For most of the season all eyes directed towards the Phillies offense have been focused on Chase Utley. And why not? After all, Chase can be found in the top five or top ten in just about every offensive category in the National League. Recently, though, Utley has hit a coldspell, posting a .203/.294/.356 slash line in his last sixteen games. Luckily for the Phillies, others have stepped up and filled the void.

My brother, who covers the Phillies at Phanatic Phollow Up, wrote yesterday about how not just one but many Phillies hitters are stepping up at this juncture. In his first 19 games, Shane Victorino had a .626 OPS; in his last 19 games it has been .773, raising his season OPS to .703. Geoff Jenkins had a .237/.284/.329 slash line through 24 games; in his last 21 it has been .339/.358/.468. Even Pedro Feliz is at a .304/.333/.478 clip over his last 12 games.

Of all the players stepping up, none is more satisfying to Phillies fans than Ryan Howard. Since May 7th, Howard has played 18 games, with a .264/.321/.681 slash line, 4 2B, 1 3B, 8 HR and 18 RBI. On the season he has 14 HR, coming in just behind Lance Berkman, Dan Uggla, and teammate Utley. Howard is still striking out, 28 K in these 18 games, but the extra base hits, about half of which have been to the opposite field, are definitely a promising sign.

He puts about one-third of his flyballs into the stands and hits a lot of balls hard, as evidenced by his ~20% line drives. Despite lacking anything resembling speed, Howard has had very high BABIPs for his career; .375 in 2004, .358 in 2005, .363 in 2006, .336 in 2007. This year, however, it is only .245. This should regress to his mean as the season progresses meaning Howard could, and probably will, defy his critics by having what ends up as a good season.

The strikeouts are definitely a problem but, unlike in April, when he was just striking out, now he is striking out and hitting the ball hard, often out of the stadium.

The Diamondbacks have one of the best outfields in baseball, with Eric Byrnes, Chris Young, and Justin Upton providing both offense and defense for the team that looks like the National League’s best. In order to make room for Upton, however, they shipped off Carlos Quentin, and he’s quickly making them regret that decision.

After another huge night, where he was the White Sox offense against John Lackey, Quentin continues to solidify his position as the best hitter in the American League so far in 2008. His .301/.415/.608 line gives him the league’s highest WPA/LI, and his 14 home runs also lead the junior circuit while matching his career total coming into the ’08 season. When you can double your career home run total in 166 at-bats, you’ve either had an amazing year or a pretty lousy career to that point, or more probably, both.

Quentin was a pretty big disappointment in Arizona, and his power was a question mark after just okay performances in some pretty good hitters parks. He’s answering those questions in a big way this year, however. 22 of his 50 hits have gone for extra bases, and when you combine the ability to drive the ball with good pitch selection (13.3% BB%, 17.8% K%), you get an all-star offensive performer. Unlike many hot starters, Quentin’s early strong performance is not driven by an unsustainable rate of hits falling in front of fielders, as his .287 BABIP is actually a little below the league average. His goodness is coming from hitting the ball over the wall, and while he won’t keep getting home runs at this rate, he’s a talented player who is breaking free of the bust label.

Considering the White Sox got him for a decent-but-not-great prospect in Chris Carter, the acquisition of Quentin has to be considered the steal of the offseason, and is one of the main reasons Chicago is a surprising contender in the A.L. Central.

Last year the Yankees struggled in the first half of the season and fought their way back into playoff contention. This year, it is no secret they are underachieving, prompting many analysts to question whether this will be the season in which the Yanks miss the postseason. In an attempt to determine what is going wrong with the team I turned to their team page and became fascinated with the numbers of Jason Giambi.

Believe it or not, Giambi is one of just three Yankees hitters with a WPA of at least 0.15; his 0.17 comes in behind just Hideki Matsui and Bobby Abreu. Additionally, he has a WPA/LI of 0.73, much higher than his WPA.

What will turn many fans off is his lowly .236 batting average. When put into perspective with the rest of his slash line—.236/.384/.516—it becomes clear that the batting average truly does not do his production justice. He has just 29 hits but 8 are doubles and 9 are home runs. Those 9 HR lead the Yankees and his 24 RBIs ranks second to Abreu.

