The Province

Getting the drop on data points

ANALYTICS GAME-CHANGER: Sportlogiq has the numbers and knows what to do with them

- PATRICK JOHNSTON

What actually happened? What was actually important?

Those are water cooler questions that go back a long time. They’re also questions that hockey’s number crunchers have been chasing for some time now.

The challenge in answering those questions since Day 1 has been the quality of data.

But now a team of computer scientists, led by a figure skater from North Vancouver and a computer scientist from Iran, may finally have figured it out.

A host of hockey people and famous sports franchise-owner and tech billionair­e Mark Cuban think so.

Craig Buntin knows so.

Buntin is the CEO of Sportlogiq, the Montreal-based tech startup that is looking to change the way coaches, scouts, players, fans and broadcaste­rs look at the game.

“Reaction’s been everything from, ‘My God, this has been what I’ve been waiting for for 10 years.’ ... The other half is, ‘This is a lot of data and we don’t know what to do with it,’ ” he said. But Buntin believes there’s no doubt the enthusiasm is there and his team is ready for the challenge.

Other sports are using high-tech cameras or radio-frequency ID chips to track player movement and record game data, but Sportlogiq has its own twist: Computer vision and machine learning.

Buntin, who grew up in North Van before finding his training home in Kelowna, founded Sportlogiq with Mehrsan Javan, who now serves as the company’s chief technology officer.

Javan completed his PhD at McGill University’s Centre for Intelligen­t Machines, where his research focused on statistica­l modelling, computer vision and machine learning. The technology Sportlogiq now employs grew out of Javan’s PhD thesis.

“The idea starts and then you meet smart people,” Buntin told The Province this week from Montreal.

Sportlogiq has developed software that can process submitted video, look for patterns it has learned from previously viewed data and then code it for further analysis. How to use the data was a question from the beginning.

“Very early on, we brought on a guy named Chris Boucher, who spent years in his house manually going through games event by event. He came up with a very labour-intensive method,” Buntin explained. “We had a template to start with. Then we brought in the computer vision tech and the engineers and we said ‘We can automate this.’ ”

Automated mass-data collection is Sportlogiq’s secret sauce.

Buntin spent a decade at the top levels of figure skating. He finished 11th in pairs at the 2006 Olympics in Turin, skating with partner Valérie Marcoux. They were national champions three times as well.

After retiring from competitiv­e skating in 2010, Buntin studied for his MBA at McGill. His interest in hockey also drew him into the emerging world of sports analytics.

Hockey analytics was growing by leaps and bounds, but a problem persisted: There were always gaps in the data. You could say “this guy is good at this” and you could look at other numbers to figure out much of that player’s skill set, but it was still an incomplete picture.

If a player gets a good scoring chance, is he solely responsibl­e for that chance or did a teammate’s win of a puck battle contribute as well? Are some players better at retrieving loose pucks over others? Do we actually know who the best passers are?

There’s also a significan­t problem — not every data point is equally useful. When you collect large volumes of data, a lot of it doesn’t tell you anything at all.

That’s been the biggest challenge to the analytics revolution in hockey — determinin­g which events (eg. hits and shots) and skills really matter. Players can be have poor puckposses­sion numbers, but how much is that about them and how much is that about their deployment on the ice or the quality of teammates.

Since the Sportlogiq system captures everything, Buntin believes they’ve solved that problem. They can build a picture of what’s happening at any given moment in a game and then break it all down to see what happened.

“We are not here to make a small impact, we’re here to fundamenta­lly change it,” he said. “Once you can locate every single player, every single joint on the ice, everything can be quantified.”

Note he said “joint.” Yes, this system can track not just player position, but the player’s individual body movements. The most effective techniques can be determined. It’s a coach or scout’s dream.

The premise is simple: Video, it doesn’t matter where from, is fed into the Sportlogiq software, which has been programmed to recognize human movement and record all the events presented to it. Machine learning allows the computers, which are processing the video, to recognize from past experience what it’s seeing in the new, never-before seen video.

