Archive for Player Analysis

One of the offseason’s most talked-about moves was the trade that sent Prince Fielder to the Texas Rangers in exchange for Ian Kinsler and gobs of cash. While universally (and rightfully so) viewed as primarily a salary dump for GM Dave Dombrowski and the Tigers camp, the Rangers have gained a strong bat to place in the middle of their batting order alongside Adrian Beltre and Alex Rios.

Yet unlike the much-theorized David Price trade, the Fielder deal was not a pure salary dump. Fielder stumbled mightily in his production in 2013. In 2012, he posted a robust .313/.412/.528 traditional slash line, with an impressive .940 OPS and 153 wRC+. According to Baseball-Reference’s oWAR calculations, 2012 was Fielder’s third-most valuable year at the plate with a 5.4 mark. All of this stands in stark contrast to Fielder’s 2013.

Last year Fielder posted a much more pedestrian .279/.362/.457, .819 OPS, 125 wRC+ and 2.9 oWAR. While of course those are still above-average numbers, when attached to the name Prince Fielder and his ubercontract, Dave Dombrowski clearly had reason for concern. However, off-the-field issues are widely believed to have contributed to the dip in Fielder’s production, and natural regression may have also contributed to the fall from Fielder’s career-high traditional slash line. Fielder also enjoyed a career-high .321 BABIP in 2012, with his 2013 mark of .307 more in line with his normal marks.

So, the question presents itself; what exactly does Texas GM Jon Daniels have on his hands in the 2014 model year Fielder? There are a number of factors contributing to this answer. Firstly, while the batters ahead of him do not contribute to his slash line, they certainly do help counting stats such as RBIs. While RBIs are naturally an utterly useless stat when evaluating individual performance, men getting on base allow a hitter to create runs, and as runs are ultimately what win games, putting men on ahead of big bats such as Fielder is part of what goes into good team creation. Therefore, I will examine the clip at which we can expect there to be runners on base when Fielder bats for Texas as opposed to his stint in Detroit.

Secondly, I will also examine the impact Arlington itself will have on Fielder’s bat. Arlington has traditionally been a much more hitter-friendly location than Detroit. But how much exactly will Texas raise Fielder’s numbers?

The top of the 2013 Tigers lineup consisted of Austin Jackson, Torii Hunter, Miguel Cabrera in front of Fielder. Those first three hitters posted OBP’s of .337, .334, and .442, respectively. That averages out to a .371 mark, albeit an imperfect one due to Cabrera’s significantly higher individual mark (also, Cabrera hit a lot of home runs last year, and while that counts towards his OBP, that means the bases were empty when Fielder came to bat). We’ll refer to this average of the top of the order as tOBP, or “Top OBP” for the rest of the article for the sake of saving space.

The top of the 2014 Rangers lineup will be made up of Shin-Soo Choo, and either Elvis Andrus or Jurickson Profar before Fielder, who will bat third. There are a number of different projection systems we can use to forecast the upcoming season, for this article we’ll be using Steamer. Choo is given a .391 OBP, Andrus a .340, and Profar a .321. With Andrus in the lineup the projected tOBP is .365, with Profar it’s .356. So despite throwing his wallet at Choo and his obscene .423 2013 OBP, Jon Daniels in fact is giving Fielder less to work with in front of him.

Or is he? Part of the smaller (projected) tOBP in Texas is that Fielder simply won’t have the best hitter in the game hitting in front of him anymore. Also, one has to expect Fielder to be better at the plate this year. Steamer awards Fielder a substantial .290/.390/.516 line with a 142 wRC+ and 3.4 WAR, a major uptick over last year’s production. If we factor him into the projected Texas tOBP, with Andrus it’s a .374, and with Profar it’s .367. That’s something you like to see if you’re Adrian Beltre, who lead the league in hits last year and launched 30 homers.

And speaking of homers, Fielder’s move to Arlington will help him in that department. The newly named Globe Life Park ranked seventh last year in home runs with a total of 107 being hit there. Comerica Park, where the Tigers play, ranked fourteenth with 99. This helps Steamer award Fielder 29 home runs, up from 25 last year.

However, can we possibly expect Fielder to exceed these projections? As mentioned earlier, Fielder’s down year was contributed to by a number of off-the-field issues according to Hunter. A change of scenery will definitely do Fielder well, and he also seems to have lost some weight if the pictures and video coming out of Spring Training are to be believed. For that reason I’m willing to bump up Fielder’s numbers by a few slots, and I expect him to be even better than what Steamer predicts. Because baseball is a fickle mistress I could easily be wrong, but call it a gut feeling. All in all, Jon Daniels may have caught lightning in a bottle here with his rather expensive gamble, and if Texas manages to overcome their pitching woes they should be a very dangerous team with Fielder anchoring their lineup.

Whenever one makes any conclusion based off of anything, a bunch of underlying assumptions get shepherded in to the high-level conclusion that they output. Now that’s a didactic opening sentence, but it has a point–because statistics are full of underlying assumptions. Statistics are also, perhaps not coincidentally, full of high-level conclusions. These conclusions can be pretty wrong, though. By about five-hundred runs each and every season, in this case.

Relative player value is likely the most important area of sports analysis, but it’s not always easy. For example, it’s pretty easy to get a decent idea of value in baseball while it’s pretty hard to do the same for football. No one really knows the value of a pro-bowl linebacker compared to a pro-bowl left guard, for one. People have rough ideas, but these ideas are based more on tradition and ego than advanced analysis. Which is why football is still kind of in the dark ages, and baseball isn’t. But just because baseball is out of the dark ages, it doesn’t mean that it’s figured out. It doesn’t even mean that it’s even close to figured out.

Because this question right here still exists: What’s the value of a starting pitcher compared to a relief pitcher? At first glance this a question we have a pretty good grasp on. We have WAR, which isn’t perfect, yeah, but a lot of the imperfections get filtered out when talking about a position as whole. You can just compare your average WAR for starters with your average WAR for relievers and get a decent answer. If you want to compare the top guys then just take the top quartile and compare them, etc. Except, well, no, because underlying assumptions are nasty.

FanGraphs uses FIP-WAR as its primary value measure for pitchers, and it’s based on the basic theory that pitchers only really control walks, strikeouts, and home runs–and that everything else is largely randomness and isn’t easily measurable skill. RA9 WAR isn’t a good measure of individual player skill because a lot of it depends upon factors like defense and the randomness of where the ball ends up, etc. This is correct, of course. But when comparing the relative value of entire positions against each other, RA9 WAR is the way to go. Because when you add up all the players on all of the teams and average them, factors like defense and batted balls get averaged together too. We get inherently perfect league average defense and luck, and so RA9 WAR loses its bias. It becomes (almost) as exact as possible.