Giambi has increased his BB% from a year ago and decreased his K% from 26 to 15. His LD/GB/FB rates were virtually identical in both 2006 and 2007, coming in at 16.4/30.2/53.4; this year he has BIP rates of 19.4/28.7/51.9. He is hitting more line drives and yet has just a .208 BABIP. We have talked here a lot about expected BABIP and how it works for hitters, so we would expect Giambi to be closer to the .314 range with this percentage of line drives. Now, this isn’t to say he will sustain 19.4% LD all season but that frequency should roughly correlate to the aforementioned BABIP.

Looking at Giambi’s numbers from 2002-2007, the only year in which his BABIP and xBABIP differed significantly was 2003; generally speaking, his BABIPs have been close to what his percentage of line drives would suggest.

What really interested me about Giambi is his shift in swing and contact percentages. He currently leads the league with the lowest percentage of swings at pitches outside the zone. Giambi has swung at just 9.9% of outside pitches, making contact on 51.7% of those swings. Last year he swung at 18.2% of the pitches outside the zone, likely contributing to his higher K%.

He has swung at 67.9% of pitches in the zone, making contact on 88.5% of them; the 88.5% puts him right in the 50th percentile. Overall, these swing and contact shifts have resulted in Giambi making contact four percent more often than a year ago. Giambi might not be the player he was five years ago, steroids or not, but his numbers seemingly absolve him from blame for the Yankees early struggles.

Right after he was released by the Toronto Blue Jays, we asked the question “is Frank Thomas done?”

At the time of his release, Thomas had posted the following core statistics: 15.5% BB%, 21.7% K%, 11.5% HR/FB%. The driving force behind his struggles was a .159 batting average on balls in play, which screamed regression to the mean. Based on the fact that his underlying skill set hadn’t changed, I concluded that Thomas still had productive baseball left in his bat, and there was no reason to believe that he had fallen off a sudden cliff.

Since signing with the A’s, Thomas has posted the following core statistics: 14.6% BB%, 22.0% K%, 11.1% HR/FB%. The driving force behind his rebound is a .350 batting average on balls in play. That’s actually regression a little bit past the mean, but the idea still works. There’s been absolutely no change in Thomas’ skills since moving to Oakland – he’s just getting better results from those same skills.

There were all kinds of subjective opinions being offered up that Thomas was overweight, had a slower bat, or wasn’t trying. All of those opinions flew in the face of the fact that Thomas’ results simply hadn’t matched his skills for a few weeks, which happens all the time in baseball. Given a larger sample, we can now state with confidence that jumping to the conclusion that Thomas was finished was obviously incorrect.

Frank Thomas can still hit a baseball, and that’s not any more true today than it was a month ago. Teams that let themselves be deceived by three weeks worth of results missed out on a solid player because they failed to grasp the power of regression to the mean.

Entering tonight’s action the Twins have a 23-24 record and are just 3.5 games behind the first place White Sox. Though the 2008 season is still relatively young, I think it is safe to say most of us did not expect the Twinkies to be so close to .500, at any point this season. By trading the best pitcher in the game, Johan Santana, for a slew of prospects, the Twins seemed poised for a rebuilding phase; one that would not necessarily bring with it much success this year. Despite this, the Twins are no cakewalk and catcher Joe Mauer is a major reason why.

Though Joe is yet to hit his first home run, he is posting a .333/.404/.413 slash line, which gives him the highest catcher-OPS in the American League; only Geovany Soto and Brian McCann have higher OPS counts for catchers. Additionally, he has struck out just 13 times in 150 at-bats, the fifth lowest K% in the AL.

He leads the Twins with a 1.39 WPA, 1.09 REW, and 11.29 BRAA. His WPA surpasses everyone else on his team so much so that it would take the aggregate sum of Justin Morneau, Carlos Gomez, Craig Monroe, and Scott Baker to roughly equal Mauer’s contributions. He is hitting the same percentage of flyballs from a year ago but has replaced 5.5% of his grounders with line drives this year.

The area of Mauer’s statistics that fascinates me most is his selectivity. He has swung at a very low 16.2% of pitches outside of the strike zone yet has increased his out of zone contact by nearly ten percent. This increase has given him the highest percentage of contact out of the zone in the league.

