The Hardball Times -- Bojan Koprivica

The Hardball Times -- Bojan Koprivica http://www.hardballtimes.com/main Baseball. Insight. Daily. en studes@hardballtimes.com Copyright 2013 2013-05-22T08:05:15+00:00 The hunt for a $130,000 water buffalo http://www.hardballtimes.com/main/blog_article/the-hunt-for-a-130000-water-buffalo/ http://www.hardballtimes.com/main/blog_article/the-hunt-for-a-130000-water-buffalo/#When:11:56:15
Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2013-04-12T11:56:15+00:00 Platooning: the value for a player (part 3) http://www.hardballtimes.com/main/article/platooning-the-value-for-a-player-part-3/ http://www.hardballtimes.com/main/article/platooning-the-value-for-a-player-part-3/#When:08:15:15
I remember this story every year, in the months and weeks leading to spring, as we listen to one baseball expert after another, trying to figure out how our favorite player or team will do. I like to imagine how my father would pull up that chair, sit next to me and say, "So, what you got for Chipper?"

In my dreams, my father not only is alive and actually knows something about baseball, but he also has a favorite player, some aging star who played for the same team his whole career. He would then patiently listen to me explaining park factors, splits, about dropping line-drive percentages and about aging curves, about how Chipper is just not the same player anymore, not now that he is 34. Not now that he is 36. And definitely not now that he is 40, Dad, 40 years old!

He would let me finish, and then he would say, "Chipper's gonna hit, Son, just you wait and see." And he would probably walk away feeling a little bit sorry for me and my faulty projection system. In his mind, he would just know that Chipper would not stop hitting next year, just like he knew back then that his heart would not stop beating within months.

If you are going against a projection, you base your expectations either on ignoring the information you have no use for or by having additional information. I am happy to inform you that my Dad beat the system using the former. I will try to show you how to do it using the latter.

One of the best ways to have an educated guess about how a player will do next year is to ask Brian about it. Brian is our own Brian Cartwright, and his Oliver projection system has been on the forefront of projecting baseball performance for years. So, I asked about Chris Young, and this is what Oliver had to say about the newest A's outfielder. Three-twenty-one. As in wOBA of .321, a number below his previous years' results of .325, .329 and .350.

Brian was the more talkative of the two, and he explained that a player of Young's profile is generally a bad fit for a park like O.co Coliseum. Young hits many fly balls, but only a below-average percentage of his fly balls leave the yard. Young also hits more pop-ups than an average player, and Oakland is the very last place you want to hit a pop-up, as it consistently ranks as a leading park in the percentage of foul pop-ups caught for outs. Adding this information to the plethora of other, Brian explains, led to Oliver predicting a decline for Young.

Now, I have no reason whatsoever to think that I can process the same information better than Oliver does, and frankly, neither do you. But imagine we had an additional piece of information that Oliver didn't consider.* Imagine someone told us that the A's will use Young as a platoon player.

* "Didn't consider yet" is probably more accurate, as I'm sure many Oliver fans will be glad to hear that Brian is working on adding the splits projections to his already excellent set of information.

Now, whether the A's will really platoon Young is not certain. However, do consider these similarities between pre-2013 Young and pre-2012 Jonny Gomes. They had virtually same wOBA splits: Gomes was at .378/.318, Young at .373/.313. Neither was heavily platooned in the past, Gomes having 33 percent of his plate appearances versus left-handers, somewhat above league average. Young has 27 percent, pretty much in line with the rest of the league. And then came 2012, and Gomes faced left-handers 59 percent of the time, turning into one of the most platooned players in the majors.

They are different players on the defensive side, so it is possible that Young, as a superior outfielder, will see more playing time. But for now, imagine that Young is not only taking Gomes' place on the roster, but his role, too. His rate stats should be better because of that, but the question is, how much?

First, we have to estimate Young's true talent level of handedness split. As explained in the first part of this mini-series, we do this as follows:
1. Calculate the harmonic mean of Young's plate appearances versus left and versus right: N = 2/(1/963+1/2625) = 1409.
2. Calculate his observed split as a percentage: S% = (.373-.313)/.373 = 16.1 percent.
3. Regress with 1670 plate appearances of league-average split for right-handers: TTL = (1409*16.1% + 1670*6.1%)/(1409+1670) = 10.7 percent.

Next, we reverse engineer Oliver's projection:
1. We assume the projection is made of 27 percent of plate appearances versus left-handers and 73 percent versus right-handers, in line with his career norm.
2. We value the true level of Young's handedness split at 10.7 percent, meaning that his wOBA vs. right-handers should be 89.3 percent of his wOBA vs. left-handers.
3. We plug in the numbers, 27%*wOBAvsL + 73%*89.3%*wOBAvsL = .321 (Oliver projection). Therefore, wOBAvsL = .348, wOBAvsR = .311.

Now, if we mix these two numbers in the way Young's were mixed so far (27 percent of plate appearances versus LHP), we obviously get back to .321, just as Oliver predicted. But what would happen to Young if he were to be used like Gomes was? We would then have 59%*.348+41%*.311, good for a wOBA of .333. Young's wOBA jumped by more than ten points without any changes in the assumption of how he will bat, only about how much.

Obviously, speculations about usage are just that, speculations. But if you understand the principles of regression and use this simple approximation of projecting the split production, you can at least put a proper number on such speculations, or any other you might have when it comes to platooning.

I know, my Dad probably would say that Young won't hit squat, except for that walk-off home run to clinch the division, and I wouldn't really argue. But if you are like me and try to put a number on almost everything, now you at least know how.

Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2013-02-11T08:15:15+00:00 Platooning: The value for a team (Part 2) http://www.hardballtimes.com/main/article/whats-a-platoon-worth/ http://www.hardballtimes.com/main/article/whats-a-platoon-worth/#When:08:31:15 Josh Hamilton and Albert Pujols in their lineup this year, and there's a good chance that neither will be their best hitter.

True, those guys did cost $365 million to get—which, as our astute readers immediately noticed, would enable you to buy your own island in the Caribbean every day of the year—but such is the harsh reality of owning and generally managing a baseball operation nowadays. If you want premier production, you have to pay for it. A lot.

Here is a funny fact, though. Compare these 2012 productions:

The first one is the Angels' new first baseman/left fielder duo. Second one is 2012 Oakland's first baseman/left fielder quartet, a construction of cheap, one-armed misfit toys, if you are rich like me and consider anything below $5 million to be but change money.

The two are eerily similar in everything but financial commitment and number of heads, and it was the production of the latter that was pinpointed by many as the main reason for the A's having won the division. But which was it? Was it another brilliant stroke made by the market inefficiency explorer extraordinaire or rather a standard case of unicorn power turning 2012 versions of Jonny Gomes, Seth Smith, Brandon Moss and Chris Carter not only into more enlightened and better human beings, but also into more productive baseball versions of their old selves?

The four players named above offer different stories of success, some more expectable, some less. To make a long story short, Carter showed some platoon split last year, in line with his minor league performance, although the big news with him is that he hit anything, let alone both left-handers and right-handers.

Moss, he of neutral major league career platoon splits, just posted a wRC+ of 172 against right-handers, a mark 70 percent better than his career norm and six points higher than what both Miguel Cabrera and Mike Trout managed to scrape together.

Smith, probably platooniest of the four platoon players, performed just as he always did, having his wRC+ splits of 47/120 (versus career norms of 46/122) and facing only 18 percent of left-handed pitchers (versus a career norm of 17 percent).

