The BABIP gods are a most fickle bunch. They come and go as they please, gracing the bats of some while abandoning others altogether. Take Chris Johnson, for example. Aided by a .394 BABIP (roughly 10% greater than his career average), Johnson finished second to Michael Cuddyer in pursuit of the 2013 NL batting title. This season, however, Johnson’s batting average has dropped 58 points following a BABIP regression. Losing a portion of his hits has certainly hurt Johnson’s offensive production — this season, Johnson has produced runs at a rate 19% below league average.

BABIP is not entirely driven by luck, however. In fact, each hitter’s batted ball profile influences their BABIP. Generally speaking, players who hit more line drives and ground balls carry a higher BABIP than fly ball hitters. While it seems reasonable for Derek Jeter and Joe Mauer to carry career BABIPs in the neighborhood of .350, expecting Adam Dunn to sustain a similar BABIP would be folly.

Now, to Chris Iannetta. Sporting a career fly ball rate of 42.8%, the Angels’ backstop is a true fly ball hitter. Iannetta’s 2014 batted ball profile bears a striking resemblance to that of his 2013 campaign. Observe the table below:

Table 1: Batted Ball Profiles for Chris Iannetta, 2013 & 2014

Very similar. Although a hitter’s BABIP is not solely dependent on his batted ball profile, we might reasonably expect Iannetta’s 2014 BABIP to reside in the neighborhood of his 2013 mark. Well ladies and gentlemen, at the time of this writing, Chris Iannetta carries a 2014 BABIP of .330, a mark 16.6% above his career average of .283!

A peculiar development indeed. Let’s take a step back and examine Iannetta’s run production in a broader context:

Table 2: Offensive Production for Chris Iannetta, 2013 & 2014

The BABIP gods have certainly smiled on Iannetta this season. Despite the same ability to hit for power and a minor dip in plate discipline, Iannetta’s BABIP spike has fueled a 16% increase in run production. Among catchers with a minimum of 350 plate appearances, Iannetta’s wRC+ currently ranks him the sixth-best hitting catcher in the league. Iannetta’s newfound singles are certainly helping the Angels’ cause.

Because of random variation and luck, it is hardly rare for a hitter to experience a jump in BABIP. What is truly remarkable, however, is that Iannetta’s BABIP has jumped 15% above his career average while he has produced fly balls at a rate 20% greater than league average. To experience such a spike in BABIP while hitting a high percentage of fly balls seems quite rare. But how rare?

In order to better appreciate the peculiarity of Iannetta’s season and look for possible comparisons, I searched the past five seasons for players who experienced a BABIP jump 15% greater than career average while producing fly balls at a rate 20% above league average. Consider the table below:

Table 3: From 2009-2013, Player Seasons with a BABIP 15% Greater than Career Average, Fly Ball Rate 20% Greater than League Average (Minimum 400 PA)

That’s a motley crew. At first glance, one commonality emerges. Unsurprisingly, each hitter experienced significant BABIP regression the year after their jump. The BABIP gods hit some harder than others. Adam Dunn seems like an unfair comparison for what might happen to Iannetta — his remarkably terrible 2011 was fueled by more than BABIP regression. Similarly, Nick Swisher, Mark Reynolds and 2011 Colby Rasmus each saw fairly significant erosion in their power numbers. Swisher retained a good portion his productivity by dramatically increasing his BB%, but I don’t think that’s a fair expectation for Iannetta.

Perhaps the best example of what might happen to Iannetta is 2013-14 Colby Rasmus. In the midst of a BABIP regression, Rasmus has maintained his power numbers and plate discipline. Nonetheless, he’s currently producing runs at a rate 27% lower than last year. Those extra outs sure do add up.

Ultimately, if Iannetta can sustain his ISO and BB%, he should remain valuable for the Angels. Although Iannetta is on the wrong side of the aging curve, a mild BABIP regression with minor skill erosion would forecast a wRC+ somewhere in the neighborhood of 105-115. The Angels will certainly take that from their catcher.

Interestingly enough, the only hitter besides Iannetta to fit the parameters of a BABIP 15% greater than career average and fly ball rate 20% greater than league average this season is Devin Mesoraco. Mesoraco, however, is currently enjoying a well-documented swing renaissance, rendering his career BABIP rate generally unreliable for the purposes of this study. Going forward, Mesoraco is much more likely to sustain his present success than Iannetta.

