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Global News
13-05-2025
- Sport
- Global News
University of Waterloo researchers develop AI technology for Baltimore Orioles
The Baltimore Orioles have called on researchers from the University of Waterloo to help them improve their pitching through the use of artificial intelligence. PitcherNet uses broadcast camera feeds and combines them with low-resolution footage shot on a smartphone. Jerrin Bright, lead researcher on the project, said the AI technology tracks different metrics to analyze a pitcher's performance. 'Most specifically, we find 18 joint positions of the human using the Hawk-Eye tracking system, and this skeleton is then basically used to find metrics like the pitching velocity and the spin rate of the ball,' Bright said. The Hawk-Eye tracking system has 12 high-speed cameras, which capture images at 200 to 300 frames per second that are played at multiple angles on the baseball grounds. Story continues below advertisement The U of W-designed system extrapolates the pitcher's entire throwing motion to re-create a level of detail using elaborate and expensive technology installed in most stadiums that host MLB teams. Its goal is to fill gaps in the technology and provide data that is typically available to the team that owns the stadium where a game is played, as is the case with Hawk-Eye. Get breaking National news For news impacting Canada and around the world, sign up for breaking news alerts delivered directly to you when they happen. Sign up for breaking National newsletter Sign Up By providing your email address, you have read and agree to Global News' Terms and Conditions and Privacy Policy 'They wanted to build a system that can basically mimic the sophisticated system like the Hawk-Eye technology itself, but the catch here would be that you wouldn't have any depth information because we are just going to use single monocular camera and have a coach or a scout be anywhere in the ground, and they'll be able to capture the data and do analysis of the players,' Bright said. The project began in 2022 when the Orioles organization approached Bright and John Zelek, a professor of systems design engineering at the U of W. Bright said the goal is not to replace humans, but to help elevate a pitcher's game. 'They can use different essential systems to find these metrics, but we are just trying to build this just from a broadcast feed that you can see in your television to try to make it more accessible and easier for the coaches or the scouts,' he said. The Orioles organization has been very satisfied with the project, according to Bright, resulting in a two-year contract extension with the professional ball club. Story continues below advertisement He said their contract is exclusive to Baltimore and the U of W researchers haven't collaborated with other MLB teams. Bright said the AI technology could be used in other areas of the sport in the future. He said the AI technology could be expanded to help coaches in amateur leagues and college programs and also help improve scouting.
Toronto Sun
07-05-2025
- Sport
- Toronto Sun
University of Waterloo, MLB team partner on pitcher biomechanics project
Published May 06, 2025 • 3 minute read University of Waterloo researchers John Zelek, right, and Jerrin Bright pose for an undated handout photo in front of an onscreen example of the software they engineered to analyze baseball pitchers. To help train AI algorithms at the heart of the technology, researchers created three-dimensional avatars of pitchers so their movements could be viewed from numerous vantage points. Photo by HO / THE CANADIAN PRESS Staying competitive in the American League East means staying on the cutting edge of technology. This advertisement has not loaded yet, but your article continues below. THIS CONTENT IS RESERVED FOR SUBSCRIBERS ONLY Subscribe now to read the latest news in your city and across Canada. Unlimited online access to articles from across Canada with one account. Get exclusive access to the Toronto Sun ePaper, an electronic replica of the print edition that you can share, download and comment on. Enjoy insights and behind-the-scenes analysis from our award-winning journalists. Support local journalists and the next generation of journalists. Daily puzzles including the New York Times Crossword. SUBSCRIBE TO UNLOCK MORE ARTICLES Subscribe now to read the latest news in your city and across Canada. Unlimited online access to articles from across Canada with one account. Get exclusive access to the Toronto Sun ePaper, an electronic replica of the print edition that you can share, download and comment on. Enjoy insights and behind-the-scenes analysis from our award-winning journalists. Support local journalists and the next generation of journalists. Daily puzzles including the New York Times Crossword. REGISTER / SIGN IN TO UNLOCK MORE ARTICLES Create an account or sign in to continue with your reading experience. Access articles from across Canada with one account. Share your thoughts and join the conversation in the comments. Enjoy additional articles per month. Get email updates from your favourite authors. THIS ARTICLE IS FREE TO READ REGISTER TO UNLOCK. Create an account or sign in to continue with your reading experience. Access articles from across Canada with one account Share your thoughts and join the