Written by Rick Matthews
On April 14, I attended a panel discussion involving the impact of analytics in baseball and the next steps that the sport will be taking in this space. The panel consisted of the VP of MLB Baseball Data Greg Cain, Director of AI and Strategy at DataRobot Ari Kaplan, and Chief Product Officer of Baseball Cloud Ryan Reinsel. Even though we only had an hour, we were able to cover a lot of interesting topics about the untapped areas of data analysis in the sport. Here are some of the key topics that stuck with me after the panel concluded.
- Personal Biomechanical Data is the Future of Analytics
As they discussed where the future of baseball analytics was going, they all seemed to agree that it is heading towards the direction of catering to specific player performance. Teams know and understand how to use analytics in a front office or GM position, teams have their own analytics departments to increase sales, and managers are deploying shifts and not letting starting pitchers pitch to hitters a third time, so they are being used in-game as well. But how can analysts teach pitchers how to throw the ball more consistently and reduce outings when their changeup “wasn’t working tonight.” This new trend of tracking physical attributes is best known today as biomechanical data, which include things such as tracking of how much pressure or strain you put on your muscles throughout a game, how one grips the ball, and what arm angles players use when they throw. The market, while starting to make some noise, is largely untapped and has potential to improve consistency and reduce injury.
- Analytics is Great, But How Do We Educate?
To go along with this, another hot topic in the baseball analytic world is not data collection, but rather data education. How does a Senior Data Analyst from Cornell effectively communicate to a 19 year old Cuban baseball player whose first language is not English? Every athlete is different and it can be hard providing a blanket solution to players with all sorts of backgrounds. Everybody absorbs information differently too; some are visual learners, some are verbal learners, and some may be auditory learners. What good is data if it cannot be properly communicated? This is another issue of chief importance for baseball teams going forward.
- The Need For Long-Term Data Tracking
Finally, importance is being placed on long-term tracking data for athletes. Being able to track data from a 15 year old high schooler to a 37 year old MLB veteran could be increasingly valuable as athletes could get a sense of how their approach has changed over the years as well as the team knowing what signs to look for in an inclining or declining player from a front office standpoint. If long term data collection could also be mixed with biomechanical data, then there is hope that sustainability and durability of athletes increase in the long term as we learn to better understand their bodies.
While there were a myriad of other topics discussed throughout the panel, these were the ones that caught my eye and the ones that seemed the most important when we begin to talk about where baseball analytics goes from here. It is a very exciting time to be an analyst in baseball and with the sport being an industry leader, and it is always fascinating to see where some of their best minds are at!