MVN - Most Valuable Network

Recapping the BIP

Before even getting into the meat of this article, no, the title does not refer to Bip Roberts… so I’ll understand if hardcore fans of his are now turned off.  What the title does refer to, however, is balls in play and how they pertain to the statistics BABIP, FIP, and ERA.  I have written a lot here and on my other stomping grounds of late about how some of these statistics are affected and, seeing as it is a holiday weekend with not much interweb usage, it seemed like the logical time to recap everything into one neat package.  For starters, what are these three statistics?

BABIP: Batting Average on Balls In Play is a statistical spawn of the DIPS theory discovered by Voros McCracken at the turn of the century.  Essentially Voros found that pitchers have next to no control over balls put in play against them, which is why certain pitchers would surrender a ton of hits one year and much less the next.  From a control standpoint, the goal of the pitcher would be to get an out.  Once a ball is put in play, unless it is hit right back to the pitcher many defensive aspects have to coincide for an out to result.  Take a groundball for instance, one between shortstop and third base: both fielders have to understand whose territory the ball occupies and that fielder has to have the proper range in order to field it, all in a very short amount of time. 

There are plenty of other variables as well but what should be clear is that the pitcher has no control over them.  He may have control over sustaining a certain percentage of balls in play each year but the hits that result are almost entirely out of his hand.  In fact, the only aspects of pitching over which he has any type of control are walks, strikeouts, and home runs allowed.  Everything else is dependant on the fielding and luck.

BABIP is calculated by dividing the Hits minus Home Runs by the Plate Appearances excluding Home Runs, Walks, Strikeouts, and Sacrifice Flies.  If Player A has 30 hits out of 90 at-bats he will post a .333 batting average.  But if 8 of those 30 hits are home runs and 8 of the outs are strikeouts, in BABIP terms he would be 22 for 74, or .297.  This explains that, of all balls put in play–any hit or batted out other than a home run–29.7% fell in for hits.

FIP: a creation of Tom Tango’s, Fielding Independent Pitching takes the three controllable skills of walks, strikeouts, and home runs allowed, properly weights them, and then scales the result similar to the familiar ERA.  The end result explains what a pitcher’s skillset suggests his ERA should be around.  Someone with an ERA much lower than their FIP is usually considered to be lucky while the inverse is also true.  The statistic is kept at Fangraphs and ERA-FIP was recently added as well in order to allow readers a glimpse at those under- or overperforming their controllable skills.

ERA: arguably the most popular pitching barometer, ERA can be calculated by multiplying the earned runs of a pitcher by nine and dividing that product by the total number of innings pitched.  While not a terrible stat it suffers from some pretty drastic noise.  For starters, what are earned runs?  The surname ‘earned’ implies there are other runs that can be given up and that these must satisfy a specific criteria.  For instance, if a fielder botches a routine play with two outs, and the pitcher then gives up seven runs, none will be earned because the inning was extended by the poor play of the fielder.  This gets into all sorts of questions regarding exactly what an error is and how that factors into a pitcher’s performance.

Earned runs are also a direct result of hits, which have been proven to be largely accrued through chance via the DIPS theory.  So, if pitchers cannot control the percentage of hits they give up on balls in play, then fluctuations in hits can either inflate or deflate an ERA regardless of the pitcher’s skill level.  Therefore the FIP is more indicative of performance level because it only measures the three aspects of pitching he has control over which should not suffer from much fluctuation at all, as Pizza Cutter showed not too long ago that these skills were some of the quickest to stabilize.

Controlling BABIP

At Fangraphs we occasionally call upon a statistic we titled xBABIP, which refers to what the BABIP of a pitcher can be expected to be given his percentage of line drives.  Dave Studeman found a few years back that the general range of BABIP could be predicted with very good accuracy by adding .12 to the LD%; if a pitcher surrendered 22.1% line drives his xBABIP would be ~.341.  Using this for predictive purposes would not be correct due to the fact that the general baseline for pitchers is .300.  What we can do is evaluate performance at a given time and attribute line drives to a rather high or low BABIP.  For instance, saying that Player B’s BABIP of .275 as of today primarily due to his ultra-low 14-15% LD rate would be correct; saying that it will continue like this would not.  The line drive percentage may change as the season goes on.  In summation, we can use something like this when evaluating the past for pitchers but not the future.

