The Hardball Times -- Dan Turkenkopf

Five questions: New York Yankees

Dan Turkenkopf — 2010-04-01T10:30:15+00:00

2009 was a obviously a very successful year for the Yankees. The offseason spending spree, which netted the team Mark Teixeira, C.C. Sabathia, and A.J. Burnett, paid off big time, with 103 regular-season wins and a 27th World Series title.

While last season's roster churn was fueled largely by free agent movement, this winter's mostly involved some big trades. Sure, Johnny Damon and Hideki Matsui came off the books, but the really big events were the deals that netted the team Curtis Granderson and Javier Vazquez.

Despite the recent success, the Yankees have faced a number of questions this offseason. Joe Girardi already answered the related questions of the fifth starter and Joba Chamberlain's immediate role, while questions as to Derek Jeter's future are unanswerable until after the season. Instead of providing yet another voice to the chorus singing answers to those questions, we'll focus here on some that may be less overdone, but no less important.

1. Is the offense susceptible to left-handed pitching?

Perhaps the Yankees biggest offseason acquisition was Curtis Granderson from the Detroit Tigers. Granderson will play center field and is currently projected to bat seventh. The biggest knock on Granderson throughout his career has been his inability to hit left-handed pitching. As Matt Klaassen points out over at Fangraphs, Granderson's career .358 wOBA breaks down to .380 against right-handers and .270 against lefties. In general, his entire offensive game degrades against lefties. He walks less, strikes out more, and hits for a lot less power. And this has been consistent for a while. Still, as Klaassen argues, that doesn't mean Granderson is expected to show that large of a platoon split going forward. Using the findings of The Book, he estimates that Granderson's projected wOBA against southpaws as .311.

So Granderson is still somewhat of a black hole against lefties, but not likely as bad as he's shown so far. What about some of the other Yankees?

There are three other lefties in the starting lineup and three switch hitters. Brett Gardner has shown a small platoon split in his short career, while Nick Johnson has demonstrated a small reverse split. Teixeira is a little bit better from the right side than the left, as is Nick Swisher, while Jorge Posadais about the same from both sides of the plate.

The bench will likely have Randy Winn and Marcus Thames, who generally hit left-handers well (although Winn was horrendous against them in 2009). And Thames may see some time in a platoon with Gardner in left field, which would help the offense against lefties (although hurt the defense).

All in all, despite being a little bit left-handed-heavy, there are enough weapons in the lineup that it won't get completely shut down by left-handed pitching. And while the AL East has some good left-handed pitchers in Jon Lester, David Price, and Brian Matusz, there really aren't that many lefties that the Yankees will see on a regular basis.

2. Will home runs continue to fly out of Yankee Stadium?

The early part of 2009 saw a tremendous number of home runs at the brand-new Yankee Stadium. The first months of the season saw many complain about the number of balls reaching the seats, with Peter Gammons going so far as to call it "one of the biggest jokes in baseball." Many people began to blame the weather patterns of the new stadium. The story was big enough news to get weather provider AccuWeather in on the discussion.

The conclusion? It was more likely the fences rather than any wind tunnels causing the home run explosion in right field. But still questions linger.

As Yankees blog River Ave. Blues explains, however, the new Yankee Stadium was actually a mild pitchers' park in 2009. While there were a lot of home runs hit, offense in general was reduced. So the "biggest joke" turned out to be missing most of the punchline.

And what's more, Greg Rybarczyk of HitTracker found in The Hardball Times Baseball Annual 2010 that Yankees pitchers managed to reduce the number of fly balls opposing batters hit to right field as the season progressed.

So 2010 may see a number of balls flying into the right field seats, but if 2009 is any indication, there will be a lot more from Yankees hitters than from visiting players.

3. Will Jesus Montero ever don the pinstripes?

For those of you who aren't aware, Jesus Montero is the best position player prospect the Yankees have had in a long time—probably since Derek Jeter. Well, that's not entirely true, since Montero is somewhat of a man without a position.

Nominally, he's a catcher—which makes him the best hitting catching prospect since Mike Piazza. The problem is that he may be worse behind the plate than Piazza was. And Piazza appeared to be pretty close to the line of "as bad as possible but still allowed to catch." So even though the Yankees would seem to have a need for a young catcher with Jorge Posada getting up there in age, Montero's future remains cloudy.

Most analysts believe he will shed the tools of ignorance before too much longer—most likely moving to first base or designated hitter. But the Yankees have Teixeira locked up long term at first and, with an aging roster, will likely want the flexibility to rotate players through the DH spot. General Manager Brian Cashman is less certain that Montero will need to move—although Cashman acknowledges the possibility. In an interview with NoMaas.org, he explained: "Whether he stays behind the plate, is a first baseman, a rightfielder, a DH—that remains to be seen. But he's got one of the best throwing arms in the minors, he's got some of the best blocking … he's just so big, mechanically he takes a lot longer in his release."

Everyone agrees Montero's bat will carry him to the majors in the next few seasons, which is why he's a consensus top-five prospect despite the defensive questions. Will he get a chance with the Yankees? That remains to be seen. If Montero's not able to stay behind the plate (and he's got competition from Austin Romine in the catcher-of-the-future battle), it seems unlikely that he'll find a spot on the Yankees unless he can make the move to the outfield. While no one has released a timetable for a decision, one needs to be made in the next year or so, since Montero's bat is nearly ready for the majors. He'll spend this season in Triple-A Scranton, where hopefully a final determination of his position can be made. Otherwise, Yankees fans can probably look forward to seeing Montero smash home runs for another team in 2011 and beyond.

4. Is this finally the year the Yankees have to stand pat?

In a question somewhat relevant to Jesus Montero, will the Yankees be able to pull of a midseason deal if the situation warrants it? The team's forays into free agency and the trade market over the past few seasons have severely depleted both the available budget and the available pool of minor league talent to deal.

Cot's has the 2010 Opening Day payroll at a shade under $210 million. With a payroll that high, there are signs the team is feeling something of a budget crunch. Many believe the recent release of Chad Gaudin was to save roughly a million dollars. Couple the current obligations with the upcoming free agency for legends Derek Jeter and Mariano Rivera (plus Andy Pettitte and Javier Vazquez) and you can understand why the team might be unwilling to take on any additional salary.

But suppose the Mariners fall out of the race early and are willing to deal Cliff Lee. Suppose also that the Steinbrenners agree to pay the remainder of the $9 million owed to him. Do the Yankees have enough firepower to make that deal?

The answer depends on the balance of tactical and strategic thinking in the front office. Clearly Lee would improve the Yankees' chances to win the World Series in 2010. But he would also cost a fair amount in terms of young players. Recent trade deadline deals for expiring contracts haven't gotten quite the return that previous ones have, but we'd have to assume that the Mariners would ask for Montero and either Phillip Hughes or Joba Chamberlain in the deal. Maybe Jack Zduriencik would settle for less, but assume the cost would be substantial.

The farm system has a lot of interesting arms and some recent draftees at the low levels, but the upper levels are fairly bare beyond Montero, Romine, Mark Melancon and Zach McAllister. Trading three of your top prospects in one offseason will do that to you—although the system wasn't necessarily that strong even before the trades.

With an aging core at the major league level, and limited financial flexibility, retaining a set of youngsters who can contribute might be more important now than it has been in many years for the Yankees. That tune has been sung before, but it seems to ring more true this time.

While it's surely possible that Cashman will pull another Bobby Abreu trade out of his back pocket, the more likely scenario has the Yankees dancing with the players that brought team. And that might not be such a bad thing in either the short term or the long term.

5. Can the Yankees repeat as World Series champions?

The Yankees are certainly in a good position to make the playoffs. Using DiamondMind and the five major projection systems, the Replacement Level Yankees Blog developed team level projections for the 2010 season. The Yankees had the best projected record in the majors—averaging 96 wins. The team won the division 41 percent of the time, and the Wild Card an additional 22 percent of the time.

That said, there are definitely things that could go wrong and keep the team out of the postseason. The AL East looks to be the toughest division in the American League this season. The Rays, Red Sox and Yankees all have reasonable claims to be the top team in the league, and only two of them can advance. It wouldn't take much for the Yankees to end up as the odd man out in that race. If any of the big five (Alex Rodriguez, Jeter, Teixeira, Posada or Sabathia) go down for an extended period of time, the team could see itself fall behind Boston and Tampa Bay. Of course the same statement is true for any team with title aspirations, but the Yankees' age means there's likely a greater chance of occurrence.

If New York can successfully navigate the treacherous AL East and reach the playoffs, the team will be positioned quite well for success. A rotation of Sabathia, Vazquez, Burnett and either Pettitte or Hughes stacks up well with any team. It's impossible to predict the playoffs, but it's fair to say the Yankees would have at least a 12.5 percent chance of winning the championship. And on Opening Day, that's about all you can hope for.

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HR/FB Park Factors

Dan Turkenkopf — 2009-11-21T11:58:15+00:00

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Picking up the pace

Dan Turkenkopf — 2009-07-30T05:50:15+00:00

Since the All Star Break, Joba Chamberlain has had two fairly impressive starts. Well, impressive when compared to his previous starts. We're not exactly talking vintage Maddux here.

Here's his line from his last three starts before the Break:

Date       Opponent    IP  H  R  ER  BB  SO  HR  Pitches  Game Score
June 30    Seattle     5.1 9  3  3   3   4   1   96       39
July 5     Toronto     3.2 9  8  3   1   1   2   86       21
July 10    Los Angeles 4.1 9  5  4   1   4   1   94       30

And his last two:

Date       Opponent    IP  H  R  ER  BB  SO  HR  Pitches  Game Score
July 19    Detroit     6.2 3  1  1   3   8   1   107      69
July 24    Oakland     7.0 2  1  1   3   6   0   100      72

Chamberlain has given up fewer hits, struck out more, and consequently has allowed fewer runs and pitched deeper into the game.

Now there's nothing that special about these last two starts, and normally it wouldn't even be worth studying. But reading the recaps after the Oakland game, something caught my eye.

Joba Chamberlain appears to be back on track after the All Star break. (Icon/SMI)

Numerous Yankees were attributing Chamberlain's success to improving his pacing.

