White Sox Bullpen Brings The Heat

Kenny Williams has a reputation as being a schizophrenic GM in terms of the talent he chooses to supply the White Sox any given season. One year he is playing Ozzie Ball the next he falls in love with the Long Ball. After several seasons of having DJ Carrasco and Ehren Wasserman tossing whiffle balls out of the bullpen, Williams decided to load up on nothing but fireballers. If you don't throw 94, you can't get a parking space in the dome the White Sox call a stadium (take that Sox fans!). Shockingly, only one member of this elite group is a product of the Sox minor league system, and he was just drafted a month ago in the 2010 draft. And as fangraphs has shown, increased velocity is correlated with increased strikeouts, especially at higher velocities. So here is the breakdown of the White Sox bullpen.

Matt Thornton - 96.1 mph, 12.17 K/9

Sergio Santos - 95.8 mph, 9.15 K/9

Chris Sale - 95.5 mph, 11.37 K/9 15K in 6IP in AAA

Bobby jenks - 94.9 mph, 11.3 K/9

Tony Pena - 94.3 mph, 4.89 K/9 WTF?

JJ Putz - 94.0 mph, 10.53 K/9

Scott Linebrink - 93.9 mph, 8.44 K/9

Fantasy Outlook: DME's Ultra Sexy Fantasy Baseball Resources Revealed

As promised, my two money leagues have drafted and I have a few interesting files to share with you, the public. You can navigate the files below by the labeled tabs at the bottom of the file. Some of the files are .xlsx files and will require Office 2007 or higher (though they can be converted to .xls files for free).

• Draft Comparison Rankings - this first file compares Mock Draft Central (MDC) rankings to those of Yahoo fantasy sports (Y!) and ESPN.com (ESPN). The theory behind this file is that MDC rankings represent free market player valuations (courtesy of mid-February data). By comparing MDC rankings to those of Y! and ESPN, one finds who is under/overvalued in each service. Nelson Cruz seems to be perfectly ranked in both Y! and ESPN!, while Y! seems to underrate Max Scherzer and ESPN seems to undervalue Dan Uggla. EDITOR'S NOTE: Yahoo Sports updated its player rankings on March 11, 2010. I have updated the data to reflect these changes.
  
• Starting Pitchers Rankings - this second file has my Top 50 Value SP rankings (players are ranked based on draft position value; thus, no Tim Lincecum or Roy Halladay) and a fully sortable spreadsheet listing all the important peripheral and 2009 statistic data for all 130 starting pitchers who logged 100+ innings last season (data courtesy of Fangraphs).
• xBABIP-based 2010 hitter projections - Using 2009 data for all MLB hitters who amassed 300+ PAs last season, I projected 2010 triple slash lines for 284 hitters (assuming that all hits added/subtracted due to "luck" were singles). For more information on how the data was calculated, click here.

A few other valuable resources I utilized for my draft and auction leagues:

• Roto Authority has Fantasy Player Rankings And Valuations By Position, an analysis of What It Takes To Win A Fantasy League In 2010, and a list of Undervalued Hitters For 2010 available online.
• If you search his Fangraphs.com Author Profile, Eno Sarris has several tier-rankings by position and positional value analysis.
• If you sign up for a free account at Mock Draft Central, you get access to a tier-by-position ranking cheat sheet.
• Fangraphs also has Sortable Projection Sheets for CHONE, Marcel and FANS data. Bill James' projections are not available to sort through (you will have to buy them to do that), but they are available to view for each player in that player's statistical profile.
  

I wish everyone the best of luck in fantasy this year. I will post some more analysis in the coming days. Long live King Felix.

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Drinking The Juice: Jon Lester

With Pitchers and Catchers reporting this week, baseball season is in the air.

Those who know me know that I do not believe in high risks when it comes to fantasy. I believe in modest upside with low-to-no downside. I draft for value, not speculation. When my fellow league members will invest their fantasy dollars in subprime mortgage like gambles, I will be focused on the consistent performance stocks. My motto is not "reach for the stars." Especially when it comes to the early rounds of baseball, the name of the game is expectations. You can't generally win a league with your first seven picks, but you can lose it.

