BDD: Baer: Statistics Are Not Like Bikinis

Does this mean I have to chuck my Jaime Lynn Fox/Paige Hopewell DVD?

I say all of this, of course, in regard to the article that Brian (Joseph) wrote yesterday about Sabermetrics. Some of the criticism was valid, but he didn’t identify the correct target, which should have been us, the fallible humans. His criticisms (such as Sabermetrics being subjectively objective) didn’t put any chinks the armor of Sabermetrics because Sabermetrics — essentially one of baseball’s sciences — is adaptable. If there’s a problem with an aspect of Sabermetrics, go ahead and change it.

Additionally, Sabermetrics — contrary to the claims of many who don’t trust it — is not adhered to religiously. Just because PECOTA says Matt Wieters is going to smoke some American League pitching doesn’t mean that he is, in fact, going to smoke some American League pitching. We can choose to accept what various analyses say, or we can reject them. Just because one prefers DIPS to ERA doesn’t mean one is bound to the conclusions reached via DIPS and cannot utilize ERA in analysis.

I don’t write this as a jab back at Brian, what with me being someone who utilizes Sabermetrics. I welcome and enjoy reading well-written, well-researched criticisms of the sciences because it can only help us improve. It is important, though, to identify who or what is really at fault, and in the case of Brian’s criticisms, it’s the people using the science and not the actual science itself.

BDD: Butterflies & Dr. Statlove (or How They Learned to Stop Watching Baseball and Love the Numbers)

or...Two Hours to of DOOM?

Sometimes I think there are baseball fans of the sabermetric sort that would rather watch FanGraphs’ Live Scoreboard than actually watch a game of baseball. This isn’t a knock on how people choose to enjoy the National Pastime, just an observation. Heck, having seen Adam Eaton pitch more times than I care to remember, there have been times I wish I wasn’t actually watching the game.

Those who love the numbers of the game are often refer to sabermetrics and almost treat as a way of life when discussing how they choose to enjoy the game. Wikipedia defines sabermetrics as the analysis of baseball through objective evidence, especially baseball statistics. While this is a simplified definition, I always found the definition ironic. The notion that sabermetrics is truly objective is silly when there are a number of ways to “objectively” look at a situation statistically depending on your subjectiveness toward the game. Take player value, for example. Some prefer VORP, others look at WAR and others consider Win Shares. Each serves a purpose and each way to evaluate players has its following and detractors. So, it is truly not objective.

...I know, I know. I’m hard on those who love sabermetrics. My guess is while I love the numbers of the game, I will never be truly accepted in the sabermetric fraternity. But, at the end of the day, you can’t understand baseball just by looking at the numbers. The statistics of the game are too malleable to make an iron-clad complex argument without someone else manipulating the numbers slightly to fit their hypothesis. And no matter how snarky you are in your commentary or how sure you are in your conclusion, there’s another way to look at it.

It’s chaos theory, at it’s best. Too bad it sometimes brings out the worst.

SNY: Salfino: What about Wang in the bullpen?

It seems ProSolution Gel works for every sabermetrician!

The other half of the equation here is putting Wang in as a starter. I first looked at this question back in 2007. Unbeknownst to me at the time, Dan Szymborski at BaseballThinkFactory.com had a formula of his own. And since then, Tom Tango on his Web site and Harry Pavlidis at the TheHardballTimes.com have looked at the question, too. They have done it from the perspective of converting a reliever (Joakim Soria) into a starter. We all agree that the same pitcher is most likely to pitch significantly better as a reliever than as a starter. The question is how much better?

Tango and Pavlidis deal mostly with Wins Above Replacement, not simple enough for our purposes. I want to convert the stats that we all understand.

My Wang conversion (based on how he’s pitched as a starter for his career) is a 2.89 ERA, 5.71 K/9, and 1.08 WHIP (baserunners per inning). Of course, he’d still be an extreme groundball pitcher. (Note: my conversion formula is based on how a sampling of modern starters turned relievers actually performed through 2006.)

Szymborski says Wang as a reliever would have a 3.09 ERA with 5.4 strikeouts per nine innings and a 1.21 WHIP.

BPro: Prospectus Idol

And it’s no slam dunkle, man!