If the A's deserve big credit somewhere, it's with Gomes, not as much for his improved performance against both left-handed and right-handed pitching, as for his improved usage, since they increased the percentage of his plate appearances against left-handed pitching from his 33 percent career norm to 59 percent in 2012.

So, the Athletics got mostly lucky on two platoon players, received just what they bargained for on the third one and were lucky and smart on the fourth one. But even if the output was on the extreme positive end of the expected spectrum, did the A's try harder than other teams? In other words, did they invest more in seeking the platoon advantage than other 29 teams did?

To answer that, we have to make the number of platoon match-ups somehow quantifiable. There are probably different ways to do that, and what I chose might not be the best, but the odds are you haven't done it at all, so my approach is still better than what you have, much like fixing the broken transmission on your four-wheel drive in the middle of the Gobi Desert by hammering sewing needles around the axle. No, I'm not kidding.

I decided to look only at starter-versus-starter confrontations. Why? Because I liked the purity of it. It's like Effron's dice—the pitching team is forced to make the first choice (it's not really a choice, as starting pitchers are used in order, not to create match-up advantages), which enables you to choose your hitting team in a way that will give you the best odds to win.

Everything that happens later in the game, once the pinch-hitters and relief pitchers enter the stage, is a game of action and reaction where both teams have a chance to turn the handedness of the confrontation in their favor. As I said, it's not the only way to go about it, but it is the one I chose.

First we need a baseline. We can not simply compare the number of same-handed or opposite-handed plate appearances for any two players without controlling for the pitching environment their teams faced.

As you see, getting your right-handed hitting specialist enough at-bats was significantly more difficult in the National League Central than in the NL West last year. Now, knowing this, we can compare the splits in any hitter's plate appearances versus opposing starters to what the baseline for his team was.

Let's stick with Gomes for a second. Against starting pitching, he had 210 plate appearances, 165 of which were against left-handers. That's a staggering 79 percent, or more than double of what Oakland as a team had (36 percent).

Had Gomes been used as often versus left-handers and right-handers as the team baseline suggests, we would expect only 75 (36 percent of 210) of his plate appearances to come against left-handers. So, by platooning him, the Athletics were able to "convert" 90 of those plate appearances in his favor. That number is what I call "PlatoonPA." The bigger the number, the more platooned the player was in 2012.

There were 25 players who received at least 50 PlatoonPA in 2012.

I actually have this Pavlov reflex where you will say Raul Ibanez, and I will say lawn dart. However, this is almost equally impressive: in 2012, Ibañez had 251 plate appearances versus right-handed starters and only two against a left-hander. You might remember the game. It was when Robinson Cano, Nick Swisher and Andruw Jones went back to back-to-back on Johan Santana. Luckily for Santana, the next batter was Ibañez.

However outlandish that 251:2 ratio might look, it created only three more PlatoonPA than Gomes' 165:45. That's because all teams face more right-handed starters, and even had his 253 plate appearances been spread out, Ibañez would have had 158 of them against right-handers. Life is good when you are left-handed.

How about the added value of a single PlatoonPA? Surely there is more value in a Gomes plate appearance vs. a left-hander or an Ibañez plate appearance versus a right-hander than against the pitcher of the same handedness. So by switching their regular mix of opportunities into a platoon mix and increasing the run expectancy, the value is being created. But how much value?

Let's look at our 25 most platooned players of 2012 again. For each, I have listed his observed career wOBA split and his regressed one. For the regressions I used the method described in the first part of this mini-series.

The weighted average of observed platoon splits is about 0.050 points of wOBA, that of the regressed one is 0.035. Now, this is obviously a very small sample size, but the fact that the values are higher than generally used to estimate the platoon splits could also be because we are not looking at the whole population of major league hitters. Instead, we are looking at the players who, for some reason or the other, earn their bread—there might be even a little something left to buy the butter—as platoon hitters.

It is a perfect example of a biased selection, so there is a possibility that by regressing them toward the mean of the general population, we neglect their true skill. Or, it might be that the managers are biased in selecting such players for the platoon roles based on their unattainable past performance.

So, there is a good chance that the following numbers are too conservative, as they are calculated with league average numbers (0.035 for LHB and 0.023 for RHB). Using these numbers to calculate the added value due to platooning for each player and then adding those added values on a team level, we can both compare which teams used the tactic the most and roughly estimate the expected increase in run creation due to it.

And no, it wasn't the A's who platooned the most but the New York Mets. Oakland came in second, followed by Chicago Cubs, San Diego Padres and Boston Red Sox. The teams that used platooning the most gained just over a win from it.

Apart from that number being an imprecise science, one has to consider further factors. Additional platoon plate appearances through pinch hitters and/or against relievers should bring that number up. The cost of a roster spot also must be considered, as it is of limited supply, and it should bring that number somewhat down.

For now, though, a somewhat educated estimate is that by aggressively matching up a lineup—provided you have the players to do so—a team stands to gain about one to one-and-a-half additional wins per season.

Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2013-02-04T08:31:15+00:00 Platooning: the meaning of mean (Part 1) http://www.hardballtimes.com/main/article/platooning-the-meaning-of-mean-part-1/ http://www.hardballtimes.com/main/article/platooning-the-meaning-of-mean-part-1/#When:08:33:15
I actually wrote a little article a few days ago, thinking I'd take it easy in my return from the dead, strictly sabermetrically speaking. It was about platoons, it was not all that long, definitely not groundbreaking, and actually made some sense.

But then, the devil in me started speaking to me, saying how it would be a truly beneficial exercise both for me and for THT readers to explain how to do the platoon skill regression from the scratch. Doing things from scratch is my favorite, as my wife and her wobbly desk can attest. Sure, Tango and his team taught us what numbers to use, but it would be much more fun doing the whole thing over again, plugging in the recent numbers and explaining everything step by step.

Or, so I thought, until I came to the very first step, my sabermetrically boiled eggs, if you will. To estimate the true talent, we have to regress to the mean. But what does mean mean?

Imagine there were only three hitters in the whole league, all three right-handed, and that they hit like this:

And now tell me, what is the league average platoon split for right-handers? The answer is: It's 0.062. Or 0.052. Or 0.047. Or 0.057.

With other stats this is a fairly simple question. You want the league average ERA? Well sum the earned runs and divide them by the sum of the innings pitched and multiply by nine for a good measure. But here? I can actually offer four different answers

1. Averaging the sum
We treat the three players as one. So we consider the three sets of data as a part of one big set, in which the league had 400 plate appearances against lefties and 900 against right-handers, and posted wOBA of .376 against the former and wOBA of .314 against the latter. We subtract the values and get the league average split of 0.062. Is that what you would do, too?

I don't know, just intuitively, this doesn't feel quite right, does it? It is the same approach as we would do with ERA, but what we are trying to measure is how pairs of values compare for individual batters , and by mixing them all together we seem to murk the picture. If you are not convinced that this is not the ideal path to pursue consider following, even simpler, scenario, where there are only two batters in the league:

We have one batter with a split of 0.060 and the other with a split of 0.040 and what we get as league average split is 0.071. Now convinced that our intuition was right?

2. Averaging the individual splits

This seems better. At least, it has "individual" in the title, so it has to be better, I say. We average 0.100, 0.015 and 0.040, the splits our three players had, and we end up with 0.052 as a league average split. But this has an easy-to-notice flaw. Our first hitter's split carries the same weight as the other two, yet he batted fewer times, contributing less information to what we are trying to measure. We need to weight the splits.

