Archive for Daily Graphings

Been talkin’ about BABIP lately. Let’s talk about BABIP again. Let’s talk about Yasiel Puig, and his BABIP.

Last week, I wrote a post on Starling Marte, in which I examined his extraordinarily high batting average on balls in play. I had a hypothesis, and that hypothesis was confirmed. It was far from revolutionary. I knew that Marte was fast, and then I found out that he hits a bunch of line drives and never hits pop-ups. Then I also found out that those three things alone can explain more than 50% of the variance in a player’s BABIP. Again, that’s really nothing new.

The metric I created, BIP Score, featured Marte prominently near the top. Also near the top were a whole bunch of guys with BABIP’s above .330. Yasiel Puig is another guy with a BABIP above .330. It’s way above .330. During his time in the MLB, only two qualified batters have a higher BABIP than Puig. But he’s nowhere to be found in the top half of the BIP Score leaderboard. From the post:

Not everyone with a high BABIP scores well in BIP Score. Yasiel Puig, for example, owns a career .366 BABIP — higher than Marte’s — but actually has a negative BIP Score, thanks to his low line drive and average pop-up rate.

I felt like that warranted an examination of its own. This post is that examination.

I guess, first, we’ll take a look at that BIP Score. That’s how this all started anyway. To get BIP Score, I simply summed the z-scores of every qualified batter’s line drive rate, infield fly rate and speed score and scaled it so 0 was league average. It’s admittedly a quick-and-dirty metric, but the higher the BIP Score, the more likely it is that a player should be able to sustain a high BABIP.

With this methodology, Puig clocked in with a BIP Score of -0.3. To get a sense of the context, let’s look at the other guys around Puig who also clocked in at -0.3.
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In 2014, relievers appeared in 14,459 games. In more than 90% of those games, the reliever faced multiple hitters, but in 1,266 appearances, the reliever pitched to just one batter. In just about ten percent of those appearances, the reliever made just one pitch. This post looks back at the 139 reliever appearances that lasted just one pitch, according to Baseball-Reference Play-Index Data.

The one-pitch pitchers skewed left with 81 appearances compared to 58 for right-handers. The pitchers were incredibly successful, allowing only 15 hits, and only four extra base hits. One of those hits was a home run. Josh Outman of the Cleveland Indians made just one pitch on May 31, 2014 against the Colorado Rockies. It did not go well.
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On Monday, the Red Sox won the bidding war for Cuban prospect Yoan Moncada, reportedly agreeing to pay $31.5 million as a signing bonus, plus another $31.5 million as a tax to the commissioner’s office for going over their allocation for international spending. That totals a $63 million acquisition cost for the organization, making Moncada one of the most expensive prospects in baseball history.

But if anything, the signing cost was perhaps a little bit on the low side of expectations, which had been rumored to be in the $30 to $40 million range for months. And while $63 million is a lot of money, the Red Sox actually guaranteed $72 million to fellow Cuban Rusney Castillo last year. Castillo broke the record for most money from a Cuban signee, set the prior year when the White Sox gave Jose Abreu $66 million. The Diamondbacks clearly used those two contracts as the inspiration for their $68 million deal with Yasmany Tomas, so Moncada became the fourth Cuban to sign for between $63 to $72 million in guaranteed money.

On the one hand, you could say that these four contracts represent a pretty clear price range that the market is willing to pay for talented Cuban hitters, but in reality, each contract has its own unique features that make the simple guaranteed dollar amounts a poor way of evaluating the true cost of the player to the team that signed them.

For instance, Moncada — unlike Abreu, Castillo, and Tomas — was prohibited from signing a major league contract, so the Red Sox do not get the benefit of spreading the cost out over the years during which he’s going to play in Boston, nor will any of the $63 million they’ve already committed to pay cover his future salaries when he does arrive in the big leagues. In other words, the $63 million payout for Moncada was simply to acquire his rights, making it more comparable to the posting fees paid to acquire players from Japan in the past.

Read the rest at Just a Bit Outside.

I don’t think the Dodgers deserve that much credit for signing Brandon Beachy. It’s not like it’s a particularly innovative idea, and a whole host of teams were interested in landing him. The Dodgers beat out almost everyone in available resources, and they beat out almost everyone in immediate outlook, and they had this other advantage, as well:

Beachy said deciding on the Dodgers was easy, mostly because the surgeon of his second Tommy John, Dr. Neal ElAttrache, is also the Dodgers’ team doctor.

“It’s the best place to be,” Beachy said. “I have a lot of faith in Dr. ElAttrache and the training room’s view for bringing me along meshes well with that.”

Beachy was drawn to the Dodgers, and the Dodgers were sufficiently drawn to Beachy to get him to sign. Given everything, the Beachy pickup hardly qualifies as any kind of genius, but for one thing, the upside is readily apparent — the upside of these things is always apparent — and for another, Beachy makes for an interesting depth play. That point isn’t Beachy-specific. Beachy and pitchers like him make for interesting depth plays.

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Finally, after what seems like an age, the appointed heroes amongst us mortal men and women have descended upon the ebullient corner of the nation, ball and glove in hand, to throw and to catch. Yes, it still snows 12 inches every week in the Northeast, but the dream is once again here — may we all rejoice in the date of winter’s true passing.

