Baseball Knowledge 101: DIPS > ERA

While the final hours before the trade deadline slip away and the Astros continue to put their head in the sand (believing that acquiring Randy Wolf and LaTroy Hawkins makes us a play off contending team), instead of restocking the farm by selling everything they can, you can sit back and dig into the how's and why's of DIPS. You'll also learn why Tim Purpura is just a total idiot.

When we last checked in on pitching, we ran you through the how’s and why’s of ERA’s deficiencies. Evan had the harder of our two tasks in breaking down ERA vs. explaining DIPS. It’s easy to explain how DIPS works and why it is that their measures most accurately capture the true skill level of a pitcher’s performance through it’s methodology, but it’s incredibly difficult to explain why ERA is a faulty statistic in general, because there so many variables that are captured by ERA that are irrelevant (scorer bias) and luck dependent (LD%, HR/FB%, etc.). Today, I will try and bring you deeper into what I consider sabermetrics most valuable contribution to baseball: defense independent metrics (defense independent pitching, luck independent pitching, and fielding independent pitching). For reasons hopefully to explicated clearly below, these metrics all do a far better job of capturing the true skill and performance of a pitcher than ERA, W-L, single rate stats (K/9, BB/9, WHIP, etc.), or even the aforementioned Support-Neutral family of statistics. While rate stats (except for WHIP) accurately gage a singular skill of a pitcher, they don’t tell us about his entire skill set. ERA and W-L, as previously discussed, are poor, to down right awful, at gauging a pitcher’s skill level. Even the Support-Neutral family of statistics is still hampered by many of the same things that ERA is, because while it gives a better feel for how a single pitching performance by a pitcher helped his team stay in a game to win it, it can’t tell us whether that pitching performance was strong or weak based on the pitcher’s ability or a the variety of randomly varying factors that impact a pitching performance.

As alluded to by Evan, the vein of pitching-analysis we’re venturing down today was inspired by the BABIP/ERA phenomenon, first observed by Voros McCracken. In his original article on DIPS, Voros surmised that, “there is little if any difference among major-league pitchers in their ability to prevent hits on balls hit in the field of play." This bold statement has since been heavily amended, but can be restated as something akin to: Major-league pitchers have little control over their ability to prevent line-drives which heavily affects their BABIP, where as they show a significant ability to control GB, IF, and FB, they however show little ability to control the outcome of any batted-ball. I know that just took out 3/4 of the kinds of balls in play and then reassigned them to the pitcher’s responsibility category. Which given our treatment of BABIP last time seems either counter-intuitive or like we were lying. Hopefully I’ll be able to clear it up.

When originally proposed by Voros the first time, he labeled the following pitching categories defense independent:

BB K HBP IBB HR

Those are all categories which are truly defense independent statistics as only the pitcher can cause/allow them to occur. The first incarnation of DIPS worked by finding the rate at which these statistics occurred for a pitcher and then subtracting out how many batters faced would have walked, struck out, been hit, intentionally walked, or homered from the total number of batters faced. From there he broke down singles, doubles, triples, and outs for each pitcher and set the rate at which these occurred to the league average BABIP. He did this because, prior to further investigation by many different analysts, it seemed like BABIP truly was out of the pitcher’s control entirely. What he had left was the number of BB, K, HBP, HR, IBB, 1B, 2B, 3B, and outs for a pitcher that would have occurred all things equal. With that he assigned each event a run value (what they were, I’m not sure, but I imagine it was the standard BaseRuns) to then calculate the number of Runs Allowed by a pitcher with the new numbers. This would result in a DIPS ERA, which could really be thought of as a DIPS RAA (runs allowed average). The measurement is still somewhat valuable as a quick way to see whether an extreme ERA is valid or not and is now cited as FIP (fielding independent pitching).

Understandably this was controversial, because conventional baseball wisdom assumed pitchers could control hits allowed. In order to prove/disprove Voros’ assertion, the last seven years has seen a tremendous amount of research go into DIPS. The results have yielded a more nuanced understanding of the batter/pitcher match-up and the subsequent dividing line between pitching and defense.

As up to date as I have seen it, here is how DIPS is calculated to reflect the more nuanced truth that has come to light since Voros’ original proposition of BABIP as pure chance.

A pitcher is assigned a league average LD%, reflecting that statistically LD’s are uncontrollable according to year to year correlations (Source). This luck-less amount of line-drives are then subtracted from the pitchers’ number of batted-balls. Next, the rate at which a pitcher surrendered Ground balls, Infield-flies (IF), Outfield-flies (OF), and bunts. Then, to correct for the role that defense plays in each of the kinds of batted balls, league average results are applied to them. So if 30 of GB% fall singles and the pitcher in question, after the adjustments, was given 100 GB’s, then he’d be credited for 30 singles. The resulting 70 would have the same thing done for 2B, 3B, HR, outs, double plays, and reached on error (ROE). The same for his adjusted number of LD, IF, OF, and bunts. With the pitcher’s new line of corrected K’s, BB’s, IBB’s, HBP, 1B, 2B, 3B, HR, ROE, and outs, a defense independent Runs Allowed is then calculated by assigning a run value to each event via BaseRuns. This methodology is DIPS 3.0.

The question that remains (if you’re still even reading) is why is it valid to count LD% as luck, but GB% and IF% and OF% as pitching skill? To this end, I will stick with Mitchel Litchman’s study of the year to year correlation of differnt types of balls in play to bolster DIPS 3.0’s methodology. Litchman studied pitchers, over a 10 year period (1993-2002), who changed teams to study their batted-ball data. Why those who changed teams? In Litchman’s words it is so “we have essentially removed the home park and defensive influences from the correlations.” His study involved over 100 pitchers who had a minimum of 300 balls in play in the consecutive seasons -- a large sample size to say the least. He than ran the year to year correlation on the different kinds of batted balls. His results indicated that pitchers show absolutely no control over LD’s, but exhibited a good degree of consistency (i.e. control) in IF, OF, and GB (each factor was listed from least amount of control to strongest.

So hopefully that clears up why it is that when we calculate a DIPS, the LD% is automatically league average, and then the pitchers own individual rate of surrendering IF, OF, and GB is left alone. However there is one issue that probably is still lingering in your mind. If GB, IF, and OF are under the control of a pitcher then why does DIPS 3.0 then assign league average rates of results to each batted-ball type (i.e. Why say if a GB goes for a single a league average 57% of the time and a pitcher surrendered 100 GB, therefore 57 defense independent GB singles, instead of however many singles he actually surrendered on GB?)? Again, we have to look back to Litchman who determined through the same study I’ve already discussed, that while pitchers show the ability to control what kinds of batted balls they allow, they show almost no control over the rate at which those balls in play go for outs. If pitchers cannot control the rate at which their batted balls go for outs, then they cannot reasonably be expected to control the outcome of the balls in play that do not go for outs. Thus, DIPS 3.0 corrects that.

Alright, we’ve come a long way. What we’ve covered so far, is that from the initial assertion that BABIP is completely a factor of luck (that the only pitcher/batter outcomes a pitcher determines is BB, K, IBB, and HBP), further research revealed that pitchers can control the kinds of balls in play they allow, just not there outcomes. I wouldn’t doubt that you’re wondering: “What the hell does that even mean, aren’t you saying the same thing which just some qualifiers?” Ok, probably not thinking that, but I did. While the outcome of batted balls are out of a pitcher’s hands, except for line-drives they can control the type of ball put in play. Since certain kinds of batted balls go for differing levels of hits/outs more often than others, pitcher’s can -- in a sense -- control their destinies. All they can do however is increase or decrease the probability that ball in play goes for an out, because (as I noted earlier) Litchman’s work indicates that increasing or decreasing outs on balls in play is not a skill pitcher’s possess. Instead, it is one that the defense backing him possess. Thus, DIPS corrects the outcomes of batted-ball types to league average, in order to neutralize the role that defense plays in a pitcher’s skill domain.

