Archive for Data Visualization

Major League Baseball is awash in advanced statistics that more reliably describe key aspects of players’ offensive and defensive performance. It has been reported that through the use of Statcast, the MLB Advanced Media group can supply teams with 70 fields x 1.5 billion rows of data per season [i]. Yes, billion with a b. This flood of information has supercharged MLB teams’ and the sabermetric community’s development of ever-more useful statistics for describing player performance.

However, this amount of data brings significant challenges. Perhaps chief among them is that while certain individuals may be comfortable with reams of tables and ever-increasing numbers of descriptive statistics, many others prefer or require analyses and visualization tools that convert disparate metrics into informative and readily interpretable graphics.

MLB’s situation has certain similarities to the discipline of safety toxicology, where the use of high-information content assays for characterizing chemicals’ toxicological profiles has exploded [ii]. Drawing conclusions from multiple biomarkers and test systems is challenging, as it requires synthesis of large amounts of dissimilar data sets. One tool that toxicologists have found useful is the Toxicological Prioritization Index, or ToxPi for short [iii]. ToxPi is an analytical software package that was developed to combine multiple sources of evidence by transforming data into integrated, visual profiles. Read the rest of this entry »

I believe that pitches aren’t thrown in a vacuum, and the effectiveness of one pitch is certainly affected by the pitches that preceded it. Thus, I wanted to identify the most- and least-potent 1-2 pitch combinations in the 2018 Major League Baseball season. To accomplish this, I built a Pitch Combo Effectiveness Tool based on all 2018 pitches thrown in the major leagues.

The approach I took was to evaluate every pitch as the second pitch in a 1-2 combo (forcing us to exclude first pitches in an at-bat). I defined these pitch combos using the pitcher, the pitch types of both the first and second pitches (e.g. “four-seam fastball followed by a curveball”), and the pitch location change from the first to the second pitch (e.g. “the second pitch was further down and more inside than the first pitch”). I then gauged the effectiveness or value of these pitch combinations using the sum of the wOBA added for both the first and second pitches. Lastly, to ensure we were only looking at common pitch combos, we filtered the results to pitch combos observed at least 10 times in 2018.

The chart showing every pitch combo is below, and you can click it to go to the full tool and results:

Read the rest of this entry »

Pitch selection is like Cold War game theory.

The pitcher/catcher (battery) and the hitter are trying to balance a guessing game of what their counterpart is thinking with their own capabilities to develop a decision or expectation about the next pitch thrown.

The battery is trying to strike the delicate balance of a pitch that will result in a strike or an out (usually by being put into play) and give the hitter the least opportunity to get on base. The hitter is trying to anticipate that decision to maximize their ability to react successfully. This becomes circular, since the hitter’s ability to anticipate correctly improves their ability to get on-base, which changes the calculus and pitch decision for the battery, which changes the hitter’s ability to anticipate correctly. Just like the nuclear stand-off of the Cold War, a low-and-inside slider hit into the gap or a Soviet Sarmak from Siberia shot down by Star Wars lasers. Same thing, right?

Pitcher: I should throw this.

Hitter: I will anticipate this.

Pitcher: Then I should throw that.

But it’s not – because baseball is fun and the Cold War was humans (not) trying to murder each other by the millions. Instead let’s say pitch selection is just like keeping secrets from your Friends:

Given this stand-off of anticipation, the battery can take one of two approaches:

1.) Complete randomness, or…

2.) Sequencing pitches that build on each other to keep the hitter off balance.

This is the old pitching-coach speak of “changing the hitter’s eye level, keeping him on his heels, and mixing speeds.” Read the rest of this entry »