With this motto in mind, let's turn to one of my favorite 2010 starting pitchers; Jon Lester. Just 26 years old, Lester is entering the early years of his prime as much more than a feel-good baseball story a la Disney's The Rookie.

In four seasons, Jon Lester has gone from highly touted prospect to bonafide stud. The K rate is improving (from 6.64 per nine in 2007 to 9.96 in 2009) and the BB rate is shrinking (from 4.76 per nine in 06 to 2.83 in 2009). The groundballs are piling up (from 40.6% in 2006 to 47.7% in 2009), his secondary pitches are improving (his curveball has gone from -1.27 runs per 100/pitches in 2006 to +1.07 last season) and his cut fastball has become downright nasty (from -5.29 runs per 100/pitches in 2006 to +1.96 -- top 5 in the AL last season amongst starting pitchers).

The results? A decreasing contact rate (from 81.3% in 2006 to 74.6% in 2009) with an increased ability to get hitters to chase his pitches (his O-Swing% of 21.3% in 2006 has increased to 26.7 %). All signs point to "yes" when we ask "can Lester sustain his improvements."

Last season, Lester posted a 3.15 FIP and 3.13 xFIP. His 3.41 ERA last season, though still quite good, was largely inflated by a 5.67 ERA (and .370 BABIP) through the first two months of the season. From June through September, Lester was one of baseballs best pitchers. Even in April and May, Lester still piled in K's (74 in 65.1 IP) and tossed players a handful of wins (four, to be exact). Even if Lester regresses a bit in the strikeout department next season, the 3.41 ERA should be seen as the baseline, not the expectation.

Let's say Jon Lester pitches 200 innings next year. Assuming that Lester maintains the GB tendencies he's advanced and maintained in each of the past two seasons, even if Lester regresses to an 8.0 K/9 and 3.0 BB/9 (even though it was 2.83 in both 2008 and 2009...) and even if he allowed a hit per inning, his FIP would be 3.65 with 177 Ks and a 1.33 WHIP to boot. That would be my low-end prediction for Lester. I expect a K rate closer to 9 per nine and a hit rate closer to 8.4 per nine. Such would put Lester in the 3.45 FIP, 1.25 WHIP range. Combine this with Boston's stellar and upgraded defense and I would project Lester's numbers as being even better.

Like another fantasy Man Crush of mine, Jon Lester has a quality 4-pitch mix built for success -- a mid-90s four-seam fastball, a high 80's cut fastball, a two-seam fastball, a mid-80s changeup, and a solid mid-70s curveball. Each is thrown at roughly the same arm slot and each has a variable level of horizontal and vertical break. Lester's weakest pitch, the change-up, is a tick above league average (+0.21 runs per 100 pitches). With such a deadly arsenal, Lester is able to effectively fool hitters and keep them off balance. There is absolutely no reason that he cannot repeat his fantasy 2009 season in 2010, if not find room to improve thanks to an improved defense and improving skill set. Say we start the bidding at $20?

Stolen Goods: Do Lefties "Break Out" More Than Righties?

In an old, but still relevant article, Rany Jazayerli of Baseball Prospectus tackles the question of whether or not southpaws develop later than their right-handed counterparts. The data is aplenty if you want to sift through it all, but the conclusions are thus:

There is simply no compelling evidence that southpaws develop any more slowly than right-handers do...

...lefties, as a whole, were not any worse than the right-handers, and in some cases were better...

Maybe a good percentage of left-handers have a breakout season around age 26, but that's only because a good percentage of all pitchers break out at that age. Yes, there are many examples of left-handers who didn't reach their full potential until their late 20s, but there are just as many examples of right-handers who took just as long.

The Quintessential Sabermetrics Argument: FIP and xFIP

A quintessential component of The Quintessential Sabermetrics Argument: Batting Average was that a lot of batted ball data tends to normalize because hitters do not have as much control over balls in play (BIP) as commonly believed. True, players who consistently make certain kinds of contact more often can maintain higher BABIPS, as can speedsters, but once the ball is in play, whether or not that balls is a "hit" is highly dependent on the positioning and ability of the defense.

