Olympic sport a numbers game, Canada’s luge team taps into analytics

CALGARY — In a sport timed to a thousandths of a second, finishing fourth can really sting.

Data analysts are working behind the scenes for Canada’s lugers to shave what is less than the blink of an eye off their times not only at the World Cup in Calgary on Friday and Saturday, but in February’s Winter Olympics.

“When we’re looking at a start which is a four-to-five second portion of our luge run and we’re looking for hundredths or even thousands of a second within that start, we’ve relied on a lot of analytics,” three-time Olympian Sam Edney said Wednesday.

Canada has never won an Olympic medal in luge and came agonizingly close in 2014 with a trio of fourth-place finishes in Sochi, Russia.

Since then, the country’s high-performance sport community has tapped into what industry has been doing a lot longer — crunching big blocks of numeric data to build projection models and predict outcomes — for both winter and summer sport.

Edney and Canadian teammate Kim McRae admit their eyes would glaze over if all the statistics from their sport were put in front of them.

“I don’t actually see the data. I get little snippets of it,” McRae said.

The analysts give information to high-performance director Walter Corey, who translates it into luge language for coach Wolfgang Staudinger and the Canadian team.

A practical application of the information showed Edney was pulling harder on the start handles with his right hand than his left, which meant his sled came off the start line crooked.

“We’ve been able to minimize that now and bring it to a point where it is an even pull coming out of the start,” he explained.

The Canadian team will have home track advantage in the World Cup, not just in familiarity but in analytics as well.

Data analysts have a huge sample size from the Calgary track to work with as they have timed runs dating back to 2001.

“We have quite an extensive data base where we can filter out all of Kim’s races on the Calgary track in major competitions over however long she’s been competing for,” data analyst Scott Hunt said.

“We can see the trend in her start times, split times, finish times. We also have targets based on podium level finishes on this track in the past 16 years.”

Predicting what it will take to win a luge medal at the Olympic Games in Pyeongchang, South Korea, is trickier because the track there is so new.

“We have a limited amount of data because the track just got built,” Hunt explained. “It’s also very dependent on weather conditions.

“If weather conditions are similar to what they were in the World Cup last year in Pyeongchang then we can make reasonable predictions.”

But data trends can prompt athletes make changes in their fitness and driving to help them slide faster regardless of the track.

“It’s definitely helping us to make sure we have the conditions in place for our athletes, the type of fitness level we want to see from them, the type of performance we want to see from a start perspective,” Corey explained.

“That type of stuff is really dialled in for Pyeongchang already from analytics.”

Analytics exploded in sport after the 2003 release of Michael Lewis’s book “Moneyball”, which chronicled the Oakland Athletics strategy of using historical statistics to drive decision-making.

Prior to the 2016 Summer Olympics in Rio, the Canadian Olympic team’s sponsorship agreement with Canadian Tire gave athletes access to brains that predict consumer behaviour for the company’s financial services arm.

That group concentrated on the sports of swimming, rowing, cycling and track and field in projecting the times it would take to stand on the podium in Rio. They went 8-for-12 in their medal predictions.

The Canadian Olympic Committee announced earlier this year a sponsorship deal with SAS, an analytics software company whose clients include professional basketball and soccer teams, banks, hotels, universities and casinos.

“If Team Canada is not doing it, you’re going to be left behind because other countries are certainly going down that road,” SAS technical consultant manager Karl Quon said.

“Why wouldn’t you want to take advantage of another weapon at your disposal to make our athletes successful, to win more medals?”

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