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.
By harnessing the power of AWS, the Toronto Raptors have revolutionized their ML model retraining process. AWS’s robust suite of services allows them 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.
By transitioning 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.
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