Freaky Batting Leaderboards

Two days ago, I wrote an article listing the pitching leaders for a number of (hopefully) insightful stats that we track here at The Hardball Times. Today, the focus is on batters.

Once again, I’ll take advantage of Baseball Info Solutions’ batted ball types to pinpoint the causes of this year’s batting successes and failures. To qualify for the leaderboards, a batter must have at least 125 plate appearances as of last Friday, which marked the end of the first third of the season. There are 240 batters with this many plate appearances—eight per major league team.

I’ve listed four stats below, starting with how often batted balls fall in for hits—otherwise known as…

Batting Average on Balls in Play

If you track batting average in your fantasy league, you’re probably aware of how unpredictable it can be—as in, “Nook Logan is out-hitting Ichiro .319 to .309!” And how great a name is Nook Logan, anyway?

Sometimes balls fall in for hits, and sometimes they don’t. Every time I see a batter line into an out, I think batting average must be sheer luck. But batters obviously do have legitimate differences in batting average, even in something called Batting Average on Balls in Play (BABIP), which is simply the number of batted balls that fall in for hits, not including home runs.

A couple of weeks ago, I found a formula that factors in line drives and fly balls to predict BABIP. If you compare actual BABIP to this Expected BABIP, you can get a feel for which batters have been good, bad, lucky or unlucky.

Here’s a list of the batters whose actual BABIPs most exceed their expected BABIPs—in other words, the lucky ones. For perspective, I’ve included each batter’s plate appearances and runs created as of last Friday:

Player           Team     PA       RC    BABIP  xBABIP    Dif
Sanchez A.       TB       132      18    .411    .288    .123
Lee D.           CHN      235      66    .404    .306    .098
Guillen C.       DET      170      27    .422    .326    .096
Inge B.          DET      232      40    .389    .299    .090
Johnson N.       WAS      231      49    .393    .316    .077
Burrell P.       PHI      207      38    .367    .290    .076
Mackowiak R.     PIT      155      28    .375    .301    .074
Cabrera M.       FLA      214      39    .384    .314    .070
Hall B.          MIL      144      24    .333    .265    .068
Catalanotto      TOR      140      18    .355    .289    .067
Wilkerson B.     WAS      231      37    .378    .311    .066
Edmonds J.       STL      203      38    .346    .284    .063
Logan N.         DET      161      20    .365    .310    .055
Abreu B.         PHI      241      52    .379    .324    .055
Anderson G.      LAA      209      32    .329    .275    .054

Alex Sanchez was near the top of this list last year too, primarily because of his bunting skills. Bunting, speed and infield hits have also been key to Logan’s success. I wouldn’t call either one lucky. But many of the other players on this list will see their batting averages fall over the next couple of months as their BABIPs regress to expectations.

I’m not saying Derrek Lee isn’t having a monster year. I’m just saying that I don’t expect him to bat .380 for the year. On the other hand, I expected Ichiro to be near the top of this list, based on his uncanny ability with the bat. His actual BABIP, however, is pretty much equal to his expected BABIP (.340 vs. .345). I’ll be surprised if this doesn’t change.

Here a list of the unlucky at bat:

Player         Team         PA       RC    BABIP  xBABIP    Dif
Boone A.       CLE          172       4    .169    .294   -.124
Hardy J.       MIL          139      10    .190    .289   -.099
Valdez W.      SEA          133       6    .248    .340   -.092
Guzman C.      WAS          201       2    .222    .314   -.091
Lamb M.        HOU          141      16    .229    .316   -.087
Martinez V.    CLE          189      13    .208    .288   -.080
Mientkiewicz   NYN          185      12    .205    .276   -.071
Piazza M.      NYN          189      24    .257    .324   -.067
Thome J.       PHI          142      16    .284    .349   -.066
Pierre J.      FLA          219      17    .277    .342   -.065
Dye J.         CHA          191      20    .250    .315   -.065
Konerko P.     CHA          221      27    .229    .293   -.064
Lowell M.      FLA          187      15    .224    .287   -.063
Polanco P.     PHI          160      20    .309    .371   -.062
Kearns A.      CIN          182      21    .299    .360   -.061

Some of the worst players in the first half of the season are on this list, such as Aaron Boone and Cristian Guzman. But Placido Polanco was also on this list in the first half of last year, and he went nuts in the second half (and he appears to even have some upside this year).

On the other hand, Mike Piazza was on this list last year too, because he’s just so gosh darn slow; don’t bet on Mikey or some of the other slower players improving their BABIP significantly the second half of the year. But there is just no way Juan Pierre will stay on this list.

