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11 wins to defend that title.

11 wins to once again reach the pinnacle of the baseball world.

Two down, nine to go.

The march to championship #28 continues tonight.

Oct 092010

In 2009, Brian Duensing had a respectable debut. He pitched in 24 games, starting nine of them. All told in ’09, he threw 84 regular season innings to a 3.64 ERA, 4.13 FIP, and 4.77 xFIP. The xFIP is a bit high because Duensing didn’t strike many guys out (5.68 per nine), but he did display decent control (3.32 BB/9), and kept the ball in the park (0.75 HR/9). He got guys to ground out 45.5% of the time and stranded 74.9% of the batters who faced him.

2009 saw Duensing work with a fastball-slider combination, while mixing in a changeup and a curveball from the left side. In the 2010 season Duensing has changed things up a bit. He’s throwing his fastball much less, has apparently added a sinker, upped his changeup usage, and kept steady with the slider. Brian doesn’t throw very hard, but the results have been there, especially in 2010.

In 53 games, 13 starts, he’s thrown 130.2 innings. The strikeout numbers stayed low–5.37 K/9–but he lowered his BB/9 to 2.41. His HR/9 “rose” to 0.76, so he’s still doing a great job of keeping the ball from landing amongst the people. His groundball rate is up to 52.5%, so we can see the results of that added sinker right there. As for the rate stats, they’re pretty solid: 2.62 ERA (3.05 as a starter)/3.85 FIP/4.10 xFIP. Again, the punchouts aren’t there, but he’s got great control and he doesn’t give up homers; that will definitely lead to a good FIP/xFIP.

There are some things that could give us some pause. For example, Duensing’s strand rate is high at 81.6%. The league average strand rate is 72.2%. His BABIP is also down to .276 from .295 last year (.302 avg. this year, .303 last year). But, man cannot live on BABIP alone. Duensing’s BABIP is so low because he’s not giving up terribly hard contact.

He’s only allowing line drives 15.6% of the time and his tRA as a starter (StatCorner) is 4.05 (3.46 as RP), good for a 109 tRA+ (122 as RP). The FanGraphs version of the stat has Duensing at 3.76 total.

By the numbers, Duensing has had a great 2010. Now, let’s look at how he’s going to attack the Yankees.

On the first pitch, Duensing varies greatly. He’s thrown three different first pitches over 20% of the time: 26.3% fastball, 24.9% sinker, 22.2% slider. Out of those three, the sinker with its 61.2% strike percentage has been the most effective on the first pitch.

Once ahead 0-1, Duensing increases his slider usage to 21.9% and gets it to be a strike 72% of the time.

When behind 0-1, he still mixes pretty well. He throws a fastball 32.1% of the time, a sinker 29.4% of the time, and a change up 24.3%.

What the Yankees can expect, then, is a guy who’s going to mix his pitches a lot and use his non-fastball stuff when he’s ahead and behind.

How should the Yankees approach Duensing? They should do what they always do: make him throw his pitches for strikes. It seems that Duensing likes to pitch backwards and if he is locating the sinkers and sliders, he’s trouble. If he can’t do that, the Yankees should be able to jump on his fastballs for hits or let him work himself into trouble with walks. If Duensing can locate his breaking pitches, the Yankees may have to wait him out and try to beat the Twins’ bullpen. They could do what they did the other night against Carl Pavano, too. In the first few innings, Pavano was getting ahead of hitters early and they couldn’t do much. As the game progressed, the Yankees got more aggressive early in the count and were able to drive the ball. A similar strategy could work in Game Three if Duensing is locating well with his non-fastballs early on in the game. Pardon the Captain Obvious appearance here, but Duensing’s sliders and sinkers will be his key tonight. If they’re good, he’s good. If they’re not, he may not be long for the game.