Is this really a big deal, though? If all of the confounding factors of RA9 WAR get factored together, wouldn’t the confounding factors of FIP-WAR get factored together too? What’s so bad about using FIP-WAR to judge value? Well there’s this: From 1995 onward, starting pitchers have never outperformed their peripherals. Relievers? They’ve outperformed each and every time. And it’s not like the opposite happened in 1994–I just had to pick some date to start my analysis. Here’s a table of FIP-WAR compared to RA9-WAR compared to starters for the last 18 years, followed by the same table for relievers.

Starter RA9-WAR/FIP-WAR Comparisons

Reliever RA9-WAR/FIP-WAR Comparisons

Ok, so that’s a lot of numbers. The basis, though, is that FIP thinks that starters are better than they actually are, while it thinks relievers are the converse. And this is true year after year, by margins that rise well above negligible. Starters allow roughly 250 more runs than they should according to FIP every season, while relievers allow about 250 less than they should by FIP’s methodologies–in much fewer innings. In more reduced terms this means that starters are over-valued by about 10% as whole, while relievers are consistently under-valued by about 25% according to FIP-WAR. Now, this isn’t a completely new idea. We’ve known that relievers tend to outperform peripherals for a while, but the truth is this: relievers really outperform peripherals, pretty much all the time always.

Relievers almost get to play a different game than starters. They don’t have to face lineups twice, they don’t have to throw their third or fourth-best pitches, they don’t have to conserve any energy, etc. There’s probably a lot more reasons that relievers are better than starters, too, and these reasons can’t be thrown out as randomness, because they pretty much always happen. Not necessarily on an individual-by-individual basis, but when trying to find the relative value between positions, the advantages of being a reliever are too big to be ignored.

How much better are relievers than starters at getting “lucky”? Well, a few stats that have been widely considered luck stats (especially for pitchers) for a while are BABIP and LOB. FIP assumes that starters and relievers are on even ground, as far as these two numbers are concerned. But are they? Here’s a few tables for comparison, using the same range of years as before.

BABIP Comparisons

LOB Comparisons

With the exception of BABIP in ’96, relievers always had better luck than starters. Batters simply don’t get on base as often–upon contacting the ball fairly between two white lines–when they’re facing guys that didn’t throw out the first pitch of the game. And when batters do get on, they don’t get home as often. Relievers mean bad news, if good news means scoring more runs.

Which is why we have to be careful when we issue exemptions to the assumptions of our favorite tools. There are a lot of solid methodologies that go into the formulation of FIP, but FIP is handicapped by the forced assumption that everyone is the same at the things that they supposedly can’t control. Value is the big idea–the biggest idea, probably–and it’s entirely influenced by how one chooses to look at something. In this case it’s pitching, and what it means to be a guy that only pitches roughly one inning at a time. Or perhaps it’s about this: What it means to be a guy who looks at a guy that pitches roughly one inning at a time, and then decides the worth of the guy who pitches said innings, assuming that one wishes to win baseball games.

The A’s and Rays just spent a bunch of money on relievers, after all. And we’re pretty sure they’re not dumb, probably.

This article was inspired by the phenomenal work on 2013 shift data at THT by Jeff Zimmerman:
http://www.hardballtimes.com/expanded-2013-infield-shift-data/

Brian McCann’s 5 year 85MM signing by the Yankees has been noted as a pretty good deal as far as Free Agent contracts go. I do not necessarily disagree since he brings leadership and not wholly quantifiable defensive contributions as a marquee catcher. He posted an ISO above the .200 mark in 2013 for the first time since 2009 and reached 20HR for the 7th time in 8 seasons despite only playing in 102 games due to injury. His generally above average OBP rebounded from a career low .300 in 2012 to .336. His heinous .234 babip from 2012 regressed upward somewhat back to .261. While there are many outward signs that his 2013 bounce back re-established him as a premier offensive contributor (122 wRC+) there are some other numbers that give me pause about his future in New York.

I found Jeff Zimmerman’s 2013 infield shift data article fascinating in so many different ways but one of the major takeaways that I got from it was the disparity of shifting frequency across MLB divisions. Granted, a division with more extreme ground ball pulling shift candidates may lead to more shifts. However, the league leading Orioles had 470 shifts implemented on ball in play events compared to just 473 shifts in the ENTIRE NL EAST in 2013 (108 of those 473 NL East shifts were implemented by the Braves). Overall there were 1800 ball in play shift events in the AL East in 2013 compared to 473 shifts in the NL East. 11 of the top 15 shifting teams in 2013 MLB were AL clubs. (AL East teams are #’s 1,2,6,8,16 overall in # of 2013 shifts)

This is where Mr. McCann and his offensive future comes in: Brian McCann hit into 123 shifts out of 402 PA (30% of PA) in 2013. He hit .179 on balls in play against the shift and .299 when the shift was not on. For comparison David Ortiz hit into 338 shifts in 2013 in 600 PA (56% of PA). Obviously there are smaller than ideal samples in this data and we all know babip fluctuates wildly. That being said the shift deflated McCann’s babip to some degree unquestionably last season and probably has been doing so for a while (I’d love to see this data for 2012, 2011 etc. broken out by batter).

If generally shift-conservative NL East teams were exploiting this aspect of McCann’s game then you can bet he’ll see even more shifts in the shift-happy AL East and across the AL in general. McCann’s GB/FB distribution has stayed slanted toward FB throughout his career around a 0.88 ratio. He has seen his babip decline like most MLB veterans do post-peak. There’s a good chance that his babip will continue to decline and perhaps quite precipitously upon his move to the AL East.

I’ll end this article with an intentionally scary and possibly not totally fair comparison since it’s a strictly left handed hitter compared to a switch hitter: McCann’s career line is .277/.350/.473 with a .289 babip and 0.88 GB/FB ratio. Mark Teixeira’s Left Handed Hitting career line is .267/.359/.518 with a .277 babip and 0.87 GB/FB ratio. If McCann’s batting average/babip were to decline at a similarly faster than normal rate like Teixeira’s I’d blame those shifty AL rivals. The short porch in New York may create some extra HRs but the AL East defensive environment could take those gains away and then some on balls in play.

It will be interesting to compare the 2014 shift data to the 2013 season and see which teams decided to implement the shift more and less frequently. The caveat must also be mentioned that not all shifts are created equal and some teams were much more effective at converting shift balls in play into outs than others. Does that have to do with superior personnel/positioning?

Thanks again to Jeff Zimmerman for the inspired shift research that made this piece possible.

When Robinson Cano signed his 10-year, $240 million deal with the Seattle Mariners, it validated two things: (1) that the going rate for players who can consistently put up +5 WAR is at least $200 million, and (2) a second baseman who can hit like a first baseman is extremely valuable. There aren’t a lot of second baseman in the league who have the 30-homer, .500+ slugging percentage, and .316+ ISO, seasons that Cano does.

Second baseman aren’t considered to be players who have an excess of power. You can make an argument for guys like Ian Kinsler and Dan Uggla. However, neither is the player he used to be. Uggla is a shell of his former self, who can run into a dinger every now and then, but he’s not going to return to the power threat that he once was. While Kinsler has shown some above-average power for a second baseman, most of that power can be attributed to the friendly confines of  The Ballpark in Arlington. Kinsler’s power has also been waning over the past three years, as both his home run totals and slugging percentage have been in decline.