There has been much discussion lately regarding the people who hold the belief that pitchers are not deserving candidates for the MVP award.  What I don’t see is very many people who actually come out and say pitchers don’t deserve the MVP award.  Perhaps, in my daily consumption of hours of baseball news, analysis, and commentary across various media, I am somehow missing out on a significant sector or demographic that holds this belief, and so it is in fact more prevalent than what I observe, but in reality it appears that very few consider it to be such a black-and-white issue.

In fact, I would argue that both the sabermetric community and the less-analytically-inclined community both agree that it is a gray area, but approach it in different ways.

In Ken Rosenthal’s recent post on the topic, he points out that it is far from black-and-white; the last time we had a pitcher named MVP (Verlander in 2011), he was on 27 of 28 ballots.  So maybe there is one sportswriter in 28 or so who believes pitchers shouldn’t be MVPs.  Although, we shouldn’t even assume said writer would never vote for a pitcher; maybe he just felt it wasn’t Verlander’s year.

In fact 2011 was an interesting year (especially for those WAR-lubbers), in that (non-MVP) Roy Halladay in the NL had a WAR of 8.1, which was ahead of NL MVP Ryan Braun’s 7.2 (though not ahead of non-MVP and non-cheater Matt Kemp’s 8.4!).  Over in the AL, Ellsbury’s WAR was 9.1 compared to Verlander’s 6.9.  In fact 10 AL hitters had a WAR of 6.3 or greater.

On the flip side, take Jeff Sullivan’s recent post:

Say the best position player comes in around 8. Say the best pitcher comes in around 8. Say, for simplicity, that all of the different WARs are even in agreement. Doesn’t that function as a conversation-ender? You can always debate a given individual’s WAR, but doesn’t that rather matter-of-factly put pitchers and position players on the same scale?

Overall I’m very much in the camp that pitchers deserve the MVP.  But we do need to acknowledge that WAR is based an up-front division of the 1000 WAR given out per season, with 43% going to pitchers and 57% going to hitters.  It’s not that these numbers are arbitrary; a great deal of thought has been put into how to value the relative contributions of various positions (WAR’s positional adjustments are in a similar vein), and this is an interesting problem across all team sports.

Nevertheless, it holds true that in any given year, the top WAR leaders tend to be position players.  When people make sweeping statements like “position players play every day, starters only play every 5 days,” I don’t think (many of) those people are unwilling to acknowledge that starters’ contributions on the day they pitch are far more impactful than position players’ contributions; they’re just saying that in general, they see more cases where the best position players are the most valuable to their teams than the best starting pitchers — which is exactly what the WAR leaderboards say as well.

Regarding the valuation of different positions in team sports: often times, the nature of the game is such that certain positions are inherently more impactful; this ends up being a great example of why replacement level is an invaluable tool.  Consider the case of kickers in the NFL.  Suppose we modified the rules so that touchdowns didn’t immediately award 6 points; rather, it gave the scoring team the opportunity to kick an extra point that was worth 7 points.  Would this make kickers more valuable?  It certainly would make them more important, but I’m not convinced kickers’ salaries would change much.  The difference between the success rates of the best kicker in the league and the worst kicker in the league (or a replacement-level kicker) would be very small — they all make extra points about 99.7% of the time.  You’d still care more about having offensive players who can score those touchdowns (and defensive players who can prevent touchdowns).

Now, if the rules were different, and that “7-point-extra-point” actually had to be kicked from 58 yards deep, then there would suddenly be a huge difference between the success rates of the best kickers and the replacement-level kickers.  The kickers capable of hitting those 7-pointers at a high success rate would suddenly command enormous contracts and be kings of the league.

To me this is the essence of the Pitcher-for-MVP Debate: almost everyone agrees that as a whole, pitchers are less valuable than hitters.  We give hitters more WAR and bigger contracts.  That doesn’t mean there aren’t years where the best pitcher isn’t better than the best hitter, but almost everyone, sabermetrically-inclined or not, seems to come to the conclusions that in general, “position players have more impact.”

It’s well documented that Yasiel Puig has been having a rough second half to the season. FanGraphs’ own Jeff Sullivan covered Puig’s troubles in a great piece here, and other articles like this one, and this one, and this one, continue to pop up. Further, a recent dugout altercation with veteran Matt Kemp have only made the media scrutiny on baseball’s most volatile player tighter. Jeff discussed Puig’s inability to do anything but roll over inside pitches of late, and his failure to lift fastballs as well. Let’s keep that information in the back of our mind for a second and look at Puig’s L/R splits for 2013 and 2014.

Notice the drastic drop in Puig’s performance against left-handed pitching. Now both samples are limited in terms of plate appearances, but I don’t think you can attribute this drop in performance entirely to luck. First, see the difference in how right-handed and left-handed pitchers have attacked Puig by location in 2014.

