With the off-season in a holding pattern, let’s spend a little more time talking win values, shall we?

One of the questions that came up in a thread last week was how well team win values match up with actual wins. So, I wanted to spend some time on that issue. The first thing to remember is that our win values are context neutral, so we are not attempting to account for the distribution of runs in regards to the value of the situation. In the win value system, a run in the 3rd inning of a 10-0 beatdown is the same as a 9th inning walkoff that decides the winner. Because we’re presenting context neutral wins, teams that have a run scoring distribution skewed towards higher leverage situations will win more games than win values would suggest.

The Angels are the best example of this. Last year, they accumulated 17.2 wins from their position players and 22.0 wins from their pitchers for a total of +39.2 marginal wins. With our replacement level set at .28852 (or just round to .289) for ’08, that makes the Angels an 85.94 win team according to our system. Basically, we think they earned 86 context neutral wins last year. They actually won 100 games – 14 more than their win values would have suggested. Why? They were the Kings of Clutch, performing drastically better in situations that mattered than they did when the game wasn’t on the line.

If you’re familiar with the concept of Pythag Win%, you’ve seen this phenomenon before. Because there’s little to no evidence that the distribution of run scoring is a repeatable skill, we’re not including it in our win values, and will match up with pythag wins better than it will with actual wins. This is born out by the correlations of each.

Win Values to Pythag: .90
Win Values to Wins: .85

Win Values correlates very well with both pythag wins and actual wins, but better with pythag because of the run distribution issue that we talked about above. Clearly, though, our system of rating players is adding up very well at the team level, even without considering the context of when runs are scored.

This evening, we’ll take a look at the differences between win value projections and pythag expectations and explore why two projected win totals both based on runs scored and allowed would diverge.

Because I just can’t stay away, let’s talk about pitcher win values again. This time, let’s look at how pitchers have performed in rolling three year totals dating back to 2002, which is the first year we calculate win values for here on FanGraphs.

2002 to 2004 leaderboard

Curt Schilling leads the way with +23 wins from ’02 to ’04, propelled to the top by his ridiculous 2002 season where he was a +9.7 win pitcher. I think people forget how good Schilling was that year – 9.58 K/BB rate in 259 innings. That’s just remarkably awesome. Pedro Martinez, Randy Johnson, Roy Halladay, and Jason Schmidt round out the top five.

2003 to 2005 leaderboard

Nobody cracks the +20 win plateau over these three years, with Pedro Martinez and Johan Santana leading the way at +19.5 wins apiece. Randy Johnson, Roger Clemens, and Jason Schmidt round out the top five.

2004 to 2006 leaderboard

Johan emerges as the dominant pitcher of this era, racking up +22.6 wins and throwing 693 innings during that time frame. Nobody else is close, with Roy Oswalt checking in second at +18.1 wins. This was the age of Johan.

2005 to 2007 leaderboard

Santana loses his great ’04 and replaces it with a less great ’07, but still manages to cling to the lead. Again, though, no one cracks the +20 win mark, as Johan’s +19.5 is best in baseball. Brandon Webb emerges, though, to take the second spot at +19.1 wins. Meanwhile, John Smoltz tries to remind everyone that he’s still pitching, and checks in with a +16.5 total that’s fifth best in baseball over those three years. Those were his age 38 to 40 seasons.

2006 to 2008 leaderboard

Finally, the last three years. CC Sabathia takes the top spot at +20.3 wins, just edging out Brandon Webb (+19.7) and Roy Halladay (+19.2). Santana plummets all the way to fourth, with Dan Haren rounding out the top five.

So, who has been the best pitcher of the Win Value era? Santana seems like the best guess, since he led (or was tied for the lead) in three of the five windows we looked at, but he actually finishes second to the amazing Roy Halladay. Since 2002, Halladay has racked up +42.7 wins, three more than Santana’s +39.8. +42 wins in seven years – not only has Halladay been an excellent pitcher, he’s been consistently excellent. He’s never got the same level of acclaim as Johan, but a seven year stretch of +6 wins from a starting pitcher is amazingly impressive. Hats off to Halladay.

As the off-season winds down, teams are starting to get a better look at how their roster is going to shake out and where certain players fit together on the field and in the line-up. However, there are several teams that have surplus players at positions and should be actively looking to make a move to redistribute some talent in a more efficient manner. Here are three players who would have more value to another club than they do to the one they’re on currently.