Kinsler’s Power Stats

2011: HR 32, SLG .477,  ISO .223

2012: HR 19, SLG .423, ISO .166

2013: HR 13, SLG .413,  ISO .136

Kinsler is obviously declining as a power threat, and the change from The Ballpark at Arlington to Comerica Park will probably not be kind to him, either. However, just because Kinsler is not hitting for above-average power doesn’t mean that he’s not a valuable second baseman. Kinsler can still hit for some power, and his glove is decent enough to make him one of the better second basemen in the game.

Uggla’s value is derived from his ability to draw walks and hit home runs. He has always had  trouble making contact, which in return drove down his OBP, making power the main reason he was good.

Uggla’s Power Stats

2011: HR 36, SLG .453, ISO .220

2012: HR 19, SLG .384, ISO .164

2013: HR 22, SLG .362, ISO .183

Like Kinsler, Uggla’s power has declined. However, this is to be expected given that he is 34 years old. What is more concerning is Uggla’s decline in slugging percentage, as he has had sub .400 slugging percentages for the past two years.  In both his 2012 and 2013 season, Uggla’s value derived solely from dingers. Uggla has  become a one-dimensional player when it comes to his bat.

Despite that two of the most powerful second basemen in baseball are declining in power, there remains hope in the form of the San Diego Padres’ new, young second baseman Jedd Gyorko.

Gyorko has the potential power of a first baseman. Last year, he hit 23 home runs, had a slugging percentage of .444, and ISO of .200. Considering that he was playing in Petco Park, which decreases homers by 13% for right-handers, his 2013 campaign was very impressive.

ZiPS and Steamer project Gyorko to hit between 20-25 homers next year, and to be somewhere between a +2.5 – 3.5 WAR player. Even if Gyorko’s 2014 campaign mirrors conservative projections, he is still going to be a top-10 second baseman.

Gyorko does comes with flaws. There are definitely some holes in his swing, which make him prone to strikeouts. He also is not going to have a high OBP. Gyorko is going to be a powerful bat with a decent glove, which recalls Uggla. Uggla has certainly had his struggles, and it’s not looking like he will turn things around. However, previously he was similar to what Gyorko appears to be: decent glove, above-average power.

Many of those who follow baseball — front offices, fans, certain baseball writers — seem to have profiles for positions. First basemen, third basemen and corner outfielders are thought of as powerful. Shortstops, center fielders  and second basemen are thought of as  having quick hands and being speedy. However, a player like Gyorko is valuable because he sets himself apart from the typical second baseman profile. Instead of being speedy and hitting for a high average, he’s powerful. Second basemen that hit like first baseman are rare, and that’s why Gyorko is a special player.

The Milwaukee Brewers have had a really quiet off season. Just how quiet? They only signed two players to major league contracts. For a team that needed a lot of help, two major league signings doesn’t seem like a lot. However, they did get a lot of help this off season. The other teams in the NL Central have failed to make a splash big enough to make the central a three team race again, and this is a potential opening for the Brewers to move in.

The Brewers were, and are, not expected to make a playoffs appearance during the 2014 season, but is that really true? They could. They very well could, and here’s how:

First, the three other teams who made the playoffs last season have regressed. The Cincinnati Reds have not done anything to improve. They lost their, arguably, two most important players to free agency in Bronson Arroyo and Shin-Soo Choo. The two players combined for an even six wins above replacement. Their replacements (Billy Hamilton and Tony Cingrani) have a combined WAR of 2.9, a 3.1 difference! Albeit, the two players have not been major players in 2013 having spent most of the season in the minors, but that is more reason to be concerned. Who knows how two second year major leaguers with little experience under their belt will do to replace two All-Star caliber players. Will the loss of Choo and Arroyo hurt the Reds? Of course! And Hamilton and Cingrani may not be the best replacements for a team who won one of the NL Wild Card spots in 2013.

The other team who didn’t make moves AND who won the NL Wild Card series, the Pittsburgh Pirates, is in a tougher boat. They lost several key players in Marlon Byrd, Justin Morneau, and A.J. Burnett and they replaced them with, well, nothing really. The only major league signing that the Buccos pulled off was for Edinson Volquez who had an absolutely atrocious season in 2013 and is the least likely replacement for an ace. Plus, first base and right field are still questions with no viable replacements at those positions. So does this mean that the Pirates will be out of the playoffs? I don’t think that the front office will go down without a fight. They want to appease their fan base and they still have many pieces in place to win over 80 games again, but unless they upgrade the rotation, first base, and left field, they are not going anywhere.

The final team and NL Central winners are perhaps in the best shape to make the playoffs again. The St. Louis Cardinals have done enough to maintain their dominance in the central. With Jhonny Peralta and Peter Bourjos in the fold including dominant young players such as Oscar Taveras and Michael Wacha, the Cards are looking like they will win another central title. But the Brewers might have something to say.

Other than the Cardinals, the Brewers have made the most important moves to improve their ballclub for 2014. They addressed all of their issues: The rotation, first base, and a left handed relief pitcher (according to ESPN). The rotation was fixed momentously with the addition of Matt Garza. Garza, one of the most sought after starters during free agency, will help to form a powerful front three rotation. With Kyle Lohse and Yovani Gallardo leading the way and Marco Estrada and Tyler Thornburg rounding things out, the Brew Crew’s rotation is looking like it can compete with the best of them. Plus, the addition of Garza helps to address another issue. Will Smith, a lefty who was acquired in the Norichika Aoki trade, will move to the bullpen. Here, the Brewers are able to add to an already strong bullpen that features a strong back-end and now a stable and reliable left handed pitcher.

Although the Brewers never signed a first basemen to a major league deal, the ones that they were able to acquire will impact the ball club in many ways. Mark Reynolds and Lyle Overbay will help what was a weakness for the Crew last season. Their combination of power, defense, ability to platoon, and familiarity to the NL Central and other leagues will impact the Brewers as if they had signed a major league contract. Plus, the Brewers have many great players in place at other positions. Jean Segura, Carlos Gomez, Jonathan Lucroy, and even Ryan Braun will make a formidable lineup while young players like Khris Davis and Scooter Gennett have shown that they can play at the major league level.

Overall, the Brewers are a much better team and are starting to look much better than the 2013 season. They have addressed all of their pieces while other teams in the NL Central have regressed. Although the Brew Crew may not make the playoffs, as many predict, they will cause havoc and surely improve from the 74-88 record they posted last season.

Ubaldo Jimenez: Check.

Suk-min Yoon: Check.

A.J. Burnett: Check.

Ervin Santana: Nope.