3. Averaging weighted individual splits

We weight the first split with 350 (number of total PA), the second one with 500 and the third one with 450. Doing that we get the third different result - 0.047. We have accounted for the fact that splits have to be measured on individual level, and we have accounted for the fact that not every individual split carries the same weight. We did almost everything right, yet something still feels wrong.

Look at our second and third hitters again. We have put more weight into the second hitter's split because he played more. But he has actually given us less information about his hitting split, because almost all his plate appearances came against right-handed pitchers. Meanwhile, our third batter had fewer at-bats, yet they were distributed more evenly. How can we account for that?

4. Averaging individual splits weighted by harmonic mean

What is harmonic mean, you say? This is harmonic mean:

We are looking at the harmonic mean of each batter's plate appearances against left-handers and against right-handers, because harmonic means tend to the least (or in our case of two elements, the lesser) of the elements. This way we can give more value to the PA that are more evenly spread, because they give us better information on the split itself. So, in the case of only two elements, the harmonic mean looks like this:

So, when we plug our values in it, we come up with the following:

You can think of it in this way. You get the weight for all the PA that you had against both LHP and RHP plus a discounted number for those you had against only one. So, our first and third batters both get 150 for the common one plus a portion of the unmatched ones. Our middle batter is weighted the least. He has only 50 PA in common between left and right, and the fact that he has batted an additional 400 times against right-handers doesn't bring him much, because it doesn't say much about the split. It means that our uncertainty about him is the greatest and he gets to represent our three-man league the least.

Where and how to cut?

Now that we have decided how to calculate the mean, we need only to choose where we want to cut off our sample. Say we decide it is 200 plate appearances over the past five years. It gives us a decent number of players to work with and eliminates those who just barely put on a major league uniform.

But nothing is simple with platoons. Should it be 200 overall PA? Or at least 100 versus left and 100 versus right? That actually does make a difference, as there seem to be different observed levels of talent for the players who were more heavily platooned as opposed to those with more average PA splits.

I have made the arbitrary (aren't they all arbitrary) cut at 200 PA for the harmonic mean of player's appearances versus left-handers and right-handers. This way we were left with exactly 150 left-handed hitters and 264 right-handers. I have excluded pitchers from this group and look only at the hitters of dedicated handedness (fancy way to say that I omit switch-hitters).

The results

The left-handers in our sample group have the observed platoon split of 9.8 percent (0.035 wOBA). The right-handers showed the split of 6.1 percent (0.023 wOBA).

First, a few words about the absolute numbers. In The Book, Andy came up with 0.017 for right-handed batters and 0.027 for lefties, basing his research on data from 2000-2004. We have used similar approaches (not because we are equally smart or versed in statistics, but because I was not too proud to ask for advice and because both Tango and Andy were nice enough to push me in the right direction). However, what you see here is a simplified version - Andy went to great lengths to squeeze the last possible drop of truth out of the platoon lemon, performing multiple iterations to properly weight the data.

Matt Klaassen has done some very good work on platoon splits in recent years, and my numbers are rather close to his latest overview. Regardless of the exact evaluation method, I think it is safe to say that platoon splits have increased since The Book was written.

As for the fact that the left-handers constantly have higher splits than right-handers, the explanation is rather simple. There are two truths about hitting in baseball. One, it is easier to hit opposite-hand pitching than same-hand pitching. And two, it is easier to hit right-handed pitching than left-handed pitching.

The reason for the latter is negative frequency dependent perceptual advantage. If you prefer your explanations in English, it means that left-handed opponents (in any sport) are harder to decipher because our brains are wired to expect right-handers' movements, because we face those much more often. Thus, while right-handed batters have one piece of good and one piece of bad news, regardless of the handedness of the pitcher they are facing, for left-handed batters it is either all good or all bad, as left-handed pitchers are also the same-side pitchers for them.

Finally, you will notice that I list the values both as the absolute delta in wOBA points and as a percentage (difference divided with the higher of the two splits). I think that industry consensus is that the former is easier to use and the latter better, as better players have larger splits.

The regression

Now that we know the league average production, we can start figuring out how much each batter's split should be regressed to most accurately estimate his true talent level.

To do that, I have taken all the above batters and split their production into even (calendar days ending with 0, 2, 4, 6 and 8) and odd days (calendar days ending with 1, 3, 5, 7 and 9). I then looked how the buckets correlate. Starting with left-handers, we have r=0.13 with N(HM) = 320. If you prefer verbatim, that means that the two buckets show a correlation coefficient of 0.13, with average sample size of 320. That sample size is a harmonic mean of PA versus left and versus right.

Now, we could stick with harmonic means throughout the regression and that would probably be the more precise way to go. That means you would have to calculate harmonic mean of the player's plate appearances and then regress that number against the fixed number of league average performance. It is probably easier for the reader to do the regression based on PA versus left, as is customary, so here is the overview of all the ways one could go about it:

A few thoughts and explanations about those numbers:

{exp:list_maker}There was a higher correlation factor for right-handed batters when I used splits as percentages, not absolute values
The N(L) is calculated using league average percentage of PA versus left-handed pitchers (29 percent for RHB and 24 percent for LHB). So, for example, a right-handed hitter with a harmonic mean of 325 and league average split will have 230 PA versus left and 563 PA versus right.
The two different numbers of PA to regress with depend on whether you count only PA versus left or you use the harmonic mean.
If I were to give advice on how to regress simply and quickly based on these numbers, I'd say: Always regress with 1,500 PA versus left, regardless of the batter handedness, and use 0.035 wOBA for left-handers and 0.023 for right-handers.
If I were to offer another piece of advice (and you should really not take too many of those from me), I'd say to regress with either 2,260 or 1,670 HM PA and use 9.8 percent and 6.1 percent if you want the best results.
The numbers I come up with are different from those we normally use (from The Book, for example). The reason is most probably the newer data, although methodology could definitely play a role in it, too. {/exp:list_maker}

(For full disclosure, my underlaying data covers 98-99 percent of all PA during the five year period (I use my own program for parsing Retrosheet data, and I parse quite a lot of data at the same time, like runner advances, placement of the batted ball and so on. On about 20-30 random games every year, I get parsing errors, sometimes because there are inconsistencies in the ways the data is recorded, sometimes because my parser doesn't know how to handle a certain rare occurrence. For example: bunt single that moved the runner from second to third, but he then got caught in a rundown between third and home, while the batter-runner advanced to second on a fielders choice, and then home on a throwing error. If my parsing program encounters an event it can't handle, it automatically ignores the game and puts it in my "to do bucket" that I periodically go back to, to both clean the files and improve my algorithm. I have no reason to believe that my samples are biased by that in any way, but if you do, please scream so. I also use the same wOBA formula for every year.)

Finally, to get a feel for how much difference there is when using different regressions, look at these four hitters. We have two left-handers and two right-handers, an experienced batter and a novice one in each group, all with pronounced observed splits.

The differences are not world-shattering, with 0.011 wOBA being the biggest delta among the four ways to regress. I think it is important that you do regress and it is important to understand why we need to do it. Which manner you use is up to you. For what it's worth, I will use the last column in the table above for the next articles on this topic—unless someone finds glaring holes in the way I went about my business—simply because it's mine and I'm like that when it comes to using things I made with my hands. If someone wants to get the underlaying data to run a personal own analysis, drop me a line.