It is our privilege to present the slate of competitors in the first-ever edition of Prospectus Idol. The objective of this competition is to find a new Baseball Prospectus columnist, but it is also an exercise in learning, from the authors for the benefit of the audience (ideally), as well as by the authors and judges from one another. As Kevin Goldstein initially laid out in his introducing the competition and explaining the basic rules for entry, this also represents a potential gateway to work within the baseball industry itself, given the increasing number of former contributors who have already landed jobs with the various clubs.

Brian Cartwright
Jeff Euston
Ken Funck
Brittany Ghiroli
Jeremy Greenhouse
Tyler Hissey
Matthew Knight
Tim Kniker
Byron Lescroart
Brian Oakchunas
Matt Swartz

WSJ: Bialik: Putting Ibanez’s Hot Start Into Perspective

Anyone catch Ibanez’s laughable dive attempt today?

In his last three seasons with the Mariners, the 36-year-old Ibanez was remarkably consistent as a hitter. Suddenly this year he’s on pace for career highs in home runs, runs scored, runs batted in, slugging percentage and on-base percentage. And he’s gone from a below-average fielder to the best leftfielder in baseball, according to an advanced measure called ultimate zone rating. Overall, he’s one of just seven players in baseball to have been worth two wins or more for their teams.

But Bill Baer was a skeptic of the signing before the season, and he’s not going to let a month and a half change his mind. “We need to wait for a decent sample size before we can draw any legitimate conclusions,” Baer writes on Baseball Daily Digest.

How much should we revise our prior opinion of a player based on a particularly strong or weak start? FanGraphs has attempted to quantify that by providing in-season updates to preseason projections of player stats. The ZiPS projection system expects Ibanez to finish with an on-base percentage of .363 and a slugging percentage of .533 — closer to his recent Mariners history than to his hot start this season.

Fangraphs: Anderson: Willie’s Blooming Power

or...A diatribe called Bloomquist.

Last season, in 192 plate appearances Willie Bloomquist recorded 46 hits, 45 of which were singles. That’s good for a batting line of .279/.377/.285, or an ISO of 0.006, one of the lowest in major league history. Naturally, Bloomquist has followed his powerless exhibition with 70 plate appearances and a .509 slugging percentage this season.

Ignore the .408 BABIP, the fact that Bloomuqist only has four extra base hits, and that his HR/FB% is well above career norms, and just focus on the sample sizes at play. Which is more likely to tell us of Willie Bloomquist’s true talent level:

A) ~70 plate appearances with a .500+ slugging
B) ~1,400 plate appearances with a .324 slugging

...Even if you park adjust and somehow attempt and objectively credit his improved power to coaching and an improved atmosphere, you still won’t be able to add nearly 0.200 points of slugging – and if you did, you probably did it wrong. At the end of the day this is still Willie Bloomquist. The hot start is certainly going to help his end of season numbers, but the reason ZiPS projects Bloomquist to finish with a .385 slugging is not because it hates him, but because there’s an entire body of evidence suggesting against Bloomquist’s new found power stroke.

FanGraphs: In Season ZiPS Projections

In case anyone missed it…

Daily updated in season projections of the ZiPS variety are now available in all the player pages!

There are two lines, the RoS line which is what a player is projected to do in only the remaining part of the season and then the Total line which is what a player’s total season stats are projected to be at the end of the season.

All the credit goes to Dan Szymborski of Baseball Think Factory for letting me implement his projection system! And a hat-tip to Dave Cameron for pointing me in the direction of his in-season projection tool! If you want to mess around with in season projections yourself, you should download his spreadsheet here: 2009 ZiPS In-Season Projection Tool

RotoGraphs: Joura: Projecting Kevin Youkilis’ Average

Youk, will never be average!

I think we may have reached that point with Youkilis and his average.

I took all of the players in 2008 who qualified for the batting title and who batted plus or minus five points from the .286 average that CHONE predicted. I came up with a group of 26 players. Then I took all of the players from this group and counted how many hits they had through 75 at-bats last season.

Our 26 players ranged from 16 to 27 hits in their first 75 at-bats last season. It is not a perfect bell curve but the right side of it does display a standard downward-sloping tail as you can see by the crude chart below:

        x
	x				x
	x				x		x
	x	x	x	x	x	x	x	x
x	x	x	x	x	x	x	x	x	x	x	x
16	17	18	19	20	21	22	23	24	25	26	27

I came up with an average of 20.7 hits and a standard deviation of 3.1 for this group. So, two standard deviations gives us a high and low of 15 and 27 hits. So, for this definition of a .286 hitter, 95 percent of the time he should have between 15 and 27 hits in 75 ABs.