What DIPS leaves a GM, Manager, Scout, Fantasy Baseball Player, or Fan with is a metric that captures the actual skill level of the pitcher. It has been adjusted to remove luck and the abilities of others from obscuring the work of a pitcher. How can we be sure of this? Because, DIPS 3.0 has a correlation of .8 with the next year’s ERA, where as ERA has a year-to-year correlation of .374 with itself. A word of caution to DIPS in any shape or form is that they are not an explanatory stat unless you dig deeper into to why there is a differential between ERA and DIPS. Although it is a predictive stat, it is only truly useful at predicting pitchers ERA given the proper context for their DIPS-ERA differential. Things like injuries, command problems, or poor pitch sequencing can all serve to artificially skew the DIPS-ERA differential while not being the result of chance. On the whole though, looking at pitcher’s with positive DIPS-ERA differentials portends to poor future performance. One $120 million oversight by an organization refusing to employ sabermetric analysis in player evaluation is the infamous Barry Zito. In his contract year, Zito posted a 3.83 ERA, but it was deflated largely due to a ridiculous 78.5% LOB%, which was reflect in his 4.65 DIPS. Brian Sabean could and should have easily been able to observe that Zito’s continued success depended on strong defense, as both his IF% had fell of the table as well as a steadily decling K/9, and that such a pitcher, no matter his past performance levels, does not warrant a $120 million contract.

Now before Astros fans start ridiculing the Giants, let’s not forget December 2006, when Jason Jennings came to town. Purpura traded for Jennings off the strength of his 2006 3.78 which for Coors Field is probably like saying Roger Clemens had a 1.87 ERA in 2005. However it, like Zito’s ERA, was deflated due to a totally unsustanable HR rate, which is represented in his 2006 DIPS of 4.61. Would anybody else like to have Willy T, Jason Hirsch or Taylor Bucholtz still in light of this? (DIPS 3.0 Source, you have to go to the bottom and open the spread sheet). **Side Note, you could do the exact same thing with Woody Williams, 2006 ERA: 3.65, 2006: DIPS: 5.03...eeesssshhh** It works the other way too, the quickest example I could find was Freddy Garcia from 2004-2005. 2004 saw him post a dismal 4.64 ERA, whereas DIPS 3.0 had him at a 3.54. In 2005, Garcia posted 3.54 ERA. Not too shabby DIPS 3.0.

Ok, that was exhaustive for me and I’m sure for you. We’ll save LIPS for next time and jam it in with pitch/fx, which actually makes a good deal of sense to do. Addendum number two the syllabus should read: “DIPS > ERA” and “The Next Frontier: LIPS and pitch/fx.

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Baseball Knowledge 101, cont'd: ERA and Rate Stats

In our last installment, Stephen detailed why a pitcher’s W-L record is not necessarily indicative of their relative merit as a player. Indeed, rare is the case where a pitcher’s record runs parallel to their on field performance. ERA is often cited as a secondary indicator of a pitcher’s value, to be looked at after W-L. True, it is a better barometer of a pitcher’s success than W-L for one big reason: it isolates the performance of just the pitcher in question, not the team as a whole. Whereas entire teams win and lose games, ERA takes the team out of the equation as well as those runs that score due to errors.

Its improvements over W/L record notwithstanding, ERA has its own share of blemishes, the majority of which have to do with the amount of data that is not included in calculating it. To start off with, ERA obviously only takes into account earned runs. This is important because no pitcher, not a starter or reliever, is held accountable for any unearned run. They sort of just fall into a baseball black hole, joining the likes of Derek Bell and Brian L. Hunter, never to be heard from again. The whole point of statistics is to allow baseball teams, fans and any other inquisitive person to take an objective evaluation of a player. The error is a sometimes arbitrarily arrived at number, handed down by an official scorer at the home ballpark (paid and employed by the home team). Already, a small chink in the armor of this venerable stat can be seen. To paraphrase the great Bill James, just think about where all the focus of anyone watching baseball is most of the time: the batter and the pitcher. The official scorer, like the guy spilling Budweiser in front of you at the park, isn’t focusing on how exactly Miguel Tejada has shifted just prior to the pitch in an attempt to get to a ball in play. In mere fractions of a second from batted ball to fielder, the official scorer gets to determine whether the ball in play and the resulting defensive attempt would have customarily resulted in a defensive stop or out. If he says yes, then the pitcher is no longer accountable for that run. Lots of human error is at play in this beloved statistic. Additionally, ERAs in certain ballparks cannot be compared to ERAs in other ballparks (or years). There is a lot of difference between pitch movement, the physical characteristics of the ball, and other factors that make balls in play easier or harder to turn into outs or hits. Further, runs credited to ERA are sometimes scored against the starter, but allowed to score by relief pitchers who weren't “responsible” for them being on in the first place -- meaning that starter had no say in preventing them from scoring, but is being tagged none the less. Finally, sample size makes ERA a less than worthy statistic when comparing a 200 IP starter against a 60 IP closer. These quibbles are of great importance in figuring out a way to analyze a pitcher’s performance.

ERA was created in an attempt to separate defense and pitching. This is one of the reasons why it’s still a semi-useful statistic. With the influx of sabermetricians and statistically minded fans and executives, new ways of evaluating a pitcher’s performance have been developed. Support-Neutral, Defensive-Independent and Fielding-Independent metrics go beyond ERA to give a more in-depth analysis of a pitcher’s performance. By in depth, I mean taking a look at what a pitcher can control, even more than ERA can. Understanding BABIP is a starting point for this. The basic premise is pretty simple, yet is pretty startling for any baseball fan not familiar with sabermetrics. In essence, BABIP (batting average on balls put into play) demonstrates the relative amount of luck that goes into balls in play being converted for outs. Consider that league average BABIP is generally reported to be with .290 and .300 and then take a look at this chart and its reported BABIP for pitchers. It’s all over the place, because even half way through a baseball season, luck hasn’t evened out for everyone.

To create a more concrete link to why ERA is a weak(er) stat because of the impact that BABIP has on it, let's look further at the batter-pitcher match-up. The “action” of a batter-pitcher match-up can be separated into two parts -- the first of which is the act of the pitcher delivering the ball to the hitter. Without a doubt, the pitcher has a great deal of control over this -- what pitch he throws, the velocity, spin, location, and deception are all within his ability to alter. The second part of this interaction begins after the hitter makes contact with the bat. This is the part that both hitter and pitcher have a relatively small impact on- other than as defender and base-runner. What the other 8 fielders do to the hitters’ ball-in play are out of their hands. Before Stephen and I learned about BABIP, we’d often be watching an Astros game where Jack Wilson would hit a little duck-snort over Adam Everett’s head for a single. Half an inning later, Lance Berkman would line out to Adam LaRoche. I’d turn to him and say, “typical Astros luck.” Well, I was partially right- it was obviously bad luck, which deep down I knew wasn’t just an Astros related phenomenon. What I didn’t know what just how much luck went into the batter-pitcher match-up.

So what does BABIP have to do with ERA? Well, ERA measures the runs that a pitcher is responsible for allowing to score. However, if a pitcher has very weak control over everything in a PA besides K, BB, and HBP, then how valuable of a statistic can it be in accessing the pitcher’s performance? The chart I asked you to click to earlier, which displayed randomly varied BABIPs and it was in an effort to drive home the point that BABIPs vary for really no discernable reason. If balls in play are unluckily landing for hits more often than they should, then we would expect a pitcher’s ERA to suffer disproportionately from his true skill-level or vice-versa if BABIP is extremely low.

Now, there is a heaping amount of gray area that go into saying BABIP is largely luck, but we’ll discuss those intimately in the “DIPS, LIPS, and FIP” next time. These measures seek to determine how well a pitcher pitched in the areas of a pitcher’s performance that they have an inordinate amount of control over: pitch speed, location and homeruns, but we’ll give you a small preview.