David Appelman showed not too long ago that, in 2007, 15% of flyballs fell in for hits, 24% of grounders turned into hits, and a whopping 73% of line drives also followed suit.  Due to this, the ideal xBABIP calculation would be .15(FB) + .24(GB) + .73(LD).

I have done studies here recently, and Jonathan Hale at Baseball Digest Daily has done others in the past as well, that show how aspects like velocity, movement, and location can all affect the BABIP of a given pitcher.  It also been shown, again by Studeman, that elite relievers have the ability to consistently post lower BABIPs than others.  More studies have shown that pitchers, if any, have very weak control over their BABIP but instead of deeming it control I would be more inclined to say that these pitchers are merely taking advantage of “cold spots.” 

If just 15% of flyballs result in hits and such a large number of line drives do, then we could intuitively expect someone with consistently low LD rates and higher FB rates to post lower BABIPs.  From a movement perspective, I found that those with above average vertical movement in different horizontal movement subgroupings post lower BABIPs as well.  Higher vertical movement usually correlates to flyballs, and voila, flyballs have the lowest percentage of hits.

This was just a recap of the three statistics and explanations pertaining to their usage.  Based on this, if we see someone like Carlos Zambrano, whose ERA consistently beats his FIP, based on consistently posting lower BABIPs, we could somewhat safely assume that he might not be controlling anything persay but rather taking advantage of all the aspects proven to result in lower BABIPs.  His controllable skills may not be as good as his ERA would suggest but movement, velocity, and location may have combined to greatly aid his efforts.

The Middle 80%

In a recent interview with Kevin Orris at Major League Report, veteran lefty Jamie Moyer said something particularly interesting with regards to how he likes to evaluate himself and other pitchers.  According to Moyer, “I have a couple of outings a year where I am just not good.  But, if you look at any starting pitcher during the course of the season when you’re getting 30 or more starts, we’re all in the same boat.  It’s just how bad are you?  The way I look at it is if you take those 3-5 bad starts away and remove the 3-5 good starts, the bulk of your season is in the remainder of 25 or so starts.  If you pitch well in those games you have a chance to make big contributions to your ball club.”

While it’s probably not the ideal way to evaluate pitchers it piqued my interest nonetheless.  Since the number of starts a pitcher makes in a season can constitute a small sample size–even in the early 1900s–the average Game Score of a pitcher may be inflated or deflated due to 3-4 tremendous or terrible outings.  Now, this isn’t to say that these starts should be removed when evaluating said pitchers, but what happens if they are removed?  Would there be significant differences in the Game Score averages?  If Moyer is right–many could argue for and against his idea–that every pitcher making that many starts will have a couple clunkers and a couple standout performances, then looking at the remaining bulk would offer up more of a general range of consistency.

With that in mind I probed the Baseball Reference Play Index for the highest average Game Scores in a single season from 2000-2007, of those making 30+ starts.  I then removed the top and bottom three Game Scores from each pitcher and re-calculated their averages.  Essentially, since the pitchers all fell between 30-35 starts, the six removed starts accounted for 20% of their total outings, leaving the middle 80% to look at… hey, that sounds like a catchy title.

The Play Index query brought back a plethora of names but the top twenty-five all happened to have averages of 60 or higher, so it seemed like a logical cutoff point.  Now, this analysis isn’t done to necessarily suggest we evaluate pitchers this way, by any means, but sometimes it’s just fun to look at interesting ideas and toy around with the numbers.  Perhaps we’ll find that the great or terrible starts really did have a true effect on the season even with their relatively small percentage of the whole.  For starters, here are the twenty-five pitchers, their seasons, and their overall average Game Scores:

1. Randy Johnson, 2002: 67
2. Randy Johnson, 2001: 67
3. Johan Santana, 2004: 65
4. Randy Johnson, 2004: 65
5. Pedro Martinez, 2002: 65
6. Curt Schilling, 2002: 64
7. Randy Johnson, 2000: 64
8. Roger Clemens, 2005: 63
9. Johan Santana, 2005: 63
10. Pedro Martinez, 2005: 63
11. Ben Sheets, 2004: 63
12. Mark Prior, 2003: 63
13. Curt Schilling, 2001: 63
14. Kevin Brown, 2000: 63
15. Jake Peavy, 2007: 62
16. Johan Santana, 2006: 62
17. Jason Schmidt, 2004: 62
18. Chris Carpenter, 2005: 61
19. Jake Peavy, 2005: 61
20. Oliver Perez, 2004: 61
21. Kerry Wood, 2003: 61
22. Andy Pettitte, 2005: 60
23. Kevin Brown, 2003: 60
24. Derek Lowe, 2002: 60
25. Odalis Perez, 2002: 60

