After last night’s Red Sox game 7 victory, I was rather curious to see who would win the ALCS Most Valuable Player award. Without looking at the numbers, I thought it should go to Kevin Youkilis. I thought there was a chance it would go to Manny Ramirez and also a chance it could go to Josh Beckett. When Beckett was announced the winner, I was a little surprised and went to check the numbers.

It turns out that Josh Beckett did lead all players in Win Probability Add (WPA) in the ALCS. In two starts his WPA was .516 wins compared to Youkilis’ .203 wins. Manny Ramirez’s WPA was just slightly below Beckett’s at .483 wins. Jon Papelbon and Hideki Okajima also were also contenders for the WPA title with .467 and .286 wins respectively.

If you look at things just in terms of run production taking the context out of the situation. Youkilis was indeed the most productive player with a Batting Runs Above Average (BRAA) of 9.3 runs. Ramirez came in second with 6.2 runs, while Beckett was the next best with 4.7 runs.

As of today, the Red Sox have the best record in baseball. If you look at their Win Probability numbers, their batting has contributed 4.38 wins, their starting pitchers 1.54 wins and their bullpen 4.08 wins. The bullpen which was considered a big question mark to begin the season has surprisingly been just as valuable as their offense, much in thanks to Boston’s lesser known Japanese import, Hideki Okajima.

For the past two seasons, David Ortiz has racked up more WPA than any other player in baseball by adding an incredible 17 wins to his team. About one-third of the way into this current season, Ortiz has accumulated a mere 1 win, but still leads all Red Sox batters in WPA.

Last season, David Ortiz had 15 hits worth more than .2 wins, not to mention a pair of home runs worth .78 wins and .90 wins. This season he has no hits over the .2 wins mark. That’s not to say he’s not having an excellent season. When you take the context out of his wins using WPA/LI he’s 3rd in baseball with 1.93 wins, but the hits just haven’t been as timely as last season. The huge disparity between his WPA and WPA/LI gives him the 5th worst “Clutch” with -.88 wins.

So who has been getting the big hits for the Red Sox if their previously “clutch” star hasn’t? Let’s take a look:

On May 13th, newcomer Julio Lugo was the catalyst for the biggest play of the season. With 2 outs in the bottom of the 9th, down by 1 and the bases loaded, Lugo singled in the tying run while Erik Hinske scored on an error. The whole thing was worth .718 wins and capped off an incredible 9th inning rally (including a Jason Varitek double worth .343 wins) that overcame a 5 run deficit. At the start of the inning the Sox had a mere .9% chance of winning the game.

In a classic Yankees-Red Sox battle on April 20th, Coco Crisp tripled in two runs to tie the game at 6-6 off Yankees closer Mariano Rivera. This triple was worth .472 wins. Immediately following Crisp’s triple, Alex Cora singled allowing Crisp to score the go ahead and final run of the game. In contrast Cora’s hit was worth .123 wins.

On April 26th, Orioles closer Chris Ray (who also gave up the hit to Lugo on May 13th) gave up a grand slam to Wily Mo Pena which put the Sox up by 3 to win the game. Down by 1 at the time, the home run was worth .43 wins.

Alex Cora on April 19th, in the top of the 9th with 1 out, tripled, allowing Julio Lugo to score the go-ahead run. While not quite as big as Crisp’s triple on the 20th, this one was still worth .373 wins.

Erik Hinske’s two run blast in the 7th inning of a tie game back on May 17th rounds out the top 5 most important Red Sox hits so far this season. Manny Ramirez owns the next two biggest which were both worth juts over .3 wins.

David Ortiz is no where to be seen on this list with his biggest hit worth .197 which came on April 25th in the 7th inning of a tie game. In the 9th inning or later in a game, Ortiz is actually a -.213 wins while in 2006 he was 2.34 wins; far and away the most in baseball.

I’m sure as the season goes on, things will start to even out and there will be some big hits here and there, but fortunately for the Red Sox, they haven’t exactly needed Ortiz to be the savior he’s been the past two seasons.

In today’s Hardball Times, Matthew Carruth did an analysis on extreme groundball pitchers and how they do not really give up more home runs-per-fly ball (HR/FB) than your typical pitcher. There has been some thought that extreme groundball pitchers do tend to give up more HR/FB because they’re only allowing fly balls when they throw a bad pitch, thus making it easier to hit the ball out of the park. Carruth’s analysis even suggests that the opposite might be true, though the correlation was quite weak.

