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Rick Lucks breaks down how to use Pitch Info data to identify pitching sleepers and busts as his series on making sabermetrics more accessible to fantasy owners continues.
One of the most fundamental questions in fantasy sports is if a player's current performance is sustainable. More than any other sport, baseball has a slew of statistical measures that can be dissected in numerous ways to analyze player performance.
Pitch Info is a publicly-available pitch tracking system that provides a lot of different data to help fantasy owners make this determination for mound breakouts and busts alike.
Let's look at how to effectively use this data to give you an edge in your fantasy baseball league throughout the season.
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Interpreting Pitch Info Data: Velocity
The first data point to understand is velocity. Generally speaking, a pitcher that loses fastball velocity is losing something to either an undisclosed injury or the aging process. Pitchers that gain velocity can expect to increase their production. For example, Lucas Giolito saw his average fastball velocity spike to 94.6 mph last season (92.8 mph in 2018). His K% soared as a result (32.3 K% vs. just 16.1% in 2018), making him a fantasy stud (3.41 ERA) instead of a dumpster fire (6.13 ERA in '18)
When evaluating a pitcher's velocity, you should always look at his baseline velocity as opposed to an arbitrary league average. Giolito's 94.6 mph isn't all that impressive by modern standards, but it clearly allowed him to take his game to a new level. Other variables like movement and location also matter, but velocity is a good introduction to using Pitch Info data.
Interpreting Pitch Info Data: Pitch Mix
Slightly more advanced is pitch mix, or what pitches a pitcher throws and how often he throws them. A pitcher may improve his production by abandoning a poor pitch or developing a new, effective one. This is a good stat to consult if a pitcher sees a sharp change in his K%, as a change in pitch mix could represent the change in approach that supports the new number. If the change does not have a corresponding pitch mix shift, it may be less sustainable.
Let's return to Giolito as our example. He made two substantial repertoire changes as part of his breakout, and Pitch Info allows us to track the performance of each individual pitch. First, he eliminated his sinker (19.9% thrown in '18. 0.1% last year) in favor of his four-seamer (39.5% in '18, 54.9% last year). Giolito's four-seamer was amazing, generating an above-average number of whiffs (11.5 SwStr%) while still spending enough time in the zone to get ahead in the count (55 Zone%). His sinker generated very few swings and misses in 2018 (4.3 SwStr%), while its 53.9 Zone% was just shy of his new heater. This was a good change.
Second, he threw more changeups (15.3% to 26.1%) at the expense of his curve (10.1% to 4.2%). Giolito's change was one of the best pitches in baseball last season, producing an incredible 22.2 SwStr% with a 52.5 Zone%. Throwing more of it could only be a good thing. In contrast, his curve doesn't accomplish anything in particular, with pedestrian SwStr% (5.1), Zone% (36.8), and O-Swing% (18.9) rates. Again, this change figures to improve Giolito's fantasy stock.
The same type of analysis may be performed for a number of other stats, including BABIP, FB%, LD%, GB%, and HR/FB. There is no point in looking at a league-average pitch mix, as every pitcher owns a different arsenal. All of these variables may be considered over a pitcher's complete repertoire to determine how good he is (or should be) without relying on any conventional metrics. This can be good for identifying sleepers, as pitchers that have one or two standout pitches could break out by simply using them more often.
Interpreting Pitch Info Data: Pitch Results
What is the baseline for this type of analysis? It depends on the observer, as there are almost as many ways to interpret this data as there are data points to consider. The league average O-Swing% was 31.6 in 2019, and most good wipeout pitches need to beat this number substantially. The overall Zone% was 41.8, including pitches like splitters in the dirt and high fastballs that were never intended as strikes.
The fastball will generally be inferior in results to pitches that do not need to live in the strike zone, as pitches hit outside of the zone offer better results than offerings in the hitting zone when they are put into play. However, getting ahead in the count is necessary to make those pitches work as intended, making (sometimes) mediocre fastball results a necessity.
It is dangerous to generalize, but 2-seam fastballs and sinkers tend to stink for fantasy purposes. They're usually hit harder than fastballs. They may post strong GB% rates, but also have high BABIPs and scary triple slash lines. Any sinker hit in the air was probably a mistake, so the HR/FB rate is usually high for the limited number of fly balls hit against them. Their SwStr% rates also tend to be poor. Overall, fantasy owners prefer a straight four-seamer to be the "zone pitch" in a pitcher's repertoire.
Personally, I look for fastball with a SwStr% of around 9% and a Zone% of at least 53%. Many pitchers succeed with a lower Zone%, but I can't stand watching walks. I then look for a wipeout pitch that offers a SwStr% of at least 17 and an O-Swing% of 40. Ideally, there is a secondary K pitch that prevents the 0-2 offering from being too predictable. Only aces really fulfill all of these criteria, but I can dream, right?
Conclusion
To conclude, Pitch Info tracks a lot of data of interest to fantasy owners, including average velocity, pitch mix, and individual pitch results. All of this data may be used to predict who will break out or which breakouts can sustain their current performance. If you would like more analytical tools to help you dominate your leagues in 2020, check out this link.
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