Player value series, part 7: How should we handle park factors?

Note: I've changed enough about the way I calculate player value for hitters that I probably need to re-write this entire series (click player value below to see the whole set of posts). But I wanted to get this online so I can show my work, so we'll run with it for now and then fix the other articles later.

One of the more unique aspects of baseball is the substantial influence that the ballpark can have on the outcome of (at the least) batted balls. While this an aspect of baseball that many of us enjoy, it also presents a challenge to our ability to assess player value. For example, Brian Giles hit 0.306/0.398/0.456 at PETCO last season, which was good for a 0.376 wOBA. And Brad Hawpe hit 0.283/0.381/0.498 at Coors Field, which gave him a 0.379 wOBA.

They had pretty similar seasons according to those numbers, with Giles being slightly better at getting on base, and Hawpe showing more power. The problem, of course, is that Giles played half of his games in PETCO park, which is a notorious pitcher's park. And Hawpe played half of his games in Colorado, which even post-humidor is the best hitter's park in baseball. Presumably, if you had swapped where the two players were hitting, Giles would have vastly outperformed Hawpe.

How do we reconcile this in our player valuations? The traditional approach has been to use park factors. The best article on the web about park factors is Patriot's, and I won't replicate his work here. But briefly, a park factor can be conceptualized as simply this ratio:

Avg Runs scored per game at a ballpark
------------------------------------------
Avg Runs scored per game at all ballparks

So, if you see a park factor of 1.18, for example, that means that more runs are scored at that ballpark than in a typical ballpark. And a ratio of 0.84 means that fewer runs are scored at the ballpark in question than in a typical ballpark.

A quick and dirty way of calculating park factors is to simply divide a team's total runs scored and allowed at home by its runs scored and allowed in away games. So, in that case, a 1.18 park factor would mean that a team scores ~18% more runs at home than they do on the road.

There are a variety of additional complications if you're going to do it properly, and Patriot discusses them. But to be honest, most of the time, that simple approach will get you most of the way there. Nevertheless, there are three factors to worry about that are important and make a big difference:

1) If you go to apply a home runs/away runs park factor to an individual player's runs stats in order to discount (in Hawpe's case) or boost (in Giles' case) his value rating, it's important to first cut the park factor in half (meaning 1.18 would be 1.09, and 0.84 would be 0.92). This is because the 1.18 park factor described above would be an appropriate adjustment only for games played in the park. Typically, though, players play half of their games in other parks, which, on average, will have a park factor of ~1.0. So, if we split the difference, we'll get a multiplier that makes sense in light of the 81 home/81 away game schedule. Once you have this number, you just divide your player's absolute runs estimate by your park factor (but see #2 and #3 below). Many people (like Patriot and Szymborski) already have done this adjustment to the numbers they post, but be sure to check on this wherever you get your park factors.

2) Park factors are variable as all heck from year to year. Patriot posts 5-year averaged, regressed park factors, which in my view are the most reliable park factors on the 'net. The reason is that by both averaging and regressing, he's accounting for the fact that any park factor estimate has large error bars around it, and the true park factor is probably a bit closer to league average than even your 5-season average indicates.

3) As pointed out by Tango and others, there may be problems with simply dividing Hawpe's absolute batted runs number by 1.09. The issue is that this adjustment will have a more significant impact on good hitters than poor hitters. A park factor of 1.10 would strip 10 runs from a 100-run hitter's totals, but only 3 runs from a 30-run hitter's totals...and yet there's no evidence indicating that the good hitters' value should be discounted at a greater rate than a poor hitter's value.

A solution to this problem--and, at the same time, a convenient way to apply park factors directly to RAA or RAR data (ratios can only be applied to absolute runs data)--is to convert our traditional ratio-based park factors to an additive park factor. Once we do this, we just add or subtract a certain small fraction of runs per PA to each hitter. It's an extremely easy and straightforward way to handle park factors, and yet is something that I rarely see done.

