Working with the Amazon ML Solutions Lab (AWS's Machine Learning Professional Services program), the Seahawks are building new capabilities that will drive deeper analysis and insights into video footage. By applying AWS ML services to practice, regular season, and playoff video footage – including NFL Coaches Film that gives coaches, scouts, and game officials a bird's-eye view of all 22 players on the field – the Seahawks are creating a cloud-based video analytics platform. The system will use Amazon Rekognition, a deep learning image and video analysis service, to identify and track players, and give the organization a better understanding of their opponents' defensive and offensive strategies. Using Amazon SageMaker, a fully managed service to build, train, and deploy ML models, the Seahawks can analyze the number of hurries, knockdowns, and sacks, to predict how specific quarterbacks will perform under pressure, as well as which defensive players will exert pressure based on the depth of throws and distance gained by a receiver after catching a pass. These new capabilities will deliver recommendations to the Seahawks coaches in preparation for practice and games to help them make better data-driven decisions.

In addition to moving the vast majority of its infrastructure to AWS, the National Football League (NFL) team will use the breadth and depth of AWS's services, including compute, storage, database, analytics, and ML to drive deep analysis of game footage to inform game strategy, improve operational efficiencies, and accelerate decision-making to advance team performance game-to-game. The Seahawks will combine the weekly NFL Next Gen Stats player tracking data, which tracks the position of the ball and every player 10 times per second, with its own player and club data to develop custom analytics and proprietary statistics. The Seattle Seahawks are relying on AWS's unmatched portfolio of services to discover actionable outcomes from its vast amount of player, team, and business data, enabling them to continue to compete at a championship caliber level. The Seahawks are building a data lake on Amazon Simple Storage Service (Amazon S3) that will combine team stats and NFL data, such as Next Gen Stats player tracking, player health and wellness data, and scouting information to provide deeper visibility into player capabilities, as well as give the coaching staff a single, real-time view of player and team performance. By applying AWS analytics services to the data, the Seahawks will be able to quickly uncover insights to better evaluate talent and develop game plans that take advantage of the team's strengths.

In addition to moving the vast majority of its infrastructure to AWS, the National Football League (NFL) team will use the breadth and depth of AWS's services, including compute, storage, database, analytics, and ML to drive deep analysis of game footage to inform game strategy, improve operational efficiencies, and accelerate decision-making to advance team performance game-to-game. The Seahawks will combine the weekly NFL Next Gen Stats player tracking data, which tracks the position of the ball and every player 10 times per second, with its own player and club data to develop custom analytics and proprietary statistics. The Seattle Seahawks are relying on AWS's unmatched portfolio of services to discover actionable outcomes from its vast amount of player, team, and business data, enabling them to continue to compete at a championship caliber level. The Seahawks are building a data lake on Amazon Simple Storage Service (Amazon S3) that will combine team stats and NFL data, such as Next Gen Stats player tracking, player health and wellness data, and scouting information to provide deeper visibility into player capabilities, as well as give the coaching staff a single, real-time view of player and team performance. By applying AWS analytics services to the data, the Seahawks will be able to quickly uncover insights to better evaluate talent and develop game plans that take advantage of the team's strengths.