After removing the top and bottom three starts from each, here is a table showing the before and after photos, so to speak, ranked by differential.  So, someone with a 60 who shot up to a 62.5 after those starts were removed would have a 2.5; the opposite would result in a -2.5 since the pitcher’s average lessened after removing these starts. In theory, those who benefited the most from three tremendous starts will see their averages decrease while those who suffered from three bad starts will see their averages increase.

Player	Before	After	A-B
Johnson, 2000	64	66.24	2.24
Clemens, 2005	63	65.08	2.08
Carpenter, 2005	61	62.93	1.93
Pettitte, 2005	60	61.78	1.78
Wood, 2003	61	62.77	1.77
Peavy, 2007	62	63.64	1.64
Santana, 2004	65	66.14	1.14
Peavy, 2005	61	62.08	1.08
Schmidt, 2004	62	62.92	0.92
Schilling 2002	64	64.89	0.89
Martinez, 2002	65	65.88	0.88
Johnson, 2001	67	67.86	0.86
Johnson, 2002	67	67.79	0.79
Perez, 2004	61	61.79	0.79
Santana, 2005	63	63.67	0.67
Brown, 2003	60	60.50	0.50
Prior, 2003	63	63.42	0.42
Santana, 2006	62	62.32	0.32
Schilling, 2001	63	63.31	0.31
Brown, 2000	63	63.22	0.22
Lowe, 2002	60	60.08	0.08
Martinez, 2005	63	63.04	0.04
Sheets, 2004	63	62.57	-0.43
Johnson, 2004	65	64.55	-0.45
Perez, 2002	60	56.16	-3.84

What initially stands out is that so few of these twenty-five players actually saw their average game score decrease. A closer look shows that not many increased either. I mean, in a relatively speaking type of sense, all but the final three “increased” but said increase was so minimal that I would say Johnson’s 2000 and Clemens’ 2005 season were the only two to experience somewhat significant increases while Odalis Perez’s 2002 season took a big hit. Everyone else may have increased or decreased a bit, but for an initial look at something like this it does not seem that removing these starts really has that big of an effect on the overall averages. So, Jamie, for now, it seems that it isn’t really hurting you to look at pitchers this way but there really isn’t any need to get rid of the starts.

How do I become a Sabermetrician?

Occasionally, I get e-mail from someone who reads StatSpeak or some of the other writings that I sprinkle into the blogosphere, and my favorite always goes something like “I’ve read a bunch of stuff around and I’m interested in learning how to do my own Sabermetric research.  Can you help me?”  Yes, I can.  I’m a therapist by training, and do you ever need help!

So you wanna be a Sabermetrician, eh?  Well, first you should know that there’s no school for Sabermetrics (well, there is a class out there…)  We’re all self-taught in one way or another, mostly in the form of guys using skills from their day jobs to study baseball.  It’s part of the charm of the field.  Most of us have respectable day jobs and we use this just to pass the time.  Just about anyone can get themselves a free blog and start posting their work.  That’s how I started out.  So if you want to be a Sabermetrician, then by the power vested in me by no one in particular and the state of confusion, I now pronounce you an official Sabermetrician.  The certificate’s in the mail.

Now of course, you don’t want to be just any Sabermetrician.  You want to be one of those cool guys that actually gets hired by an MLB team someday.  You want to publish a book.  You want to be the next big thing.  I suppose I’m not any of those things either, but I can give you a few tips on how to get started.