So, here are conversions of Patriot's 2008 5-year regressed park factor ratios into additive park factors. I show them per PA and per 700 PA's (a season's worth) to help us understand how large of an effect we're working with here. (Methods: I took the total MLB runs in 2008, divided a given the park factor, and took the difference in runs between the adjusted and unadjusted runs. I then divided this difference by total 2008 MLB PA's to get the per-PA adjustments)

Year	TEAM	PF	Runs/PA Adj	R/700 PA Adj
2008	ARI	1.05	-0.0060	-4.2
2008	ATL	1	0.0000	0.0
2008	BAL	1.01	-0.0012	-0.8
2008	BOS	1.04	-0.0048	-3.4
2008	CHA	1.04	-0.0048	-3.4
2008	CHN	1.04	-0.0048	-3.4
2008	CIN	1.02	-0.0024	-1.7
2008	CLE	1	0.0000	0.0
2008	COL	1.09	-0.0108	-7.6
2008	DET	1	0.0000	0.0
2008	FLA	0.98	0.0024	1.7
2008	HOU	0.99	0.0012	0.8
2008	KCR	1	0.0000	0.0
2008	LA	0.98	0.0024	1.7
2008	LAA	0.99	0.0012	0.8
2008	MIL	1	0.0000	0.0
2008	MIN	1	0.0000	0.0
2008	NYY	1	0.0000	0.0
2008	NYM	0.97	0.0036	2.5
2008	OAK	0.98	0.0024	1.7
2008	PHI	1.02	-0.0024	-1.7
2008	PIT	0.98	0.0024	1.7
2008	SD	0.92	0.0096	6.7
2008	SEA	0.97	0.0036	2.5
2008	SF	1.01	-0.0012	-0.8
2008	STL	0.98	0.0024	1.7
2008	TB	0.99	0.0012	0.8
2008	TEX	1.03	-0.0036	-2.5
2008	TOR	1.02	-0.0024	-1.7
2008	WAS	1.01	-0.0012	-0.8

Essentially, for each "unit" of a park factor, you add or subtract 0.0012 runs per PA, which works out to be ~0.8 runs per season. This results in a park-induced range of ~15 runs per season between the best hitter's park (Coors) and the best pitcher's park (PETCO).

Put another way, if you took a true 30 RAR hitter and played him on the Rockies Colorado, you'd expect him to produce ~38 RAR (raw, without park adjustments). That same hitter would be expected to produce ~23 RAR in San Diego. So by subtracting 8 runs/season from your Colorado hitter, or adding 7 runs to your San Diego hitter, you can properly estimate the player's true hitting performance (~30 runs above replacement).

Isn't that easy?

The same approach could potentially be used on pitchers, but we unfortunately don't tend to use per-PA data to evaluate pitchers. For now, I'm still just using ratio park factors on pitchers, but I'll likely switch to a new approach in the near future once I incorporate some other changes to how I do their player valuations (probably involving pythagorean-based win estimates for pitchers, like Tango does). More on that at a later date.

Thanks to folks in this thread at Baseball Fever for helping me to finally figure some of this stuff out. Assuming, of course, I really have figured this stuff out...

Twittering

So I'm going to jump on the Twitter bandwagon and see where it goes. Should be a nice way to make occasional updates around here without much of a time investment. We'll see. I've been pretty reluctant to start on this, but then I didn't think I'd like facebook either.

FWIW, my first two tweets were exactly 140 characters long. :)

As far as my inactivity recently, two things have happened. One, my dad and sister visited last weekend, which "interfered" with my friday night links. And two, it's exam season, which means there's one last big push before I have the summer to myself. Last final is given on Saturday, with grades due Wednesday. I'm pretty excited to have this first year in the bag!

Update: As Matty G so astutely pointed out, it would help if I provided my handle: jinazreds

Also, you can see all of my recent tweets in the upper-left corner of this blog's sidebar. :)

Friday Night Fungoes: Larkin, run estimators, CHONE, and the Dunning-Kruger Effect

Looks like I'm going to the Curve game tomorrow night. Whether I'll post a report may depend on how they do...they've yet to win this year! Weather should be nice, though: 72 degrees & sunny.

