All anyone can seem to talk about today is how the 103 million dollar pitcher, Daisuke Matsuzaka, was “bombed” yesterday in a spring training start. He gave up 2 home runs, to two “non-roster” players, and ended up surrendering 4 runs (3 earned) in 4 innings, which raised his ERA from 0 to 3.86. He also struck out 3 and walked none.

What about the highly paid pitchers not named Matsuzaka? Surely some of them had an equally atrocious day. Here were the highlights from Sunday’s action:

– Brad Penny ($8.5 Million): He gave up 9 hits and 4 runs yesterday in only 3 innings. He also struck out none and has a 12.86 ERA this spring.

– B.J. Ryan ($9.4 Million): 1 inning, 4 hits, 3 runs, 1 strikeout.

– Freddy Garcia ($9 Million): 3 innings, 5 hits, 3 runs, and 2 walks. He didn’t strike anyone out.

– Mark Buehrle ($9.5 Million): 4 innings, 6 hits, 6 runs, 2 walks, and 4 strikeouts. His ERA stands at 11 this spring. It’s only 1.5 higher than he makes in millions.

And that was only yesterday. On Saturday:

– Barry Zito ($18 Million): 4 innings, 5 hits, 3 runs, 2 walks and 4 strikeouts.

Everyone panic!

We’ve just added play-by-play data in the Play Log section for each game. At this time, play-by-play data includes the Leverage Index, Run Expectancy, Home Team Win Expectancy, and the Batter’s Win Probability Added (WPA) for each and every play of the 2002-2006 season.

Win Expectancy is calculated as the result of the play, while Leverage Index and Run Expectancy are calculated before the play happened.

Everything is calculated before the play happened. We’ve also added BRAA which is the difference between Run Expectancy at the start of the play and the end of the play.

If you click on the play, you’ll get the pitch sequence for each play in a little pop-up box. The playoff games pitch sequence is a little screwed up right now. It “snakes” around, so for the first line it will be “pitch1, pitch2, pitch3, result” and then for the next line “result, pitch3, pitch2, pitch1”. We’ll try to get this cleared up soon.

We’ve also moved all the Win Probability graphs out of the Team section and into the Scoreboard section. We’re just trying to make things a little more organized and it will allow us to eventually vastly enhance our team stats.

If you have any problems or suggestions on how to improve the new scoreboard or play-by-play sections, don’t hesitate to let us know!

Thought I’d show a quick preview of our new scoreboard. This way you’ll be able to quickly see all the day’s graphs in one convenient place.

You’ll also notice that the box score and play log links aren’t quite working yet. I’m hoping they will be sometime next week.

Earlier this week the much anticipated Hardball Times 2007 Season Preview was released, and with it a brand new projection system. I recently took a look at Bill James, CHONE, ZiPS, and the Marcel projection systems to see how they differed. Let’s throw THT into the mix and see where it has its major differences.

First off, let’s see how THT fares against the other projection systems in OPS and ERA as a whole when compared to the Marcel projection system (the simplest of the five).

System        ERA-R^2    OPS-R^2
ZiPS             .725       .908
Bill James       .714       .875
CHONE            .699       .865
THT              .681       .837

And in English, when comparing the other projection systems to the Marcel projection system, THT’s system is the least similar. (When look at batters with 300+ at-bats and pitchers with 100+ innings.)

So which batters does THT disagree on the most in terms of OPS?

Name            Bill James    CHONE   Marcel     THT    ZiPS
Frank Thomas          .939     .853     .874    .982    .892
Hanley Ramirez        .801     .791     .843    .714    .777
Robinson Cano         .860     .842     .852    .766    .836
Chris Duncan          .862     .776     .891    .753    .803
Melky Cabrera         .766     .796     .787    .715    .800

Except for Frank Thomas, who THT projects is going to have a phenomenal season, they’re the low point for the other four players. It’s interesting to note that those four are also first or second year major league players. There’s generally a lot of disagreement about Chris Duncan and Hanley Ramirez, but the THT projections for Robinson Cano and Melky Cabrera appear to be the sole point of difference. Let’s look at the pitchers:

