FanGraphs Baseball

With the World Series a week and change behind us, but with the offseason still almost entirely ahead and unknown, now seems like the right time to try a little project I’ve had on my mind for a month or so. The annoying(?) bit is that the project requires your participation, in the form of voting in a poll, but then that’s a really easy thing to do, and the question should be pretty simple, and on my end, I get to spend a couple posts embedding polls for your own feedback. Something easy for you, and something easy for me? Everybody wins!

This post is for fans of teams in the American League. The National League post will go up Tuesday morning. If there are multiple teams you hold near and dear, feel free to vote in multiple polls. If you consider yourself more a fan of the game in general, then you can either sit this out, or vote in the poll for the team you feel most strongly about.

All I want to know: how did you feel about the 2015 season? As far as following your favorite team was concerned, how would you rate your overall fan experience? Use whatever criteria you like. How you feel is how you feel — vote according to that feeling. How was the regular season? Did the end spoil the middle? Did your team have a bunch of exciting young players? Did you love going to the ballpark? I understand there’s a lot of input here — there are months of individual days, each day with its own feeling. I just want to know your overall grade, as you reflect on the season that was. There are no wrong answers. Except probably in the Royals poll.

All the polls are below. Hopefully the anchor text works to send you to your team directly!

Read the rest of this entry »

In case you haven’t heard, the new Baseball Hall of Fame ballot was announced today. Fifteen newcomers — players who retired in 2010 — join 17 holdovers. As usual, the list is a mix of token candidates, interesting players and slam dunks. Here is a custom leaderboard for position players and pitchers for just the newcomers. And here’s a table for them, in case you don’t want to play around with the leaderboard.

2016 Hall of Fame Ballot – Newcomers

Name	G	IP	ERA	FIP	xFIP	PA	wOBA	wRC+	BsR	Off	Def	WPA	RE24	WAR
Ken Griffey Jr.	2671					11304	0.384	131	-7.3	444.1	-39.6	45.2	529.0	77.7
Jim Edmonds	2011					7980	0.385	132	-8	317.7	73.3	31.5	352.0	64.5
Jason Kendall	2085					8702	0.334	99	0.7	-6.8	130.8	11.1	92.8	39.8
Mike Hampton	425	2268.1	4.06	4.27	4.57	845	0.289	67	-1.2	-36.9	91.2	0.4	-5.3	35.9
Troy Glaus	1537					6355	0.365	120	-2.4	157.7	-20.4	12.1	159.1	34.4
Luis Castillo	1720					7471	0.327	97	33.4	7.1	37.9	1.4	18.3	28.4
Randy Winn	1717					6878	0.333	100	28.2	28.8	23.5	9.7	70.1	28.1
Mike Lowell	1601					6500	0.346	108	-39.7	25.8	22.7	1.8	77.9	26.0
Trevor Hoffman	1034	1089.1	2.87	3.08	3.78							32.2	174.8	26.0
Billy Wagner	853	903	2.31	2.73	2.76							28.5	196.6	24.1
Garret Anderson	2228					9177	0.334	100	-7.2	-12.6	-59.6	5.5	101.6	24.0
Mark Grudzielanek	1802					7603	0.32	91	4.1	-80	69.4	-8.2	-60.1	23.2
Mike Sweeney	1454					5848	0.366	117	-2.7	121.2	-106.5	15.0	206.1	21.1
Brad Ausmus	1971					7102	0.299	76	-23.2	-244.9	183.7	-22.5	-219.2	17.2
David Eckstein	1311					5705	0.316	92	10.6	-49.7	28.6	-2.7	-40.7	16.8

Note that for the pitchers, I included their position player WAR, as well as their RE24 and WPA. For Mike Hampton, that’s a bump of 7.9 WAR. For the two relievers, it’s a demerit of 0.1 WAR.

The most interesting questions are what you think of Jim Edmonds and Trevor Hoffman. Edmonds makes for a fascinating debate. I’m not sure Hoffman does. Honestly, looking at these dashboard numbers, it’s hard to make the case that Hoffman deserves inclusion. Or, if he does, then Wagner definitely deserves inclusion as well.