The biggest thing, though, is that's this is not at all about which numbers will yield the best results. It is much more about the journey, about trying to see what our obstacles are while we try to understand baseball better. It's a look under the sabermetric hood, if you will.

Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2013-01-29T08:33:15+00:00 Chasing a dream http://www.hardballtimes.com/main/article/chasing-a-dream/ http://www.hardballtimes.com/main/article/chasing-a-dream/#When:09:10:15
As he reached the cellar, he saw that Kruno and Damir Karin, the representatives of Baseball Klub Olimpija Karlovac, were already there. The brothers K were standing between the bar and the Ping-Pong table, flashing broad smiles and holding a bottle of vodka.

Jimmy looked at his beer and realized that he had brought a knife to a gun fight.

* * *

Life was different in 1994. A gallon of gas was $1.11, the Montreal Expos had the highest winning percentage in baseball and there was a war in Europe. Well, there wasn’t a war in most of Europe, but there was a war in Croatia and, as Jimmy learned from George, that’s where Karlovac was.

George was George Vukovic, and without him neither this meeting nor any of what was to follow ever would have happened. But as chance will have it, in 1989 the basebal- crazed Ohioan did decide to visit the country his parents came from. And while in Croatia he did hear about some crazy students playing some sort of stick ball. One of them was the elder Karin, Kruno, who founded Olimipija.

George brought a baseball team from Ohio to play in Karlovac the following year, and in 1991 he organized the rematch in the States. The bond was formed.

His son Ross played alongside Jimmy on that 1994 national amateur championship team. Ross invited the Croatian visitors to the championship party, and a day later, in his dad’s cellar, Jimmy’s life was about to change forever.

* * *

It was an unorthodox signing, to say the least. The brothers K stressed all the advantages of playing in Karlovac (“Yes, there is technically a war in Croatia, but Karlovac is at least two miles from the front line”), while young Mr. Summers stood firm by his contract demands (“Guys, I don’t want to lose any money on this,”).

There were cups on the Ping-Pong table, and there were shots of vodka taken when one’s cup was hit by a skillful shot. As Jimmy later said, “I had no idea that Croatians were that good in Ping-Pong.”

When everything was said, drunk and done, there were no papers and no signatures. There was a hug and a handshake between the two 21-year-olds. “Dude, I’d really love it if you would come and pitch for us next year,” said Damir. “I will, I promise,” said Jimmy.

It was up to Kruno to organize the plane ticket, a place to stay, free food and a little allowance every now and then. The brothers left, hoping Jimmy wouldn’t change his mind between November and March, and the winter fell on Ohio.

* * *

Baseball in Croatia dates to the end of World War I, when Americans from Navy vessels played exhibitions in the coastal city of Split. The local kids took to it and played a bit on their own. They got the equipment in exchange for other goods, as gifts and, as a legend has it, by opportune usage of moments when the sailors were not paying enough attention.

Or, as one historian phrased it, “they were more base stealers than home run hitters back then.”

But then, the Americans left, interest died down and it was going to be a long time before baseball was to be played in Croatia again.

* * *

The radio station the Summers family followed kept talking about bombardments in Bihać all winter long. Finally, Mrs. Summers opened a map, only to see that Bihać was as far from Karlovac as Columbus was from Dayton. She wasn’t thrilled.

But Jimmy was 21, he wanted to play ball and see the world, he had given his word and he just hated his job at KFC. “It was terrible. I mean, literally, I had to sink my arms up to my elbows into the buckets of frozen chicken parts and deep fry them. Over and over again.” Overseas, there was an opportunity to play baseball for money waiting for him.

The fear of the unknown, of bombs and conflicts was real. But the fear of wasting his life without trying something extraordinary was even bigger and Jimmy started packing.

* * *

One plane took Summers from Cleveland to Chicago and when the next one landed in Frankfurt, Germany, he was abroad for the first time in his life.

He was also scrambling to get his entire luggage transferred, for Jimmy Summers was not traveling light. “Everybody and their grandmother ordered something." he said. "I’m talking jerseys, gloves, bats, chest protectors, balls, cleats, batting gloves, you name it. I had a home plate, the four inch thick one. I was carrying duffel bags you could have hidden a NFL lineman in. Everything you can imagine, I had it.”

* * *

Not far away from that airport, a 12-year-old German kid was getting acquainted with the game of baseball. Simon Gühring, like his siblings, was blessed with both athleticism and curiosity, and when his older brother offered him the chance to come along to an introductory course on the American pastime his school was organizing, Simon said yes.

Simon had no idea just how deep his love for the new sport would grow to be. He was good at soccer and handball, but it was going to be baseball that would define his athletic career.

He also had no idea that he was going to cross paths with a pensive young American flying over him, on his way down South.

* * *

The war in Croatia started in 1991, and by the time March of 1995 came around, people were already used to it. There isn’t really a way to truly get used to war, but as worn out as the phrase sounds, life does go on.

As much as they could, people kept working, going to school, raising children, visiting relatives, falling in love and doing sports. War was like a dark gray background on the painting of everyday life and with time the focus went more and more to whatever bright spots could be found in the foreground.

* * *

Kruno was waiting in Zagreb, which is a 45-minute drive from Karlovac, as the plane from Frankfurt landed. The closer they drove toward Jimmy’s new home, the more visible were the signs of destruction. Most houses were scarred by shrapnel shots, some were completely destroyed and the ones that weren’t had their windows protected either by wooden planks or stacked sand bags.

There was also a funny rattling sound as they drove down the freeway. “What’s this noise?” Jimmy asked. “Oh, it’s just that the roads are like that after the tanks pass on it,” Kruno answered calmly. “No big deal.”

It was for real. It was different. It was unlike anything Jimmy could have imagined.

* * *

The first game Summers pitched was a spring training game against Zagreb, Karlovac’s archrival. He didn’t have his best stuff that day and he felt like he was getting squeezed a bit by the home plate umpire. He didn’t complain, though.

Jimmy Summers pitching for Croatia

“Croatian umpires were real characters," he said. "I remember one guy who was a policeman and always made a point of leaving his sports bag half open, so everybody could see he had a gun in it.”

Whatever the reasons, the new acquisition got hit around by the Zagreb squad and failed to make the impression he had hoped on both the fans and his new teammates. After the game, Damir, the starting shortstop, took him to the side.

“Jimmy, it’s not looking good," he said. "Our team president was in the stands, and he didn’t like what he saw one bit. He says your velocity is not where it should be, that you’re not holding the runners well and that, frankly, he thought your slider would have quite a bit more bite to it. He just doesn’t know what to do.”

Jimmy felt crushed. He had traveled to the other end of the world and after only one game there were already doubts about whether he had any future here. He pleaded his case vigorously until Damir’s face turned into a grin.

“Dude, I’m messing with you. He doesn’t even know the rules and he just said you looked like a nice kid. Let’s have a beer.”

* * *

The teams in Croatia had problems getting their hands on equipment, but the playing fields were a challenge, too. Karlovac had a nice field, somewhat ambitiously called the “Four Rivers Stadium” (take that, Pittsburgh!). The “four rivers” part was absolutely true, and by Croatian standards, “stadium” was probably in order, too.

Zagreb was constantly reshuffling its field and the work was carried out by the players themselves. As one player said, “We never knew when to bring the gloves and when to bring the shovels to the practice.”

Varaždin was using a multipurpose field shaped as a soccer pitch, posing problems of its own. Right field went on forever, meaning that any sharp shot over the right fielder meant an easy stroll for an inside the park home run. Left field, however, was only some 250 feet down the line. That called for some creative ground rules. Anything leaving the park to the left of the top of the poplar in left-center field was a double. Anything to the right of it was a home run.