Hidden within BABIP are a few characteristics that need be mentioned. Earlier in this post, I attempted to impress upon the fact that BABIP itself is an essentially random statistic. Well, it is, and it isn’t. What is not random about it is the less than a second’s worth of time between the ball leaving the pitcher’s hand before either being hit by the batter, or caught by the catcher. Factors such as where the ball is pitched relative to the strike-zone, how many pitches the pitcher has in his repertoire, and how often the pitcher gets ahead or behind in the count are factors that all pitchers have under their immediate control and these all impact the degree of luck associated with BABIP -- because in the end these afformentioned factors make a pitched ball easier or harder to make solid contact with for the hitter. The further sabmetricians have probed the batted-ball issue, the more they have come to believe that LD% is almost completely a factor of luck. However, buregoning evidence suggests that he can control ground balls, and outfield flys and in-field flys. This seems reasonable given GB% has a year to year correlation of .807, statisitically significant, indicating it is repeatable skill.(Source, also click for explanation of correlation if your fuzzy on it).

Further influencing the degree to which BABIP plays a part in ERA are the skill sets of K/batter and BB/batter, which carry year to year correlations of .790 and .676 respectively (Source). These two skill sets are statstically significant and again indicate that their outcome is based on the pitchers skill. To the extent to which a pitcher limits balls in play by walking batters and striking out batters, he influence the amount of luck that will enter into his ERA. This is all the more reason why the aforementioned means of analysis (support neutral wins and losses, defensive independent pitching statistics, etc.) are important and valuable. Predictability is ideal for a franchise in evaluating a player, because they want to know ahead of time how a player will not only perform next season, but in seasons multiple years into the future, or whether past performances have been the result of skill or luck. Understanding, for instance, that ground-ball pitchersare overvalued in their ERA numbers because more unearned runs score when groundball pitchers are on the mound than do fly-ball pitchers is very important. Why? Because, as mentioned earlier, at the end of the game, they don’t subtract UER from the total score to determine the winner. We hope we demonstrated that so much of what goes into turning out an ERA does not accurately reflect the performance skill of a pitcher. Much of what ERA reports is context dependent on the “type” of pitcher, the defense backing him, the skill of the bull pen, and a measurable degree of luck; making ERA uninformative and often misleading. Support-neutral and Defense-independent statistics do a better job of capturing what is really happening on the baseball diamond -- something that ERA cannot do.

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Baseball Knowledge 101 - Wins (Suck)

We’re tackling Wins as our first stop in Baseball Knowledge 101. We had planned on including the full line from the syllabus: “Wins, ERA, and Rate Stats,” but quickly realized that these could get ugly and dense due to the quality and depth we wish to treat each subject with. So addendum one to the syllabus finds “Wins, ERA, and Rate Stats,” into two separate articles: “Wins (Suck)” and “ERA and Rate Stats”

Traditional pitching statistics are pretty much useless when it comes to evaluating and helping us predict the performance of a pitcher – especially wins. To begin, let’s take a more detailed look at what goes into making a pitcher successful in the first place. The pitcher is one of nine defensive players on the field. He is responsible for starting play by standing 60 ft. 6 in. away from the batter and delivering the ball to him. His goal is to get the batter out. He can throw strikes that are actually strikes, but his movement or speed fool the hitter into missing the strike. He can throw a strike that isn’t a strike, but again, his movement could fool the hitter or it could be a deceptive arm-angle that fools the hitter. The hitter could take the pitch that pitcher pitched and put it in play. The hitter might get good contact through a variety of variables all coming together and he could hit a solid line drive through the gap and notch a double. Perhaps on that play though, the center fielder had cheated just a little and was able to make a Sports Center worthy diving catch to make the ball put in play, an out. Of course the hitter could have just meekly grounded to the SS, resulting in an easy 6-3 ground out. Yet, the SS could have a momentary lapse in concentration, perhaps he’s having marital problems or just really has to pee, and as a result of whatever is on his mind, he bobbles the ball and the meek ground ball turns into an E6. The pitcher, in the opinion of the official scorer, probably earned an on that batter, but because the SS had to pee, now has no outs, and a runner on first base.

I’m not going to go back and count, but there are a lot of variables that going into a pitcher getting a single batter out. A lot of which end as soon as the pitcher releases the ball from his hands. So it makes little sense that we put so much stock into a pitcher’s W-L record. Just last year, the Cy-Young race was just as controversial as a West African presidential election, because 20 game winner Josh Beckett trumped 19 game winner CC Sabathia. In 241 IP Sabathia struck out 209 while only walking 37. He was responsible for almost a 1/3 of all of his outs. Beckett threw 200.7 IP Beckett struck out 194 batters while walking 40. Again responsible for about 1/3 of his outs. The difference I instantly see is that Sabathia and Beckett were clearly two of the best in the business, yet the Red Sox had to use a lesser bull pen arm in 40.3 innings more then the Indians did. Sabathia is more valuable than Beckett in those terms alone. Yet, pundits everywhere were crying afoul because of that one win that separated them.

So what goes into to a pitcher winning a game? Well, take that first paragraph and multiply it up to as many as 50 times. Only sprinkle in fatigue for the pitcher and the ability of the hitter to better recognize a pitcher’s guile as the game progresses. Also, you have to have your team score more runs than the other team, before you exit the game, and then trust your lead in the hands as up to as many as five different relievers – other wise you’re heading for a no decision. In that exercise, how much responsibility does a pitcher have for a win? Especially the run-scoring for the two AL pitchers who never hit. Well, in 2007 Sabathia’s Indians provided him 5.10 Runs/9 in his starts. That’s not how many runs that got in the innings while he the pitcher of records, but it’s a best I can do. Josh Beckett, of 20 Win glory, had 6.42 Runs/9 in his starts from the Red Sox. Meaning that Beckett didn’t even have to be as good to earn a win as Sabathia did, but he could only muster one more win.

This doesn’t even to begin to say who had the better bullpen support. We’ll skip the nuances of measuring that for now, but it’s pretty straight forward. How many times can we recall Oscar Villareal blowing a lead this year? Or remember the time when Wesley Wright came in a game with 3 on and 1 out, but got us out of the inning with only one run given up? He converted a 2.42 Run Expectancy into a 1 run performance and saved 1.42 runs from scoring. Those 1.42 runs weren’t even his responsibility, but he saved them anyway. That’s the level of inane-ness that evaluating starting pitchers on wins is provided when you focus it through the lens of bull-pen support.

So a Win is certainly a very poor measure of how to evaluate a pitcher. I believe I’ve made a case for it, and I hope it makes sense to you. So how then do we then measure a pitcher’s performance if Wins an inept tool? To that effect, a very valid tool developed by Baseball Prospectus is the Support-Neutral Statistics. “The Support-Neutral name comes from the fact that [Baseball Prospectus] is removing, or neutralizing, the variability of different levels of run support and bull-pen support...This gives a truer sense of how well a pitcher performed, without the distortions of offensive and defensive support.” (Baseball Between the Numbers: Why Everything You Know about the Game is Wrong, 2007 pg. 52). It works like this: say Roger Clemens went 7 IP of shut out baseball, BPro would then take that performance and assign it to a hypothetical league-average team and see how many times a league average team would win given that performance. It turns out, that is 85% of the time. So Roger Clemens earns .85 SNW and .15 of a SNL. These are the same things as the E(W) we presented in our statistical recaps earlier this year. While they are not the perfect tool for analyzing a pitcher’s performance, they certainly come closer to analyzing how much of a pitcher’s performance went into earning a win. Even there though, there are limitations. These will be discussed in DIPS, LIPS, and FIP section.