Youkilis ended play last night with 74 at-bats and 30 hits, meaning he falls outside of our 95 percent range. Our most likely conclusion is that he is a better hitter than the CHONE projection prior to the start of the season.

This is just a first step and I have no projection on what Youkilis will end up hitting in 2009. ZiPS projected Youkilis to bat .288 this season. Dan Szymborski just came out with an update to ZiPS based on 2009 stats. He now projects Youkilis to bat .298 for the rest of the season and finish with a .313 average.

Sickels: Not a Rookie: Pablo Sandoval

“Bring your own lampshade, somewhere there’s a party”

As you know, Sandoval had a remarkable ‘08 season, hitting .359/.412/.597 in 68 games for San Jose, then .337/.364/.549 in 44 games for Double-A Connecticut, followed by a .345/.357/.490 mark in 41 games for the Giants, just edging past the rookie eligibility limit. The defense issue is still kind of strange; he’ll likely end up fantasy-qualifying at third base, first base, and catcher this year. Is the bat for real? Although I don’t think he’s going to hit .345 over a full season, yes I think his bat is legitimate. He will never be a walk machine, but he seems like a .real 280-.300 hitter to me. He’s one of those players who makes “hard contact” even on pitches most hitters shouldn’t swing at. Such hitters can win batting titles when things go well, and Sandoval does have that kind of potential. He really snuck up on both statheads and scouts last year.

PECOTA comps are all over the map and show how odd of a player Sandoval is: Arquimidez Pozo, Benito Santiago, Ruben Sierra, Leo Hernandez, Pedro Munoz, Jose Desa, Jose Guillen, Ron Jones, Ivan Rodriguez, Victor Diaz, Darryl Motley, Rafael Palmeiro, Carlos Baerga, and Richard Hidalgo all show up. Talk about a huge range of possible outcomes.

For 2009, projections

PECOTA      .289/.329/.455
Shandler:   .294/.319/.482
James:      .320/.346/.500
ZIPS        .284/.313/.455
CHONE       .283/.315/.426

RLYW: The 2009 Diamond Mind Projection Blowout - American League Edition

Opening Day is almost here, so it’s time to present my annual Diamond Mind Projection blowout.  The idea behind this is to take several projection systems and run the 2008 season through Diamond Mind Baseball, which I consider to be the most statistically accurate baseball simulator out there.

Thanks to The Los Factor.

Crawfish Boxes: Optimizing the Astros line up by THE BOOK

I know that there has already been some discussion about Beyond the Box Score’s article on how to best fit the Astros line up to Tango, Litchman, and Dolphin’s seminal sabermetric inquiry to “The Book,” but I figured I’d try my hand it.  I used PECOTA’s weighted mean forecast because:

1. I needed to use a standardized source for player forecasts.
2. PECOTA is my go to projection for hitters, which is just personal preference.

After the jump, I’ll delve more into the reasons for placing each hitter where they were per THE BOOK and BtB’s analysis of its suggestions for optimizing a line-up.  However, I’ll offer you a teaser to entice you to read more:

1. Pence
2. Berkman
3. Tejada
4. Lee
5. Matsui
6. Bourn
7. Blum
8. Pitcher
9. Pudge

Cecil: I’m comin’, Beane-y boy!

SNY: Salfino: Crystal ball: Mets pitching staff edition

Salfino with a look at the Mets palantíer of pitchers…

Thanks first to the fine work referenced below in Ron Shandler’s Baseball Forecaster, The Bill James Handbook and Dan Szymborski’s ZiPS projections courtesy of BaseballThinkFactory.com.

We’ll first work our way down the projected Mets rotation before looking at key relievers. For fun, we’ll address the starters in the order of innings pitched projected by Szymborski. (Warning: Keep the air-sickness bags handy.)

Johan Santana: Shandler: 218 innings, 202 strikeouts, 3.19 ERA; James: 230/234/3.01 ERA; ZiPS: 220/232/3.23.

