The keystone of yesterday’s big trade is the Yankees’s new centerfielder. As Dave Cameron noted Curtis Granderson is an all-star level player: under 30, an above average hitter and an above average fielder at a premium defensive position.

Granderson is a legitimate power threat, a big part of his offensive game. He has a career ISO of .211, and in 2009 busted out with a career high 30 HRs. One reason for the additional HRs was his career low 29.5% GB/BIP second lowest in the game. His power, unlike Joe Mauer’s, is fairly standard pull power.

Comerica Park is a pitcher’s park and Granderson has generally had a better ISO away than home. At Yankee Stadium, which might be the best place for lefty pull-power hitters, this should change. Here is the HR/BIA rate by angle of the ball in play for LHBs in Yankee Stadium versus Comerica Park.

Right field, where Granderson hits most of his HRs, at Yankee Stadium has a much higher HR rate than right at Comerica Park. So, Granderson should see a boost to his already solid power in New York. The Yankees got not only a all-star-level player, but one well suited to their park.

Before the flurry of activity begins at the winter meetings I thought I would look back to a signing late last week that I didn’t get a chance to check out. The Brewers signed Gregg Zaun to a $1.9m deal with a $2.25m club option in 2011 or a $0.25m buyout. Not an earth-shattering deal, by any stretch of the imagination, but because on the same day I posted at Baseball Analysts that, based on my pitchf/x model, Gregg Zaun is one of the best pitcher blockers in the Majors, it interested me.

The model predicts how often the average catcher lets a pitch by (Passed Ball or Wild Pitch) based on some pitchf/x values of that pitch and then looks at all the pitches a given catcher has seen to predict how many pitches the average catcher would have let by if he saw those pitches. By this model Gregg Zaun has seen the toughest set of pitches over the pitchf/x era (part of 2007 and all of 2008 and 2009). The data show that low pitches are the toughest and Zaun saw particularly low pitches. His are in blue with average in gray. They are broken up for fastballs (solid) and all other (dotted).

But Zaun did a great job with those tough pitches, and over the 1610 innings he caught covered by the pitchf/x data, he let by 32 fewer pitches than expected (more than any other catcher according to my model and also one of the top on a per inning basis). That works out to 0.02 fewer WPs+PBs per inning than the average catcher. That is probably not his true rate, though. Let’s regress it back to zero by a third, say he gets 600 innings at catcher, and apply 0.28 runs per WP or PB and he projects to be about two runs better than the average catcher just at blocking pitches. That is a fifth of a win or almost a million dollars of value right there.

Yesterday when I was looking at Joe Mauer’s numbers I noticed he sees a lot of fastballs. Generally the better the hitter the fewer the fastballs he sees, but Mauer, the second best hitter in baseball last year, saw more fastballs than anyone else in the top twenty. (Todd Helton, with the 21st best wOBA, is the player with the best wOBA who saw more fastballs than Mauer).

Part of this has to do with the fact that the true relationship is between power and fastballs seen. So it is not that good hitters see fewer fastballs, but that power hitters see fewer fastballs and good hitters are often power hitters. Dave Cameron showed us this relationship last year. Compared to other top hitters, Mauer is not as much of a power hitter, which explains, somewhat, why he sees more fastballs. Here is the relationship for 2009 with Mauer indicated with the filled circle.

He is not the farthest from the trend line, but pretty far, meaning he sees more fastballs than you expect for a hitter with his power. Part of this is because Mauer’s power is so new, and pitchers have not changed their strategy. But pitchers rapidly changed their pitch usage against Ben Zobrist, who busted out this year and saw just 53% fastballs after seeing over 64% every previous year.

The excess of fastballs to Mauer is particularly interesting because he was the second best fastball hitter in baseball in 2009 (only Albert Pujols was better) and 25 of his 28 HRs were off fastballs. (That is based on the pitchf/x pitch classifications. The BIS classifications backs this up, saying he hit 24 HRs off of fastballs).