Does Larkin Belong in the Hall of Fame? Revisited

I can't remember if I linked to this or not, but even if I have it's worth linking again: Rally has posted season-by-season WAR estimates for all players in the Retrosheet era. He also has a top-300 ranking, so we can look at the best of the past 50+ years using these numbers.

Rally's data include offense, defense (including turning double plays, etc), baserunning, and era-specific position adjustments. This is similar to what I tried to do in my piece on Larkin, but better because of the baserunning & especially the era-specific position adjustments. Here is how the shortstops I included in my Larkin study pan out in Rally's WAR data, plus a number of others who came up in discussions following my Larkin piece:

	MyWAR	RallyWAR
Alex Rodriguez	82.4	96.5
Cal Ripken+	73.8	91.2
Robin Yount+	62.1	75.9
Barry Larkin	57.6	70.1
Ozzie Smith+	45.3	67.6
Alan Trammell	53.7	66.8
Derek Jeter	49.5	62.4
Ernie Banks+*	54.8	59.2
Luis Aparicio+	30.9	50.5
Toby Harrah		47.1
Omar Vizquel	28.0	45.2
Bert Campaneris		44.5
Normar Garciaparra		43.7
Tony Fernandez		43
Miguel Tejada	39.2	40.9
Jay Bell		35.5
Davey Concepcion	26.0	34
Mark Belanger	26.2	32
Edgar Renteria		31.9
Chris Speier		24.8
Bill Russell		24.4
Rick Burleson		21.3
Freddie Patek		20.4
Steve Sax		19.8
Larry Bowa		18.9
Bucky Dent		12.4
Don Kessinger		7.2
Tim Foli		3.5

Some players got a big boost in their rating, like Ozzie and Aparicio, once you include baserunning (I only included SB's & CS's) and double play turning. But as you can see, the results are more or less the same as far as Larkin is concerned: probably the 4th best overall, and 2nd-best pure shortstop in the Retrosheet ERA, at least based on total contributions to their ballclubs relative to their league.

Career-level WAR accumulation isn't the be-all, end-all of hall of fame voting, as peak performance is also important. But in Larkin's case, career WAR is crucial. No one disputes that he was brilliant player when healthy. The knock on him is that he didn't play enough due to all of his injuries. These data clearly indicate that his total contribution, including playing time, was among the best in baseball history at his position.

Rally has Larkin as the 30th-best position player of the Retrosheet era. I know he almost certainly will not be a first-ballot Hall of Famer, but he probably should be.


Why I'm trying to stop using OPS

Colin followed up his study posted last week on run estimators with an improved method. This time, instead of looking at half-inning or even game-level combinations of team offense, he instead focused on identifying the average value of particular offensive events to games. His methodology was to take matched games--games that had the same numbers of major counting events, but that differed in how many of one specific event they contained.

For example, he might have a game with 5 singles, 3 doubles, 1 homer, and 3 walks, and he'd compare that to a game with 5 singles, 3 doubles, 1 homer, and 4 walks. Finding the average difference in runs scored between pairs of games like this would tell you the average value of a walk in runs. He then compared those actual differences in runs scored to the expect difference in runs scored according to a variety of run estimation mechanisms.

The results? Linear weights-based methods did the best. This includes his "house" linear weights (which he kindly shares), as well as manipulations of linear weights like wOBA. A bit behind them were GPA (aka 1.7 OPS), Base Runs and BPro's EqR, followed a bit more distantly by Bill James' Runs Created. The worst of the bunch were the OPS-based methods, as well as the even-more-horrible Total Average (bases/outs).

This is strong evidence that we should more or less stop using OPS to evaluate hitters. It's unnecessary, given how easy wOBA is to calculate. Is it better than batting average? Sure, of course. But it misses badly enough and often enough that we should really move past it. It's a tough habit to break, but it's time to wOBA, folks.


CHONE is a really good projection system

Matt has a fairly exhaustive projection roundup here. He notes that each system seems to have its own strengths, but often also some weaknesses:

--CHONE was the best at projecting most things.

--PECOTA was very close behind but had some systematic biases, specifically for speedy players' BABIPs, which ZIPS struggled with as well.

--ZIPS is behind the other systems, except it does quite well with projecting the three true outcomes for players over 35.

