Automation for Racing Sailboats

Improving Your Skills

Sailing is a complex sport. The racing skipper must read inputs from many sources, process them against their vision of how the weather and competition will change, and translate that into action. All in seconds or less.

So how does the average racing sailor improve? Experience? Lots and lots of experience? This is a hard question. Many successful racing sailors have turned into either authors (Stuart Walker, Buddy Melges) or coaches (Tucker Thompson) or both.  We can buy and read their books and translate them into our experiences on the water. If we are fortunate, we can hire the coach.  But for the average club racer, much of the writing is either impenetrable or is not situation-specific. And coaches are a luxury out of reach of most of us.

The trick is in learning to discern the import changes in the sailing situation and take quick action on them. Most often the mistakes we make are in missing an important change or in wrongly assessing the importance of a change. This isn't surprising - the sheer volume of information steadily flowing to the skipper is daunting:
  • Wind velocity
  • Wind direction
  • Expected wind changes
  • Current
  • Crew capability
  • Sails and gear
  • Nearby boats' affects
  • Shallows and obstructions
  • Desired positioning
And many others.

There are some fantastic instrument packages out there and they can feed us yet more information to process.  On bigger boats, crew are assigned just to read the instruments and make recommendations to the skipper. And again, this isn't a luxury most of us have.

We feel that there are two specific things we can do to train ourselves more effectively as racing skippers. First is to have a thorough, up-front assessment of the expected conditions for the duration of the race. This embedded understanding reduces the time it takes us to process changes against that model.  Second is to have a thorough post-race evaluation of our decisions and their impact.

Our automation team is developing software for these two purposes. First, to predict the conditions for upcoming races and to optimize route and strategic planning. Second, to analyze data post-race against the observed conditions and the leading competitors to find and optimize the race-course decision points.