Luis Valbuena struggles against fastballs, and is Michael-Jackson-bad against all other pitches. In an alternate world in which the Cubs actually cared about the difference between 61 and 65 wins, Luis Valbuena does not get 303 plate appearances last season. But in this world, where the Cubs are suppressing arbitration clocks and dropping bench players into starting roles, Luis Valbuena gets 303 PA. Barring something magical, do not put Luis Valbuena on your fantasy team in 2013.

That was me. I wrote that very review of Cubs third baseman Luis Valbuena for his 2013 FanGraphs+ fantasy profile. At the time, Luis Valbuena had a career .224/.292/.343 slash and a 73 wRC+. On the merit of some impressive defensive output in 2012, he had managed to increase his career WAR to a sterling -0.3 wins through 1109 PA.

Nothing outside of some solid PCL numbers suggested Valbuena could be a solid third baseman in 2013. So far, I’ve been quite wrong.
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If you are similar to me, then you spend more than a trivial amount of time on the teams leaderboard page. I find myself sorting the wRC+ column for my daily Ottoneu, The Game, and game preview needs. But, like a suspicious man at a bus stop, BABIP lurks just a few columns away. It haunts my well-crafted insults hurtled brazenly towards the Miami Marlins from the comfortable solitude of my home office.

I have spent the past year or two studying BABIP, in part because it has shown the power to unlock a fielding independent hitting metric I so cleverly and regrettably titled ShH or Should Hit. But other than confusing friends during spoken conversation, Should Hit can also regress offensive production based on four simple factors: walks, strikeouts, home runs, and BABIP.

We have previously employed ShH and its stepchild, the De-Lucker X (DLX), to regress players according to their previous performances. But now, let us throw whole teams into the De-Lucker vat. It will be great opportunity to kick the already over-kicked Marlins — as well as offer uncommon accolades for the San Francisco Giants and San Diego Padres lineups.
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He leads all rookie pitchers with 1.0 WAR, and is tied with the thus-far sensational position players Evan Gattis and A.J. Pollock. Sunday night, Hyun-Jin Ryu completed six innings against the San Francisco Giants, and though he took a loss, Ryu induced weak contact from a line-drive team. If the national audience was paying attention, they saw perhaps the best rookie in the league.

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There are few reversal of fortune so dramatic as the 0-2 home run. When pitchers corner a batsman into an 0-2 count, said batsman has hit .154/.160/.216 through the 2013 season. The following sample of at bats combine for an immaculate 1.000/1.000/4.000 slash.

Let’s take a look at them.
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Through five starts, St. Louis Cardinals pitcher Adam Wainwright has a 1.93 ERA, 1.09 FIP, and 2.13 SIERA. Of the 144 batsmen to face Wainwright, 37 struck out and just 1 walked — Bryce Harper in the 6th inning of last Tuesday’s game. Wainwright has induced a career-high 55.8% groundball-rate; he has held opponents to 8 earned runs, 9 runs total, scattered across 37 and 1/3 innings.

Wainwright is not “on fire.” He is fire. Butane lighters hang pictures of him on their bedroom walls. Local volunteer firemen warn children about Wainwright during school visits.

So how does an excellent pitcher produce results like a deity pitcher? For Wainwright, the tactic appears to be: (a) Throw a full spectrum of fastballs, (b) select from that fastball spectrum at an increasingly unpredictable rhythm, and (c) pitch against the right teams.
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Yes, well obviously Roberto Hernandez is not Fausto Carmona. The name Fausto Carmona belongs to someone else, and though the history of Cleveland Indians starting pitcher “Fausto Carmona” belongs to Roberto Hernandez, the two pitchers (the one pitcher) are not the same.

What I’m saying is: Roberto Hernandez is striking out batters.

He has a 22.5% K-rate right now. His previous career high was 17.1%, but that was mostly as a rookie reliever. As a starter, his highest K-rate was 15.6%. In fact, if we dig even deeper, we find his 22.5% K-rate is the highest strikeout rate he’s ever posted over a four game period:

His recent success — underscored and even underappreciated in his 3.75 FIP and 3.60 SIERA — appears to be the product of deliberate changes. That suggests he could maintain a new level of success.
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After a hard-fought, closely-followed battle, Bryce Harper beat out former relief pitcher Micah Owings for the starting left field position in Washington. Okay, Owings was never really in competition to take playing time from the reigning Rookie of the Year, Jayson Werth or Adam LaRoche — the three players in positions accessible to Owings’s limited defensive upside.