Name            Bill James    CHONE   Marcel     THT    ZiPS
Tony Armas Jr.        4.85     4.64     4.96    5.81    4.88
Carlos Zambrano       3.40     3.47     3.48    2.77    3.46
Cliff Lee             4.43     4.20     4.48    5.04    4.55
James Shields         4.03     4.29     4.72    5.03    4.70
Brandon Webb          3.53     3.60     3.65    3.07    3.85
Randy Johnson         4.31     3.77     4.33    3.43    3.63

THT clearly hates Tony Armas Jr. (more) with his ERA about a point higher than the others, while they love Carlos Zambrano who they have at about a .75 lower ERA than the other systems. I threw in Randy Johnson since he was next on the list. It looks like the projections are pretty well divided for him between the 4.30-ish ERA, and the 3.50-ish ERA.

Anyway, the THT projections are certainly similar to the others, but there are clearly a number of key differences which are definitely worth a look. There’s also a lot more to projections than ERA and OPS, so I’m sure you’ll find many other unique aspects to THT’s projection system. Like with any projection system, we’ll have to wait and see which one happens to be the most accurate for 2007.

I thought I’d mention that the Bill James Handbook projections on FanGraphs have been updated with the latest and greatest.

“… many things happen during the offseason that change playing time for the coming season. That’s why we produce The Bill James Handbook: Projections Update with cutting-edge projections reflecting changes through the last couple days of February.

We adjust projections for many reasons, including:

-Playing time adjustments
-Free agent signings (including four Japanese rookies)
-Trades
-Injuries
-Ballpark changes”

I think FanGraphs has three of the four rookies in the database now with the exception of Daisuke Matsuzaka. He’ll show up next time he makes a spring training start. For those who can’t wait, the Bill James Handbook has him at 19-2 with a 3.13 ERA in 190 innings.

As always, if you’d like to dice, slice, and sort the Bill James Handbook projections to your heart’s content, you’ll have to purchase them here.

While we’re on the topic of projections, I’d like to give a quick shout-out to the new Hardball Times 2007 Season Preview. Besides the great commentary on teams from many of your favorite bloggers, it has player projections through 2009. I’m still digging in, but it’s full of fun and useful stuff.

You may have noticed the Win Probability numbers have changed slightly. Don’t panic! There have been a few changes, for the better.

First off, we’re now using Tangotiger’s updated win expectancy tables which are no longer a flat 5.0 Runs per Game environment. Instead, we’re using the home team’s league, average run environment. This now puts batters and pitchers on “equal footing” and you should now be able to accurately compare batters and pitchers using WPA.

Second of all, we’re also using Tangotiger’s run expectancy tables to calculate Batting Runs Above Average (BRAA) for both batters and pitchers. Once again the run environment is set at the home team’s league, average run environment.

Next to BRAA there is a column titled “REW”, which stands for Run Expectancy Wins. This is a replacement for OPS Wins because we no longer need to estimate wins in a context neutral environment since we’re now using run expectancy.

Finally, Clutchiness has been shortened to Clutch (Clutchiness was excessively long) and is calculated as WPA/LI – REW.

Update (3/4/2007): Clutch has been switched back to being calculated with OPS Wins. More on this later.

Typically players remain in the same order, but their values have changed slightly. Batters should be slightly more valuable and pitchers slightly less valuable based on WPA scores.

I’ll admit, I’m a Heath Bell protagonist. Last year I expected big things from the 28 year old reliever who ended up posting a 5.11 ERA in just 22 relief appearances. He didn’t quite live up to my lofty expectations:

“Don’t be surprised if he becomes an important piece of the Mets bullpen next season.”

Well Heath, it’s a new year and you have a brand new team (Padres) with new fans to impress. Let’s see where things went wrong last year and if they’re going to happen again this year.