Apparently the team had noticed Joba taking a lot of time between pitches, to the point where it was affecting his concentration. Jorge Posada provided an illustration of just how bad it had become:

"He was wandering. I'd look up and half the time he wasn't on the mound, especially with men on base."

Manager Joe Girardi and pitching coach Dave Eiland agreed with that assessment. Girardi stressed the importance of pace, explaining

"It's understanding what you have to do very quickly. Knowing exactly what you want to do with the baseball and doing it."

Even the Captain, Derek Jeter, weighed in:

"He did a lot better job of working quick. The last thing you want to do when you're out there playing defense is have someone working slow. And offensively, pitchers that work quick give you a problem too. His pace of game was a lot better."

That's all well and good and sounds completely plausible. But did it really happen?

Luckily for us, the PITCHf/x data gives us the exact moment (well, precise to the second anyway) when each pitch was thrown. If there's anything to what the Yankees are claiming, we'd expect to see the time between Chamberlain's pitches go down in his most recent starts.

The methodology I used is pretty simple. Look at each one of Joba's appearances, count the time between pitches and figure out the average for that appearance. Following in Mike Fast's footsteps, I've thrown out any set of pitches with more than one minute between them under the assumption that some non-pitcher related happened (a coach's visit, for example).

Let's start off with a graph showing Joba's average time between pitches for all his appearances since 2008 (when the pitch time became available).

The red dotted line is the average time between pitches across all measured pitches. For this set of data, it's just over 26 seconds.

Chamberlain has been all over the map in terms of his pacing. This graph is a little misleading though. Many of his appearances over this time frame were relief appearances, and suffer from small sample size concerns and well as possibly a difference in approach.

Here's another chart showing the same information, but only for appearances with more than 30 pitches.

Many of the peaks and valleys from the previous graph have disappeared in this view. The line representing his average time between pitches has stayed at roughly 26 seconds.

It is true that Chamberlain had slowed down in June, and has gotten faster in July. Of course the average difference is only somewhere between two and three seconds per pitch. I'm not sure how noticeable that really is on the field. It is five to 10 percent faster, but does it really make that much of a difference to the game play?

One way to find out is to compare Chamberlain's game score with the time between pitches. Although game scores aren't that scientific, they do give a pretty good indication of a good start versus a bad start. So if there's anything to be found, game scores might give an indication.

It doesn't look like much of relationship, does it? He has both good and bad starts at both ends of the time spectrum. The red line represents the best-fit equation, which tries to mathematically describe the relationship. As you can see from the R² value in the upper right corner, the best-fit line doesn't do a very good job of explaining the data.

Jeter gave us a couple of other places to explore for a noticeable effect on the game. He suggested that the fielders might play better when a pitcher pitches faster, and that batters tend not to like pitchers who work quickly.

Let's consider the fielders first. This isn't new ground. In his article "Short work," Mike Fast looked for any effects of "bored" fielders, breaking it down a variety of ways. He concluded an effect might exist, but it is small, and visible mostly at the extremes. I'm not going to rehash his work here. Instead, I'm going to see if Joba breaks away from the norm and demonstrates some noticeable effect.

This next graph shows the relationship between the time Joba takes between pitches and the defensive efficiency (DER) of the fielders behind him. I limited my data to only those appearances in which Chamberlain allowed at least 10 balls in play.

There are definitely sample size concerns here, so it's impossible to make any firm conclusions, but there's nothing that looks very promising. Some of the worst fielding performances happened when Joba took the most time between pitches, but some of the others happened when he pitched his quickest.

It doesn't look very likely that the fielders perform any better or worse for Chamberlain depending on how quickly he gets back to the rubber and releases the next pitch.

What about batters? How is their performance affected by Chamberlain pitching faster?

I'll be honest and say I'm not entirely certain where to look. What stats would indicate that batters have trouble with pitchers who pitch fast? It would have helped if Jeter had been a little more clear as to why pitchers who work fast cause problems for batters. Oh well.

Also, it's very tough to disentangle the batter's performance from Chamberlain's. Anything indication of something going on could be the result of Joba pacing himself better, or it could be the result of Chamberlain just plain pitching better. So it's almost certain we won't be able to come to any sort of conclusion on this one.

A couple of places to look might be swing rate and contact rate. If a batter is a little out of sorts he might get a little jumpy and swing at more pitches. Of those pitches he swings at, perhaps he misses a higher percentage of them. Of course I could see it working the other way too. A batter who's thrown off his game by the pitcher's pacing might not feel ready to swing and take more pitches. Let's see if there's a noticeable difference when Joba is pitching.

First, we'll look at the percentage of pitches a batter swings at for different levels of pacing.

Again, there's really not a whole lot there. Definitely nothing to indicate that batters are more or less likely to swing based on the time Joba takes between pitches.

What about contact rate? Are batters swinging and missing more when Chamberlain works faster?

Still a whole lot of nothing in the data.

There's absolutely no indication from these two measures that batters are at all affected by how much time a pitcher takes between his pitches.

We haven't found a lot of evidence to support the Yankees' theory that Joba Chamberlain is a better pitcher when he takes less time between pitches. We did see that he has spent less time in between pitches over his last few starts, especially compared to his starts just before the All Star break. But the total amount of time over 100 pitches is something like five minutes, which probably isn't all that noticeable.

We looked at his overall performance in his starts, as measured by game score, and found little to no relationship to his pacing there. We also struck out while examining Derek Jeter's claims that it's better for the defense and harder on the hitters when a pitcher speeds up his game.

It's getting pretty hard to lend any credence to the idea that a pitcher's pacing has anything to do with his performance in a game.

There are some reasons to think we might not have the whole story though. First off, we're working with a very small sample size - a handful of pitches in a handful of appearances. Any effects might be hidden by random noise in our data set.

Second, our measurement tool might not accurately affect Chamberlain's pace. The batter may step in and out of the box causing a lot of time to pass between pitches even if Chamberlain is ready to throw. Also, Posada mentioned that Chamberlain was often wandering around the mound between pitches. Perhaps the improvement noticed by the team is mental focus and faster preparation as opposed to faster delivery.

Finally, maybe we're not looking at the right metrics to detect an improvement. Maybe overall defensive efficiency isn't the right measure because we should only be looking at tough plays. Or maybe batters aren't more likely to swing at bad pitches, they're instead more likely to hit the ball weakly.

So there are definitely some further avenues to explore. But based on our initial look at this, I'm going to have to call this one busted.

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Predicting double play rate

Dan Turkenkopf — 2009-07-16T05:04:15+00:00

It seems pretty intuitive, right? Big, slow sluggers will hit into more double plays than speedsters.

They hit the ball harder, so the ball gets to the infielders a lot faster. And they obviously don't run as well, so they're easier to double up. But sluggers also are less likely to put the ball in play and less likely to hit a ground ball when they do put the ball in play.

So is our theory really true? Do power hitters hit into more double plays than weaker hitter who might be faster?

Methodology

The approach I used is a pretty simple one. I figured the double play rate for every player season since 1954 that had more than 50 opportunities, where an opportunity is a plate appearance with a runner on first and fewer than two outs. This left me with 13,169 player seasons. For each of those player seasons, determine isolated power (slugging percentage - batting average), isolated walk rate (on base average - batting average) and speed score. I calculated speed score the same way Fangraphs does; using stolen base percentage, stolen base frequency, triple rate and runs scored percentage.

Using isolated power (isoP), isolated walk rate (isoW), speed score and a dummy variable for handedness (0 for right handed, 1 for left handed and .5 for switch hitters) as my independent variables, I ran a linear regression against double play rate.

This approach has some possible concerns though. The most problematic is that handedness, isoP, isoW and speed score might not be completely independent.

In fact, only two of the relationships are correlated even somewhat strongly. Isolated power and isolated walk rate have a 0.31 correlation (where a number closer to one or negative means represents a stronger relationship), while batting hand and isolated walk rate have a 0.15 correlation. Apparently lefties have a higher isolated walk rate than do righties.

The full set of correlations is:

isoP / isoW	0.31
isoP / speed score	-0.02
isoW/ speed score	-0.10
handedness / speed score	0.06
handedness / isoP	0.02
handedness / isoW	0.15

Also, I'd really like to include ground ball/fly ball ratio but I don't have reliable data for the entire Retrosheet era. Finally, it's entirely possible that the relationships between skills have changed over time, and we might be better suited looking at smaller time period to find the proper equation.

Results

The equation to predict double play rate, or the chance of a batter grounding into a double play when faced with at least a runner on first and less than two outs, according to my regression is:

gidpRate = 0.215 * isoP + 0.529 * isoW + 0.009 * speed score - 0.015 * (0 if batter is right handed, 0.5 if batter is a switch hitter, 1 if batter is left handed).

All the variables are significant at the 99 percent confidence level, and the entire formula describes roughly 76 percent of the variation in double play rate.

Interestingly enough, power, batting eye and speed all contribute positively to the rate of double plays. Being left handed is about the only advantage. Of course, since you rarely find players who are fast power hitters with good eyes, the formula probably doesn't do a good job of capturing the real interaction between those skill sets.

Now that the hard work is out of the way, let's look at the fun stuff.

Most expected double plays

Player	Season	Expected DPs
Barry Bonds	2001	37
Jeff Bagwell	1999	36
Barry Bonds	1998	35
Jeff Bagwell	1996	33
Jeff Bagwell	2000	32
Willie Mays	1962	32
Jeff Bagwell	2001	32
Sammy Sosa	2001	31
Alex Rodriguez	2007	31
Mark McGwire	1998	31
Larry Walker	1997	31

Wow, that's definitely the Jeff Bagwell list. Basically, the better hitter you are, the more double plays you're expected to hit into. This causes me some concern. More on that later.