My guess is next year Mauer will not see 60%+ fastballs like he has so far in his career. Do you think that will have any effect on his game? Head over and project his 2010 performance.

Joe Mauer has denied making any sort of deadline on negotiating a contract extension with the Twins, which gives both sides some breathing room. This is an important decision for the Twins. Joe Mauer is a superstar, providing amazing offense from the toughest defensive position, a fan-favorite, a local boy and the “face of the franchise.” In addition, because of the Johan Santana trade the Twins have a reputation of being cheap when it comes to keeping their stars, and they are entering an expensive taxpayer supported ball park. On the other hand what fans really want are wins, not stars, and extending Mauer could hamstring the franchise by forcing them to pay him a huge portion of their payroll to one player for many years.

Mauer is coming off his best year ever, and there is little chance he will repeat these numbers next year, not that he needs to to be a superstar. But that must be considered. The big reason for his career year was his power outburst:

The 2004 numbers were based on just 122 PAs, so seem like a small sample size artifact . Previous to this year he had slightly below average power, which coupled with his excellent K/BB ratio and BABIP, made him a very good offensive player. But the power breakout, while keeping the amazing other numbers, made him the best non-Pujols offensive player in the game.

The question is how much of that power stays. As Dave Cameron noted earlier most of his power is of the opposite field variety, an extreme rarity. Here is a diagram of where the pitches Mauer hit for HRs crossed the plate and where he hit them in 2009. It is similar to the image I created for Adam Lind, but I incorporated some of the suggestions based on that post. The major suggestion was that the angle of line indicate the angle of the ball in play, which is not how I had it in the previous diagram. Sal Paradise incorporated these suggestions into a diagram and what I present here is close to what he did.

Mauer pulls inside pitches, but takes outside pitches the other way. This is very different from how most LHBs do it.

I am not sure if this extreme opposite field power and tendency to take the outside pitches the other way makes his power any more or less likely to stay. The fans, 72 of whom have projected Mauer, seem to think he will keep most of his power, projecting his ISO at .200, closer to his .222 of last year than his .156 career average. The question of how much of the new found power Mauer keeps, along with the unrelated and unaddressed-here question of how long he stays at catcher, are of the utmost importance to the Twins as they think about the extension.

As you know by now, FanGraphs is hosting a new projection system year, the Fan Projections. Dave Cameron filled us in on why projecting players in this manner can be effective, thanks to the wisdom-of-the-crowds idea. My piece of wisdom to impart is the value of pitch data to inform your projection. This data can tell you if a pitcher has gained or lost speed on his fastball, picked up a new pitch or is throwing a certain pitch more or less often. Thus it is another tool in diagnosing if a big shift in pitcher performance was luck-based or a shift in true talent. You can find that data in the pitchf/x section of each pitcher page or in the Pitch Type section (these pitch classifications are from BIS, which can be slightly different than the pitchf/x ones).

A fitting example is Brian Bannister, a pitchf/x devotee himself. Although we don’t ask you to project it here, one value you could project is his 2010 GB%, which will heavily influence his HR/9 and ERA. Here are Bannister’s GB%s over his career (in green).

Using a Marcel-like 5/4/3 weighting of the past three years to project his 2010 GB% we would get around 43% . But we know that Bannister is a much different pitcher in 2009 than he was in 2008 and 2007. In 2007 and 2008 he threw almost 60% fastballs, but in 2009 he threw the fastball just 17% of the time and a previously unused cutter 50% of the time. This change in pitch type supports the change in GB%, since cutters tend to result in more ground balls than fastballs, and makes us more confident this increase in ground balls is for real going forwards.

We still want to regress somewhat to prior performance and league average, but the change in pitch usage means we should value 2009 more heavily, and project him around 47% or so. From there we can project his HR/9 and ERA based on the assumption that he is above average at getting grounders.

Congratulations to Zack Greinke not only for his Cy Young season, but his historically great season. For us here at FanGraphs, it is especially nice for a stat-loving guy to win.

