Can we identify subtle changes in release point that may not be evident to the naked eye?
As the draft begins, KATOH tackles college pitchers.
Applying the KATOH formula to college hitters.
The strike zone has morphed in a way that is less equitable to certain hitters.
Now that we have more information, is it time to update our values?
if you want to understand Statcast, you need to know a little bit about radar.
This in-depth look at run values examines the value of each ball not put in play, and thus, the value of catchers who know how to frame.
Changing speeds and location? More questions lead to … more questions.
Is Kris Bryant’s eye color going to pose him a problem in Chicago?
Pitches might vary substantially in value based solely on when they’re thrown
Who really does have the best pitch?
Why did two seemingly similar home runs carry so differently?
Will throwing harder land a pitcher on the disabled list?
Taking a deep dive into the multitude of fascinating statistical anomalies and oddities to look forward to this season.
A 0.00 ERA this season? Or 73 home runs? There’s a (tiny) chance.
Projection systems do most of the heavy lifting, but there are marginal improvements to be made.
Even if we completely trust projections, some win totals will miss by a fairly large margin.
Proposing a new pitcher quality estimator that approximates the pitcher’s current ability.
The beginning of a step-by-step look at the questions we should be trying to answer when we explore pitch sequencing.
Can various stats be combined to give a clearer look at pitcher values?