Jimmy remembers his first game there. “(A huge teammate very appropriately nicknamed) Konan hit an absolute monster of a home run. I mean, he got everything on that one, it must have gone over 450 feet. I was in absolute awe.” It was also a double, as it left the field on the wrong side of the poplar.

You might think that playing left field in Varaždin was easy, with so little ground to cover. You might not know that there was a concrete Ping-Pong table in the middle of it.

Split had a quadrangular field as well, only switched so that the right field was the short one. The rugby team shared it, making Coliseum in September look as flat as an ice rink in comparison.

And those were the good fields.

Second division teams like Medvednica or Dugave didn’t really have a field at all. Before each game, they would build the field, and after every game they would pack all the stuff back and take it home. Sometimes, goats had to be chased off the field before the game. Sometimes, games had to be stopped as old ladies guided their wheelbarrows through the infield on their daily route they had no intention of changing for some kids’ games. But baseball was played regardless, with dedication and enthusiasm that impressed the young American.

* * *

Fields in Germany were scarce in the beginning, too, although unlike in Croatia, there was a lot of baseball played in and around American military bases, most notably in Mannheim area. Interestingly, the perhaps most instrumental person in popularization of baseball in Germany was neither an American nor a German, but—a Dutchman.

Jan van den Berg saw his first baseball game way back in 1951, when he was a 15-year-old. Roaming the streets of Amsterdam on a lazy August Saturday on his way back from a movie theater in another part of the city, he heard activity from a sports field nearby.

“I knew it couldn’t be soccer," he said. "There was a summer break and back then, it really meant that nobody was playing.”

Instead, it was baseball, a strange game Jan didn’t know a thing about. In the '50s, it was common for soccer players in Netherlands to play baseball during summer league stoppage. Almost every soccer team had a baseball department, and such great names of European soccer as Johan Cruyff of Ajax could be seen crouched in the catcher’s box or swinging the bat.

Jan watched the game for a while and he liked it. Soon after, he practiced for the first time and learned that he could throw the ball exactly where he wanted, albeit not very fast. He worked his way through the system for years, rising through the ranks of the juvenile teams first, and the senior competition later. By 1958 he played for the second team with occasional starts for the first team.

“We had a much better pitcher,” he laughs, “but he could go only once a week. So I got to pitch a lot of midweek games.”

Nobody confused van den Berg with an all-star caliber player, least of all he himself. But his talents were immense, nevertheless. Jan was a brilliant organizer, a persistent builder and an enthusiastic teacher. When a lovely lady he met in 1960 on Lake Constance turned to be the woman of his life, and when love made him move to southern Germany and spend the rest of his life there, the ground was set for Jan van den Berg to do what he does best—proselytize baseball.

* * *

By late April, Jimmy settled down. He had traveled to Rome for a tournament and played another one in Split, seeing beautiful European places he hoped to get to know. The team was finding the groove, winning the latter tournament against an ex-major league pitcher in the finals. They were doing well in the league standings and Jimmy himself was pitching well.

Then came May 1 and the Croatian Cup home game against Varaždin. Jimmy was the announced starter. It was a public holiday and there were to be festivities on the field after the game. He was psyched, wanting to show the home crowd what he was capable of. Kruno and Damir walked over to him and stopped his warm-up routine.

“We are going to be bombed in 20 minutes.”

There were no smiles and no fooling around this time. They dressed in silence and rushed off the field.

* * *

By the time Simon Gühring was born in 1983, Jan van den Berg had already founded or co-founded several teams around Simon’s birthplace and he was showing no signs of slowing down. He would hold seminars explaining the rules, he would help set the training programs, he would play, he would bring equipment from Holland in his old car. In short, he would do anything except take no for an answer.

Baseball always in the foreground - Jan van den Berg.
Photo Iris Drobny

His bouts with the city of Tübingen, another place where he co-founded a baseball team in 1985, are legendary.

When the city claimed there were no available fields for baseball teams to use, as they were all used by soccer teams, he divided the city in regions and sent his players on bicycles to check every single field on every weekend for a month. He then appeared in City Hall with a thick folder proving that many fields were not used to their full potential.

“The sports deputy was amazed that there were so many fields in Tübingen to start with,” remembers van den Berg with a smile.

When the city still declined to offer a dedicated baseball field, he devised a rotating plan and hosted a game in a different place each week. “Our opponents would come to the same place every weekend and then we would drive together to the field that was available for the day. Backstop, bases and everything else was in the car. We got pretty skilled in quick-building the field.”

When the city declined to make a gym available for baseball training during the winter, he organized practices in an abandoned theater. “I put the pitchers on the stage. These guys always wanted to be placed higher than anyone else and they craved for the spotlight,” he laughs.

Whatever problem arose, van den Berg had an answer. By the time Simon was starting to delve deeper into the game and Jimmy was scrambling for his life, Southern Germany had a pretty robust league structure already in place.

* * *

Jimmy and the brothers entered Karin family house just as the bombing began. For the second time they were sharing a basement, only this time there was neither a bar in it nor a Ping-Pong table. Kruno’s kids were with them and they were crying. So was his wife and so was his mother. They got the kids wrapped up and put them in a bathtub, trying to protect them as much as possible.

And then, Kruno walked over to the corner, turned on the TV and put a tape in the VCR.

Jimmy couldn’t believe it: “We were in the middle of a heavy, heavy bombardment. And there he goes, and plays a recording of the 1986 World Series.” Not that seeing that really helped improve the spirits of the Red Sox fan Jimmy was. But it did help cover the noises from the outside and only when Kruno would rewind a tape would they hear the explosions.

After a while, Damir slid over to Jimmy and said: “Let’s watch. C’mon let’s go upstairs and have a look what’s going on. But when we pass by the window in the hall, you have to walk quickly. A bomb just fell in the backyard. They might hit there again.”

Suddenly, NFAB Championship, KFC job and every other memory Jimmy had seemed as distant as if they were from another person. This was an utterly surreal dream and he was not about to wake up anytime soon.

* * *

Simon shot through German league system with ease. By the time he was 16, he was already on the junior national team, and by the time he was 18 he was so invested in baseball that he took up the offer to play in Winter League ball in South Africa. He did well and as he was staying in the apartment of Chris Miller, who was a scout for the Brewers, the question came. So did an answer. Just as with Jimmy, financial details didn’t matter much to Simon. The opportunity to play baseball professionally did, and a tiny signing bonus later, he was a member of Milwaukee Brewers organization, and he was about to play in Rookie ball in Arizona.

And just like Jimmy, he was a pioneer, one of the first to take that path into the unknown.

* * *

The next day Jimmy found himself trying to find some positives while giving the first-hand report to his family over the phone.

“Mom, the good thing is that Zagreb wasn’t bombed at all and it’s only half an hour away. So, if things get any worse, they promised to move me to Zagreb. Everything is under control, seriously. You can relax a bit."

Mrs. Summers was not relaxed at all. Her son was in an unknown world, thousands of miles away, being shot at, and he was barely old enough to legally drink. Of course, it didn’t help that Zagreb was bombarded on the next day.

While Jimmy was trying to sound confident and in control on the phone, he was anything but. Everything his mother was thinking was going through his head, too. So, it was Kruno’s turn to try to put things in perspective. He patiently explained to the young American that this was an anomaly, that things were not really as bad as they seemed to be. That many people, including himself, would have already been drafted to the Croatian Defense Forces if it were to get any worse. That he hadn’t been drafted and that he was still right there, talking to him, now wasn’t he?