Greinke throws four- and two-seam fastballs, a change, a curve and a slider. A couple days ago, Harry Pavlidis checked out his curve, and here I am going to look at his slider.

It is nothing short of amazing. On a total runs saved level, it was second only to Brett Anderson’s slider, which I profiled earlier. But Anderson throws his more often, so on a per slider basis, Greinke’s was even better.

Anderson’s slider was successful because it induced a ton of grounders (66%) and weak contact (slugging on contact of .435), but it got a below average number of whiffs (25% compared to 29% average for sliders in 2009). Greinke’s slider succeeded in the exact opposite manner. It gave up an above average slugging on contact (.502 compared to an average of .485), but gets tons and tons of whiffs (almost 45% of swings against his slider did not make contact). In fact no starter’s slider got more whiffs and only a handful of relievers’ sliders did.

+--------------------+-------+
|          Slider Whiff Rate | 
+--------------------+-------+
| Mike Wuertz        | 0.503 |
| Brad Lidge         | 0.467 |
| Luke Gregerson     | 0.455 |  
| Zack Greinke       | 0.447 |  
| Jorge de la Rosa   | 0.430 | 
+--------------------+-------+

Wuertz, of course, has an amazing slider, Lidge does, too, even in a down year, and Gregerson is surpinsingly unhittalbe. Then there is Greinke, the first starting pitcher on the list. He was the best pitcher of this year and one of the top performers of the past decade, and a huge part of it was his unhittable slider.

Joel Pineiro is a guy who got a lot of press this season because of his drastic shift from an ok pitch-to-contact, slight ground ball pitcher to an amazing tiny-BB-rate, extreme ground ball pitcher. Now that Pineiro is a free agent, it is incumbent on teams examine the roots of this change as they evaluate him.

First, looking at his BB rate, here is his career history.

He has always been above average at limiting walks but, last year, entered the “good” range and, this year, dropped even farther to 1.14 BB/9, the lowest rate for a starting pitcher. He also had the lowest walk per batter faced, 3.2%.

At first blush the per-pitch data does not back up this extraordinary control. His Zone% is just 52.5%, which is good, but is the lowest rate of his career and only 14th best in the majors. How can this good, but not great, Zone% lead to the best walk rate in the majors?

The answer lies in his 87.7% contact rate, the highest of his career and third highest in the majors. Since he rarely misses bats, his at-bats just don’t go long enough for him to walk many batters. This is sort of the opposite of what I noticed with Scutaro and Castillo, who take strikes in hopes of extending the at-bat long enough to get a walk. Pineiro’s pitches are so hittable that at-bats rarely last long enough to reach four balls even if they aren’t in the zone at the same rate Cliff Lee or Johan Santana. On the other hand, this hittableness resulted in his 4.42 K/9 rate, third worst in the game.

So Pinerio is an extreme pitch-to-contact pitcher, but if you are going to give up a ton of balls in play, you want to do it the way he does. He led the league by a fair margin in ground balls per ball in play, which results in more double plays and fewer extra base hits. That was the second big change for Pineiro. Red is LDs, blue FBs and green GBs.

Over the past couple years, 2006 to 2008, he had a ground ball rate of 48% — good, not extraordinary — but in 2009 it jumped over 60%. Obviously this was the result of his development of and increased use of a sinker or two-seam fastball. Here are his pitch use break downs in 2007 through 2009 (the years we have the pitchf/x data, which I used to classify his pitches).

+--------------------+------+------+------+
|                    | 2007 | 2008 | 2009 |
+--------------------+------+------+------+
| Four-Seam Fastball | 0.54 | 0.36 | 0.11 |
| Two-Seam Fastball  | 0.03 | 0.23 | 0.59 |
| Slider             | 0.16 | 0.20 | 0.12 |     
| Curve              | 0.16 | 0.09 | 0.09 |     
| Changeup           | 0.11 | 0.12 | 0.09 |     
+--------------------+------+------+------+

That two-seam fastball he is using so much more often has a 68% ground ball rate and a 91% contact rate. Thus it is the big reason he is so hittable, which plays a role in the decrease in walks, and the big reason he got so many ground balls this year.

