Projecting the 2013 Nationals, Part 1: Ground Rules & Starting Line-ups

Spring Training is well underway down in Viera. This is the season, then, of portents and omens–the latest and most amusing of which was the story of an osprey dropping a fish onto the Nats outfield. Not having any expertise in the art of augury, I don’t think I can really comment about the auspiciousness or inauspiciousness of such an omen for the upcoming season.

What I can offer you, however, is the results of my own admittedly crude projection system. Long-time readers will know that I like to think of the baseball season as a single inning of a baseball game writ very very large. In the top of the inning, we see the home team take the field, and see how good the pitching and the defense are at getting opposing batters out. In the bottom of the inning, we watch the home team at bat, and see how well they drive in runs. Then we count the runs allowed in the top of the inning and the runs scored in the bottom of the inning–if the home team scored more runs than the other team, they win.

If you want the nuts and bolts of my projection system, please, read the post I’ve linked above. It describes the general outline of the system as clearly as I can.

This year, however, I’m making a few changes to the Natstradamus projection system.

First, in pitching, I have replaced FIP with xFIP. I don’t know enough about home run/fly ball rates to tell, really, which pitchers are “lucky” or “unlucky” with respect to how many home runs they give up on fly balls. xFIP fixes that for me by normalizing runs allowed by a pitcher to a league-average home run/fly ball rate. Some pitchers get better; other pitchers get worse; but I think over all that might be a more fair way of evaluating pitchers for the purposes of this projection system.

Second, I have tweaked the defensive calculations slightly. Instead of using UZR, I have calculated a UZR/game, and then multiply that  by the number of games in which I expect each player to appear. Again, this is crude, and defensive metrics are highly unstable anyway, but hey, it’s all I’ve got.

Remember, my projections are based on four-year trailing averages for each stat. That is, they’re the averages of the past four years.

With those preliminaries out of the way, let’s start this year’s predictions off by going through the 2013 Nationals’ projected 25 man roster:

Starting Rotation

• Stephen Strasburg, xFIP 2.56
• Gio Gonzales, xFIP 3.81. I do not believe Gio will be subject to a suspension for his alleged involvement in the Biogenesis scandal. I explained my view on the situation here.
• Jordan Zimmermann, xFIP 3.71.
• Ross Detwiler, xFIP 4.44
• Dan Haren, xFIP 3.37.

Starting Position Players

• Adam LaRoche, 1B.
• Danny Espinosa, 2B
• Ryan Zimmerman, 3B
• Ian Desmond, SS
• Bryce Harper, LF
• Denard Span, CF.
• Jayson Werth, RF
• Wilson Ramos, C
• Kurt Suzuki, C. I have Ramos and Suzuki splitting playing time evenly.
  

Bench

• Chad Tracy, OF/3B
• Tyler Moore, OF/1B
• Steve Lombardozzi, IF/OF
• Roger Bernadina, OF

Bullpen

• Rafael Soriano, xFIP 3.6, Primary Closer
• Drew Storen, xFIP 3.46, Primary Set-up, Back-up Closer
• Tyler Clippard, xFIP 3.54
• Ryan Mattheus, xFIP 4.48
• Zach Duke, xFIP 4.34, Left-handed long reliever/Spot starter
• Craig Stammen, xFIP 3.96, Right-handed long reliever/Spot Starter
• Bill Bray, xFIP 4.19, Left-handed one-out guy. This is probably the most controversial pick; others might put Henry Rodriguez or Christian Garcia here instead. But I’m going to assume Bray heads north with the club.

No surprises, then. Stay tuned as we discuss pitching and defense in Part 2 of our projections.

The Limits of Prescience

A thread over at the Washington Nationals Fan Forums pushed back against some of my projections here and raised a few points that I neglected to address in my 2012 projections.

Margins of Error

Interesting projections but the missing piece would be an estimate of how much of a margin of error there would be for both the offensive and defensive estimates that would provide a range for the expected number of wins as opposed to a hard number.

This was a serious omission on my part. All projections have a certain degree of uncertainty built into them, and I really should have discussed the degree of uncertainty built into mine.

I took my method for calculating the projected runs allowed by pitching and defense from this site. The author tested this method against 7 years of complete season data from 2002 through 2008. As he writes:

I found the R^2 value. Not to oversimplify things too much, but this value basically shows what percentage of the variation can be accounted for by the model. The value ranges from 0 (worthless) to 1 (perfect). For my 210 data points, I had an R^2 value of about 0.78 (i.e. 78% of the variation).

That means that my defense and pitching runs allowed projections should be good for plus or minus 22%. That gives a lower bound of 482.84 runs allowed and an upper bound of 755.20 runs allowed.

If we assume that my offensive predictions are correct (a problem I’ll get to in a second), that means the 2012 Nats will win anywhere between 68 and 103 games

I know that’s an immense difference. I’m not sure how I could close that gap. UZR doesn’t account for pitcher or catcher defense, for instance. But even then, I think the method at least gets us in the ballpark.

The offense numbers are a lot more troublesome. I haven’t been able to do any real regression analysis to determine how good my model is–I simply haven’t had the time.