It did make some sense, and Jimmy went to sleep a bit more at ease, if only a tiny little bit. Then, in the morning, Kruno woke him up to say goodbye, wearing camouflage from head to toes.

* * *

When Simon arrived in Arizona, there was a familiar face. His countryman and soon-to-be roommate Mitch Franke was repeating the level, so he helped Simon ease into things. The first year in the pros was a challenge for Gühring, as everything was new and the competition was tougher than anything before.

It also gave him an inside look at how tough a life in organized baseball can be outside of the diamond. “Anything and everything can change in a heartbeat. Today you are playing, tomorrow you can be cut or called up—you never know when you will need to move.”

Getting fully invested in such a lifestyle presented perhaps even a bigger challenge to Simon than nasty sliders and speedy baserunners trying to steal against him.
“My present wife and I had been together for a while back then already. Slowly, I started getting the feeling that family and baseball might not get as much hand in hand as I had envisioned."

Regardless, Simon returned in 2003. Having worked on his game hard, he saw his OPS rise by more than 100 points in his second go at the Arizona League. Even more importantly for a catcher, he was a bank behind the plate, cutting down more than 40 percent of potential base stealers, leading the team in that category.

Still, he was struggling for playing time. Just like Jimmy, Simon didn’t care much about the money, but while Jimmy’s playing days in Europe were made possible because he could fit into the tight Karlovac budget, Simon’s almost-nonexistent signing bonus demands were detrimental to his potential career.

* * *

You will not find many Americans who know as much about European baseball as Josh Chetwynd does. He played in the UK and in Sweden, and he compiled a very thorough and entertaining book, Baseball in Europe, covering the origins and history of baseball in 40 European countries.

He is also, as one scout put it, the reason European players became more expensive. Josh laughs, “I’m flattered to be mentioned like that, but I don’t know if I would go that far.”

His involvement with European baseball started in 1996 when he went back to his country of birth and became a member of Great Britain National Team. He later worked for the MLB office in London. During his playing days, he got to know European players better, a trend that continued after his playing career. Soon, he put his law degree to good use and started advising young European players who were about to sign with major league teams.

“The thing that many youngsters are not aware of," he says, "is that in most organizations the playing time and the willingness to be patient with the player are proportional to the amount of the signing bonus. And the players don’t really have any feel for what someone of their talent is worth. ”

Josh helps some negotiate a contract, but some get a scholarship to a university or a junior college, something without any financial advantage to him. And as for signing bonuses, he feels that they now much better represent true market value.

“I know of a situation where a kid was taken to a back room after a good showing in the MLB Academy in Italy and handed a phone. The voice on the other side said ‘We’ll take you for $15,000’ or whatever and that was basically it. The kid did not have any leverage, did not know whether it is a fair value or not. This is where I try to help.”

The other reason that signing bonuses in Europe have evolved so much (solid six-figures are not uncommon nowadays) is a much stronger scouting presence in Europe. While the Twins, the Reds and the Mariners were among the first to invest significantly, now every team covers the region, with either a full time scout or a combination of several part time scouts concentrated on specific countries.

Installment of the MLB Academy in Tirennia back in 2005 was a huge push, both for players' development and their visibility to the scouts. For two and a half weeks every year, the most promising teenagers selected from European and African national team programs train under the careful eyes of talent evaluators. These were several great breakthroughs for European players, but they all came too late for Simon Gühring.

* * *

Jimmy didn’t get bombed again that year, neither by artillery nor by opposing hitters. By the time playoffs came around, the rosters around the league were full again, baseball uniforms replacing the military ones, and Karlovac marched to the title, beating Zagreb in the finals.

The war was over in Croatia and Jimmy didn’t feel like going home just yet. Using a law provision for successful athletes, he became a Croatian citizen and a starter on the national team. For years he would keep playing and coaching, both in Croatia and Holland, enjoying every step of the way.

***

After a 2003 season in which he had only 63 plate appearances, Simon knew his days with Brewers were over. On one side the team had Bryan Opdyke playing his position; they had invested more than $200,000 in the fifth-round draft pick. On the other, it was not only that Gühring was not representing a significant investment, it was also that he was—a foreigner.

“I never had any problems being from what is an exotic baseball country. All the coaches and teammates treated me great. But, I needed a visa and they didn’t have any left for me.”

Simon Gühring in Berlin with Mike Piazza. Photo: Uwe Toelle, uwetoelle.de

In the post 9-11 era, major league teams saw their visa contingent dramatically reduced. Each organization had 40 visas for all the levels together and Simon knew the reality: “Why should a team give one of the coveted visas to a 20-year-old German, when they can give it to a 16-year-old Dominican?”

The timing for him could not have been worse; the Brewers shut down their teams in Dominican Republic and Venezuela in 2003 to keep costs down. That meant that the best players from those leagues got moved to the U.S. in 2004, further reducing the possibility of a spare visa for Simon.

It was time to go home and Gühring had no regrets.

“I gave it a shot. I’ve seen what it was like and those two years were very valuable to me. But, I’m not looking back and thinking ‘if only they had another visa,’ ‘if only I were born later and signed for a bigger bonus.' Things in life happen for a reason.”

Simon exchanged the 100-degree heat of Arizona for Heidenheim, Germany, where games can get snowed out in late April and never looked back. Every now and then he gets approached by players or scouts who say that they can’t believe he is not playing in the States, but he just shakes it off.

“I have my family with me, I have my home. I play good, competitive baseball and I have great fun doing it. Looking back, even if the alternative might have ended in the majors, I wouldn’t change a thing.”

***

It was in 2004 that the roads of the two baseball players crossed for the first time. Jimmy was pitching coach at ADO in Den Haag, Netherlands, when the club signed Simon. The two teamed up in giving clinics to Dutch baseball youth, many of whom are now a part of that national team that won the World Championship last year.

Jimmy kept postponing a return to the States, but when his wife got pregnant in 2007, the couple decided it was time to go home. He now splits his time between the family construction business and a Play Ball Sports Academy, a baseball academy he runs in Stow, Ohio. It’s exactly the wealth of experience of playing overseas that enables him to offer unique teaching style that resonates extremely well with local youth.

“Not only have I seen different styles of play, but lot of the kids that I taught how to play didn’t speak English well. That forces one to be very methodical and instructive.”

He hasn’t lost his competitiveness and still has one big goal—to pitch for Croatia in the World Cup opener against Mike Piazza’s Italy this year. He says, it's that exact thought that gets him out of the bed in the morning.

Looking back on that fall afternoon in 1994 and asked if he has any second thoughts about having chosen to go to Europe, Jimmy briefly pauses and speaks smilingly.

“None whatsoever. The only second thoughts I had were about going back to the States. My buddies who stayed in the States and played ball here were riding buses through Iowa and Indiana. I got to play in Rome, Amsterdam and Barcelona. I learned so much about life, but also about baseball. I’ve seen baseball grow over there, and not without some pride can I say that I was a part of it.

"I’ve seen a Croatian team beat the Pirates' Single-A affiliate, the Dutch one beat the Braves' Triple-A team. I’ve seen some of the kids I taught end up in the pros. There is no question in my mind—put me back in that cellar in 1994 and I’d do it all over again.”