In the strike zone, Mauer has an almost identical percentage of swings to last year, and only Bobby Abreu has swung at less in the zone in the AL. Despite his low frequency of swings in the zone he ranks 8th in zone contact.

A commonly accepted creed is for the batter to “wait for his pitch.” Well, Mauer not only waits for his pitches more often than the vast majority of the league, but he makes good use of them!

On Thursday night, Dodgers prospect Clayton Kershaw was pulled from his start after just one inning. He’s healthy, he’s pitching well, and the Dodgers need a fifth starter exactly five days from last night. Putting two and two together, it’s becoming obvious that Kershaw will be making his major league debut next Tuesday in Wrigley Field.

So, what should Dodgers fans expect from Kershaw?

Let’s start with his stuff. Kershaw features a 93-96 MPH fastball from the left side and a knee buckling 72-78 MPH curveball that is a true knockout pitch. He’s fiddled with a change-up, but I wouldn’t expect to see much of it on Tuesday; 20 year olds making their major league debut often stick with what they’re comfortable with, and Kershaw’s most comfortable with his top two offerings. Command had been his primary concern heading into this season (he walked 15.9% of batters he faced in Double-A last year), but he’s improved his fastball location and is learning to pitch more efficiently. However, he’s still not a great bet to work deep in games right off the bat.

Kershaw’s fastball/curveball combination gets him plenty of strikeouts, drawing comparisons from Dave Righetti to Josh Beckett, though he adds in the wrinkle of being a southpaw as well. His minor league career strikeout rate is right around 30%, and even when matched up against Double-A hitters, his inexperience hasn’t stopped him from ringing them up left and right. Kershaw’s stuff is good enough to get a lot of swings and misses, no matter what caliber of hitter he’s facing.

Generally, when a kid this good comes up from the minors, the adjustment period isn’t a long one. He will take some lumps as he grows, but let’s not confuse him with good but not great pitching prospects who have come up before their time and struggled. Kershaw has all the skills to be a legitimate major league starter right now, and the Dodgers are making the right call by sticking him in their rotation. The race for the N.L. West is a two team sprint, and the Dodgers are on the verge of adding a pretty significant horse.

Tuesday should be a lot of fun.

Arizona’s Yusmeiro Petit is an interesting pitcher. New York Mets fans will recognize his name as a former top prospect with the organization before he was traded to the Florida Marlins, along with first baseman Mike Jacobs and infielder Grant Psomas, for veteran first baseman Carlos Delgado in November of 2005. Petit was then flipped to Arizona in March 2007 for reliever Jorge Julio.

The right-hander, a Venezuela native, was originally signed as a non-drafted free agent by the Mets in 2001. He spent some time honing his skills in Latin America before coming over to play in Rookie ball in 2003 at the age of 18. Petit turned heads by allowing only 6.82 H/9, 1.16 BB/9 and posting a rate of 9.44 K/9. He even earned a late-season, two-game promotion to the New York Penn League.

He really got noticed in 2004 when, as a 19 year old, he started out in full-season ball in the South Atlantic League. In 15 starts, Petit posted rates of 5.10 H/9, 2.39 BB/9 and a dazzling 13.23 K/9. He was promoted to High-A ball in the Florida State League where he made another nine starts and posted rates of 5.48 H/9, 2.84 BB/9 and 12.59 K/9. He also made two late season starts in Double-A and posted similar rates, although the hits were a little higher, as were the walks. On the season, in just under 140 innings, Petit struck out 200 batters.

Right about now, like Mets fans at the time, you are probably beginning to salivate at the thought of a young, hard-throwing phenom, yes? Well the thing about Petit is that he throws in the upper-80s and doesn’t have any one pitch that will wow you. Frankly, no one really understood how he struck out so many batters… although he did have above-average command and some deception in his delivery. But most scouts agreed on one thing: It probably would not last. And it didn’t.

Petit spent most of 2005 in Double-A where he made 21 starts and posted rates of 6.88 H/9, 1.38 BB/9 and 9.94 K/9. In two late season starts in Triple-A, he posted a 9.20 ERA and allowed 14.73 H/9. He was rated the second best prospect in the Mets system by Baseball America. The Mets then sold high on Petit in the off-season with the trade to Florida.

