In every aspect, these projections are better than last year’s. Why?

1. Custom weights. Each stat is weighted based on error tests from 1970 onward; for instance, BABIP for hitters is weighted at 0.88, while strikeout rate, which is more stable year-to-year than BABIP, is weighted at 0.49 (i.e., 2009 has a weight of 1, 2008 has a weight of 0.49, etc.). I use the past four years’ stats for hitters and three years for pitchers.

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(First off, sorry for the absence. Vacation and all…)

Ken Rosenthal reports that the Phillies have agreed to trade pitcher Jason Knapp, pitcher Carlos Carrasco, shortstop Jason Donald and catcher Lou Marson to the Indians in exchange for Cliff Lee and Ben Francisco.

The main piece in this deal is Lee, who has a 3.14 ERA a year after winning the AL Cy Young award. You may think that his stats will take a hit by his move to a hitter-friendly park in Philadelphia, but you are forgetting the fact that he’s moving to the NL, a clearly inferior league to the AL.

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On today’s ESPN fantasy baseball podcast, an e-mail sent in by “Jeff” tried to debunk the myth of Dan Haren’s post-All Star break collapse. He said that even though his ERA and WHIP have rose from the first to the second half, his peripherals have either increased or stayed the same. He points out that Haren’s second-half numbers are worse because of luck—namely, his FIP has been the same as his first-half FIP, but his ERA is much worse.

(Side note: The hosts—Nate Ravitz and Matthew Berry, the Talented Mr. Roto—are unsure what FIP even means, and Berry guesses “fly balls in play.” How can two fantasy analysts not know what FIP is? The guys at Yahoo! use FIP in almost every article!)

Here’s a comparison of Haren’s career first- and second-half numbers:
 
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I enjoyed this article from THT’s Fantasy Focus.

Fantasy leaguers love strikeouts. And it’s a fair point that a high strikeout rate can contribute to a high K/BB. However, these graphs say that a low walk rate deserves allegiance on its own. A walk rate under 2.0 BB/9 is a sign of not only control but also good health and, within a game, an absence of fatigue. And it’s the pitcher’s walk rate, not his strikeout rate, that determines whether he will stay in a game in which he is pitching well.

If you’re scouting for wins, you should leap at the chance to roster a starter with a 2.5 K/BB, even if he has a sub-6.0 K/9. What he costs in Ks, he could recoup in Ws.

In his first 76 at-bats this year, Youkilis has 30 hits, good for a .395 AVG. In his first 49 at-bats, he batted .469, but he’s hit only .259 in his last 27 AB.

Should you trust his hot start? I posted this elsewhere:

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Gil LeBrenton argues for a more realistic and sabermetric form of fantasy baseball.

No, our league uses a sophisticated, highly accurate piece of computer software, Diamond Mind Baseball, that realistically recreates the game of baseball down to its every statistic. We draft the players, we manage the teams, we play the games.

…

Foot speed is a wonderful asset for a baseball player to possess. His ability to score runs, however, is largely dependent upon the real-life team that he plays for, along with his position within that team’s batting order.

For years Juan Pierre was a hot pick in everyone’s fantasy draft. In our simulation league, where things such as on-base percentage, lefty-righty splits and throwing arm all matter, the manager who selected Pierre in the late rounds could expect mocking snickers.

I largely agree with his assessment of steals and runs. I don’t like runs or RBI as a fantasy baseball category, either. (Will ESPN or Yahoo! ever track RBI per RBI opportunity?) That said, I know fantasy baseball isn’t supposed to be just like real baseball—if it were, then there’d be scoring categories such as Win Probability Added or linear weights or a defensive-independent pitching stat available to choose.

I have added fantasy dollars to the projections. These assume a $260 cap in a standard Yahoo! league (12 teams, 5×5, with nine batters and seven pitchers).

They can be viewed at the same place as last time: batters here, with a CSV file here ; and pitchers here, with a CSV file here.

(EDIT: The reason Alex Rodriguez’s value is so low is that his projected stats were lowered by 20 percent in the calculations to account for his injury.)

They were calculated using the process outlined here, with the exception of two things: one, I used the standard deviations of last year’s actual stats, because the projections can be too modest in some areas and the SDs become too low for each stat (meaning there is not enough spread in the projections). Second, I calculated the actual dollars for batters and pitchers separately and forced a 65:35 split in money between the two.

The auction values point to Randy Johnson as a late sleeper and Javier Vazquez as the No. 6 pitcher (and I’m even backed up by CHONE, which ranks Vazquez at No. 2 among pitchers). Currently Vazquez is going in the 11th round in Yahoo! leagues and the 13th in ESPN.com leagues. Vazquez and Johnson are two pitchers to aim for in your draft.

I’ve finished my team projections (which will be posted one division at a time in the next few days), and I’ve changed the pitchers’ projected wins and losses as well as saves.

I also added Chris Ray. He missed all of last year, but he should compete with George Sherrill for the Orioles’ closer role. The new projections can be found in the same place as last time: here, with a CSV file here.

For wins and losses, I use the player’s team’s projected runs scored per game as his offense instead of the league average runs per game.

Saves, on the other hand, are more complicated. This is the method I use to find projected saves:

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Apparently, there was a slight bug in the regression part of the batter projections (the part I had updated), which caused the big, heavy, tall guys to be projected for much more what they should have been—-if I remember correctly, Kila Kaahue was projected for 35 home runs or so in 600 PA.

Anyway, the projections have been updated and posted at the same link as last time (here, with a CSV file here).

Now, onto those team projections….

I have updated the batter projections—-not only moving Nomar and Manny to their new teams (the A’s and Dodgers, respectively, and even though Manny hasn’t officially signed there’s no where else he is going), but also making one last change to the projection system.

Namely, I have added into the regression stage a factor that adjusts based on height, weight, and speed. For example, I found a significant correlation between weight multiplied by height with home runs and RBI—-instead of regressing a player’s HR and RBI to the league average, I regress them to his weight multiplied by height. This affects almost every component projected.

I really think that this is the last set of projections, with the exception of moving free agents to their teams. Some time I have to just stop and start up the team projections. The newest projections can be found here (CSV file here). The same players from last time have been projected, so you can match up the names or playerIDs from the last set to this set and see who has been affected the most.