Next Year’s Pitchers, Projected With Uncertainty Constraints

A little while ago, I took a look at the potential variability in a pitcher’s ERA based on their peripherals, with the promise that this week I would look at each individual pitcher’s likely ERA spread for this year.

Here is that. There’s a (sortable) table within this post with some information including a point estimate, the standard deviation of each pitcher’s ERAs (with 1,000 simulations), and the 10th and 90th percentile ERAs. Download this .csv file for a more detailed table with more percentile estimates, BABIP estimates, some more various information, and about 200 more pitchers (the following table is cut off at pitchers projected for 55 innings or more).

Speaking of innings, the number of innings used for this is the number projected by the FanGraphs Depth Charts, which are set by humans who know what’s going on with each team and player. This is the most accurate way, probably, of predicting how many innings each pitcher will throw. Of course, the results will be different for a given pitcher if he ends up throwing a different amount of innings, as the number of innings pitched greatly affects the variability. Additionally, the K% and BB% that were used as inputs were obtained from those depth charts, which use ZiPS and Steamer averaged together (they do not, however, have batted ball distribution projections; for that, I used the methods in this post).

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Ongoing Coverage of LSU Freshman Alex Lange’s Curveball

Recently in these electronic pages, the author — an amateur in all the saddest ways — utilized the few skills he possesses to compose a paean in praise of LSU freshman right-hander Alex Lange’s curveball. Lange’s name had appeared among those players who’d produced the (maybe) best predictive pitching stats in the Southeastern Conference. That curveball, it seemed, was responsible for no little part of his success.

Over this past weekend, Lange producing perhaps his best start of the season, striking out 13 of the 30 batters he faced against the University of Kentucky (box). A brief inspection of that game’s video highlights reveals that Lange once again utilize his curveball to good effect.

Here, for example, is Lange utilizing his curveball to the effect of striking out an anonymous Kentucky batter:

Lange 1

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2015 Pitching Projections — Interactive

Last week at FanGraphs, we looked at our Positional Power Rankings for position players. As a companion to our rankings, we had our offensive projections built into an interactive data visualization. This week we are ranking pitching staffs. In the interest of synergy and symmetry, I constructed an analogous pitching projections data visualization using FIP as the primary comparison metric.

This interactive chart is similar to the one I constructed for the batters’ OPS, except there are a few more options to choose from regarding metrics. The chart defaults to FIP, but you are able to view the data by either ERA or WAR as well. Since relief pitchers have a fundamentally different role and stats than starting pitchers, you are also able to filter the players based on those two positions.

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If Jonathan Lucroy Never Struck Out Again

Milwaukee’s Jonathan Lucroy has distinguished himself in recent years as one of the major leagues’ best players. Not only, for example, did he rank among the top-ten hitters by WAR last year, but also added the third-most runs by way of catcher framing according to the methodology used by Matthew Carruth at StatCorner — which metric isn’t included in the WAR figures here at the site. Overall, he produced the fifth-best season in the majors last year, according to our writers.

This spring, Lucroy is pursuing another means by which to improve his already impressive skill set — namely, by never striking out. No batter this spring has recorded as many plate appearances as Lucroy (33) while also recording a strikeout rate of 0%.

Insofar as literally zero qualified batters since 1913 (since which year the relevant data exists) have produced a 0% strikeout rate — and also insofar as league-wide strikeout rates are currently at an all-time high — it’s unlikely that Lucroy will be able to parlay this particular brand of success into a full major-league season.

“What if he did, though?” is the sort of idle question one fortunate enough to have been born and raised in a middle-class family is able both to ask and attempt to answer in exchange for even more money. The results of that inquiry are below.

What I did was to start with Lucroy’s Depth Chart projection and then convert every strikeout into a batted ball, assuming that those batted balls would be distributed as singles and doubles and triples and home runs at the same rate at which Lucroy’s actual hits are projected to occur. I made no adjustments to walk rate or BABIP or, like, sacrifice flies — all of which would also certainly change if the actual Jonathan Lucroy were never to strike out. Attempting to account for all those numbers, however, would require even more and weirder assumptions, so I’ve opted just for this simpler version.

