Recently, SportsX, MLSE Digital Labs, and Amazon Web Services (AWS) held their Technology Showcase at Scotiabank Arena in Toronto. While on the Toronto Raptors’ turf, I had a chance to take a look at the new cloud-based technology innovations from the companies, including the ‘Shooting Lab’.
Over the course of an afternoon, I was able to get a sense of what the Shooting Lab was and how it’ll impact training and coaching. From a very top level, the Shooting Lab was developed by MLSE and AWS in conjunction to provide biomechanical data of players to highlight mechanics and efficiency. By analyzing this data, coaches and players can receive feedback on their performance, their movement, and other novel pieces of data. Utilizing AWS’ cloud and generative AI, the Shooting Lab can then render personalized feedback in near real time.
During the Technology Showcase, I was able to try out the Shooting Lab myself and see how impactful and accurate this innovation may be, even for someone who hasn’t shot a basketball in a handful of years.
Stepping onto the Raptors’ court is a surreal experience to begin with. But once I took my first steps onto the shiny hardwood, I began to see the intricate setup needed to utilize the Shooting Lab. A series of GoPro cameras was mounted on tripods, all pointed towards the free-throw line. These were used to read and record the biomechanical data from me and the other attending journalists as we independently walked up to take three to five shots.
Thanks to AWS, biomechanical data is then analyzed in real time throughout the process. Amazon SageMaker is able to register data such as elbow velocity, release angle, stance width, and trajectory. Over the course of the three to five shots I took, the AI was able to provide personalized feedback on my performance. All of this is then averaged out.
To contextualize some of the data taken from my session, I was shown to have a 125-degree release angle. It was also determined that I have a 7.6-foot release height. I was also shown to have a poorer level of consistency, averaging a 68 percent score. As part of the demonstration, MLSE and AWS provided personalized ‘Player Similarities Scores’. This helped actualize my data and matched it with a player from the Toronto Raptors and their style. Lo and behold, it turns out that I have a 78 percent shot similarity with Jonathan Mogbo. While this aspect of the Shooting Lab isn’t applied to the actual players on the team, it does go to show the level of detail in rendering useful feedback.
We’re able to pull the biomech data, and have basically an infrastructure where we can look at it, analyze it, show it to coaches, show it to players, figure out what it’s telling us, and take the insights away from it, and then make that available to coaches and general managers, who then will decide, what do we do with this?,” Humza Teherany, Chief Strategy and Innovation Officer at MLSE, explains. “I think that experimentation is so important. Those partnerships helped us to go much faster in terms of experimentation, and ultimately, from a player performance perspective, keeping our guys healthy and sharp in terms of performance enhancement. Whether it’s a slap shot, you’re trying to get a goal, or you’re shooting a three-pointer, the ability to drive performance and consistency on those is generally what coaches do.”
Now you have this overarching data layer where you can bring such an amount of precision to it.. The total value in all of that is how we use it. What do the coaches see? What do we see? And how are we going to use it to drive performance? I think that’s the continuum of all the things that happen. The last part is the most important thing. The first part has to be done. It has to be done in probably many iterations to figure out what you want to focus on.”
The implementation of the Shooting Lab is a part of AWS’ ongoing partnership not only with MLSE but with the NBA. Earlier this year, the two announced a multi-year partnership to bring cloud-based stats and innovations to the game and fans. This includes providing AI-powered stats to fans to provide more information about the game and the players on the court.
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