The first three names have all signed contracts within a week and a half, the last one has not. Ervin Santana, a top 50 free agent according to many, is still unsigned and, according to MLB Trade Rumors top 50 free agents list, the only starting pitcher unsigned. So what does that mean for Santana? Well, it means that he may garner a large contract with a large sum of money from a desperate team, or he’ll be robbed of what he’s actually worth. Steve Adams of MLB Trade Rumors predicted that Santana would receive a 75 million dollar contract over five years. Pretty good by any standards, but most likely not what he will get. Jimenez received 50 million while Matt Garza received 50 million as well only weeks ago, while Ricky Nolasco early on in the winter received a 49 million dollar contract. Of course, the annual average salary varies for each player, the highest guarantee salary is 25 million less than that predicted for Santana. So although he may still receive his projected 75 million, the likelihood of that happening looks slim. At this point in the stage, a four year deal seems logical, but I think with an annual salary of ~12 million, perhaps less. Although his career numbers and career in general don’t garner a salary like this, teams will match this price, or exceed it, in order to fill a hole.

The fact that Santana, and many other free agents, took so long to sign does not bode well with the player’s association and reflects negatively on the qualifying offer. The fact that a team is passing over a player with ties to a draft pick means A) that teams value their picks more so than ever and B) that the ability to win now is not as important as the future. Let me explain.

Option A makes sense. Many teams have depleted farm systems a la the New York Yankees and the Los Angeles Angels, so restocking their farm system and building towards the future (whether that be future trades, future post season aspirations, etc) is a viable, and necessary, option for all teams whereas option B is only for a few teams. Not every team is in a position to win now, so signing a player tied to their draft picks would be a lose-lose, but then you have the other teams who can win, and can win now. The Yankees clearly have attested to this. They have signed players tied to draft picks and thus lost those picks, but they are in an excellent position to win now, and for the future. You see, since a team loses a draft pick, they are obligated, but not obliged, to sign players to long term deals in order to make the signing worth wile. The Seattle Mariners believe this as do the aforementioned Yankees.

Thus the qualifying offer, although in place to help players which it does, can hurt teams and players alike. Teams can’t make respectable offers to players without losing their draft picks, and if they do, they tend to offer the player more money than he is worth. While the players, on the other hand, receive large paydays and security for their families, they do have to wait for a team to take a chance on him, if they even want to and lose their draft pick. And Santana perfectly reflects this. The notion that a team in need of a player (the Toronto Blue Jays for example) is not willing to offer a worthwhile deal to a player because they need the picks, while the player has to hope that what he receives is a viable, and legitimate, contract.

In conclusion: I do not like the qualifying offer. It ruins a team’s ability to sign a free agent while at the same time makes a player less valuable since his is tied to a draft pick.

So last year in my 10-Team, 35 man roster, dynasty fantasy baseball league, I found myself in need of some starting pitching after the first two months of the season. I was last in my league in quality starts, and near the bottom in ERA and WHIP. Manny Machado was my cornerstone 3^rd baseman, and he was hitting a fiery .355 for the month of May. For how good he is, I did not believe he was a batting title contender, so was interested in seeing what I could get for him.

Enter Justin Verlander. The Tigers’ ace, (at the time) had a 1.83 ERA and was 3-2 in April, and had hit a rough spot in May where he surrendered 16 ER in 12.2 innings. After going 17-8 with 239 K’s in 2012, I felt like this was a great time to buy low on the guy, while selling high on Machado. So I traded the Orioles’ phenom for the Mr. Kate Upton. Well, safe to say, that WAS NOT the trade that ended up winning me the league. From the end of May forward, Verlander posted a 3.36 ERA for the remainder of the season and was walking batters like it was the cool thing to do, posting a 3.07 BB/9 (which is AWFUL for him). He ended the season with a 3.46 ERA and only 13 wins, which were his worst totals in those categories since 2008. This isn’t an argument against Machado’s lack of offensive ability, which I will discuss at a later date. Instead, I will be telling you why Verlander’s performance last season was a fluke, and he will regain his Cy Young form in 2014.

As pitchers age, they usually lose a little oomph on their fastball. People will probably look at Verlander and assume this is the reason why he was less effective in 2013.

Based on the table above, you can see how he has lost some velocity on his fastball. For more detail, follow this link to view his velocity charts for 2013 and compare it to his prior years. If you notice, in his first five starts of 2013, his fastball average was hovering around the 93 mph mark, well below his average of the last four years, 95.2 mph. In those first five starts, Verlander posted an ERA of 1.83, had a K/9 of 9.38, WHIP of 1.19, and held batters to a .242 average. Even with a fastball that seems to be slowing down, Verlander has still found a way to retire batters, and more importantly, still strike them out. So the argument that his fastball is becoming “too hittable” isn’t necessarily correct.

BABIP, for those of you who don’t know, is the percentage of time that if a batter makes contact with a ball and puts it in the field of play, it will go for a hit. Generally, the league average for hitters falls somewhere between .290-.310. But there are plenty of factors that can influence BABIP, such as a player’s skill, defense behind a pitcher, and our good friend LUCK. More on that in a moment, but first, let’s establish what factors influenced Verlander’s BABIP. From 2008-2012, Verlander had an average BABIP of .282, which is below the league’s average range of .290-.310. Based on this sample size, we can assume Verlander’s skill set is above the mean for pitcher. Secondly, Defense. According to baseballreference.com, the Detroit Tigers ranked 12^th out of 15 AL teams last year in errors and double plays. On a more optimistic note, they were 4^th in fielding %. Those numbers indicate that they were a mediocre, at best, defensive team, which would cause Verlander’s BABIP to slightly increase toward the league mean. Lastly, we don’t have a way to measure luck, but Verlander’s 2013 BABIP was way above his recent average of .282, sitting at .316.

Point being, there were too many balls that were put in play that fell for hits considering all the conditions I stated above for Verlander.

It was not just his inflated BABIP that led to a down year in 2013 for Verlander. He posted a five-year high in BB/9, at 3.09. When you walk people and then give up hits, runners are bound to score. In 77.2 innings in June and July of last year he walked 33 batters. In the final 97.2 innings of last season and the playoffs, he only walked a combined 22 batters. He was able to regain his control in the second half that he had lost mid-way through 2013. I think the control he demonstrated toward the end of 2013 will carry over into 2014.

One more random stat to consider: Verlander’s IFH% (infield hit percentage) for his career sits at 5.9%. Last season, that stat jumped up to a recent high at 8.3%. Reasons for that stat being high could result from the inefficiencies of Miguel Cabrera at 3^rd base, or inconsistent defense of Jhonny Peralta. The Tigers now have the more athletic Nick Castellanos at 3^rd, and made a mid-season trade last year for Jose Iglesias. Both of those additions provide upgrades defensively for the Tigers compared to last year.

With everything that I’ve discussed, this guy is being way undervalued in fantasy drafts this year, going in the 5^th or 6^th rounds depending on the format. If you can grab him in the 4^th over guys like Zach Greinke or Madison Bumgarner, I would do so. He still strikes people out at a high rate, posting 217 K’s last year. Also, don’t forget that he pitches for a team with one of the most potent offenses in the game. When Verlander’s BABIP regresses, his improved defense and control kicks in, he will regain his righteousness.