Best at avoiding the double play

Player	Season	Expected DPs	Actual DPs	Delta
Barry Bonds	2001	37	5	32
Barry Bonds	2001	37	5	32
Joe Morgan	1976	28	2	25
Sammy Sosa	2001	31	6	25
Joe Morgan	1975	27	3	24
Mickey Mantle	1955	28	4	24
Jimmy Wynn	1969	29	5	24
Mickey Mantle	1961	25	2	23
Barry Bonds	2004	28	5	23
Mickey Mantle	1956	27	4	23
Barry Bonds	2002	27	4	23

Not surprisingly, there are lot of the players we expected the formula to handle poorly: those who have good eyes, good power and fairly good speed. At this point, I'm thinking I probably should have included contact rate in this regression as well, although that will likely raise problems because of its relationship to isolated power.

Now the worst seasons:

Worst at avoiding the double play

Player	Season	Expected DPs	Actual DPs	Delta
Brad Ausmus	2002	9	30	-21
John Bateman	1971	7	27	-20
A.J. Pierzynski	2004	7	27	-20
Jerry Adair	1969	5	24	-19
Miguel Tejada	2008	13	32	-19
Paul Konerko	2003	9	28	-19
Tony Armas	1983	12	31	-19
Sean Casey	2005	9	27	-18
Ken Reitz	1976	6	24	-18
Al Oliver	1984	5	23	-18
Ted Simmons	1973	11	29	-18

Looking at this list, I'm thinking speed isn't being considered enough. Most of the players who miss on the low end are quite slow. Perhaps speed score isn't the best way to estimate speed of a player. It definitely doesn't seem to be a normal distribution which might cause problems when using it as part of a regression.

The wrapup

I've got a lot of misgivings about the usefulness of these results. I think as they stand right now, they mostly prove the hypothesis that the stereotypical beer league softball player (a.k.a. the Moneyball player) is expected to hit into more double plays than the weaker hitting speedster.

The regression formula seems to go too far though. Those hitters who best combined speed, power and batting eye are predicted to hit into the most double plays. The top hitters in the game dominate both the list of most expected double plays, and the list of best at avoiding expected double plays. I'm thinking the regression equation misses most at the extremes, which calls into question its entire applicability.

At this point, I'm not sure what it's really useful for, besides being a potentially interesting piece of data. If we're trying to predict future double play rate, then we might be better off using the next season's double play rate as our independent variable. If we're attempting to predict whether it makes sense to intentionally walk the current batter because we think the next one might hit into a double play, this calculation might help, but perhaps not as much as looking at his actual double play rate. It's not a value measure, so it can't be used looking backwards.

Perhaps the best we can hope for is that it sheds some light on the interaction between batter skills and that strength at the plate overcomes any negative that stems from grounding into double plays. Future work on the topic can better account for ground ball / fly ball tendencies and contact rate, as well as speed of the runners on the bases, which may provide a more accurate picture of how double plays really unfold.

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Stacking the middle

Dan Turkenkopf — 2009-07-02T06:48:15+00:00

It's yet another baseball cliche: championship teams are strong up the middle.

In his Gold Mine 2008, Bill James explains "Perhaps the first lick of old baseball wisdom that I ever encountered was the championship teams are strong up the middle."

In the article that follows that statement, James uses Win Shares to demonstrate that championship teams do tend to be stronger at catcher, second base, shortstop or center field than at first base, third base, left field or right field.

For each season of major league baseball from 1900 through 2003, James chose three teams from each league to represent a championship team, an average team and a bad team. He then compared the amount of value each team received at each position using Win Shares. The end result is that championship teams were 98 percent better than bad teams up the middle, and only 73 percent better than bad teams at the remainder of the positions.

The results were intuitive, but there are issues with the study that made me want to look a little deeper.

James answered the question, "Given that a team has won a championship, did it get strong performance up the middle?" This question looks backward in time to explain a championship. We know the team was successful and we're trying to ascertain why.

I'm more interested in the forward looking question: "Given that team has focused its strength up the middle, how successful will it be?"

You might argue that these questions aren't all that different, or that the answer to one is the answer to both, but choosing only championship teams may introduce a selection bias that we can eliminate with the later question.

The way we phrase the questions drives how we select the samples. James wanted to answer whether championship teams are strong up the middle, so he understandably identified championship teams. But that removes a lot of teams from the equation—teams good and bad, strong up the middle and weak. I want to know whether teams that get good production from middle of the field perform well in general, so I decided to classify teams by how much value they got from those positions.

Rather than use straight Win Shares, I decided to use Win Shares Above Bench (WSAB) which do a better job of determining the actual value of a given player. I know this is still technically a backwards looking study, but the lessons should apply equally going forward.

I took each team season since 2005 and determined what percentage of the team's total position player WSAB value could be attributed to the middle positions. Center field proved to be a little tricky because the WSAB calculations don't separate out the various outfield positions. I decided to let laziness be the better part of valor and simply counted the full WSAB value for the player who played the most games at center field.

The teams were divided into one of three categories based on the percentage of total position player value came from up the middle. Anything above 50 percent was considered high, and anything below 25 percent was low. The rest of the teams were in the middle. This made a nicely symmetrical distribution of 37 teams in both the high and low categories and 46 in the middle.

Let's take a look at the aggregate winning percentages for each of the levels:

Category	Winning %
High	0.526
Middle	0.498
Low	0.476

You can see quite clearly that teams that are stronger up the middle tend to win more than those who get more value out of the corners.

And this isn't a result of good teams having more Win Shares in general. We're not looking at total Win Shares here, but rather the percentage contribution of the position players up the middle.

How well does the relationship hold on the individual level?

The linear correlation (r-value) is 0.28 which makes for a mildly strong relationship. We see though, that the percentage of Win Shares attributed to pitching is correlated more highly with winning percentage at 0.33.

So it appears that Bill James and the baseball cliche are right, at least to an extent. Devoting more of your resources to better players up the middle does seem to give your team a better chance of winning.

The reason is most likely positional scarcity and the defensive spectrum (which are really two ways of saying the same thing). There are fewer athletes who can field the more difficult positions passably, and the most difficult positions tend to be up the middle.

It's just a lot easier to find quality players who can handle the corner positions, so it's harder to gain a big advantage over another team that way. Plus, up the middle players may actually cost less per win than corner players because defense and positional value appear to be relatively undervalued compared to big offensive numbers.

In actuality, the relationship appears to be a quadratic rather than linear. The actual data points are fairly scattered, but the quadratic best-fit line improves the correlation up to 0.40.

That may not mean a whole lot, but the key takeaway is that there's a point of diminishing returns where investing more in your up the middle spots. At the extreme, spending 100 percent of your resources on those four positions means a lot of balls are going to drop in for hits.

But the real point where it's not really worth it anymore is quite a bit lower. The 13 teams (from the total sample of 120) who got at least two thirds of their position player WSAB up the middle had an aggregate winning percentage of 0.489. Interestingly enough, the tipping point seems be right around the 50 percent mark, which perhaps means a balanced team is more important than anything else.

Despite the notion that a win is a win no matter where it comes from, concentrating your resources on players who play the skill positions seems to lead to more wins. This could be a real effect, or it could be Win Shares undervaluing tough defensive positions. It would be interesting to repeat this study using one of the available WAR measures and see if we get the same outcome. If so, the result may force us to reconsider how we currently value players.

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Adjusting steals for win value

Dan Turkenkopf — 2009-06-18T06:39:15+00:00

There's already been a lot of noise on the basepaths in 2009. Dexter Fowler stole a rookie record five bases against Chris Young in April. Carl Crawford bested him less than a week later when he stole six bases on Jason Varitek and the Red Sox pitchers. Jacoby Ellsbury made a splash stealing home behind Andy Pettitte's back and seemed to have started a trend. Crawford is currently on pace for almost 90 stolen bases this year, a number not reached in 20 years.

These incidents and more have caused some to ask whether the stolen base is re-emerging as an effective offensive weapon.

Rather than answer that question, I prefer to look backwards to rate the speedsters of the past. Which base runners have been the most effective stealing bases across history?

Unfortunately for this exercise, history can only go back as far as Retrosheet's play-by-play records, but that still gives us over 50 years to look at.

What do I mean by most effective? There's really two ways we can look at that; overall value, and rate value. We'll get to the particulars in a minute, but first let's take a little detour down the win probability path.

Adjusting stolen base attempts using win probability

Not all stolen bases are created equal. Stealing second base in the ninth inning of a 10-0 laugher is very different from stealing home with two outs in the bottom of the 10th in a tie game. This means we need to adjust the actual stolen base attempts to put them on equal footing.

As opposed to many events that take place on the diamond, a stolen base has some choice associated with it. Runners choose when to attempt a steal; basing their decision on score, number of outs, the man at the plate, the pitcher on the mound and a whole host of other things.

It's entirely possible that the circumstances when players decide to run have shifted over time. Some of that will be due to the run environment, but some of that might be for other reasons like risk of injury or changes in etiquette (Joe Morgan claims he never liked to run once his team was up by four runs).

But timing isn't the only adjustment we need to make to the win value of our base stealing events.

In The Book, Tom Tango, Mitchel Lichtman and Andy Dolphin found that the win value for a stolen base between 1999 and 2002 was .018 wins. On average, a runner who successfully stole a base would increase his team's chance of winning by roughly 1.8 percent. On the other hand, a runner who was thrown out attempting a steal cost his team .043 wins.

This means that the necessary success rate to break even—where a team was no better or worse off running or staying point—was right around 70 percent. Runners who exceed that number help the team, while runners below that number hurt the team.

The concept of a break even point holds true throughout baseball history. What changes, however, is the actual value of the break even point. As you can see above, that number is determined from the win value of the stolen base compared to the win value of the caught stealing.

Those win values are quite sensitive to the run environment. In a higher run environment, the stolen base is less valuable because there's a greater chance the batter will be able to drive in the runner from first with a double or a home run.

For the same reason, outs are more precious, which makes a caught stealing even more devastating. As an example, the win value of a stolen base in 1968 (the Year of the Pitcher) was .027 wins, while being caught stealing only cost the team .04 wins. This lead to a breakeven point of just below 60 percent.

Luckily we don't need to isolate the factors which caused changes in the win value. We can simply measure the win value of all stolen base attempts in each season to determine the average value for a stolen base and for a caught stealing.

Since looking at a single season's data causes some fluctuation in the win values, I calculated five year rolling averages (except for the first four seasons of course), which formed the baseline for my adjustments.