From here, we turn from batters to pitchers. A pitcher controls a few things about the outcome of an at bat, each to a variable degree:

A pitcher is in almost absolute control over the general location of his pitch. There are some marginal variants such as temperature, wind speed and wind direction in effect, but a pitcher who does not hit his spots can generally only blame himself. He either gripped the ball incorrectly, released it too late, "has the jitters," just can't pitch, etc. The location of his pitch is something in his control.

A pitcher also almost completely (though less completely than location) controls intentional walks. The Jeff Francouer and Miguel Cabreras of the world aside, if a pitcher wants to intentionally walk a batter, it will happen.

Compared to intentional walks, a pitcher exercises less control, but still a large degree of control, over unintentional walks. Unintentional walks integrate the batter more into the outcome equation and the result is less guaranteed (largely because players like Bengie Molina and umpires like Tim McClellan do not understand the concept of a strike zone). Generally speaking, however, a pitcher controls the general location of his pitches and batters will more often than not lay off pitches outside of the zone.

A pitcher exercises much less control over strikeouts than he does walks, but he still exercises a large degree of control over them. This decline in control over the outcome occurs because the batter is more integrated into the strikeout process. Whereas with walks a player takes a passive role, the hitter is now taking active participation against the pitch; he can lay off or swing and the result will either be contact or no contact. A pitcher with deceptive release points, sharp break and a large velocity disparity between pitches will tend to "fool" batters more often, whereas hitters can more easily square up straight pitches with no movement. Although the pitcher controls the type of his pitch, the degree of deception, the movement, etc., he does not control whether or not the hitter will be able to guess where the ball's true location will be. What the pitcher controls, therefore, is the ability to influence batter's probability of contact; we just simplify this statement in the form of "strikeouts."

As we move from no contact to contact, the degree of control a pitcher exercises over the outcome of an at bat declines further. A pitcher does not control the actual outcome (type of contact) of the at bat (this is because there is no magic "groundball-only-and-always" pitch), but he does exert influence over the tendency of type of contact to result from the at bat. A pitcher who throws pitches with sharper break is more likely to have a hitter get "on top of the ball" and chop it into the ground.

A pitcher does not, however, control the strength of the resulting contact. I would say that pitchers with more deceptive "stuff" are more likely to induce weaker contact than the average pitcher, but once the ball is out of their hands, the question of contact becomes something only the hitter can answer. The ball en route, the hitter must guess where and how to swing. Assuming he does not strikeout, if he guesses poorly, the result with be weak contact -- an infield flyball or weak grounder. If he guesses correctly, the resulting contact will be stronger and harder hit.

Because the pitcher controls the tendency of the ball to be in the ground or in the air, but he does not control how hard it will be hit on the ground or in the air or how far, then it makes sense that a pitcher does not control home runs; only the tendency thereof. Pitchers face so many batters that we can generally assume that the average hitter they will face will have "league average" power. The guy with the league average power hits just over a home run per every 10 flyballs he hits. We call this HR/FB rate (I prefer HR/non-GB rates as a whole, as line drives also turn into home runs sometimes, but HR/FB rate is sufficient for our purposes). The league, as a whole, averages a HR/FB rate in the 11% range, though most pitchers have HR/FB% which normalize to the 9-12% range (depending on where they play). Pitchers, over a large enough sample size, regress into this range because they do not control how hard batters will hit their non-groundball-resultant offerings. Since 2002, 73 pitchers have cumulatively thrown 1000+ innings. Of them, only Jason Schmidt (7.5%), CC Sabathia (8.4%), Cliff Lee (8.5%), Barry Zito (8.6%), Mark Redman (8.8%), Jarrod Washburn (8.8%), Roger Clemens (8.9%), Pedro Martinez (8.9%), Odalis Perez (12.3%), Nate Robertson (12.7%), Derek Lowe (12.7%), Brandon Webb (13.2%), and Brett Myers (15.5%) -- at total of 13 pitchers (five of whom just barely made the cut) -- did not fall into the 9%-12% HR/FB ratio range. Of them, Lee, Sabathia, Zito, and Washburn pitched at exteme home run suppressing parks for most of the sample size, while Webb and Myers pitched at extreme home run exaggerating parks. You might also notice Derek Lowe and Brandon Webb's presence here, despite being the league's two most extreme groundball-oriented pitchers; this only further drives home the point.