1. I can’t stress this enough.  There are far too many junk stats out there.  A junk stat goes something like this.  “I just came up with the formula HR x 15 + RBI x 7 + HBP x 4.5 + SLG x 90 based on how important I thought each one was”  I’ve heard that particular reasoning far too many times.  There are formulae that look like that, but they are developed using a very specific process.  I’ve seen several cases of someone posting one of those, being ignored, and then disappearing never to be heard from again.  I’m guessing that they were frustrated that no one saw their brilliance.  Don’t start with a junk stat and be frustrated.  There is good work to be done and you might be the one who can do it.  Read on.
2. Spend a few months reading Sabermetric work.  There are plenty of good sites out there.  We all link to each other.  Read their stuff.  Read the comments.  Read Baseball Between the Numbers.  (When you get advanced enough, read The Book: Playing the Percentages in Baseball)  Go over to the Baseball Fever boards and read the discussions that go on over there.  Participate.
3. One of the things that can frustrate newcomers is the thought that their brilliant ideas that came to them in the middle of the night… have already been studied by someone else.  We’ve all done studies on the illusion of clutch and why RBIs are a bad stat (and bad grammar).  They’ve been studied to death… unless you can take a little more nuanced look at things.  And to do that, you’ll need a good understanding of what research has come before you.  Probably the biggest mistake that people make is to try to jump into Sabermetrics with both feet, not really knowing what they’re doing.  Slowly, my friend.  Slowly.
4. You’ve probably already read Moneyball, which should give you a broader idea of what’s going on.  We are not in the business of making baseball more “pure” or more enjoyable or more special or more cosmic or more whatever.  (Do watch Field of Dreams, because it’s a good movie… but understand that’s not what we do here.)  Sabermetrics is the scientific method applied to the goal of winning a baseball game/championship.  I’ll type that again.  Sabermetrics is the scientific method applied to the goal of winning a baseball game/championship.  May I recommend that you have some background in the scientific method before you begin.  I’m not saying that you need to be a Ph.D. level physicist, but simply that you need to understand how science works.  Yes, we spend a lot of time debunking some sacred conventional wisdom.  Be prepared to have some of your basic beliefs about baseball challenged.
5. It’s good to be a fan.  In fact, I recommend that you watch/listen to/go to as many baseball games as you can.  It’s OK to have a favorite team and to occasionally be irrational in evaluating them, because you love them.  Ask me about growing up with the Cleveland Indians some time.  But, with that said, understand that science is a dispassionate process.  We go into a situation not looking to confirm that so-and-so is the best player in baseball, but we come up with a reasonable definition of things and let the numbers fall where they may.  Sometimes that means realizing that the numbers don’t bear out what you used to think as a kid (or as a fan now).  That’s actually a lot harder to come to terms with than you might imagine.  If you can get past that, you’ll make a fine Sabermetrician.
6. Are you in college?  (Surprise!  A lot of the guys who travel in these circles are in/barely out of college themselves!)  Sign up for a class in statistics.  Trust me on this one.  Even if you’re an English major, it’ll come in handy both in Sabermetrics and in the rest of life.  Plus, it’ll teach you a little bit of how to use some of the computer programs that Sabermetricians like to use.  And computers make life so much easier.
7. Draw from your background.  I’m a psychologist by training.  Most of the questions that intrigue me center around “Why did he do that?”  That’s what I’ve been trained to look for in life.  You may think that your chosen field has nothing to do with baseball, but you’re wrong.  Sure, there are a lot of guys who are physics/math majors who look at algorithims for figuring out what a player will do next year, and that’s fine.  I’m personally waiting for a good Sabermetric sociologist to come along to figure out why it is that baseball teams and society in general are so poor in assigning value to baseball players. 
8. You do not need a doctorate in math.  Sure, the more analytical techniques you know, the more complicated questions you can ask.  And you do have to know some statistical/analytical techniques, but some of the biggest discoveries in Sabermetrics involve little more than knowing what a correlation is (e.g., DIPS) and are simple to the point of elegance.  The math can be taught.  The real work in Sabermetrics is perceptual and creative.  It’s in seeing the game in a slightly new way and understanding how that insight can be measured and then tested.  The rest is just an engineering problem.
9. Keep a running idea list of things that you want to accomplish and ideas that you’ve had.  Any time I have an idea pop into my head, I put it into my special file.  When I need a project, I go back and pick one that sounds fun.  Even if you don’t know exactly how you’d do it, if an interesting question or idea occurs to you, write it down.
10. You’ll notice that I haven’t specifically pointed you to any how-to guides.  The reason is that you’ll come across those in the process of reading through things.  And you’ll also learn what other statistical tricks that others use by osmosis.  Don’t focus so much on the actual technical details of how Pitch f/x works or what’s available from Retrosheet.  If you really get restless, download some Retrosheet files and play around with them, but you’ll probably learn naturally just by doing some reading.