But here is the deal:

A) Pitchers do not consistently practice hitting. (Simple fact.)

B) The more time between at bats, the more a hitter struggles. (The Book.)

C) The more times a player faces a certain pitcher, the greater the advantage for the hitter — both in a game and in a career. (The Book Blog.)

All three of these elements suggest pitchers should hit, let’s say, about .145/.180/.190, or -10 wRC+ (that is, 110% worse than league average). Micah Owings — a pitcher — has, through 219 PA, hit .283/.310/.502 with 9 home runs and 14 doubles, a 104 wRC+.

Micah Owings is a good hitter. Possibly a great hitter. The Nationals have a bunch of those. But surely someone else out there could use a bench bat — or a starting outfielder — with the ability to pitch a 111 ERA- every now and then.
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Note: Due to an unfortunate data error, the numbers in this story did not include park factors upon publication. We have updated the data to include the park factors, and the data you see below is now correct. We apologize for the mistake.

For an explanation of this series, please read the introductory post. The data is a hybrid projection of the ZIPS and Steamer systems with playing time determined through depth charts created by our team of authors. The rankings are based on aggregate projected WAR for each team at a given position.

Update: Boy! What a difference park factors make! In the original iteration of this article — the one where we thought the park factors were park factoring, but they weren’t — the distribution of DH talent appeared skewed left. Now, not only have the teams shifted closer together, but teams from hitter-friendly parks — such as the Yankees and White Sox — have slunk to the rear while those in pitcher havens — the Mariners and Rays — have edged to more prominent slots.

Because I attempted to weave together these rankings into a grander sort of narrative, much of my original text requires revision. I am happy to report, however, the majority of my in-post complaining about the rankings became validated by the fixed park factors. However, in lieu of covering this article with strike-throughs, I am going to just update the test (as minimally as possible) to reflect the updated rankings.

Originalish post: These rankings are fun. They do not affect the results on the field or the players ranked in them or the GMs glowering over the players. But we are inexorably drawn to these sorts of rankings. With egos invested into our teams, rankings give us pre-season bragging rights or grinding axes.

In all this fun, however, it is important to remember the function of our list. As we are wont to do at FanGraphs, we have attempted to make our lists in the most clinical, mathematical and unbiased ways as possible. Whereas many MLB power rankings are based on gut judgements or broad, basic analyses, we have computed a scientific power ranking system that requires human input only when it is an improvement over an algorithm.

This means, however, the space between each team is discrete. The distance between No. 1 and No. 2 is much greater than, as you will see, between No. 13 and No. 14:

Two are clustered near the top, others are rounding errors apart, and two teams appear clustered near the bottom. But an ordinal ranking does not represent that accurately.

And even despite our best utilization of projection systems and playing time predictions, the season is unpredictable. Not just hard to predict, but unpredictable. If it weren’t, who would watch it? But as of now, as of our best playing time estimations, as of the best projection systems, this is how the DH world settles. This is how the big and sluggerish stand.

Without further ado, I present the Slow and Sluggering Show:
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Can you believe it!? Friday night, tonight!, the World Baseball Classic commences with an 11:30 p.m. ET game between Chinese Taipei and Australia!

For those of us who spent the snowy preceding months watching grainy online feeds of Australian and Latin American winter ball, this day — this meaningful day — is precious. But precious also describes the amount, the scarcity, of WBC enthusiasts in America. Tragic, but true: America and Canada do not share foreign fervor for the WBC.

Well, in an effort to correct that, I have offered studies of some Taiwanese sluggers, and today I will conclude that cultural and statistical foray. For the previous pieces, see:

INF Ngayaw Ake
1B/DH Yi-Chuan Lin

Today, let’s examine Taiwan’s likely starting left fielder, Szu-Chi Chou.
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The World Baseball Classic nears like an orange and pink dawn, a dawn that breaks once every three years — so like an Alaskan dawn. But Americans, in general, are not setting their alarm clocks. We and our brother Canadians have not taken to the tournament with the equal fervor of many foreign baseball fans.

I suspect one reason is limited knowledge of the foreign rosters. Outside of the main North American teams — the USA, Canadian, and DR rosters — we struggle to recognize more than a handful of players.

So let’s try to wrest away some passion from these non-American, non-Canadian types and learn a bit more about the other teams! Particularly, let’s examine Taiwan’s three best sluggers. Why Taiwan? Your humble author speaks a little Mandarin. Taiwan speaks a lot of Mandarin. It’s like a match!

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