So, 7IP of shut out baseball is actually worth about .85 of win, if we exclude defense backing the pitcher from this analysis. Now, I think every Astros fans can hearken back to 2005, when Roger Clemens went 13-8 on the strength of a 1.87 ERA. How could he have possibly gone 13-8 with that ERA? Because the Astros only averaged 3.43 Runs/9 in his starts. Roger Clemens missed out on the Cy-Young that year, in spite of the fact that he was clearly the best pitcher in baseball, because he was deficient in an asinine and almost entirely luck based statistic. So the next time you here Steve Philips, Joe Morgan, or Ed Wade talking about how many decisions a pitcher has won as a basis for defending an acquisition, you should bristle with indignation. If that’s the only good thing they can say about a pitcher, then they’re telling you he’s effectively worthless, but he sure did get a lot help from the bats and gloves backing him. Just to make it concrete. Knowing a pitcher’s winning percentage has a year to year correlation of .202 in predicting his future performance. For those of you have forgotten your Stats 101 (I had to Wikipedia it so don’t feel too bad) Correlation measures the linear relationship between two variables. In this case Win percentage one year, to the next. Correlation coefficients range from -1 to 1. -1 means that there is an opposite relationship, high one year predicts low the next year. 0 means the two variables are completely unrelated and knowing one tells you nothing about the others. 1 means that there is a lot of stability in predicting the variable from year to year, given the first (click the .202 link for better explanation then what I just paraphrased). In general Correlation co-efficient less than .3 any direction are weak and pretty meaningless. .7 marks the statistically significant level, but that won’t be important until later.

Next time (when we look at pitchers again), we’ll look at ERA and how valuable of a tool it is or is not at determining a pitchers performance and why looking at a pitcher’s rates stats paints a much better picture.

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Examining the Wizard: Long Balls and Luck

**UPDATE - Links Fixed, I hate Blogger**

So I found another tool to throw at the Roy Oswalt mystery. It’s called Hit Tracker and it’s an incredible tool. Basically, it corrects for wind, atmospherics, and probably some more stuff, to say how far the ball would have traveled. It then categorizes HR by the following categories:

No Doubters - the HR cleared the fence by 20 vertical feet and landed at least 50 feet past the fence.

Just Enough - the HR cleared the fence by less than 10 vertical feet and landed less than once fence height length beyond the fence. It’s just snuck out.

Lucky - the HR wouldn’t have gotten out if it had been hit on 70 degree, calm day.

Plenty - Not a Just Enough or No Doubter HR.

So with that in mind, lets look at the 18 HR that Roy Oswalt has allowed, because, as we noted, he’s been especially unlucky with the HR ball this year. Given that we’re chalking some of this up to luck, we should expect him to have a fair amount of HR due to luck (i.e. Just Enoughs or Lucky HRs).

Just Enoughs: 3 HR

Plenty but Lucky: 2

Just Enoughs that were Lucky: 1

So, of the 18 HR balls that Roy Oswalt has surrendered, 6 could have just as easily stayed in the park if there was the slightest change in any variable. While this information doesn’t change the fact that Roy has struggled or explain why he has, it does provide credence to the idea that his HR/FB rate is inflated due to luck. Hopefully a Roy Oswalt with a healthy hip abductor and his luck/statistical randomness due to correct will emerge and be an effective Roy Oswalt in the 2nd Half. Perhaps one that decides to wave his no trade clause in the off-season and nets us some top prospects/major league ready players, too.

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HALF WAY!!

Back in the day, when I fancied myself a pseudo athlete (I ran track and cross country and to this day, I insist they're not sports), I remember that Matt Munoz, the best runner on the team, would scream, "HALF WAY!!" in the middle of long-runs and intervals. While I don't know for sure why exactly he did it, it usually inspired two emotions in me: fear or determination. Whether it was fear or determination depended on how I was doing at that point in the run/workout.

So, the Astros are, "HALF WAY!!" plus one, through their 2008 season. My question is, should this inspire fear or determination in us? Let's take stock of our present and then disect the past, to discuss the future.

Yesterday afternoon, we finished off our third straight series win over the AL. Two series victories over the top team in the AL East is a feat that seemed impossible as recently as two weeks ago when the team was getting swept out of Baltimore. However incredible the last week has been, the fact is that the Astros have been a disappointment for 50% of the 2008 season. A 39-43 disappointment, to be exact. What follows is a break down of some key statistics through the first 82 games to analyze how we’ve gotten to where we are. Hopefully, these will paint a picture of what we might expect for the next 80 games we play.

Here's the quick and dirty of where we rank with our stats in terms of the rest of the National League with our offense:

Tied for 5th in BA
15 (Second to Last) in OBP
9th in OPS

Next, a chart of how our hitters (pitchers have been excluded) have performed at the plate through the first 81:



The last time we took a meaningful look at the Astros numbers at the team level, was May 13th. We were tearing it up, and everyone in baseball loved us. I urged for cautious optimism, because the only aspect offensively that we were doing exceptionally well at was hitting .292 with men in scoring position. As you can see, we're now actually hitting worse, on average, with men in scoring position then we are overall. Which goes a long way to explain our absymal month of June. Our ISO has also totally fallen off, indicating that our bats just are not generating the power that they once were. A 19% line drive percentage coupled with a BABIP below .300 should inspire some optimism for an increase in offensive production for the second half. Carlos Lee in particular has a rather low BABIP, but a respectable 18.2% LDP, we're begining to see his BABIP fall in line with his LD% even, and with the revamped line-up it should help us produce more than the 2 or 3 runs a game we did for most of June. The absurdly low OBP is still troubling. As long as it stay's low, we'll have to rely on hitting well in with men in scoring position, because our opportunities to produce runs will be fleating. All in all, things should get better in the offensive department, but it won't be anything to write home about.


To the pitching:



What should jump off the stat sheet is the pitching staff's ridiculous HR/RB ratio. A majority of Astros pitchers have a tendency to induce a great deal of fly balls (probably wasn't the ideal rotation to create for MMP), but when fifteen percent of them are leaving the yard, you have to just shake your head. There are two ways to look at this development. While it's not as if their BABIP is just outlandishly high, a LD% of 20% is startling to see, especially when it's coupled with our HR/FB. Opposing hitters are getting in some good swings, which is most likely apparent to anyone who follows the Astros. More important than the HR's perhaps, are the line drives, which have a greater chance of going for extra bases than do ground balls or fly balls, thus putting runners in scoring position with relative frequency. However, and oddly enough, the Astros staff has the second best LOB% at 74%. Given that we should see the LD% drop down a tick and the FB stay in the yard more often as well, there's room for the hope that our pitching should improve a pretty good deal in the second half. This definitely surprised me.

As we noted last time, the defense has been phenomenal this year, and certainly goes a long way in explaining why our pitchers' LOB% is so good. We are currently 3rd RZR with an .852; surprisingly (to me at least) 2nd in infield RZR with an .815. If the defense holds up it's in the of the bargain, and the LD% and HR/FB rate of our pitchers levels off, the result should be some pretty well pitched games.

Taking stock of our first 81 games has lead to these insights:

1.) Our offense will struggle to consistently put runs on the board because they're just not getting on base frequently enough, but with a big-bat in Carlos Lee due for a resurgence, we should do better than we have in June. Just don't expect a repeat of May by any stretch.

2.) Though on pace to set all kinds of records with our HR's allowed, our pitching staff has been one of the best at stranding their base runners. With the possibility that LD's will decrease ever so slightly and the expectation that HR/FB should diminish a significant amount, we should see a lot fewer runs posted by our oppents. Especially, given that...

3.) We have a great defense, especially in the in-field and CF and RF too, backing our hurlers.

So, "HALF-WAY," shouldn't inspire fear in us going further in terms of our ability to win some more ball games. However, it also shouldn't necessarily inspire determination or an excess of optimism going foward. We've dug ourselves a large hole to climb out of in the NL Central and the Wild Card race. While this franchise has over come some long odds, we don't seem to be made of the caliber of stuff that overcame them in 2005. That we should do better moving forward does inspire fear in me, because it will probably convince Drayton McLane to stay the course with this team -- or worse, try to acquire some missing piece. We look like a team that might be able to put up a good fight to reach .500, but as fans we have to ask ourselves, is that what we want? Is obtaining a respectable, but hardly noteworthy, amount of wins worth trying to build for a successful, stable future? I say, not at all.