World Famous StatSpeak Roundtable: June 30

OK, so I lied.  Last week, I said that there would be no roundtable this week.  Through the magic of technology, we were able to gather together a roundtable, although don’t ask exactly how that was accomplished.  It involves the fact that as this is being published, Pizza Cutter doesn’t have internet access.

Anyway, this week, in the ultimate act of nepotism, we welcome as our guest Corey Seidman from MVN’s Phillies blog Phanatic Phollow Up.  Won’t you read on as we discuss set up guys, division leaders and Curt Schilling.

Question #1: Of the current division leaders, which ones don’t you expect to be there at the end of the season.  Whom do you expect will overtake them?

Corey Seidman: We find ourselves at the halfway point with the Red Sox, White Sox, Angels, Phillies, Cubs, and Diamondbacks in first place. I see all six of these teams winning their respective divisions.

The Red Sox have been the best team in the American League to this point, with their only criticism being their sub-.500 road record. But they haven’t been as bad as they have been unlucky on the road. They were swept in Toronto following their season opening series against the Athletics … in Tokyo. It’s hard to hold a team accountable when they’re given a day to travel from Japan to Canada and start another series. Of their 19 other road losses, 10 were one-run games. This doesn’t show that they can’t win on the road, it merely shows they have been unlucky on the road through the first half of the season.

The White Sox pitching has been great, which is why they find themselves ahead of the surprising Twins and disappointing (yet surging) Tigers. The Sox rank second to only Oakland in ERA (3.43), opponent’s OBP (.307), and WHIP (1.24.) They lead all of baseball with 49 quality starts. Their bullpen is second in reliever’s ERA and features two late-inning guys with 0.84 WHIP’s in Scott Linebrink and Matt Thornton, as well as Bobby Jenks.

Unfortunately, their two most heralded run producers are having the worst seasons of their career, in the same year. Paul Konerko has a .368 slugging percentage (career .490), and Jim Thome has driven in only 38 runs in 73 games. Thome is on pace for 81 RBI, his lowest total in a full season since 1995. Despite Konerko’s and Thome’s struggles, the White Sox are still the best team in the A.L. Central. Carlos Quentin, A.J. Pierzynski and Joe Crede have held them together offensively, and let’s face it, Konerko and Thome couldn’t be any worse in the second half than they were in the first.

The Angels are the best team in the A.L. West. Their 3.5 game lead and 4-3 record against the second place A’s doesn’t show their dominance, but don’t expect the A’s to continue their winning ways much longer. They’ve pitched out of their mind, and we’re one Rich Harden pulled muscle and one Justin Duchsherer look in the mirror away from seeing them fall fast. The Angels have the best starting staff in baseball from 1-5 with the emergence of Joe Saunders and the return of Ervin Santana. Francisco Rodriguez is on pace to set the single-season record in saves, Scot Shields continues to look like he could close for any other team in baseball, and the back end of their bullpen has only improved this year with the addition of Jose Arredondo (1.40 ERA, 0.72 WHIP, 19 K in 19.1 IP.) Add in a collection of little speedy guys (Figgins, Izturis, Aybar, Kendrick), good defense (Hunter and Matthews Jr.) and a slugger returning to form (Vlad), and you’ve got a team that makes the playoffs every year.

For the wild card, I expect the Yankees to make a late push as they have done in recent years to overtake the Rays. Right now, the Rays look like an unstoppable team, but they just strike me as being a year or so away from seriously competing. I could see them winning it but could also see them having a bad September and letting the Yankees slip past, then have a disappointing season in 2009 that leads everyone to say this year was a fluke, before making the playoffs in 2010. Either could happen but neither would surprise me.