As you can tell, one of the ways I can improve this analysis is by including some sort of speed indicator in expected BABIP. I’ll keep working on it.

Polanco, by the way, has the second-highest expected BABIP in the majors (.371). The highest mark belongs to little Nicky Punto of the Twins, at .377.

Home Runs Per Outfield Fly

As discussed in our pitching article, about 11% of outfield fly balls are hit for home runs. Although most established major league pitchers will regress to the mean of 11% over time, batters do have legitimate differences in their home run rates. Here’s a list of the batters who have hit the most outfield flies for home runs (adjusted for ballpark) so far this year, along with their Ground ball/Fly ball Ratio and Isolated Power (SLG minus BA):

Player         Team        PA   RC   HR/F     G/F    ISO
Alou M.        SF         157   25   0.32     1.2   .248
Sexson R.      SEA        206   42   0.29     0.8   .277
Rodriguez A.   NYA        236   48   0.28     1.1   .308
Klesko R.      SD         207   30   0.28     1.0   .224
Young D.       DET        205   26   0.27     1.7   .223
Varitek J.     BOS        185   28   0.27     1.2   .244
Martinez T.    NYA        168   28   0.27     1.1   .280
Nevin P.       SD         226   31   0.27     1.3   .168
Floyd C.       NYN        197   31   0.26     1.0   .247
Pujols A.      STL        243   52   0.26     1.2   .255
Delgado C.     FLA        220   38   0.25     0.9   .265
Stairs M.      KC         150   22   0.24     1.0   .252
Edmonds J.     STL        203   38   0.24     0.8   .267
Peralta J.     CLE        137   17   0.24     1.5   .248
Ensberg M.     HOU        201   30   0.24     1.0   .229

I included the Ground ball/Fly ball Ratio of each batter on the list because if a player hits a lot of fly balls for home runs, you want him to be a fly ball hitter. Most of these players are fly ball hitters, though Dmitri Young has got to get more loft on the ball. Meanwhile, Jhonny Peralta???

When I looked at the players with the lowest HR/F ratios, I found a lot of guys at .000, because they haven’t hit any home runs. So I compiled a slightly different list, which only includes players with a G/F ratio below the general major league average of 1.25.

In other words, here is a list of fly ball hitters who aren’t hitting many fly balls for home runs. This is not a formula for success:

Player         Team       PA    RC   HR/F     G/F    ISO
Loretta M.     SD         184   28   0.00     1.2   .044
Lee T.         TB         127   16   0.00     0.9   .088
Bell D.        PHI        207   19   0.02     1.1   .075
Hairston Jr.   CHN        168   19   0.02     1.0   .099
Ellis M.       OAK        139   17   0.03     1.1   .088
Cirillo J.     MIL        133   18   0.03     1.2   .118
Estrada J.     ATL        175   22   0.04     0.8   .131
Millar K.      BOS        208   19   0.04     1.0   .083
Lowell M.      FLA        187   15   0.04     0.6   .124
Scutaro M.     OAK        181   18   0.04     1.1   .119
Wilkerson B.   WAS        231   37   0.05     0.6   .172
Alfonzo E.     SF         204   35   0.05     0.9   .110
Michaels J.    PHI        125   16   0.05     1.0   .107
Cabrera O.     LAA        217   21   0.05     1.0   .110
Ledee R.       LAN        140   18   0.06     0.7   .143

Mike Lowell is just having a terrible year, isn’t he? He’s on both this list and the unluckiest BABIP list.

Clutch Hitting

I don’t hate RBI as much as I hate saves, but I ignore them just the same. Most of the time, I couldn’t tell you the league leader in either category, though it recently came to my attention that Carlos Lee is leading the majors in RBI. I was surprised by this, so I did a little digging. Want to know why Lee leads the majors in RBI, at least as of the time I’m writing this article?

As your answer, here’s a list of the batters with the most at-bats with runners in scoring position (second third base), along with each player’s slugging percentage. I included SLG because you want to have your best sluggers at bat with runners in scoring position.