Left-handed pitchers have made a significantly more concerted effort to pitch Puig inside, the same area that Jeff acutely pointed out Puig has been struggling. However, this isn’t much different than the way left-handers pitched Puig a year ago. See below for 2013 chart:

What has changed though is Puig’s ability to hit left-handed change-ups, and off-speed pitches in general. In 2013, Puig swung and missed at a lot of change-ups (28% whiff rate), but when he did make contact he did damage (.539 SLG in 26 AB’s where he put a change-up in play). In 2014 though, Puig has cut down on the misses (20% whiff rate), but also lost his ability to impact the baseball against the pitch (no extra base hits vs. lhp change-ups). A similar trend, but not as exaggerated one, can be found if you look at Puig vs. breaking pitches.

This isn’t a secret either. In last night’s contest, during his at bats against the Cubs lefty Tsuyoshi Wada, 4 of the 7 pitches Puig saw were change-ups. Wada did let one creep over the plate in his second at bat and Puig was able to hit a grounder through the left side.

But let’s go back to the examples in Jeff’s article. In the at bats where Puig is successful he gets to the ball out front and is able to get extension through his swing. Yet, in the examples where Puig is unsuccessful he rolls over the ball, is late, hits the ball deeper in accordance to his body, and cannot get the same extension. Granted both of the examples are against righties, but it illustrates the greater point of how Puig’s timing right now is off against fastballs (particularly fastballs on his hands and up).

And the problem with being late against the fastball is the rest of the game starts to speed up. To try and account for his deficiency, Puig has likely started to to cheat (start his swing earlier), leaving him more vulnerable to off-speed pitches away. And if you’re a lefty with a good change-up, you have a serious advantage versus Puig right now.

The question you might be asking yourself is why can’t righties take advantage of the same flaw. Well, since August 1, they have to an extent, and against right-handed four-seam fastballs Puig is a mere 5 for 35.

However, against off-speed pitches it’s a different story. For his career Puig recognizes and hits breaking balls considerably better than change-ups. Against sliders and curveballs, he’s batted .327 and .298 respectively, compared to a lowly .219 against change-ups.

And given that Puig is right-handed he’s a lot less likely to see change-ups from right-handed pitchers. Per Max Marchi’s data, pitchers are more than twice as likely to throw change-ups to opposite-side hitters than same-side hitters. This holds true for Puig, who in 2014, has seen 16% of pitches from left-handers be change-ups, compared to only 7% of pitches from right-handers. So while the advantage is still there for righties, it’s less likely they’ll get to it, or can do so within the limits of their arsenal.

What’ll be interesting to see is if a team will actually bring a lefty out of the bullpen to face Puig in the postseason. If it happens, one likely scenario would be Marco Gonzales of St. Louis (if he makes the playoff roster), whose profile suggests him being Puig’s kryptonite. He throws over 30% change-ups against right-handers and 51% of his fastball to righties have been located inside.

Another poor match-up would be if the Dodgers face the Nationals and Gio Gonzalez is on the mound. Gonzalez has upped his change-up usage against right-handers to 23% in 2014, and has limited hitters to a .230 average against the pitch with a 23% whiff rate.

I also think it’s important to watch how Puig handles inside fastballs the remainder of the season. It’s conceivable the adrenaline of a playoff series could help him regain his timing against the pitch and get him back in sync. Like any hitter his swing is constantly adjusting, and it could start clicking for the Cuban slugger at any point in time. The Dodgers are hoping it clicks soon, or else they’ll be stuck searching elsewhere for offensive production when October rolls around.

Data courtesy of FanGraphs and Brooks Baseball

Featured Image courtesy of USA Today

We’re used to hearing about teams having balanced or deep lineups. Other teams are defined as “stars and scrubs”. While I think we all know what these term mean, it’s not something that’s ever been quantified (at least, not to my knowledge). Since the issue of depth is an interesting one to me, I thought it’d be fun to to tackle this using wOBA.

For each team, I calculated wOBA on a team level, then the weighted standard deviation for all players. This produces each teams’ distribution, but since the size of the standard deviation is dependent on the average, (meaning that it’s not standard when comparing teams) I used the coefficient of variation (aka CV, simply standard deviation/average) as the final measure of consistency. The lower the CV, the smaller the spread of wOBA performance.

