The Yankees already had a damaged Alex Rodriguez. They already had a damaged Curtis Granderson. They already had a damaged Michael Pineda, and a damaged Phil Hughes, and a damaged general freaking manager. Now they get to deal with a damaged Mark Teixeira on top of everything else. The word:

The Yankees’ injury-riddled spring took another serious hit on Wednesday, as the team announced Gold Glove first baseman Mark Teixeira will miss eight to 10 weeks with a strained tendon in his right wrist.

Teixeira’s going to do nothing for four weeks, then he’ll begin rehabbing, provided everything has healed up. According to the timetable, Teixeira should return to the Yankees around the middle of May. In theory, he’ll be 100%, but this is a wrist injury, so it’s possible Teixeira could play with diminished power. No hitter ever wants a wrist injury. Actually no hitter ever wants an injury at all. Who would?

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Kyle Lohse is a free-agent starting pitcher, and the Texas Rangers are a good baseball team, so off and on there’s been talk about the Rangers potentially making an effort to sign Kyle Lohse. This has picked up in light of the recent Martin Perez injury, as Perez was the favorite to be the Rangers’ fifth starter. Lohse, though, remains unsigned, and it looks like the Rangers might be on the verge of going elsewhere for help:

Source: Rangers on verge of signing RHP Derek Lowe to minor league deal, but he will make club, probably in swing role. Story coming.

— Evan Grant (@Evan_P_Grant) March 6, 2013

It’s not done, but it’s probably close, if this is the report. It makes a certain degree of sense, too — Lowe could offer short-term services to the rotation, and then get bumped upon the return of Perez or Colby Lewis. Lowe pitched out of the rotation and bullpen a year ago, and he’ll be a cheap investment for a team scared off by Lohse’s price tag. Lowe would cost the Rangers something in the low seven figures, most probably, with some incentives, most probably.

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If you haven’t already, go read David Laurila’s Q&A this morning with Dan Rosenheck, writer for the Economist and New York Times, who gave a presentation on predicting BABIP at the Sloan Conference last week. In that piece, Rosenheck notes that he created a model using just two variables — infield fly rate and rate of contact on strikes — that helped explain 15% of the variance in a pitcher’s future BABIP. The part about infield flies helping reduce BABIP has been noted before, as others have created takeoffs of ERA estimators that incorporate batted ball data — SIERA, tRA, bbFIP, etc… — and Steve Staude wrote a Community Blog post on this topic back in October, also identifying infield fly rate as a significant explanatory tool for BABIP. The potential explanatory effects of inducing popups and the link to Z-Contact% is fascinating, however, and makes Rosenheck’s study a real step forward.

It makes perfect sense that infield flies would help explain some of the variation in a pitcher’s BABIP, of course, since infield flies are almost always outs. In fact, in 2012, there were 4,377 batted balls that were categorized as infield flies in Major League Baseball, and only 13 of those went for base hits. Another 28 did not result in an out due to an error by the fielder, but even with 41 non-outs, that leaves IFFBs with an out rate of 99.1%.

Infield flies are, for all practical purposes, the same as a strikeout. They are basically an automatic out, runners do not advance on infield flies, and perhaps most importantly, we can state with a pretty high level of confidence that the relative abilities of the defenders have nothing to do with the outcome of the play. Sure, maybe you or I wouldn’t turn every IFFB into an out, but for players selected at the Major League level, there is no real differentiation in their ability to catch a pop fly.

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A few weeks ago, I took a look at how the profile of corner outfielders has changed over the past decade, and it led to a little discussion between Wendy Thurm and I. She shared some research she had done on catchers, and she wondered whether or not catchers were changing as well. Catchers such as Buster Posey, Brian McCann, Matt Wieters, Carlos Santana, Miguel Montero, and even Yadier Molina of late have been producing offensively, eschewing the traditional idea of a catcher as an offensive pipsqueak. But are these players exceptions or the beginning of a new rule?