The 2013 All-Star Game has already been played, and the result was decided. The AL defeated the NL in a 3-0 effort in a game  that was filled with players of all different types. The aging veterans who want a last hurrah. The rising stars who are getting their first taste of what it is like to play among the elite in baseball. The overpaid superstars and the underpaid superstars. However, I thought it would be interesting to assemble an all-star team of players with large platoon split.

Call it an Island of misfit toys or misfit all-stars, if you’re feeling Moneyball-esque.

Catcher

Vs. RHP Jason Castro: PA’s 380, wOBA .371, wRC+ 137

Vs. LHP Derek Norris: PA’s 173, wOBA .426, wRC+ 177

Combined: PA 553, wOBA .387, wRC+ 149

Castro doesn’t actually lead all catchers against RHP. That honor belongs to Joe Mauer. However, Mauer ranks within the top three catchers against left-handed pitching, which makes him not really have a huge platoon split. Therefore I rendered him ineligible as a platoon partner. It makes sense that the Athletics would have a catcher who is so effective in hitting left-handers, because they also have John Jaso who is known to mash righties (.363 wOBA vs RHP). If there is anything an Astro fan should be happy about  — which there isn’t much — it’s the fact that Jason Castro eats right- handed pitching for lunch and he also is one of the better catchers in the league.

First Base

Vs RHP Chris Davis: PA’s 434  wOBA .473, wRC+ 203

Vs. LHP Nick Swisher: PA’s 224 wOBA .398 wRC+ 158

Combined: PA’s 658, wOBA 447 wOBA, wRC+ 187

Davis was considered the best first baseman, as he led the league in dingers and compiled a WAR of 6.8. While Davis was performing at near-immortal levels against right-handed pitching, he was also very vulnerable against left-handed pitching with wRC+ of 104 against LHP. Nick Swisher is an interesting case because he is a switch hitter, but really struggles against right-handed pitching with a wRC+ of 93. This makes me wonder if Swisher should consider going the Shane Victorino route, and drop batting lefty to focus solely on batting right-handed. We don’t know if this strategy works for everyone — it’s probably a case-by-case situation — but it’s something to keep in mind.

Second Base

Vs RHP Robinson Cano: PA’s 420, wOBA .410, wRC+ 160

Vs LHP Brian Dozier: PA’s 148, wOBA .421, wRC+ 171

Combined: PA’s 568, wOBA .408, wRC+ 161

I had a hard time picking Cano simply because while Cano is definitely better at hitting righties than lefties, he’s not that bad at hitting lefties. Last season, Cano had a wOBA of .343 and wRC+ of 114 against LHP. That’s not a bad mark, however it is a sizable enough difference to create a platoon split. On the other hand, this points out that Dozier is a little underrated, and if he is used in the right roles, he could be a very valuable player. I find this platoon an interesting dichotomy: an overpaid superstar in Cano and a cost-effective role player in Dozier.

Shortstop

Vs. RHP Ian Desmond: PA’s 507, wOBA .344, wRC+ 118

Vs. LHP Jhonny Peralta: PA’s 136, wOBA .414, wRC+ 164

Combined: PA’s 643, wOBA .344, wRC+ 126

Shortstop was by far the hardest position for which to make a platoon. The LHP side was easy with Peralta because he led all shortstops when it came to facing lefties. The problem came with the right-handed side because the guys who could hit righties well — such as Tulowitzki and Lowrie — could also hit lefties pretty well. I settled with Desmond because even though he is well balanced against LHP and RHP, he wasn’t as balanced as Tulo or Lowrie.

Third Base

Vs. RHP Adrian Beltre: PA’s 516, wOBA .370, wRC+ 129

Vs. LHP David Wright: PA’s 150, wOBA .454 wRC+ 199

Combined: PA’s 666, wOBA .397, wRC+ 143

There were a lot of good-hitting third baseman last year. Miguel Cabrera led all third baseman in hitting against right handers and left handers. Wright and Beltre are number two to Cabrera. They also both have large platoon splits. Wright can hit RHP, it’s just that the split between PA’s against RHP versus his PA’s against LHP is huge. Beltre, on the other hand, is somewhat insignificant against lefties.

Right Field

RHP Daniel Nava: PA’s 397, wOBA .392, wRC+ 146

LHP Hunter Pence: PA’s 178, wOBA .415, wRC+ 174

Combined: PA’s 575, wOBA .399, wRC+ 154

This is where things can get a little arbitrary because there are a lot of corner outfielders, and therefore a lot of corner outfielders who have platoon splits. You could sub out both outfielders for a combination of Michael Cuddyer and Giancarlo Stanton. However, I thought that it would be more fun to point out how undervalued Nava is. Nava had a breakout year in Boston, and he did so by destroying right handers. Pence actually isn’t all that bad against RHP, wRC+ of 119 against RHP, which is kind of surprising considering he’s a lefty with a long swing. Bruce Bochy should probably take more advantage of Pence’s ability to hit left handers well. I think that both players are underrated.

Center Field

Vs. RHP Shin-Soo Choo: PA’s 491 wOBA .438, wRC+ 183

Vs. LHP Carlos Gomez: PA’s 140, wOBA .421, wRC+ 171

Combined: PA’s 631, wOBA .430, wRC+ 179

Choo is easily one of the worst defensive center fielders in the game, and he probably should shift over to a corner outfield spot in Texas. A lot of people express concern over the Choo contact because of the poor defensive play combined with a massive platoon split. Choo is godly against RHP, but below average against LHP (wRC+ of 81). The three-year, $24 million contract extension that the Brewers gave Gomez looks like it was a steal. Not only did they get a guy who punished left handers, but they also got a guy who led the NL in WAR, had great defense, and even some decent pop.

Left Field

Vs. RHP Dominic Brown: PA’s 381, wOBA .366, wRC+ 133

Vs. LHP Justin Upton: PA’s 164  wOBA .422, wRC+ 174

Combined: PA’s 545, wOBA .382, wRC+ 145

There isn’t anything interesting about why I picked these two, other than the fact that I did consider Matt Holliday instead of Brown. However,  Holliday’s split wasn’t as large as Brown’s. I wouldn’t expect Dominic Brown to perform as well against righties again; he’s in for some serious regression to the mean.

If these platoons were put into practice you could probably get as good or better production than the elite hitters in baseball. This list, just like the actual all-star game roster, is diverse. You have players who are considered elite — such as Choo, Cano, Wright, and Beltre — and then the undervalued guys such as Dozier, Nava, Norris and Castro. It’s surprising that most teams don’t take more advantage of platoons since they could get elite production from two players for a fraction of the cost.

Although the Nationals had a disappointing 2013 season overall, Tanner Roark (RHP) was one of their more pleasant surprises. The Nats brought him up in August, as injuries and performance problems created openings for several pitchers in their minor league system.