conversation in the comments Enjoy additional articles per month Get email updates from your favourite authors Don't have an account? Create Account That's why the Baltimore Orioles have partnered with researchers at the University of Waterloo to develop artificial intelligence technology, called PitcherNet, that will help the MLB team track the biomechanics of pitchers at every level of the organization, from the collegiate ranks and through its minor-league system. PitcherNet takes the main camera feeds fans are used to seeing — either from behind the pitcher or behind the batter — and combines it with video footage shot on a smartphone by a scout or team official. Using AI, PitcherNet then extrapolates the pitcher's entire throwing motion, recreating the level of detail that the 12-camera Hawk-Eye system is capable of producing. 'What we do is we try to extract 2-D information, 2-D joint position information, and then extrapolate using 3-D avatars,' said Waterloo PhD student Jerrin Bright. 'The 3-D avatars are like blobs encompassing a human itself and we use those blobs to basically find the 3-D human pose, which can be represented with the shape of the person, so that's the idea behind it.' Your noon-hour look at what's happening in Toronto and beyond. By signing up you consent to receive the above newsletter from Postmedia Network Inc. Please try again This advertisement has not loaded yet, but your article continues below. Read More Sig Mejdal, the Orioles' assistant general manager, said that in his experience it's a necessity to evolve, even in a sport as old as baseball. 'It's completely mandatory,' said Mejdal, who worked for NASA and Lockheed Martin's satellite operations unit at Onizuka Air Force Station in Sunnyvale, Calif., before moving to the St. Louis Cardinals and then the Houston Astros. 'The success that I've been a part of in St Louis, Houston and Baltimore, so much of it has come from innovation and change. 'We're the Baltimore Orioles, we're not a large-market team, and we're in the American League East. We have to do everything right, and it would be foolish not to explore every avenue of improvement.' This advertisement has not loaded yet, but your article continues below. As part of that need to stay ahead of the competition, Mejdal wanted to expand the Orioles' ability to track the biomechanics of their pitchers. Currently, every MLB ballpark and over 60 minor-league stadiums are equipped with Hawk-Eye technology, a series of cameras strategically located throughout a venue for precise 3-D imaging. Primarily used by officials in tennis, soccer, and other sports for review calls, it's increasingly used in baseball to help track the throwing motion of pitchers. This is important for two reasons. First, a successful pitcher is able to replicate the same throwing motion over and over again. Second, close analysis of a pitcher's biomechanics can help find likely causes of injuries. RECOMMENDED VIDEO But Hawk-Eye cameras are only accessible to the home team at MLB and triple-A ballparks. Any minor-league team at a lower level or a scout at a college or high school field doesn't have access to those analytics because the expensive infrastructure is almost always unavailable. This advertisement has not loaded yet, but your article continues below. That's where PitcherNet, a joint project between the Orioles, Bright and Waterloo professor John Zelek, comes in. 'The whole premise of the project was to replicate those capabilities from just using your smartphone by a scout sitting in the stands,' said Zelek, a systems design engineering professor at Waterloo and co-director of the university's Vision Image Processing lab. 'So rather than the scout reporting qualitatively, now you have quantitative data from the scout at a college-level game, or wherever.' Although similar products exist, the proprietary rights to PitcherNet will be owned by the Orioles and, once it's operational, they can explore using it in more ways. 'So much of this game is using your body to generate leverage, whether you're a pitcher to throw the ball or whether you're a hitter to swing the bat,' Hejdal said in a video call from his office at Oriole Park in Camden Yards. 'We had to start somewhere, and the pitching seemed the obvious starting point.' Columnists Toronto & GTA Toronto Blue Jays Columnists Toronto & GTA
Edmonton Journal
07-05-2025
- Sport
- Edmonton Journal
University of Waterloo, MLB team partner on pitcher biomechanics project
Article content PitcherNet takes the main camera feeds fans are used to seeing — either from behind the pitcher or behind the batter — and combines it with video footage shot on a smartphone by a scout or team official. Using AI, PitcherNet then extrapolates the pitcher's entire throwing motion, recreating the level of detail that the 12-camera Hawk-Eye system is capable of producing. 'What we do is we try to extract 2-D information, 2-D joint position information, and then extrapolate using 3-D avatars,' said Waterloo PhD student Jerrin Bright. 'The 3-D avatars are like blobs encompassing a human itself and we use those blobs to basically find the 3-D human pose, which can be represented with the shape of the person, so that's the idea behind it.' Sig Mejdal, the Orioles' assistant general manager, said that in his experience it's a necessity to evolve, even in a sport as old as baseball.