As I wrote before, Pineiro will regress in 2010 and very likely not perform as well. This season was about the best you can expect from a pitcher who strikes out less than one batter every two innings. But assuming he keeps throwing that sinker so often, he will limit walks, get tons ground balls and be a solid pitcher.

Earlier in the day, RJ took a look at David Wright’s drop in power. Although a number of Mets lost power in 2009 (most likely as a result of the move to Citi Field), Wright saw the biggest decline. In addition, Wright showed little difference between his home and away ISO, suggesting that the drop was not entirely the result of playing at Citi.

Wright’s drop in power intrigued me as well. In addition to this power drop, another striking trend was that his strikeout rate, which had averaged 19% previous to 2009, jumped to 26%. The fact that he still took a healthy number of walks and hit for his absurd .400 BABIP kept his overall performance with the bat quite good (.368), though down for his career average of .391. Here I am going to look at that increase in strikeouts and drop in power on a per-pitch basis with the pitchf/x data.

His increase in strikeouts was driven completely by his performance against RHPs. Below is his strike out rate by pitcher handedness (green is average, red RHP and blue LHP).

I am sure there are many interesting things to examine here. As a first step, I found that his contact rate against RHPs dropped from 82% in 2008 and 2007 (when I have the per-pitch data from pitchf/x) to 79% in 2009. This is one of those seemingly small changes, which magnified over the entire season, has a large effect. Just as I looked at the contact rate by location for Scutaro last week, I do that for Wright here, breaking it up by year.

Previously, Wright had a large sweet spot mid-height and middle-in, where he made contact over 95% of the time. This region has shrunk drastically and moved further down and in. Previously, he made contact with pitches over 87% of the time throughout maybe half of the zone, down and away. Again this zone shifted even further down and away and got smaller. Overall, it seems like he is making poorer contact on pitches in the middle of and away half of the zone, as well as pitches higher in the zone.

His power was down against both RHPs and LHPs. Again here there are many ways one could look at this, but one of the more striking patterns I found was how his ISO varied with horizontal pitch location.

Wright’s power peaks middle-in, like most hitters. In 2009, it was down throughout the strike zone, but particularly on pitches in the middle and outside of the plate. Put together, in 2009 Wright lost the most power and contact on pitches from middle-in to the outside edge of the plate.

As RJ noted, most likely Wright will rebound next year. The question is how much of this was drop in true talent and how much just flukey bad luck.

One of the more intriguing free agents, to me, is Marco Scutaro. After years of solidly below-average production, he was traded to the Jays and in 2008 had a good year last year (WAR 2.7) and then busted out this year with a WAR of 4.5 (making him one of the top 35 position players).

The big change came at the plate. Prior to this year, he had always been a below-average offensive player (negative wRAA every year), but this year he posted a wOBA of .354 over 680 PAs to provide 14 runs above average at the plate. Doing that while playing average defense at short will result in huge value, as seen by his 4.5 WAR.

The increase in offensive value came, largely, from an increased walk rate, 13.6%, a career high for him and in the top 25 of all of baseball. He coupled that with a low strikeout rate; he was one of the few players in the game to have more walks than strikeouts. This led to a jump in his OBP, and thus offensive value.

A big drop in his swing rate and increase in his contact rate caused to the increase in walks. He was the second best at not swinging at pitches out of the zone (12.3%), had the third lowest overall swing rate (34.5%, behind only Bobby Abreu and Luis Castillo), and he tied Castillo for the highest contact percentage (93.3%). His offensive game is very similar to Castillo’s, which I described in this post.

Here is what it looks like to swing at almost nothing. I mapped out his swing probability by pitch location and then drew the contour line where it switches from greater than 50% to less than 50%. So he is more likely than not to swing at pitches inside the contour line, and less likely than not to swing at those outside. I broke it up based on the number of strikes and, for the zero-strike case, also plotted the 25% contour. I plotted Scutaro’s contours and the average for all right handed batters.