Here’s the same leaderboards (position players, pitchers) and table for the entire ballot.

2016 Hall of Fame Ballot – Everyone

Name	G	PA	wOBA	wRC+	BsR	Off	Def	RE24	WPA	WAR
Barry Bonds	2986	12606	0.435	173	30.4	1173.8	67.6	1348.3	127.0	164.4
Roger Clemens	360	213	0.207	15	0	-23.8	23.2	736.4	74.3	134.4
Mike Mussina	376	54	0.172	5	0	-7.1	5.9	400.4	39.2	82.3
Jeff Bagwell	2150	9431	0.405	149	6.5	594.6	-82.1	698.7	59.6	80.2
Curt Schilling	495	901	0.161	-16	-0.3	-132.8	94.6	277.5	25.0	78.8
Ken Griffey Jr.	2671	11304	0.384	131	-7.3	444.1	-39.6	529.0	45.2	77.7
Larry Walker	1988	8030	0.412	140	21.5	427.9	3.5	534.1	48.9	68.7
Tim Raines	2502	10359	0.361	125	100.4	408.2	-109.6	503.5	50.4	66.4
Mark McGwire	1874	7660	0.415	157	-2.5	555	-138.5	581.3	53.5	66.3
Edgar Martinez	2055	8678	0.405	147	-21	500.5	-133.5	514.9	45.2	65.5
Jim Edmonds	2011	7980	0.385	132	-8	317.7	73.3	352.0	31.5	64.5
Alan Trammell	2293	9376	0.343	111	2.3	124.1	184.4	124.9	13.0	63.7
Mike Piazza	1912	7745	0.39	140	-31.6	370.1	20.7	497.4	43.5	62.5
Gary Sheffield	2576	10947	0.391	141	9.7	575.7	-300.9	625.2	60.2	62.1
Sammy Sosa	2354	9896	0.37	124	-7.9	300.4	-8.1	383.0	24.9	60.1
Fred McGriff	2460	10174	0.383	134	-8.6	409.1	-186.3	527.6	47.5	56.9
Jeff Kent	2298	9537	0.367	123	-19.8	259.7	1.2	346.5	24.3	56.1
Nomar Garciaparra	1434	6116	0.376	124	4.8	199.9	18.8	239.2	17.1	41.4
Jason Kendall	2085	8702	0.334	99	0.7	-6.8	130.8	92.8	11.1	39.8
Mike Hampton	425	845	0.289	67	-1.2	-36.9	91.2	-5.3	0.4	35.9
Troy Glaus	1537	6355	0.365	120	-2.4	157.7	-20.4	159.1	12.1	34.4
Luis Castillo	1720	7471	0.327	97	33.4	7.1	37.9	18.3	1.4	28.4
Randy Winn	1717	6878	0.333	100	28.2	28.8	23.5	70.1	9.7	28.1
Lee Smith	549	71	0.09	-55	0	-13	6.1	156.4	22.9	26.1
Mike Lowell	1601	6500	0.346	108	-39.7	25.8	22.7	77.9	1.8	26.0
Trevor Hoffman	551	36	0.127	-28	0	-6.3	3.8	174.8	32.2	26.0
Billy Wagner	452	21	0.119	-30	0	-3.8	2.2	196.6	28.5	24.1
Garret Anderson	2228	9177	0.334	100	-7.2	-12.6	-59.6	101.6	5.5	24.0
Mark Grudzielanek	1802	7603	0.32	91	4.1	-80	69.4	-60.1	-8.2	23.2
Mike Sweeney	1454	5848	0.366	117	-2.7	121.2	-106.5	206.1	15.0	21.1
Brad Ausmus	1971	7102	0.299	76	-23.2	-244.9	183.7	-219.2	-22.5	17.2
David Eckstein	1311	5705	0.316	92	10.6	-49.7	28.6	-40.7	-2.7	16.8

Again, the RE24, WPA and WAR numbers are combined for the pitchers.