* * *

Jan van den Berg stands next to the long line of people waiting for autographs and he can’t hide a smile. Long gone are the days in which he had to beg for an occasional usage of a soccer pitch. There are some great new baseball facilities and baseball boarding schools around now. The game between German and U.S. national teams during the World Cup qualifier in Regensburg was attended by more than 10,000 people. And now, during the European Championship in his Stuttgart, on a brand new field, people are lining up to get an autograph from—baseball players.

The German national team, captained by Simon Gühring, has closed the gap to traditional powerhouses Italy and Netherlands and played some close games against such teams as Cuba. Max Kepler-Rozycki of Berlin was signed by the Twins for $800,000. Kai Gronauer, with the Mets organization, made it to Double-A last year. Germany was added to the World Baseball Classic 2013 qualifying field. Things are looking up.

But much more than the success of its best, the essence of European baseball remains the one of unspoiled enthusiasm. Its most defining stories are not of its stars, but of thousands of others, who play because they love the game, perfectly aware that they will never in their lives enter a major league stadium without paying admission, yet hustling and caring and giving the game all they have just the same.

In a sense, it’s baseball how it used to be.

The fields might be scarce, but Daimlers are not. Memmingen, Germany

10,000 people gather in Regensburg, Germany to watch the home team take on U.S. in a World Cup qualifier.
Photo: Walter Keller, walterkeller.de

Team Germany gathers before a bronze medal game against Sweden. European Championship, Stuttgart, 2010

Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2012-03-26T09:10:15+00:00 Outfield assist of another kind http://www.hardballtimes.com/main/blog_article/outfield-assist-of-another-kind/ http://www.hardballtimes.com/main/blog_article/outfield-assist-of-another-kind/#When:08:38:15
Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2012-01-27T08:38:15+00:00 Losing Greg Halman: The view from Europe http://www.hardballtimes.com/main/blog_article/losing-greg-halman-the-view-from-europe/ http://www.hardballtimes.com/main/blog_article/losing-greg-halman-the-view-from-europe/#When:22:00:15
Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2011-11-21T22:00:15+00:00 Another one bites the dust http://www.hardballtimes.com/main/article/another-one-bites-the-dust/ http://www.hardballtimes.com/main/article/another-one-bites-the-dust/#When:05:05:15
Had I known from the beginning that the idea of designing a model to estimate the difficulty of blocking every major league pitch is not a new one—let alone a groundbreaking one—I might have spent significant portions of my free time doing stuff that involves sun and physical activity instead. But, I didn't. And, anyway, as Jovanotti already sang: "Se tutti i grandi libri qualcuno li ha già scritti, mi chiedo ragazzi voi che cosa fate?"

And, yes, I am aware you have no idea who Jovanotti is. Your loss, really.

Vertical or horizontal plane?

When deciding how to track the location of the pitches to be caught, I was considering two options, neither of which really seemed completely appropriate. With help from Mike Fast I was able to calculate the spot where every pitch would have landed had the ball traveled untouched until it hit the ground.

While this was really helpful for pitches that clearly landed in the dirt in front of the catcher, it gave us only obscure information about the rest of the pitches. Is a pitch that would otherwise land 40 feet behind the catcher easier or harder to block than the one that would land 30 feet behind him? And if two pitches both land 40 feet behind the catcher, do a curveball and a fastball cross the plane where the catcher is placed at the same height?

On the other hand, the PITCHf/x data offered the height and the width of every pitch as it crosses the front edge of the plate. This leads to similar problems. First, the catcher finds himself several feet behind that plane. Second, the balls in the dirt are represented with the negative height number, again leading us to guess where they bounced.

Discussing these issues with Tom Tango, it became clear that if we want to model reality, we have to make the model as real as possible. In this case it meant working in three dimensions and using both the horizontal and a vertical plane, the former for the pitches that usually bounce in front of the catcher and the latter for those that don't.

Catcher positioning

I placed the vertical plane three feet behind the back edge of the home plate, because that is where I expect the catcher's mitt to be most of the times. You might or might not agree with this. I don't think there is a singular correct distance from the plate that can be always used, as some catchers position themselves deeper than others and they also adapt to the batter positioning himself in the batter's box. Generally, they try to move as far ahead as possible without interfering with the swing.

The letter C in the above graphic is placed just about three feet behind the back edge of the home plate. And although the angle on the following shot of Yadier Molina doesn't show great perspective, I think it can be assumed that his glove—not his body—is just behind the end of the batter's box.

For sure, some of the pitches that would touch the ground a bit more than three feet behind the home plate will not be caught in the air. Similarly, some of the ones that would bounce just a bit in front of that imaginary line will be caught on the fly. As we are not dealing with the binary model here, it doesn't really matter all that much.

The model

After calculating the appropriate landing/crossing spots and creating some quick buckets, this is what the probabilities of a pitch getting away from the catcher looked like, depending on its location:

In a nutshell, we see that pitches that bounce are harder to block than the ones that don't and that pitches further away from the center of the plate pose more problems for the catchers than the ones which are over the plate. Incredible, right? Still, this kind of data presentation made it easier for me to visualize the certain areas where catchers have to receive the pitches.

Methodology

For the purposes of this research, I didn't really care whether the balls that got away from the catcher were scored as a wild pitch or as a passed ball. So, quite ingeniously and after many hours of creative brainstorming, I came up with a name for both of them together—Passed Pitch (PP). To determine the percentages in the above chart, we have to filter the pitches where a PP can happen in the first place. These are:
{exp:list_maker}With runners on base, all the called strikes, swinging strikes and balls*
With no runners on base, all the called and swinging strikes when the count is already two strikes
{/exp:list_maker}
* In addition, I decided to ignore all the pitchouts and intentional balls, although PP can occasionally happen on such pitches. The price of losing a few passed pitches seemed acceptable when compared to the danger of seriously skewing the data by including them.

Pitch location

I first looked at the PP dependency on pitch length/height. From the model above, the "length" of the pitch is the distance between the spot where the pitch bounced and the catcher's plane. It is represented with a positive Y number. The "height" is the distance above ground at the catcher's plane for the pitches that didn't bounce. It is represented with a negative Y number.

The further in front of the catcher the pitch bounces, the harder it is to block. The pitches between two and three feet above the ground are the easiest to catch and it deteriorates from there upwards. That was rather easy, the pitch width is more complicated:

What you see is the overall dependency and the absolute distances from the center of the plate. Before going into more detail, it can be said that in general, the pitches further away from the center of the plate are harder to block.*

* As I mentioned above, I ignore intentional balls and pitchouts. When I don't, it looks as if a ball four to five feet off the plate is easier to catch than the one three feet off.

Three more factors come into effect regarding pitch width. The batter handedness is one and it is basically a disturbance factor. The pitches inside are harder to block than the ones outside because the catcher has the batter and his bat to deal with and to obscure his vision of the ball. The other factor is that the width of the pitch doesn't seem to matter the same on different lengths of the pitch. A pitch that is a foot away from the center of the plate will not increase the chances of a PP by the same rate when it is in the dirt as it will when it is belt high, so I had to use multiple regressions.

And, finally, the center of the plate is not the easiest place to catch the ball, but rather a spot about half a foot to the left of it, as seen from the catcher's perspective. I assume it has something to do with the fact that all the catchers are right-handed.