I decided to run a similar analysis using data from 2002 to the present. The average HR/FB rate during that same period is 10.7%. If we look at the 2002-present totals of all pitchers with a groundball percentage (GB%) greater than 55% and more than 100 innings pitched, they have an average HR/FB of 12.2%. That 12.2% is not a weighted average, it’s just a simple average of each qualified pitcher’s HR/FB.

Using the same method, if you look at pitchers with a GB% less than 35%, they have an average HR/FB of 9.9%.

Now I’ll admit this is a much simpler approach than the route Carruth took, but the results seem to be considerably different and I wondered why this would be the case.

First off, if you use my approach with the 20 pitchers Carruth selected in each group, you come to the same conclusions as Carruth did. This leads me to believe the batted ball data from Retrosheet (which Carruth used) and the batted ball data from Baseball Info Solutions don’t quite match up.

Just taking a quick look at the top 10 players, their GB% don’t match. For exampe, Retrosheet has Brandon Webb with a GB% of over 70% and BIS has him at 65%. That’s the first difference.

The second difference is that the time period he used was between 1988 and 2006 where the HR/FB according to Retrosheet was 13.57%. This is considerably different than the HR/FB of 10.7% that Baseball Info Solutions reports between the 2002-present time period. Using the 13.57% for all pitchers over a 18 year period where there’s been some considerable influx in home run totals is probably going to cause some issues as well.

To me it seems there is at least some evidence that extreme groundball pitchers as a group do give up more HR/FB than your typical pitcher. The two most extreme groundball pitchers in the past 5 years have an average HR/FB of 15.5% (Brandon Webb) and 13.1% (Derek Lowe).

The other option is it really has nothing to do with GB% at all (sampling size issue maybe?) and it’s just that some extreme groundball pitchers tend to have higher HR/FB. In their case instead of regressing to the league average, you’d just regress to the player’s actual average; treating it more like you’d treat a batter’s batting average on balls in play (BABIP) than you would a pitcher’s BABIP.

One of the biggest complaints I see about WPA is that it’s not predictive. The mere mention of it’s non-predictability seems to be enough for many to write it off as a mere toy used by some of stats community.

So let’s see how it actually correlates from year to year compared to the stats we all know, like AVG, OBP, SLG, and OPS. I’ll throw in Batting Runs Above Average for fun too.

Looking at the r-squared from 2005 to 2006 for batters with over 300 plate appearances, here’s how WPA stacks up against the regulars:

AVG: .12
WPA: .27
BRAA: .35
OBP: .36
OPS: .36
SLG: .38

Here’s the same deal, 2004 to 2005.

AVG: .14
WPA: .24
OBP: .27
OPS: .30
BRAA: .31
SLG: .33

It’s true, WPA doesn’t correlate as well from year to year as OBP, SLG, or OPS, but it does have some correlation from year to year. In 2004, a players OBP was almost indicative of his 2005 OBP as his 2004 WPA was of his 2005 WPA. Yet, that wasn’t quite the case in 2005 to 2006. BRAA which is calculated by using Run Expectancy on a play-by-play basis (much like WPA uses Win Expectancy), holds its own against the regulars.

Anyway, the point is, let’s stop using the argument that WPA isn’t predictive as a crutch, because it does actually show some correlation from year to year.

In yesterday’s 10-7 victory win against the Orioles, Alex Rodriguez’s game winning grand-slam was the second biggest hit he’s had in the pats 6 years according to Win Probability Added (WPA). It brought his team from a mere 28.8% chance of winning to a complete victory.

In 2006 however, Rodriguez was about as far from being a clutch hitter as you could possibly get. But before we delve into why, let’s get familiar with two stats: REW and OPS Wins. REW is calculated much like WPA, except it uses Run Expectancy (as opposed to Win Expectancy), which doesn’t take the score or inning into account. It does however account for how well a batter does with runners on base. OPS Wins on the other hand is how a player would do in a completely context neutral environment.

Looking at 2006, Rodriguez’s 3.18 OPS Wins and his REW of 3.34 wins are fairly close, but in general he did a little bit better than expected with runners on base. When you take into account the inning and the score (or late and close situations), he accumulated just 1.18 wins. Basically he performed much worse than he should have in high leverage or “clutch” situations. This is measured by a stat called “Clutch” which is the difference between WPA and OPS Wins once leverage adjusted. Rodriguez’s Clutch was -2.16 wins; the third worst among qualified players in 2006.

