Inside Edge has developed a metric to collect all the things that simply don’t show up in the box score.
The designated hitter didn’t materialize out of nowhere.
Do low-strikeout hitters receive special strike zone preference?
How often does a batter make the “correct” decision on the pitches thrown to him?
How low can it go?
The data show that it is high time to give the vertically-challenged their due.
Against the right team, a “beard” pitcher might be just the thing.
Continuing the quest to determine how many wins consistent play is or is not worth to major league teams.
We are facing a troubling decline in offense, but are shifts really the cause?
It’s time to build a better heat map.
Do teams re-sign only their healthy players? The answer may surprise you.
How much credit should the pitcher get for reining in runners? Here’s a framework for figuring that out.
We’ve just scratched the surface when it comes to using PITCHf/x data to tell us about hitters.
Diving back into the effects of extra-long games — before noticing someone drained the pool.
Creating a tool to show when or if a player should be shifted.
Introducing Weighted Batted Ball Runs Above Average.
Offensive production is not linear – one and one equals more than two. How can a team take advantage of this blind spot in advanced statistics?
In part three, we lay out the net value for 2014 draft picks and ruminate on this from both the team and player perspective.
In part two of three, we examine the value each draft pick provides relative to its cost.
In the first part of a three-part series, previous studies to quantify draft pick valuation are updated.