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The Mets took a chance last year and inked Curtis Granderson, age 33, to a four-year contract worth $60 million. Granderson was just coming off an injury plagued season with the Yankees in which he fractured his right forearm, and then the pinky in his left hand, sidelining him for over 100 games. In 2013 he posted a slash line of .229/.317/.409. Prior to his 2013 season, Granderson finished 4th in MVP voting in 2011, and was an All-Star in 2011 and 2012, finishing with more than 40 HR and 100 RBI’s.

So what can we expect from Curtis Granderson for the rest of his career with the Mets? Is there hope that he will be the big clutch hitter the Mets desperately need and come close to his 2011 and 2012 seasons with the Yankees? Or will his name be forever remembered by Mets fans in the same category as Jason Bay and Chris Young, forged in the hall of ineptitude? Here is a look at Curtis Granderson’s numbers after 2010 when Granderson turned 29 and started his stint with the Yankees. Here is a look at some of his numbers from 2010-2012, before his injury-riddled 2013 campaign:

It is important to note that he is playing the majority of his games at notoriously hitter-friendly Yankees Stadium. Using a measure of the effect of Yankee Stadium called park index, it can found that Yankee Stadium has about a +3% increase on a left-hander’s average, and a +53% on a hitter’s home run total. Granderson hit 56 total homers at Yankee Stadium from 2010-2012. After the Mets reconfigured their outfield, their left-handed batters hit on average +2% more home runs. If we adjust Curtis Granderson’s home run total to playing at CitiField for these years, his adjusted home run total is somewhere between 26-27 per year.

This still is a great total, and I think any Met fan would welcome a 25+ home run season from Granderson with open arms. Right now there are 10 games left in the season and Granderson has 18 home runs. He could sit around 20 this season which would not be terrible unless we remember his atrocious .218/.320./.374 slash line. We also have to consider the unfortunate factor of Granderson’s age to this equation. Granderson has a little bit of a strange aging curve because of his incredible seasons at age 30 and 31. I decided to look at how similar players performed at ages 32, 33, 34, and 35 (no player that has a top-ten similarity score has played a season at age 36 yet). The similarity scores were calculated based on Baseball-Reference’s similarity scores equation.

All of my worst fears came true and I started having flashbacks of one of the all-time worst Mets busts as I saw the name that popped up at number 1 — Jason Bay. Here is what other similar players did at age 32, 33, 34, and 35 (I omitted information if a player played less than 70 games aside from Granderson’s season at age 32.):

This does not paint a good picture of what we hope to expect from Granderson. For a player signed to the amount of money as Granderson, I would like to see an OPS around or above .800. There are only two out of ten players — Phil Nevin and Jayson Werth, that hit decently at the advanced ages of 34 and 35 (Werth is hitting pretty well with over 80 RBI’s with an OPS above .800, Nevin hit decently with a 0.76 OPS and 22 home runs at age 35). Six out of ten players ended their careers following a tremendous decline before getting to age 34 (I included Jason Bay whose career was arguably over before age 31, a year after signing with the Mets), Edwin Encarnacion is too young to make any conclusions about, and it is looking like Jose Bautista will play well, or at least decently at ages 34 and 35.

Even though most similar players did not have good seasons, or even reach seasons at ages 34, 35, and 36, similar players like Jayson Werth, Phil Nevin, and Jose Bautista give us a glimmer of hope. Similar players in no way give us a definitive look at a player’s future, so there is also always the possibility Granderson carves himself a much different path than any of the players on this list. To determine what might be causing Granderson’s decline, I’m going to look through Granderson’s batted ball statistics along with walk rate and strikeout rate:

The most glaring discrepancy between Granderson’s time with the Mets and Yankees is his HR/FB rate. His BABIP has gone down a little, but it is not that far removed from his numbers from 2010-2012. BABIP is a good statistic to look at to determine if a player is having a relatively unlucky season by comparing it to that player’s normal BABIP. It looks like he might have been a little lucky getting hits in 2011. Other than that, BABIP does not tell the story of what has happened to Granderson in 2014.

My initial thought from watching Granderson play daily was that he is striking out at a much higher rate. In fact, his K% is lower than it was in 2011 and 2012, and on par with what it was in 2010. And here is where we come to his HR/FB. Although Granderson is hitting about the same FB%, the percent of his fly balls that are going out of the park is dismally low compared to how it was when he was hitting 40+ home runs at Yankee Stadium. Although this could partially be age-related, it could be easily argued that a huge component of this is also the change in ballpark where Granderson plays. It is hard to determine if Granderson could possibly change his approach somehow to adjust to CitiField’s landscape when he is going to be 34 years old next year. The future is looking bleak for Mets fans unless Granderson can figure out how to turn things around next season.