He has pretty much everything you’re looking for in a relief pitcher: high strikeout rate, low walk rate, and he’s even a ground ball pitcher. He’s clearly mastered Triple-A where in 2006 his K/9 was over 14! Not to mention he posted an ERA of 1.29 in 35 innings.

Yet what plagues him in the majors has been his extraordinarily high batting average on balls in play (BABIP). The past two years his BABIP has been .374 in 2005 and an insanely high .394 in 2006, which just happened to be the highest in the majors for pitchers with over 30 innings pitched. This same problem plagued him last year in AAA too, where he had a .378 BABIP, the 11th highest at the AAA level.

Typically with BABIP this high, you’d think he was just getting unlucky, but it’s hard to ignore the past two years worth of data, so despite his incredible peripherals, maybe this is just who he is?

It’s clear the Mets, at least at the major league level, never had a whole lot of confidence in him. Of the regular relievers he was used in the least important situations possible. His average Leverage Index (LI) was a measly 0.35, with a Leverage Index of 1 being an average situation (the higher the leverage, the more important the situation). The previous year was not much different where his LI was 0.65, the third lowest on the team.

His 2006 ERA of 5.11 is mainly the result of 3 games which were completely out of hand before he even entered the game.

– On 9/26 he entered the game with the Mets trailing by 6 runs and gave up another 6 runs.

– On 9/11 he entered the game with the Mets trailing by 6 runs and gave up 5 additional runs.

– On 7/2 he entered the game with the Mets trailing by 3 runs and gave up 4 runs and an additional 4 unearned runs.

So, if we take away these three horrible (meaningless) outings, his ERA ends up being 1.76. Maybe you have questions whether or not the game on 7/2 was completely meaningless. If we leave that one in, his ERA is still a pretty nice 2.72.

Heath Bell is getting a fresh start this year and despite his historically awful BABIP, his strikeout and walk rates are just too good to ignore. I’ll stick with my same prediction as last year: I’d be surprised if Heath Bell didn’t become an important fixture in the Padres bullpen.

Don’t worry Cactus and Grapefruit Leagues; you have not been forgotten. 2007 Spring Training stats are now included in the FanGraphs player stats pages. Unfortunately, the stats are very basic. But, at least you can get a feel for how your favorite players are doing.

These will be updated nightly and Spring Training leaderboards should be up sometime tomorrow.

There was an excellent study done by Dave Studeman in the 2007 Hardball Times: Annual that looked at the run value of each event in baseball using linear weights. I thought it might be fun to look at your typical splits by batted ball type instead of by run value:

Type     AB      H     2B    3B     HR    RBI   AVG   SLG    OPS 
FB    43439  11512   3434   483   5127  11734  .265  .720  0.978 
GB    59246  13996   1212    67      0   4300  .236  .259  0.495 
IFFB   5083     15      4     0      0      1  .003  .004  0.007 
LD    26447  19005   4485   402    259   6028  .719  .948  1.663

And a few more stats:

Type      ISO  BABIP   HR/Type      RC   RC/G 
FB       .455   .167    11.47%    8227   6.70 
GB       .023   .236     0.00%    2614   1.44 
IFFB     .001   .003     0.00%       0   0.00 
LD       .229   .716     0.97%   17947  63.62

Clearly line-drives are the cream of the crop. Oddly enough, about 1% of line drives turn out being home runs, which means about 10.5% of all fly balls (including infield fly balls) end up being home runs.

Fly balls are a tricky one because as long as you’re hitting 11.5% of them out of the park, you’re better off hitting them than groundballs. But if you’re hitting them in the park, then it’s a completely different story. Fly-balls that aren’t home runs have a mere .167 batting average compared to groundballs that have a .236 batting average.

Infield fly-balls or pop-ups are completely worthless. Of all 5000 of them in 2006, only 15 landed for hits. Pretty amazing 4 of them were doubles. I’m not sure how that’s even possible. If you’re going to hit pop-ups all day long you’re better of just not swinging the bat and hope for a walk.