Winnipeg Free Press
06-05-2025
- Sport
- Winnipeg Free Press
University of Waterloo, Orioles partner on AI project to track pitcher biomechanics
Staying competitive in the American League East means staying on the cutting edge of technology. That's why the Baltimore Orioles have partnered with researchers at the University of Waterloo to develop artificial intelligence technology, called PitcherNet, that will help the Major League Baseball team track the biomechanics of pitchers at every level of the organization, from the collegiate ranks and through its minor-league system. PitcherNet takes the main camera feeds fans are used to seeing — either from behind the pitcher or behind the batter — and combines it with video footage shot on a smartphone by a scout or team official. Using AI, PitcherNet then extrapolates the pitcher's entire throwing motion, recreating the level of detail that the 12-camera Hawk-Eye system is capable of producing. University of Waterloo researchers John Zelek, right, and Jerrin Bright pose for an undated handout photo in front of an onscreen example of the software they engineered to analyze baseball pitchers. To help train AI algorithms at the heart of the technology, researchers created three-dimensional avatars of pitchers so their movements could be viewed from numerous vantage points. THE CANADIAN PRESS/HO-University of Waterloo, *MANDATORY CREDIT* 'What we do is we try to extract 2D information, 2D joint position information, and then extrapolate using 3D avatars,' said Waterloo PhD student Jerrin Bright. 'The 3D avatars are like blobs encompassing a human itself and we use those blobs to basically find the 3D human pose, which can be represented with the shape of the person, so that's the idea behind it.' Sig Mejdal, the Orioles assistant general manager, said that in his experience it's a necessity to evolve, even in a sport as old as baseball. 'It's mandatory. It's completely mandatory,' said Mejdal, who worked for NASA and Lockheed Martin's satellite operations unit at Onizuka Air Force Station in Sunnyvale, Calif., before moving to the St. Louis Cardinals and then the Houston Astros. 'The success that I've been a part of in St Louis, Houston and Baltimore, so much of it has come from innovation and change. 'We're the Baltimore Orioles, we're not a large market team, and we're in the American League East. We have to do everything right, and it would be foolish not to explore every avenue of improvement.' As part of that need to stay ahead of the competition, Mejdal wanted to expand the Orioles' ability to track the biomechanics of their pitchers. Currently, every MLB ballpark and over 60 minor-league stadiums are equipped with Hawk-Eye technology, a series of cameras strategically located throughout a venue for precise 3D imaging. Primarily used by officials in tennis, soccer, and other sports for review calls, it's increasingly used in baseball to help track the throwing motion of pitchers. This is important for two reasons. First, a successful pitcher is able to replicate the same throwing motion over and over again. Second, close analysis of a pitcher's biomechanics can help find likely causes of injuries. But Hawk-Eye cameras are only accessible to the home team at MLB and triple-A level ballparks. Any minor-league team at a lower level or a scout at a college or high school field doesn't have access to those analytics because the expensive infrastructure is almost always unavailable. Winnipeg Free Press | Newsletter Winnipeg Jets Game Days On Winnipeg Jets game days, hockey writers Mike McIntyre and Ken Wiebe send news, notes and quotes from the morning skate, as well as injury updates and lineup decisions. Arrives a few hours prior to puck drop. Sign up for The Warm-Up That's where PitcherNet, a joint project between the Orioles and Bright and Waterloo professor John Zelek, comes in. 'The whole premise of the project was to replicate those capabilities from just using your smartphone by a scout sitting in the stands,' said Zelek a systems design engineering professor at Waterloo and co-director of the university's Vision Image Processing lab. 'So rather than the scout reporting qualitatively, now you have quantitative data from the scout at a college-level game, or wherever.' Although similar products exist, the proprietary rights to PitcherNet will be owned by the Orioles and, once it's operational, they can explore using it in more ways. 'So much of this game is using your body to generate leverage, whether you're a pitcher to throw the ball or whether you're a hitter to swing the bat,' Hejdal said in a video call from his office at Oriole Park in Camden Yards. 'We had to start somewhere, and the pitching seemed the obvious starting point.' This report by The Canadian Press was first published May 6, 2025.