Below are the results of those math tricks. Proj denotes Lucroy’s Depth Chart projection. 0 Ks denotes his projection with strikeouts converted into batted balls. Diff is the result of the first line subtracted from the second.

Type PA AB BB% K% BABIP H 1B 2B 3B HR AVG OBP SLG wOBA wRC+ Bat WAR
Proj 559 503 8.4% 12.0% .306 144 96 31 3 14 .287 .349 .444 .349 120 12.5 4.0
0 Ks 559 503 8.4% 0.0% .306 164 110 35 3 16 .326 .384 .503 .390 148 30.1 5.9
Diff 0 0 0.0% -12.0% .000 +20 +14 +4 0 +2 +.039 +.035 +.059 +.041 +28 +17.6 +1.9

If Lucroy were never to strike out, he’d produce nearly 18 runs over the course of a season — or, roughly two wins. A considerable improvement, that. And yet, if that number seems perhaps underwhelming, it’s because Lucroy is already projected to record just a 12.0% strikeout rate this year — already greater than a standard deviation better than league average.

To find the largest possible gain provided by a zero-strikeout projections, it’s necessary to identify a player who both (a) strikes out frequently and also (b) produced considerable damage on contact. Houston’s Chris Carter is that precise sort of player.

What would happen, in this hypotethetical world, if Chris Carter never struck out. Here are thes results using the same methodology as with Lucroy:

Type PA AB BB% K% BABIP H 1B 2B 3B HR AVG OBP SLG wOBA wRC+ Bat WAR
Proj 616 539 10.8% 32.7% .285 121 63 24 1 33 .225 .313 .459 .338 118 11.9 1.9
0 Ks 616 539 10.8% 0.0% .285 183 95 36 2 50 .340 .414 .692 .474 213 76.3 9.0
Diff 0 0 0.0% -32.7% .000 +62 +32 +12 +1 +17 +.115 +.101 +.233 +.136 +95 +64.4 +7.1

Seven wins! Chris Carter would become more or less Mike Trout’s equal in this particular case. The contingency is unlikely, of course.


Delightful Thing: UNC Junior Trent Thornton’s Delivery

North Carolina’s series at home this weekend against Miami is notable insofar as it features a number of players — UNC right-hander Benton Moss and Miami third baseman David Thompson, among others — a number of players who’ve produced the best (maybe) predictive stats within the ACC.

Largely owing to a high walk rate, UNC closer Trent Thornton has produced only pretty good numbers within that same conference. What he has done, though, is exhibit some considerable proficiency in the art of human movement — which may or may not be accurately referred to as kinaesthetics.

Here, by way of illustration, is Thornton delivering a pitch during last Saturday’s game against Georgia Tech (in which he struck out five of the nine batters he faced):

Thornton 1

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Notable Weekend College Series Based on the Performances

Yesterday, the author published a post claiming to include the top players by (maybe) predictive stats from college baseball’s most competitive conferences.

What follows are the three weekend series likely to feature the greatest number of players whose names appeared within that post. KATOH+ and KATOH- are index metrics based on those (maybe) predictive stats and designed for batters and pitchers, respectively. In each case, 100 is average, while above 100 is better for batters and below 100 is better for pitchers. Read more about the author’s questionable methodology here.

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Miami at North Carolina
Who It Features
Definitely probably UNC senior right-hander Benton Moss (21.2 IP, 72 KATOH-) on Sunday. Moss missed some time with arm trouble, but returned this past Sunday and was once again excellent, producting an 8:1 strikeout-to-walk ratio against 25 batters over 8.0 innings (box). He’s scheduled to start the Sunday. Among Miami hitters, junior center fielder Ricky Eusebio (113 PA, 116 KATOH+), senior catcher Garrett Kennedy (81 PA, 120 KATOH+), and junior third baseman David Thompson (116 PA, 147 KATOH+) all rank among the ACC’s top-20 batters.