Anyway, that’s just a quick look at the aggregates. Not all players hit line-drives, fly balls, and ground balls the same as you’ll soon see. Let’s look at the best and worst fly ball batters first.

Name             AVG    SLG    OPS    ISO  BABIP     RC  HR/FB  RC/27    FB% 
Ryan Howard     .507  1.824  2.309  1.316   .173    122  38.7%   45.1  36.2% 
Travis Hafner   .448  1.425  1.873  0.978   .237     86  27.6%   31.2  40.3% 
Chris Duncan    .418  1.463  1.868  1.045   .133     40  31.9%   26.5  35.2% 
Lance Berkman   .435  1.367  1.780  0.932   .210     85  27.1%   25.1  41.8% 
Jim Thome       .415  1.400  1.803  0.985   .160     77  29.5%   25.0  43.1% 
Manny Ramirez   .406  1.256  1.639  0.850   .194     66  24.8%   20.3  42.0% 
Wilson Betemit  .404  1.096  1.500  0.691   .273     42  18.1%   20.1  36.6% 
Adam LaRoche    .396  1.245  1.624  0.849   .215     67  22.1%   20.0  40.9% 
Preston Wilson  .414  1.103  1.503  0.690   .282     39  17.8%   19.5  26.7% 
Jacque Jones    .388  1.155  1.540  0.767   .213     46  22.1%   19.4  25.5% 
David Ortiz     .366  1.274  1.632  0.909   .119     86  27.4%   18.9  46.8% 
Alex Rodriguez  .385  1.142  1.517  0.757   .202     64  22.4%   18.2  39.6% 
Carlos Beltran  .376  1.194  1.554  0.818   .183     72  22.7%   17.8  46.6% 
Jermaine Dye    .376  1.178  1.540  0.803   .176     68  23.3%   17.7  40.4% 
Derek Jeter     .393  1.056  1.433  0.663   .280     36  15.1%   16.8  18.3% 
Richie Sexson   .366  1.131  1.487  0.765   .192     62  21.0%   16.7  39.9% 
Andruw Jones    .356  1.228  1.564  0.872   .111     63  26.0%   16.2  41.6% 
Nick Johnson    .372  1.047  1.410  0.674   .243     50  16.7%   16.0  35.6% 
Vlad. Guerrero  .377  1.017  1.386  0.640   .243     66  17.3%   15.9  37.2% 
Jason Bay       .371  1.106  1.458  0.735   .219     68  18.4%   15.8  44.0%

On this list, four names really stand out to me: Preston Wilson, Jacque Jones and Derek Jeter. Even though Jeter hit fly-balls an extremely low 18.3% of the time, he really did make the most of them. I’ve written several times about Jacque Jones’ “hidden power”, and clearly when he gets the ball in the air he’s really quite successful. Same goes for Preston Wilson. Let’s have a look at the worst fly-ball batters.

Name             AVG    SLG    OPS    ISO  BABIP     RC  HR/FB  RC/27    FB% 
D. Eckstein     .123  0.211  0.331  0.088   .107      3   1.7%    0.8  29.1% 
P. Polanco      .119  0.284  0.402  0.165   .086      4   3.6%    1.0  27.9% 
Joey Gathright  .114  0.314  0.417  0.200   .088      1   2.6%    1.0  16.9% 
Jason Kendall   .148  0.235  0.376  0.087   .140      4   0.8%    1.1  25.9% 
Neifi Perez     .133  0.267  0.396  0.133   .114      3   2.2%    1.1  41.0% 
Abraham Nunez   .130  0.296  0.426  0.167   .096      2   3.7%    1.2  23.1% 
So Taguchi      .145  0.303  0.444  0.158   .122      3   2.6%    1.4  30.5% 
Kenny Lofton    .152  0.333  0.483  0.182   .132      7   2.2%    1.6  33.4% 
Nick Punto      .168  0.307  0.467  0.139   .160      5   0.9%    1.6  30.1% 
Jack Wilson     .139  0.391  0.525  0.252   .083      6   5.8%    1.7  30.3% 
Mark Loretta    .167  0.312  0.475  0.145   .144     10   2.6%    1.7  37.6% 
Juan Pierre     .153  0.343  0.496  0.190   .134      7   2.2%    1.7  23.8% 
Alf. Amezaga    .156  0.377  0.530  0.221   .122      5   3.9%    1.9  32.6% 
Yadier Molina   .159  0.373  0.530  0.214   .117      7   4.7%    1.9  39.1% 
Luis Castillo   .163  0.370  0.531  0.207   .135      6   3.2%    1.9  20.8% 
Y. Betancourt   .162  0.372  0.533  0.209   .121      9   4.7%    1.9  35.7% 
Clint Barmes    .173  0.358  0.524  0.185   .141     10   3.6%    2.0  47.9% 
Brian Roberts   .155  0.423  0.573  0.268   .101     11   5.8%    2.0  35.5% 
Aaron Miles     .177  0.367  0.538  0.190   .156      5   2.4%    2.1  24.5% 
Brad Ausmus     .179  0.358  0.533  0.179   .161      6   2.1%    2.1  28.1%

