What’s That Pitch Worth? 2009 f/x Summit Harry Pavlidis

Pitch-by-Pitch Run Values Feb Joe P. Sheehan wOBA converted to runs to determine run expectancy changes between counts.

Things We Can Do Rank pitches –The Wall Street Journal prefers whiff rate  Study Pitch Locations

Rich Harden Locations

Caveats No regard to base state or outs Depends on actual batted ball outcomes

Assigning Value Balls and Strikes Hits and Outs Run Expectancy based on Count An 0-2 double has more value than a 2-0 double –But the run expectancy was effected by, and assigned to, the first two pitches rv100 –Start with Run Value Against Average (RVAA) –Average per pitch, multiply by 100 –Keeps the pitch in context Doesn’t say “use this pitch more”

Expected Value rv100 is expected value –Not actual runs and change in base state, but established linear weights for hits and outs –Remember the caveat about batted ball outcomes –So let’s talk about expected outcomes

Expected Outcomes Forget about the actual batted ball outcome Establish probability of an outcome by batted ball type –Ground Ball –Line Drive –Fly Ball –Pop-up

What Do You Expect? Expected outcomes are derived from Gameday Stringer records the hit type Park based outcome probabilities –Normal park effects (deep alley, short fence) –Stringer bias Not all line drives created equally, or tagged the same for the matter Could be improved by adding in direction (pull vs. straight vs. opposite)

HITf/x and Pitch Value Peter Jensen already showed us the way Bucket the batted balls –Speed off bat –Launch (vertical) angle –Spray (horizontal) angle Find the distribution of outcomes, use the same linear weights …

Event Values EventRun Exp. Walk0.32 Single0.48 Double0.78 Triple1.06 Homerun1.40 Out-0.28

Sample Event Outcomes: Hard Grounders Ground BallsSOBLaunch1br2br3brhrroutr*Run Exp. Opposite (-21.8) Middle (2.9) Pull (27.4) The labels aren’t needed, that’s the point But this makes it understandable Under the hood, they go away