Can Big Data and Predictive Analytics Forecast the Olympic Medal Count?

SochiPredictEveryone has the friend who “knew that was a gold medal run” or “would have put money on that game”, after the results are in, but is it possible predictive analytics could have forecasted the podium standings before?

With all the hype around big data these days it’s no surprise there were multiple groups taking a stab at 2014’s results. Using only publicly available data, there were some pretty impressive attempts. The good people at MicroStrategy put together an entire analytics dashboard, taking into consideration historic standings, GDP and population.

With the Olympic Games coming to a close this weekend, it’s interesting to see how close they came. We applaud their efforts!


Looking for even more accurate predictions? You need some inside information! A big data rule of thumb highlights the dependance on the 3Vs: volume, variety and velocity. Although there are years of publicly available Olympic data, it can only go so far when it comes to variety and velocity.

The probability of successful forecasting increases as you collect more diverse data. How many hours did Apolo Ohno spend on the ice in September? Any recent weight fluctuations on the hockey team? How much did Alexandre Bilodeau’s skis cost? In a perfect world, you would have access to some metadata as well – what browser did Shaun White use booking his flights to Sochi?

We’re always fascinated to see the different ways predictive analytics are being put to use. As understanding and application of big data continues to disrupt industries such as credit reporting, sales recruiting and insurance, it looks like sports betting might be next. We’ll keep an eye out for 2018’s predictions!

See MicroStrategy’s entire analytics dashboard here.

Share on LinkedInShare on FacebookTweet about this on TwitterShare on Google+Email this to someone
Kayla Kozan

Kayla Kozan

Director of Marketing at Ideal
Kayla spent the last few years studying Marketing and Entrepreneurship on 3 different continents. Now covering the latest in predictive analytics, workplace diversity and big data. She has a keen interest in tech and discovering underrated brunch spots.
Kayla Kozan