No surprises here really. These guys are not your power hitters and as mentioned before, if you’re not a power hitter, you’re better off hitting groundballs. Maybe Clint Barmes and Neifi Perez are trying to be something they’re not. Moving on to groundballs, here are the best groundball batters:

Name             AVG    SLG    OPS    ISO  BABIP     RC   IFH%  RC/27    GB% 
Rocco Baldelli  .342  0.389  0.732  0.047   .342     19  10.1%    5.2  50.5% 
Carl Crawford   .321  0.366  0.687  0.045   .321     28  10.6%    4.1  52.2% 
Hanley Ramirez  .303  0.376  0.679  0.073   .303     23  10.6%    3.9  43.8% 
Esteban German  .338  0.369  0.708  0.031   .338     13   7.7%    3.8  58.0% 
S. Victorino    .316  0.354  0.671  0.038   .316     16   8.2%    3.8  44.5% 
Wily Mo Pena    .355  0.382  0.737  0.026   .355      8  11.8%    3.7  39.8% 
Ichiro Suzuki   .307  0.316  0.623  0.009   .307     30  13.0%    3.7  50.7% 
Ryan Freel      .312  0.351  0.662  0.039   .312     15  12.3%    3.7  43.9% 
Daniel Uggla    .310  0.330  0.640  0.020   .310     19   9.5%    3.6  41.0% 
Rickie Weeks    .320  0.352  0.672  0.033   .320     12   9.8%    3.5  46.2% 
Ben Broussard   .328  0.351  0.679  0.022   .328     13   3.7%    3.5  40.2% 
Chris Burke     .324  0.353  0.676  0.029   .324     10   5.9%    3.4  36.0% 
Marcus Thames   .273  0.333  0.606  0.061   .273      6   7.6%    3.4  25.7% 
Mike Lamb       .328  0.351  0.679  0.022   .328     12   3.7%    3.2  40.5% 
Y. Betancourt   .303  0.333  0.637  0.030   .303     20   6.8%    3.2  46.4% 
Chris Duffy     .284  0.306  0.590  0.022   .284     11  10.5%    3.2  58.0% 
Alf. Amezaga    .298  0.319  0.617  0.021   .298     12  11.4%    3.1  50.5% 
Mike Cameron    .299  0.344  0.643  0.045   .299     13  12.3%    3.0  37.6% 
G. Matthews     .284  0.321  0.604  0.037   .284     22   7.1%    3.0  51.0% 
Rafael Furcal   .285  0.311  0.596  0.026   .285     21   6.4%    2.9  49.9%

The one name that really stands out for me here is Wily Mo Pena. He just hits the ball hard, so chances are it makes his groundballs just that much more difficult to field. The rest of these guys are pretty much groundball batters, many of them quite fast. And now the worst groundball batters:

Name             AVG    SLG    OPS    ISO  BABIP     RC   IFH%  RC/27    GB% 
Barry Bonds     .135  0.135  0.271  0.000   .135      1   1.0%    0.2  30.3% 
Adam Dunn       .136  0.146  0.282  0.010   .136      1   1.0%    0.2  27.8% 
Bengie Molina   .153  0.153  0.307  0.000   .153      1   2.0%    0.3  38.7% 
Adam Kennedy    .161  0.168  0.329  0.006   .161      2   2.6%    0.3  40.7% 
Yadier Molina   .156  0.181  0.338  0.025   .156      2   3.7%    0.3  42.5% 
Gregg Zaun      .168  0.189  0.358  0.021   .168      1   2.1%    0.3  37.6% 
Phil Nevin      .168  0.192  0.360  0.024   .168      2   4.8%    0.4  42.7% 
Alex Cintron    .157  0.165  0.322  0.009   .157      1   3.5%    0.4  46.0% 
Damian Miller   .173  0.182  0.355  0.009   .173      1   5.5%    0.4  44.2% 
Dd. Navarro     .171  0.184  0.355  0.013   .171      1   4.0%    0.4  35.0% 
B. Schneider    .172  0.172  0.344  0.000   .172      2   3.1%    0.4  47.3% 
Brad Ausmus     .183  0.198  0.381  0.015   .183      3   4.1%    0.4  53.2% 
Jason Giambi    .171  0.200  0.371  0.029   .171      2   2.9%    0.5  30.3% 
Adr. Gonzalez   .194  0.219  0.413  0.025   .194      3   1.0%    0.5  43.8% 
Khalil Greene   .204  0.239  0.442  0.035   .204      2   0.9%    0.5  34.6% 
Kevin Millar    .189  0.220  0.409  0.031   .189      2   3.9%    0.5  35.5% 
Russell Martin  .187  0.192  0.379  0.005   .187      3   2.2%    0.5  50.4% 
Mike Lowell     .194  0.230  0.423  0.036   .194      4   5.6%    0.6  37.8% 
Brian Giles     .183  0.188  0.372  0.005   .183      4   4.1%    0.6  39.8% 
Eric Chavez     .212  0.232  0.444  0.020   .212      3   2.7%    0.6  38.6%

It’s not often you find out that Barry Bonds is the worst at something. All in all, I find this a rather bizarre mix of players and I’m really not sure what to make of it. Let’s look at the best line-drive batters:

Name             AVG    SLG    OPS    ISO  BABIP     RC  HR/LD  RC/27    LD% 
Eric Hinske     .875  1.188  2.063  0.313   .875     33   0.0%  224.4  16.2% 
J.D. Drew       .865  1.216  2.081  0.351   .865     78   0.0%  210.2  18.8% 
Wily Mo Pena    .872  1.179  2.029  0.308   .868     40   2.5%  177.9  20.9% 
Mig. Cabrera    .842  1.123  1.965  0.281   .841    108   0.9%  161.7  24.2% 
Jason Bay       .848  1.045  1.894  0.197   .844     59   3.0%  158.1  15.6% 
Austin Kearns   .833  1.154  1.987  0.321   .831     75   1.3%  155.8  19.2% 
Brad Hawpe      .829  1.134  1.963  0.305   .829     77   0.0%  148.7  21.7% 
G. Sizemore     .810  1.170  1.980  0.360   .806     95   2.0%  134.7  19.8% 
Scott Spiezio   .805  1.171  1.976  0.366   .800     39   2.4%  130.4  19.9% 
Russ. Martin    .817  1.169  1.975  0.352   .814     67   1.4%  129.8  19.9% 
Matt Stairs     .826  1.000  1.826  0.174   .826     38   0.0%  128.3  17.4% 
Jay Gibbons     .809  1.085  1.894  0.277   .809     41   0.0%  123.7  15.9% 
Reed Johnson    .808  1.055  1.863  0.247   .808     62   0.0%  120.0  19.7% 
G. Matthews     .788  1.192  1.980  0.404   .781     93   3.0%  119.5  18.8% 
Jose Valentin   .796  1.122  1.918  0.327   .796     44   0.0%  118.2  15.6% 
Chase Utley     .804  1.118  1.914  0.314   .798     91   2.9%  117.2  19.5% 
Todd Helton     .807  1.088  1.888  0.281   .805    100   0.9%  116.9  23.6% 
Matt Holliday   .788  1.144  1.933  0.356   .780     94   3.9%  115.2  21.0% 
David Wright    .824  1.033  1.839  0.209   .822     77   1.1%  115.0  19.5% 
Bill Hall       .789  1.225  2.003  0.437   .783     68   2.8%  114.9  19.2%