***Note: Evan contributed a significant amount to this, won't be credited in the by-line, but deserves equal share of either the props or criticism (well maybe just the criticism) too.***

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Examining the Wizard: Roy Oswalt, a Case Study in Luck

Today, I was excited to see this article from The Hardball Times. For those of you who are too lazy to click the link and read the article, I’ll quickly summarize. The article looked at pitchers who were the unluckiest so far this season; measuring their rate stats against league averages to define unlucky. Astros fans should not be surprised to find out that Roy Oswalt was the most unlucky pitcher in terms of HR/FB (Home Runs per Fly Ball), posting an absolutely astounding 21.05% HR/FB so far this season. The article by, Derek Carty, goes on to normalize Oswalt’s (and the other pitchers listed in the article’s) outlandish rates stats back to league average levels, plug it into a very complex formula, and determine Oswalt (and company’s) LIPS ERA (Luck Independent ERA). Carty finds that by normalizing Roy Oswalt’s HR/FB back to league-average, Roy Oswalt owns a LIPS ERA of 4.08. Not an outstanding ERA, but I don’t think any Astros fan would quibble with having Roy Oswalt’s ERA be 1.30 earned runs lower.

The LIPS ERA concept works, because by-in-large, things like BABIP, HR/FB, and LD% are largely beyond the pitcher’s control (See above linked articles and this one for supporting evidence). However, what does the knowledge that Roy Oswalt has been unlucky tell Astros fans, or fantasy owners for that matter, about what to expect? Thankfully, Derek Carty again, provides some insight into a favored term bandied on this blog “the law of averages” or “regression to the mean”. Once again, for those to lazy to click the link, essentially we can expect Roy Oswalt to surrender HR/FB at a rate consistent with his career levels from here on out, meaning somewhere around 9% HR/FB, ( he’s never exceeded 12.9%).

To dig further than just discussions of luck and regression to the mean, I was graciously given Roy Oswalt’s pitch-result data from the talented and majestic Josh Kalk. Honestly, I cannot thank him enough for helping me, who knows absolutely nothing about database coding, for providing this data. While I had just about anything you’d ever want to know (and a lot you wouldn’t about) Roy Oswalt’s every pitch in 2008; save his last two starts (tonight’s start included) due to when I actually obtained the info. I’ve isolated only the pitches that resulted in HR, since that’s what we’re looking at (click here for an explanation of the data):



Quickly, here are the pitch averages for all of the available data on Roy Oswalt for 2007:



And then his 2008 pitch averages:



Clearly, movement is down on his Fastball (FB) and slider this year. Velocity does not seem to be the issue for Roy on his fastball in terms of HR allowed either. Of the 11 FB’s that turned into HR in 2008 for Roy, the average speed was 93.23 MPH (min: 91.62 max: 95.61), so that’s clearly not the issues as evident by just looking at his 2007 average. His movement on the FB’s that turned into HR: -4.09 in. X (min: -1.44 in. max: -8.16); 6.00 in. Y (min: 1.99 in. max: 10.85). There’s not as much life on the FB’s that became HR this year by comparison to Roy Oswalt’s 2007 numbers and on the whole his movement is just down. This probably explains his overall decline in strikeout related rate stats, but I don’t know that it really explains why he’s just getting crushed so much. However, I get the feeling that 11 FB's is just far to small of a sample size to say anything meaningful about. In fact if anyone can see any clear trait from the FB velocity or movement from the chart that indicates he's doing something that's allowing his HR spike, please speak up.

Note: I’m ignoring the three sliders, because his slider is just God awful this year, but not the issue apparently.

In my last attempt to decipher the enigma that is Roy Oswalt in 2008, I cited the fact that his release point seems excessively bunched, most likely in an effort not to tip his pitches, thus causing him to lose life on his pitches. While my initial conclusion from that observation was that it must be his slider that is getting pounded was wrong, I none the less stand by the observation as providing insight into his struggles to date.

Tonight, however, I am offering another observation. Looking back at Roy Oswalt’s HR pitches, all of but three of the fourteen pitches have one thing in common: men on base. While it is clearly a limited sample size, perhaps either pitching from the stretch, or the distraction of holding runners is causing Roy to throw pitches that are a bit more crushable. Food for thought at least. While it’s not an earth shattering observation, the pitch/fx data of his HR pitches revealed no other apparent trend. Oddly though, his 50/50 split of RHB/LHB going yard is elevated for his career 75/53 RHB/LHB HR split. There wasn’t a meaningful home/road split for the HR’s either.

Having spent the entirety of the game researching and writing this article, we saw some dominant pitching from Roy Oswalt tonight, but the Ryan Braun long ball makes it 17 HR the season. During the post game so far I’ve heard a lot of discussion centering around Roy Oswalt trying to pitch to contact more vs. trying to strike guys out. Our first attempt to discern what was ailing Roy Oswalt revealed little in the way of evidence that Roy was attempting to pitch to contact from his numbers, but there are probably short comings in trying to prove or disprove pitching philosophy from limited statistics. After an exhaustive combing of pitch/fx data, I’m left scratching my head. It seems that although pitch/fx is an incredible tool that is sure to further revolutionize baseball analysis, it also seems to support the assertion that pitchers have little control over their BABIP, DIPS, HR/FB, LD%, etc. If this is the case, we can only have one logical expectation of Roy Oswalt from here on out: that he should pitch in-line with his career numbers. Astros fans should rejoice and fantasy owners should do what they can to acquire him.

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Examing the Wizard: The May Report

In April, we looked at Roy Oswalts’ struggles and determined that it wasn’t his fastball’s velocity that was hurting him, it was that his curve ball, just simply wasn’t curving. Well over a month has passed, and Roy Oswalt is still sporting a 5.61 ERA. While his ERA is inflated, his K-related rate stats have been solid: 6.9 K/9, 2.94 K/BB. It's the hits and the HR that's are killing him: 11.08 H/9 and 1.96 HR/9.

So, what’s changed? Last time we noted that his curve was flat. Looking again at his pitch/fx data from 2007 and 2008 we can see that there some disticnt changes to Roy’s pitches. The fast ball is 1/2 MPH slower, broke 9.51" down in 2007, but only 7.51" down in 2008. That's a significant amount of elevation to his fastaball. Roy's curve is now breaking as far down as it did 2007 (the red flag we sounded in our last post), but only moving away from RHB 4.33", where as in 2007 it broke 6.69 away, a 2.33" difference. So it's staying closer to RHB and not getting in as much on LHB, both if which makes easier to get wood on. Both of these 2" changes are very much the differnce between a swinging strike or a meekly hit ball, and an absolutely crushed ball. His slider has been even worse. In 2007 it broke 3.74" away from a RHB while dropping 2.46". However, in 2008 it's only breaking 1.86" away from RHB and only dropping 1.78" down -- I believe the term is hanging slider. Yet he’s throwing it at a much higher percentage, 17% this year compared to 14% in 2007. It’s an absolutely crushable pitch, and it might explain his unprecedented 15 HR surrendered.

In attempting to explain why it is that his pitches aren’t breaking as well as the used to, we’ve discerned a small, but perhaps meaninful difference in his release point.

2007 Release Points:


2008 Release Points:



It appears that, perhaps, in an effort not to tip his pitches, Roy is trying keep his release point constant. Our guess is that by tightening it release point up, he’s losing life from his pitches.

So there you go, impress your friends and family with your new found knowledge.

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The Astros, They're So Hot Right Now

Incase my lame movie reference failed, it's Mugatu from Zoolander. Ok, Pop-culture references will be shelved now. For we college students, it's officially summer and the Astros have continued sizzle--big time. Lance is setting all sorts of records for his streak and thus far has exhibited no signs of cooling off, though a nagging leg injury could spell cooler temperatures for Lance. While Lance has been the main attraction with his bat, we should not overlook the fact that Lance has been, to date, the best defensive first baseman in all of MLB, with an outstanding RZR of .926. Yes, not only has Lance hit better than everyone in MLB, he's also played better defense than anyone at his position, including the much lauded Albert Pujols (the guy who won the gold glove last year). Right now, it appears that the NL MVP award is a two man race between Berkman and Utley, however, it is only mid-May, but an exciting prospect none-the-less.