So, who would you vote for? I made a survey so you can vote. You’re on the honor system here — don’t pick more than 10 players, please. If you’re looking for my two cents, here’s how I’d vote:

• No Doubters: Bonds, Clemens, Griffey, Mussina, Piazza, Raines
• Don’t Want To See Fall Off Ballot: Sheffield, Walker
• Last Chance: McGwire, Trammell

Because I would want to give McGwire and Trammell their best shot in their final year on the ballot, I’d leave off Bagwell and Schilling, and cross my fingers that Edmonds gets enough votes to stay. Either way, it’s a tough puzzle. Rock your vote below!

Major League Baseball teams are not in the habit of revealing their expected payroll numbers for the following season prior to free agency. Revealing such figures would provide agents negotiating deals with their clients important information regarding how much teams planned to spend. Additionally, telling fans how much a team plans to spend could be harmful from a public relations perspective: if a team misses out on a desired target, it is not always a great idea to spend money for the sake of meeting a budget if that spending would not improve the team and the money could be better spent elsewhere. None of those reasons obscure the fact that we still want to know how much money teams will spend.

Last year’s spending should provide a pretty good proxy for where teams will end up on Opening Day next season. By looking at guaranteed salaries and arbitration estimates, we can come with a decent idea of how much money each team has to spend going into the winter unless they make significant changes to the budget from previous seasons. In the American League, teams like the Tampa Bay Rays, Oakland Athletics, and more recently the Houston Astros have kept spending to a minimum while the New York Yankees, Boston Red Sox, and Detroit Tigers have had no issues with payrolls double or even triple the size of those at the bottom. Much of next year’s spending has little to do with potential free agents, and more to do with players who have already signed.

American League teams have already committed more than $1.2 billion in guaranteed contracts to 2016 payrolls, equal to roughly two-thirds the amount of 2015 AL Opening Day payrolls. As we might expect, there are considerable differences across the league, per Cot’s Contracts.

The Yankees have committed nearly $200 million in salaries before the offseason even starts. At close to $185 million, the guarantees in the Bronx are roughly equal to Oakland, Tampa Bay, Baltimore, Houston, and Cleveland combined. In Oakland, the team has signed Billy Butler, Coco Crisp, and Sean Doolittle to contracts already, giving them around $24 million in 2016 before arbitration and free agent signings.

Read the rest of this entry »

A few days ago, it was reported Miguel Sano would play some outfield during winterball. That’s easy enough to evaluate in isolation — there’s nothing wrong with trying to increase flexibility, and Sano is a bit young to permanently stuff into the DH box. But that’s also easy to interpret as part of a larger process. Word’s out the Twins placed the high bid to negotiate with South Korean first baseman Byung-ho Park. The winning bid of $12.85 million is more than double the winning bid a year ago for Jung-ho Kang, and it’s more than the total value of the four-year contract Kang later signed. It’s pretty clear now that Kang opened some eyes, and though the Twins and Park will still need to reach an agreement, you assume something will get done. The Twins are among baseball’s Byung-ho Park believers.

The question following any transaction is always, is it good? Is it worth it? That can be hard enough to answer when we have a ton of information. It’s far more difficult here. Park, obviously, has no major-league experience, no American track record to examine. We don’t know what the terms of his contract are going to be. We don’t even know that much about the market, or about how the Twins evaluated all their options. I don’t know if this is going to be “worth it,” to the dollar. What I do know is it’ll be good to see what Park can accomplish at the highest level. He’s earned this opportunity, and he’s earned it by demonstrating that he can hit the living crap out of a baseball.

Read the rest of this entry »

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.

Read the rest of this entry »

It’s free-agent time again. Our yearly intrigue is upon us! It’s the time of year when, after hearing for a full baseball season about how teams shouldn’t be built through free agency, teams are built through free agency. So let’s play a game. Let’s forget all about trading, drafting, and developing players. Instead, let’s build a team entirely out of free agents.