“It looks like he’s going to be able to stay in an up-the-middle position on the defensive spectrum,” added the National League scout. “When you have a combination of speed, defense and power, like he has, that’s hard to find in the middle of the diamond. In the end, he looks like a player who has a chance to legitimately contribute to a major-league club on both the offensive and defensive sides of the ball.”

No, that scout wasn’t talking about Cubs uberprospect Javier Baez, but rather about Cubs ex-uberprospect Brett Jackson , as told to David Laurila back in March, 2011. Before Baez, and Jorge Soler, and Kris Bryant, it was Jackson who was the Anointed Expurgator of Ruminant Curses. As you probably know, the goat turned out to be too strong for B-Jax, who struck out at an epic 41.5% rate with the Cubs before being exiled to the minors, where his bat continued to avoid contact with the same unerring purpose with which children avoid vegetables. Theo ultimately traded him to the Diamondbacks for a few Jerry Colangelo bobbleheads.

Here’s Jackson’s line from his fly-on-windshield season in 2012 with the Cubs:

144 PA, 41.5% K, .175/.303/.342, 78 wRC+.

And here’s Javy’s line as of September 14:

166 PA, 41.6% K, .174/.229/.387, 68 wRC+.

Scary stuff, kids. Now several caveats obviously apply here, including small sample size. The players themselves are quite different. Jackson was a five tool guy who was good at everything but exceptional at nothing. While Baez has certainly had to rearrange his garage to fit all his tools, his calling card is Sheffield-like bat speed. Baez is almost without doubt the most exciting .174 hitter the game has ever seen. But the question is whether the rapidly bleaching bones of Brett Jackson’s career stand as a warning to Baez, and to those in the Cubs front office that see him as an anchor tenant at Wrigley for years to come.

To examine this, I compared Baez’s progress from high-A to the majors with Jackson’s, and I also threw in two guys that have had immediate success in The Show. George Springer (another high K guy) and Soler (a much more disciplined prospect).

Starting at high-A, the players looked like this:

Baez:          337 PA, 23.1& K, .274/.338./.535, 145 wRC+

Jackson:    312 PA, 20.2%, .316/.422/.517, 170 wRC+

Soler:         236 PA, 16.1% K, .281/.343/.467, 128 wRC+

Springer:   500 PA, 26.2% K, .316./.398/.557, 143 wRC+.

This includes only Baez’s high-A appearances in 2013 — I’m leaving out 86 PAs from 2012 in which Baez was only modestly effective. B-Jax wins this round, although Soler’s advanced approach is already apparent.  All four had good years.

Here’s how they performed at AA:

Baez:          240 PA, 28.8% K, .294/.346/.638, 180 wRC+

Jackson:    297 PA, 24.9% K, .256/.373./.443, 123 wRC+

Soler:           79 PA, 19.0% K, .415/.494/.862, 265 wRC+

Springer:  323 PA, 29.7% K, .297/.399/.579, 174 wRC+

Jackson had two roughly equivalent AA seasons in 2010 and 2011 — I’m showing the latter here. Springer had 87 difficult appearances in AA in 2012 — I’m showing his breakout 2013 season. All four struck out more often in AA, but all except Jackson improved on their performances at high-A. Soler’s numbers were insane, and the Cubs quickly promoted him to AAA to give him some more challenging pitches to work with.

And speaking of AAA:

Baez:         434 PA, 30.0% K, .260/.323/.510, 108 wRC+

Jackson:   467 PA, 33.8% K, .256/.348/.479, 107 wRC+

Soler:         127 PA, 20.5% K, .282/.378/.618, 149 wRC+

Springer:  266 PA, 24.4% K, .311/.425/.626, 175 wRC+

This is Jackson’s 2012 line at AAA. He put up a better wRC+ of 128 in 2011, in 215 appearances. I’m showing Springer’s AAA numbers for 2013; he had 61 arbitration-delaying PAs in 2014, in which he performed even better before being promoted. Springer actually improved his whiff rate in AAA, turning in a dominating season. Soler’s ludicrous AA numbers came somewhat back to Earth, but he still raked, with a K% only slightly worse than in AA.

Baez and Jackson, on the other hand, began shipping water. Their seasons were not horrible, but they performed significantly worse than they had in AA, with rising (and in B-Jax’ case, skyrocketing) strikeout rates. Both would carry their decaying swings to the major league level, where they both have paid a huge price, whiffing over 40% of the time. Springer also added about 10% to his K rate on reaching the majors, but he started from a lower base, and retained enough on-base to be a plus hitter (.231/.336/.468) before injuries sidelined him.

