Making a pitch to change the game: Waterloo tech to analyze baseball pitcher’s performance with smartphone

CTV's Spencer Turcotte brings us the story of new Waterloo tech that could change the way MLB scouts keep an eye on the competition.

One of the greatest sounds in baseball is the sound of a bat connecting with a powerful pitch.

It’s great for the hitter, but not so much for the pitcher. Major league teams dedicate a lot of resources analyzing how to prevent hits.

A team of researchers at the University of Waterloo has been asked to help with that.

“The [Baltimore] Orioles actually approached us. They explained the problem in this particular way that they do the analytics. Most baseball stadiums are equipped with this Hawk-Eye system, which has a dozen cameras so they can get the skeleton of a pitcher so they could do the biomechanical analysis,” said John Zelek, a professor of systems design engineering at the University of Waterloo.

The problem is these systems are expensive, and the data is often only available to the home team. That’s not all.

“When they go to the college level or minor league level they don’t have access to that infrastructure,” said Zelek.

That creates challenges when scouting players. Without those analytics, teams mostly eyeball it, which is a big gamble for teams looking to invest in players.

“They want to know if how the pitcher is throwing, that they’re susceptible to injury within a couple of years and then that’s it for their career,” said Zelek.

That’s where the University of Waterloo researchers come in. Through artificial intelligence and a system they’ve developed called PitcherNet, scouting can be done from any baseball diamond, and anywhere in the stands, using a smartphone.

“We have various AI algorithms that dissect that motion sequence to get where all the limbs are,” Zelek said.

The same analysis can be done using video from a game feed.

While this tech is specifically for the Orioles at this point, down the line it could help minor league baseball teams gather analytics too.

It’s an exciting idea for PhD student Jerrin Bright, who has had a big hand in this project.

“Getting to work in the intersection of AI and sports, that’s very, very interesting,” said Bright.

The system is still under development and they’re working to analyze other positions.

But so far, these researchers seem to be knocking it out of the park.