I determined the actual change in win value for every stolen base, caught stealing and pickoff from 1954 through 2008. I then calculated the equivalent number of events as if each occurred in the average situation. I realize that's confusing, so it's probably best to demonstrate with an example.

Rickey Henderson in 1982

In 1982, Oakland Athletics outfielder Rickey Henderson smashed the major league record with 130 stolen bases in a single season. This performance will be our case study to walk through the methodology.

For the purposes of this analysis, Rickey had 128 steals. My WPA calculator only gives credit to the leading runner on stolen bases, so being the back end of a double steal isn't worth anything. The actual win value of those steals was 2.93 wins. The average win value of a stolen base in 1982 was .023. So Rickey's 2.93 wins equates to just over 129 steals (2.93 / .023 = 129.4). I'll refer to these as equivalent stolen bases or steal equivalencies.

This means that Rickey stole his bases in slightly higher leverage situations than average (very slightly higher).

Our analysis isn't complete yet though. Besides looking at the successful steals, we also need to consider caught stealing. Ricky was caught stealing 31 times in 1982, and was picked off 17 more times.

You may have double-checked and seen that Baseball Reference debits Rickey for 42 times caught stealing that season. Unfortunately, not all pickoffs in the Retrosheet dataset are marked as caught stealing. I'm guessing it has something to do with whether the runner makes a move towards the next base. In calculating the win values, I've treated caught stealings and pickoffs separately.

Anyway, back to Rickey. His 31 times caught stealing cost the Athletics 1.6 wins. Based on the average cost of .046 wins, that means Rickey deserved to be caught 34 times.

His adjusted steals line is 129 stolen bases, and 34 times caught, which is worth 1.4 wins.

If you add in his pickoffs (17 actual, for a win value of -0.7 and an adjusted count of 30), Rickey's base stealing in this record-setting year was only worth 0.7 wins.

We'll come back to this season in a little while to illustrate the different ways we can measure the value of stolen bases.

How to measure value

As I mentioned above, there are two different ways to measure value; one looking at total value, and one looking at value per attempt.

Overall value we'll measure using "net stolen bases," which adjusts stolen bases based on how often a player is caught.

For rate value, we'll use win value per attempt where attempts consist of successful steals, times caught, and pickoffs.

Which stat is better? It really depends on what you're trying to measure.

Rate stats theoretically treat runners who attempt to steal at low frequencies the same as those who attempts steals at a high frequency. A counting stat like net stolen bases gives additional value each time the event occurs. If we have two players who have the same success rates (and who run in the same situations) the one who attempts more steals will score better.

Those with a high net stolen bases did more to help their team win overall (think batting runs above average), while those with a high win value per attempt contributed to more wins per attempt (think OPS+).

Let's dive into each and see what we can find.

Net Stolen Bases

Net stolen bases uses the break even concept as a way of "rewarding players for steals and penalizing them for caught stealings." The formula put forth by Rich Lederer is (SB - 2 x (CS + PO)).

This puts too much weight on pickoffs, so I'm using (SB - 2 x CS - PO) for my calculations. There's some more detail in the References section for those who are interested.

For 1982, Rickey's adjusted totals give him 31 net steals (129 SB - 2 x 34 CS - 30 PO), which is a good total, but not that impressive. It barely ranks in the top 150 seasons since 1954.

Let's first look at the top individual seasons:

Rank	Player	Season	Net Stolen Bases
1.	Maury Wills	1962	106
2.	Ron LeFlore	1980	97
3.	Rickey Henderson	1988	95
4.	Vince Coleman	1986	76
5.	Eric Davis	1986	72
6.	Davey Lopes	1975	70
7.	Tim Raines	1986	66
8.	Rickey Henderson	1983	65
9. (tie)	Bert Campaneris	1969	64
9. (tie)	Vince Coleman	1987	64

The most impressive result of the top 10 seasons is Bert Campaneris' in 1969. He achieved 64 adjusted net steals with only 61 actual stolen bases. His steals tended to come in very high leverage situations, which gave him the equivalent of 90 steals in average situations. The extraordinarily high value of his successful steals is coupled with a very low percentage of outs on the bases (eight equivalent caught stealing, and eight equivalent pickoffs), leading to the astounding total.

On the other end of the spectrum, the worst season according to this measure is Greg Gross's 1974 where his actual line of 12 SB, 21 CS, and 2 PO led to -47 adjusted net stolen bases.

What about for a career?

Rank	Player	Net Stolen Bases
1.	Rickey Henderson	548
2.	Tim Raines	472
3.	Vince Coleman	382
4.	Willie Wilson	347
5.	Davey Lopes	297
6.	Joe Morgan	286
7.	Lou Brock	274
8.	Bert Campaneris	252
9.	Marquis Grissom	233
10.	Ozzie Smith	230

There's nothing that shocking looking at the career list, although I'm slightly surprised how well Marquis Grissom fared. He combined timely stolen bases with relatively few times caught stealing.

As you'd expect, the players at the top of the real steals list are near the top of the net steals list. Lou Brock drops quite a bit from his second place ranking due to almost 300 caught stealing equivalencies. Henderson is the only person within 80 and he had 550 more attempts.

Win value per attempt

Another way to judge stolen base efficiency is to look at the average win value per attempt, Looking at it this way, Rickey's 1982 comes to only .004 wins per attempt.

The top 10 seasons according to this measure, with a minimum of 20 attempts are as follows:

Rank	Player	Season	Attempts	Wins/Attempt
1.	Pokey Reese	2001	30	0.030
2.	Bill Doran	1989	26	0.029
3.	Eddie Miller	1981	29	0.026
4.	Junior Gilliam	1957	39	0.025
5.	Garry Maddox	1978	43	0.024
6.	Bert Campaneris	1978	27	0.024
7.	Matt Alexander	1976	27	0.023
8.	Ruben Amaro	1995	23	0.023
9.	Bill Almon	1983	34	0.023
10.	Bob Dernier	1983	44	0.022

You'll notice that none of the really prolific seasons make this list. That's largely related to the small sample sizes and the huge effect any given stolen base in a tight game can have on the overall win value. Also, the runners who steal a lot of bases tend to get caught more often than others might, and a single caught stealing can erase a lot of positive value.

Now for the career; this time requiring at least 100 attempts.

Rank	Player	Attempts	Wins/Attempt
1.	Eric Davis	372	0.012
2.	Stan Javier	180	0.012
3.	Tim Raines	911	0.011
4.	Matt Alexander	119	0.011
5.	Willie Wilson	748	0.010
6.	Davey Lopes	704	0.010
7.	Henry Cotto	139	0.010
8.	Shane Victorino	109	0.009
9.	Carlos Beltran	273	0.009
10.	Bill Sample	118	0.009

The career list contains a lot of the players you would expect to see at the top of a stolen base efficiency list. Of active players, both Carlos Beltran and Shane Victorino are considered excellent base stealers. Eric Davis and Tim Raines are other players who are noted for their "smart" base running and their placement on this list supports that assertion.

Wrap-up

We've looked at two alternative ways to measure the value of a base runner's stolen base attempts. Both approaches start from the win value achieved by the player in his actual attempts and then adjusts the results in different ways to answer two different questions.

Net stolen bases can be used to demonstrate overall value from stolen bases. It closely representing the overall win value, but in an manner that scales the value to stolen bases.

Wins per attempt tries to show who the most efficient base stealers are by showing who earns the most value from each stolen base attempt.

As with any stat, these are just more tools to have at your disposal when studying player value. The key facet is not whether you choose counting or rate, but that you appreciate the adjustments for the situational stolen base, and credit or debit players correctly for that.

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A tale of two roles

Dan Turkenkopf — 2009-06-04T05:03:15+00:00

While there are many relievers who were starters in a past life, most make the move because they couldn't cut it in the rotation. Maybe they had only one or two quality pitches, maybe they tired too quickly, or maybe they just weren't very good and the team had invested a lot of money in them. For whatever reason, the pitcher was deemed a failure as a starter and was shipped off to the bullpen—with hopes of being reborn as a reliever.

Much smaller is the number of effective starters who are then moved to the bullpen—usually to closer. This seems to happen for one of two reasons. Either the team has a lot of depth in the rotation but no one to close (Brett Myers in 2007), or because injury concerns disqualify the pitcher from starting every day (John Smoltz in 2001).

The two most famous transitions, and arguably the most effective, are Dennis Eckersley and Smoltz. Both were above-average starters for at least a decade before moving into the bullpen and finding success there as well.

Smoltz made the move due to injury problems. He was coming off major elbow surgery that caused him to miss the entire 2000 season. Not knowing whether his arm could hold up under the strain of the full workload of a starter, the Braves moved him to the closer role once he was healthy. He thrived in that role, saving 10 games down the stretch in 2001, and became the full-time closer for the next three seasons.

Injury concerns also prompted his return to the rotation in 2005. Smoltz believed he'd hold up better with the predictable workload of a starter rather than the erratic usage of a closer. He successfully completed the transition back to starter, throwing more than 200 innings in each season between 2005 and 2007. However, injuries have crippled him the last few seasons and he's working his way back in the Red Sox organization.

The reasons for Eckersley's transitions are less clear. His ERA had shot up in 1986 while with the Cubs, from 3.08 in 1985, to 4.57. In the mid-1980s, 4.57 was good for only an 88 ERA+. Many were concerned he was done. Tony LaRussa thought differently, however. He decided to move Eckersley to the bullpen, where the experiment surpassed everyone's wildest expectations.

In 1988, LaRussa went even further, and began limiting Eckersley's innings. Eckersley began to pitch only when he had the chance for a save; and generally only one inning at a time. Today, this is common usage for closers, but at the time it was revolutionary. And Eckersley made it pay off big time, with five consecutive tremendous seasons, highlighted for statheads by his 606 ERA+ in 1990, and for other fans by his Cy Young/MVP season in 1992.

So these moves were obviously successful, but were they the right moves? Should the Braves and the Athletics have kept our duo in the rotations (assuming, of course, they could have held up to the wear and tear)?

Let's look at how each performed in the two different roles. We're going to focus on the defense independent pitching stats because we're interested in understanding the pitcher's value, not the rest of the team's.