Player         Team       PA     RC  AB/RSP    %     SLG
Lee C.         MIL        238   42      76    35%   .526
Rodriguez A.   NYA        236   48      70    35%   .621
Renteria E.    BOS        220   23      68    33%   .395
Bell D.        PHI        207   19      68    37%   .339
Burnitz J.     CHN        225   31      66    32%   .451
Jones A.       ATL        221   22      66    33%   .505
Chavez E.      OAK        233   22      65    31%   .347
Lugo J.        TB         231   34      64    30%   .363
Ramirez A.     CHN        207   26      64    34%   .489
Feliz P.       SF         205   21      63    33%   .461
Tejada M.      BAL        238   46      62    28%   .611
Nevin P.       SD         226   31      61    29%   .442
Beltre A.      SEA        216   23      61    30%   .354
Mora M.        BAL        242   38      59    27%   .491
Ortiz D.       BOS        240   41      59    29%   .563

Yes, Carlos Lee is at the top of the list, which is what happens when you have 2005′s Brady Clark and Lyle Overbay batting in front of you. That’s why he leads the majors in RBI. In the meantime, who leads the Phillies in at bats with runners in scoring position? David Bell, he of the .339 Slugging Percentage. This needs to change for the Phillies’ offense to turn around.

Most sabermetricians ignore clutch statistics, because they tend to be random and unpredictable. But if a player hits in the clutch, he has helped his team, whether or not he’s likely to do it again. So it’s still good to know which players have delivered the most when it means something.

Here’s a clutch stat based on Bill James’s clutch adjustment in runs created. It consists of one point for each hit with RISP above the batter’s overall batting average, plus one point for each home run hit with runners on above the batter’s overall Home Run/At Bat ratio. Got it?

Essentially, this stat measures how often each player delivers more (or fewer) hits and home runs with runners on base—when they count for more. Here’s the list of the leading “clutch” hitters, along with their batting averages with runners in scoring position and the percent of home runs hit with runners on:

Player         Team        PA   RC  BA/RSP    HR%  Cltch
Sexson R.      SEA        206   42    .346    62%    7.6
Encarnacion    FLA        210   40    .388    71%    7.2
Lugo J.        TB         231   34    .391     0%    6.5
Rollins J.     PHI        246   36    .391    40%    5.7
Miles A.       COL        147   20    .481   100%    5.6
Roberts D.     SD         175   31    .464    50%    5.4
Lamb M.        HOU        141   16    .353    50%    5.2
Monroe C.      DET        197   33    .340    71%    5.1
Matheny M.     SF         161   24    .387    60%    5.0
Ramirez M.     BOS        223   37    .304    73%    4.9
Figgins C.     LAA        223   36    .400    33%    4.9
Sheffield G.   NYA        228   50    .354    80%    4.8
Gonzalez A.    FLA        184   27    .386    33%    4.6
Beltran C.     NYN        199   35    .333    86%    4.5
Phillips J.    LAN        168   24    .375    33%    4.4

There are lots of interesting batters on this list, such as Julio Lugo and Jimmy Rollins. And check out Aaron Miles’s clutch stats. As a Mets fan, I keep reading that Carlos Beltran hasn’t really delivered at the level expected of someone with his salary. These commentators might want to compare his clutch stats to the other Mets batters before making their conclusions.

Here are the “unclutchiest” players in the majors, measured the same way:

Player         Team        PA   RC   BA/RSP   HR%   Cltch
Jones A.       ATL        221   22    .167    25%   -9.1
Taveras W.     HOU        205   15    .103     0%   -6.9
Lieberthal M   PHI        155   12    .103     0%   -6.5
Soriano A.     TEX        231   29    .175    43%   -6.4
Patterson C.   CHN        220   22    .229     0%   -6.3
Glaus T.       ARI        221   30    .175    46%   -5.4
Green S.       ARI        221   19    .185    25%   -5.4
Helton T.      COL        223   21    .200     0%   -5.2
Bradley M.     LAN        205   29    .217    30%   -5.1
Adams R.       TOR        148   11    .163     0%   -5.0
Pierre J.      FLA        219   17    .156     0%   -5.0
Delgado C.     FLA        220   38    .235    36%   -4.8
Varitek J.     BOS        185   28    .225    30%   -4.7
Hall T.        TB         153   17    .179    50%   -4.7
Guillen J.     WAS        222   30    .220    30%   -4.6

Andruw Jones is not only at the bottom of this list, he’s at the bottom by a wide margin! For those of you who have watched these players in action throughout the year, I’ll leave it to you to figure out if they’re likely to continue to underperform when it matters more.

The Force

In my May 10 article, I introduced a new “fun stat” called Force, which I defined as LD% plus HR/F (percent of batted balls hit for line drives plus percent of outfield flies that were home runs). It purported to measure how hard each player was whacking the ball.