However, while we could analyze Lance's bat and glove all day, the thing I want to focus on today, is the Astros as a team. We've done a few 10-Game Recaps, trying to analyze the changes in key stats that allow us to predict where the Astros fortunes might end up. These, however, have been pretty skin deep, with a focus on Offense and pitching only. So today, I'm going to attempt to break down the Astros as a Team, in lieu of doing another 10 Game Recap tomorrow, as they seem to have a very tepid response so far. I'm using stats available from the Hard Ball Times, an excellent site that provides a treasure trove of statistics, research, and analysis for free.

Courtesy of the Hardball Times' Team Reports, a look at the Astros record in terms of XW-L reveals that Astros are not a product of luck and their 22-17 record is in line with their runs scored/allowed. This good news, but looking at the Cubs and Cardinals record is a mixed bag of news. The Good News: The Cardinals are 1 game ahead of their XW-L, and in general seem to be due to come back to earth, and probably already are. That fact puts the Astros in 2nd place in the NL Central. However, the Bad News: the Cubs are 2 games below their XW-L, and should instead be at 25-13, making us 3.5 games behind the NL Central leader is hypothetical terms.

Breaking down the offense, we can see that the Astros are improving their OBP, but are still below league average with .321 mark, but by being 5th in the NL in slugging (.422) they've managed to post a league average OPS of .743, and keep the offense moving, simply by hitting the tar out of the baseball. While OBP is down, it is interesting to note that the Astros are 7th in the NL (and exactly league average) at P/PA (pitches per plate appearance) 3.82 P/PA. That's a pretty good rate and portends to either a higher BB% or is just a indication that they seem to have be able work the count, waiting for the right pitch. Either way, it assuages fears that our offense will collapse. Perhaps cautionary, the 'Stros have hit .292 with RISP and only .265 overall. Maybe they're exhibiting clutchness or it could be harbinger of a deflating offense unless the hits keep coming when we have men on.

The one thing that we have overlooked this year when talking about pitching, is how much this team is getting killed by the long ball. We have well above average K/9 (7.0), better than average BB/9 (3.3), and are league average in GB% (44%) and LD% (19%), we've even stranded more runners than any other pitching staff in the league with a LOB% of 77%, but when it comes to HR/8 we're tops with 1.3 HR/9. Correlated to that, we also lead the league in .SLG allowed with .453, well above the league average of .408. I'm at a loss to explain the HR's, because we have excellent rate stats that indicate strong control. I guess when we're making mistakes, we're just getting punished for them big time. I'd imagine that this has to be a fluke of some sort, and via mechanics being corrected or luck evening out, will drop. As such, given our strong rate stats, the staff appears to be much better than expected so far and due for some improvement in the ERA department.

Finally, and what I feel is the most important part of this team that has been overlooked, is their defense. The team owns a .847 RZR, which is second in the NL, second only to the Cardinals. It's been outstanding so far, especially given all the pre-season doubts about Tejada's glove, Bourn's maturity in the field, and Carlos' waist-line. Speaking of Lee and Bourn, consider this the fact that Astros own an above average Out-Field RZR in the NL with a .910, while having the second worst LFer (Lee, RZR of .804). The infield is tied for second in the NL with an RZR of .810, second again to the Cardinals. Over the off-season, we observed a few Astros-centric blogs, and one in particular, that chastised this teams defense over and over again. Their main fears were that Lance was a bad 1B, Tejada would look like Carlos Lee at SS, and that the hot corner would be devoid of anything you could begin to call adequate defense. Tejada has posted a .873 RZR (good for 3rd in the NL behind the injured Tulowitzki and the Brave’s Yunel Escobar), Lance, as we already mentioned is the best defensive 1B in all of baseball, and the hot corner has been average (Wigginton .711) to above average (Blum .756).

So here’s the quick and dirty of it: This team has been getting the hits that count, when they count, which so long as their plate discipline remains, should hold true. Our pitching has been very good with the exception of the long ball, which one has to assume that will even out of the season--leaving just solid pitching. Our gloves have been great; they’ve been exceptional in some areas, average in others, and just pitiful for Carlos Lee. This looks like a team that is capable of staying the course, they’re confident, capable of winning games in any way (just look at the Dodgers series) and if anything, have room for some improvement still. In sum, we look like a contender, which in the end is all we could hope for and more than a lot of us expected.

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3rd 10 Game Recap (Though none are 10 Game Samples...)

After a weekend that saw our first three game series sweep of the season, let’s take a look at the recent returns.

Hitting
Stats	PA	R	HR	RBI	BB	SO	AVG	OBP	OPS	ISO	K:BB
Last 10 Games	347	47	14	46	20	56	.241	.285	.725	.198	2.8
The Previous 12 Games	426	66	13	61	41	62	.286	.357	.809	.167	1.51
1st 10 Games	339	36	11	34	22	56	.232	.286	.707	.190	3.65
2008	1,112	149	38	141	83	174	.255	.313	.752	.184	2.09

Offensively, the Astros have been a mixed bag. On one hand, the team has scored more than five runs in five straight games. It's terrible BABIP numbers have arrived at the mean, as we’ve been scoring more runs in spite of our low team batting average and on base percentage. What could be a harbinger of darker days to come is the incredibly low team OBP. Given that our team OBP in the previous twelve games was .357, a dip all the way to .285 is startling. For comparison’s sake, the San Diego Padres have the worst team OBP of any NL team, but our guys have outscored the Friars by 34 runs this season, or a little over a run per game played thus far. How is this possible? A look at our team’s ISO (isolated slugging percentage) tells us that although the Astros aren’t getting on base with any regularity, they are getting tremendous bang for their buck. It seems as if the team may settle around where their season totals current stand, as far as the type of offensive production that we will see. In other words: don’t hold your breath as far as hoping this team will challenge the Cubs for OBP supremacy.They're simply aren't built that way. But, that may ok as long as the folks in the Crawford Boxes keep getting souvenirs that they don’t throw back. Look for JR Towles and Carlos Lee to start racking up hits at a greater rate, and for Lance to slide a little, based on his average BABIP, but fairly low line drive percentage (LD%).

Starting Pitching
Stats	IP	W	L	K	BB	K/9	K/BB	ERA	BABIP	GB%	E(W)	E(L)
Last 11 Games	49.3	3	2	37	29	6.75	1.28	5.47	.327	46%	2.2	3.2
Previous 11 Games	58.7	4	3	45	22	6.90	2.05	4.76	.290	44%	3.9	3.8
1st 10 Games	58	0	4	36	18	5.59	2	4.03	.303	44%	1.9	3.7
2008	166	7	9	118	69	6.40	1.71	4.72	.312	45%	9.2	9.7

Relief Pitching
Stats	IP	W	L	SV	K	BB	K/9	K/BB	ERA	BABIP	BB/9	H/9
Last 11 Games	45.3	3	2	4	41	13	8.15	3.15	2.78	.213	2.58	6.15
Previous 11 Games	37.7	2	2	2	35	12	8.36	2.91	4.78	.293	2.87	9.8
1st 10 Games	27	3	3	1	19	12	6.33	2.03	5.67	.379	4	12.33
2008	110.0	8	7	7	95	37	7.72	2.56	4.17	.289	3.02	8.92

The pitching staff has also seen a bit of a regression over the past 10 games. More walks and a much higher ERA jump off the stat sheet for the starters. Chris Sampson has struggled in his past two starts in Arizona and yesterday against the Brewers, after dominating the Reds in the Queen City. The team leads the league in home runs against, couple that with a ground ball ratio below 50%, and this team is staring at a potential problem in the first 30 games of the season. However, the team’s K/BB and K/9 ratios have been adequate, which is due in large part to a bullpen that has been led by closer Jose Valverde, who has converted his last four saves , while not giving up a run in that same stretch. Again though, a very low BABIP indicates some regression is imminent, hopefully the K rates maintain near their current levels, so the pen’s overall effectiveness will not diminish.