On the other hand our offense has way too many question marks to estimate the total number of runs scored with enough precision to come up with a meaningful value that can be used in a secondary projection as you did in calculating our win total.

Any type of future projection is likely to involve more than a little handwaving. Here, I’ve drawn an arbitrary line: all players included in this analysis are players on the Nats’ 25-man roster as of January 27, 2012, some 23 days before pitchers and catchers are due to report at Viera.

Individual Players and the Projections

Will Werth stay Werthless?

2011 Jayson Werth was astonishingly bad. I’m going to believe that his 2011 numbers are aberrations and not indicative of a “new normal.” I’m fairly confident that the 4-year average from 2008-2011 is a fair picture of what kind of player Werth is now–somewhere between his Philly days and the debacle of 2011.

Will Desmond, Ramos, and Espi improve or stagnate?

As far as Desmond and Espinosa, I have no idea. I don’t think I have nearly enough data about them to make any predictions going forward. Ramos, however, gets a nice bump from more playing time and more PAs. His wRC/PA isn’t terrible, so that’s to be expected.

Will Morse fall back to Earth?

I’m going to go ahead and say No. As I said in Part 3, Morse’s modest offensive outputs in 2008-2010 might make you think that he’s going to crash down to Earth in 2012. But, remember, I’ve taken a four year average of his wRC/PA over the same period. Giving Morse 600 plate appearances in 2012 gives a projected wRC of 97.00: exactly the same as his breakout 2011 “beastmode” year. Indeed, even if we throw out Morse’s 2011 season, running the same calculation over data from 2008-2010 yields a projected wRC of 90.00: Seven runs short of our prior projection and of the 2011 total, but still enough to make him almost as good as Ryan Zimmerman (projected for 90.69 wRC). Indeed, all of this taken together seems like pretty persuasive evidence that “beastmode” has been lurking inside him the whole time, and only needed to see enough PAs.

Will Zimmm get hurt again? Will LaRoche bounce back?

My response: Dammit, Jim, I’m a baseball fan, not a doctor!. I have really no good way of figuring out La Roche’s prognosis post-surgery, nor can I really know anything about the state of Zimmerman’s joints and muscles. The only real response I have here is that the four-year interval I picked should be fair to both men in terms of their expected production.

Who plays centerfield?

Again, I had to draw an arbitrary line and go with who was in the organization as of the day I began compiling the statistics. That means that for now, we’re looking at a DeRosa/Bernadina platoon in center field. This might not be ideal, but I didn’t want to mix players who weren’t officially in the organization into these projections. Blown Save, Win, however, has attempted to address the center field question in a recent post, where he suggests that perhaps the short-term answer is Rick Ankiel. I’ll have to go back and study this, obviously.

Projecting the 2012 Nationals, Part 1: Ground Rules & Starting Line-Ups

In keeping with the prophetic nature of the blog, I promised you all some projections about the 2012 Nationals. As you might imagine, trying to see the future is a fair bit of work, and I wanted to be able to walk you all through my reasoning step by step, so I’m going to break my analysis up into a 4-post series.

And because this is about baseball, after all, I’ll break it down in a baseball-like fashion. Imagine yourselves in Davey Johnson’s shoes, stepping out towards home plate at Nats park, line-up card in hand, ready to meet the umpire and the opposing manager. You’d have to discuss the ground rules first, and then exchange line-up cards. That’s what we’ll be doing in this post: sketching out the outlines of my method and telling you just who’s in the starting line-up.

Ground Rules: What Are We Doing and How Are We Doing It?

A baseball team’s winning percentage can be estimated fairly accurately using Bill James’s Pythagorean win expectation formula:

 This is of course pretty intuitive, particularly in its simplified form on the right. The team that scores more runs than it gives up will win a baseball game. A 162-game season is thus just a day in the [ball]park, but in macrocosm. Our calculations feel pretty much like watching a ballgame, too:

1. Figure out who makes the team.
2. Watch the top of the inning: how many runs do the pitchers give up? To do this, we’ll need a stat called FIP, or Fielding-Independent Pitching.
3. Still in the top of the inning: how well is the team defending? To answer that, we’ll need an esoteric stat: UZR, or Ultimate Zone Rating [Yes, I know it’s a dumb name. The sad thing is that if Sabermetricians were more articulate, they’d be baseball writers–and thereby deprive us of their statistical insights].
4. Finally, at the bottom of the inning, we figure out if the home team can score more runs than the visiting team did in the top of its inning. To find that out, we’ll need wRC, weighted Runs Created.

Projections should be pretty straightforward, right? There are a couple of pitfalls. UZR is notoriously unstable, and needs at least 3 years of data to be any good at all in calculations like this. Because we’re dealing with a pretty mixed bunch of ballplayers here, I can’t just use career UZR figures and take an annual average. Jayson Werth’s figure would have to be divided by 9, while Danny Espinosa’s would only be divided by 2. To even things up, I’ve decided to use a four-year average of each of the stats above. That gives just about enough of a sample size, I think, to be useful. It’s also fair: the four-year moving average sweeps from 2008 through the end of 2011–good news for Jayson Werth, who gets to include his phenomenal run with the Phillies with his near-abysmal 2011 campaign.