While Taylor Jordan also performed well, I think it’s fair to say that Roark had the most impressive and intriguing debut for the big-league team. Roark accumulated excellent “traditional” stats, and he did so at least in part by exploiting an unusual but highly effective talent: making batters not swing at good pitches. This post explores Roark’s story, and opens up the question of how his distinctive forte, zone-swing rate, contributes to effective pitching.

To recap, Roark finished 7-1 with a 1.51 ERA over 53 2/3 innings. He allowed only 1 home run in total, or 0.17 home runs per 9 innings; and the league batted .197 against him (– “batting average against” or “BAA”). The Nationals’ ace, Stephen Strasburg, allowed 0.79 home runs per 9 innings, with a BAA of .205. Roark was comparable in BAA to Strasburg, and much, much better at preventing home runs.

Of course, Strasburg reached his figures in 183 innings of pitching as compared to Roark’s 53 innings of pitching. This is what is sometimes described as a smaller sample. But we should not discount Roark’s performance too quickly. His 53 innings involved five starts and nine relief appearances, and a total of 12 appearances with at least two innings pitched. This is considerably more than, say, one start and no relief appearances. Roark played for the Nationals for the last two months of the season. His stint in the majors last year was substantial enough, I think, to merit serious interest.

Roark’s 2013 performance was surprising in part because of his pedigree. In 2012 Roark was 6-17 as a starter in Triple-A, pitching for the Nationals. His 2012 ERA in Triple-A was 4.39 (although his FIP [Fielding Independent Pitching rating] of 3.85 was better). Providing more background, Adam Kilgore wrote in September 2013 that

Roark has never been regarded as a star or a significant prospect. In 2008, the Rangers drafted him in the 25th round. The Nationals acquired him and another minor league pitcher for Cristian Guzman at the 2010 trade deadline. Last winter, the Nationals left Roark unprotected from the Rule 5 draft for the second straight year. They invited him to major league spring training this year, and shipped him out in the first round of cuts.

(Washington Post, Nationals Journal, 9/17/2013; http://www.washingtonpost.com/blogs/nationals-journal/wp/2013/09/17/tanner-roarks-incredible-start-built-on-command-feel-for-pitching/)

Roark’s 2013 performance was also surprising because, with a fastball averaging 92.6 mph, he had good but not overwhelming velocity.

Going back to FIP and similar topics, another reason why Roark’s 2013 performance was surprising was because of some relationships between his statistics. For instance, although his 2012 Triple-A ERA (4.39) was higher than his 2012 Triple-A FIP (3.85), this relationship reversed itself last year in the majors, with Roark posting a 1.51 ERA and a 2.41 FIP. In addition, his xFIP (“expected Fielding Independent Pitching”) was 3.14, significantly higher than the FIP.

“ERA < FIP < xFIP” spreads of this size are not unheard of, but they are rare, especially when your ERA is less than 2.00. In fact, ERA < FIP < xFIP distributions of this type suggest that you are identical to Clayton Kershaw (1.83 ERA / 2.39 FIP / 2.88 xFIP) and that you have just signed a contract worth 215 million dollars!

These observations about Tanner Roark’s performance and pedigree raise several questions:

How did he perform so well in 2013?

What is going on with his ERA<FIP<xFIP distribution?

What can we say about his future performance?

Taking a quick initial look at the ERA<FIP<xFIP distribution, a “negative” delta between ERA and FIP is often attributable to the pitcher having a low Batting Average on Balls in Play (BABIP). Roark’s BABIP was indeed very low, at .243. (Kershaw’s was .251).

Also, although this might sound odd, Roark’s extremely low HR rate (0.17 per 9 innings) pushed his ERA below his FIP, even though home runs are a fielding-independent matter. Roark was fine (league average or better) on the other FIP elements — walks, K’s, HBP’s. But combining these normal-range statistics with his homer rate produces a compromise number and some information loss.

Turning to xFIP, this calculation substitutes out the pitcher’s own homer rate for the league average homer rate. As we might expect, the league average homer-rate was much higher than Roark’s, and this explains the FIP < xFIP delta, while also contributing to the delta between his ERA and his xFIP.

These observations tend to intimate that some of Roark’s statistics are not likely to repeat themselves. Before turning to the “future performance” question identified above, I want to look more at the first question of trying to understand Roark’s 2013 success. There are aspects of Roark’s pitching last year which suggest that his strong performance numbers were not an accident, and that his apparent prowess is not simply overmagnified by the small prism of his innings total.

The first statistic of interest is that Roark was seriously good at throwing pitches in the strike zone which batters did not swing at. This is the Z-Swing% statistic recorded on FanGraphs and other places. Roark’s Z-Swing rate in 2013 was 54.8% (per Baseball Info Solutions [BIS]), or 55.9% per PITCHf/x. This means that batters only swung at Roark’s pitches in the strike zone about 55% of the time.

(BIS and PITCHf/x converge around 55% for Roark’s Z-Swing%. These systems actually diverge, or report different percentages, for some other stats which are not independent of Z-Swing%. Although this is interesting, the differences do not materially affect our evaluative questions. I will cite the BIS plate discipline statistics throughout and compare them to PITCHf/x at various points below).

The complement of Z-Swing% is what I will call “Z-pass” — the phenomenon of non-swings on pitches in the strike zone. Tanner Roark’s Z-pass rate last year was 45% — batters passed on about 45% of his pitches in the strike zone.

This was a very high Z-pass rate. In fact,

• It was the highest Z-pass rate on the Washington Nationals, by about 5 percentage points, among Nationals pitchers with at least 50 innings.

• It also was more or less the highest Z-pass rate in all of major league baseball, again among pitchers with at least 50 innings. Roark came in first in Z-pass rate according to BIS. According to PITCHf/x, Roark was tied for sixth-best in Z-pass rate, behind Sonny Gray with a 47% Z-pass rate.

A high Z-pass rate is indicative of several good pitching qualities. Z-passes are good because they mean that batters are laying off a higher number of pitches which damage their cause and advance the pitcher’s cause. A high Z-pass rate indicates that the pitcher is accumulating strikes while maintaining an atypically lower risk of allowing a hit. (This is true if the pitcher is hitting the strike zone at a reasonable rate. More on this below). Tactically speaking, the Z-pass is the best outcome on the swing v. strike zone matrix below.

Swings on pitches in the zone and out of the zone can lead to hits, and worse. By contrast, if we assume that non-swings in the zone lead to strikes, the Z-pass simply constitutes a good outcome for the pitcher.

How often did Roark throw strikes? In 2013 Roark hit the strike zone 47.7% (BIS) of the time. This was about 3 percentage points ahead of major league average (44.9%). 3 percentage points comes out to about one standard deviation above average. (PITCHf/x reports a higher league-wide strike-zone rate — 49.4% — and a higher strike-zone rate for Roark as well, at 53.8%. PITCHf/x appears to have a larger strike zone than BIS).