Before we construct this hypothetical all free agent team, we must lay some ground rules. First, this is an expansion team, so there are no current payroll obligations on the books nor are there any minor leaguers coming up through the ranks yet. Our owner is Mr. Fatpockets and he’s authorized a payroll of $200 million, and because we like our job pretending to sign free agents more than cleaning out Mr. Fatpockets’ cats’ litter box, we’re going to stay at that figure.

Read the rest of this entry »

Read the rest of this entry »

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.

Read the rest of this entry »

No, we aren’t just going to do a leaderboard sort for best movement in each direction and call it a day. It’s a little bit more complicated to figure out the best changeups by shape and speed, mostly because it’s all relative. The changeup, as the name implies, functions off of the fastball, as a change of pace and movement. So we need to define anything the changeup does relative to the pitcher’s fastball.

Then we can do a sort and call it a day.

In order to define fastball movement, let’s just group together all of the fastballs thrown by a pitcher. It’s probably more nuanced than that; the concept of tunneling or sequencing shows that pitchers can pair their changeup with one fastball or the other for different results. But some of this comes out in the wash: by averaging movement across fastballs, their selection of different fastballs will weight the movement in the direction of the pitcher’s usage.

So then our x and y movement, and velocity, are defined against this average fastball for each pitcher. Using a minimum of 50 changeups thrown, and z-scores to sum up the values, we can get a list of best changeups quickly.

First, the relievers.

Best Reliever Changeups by Movement, Velocity

Pitcher	FB (pfx_x)	FB (pfx_z)	FB (velo)	CH (pfx_x)	CH (pfx_y)	CH (velo)	Sum Z	CH swSTR%
Brad Boxberger	-3.3	10.6	92.6	-7.8	2.0	79.8	6.7	14%
Shawn Tolleson	-2.6	11.0	92.9	-4.8	4.0	79.8	4.9	15%
Josh Fields	0.1	11.5	94.1	-0.6	3.7	81.4	4.5	8%
Roberto Osuna	-4.2	10.7	95.5	-8.0	6.9	82.3	4.0	16%
Josh Smith	-4.1	7.6	89.9	-8.4	1.9	79.4	4.0	8%
Chasen Shreve	7.3	10.6	91.4	6.3	1.5	82.6	3.5	18%
A.J. Ramos	-3.0	8.6	92.4	-7.5	1.0	85.5	3.5	35%
Jeff Ferrell	-4.1	10.2	93.0	-7.4	4.9	82.4	3.5	20%
Danny Farquhar	-5.0	8.5	92.7	-7.5	1.0	84.5	3.2	24%
Fernando Rodney	-6.7	7.1	94.7	-9.6	3.3	82.7	3.1	17%
Andrew Schugel	-7.9	7.8	91.6	-9.6	2.3	80.5	3.1	23%
Joaquin Benoit	-6.5	8.9	94.2	-7.5	1.9	84.1	3.1	24%
Tyler Thornburg	-0.8	11.1	92.2	-5.8	6.3	83.8	3.0	19%
Arnold Leon	-5.1	9.8	91.6	-4.6	2.8	80.2	2.9	22%
Pat Neshek	-8.5	4.9	89.9	-4.6	3.7	68.4	2.9	9%
Tommy Kahnle	-1.9	7.4	94.8	-7.6	2.8	87.2	2.8	23%
Mike Morin	-4.7	8.9	92.3	-0.5	6.8	71.7	2.8	25%
Deolis Guerra	-5.1	10.0	90.8	-6.7	4.0	80.7	2.8	15%
Daniel Hudson	-6.6	8.3	96.0	-9.9	4.9	84.8	2.7	18%
Erik Goeddel	-3.9	9.2	93.0	-4.7	2.0	84.3	2.5	32%

SOURCE: PITCHf/x

pfx_x = horizontal movement
pfx_z = vertical movement
Sum Z = sum of the z-scores for the differentials between fastball and changeups in x, y movement and velocity
swSTR% = swinging strikes over pitches for the changeup
Minumum 50 changeups thrown in 2015

If you listen to The Sleeper and The Bust, you know I talk about this all the time and do the math in my head. Now the math is there for us on the sheet of paper.

Read the rest of this entry »

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.

Read the rest of this entry »