Last season was the worst season he’s had in the past 5 years in terms of clutch hitting and probably his worst season ever. Yet in his previous two seasons with the Yankees he was actually a clutch hitter with a Clutch of .76 wins in 2004 and .41 wins in 2005.

Since joining the Yankees, he’s still the 9th most valuable player in baseball according to WPA. If we look at just the Yankees batters since 2004, he ranks first in terms of WPA.

Batter                WPA
Alex Rodriguez      11.27
Derek Jeter         10.54
Gary Sheffield       8.91
Jason Giambi         7.61
Hideki Matsui        6.46
Jorge Posada         2.92
Bobby Abreu          1.96
Johnny Damon         1.76
Tony Clark           1.05
Tino Martinez         .77

Whether you like him or not, he has been the most valuable Yankees batter according to WPA the past 3 seasons including the few games played this season. Of course, Mariano Rivera bests him by half-a-win with a WPA of 11.73.

The Nationals just had a great comeback against the Marlins this afternoon. The final game graph (unofficially) looks like this:

The Marlins newly acquired Jorge Julio pretty much blew the entire game for them with a WPA of -.903 wins. The Nationals low point in the game was in the bottom of the 6th with 2 outs when they had a mere 3.7% chance of winning the game.

But let’s draw our attention to one very specific play at the end of the game: the sacrifice bunt when the score was 6-5 in the bottom of the 9th. Before the sacrifice bunt there was a runner on first with no outs. The Nationals at the time had a 34.4% chance of winning. Manny Acta, the Nationals new manager, had Felipe Lopez hit a sacrifice bunt. It was successful, but it didn’t improve their chances of winning the game. Instead of increasing their chances, it actually decreased it by 6% to give the Nationals a 28.8% chance of winning.

If you were watching the game on FanGraphs, you got to see exactly why the following is true:

To quote The Book: “With a non-pitcher at the plate, and a runner on first and no outs, advancing the runner in exchange for an out is a terrible strategy. It significantly reduces the RE in almost any run environment. It also reduces the WE in almost any run environment, even late in a close game.”

Fortunately for Nationals fans (while unfortunate my hopes and dreams), they ended up winning anyway.

After causing a major panic from his March 11th “bombing”, Daisuke Matsuzaka threw quite the gem yesterday. He struck out 7, while allowing only 1 walk and 1 hit in 5 and 2/3’s innings of work against the Pirates. This no doubt gave Red Sox fans that warm fuzzy feeling that was sorely lacking the 10 days in between Daisuke’s starts.

While we learned last week that his March 11th start was fairly typical of high priced pitchers, the 7 strikeouts he recorded yesterday was a rare feat indeed. There were only nine times this spring that a pitcher has struck out seven or more batters:

Ian Snell – Way back on March 6th, Snell threw 3 innings while striking out 7. Snell showed a lot of promise last year and this spring he’s showing why he’ll be the ace of the Pirates pitching staff (even if no one knows who he is).

Rich Harden – On March 15th the oft-injured Harden threw just 3-plus innings and struck out 9. Then he struck out 7 on March 20th in 5 innings. Overall, Harden has struck out 25 batters in a mere 13 innings of work this spring. Please stay healthy this year! There’s nothing I enjoy more than watching the Ks pile up.

Oliver Perez – He matched Harden on March 15th with 9 strikeouts, but it took him 5 innings to do it. He’s having a fine spring and he was dazzling to watch just three years ago. Perhaps he’ll find some of his 2004 magic in the Mets rotation this season.

Aaron Harang – Three days after Harden and Perez fanned 9, so did Harang. His spring has not been so stellar. He’s given up 28 hits which sets his H/9 at a mere 17-something. On the bright side, he’s still striking out a batter-an-inning, and has given up zero walks.

Scott Kazmir – He struck out 7 in five plus innings of work on March 18th. Yet he’s walked 6 in 12-plus innings so far this spring. It will be interesting to see if he can recapture the much improved control he exhibited in 2006.

Brett Myers – He also struck out 7 on March 18th. He’s one of those guys who took the off-season “seriously” by shedding 25 pounds off his frame. He’s mentioned that he’s been a bit “uncomfortable” pitching at his new weight, but the discomfort isn’t showing in his stats.

Josh Beckett – The 2006 home run king struck out 8 on March 20th. He’s only given up a single home run in 16-plus innings this spring. He’s also given up just a single walk while he’s struck out 17 batters.

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!

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.

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.