Following our class last week on data and analytics, I wanted to take a look at how analytics and other innovations are changing the game of baseball. Major League Baseball has always been data-driven, with statistics easier to record than other sports and longer seasons creating large datasets ripe for analysis. Data has become even more essential in decision-making by teams today, which coaches and players need to buy into. Most teams have full-time analytics departments who are trying to find variables that will lead to success which are undervalued by other teams, allowing them to pay less for more. Each team has its own top secret algorithms to measure the value of players, which can be used to find talent that fits their organizational approach and forecast player performance.
Some teams that rely on numbers the most include the Houston Astros, Pittsburgh Pirates, and Tampa Bay Rays. The Astros are the most analytics-driven team in baseball, with an analytics staff that includes Sig Mejdal, Director of Decision Sciences, who is an engineer and former rocket scientist at NASA, as well as a medical risk manager and mathematical modeler. They have a database called Ground Control, detailed in a Sports Illustrated cover story, that attempts to synthesize quantitative and qualitative information about a player. Quantitative data primarily consists of on-field performance of players. Qualitative information includes scouting reports, biological factors and family history, psychological tests, work ethic, personality, durability and health. They use this to see how past prospects with similar attributes to the current prospect turned out and arrive at a projection of the future value of that player. In the minor leagues, they assign grades to starting pitchers for each game, which total to a GPA at the end of the season. They also have spray charts for every situation for each batter and pitcher to help determine where to best position fielders. Their system is so unique that it was hacked by the St. Louis Cardinals this past summer.
Several teams have invested substantially in data-based injury prevention initiatives, including the Pittsburgh Pirates. The Pirates use wearable sensors and special player tracking technology installed in their stadium to measure energy levels and signs of fatigue. They found that resting players more often resulted in less injuries and better performance. They are also one of many teams who utilize pitch framing, which is the ability of a catcher to turn borderline calls into strikes, since data shows that the best catchers can save a team up to 50 runs in a season, equivalent to five additional wins. This could be one reason behind why strikeouts have increased across baseball.
The Rays try to find any advantage they can over the competition due to their financial constraints, which is detailed in The Extra 2% by Jonah Keri. Led by former Goldman Sachs executives, they used the same approach that worked for investments on Wall Street to gain an edge, particularly focusing on defensive shifts, where fielders change their positioning for every pitch, based on where data indicates the batter is likely to hit the ball. Teams such as the Kansas City Royals and Chicago Cubs use machine learning techniques and predictive modeling to inform their decisions. The New York Mets use models to determine the optimal lineup to maximize runs scored for each game. All of the teams detailed above have experienced recent success with 11 playoff appearances and 3 World Series appearances between them since 2010.
There are also tools available to every team including a sensor created by Zepp Labs that you attach to the end of a bat, which analyzes over one thousand data points for every swing including bat speed, hand speed, and time to impact. It is used by professional players such as Mike Trout, David Ortiz, and Giancarlo Stanton, but can be used by anyone to improve their skills and compare their swing to the pros. The sensor helps scouts get consistent data on players. It is used to evaluate players at all events put on by Perfect Game, the largest baseball scouting organization in the world. Additionally, technology including cameras and radar are installed in every Major League stadium, which capture real-time data supporting the PITCHf/x and Statcast systems.PITCHf/x provides detailed pitch by pitch data including speed, location, trajectory and movement, which is made available to public. It also measures biomechanical information on pitchers (location of foot, shoulder, elbow, and hand at release of pitch) and batters (location of hands, back, front feet, tip of bat at point of contact), which can be used to detect injuries. This can be especially useful for pitchers due to the rise in Tommy John surgeries. Statcast tracks the location and movement of the ball and every player on the field during the entire game. It is creating new ways to quantify player talent and performance. For example, it can be used to find out how hard the ball is hit off the bat, how fast a fielder got to the ball when making an amazing catch, or the speed of a baserunner when stealing a base.
The ubiquity of data and technology brings up a debate about whether it is better than relying on humans, including coaches, players, scouts and umpires. Presenting this data to coaches and players can be overwhelming and result in overthinking, so it is important to achieve a balance, where both numbers and human judgment are used to make decisions.