To be honest, this might be a post I’ve already written before. It feels like that sort of thing. But I’ve got pitch-framing on my mind, again, and even if I have done this before, at least now we’ve got more data. Why not revisit something whenever you have more data?

When we talk about framing, so often the focus is on the catchers. This is appropriate because it’s the catchers who are doing the framing — sometimes with a little assistance from other sources. But it’s the pitchers who are actually affected, because it’s the pitchers throwing the balls, and the catchers are involved only after the rest of the play has been carried out. It’s not entirely clear how pitchers are impacted by their receivers. We have estimates, we have some pretty good ideas, but the reality is complex. In this post, I try to examine something simple: What happens when a pitcher goes from better receiving to worse receiving? What happens when a pitcher goes from worse receiving to better receiving? As is literally always the case when I run an investigation, there are better and more thorough ways to do this, but I’m woefully limited by my own lack of ability, and if I don’t have the quick-and-easy stabs, I don’t have anything.

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By request:

@based_ball Hey Jeff, because you’re great at this stuff, can you write an article GIFing all of Ben Revere’s outfield assists? It’d be fun!

— David Shemie (@dshemie8) January 28, 2015

Ben Revere has 19 career outfield assists. Please understand what you’re getting into: this post is going to have .gifs, so many .gifs. Probably too many .gifs. It was absolutely too many .gifs for me to try to make in a morning, with a fussy and very particular MLB.tv. Also, many of the .gifs are flat-out bad, either because the streaming was going poorly, or because the play was too long and I had to take some shortcuts. Close this window right now if you’re not into what’s coming. If you haven’t closed the window yet, hi there. These are Ben Revere’s 19 outfield assists.

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On Monday’s edition of the podcast, Dave Cameron and I discussed in some depth his trilogy of posts from last week concerning the intersection within baseball between run-scoring and time of play. The former is trending downward; the latter, upward. The reasons for these twin developments are surely manifold, but one definite influence is greater specialization among relievers. More relief pitchers leads to greater effectivenss on a per-batter basis for those pitchers. It also leads to shorter outings for starters, allowing them to exert themselves more thoroughly and thus prevent runs at a greater rate, as well.

During the course of that discussion, when asked to identify a historical example which might serve to guide hypothetical rule changes by Major League Baseball, Cameron offered the 1985 St. Louis Cardinals as an aspirational model. Before losing the World Series to Kansas City in seven games, the 1985 Cardinals led the National League in runs scored while also hitting the second-fewest home runs. As a club they relied on excellent baserunning and making the most of the contact they did make.

Tom Herr, Willie McGee, Ozzie Smith, and Andy Van Slyke all stole at least 30 bases for that St. Louis club — and all produced above-average batting lines relative to league average despite a dearth of power. Vince Coleman failed to record a league-average batting line and Terry Pendleton stole just 17 bases, but each more or less embodied the Cardinals offensive profile, as well.

“Who,” I thought recently, “who, among the game’s current players, might have best fit on that edition of the Cardinals — and who, in turn, might serve as the model by which any potential rule change ought to be made?”

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Well, this whole James Shields situation sure is bizarre.

Back in October, the FanGraphs Crowd collectively projected that Shields would be the fourth-highest-paid free agent of the winter, in line for something like a 5-year/$90M contract. And now, this week, Tony Blengino took a look around the league, found very few teams who both had available money and a need to add to the top of their rotation, and predicted that Shields would sign with the Giants for 4 years/$75M.

If Tony’s prediction comes to pass, Shields would be leaving more than just $15M on the table. The actual contracts received by other top-flight free agents have well outpaced the Crowd’s projections. Max Scherzer received $210M (or so) over seven years after being projected to receive $168M. Fellow mega-earners Jon Lester ($155M v. $132M), Pablo Sandoval ($95M v. $80M), and Russell Martin ($82M v. $56M) also saw very meaningful increases over their crowdsourced projections.

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Yesterday, FanGraphs facilitated a brief crowdsourcing project with a view towards estimating Cuban defector Yoan Moncada’s signing bonus and other relevant information concerning the 19-year-old infielder.

What follows are the results of that effort followed by analysis courtesy FanGraphs’ lead prospect analyst Kiley McDaniel.