The computers code the video and record events. Buntin said his team has found an average game has between 2,500 and 3,000 events. Once the software has processed the video, the data are double-checked by the Sportlogiq team to make sure nothing has been missed. With all this new data, they have looked at stats and skills which convention­al analytics has already revealed to be useful and are now finding new ones as well.

One of the skills Sportlogiq has uncovered is “loose puck recoveries.”

“It’s a combinatio­n of speed, strength and hockey sense and has a huge impact on scoring,” said Andrew Berkshire. Berkshire was the lead writer and editor for noted Canadiens blog Habs Eye on the Prize, but was hired this summer to manage editorial content for Sportlogiq’s site. Data-focused hockey writer Thomas Drance has also been brought into the fold as a freelance contributo­r.

“Loose puck recovery has a huge impact on scoring, we’ve found,” Berkshire said. “It’s a data point that emerged because the whole picture was now available.

“We’re looking at what’s the most common outcome when a player does ‘X.’ Another was looking at whether certain players were more effective in throwing hits that turned over possession.

“Alexei Emelin had many hits that took guys off the puck, but few that turned over possession.”

A famous teammate of his was far better: 65 per cent of PK Subban’s hits led to a change in possession.

The reception in the industry, from teams and analysts alike, has been positive.

“We’ve been working with about a half-dozen NHL teams in the last five or six months. We provided data on at least half of the players who were drafted,” Buntin said. Two broadcaste­rs have also expressed interest.

And then there’s Mark Cuban, owner of the NBA’s Dallas Mavericks, who made his billions in the tech industry and has long held interest in the developmen­t of sports analytics.

Buntin and Javan started their funding search a year and a half ago with Montreal-based startup-incubator TandemLaun­ch, who told them to go out and find the people on the tech side, on the communicat­ions side and on the developmen­t side.

“When we first put the fundraisin­g plan together, we set a target and went after smart money. Cuban was top of the list. Having him on board, I knew, would be big from a product and market developmen­t standpoint, but also for networking in general,” he said.

As soon as Cuban saw what Buntin’s team was working with, he was impressed. That Sportlogiq’s technology will be available to anyone with a camera — not just profession­al teams — is what sold him, Buntin said.

“It’s the thing we offer that no other tech does,” he said. “Other systems use expensive multi-camera setups or wearable chips.

“We said, if you could do what they do but with just one camera, you could change all this. You look at every single sport at every level, there’s at least one camera. We can bring what the pros have to everybody.”

Last month, Cuban put $1.7 million worth of seed money into the company alongside a number of other new investors so Sportlogiq could bring more talent on board.

The company is hiring computer engineers left, right and centre because interest is so great.

“What we’re doing first is really explorator­y,” Buntin said. “We’re coming up with every thing that’s possible to look at in a game and then looking at how the data clusters. There are really clear initial stories that pop out.”

“Once you can locate every single player ... everything can be quantified.” — Sportlogiq CEO Craig Buntin

 ?? — PIERRE OBENDRAUF/MONTREAL GAZETTE FILES ?? Sportlogiq CEO Craig Buntin, a former Olympian, has turned his attention to sports analytics with computer scientist Mehrsan Javan.
— PIERRE OBENDRAUF/MONTREAL GAZETTE FILES Sportlogiq CEO Craig Buntin, a former Olympian, has turned his attention to sports analytics with computer scientist Mehrsan Javan.
 ?? — PHOTOS: SPORTLOGIQ ?? Sportlogiq’s sports analytics software reads submitted video and tags any play it sees based on knowledge it has gathered from all the videos it has seen before. This is machine learning, where the computer discovers new connection­s on its own.
— PHOTOS: SPORTLOGIQ Sportlogiq’s sports analytics software reads submitted video and tags any play it sees based on knowledge it has gathered from all the videos it has seen before. This is machine learning, where the computer discovers new connection­s on its own.
 ??  ?? Sportlogiq’s researcher­s have found that an average game features as many as 3,000 events or different plays. The data is collected and the resulting data sets are displayed in user-friendly presentati­ons.
Sportlogiq’s researcher­s have found that an average game features as many as 3,000 events or different plays. The data is collected and the resulting data sets are displayed in user-friendly presentati­ons.

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