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So things didn’t start out well this year and a lot of the players you were relying on to keep you in contention have turned into duds. Now, just over 1/3 of the way through the season you realize there is no way in hell your team can get back in the race with the players you drafted.

What can you do? You could start with targeted trades that manipulate the scoring categories and maximize the potential of your team. This can help, but in and of itself, it is not really making your team better and can only get you so far with it.

You need to find a way to actually add net value to your team. Instead of rearranging value to maximize points, you need to flat out get better players than you trade away. Unless you play in a league filled with idiots, this is not so easy. We need a tool that can help us find players who will outproduce what they’ve done so far this season; otherwise known as Buy-Low Hitters.

Batting Average on Balls in Play (BABIP) is one of my favorite tools to identify buy-low hitters, but way too many people use it in the wrong way.

Why Use BABIP?

BABIP is widely acknowledged as a solid indicator of the amount of luck a hitter has benefited (or not) from. But BABIP is really only related to batting average. So why so much weight put on BABIP. Honestly there shouldn’t be, but a player’s perceived value is affected greatly by batting average. So while a player like Ryan Zimmerman or Mookie Betts might have plenty of other positive stats, they’re still seen as disappointments. Also, while BABIP’s main effect is on batting average, a BABIP correction is also going to positively effect runs scored, RBIs and even stolen bases. The only scoring category (traditional 5 X 5) that BABIP will have no effect on is home runs. So BABIP, while limited, still offers value in finding hitters who have performed better than their stats would indicate.

Using BABIP the Right Way

As we’ve discussed BABIP can be of help in finding buy-low hitters, but not by looking at just this year’s results. Different players will have a wide range of BABIP baselines. A speedy left-handed slap hitter is going to have a higher BABIP than a slow-footed right-handed power hitter who hits a ton of fly balls. In order to determine whether a player has been the victim of unfortunate BABIP, we need to compare it to their career history. This is what I call BABIP Differential.

My first step was to find the BABIP numbers for every hitter with over 70 plate appearances. Why 70? It’s just the line I drew where I thought I could grab most every hitter that has gotten substantial playing time. Then I found out their BABIP for the previous five seasons (Thank you FanGraphs).  I subtracted each player’s 2015 BABIP from their 5-year BABIP to arrive at their BABIP differential.

Because BABIP alone doesn’t tell the complete story, I also included line drive percentage (LD%) for the same time periods. After all, a lower BABIP might not be entirely bad luck if a player is hitting substantially fewer line drives.

I set the cutoff at -.030 or higher in order for me to consider a player a potential buy-low hitter. I also got rid of most hitters who didn’t have enough of a five-year profile to really use as a baseline. I did leave Mookie Betts in there because I think his 2015 BABIP is absurdly low for a hitter with his skill set. I also left players like Mike Trount and Buster Posey on here even though I doubt anyone is going to sell low. It’s still interesting to see where their numbers could be.

Check below the table for a deeper look at a few of the players.

22 Players to Consider as Buy-Low Hitters

Name
5-Year BABIP
2015 BABIP
BABIP Diff
5-Year LD%
2015 LD%
2015 AVG
Ryan Zimmerman
.321
.232
-.089
18.7%
16.2%
.221
Steve Pearce
.301
.216
-.085
18.0%
21.3%
.183
Chase Utley
.286
.209
-.077
20.0%
18.0%
.198
Carlos Gonzalez
.349
.275
-.074
19.9%
23.1%
.227
Melky Cabrera
.326
.253
-.073
20.8%
19.1%
.236
Mookie Betts
.327
.255
-.072
20.9%
19.0%
.238
David Ortiz
.305
.235
-.070
20.1%
21.4%
.227
Starling Marte
.363
.294
-.069
22.0%
24.1%
.254
Adam Eaton
.333
.269
-.064
18.9%
19.5%
.234
Leonys Martin
.325
.270
-.055
21.7%
14.7%
.230
Albert Pujols
.277
.226
-.051
18.3%
17.0%
.258
Mike Trout
.361
.310
-.051
21.5%
24.2%
.289
Hanley Ramirez
.314
.263
-.051
18.5%
21.4%
.259
Jose Abreu
.356
.306
-.050
23.3%
21.2%
.286
Elvis Andrus
.316
.267
-.049
21.2%
24.6%
.238
Jimmy Rollins
.270
.222
-.048
20.0%
18.8%
.211
Dexter Fowler
.350
.302
-.048
23.0%
19.1%
.235
Robinson Cano
.326
.280
-.046
23.1%
23.4%
.244
Buster Posey
.328
.283
-.045
21.7%
22.3%
.285
Edwin Encarnacion
.262
.220
-.042
18.6%
16.3%
.216
Pablo Sandoval
.302
.261
-.041
19.7%
20.4%
.244
Alexei Ramirez
.296
.260
-.036
20.0%
19.1%
.226

Steve Pearce, 1B/2B/OF, Baltimore Orioles

Did you happen to notice that 2B in his position eligibility above? That could be huge. I don’t think anyone expected Pearce to replicate his 2015 season, but he’s a lot better than his current .183 average. He’s hitting more line drives and grounders than last year, so the average should be on the way up. If you’ve got a hole at second base, Pearce should come cheap and could deliver some good power numbers from here on out.