Obviously there are a lot of solid to excellent players on this list, but nothing especially noteworthy. And last but not least, the worst line-drive batters:

Name             AVG    SLG    OPS    ISO  BABIP     RC  HR/LD  RC/27    LD% 
Cliff Floyd     .540  0.740  1.280  0.200   .540     20   0.0%   23.5  18.1% 
David Bell      .600  0.730  1.313  0.130   .596     43   1.0%   27.3  23.4% 
Endy Chavez     .593  0.780  1.373  0.186   .593     27   0.0%   28.6  20.1% 
Juan Uribe      .585  0.862  1.437  0.277   .578     32   1.5%   29.5  17.2% 
Rondell White   .600  0.767  1.357  0.167   .593     27   1.6%   29.7  21.3% 
Alf. Amezaga    .617  0.702  1.319  0.085   .617     20   0.0%   30.5  16.9% 
Ronny Cedeno    .594  0.841  1.435  0.246   .594     34   0.0%   33.2  16.4% 
Chone Figgins   .627  0.745  1.373  0.118   .627     48   0.0%   33.9  20.7% 
Carl Crawford   .609  0.848  1.450  0.239   .609     47   0.0%   34.5  18.3% 
Moises Alou     .594  0.906  1.500  0.313   .587     34   1.6%   35.8  20.1% 
Damon Hollins   .600  0.940  1.528  0.340   .583     28   3.9%   35.9  19.0% 
Willy Taveras   .620  0.817  1.437  0.197   .620     36   0.0%   35.9  17.5% 
B. Phillips     .635  0.800  1.428  0.165   .635     43   0.0%   36.3  19.2% 
Chris Duncan    .622  0.822  1.444  0.200   .622     23   0.0%   36.6  21.1% 
Jason Kendall   .642  0.758  1.400  0.117   .642     58   0.0%   36.7  23.9% 
Aaron Boone     .639  0.778  1.417  0.139   .639     36   0.0%   37.2  24.7% 
W. Betemit      .643  0.857  1.478  0.214   .636     30   1.7%   37.4  21.3% 
Cory Sullivan   .651  0.831  1.459  0.181   .651     44   0.0%   37.4  31.5% 
Joey Gathright  .622  0.844  1.467  0.222   .622     24   0.0%   37.6  16.2% 
S.Hatteberg     .651  0.779  1.423  0.128   .651     43   0.0%   37.9  20.8%

Line-drive percentage will fluctuate from year to year, but I wonder if how a player hits line-drives changes much from year to year. I suppose you could ask that question for any of the batted ball types. When I get the data I’ll be sure to take a look at that, but just thinking off the top of my head, I’ll bet the fly-balls and groundballs remain fairly constant, while line-drives do not.

Furthermore, at some point this season, we’re hoping to have batted ball splits available for all players for 2002 onward.

Just thought some of you might be interested in an article I did for SI.com about the four different projection systems available on FanGraphs.

It looks at which players the systems are in agreement with and which one’s they’re at odds on using OPS and ERA.

“Everyone expects [Ryan Howard] to be very good, but there’s certainly some question about how great he’ll actually be. At least CHONE and ZiPS seem to think Carlos Delgado is in for a rather steep decline next year, while the other two think he’ll keep chugging along at his .900+ OPS.”

Anyway, take a look if you get a chance; I thought some of the differences and similarities were quite interesting. You can find the article here.