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2nd 10 Game Recap: Finding Solid Ground

Since we waited an extra day, you guys get a bonus 11 Game Recap...that also means we get to do less work the next time around (9 games).

In this eleven game span, we’ve been 6-5, a marked improvement from the last time we reported in this fashion. Our XW-L is 10-11 on the season, while we really stand at 9-12. Things seem to have evened out in the luck department -- just slightly the opposite of what we’d hoped for, but hey, we should still be a win better than we are. AND if you look at the NL Central’s XW-L record, we’re only trailing the Cubs by 3.5 games (Cubs XW-L 13-7). So, 21 games in, we’re still in the thick of it -- in theory.

Aside from XW-L records, what can the numbers tell us about our team and how they’ve been playing 21 games into the season.

We’ll shake things up this time and lead-off with:

Starting Pitching
Stats	IP	W	L	K	BB	K/9	K/BB	ERA	BABIP	GB%	E(W)	E(L)
Last 11 Games	58.7	4	3	45	22	6.90	2.05	4.76	.290	44%	3.9	3.8
1st 10 Games	58	0	4	36	18	5.59	2	4.03	.303	44%	1.9	3.7
2008	116.7	4	7	81	40	6.25	2.03>	4.40	.305	44%	7	7

In the last 11 games, we’ve seen our starters BABIP fall right in line with the league average, which is good, however, it is important to note that in that time frame, Backe’s BABIP in this was .327, which is easily explained by/explains his poor outing in Philly. It is frustrating to have an overall record of 4-7 for your starters, when they’ve pitched well enough to be 7-7, but we’ll leave much of that analysis for the bull pen. Our peripherals have been remarkably consistent, which is an early indicator that what we’re seeing so far, is probably what we’re going to get, with the exception. Of course, with the exception of Roy who should continue averaging out his poor start with performances more in line with his talent, as we mentioned earlier.

Relief Pitching
Stats	IP	W	L	SV	K	BB	K/9	K/BB	ERA	BABIP	BB/9	H/9
Last 11 Games	37.7	2	2	2	35	12	8.36	2.91	4.78	.293	2.87	9.8
1st 10 Games	27	3	3	1	19	12	6.33	2.03	5.67	.379	4	12.33
2008	64.7	5	5	3	54	24	7.52	2.25	5.15	.328	3.34	10.86

The W, L, and Saves columns are pretty straight forward, if you’ve been watching the games. The two columns that should give every Astros fan hope is the BABIP, K/9, and K/BB. Our peripherals have improved dramatically in the last 11 games compared to the first and the BABIP has dropped to a very sustainable level. While a 4.76 ERA is certainly not what everyone was hoping from this bull pen, it is necessary to note that if you take away Brocail’s shelling last night, the ERA probably isn’t all that bad. What I am trying to say is, things seem to be stabilizing and at this stable state, the Astros’ bull pen looks solid.

Hitting
Stats	PA	R	HR	RBI	BB	SO	AVG	OBP	OPS	ISO	K:BB
Last 12 Games	426	66	13	61	41	62	.286	.357	.809	.167	1.51
1st 10 Games	339	36	11	34	22	56	.232	.286	.707	.190	3.65
2008	765	102	24	95	63	118	.261	.325	.764	.177	1.87

For those who've been keeping up, sorry that it took an extra day to get the hitting data in. Due to our ineptitude, we're giving you a bonus game in the hitting because the method we're using to get the stats can't spit out specific game sets...our bad. But in the end, it's probably good because it gives us a chance to see what the Astros have been doing as they began to heat up. The stat that immediately pops out is the .OBP which is a tremendous .357 -- for a team OBP that's outstanding. The leading indicator, if you're going to simply choose a single stat, for run production is OBP, because you can't score anyone if they're not on base -- unless Adam Dunn is all nine of your hitters and just crushing solo shots. While that team OBP seems high, in reality it shouldn't fall too much. Last time, we reported that our projected team OBP is .344, meaning we shouldn't see too much of a drop off in run production. While it correlates to OBP, our vastly decreased K:BB ratio for our hitters is also a number that portends to more good things, because it indicates that our hitters are being very patient and selective -- hopefully that holds. There is reason to believe that it will as the number of PA our team has is inching close to most of these stats becoming statistically significant. Run production during this period has averaged 5.5 runs a game, which, again, utilizing an RC/27 formula, we predicted the line-up should produce about 5.1 runs/per game. So all in all, it appears that our hitters are beginning to settle in and perform at their true talent levels. Thus, while it is improbable to believe that the team will keep notching 8+ runs a game, we should see a steady stream of 5-6 run games as we move forward, which as the pitchers find their grove should put us in the position to stay in contention in the NL Central.

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Examining the Wizard, 2.0

This past offseason, Astros fans heard quite often that our starting pitching would be a worrisome aspect of our club. Thirteen games in, the rotation has a total of two wins to show for it's otherwise competent work. For instance, every Astro starter has at least one quality start, except for one. Roy Oswalt has started his ninth major league season with an 0-3 record a 9.00 ERA. He has made no admissions about an injury being the cause (although he was hit with a batted ball in his first start against the Padres), and his fastball has been consistently around 93-94 MPH. Oswalt wondered openly whether or not he was tipping his pitches in last Friday’s loss to Florida. Whatever the case may be, Astros fans, Fantasy owners and the team itself are searching for reasons why one of the most consistent pitchers in the game has struggled to open the season.

For the past few years, writers and broadcasters have come to the conclusion that Roy Oswalt just doesn’t throw that hard anymore. Opinions differed as to whether this was due to declining skills or because he simply changed his philosophy, but this theory is becoming more entrenched in the baseball community. However, looking at his pitches from 2007, seem to indicate that he's still throwing hard. A glance at his average numbers should give 'Stros fans and fantasy owners a like a ray of hope, given that his pitches' speeds (hopefully he gets his location down or discerns whether or not he was tipping his pitches) have been in line with his 2007 averages, and 2007 was certainly a very effective year for Roy.

So why's he struggling then if velocity can't be blamed?

When looking at his career numbers, it is apparent that Roy has declining rate statistics associated with strikeouts. His walk rate jumped quite a bit in 2007, as evidenced by his sharp decline in K/BB. Besides that however, his statistics are remarkably consistent. Even his much talked about K/9 rate diminished only slightly after a fairly dramatic dip after the 2004 season. Has Oswalt has made an effort to reduce his pitch count by attempting to pitch to contact more, thereby using less pitches to get hitters out? Looking back at his split-season statistics, this hasn’t not been the case. Though, in 2007 this may have been due in large part to the high amount of walks he surrendered, stymying his ability to get contact.

Looking at his small sample of pitches from 2008, we can see that the problem has been his curve ball has significantly flattened. In 2007, his legendary curve ball broke, on average, 6.69" away from a right-handed batter, while dropping 6.35". In '08, his curve is breaking a scant 3.45" away from a right-handed batter and only dropping 3.73". Roy has said in a few interviews that he hasn't found the right grip for the pitch this year, and it certainly seems the case. As a result of not being able to use his curve ball effectively, Roy Oswalt is now throwing 5% more fastballs (from 65.53%, to 70.9%). If hitters are getting a steady diet of fastballs, Roy's bound for trouble.

What leads us to believe that his stuff will return and his 2008 struggles end, is his that his PERA from 2005-2007 have been improving (3.98, 3.73, 3.60 respectively) as his PECOTA projections indicate he should be regressing, if ever so slightly. Simply summed, the man is learning how to adjust to the fact that he's not as dominant as he used to be. Roy struggled at times last year to get a grip on his curve, but found his stride. While this is assuredly the worst period of his career, in reality, it's only been 16IP, and we should see him return to form.