Signing Bonus
Moncada will likely receive the largest bonus ever given to a free agent who’s also subject to Major League Baseball’s international free agent rules. (Note: the figures below do not include the 100% tax to which Moncada’s signing club will be subject.)

Here’s the median figure as projected by the crowd: $45.0 million.

And here’s the average figure: $43.3 million.

And here’s a histogram of all possible outcomes with also a Cuban flag in the background:

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. The third installment of this series features the NL East. Read the rest of this entry »

We can say some things about how Mike Fiers went astray in 2013, and how changes to his pitching mix, pitches, and spot on the rubber contributed to his return to relevance in 2014. Those things show up just by looking at the different stats and heat maps we have at our disposal. The harder thing to figure out (if it’s at all possible) is *why* these changes worked.

First, the how.

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When the Atlanta Braves announced 15 months ago that the team would be moving to a new stadium in nearby Cobb County in 2017, the news surprised a number of people. The announcement was unexpected in part because the Braves’ current stadium, Turner Field, is less than 20 years old.

The news was also surprising, though, because it largely seemed to come out of the blue. There had been relatively little speculation that the Braves would be building a new stadium – let alone moving out of the Atlanta city limits – ahead of the formal announcement in November 2013. This was due in no small part to the fact Cobb County and the Braves negotiated the $397 million in public funding for SunTrust Park largely behind closed doors, without public input.

The lack of a public referendum for the stadium project is the basis of three legal challenges the Georgia Supreme Court heard earlier this week. If successful, these appeals could not only delay construction of the Braves’ new stadium, but could potentially disrupt the project’s financing.

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Pretty often, we get accused of overvaluing young players and prospects. The line of thinking is that we don’t properly appreciate the chances of a player flaming out and failing to accomplish anything of consequence. Yet, I don’t think we’ve ever been accused of overvaluing Kris Bryant. Around Bryant, there’s developed a consensus. Kiley ranked him first among Cubs prospects, obviously. Keith Law ranked him first in baseball. ZiPS is in love with Bryant, projecting a .364 wOBA. And Steamer, too, projects a .364 wOBA, exceeding its projections for Adrian Beltre and Robinson Cano. The No. 1 ZiPS comp is Evan Longoria. Bryant has yet to play in the major leagues, but already he’s considered a huge reason why the 2015 Cubs ought to contend for a playoff spot. He probably won’t be on the team out of camp, but he should be locked in before Memorial Day.

What I don’t intend to do is try to convince you that Bryant is going to bust. I don’t think Bryant is going to bust. He is uncommonly good, and uncommonly powerful, with power to all fields that comes out of a shorter swing than you’d expect. Yet there is one thing about Bryant worth considering as hype continues to build. He’s not a perfect prospect; there’s no such thing as a perfect prospect. Every prospect has a flaw, and Bryant’s is enough to raise the eyebrows. Think of it this way: if Bryant were to disappoint, why might that be? It seems we could already have a sign.

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Remember when you thought baseball statistics were easy? Now, analytically, a statistic is hardly worth anything if it’s left unadjusted. You know all the adjustments that go into numbers. Adjustments for ballpark environment. Adjustments for era. Sometimes adjustments for league. As far as WAR is concerned, there are adjustments for position. There’s one adjustment we still don’t make, though: that’s adjustment for quality of opposition. In theory, if there were a pitcher who only ever faced the best teams, and a pitcher who only ever faced the worst teams, that wouldn’t be accounted for. That’s something you’d have to figure out yourself.

Related to this, James Shields has obvious selling points: first and foremost, he’s been good. He’s been durable, and he’s experienced, and he’s pitched in the playoffs, and everything. Then there’s one other thing I don’t think has gotten much attention: Shields has, relative to the average, faced a fairly tough slate of opponents. In the past, I’ve manually calculated average opponent wRC+. Baseball Prospectus has its own version, oppRPA+, and the big advantage of oppRPA+ is it’s already been calculated for me. The average, as usual, is 100. Last year, Shields’ opponents came in at 105. The year before that, 105. The year before that, 105.

Seems like this should be a good thing for Shields’ market; seems like, if you adjust for this, Shields’ numbers would get a boost. But how much does this matter, really? Coming up soon, a first attempt at an answer.

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