--CHONE does better with older players in general, since its specialty is aging curves, but PECOTA does better at finding comparable players for younger players for whom less data is available (unless they fall into the speedster category).

--OLIVER clearly contends and even takes the lead at some things--especially at projecting hitters with lower homerun totals and other players significantly affected by park effects. However, OLIVER under-projects walks and strikeouts systematically and over-projects homeruns systematically, and could probably be improved by adjusting how those outcomes are computed.

The nice thing about this is that we can use this information to give more or less weight to a given projection system when it differs from others in predicting a given player's performance based on the sort of player we're looking at. Or, we can do what I've essentially decided to do around here, which is to just use CHONE. :)

It's worth noting that Matt's is just the latest projection roundup in which CHONE did particularly well. Whether it will continue to do so in the future is an open question, of course, but the data suggest that it's as good as they come.


The Dunning-Kruger effect

JC posted about this terrific psychological concept: that people incompetent in a particular discipline will massively overestimate their competency in that discipline. That's pretty much the definition of a baseball fan, isn't it? :)

I'm jesting, mostly. You certainly see arguments between baseball fans who really know their stuff and baseball fans who just think they know their stuff. And I tend to think that most of what you hear on talk radio (sports, or otherwise) involves people who fall into the latter category rather than the former category. And, of course, I tend to think that on at least some issues (some areas of biology, some areas of baseball research, etc), I fall into the reasonably competent category.

But the great part of this is that the Dunning-Kruger effect predicts that we'll have a very hard time being able to tell whether we're competent or not...because the more incompetent we are, the less we'll realize it! :)

Reds acquire Drew Sutton

Today the Reds announced the acquisition of Drew Sutton from the Houston Astros in return for Jeff Keppinger, who was dealt at the beginning of the month.

My thoughts: he repeated AA last season and had a dynamite year as a 25-year old (which is a bit old for that league, at least as far as prospects go). Seems to have a little bit of pop, though my feeling is that it's more likely to be doubles power in the majors than the 20-homer power he showed in AA. He hit over 0.300 last season, but more routinely has been a 0.260-0.270 guy...but he does take walks. The last three years he's walked in over 10% of his plate appearances.

Defensively, TotalZone has him somewhere around average 2B & 3B cutting across years, which would mean he's probably a slightly above average fielder overall compared to other AA'ers. And this makes him roughly an average big league infielder, as the quality of MLB infield defense is better than it is in AA.

Is Sutton better than Keppinger? I dunno. He's a few years younger, but was probably the Astros #8 prospect more by default than anything else--their minor league system is awful right now. Unless he can translate his AA success (and 0.361 BABIP) to AAA, I won't feel very confident that he can be as valuble offensively as Keppinger can be. But he might make that up with his decent defense compared to Keppinger's increasingly below average fielding. We'll see.

Sutton apparently does require a 40-man roster spot, as the Reds were forced to outright Danny Richar, who I imagine might not make it through waivers. Richar was reasonably hyped when acquired in the Griffey trade, so I'm surprised to see him go so soon. Hopefully he'll pass through waivers so we can keep him, as he had pretty decent projections this season.

Sutton can write a decent blog post--this is from the AFL last November.

Another reason to scrap the DH

I'm pretty sure this means I'm a bad person, but I'm very uncomfortable with this idea.

The York Revolution have decided to find out by bringing in a former member of the Tampa Rays organization, 3'2 Dave Flood as a pinch-hitting specialist. ... "If I were seven feet tall I'd be putting a basketball through a hoop," said Flood. "I should be able to take advantage of my height to draw a walk. Sometimes this might be leading off a game, sometimes it could be as a pinch hitter with the bases loaded in the bottom of the 9th."

It's probably mostly just a publicity stunt by an indepedent-league team. But the thing is, I can't work out any reason to be directly opposed to this idea that isn't blatantly prejudicial. The only thing I can say is that I think that anyone who plays on offense should have to play defense as well, and vice versa. The only exception in my mind should be pinch hitting or pinch running, where you've chosen to remove a player from a game rather than allowing their weakness to be exposed.

