How Big Data helped US Women Cycle team move from underdogs to silver medalists at the 2012 London…

How Big Data helped US Women Cycle team move from underdogs to silver medalists at the 2012 London Olympics

Welcome to my #datastories series, where I talk about data and how it’s influencing businesses to take decisions at scale.

#datastories Series 1 - Story 1

This story will help you understand how Big Data helped athletes to optimize their performance. People never thought sports and big data would become friends in the late ’90s. But later they understood things are moving in a different direction and developers started thinking why can’t we marry big data with any data-driven problems.

I would like to include a problem solved by a high school club that uses data science to predict which teams the NCAA will select for the Division I Men’s Basketball Tournament.

Bracketology Club: Using March Madness to Learn Data Science - Bracketology Club: Using March Madness to Learn Data Science

Back to the story: How the U.S. women’s cycling team used analytics to leap from underdog status to silver medalists at the 2012 London Olympics.

The team was struggling when it turned to Sky Christopherson for help. Christopherson, is an American entrepreneur, Olympic Athlete, World Record Holder, and public speaker. He is known for breaking a World Record[6] in 2011 in the velodrome sprint, notably using a ‘digital health’ model inspired by Dr. Eric Topol. He started a community to help improve the US women’s cycle team’s possibilities of winning in the Olympics by identifying the secret sauce to success. He wanted to develop a program for athletes that consumed data to improve their performance instead of consuming drugs. He came up with OAthlete project, which helped find the Lance Armstrong Drug Scandal

Lance Armstrong Is the Dirtiest Cheater in Sports History

The philosophy behind the OAthlete program is “data not drugs”. Christopherson came up with a sophisticated design to capture the athlete’s performance versus their diet, sleep patterns, environmental factors, training intensity, and whatever feature that can help find the pattern and help them perform better in Olympics. Big Data enables a high-performance sports team to quantify the many factors that influence performance. Which helped him to identify key elements and to plan their training accordingly with stopping of overtraining that often resulted in injury.

Data captured from athletes were structured and unstructured. It mainly had information such as blood sugar level, skin parameters, pulse, ambient information, sleeping patterns, and diet. Christopherson partnered with Datameer, San Francisco based data analytics provider. Where the data is pushed to the cloud in a Hadoop Distributed File System and the company was analyzing their data and coming up with a dashboard for helping the athletes.

Domain knowledge plays an important role in any industry for solving real-world problems. Christopherson partnered with Datameer to help optimize the athlete’s performance. Datameer’s CEO, Stefan Groschupf, himself a former competitive swimmer at a national level in Germany, immediately saw the potential of the project. Christopherson said “They came back with some really exciting results — some connections that we hadn’t seen before. How diet, training, and environment all influence each other — everything is interconnected and you can really see that in the data.”

Here the idea is to find patterns across different datasets and combining the knowledge to really improve the performance of the athletes to ensure their possibilities of winning in the Olympics.

How Big Data helped US Women Cycle team move from underdogs to silver medalists at the 2012 London Olympics

Credits