CBC
03-05-2025
- Sport
- CBC
The Baltimore Orioles wanted to pitch better, so they asked the University of Waterloo for help
How local researchers are using AI to help the Baltimore Orioles play better 34 minutes ago Duration 1:41 Baseball teams are always looking for ways to perfect a pitcher's throw, but sometimes it can be difficult to access the feedback needed to improve. At home games, teams use high-resolution cameras to analyze their players' movements. But when they're playing away games, they don't have that same why the Baltimore Orioles decided to ask researchers at the University of Waterloo to find a way to accurately analyze lower quality footage from a cellphone or a TV broadcast. Jerrin Bright found a solution with his project called PitcherNet. He spoke to CBC's Aastha Shetty about his AI innovation. Sports teams are always looking for tweaks they can make to help athletes perform better and a new artificial intelligence system being developed at the University of Waterloo is focusing on baseball pitchers. The project, called PitcherNet, started in 2022 and is a collaboration between the university and the Baltimore Orioles. It looks to use artificial intelligence to analyze how a pitcher throws a ball. Many Major League Baseball stadiums are equipped with high-resolution camera systems from a company called Hawk-Eye Innovations, which allows the home teams to capture and analyze the movements of their players. The system has up to 12 high-speed cameras placed around the field. But when teams are playing away games, or if teams want to analyze the movements of players in the minor league system, they don't have access to the same technology. "They came to us and the project was basically to find a way in which we can mimic the Hawk-Eye tracking system with just one camera, or maybe you can just use the broadcast feed," Jerrin Bright, a PhD student who is part of the research project, told CBC K-W's The Morning Edition host Craig Norris. "They wanted to go into quantitative metrics, like trying to find the release point, the extension. But the problem is when you go into a minor league or an amateur league, the scouts wouldn't be having access to this Hawk-Eye system, which means that they will have to go with qualitative analysis. And this is where our system comes into play." Bright says the AI system developed at the university uses a video, from a broadcast feed or someone's cellphone, and figures out the pitcher's skeleton by using 3D human modelling. It then pinpoints 18 joints on the body. "Once we get these 18 joint positions, we do quantitative analysis using machine learning models. And with that, we'll be able to extract different pitch metrics," Bright said. To train the AI algorithm, the researchers create 3D avatars of pitchers to track their movements and view them from different vantage points. The system goes over pitch type — whether it was a fastball, slider, curveball or other type of pitch — the release point, velocity, release extension and handedness, which means they can isolate the pitcher's throwing hand to analyze how the ball is held. "These pitch metrics could ultimately be used to do a lot of performance indications, look into the longevity of the players and look into ways in which they can optimize their pitching action," Bright said. Scouts could use cellphone video CBC News reached out to the Baltimore Orioles for comment on PitcherNet but did not receive a response. The team is partially funding the research. Sig Mejdal, the team's assistant general manager, told the Baltimore Sun newspaper that the system is "still a work in progress, but there have been cases already where it's been useful to use." Mejdal told the newspaper biomechanics is "relatively new" in the baseball world, but "there has to be many things we could uncover that right now remain out of reach." John Zelek, a professor of systems design engineering and co-director of the Vision and Image Processing Lab at the University of Waterloo, says what they've designed is a simple system compared to Hawk-Eye, but it's effective. Zelek said the system could be used in a variety of different ways, including by scouts who are looking at potential players to sign. They could take videos while sitting in the stands watching a ball game and the video could be sent through the PitcherNet system to analyze an up-and-coming player's performance. On-site work this summer Bright admits he's more of a cricket fan and "a numbers guy" but he "got into baseball after joining this project and it has been very interesting." He said Waterloo researchers meet with team representatives about once a month to talk about progress and how the system can be improved so the team gets the metrics they need. Bright says there are other applications for the software, and they're looking into how it could help hockey teams, too. He'll be going to Baltimore this summer to work on the system in the Orioles' stadium and further develop it. "I think the potential that AI systems like PitcherNet can have on a real game, that is very fascinating and I look forward to what I can contribute in this aspect," Bright said.