Even then, however, I can't justify a reason to prevent teams from using one of their roster spots for someone who can only pinch hit, and will require a pinch runner if s/he gets on...which they will probably do at least 50% of the time (0.500+ OBP). It'll be interesting to watch this.

Update: Additional discussion at Tango's blog.

Friday Night Links

(I've gotten out of the habit of doing these, but they were fun to do last season and I'm going to try to get back into doing them this season. Otherwise, links just pile up in bloglines and never get shared...)


Will 2009 show an offensive spike?

Early word from hittracker that we might be seeing something interesting this year. My feeling is that this is probably just noise (no matter what the 2-sample t-test says), but you never know.

Update: more on this at Tango's site.


Is baseball's franchise value bubble about to burst?

I didn't see much discussion of this, but I thought Craig's post (and especially his excerpt from Ethan Stock's post) on this was pretty interesting...and something that could be a real problem for a small market franchise like the Reds.

If a team isn't worth as much as it was before, it might not be willing to take on the kinds of liabilities (i.e. player contracts) that it had before for fear of reducing the potential sale value of their franchise. At least, I think that's right (everything I know about economics I learned from Planet Money).


Q&A With Jeff Luhnow at BtB

Really excellent interview with the Cardinals' VP of Amateur Scouting and Player Development at BtB. Here's a good excerpt:

How would you compare advanced insider sabermetrics to public sabermetrics?

Great question. First of all, I am constantly impressed with the quality of the publicly available research on the game of baseball. It is clear that there are numerous very talented and smart people who study the game and develop amazing and true insights. MGL and Tango’s book is a great example of this, as is the work shared and discussed on their website. I’ve had a chance to talk to and work with both of them and they are first rate baseball thinkers. To me, these two and many more like them are an important part of our industry… both in terms of helping shape the game in some ways as well as generating public interest in the analytical part of the game.

As a baseball club, we read much, if not most, of the thoughtful research done on the topics that matter to us. When we know the people and the quality of the work, we consider the findings useful and may even act on them. However, since we don’t control the work and can’t do the quality checks to make sure the data was clean, the methods were up to our standards, etc, it becomes more difficult to act on the conclusions. That drives us to develop our own capabilities, which we have done for the past six years, since fall of 2003 when I arrived at the Cardinals.

Beyond the Boxscore has really improved over the past six months and has become a place I visit daily (at least on days I have time to visit baseball sites). Hopefully it's talent won't get poached as quickly as it did over at StatSpeak, though that is already starting to happen...

How important is fielding?

Two links on this one.

First, Tom Tango came up with a neat way of looking at the value of outstanding fielders that gets away from all these fuzzy math that tries to figure out whether a player should have gotten to a ball:

I selected the best twenty or so infielders (2B, SS, 3B) since 1993. It’s mostly the names you know: Everett, Sanchez, Bartlett, Rolen, Reese, Hudson, Inge, etc.
.....When the star fielders were on the field, their team allowed 4.60 runs per game, and when they weren’t on the field, they allowed 4.83 runs per game. Per 162 games, this difference comes out to 37 runs.....I repeated this exercise with the outfielders: Erstad, Beltran, Cameron, Endy Chavez, etc. Their teams allowed 4.89 runs with them, and 5.00 without them, for a difference of 19 runs per 162 game season......And I did the same for firstbasemen: Minky, Derrick Lee, Tex, etc. They allowed 4.89 runs with these great fielding 1B, and 4.99 without, for a difference of 15 runs......Roughly speaking, that gives us 26 runs (3 parts 37, 3 parts 19, 1 part 15) of fewer runs scored when you have one great fielder on the field, than when you don’t.

So, that's saying that your top-notch defenders give you 25 extra runs a season saved vs. bench. Now, a star offensive player may provide you with 50 or more runs over a bench player with his bat, or more (Pujols was ~75-80 runs over bench last year on offense alone). So fielding isn't as important as offense. But it's important. 20 runs is the difference between a replacement player and an average player in the National League, so fielding can change your evaluation of a player from being a 25th man to being a decent starter (remember Adam Everett?). Or, it can cut your star offensive player's value in half (remember Adam Dunn?).