If Jackson represents the sum of all Baez’ fears, Springer represents the hope. Springer actually struck out more frequently than Baez in the lower minors, but Springer found a way to reduce his strikeout rate at AAA, and has found a way to produce at the major league level even while whiffing a third of the time. While Springer may not be able to sustain this productivity unless he once again addresses his contact problems, his strikeout rate isn’t unheard of in the majors. Baez’ rate, at 41%, lies largely outside the realm of civilized baseball discourse.

As of this writing, no qualifying hitter has a K rate anywhere near 40%. Indeed, there are only four hitters with a K rate exceeding 30% (Chris Davis, Chris Carter, Adam Dunn, and B.J. Upton). Two of these guys (Carter and Dunn) are have a wRC+ over 100; the other two do not. The worst career strikeout rate (minimum 1000 PAs) belongs to Tyler Flowers at 34.8%. No player has long survived in the majors beyond this forbidding boundary. The worst career K rate for a player with a career wRC+ over 100 is the aforementioned Chris Carter, checking in at 33.6%. Baez has a long way to go to even reach this dismal rate.

He has perhaps taken some baby steps: after striking out at a 42.2% clip in August, he’s shaved that to 40% in September. His last golden sombrero was on September 5, so it’s been over a week. Umm … yeah … these are the flimsiest of straws to grasp. With Addison Russell, Starlin Castro, and Kris Bryant all staking claims on the Cubs infield, Baez may be running out of time to prove that he can prevent strikeouts from getting his goat.

Watching a team struggle in key games in September is possibly the most painful part of being a baseball fan.  Sometimes they turn it around, but on some occasions a fan base watches a team go from a near certain playoff birth to watching October baseball.  If it looks like your team might fall apart what is it that should worry you most?  My guess is that it should be mental lapses, which would be the most likely thing to increase if the team is feeling pressure.

Mental lapses have a couple of possible proxies in baseball statistics, and one would be errors.  Teams that are on the path to collapse might be identifiable if they start having more blunders in the field than they had earlier in the year.  Historically it looks like this might be true.  Coolstandings has a list of some of the greatest collapses from a playoff odds standpoint.  Eight of the top ten collapses show an increase in errors during the month of September.

Only the 2011 Braves and the 1999 Reds had lower errors per game in September while collapsing and the Reds were pretty close to the same as the season as a whole.  These gaps are also somewhat conservative since I included September in the whole season number, so the differences from the rest of season would be greater.  Also, the September number includes regular season games that end up in October.  As you an see, the difference on average for the collapsing teams is .117 more errors per game or 17.6% more errors per game than their season as a whole.  The 2011 Braves might be the exception that proves the rule as they were way, way better in September at avoiding errors only having 5 the entire month.  If you take them out the average difference shows almost 25% more errors for collapsing teams in September.

This could be something other than mental issues.  It is possible that errors are higher in general in September due to things like expanded rosters, but of course contending teams aren’t going to be giving a lot of opportunities to unproven talent and shouldn’t be subject to that sort of thing.  Errors  don’t need to be the only proxy either, as I think making outs on the base paths or throwing to the wrong base/missing cutoff men sorts of mental lapses might work too.  Maybe it work better to add up all “mental mistakes” and then look for differences.  We could also look at it in a sort of contagion effect, but I am going to need a site to start giving monthly splits for all team data in an easily accessible way first.

Pressure and other intangible sorts of ideas are always hard to directly study, but we have all felt it manifest in our own lives so we can’t expect professional athletes to be immune to such things.  Watching the Royals the last two weeks or so I have felt like this is happening at times (though Lorenzo Cain literally just smashed a three run bomb off of Chris Sale).  Any Oakland fans feel like they have seen this too?

Phil Hughes is currently enjoying his most fruitful season as a starter. Indeed, he has already received considerable attention for his improved control  and refined repertoire. Nonetheless, several recent feats merit additional attention.  Indeed, Phil Hughes’ most recent start against the Chicago White Sox saw several notable streaks come to an end.

Hughes certainly wasn’t pleased with himself, and for good reason: he had just issued a free pass and put a runner on first base. Perhaps Hughes grasped the historic implications of that BB — he hadn’t issued a walk since August 10^th against the A’s. That streak spanned 160 consecutive batters faced, including five walk-free games. Hughes pitched 37 innings without giving up a walk over those five games — the average MLB starting pitcher, posting a BB/9 of 2.7, would have walked over 11 batters during that span.

