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Advanced Analytics for Team SCA

Advanced analytics, combined with boat-speed sensors and GPS-based speed measurements, gives Team SCA a competitive edge.


There's no doubt that technological innovation continues to improve performance in sports, and in all other aspects of life. Changes in yacht rigging, materials, new instrumentation and techniques have all contributed to improved results over the years. Consider this: In the first Volvo Ocean Race (then called the Whitbread Classic) in 1973, the winning team went 305 miles in 24 hours. In 2008, the winning team went almost 600 miles in the same time. All-women crews have competed in the Volvo Ocean Race in the past. But for this race, SCA wanted to give them every possible advantage to increase their chances of winning.

Download the complete case study [PDF, 473 KB]


In 2015, for the first time, the Volvo Ocean Race regulations required all teams to sail an identically-constructed vessel. So competitive advantage comes from the crew on board and the information steering their decisions. To give Team SCA an edge, the company chose Accenture as their principal Team SCA digital supplier to provide data analytics and visualization tools that shaved precious seconds off time.

Download the Case Study

How Accenture Helped

Accenture partnered with Team SCA to gain critical insights through analytics on their performance onboard by helping them:

Calibrate boat speed

Data from sixty different sources including boat-speed sensors and GPS-based speed measurements was analyzed at ten-second intervals to determine the speed of the water current and how to choose the fastest track towards the finish line. Using live sensor data combined with historical data, the calibrated boat speed was featured in the navigation software onboard, and applied to other calculations including performance reports and data visualizations such as polar diagrams (a calculation of the maximum potential speed of a vessel in any given condition).

Anticipate weather conditions

Routing decisions based on expected weather conditions were made by analyzing both historical weather data and actual weather data as the race unfolded. The analytics results were displayed through data visualizations.

Get regular progress reports

By analyzing both the boat sensor data and manually recorded data from the team – including sail usage and configurations and crew member roles – custom reports and post-leg performance summaries supported the team’s performance. The reports typically compare actual boat performance to the polar diagrams that suggest data-driven decision options including different sailing configurations or helmsmen.


As the race progressed, it was clear that the performance of Team SCA’s crew improved. That was partly thanks to the insights fed through boat sensors that optimized every aspect onboard.

Leg eight featured difficult sailing conditions from Lisbon, Spain to Lorient, France. Yet Team SCA won, crossing the finish line after 3 days 13 hours 11 minutes and 11 seconds. It was an intense 647-mile leg marked by light winds at the start to brutal upwind conditions blowing at 30 knots (35 miles per hour) toward the finish. The team received insights that steered them toward a more offshore course as they headed into the Bay of Biscay. And came in first against the rest of the fleet.

Download the complete case study [PDF, 473 KB]