To that end, John Dewan posted this shortly afterwards, claiming it was "the most significant discovery" of his career:

The worst defensive team in baseball in 2008? The Kansas City Royals. Their defense cost them about 48 runs relative to the average team. Comparing the Phillies and the Royals, the difference between the best and worst defensive teams in baseball was about 130 runs.

Now, remember that number. 130.

The best run-scoring team in baseball was the Texas Rangers with 901 runs in 2008. The San Diego Padres were the worst with 637 runs. That's a difference of about 260 runs.

Here's the discovery, and I found it because the numbers just jumped out. The 130 difference in runs saved on defense is exactly half of the 260 difference in runs scored. That's exactly half. The implication is that defense is worth about half as much as offense.

(John should have said fielding instead of defense, because defense includes pitching.)

Anyway, I think we can reasonably disagree (and we have) that this was a new discovery. It was new to John because he just got around to finally converting his plus/minus stat into a runs-based statistic for his new book. But I don't think it's really new, as we've been talking about how important fielding is to teams and players in a quantitative way for years now. MGL has been posting UZR since at least 2003, for example, and I still consider UZR to be superior to Dewan's plus/minus stat.

That said, Dewan's post was a nice way of presenting the importance of fielding, and it's something that has seemed to resonate with people.

What should we use to estimate player or team offense?

Colin has the first of a two(?)-part series comparing run estimators. It's similar to what I did here, but with two improvements. First, he does more tuning (somehow) to give each estimator a slightly better chance at performing well within each season.

Second, and most importantly, rather than looking at team season totals, he instead uses the statistics to compare offense on a half-inning basis. In other words, for each 3-out sequence of play, which estimator is the best at predicting how well teams perform? This lets him compare run estimators across a huge range of run scoring environments, everywhere from 0 runs (which would be the most common in his dataset) to 10 or more runs in a half inning. In my study, I effectively compared across 3.5-5.5 runs per game, which works out to a range of just 0.4 to 0.6 runs per half-inning. Colin's way is much better because it considers a much larger range of situations.

The results? Base runs wins, though whether you think by a lot or by only a little might be open for interpretation.

It's worth noting that one of the basic reasons that Bill James's RC doesn't do as well here as BsR does (and wouldn't no matter what form of RC is used) is that it won't correctly predict a 1-run inning with a solo homer because home runs aren't given special consideration in RC. Base Runs will predict such an inning perfectly.

The best part is that Colin isn't done yet. As others point out, there are still problems trying to generalize his results to rating individual performances, which is what most of us like to do with these stats. Colin's next effort looks even more promising--looking at matched sets of games that are identical in all counting stats but one. I'm not sure how he's going to pull it all together, but it should be at least an interesting contrast to today's article.

Nick Adenhart

I don't know what to say about this except that it's just awful. It'd be like losing Johnny Cueto the night of his first start last season. A guy who worked his whole life to get where he was, and was just starting to show his promise, and now he's gone. My deepest sympathies to his friends and family. The link at the beginning of this paragraph is everyone's favorite Angels fan, Rally's, take on this. And here is a bit more of a personal story about Nick.


John Brattain

Same as above, except that instead of a young player we have a fellow fan and writer who has left us. I don't earn much in the way of money from running this site, but I had a little bit of cash left over in a Paypal account from a sponsorship I received a few years ago and sent a small donation to THT's collection pot to help John's family. If you can, I encourage you to do the same.


Teaching Baseball

While this will only directly interest you if you happen attend my university (and no, I'm not out of the closet about my baseball life yet, so I'm not ready to share where this is), I have preliminary approval to teach a 2-credit freshman general education seminar on baseball next spring. The goal of these courses is to emphasize interdisciplinary subjects, reading, critical thinking, quantitative reasoning, and also serve as a student retention device. Here's the proposed course description:

Perhaps no other sport relies as much on tradition, hearsay, and loud opinion as baseball. But what is gained (or lost) when these claims are examined using a scientific approach? Can a player really watch the ball hit the bat? Do clutch hitters exist? Do steroids really help performance, and if not (or even if so) should they be banned? Why does a scrub MLB player earn 10x more money than a teacher? We will discuss these and other questions while considering studies from literature from exercise physiology, psychology, economics, and “sabermetrics.”