Hughes’ streak certainly appears impressive, but exactly how does it compare to his peers? Well, no other starting pitcher has managed such a streak this season… except for Phil Hughes. That’s right — Hughes had already posted a streak of 178 consecutive batters faced without a walk. Spanning from April 20^th to June 1^st, that streak included six walk-free games!

Hughes’ refusal to issue walks puts him in some pretty elite company. Observe the table below:

Table 1: For Starting Pitchers from 1969-2014, Longest Consecutive BB-Free Game Streaks, Sorted by IP.

Since the mound was lowered 45 years ago, Hughes’ streaks rank 9^th and T-17^th respectively. Notice the other pitchers who have multiple streaks in the top 20: Greg Maddux, David Wells, Randy Jones and Curt Schilling. For a guy who signed for $8M/year, that’s some impressive company (and Randy Jones). While Phil Hughes certainly isn’t Greg Maddux, his ability to limit walks has helped him post an xFIP of 3.17 this year, giving the Twins the closest thing to a true No. 1 starter they’ve had since Johan Santana.

Interestingly enough, Hughes made even more history against the Chicago White Sox, this time snapping a team-wide streak for the Minnesota Twins.

At first glance, there is hardly anything remarkable about this outcome. Hughes has struck out 175 other batters faced this season, and Tyler Flowers has struck out in 152 other plate appearances. This, however, was Hughes’ 10^th strikeout of the day — an arbitrary but nonetheless impressive feat.

With this punch-out, Hughes finally put an end to an ugly streak in Twins’ recent history: a Twins’ starting pitcher hadn’t fanned 10 batters in an outing since Francisco Liriano’s 10K performance against the Baltimore Orioles on July 18^th, 2012. The Twins’ streak of 379 games without 10 punch-outs from a starting pitcher was the longest active streak in the league. During that 379-game drought, starting pitchers from the league’s 29 other teams amassed a total of 497 10-strikeout performances.

It’s no secret that Twins’ starters have been remarkably inept at missing bats in recent history. The table below depicts the depth of their woes over the past five seasons.

Table 2: From 2009-2014, Starter K/9 Including Mean & Standard Deviation

At more than 2.5 standard deviations below the mean K/9, Twins’ starting pitchers have been tremendously poor at striking hitters out over the last five seasons. Whether or not this has been a function of design or merely ineffectiveness, the Twins’ rotation has severely hurt the team, posting an ERA of 4.88 during that period. Within this context, Hughes’ outing is truly shocking.

Perhaps Hughes’ outing is a sign of better fortunes to come for the Twins. Perhaps it was an anomaly. Both Hughes (11K) and Quintana (13K) set career-high strikeout totals in their respective starts. At one point, the never-prone-to-hyperbole White Sox broadcast team proclaimed, “You give Chris Sale this visibility, starting every game at home…he would re-write the strikeout record book.”

Regardless of the game conditions, Hughes’ start featured several remarkable feats. Ironically, while Hughes’ lone walk (a negative outcome) allows us to appreciate his greatness, his 10^th strikeout (a positive outcome) allows us to contextualize the Twins’ incompetence. Here’s to you, Phil.

Editor’s Note: As I conclude this article, the Twins’ Trevor May has just fanned 10 batters in his Sunday start against the White Sox. Here’s to you as well, Trevor.

Statistics courtesy of FanGraphs, historical data courtesy of Baseball-Reference, and gifs courtesy of MLB.TV.

Ben Cermak lives in Manhattan and spends far too much time thinking and writing about baseball. You can contact him via email at bcermak14@gmail.com

Normally, one would leave a comment in response to an column, rather than writing a full blown piece, but that FanGraphs is devoid of response pieces may mean that FanGraphs is devoid of a possible method of furthering our understanding of baseball. Different opinions and viewpoints lead to different ideas, possibly allowing other readers to think about the game in different ways. So, without further ado…

Jose Ramirez has certainly had an adventurous 2014 professional season. After starting the year in Triple-A Columbus, the 21 year old Dominican had a brief and unsuccessful stint for Cleveland, and was promptly sent back down after the recovery of second baseman Jason Kipnis. Since Asdrubal Cabrera was traded, Ramirez has been an everyday player, and from that point onward, Ramirez has been batting at a 105 wRC+ with a .328 BAbip, a reasonable number for someone with his kind of speed and spray hitting ability. Additionally, while not sterling, his 5.8 BB% and 12.7 K% are acceptable numbers for a rookie shortstop, particularly when compared to the average shortstop, who measures at 6.8% and 18.1% respectively.

