Steamer Projections

The Basics of Projection SystemsForecasting the upcoming season is essentially the same as determining current ability.Most projection systems are modifications on the same simple system (Marcel “the monkey):

Weighs stats from more recent seasons more heavily

Regress to the mean

Why regress to the mean?Results = Ability + Luck

Two Examples of Marcel in Action

18.3%23.0%

SteamerAlong with most “fancier” systems:

Uses adjusted minor league statistics in addition to MLB stats.

Adjusts for home ballparks, league, starting v. relieving

What makes Steamer distinct: We use a different system for each component (K%,

BB%, HR%…) We regress to a different “prior” for each player

Projecting Joaquin Benoit’s K% in 2011:4 possible forecasts

28.0%

26.1% 23.7%

24.9%

Actual K%: 26.1%

K/PA for All Pitchers: 1993-2011

HR/PA for All Pitchers: 1993-2011

Regression is Bayes

Distribution of MLB talent

ProjectionLikelihood of player statisticsGiven different levels of talent

K% v. FBV for Starters

K% v. FBV for Relievers

Matt Thornton 2012

24.0% 27.2%

Marcel error v. Fastball Velocity

More regression = Stronger Relationship

It might be working…

Where to go from here?For Pitchers:

Develop a better measure of stuff than fastball velcoity Jeremy Greenhouse: StuffRV based on velocity and

movement Josh Kalk/Brooksbaseball: Similarity Scores based on

pitchf/x

For Hitters: Can something similar be done with hitf/x? Trackman?

Speed off the bat Trajectory