This is why Santana gets the big bucks: his ceiling is high and not much higher than his floor. Of course, there is the ever-present injury risk. Perhaps the Pitching Mechanic (Chris O’Leary) is right and it’s elevated in Santana’s case. But note that Stanford researchers say the idea that pitchers (or any athletes) can repeat motion to the degree suggested in this analysis defies evolution and runs contrary to very persuasive movement studies of other primates.

Jonathan Niese: Shandler: No projection; James: No projection; ZiPS: 165/101/4.85.

Did Pedro Martinez help with these ZiPS projections? No way can all these non-Santana guys get 165 innings unless the forecast is for the Mets to win 70 games. I like Niese. A National League scout I trust says he’s worth developing. The Mets schedule doesn’t feature many early days off. Let’s see what Niese can do with a quick hook at the ready every fifth or sixth day.

Swartz: Does PECOTA overestimate the batting averages for fast players?

Yeah...that 1975 BPro prediction of “Herb Washington: Batting Champion” was waaaaaay off base.

Moving on to 2009, I decided to compare how the top 26 base-stealers as projected by PECOTA (speed score is not listed for 2009 PECOTA projections) looked compared to CHONE and ZiPS projections.  I dropped the players who did not have any significant amount of major league experience.  Then I did the same thing for the top 26 homerun hitters as projected by PECOTA, again comparing those to the CHONE, ZiPS, and Marcel projections.  Sure enough, PECOTA projected the batting averages for the speedy players higher than CHONE, ZiPS and Marcel, but not for the homerun hitters.

I would paste in the table here, but again, since PECOTA’s projections are proprietary, I will only summarize the results.

For the 26 speedsters, PECOTA was the highest of the four systems for 14 of them.  It was the second highest for 2 of them, third highest for 2 of them, and the lowest for 8 of them.  For the 26 sluggers, PECOTA was the highest for 7, tied for the highest for 4 of them, second highest for 1 of them, third highest for 5 of them, and the lowest for 9 of them.  It estimated a batting average ten points higher than the average of CHONE, ZiPS, and Marcel for 8 speedsters, but for only 5 sluggers (2 of whom were Beltran and Hanley Ramirez, also speedsters).

The 8 speedsters that it was the highest for were: Jose Reyes, Jimmy Rollins, Hanley Ramirez, Michael Bourn, Carlos Gomez, Brandon Phillips, Rickie Weeks, and Nate McLouth.  It was also pretty high on Willy Taveras, Shane Victorino, Juan Pierre, and Corey Hart.

I would be cautious about trusting PECOTA on these guys.  It does seem that PECOTA does indeed overestimate these hitters by a bit.  By the regression estimate, it looks like fast players may get an exaggerated batting average boost of about 4 points.  I would guess that each of the projection systems has their weaknesses on certain players.  If it were possible to determine which types of hitters were better projected by different systems, I think that would be extremely useful to know.

PECOTA Discussed on the MLB Network (Video)

“Stats are ridiculous.” - Harold Reynolds.

Thanks to Vegas Watch for the headsplosion.

Driveline Mechanics: A Stupid Position Battle: Yankees Right Field

“or, How Much Better Would the Yankees Be With Manny Instead of The Swish?”

Of the players currently on the Yankees, Swisher isn’t just the projected to be best hitter among them, but CHONE’s projection sees him as practically equal to Johnny Damon defensively, as well (and we’re being generous to Damon by assuming he would be as good in right as he is in left).

There’s no contest between Swisher and Nady. As for the man the Yankees are trying to replace, while Abreu is about as good as Swisher on offense, Swisher projects as 16 runs better (about 1.5 wins) on defense over a full season.

But is he “good enough” for the Yankees? 34 runs above replacement is almost 3.5 wins above replacement, or 1.5 above average. There are many teams who don’t have a single outfielder that good. But we’ve only looked at the internal options.

While the Manny boat has probably sailed by now, it’s worth discussing him because if the Yankees had signed him, all the pundits would call the Yankees therunaway favorites. But assuming that dumping Swisher (or putting him on the bench) would be part of that (and leaving aside the issue of who would play in right field), would it make the Yankees that much better. Manny, even at his age, is still projected to be an incredible hitter by all three systems. But his defense gives almost his entire advantage against Swisher away. He only projects as 2.3 runs better—for all practical purposes, they are equal. And keep in mind that playing time hasn’t been considered. Swisher hasn’t had major injury problems that I know of, and is still a bit of a way from 30. Manny barely played 130 games in 2006 and 2007 and will be 37 in May. And Swisher clearly has positional versatility Manny doesn’t.

