Pitcher Comparison

The Impact of First Pitch Strike Precision on All Outcomes

We analyzed three distinct Starting Pitchers from the 2024 season:

  1. The Sniper: The pitcher with the Highest First Pitch Strike rate.
  2. The Average: A pitcher representing the league median.
  3. The Coin Flip: The pitcher with the Lowest First Pitch Strike rate.

Does throwing that first strike actually change the composition of how their season goes?

The Strategy: This chart represents a pitcher who dominates the strike zone early (~74% FPS).

What to look for:

  • Massive Green Slices: Because he gets ahead 0-1, batters are forced to protect the plate, leading to high Strikeout and Field Out numbers.

  • Tiny Yellow Slice: He rarely walks people because he doesn’t fall behind in the count.

  • The Takeaway: This is the model of efficiency. By attacking early, he minimizes damage and controls the pace of the game.

The Strategy: This represents the league median. This pitcher lands a first-pitch strike ~63% of the time.

What to look for:

  • Balance: You see a healthy mix of green (outs) and red/yellow (offense advantage).

  • The Baseline: This chart serves as your “Control Group.” It shows what a typical MLB performance looks like.

  • The Takeaway: Compare the other two charts to this one. You will clearly see how deviating from this baseline (either better or worse command) dramatically shifts the color balance.

The Strategy: This pitcher has the lowest FPS rate (~52%). He constantly falls behind 1-0.

What to look for:

  • The Yellow Danger Zone: Notice how much larger the Walk slice is compared to The Sniper.

  • Hidden Damage: When batters know a pitcher can’t find the zone, they sit on specific pitches, leading to harder contact.

  • The Takeaway: This visualizes inefficiency. Falling behind extends innings, raises pitch counts, and gives the advantage to the batter.

Disclaimer


1. The “Good Strike” vs. “Bad Strike” Problem

This data treats all strikes as equal, but in reality, pitch quality matters more than pitch result.

  • A generic “Strike” could be a 98mph fastball on the black (an excellent pitch).

  • It could also be a 90mph slider hanging in the middle of the plate (a terrible pitch).


Both count as a “First Pitch Strike” on these charts. However, a pitcher with a high strike percentage might actually be struggling if those strikes are low-quality “meatballs” that get crushed, whereas an Ace might throw fewer strikes but with much higher precision.


2. Sample Size & Context

Baseball is a game of large numbers. If these charts are based on a small sample (like a single game or a specific month), the data can fluctuate wildly. A pitcher might have a 70% First Pitch Strike rate in one game simply because the opposing batters were swinging aggressively at bad pitches, not because the pitcher had elite control.


3. Outcome Bias

We often judge the process by the result. Getting ahead 0-1 is statistically better, but it is not a magic wand.

  • If a pitcher falls behind 1-0 but induces a double-play on the next pitch, the “bad” start didn’t matter.

  • Conversely, getting ahead 0-1 is useless if the pitcher immediately gives up a home run on the very next pitch.


First Pitch Strikes are a tool for success, not a guarantee of it.