When It’s On (ET)
Friday at 6:30pm
Saturday at 3:00pm
Sunday at 12:00pm

How to Watch It
Watch ESPN (link).

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Ole Miss at Arkansas
Who It Features
The top starter currently in the SEC, Ole Miss sophomore right-hander Brady Bramlett (35.0 IP, 79 KATOH-). Bramlett was actually averaging a strikeout per inning as a freshman in 2013, working both in a starting and relief capacity, before tearing his labrum. He sat out the 2014 season and has made a formidable return. He’s schedule to start Friday’s game. Arkansas, meanwhile, features two of the conference’s top-15 hitters: sophomore center fielder Andrew Benintendi (106 PA, 128 KATOH+) and junior third baseman Bobby Werne (98 PA, 120 KATOH+).

When It’s On (ET)
Friday at 7:00pm
Saturday at 3:00pm

How to Watch It
SEC Network or SEC Network Plus on Watch ESPN (link).

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UCLA at Washington State
Who It Features
Two UCLA right handers, junior James Kaprielian (38.0 IP, 79 KATOH-) and freshman Griffin Canning (35.0 IP, 76 KATOH-), who make starts on Friday and Sunday, respectively. They’re fifth and third, respectively, among Pac-12 pitchers at the moment. UCLA also features two of the conference’s top-10 hitters: senior third baseman Chris Keck (103 PA, 131 KATOH+) and junior shortstop Kevin Kramer (110 PA, 127 KATOH+).

When It’s On (ET)
Friday at 9:00pm
Saturday at 5:00pm
Sunday at 3:00pm

How to Watch It
Washington State’s live video feed (link).


The Last Expo Standing: Poll Results

Yesterday I examined all seven viable candidates who could one day hold the title of the last ex-Expo playing in the Major Leagues. What I found remarkable about this “race” is that there really is not an obvious favorite when it comes to who will outlast the others. With the possible exceptions of Luis Ayala and Jon Rauch, neither of whom appeared in the majors in 2014, there also isn’t an obvious dud in the group: each player has had such long journeyman careers, with so many ups and downs, it’s hard to tell what confluence of events and old age will actually knock these men out of the majors for good.

The voting separated the players into three tiers. In the first tier we had Ayala and Rauch, each receiving about 2% of the total vote. I would be encouraged by this result, if I were Ayala and Rauch: this means that dozens of FanGraphs readers believe they will in fact claw their way back to the Majors despite their recent series of roster cuts. I consider this the equivalent of a write-in candidate earning 2% of a vote for political office, which would be quite an uncommon display of public support indeed.

In the second tier we have Bruce Chen, Endy Chavez, and Scott Downs, each receiving about 6-10% of the vote. I believe the tie that binds these players is age: Chen would be entering his age-38 season, Chavez his age-37, and Downs his age-39. I do find it interesting that Chavez’s guaranteed contract for 2015 did not elevate him above Chen and Downs, who were both informed in recent days by the Cleveland Indians that they would not make the team’s Opening Day roster.

No matter: in the final tier, way ahead of the pack, we have Maicer Izturis and Bartolo Colon. At the time of this writing — about lunchtime on Friday, Pacific Standard Time — Izturis has the lead, 37% to 32%.

Despite easily being the oldest player on the list, Colon — entering his age-42 season — nonetheless seems as impervious to the effects of time better than any player since Jamie Moyer. I interpret his robust vote tally as the readers of FanGraphs saying: “What, really, is the difference between the lovably rotund Colon pitching in the big leagues (and earning Cy Young votes) at age 40, and pitching in the big leagues at age 47?”

And in the lead we have Izturis, who leads perhaps because he is comfortably in his mid-thirties instead of his late-thirties. Perhaps also in Izturis’ favor: he spent years as a utility man for the annual playoff entrant Los Angeles Angels — meaning that he rarely got over 100 starts a year, and perhaps has comparatively little wear-and-tear for a long-time veteran.

