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Pitch Info: Using Sabermetrics for Fantasy Baseball

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 managers 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 managers make this determination for mound breakouts and busts alike. Unlike many of the other metrics we've looked at in this series, Pitch Info data stabilizes (or becomes predictive) very quickly so you can use it in May or even April. Let's look at how to effectively use this data to give you an edge in your fantasy baseball league throughout the season.

The first step is finding it. Basic Pitch Info information such as pitch selection and velocity can be found toward the bottom of a pitcher's page on FanGraphs, but you'll have to use the Pitch Info tab for more detailed information. Hit the Splits tab located on the banner toward the top of the page and then choose the option on the far right, Pitch Info. That will bring up three tables that are loaded with information, the third of which is most important for fantasy purposes.

Be sure to check all of our fantasy baseball lineup tools and resources:

 

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, Robbie Ray saw his average fastball velocity spike to 94.6 mph last season (93.7 mph in 2020), giving him more confidence when throwing it. Not only did his K% improve from 27.1% to 32.1%, but he also dramatically cut his BB% from 17.9% to 6.7%. The result was a four-run improvement in ERA (6.62 vs. 2.84) and the AL Cy Young award.

When evaluating a pitcher's velocity, you should always look at his baseline velocity as opposed to an arbitrary league average. Ray'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 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 prove less sustainable.

It wasn't just a velocity spike that propelled Ray's stellar season. He also threw his fastball more often, 59.8% of the time as opposed to 51.2% in 2020. He was better at throwing it for strikes (62.4 Zone% vs. 50% in '20) and generated more whiffs on it (11.3 SwStr% vs. 6.7%), helping him get ahead in the count and cut down all those walks. The more effective heater also made Ray's lethal slider better, as batters chased it out of the zone 37.4% of the time against just 33.3% in 2020. Its 23.6 SwStr% is exactly what you look for in a wipeout offering.

Throwing one pitch more often means featuring something else less, and it was Ray's curve that declined in usage from 16.5% in 2020 to 5.8% last year. Ray's curve had a great 20.4 SwStr%, but its low 39.8 Zone% and 31.2% chase rate meant too many walks as a featured piece of the arsenal. Cutting back on the curves likely helped Ray keep baserunners off the bases just as much as throwing more effective fastballs did.

The same type of analysis may be performed for a number of other stats, including BABIP, FB%, LD%, GB%, and HR/FB. All of these variables may be considered over a pitcher's complete pitch mix to determine how good he could 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? The league-average O-Swing% was 31.3 in 2021, and most good wipeout pitches need to beat this number substantially. The overall Zone% was 42.1, including pitches like splitters in the dirt 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 hitters generally fare better on pitches in the hitting zone. However, getting ahead in the count is necessary to make those put-away 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 managers usually prefer a straight four-seamer or a cutter to be the "zone pitch" in a pitcher's repertoire.

Personally, I look for fastballs with a SwStr% of around 9% and a Zone% of at least 53%. I then look for a wipeout pitch that offers a SwStr% of at least 17 and an O-Swing% of at least 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 managers, 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 2021, stay tuned!

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