Archive for Featured

Last Wednesday, we looked at the most extreme home runs of the 2015 postseason. There was Daniel Murphy‘s off-the-shoetops homer, one of many ridiculous Kyle Schwarber blasts, and Jose Bautista’s now-infamous bat flip that caused such an uproar. And, while it was great to relive all of those home runs from the playoffs, a simple constraint to that piece was this: there were only 91 home runs hit during the postseason. We’re searching for extreme home runs, and that wasn’t the largest sample size from which to draw. Fun, absolutely, but there is more fun when more homers are involved.

And so we find ourselves here, staring at a sample of every home run hit during the regular season: all 4,907 of them. There are a lot of strange occurrences in that many separate events, and so I’ve pulled out some of the finest moments involving home runs during the entire 2015 regular season. As always, data has been mined from Baseball Savant and HitTrackerOnline. Let’s get to it!

Hardest-Hit Home Run: Josh Donaldson, 4/23/15

Josh Donaldson might win the American League MVP award this year. However, regardless of whether he wins or not, he beat out his biggest competitor in that award (Mike Trout) by almost a full mph in this category, producing an exit velocity of 120.5 mph on a belt-high changeup from Chris Tillman. Whether that fact will give Donaldson any solace if he loses the MVP award cannot be known, as we do not have an accurate knowledge of whether he reads these digital pages, or puts any stock into made-up awards related to home run compilation articles.

Also of note: the sound that emits from this particular contact of ball on bat. I’ve been trying to think of a way to describe it, and the best I can come up with is that something shattered. That something could’ve been the bat, or the ball, or might simply be the sound of a small fusion reaction. Read the rest of this entry »

Since we don’t have much more than velocity readings from Japan, it can be difficult to rely on anything but scouting reports when evaluating pitchers coming over from Nippon Professional Baseball. And now that 27-year-old Kenta Maeda is once again rumored to be coming to America through the posting system, we’re once again left wondering how to place him in context.

We have his Japanese strikeout and walk rates, which we can compare to recent postings to find comparable countrymen. We also have his velocity readings and a general sense of the quality of his pitches that we can use to compare him to pitchers beyond just ones that have come from Japan. We even have one game of PITCHf/x data to help us look at the movement of his pitches.

And the few comparable players we produce might be the best we can do from out here in the public sphere.

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What they may lack in impact bats, the Diamondbacks make up for with pitching depth. They have a lot of pitchers with high floors in the upper levels of the minors, and a few in the low minors that should move quickly. A few have top of the rotation potential. The addition of Dansby Swanson to the organization this June does a lot to help reinforce the offensive pipeline, but the team will have to do a better job developing hitters over the next few years.

Their quantity of outfield options is solid, and was something of a logjam in the upper minors this season. That four players who started playing for the team in 2015 make the top eight here is a good sign for their talent acquisition going forward. Look for the pitchers to start making their presence felt in the big leagues in 2016 and 2017, while we wait on some of the lower-level hitting prospects to put things together.

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We have been working hard to get our team prospect rankings out to you as soon as possible. Starting with the Arizona Diamondbacks, the lists will proceed in alphabetical order by city and team name. As we start rolling out the organizational reports, I wanted to give you some guidelines for understanding my ideas and grades, to avoid confusion over why the grades here differ from other publications, even in cases where we may be saying the same thing. Though this will not be an all-encompassing article of my scouting opinions, it should provide the framework for our conversations on each of the team’s prospects.

I want to go through each of the five tools for hitters and the grades for pitchers, and explain basically what I believe are the most important factors going into them. Since some of you may not read this whole blurb, and then ask questions about why a pitcher who throws 95 only got a 50 grade on his fastball, I will admit to one overarching theme: functionality. How functional is that 95 mile-per-hour fastball if it’s straight and the pitcher who threw it has no idea where it’s going? Similarly, what is the use of an 80 grade for power if the hitter is blind and doesn’t also possess echolocation or some other means to hit a baseball?