Where does my vote go? Um, I really don’t know.

While I understand why Izturis is in the lead, and am tempted to vote for him as well, his abilities as a major leaguer have fallen off quite dramatically and abruptly in his mid-thirties — an age when the rest of these dudes really seem to come alive. It remains to be seen if Izturis’ terrible tenure with the Blue Jays is just a blip on the way to his grandfatherly veteran-hood, or whether it’s all over at the end of 2015, his last year on a guaranteed deal.

Because of his established track record of sticking around the Majors despite below-replacement performance (and on some pretty great teams recently, at that) — not to mention that he has already survived a year-long hiatus from the majors in 2010 — I am inclined to vote for Chavez.

That said, I also would not be surprised if Chavez plays his last game before any of the other six players. This will no doubt be a thrilling race to keep an eye on in the coming months and years.


All The Positional Power Rankings Thus Far

This morning, we wrapped up our look at the guys who play the field in our Positional Power Rankings series; we’ll be tackling the pitching staffs next week. But for those of you interested in playing catchup or going back over the posts, I’ve collected them all in one handy place here; you’ll still always be able to reference all of the posts in the category, but I figured I’d make them a little bit easier to find here.

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Interactively Graphing Forbes’ Team Values

Yesterday, Forbes released its franchise values for all 30 Major League Baseball teams. Briefly, the team values are estimates of the price that the franchise is likely to sell if the team’s management group began fielding offers. There are always debates about the accuracy of revenue and valuation figures, and I would recommend reading one of the many FanGraphs articles that already has examined the methods and discrepancies in both Forbes and Bloomberg’s valuation metrics.

In this post, I want to provide some graphical context for Forbes’ data and allow you to explore the data in a different way than on a table.

Being a financial news outlet, the team value is the heart of the Forbes’ data. The graphic below shows that data as a simple bar graph. From this, there are four different tiers of teams. There’s a small-market plateau that constitutes the lower half of MLB teams. These teams are valued under $1 billion and come from smaller cities (except Toronto and Houston). The next tier has larger metropolitan areas or teams that are the secondary team in the largest markets (White Sox, Angels, Mets). The third tier is composed of ‘big market’ teams that come from the largest US cities. Finally, the Yankees are in a tier by themselves.

2015 Forbes Team Value

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Dodgers Reportedly Throw Money Around, Sign Hector Olivera

Last week, I suggested that the Dodgers don’t really need Hector Olivera because they already have something pretty similar in Justin Turner. Obviously, Andrew Friedman and his crew do not agree.

Kiley McDaniel did a nice job breaking down Olivera a few weeks ago, and in that piece, he wrote this: “The Dodgers are the only team that’s in on Olivera that can afford to pay whatever they want.” And this signing is a reminder that they really can do just that; a team with the largest payroll in baseball and no obvious spot for Olivera this season just ponied up a $28 million signing bonus and $34 million in future salary commitments for a guy who probably doesn’t make a significant impact for them until 2016, when he’ll be 31 years of age.

Of course, it’s quite possible that my Justin Turner comparison was quite light, and perhaps Olivera is even better than Juan Uribe by the second half of this season, giving the team a bit of an upgrade at third base for the stretch run. It’s not impossible that Olivera will contribute this year, though he’d have to be pretty great to represent a substantial upgrade over Uribe, Turner, and whatever Alex Guerrero could potentially give them at third base.

Right now, we have the Dodgers third base contingent combining for about +3 WAR this season; Olivera might push that to +4 if he comes up quickly and is awesome, but this is unlikely to move the needle for LA that much this year. This is basically the Dodgers spending $63 million to solve a 2016 problem — when Uribe and Howie Kendrick are both set to hit free agency — a few months in advance. And they’re basically the only team in baseball that can still afford to do stuff like that.

It’s great to be smart and find all kinds of hidden bargains, constructing a good team out of undervalued pieces. It’s also great to just be able to outbid everyone for anyone you want. The Dodgers apparently are going to do both.