Luke Scott, OF, Baltimore

With the acquisition of Felix Pie to play LF, the Orioles are relegating Scott to the DH spot, since he doesn’t fit into their Three CF plan. However, Scott just doesn’t have a DH skillset – he’s a decent enough hitter (CHONE has him .255/.343/.462 for 2008), but he’s also a pretty decent defensive outfielder. He has a career UZR/150 of +8.5, well above average for a corner OF. In 1,300 career plate appearances, he’s racked up +7.3 wins, or just about +3.5 wins per full season.

As an OF, he’s projected for something like +2.0 to +2.5 wins for 2009. As a DH, though, where his defensive value would be nullified, that drops to +1.0 to +1.5 wins. There are a pretty long list of teams who could use a low cost, league average corner outfielder, and the Orioles would do well to find one of those teams and strike a deal. Finding a guy to DH and give you a .350 wOBA isn’t very hard, particularly in this free agent market. They’ll get more value by trading Scott and signing a stop-gap DH than they will by using him as just a hitter.

Willy Aybar, 3B, Tampa Bay

We’ve talked Aybar earlier this winter, but he still remains the best reserve player in baseball. A 25-year-old switch-hitting infielder who has accumulated +3.9 wins in 745 career PA shouldn’t be looking at a job where he only plays a couple of times per week. Aybar is an everyday major league player, and only Tampa’s loaded organizational depth chart prevents him from laying hold of a full time job. The question in his case, though, is what motivation would the Rays have to deal him? What else do they need?

In many ways, Aybar is being punished for the fact that the Rays have done such a great job of building a roster around him. Not only do they not have a regular job for him, but they don’t have any glaring needs that they should be trying to fill via trade. Their weakest link is in the bullpen, but as they showed last year, you don’t have to give up talented players to build a success relief corps. Realistically, Aybar’s going to have to hope for an injury to get any real playing time. For his sake, let’s hope he gets an opportunity before the reserve infielder label sticks.

Austin Kearns, OF, Washington

Jim Bowden’s fondness for toolsy outfielders is no secret, as he routinely scoops up every available power/speed guy who hasn’t figured out how to hit a baseball. Thanks to his obsessive nature of collecting upside guys and shoving them into a locker room together, the Nationals have an overloaded outfield and not enough room for everyone to play. Elijah Dukes is the one guy who should absolutely play everyday, no questions asked, but the other two spots have to be split among Lastings Milledge, Josh Willlingham, Willie Harris, Wily Mo Pena, and Kearns, not to mention the always lurking Corey Patterson, who got a minor league contract and will be in spring training with the Nationals.

Kearns has fallen a long way from his top prospect days, and was especially horrendous last year. However, he’s still an excellent defensive outfielder heading into his age 28 season and a year away from free agency (the odds of his $10 million option for 2010 being exercise are slim), so he’d make a useful reclamation project for a team with at-bats to spare for an outfielder. Kearns simply has less utility for a team like Washington than he would for a club that is one OF short of filling out their roster, and with a limited future in the nation’s capital, it’s in everyone’s best interests if he moves on before the year starts.

One of the truisms in sports is that whenever an organization emerges as a new success story by doing things unconventionally, other teams often try to copy the pattern. In football, we’ve seen this with the rise of the west coast offense after the 49’ers rose to power in the 1980s, and in basketball, we’ve seen teams get away from big line-ups after the Phoenix Suns won a lot of games with their seven seconds or less philosophy. Last year, the Tampa Bay Rays were the new success story, one of the foundations of that success was their outfield defense.

Carl Crawford is, for all intents and purposes, a center fielder. He’s just been assigned to left field for the Rays. B.J. Upton is the prototypical center fielder with long strides and blazing speed. And, while Gabe Gross might not look like a center fielder, he’s performed like one during his major league career. These three spent the majority of the time in the outfield for the Rays last year, and were the reason why Tampa racked up a +45 UZR from their outfield in 2008.

Based on what we’re seeing in Baltimore and Seattle, it appears that the Three CF model of outfields that Tampa made en vogue is catching on in other cities as well.

The Orioles just completed a trade for Felix Pie, an outstanding defensive outfielder who has struggled to hit major league pitching so far in his career. Those struggles haven’t carried over to the outfield, though, where Pie’s UZR/150 in limited playing time is +11.2. Based on the scouting reports, his physical skills, and even the limited data we have, there’s significant evidence to suggest that Pie is a well above average defensive center fielder. The Orioles, however, have tapped him to play left field, where he’ll roam alongside Adam Jones (+4.6 UZR/150 as a CF last year) and Nick Markakis (+3.6 UZR/150 as an RF last year).

