Having more and better data will increase the skills of our seers.
Using Statcast data to study the flight of a baseball.
What hitters did, what they should have done, and how some over- or under-achieved.
What pitch type can be hit the farthest, and how is that accomplished?
Let’s apply defense independent statistics to batters!
Is the Rogers Centre’s new turf unfriendly to ground balls?
We have neat new statistics. Now we have to figure out what they they mean — and don’t mean.
One more entry to Fenway Park’s already substantial catalog of quirks.
Why did two seemingly similar home runs carry so differently?
Updating a particular slice of the record book that doesn’t reflect how the game is played today.
An examination of the potentials of batted-ball platooning.
Getting ground balls is definitely a good thing. But does that make a pitcher who gets tons of them a good pitcher?
Can various stats be combined to give a clearer look at pitcher values?
With the Giants back in the postseason, it’s an appropriate time to examine how a home run comes to land in McCovey Cove.
A spinning baseball does amazing things, as every good pitcher and frustrated hitter knows.
We are facing a troubling decline in offense, but are shifts really the cause?
It’s time to build a better heat map.
We’ve just scratched the surface when it comes to using PITCHf/x data to tell us about hitters.
Just in time for the holiday weekend, we reach back in time to reminisce over some more great throws.
Creating a tool to show when or if a player should be shifted.