The Nady issue is clear, as my Driveline colleague David Golebiewski points out elsewhere (although in much less wordy fashion). My point here, however, is that not only is he better than Nady, but that he’s projected to be at least as good Manny Ramirez, player whose acquisition by the Bronx Bombers would make every talking head call them a lock for the division title in 2009.

Thanks to Wims.

Shysterball: Beanster: The Alyssa Milano Effect

BAH! The Maimed Van Doren Effect busted up a lot more pitchers!! Why...why..Gene Brabender was never the same again!

I don’t believe the Alyssa Effect has received sufficient attention by the statistical community. I took a closer look at the data based on dating information provided by this site.

While only 3 of her 26 documented relationships are major league starting pitchers, I think the results are interesting and reasonably predictive in the event she reneges on her 2008 pledge to swear off dating baseball players.

Exhibit A: Carl Pavano (2003)
During their 2003 relationship, Pavano made 33 starts and posting 12 wins with a 4.30 ERA (33/12/4.30). In 2004 after their breakup he improved dramatically to (31/18/3.00). However this euphoria proved short lived, as Yankee fans can attest, and he regressed in 2005 to (17/4/4.77).

Exhibit B: Barry Zito (2004-05)
Zito’s dating numbers averaged (34.5/12.5/4.53), remarkably similar to Pavano’s. After the breakup he also improved in 2006 to (34/16/3.83), nearly as big an improvement as Pavano’s. What happened the year after? You guessed it, regression to (33/11/4.53).

Exhibit C: Brad Penny (2006)
Penny’s dating year of 2006 was also an unspectacular (29/7/3.90). He then experienced what I am now terming the Milano Bounce with a nice (33/16/4.33) and continued this into 2008 with a (33/16/3.03). Because we are not using precise dates on the relationship, the numbers are only estimates but it appears Brad remained mentally strong for a longer period before succumbing to the inevitable Milano Meltdown with a 2009 line of (19/6/6.27).

Thanks to Rob Neyer.

Judge Delivers KO Punch to Clemens

This hurt more than the Icy Hot to the gonads.

FOX Sports: Perry: Despite injury concerns, Sheets is worth the risk

Don’cha think there’s a place for him
In between, for Sheets?

Mets

The Mets are focused on bringing back Oliver Perez, but even if they do Sheets would remain a great fit. The recent signings of Freddy Garcia and Tim Redding? Half-measures at best. The addition of Sheets (and Perez) would allow the Mets to slide Mike Pelfrey down to the fifth spot and perhaps use the lefty Jon Niese out of the bullpen. More to the point, the NL East figures to be another close race between the Mets and Phillies, and adding Sheets and Perez would be enough to make New York the favorite. It’s the Mets who provide Sheets with the best union of need, payroll flexibility, and contender status.

Cardinals

Cards ownership seems disinclined to make any major investments this winter, but the depressed market means Sheets might be in their price range. With Chris Carpenter’s status — and even his role — uncertain, St. Louis may be forced to open the season with Joel Pineiro and Kyle McLellan in the rotation. Not an optimal state of affairs, that. The front office can’t afford to squander Albert Pujols’ prime seasons by failing to surround him with a pennant-worthy supporting cast, but that’s precisely what they’re doing. Inking Sheets would be anifty corrective measure.

Postcards from Elysian Fields: Sullivan: Somebody Explain This

Here is the link:

http://www.baseballthinkfactory.org/files/oracle/discussion/2009_zips_projections_texas_rangers/

Go there and you will find out how every Ranger is going to perform in 2009.

Now somebody explain this to me. Somebody explain what this means and why somebody would go to all this trouble. There’s no doubt this is impressive work. There is no doubt that this is the product of a beautiful mind. Euclid couldn’t be more brilliant.

Basically, if you read this, David Murphy and Matt Harrison are going to regress. Why?

Looks like Josh Hamilton is going to regress. Apparently Elvis Andrus is going to hit .242 with a .298 on-base percentage and steal 42 bases. Nelson Cruz - if the Rangers are going to give him a chance - will hit .282 with 31 home runs and drive in 92 runs. Take that right now?