The next season in Triple-A, he posted rates of 9.40 H/9, 1.86 BB/9 and 6.33 K/9. In 15 games at the major league level, including one start, Petit posted a 9.57 ERA. He allowed 15.72 H/9. He was then sent to Arizona in the off-season.

Petit pitched respectably in 17 starts for Triple-A Tucson and also held his own in the majors. In 14 games, 10 starts, he posted rates of 9.16 H/9, 2.84 BB/9 and 6.32 K/9. OK numbers, but nothing like the eye-bulging rates he was posting as a 19-year-old in A-ball. So far in 2008, Petit has been on the shuttle between Triple-A and the majors, which may very well be his future. Although he is still only 23, Petit’s stuff and recent numbers would suggest he is a pretty good Triple-A pitcher and an OK 12th or 13th pitcher on a major league staff.

The lesson for today is this: Stats are great, but sometimes you just have to trust the scouting report.

When I posted my article on Kosuke Fukudome yesterday, loyal reader VegasWatch pointed out that the Cubs outfielder’s opening day home run likely contributed the bulk of his 0.52 clutch score. Therefore, after being given the label of “clutch” the net sum of all of Kosuke’s clutchiness would not add up to much.

The formula for clutch, as defined in the glossary here, is:

Clutch = WPA/pLI – WPA/LI

For further clarification, pLI refers to the average leverage index of all game events for a given player while WPA/LI refers to context neutral wins; in other words, what the player produced regardless of the situation he entered into. This formula calculates the performance level of a player in crucial situations relative to his standard production. If a player has a .330 batting average in high leverage situations but hits .330 everywhere else, he is not considered clutch. This is not to say he lacks talent, but rather he just produces at a high level in all situations and isn’t necessarily stepping his game up in crucial plate appearances.

The Kosuke example made me wonder which other players were greatly benefiting from a big play. Looking at the top eight clutch scores before the stats updated last night, I tracked the biggest individual play for each of the eight and compared the clutch score of that singular play to the net sum of their other plays. This way we can see which player’s clutch labels are truly derived from one big play as opposed to those who have been a bit more consistent in stepping up. Here are the eight, with their overall clutch score and the three required components of their biggest play – note that the pLI refers to the season average, not the game average:

Pat Burrell (1.33): 0.899 WPA, 3.56 LI, 1.09 pLI
Melvin Mora (1.30): 0.418 WPA, 5.14 LI, 1.04 pLI
Freddy Sanchez (1.27): 0.363 WPA, 4.65 LI, 1.03 pLI
Skip Schumaker (0.93): 0.287 WPA, 4.29 LI, 1.04 pLI
Jeremy Hermida (0.86): 0.294 WPA, 2.61 LI, 0.94 pLI
Bobby Abreu (0.84): 0.512 WPA, 5.44 LI, 0.92 pLI
Manny Ramirez (0.81): 0.482 WPA, 2.38 LI, 0.95 pLI
Joe Mauer (0.80): 0.364 WPA, 4.35 LI, 1.07 pLI

With these figures, here is the breakdown of the big play clutch vs. the clutch in all other plate appearances:

Pat Burrell: 0.57 big play, 0.76 other
Melvin Mora: 0.32 big play, 0.98 other
Freddy Sanchez: 0.27 big play, 1.00 other
Skip Schumaker: 0.21 big play, 0.72 other
Jeremy Hermida: 0.20 big play, 0.66 other
Bobby Abreu: 0.46 big play, 0.38 other
Manny Ramirez: 0.30 big play, 0.51 other
Joe Mauer: 0.26 big play, 0.54 other

Pat Burrell had the most clutch “big play” when he hit a walkoff two-run home run against the Giants on May 2nd. However, according to these numbers, Abreu actually benefited the most from his play; he is the only one whose big play exceeded the net sum of all other clutch plays.

On the flipside, Freddy Sanchez and Melvin Mora have been very consistent in raising their performance level in high leverage situations. When talking about a player’s clutchiness, though, it really only takes one or two big plays to cement the label. We could remove the one big play and look at all other performances but since one play can change a fan’s perception of clutchiness that just would not be fair; regardless of whether or not the clutch benefits from a huge play or a group of smaller plays added together, the bottom line is that these players have helped their team win games by stepping up in crucial situations.