With Pie and Jones, the O’s have two above average center fielders. Markakis, the least rangy of the three, is still above average for a corner OF and is better defensively than some players masquerading as center fielders (Josh Hamilton, I’m looking at you). With an outfield of Pie/Jones/Markakis, the Orioles should expect something like a +15 to +25 UZR from that trio, which would almost certainly give them one of the best defensive outfields in baseball.

However, depending on how Jack Zduriencik fills out his roster in Seattle, it probably won’t be the best. Right now, the Mariners are looking at a potential outfield of Endy Chavez in LF, Franklin Gutierrez in CF, and Ichiro Suzuki in RF.

Chavez is, without question, an outstanding defensive outfielder. In nearly 3,000 innings in CF, he’s racked up a +2.8 UZR/150, but that doesn’t even compare to his staggering +20.2 UZR/150 in 1,600 innings in LF/RF. The scouting reports agree – his defense is off the charts good.

He might not even be the best defensive outfielder in Seattle, though. Franklin Gutierrez has drawn raves from scouts for years for his jumps, range, and arm strength, and his defensive performances in Cleveland back up all the superlatives you could throw at him. He only got 159 innings in CF for the Indians due to some guy named Sizemore, so you have to take his +17.7 UZR/150 in center with a lot of salt due to the small sample size. However, it becomes a little easier to ingest when you see his +21.9 UZR/150 in LF/RF. Gutierrez is just a defensive monster.

That leaves Ichiro, the forgotten guy over in RF. For his career, he’s been +7 UZR/150 in right, making him a well above average corner outfielder. He’s been basically average while playing CF as well, confirming the belief that he’s going to look very good when compared to less rangy right fielders.

If they go with a regular OF of Chavez, Gutierrez, and Ichiro, it’s not hard to project the M’s as a +30 to +40 outfield in 2008. No one else in baseball – not even the Rays with newly added Matt Joyce in the mix – project to have that kind of outfield defense in 2009.

It will be interesting to see how these Three CF outfields turn out. All of them lack the traditional slugging corner outfielder, but if you see the Orioles, Mariners, and Rays once again exceeding national expectations, don’t be surprised if even more teams start copying the Three CF model.

Like a lot of free agents, Ivan Rodriguez is looking for a job. However, while most of the big names will eventually find work, even if it’s for less than they had hoped, it appears at least somewhat likely that Pudge might be on the Kenny Lofton/Sammy Sosa forced retirement path. David Samson, president of the Marlins, recently stated that there is zero chance that Florida will sign Pudge, and the other teams with catching needs simply don’t sound interested.

I find this pretty strange, honestly. Over the last four years, Pudge has been worth 2.2, 2.5, 1.6, and 1.9 wins, if you assume that he’s been average defensively. I know pitchers have reported having problems with his pitch calling, but he’s still generally regarded as one of the best defensive catchers of all time – it’s hard to imagine that he could have declined so much that his defense would take away all of his offensive value.

This is, after all, a catcher who hasn’t posted a wOBA below .300 since 1992. Those aren’t exactly laying around on the waiver wire. Brad Ausmus, who just signed for $1 million with the Dodgers yesterday, has had a wOBA of greater than .300 only one time this decade. His career wOBA is .298, compared to Pudge’s .350. Ausmus found two suitors, and when the Padres lost him to LA, they turned to Henry Blanco, who has a career .282 wOBA.

Both of those guys have good reputations for their work with pitchers, but that is apparently the only criteria teams are using when choosing which catchers to sign. You’d have to believe that Pudge was the worst handler of pitchers of all time to make up for the offensive gap between him and guys like Ausmus or Blanco.

Clearly, there’s something about Pudge that teams don’t like. Much like with Kenny Lofton, though, he’s definitely still a major league caliber player who wants to keep playing. He may not get that chance, however.

This afternoon, I showed that the pitcher win values are actually fairly decent predictors of the next year’s win values, with an average year to year correlation of around .63 for the last four years. How does this compare to the hitter win values we publish here on the site? They’re pretty comparable. How comparable?

2004 to 2005: .59
2005 to 2006: .63
2006 to 2007: .64
2007 to 2008: .66

That’s also an average year to year correlation of .63 – the same as we found for pitchers. Just knowing a player’s prior year win value, you’ll have a rough idea of what his following year’s win value may be. Now, a the advanced projection systems (CHONE, PECOTA, etc…) will do a better job of incorporating more data and weighting it appropriately, so we’re not suggesting that single year win values replace those systems for projecting future performance. However, it’s a good sign that the win values correlate fairly well from year to year.

