Athletes are always working to improve, and big data could be the next catalyst in the development of training techniques for the 2016 Rio Olympics. Coaches and athletes alike have been working with analytics and big data to gain the highest amount of insight possible. This is especially true in the highest levels of each sport, so naturally big data is used in the training for the Olympic Games. There is a lot of pressure on Olympic athletes to use the newest analytics technology.

 

The British Olympic rowing team certainly feelt this pressure. They are the only team from Great Britain that has won the gold medal in every Olympics since 1984, and they definitely wanted to keep it up. (In case you didn’t follow the Olympics this year, Britian’s men’s coxless four and men’s coxed eight both took gold in Rio, as did women’s coxless pair.) They have been utilizing the most advanced data-driven analytics with the goal of making their boats go faster.

 

Rowing is, in some ways, automatically compatible with analytics. The majority of what the athletes do can be measured. Whether it’s a session in the gym or on-water training, the data will most likely be quite similar to the actual performance. However, there are also a few challenges in using analytics for rowing. For example, rowing occurs outside where weather and water conditions are unpredictable.

 

Sir David Tanner who has led both the Olympic and Paralympics rowing program since 1996, is a large part of the analytics process. Two of the most important uses of the analytics are in the identification and and tracking of talent. While both of these aspects are important, talent tracking is the most crucial. After every possible bit of data is collected about each athlete who enters the training program, the profiles of new entrants can be compared to those of former entrants in order to figure out which approach will set each individual up for success.

 

Just like a number of businesses, sports teams are seeing that positive results will likely be generated by a holistic approach to data management and strategy. Sir David Tanner feels that longitudinal profiling of athletes, as well as biomechanics and exercise physiology are the fields with the most potential.

 

Another common thread between the methods of sports teams and businesses is the importance of partnership. Most people in the field of elite sports science and physiology are not well-versed in the technical skills necessary to create a Big Data-driven analytics system. Great Britain’s rowing team has worked alongside several tech partners such as Siemens and SAS to implement an analytical framework. Collaboration is also occurring on the managerial level, where the data strategy is planned.

 

Rowing requires a balance of strength and endurance. As a result, conflicts can arise in training practices. Endurance training can work counter-actively to strength training, and vice versa. This challenge can be combated using large amounts of past performance data, which can show what gains a certain rower will most likely make after being trained using a particular regime.

Another positive effect of this system is the decrease in injuries. The analytics system is able to highlight warning signs and match them against past data to indicate when an athlete is at risk of pushing themselves too hard. Analytics and Big Data are playing a significant role in the training of Great Britain’s rowing team, and they showed that it can make a big impact with this legendary team’s performance at the 2016 Olympic Games in Rio.