The Starting Lineup: Meet your 2012 Washington Nationals!

With today’s acquisition of veteran relief pitcher Brad Lidge, I think it’s pretty safe to say that the Hot Stove League is at an end. Without further ado, meet your 2012 Washington Nationals! [All of the data here, by the way, is from Fangraphs.]

Starting Rotation

Pitcher Name	2012 IP (Projected)	FIP (2008-2011 Average)	Remarks
Stephen Strasburg	160.00	1.87	Strasburg’s coming back after Tommy John surgery, so he’ll be on an innings limit, just like Jordan Zimmermann was in 2011. I’ve set his limit at 160 innings, around about where J.Z. was limited last year.
Jordan Zimmermann	180.00	3.59	Now that J.Z. is healthy again, I’ve allocated him what I feel is a fair load for a starting pitcher.
Gio Gonzalez	200.00	4.06	Gio’s had a few 200 IP seasons, and he comes billed as an inning-eater, so I’ve given him a heavier IP load.
Chien-Ming Wang	180.00	4.35	Wang is also coming off a long injury. I wonder if giving him a regular starting pitcher’s load isn’t a bit ambitious. Also, Wang gets hurt by my somewhat arbitrary 4-year window. His career FIP is really 4.04, but for now I’m going to accept the 4.35 number because…
John Lannan	180.00	4.57	Lannan’s FIP is really really high compared with the rest of the rotation. I’ll get a lot of flak for putting him in the rotation at all, especially from Detwiler’s (4.30 FIP) partisans. On a wholly subjective level, though I think Lannan’s pitched well enough for long enough to land a spot in the rotation. Detwiler, to me, anyway, seems to have a much harder time the second and third time through an opposing batting order, but I don’t have any data to confirm that at the moment.

Bullpen

Pitcher Name	2012 IP (Projected)	FIP (2008-2011 Average)	Remarks
Ross Detwiler	63.2	4.30	Long relief.
Tom Gorzelanny	98.1	4.64	Long relief.
Craig Stammen	61.0	4.23	Middle relief
Sean Burnett	62.0	4.20	Middle relief
Brad Lidge	60.0	3.72	Middle relief. Lidge figures to be a 6th-inning pitcher to get to Clippard & Storen. Also, as far as I can tell, Lidge has never had a plate appearance, so he doesn’t mess with my offensive calculations.
Henry Rodriguez	72.2	3.22	Middle relief; alternate closer; last-ditch pitcher in losing efforts.
Tyler Clippard	72.2	3.61	Clip’s 2008-2011 FIP is better than his career FIP of 3.91
Drew Storen	73.0	3.29	Closer.

Starting Position Players

Note on position players: because UZR is calculated per-position, players will appear more than once on each table. In effect, it’s like having lots of players, one at each position, on defense, but having them form like Voltron into a single batter for offense. Also, I’ve omitted the pitchers’ offensive numbers from these tables–they were getting too cluttered, anyway. Don’t worry, I’ve factored the pitchers’ offensive contributions, such as they might be, into my final projections, but it would be tiresome to list them here. Also, UZR ignores defense from pitchers & catchers, so you won’t see any UZR numbers by Ramos or Flores.

Player	Position	UZR 2008-2011	wRC 2008-2011 annual average	wRC/PA 2008-2011 annual average	2012 PA (projected)	2012 wRC (projected)
Adam LaRoche	1B	4.30	65.50	0.132658	600	79.59
Danny Espinosa	2B	3.00	22.50	0.116883	600	70.13
	SS	-0.20
Ryan Zimmerman	3B	30.20	83.25	0.151158	600	90.69
Ian Desmond	SS	-13.70	33.25	0.102151	600	61.29
	RF	-0.70
	2B	-2.80
Michael Morse	LF	-6.90	37.75	0.161670	600	97.00
	1B	-3.50
	RF	-7.50
	3B	0.40
Roger Bernadina	CF	-8.40	22.25	0.100112	400	40.04
	RF	-4.10
	LF	6.60
Jayson Werth	RF	17.40	95.25	0.154941	600	92.96
	CF	0.00
	LF	-1.60
Wilson Ramos	C		15.75	0.121857	400	48.74

Bench Players

Player	Position	UZR 2008-2011	wRC 2008-2011 annual average	wRC/PA 2008-2011 annual average	2012 PA (projected)	2012 wRC (projected)
Mark DeRosa	RF	6.10	44.50	0.129927	400	51.97
	LF	2.70
	SS	0.00
	1B	-1.20
	2B	-2.80
	3B	-4.50
Steve Lombardozzi	3B	1.10	0.25	0.031250	350	10.94
	2B	0.10
	SS	-0.90
Jesus Flores	C		13.25	0.101727	300	30.52

Unless something unusual happens in the next couple of days, I don’t see the Nats’ opening-day 25-man roster looking too different from this. How will they do in 2012? Stay tuned for the next part of my 2012 projection series, Top of the Inning: Pitching, Defense, and Runs Allowed.