Does a pitcher control pop ups? A pitcher certainly controls flyball tendencies, but it is uncertain if "inducing pop ups" is a skill possessed by pitchers. Certainly 2002-2006 Barry Zito would have you believe so. I have no seen any conclusive scientific evidence either way, but I can affirmatively state that pitchers who induce more infield flyballs tend to have lower BABIPs.

What about hits? A pitcher exerts almost no control over non-home run hits. As mentioned above, once the ball is out of the pitcher's hand, it is out of his control (at least from the perspective of pitching ability). Once the ball is put in play, it is the fielders who determine whether or not a ball is going to be a hit. The pitcher may control the direction of the ball, like he does the type of contact, but it is the hitter's guess of the pitch (often which is random in and of itself) which determines if it is a ball down the line, right to the third basemen, hit to the gap, etc.

Left On Base Percentage (LOB%) is another element that pitchers exercise very little control over. Although better pitchers tend to have higher LOB%, LOB% nonetheless regress to some mean, whether it be that of the league average or player's career average. The reason why is very closely related to the "pitcher does not control hits" argument. Because the pitcher does not control if a specific at bat where contact is made results in a hit, a pitcher does not control when contact is made. This means that they do not control BABIP by leverage (a term used to describe how important or impactful upon the probability of outcome a specific situation in a game is). Sure, a pitcher is more likely going for the strikeout or for a groundball when there are runners on base and the game on the line, but the BABIP results and contact% generally remain stagnant over large enough sample size comparisons of situations with variable leverage indexes. This goes towards that whole "there is no such thing as clutch" argument.

From all of the aforementioned reasons, it is important to look beyond ERA and WHIP in evaluating a pitcher's true ability beyond the success he does or does not experience in a single season. ERA measures single-season results with all the non-neutral luck variables factored in. Using ERA to identify a pitcher's talent is like trying to identify a pieces of strawberry in a finely blended all-berry smoothie (food metaphor). We need to look beyond what a pitcher does not control and into what a pitcher does control. This is where FIP or Fielding Independent Pitching statistics (which you may know it as DIPS, or Defense Independent Pitching Statistics) comes in handy. The statistical analysis grunt work has already been done (thanks to Tom Tango) and the coefficient of determination is pretty high (approximately five times that of ERA).

FIP is a better measure of future success than ERA. FIP essentially takes the three elements a pitcher exerts the most control over (K's, BB's and HR's) and weights them in regard to their historical impact on ERA and then adds to them a league-specific factor to round out the resulting number to an equivalent ERA number. The formula for calculating FIP is 3.2+((13*HR)+(3*(BB+HBP-IBB))-(2*K))/IP. ERA tends to regress towards FIP over time. It likely will not match it (too many variables at play), but you can determine whether a player is likely to improve or regress in the future based on FIP-ERA differentials (FIP-based trading and team management is a cornerstone of fantasy baseball success).

But wait, DME, you say, didn't you just say, and I quote, "a pitcher does not control home runs; only the tendency thereof?" You are correct and this brings me to the advanced form of FIP I prefer to utilize called expected FIP or xFIP ("x" is a general term you see in front of statistics to represent some predicative value). xFIP is similar to FIP in how it incorporates the historical weight of K's, BB's and HR's on ERA, but whereas FIP uses a pitcher's in-season home run totals to calculate a pitcher's in-season FIP, xFIP uses a metrics we might call xHR, where xHR is a specific function of the league average HR/FB rate. xFIP measure's a player's future ERA under the theory of HR/FB rate regression.

There is another FIP-like metric out there called tRA, which utilizes a pitcher's total batted ball profile to evaluate his luck-neutral results from a single season and predict a player's future ERA. tRA is not exactly scaled to reflect ERA, so it can be a bit confusing. I personally do not use tRA because I do not believe a pitcher controls "line drives" (at least not as classified and encapsulated in box score data).

