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One of the most fundamental questions in fantasy sports is if a player's current performance is sustainable. PITCHf/x 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.

The first data point, and the easiest 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. The average major league heater was 92.4 mph in 2015, though of course a pitcher's established baseline is a better indicator of future performance. Other variables like movement and location also matter, but velocity is a good introduction to using PITCHf/x data.

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 GB% or K%, as a change in pitch mix could represent the change in approach that justifies the new number. If the change does not have a corresponding pitch mix shift, it may be less sustainable.

For example, consider Detroit's Justin Verlander. His GB% declined last year relative to 2014, 39.6% to 34.6%. His K% spiked in the same time frame, from 17.8% to 21.1%. Are these numbers the result of random fluctuation, or did Verlander change his pitch selection to bring them about?

PITCHf/x tracks each pitch's individual results, so any change in pitch selection can be evaluated by comparing an offering's usage percentage and its performance, in this case GB% and SwStr%. The biggest change in Verlander's pitch selection was that he threw more heaters (37.4% to 49.6%) and fewer changeups (28.5% to 18.3%) in 2015. The fastball had a GB% of 24.9%, while the change offered a 39.1% rate. More fastballs and fewer changeups would be expected to lead to a decline in overall GB%, and that is exactly what happened.

Verlander's heat generated whiffs 9.8% of the time, while the change posted a SwStr% of just 7.6%. We would expect this to lead to an increased K%, and again that is exactly what happened. The same type of analysis may be performed for a number of other stats, including FB%, LD%, BB%, HR/FB and even BABIP. 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, pitchers that have one or two stand out pitches that could break out by simply using them more often. Lets have some fun with our example and use Clayton Kershaw.

Kershaw threw four different pitches in 2015: a fastball 53.9% of the time, a slider 27.3% of the time, a curve 18.2% of the time, and a change 0.5% of the time. The change was thrown 18 times over the entire season, so it may have been a misrecorded slider or a rare mistake pitch. At any rate, the sample size is too small to consider it in this discussion, leaving three offerings for our analysis.

The fastball averaged 93.6 mph, a couple of ticks better than league average. It spent a good portion of time in the strike zone, registering a Zone% of 57.9%. That may seem low, but remember that a pitcher that throws too many strikes is likely to be hammered. The pitch recorded an above average 10.1% SwStr%, a hair better than the overall league average of 9.9%. It was a good pitch, but does not seem to make Kershaw Kershaw.

That is what the slider is for. It was only a strike 41.1% of the time, but compensated by making hitters chase it at a whopping 46.4% clip. That helped give it a SwStr% of 25.6%, absolutely obliterating the average rate and explaining how Kershaw compiled 300 Ks last year.

Kershaw also has the curveball. It was a strike even less frequently at 38.2%, but also posted an above average O-Swing% of 38.9%. This gave it a SwStr% of 18.8%--very good, but inferior to Kershaw's slider. Why throw it?

Sometimes, hitters actually put the ball in play. Batters managed a triple slash line (AVG/OBP/SLG) of only .116/.116/.169 against Kershaw's curveball in 2015, compared to .175/.200/.260 against the slider and .233/.297/.340 against the heat. All three are well above average, and Kershaw's arsenal is an embarrassment of riches if there ever was one. He's fun to look at, but he can't be a baseline.

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 31.3% in 2015, and most good wipeout-type pitches need to beat that substantially. The overall zone% was 45.3%, including pitches like splitters in the dirt and high fastballs that were never intended as strikes.

The fastball will always be inferior in results to pitches that do not need to live in the strike zone, like Kershaw's slider. Pitches hit outside of the zone also 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 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 in the strike zone, but get 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. Overall, fantasy owners prefer a fastball or cutter to be the strike zone pitch in a pitcher's repertoire.

Personally, I like a fastball with a SwStr% of around league average and a zone% of around 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 15% and an O-Swing% of 40%. Ideally, there is a secondary K pitch, like Kershaw's curve, that prevents the 0-2 pitch from being too predictable. Only aces really fulfill all of these criteria, but I can dream, right?

To conclude, PITCHf/x 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. The last entry in this series will discuss how to deal with minor league stats, which do not include all of the advanced metrics discussed thus far. Projecting prospects has increasingly become a part of every fantasy owner's job, and there are ways to analyze them beyond a blind faith in homers and ERA.


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