Kevin Millwood is 11-11 but with a 4.20 ERA in 29 starts. Guess here is a 4.20 ERA for the Rangers would produce a record better than just .500. Vicente Padilla is 10-11 with a 5.04 ERA. Guess Millwood won’t get adequate run support.

Love to see what was said about the Rays a year ago.

And if that isn’t enough...go to the comments section for real postcentral gyrustoleum action!

Baseball America’s Top 10 Prospects: New York Mets

Right on time for Dan’s ZiPS Projections for the Mets.

1. Fernando Martinez, of
2. Wilmer Flores, ss
3. Jonathon Niese, lhp
4. Brad Holt, rhp
5. Bobby Parnell, rhp
6. Jefry Marte, 3b
7. Jenrry Mejia, rhp
8. Reese Havens, ss
9. Nick Evans, 1b/of
10. Eddie Kunz, rhp

Interestingly, the third of those three choices made the biggest impression. Righthander Brad Holt has the best fastball in the system and has jumped on the fast track to the majors. The Mets expect fiirst baseman Ike Davis and shortstop Reese Havens to fare better in 2009 after uninspiring pro debuts.

Because many of the top players in system are still teenagers, there won’t be many new faces making their debuts when New York unveils Citi Field this season. The lone player not already exposed to the majors who may have an impact is Martinez.

Royals Review: Projecting the Royals’ 2009 Offense with Bill James (Not Really, Though)

Yeah...but it sells the article!

Let me say from the get-go that, in my utterly amateur opinion, the James projections aren’t that good. I don’t know why. They tend to be overly optimistic regarding power hitters. In post-season discussions about the relative success of different projection systems, I don’t recall the Bill James projections ever coming into a serious conversation among the “winners” (generally ZiPS, CHONE, and PECOTA are at the top.). But this was the first full set of “free” projections that came out, and they aren’t totally uninformed. Yeah, I could use a Marcels (I’m going to start doing them myself one of these days, and Colin Wyers has already done some for 2009 to tide you over until Tango does his “official” set), which do surprisingly well. However, they don’t work as well for young players with less than three years of experience in the majors, and the Royals best players fit that description.

In short, I am not endorsing the James projections. I’m not saying they’re worthless, either. I just wanted an excuse to work with converting stuff to wOBA and bRAA and to get an idea of what sort of offense Royals fans might expect, as these projections, while probably not the greatest, aren’t completely unrealistic.

Dallas police officer, former minor leaguer, arrested in connection with armed robbery

Officer Alph Coleman was arrested Tuesday evening on suspicion of aggravated robbery. When investigators spoke to him Tuesday, he refused to answer questions about the June 27 robbery of the Sam’s Club in the 2900 block of West Wheatland Road.

Police say the getaway driver was behind the wheel of Officer Coleman’s civilian car. They also obtained cellphone records showing that Officer Coleman called the driver several times just before the gunman entered the store.

Police officials said Officer Coleman, hired in 2004, had no prior disciplinary history.

Alph Coleman spent 2000-2002 in the Braves minor league system compiling a .266/.299/.360 line in 287 games.  I wonder what those ZiPS look like when translated to the Texas Penal League.

Seattle Times: Baker: Bad talent or underachievement?

Geoff Baker needs your help!

A part of yesterday’s debate centered around whether the Mariners truly are a bad team, built with inferior talent, or merely an underachieving team with players who can’t win when they have to. As many of you know, I’m siding with the latter part of that argument. And no, it’s not because I’m afraid of being proven wrong about my pre-season prediction. I’ve already been proved wrong. So, that’s not really part of this discussion. The team hasn’t won. It hasn’t contended. Whether it’s for one reason or another, I was still wrong. This isn’t an attempt at excuse making. It’s an attempt at figuring out what the heck went wrong this year. Something the team is no doubt doing as I type this. In the spirit of catching my plane on time, I’ll make this brief.

...So, there you go. Obviously, a bunch of players are no longer here. Wilkerson appears to be a case of a guy who simply fell off the planet. I’ll grant you that. It happens. But as for the rest, what I do is look at where they were projected to be in 2008, using whatever system you want. Try PECOTA, or ZiPS. Any system at all. Plug it in and see what was projected for them. Then, you look and see where those numbers correspond to the actual ones put up right now. Or, see where they corresponded to those that had been put up at about the mid-May point this team fell out of it.

If they are close, then take that system you used to project performance and put it in the bank.

