During the course of a Major League Baseball game, there will inevitably be a moment when a fielder examines the inside of his cap.

He’s not wondering about the fit, rather he’s checking a sophisticated data report prepared by the team’s analytics staff.

“If you actually watch a broadcast, you may see a player take off his hat, check the inside of his hat, or the catcher trying to check his wrists or armbands,” said Alexander Booth (pictured), assistant director of R&D at Texas Rangers Baseball Club. “Those are preloaded with reports that we’ve generated using our data and visualizations. Everything is data driven now, and baseball is no exception.”

Booth spoke with theCUBE industry analyst Rob Stretchay at the Databricks Data + AI Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the Rangers and Major League Baseball have embraced the data revolution.

Weather and motion tracking

Baseball at the professional level is awash in unstructured data, generated by cameras and sensors positioned throughout a ballpark. These systems capture wind, humidity and temperature information on every pitch and biomechanical data on how players on the field are moving.

“We have pose tracking data coming from markerless motion capture systems that track the movements of the body for all the players,” Booth said. “Over the last couple of years, there’s been an explosion of new big data sources in baseball. These large unstructured data sources off the biomechanical data, off the wind data that has to be transformed into actionable insight.”

To handle this influx of data and channel it into results that will lead to on-field success, the Texas Rangers have turned to Databricks.

“We utilize Delta Live Tables and Unity Catalog for all of our governance,” Booth said. “We’ve sped up a lot of our workloads with Photon, and we’re pretty heavy users of Auto Loader too.”

One of the tools being closely examined by major league baseball is artificial intelligence, according to Booth. Recent reports have documented how major league scouts are already using AI to identify player potential.

“I know that they’re definitely interested in the product and trying to keep all the teams on an equal playing field,” Booth said. “Being cutting edge with AI, adopting these new machine learning models, exploring use cases for LLMs, being at the lead of that will be a competitive advantage for us against these other teams.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Databricks Data + AI Summit:

Photo: SiliconANGLE