From all this explanation and ramble, we derive the following maxims. A pitcher who walks less batters, strikes out more batters and keeps the ball on the ground is likely to succeed. A pitcher who induces more contact and pitches for the 2007 White Sox is not.

Does the bullpen really matter?

I have always had an idea that the major league bullpen does not matter. Not to say that the performance of the bullpen is irrelevant, but the constitution of the bullpen is overstated. I don't believe any team needs any high priced or high reputation guys in the pen. The cliche that a team can't win in the playoffs without a strong bullpen is accurate, but it seems most GMs take it to mean you need a bunch of millionaires.

Firstly, bullpen pitchers are failed starters. They are inherently flawed in not having great stuff, or not having enough pitches to go all 9 innings. What do Ryan Franklin, Joe Nathan, Mariano Rivera, Carlos Marmol, and Rafael Soriano have in common? They are all failed starters but are considered among the elite relievers. Hence, an argument can be made that every team has a bad bullpen. No team would prefer to face the starting pitcher as opposed to the relievers. You always want to get into the bullpen.

Secondly, there is very little predictive value into which teams/players will have good and bad years. You can look through the best and worst bullpens per year on ESPN, and it will show you that there is no rhyme or reason to who has the best bullpen on a yearly basis. The Dodgers are best this year, but who could have known? Who even knew who Ramon Trancoso, Ronald Belisario, Cory Wade, of Hong-Chih Kuo were before this year? Who could have guessed that Guillermo Mota would wake up from the dead? Relief pitchers are awesome one year and atrociously bad the next. What happened to Grant Balfour, Marmol, Putz, Rafael Perez, and Brad Lidge? Just fell off the map, just like relievers every year.

Thirdly, can you think of any great bullpens of the past? I can think of a handful in the past decade, out of 10 x 30 = 300 bullpens in the last 10 years. The 2001 Mariners with Suzuki, Jeff Nelson, Arthur Rhodes. The 2002 Angels with K-Rod, Percival, and a great Scott Shields. The 2004 Astros with Wagner, Dotel, Lidge. The 2005 White Sox with Jenks, Hermanson, Cotts, and Politte. That is it! Everyone else sucked

Conclusion: Stop paying people 4 million, let alone 10, to relievers when your team probably has an equivalent replacement in the minors for 400K. If the Cubs are smart next year, they should dump Gregg, Heilman, Gorzy, Grabow, and anyone making over 2 mill for John Gaub, Blake Parker, Jeff Stevens, And Jeff Samardjia. They can't do much worse than the 19th ranked bullpen we have now

Difference between K/9 and K/BB

After writing the Zimmermann vs Hanson post regarding their peripheral statistics and future prospects, I had a conversation with DME regarding the differences between K rate and K/BB ratios. Although both stats involve the strikeout, they identify different aspects of a pitchers abilities. Instead of making generalized opinions based on years of observations, much like most humanities tend to do, I decided to take a more scientific approach and find correlations between pitching statistics.



These correlations are taken from 2009 pitchers with a minimum of 70IP on the season. The first striking revelation is the extremely low correlation between K rate and walk rate. It seems these two qualities in a pitcher are independent of each other. A guy like Steve Phillips may believe a strike out pitcher might be more wild causing an elevated walk rate. While a guy like Rick Sutcliffe may believe a superior strike out pitcher also has superior ability to the control the strike zone leading to a lower walk rate. Well, this year's data strongly suggests there is no overlap of K and BB within a population.

A high K rate is also associated with a lower batting average against when compared to high K/BB ratios. Clearly, lots of strikeouts makes it difficult for hitters to have the opportunity for base hits, however it is K/BB ratio that has a significantly stronger correlation to base runners allowed(WHIP).

I believe the thing to take away from this post is that a high K rate is obviously beneficial for a pitcher, but if their overall K/BB ratio lags behind due to a high walk rate it, it will most likely lead to an underachieving pitcher. We have seen many such examples such as Carlos and Victor Zambrano, Kerry Wood, Chad Guadan, Carlos Marmol, Jose Contreras, and Jonathan Sanchez just to name a few.