I hope it goes through all remaining channels, because it's going to be awesome. Reading list currently includes the Psychology of Baseball for sure, and may include JC Bradbury's new book if it's out by then or possibly Vince Gennaro's book. I will probably also supplement with readings from THT Annuals, or web-published studies. And I might even assign The Book.

Hopefully I can convince enough students to geek it out with me to make this class really work. :)


Mulling the future of this site.

The end of the semester is approaching! And while that will be coincident with the arrival of a new baby in our house (i.e. a time & energy suck), it also means that my first year of 12-credit/semester teaching will be over. I will always be busy with this job, but given that I won't likely have semesters with three+ new classes again, the days of spending 3+ hours every night preparing lectures will at least largely be over.

What this means is that I may have a bit more time going forward to toy around on the blog. And one of the things I'm considering doing (among many), since I live only a few miles from the Altoona Curve's home ballpark, is to start doing a little bit of work on the minor leagues. Player valuation, fielding, league comparisons, stuff like that. Some of this would probably include work on the Reds' minors, but it would also include work involving the Curve team as a way of following my local team.

So, I'm thinking about making some changes around here. One possibility that I'm strongly considering would be to make this more of a two-team blog, with content about both Reds and Pirates. Or even just moving away from an explicit focus on Reds altogether (though I'll always have a lot on them, as they'll always be my team). I am concerned that this change in focus might hurt readership, though, so another possibility would be to just start up a new blog to focus on issues related to the Curve and, by extension, the Pirates organization. Feedback is welcome...though part of the decision making process might depend on whether I can get a bitchin' domain name that I want. :)

Man, I looooove winning! Like, it's better than losing!

First win of the year. Votto's kind of a stud, isn't he? I probably need to get more on board with him than I have been around here.

Reds lose a low-scoring game at GABP

The start of a theme for this season? Hopefully we'll win as many as we lose.

13 walks in one game? Must have been freaking cold out there.

Thoughts on the opening day roster

--Opening Day roster:

Outfielders:Jay Bruce, Chris Dickerson, Willy Taveras, Layne Nix, Jerry Hairston Jr., Darnell McDonald

Infielders:Joey Votto, Brandon Phillips, Alex Gonzalez, Edwin Encarnacion, Paul Janish.

Catchers:Ramon Hernandez, Ryan Hanigan

Starting pitchers:Aaron Harang, Edinson Volquez, Micah Owings, Johnny Cueto and Bronson Arroyo

Relievers:Francisco Cordero, David Weathers, Jared Burton, Mike Lincoln, Arthur Rhodes, Daniel Ray Herrera and Nick Masset

Some thoughts:

* The biggie, of course, is Darnell McDonald making the team and starting on opening day. I understand the need for defense if Taveras is ill, but I also tend to think that Dickerson could play there competently in a pinch. I'd rather take a platoon-disadvantaged Dickerson over a platoon-advantaged McDonald, even against Santana. But whatever, it's just a start and there's no reason to think that he'll be around all season in any kind of significant role. Right?

The consequence of this, however, is that Gomes didn't make the team and may not agree to an assignment in Louisville. Yes, his terrible defense curtails his value, but Gomes might a better hitter than Bruce at this point in their respective careers. That sort of bat off the bench, or in a platoon in left, could be awfully valuable to a team that may struggle to put up runs. I hope he does take the assignment to AAA, because I'm sure he will get a chance to play this season.

* Bailey didn't make the rotation, and was sent to Louisville rather than risk losing Nick Masset to waivers. I have to say, while I understand the move on some level, I think this sends a terrible message to Bailey. The kid clearly did everything he possibly could do, drew raves from everyone who saw him, including claims that he'd made more progress in the offseason than he had in the past two years. So what do they do? The same thing you would have done if he'd screwed off all offseason and had gotten lit up in spring training. Part of me hopes that Arroyo is, in fact, going to have to go on the DL, just so Bailey can get back to Cincinnati as soon as possible. It's time for the guy to be on this roster, period. Keeping him down so that the Reds can keep the 7th man in the bullpen under their control leaves a bad taste in my mouth.