Pitcher	Role	K/9	BB/9	HR/9	FIP
Eckersley	Starter	5.87	2.25	0.97	3.61
Eckersley	Closer	8.82	1.30	0.90	2.79
Smoltz	Starter	7.85	2.71	0.74	3.29
Smoltz	Closer	9.46	1.73	0.66	2.45

Both Eckersley and Smoltz performed much better as relievers than as closers. That's a fairly normal phenomenon. In The Book, Tom Tango, Mitchel Lichtman and Andy Dolphin found that the average pitcher improved his ERA by about 0.8 runs when pitching in the bullpen, which is right about where both Eckersley and Smoltz ended up.

Looking at these tables, it seems obvious that making these pitchers relievers was the right decision. But I've left off one very important column.

Pitcher value is composed of two major components; performance and durability. You could have the best pitcher in the world—someone who's completely unhittable—but if he could throw only one inning a year he wouldn't be very valuable (well, maybe if you were the Mets). So we need to consider how many innings Smoltz and Eckersley pitched in each role before we get a good understanding of how valuable they were.

Let's take the same tables as before, but add a column showing each pitcher's average innings pitched per season.

Pitcher	Role	K/9	BB/9	HR/9	FIP	IP/Season
Eckersley	Starter	5.87	2.25	0.97	3.61	208
Eckersley	Closer	8.82	1.30	0.90	2.79	66
Smoltz	Starter	7.85	2.71	0.74	3.29	194
Smoltz	Closer	9.46	1.73	0.66	2.45	71

Those are some pretty big drops from starting to relieving. Eckersley saw his workload decrease by 140 innings a season, while Smoltz was pitching 120 fewer innings per year.

How do we compare these situations? On the one hand, we have lesser performance in a lot of innings. On the other, we have phenomenal results, but in a handful of innings. There are lots of different ways we can go in trying to make sense of these results. Some are quick and dirty (multiplying ERA+ by innings pitched, for example). Others are more involved (determining the statistics of a hypothetical pitcher that would make the two performances equally valuable). I'm going to use an overall measure called Wins Above Replacement (WAR).

The WAR concept has been around for awhile in different incarnations. Basically, it measures how much more valuable a given player is than a replacement the team could pick up at any time (often called freely available talent). If you're interested in a couple of different ways to calculate WAR, check out the links in the references section. I'm going to use Sean Smith's historical WAR database for my comparisons.

Let's look at a new table. This one just measures the WAR value for our pitchers in each of their roles.

Pitcher	Role	Total WAR	WAR/Season	WAR/IP
Eckersley	Starter	42.2	3.5	0.017
Eckersley	Closer	16.7	1.4	0.021
Smoltz	Starter	56.8	3.6	0.018
Smoltz	Closer	7.8	2.0	0.027

Even though Smoltz and Eckersley were more valuable on a per-inning basis as closers, the small number of innings they pitched out of the bullpen really takes away from their overall value.

Some graphs put together by Erik Manning at Beyond the Box Score illustrate this as well.

Both pitchers had many seasons as starters better than their best relief season and it's simply due to the number of innings they pitched.

Did Bobby Cox and Tony LaRussa make the right decisions in moving their starters into the closer role? It depends. Neither pitcher was anywhere near as valuable while closing as he was in the rotation. But as we touched on above, perhaps neither pitcher could survive in the rotation.

With Smoltz, we have three seasons after he returned to his starter role that suggest he was up to the task of starting. He probably should have returned to the rotation earlier—perhaps in 2002. Eckersley is harder to figure. After 1987, he never threw more than 80 innings in a season. But when he was moved to the bullpen he was coming off a season in which he racked up 201 innings pitched. To the casual observer, he looked to be on the downswing as his ERA jumped. A closer look at his fielding independent stats suggest that he may have been unlucky in 1986, and perhaps could have survived as a starter for at least a few more seasons.

It's hard to argue with the success both Smoltz and Eckersley had as closers. It's certainly the reason Eckersley was elected to the Hall of Fame in his first showing on the ballot. But it's also hard to argue that their respective teams wouldn't have been better off keeping them in the rotation and garnering the same level of performance each had proved capable of. The A's would have been roughly two wins better per season (1.2 for the seasons when Eckersley was at his best as a closer), and the Braves 1.5 wins.

Now it might not have mattered that much, or worked out that way, had history gone differently, but the evidence suggests moving quality starters to the bullpen is a bad idea. So all the Yankees fans and writers who want to move Joba Chamberlain to the bullpen may want to note how even the most successful of those transitions turned out for the teams.

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Stealing a run

Dan Turkenkopf — 2009-05-22T05:04:15+00:00

Arguably the most exciting play in baseball, the straight steal of home is rarely seen these days. It happens so infrequently that Jacoby Ellsbury successful attempt against Andy Pettitte became major news— although the Yankees / Red Sox rivalry probably has a little something to do with that. Not to be outdone, Jayson Werth accomplished the feat a little more than two weeks later, to somewhat less fanfare.

Seeing two successful attempts in the first six weeks of the 2009 season has caused some to ask whether we're seeing a rebirth of the steal of home. Being unable to see the future, I can't answer that question, but it did spur my interest in past attempts to steal home. I wanted to focus only on straight steals of home, and not double steals, busted squeeze plays or anything that doesn't involve the runner breaking down the line while the pitcher waits to deliver his pitch.

Determining a straight steal of home from the play-by-play record can be a daunting chore. The official record doesn't capture whether the runner broke on the pitch, or whether he took off because of a pickoff throw to first. It doesn't record whether the batter squared to bunt and pulled back, or if the runner attempted a delayed steal by waiting for the catcher to lob the ball back to the pitcher.

Because of this difficulty, I supplemented the Retrosheet play-by-play data with game recaps whenever possible. Since freely available recaps become harder and harder to find the further back in time we go, I limited my look to the past decade, starting in the year 2000.

Since 2000, the straight steal of home has been attempted no more than 25 times. Unfortunately that's as specific as I can be because descriptions of failed attempts are even harder to find than of successful ones.

In the past 10 seasons, 12 times the runner on third was caught stealing at home with the line reading "1-2" (pitcher throwing him out to the catcher). I wasn't able to find recaps for most of the games that mentioned the play at the plate, so it's a mystery in most cases whether the play involved an aborted suicide squeeze or an attempted delayed steal, or was truly a straight steal attempt. I was unable to classify nine of the attempts because of lack of information. For the sake of analyzing whether the attempted steal of home is a good idea, let's assume that all nine were straight steal attempts.

On the positive side of the ledger, we can tally 15 successes. One man, Omar Vizquel, accounts for three of those (although he also tallies two caught stealings). And Jayson Werth doesn't make the list because his was a delayed steal.

We'll delve into each of the stolen bases in more detail in a little bit, but first let's look at some aggregate numbers.

Here's a list of possible straight steal attempts of home since 2000. I've marked the ones I'm unsure of with a *.

Date	Runner	Pitcher	Success
May 26, 2000	Scarborough Green	Eric Milton	Yes
June 12, 2000*	Turner Ward	Darren Dreifort	No
Sept. 20, 2000	Omar Vizquel	Rheal Cormier	Yes
Sept. 22, 2000*	Felix Martinez	Frank Castillo	No
April 17, 2001	Raul Mondesi	Randy Keisler	Yes
April 22, 2001*	Vladimir Guerrero	Armando Almanza	No
May 16, 2001*	Tom Goodwin	Britt Reames	No
May 6, 2002*	Omar Vizquel	Sean Douglass	No
June 29, 2002	Roger Cedeno	Ted Lilly	Yes
July 3, 2002	Kerry Robinson	Trevor Hoffman	Yes
July 4, 2002*	Albert Pujols	Kazuhisa Ishii	No
Aug. 26, 2002	Mike Sweeney	Andy Pettitte	Yes
May 27, 2003*	Milton Bradley	Nate Cornejo	No
May 27, 2003	Omar Vizquel	Steve Avery	Yes
Sept. 11, 2003*	Reggie Sanders	Phil Norton	No
May 7, 2004	Omar Vizquel	Erik Bedard	No
Aug. 26, 2005	Grady Sizemore	Dustin McGowan	Yes
July 2, 2006	Orlando Cabrera	Chad Billingsley	Yes
July 5, 2006	Carl Crawford	Jason Johnson	Yes
May 29, 2007	Aaron Hill	Andy Pettitte	Yes
July 20, 2007*	Milton Bradley	Adam Eaton	No
Sept. 17, 2007	B.J. Upton	Kelvim Escobar	Yes
June 13, 2008	Omar Vizquel	Greg Smith	Yes
April 26, 2009	Jacoby Ellsbury	Andy Pettitte	Yes

Out of the 25 attempts, there were 15 successes and 10 failures—a 60percent success rate. It's possible that actual success rate is higher, since many of the 10 failures were difficult to classify as actual straight steals.

We'd assume a runner on third has an easier chance of stealing home with a lefty on the mound than a right hander, since the southpaw's back would be to the runner. The results seem to back up our intuition. More steals were attempted against left handers—13 to 10. Of the successful steals, nine were against left-handed pitchers and six were against right-handed pitchers. Only four of the times the runner was caught were against left handers; the remaining six were against righties. The bottom line of the success rate by pitcher handedness is 50 percent against right handed pitchers and 69 percent against southpaws.

The average leverage index for a steal attempt was 1.8, substantially higher than the average for all steal attempts (1.2). Of course that's largely because you have to have a runner on third to be able to steal home, which will raise the leverage index. Attempting to steal home was worth an average of .03 wins.

Enough of the raw numbers. Let's dive into the weeds on the successful steals of home.

Scarborough Green

Date: May 26, 2000
Opposing pitcher: Eric Milton
Base state: Runner on third
Outs: 2
Leverage index: 1.23
Win value: 0.07
Break-even point: 35 percent success rate

The situation: The Rangers had just taken a 1-0 lead over the Twins in the top of the second inning on Green's two-out double. He moved up to third on an error by the catcher. Luis Alicia was at the plate with a 1-0 count when Green stole home.