THE PROTRADE JOURNAL: An Earnings Projection Method for Hitters

And here’s Part 1 of Bosox Bob’s work...using Dan’s ZiPS projections.

In my first pass using this approach, I pro-rated the ZiPS earnings projections for the remaining May-September ABs. The result? The average error dropped to 23.2% - less than either data set’s projections taken separately. This approach is flawed however, as it would overweight the ZiPS projection and underweight any performance level changes as the season progressed.

To counter this, I computed a combined earnings rates from the April and ZiPS data, weighting by ABs to date and projected ABs respectively (aprox. ? April data to ? ZiPS data). This rate was used to project the remaining earnings for the year. With this method, the average error went down to 21.5%. As a check of this projection method, I repeated the process using stats through the end of May, which yielded an average error of 19.2% - more accurate than a month prior.

2008 Hitter Projections

Now that we’ve established a projection method, let’s see what players it currently identifies as good buys. Using 2008 ZiPS and player stats to date for the season, I generated projections for all hitters (note: expected ABs were based on player’s average ABs per team games played, minus games missed on DL). The following table contains all hitters whose pace and projection are at least 25% greater than their current price:

Mets Geek: Peterson: Interview: Tom Tango

New findings from the Tango Investigation Group…

Do you think it’s important that baseball researchers share findings and discuss process? Or can interesting and worthwhile things happen when someone like Bill James does his own thing and isn’t really aware of what others are doing?

Sure, interesting things can get done, but also a whole lot of redundant and terrible things too. Bill James has a few pieces that are simply things that I have already done. Why he would waste his time doing that, I don’t know. But that’s the way he is, by his own admission. Sometimes, you get a pearl out of it. So be it. Researchers at The Hardball Times is the model, as far as the web is concerned. I get immense satisfaction of reading sabermetric works. You’d think all researchers would think like that.

You always seem to be working on the next great statistical project. Tell us what you’re working on right now.

I’ve got a list I posted on my site somewhere called Tango On Demand. Next up for me is creating a Fielding Database. Normally, I would be tacking the PITCHf/x data, but (a) there’s a lot of bright people already there, so I’m happy to be an interested observer at the moment, and (b) the data is still in flux, and I’d rather work on stable datasets.

Comcast: Salfino: Phils Pitching by the Numbers

Live from the Bowl-O-Rama-Slamma-Lamma-Ding-Dong Lanes...the latest from Salfino!

Cole Hamels

ZiPS says, 14 wins, 192 innings, 185 K’s and 50 walks. He’s great. 4:1 K:BB ratio. Only 2:1 this year, but it’s early. At age 24, he should get better. The homer rate has been high, but there are park factors at play. Hamels threw more changeups (34 percent of all pitches) than any starter in the league last year other than Tom Glavine. A number of scouts I’ve spoken to this year consider the changeup to be the most effective complementary pitch, all things being equal. Hamels is clearly one of the top 10 pitches in the sport and reasonably can be grouped in the top half dozen.

Kyle Kendrick

ZiPS only gives him 60-something innings. So we’re going to have to fly solo here, too. I hate to keep beating the same horse here, but when you strike out less than 4.0 per nine innings like Kendrick in ‘07, you are swimming upstream against a swift current. He’ll survive that only if he continues to flash the great control he showed in 2007: (just 2.0 walks per 9 innings). But this year, he’s walked eight guys and K’ed one. Hitters are also crushing liners off him (well above average rates of 21.1 percent in ‘07 and 27.3 percent this year). Oh, and his K-rates were terrible in the minors, too.

Vegas Watch: Somebody’s Gonna Be Wrong

I know, I know...it sounds like a lost title from the Penn-Oldham catalog, but it’s buggy good stuff from the VW boys.

Seattle Mariners
Average: 86.2
High: Steve Phillips (ESPN), 92
Low: PECOTA, 75

Do you think Phillips can spell “Pythagorean”? I don’t.

That being said, 75 is really low. The PECOTA projection does come with something of a disclaimer, since it has Ichiro hitting .303/.346/.384. In 4774 career ABs, Suzuki has hit .333/.379/.437; this is his age 34 season, but thats a huge drop, and Ichiro has outperformed his PECOTA pretty much every year.