The first thing we’ll do is take a look at MLB catchers’ overall performance using wOBA and wRC+. Read the rest of this entry »

Over much of the offseason, a lot was said about the Detroit Tigers heading into 2013 with Bruce Rondon slated to close. Rondon, 22, has a big fastball, and is a quality prospect. But it turns out there’s more to pitching than throwing really hard, and Rondon has limited experience in the upper minors and a demonstrated inability to throw strikes consistently, especially against left-handed hitters. Right now, in Tigers camp, Rondon is being given special instruction, and while there’s plenty of time in spring for him to right the ship, it’s looking less likely by the day that Rondon will close out of the gate. The Tigers want to go to the playoffs, see, and a shaky rookie closer isn’t going to help them if he’s sufficiently shaky.

Rumor has it the Tigers are exploring the current closer market. How important is a closer to the Tigers? On the one hand, closer Jose Valverde had some memorable meltdowns last October, nearly costing the Tigers their season. On the other hand, with Valverde, the Tigers won their division and advanced to the World Series before getting swept away by San Francisco. So Valverde didn’t bring everything down. But the Tigers want security — security in the person of not-Valverde, it turns out — and among the considered options, Rick Porcello makes for a curious one.

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It might be hard to believe this after Sergio Romo closed out the World Series and probably wrapped up the stopper role going forward for the Giants and Team Mexico, but there was a time when the prognosis for his career was much more negative. After all, he’s a small righty (five-foot-ten and a buck-eighty-five) with a fastball that doesn’t normally crack 90 miles per hour who throws his slider more than half of the time. Given what we might know about injuries and platoon splits, there was probably one role waiting for him in the bigs: ROOGY.

But Sergio Romo is not a Righty One-Out GuY. I asked him why.

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Table of Contents
Here’s the table of contents for today’s edition of the Daily Notes.

1. A Loathsome Semantic Point Regarding Spring Stats
2. SCOUT Leaderboards: Spring Training
3. Mostly Unhelpful Video: Michael Wacha Strikes Out Five

A Loathsome Semantic Point Regarding Spring Stats
It has been noted by people smarter than the present author — and also by Jeff Sullivan — that it’s best to approach spring numbers with a great deal of caution so far as drawing conclusions is concerned regarding what they might suggest about a player’s true-talent level. While research from last March by Mike Podhorzer and Matt Swartz reveals that, in certain cases, spring numbers actually do possess some predictive value, this is likely an instance of exceptions proving rules.

Still, to say that spring numbers are “meaningless” because they lack predictive value for the upcoming season is likely not quite right, either. As Dave Cameron recently noted in a February piece on the relevance of WAR, every stat “is simply the answer to a question.” A question that the present author has some interest in answering is “Which players are performing the best this spring?” — not necessarily with a view to how it might inform their regular-season production (although I’m willing to become irrationally exuberant with little provocation), but merely in and of itself. Any numbers that answer that question have “meaning” to that end.

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The Yankees system isn’t as deep as it’s been in the past, but there are some high-ceiling talents at the top of the Top 15 list. The organization has some intriguing hard-throwers but the overall pitching depth is thin.

#1 Mason Williams (OF)

Williams was a steal as a fourth rounder from the 2010 amateur draft and he’s out-performed higher Yankees picks from that draft including Cito Culver (32nd overall) and Rob Segedin (third round). He’s moved somewhat slowly through the system to date but he looks ready to explode in 2012. Williams, 21, shows a solid approach at the plate with the ability to make a lot of contact, which should help him hit for a high average. He’s also doing a better job of driving the ball.

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Last weekend’s MIT Sloan Sports Analytics Conference included a number of Evolution of Sport presentations. Among the best was a study of BABIP factors titled “Hitting ‘Em Where They Are,” by Dan Rosenheck. He is the sports editor of The Economist and a writer for The New York Times’s Keeping Score column on sports statistics, and he gave an overview of his study prior to presenting it on Day Two of the conference.