It therefore appears Roark was exploiting his elite Z-pass rate often enough for it to be useful, and indeed for him to have an advantage over hitters. Roark accumulated strikes at a good rate; and, by strongly suppressing swings at pitches in the zone, he lowered the risk of allowing a hit. It appears this dynamic was a main factor in Roark’s success in 2013. That’s part of the answer to our “How did he perform so well” question.

Another factor which stands out from Roark’s strike-zone data is that he threw first-pitch strikes 70.6% of the time. This tied for third in major-league pitchers with at least 50 innings in 2013. Consistently gaining an initial advantage over hitters, and doing so at an elite rate, was another main factor in Roark’s success.

Other discussions of Roark have cited his command, his aggression, and an improved mental approach. Going back to Adam Kilgore, he writes:

Roark’s ascension began last season, when he told himself he would not allow his temper to control him on the mound. He would not the things out of his control – fluky hits, errors, whatever – distract him. He would throw strikes. He would be confident. He would attack, above all else.

“I feel that last year is when I had my, I guess, mental turnaround,” Roark said. “That was the biggest thing for me.”

(Washington Post, Nationals Journal, 9/17/2013; http://www.washingtonpost.com/blogs/nationals-journal/wp/2013/09/17/tanner-roarks-incredible-start-built-on-command-feel-for-pitching/)

We can certainly see command at work in Roark’s low homer rate, and his low walk rate (5.4%). We can see both command and aggression at work in his first-pitch strike rate. Roark’s league-leading Z-pass rate substantiates the command/aggression understanding of his performance, and also adds to this understanding.

A pitcher who suppresses swings on pitches within the zone is presumably hitting unattractive parts of the zone, but he may also be throwing in-zone pitches which do not present to hitters as strikes. This sounds like a pitcher on whom it is difficult to make good contact. This is a third idea, beyond Z-pass rate and first-pitch strike rate. One way, however, to be averse to good contact is to be a high Z-pass pitcher.

Being a high Z-pass pitcher does not entail being a high strikeout pitcher. Roark’s strikeout rate was only one percent below major-league average (again, among pitchers with 50 innings and up). Of course, on other measures, like ERA, Roark was much better than league average. I think that connecting Z-pass rate with suppression of good contact can help us understand why.

Z-passes represent hittable pitches – pitches in the zone – which were not hittable enough to induce a swing. Poetically speaking, Z-passes involve real visual ambiguity: since they end up in the strike zone, they can’t look that bad; but they do not look good enough to induce a swing.

How well does this characterization actually apply to Roark’s pitches? On this question, we have the following from the Atlanta Braves:

“He wasn’t missing with any pitches over the plate, it seemed like,” said Braves catcher Gerald Laird. “When he was going away, he was throwing that little two-seamer back door, when he was coming in he was running that two-seamer in on your hands, and he had that little slider working.

“Tonight it seemed like he was hitting his spots and wasn’t making any mistakes. I know (Freddie Freeman) was saying he was starting it at him and running it back over. When he’s doing that it’s hard to pull the trigger.”

(http://www.washingtontimes.com/blog/nationals-watch/2013/sep/17/tanner-roark-shines-nationals-complete-doubleheade/#ixzz2prxGGOUh)

Of course, these descriptions of visual ambiguity — or of evidence which shifts within a fraction of a second — presumably apply to all or most of a high Z-pass pitcher’s offerings, not just to his pitches in the strike zone which do not elicit a swing. The image that emerges is of a player whose whole volume of pitches is tough to react to in a manner that creates good contact.

Roark was actually pretty good at inhibiting contact of any kind, especially on pitches within the strike zone. However, a look at his contact numbers does not immediately confirm this interesting and important point. As we see in the table below (from BIS by way of FanGraphs, again looking at 50+ IP), many of Roark’s contact rates were actually above league average, sometimes by more than one standard deviation.

Before turning to contact rates, you will have noticed that this table also gives us a look at how Roark’s Z-swing rate compared to the rest of baseball. According to BIS, Roark was 3 standard deviations above average on a positive pitching statistic which is completely independent of fielding. He was two standard deviations (56% Z-Swing%, as opposed to 63% league average) ahead according to PITCHf/x — this is still pretty good for a former 25^th-round pick! Some other observations:

• O-contact. Here Roark was much higher than average, but this may not be a bad thing, since contact outside the zone is less likely to be productive for the hitter.

• Z-contact. Roark again was higher than average. But this somewhat unsettling number should not be digested outside of its relevant context, which is helpfully provided by Roark’s Z-swing rate. Looking at Z-contact multiplied by Z-swing yields the interesting result that Roark allowed contact on 51 percent of his strike zone pitches, as opposed to a league average of 57 percent, with a standard deviation of 3 percent.

(PITCHf/x condenses this gap, in much the same way that it condenses the gap between Roark and MLB on Z-pass. PITCHf/x reports Roark at 52.2% contact on all pitches within the zone, and MLB at 54.6%. Thus, if we switch from BIS to PITCHf/x, Roark’s contact rate goes up, and MLB’s goes down.

However, as noted above, PITCHf/x appears to be working with a larger strike zone than BIS (MLB-average Zone% of 49.3 vs. MLB-average Zone% of 44.9). This point complicates Roark’s apparent movement back towards league average. In brief, the fact that Roark’s swing rates go up — while the MLB average goes down — on larger renditions of the strike zone may be a testament to his effectiveness, rather than a knock against it.

• SwStr (swinging strikes/total pitches). Since Roark did a good job suppressing contact within the zone, Roark’s low swinging-strike number does not seem to be an especially important piece in his overall puzzle.

The standard contact rates reported by BIS and PITCHf/x do not do a good job of communicating how well a pitcher actually prevents contact, because these contact rates only look at swings. Since you can suppress contact by suppressing swings, multiplying the contact rate by the swing rate provides a better view of how a pitcher is actually doing along this dimension. Despite a “zone-contact” rate which was higher than league average, Roark was very good to excellent at suppressing contact within the strike zone.

We are exploring a clue provided by Roark’s excellent Z-pass rate that Roark was good at inhibiting solid contact. This clue was supported by our look at Roark’s contact rates, which indicate that he was pretty good at suppressing contact flat out. The idea that Roark’s pitches were visually ambiguous enough to limit good contact receives further confirmation from his batted-ball statistics. In addition, looking at these statistics (2013, 50+ IP) will bring us around nicely to the question of how well Roark might sustain his performance in future seasons.

Roark’s ground-ball, fly-ball, and infield-fly rates combine to indicate a strong bias against good contact. Roark had a somewhat high line drive rate, and, admittedly, line drives are a form of good contact. For instance, I suspect it’s unusual to have a somewhat high line-drive rate and a markedly low BABIP. Roark’s line-drive rate provides one specific indication that his BABIP is due to increase. However, a low line-drive rate is not entirely at odds with the idea that a pitcher is suppressing good contact — especially if we are thinking about home runs. Since most line drives are not home runs, a slight tendency towards line drives is a small but genuine homer-prevention measure.

