Achieving breakthroughs in baseball data with analytics and AI

The world of baseball has changed dramatically since the Oakland A’s first used sabermetric methods to evaluate players (popularized by the 2011 film Moneyball). With the right data, MLB teams can now get a distinct competitive edge by better understanding player performance, improving coaching strategies, and enriching fan experience. Discover how the Texas Rangers have fully embraced a data-driven approach by adopting Labelbox and Databricks in order to deliver breakthroughs and uncover deeper insights.

In this webinar, we’ll be covering:

- Best practices on how to create better data availability to catalyze innovation. This can be achieved by using Databricks and Labelbox to curate all your unstructured data, automate finding business insights, and accelerate data quality and data labeling for powering AI-applications.

- How new use cases that tap into generative AI and LLMs for things like text summarization can feed into baseball report insights and business intelligence reports that allow the Texas Rangers to make faster and more accurate decisions.

- How improved collaboration across the data science and machine learning teams at the Texas Rangers is helping productionize ML and AI products faster.

Watch on-demand

ALEXANDER BOOTH

Assistant Director of R&D - Texas Rangers Baseball Club

Featured Speakers:

Achieving breakthroughs in baseball data with analytics and AI

NITIN WAGH

Head of Product Growth, Machine Learning - Databricks

Trusted by leading Fortune 500 enterprises and AI-fueled companies

Trusted by leading startups and Fortune 500 enterprises

MARK GHANNAM

Head of Solutions Engineering - Labelbox