From cars to catamarans, how big data plays in sports

From cars to catamarans, how big data plays in sports

Summary: Data analytics can do a lot more for business than just predict consumer shopping habits.

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Team sports aren't the only area for big data to make a big impact.

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For years, sensors have been used on the auto racing circuit by drivers looking for an edge.

Speaking ahead of the start of the IndyCar GoPro Grand Prix series race at the Sonoma Raceway on August 25, Penske Racing strategist John Erickson told this ZDNet reporter that there are some 200 data points scattered around a one-person vehicle. With them, strategists on the sidelines can get immediate readings for the car's tire pressure and temperature, oil temperature, brakes and more.

Ron Ruzewski, technical director for Penske Racing, acknowledged that the sensor data still requires a person to make a decision. At Penske Racing, there are typically three people analyzing the data during a race. Real-time availability matters: Penske team representatives say they can make decisions about the race in as little as 30 seconds and then implement them within a window of five to six laps, depending on the car's fuel level.

And how much data, you ask? Erickson said that the sensors collect roughly five gigabytes per lap. With 85 laps per race in the IndyCar Series, that is a lot of data—not only to be monitored during the race, but also to be saved somewhere for post-race analysis.

Penske reps said the organization partners with Hitachi to offload the data in the cloud and on a physical server. Some of the data arrives already structured, thanks to post-processing done on the car itself.

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As streams of data rapidly flood the world of professional sports, regulatory bodies aren't always quick to welcome the added effect.

In NASCAR auto racing, for example, data can be recorded during the race for later use but it cannot be used while the race is underway, Erickson said.

The approach is similar for the sailing world's oldest event, America's Cup. The 45- and 72-foot long catamarans that race around the San Francisco Bay (now through September 21) have some 2,000 data sensors on board.

On August 24, Oracle chief marketing officer Judy Sim gave ZDNet a preview of how the sensors work during a practice session ahead of the Louis Vuitton Cup, the challenger series of the America's Cup. (Oracle sponsors the event.)

Tracking wind and pressure on the sails, among other metrics, the sensors allow the boat's crew to make alterations, such as trimming the flaps on the wings to change speed and direction, as necessary.

In the case of the United States team sponsored by Oracle—the defending champion—it's fairly obvious who is providing the technical back-end infrastructure for the catamaran's sensor system.

The U.S. team is fortunate in that it has two boats available to race, twice as many as challengers Italy and New Zealand have at their disposal. The U.S. team uses some of the collected data to determine which catamaran to use in a race on a particular day, up to an hour before the race starts.

But the power of big data goes away with the firing of the starting gun. According to event rules, all electronic sensor data is barred from use during the race. The equipment is packed into floating black boxes and must be dumped off the side of the boat before taking off. (The boxes are then later picked up by race officials.)

Not that it would be helpful. Sim says that, given the constantly changing weather conditions on the San Francisco Bay, the data can be misleading. As the great American baseball player Yogi Berra once said, "If you don't know where you're going, you'll end up somewhere else."

Images: Rachel King, ZDNet

Topics: Big Data, Data Centers, Data Management, Oracle, Tech Industry

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  • Old news in bicycle racing

    Pro teams in bicycle racing have been using power meters, heart rate monitors, and cycle computers to gather data since at least 1995 and probably earlier. When I was an amateur racer in 1994, all were within the budget of an amateur racer with a middle class income. I used both a cycle computer and a heart rate monitor in my training and racing.
    Marc Erickson