Unlike batter handedness, the pitcher handedness didn't influence the outcome, although it did seem so in the beginning. Right-handed pitchers appeared to be tougher to catch, but it turned out it is due to the two factors we can otherwise control, pitch location and speed. More on speed in a second. On average, right handers threw about a mile and a half per hour faster than their left-handed counterparts and they threw to the places where catchers have tougher time catching the ball:

Other factors

Speed matters, but mostly only on the pitches in the dirt. There was a great correlation between pitch speed and PP percentage (controlling for the pitch location), but only on the pitches about a foot above the ground or lower ones:

As for the pitch movement, I saw some correlation between vertical movement and PP percentage on the balls in the dirt, but that mostly came by the way of speed correlation (faster pitches generally had more vertical movement). Horizontal movement did not seem to affect the probabilities on the short pitches, but showed some correlation on the higher ones. I decided against incorporating both of them into the model, as the correlations seemed inconclusive.

Instead of classifying the pitches by the type, going with speed and movement gives a fairer comparison, as both Jamie Moyer and Justin Verlander throw "fastballs," for example. But, at latest when I started with the individual rankings and saw where poor Jarrod Saltalamacchia ended up, it was clear to me that there is one pitch type that needs to be looked at separately:

On average, a knuckleball is seven times more likely to get away as other pitches of the same speed and in the same location are. Not everybody has the same problems with the knuckleball, though. Here is the list of all the catchers with at least 100 knuckleball pitches that needed be caught over the last four years:

These are rather small samples, but that's all we have (we'll get to what the numbers mean in a second, for now it's enough to know that numbers in the last two columns are bad when negative and good when positive). Every catcher performs worse against a knuckleball, but Saltalamacchia seemed to do an even poorer job than the rest of them.

Once the ball is not cleanly fielded by the catcher, other effects come into account, too. How far away from the catcher did the ball end up? How fast are the runners involved? Were they inclined to run based on the score? How much respect do they have for the catcher's throwing arm? How far do they have to run? The answers to the first four questions are evenly spread between "no idea" and "too much work to check it out," but the last one is rather easy. We can check the base runner's state and how it affects the probability of a pitch getting away:

Scoring from third and reaching first happen less often than the model predicts, while advances to second and third are more likely than what is calculated from other factors. It makes sense, too. Second base means the longest throw, and while first and third are equally far away from the catcher, the big difference is in getting the jump. The runner from second already has the lead and has nothing to worry about but running. The batter who just struck out might not even realize he has a chance to run until it's too late.

And here is the final one, the one that I found to be quite counter-intuitive. If a batter disturbs the catcher just by being there, him swinging will cause even more of a disturbance, right? So, controlling for everything else and looking just at swing-versus-no-swing states we come up with this:

The only explanation I can come up with is hit-and-run. The runner is being sent, the batter protects and swings at the bad pitch, the ball rolls away from the catcher. The runner from first would have made it to second anyway, but due to the fact that he started prior to the pitch, his advance is being credited as a stolen base and not as a variety of a PP. I let this one just be.

Putting everything together

I originally only used the 2010 and 2011 data to model the expectancies, because I wanted to use the 2008 and 2009 as a sort of a control group. That's true for the most of the regressions I used, although few of them occurred to me after I have imported the 2009 season (base runners, pitch type and swinging). After importing 2008, I ran a number of checks, comparing what my model would expect and what really happened. I looked at close pitches, clearly wild pitches, slow ones, fast ones, the ones by left handers, the ones by right handers, split them by inning, year and month and they all held up rather well. Here is the most random split I thought of:

I thought of using the day of the week, too, but I was afraid I could run into a replacement-catcher-on-a-Sunday-morning bias.

The bottom line is that this model has its inaccuracies. With what I looked at and the way I looked at it, they seemed to be acceptable. In no way or form am I suggesting that it is perfect—and I'm certain that there will be objections and/or desired improvements out there—but in order to carry on from here I will use it as an evaluation tool for the catchers. For better or for worse.

Evaluation

You want some names, right? Here are some names. This is the list of 15 best catchers in blocking pitches over the last four years:

What columns mean:
{exp:list_maker}cPP: Expected number of passed pitches from the model
Pitches: Number of qualifying pitches as described above
PP: Actual number of passed pitches
PP+/-: The difference, with positive numbers indicating catchers who blocked more than their fair share of pitches
Rpp+/-: The number of runs above or below average, using 0.28 conversion rate from The Book
Rpp120: Prorated runs saved using 120 games and the league average 42 PP qualifying pitches per game{/exp:list_maker}

And here are the 15 worst ones:

(complete data here)

The swing between the best and the worst catchers seems to be about one win a year. Or, put in absolute terms, over last four years Yadier Molina's performance blocking pitches was about three-and-a-half wins more than that of Miguel Olivo.

Is it a skill?

I used all the catchers with at least 1,000 chances in each of the last four years and split their even and odd years. This is how these two buckets compare:

(complete data here)

Glove versus arm

I mentioned that perhaps some catchers get good results blocking pitches because the runners are afraid to take their chances against good throwing arms. I checked the correlation between preventing base stealing and preventing advances on passed pitches, but found none:

Playing with the numbers

Recently, Mike presented his great research on catchers' skills in framing pitches. FanGraphs offers the data on the catchers' abilities to prevent stolen bases. What if we combined all these numbers for 2011?

(data for catchers with at least 500 defensive innings in 2011 here)

We see the heavy influence of the framing component. Alex Avila was below average both with his glove and his arm, yet he more than made up for it with the framing part. Mike Napoli lost his overall lead, but—for those of you counting at home—he was still five-and-a-half wins better than Jeff Mathis.

And, finally, I looked at the defensive talent spread observed in 2011, by defensive positions. I included all players with at least 500 innings played at that position and for everyone but catcher, I used UZR/150 numbers. For catchers, I once used only the stolen bases component of their defense and once the cumulative number comprised of all three components:

Next steps

Or, perhaps, previous steps? There are at least two other researches on this topic. Dan Turkenkopf wrote about it more than three years ago and Dave Allen took a similar approach as I did back in 2009. When I started my work, I was aware of the former, but not of the latter. Before you start asking me whether I've been living under a sabermetric rock or on a deserted island, let me preemptively admit—I did grow up on a small Mediterranean island that, by most standards, could be considered pretty deserted. So, I have that working for me.

What can be done next?

First, this model can be further improved upon. Just as I was finishing this article, I realized another dependency:

It took me a while to realize why the relative PP percentages went down in the last three rows. When there are runners on first, first and second or on every base and the count is already three balls, a passed pitch that was not swung at will be masked by the runner advancing on base on balls. I'll implement that into the model, but I do not expect any significant changes out of it.

The other thing we can see from this chart is that pitchers throw tougher pitches to block when they are ahead. So, a possible further step would be to look at the whole issue from the pitchers' side. Are pitchers more likely to go for the strikeout by bouncing the curveball in the dirt when they have a good blocking catcher? Is it quantifiable?

And, you know, you could always go discover Jovanotti's music.

Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2011-10-18T05:05:15+00:00 What can you get for $50 million? http://www.hardballtimes.com/main/blog_article/what-can-you-get-for-50-million/ http://www.hardballtimes.com/main/blog_article/what-can-you-get-for-50-million/#When:17:19:15
Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2011-10-02T17:19:15+00:00 The AL glad you left award http://www.hardballtimes.com/main/blog_article/the-american-league-glad-you-left-award/ http://www.hardballtimes.com/main/blog_article/the-american-league-glad-you-left-award/#When:17:25:15
Click here to learn about THT's download subscriptions.]]> Bojan Koprivica 2011-09-12T17:25:15+00:00