* The only other move that looks mildly controversial is Bray being sent to Louisville in favor of Daniel Herrera. But if Bray really has lost 5 mph off his fastball velocity as Baker suggested a week or so ago, then I can't disagree with this. Hopefully it's just a matter of building up arm strength. Because with all due respect to Arthur Rhodes, this team needs a healthy Bill Bray in its pen.

* I have no problem with Janish over Rosales, especially given Alex Gonzalez being the question mark that he still is.

* What, just two catchers? Is that legal?

Update: Here's something I wrote in response to Chad's link to me and the subsequent comments at redlegnation. It basically amounts to a rant, but here it is anyway:

@Chad, I probably stole the 3-catcher comment from your and Bill's podcasts, which I've started listening to now and then on my ipod during my commute. :)

@Nathan (and in general), I'm sure they did have a good conversation with Bailey about this. But we're dealing with a guy who is FINALLY getting where we want him to be from a maturity standpoint. And my feeling is that this is a stupid thing to do to a guy who you're trying to encourage.

If I were Homer, no matter what was said in that conversation, I'd be at the very least disappointed and at worst really pissed off. Opening day roster spots are definitely overrated, and I have no doubt we'll see a lot of him this year. But I think it's the wrong way to handle him. It probably won't make much difference in the long term...but I still don't like it.

As for Masset's experience and the peculiarities of a bullpen gig...what I'll say is that this team won't make or not make the playoffs based on whether they have an experienced long reliever in the bullpen. Masset just doesn't matter very much. What could matter, however, is keeping an encouraged, hard-working Homer Bailey on the staff and exposed to big league hitters every outing early in the season. I mean, seriously, what good is going to come from him pitching effectively in AAA?

I don't frankly care if my long man can only pitch twice a week--you shouldn't need him more often than that with as many pitchers as a modern team carries. As Baker himself said, there are a lot of top-flight starters that made their debut as a long man in the bullpen and spot starter before securing a full time starter job. It's a good way to break in.

Or heck, another choice is to option Herrera and keep both Masset and Bailey. We already have Rhodes for LOOGY duties. Some successful teams don't carry even a single left-hander in the 'pen.
-j

Baby Sheldon

Congrats to beat writer Mark Sheldon on his new child!

first things first -- Congrats are in order to the usual author of this blog and his family. Mark Sheldon and his wife's clan got bigger by one baby boy this morning. Everyone is healthy and happy. So Mazel Tov to the Sheldons and all their family.

Have to say, though...I know you can't always plan these things, but the timing kind of stinks given that the season is just beginning and road trips are on their way.

Then again, thinking as a father of one young child and someone expecting his second in about 6 weeks, maybe that was all part of Mark's plan!

"What? Make another bottle? Change another diaper? Hold the screaming baby? Sorry, babe, I gotta go!"

Keppinger traded for PTBNL

Per John Fay.

What does this do to the team? To try to figure this out, I again used CHONE projections and my playing time allocations from the 5 questions study.

Keppinger previously received 294 PA's with a strong offensive projection. I was already allocating playing time to Rosales, Richar, and Janish, so I had a hard time figuring out who to replace Keppinger with on my roster (Valaika? Gil came to mind, but he's apparently a pitcher now). So instead of moving up a new player, I increased Jerry Hairston's PA's to the maximum allowed by his CHONE projection (about a 90-PA boost, assuming he'd play more shortstop now), and then split the rest of Kepp's PA's evenly between Rosales, Richar, and Janish.

What was the effect of this? Overall team offense projections declined to from 25 runs above average to 20 runs above average. And overall team fielding projections improved from 9 runs below average to 7 runs below average. So, the net effect of this move on the team is probably negligible, and certainly within the margin of error in my estimates here.

I'll be sorry to see Keppinger go, as he was a nice player to have on the roster. Good contact hitter, good plate discipline, and with a history that includes good gap power. Apparently, though, the Reds weren't convinced he'd rebound this year. Maybe there's scouting to back that up. He definitely is a player that needs to hit to have much value.