The reaction:

"I'm not really sure what happened. I'd have to look at the replay. I was just trying not to rush and to keep the ball down. I tried to forget about that and just shut them down."
—Eric Milton, courtesy of CNN/SI

Notes: Green stole five bases on Sept. 28, 2000, which is the record for steals by a rookie (matched by Dexter Fowler this season).

Technical interlude

You may be wondering how the break-even point is calculated. The Rangers had a 57.8 percent chance of winning the game after Green's double and the error left him at third. Successfully stealing home raised that to 64.5 percent. If Green were thrown out, the chance of winning would have dropped to 54.2 percent. The break-even point is simply the value of the failure event divided by the spread in value from success to failure. Or, in this case, (54.2-57.8)/(54.2-64.5), which is roughly 35 percent. That means Green should attempt the steal if he has at least a 35 percent chance of making it successfully.

Of course this is an extremely simplified way of figuring the break-even point, since it assumes that there are only two outcomes—success and failure. There's actually an additional option: Don't attempt a steal. The average value of staying put is captured in the starting win probability when the runner is on third, but there are lots of reasons why the actual value may differ from that average.

Let's assume that the bases are loaded with two outs, and the calculated break even point is 50 percent. So in the normal situation, a steal attempt makes sense if the runner can make it home safely half the time. But what if the match-up is Albert Pujols against Sidney Ponson? The chance of Pujols reaching base is probably pretty close to 50 percent, and that would score at least the one run that a steal would bring in. And while the steal is limited to a single run, there's a fairly good chance that Pujols could bring home multiple runners with a base hit.

Now, the value of the steal is reduced compared to the alternative of staying put and letting Pujols swing away. It's possible to construct a more accurate break-even point based on the upcoming events, but that's way too involved for this survey. I'll continue to use the simple break-even point for the rest of the events, but keep in mind that the situation is a lot more complex than this analysis makes it sound.

Omar Vizquel (No. 1)

Date: Sept. 20, 2000
Opposing pitcher: Rheal Cormier
Base state: Bases loaded
Outs: 2
Leverage index: 3.8
Win value: 0.08
Break-even point: 56 percent

The situation: After the Indians closed their deficit to a single run in the top of the fifth, and a walk to Manny Ramirez loaded the bases, the Red Sox brought in Rheal Cormier to face Jim Thome with two outs. The shift was on, leaving Lou Merloni as the only infielder left of second base. This allowed Vizquel to take a huge lead off third. He took off for home and scored to tie the game without ever drawing a throw.

The reaction:

"I tried to scream (to Cormier) but he had already gone. It was a great play on (Vizquel's) part."
—Lou Merloni, courtesy of the Boston Herald by way of ESPN

Raul Mondesi

Date: April 17, 2001
Opposing pitcher: Randy Keisler
Base state: Runners on second and third
Outs: 2
Leverage index: 2.34
Win value: 0.08
Break-even point: 46 percent

The situation: In the bottom of the third inning, the Blue Jays were trailing the Yankees 3-2, and had runners on second and third with two out. With Keisler pitching out of the windup, Mondesi broke for home and scored easily as the pitch sailed high.

The reaction:

"I didn't swing so I didn't kill him. It wasn't rehearsed, I'll tell you that much."
—Jose Cruz, courtesy of ESPN

Roger Cedeno

Date: June 29, 2002
Opposing pitcher: Ted Lilly
Base state: Runner on third
Outs: 2
Leverage index: 0.84
Win value: 0.05
Break-even point: 31percent

The situation: With the Mets already holding a three-run lead in the top of the fourth inning, the Yankees and Lilly probably didn't expect Cedeno to try for home with Edgardo Alfonzo at the plate. Lilly chose to pitch from the windup, and that gave Cedeno the jump he needed to scamper home safely.

The reactions:

"Bobby (manager Bobby Valentine) yelled, 'Roger, go!' One guy whose voice I can recognize is Bobby's. I looked over at the dugout like, 'You sure?' I just took a chance. I'm glad it worked. You've got to make things happen."
—Roger Cedeno
"That was me. I just fell asleep at the switch. He should have been pitching from the stretch."
—Joe Torre
"I had no clue he was coming. Lilly looked at him twice, but I didn't know until just at the end. I went down to catch the ball and tagged him. He never touched home plate, I don't know how he could be safe."
—Yankees catcher Alberto Castillo
All quotes courtesy of CNN/SI

Kerry Robinson

Date: July 3, 2002
Opposing pitcher: Trevor Hoffman
Base state: Runner on third
Outs: 1
Leverage index: 0.41
Win value: 0.01
Break-even point:65 percent

The situation: The Cardinals already had a 3-1 lead against the Padres when Kerry Robinson led off with a triple. After Fernando Vina grounded back to Hoffman, Placido Polanco stepped to the plate. On the third pitch, Robinson broke for home. Polanco checked his swing and the ball bounced away from catcher Wiki Gonzalez, allowing Robinson to score easily.

The reaction:

"I definitely broke early. I feel bad because Placido almost got his head taken off because of my mistake. He doesn't get any reward out of it and I feel more bad than good, but it worked out for us."
—Kerry Robinson, courtesy of the AP and USA Today

Mike Sweeney

Date: Aug. 14, 2002
Opposing pitcher: Andy Pettitte
Base state: Runner on third
Outs: 2
Leverage index: 2.13
Win value: 0.13
Break-even point: 33 percent

The situation: Sweeney drove in the tying run off Pettitte in the top of the sixth inning with a double. He moved to third on a sacrifice bunt by Joe Randa. With two outs and Aaron Guiel at the plate, Sweeney took advantage of Pettitte repeatedly looking down at the ground. He gained a big lead and then headed home. While Pettitte was able to get the ball to the plate in time for a play, Sweeney managed to get in safely before Jorge Posada's tag, allowing the Royals to take the lead.

The reaction:

"It's obviously frustrating to give them a run like that. He made a great slide. I thought he'd be out. I couldn't believe he was safe."
—Andy Pettitte, courtesy of the The New York Times

Omar Vizquel (No. 2)

Date: May 27, 2003
Opposing pitcher: Steve Avery
Base state: Bases loaded
Outs: 2
Leverage index: 5.58
Win value: 0.20
Break-even point: 42 percent

The situation: The Indians and Tigers were knotted at two with two outs in the eighth inning, but Cleveland was threatening with the bases loaded. With Ben Broussard at bat, Vizquel decided to take the game into his own hands. Avery was so surprised by the move that he didn't even get a throw off, and Vizquel scored easily. Avery, rattled, promptly gave up a triple to Broussard, bringing home two more runs. At least that's my take on the story. An alternative narrative is that the steal didn't matter because Broussard hit the triple. Take your pick.

Note: Milton Bradley was thrown out attempting to steal home in the first inning of this game.

Grady Sizemore

Date: Aug. 26, 2005
Opposing pitcher: Dustin McGowan
Base state: Runner on third
Outs: 2
Leverage index: 1.29
Win value: 0.07
Break-even point: 32 percent

The situation: The Blue Jays hadn't even had a chance to bat when Sizemore stole home with two outs in the top of the first inning. After reaching on a leadoff single, he moved up on a bouncer back to the mound and wild pitch. He started for home before McGowan even began his windup, and scored without a tag.

Orlando Cabrera

Date: July 2, 2006
Opposing pitcher: Chad Billingsley
Base state: Runner on third
Outs: 2
Leverage index: 1.28
Win value: 0.08
Break-even point: 31 percent

The situation: Cabrera reached third after his double and an error by J.D. Drew in right field allowed the Angels to take a 1-0 lead. With Vladimir Guerrero at the plate, Cabrera recognized that Billingsley was pitching from the windup and not paying him enough attention. On the second pitch, Cabrera stole home without a throw.

The reactions:

"After the first pitch, Orlando openly told me, 'This guy's doing something that's giving me a chance, so please get out of the way. I always look to the third base coach. I saw Orlando, he said a word or two in Spanish. His hand gesture was really enough."
—Vladimir Guerrero
"When he goes into his windup, he has this routine where he steps back and looks down. I guess Cabrera picked it up because as soon as he put his head down, Cabrera took off. And by the time he picked his head up, Cabrera was already starting to slide. So we didn't really have a chance."
—Russell Martin
Both quotes courtesy of ESPN

Note: Cabrera's double allowed him to reach base for the 59th consecutive game, the longest streak since Ted Williams in 1940.

Carl Crawford

Date: July 5, 2006
Opposing pitcher: Jason Johnson
Base state: Runner on third
Outs: 2
Leverage index: 0.72
Win value: 0.05
Break-even point: 30 percent

The situation: The Rays were ahead 4-1 of the Red Sox in the bottom of the fourth when Crawford found himself on third with two outs. The previous night, with Crawford in the same position, Curt Schilling pitched from the windup. On the first pitch to Jorge Cantu, Johnson did the same, and Crawford decided to try for home on the next pitch, without cluing anyone into his plans. He made it easily.

The reactions:

"I said it's going to be do or die. I'm going to take this chance right here. If I'm out, I'm out. If I'm safe, everybody will be happy about it."
—Carl Crawford
"It's just a tough thing to watch"
—Red Sox manager Terry Francona
Both quotes courtesy of ESPN

Aaron Hill

Date: May 29, 2007
Opposing pitcher: Andy Pettitte
Base state: Runners on first and third
Outs: 2
Leverage index: 3.18
Win value: 0.18
Break-even point: 35 percent

The situation: The Blue Jays and Yankees were knotted at one in the bottom of the seventh inning. Hill reached third with two outs after an Alex Rodriguez error trying to complete a 5-3 double play kept the inning alive. Although Pettitte was pitching from the stretch, he still glanced over to first base in the middle of his motion. As his back was turned, Hill took off from third and slid under Posada's late tag.