In honor of the fine March spectacle we’re about to witness, or rather to honor the sometimes low-level professional baseball that passes for spectacle because of the state of our desperation, I thought it might be a good exercise to relive some of the glories of past spring trainings. The reason for this is twofold: to remind everyone that spring training stats are next to worthless, and also to celebrate how weird baseball can be when constrained to a small sample size. Today we’re going to revel in the fact that we’re playing the game again by looking at freak occurrences that can only happen in Arizona in March.

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You play 81 games at home a year, so it seems like it might be a good idea to think about that park when you’re building your team. Then again, you play 81 games on the road, maybe it’s not a good idea to worry too much about one half of the ledger, particularly if your home park is an extreme one.

Extreme parks lead to extreme home-road splits. That part seems obvious, but it bears out in the winning percentage, too. Take a look at how teams that have called extreme parks home have faired over the last five years compared to the middle.

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Throughout the early stages of the calendar year, I’ve been taking a pre-spring training look at each of the six MLB divisions from a slightly different perspective. Utilizing batted ball data, we’re going back over the 2014 season, attempting to calculate each club’s true talent level. Making adjustments for teams’ offensive and defensive K and BB rates and team defense, each team’s true talent 2014 won-lost record is calculated. Then, we’ll take a look at the current Steamer projections for 2015, evaluate key player comings and goings, and determine whether clubs are constructed to be able to handle the inevitable pitfalls along the way that could render such projections irrelevant. Today’s last installment of this series features the AL Central.

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The fantasy baseball industry is more popular every day, but it sometimes seems rooted in yesterday. The statistics have moved on since it was invented in the seventies, at least. Is today’s fantasy baseball too far removed from real baseball? Is it just fake?

Fantasy’s traditional scoring system does seem arcane. That old 5×5 fantasy rotisserie game uses runs, RBI, batting average, home runs, and stolen bases as the key batting statistics, and many of those stats have fallen by the wayside as we attempt to better evaluate players. Runs and RBI, in particular, are not consulted at all when it comes to the modern stats of the day. They are just too context-dependent, since your teammates are heavily involved in both.

On the pitching side, the story is the same. Wins are one of the five categories, and a prominent numbers-savvy analyst has declared war on that statistic. Strikeouts, like home runs, are remarkably clean in that they require two participants and no judging from a scorer. But WHIP (Walks plus Hits over Innings Pitched) is full of noise — each hit is not only declared as such by a scorer, but it’s made into a hit through some nebulous combination of pitching and fielding as well.

But if that makes you want to pet fantasy baseball on the head, you might be surprised by how well those ten “old” statistics track with the more modern versions we have today.

Over at FanGraphs, we’re debuting a fantasy auction calculator and ranking tool today. The basic mechanism that powers the calculator is an attempt to look at the spread of certain statistics over a common baseline, look at a player’s production in each stat compared to that spread, and then adjust for position. If that sounds familiar, it’s because it generally follows the roadmap for Wins Above Replacement, one of today’s more sophisticated and complicated advanced summary stats.

If you compare the results of that auction calculator using 5×5 roto stats — batting average, home runs, RBI, runs, stolen bases, wins, ERA, WHIP, strikeouts, and saves — to the current WAR projections for next year, the two valuations are actually fairly close. In laymen’s terms, the ‘old’ 5×5 stats predict over three-quarters of the variance in WAR projections. That’s a strong relationship.

Here are the relevant correlations for a few different sets of scoring systems. (All p-values less than .0001, r value shown.)

Read the rest at Just a Bit Outside.

Following the departures of free agents Melky Cabrera and Colby Rasmus, the Toronto Blue Jays were down two-thirds of last year’s opening day outfield. They filled one of these holes when they traded for Michael Saunders, but have opted to go the internal route in filling the other, turning to the inexperienced duo of Dalton Pompey and Kevin Pillar to handle center field duties.

Pompey easily has the brighter future of the two. Kiley McDaniel ranked the 22-year-old 80^th in our top 200 list, giving him a Future Value of 50, which equates to an average everyday player. Pillar, on the other hand, hasn’t done much of anything in parts of two seasons with the Blue Jays, and at 26, he’s unlikely to get much better than he currently is. Non-roster veterans Chris Dickerson, Ezequiel Carrera and Caleb Gindl are also theoretically in the center field mix, but are likely in camp to provide depth more than anything. Given his competition, the starting center field job is Pompey’s to lose this spring.

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Last Friday, I took a look at the exceptional nature of Carlos Carrasco‘s split-change. I had trouble finding any kind of decent comparison for it, and when I did a little further analysis in the comments, the best I could come up with was Masahiro Tanaka’s splitter, and Tanaka’s splitter is supposed to be one of the best in the world. So, that was neat, and fun, and people are all about Carrasco hype because of the statistics he just posted down the stretch last summer. This post is about Odrisamer Despaigne. Despaigne isn’t nearly as statistically appealing as Carrasco is, and he’s not even assured a starting spot in the majors this coming season. But, just as Carrasco has an unusual split-change, Despaigne has an unusual changeup. A very, very, very unusual changeup.

Maybe that’s not a total surprise — last July, Eno talked about his weird grip. And Eno, see, knows a lot about grips. Here’s an image:

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