The Phillies are the best team in the N.L. East, and will win it, barring a catastrophic injury (Utley or Hamels.) They are considerably younger and healthier than the Braves and Mets, and haven’t had nearly the amount of different lineups the other two have had. The Marlins were a young team that overachieved for two months and are coming back to reality now. They don’t have the pitching to continue. Tell me all you want about Josh Johnson coming back, but I see a starting staff that’s best piece is Scott Olsen and his 4.89 K/9. Andrew Miller is struggling, Mark Hendrickson looks like this year’s Adam Eaton, and only Ricky Nolasco is picking it up lately. The Phils have the 3rd most quality starts in the N.L., the best bullpen ERA in baseball, and a lineup that is finally breaking out of a 10 game slump. Ryan Howard has struggled all season, yet still leads the N.L. with 67 RBI. Imagine if he was hitting .250 instead of .215. He’d have closer to 80.

The Cubs had been awesome all season, but have struggled lately. Regardless, they are the Red Sox of the N.L. this year. They are the best team, have a ridiculous home record of 33-10, and are below .500 on the road. They lead baseball with 442 runs scored, are 4th in the N.L. in runs allowed, and their Pythagorean W/L is a game better than they are. Offensively, they have done it through periods without Alfonso Soriano. Probably because they have 7 regulars hitting above .280. They’ll have home field advantage.

The Diamondbacks will win it because they are in the worst division in baseball. The N.L. West was extremely tight last year, but the Padres and Rockies forgot how to win this season. The Dodgers aren’t good enough to overtake the D-Backs or they already would have. The Diamondbacks have been scuffling for a while and still haven’t lost much ground. The advantage in pitching goes to Arizona and their two aces, as does the division. They aren’t anything spectacular offensively, and Eric Byrnes might have only hustled and gritted his way to a big contract, but nobody else in the West is good enough.

The wildcard will go to the Cardinals here. The Brewers are making a push, but they have shown us over the last season and a half that they are a streaky team. The Cards had been getting it done without Albert Pujols, and despite the numbers suggesting Ryan Ludwick can’t keep this up, he likely won’t need to for the Cards to win the wildcard. (Check who leads the Cardinals in ERA. You won’t regret it.)

Eric Seidman: So, right now we’re looking at the Phillies, Cubs, and Diamondbacks in the National League. If forced to bet money it would be put on all three of these teams winning their division. As a Phillies fan I am still not sold on the division being as easy as it has been; easy as in, the Phillies lose 8 of 11 games and gain ground. I just have a funny, non-saber feeling, that if the Mets or Braves sweep them in an upcoming three-game series, it could rejuvenate their season and propel them toward some relative success.

I don’t see the Cubs dropping off though keep in mind the Cardinals have Wainwright, Carpenter, Mulder, and Clement on the DL. Who knows if any of them will come back and/or be successful, but it is a possibility. Ultimately, though, I really don’t see them posing a significant threat to the Cubs (in the regular season).

Out west, the DBacks should win the division fairly easily but we all saw last year how an insane winning streak at the end of a season can come out of nowhere and potentially skyrocket a team toward the top of the division. Without Rafael Furcal the Dodgers, essentially, have an ugly offense, even going hitless last night (yet still winning!). So, in the NL I will pick the three current winners though if I have to pick a team to potentially overtake the leaders I will go with Mets, Cards, Dodgers.

In the AL, I see the Red Sox, White Sox, and Angels winning their divisions. The Tigers have been on fire lately and the Athletics have performed well this year, too. Oh, and the Rays! And the Yankees! And the Orioles are 41-38! Okay, I’ll calm down a little. I’ll take Red Sox winning the division with the Rays winning the Wild Card and the Yankees finishing 1-2 games behind the Rays. I’m going to take the White Sox to win the Central, and the Angels to, very soon, separate themselves from the As.

Pizza Cutter: As I write this, the AL division leaders are Boston, the White Sox (by half a game over Minnesota), and the Angels.  I think all three are vulnerable.  I’ve sung the praises of Tampa Bay previously, although that one might just be hope on my part.  Boston’s still the better team, but weird things happen in baseball.  The White Sox will win the Central.  If Minnesota is actually leading the division by Monday morning, put them in as my pick to be de-throned.  The Angels are a few games up on the A’s, but the A’s have the far better run differential.  And the A’s will probably make a few moves at the trading deadline.  This could turn into a matter of who adds more at the trading deadline.  In the NL, on the other hand, I don’t see anyone moving up over Philly or the Cubs.  The NL West doesn’t matter because everyone in the division is slouching toward mediocrity.  It’ll probably be Arizona… but that’s only beause someone has to win it.

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