Much Ado About Bunting
What makes a player a good, or successful, bunter? Is it because they have good to great speed? Is it because there truly is a skill associated with laying down a good bunt?
What makes a player a good, or successful, bunter? Is it because they have good to great speed? Is it because there truly is a skill associated with laying down a good bunt?
While OBP and SLG correlate almost equally to scoring, we will dive in further, seeing if the individual hitters make any more of a difference.
It is generally assumed that a balanced lineup is the most efficient, but is there any truth to this? Using team OBP, wOBA, and R/G, are there any trends that pop up over the past 17 years?
Which pitchers strikeout and walk more or fewer batters than we expect and what similarities do they have?
Taking a look at fastball velocity trends of starting pitchers over the course of a typical game.
With pitcher performance partially influenced by the opponent they face, we develop the statistic OARA (Opponent Adjusted Runs Average, pronounced like "aura") to adjust for this.
WHB analysis has provided a new way to look at baseball. Before leaving the subject, it's essential to know why the WHB theory is important and what it could mean for the future of baseball analytics.
Splitting up the Home Run Perception data in any way possible.
Which pitchers are best at preventing the stolen base? And which pitchers are giving away the extra base?
I threw everything at the wall and not much stuck. Walks remain somewhat of a mystery.
A look at pitch selection for starting pitchers as they face the same hitters multiple times in the same game.
Building on a 2012 study, attempting to predict changes in K% based on Whiffs and fastball velocity.
We compile play by play data since 2002, using the overall run expectancy of teams to calculate the most efficient offenses of the 2000's. Then we look at last year's most efficient offensive attacks.
With the DH not coming to the NL until A.S. (After Selig), what type of hitting could we see from pitchers in the coming years?
How can we quantify the goosebumps we get from deep home runs down the line?
Many writers have been critical of the passive approach now widespread in the major leagues. Is this approach really hurting scoring?
This installment takes WHB and gives it more game context, which leads to the development of a new metric: SMASH
Jordany Valdespin and the umpires intentionally or unintentionally ignored ball 4. How did that affect Valdespin's chances of getting doing anything better on the next pitch.
What is the average height of each home run hit to each field at each park and how is that affected by the park dimensions?
Before I make the big jump and create my advanced WHB metric, we will look into what WHB data shows us that BIP data cannot.
Looking at outlier months in league average runs-per-game.
The Cardinals have a winning record once again. In fact they lead the tough NL Central, but how has Mike Matheny's squad done it?
After developing Similarity Scores, we go through testing and visualizing these scores.
Part of understanding offense is understanding what pitchers are going to try to do to create outs. In this installment, I'll challenge the DIPS theory and shed light on what pitchers can do to get batters out.
We take a look at six of April's hottest stars, and simulate their full season outputs one-thousand times through a method we call bootstrapping, to arrive at a prediction for where their WAR totals will end up at the end of the year!
The ability to work the count and be patient at the plate is a highly praised skill in baseball. But does it actually lead to more wins?