One other difference for the way I’ll be communicating scouting grades to you is the presence of three numbers on each tool instead of just two, at least for the professional players. Here’s an example. Consider Rick Vaughn’s fastball before he was given his magical spectacles: 35/50/70. The first number is the current grade; it’s fast, but he can’t locate it, and when it does find the zone, it gets tattooed for a home run by a stereotypically douchy slugger. The second number is the likely future grade; he’s still young and not in prison, and he’s played by Charlie Sheen (the star of the movie), so you know it will get better. Still, the current state of the pitch makes it unlikely to be crazy effective, so an average future fastball could be the most likely outcome. Or, if you prefer percentiles, call this the 50th percentile projection. The third number is the ceiling grade, or 90th percentile projection, to help demonstrate the volatility and raw potential of a tool. I feel this gives readers a better sense of the possible outcomes a player could achieve, and more information to understand my thoughts on the likelihood of reaching those levels.

Kiley gave us a great conversion table last year for understanding scouting grades in an objective (though admittedly estimated) context. I absolutely loved the idea, especially because my brain tends to think more in terms of what statistical production a player’s future ability will produce, and then convert it into the more universally used 20-80 scouting scale. Here is my slightly altered version of the same table for hitters, followed by a breakdown of the individual tools:

Scouting Grades in Context: Hitters

Grade	Tool Is Called	Batting Average	HR	ISO	Baserunning Runs	Fielding Runs
80	80	0.320	40	0.300	12	30
75		0.310	35-40	0.275	10	25
70	Plus Plus	0.300	30-35	0.25	8	20
65		0.290	27-30	0.225	6	15
60	Plus	0.280	23-27	0.200	4	10
55	Above Average	0.270	19-22	0.175	2	5
50	Average	0.260	15-18	0.150	0	0
45	Below Average	0.250	12-15	0.125	-2	-5
40		0.240	8-12	0.100	-4	-10
35		0.230	5-8	0.075	-6	-15
30		0.220	3-5	0.05	-8	-20

Remember these are estimates of true talent that we are trying to project multiple years down the road. Please don’t hate on me in two years when a player with a 55-grade power hits 25 home runs. First, why be so mean? And second, scouting grades are an attempt to peg true talent. Even if a tool remains static for years, the statistical evidence of the quality of that tool can vary due to league adjustments to the player, hidden injuries, randomness, etc. Think of it like BABIP and UZR, of which you need a few years of data to know anything about where a player really stands.

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Ian Desmond is 0-for-14 with 10 strikeouts and zero walks against Craig Kimbrel.

I know, I know. Small samples, noise, predictive value and whathaveyou — I get it. Usually, it’s best not to read too much into batter-pitcher matchup stats. Sometimes, though, it’s clear that a certain batter just doesn’t stand a chance against a certain pitcher. Sometimes, it’s clear that a Craig Kimbrel can turn an Ian Desmond into a helpless puddle of mush in the batter’s box simply by standing on the mound.

What if I told you that, in rare cases, fielders could possess the same ability? What if I told you that, in early 2014, Andrelton Simmons learned he had such a power? That simply by taking the field, he could render Travis d’Arnaud completely and utterly powerless? Not only that, but that Simmons could actually control the game with his mind, so long as d’Arnaud was on the field with him?

* * *

The date was April 9, 2014. Spirits were high in the Mets’ clubhouse. The season was young. They’d shut out the host Braves in their home opener the night before. Young catcher Travis d’Arnaud had collected his first two hits of the season and scored a run. He hoped to build upon that success against Braves hurler Ervin Santana the next day. He strode to the plate, confident and unknowing.

This was young d’Arnaud’s first encounter with Simmons. The result was unexpected, yet also unsurprising. d’Arnaud had heard tell of Simmons’ skills. Now, he’d experienced them firsthand.

“What can you do?” d’Arnaud thought to himself. “Gotta tip your cap.”

In fact, as he lunged toward first base, d’Arnaud did tip his cap. It fell right off the back of his head and down to the Earth behind him. As the helmet hurtled toward the dirt, it eclipsed the print on the back of d’Arnaud’s jersey, momentarily displaying the word “dUD.”

This could be interpreted as foreshadowing.

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If you’re a team looking to add a significant piece to your roster, this is a pretty great winter to be a buyer. Unlike most recent free agent crops, this group of available players boasts both legitimately elite players and a host of quality mid-tier options. Especially for teams looking for starting pitching or outfield help, the supply of talent is unlike anything we’ve seen in a while, since the boom of early-career extensions has served to keep a lot of the game’s best players from reaching the open market.

Of course, supply and price are often inversely correlated, so when there’s a lot of talent available, it’s easy to conclude that teams will price-shop across multiple options, and we might see less inflation this year than we have in previous years. However, in this case, I don’t know that the increased supply of talent is actually going to lead a stagnation in salary inflation; in fact, I think there are some reasons to believe that we may see some significant spending, above and beyond what is already expected, by MLB teams this winter.