So, hopefully, the posts we’ve done the last few weeks have helped you understand what the win values system is telling you, and the transparency we’ve tried to apply to the system should allow you to trust the results. The win values system captures player value very well, and predicts future win values for both batters and pitchers with solid reliability.

We’re not claiming this system is perfect. This isn’t the perfect single number metric that sums up all player value with no error that people seem to want. But, it’s pretty darn good, and as good or better than anything else out there. Right now, if you want to know how much a player is worth to his team, Win Values are your best bet.

Now that we’ve worked through the logistics of the pitcher win value formula that we recently added here on FanGraphs, I figured it was time to answer the important question – how predictive are they? Since pitchers have historically been evaluated by ERA, the belief has been that they are wildly inconsistent from year to year. However, we know that ERA includes a bunch of non-pitcher variables, and since we’re using FIP, we shouldn’t have to worry about the variation in those external forces.

So, how well does a pitcher’s Win Value correlate from one year to the next? Better than I expected, honestly. I took all pitchers with at least 10 IP in 2004/2005, 2005/2006, 2006/2007, and 2007/2008, and found the following year to year correlations:

2004 to 2005: .62
2005 to 2006: .69
2006 to 2007: .67
2007 to 2008: .55

That’s not bad at all. ERA, for example, has a year to year correlation to itself of around .4. Clearly, the inputs of FIP are more stable than the inputs of ERA, but we knew that already. However, since FIP is a rate stat and Win Value is a counting stat, I’m a bit surprised at how well the win values hold up, since it requires a combination of similar performance and playing time.

As time goes on, I’m sure we’ll improve the formula and push the year to year correlations higher, but as it stands, Pitcher Win Values 1.0 do a pretty nice job of predicting pitcher value from one year to the next.

So, we’ve walked through the pitcher win values formula, and they’re now available on the leaderboard and the team pages going back to 2002. As a wrapup, let’s take a look at some final win value housekeeping notes.

If you sum up the 2008 win values for the position players and the pitchers that we have here on the site, you’ll notice that we’re handing out 583 wins to position players and 445 wins to pitchers. That’s 1,028 marginal wins – 57% of them are earned by position players and 43% of them are earned by pitchers. You know that whole “good teams are built around good pitching” thing? It’s bunk. Position players are more valuable than pitchers.

With a league wide total of 2,430 wins available every season (81*30) and 1,028 of those being distinguished as wins above replacement level, that means that the average team is 34.26 wins above replacement. 81 – 34.26 = 46.74. That’s what our numbers say a true talent replacement level team would have won in 2008. Just shy of 47 wins, or a .289 winning percentage, is the replacement level we’re using. It will vary slightly from year to year, but the .290 to .300 win% range is what is generally accepted as replacement level.

Over the last four years, Oliver Perez has been worth a total of 2.5 wins in nearly 600 innings. And he wants $12 million a year for five years. Maybe he’s the left-handed Gil Meche, and he’s going to turn the corner immediately after signing a big contract, but there’s about a 5% chance of that being true and about a 95% chance that he’s the most overrated pitcher in baseball.

In talking about how we calculate pitcher win values, we’ve covered FIP, differences in replacement level for each league and role, run environments, the dynamic runs-to-wins conversion, and park factors. What we haven’t done is walked through an example, from scratch, of how the pitcher win values are calculated. That’s what we’re going to do today.

We’ll use Felix Hernandez as our guinea pig. In 2008, he threw 200 2/3 innings with a 3.80 FIP as a starting pitcher in the American League. Remember, we noted earlier that the league average runs per game in the AL was 4.78 last year, so we rescaled Felix’s FIP to make 4.78 equal league average. Adding in a park adjustment for a half season in Safeco Field (with a park factor of .96), we get a 4.28 neutral park FIP scaled to RA for Felix’s 2008 season.

Now, we have to figure out the runs to wins conversion based on Felix affecting the run environment he pitches in. To do so, find his innings pitched per start (6.5), subtract that from 18, and multiply that by the league average runs per game. Then, we add to that those 6.5 innings multiplied by his park adjusted FIP, and divide that by 18, and then use Tango’s +2*1.5 runs to wins converter. So, the formula for Felix would be ((11.5 * 4.78 + 6.5 * 4.28)/18)+2)*1.5, which would give us a run environment of 9.90 runs per win. So, for every 9.9 runs he saves, he gets credit for one win.