Still, even if we bump PECOTA’s projection up to 77, that’s a 15 win difference. And this is far from an isolated incident. The four ESPN guys (Stark, Kurkjian, Olney, and Phillips) and the three Yahoo! guys (Henson, Brown, and Passan) have the winning an average of 90 games. Sheehan, Law, and various computer projections predict an average of 79 victories.

They won 88 games last year, while being outscored by 19 runs. The high predictions employ the “88 wins + Bedard” logic. The others are starting with a baseline of 79, and giving them a boost for Bedard but factoring in some regression for their aging lineup. I don’t think it’s particularly hard to figure out who to side with here.

Comcast: Salfino: A Look at the Phils by the Numbers

From the city that gave us Jim Murgie’s legendary 900 Series...Salfino checks out the hitting zone conditions in Philadelphia.

Chase Utley, 2B
James: .910 (26 homers, 10 steals); PECOTA: .900 (27, 10); ZiPS: .896 (26, 12).

You identify greatness by having such a high and narrow range of projection. I think he’ll steal at least 15 bags; last year’s total dipped only because of time missed due to injury. There is more concern about the dip in power as measured by percentage of fly balls that cleared the wall. His rate of 10.4 percent is now only average and down from about 13 or 14 percent – likely a random variance. Utley hit only eight bombs on the road, but still sported an .886 OPS in those games. The .332 overall average last year was largely a function of great luck on batted balls (not including homers). He converted 36 percent of them into hits last year, about 34 percent in 2006 and 31 percent in 2005. Average is 30 percent. Utley’s range represents a 40-point average swing. Expect him to trade batting average gains for more homers in 2008.

Ryan Howard, 1B
James: 1.068 (53 homers); PECOTA: .957 (44 bombs); ZiPS: 1.028 (50 jacks).

Howard’s homer range is connected directly to his ability to convert fly balls. 2006 likely was a career year because his rate soared to 38 percent. Last year’s 28 percent is still outstanding (almost three times average). I think PECOTA is significantly light here because Howard was the fifth most extreme fly ball hitter in the majors, improving his rate significantly from 2006. The next guy was third most fly ball extreme.

The 2008 Diamond Mind Projection Blowout

Opening Day is almost here, so it’s time to present my annual Diamond Mind Projection blowout. The idea behind this is to take several projection systems and run the 2008 season through Diamond Mind Baseball, which I consider to be the most statistically accurate baseball simulator out there.
[...]
As you can see if you look at the prior runs, the results can be hit and miss, but that’s certainly understandable. This year, I’m using six different projection systems, and I’ve run each one 1000 times for a total of 6000 iterations.

There’s also a part 2 with awesome pie charts. Check out the NL West chart!

SNY: Salfino: Projecting the Yanks’ staff

More colorful than waking up in Ernie Schlegel’s closet...it’s the latest from Mike Salfino!

Andy Pettitte - James: 205/156/3.79; PECOTA: 176/117/4.22; ZiPS: 213/141/4.06. Is Baseball Prospectus right in projecting such a decline in K rate? Well, as I often write, the circus eventually leaves town for everyone. It’s not going to be clowns and cotton candy for Pettitte much longer (especially without Brian McNamee working the snack bar). Pettitte did go down to about 5.6 K’s per nine last year and will be 36 in June. But the K’s spiked to 7.0 per nine innings in the second half of ‘07. Even with those extra whiffs, the ERA and ratio were significantly worse because teams went from hitting a league-average .300 on balls in play to .350 (” ... just past a diving Jeter"). If Pettitte pitches 200 innings, I think he comes closest to James. But I think there is a very good chance he won’t. When guys get hurt there usually are about 30 or 40 terrible innings before they fess up and surrender to the MRI.

Phil Hughes - James: too young to project; PECOTA: 152/129/4.42; ZiPS: 141/106/3.70. Remember when Hughes was the best pitching prospect in baseball? Now most scouts I talk to say his ceiling is “No. 2 starter.” That’s not exactly an insult in scouting parlance, let’s be clear. But that is a clear step down from the 2007 scouting forecasts. What happened? He hurt his hamstring and then his ankle and never ironed out his mechanics to get back some lost velocity. Again, scouts tell me that mid-90s fastball talk was hyperbolic jive. But I see solid-plus velocity and the ability to spot the fastball. And his curve is top notch, too, though the change-up seems to have replaced it as the complementary pitch of choice. Hughes’ change is in the developmental stage, but it shows promise.