Even though I said it was a fun stat, I received several e-mails from readers telling me that it wasn’t a legitimate measure for such-and-such a reason and blah, blah, blah. Man, I guess I’m just not allowed to have any fun in this gig.

But I always try to respond positively to my critics (when not totally besieged by them!), so I’ve made a few changes to Force, renaming it “The Force,” as suggested by JC. I mean, where are my marketing people anyway?

I’ve reconfigured The Force to equal:

(LD% times HR/OF) divided by G/F ratio

Now, the line drive and home run factors are multiplicative (in other words, a player has to do both relatively well to get a high score), and players who hit more ground balls will receive lower scores. I also multiplied the outcome by 10 to get a number that sort of looks like slugging percentage. So here’s the list of top 10 players with The Force:

Player         Team        PA   RC   Force
Roberts B.     BAL        235   56    .696
Lee D.         CHN        235   66    .662
Choi H.        LAN        152   20    .635
Sexson R.      SEA        206   42    .599
Konerko P.     CHA        221   27    .568
Dye J.         CHA        191   20    .516
Dunn A.        CIN        218   39    .509
Soriano A.     TEX        231   29    .495
Encarnacion    FLA        210   40    .491
Delgado C.     FLA        220   38    .466
Lee C.         MIL        238   42    .456
Utley C.       PHI        148   23    .453
Varitek J.     BOS        185   28    .443
Byrnes E.      OAK        153   18    .443
Ensberg M.     HOU        201   30    .437

Obviously, a lot of good players have The Force. In fact, it turns out that this version of The Force is a reasonably good predictor of Isolated Power (with an R squared of .70). So, for my last two lists, here are the batters whose ISOs most exceed their expected ISOs (based on The Force). In other words, these are the players who probably won’t slug as well the rest of the year:

Player         Team        PA   RC     ISO   xISO   Diff
Peralta J.     CLE        137   17    .248   .151   .097
Lopez F.       CIN        167   24    .253   .167   .086
Mench K.       TEX        177   27    .294   .209   .085
Rodriguez A.   NYA        236   48    .308   .224   .084
Stairs M.      KC         150   22    .252   .170   .082
Gibbons J.     BAL        185   28    .273   .193   .080
Jones C.       ATL        185   32    .237   .160   .077
Hall B.        MIL        144   24    .216   .140   .076
Tejada M.      BAL        238   46    .285   .220   .065
Martinez T.    NYA        168   28    .280   .216   .064
Biggio C.      HOU        207   34    .221   .159   .062
Dunn A.        CIN        218   39    .335   .273   .062
Guerrero V.    LAA        166   27    .217   .159   .058
Sanders R.     STL        169   22    .242   .187   .055
Ellison J.     SF         142   22    .192   .138   .055

Ah. Jhonny Peralta.

Here’s the other list—players most likely to slug better the rest of the season. You will notice sabermetric favorite Hee Seop Choi at the tippy top:

Player         Team       PA    RC     ISO   xISO   Diff
Choi H.        LAN        152   20    .183   .319  -.135
Giambi J.      NYA        153   20    .121   .206  -.086
Byrnes E.      OAK        153   18    .164   .250  -.085
Burroughs S.   SD         169   17    .027   .102  -.075
LaRue J.       CIN        145   18    .112   .180  -.068
Roberts B.     BAL        235   56    .275   .341  -.066
Encarnacion    FLA        210   40    .203   .267  -.064
Konerko P.     CHA        221   27    .234   .294  -.060
Womack T.      NYA        209   20    .031   .090  -.059
Podsednik S.   CHA        203   27    .034   .090  -.056
Carroll J.     WAS        139   11    .034   .090  -.056
Patterson C.   CHN        220   22    .175   .229  -.054
Thome J.       PHI        142   16    .099   .152  -.053
McPherson D.   LAA        134   15    .194   .244  -.051
Guzman C.      WAS        201    2    .048   .098  -.050

You know, I may have ruined a perfectly good fun stat by using it like this. Hey, at least I’m having fun with it. And let me say again that the math itself is meaningless except to the extent that it correlates with ISO.

Thanks for reading; I’ll be back with a “Ten Things” column next week.

References & Resources
Many thanks to Jeff Angus of The Seattle Times, for his nice review of our batted ball analyses.

One reader wrote in to let me know that Carlos Lee has batted ahead of Lyle Overbay most of the season. Sorry about the misinformation — though it doesn’t change the fact that Lee has had the most RBI opportunities in the majors so far this year.

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