Analyzing In-Game Pitcher Performance Using Google Sheets
Look into any dugout during a baseball game and you will see coaches and players writing on all kinds of game charts, such as this one from the high school team I coached last year:
Logging information in game charts has long been a method used by coaches to evaluate various performance metrics and assist in making sound coaching decisions.
Typical insights from these charts range from something as simple as knowing a pitcher’s pitch count, to something more advanced like knowing a pitcher’s tendency based on any given count.
I’ve played on several teams that enforced elaborate game charts, and I’ve often wondered “What are coaches doing with all of this information?”.
In order to drive useful insights, additional calculations are usually required to make it actionable. If nothing is being reported from these charts, then players are left to wonder why the information is being tracked in the first place.
While it’s great to keep an elaborate record of what is happening, having detailed information only exist on pen and paper limits the potential for how it can be analyzed and implemented.
Let’s face it: computers are much faster at making calculations and are more helpful in visualizing trends. It is not a feasible process for a coach to manually calculate numbers like these on a game-by-game basis:
Without transferring the information to a computer, I have to imagine that coaches are either spending a ton of time calculating these numbers by hand or that they are leaving valuable analysis left unexplored.
The problem that I faced as a high school coach was that I had no easy way of knowing how well my pitchers were performing outside of the common box score stats. However, box score stats are not the most reliable performance metrics due to factors such as poor defense, a high variance of batter talent, and pure luck scattered across the low number of games played.
Unfortunately, high school baseball is not blessed like the MLB is with Statcast Data showing the velocity, movement and location of every pitch during a game.
From an unbiased perspective, how was I supposed to know the true effectiveness of certain pitches?
I needed a way to quickly analyze my athletes’ performances without it taking hours every game (after all, I’m just a volunteer high school coach!).
Rather than subjectively telling one of my pitchers that their curveball needs improvement, it is easier to get this point across using facts supported by data such as:
- “your curveball is only being thrown for a strike 50% of the time”
- “your curveball has generated 0 whiffs in the last three games”
- “batters are slugging over .600 against your curveball”
This type of feedback helps the athlete understand the need to improve in a way that relates to their performance on the field. Using this approach seemed to help the athletes “buy in’’ to any suggestions I would make in an attempt to improve a particular pitch.
To facilitate the gathering of this feedback, I made a spreadsheet that performs necessary calculations to help me analyze the effectiveness of each pitcher’s pitch type.
Outside of date and pitcher name, the only inputs needed for this spreadsheet are:
- pitch type
- ball or strike
- outcome of at-bat
Upon entering the inputs of each pitch during a game, the spreadsheet automatically generates tables showing strike percentage, whiff percentage, batter handedness splits (optional), and more for each pitcher’s pitch type by game and throughout the season.
Charts like the ones above are immediately available after entering the data which only took me about 10 minutes per game once I got comfortable using the sheet.
A more efficient approach would be having a coach or staff member enter data directly into the spreadsheet during the game to provide real-time feedback.
Here is a walkthrough video tutorial on how to use the spreadsheet:
This Pitcher Performance Game Chart Template is publicly available and you can “Make a copy” and use it to evaluate your own team:
Feel free to leave a comment suggesting improvements or additional analysis that you would like to be included. I would love to know which teams, coaches, or players have benefitted from using it!