When there are zero strikes Scutaro’s 50% contour is non-existent. On average he takes a pitch even if it is right down the middle when he has no strikes. Generally, he swings at fewer pitches out of the zone, but he is also taking lots of pitches in the zone compared to average. By swinging, Scutaro has a chance to end the at-bat; instead, he will take pitches in hopes of continuing the at-bat and getting enough balls to earn a walk. He will take some strikes, but that is ok, because once he gets two strikes, his contact skills are so good he will rarely strike out swinging.

Here are the same graphs as above but for contact rate, and the contours are for the 90% contact rate. So on pitches inside the contour Scutaro has a greater than 90% contact rate.

Scutaro’s are, not surprisingly, much larger than average, and they get bigger as the number of strikes increases. So he is able to swing defensively at two strikes and rarely miss a pitch. This means he can take pitches freely up to that point, hope they are balls to get a walk, but even if they are strikes, he will be ok.

As I noted, Scutaro’s approach is very simliar to Castillo’s. The difference is that Scutaro hit only 37% of his balls in play on the ground compared to 59% for Castillo. So when Scutaro puts the ball in play, he actually has some chance at extra base hits (ISO of .127 compared to Castillo’s .043). Scutaro has Castillo’s excellent plate discipline and contact skills, coupled with at least a modicum of power, making him a solidly above average hitter.

Scutaro is due for some serious regression to his offensive level, as is anyone who posts 2400 PAs at wOBA of .311 and then 680 at .354. But I think that, because the change is supported by the per-pitch level data, which is not immune from regression itself, we can temper that regression somewhat.

Scutaro can play average defense at second or slightly below average at short, is 34 coming off far and away a career year at the plate, and is a type A free agent. It will be interesting to see what kind of deal he gets.

Tim Wakefield renegotiated his perpetual team option deal and instead will have a guaranteed two-year 5 million dollar contact, which he signed on Monday. Wakefield will turn 44 in the middle of next year and has 189 wins. The deal gives him a solid shot at 200 wins for his career. Additionally, 175 of those wins have come with the Sox, so he also has a chance at becoming the franchise leader in wins. Right now, Roger Clemens and Cy Young are tied with 192 wins.

I think it is a treat for all baseball fans that we can continue to watch Wakefield pitch, and pitchf/x analysts seem to love looking at the knuckle ball. Wakefield throws his knuckler about 85% of the time, and mixes in a fastball 10% of the time and a curve 5% of the time.

As you can see. his curve and fastball move in a similar manner to most. The fastball “rises” about ten inches and moves in to RHBs, while the curve drops ten inches and tails away from RHBs. His fastball averages 72 mph. making it far and away the slowest fastball in the game. I showed in a previous article that he uses it sort of like an anti-changeup. It is about 8 mph faster than his knuckleball, and its success is tied to its speed difference from the preceding knuckleball.

His curveball averages 59 mph, making it the game’s slowest pitch.

But the important thing here is the knuckleball, which has no consistent movement. It does not have a neatly defined area in spin deflection space like his curve or his fastball or almost all other pitches do. That is the key to its success; the batter doesn’t know how the pitch is going to move (neither does the catcher for that matter). John Walsh showed that the success of each pitch is tied to how much it moves. Those with little spin deflection (little movement) are hit often and hit hard. While those at the edge with more movement are whiffed at more and, when hit, for poorer contact.

Josh Kalk followed that up by showing that Wakefield’s knuckleballs have a greater “spread” in their movement than those of other pitchers who have recently tried the knuckbleball, like Josh Banks, Charlie Zink and Charlie Haeger, which is why Wakefield is the most successful.

I am a huge fan of the knuckleball, generally, and Wakefield, specifically. I hope that he can pick up those eighteen wins, so he will have over 200 and Red Sox franchise record.