Is Fastball Velocity Predictive of Usage?

As its title indicates, this post aims to address whether or not a pitcher’s fastball velocity corresponds to, or is predictive of, how often he turns to that pitch. One would imagine that the harder a pitcher throws, the more he would utilize his fastball. But, as we will see, that is not always the case; really, it’s hardly a trend at all in 2019.

The scatterplot below, using FanGraphs’ data, maps each qualifying starter in 2019, plotting his average fastball velocity against his usage rate. There are 78 pitchers in the dataset who at the All Star break made the innings threshold.

Here are a few summary stats: average fastball velocity within this group is 92.75 mph (the median is 92.73 mph). The average fastball usage is 51.2%, indicating that, for starting pitchers, the fastball is used really just a bit more than half the time. 

These data are really quite noisy. Without the turquoise trend line, it might take a moment to recognize a slight upward trend. Regardless of the gentle incline though, the fact is the line is upward sloping. 

Traditional regression markers back up the simple eye-test. The R-Squared value, a number ranging from 0-1 which quantifies the “goodness of fit” of a regression line, is just 0.081 for the above turquoise regression line. That indicates, very generally speaking, that velocity alone does a poor job mapping, let alone predicting, fastball usage. 

So the relationship between fastball velocity and usage is a positive one, just not nearly so correlated as I, for one, might have imagined.

Today, pitches are thrown with horizontal and vertical break at the forefront of some pitchers’ minds, spin rates are tracked fastidiously, a pitcher’s extension is publicly scrutinized, and more. Breaking pitches tend to beget swings and misses at higher rates. In today’s game, it makes sense that starting pitchers aren’t relying terribly heavily on fastballs. 

So fastball velocity doesn’t correspond all that much to fastball usage for starting pitchers. Next, let’s take a look at the pitchers who deviate especially from that trend line superimposed in the scatterplot above. Below is a table that offers a look at those pitchers who actually throw more fastballs than their velocity might suggest that they would.

J.A. Happ and Lance Lynn jump out ahead as highest raw users of their fastballs, turning to those pitches nearly 70% of the time. Lynn, who employs several variations of fastball, is having considerable success using his fastball this year. Happ, on the other hand, hasn’t been at his best for much of 2019. 

Kyle Hendricks, owner of the slowest average fastball among qualified starters, is second highest on this list (likely because of that fringy velocity). The column labeled “Difference” indicates that he uses a fastball nearly 20% more often than the simple regression anticipates. For Hendricks, control supersedes velocity and enables this usage, and more recently usage up in the zone.

On the opposite end of the spectrum, two young particularly hard-throwing starters, Brandon Woodruff and Walker Buehler, also rely heavily on their elite fastballs. 

This next table contains those players who throw their fastballs considerably less than the simple model estimates.

Wade Miley, despite throwing roughly 2.5 mph slower than this cohort’s average, throws a fastball 25% less often than anticipated based on the fact that he deploys that classification of pitch just 22.90% of the time, easily the least this year. He has clearly found a way to succeed with an Astros organization that emphasizes spin and pitch mixing. In fact, Miley throws no fewer than 5 pitches at least 5% of the time.

Max Scherzer owns the hardest fastball on this leaderboard, and 11th hardest among all qualifying starters this year; despite that heat, he relies on other pitches roughly 52% of the time. Even slightly more drastic, Trevor Bauer, who averages a 94.7 mph fastball, spurns the fastball nearly 58% of the time for another offering.

Clayton Kershaw, who represents another interesting case study in this chart, is currently adapting to his diminishing fastball (now just over 90 mph on average). He has been throwing that fastball just 42.50% of the time this season, a stark drop off from his early years in the league. Up until the 2013 season, his fastball use ranged between 60-70%, and its usage has been consistently giving way to the slider in the last half decade.

But don’t leave here considering the players that make up each of the last two charts as the “outliers”. Outliers really isn’t an apt term given how spread these data are. In fact, each of the two featured charts include 20 names, so in a 78 player dataset, they actually represent more than half of the total players and the entire outer quartiles of the data. Hopefully, this illustrates how much spread exists here. 

In today’s game, power pitchers are about more than just power. Particularly crafty pitchers who rely on finesse can still sneak by fastballs with some regularity. In a game in which everyone knows exactly what everyone throws, and where they throw it, and how often they do, and in which counts, mixing pitches is a necessity, and might be part of why no real trend is particularly clear.