MLSE

AWS + MLSE Building Extraordinary Sports Moments and Enhanced Fan Engagement

They are working together to transform experiences for fans of Toronto’s premier hockey, basketball, soccer, and football teams, and aid scouting and coaching decisions.

  • This post is authored by Devin Pleuler, Senior Director of R&D at MLSE, and Ari Entin, Principal of AWS sports marketing communications. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.

    Introduction

    In the high-stakes realm of the National Basketball Association (NBA), every team is on a relentless pursuit of excellence. For the Toronto Raptors, a crucial element of this quest is underpinned by data-driven insights that form the bedrock of strategic decision-making. One fundamental part of this puzzle involves maintaining and regularly updating player performance models throughout the season. With fresh players being introduced into the league, and current ones continually evolving, these models must be kept up-to-date and accurate.

    Keith Boyarsky, VP, Basketball Strategy and Research at the Raptors, puts it succinctly, "Our player performance models are key to the decision-making process across various aspects of team operations - from scouting to coaching, and health management. It is imperative that these models are accurate and current to reflect the evolving dynamics of the league."

    From On-Premises to the Cloud

    A few years ago, the Toronto Raptors started utilizing an on-premises GPU for this crucial retraining process. This choice was primarily influenced by factors such as model size, security, and the volume of inbound content for retraining. However, the computational demands of the deep learning models quickly outpaced the capacity of the on-premises resources, resulting in retraining times that could span several days. As a result, the heaviest models could only be retrained on a weekly or monthly basis, leading to potential periods of stale models, especially when new players entered the league.

    These deep learning models produce statistical player representations that are fed downstream into various other models that are used across the Toronto Raptors organization. The more data available on a player, the more accurate that player representation will be. Therefore, in low-sample size situations, it is critical to regularly retrain these models so their outputs accurately represent current player behavior and tendencies.

    Boyarsky recalls, "We had to find a solution that would enable us to retrain our models more frequently and efficiently, to keep up with the rapid inflow of new data in an NBA season, as well accelerate our ability to iterate on the model architectures themselves.

    Model Retraining - An Imperative for Accurate Insights

    Retraining multiple ML models is no small task. This could mean training on entirely new data, adding more recent data to the existing data set, or updating certain components of the model, such as feature weights or parameters. 

    To provide a sense of the size and scale of the data involved, the Raptors leverage roughly 10-years of full player tracking data, and each season has 1,230 games. Each of these games represent about 100-200 MBs worth of data in their raw form and can grow exponentially when additional metadata is calculated and layered on top. In practice, this means the models process 1-2 terabytes of data during the training process.

    However, constantly retraining the models is essential to address variables like model drift and ensure player performance models stay relevant, reflect the latest performance levels, adapt to strategic or style changes across the NBA, and This concept of model drift is a phenomenon where the predictive performance of a model decreases over time because the underlying relationships between inputs and outputs, originally captured during model training, change or 'drift' away from their original state. This is particularly pertinent in a dynamic landscape like professional basketball where player conditions, team strategies, and rules are in a state of flux.

    Unleashing New Possibilities with AWS

    That is where Amazon Web Services (AWS) came in. By harnessing the power of AWS, the Toronto Raptors have revolutionized their ML model retraining process. AWS's robust suite of services allows us to retrain models with unprecedented speed and efficiency, delivering accurate insights promptly to coaching and scouting departments, as well as the player health management team. This scalability will be even more critical in the upcoming season and beyond as the Raptors will start to incorporate full body pose tracking data – which represents 4 GB of data per game - into their player performance models."Our migration to AWS marked a major turning point in our data analytics journey. The enhanced speed and efficiency brought about by AWS's suite of services allowed us to deliver data-driven insights faster and more accurately," remarks Boyarsky. "This has empowered our team to make swift, informed decisions that are crucial in the fast-paced NBA environment."

    The shift to AWS began with a strategic migration to Amazon SageMaker, an industry-leading platform for machine learning that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly. Amazon EC2 instances, optimized for GPU-intensive workloads, further expedited model retraining.

    Conclusion

    The Toronto Raptors journey with AWS has not only transformed the way they utilize data, but it has also created an environment conducive to rapid, data-driven decision-making. By transitioning from on-premises GPU to AWS, they’ve not only streamlined operations but also significantly increased their capacity for agility and precision in decision-making. AWS's scalable and adaptable solutions have equipped them with the tools to keep pace with the ever-changing landscape of the NBA.

    Boyarsky concludes, "Our partnership with AWS has been a transformative journey. And we believe this is just the beginning. The future of basketball is data-driven, and we're excited to be at the forefront of this revolution, thanks to AWS.