For a man that is entrusted with anchoring perhaps the least proven (read: worst) pitching staff in baseball, this is welcome news. Oswalt probably will not achieve the levels of success that he had from 2001-2006, but rumbles concerning his eminent demise seem to be far from the truth, statistically speaking.

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Examining the Wizard

Lance Zierlein readers: We have a more recent analysis of Roy Oswalt's struggles:

EXAMINING THE WIZARD: THE MAY REPORT -- It's much more relevant and thorough.


This past offseason, Astros fans heard quite often that our starting pitching would be a worrisome aspect of our club. Thirteen games in, the rotation has a total of two wins to show for it's otherwise competent work. For instance, every Astro starter has at least one quality start, except for one. Roy Oswalt has started his ninth major league season with an 0-3 record a 9.00 ERA. He has made no admissions about an injury being the cause (although he was hit with a batted ball in his first start against the Padres), and his fastball has been consistently around 93-94 MPH. Oswalt wondered openly whether or not he was tipping his pitches in last Friday’s loss to Florida. Whatever the case may be, Astros fans, Fantasy owners and the team itself are searching for reasons why one of the most consistent pitchers in the game has struggled to open the season.

For the past few years, writers and broadcasters have come to the conclusion that Roy Oswalt just doesn’t throw that hard anymore. Opinions differed as to whether this was due to declining skills or because he simply changed his philosophy, but this theory is becoming more entrenched in the baseball community. However, looking at his pitches from 2007, seem to indicate that he's still throwing hard. A glance at his average numbers should give 'Stros fans and fantasy owners a like a ray of hope, given that his pitches' speeds (hopefully he gets his location down or discerns whether or not he was tipping his pitches) have been in line with his 2007 averages, and 2007 was certainly a very effective year for Roy.

So why's he struggling then if velocity can't be blamed?

When looking at his career numbers, it is apparent that Roy has declining rate statistics associated with strikeouts. His walk rate jumped quite a bit in 2007, as evidenced by his sharp decline in K/BB. Besides that however, his statistics are remarkably consistent. Even his much talked about K/9 rate diminished only slightly after a fairly dramatic dip after the 2004 season. Has Oswalt has made an effort to reduce his pitch count by attempting to pitch to contact more, thereby using less pitches to get hitters out? Looking back at his split-season statistics, this hasn’t not been the case. Though, in 2007 this may have been due in large part to the high amount of walks he surrendered, stymying his ability to get contact.

Looking at his small sample of pitches from 2008, we can see that the problem has been his curve ball has significantly flattened. In 2007, his legendary curve ball broke, on average, 6.69" away from a right-handed batter, while dropping 6.35". In '08, his curve is breaking a scant 3.45" away from a right-handed batter and only dropping 3.73". Roy has said in a few interviews that he hasn't found the right grip for the pitch this year, and it certainly seems the case. As a result of not being able to use his curve ball effectively, Roy Oswalt is now throwing 5% more fastballs (from 65.53%, to 70.9%). If hitters are getting a steady diet of fastballs, Roy's bound for trouble.

What leads us to believe that his stuff will return and his 2008 struggles end, is his that his PERA from 2005-2007 have been improving (3.98, 3.73, 3.60 respectively) as his PECOTA projections indicate he should be regressing, if ever so slightly. Simply summed, the man is learning how to adjust to the fact that he's not as dominant as he used to be. Roy struggled at times last year to get a grip on his curve, but found his stride. While this is assuredly the worst period of his career, in reality, it's only been 16IP, and we should see him return to form.

For a man that is entrusted with anchoring perhaps the least proven (read: worst) pitching staff in baseball, this is welcome news. Oswalt probably will not achieve the levels of success that he had from 2001-2006, but rumbles concerning his eminent demise seem to be far from the truth, statistically speaking.

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10 Game Recap: Searching for Silver Linings

As promised, here is our 10 game wrap. For this, our inaugural edition, we decided to look at some raw statistics to see what they tell us about our dismal 3-7 start.

Hitting
PA	R	HR	RBI	BB	SO	AVG	OBP	OPS	ISO	K:BB
339	36	11	34	22	56	.232	.286	.707	.190	3.65

Not a lot of surprises here, we just aren’t hitting and more importantly, we’re not getting on base. A positive note, though, is that when we are hitting, we’re hitting for a pretty decent power (note: Isolated Slugging of .190). Even this positive sign is due in large part to a four home run performance on Monday, capped off by this welcoming present from Mr. Tejada.

Our hitting woes are a surprise to say the least. This team has been heralded all off-season long as one of the best line-ups in the NL. Lance’s career .412 OBP always gives reason to be optimistic, but Carlos Lee (.341) and Miguel Tejada (.343) do not have the track record of getting on base. Balancing the good with the bad, we wanted to find a reasonable prognostication about our team’s ability to score runs. In this pursuit, we decided to use a metric called RC/27. It’s an approximation of the number of runs, per 27 outs (the length of a ball game) a player or team is creates. In 10 games our hitters (the hitting stats above exclude pitchers, for the purpose of solely analyzing what the men who are paid to hit the ball are doing for us) have manged 36 runs, which is an average of 3.6 runs/game (tough math, I know). I am using PECOTA’s projections to come up with our projected RC/27 score. Though there are many formulas for RC/27, most just trying to be more and more precise, I used the quick and dirty formula of:

RC= 25xOBPxSLG / (1-AVG)

The projected values for our lineup (including bench players, but Kaz Matsui is excluded because he has not played yet):

OBP: .344 SLG: .437 AVG: .274

This yielded a RC/27 of 5.17. So clearly, we have been vastly under performing at the plate, but we clearly are bound for a regression to the mean -- i.e. something’s got to give. Regardless of notions associated with clutch hitting, luck is a big part of hitting. Hit ‘em where they ain’t may be an old baseball axiom, but it’s very much true. Line drives are often caught, while bloop singles go for RBI’s just as frequently it seems. This offense has a track record of success. Regardless of regression due to age, or questionable lineups, it should (based on our projections) start to hit better, and score more runs as a result.

Starting Pitching
IP	W	L	K	BB	K/9	K:BB	BABIP	ERA	E(W)	E(L)
58	0	4	36	18	5.59	2	.303	4.03	1.9	3.7

For all the talk about how bad the starting rotation was going to be this year, through 10 games, it has been the one bright spot on the club. Even with Roy Oswalt’s hip being a purple bruise and Chris Sampson struggling through the flu yesterday, we’ve put up solid numbers. Brandon Backe went toe to toe with Chris Young and Carlos Zambrano, and kept us in the game both times. Wandy Rodriguez bounced back form a rocky outing in San Diego, and has pitched over nine innings of scoreless ball in a row.

The vacancy in the win column is a testament to our bullpen’s ineptitude. The E(W,L) values are slightly skewed, namely because of both Roy and Chris’s rotten starts. E(W,L) cannot be read as though you were looking at a W-L column, quickly said, it is the expected win share a pitcher earned for getting through X number of innings having allowed X number of runs, determined by the number of wins and losses pitchers through out history have earned with the same IP and RA. The good thing to note is that our BABIP is close to the mean, meaning that should our rate stats stay as strong as they are, then this just might be the way things will go.

Relief Pitching
IP	W	L	SV	K	BB	ERA	BABIP	K/9	K/BB	H/9	BB/9
27	3	3	1	19	12	5.67	.379	6.33	2.03	12.33	4

Like we said last night, this team has been built around hitting and strong bullpen, and just like hitting, the bull pen has STRUGGLED. Just like hitting though, it appears that bullpen is also do for a regression to the mean given their absurdly high BABIP of .379 reflected in a astronomical H/9 of 12.33. While the other rates stats haven't been phenomenal, expect them to improve slightly, but not much. Just expect the bullpen’s BABIP’s regression to the mean to make all the difference in the world.

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