His 4.28 FIP is 0.50 runs per nine innings better than league average. What does Felix’s 4.28 FIP translate into in terms of win%? 0.50 divided by 9.90 equals .050. Add that to .500 and we get .550, making Felix a .550 win% pitcher. Remember, an average pitcher would post a .500 win%, and a replacement level starting pitcher would post a .380 win%. So now we subtract .380 from .550, and we get Felix as .17 wins better than a replacement level starter every nine innings.

Factoring in his actual innings pitched, we get .170 * 200.67 / 9, which comes out to 3.8 wins. That’s his wins above a replacement level starting pitcher, or what we call his win value for 2008. Remember, though, these are context neutral win values. Actual wins contributed to a team’s ledger will also be affected by how each pitcher performed with runners on base, as well as the performance of the defenders behind the pitcher. There are going to be cases where a pitcher has a much better (or worse) context neutral win value than you might expect if you’re used to looking at his W-L record or his ERA.

That does not mean these win values are “wrong”. We’ve removed the situational context of the pitcher’s performance, just as we do for hitters. Pitchers can either underperform or outperform their win values with extreme performances in “clutch” situations. We can measure the differences in these situational performances by looking at a pitcher’s WPA or WPA/LI and comparing it to his Win Value. For too long, we’ve lacked a resource for context neutral win values for pitchers, having to settle for situational win values that include a lot of variables. These pitcher win values offer us a great opportunity to explore more of what is in a pitcher’s control and what is not.

We took a day off from the pitcher win value explanations yesterday so I could help a friend move (when you need to move on a weekday, call the baseball writing friend with the flexible schedule – he’s always available), but we’ll tackle park factors this afternoon and wrap up the series on Monday and Tuesday of next week.

As mentioned earlier, the win values are based on a park adjusted FIP. However, we never covered how we handled the park factor. There are lots of different park factors floating around out there, so I figured it would be useful for us to spend a bit of time talking about them. For those that aren’t aware, a park factor is basically the run environment of a particular ballpark expressed as a decimal, where 1.00 is average. A ballpark with a park factor of 0.90 would depress run scoring by 10%, so that if the league average runs per game is 5.00, then the runs per game in that park would be 4.5. On the flip side, a ballpark with a park factor of 1.10 would have an average of 5.5 runs per game.

Park factors are determined by the relative offensive level between each park and the league average. One of the common misperceptions about park factors is that they will be overly influenced by the home team. However, because the home team plays equal amounts of games per season in their home park and on the road, and the visiting team’s also play 81 games per year in that park, we get a decent sized sample with which to understand how parks affect run scoring.

‘That doesn’t mean that there isn’t noise in a single year’s park factor, however. Let’s take Turner Field in Atlanta as an example, for instance. Here are the single year park factors for that park since 2002:

2002: .88
2003: 1.04
2004: .94
2005: 1.01
2006: 1.02
2007: .95
2008: 1.01

That’s a six year average of .98, which makes it just barely below average in term of runs per game, but it obviously hasn’t been very consistent from year to year. The 2002 to 2003 change, especially, would suggest that the park went from being something like Petco Park to being more like Fenway Park. Most parks don’t have swings that large, but single year park factors can still be a bit unreliable. So, to calculate the win values, we’ve used a five year regressed park factor. For 2008, here are the park factors we used for all thirty teams:

Season	FullName	         PF
2008	Arizona Diamondbacks	 1.05 
2008	Atlanta Braves	         1.00 
2008	Baltimore Orioles	 1.01 
2008	Boston Red Sox	         1.03 
2008	Chicago Cubs	         1.04 
2008	Chicago White Sox	 1.04 
2008	Cincinnati Reds	         1.02 
2008	Cleveland Indians	 0.99 
2008	Colorado Rockies	 1.09 
2008	Detroit Tigers           1.00 
2008	Florida Marlins	         0.97 
2008	Houston Astros	         0.99 
2008	Kansas City Royals	 1.00 
2008	Los Angeles Angels       0.99 
2008	Los Angeles Dodgers	 0.98 
2008	Milwaukee Brewers	 1.00 
2008	Minnesota Twins	         0.98 
2008	New York Mets	         0.97 
2008	New York Yankees	 1.00 
2008	Oakland Athletics	 0.98 
2008	Philadelphia Phillies	 1.02 
2008	Pittsburgh Pirates	 0.98 
2008	San Diego Padres	 0.92 
2008	San Francisco Giants	 1.01 
2008	Seattle Mariners	 0.96 
2008	St. Louis Cardinals	 0.98 
2008	Tampa Bay Rays	         0.98 
2008	Texas Rangers	         1.04 
2008	Toronto Blue Jays	 1.01 
2008	Washington Nationals	 1.01