wOBA Added – A New Metric for Measuring Single Pitch Effectiveness

My goal with Baseball POP is to find the strategies that make every single pitch most or least effective and move the pitcher or hitter closer to their end goal of an out or getting on-base. To do this, first we need to have a measure of single-pitch effectiveness.

Pitches that terminate an at-bat are relatively easy to assign a value to – did at-bat end in an out or hit. However, in 2018, almost 500k pitches (or 75%) of pitches thrown in Major League Baseball game didn’t end an at-bat. So how are to determine which pitch is good and which isn’t? Is moving from no strikes to one strike just as valuable as moving from two to three? What if there are two balls? three? How does the hitter’s change in approach in these counts change the marginal value of each new strike or ball?

And is there more going on? Are all 1 ball, 2 strike counts created equal? Is the hitter in better or worse shape if they got there after seeing three fastballs; or a fastball, breaking ball, and change-up? My hypothesis is the movement from one count to the next has a unique value to the hitter and pitcher, and the journey to get to those counts matters as much as the count itself.

To begin this test, I must first have an objective measure of success for each marginal pitch, especially if they don’t terminate an at-bat. I need something that is objective, universal, and clearly correlated with the hitter or pitcher’s chances of ultimate success. Pitch count is that variable.

By looking at the occurrences of every possible count and aggregating the wOBA outcome of those at-bats, we see a clear and predictable relationship between pitch count seen during an at-bat and ultimate at-bat outcome. For example, the chart below shows that all at-bats that passed through a 1 ball, 2 strike count had an average wOBA of .219, regardless of how many more pitches the hitter saw before ending the at-bat. Thus, advancing the pitch to more favorable counts has significant value to the pitcher or hitter.

wOBA Added would just be the improvement or decline of the hitter’s prospects as the count advances. A ball that moves the count from 0 balls, 1 strike to 1 balls, 1 strike would have the wOBA Added that reflects the hitter’s improved prospects from having a more even count. From the chart above, we can see clearly that marginal balls and strikes have different values based on where they come in the count:

  • Most pitches have an amplified impact on the eventual outcome later in the count
  • Marginal balls help the hitter significantly later in the at-bat than earlier. Going from 0-0 to 1-0 is almost completely inconsequential. However, going from 2-0 to 3-0 is enormous.
  • Strikes are slightly less important later in the count, and oftentimes are more important early in the count

So what does an example at-bat look like as the count advances and wOBA added gets tabulated? Here is a set of examples from a 2018 game:

In Sum: pitch count matters greatly to the pitcher and hitter’s chances of eventual success. Also, strikes matter more early and balls matter more late.

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2 replies to “wOBA Added – A New Metric for Measuring Single Pitch Effectiveness”

  1. […] I then gauged the effectiveness or value of these pitch combinations using the sum of the wOBA Added for both the 1st and 2nd pitches. Lastly, to ensure we were only looking at common pitch […]

  2. […] test this, I looked at the standard deviations for wOBA Added for both discretepitch types by pitcher as well as pitch combos by pitcher. I defined a discrete […]

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