  • MLSE DIGITAL LABS AND AWS ANNOUNCE SPORTSX - A NEW R&D PROGRAM TO ADVANCE INNOVATION IN SPORTS

    SEATTLE – January 24, 2023

    MLSE Digital Labs and Amazon Web Services (AWS) unveiled today a new research and development program called SportsX, focused on creating new, innovative digital solutions that achieve technological advancement in sports to enhance team performance and the fan experience.   

    “We’re thrilled to announce SportsX, a new incubator in collaboration with AWS rooted in research, applied sciences and product development,” said Humza Teherany, Chief Technology & Digital Officer at MLSE. “The program is an extension of our ongoing work with AWS and combines the expertise from both of our organizations with ideas shared by our passionate fans, to create a powerhouse in sports innovation.” 

    SportsX aims to push the boundaries of what’s possible in sports by exploring and innovating in three focus areas: 1. Creating extraordinary fan experiences, 2. Giving teams a winning edge and 3. Creating positive social and environmental impact. SportsX believes in the power of collective efforts, and that great ideas start with those who share our passion of sport, both professionally or as a fan. 

    The program is designed with a bottom-up approach to capture, analyze, and build out the best ideas from key stakeholders, which include coaches, fans, partners, and employees. Chosen ideas will be evaluated for viability, developed, and tested in the MLSE environment with the goal of creating solutions that can benefit the sports industry at large. A dedicated SportsX web portal accompanies the launch where interested stakeholders can join the collective and receive updates regarding idea submission openings. 

    “Just as AWS is democratizing technology by giving businesses of all sizes access to the same cloud and AI solutions, SportsX aims to level the playing field in sports innovation,” said Eric Gales, country manager AWS Canada. “MLSE and AWS will give anyone, from organizations to superfans, the opportunity to take their amazing idea and transform the sport they love.” 

    The launch follows a successful pilot that generated industry-leading ideas under the R&D program. One of the first concepts in flight includes the NHL Extended Reality Stats Overlay; an augmented and immersive NHL game viewing experience through extended reality that brings broadcast and video game capabilities to those watching in-person. Another standout concept includes the Immersive Basketball Experience that uses optical data to give the user a life-sized augmented reality experience as if they are viewing a game as a player or sitting courtside. 

    “MLSE’s partnership with AWS was built on the vision of disrupting the sports and entertainment industry and enhancing the fan experience through technology innovations,” said Jordan Vader, Senior Vice President, Global Partnerships at MLSE. “We are proud to deliver on that promise with SportsX and work with AWS to bring to life a pipeline of extraordinary ideas.” 

    SportsX builds on the recent announcement that MLSE and AWS are innovating together to transform the sports experience for its teams and Canadian sports fans. AWS is MLSE’s official cloud provider and the official provider of artificial intelligence (AI), machine learning (ML) and deep learning cloud services. Using AWS’s comprehensive portfolio of cloud services, MLSE is building solutions that will support its teams in creating and delivering extraordinary moments for their sports fans. 

    The program is being launched in phases, starting with the SportsX website where interested stakeholders can join the collective and sign up for updates. Details on the submission portal will be released at a later date. 

    For more information about SportsX and to join the collective, visit sportsx.io.

     

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    About Maple Leaf Sports & Entertainment

    Maple Leaf Sports & Entertainment (MLSE), one of the world's premier sports and entertainment companies, owns the Toronto Maple Leafs (NHL), Toronto Raptors (NBA), Toronto FC (MLS), Toronto Argonauts (CFL), Toronto Marlies (AHL), Raptors 905 (NBA G League), TFC II (USL) and Raptors Uprising Gaming Club, the Toronto Raptors esports franchise in the NBA 2K League. Its charitable arm, MLSE Foundation, focuses on funding initiatives to support youth through sport and recreational programs. In 2017 MLSE Foundation, with support of community and corporate partners, built MLSE LaunchPad, a 42,000-sq. ft. space dedicated to programming that support its four Pillars: Healthy Body, Healthy Mind, Ready For School and Ready For Work. MLSE also owns and operates Scotiabank Arena, Canada’s premier sports and entertainment venue hosting more than 200 events each year, two digital channels - Leafs Nation Network and NBA TV Canada and has a partnership with Live Nation - the largest concert promoter in the world. MLSE has also invested in and operates five of Toronto's sports facilities – Coca-Cola Coliseum, BMO Field, BMO Training Grounds at Downsview Park, home of Toronto FC's Academy and the First Team's practice facility, OVO Athletic Centre, the practice facility for the Toronto Raptors, and Ford Performance Centre for Hockey Excellence, the practice facility for the Maple Leafs and Marlies.

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