There’s a good chance that Jose Contreras is currently 64 years old. I wouldn’t be surprised to learn that his grandchildren were throwing 94 and learning a split finger. If you need some ammunition for baseball related comedy, you can’t go wrong with making fun of Jose Contreras’ age. But, however old he is (and his listed age of 37 seems about as likely as 16), we should notice that he is reinventing himself to extend his career.

After getting bombed in New York on July 31st of last year, Contreras’ ERA stood at 6.60 and people were speculating that he had reached the end of his career. Unable to trade him, the White Sox placed him on waivers, where every single team in baseball passed on taking on the last year and two months of his contract. He got pulled from Chicago’s rotation, called out publicly by the manager, and given his proverbial last rights.

However, he apparently wasn’t done, and so Contreras decided to become Aaron Cook.

See that straight green line? That was a remarkably consistent ground ball rate during the 2004-2007 seasons, fluctuating from 44.1 to 44.9%. In 2008, he’s getting ground balls at a 57% rate. However, Contreras’ strikeout rate wasn’t holding as steady.

Doesn’t take a scientist to see the pattern there.

Realizing that his ability to miss bats was deteriorating, Contreras has focused on getting ground balls, and the results speak for themselves – a 3.26 FIP that is the best he’s ever posted as a starting pitcher. Now, that’s not sustainable, as he’s posting a ridiculously low 4.3% HR/FB rate that just won’t continue. However, the extra ground balls will cut down on his home run rate, and when combined with his above average command, this version of Jose Contreras is a pretty good pitcher.

Apparently, you can teach an old dog new tricks, as long as you don’t have any idea how old the dog really is.

Recently on FanGraphs, we’ve been referring to a stat called xBABIP or Expected Batting Average on Balls in Play to help justify a pitcher’s current BABIP. There’s been a few questions about what this stat means, so I thought it’d be as good a time as any to try and explain the ins and outs of this particular metric.

The initial concept of BABIP is that pitchers do not have control over what happens to balls once they are hit into the field of play.

BABIP typically fluctuates from year to year with a baseline of around .300. If a pitcher has a particularly high or low BABIP, we may say he’s been lucky or unlucky. Things are of course not quite this simple, but for the most part the rule holds true.

In enters ball in play data; we know how many line drives, fly balls, and ground balls a pitcher allows in to play. Line drives fall for hits the most often and ground balls fall for hits more often than fly balls. What types of batted balls a pitcher allows into play are going to effect a pitcher’s overall BABIP.

BABIP by Type (2007):
Fly Balls – .15
Ground Balls – .24
Line Drives – .73

Ideally, the formula is going to look something like this to find out a player’s expected BABIP:
expected BABIP = .15 * FB% + .24 * GB% + .73 * LD%

For more accuracy you could remove home runs from the batted ball percentages at a rate of 92% from fly balls and 8% from line drives. You could even account for infield fly balls and remove that from total fly balls, but the formula above will get you pretty far.

Dave Studeman a couple of years ago calculated that adding .12 to LD% was good enough for a ball park estimate of a player’s expected BABIP. This is what you’ll often see writers on FanGraphs refer to as xBABIP.

The best way to use this statistic is to attempt to validate a pitcher’s current BABIP. For instance, a pitcher might have an high line drive percentage and a high BABIP. This would give a pitcher a high xBABIP as well and you could say: “Yes, his high line drive percentage is responsible for his high BABIP.”

While this is useful for looking at past performances, the difference in xBABIP and BABIP should not be used in an attempt to evaluate future performance. This is because LD% and BABIP are somewhat independent of each other. While there is some correlation between LD% and BABIP, it isn’t enough to suggest that they will always track each other.

LD% in itself is highly variable and it would be difficult to say that a pitcher with a BABIP of .300 and a LD% of 22% (xBABIP of .340) should do considerably worse going forward because you really don’t know what his LD% is going to be the rest of the season. His xBABIP of .340 was his expected BABIP and will not be his expected BABIP in the future. Typically a pitcher’s expected BABIP in the future will be around the original baseline of .300.