The reactions:

"I definitely felt my heart beating, that's for sure. I've never done that. I didn't know what was going to happen. I just pictured the umpire calling me safe and hoped that'd give me a little extra boost."
—Aaron Hill
"You've got to go as soon as you can when any left hander turns his back to you. Obviously, you can't wait until he comes set or anything like that. He's looking forward, and right when he starts to bring his hands up and starts looking at first base. That's really the only time you can go."
—Hill
"This isn't the only situation that we've had a plan. It just so happened that everything was right. We had an aggressive baserunner at third base and we had a runner at first base. We were deep into the game and (Pettitte) had really pitched well, so it was kind of one of those roll-the-dice type things where you hope that you get the right break."
—Blue Jays third base coach Brian Butterfield
"I know someone stole home off of me a long time ago in the windup. But to be out of the stretch, what can you say? It's embarrassing. The guy's able to get home and cost you a ballgame."
—Andy Pettitte
All quotes courtesy of MLB.com

B.J. Upton

Date: Sept. 17, 2007
Opposing pitcher: Kelvim Escobar
Base state: Runner on third
Outs: 2
Leverage index: 1.51
Win value: 0.09
Break-even point: 32 percent

The situation: With the scored tied at three in the top of the third, B.J. Upton watched Kelvim Escobar use a slow windup to deliver to Brendan Harris. After timing the release for a few pitches, he stole home under the tag of catcher Jeff Mathis

Omar Vizquel (No. 3)

Date: June 13, 2008
Opposing pitcher: Greg Smith
Base state: Bases loaded
Outs: 2
Leverage index: 2.89
Win value: 0.07
Break-even point: 51 percent

The situation: In the bottom of the second inning of a scoreless game, the Giants had Oakland's Greg Smith in a tight spot. Although there were two outs, the bases were loaded and Jose Castillo was at the plate. Rather than risk losing the scoring opportunity, Vizquel stole home easily.

The reaction:

"I had checked (Vizquel) before but I had things on my mind. He picked the right time to go. I didn't hear a thing. For some reason, him not being on third relaxed me."
—Greg Smith, courtesy of ESPN

Jacoby Ellsbury

Date: April 26, 2009
Opposing pitcher: Andy Pettitte
Base state: Bases loaded
Outs: 2
Leverage index: 2.67
Win value: 0.08
Break-even point: 45 percent

The situation: The Red Sox had taken a 2-1 lead in the bottom of the fifth inning against the Yankees. With two outs and runners on second and third, Kevin Youkilis was intentionally walked to get to J.D. Drew. With Pettitte pitching from the windup (didn't he learn his lesson from Aaron Hill?), Ellsbury decided to go for it, and beat Pettitte's curve ball to the plate.

The reactions:

"It could be one of the worst baserunning mistakes if you don't make it, but I was pretty confident I could get in there and make it, so that's why I went."
—Jacoby Ellsbury
"What we have is a really fast player with some guts."
—Terry Francona
"Obviously, that's frustrating. Jorgie (Posada) had just told me to watch him, and I was in the windup. I should have been in the stretch. I watched him out of the corner of my eye and just didn't think I needed to go to the stretch. I saw him take off and sped through my windup to kind of throw a ball in there. I thought we might have a chance to get him, but obviously he's extremely fast. He got in there."
—Andy Pettitte

Summary

The straight steal of home appears to be an underused weapon. Players seem to be successful at least 60 percent of the time; you need to be successful roughly only 30-35 percent of the time for the tactic to be worth it. The break-even point is higher if the bases are loaded (between 40 and 60 percent generally), but the chance of success may increase if the pitcher pays less attention to the runner on third. As Pete Palmer and John Thorn say in The Hidden Game of Baseball, "the two-out steal of home is the unknown great percentage play."

And if you really want to be successful stealing home, be sure to go when Andy Pettitte is on the mound.

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A pitch is a terrible thing to waste. Or is it? (Part 2)

Dan Turkenkopf — 2009-05-08T05:02:15+00:00

In my last article I began delving into the topic of wasting pitches. The idea of wasting an 0-2 pitch by throwing it well outside the strike zone is something that I know I heard growing up, from my Little League coaches and from major league baseball announcers. But is there any merit to the idea?

When the pitcher has gotten ahead of the batter 0-2, there's generally not a lot of offense to be found. Joe Posnanski found that batters hit .162/.173/.236 (AVG/OBP/SLG) when the 0-2 was the "action pitch" or last pitch of the plate appearance. For all plate appearances that pass through 0-2, batters managed only a .179/.210/.269 line.

Before we start looking at the results of wasted pitches, we should define what outcomes would constitute "success" for the waste strategy.

There are many possibilities to consider, but I think we can suggest some level of success in one of two circumstances:
1. Overall performance, measured by wOBA, is worse in a plate appearance where a pitch was wasted.
2. A higher percentage of strikeouts occurs when a pitch is wasted.

Keep those in mind; we'll examine them again at the end.

Now let's dive a little deeper into the pitch sequence at 0-2. Let me make it clear up front that there's definitely some double counting here. Any time the ball was fouled off at 0-2, I counted both the initial pitch and the next pitch as 0-2 opportunities. Also, I've removed all pitchers batting to get a better feel for the effects with quality batters at the plate (sorry Micah Owings).

The 0-2 pitch

From Part 1, we know that on roughly 11 percent of 0-2 counts in 2008, the ball ended up nowhere near the strike zone. Let's assume that this was a conscious decision most of the time. How did most pitchers accomplish their wasting?

This pair of pie charts shows the pitch selection in the case of wasted pitches and non-wasted pitches. I'm using the Gameday identified pitch types, so they need to be taken somewhat with a grain of salt.

It's clear that pitchers are throwing a lot more breaking balls when they're wasting a pitch. While we're assuming the wasting was intentional, it could be at least partially a result of pitch selection.

On the 0-2 pitch, when pitchers weren't wasting a pitch, they managed to hit the strike zone about 35 percent of the time. By definition, there were no wasted pitches in the strike zone.

Batters chased non-wasted pitches out of the strike zone 39 percent of the time. I'm using chase to mean swung at pitches outside of the strike zone, not necessarily swinging and missing. Wasted pitches were chased only 5 percent of the time.

That's not too surprising considering how far out of the strike zone these pitches were. But it does call into question one of the supposed motives for wasting a pitch. If pitchers are hoping the batter will chase a wasted pitch, they're going to be disappointed far more often than not.

This next set of graphs breaks down the outcomes of the 0-2 pitch.

Pitchers fared extremely well when they chose not to waste the 0-2 pitch. They managed to turn this pitch into the action pitch more than 35 percent of the time, resulting in a .147 OBP for the batters. Batters swung at 54 percent of non-wasted 0-2 pitches and struck out in 61 percent of the times the at-bat ended, or nearly 16 percent of the time overall.

Not surprisingly, not many plate appearances ended on a wasted pitch. More than 90 percent of wasted pitches were taken for balls. A wasted pitch was the action pitch only 314 times. Of those cases, 99 ended up with the batter reaching base for a .315 OBP. All but one of those instances involved the batter being plunked. The one instance of a batter getting a hit on a wasted pitch was by Jose Reyes—it was a single.

Of the 215 outs made on wasted pitches, 99 percent were strikeouts, all of the swinging variety. Because there were so few swings, the pitcher garnered a strikeout on only 5 percent of the wasted pitches.

But we wouldn't necessarily expect a lot of strikeouts on the 0-2 count if pitchers were wasting pitches to set the batter up for the next pitch. Let's now look at the results of the pitch following the 0-2 count to see if the strategy pays off.

The next pitch

Pitchers had similar approaches for the next pitch whether they wasted the 0-2 pitch or played it straight. In general, they threw fewer breaking balls than when wasting the pitch, but also fewer fastballs than if they didn't waste the previous pitch.

The similarity in pitch breakdowns implies that pitchers are not trying to set up a specific type of pitch when they're wasting a pitch—perhaps instead focusing on location.

There's really no pattern to where the "next pitches" are thrown. They tend to be clustered around the strike zone, with very few being ones we'd consider waste pitches. Of the pitches following a wasted pitch, 39 percent were in the strike zone, which is pretty much equivalent to the 38 percent that follow non-wasted pitches.

Where we start to see some differences are in the swing rates and chase rates. Batters swung at 57 percent of the pitches after non-wasted pitches (regardless of their location), a 3 percent jump from the previous pitch. For pitches following wasted pitches, however, batters swung 61 percent of the time.

The discrepancy is even more pronounced when we look at swings outside the strike zone. For the pitch following non-wasted pitches, batters swung at a ball out of the strike zone 39 percent of the time, or roughly the same percentage as the previous pitch. After a wasted pitch, batters chased a pitch out of the strike zone 45 percent of the time.

It appears there may be something to the idea that waste pitches can set up batters for the next pitch. What sort of results do we see on the "next pitch"?

No matter whether the previous pitch was wasted, the at-bat ended on the "next pitch" roughly 15 percent of the time. After a wasted pitch, batters managed a .151 OBP, and a .248 BA, giving up 13 points of on-base percentage and 11 points of batting average to non-wasted pitches (.164 and .259 respectively).

Strikeouts accounted for roughly 58 percent of total outs in both cases, but made up a slightly higher percentage of chances (17 percent versus 15 percent) for pitches following wasted pitches.

The results

We started this examination looking at two possible outcomes that would indicate it's helpful to waste a pitch. How do the results stack up to the claims?

1. Overall performance, measured by wOBA, is worse in a plate appearance where a pitch was wasted.

We haven't actually talked about this one much yet, but it's very easy to measure. In plate appearances where the 0-2 pitch was not wasted, the aggregate wOBA was .226. In plate appearances where the 0-2 pitch was wasted, the aggregate wOBA was .245—substantially higher. Just to be clear, these numbers include all plate appearances that pass through 0-2, not just those that ended at 0-2 or the next pitch.

It doesn't seem that wasting the 0-2 is a good idea in general. It also appears that pitchers have largely figured that out, since they waste the pitch only about 11 percent of the time.

2. A higher percentage of strikeouts occurs when a pitch is wasted.

But what if a wasted pitch were more likely to lead to a strikeout? Then there might be circumstances where it makes sense to waste a pitch even though the likely outcome might be worse. We did see in Part 1 that pitches were wasted more often with multiple runners on base than with a runner on first.

Here the results are a mixed. If we make the assumption that wasted pitch is used to set up the next pitch (and has little to no effect on later pitches), then we can compare strikeout rates combined over the 0-2 pitch and the next pitch.