Of course, as promising as Ramirez has appeared, he has only accumulated 173 PAs since the Cabrera trade, and his true value offensively may be less than he has shown. As Sarris points out, his defense though is where Ramirez truly shines. His defensive ratings statistically check out, and though it takes years for these ratings to stabilize, there is some possibility that these numbers are accurate or they even undersell his value. Already this year, Ramirez has been worth 1.4 WAR, thanks to his 5.8 UZR (placing him fifth amongst shortstops on the 2014 season). And as Sarris also pointed out, Ramirez has passed the eye test with flying colors.

It appears that Cleveland’s future would be more successful with Ramirez than without him. The Indians also have Francisco Lindor waiting in Triple-A Columbus ready to take his throne as long-term shortstop. Since his defensive value is supposed to make up the majority of his overall value, his floor would seem to be higher than the average shortstop prospect. Even if his bat is just league average, his defense should elevate him to an All-Star level, if everything goes according to plan. Sarris’s metric of 69.3% bust rate amongst shortstops rated in the top 100 prospects includes players at all levels of the minors. Of course, players in the lower minors have more volatile futures as their high praise is based more upon projection than offensive or defensive output. Lindor has made it through the minors, and is ready to assume his throne.

Ramirez’s defensive value lies in his cavernous range and sure-handedness, traits that will suit him almost as well at second base. Kipnis’s skills at second base have been only so-so in his career, and unless he learns the secret of Jhonny Peralta, he is unlikely to improve as his career transpires. A switch to the outfield, or even first base (with Santana switching to a full-time DH role), would be acceptable, as Kipnis’s value lies in his offensive game. However, if anyone should be traded, it is Kipnis, who, like Starlin Castro in Chicago, may be usurped by better, younger players, and whose trade value lies in past success.

WAR is considered by many members of the baseball community to be the best all around evaluator of a player’s value to his team.  It is used to evaluate player’s of different positions and from different eras.  However this might not be as useful in looking at players from different position.

I have developed a model that shows that one win at each position is not actually created equal.  This season Buster Posey and Ben Zobrist have a similar WAR — 5 and 4.9 respectively — but I don’t think anyone will argue that Posey is the better player. In order to determine how much more valuable Posey actually is I created a regression equation.  In order to develop this equation I took stats from the past 5 full seasons (2009-2013).  I took each team’s total number of wins and found the average win total over those 5 seasons.  Then I used the FanGraphs section that allowed me to look at each team’s total WAR by position.  For each position I took the total WAR and divided it by number of games “played” at that position and then multiplied it by 162 to find a season equivalent for each team at each position.  For starters and relievers I just took the WAR numbers and divided by 5.  Then I took these numbers for each team and regressed it against average wins.

Note: I did not include DH as the stats that come from the DH are included in other positions (ex: If Joe Mauer DHs then his stats are included in the catcher WAR).

The resulting equation is as follows:

Wins= 49.3870 + 3.3251 * C + 0.9527 * 1b + 1.5122 * 2b + 1.4703 * SS + 1.5447 * 3b + 1.0027 * Rf + 1.4031 * Cf + 0.4450 * LF + 0.7521 * SP + 0.5137 * RP

R: 0.95

R-squared:0.91

A few quick observations of the equation make sense. An additional win at the catcher position is worth much more than any other position because teams value catchers who can both hit and play solid defense but are extremely willing to sacrifice offense if the guy can play defense. Additionally it supports the theory that the best teams are strong up the middle with SS, 2B, and CF being more valuable than corner OF spots and 1B.

While it is regressed against wins I don’t feel the best application of this model is to predict a team’s wins.  The best application of this will be to evaluate the players to sign in free agency.  This past offseason the Yankees did not sign Robinson Cano to a large contact and instead signed players like Jacoby Ellsbury, Brian McCann, Kelly Johnson, and Brian Roberts.  Johnson and Roberts were supposed to split time at second and Ellsbury and McCann were supposed to be upgrades and C and CF over what the Yankees had had.

Looking at this chart this shows the WAR by position extrapolated for 162 for the three positions where the Yankees made major changes this offseason. Using the model the moves the Yankees made have actually led to a decrease of over one win.  While that may not seem like a very large difference the Yankees are in the middle of the wild card chase and could fall around one game out the playoffs.  Additionally, the lack of Cano and the struggles of Johnson and Roberts forced the Yankees to go out and trade for Martin Prado and Stephen Drew.  Without the contributions from Prado the Yankees second base position would actually have a WAR of below 1 which would have created an even bigger difference caused by not re-signing Cano.

This model is extremely useful for teams with limited budgets as it could help them determine what players and what positions they should sign in order to maximize their win totals.