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Four days. It took MLB all of four days to bring us the first transaction of the off-season, as the Mariners and Rays got together on a six player trade that ships some interesting players in both directions. The full trade, as announced on Thursday evening.

Tampa Bay receives:

SS Brad Miller
1B Logan Morrison
RHP Danny Farquhar

Seattle receives:

RHP Nate Karns
OF Boog Powell
LHP C.J. Riefenhauser

While this is a six player deal, for simplicity, we can mostly break this down into three one-for-ones.

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Yesterday, Carson Cistulli revealed the results of our Contract Crowdsourcing project, listing the aggregate salary projected for 82 different free agents this winter. The project is a very useful tool to get an understanding of what a broad spectrum of perspectives see as fair market value, but the nature of aggregation means that the totals — especially on the high-end — will almost always end up being a bit lower than what the players actually sign for. After all, players don’t sign for the median value of all of their offers; they take the highest one, in most cases.

So, as a follow-up, I’ve put together my predictions for the 50 largest free agent contracts signed this winter. I did this last year too, though I took some pretty big wild guesses when it came to putting players and potential teams together, so some of my guesses look pretty ridiculous in hindsight. I did get a few contract terms right, and managed to match the Yankees with Chase Headley and had the Tigers re-signing Victor Martinez, but we’ll see if we can clear last year’s pretty low bar.

Obviously, this is mostly just for fun, since predicting what teams will do in advance is very difficult. But it also serves as a chance to talk about what I think teams may do in general this winter, even if the specific players end up going elsewhere. As we did last year, we’ll go team by team, then put the full table of contracts at the end. Just for fun (or because that’s how I sorted the list in Excel), we’ll go in alphabetical order of team nickname.

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The Gold Glove Awards are getting better. They really are! Two years ago, when I did this post for the first time, the numbers and the MLB finalists agreed on 28 selections. Last year, it was 30. This year, it’s 32. Furthermore, there appear to be fewer notably egregious selections. There are still a couple here and there, and we’ll get to those, but the days of Rafael Palmeiro — or even Derek Jeter, for that matter — winning Gold Gloves are behind us. When MLB decided to begin folding advanced defensive metrics into the selection process, everything improved markedly.

For the thousandth time: no defensive metric is perfect. However, they’re the certainly better than fielding percentage, the eye test, and “who is the best hitter,” and they’re currently the best public way we have to evaluate defense, so they’re what we use. For a while, Gold Gloves were held to a high standard. It was an honor to win them. They meant something. Then, there was a stretch when the Gold Glove became a farce. People realized they weren’t being given to the best defenders — they weren’t being given to good defenders, even — and it was all a joke. Now, the Gold Gloves are earning their back their status, and that’s a good thing. The awards should matter. It’s nice to see the players who deserve to be recognized, recognized.

So let’s recognize. The way the finalists are determined now is part manager/coach vote, part metrics. But what if it was all metrics? Just the objective numbers, and no human bias. That’s what I aim to do here.
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It’s really easy for me to get sucked into our Clutch leaderboards. We spend so much time focusing on true-talent levels, because true talent is what’s mostly stable, but timing is a huge part of winning or losing, and just because it’s hard to predict doesn’t mean it can’t be analyzed later on. We have win-probability numbers since 1974. On a per-plate-appearance basis, the most clutch position player has been Jim Leyritz. The least has been Ron Kittle. The most clutch active position player has been Willie Bloomquist or, if you figure he’s about to retire, Eric Hosmer. The least has been Giancarlo Stanton. Doesn’t mean Willie Bloomquist has quietly been a better hitter than Giancarlo Stanton. It’s just, timing closes the gap. (It remains an enormous gap.)

Because of the Royals, I’ve thought about Clutch a lot lately. Good offensive timing was a critical part of their run to the playoffs and then to the title. And when you think of the Royals lineup, you also immediately think about strikeouts, and about how they don’t collect very many. It’s only natural to try to establish a link between one and the other. I’ve tried to glance at this before, but now I’m coming at it in a different way. And I’m also trying to investigate a different but related point. Question No. 1: is there a link between Clutch and strikeouts? Question No. 2: if there is, has it changed at all lately, with velocity and strikeouts on the rise?

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