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.