Melt down the Winter Olympics data!

Data Olympics

Data is gold. (Or so they say nowadays.) Therefore, along with the start of the Winter Olympics in Sochi, Russia, we set out to create our own gold medal in the data olympics behind the sports olympics. We mixed multiple online sources and databases of historical data going back to the first winter olympics in 1924! And created the ultimate interactive dashboard dedicated to the Winter Olympics. Thus, we were able to outline a series of unquestioned trends that are going to impact the event this year.

Winter Olympics Dashboard.png

Hidden Data

All the media’s talk these days is focused on outlining the boasting numbers and records that the Winter Olympics in Sochi has reached. By far, the most talked about fact was that the Sochi olympics costed 40 billion €, more than all the previous olympics put together. But if you have a look at a chart showing the total costs of all the winter olympics in comparison to the number of participating athletes, you may see that the 1998 event in Nagano had a similar cost per athlete rate as the one in Sochi this year. So, at first glance, this fact does not seem unique anymore. But then, if you cross these pieces of information with national economic trends such as the GDP per capita and inflation in each country at the specific year of the winter olympics, you start noticing deeper differences in the power of each country of organizing the winter olympics and affording the costs.

Crowdstar

The number of athletes participating in the winter olympics has grown exponentially in the last decade reaching more than 6000 in Russia and more than 26000 all time. But if you look at the data closer, in the olympic village, every athlete has their own imaginary crowd (not taking into consideration the countless fans). Imagine that more than 4 journalists and 7 volunteers hypothetically followed each athlete at the 2006 Torino Winter Olympics! And the ratio is only due to increase in the following years.

It’s just about talent

What separates a gold medal from a silver one is sometimes a split second, a patch of tougher snow, colder weather, even a bad sleep… Favorites are not always the winners. At what data factors could we look at that could give us insights into the way athletes performed at a certain moment in time. Discover in our dashboard  which were the coldest Winter Olympics and send us your ideas about what other performance data factors we can analyze to extend our queries.

History never lies

Counting on the historical data and applying predictive analytics algorithms, we included our Winter Olympics dashboard the prediction for the Top 10 countries that will win the most medals in Sochi. And this is just the beginning. Think about what level of accuracy we would have if we could access personal performance indicators of the athletes set to compete in the olympics right before the start of the events. History never lies but the age of devices that empower the Quantified Self will sharpen the predicted truth.

Questions vs. Queries

Why did we dig into the history of the Winter Olympics? Because names, medals or performances are no longer the only things that are being recorded when a major sport event takes place. We are now recording how many bottles of water are sold, how many tweets are being sent or how many fans watched a certain sport event at a specific moment in time. We now have vast amounts of data about all these. BigData has conquered sports, too and, as competition only rises with each grand prix, world championship or olympics.

We can now find in an instant which sportsmen won the gold medals in the alpine skiing events in 1968 in Grenoble just by asking a simple question from an online database incorporating information regarding the Winter Olympics history. This is curiosity. We want to go further and this is why we do not put questions. We set up queries. This is understanding.

 

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SOURCES:

1. http://www.databaseolympics.com/

2; http://www.topendsports.com/events/winter/index.htm

3. http://www.inflation.eu/inflation-rates/cpi-inflation-1968.aspx

4. http://en.wikipedia.org/wiki/List_of_countries_by_past_and_future_GDP_(nominal)_per_capita

5. http://thinkprogress.org/sports/2014/02/03/3239131/sochi-olympics-cost-winter-olympics-combined/

6. http://www.wunderground.com/history/

CREDITS (ICONS):

Medal by Andrew J. Young from The Noun Project
Trail View Hiker by Luis Prado from The Noun Project
Skiing by Nithin Viswanathan from The Noun Project
Coins by Rémy Médard from The Noun Project
Volunteer by deadtype from The Noun Project
Crowd by Shane Holley from The Noun Project
Newspaper by Yorlmar Campos from The Noun Project
Video by Thomas Le Bas from The Noun Project
Woman by Monika Ciapala from The Noun Project