Data Analytics Is Winning Gold in Rio
Posted by Shaziya B on Wednesday, August 10, 2016 - 18:48
Team USA is staying on a cruise ship. Michael Phelps has 25 gold medals. Katie Ledecky, Lilly King and Simone Biles seem to be the up-and-coming legends for Team USA.
Alright, big things are happening in Rio this week, but none bigger than the data. The least exciting sounding part plays possibly the biggest role in the ongoing success of the games, the contenders and the countries.
With a total IT budget for the 2016 Olympics at a whirlwind $1.5 billion, the amount of data transferred and used by the world will be a marked increase from just four years ago in London.
Predictive win efficiency.
In a world with live-tracking of each contender’s current physical state as they compete, it’s almost impossible to miss the final results. What if, however, you were able to predict the outcome even before contenders reach the finish line?
Data analytics makes predicting results an absolute breeze.
Gracenote, a provider of entertainment data, is using its predictive analytics expertise to provide detailed predictions on which countries will top the medal tally and the athletes that will help them get there. Gracenote has performance data from thousands of events and its database even backlogs to 100 years, ensuring the system is composed of the most accurate, real-time performance results. These predictions are then used by broadcasters and web services to pick-and-choose from, and provide their audiences with the relevant results.
Big data = gold medals.
Athlete efficiency is key to the success of teams across the globe, but apart from physical and mental endurance, athletes now have datasets to compare from and use for optimal performance.
Data intelligence is used across the globe and mostly paired with traditional business practices, but in sports, it’s used to help franchises and countries make better athlete-related decisions. One way to do this is through the practice of using data sets with predictive modeling to build a winning team.
A great example of the use of data to ensure elite performance is the British Olympic rowing team - the only GB team to have won gold in every Olympics since 1984. As one of the most intrinsically analytics-friendly events, athletes can be measured from on-water training to sessions in the gym, truly bearing relation to actual performance.
As with any data, sets change with every play, which then shifts the emphasis from the amount of points scored to more in-depth and accurate measurements of an athlete’s overall efficiency, productivity per touch and defensive effectiveness. This data then helps the coaching staff determine what changes need to be made on subsequent plays and during future events.
Using information, such as longitudinal profiling, biomechanics and exercise physiology, helps sporting organizations not only gain a view of the athletes’ efficiency and processes, but also partner with tech giants to create a view notable to both fields.
Sports organizations need data to win, and tech companies need data to continue to innovate. Together, there’s plenty of commonalities to create a win-win situation for both parties.
Keeping Zika (or any potential harmful viruses) miles away.
Naturally, we want our contestants to be healthy, and with the threat of the Zika virus looming over Rio, it’s important for athletes and staff to be safe.
To ensure this from a technological standpoint, IBM is helping the Olympics committee by leveraging big data analytics to crowdsource data from social media, such as organizing and arranging huge amounts of data, including the frequency and distribution of social media comments and conversations about Zika and other viruses.
Using information, coming directly from the people, helps the committee focus on using weather and location to further determine high-risk areas and prevent probable infection to athletes, as well as visitors and the audiences of the Olympics.
As I complete this, I envision a Zach Galifianakis meme - showing numbers being calculated in his head - and I think, “woah, data analytics is pretty cool.”
Back to Rio.