Back in 2016, a mere 13% of MLB plate appearances involved a shifted defense. In 2020, that percentage has nearly tripled to 36%. Strategic defensive positioning has become widely accepted and increasingly prevalent in MLB. Since all MLB teams have an analytics department, most teams are likely leveraging internal analysis to develop a strategic defense against any opposing hitter in the MLB. On the other hand, many college teams aren’t as analytically advanced. Therefore, defensive shifting is not as widely accepted nor as prevalent compared to MLB.
ShiftR, BaseballCloud’s newest product in development, will address this issue by allowing a team to receive batted ball analysis and the most efficient defensive position for each fielder against any given college batter. The underlying model will output any batter’s batted ball profile and the optimal position for each of the seven fielders to maximize the probability of getting that batter out on a ball in play. With ShiftR, college teams will be able to run their opposition’s lineup through this Machine Learning model to generate a batted ball profile and a visual representation of the best shift against any batter.
ShiftR will also be available for the MLB organizations and will be showcased on BaseballCloud’s Twitter soon, so stay tuned! Feel free to DM @BaseballCloudUS for any questions or comments regarding ShiftR.