In this way, Roark’s line drive rate coheres with his ground-ball, fly-ball, and infield-fly rate statistics. All of these rates, and especially their combination, suggest a low-homer pitcher. Why didn’t Roark give up a lot of home runs? Well, he got a lot of grounders and infield flies, while limiting his fly balls overall, and he gave up a somewhat high proportion of line drives. It is very plausible to suppose that Roark’s extremely low HR/FB rate overshoots the anti-homer bias suggested by his other batted-ball rates. Equally, however, the other rates tell a clear enough story that a low homer rate is not at all a surprise. Roark was very good at inhibiting good contact.

How will he do in the future? A nice way to frame this question is in terms of Roark’s ERA, FIP, and xFIP numbers mentioned earlier. And, leading up to that, I think it’s helpful to assess the respective importance of two things: (1): the overall coherence of Roark’s 2013 statistics; and (2) the sample sizes in which they were achieved.

In terms of coherence, Roark’s statistics tell a consistent story:

• Looking at Z-pass, Roark was very good at limiting swings on good pitches

• Looking at Z-swing * Zone%, Roark was very good at limiting contact within the zone

• Looking at his batted ball rates, Roark was very good at limiting good contact

I could be wrong about this, but I do not see relationships among Roark’s 2013 statistics which point to trouble looking ahead. These statistics tell a consistent story of effectiveness. You can focus on his low swinging-strike rate if you like, but this rate was consistent with Roark being at least one standard deviation (two sd’s according to BIS) better than average on limiting contact within the zone.

In addition, there are pockets within Roark’s portfolio where some stats are very good and others are even better, like the HR/FB rate relative to Roarks other batted-ball statistics. However, this type of overshooting is a good problem to have. To the extent that the non-harmonic components of Roark’s statistical portfolio are extremely good statistics, this relates to the issue of our expectations for future years. A version of Tanner Roark based on 2013, but without the extra anti-homer overshooting, would still be above MLB-average.

As noted above, Roark only pitched 53 innings, and that’s a much lower total than what a starting pitcher would typically accumulate over a full year. Although we intuitively regard this as a small sample, it does not follow that Roark’s performance is without predictive value. As is often pointed out on the pages of FanGraphs, statistics stabilize, or acquire predictive value, at different thresholds (http://www.fangraphs.com/library/principles/sample-size/). Generally speaking, fielding-independent stats stabilize more quickly for pitchers than fielding dependent stats; this is a helpful point in assessing the forward relevance of Roark’s 53 innings.

Some of Roark’s relevant statistics are above their stabilization thresholds. Roark allowed 153 balls in play (BIP), which puts him above the stabilization points for groundball rate and flyball rate:

70 BIP: GB rate

70 BIP: FB rate

Roark faced 204 batters, which is above the stabilization points for walks and strikeouts:

70 BF: Strikeout rate

170 BF: Walk rate

However, Roark was league-average in K’s and was “only” one standard deviation above average in walks; these numbers are not as good as Roark’s plate discipline statistics like Z-pass and suppression of contact within the zone. So it’s not clear whether Roark reached the stabilization points for key parts of his performance.

But this is more or less where I will have to leave it. Figuring out the stabilization point for Z-pass is beyond the scope of the present study. Indeed, my post has probably pushed us to near overload regarding things that we ever wanted to know about Tanner Roark! By the same token, it’s not clear that learning more about Roark’s statistical profile would shift our opinion much about his prospects for future performance. This is what I think we have to consider:

In an intuitively small sample size, Roark put up a consistent portfolio of excellent fielding-independent stats: on limiting zone-swings, limiting contact in the zone, and limiting good contact. Very broadly, the size of a sample has to be balanced with the consistency of the evidence within it. Just imagine watching a one-round boxing match in which one competitor knocks the other one down three times. This is a small sample which tells a very compelling story about the respective abilities of the boxers. Roark’s sample size is larger, of course, and his performance was not as dominant. Nonetheless, his limited 2013 season is packed with a lot of positive indicators.

Here are a few final comments about what Roark might do in the future, framed in terms of his ERA, FIP, and xFIP:

As we discussed above, the delta between Roark’s ERA and FIP is primarily a matter of his low BABIP and his very low homer rate. Although Roark’s BABIP will probably go up, there are signs he may be better than average at suppressing hits: he showed a tendency to induce ground balls and infield flies; the latter especially inhibit BABIP.

Roark’s very low homer rate pulls down both his ERA and his FIP. Although his .17 homers per 9 innings will almost certainly go up, there are signs he may be better than average at suppressing home runs…signs which are distinct, that is, from his one homer allowed in 53 2/3 major league innings!! Roark’s tendencies toward ground balls, infield flies, and line drives are all anti-homer measures. These tendencies flow, by hypothesis, from his ability to inhibit good contact by throwing visually ambiguous pitches.

The most eligible view by far is that Roark will regress towards league average in future years. But accepting this view should not deprive us of optimism. Roark could go back at least one standard deviation on each of the ERA-like measures and still be at league average or better than league average. That’s a good position for any pitcher. It’s a great position, albeit a paradoxical one, for a pitcher who is currently slated to compete for no better than the 5th spot in the Washington Nationals’ 2014 starting rotation!! Suffice to say I think that Roark ought to receive full consideration for the opportunities available to him.

Earlier today, I was looking at trends and projections for some Cubs prospects and looked up Starlin Castro.  A trend immediately struck me: his 2010 batted ball statistics are nearly identical to his 2013 peripherals.

Stat:      ISO         LD%        GB%       FB%      IFFB%

2010:   .108      19.5%      51.3%     29.2%     7.0%

2013:   .102      19.9%      50.7%     29.4%     7.6%

These two seasons are closer than any of his other seasons in batted ball numbers.  A key difference?  2010 BABIP was .346, 2013 BABIP was .290.  His career BABIP is .323.  So is it we assume some good luck in 2010 and bad luck in 2013?

It should be noted that his BB% in 2013 was his career low, and his K% was his career high mark.  So can we expect some regression in those numbers as well?

I think the answer is yes to both questions.  In 2012, his BABIP was .315.  Even if Castro could return to that level (right around his career average), he looks much better than the .245 hitter we saw in 2013.

Additionally, his K% in 2013 was 3.8% higher than his previous career high, so I tend to expect a slightly lower rate in 2014 (though his contact rate in 2013 was also the lowest in his career, so if that is a trend, it is possible the K% could stay).

I’m still a firm believer in the idea that the past management, while trying to teach Castro to be selective and patient, actually taught him to take pitches for the sake of, well, taking pitches.  This could also potentially explain the low contact rate.  The numbers indicate that he didn’t learn to distinguish balls from strikes any better, and that maybe for him, the best approach is to swing at whatever looks good.

Given the striking similarities between his rookie season in which he hit .300 and garnered national attention as an upcoming star and 2013, it’s easy to dream about a bounceback 2014 season.  Only time will tell if that’s a reality, but I believe that Cubs fans have reason to be optimistic.

(I posted this earlier at the-billy-goat.mlblogs.com.  For more Cubs news and analysis, feel free to check out the blog.)