There is an incredible wealth of available data in sports, but capturing and making use of that data in a way that will lead to better outcomes for the team remains a major problem. Factor in long data science time horizons that make it difficult to implement predictive solutions in the space of a season and prohibitive provisioning costs for data science teams, and it’s easy to see why many sports organizations find traditional data science methods to be out of their league.
Enter DataRobot’s automated machine learning platform. This overview will detail exactly how sports organizations are already using this technology to make better decisions, including specific use cases and the challenges most sports organizations face when implementing machine learning initiatives.
This overview will cover:
- Specific use cases and tangible benefits of predictive analytics
- The unique challenges of implementing machine learning in sports
- Why automation is the solution