals for the Americans, with 37 gold. The final results: 102 and 36.
He admits that China causes problems for his model, because there’s no one to compare them to. But other than that, the key to Olympic victory is clear: a successful country should be rich, big, and cold. It should also have a single-party government, and most importantly, it should host the games itself.
The model has held up remarkably well, and not even the anomaly of Michael Phelps threw it off much. But while it’s interesting that a handful of variables can tell you so much, it’s also a bit depressing that the world is so predictable. You could say they might as well just hand out the medals and skip the formality of actually competing.
When I heard about Daniel K.N. Johnson a few weeks ago, I made a note to see how well he predicted the 2010 Winter Games in Vancouver. The results are in, and surprisingly, he did a really awful job:
| Country | Predicted Medals Total (Gold) |
Actual Medals Total (Gold) |
| Canada | 27 (5) | 26 (14) |
| United States | 26 (5) | 37 (9) |
| Norway | 26 (4) | 23 (9) |
| Austria | 25 (4) | 16 (4) |
| Sweden | 24 (4) | 11 (5) |
| Russia | 23 (8) | 15 (3) |
| Germany | 20 (7) | 30 (10) |
| Italy | 19 (3) | 5 (1) |
| Finland | 14 (4) | 5 (0) |
| Switzerland | 13 (4) | 9 (6) |
| China | 12 (2) | 11 (5) |
| South Korea | 11 (4) | 14 (6) |
| Netherlands | 10 (3) | 8 (4) |
Not sure what happened here, but it looks like the world isn’t so predictable after all. I guess computers don’t believe in miracles.
Photo by Duncan Rawlinson
March 3rd, 2010 at 8:21 am
The majority of economists seem to be rather useless, as it appears to be much more of an art than science. The models they create are great for analyzing the past. However, at some point the models always fail because they can’t possibly include every variable and probably include some useless variables that just happen to be a coincidental indicators. Plus, there is always some Black Swan event that pops up to screw with the model.
It is also kind of like in physics, which suggests you could predict everything if you knew every bit of information about every particle in the universe. However, just observing the particle changes its properties.
Just knowing what the models look for causes people to artificially change those variables.
March 4th, 2010 at 1:00 am
@ Chad, did you hear about the Motley Fool back in the 90s? They had a stock-picking formula that was purported to double the return of the Dow.
But this claim was based on its return over the 20 year period ending in 1994, or something like that. They just looked at that range of the past data, and found a formula that worked over that time. But it didn’t work before that period, and there wasn’t any data to see if it would work going forward (it didn’t).
March 4th, 2010 at 6:44 am
I had never heard of the specifics behind Motley Fool. Not surprising it was essentially fake. Of course, it was amazing popular for a few years because it promised easy money.
The interesting thing with economics is that I bet people with decent experience in whatever field the economist is modeling could be as accurate with off-the-cuff predictions.
For example, with the olympics, I’m fairly confident I could guess and get an accuracy rate of 80% and up. My method would take 15-20 minutes total (guessing for each country based on prior olympic medal totals) and this economists method took how long to develop? Days? Weeks? Sometimes I wonder if we try to be too precise with a lot of things and make them more expensive or labor intensive than necessary.
Another example would be the housing bubble. When people making $100k a year were having trouble buying a house in half the country it seems rather obvious something was wrong. It’s not like the U.S. population doubled in 5 years and space was at a premium. How much more info did these economists who failed to predict this event need?
March 4th, 2010 at 2:33 pm
Whew! We can go on living life! These predictions remind me of a movie where people just sit at home with a cap on their head thinking about what they want while androids read their thoughts via the cap and then live the peoples’ lives for them by acting on the thoughts. Yuck! Who the hell wants that?!
There are too many variables for such a prediction and by his own admittance China, who wins a lot of medals, throws it off. (So we just ignore China.) You can’t account for passion, drive, spirit, etc, especially in sports that don’t lend themselves to the most stacked teams winning. The U.S. hockey team is a great example. No way that team wins silver, let alone almost gold, on paper.
People are always disproving not only formulas but science itself. Formulas fail to measure one thing: Choice. They make it look like you have no choice, as you note when you say “just hand out the medals” without competing. (Incidentally, in their previous two Olympics as host, Canada didn’t win one gold, which really throws a wrench into the professor’s formula.) A great example is wind musicians. Science claimed for ages that you can’t exhale or inhale simultaneously. We used to argue with our teachers about it in high school because we had trumpet players in band who could “circular breath,” inhale while exhaling, holding notes for several minutes. I had a biology professor who called me a flat out liar! Then Kenny G came along years later and held a note for over a day… pretty sure he had to breathe while doing it! These musicians made a choice to go against the scientific rules of the body and got their body to do what they wanted. Remarkable! And something that won’t show up in any formula.
March 5th, 2010 at 12:54 am
@ Chad, bubbles always seem to sneak up on even the experts, because for some reason they think the rules are different this time.
When I first started looking into investing in stocks in the mid 90s, what I heard from everyone was “The market used to average 10% a year in the long run, but that was in the old economy. The internet changed everything. In the new economy, it averages 15% a year in the long run.”
Of course, it didn’t last. I wonder what economic models predicted that it would.
@ Ian, I don’t know if I’ve seen a formula that attempted to account for choice. I just started reading your book Choice – The Meaning of Life, so I’m interested in seeing what you have to say about how we make choices.
I hadn’t heard of circular breathing, and I would have thought it was impossible. I sure can’t do it, but I guess it’s supposed to be hard.
March 8th, 2010 at 12:34 am
Hi there,
Thank you for for using my photograph in this post!
Please attribute the photograph to Duncan Rawlinson and link to me @ http://www.TheLastMinuteBlog.com
Thank you.
March 8th, 2010 at 12:53 am
@ Duncan, it’s a great photo, thanks for taking it! I changed the attribution from your Flickr account to the URL you gave.
March 9th, 2010 at 12:49 am
You know, I wonder if he regresses his model against this new data if he’ll find another variable that he was missing that corrects for it.
I’m surprised at how bad the predictions were for the recent Olympics – perhaps the home court advantage was stronger than he expected it to be? Or perhaps he needs a different model for summer versus winter olympics?
I was an econ major in college, and I love taking looks at stats like these, since I have a background in statistics, and now with software development, I am able to manipulate datasets
Or you’re right – perhaps we just can’t account for miracles in medal counts, and there will always be some outlier cases that beat the odds =P
March 9th, 2010 at 1:55 am
@ Sid, I hope we hear what he has to say about it. Considering how accurate he was before and how inaccurate he was in Vancouver, maybe there was just a glitch. Anyway, I’d love to hear his explanation of what happened!
March 16th, 2010 at 1:10 pm
Thanks for updating attribution!!!