Chase Utley, 2B, Philadelphia Phillies

Utley is too good a hitter to keep doing what he’s doing, but he’s just an NL-only play at this point. At 36 years old that 18.0 LD% is real cause for concern. There’s probably a little bounce left, but not high enough to take you anywhere in mixed leagues.

Carlos Gonzalez, OF, Colorado Rockies

It’s been hard finding much room for optimism with Cargo. His lackluster 2015 numbers look eerily similar to what he did in an injury-filled 2014 season. Even his BABIP is similar. There is one major difference though that makes me think he may bounce back. Gonzalez has a 23.1 LD% this season, a number that is 7.8 percent better than last year and if it holds would be the second highest of his career. It’s not a given that Gonzalez returns to his previous heights, but he does offer proven upside you won’t find easily elsewhere. Has his value fallen far enough to take that risk? If you’re in the bottom third of the standings I say go ahead and make the play.

Mookie Betts, OF, Boston Red Sox

Betts does not have enough career plate appearance for his BABIP Differential to mean much. I include him here because that .255 BABIP is not gonna stay there. Other than batting average Betts is doing pretty much everything we thought he would. He’s on pace for 13-15 HRs and 30 SBs. Put him on base more with a BABIP correction and that runs scored total will start popping. If the Betts owner in your league is starting to sour on him, help him out and make an offer paying for what Betts has done so far. You’ll gain value in the end.

Albert Pujols, 1B, Los Angeles Angels

One thing jumped out at me when I checked out Pujols’ peripherals on FanGraphs. Despite being widely regarded as one of baseball’s best hitters, Pujols has not had a BABIP above .300 since 2008. So while his current .226 BABIP will likely rise, don’t expect a drastic change. In fact a career-low LD% and a somewhat fluky 18.9 HR/FB% has me thinking Pujols might actually be in sell-high territory, with Fantasy owners respecting him maybe too much.

Robinson Cano, 2B, Seattle Mariners

Cano’s numbers are an enigma wrapped in a mystery wrapped in… oh you get the idea. His 16.9 strikeout percentage is a career-worst by a wide margin, but his LD% is actually better than what he put up in 2014. A 4.5 HR/FB% seems a bit fluky, but a return to his Yankee heyday is not gonna happen. In the end, I’m on board for a Cano rebound; I’m just not sure he’s a real difference maker these days. Send your feelers out, but make sure you get him cheap enough to leave room for profit.

David Ortiz, DH, Boston Red Sox

The peripherals seem to indicate that Ortiz’s average will bounce back. The problem is we didn’t draft Big Papi for his batting average. Where’s the power. While his LD% is up this season so is his ground ball percentage. At 44.7%, it’s the highest of his career. It pretty much corresponds with an 11.1 HR/FB%; the lowest of his career. His Pull% is also at a career low. All of these seem to indicate a slower bat, something that is a real possibility for a 39-year-old player. Ortiz may rebound a bit, but I’m not sure his current owner will sell low enough for me to take the plunge. Among this list of buy-low hitters, Ortiz offers the least return on investment in my opinion.

Edwin Encarnacion, 1B, TOR

MOst of Encarnacion’s peripherals are within his career norms, but his K% has risen over 10 percent over the last two years. That does concern me a bit, but not many hitters can go on a power tear like EE can. I’m not sure he’s struggled enough for his owners to give up on just yet, but if you can deal for him at current value, one of his home run barrages could do some real damage. That’s the kind of upside you need to turn a season around.

So as you can see, I think BABIP Differential can be a useful tool in identifying buy-low hitters. It just doesn’t tell the whole story. While I think all the players on this list will play better than they have, only some of them can be real difference makers in a mixed league context.

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Doug "RotoDaddy" Anderson

Doug Anderson took on the moniker RotoDaddy with the birth of his son in 2003. He's a veteran of the industry and has been playing Fantasy Baseball for over 20 years. His work has been seen on RotoExperts.com, SI.com, Yahoo, USAToday.com and also in the pages of various Fantasy magazines. He's currently also in charge of aggregation efforts at The Fantasy Sports Network and represents them in the LABR Mixed Experts League.
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