BASE 1001: Introduction to Baseball — TrackMan
The Beginner’s Guide to Baseball, From Someone Who Never Played
I never played baseball. I never played softball. I was a classically trained ballet dancer. Yep, pointe shoes and tutus, not long socks and cleats that brought me to Iowa Baseball. Long before I was analyzing spin axis, I was “spotting” turns on stage. I didn’t run bases; I ran between the wings backstage. Counting the music beats is how I was trained to “work the count.” But all the while I was going through classical ballet training, I was also growing up with a brother, dad, and grandpa who adored the game of baseball. Our dinner vernacular often involved baseball. We talked about current players, planned trips to minor league and professional baseball games, and discussed strategy for “MLB the Show” on “PlayStation.” As a math major, I’ll admit it, I love math. I’m a math nerd. The more I learned about baseball, the more I saw how numbers permeate the game. It’s not a stretch to say the math nerd also loves to read. I do. I soon found myself getting my hands on all kinds of baseball books, from the history of the game to past and present players’ statistics. Then came the treasure trove of podcasts and YouTube videos. Soon, I was able to converse with my baseball loving family and discover that I love a sport I’ve never played.
But as a data analyst for the Iowa Baseball Managers staff, I have learned more than I ever could’ve imagined. During my onboarding process last semester, I began understanding the details of the crucial technologies enabling our analysts to do their job. Part of what we believe as managers is in order to Move the Needle, we need to share our research and findings so anyone can learn and benefit, not just our own players and managers. As a staff, our goal is to help Iowa Baseball win games on the field, but also benefit the baseball industry as a whole. So, to those wanting to learn about being an analyst, I offer some insight into how we retrieve and process data to assist our players and coaches. I’ll start with our most important technology…TrackMan.
TrackMan is a doppler radar ball flight tracking system. It was first popular in the golf world, so much so that Minnesota Twins All-Star third baseman, Josh Donaldson, had a unit installed in his house. But, TrackMan did develop a unit unique to baseball. At Iowa, our unit is attached to the top of the press box because it needs to have enough distance to accurately track baseballs. The tracking begins when the ball is released from the pitcher’s hand and ends shortly after the ball leaves the bat or is caught by the catcher.
TrackMan is a valuable resource for any data analyst because there are so many metrics that are tracked. Plus, TrackMan conveniently outputs its data into a CSV file accessible through a spreadsheet program such as Microsoft Excel or easily imported into a database. These CSV files are then what we access and manipulate with custom computer programs, written in various programming languages such as R, to begin diving into the data. The data is easy to navigate, as one row, called an observation, is one pitch. The different column names each show a data point collected from the specific pitch. Every data point you could possibly think of is included in this CSV file. There are seventy-five different data points, but here are just a few examples of data points we use frequently.
The first data point we use is TaggedPitchType. This is the pitch type labeled by the tagger. TrackMan has the capability to tag the pitch type on its own, but we utilize TaggedPitchType to ensure 100% accuracy. TaggedPitchType also directly corresponds to a list of colors we use when creating visualizations in R. We utilize InducedVerticalBreak and HorzBreak to create pitch movement plots with that corresponding list as well.
Horizontal Break (HorzBreak) is the distance, measured in inches, from where the pitch crosses the front of home plate horizontally to where it would have crossed home plate horizontally if the pitch was released with no spin. From the perspective of the pitcher, a positive break is toward the right-handed batter’s box, and a negative break is toward the left-handed batter’s box. There are two metrics for vertical break, however. The one we use is InducedVerticalBreak. The only difference between InducedVerticalBreak and VerticalBreak is that InducedVerticalBreak accounts for gravity, while VerticalBreak does not. But gravity or not, a vertical break is the distance, measured in inches, between where the pitch crosses the front of home plate vertically to where it would have crossed home plate vertically if the pitch was released with no spin. From the pitcher’s perspective, breaking down is a negative value and a positive value does not drop as much as a result of resisting the effects of gravity.
These two data points create a pitch movement plot. We find these plots useful when analyzing any pitcher’s arsenal because they describe how their pitches move. When a pitcher has a lot of positive vertical break, that pitch will not drop as much, or have “ride.” But if a right handed pitcher has a lot of negative horizontal break, they will have more sidespin, and less “run.” These plots are useful in conjunction with watching videos as we can see how the pitches move both according to data and to the eye.
As for the hitting side, we analyze PlayResult like we do with TaggedPitchType with another corresponding color list. The PlayResult data point tells you if the pitch led to something. TrackMan includes the following nine options: Single, Double, Triple, Homerun, Reached on Error, Fielder’s Choice (No Out Recorded), Out, Sacrifice, Undefined (ball was not put in play).
We work with PlayResult when making hitting spray charts and exclude Undefined, Sacrifice, Fielder’s Choice, and Reached on Error. We do keep outs, however, because they can signify if the out was a weakly hit single or the result of a great defensive outfielder. These plots, in my opinion, are similar to pitch movement plots because you can learn about a hitter with only one graphic. Once you know the hitter’s handedness, you can then begin understanding their hit location happy areas. Does the hitter like to pull the ball? How often do they hit balls to the opposite field? These are all things that spray charts are good at showcasing.
The last metric to look at for hitters is HitSpinRate. We apply spin rate for pitchers as well, but HitSpinRate is a unique metric to find. HitSpinRate measures the revolutions per minute (RPMs) of a baseball as it leaves the bat following contact. Based on a particular swing, spin may be added or subtracted from the ball. Adding spin typically comes from hitting the lower portion of the ball. This results in just enough energy for the ball to carry a bit farther. But, too much spin could result in a pop fly. As for subtracting spin, energy is being taken away from the ball, as the ball is being hit on the upper half. Subtracting too much spin can result in a weak ground ball. Generally, with HitSpinRate, adding or subtracting too much spin energy is damaging. According to the Rapsodo hitting certification class, the optimal range is between 1500 and 2000 RPMs.
This is just a brief introduction into some of the various data points TrackMan provides its users. TrackMan CSV files and programming in R play a big role in how Iowa Baseball Managers Move the Needle and help the Hawkeyes compete on the field. What a humbling mantra for life; the more you think you know about something, the more you discover you are just scratching the surface. I love that Iowa Baseball believed in a ballet dancer to crunch numbers for them. At Iowa, and during this pandemic, I have had some excellent mentors show me the ropes and help me realize how cool it is to be a math nerd and productively blend that passion with a passion for baseball.