At Baseball Prospectus yesterday, Colin Wyers offered an unusual take on the Pavano/Berkman umpiring controversy.  I’ll attempt to summarize his piece, but if you have a BP subscription you should go on over and read the whole piece.  It’s rather well-done.  Wyers first notes that there are a plenitude of factors conspiring against the viewer to prevent them from calling a pitch a ball or a strike.  Part of the problem is that the camera is not positioned directly behind the pitcher, as it would have us believe.  The camera is positioned in the outfield at an offset and zoomed in (which really says something about the quality of the camera, no?).  This also affects our depth perception and our ability to perceive the distance between the pitcher and the catcher and the break of the pitches, no small thing.  The result, Wyers argues, is that the umpire has a leg up on the viewers at home:

The act of recording a pitch on video significantly changes how it looks compared to how it really is. This is why if you’re watching on TV, and the umpire calls a close pitch in a way you disagree with, it is far more likely that the umpire is right than you.

(And of course, the exact offset and the amount of magnification changes from park to park and sometimes batter to batter. Some camera setups are going to make it look like more pitches are inside than they really are, others may make it look like pitches are lower than they are, and so on.)

And then there’s the question of Pitch F(x).  The reliability of Pitch F(x) data is predicated on proper calibration, which is why the operators calibrate it before every game.  Yet the presence of some 42,000 people in the stadium that night would cause the stadium to actually move, taking the cameras with it.  This heightens the margin of error:

PITCHf/x reported the pitch at .67 feet away from the center of home plate as it crossed the front of the plate; according to Mike’s corrections, it was probably .72 feet away, with a margin of error of .06 feet (accounting for the random error in pitch location measurement, plus the estimated error in the correction.) The edge of the zone (in other words, the edge of the plate) extends to .71 feet from the center of the plate in either direction. Now, PITCHf/x is giving us the center of the ball—if any part of the ball catches the plate, it’s a strike. So the effective zone extends to roughly .83 feet from the center of the plate.

So we think that pitch was probably a strike, given what we’ve seen with PITCHf/x—but we’re not entirely certain. (Remember, standard error means a 68 percent chance outcomes occur within the MOE.) It is, essentially, a borderline pitch.

Not only that, but there is some difficulty in judging the vertical zone.  Every baseball observer knows that the strike zone varies from batter to batter, and so Pitch F(x) operators will set the top and bottom of the zone before every at-bat.  This adds margin of error to Pitch F(x) data:

So when using the F/X data to judge whether or not a pitch is in the zone, you need to account not only for measurement error in the pitched ball, but the operator’s estimate of the strike zone as well.

This is why it is expressly unhelpful to go to your favorite PITCHf/x website, pull up a scatterplot from a single game, and use it as evidence the umpire did a bad job. The responsible thing to do (and this is what MLB does when using PITCHf/x to grade umpires) is to correct for these calibration errors and to look at a larger sample of data.

This is also one reason it’s infeasible right now to use PITCHf/x to call balls and strikes in a live game. (There are others—timeliness is one, of course. Another is operator error—game scorers are just as human as umpires, and they sometimes make mistakes in associating the PITCHf/x data with the right pitch in the game, for instance.)

Over at Inside the Book, MGL offers a response to Wyers.  His argument is essentially that astute baseball observers have developed advanced pattern recognition that enables us them to judge with relative accuracy whether a ball was a strike or not.  In classic MGL form, he writes:

I say poppycock!  I claim I can call most pitches almost as well as the pitch f/x graphics you see on TV.  How can I do that even with all those camera problems that Colin talks about?  Well, when you watch thousand of games and you get feedback from umpires, batters, pitchers, AND, most importantly, the “pitchtrax” graphics on TV over the last 5 or 10 years, you somehow mentally can make all the necessary adjustments, the same way that a batter can figure out whether a pitch is going to be a ball or strike (Jeff Francouer and Pablo Sandoval excepted of course) in less than 1/2 a second.  In other words, for every pitch you see, you have seen that same pitch in the same visual location hundreds of times, and you have also seen what the umpire calls it, the reaction of the players, and many times, the exact location according to the TV strike zone graphic.  You can reach into your memory bank, and call the pitch pretty much as well as the average umpire, the average player, the pitchtrax graphic, etc.

Of course, there’s no real way to judge whether MGL is right unless he actually got behind the plate and tried to call balls and strikes as an umpire.  Wherever you come down on the issue, it’s safe to say that the issue is more complex than: “the umpire is an idiot because Gameday/Brooks says so”.  The umpire probably is an idiot though.

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