Hitters struck out on the 0-2 pitch or the next pitch 25 percent of the time when the 0-2 pitch was not wasted. They struck out over the two pitches only 20 percent of the time if the 0-2 pitch was wasted. That seems to put a nail in the coffin of the benefit of wasting a pitch.

But that may not tell the whole story. Because so many fewer balls are put into play when a pitch is wasted (11 percent versus 22 percent), 65 percent of all outs in the wasted pitch scenario come by strikeout, as opposed to only 60 percent of outs for non-wasted pitches.

Unfortunately for the concept of wasting pitches, that's not very meaningful because the plate appearance is much more likely to continue past our realm of observation once the pitch is wasted.

It seems pretty definitive that wasting an 0-2 pitch doesn't pay off at the major league level. Hitters hase the wasted pitch only 5 percent of the time, hit for a higher wOBA in plate appearance where a pitch is wasted, and are less likely to strike out despite being more willing to swing at a following pitch outside of the strike zone.

So why do we see any wasting at all? There's the possibility that pitchers aren't intending to miss the strike zone by so much—although if that were the case, we wouldn't see so many wasted pitches on the 0-2 count compared to other counts. It's likely one of those circumstances where game theory comes into play and pitchers will waste some amount of their pitches to keep the batter guessing. Regardless of the fact that wasting pitches appears to be worse than playing it straight at the 0-2 count, in either case the pitcher still has a major advantage over the batter, so it's probably worth it to mix things up occasionally.

Appendix

One of the hypotheses in Part 1 was that pitchers wasted pitches less frequently in a double play situation so as to be more likely to gain two outs. Pitchers do waste slightly fewer pitches in double play situations, 9.6 percent compared to 11 percent across all situations. And they do convert the double play more often in plate appearances where there is no wasted pitch—a rate of 6 percent to 4 percent. It's unclear whether this success is solely attributable to the higher ball in play totals when a pitch is not wasted or if there's something else increasing the likelihood of double plays.

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A pitch is a terrible thing to waste. Or is it? (Part 1)

Dan Turkenkopf — 2009-04-24T05:06:15+00:00

In many ways the mind game between batter and pitcher represents the core of baseball. Yes, the pitcher has eight men behind him who can and will make the difference between a hit and an out, often spectacularly. But the heart of the game is the confrontation between the man on the mound and the man at the plate.

Many other researchers have examined various aspects of the struggle—from pitch sequencing, to pitch location, to the game theory aspects of a 3-2 count. I'd like to focus on a different situation—one of baseball's cliches— that a pitcher should waste a pitch when he has the batter in the hole at 0-2.

The proper approach in the 0-2 situation is something of a debate. Many guides to youth baseball (and therefore youth baseball coaches) appear to teach that the pitcher should avoid the strike zone with an 0-2 count; perhaps hoping the batter will chase, but at least setting up the next pitch. That stance does not necessarily follow players up the chain to higher levels of play.

Joe Posnanski illustrates two opinions (although he doesn't really discuss wasting a pitch).

There are different philosophies about what to do with an 0-2 pitch. There are some pitching coaches and pitchers who think that this is absolutely the time to go for the strikeout pitch … the nasty slider tailing away, the split-fingered fastball in the dirt, the fastball up around the eyes. But there are others—and I tend to agree with this—who think that batters are so defensive at 0-2, that this is perfect time to go get them with a pitch over the plate (especially with pitch counts being SO important in today’s game).

Part 1 of this series will identify the situations in which pitchers choose to waste a pitch. Part 2 will study whether wasting a pitch is a good idea.

The methodology

Diving right in, what do we mean when we talk about "wasting a pitch?"

Traditionally, it means throwing a pitch far enough out of the strike zone that the batter can't put it into play, and using it to somehow set up the next pitch. This can take the form of forcing the batter to change his eye level (going high, then coming back with a pitch down), backing him off the plate before throwing a back-door breaking ball, or allowing him to gauge the fastball speed and then getting him out in front of a change-up.

How far out of the strike zone does a pitch need to be before we considered it wasted?

That's not an easily answered question. It can't be determined based on how a batter performs on the pitch for two major reasons. First, these pitches tend to be balls, so the sample size of actual outcomes is very small. Second, the balls that are put in play are likely hit by free swingers, introducing a selection bias into the mix.

If using results is out, we're pretty much left with location as our only option for classifying a pitch as wasted. For lack of a better definition (and with some advice from PITCHf/x guru Harry Pavlidis), I decided to use a zone that extended roughly 16 inches above and below the strike zone, 16 inches wide, and 14 inches tight. Any pitch inside that zone was considered good. Any pitch outside that zone was wasted.

Since the actual strike zone differs slightly for right-handed and left-handed batters, the waste zone is slightly different as well.

Waste Zone for a RHB

Waste Zone for a LHB

There were 38,606 pitches thrown at an 0-2 count in 2008. Of those, 4,297, or roughly 11 percent, were wasted according to this definition.

By quality

Do certain pitchers waste more pitches than others? Are pitchers more likely to waste a pitch to a good hitter than a bad hitter?

There is basically no difference in FIP between pitchers who waste pitches and those who don't. The FIP for wasting pitchers was 4.29, while non-wasting pitchers had a 4.28 FIP.

On the other hand, we can see a slight difference in batter quality.

As an aggregate, batters who reached an 0-2 count were slightly below average. The weighted average wOBA for such batters was .333 (for the entire season, not for the 0-2 count) compared to an average of .335 for all batters. This isn't too surprising, as you'd expect weaker hitters to get to an 0-2 count more often than good hitters. If we remove pitchers from the equation, the remaining batters had a .337 wOBA compared to a .339 league mark.

Batters who saw wasted pitches had a .333 wOBA for the season, while batters who were pitched straight up had a .329 wOBA. That suggests that pitchers were more likely to waste a pitch with a better batter at the plate. Most of the effect appears to be related to pitchers at the plate. Because of their relative ineptitude at the dish, there's very little reason not to challenge them each and every pitch. If we remove pitchers from our sample, the gap shrinks to .338-.337; or basically even.

By hand

What about handedness of the batter or pitcher? Do certain match-ups lead to more wasted pitches? And where are those pitches thrown?

There was no difference when looking at the handedness of pitchers or batters. No matter how the data were sliced, the waste rate was always just about 11 percent.

By examining where the pitches were thrown, we can get some idea of the intent of the wasted pitch.

RH Batter and RH Pitcher

RH Batter and LH Pitcher

LH Batter and RH Pitcher

LH Batter and LH Pitcher

Pitchers tended to waste pitches along a diagonal. Right-handed pitchers missed high and to the left side of the plate, or low and to the right side of the plate. Left handers were just the opposite.

I would guess that the high pitches tended to be fastballs, while the low ones were some sort of breaking pitch. The locations seem to suggest that pitchers are looking for batters to chase the ball rather than using the waste pitch to set up the next pitch.

By base/outs

Are pitchers more likely to waste pitches at certain times? Does it matter how many outs there are or who's on base?

The number of outs in the inning appears to have no effect on a pitcher's willingness to waste a pitch. The waste rate stayed at 11 percent in all cases.

Outs	Wasted	Not Wasted	% Wasted
0	1523	11776	11
1	1368	11548	11
2	1406	10985	11

The base state, on the other hand, showed major fluctuation in waste rate.

Base State	Wasted	Not Wasted	% Wasted
No runners	2589	19353	12
Runner on 1st	585	6414	8
Runner on 2nd	370	2662	12
Runner on 3rd	272	2434	10
Runners on 1st and 2nd	132	830	14
Runners on 1st and 3rd	121	941	11
Runners on 2nd and 3rd	106	717	13
Bases Loaded	122	958	11

Pitchers were least likely to waste a pitch with a runner on first base. With a runner on at first, pitchers wasted only 8 percent of their pitches. With runners on first and second, the waste rate skyrocketed to 14 percent. One possible explanation is that pitchers want batters to put the ball in play with a runner on first to get a double play, while with runners on first and second a strikeout becomes much more valuable.

For the sake of completeness, here's the full breakdown by base/out state.

No outs

Base State	Wasted	Not Wasted	% Wasted
No runners	1154	8298	12
Runner on 1st	164	1947	8
Runner on 2nd	76	526	13
Runner on 3rd	52	501	9
Runners on 1st and 2nd	15	81	16
Runners on 1st and 3rd	28	140	17
Runners on 2nd and 3rd	20	131	13
Bases Loaded	14	152	8

One out

Base State	Wasted	Not Wasted	% Wasted
No runners	808	6241	11
Runner on 1st	203	2239	8
Runner on 2nd	116	907	11
Runner on 3rd	77	900	8
Runners on 1st and 2nd	46	301	13
Runners on 1st and 3rd	39	343	10
Runners on 2nd and 3rd	35	268	12
Bases Loaded	44	349	11

Two out

Base State	Wasted	Not Wasted	% Wasted
No runners	627	4814	12
Runner on 1st	218	2228	9
Runner on 2nd	178	1229	13
Runner on 3rd	143	1033	12
Runners on 1st and 2nd	71	448	14
Runners on 1st and 3rd	54	458	11
Runners on 2nd and 3rd	51	318	14
Bases Loaded	64	457	12

Wrapping up part 1

This post has been long on the data and short on the conclusions. But we have learned a few things.

Pitchers waste pitches about 11 percent of the time on an 0-2 count. Once we remove the results of pitchers batting, it doesn't seem to matter how good the batter is, or how good the pitcher is; the waste rate will be about the same. The waste rate holds steady for batter and pitcher handedness and the number of outs in an inning as well.

The only real difference we found depends on the runners on base. Pitchers are less likely to waste pitches with runners on first base than they are in any other situation—only about 8 percent of the time they have an 0-2 count with a runner on first will they waste a pitch. Early conjecture suggests that might because a ball in play in that circumstance is more valuable than a strikeout due to the chance of the double play.

Looking at the pitch charts for the different batter/pitcher matchups, it appears that pitchers waste pitches mostly while trying to get batters to chase. So we see a lot of low pitches, which are more likely to fool batters.

In part 2, we'll dive into the results of these at-bats to see whether wasting a pitch is a good percentage play for a pitcher.

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