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Dan Rosenheck: “It was a great surprise to find out that one of the distinguished presenters on the Baseball Analytics panel was Voros McCracken. His discovery, in 1999, was that BABIP allowed by starting pitchers is, at the very least, extremely noisy and hard to predict from year to year. It was a revolution in sabermetrics and opened the door to a vast amount of research. It changed the way many of us understand the game.

“The BABIP question has been the Great White Whale of the sabermetric enterprise. It is the mystery that, 14 years later, has continued to defy the best efforts of quantitative analysts using public available data. Tom Tango’s FIP assumes that all pitchers have exactly league-average BABIP ability. Even a small increase in predictive ability of that question leads to a huge increase in the accuracy with which you can predict how valuable players will be.

“I studied a bunch of variables I thought might have something to do with hit suppression on balls in play. I came up with two — both FanGraphs stats — that seem to have significant predictive power. The first is pop up rate. The second is z-contact, which is when batters swing at a strike — balls in the strike zone — thrown by a pitcher. What percent of those times does the batter make contact? It turns out that, just like inducing pop ups, it reduces BABIP and correlates consistently year to year. Getting batters to swing and miss at your strikes has strong predictive power on hit suppression.

“I came up with a simple model with two curved fits, using data from 2005-2011, with an R-squared of .15. It accounted for 15 percent of the variance in BABIP for starting pitchers relative to rest of that team’s starting rotation. That factors out for defense and ballpark.

“Fifteen percent might not sound like a lot, and the data is noisy, but it’s a lot relative to zero, which is what FIP will tell you. This little equation correctly identifies every single major BABIP outlier of the last decade. If you look at its leader boards, the guys who most often appear as being projected to have the lowest BABIPs relative to their team, using only data from prior seasons — no cheating — it is Tim Wakefield, Ted Lilly, Barry Zito, Johan Santana, Matt Cain. It is the famous exceptions, one right after the other, after the other.

“The second thing is that it works out of sample. I calculated this equation in March 2012 on data from 2005-2011, and when I applied it to the 2012 season, the R-squared actually went up. It predicted the out-of-sample data even better than the in-sample data. There’s no over-fitting, no cheating or spurious relationships. This is real.

“The third thing that works well is you could have a 15 percent R-squared with a very narrow range of predictions. Let’s say you have the best guy at five points below his teammates and the worst at five points above. That might marginally improve your forecast, but it’s not game changing. This equation gets the magnitudes right. It can forecast very big outliers. The guys who have the lowest BABIPs — Chris Young when he was with the Padres, Jered Weaver now, some of the Ted Lilly seasons — it’s projecting these guys for 30, 40 points of BABIP below their teammates. Huge magnitudes, far and above what you would see in any of the standard projection systems like ZIPS, Steamer or PECOTA. I don’t think any of them are projecting anything close to 40 points of differential. And it’s getting them right.

“The reason the R-squared went up last year is that it made a very bold prediction that Jered Weaver was going to have a BABIP over 40 points lower than his teammates. It got it right to .001 of accuracy. That’s lucky, and just one great prediction, but overall it’s not just improving your accuracy at the margins. It’s identifying big outliers to a big degree.

“I will post my data online, so if anyone wants to poke holes in it, all the better for our understanding of this troublesome phenomenon. I think the best avenue for future research is looking at this equation — at basically the favorite and least favorite pitchers — and asking, ‘What do they have in common?’ The guys who have high pop up rates and low z-contact rates are the guys projected to be good hit suppressors, so what do they throw? How hard do they throw? Are they deceptive? And vice versa for the pitchers the equation doesn’t like.

“I had two hypotheses. I thought tall pitchers, like Young and Weaver, might be good at this. I also thought guys who throw a lot of changeups might be good at this. Cole Hamels and Johan Santana come up very high and they’re great changeup artists. But, in fact, the height and changeup percentage in my high and low BABIP samples were identical.

“I don’t have any piercing insights as to what the guys who are good at this are doing to be good at this. Fortunately, the data is available to everybody and the internet has plenty of smart people who can move our understanding of this issue even farther forward.”