Monday, July 06, 2009
Fielding-independent hitting stats
Peter (correctly) points to the future:
The methodology for a skill-based batting metric is relatively simple: Use the usual linear weight values for the non-hit ball events—strikeouts, non-intentional walks. intentional walks and hit-by-pitches—but substitute the average outcome of a hit ball described by its SOB, VA and HA for all hit ball events. I call this metric SDBR, Skill Dependent Batting Runs. The formula is:
SDBR = K_LW + NIBB_LW + IBB_LW + HBP_LW + HIT_BALL_FX_LW
The idea is correct that you basically want to strip out anything that happens after the batter hits the ball. The question is what are the parameters that you can capture so that you can do that. Peter basically gives a basic view as to what the very complex future will look like.
Indeed, it’s really a way to come full circle to the view of the scout. The way the scouts have approached this has always been correct. The question was purely of the measuring device: human eyes versus high-speed cameras. The processing of that data will remain to the human brain. But there again, the speed of the computer to process that data is what we want. Cameras and computers are the slaves that human scouts should kill for.


One interesting variable- speed. “HIT_BALL_FX_LW” on the exact same batted ball is not the same for every hitter. A hard line drive in the gap from Carl Crawford is clearly more valuable than the same batted ball from Jim Thome or Adam Dunn. JC Bradbury ran into this same problem with PrOPS in THT a few years back.
Any ideas how to deal handle this?
On the flip side, there’s an interesting situation for fielders as well. One fielder could play a ball into a double, where as another fielder might hold the runner to a single. Of course, this is also dependent on the runner’s speed and aggressiveness. How much of the result is due to a speedy runner, and how much is due to a poor fielder?