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Trying to project Vogelsong in Giants Primer, Part II

April 2, 2012

Click here for Giants Primer, Part I

The performance of Ryan Vogelsong will be one of the biggest factors in determining if the Giants return to the playoffs. Last year, the journeyman pitcher was spectacular, earning an All-Star appearance and one vote for the Cy Young Award. ‘Twas a wonderful tale of redemption and determination. After the season ended, though, the conversation, at least for many analysts and talking heads, shifted to how his success could not possibly be repeated in 2012. After all, Vogelsong is the same person who couldn’t make it with the lowly Pirates and had to pitch in Japan for three years to keep his baseball career alive.

If Vogey can perform at or near the level he did last year, the Giants will have one of the best starting rotations in the league yet again, with four starters that could match any other team’s top four, which is all that matters in the playoffs. If he regresses, then Tim Lincecum, Matt Cain and Madison Bumgarner are tasked with carrying an average offense to the postseason. The bullpen will be stretched thin from extra work on the days those three don’t start, and Giants relievers, though stellar across the board, will be worn out by September with fatigue and probably injury.

Enjoy this picture, for this post is text-heavy and technical.

What I would usually do in this situation is head over to and take a look at some of Vogey’s peripheral stats—lesser known, underlying statistics that are generally better predictors of future success than Wins, ERA and the like. But since Vogelsong has been out of the league for so long, he doesn’t have a reliable baseline for those statistics. The next paragraph gets a little technical, so skip it if you want or are already familiar with this stuff.

This article in the Fangraphs glossary sums up the problem with sample sizes succinctly. In short, it states that very few pitching statistics become reliable enough to draw conclusions from them if the sample size is 750 batters faced (BF) or less. Vogelsong faced 752 batters last season, so his statistics from 2011 aren’t reliable enough to predict his performance in 2012. Some of the most useful stats: a pitcher’s strikeout rate (K%), walk rate (BB%) and groundball-to-flyball ratio (GB/FB), become reliable after about 200 BF, but Vogelsong is such a special case that I’m hesitant to lean on those three (and besides it’s hard to glean much without using anything else). Compound metrics like and Fielding Independent Pitching (FIP) don’t become reliable until after multiple seasons. Only then can we view them as indicative of a player’s true talent level. From that baseline, amateurs like me can look at seasons in which a significant spike or dip in those stats occurred, and that can be interpreted as luck, random statistical noise, a change in the player’s home park or anything like that.

Now that I’ve explained why I couldn’t look at Vogelsong’s history to predict his future, let me tell you what I ended up doing. I decided to look at pitchers who were similar to Vogelsong in 2011, in order to gather a larger sample from which to draw conclusions.

How did I decide that a pitcher was similar to Vogelsong? I’m glad you asked, other Marciano.

I began with the pool of pitchers who pitched enough innings—162—to qualify for the ERA title, 94 pitchers in all. Vogelsong’s average fastball velocity in 2011, according to PITCHf/x technology made available on Fangraphs, was 91.6 mph, so I then filtered it down to pitchers whose fastballs fall in the 90-92 mph range. Then I narrowed the results again to only pitchers with the same assortment of pitches as Vogelsong, who throws a four- and two-seam fastball, a slider, a curveball and a changeup. I included pitchers who throw a cut fastball if they shared other pitches with Vogey, as sometimes PITCHf/x mistakes cutters for sliders, two-seamers and vice versa.

I ended up with a group of 15 pitchers (including Vogelsong). Here is a table of them, which I turned into a picture file because I’m a noob and can’t do tables. Please click on it to see all its resplendent glory. I will post the actual excel file at the bottom of the article.

The table shows that Vogelsong has an above-average fastball (of both the four- and two-seam variety) and a very good curveball. His changeup is slightly subpar and his slider is his worst pitch.

Now that we have a group of pitchers with similar tools, lets look at how they performed in 2011.

Each column is given a color gradient (red=bad, green=good, brown=ok).

The above table is sorted by SwStr% because it becomes reliable pretty quickly and it is a pretty good indicator of a pitcher’s stuff (or maybe we just define good stuff by the ability to induce swinging strikes—it doesn’t matter here). It makes intuitive sense that pitchers who get batters to swing and miss more often will rack up more strikeouts, which will manifest in a higher K%. Just by looking at the colors, we can see that Vogelsong was either average or below-average in every category except ERA-, where he was one of the best; the underlying stats don’t match the results—based off his place on the table, he should be producing more like Chad Billingsley than Cole Hamels.

He had an especially poor SwStr%, but his K% was decent, suggesting that he got a lot of called (as opposed to swinging) strikeouts. This can happen regularly if a pitcher has a pitch that can freeze hitters (like a nasty curve), or if he can paint the corners. We already established that Vogelsong has a good curveball, and indeed he used it as an out pitch in 2011, throwing it 38% of the time in both 0-2 and 1-2 counts (this fell to 17% in 2-2 counts and 7% with a full count). Vogelsong’s walk rate was a tad high, but if he did have a tendency to pitch toward the edges of the strike zone this would be a natural consequence.

Tomorrow, I will look at some heat maps to better illustrate Vogey’s command of his pitches. With that knowledge the question of how he will perform going forward will be easier to answer. Right now the outlook is poor, because his stuff is subpar and doesn’t suggest that he should be a consistently great pitcher.


The Giants signed Matt Cain for a while. Hooray.

Here is the excel file: vogelsong

If anyone who understands statistics or sabermetrics better than I do is reading this, I would love to hear your feedback on my methodology. I would love to hear anyone’s feedback, actually.

From → Baseball

  1. Molls Balls' Balls permalink

    Is the color gradient a feature in Excel or did you do them all individually?

  2. It’s a feature.

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