When I started playing fantasy baseball there were no advanced metrics such as wOBA, xFIP, and SIERA. HGAB and HBAB were the only two things we went by: He’s Good at Baseball and He’s Bad at Baseball. It’s great that all these stats are out there; we should all consider ourselves fortunate. Of all the stats the one that intrigues me is BABIP because when you read about it, it always says that part of it is luck – the one intangible that can throw a wrench into any analysis.
I thought about what went into a good BABIP and logically thought that if you hit line drives, it’s probably better than hitting fly balls. Being that I’m new at this writing thing, my research showed me that this was written about over and over and my logic was indeed correct. Since this wasn’t a dead end I decided to look into a few things. First was if BABIP was following it’s usual pattern this year, and secondly can we predict whether or not some under achieving players will rebound based upon BABIP.
Taking 30 players randomly, 10 each from the top 50, middle 50, and bottom 50 in BABIP as of May 17th, I compared BABIP to line drive, ground ball and fly ball percentages for each of these players. As has been found to be true in the past there was correlation with a high BABIP and low FB%, low BABIP and high FB%, high BABIP and high LD%, and low BABIP and low LD%. There was little correlation to GB%. Ground balls have the most variance as there are hard hit ones, softly hit ones, those that are hit at someone, and those that find a hole. This must be where the “luck” comes into play. Very few fly balls “luck” into hits.
Let’s take a look at 4 players that fantasy owners invested a fair amount of ADP or auction dollars to who are underperforming, and see if we can use BABIP and the types of batted balls to predict whether these players will rebound.
Travis Shaw is currently on the IL which gave the Brewers a reason to call up hot prospect and AFL MVP Keston Hiura. Shaw has been horrendous, and there is speculation that an injury was hampering his production. His batting average sits at .169 with a BABIP of .222. Last year he had a BABIP of .242 and his lifetime number is .282. Although not a part of the BABIP formula, Shaw’s K% is way up this year at 32.5% from an average of 22.9% and last year’s 18.4%. Looking at his batted ball percentages – they are very similar to last year’s, and his high FB and low LD percentage predict a low BABIP.
There is very little variance in this year’s numbers compared to last year and his career. In Shaw’s case, it appears the injury and lack of contact are more of an issue and you shouldn’t expect “luck” or a “return to his mean”. I would not expect much when he returns, and hopefully if you’re an owner, you spent some FAAB on Hiura.
Matt Carpenter is off to a slow start that is similar to what he did in 2018. His BABIP last year ended up at .314 – after a horrific start he turned things around in the middle of May. This year it’s .246 with very similar numbers across the board as compared to last year. He lowered his GB% last year from a career average of 33.2% to 26.4 in 2018 and 25.6 thus far this year. This would correlate to a better BABIP if the shift went to hitting line drives, but it was mostly an increase in fly balls.
Carpenter is still making contact, so we can expect him to trend more towards his historic average of .291 as long as his FB% doesn’t continue to rise.
The Yasiel Puig hype train was chugging along during spring training. Most thought that he would have a breakout season hitting in the friendly confines of the Great American Ballpark. His BABIP is .235 – last year it was .286 and his career average was .313. This year’s FB% is at a career high (41.3%), up from last year’s 36.1%. He only has 7 HR so the increase in fly balls hasn’t translated into many more dingers. He has lowered his GB% from a career average of 47.3% to 36.4% and upped his LD% by about 5%.
Puig has been showing signs of breaking out of his slump. He needs to continue hitting line drives and join the HR parade a little more often. I’m expecting him to improve from this point, but keep an eye on his FB%. If it gets any higher, you can start looking for a trade partner.
Last to ponder is first rounder Jose Ramirez. If it weren’t for his stolen bases (and resume) Ramirez would be waiver wire fodder. Ramirez’s lifetime BABIP is .286. Last year it was .252 and now it’s down to .204. Following the downward trend in BABIP is a rise in FB% to 47.9%. His LD% has remained stable while his GB% has dropped to 31.4%. The rise in his FB% of 8% isn’t enough to explain an 82 point drop in BABIP. I looked at his other peripherals and the one thing that stuck out is that he’s hitting the ball to the opposite field more (+5.7%) and pulling the ball much less (-9%).
Ramirez is a tough one to figure out. Considering his poor second half last year and his slow start this year it is hard to think that he’s going to have a massive improvement going forward. It’s hard to give up on a first round pick. Be a little more patient as his stolen bases are giving him some value, and hope he finds his first half 2018 stroke again.
The one consistent thing we see here is that hitting a lot of fly balls isn’t good unless they are going over the fence. We have seen an increase in players at this point in the season with 8 or more home runs, from 55 last year to 70 this year, and none of these highly touted players are in that group.
BABIP is a way to evaluate players, but because of the “luck” involved and no clear cut way to evaluate why someone’s BABIP is higher or lower than normal, I don’t see how you can expect that player’s BABIP to “get back to it’s norm”. If players today are hitting more fly balls you should expect lower a BABIP in general. And because of this, is BABIP going to become less useful or will we have to look at the number a little differently?
All stats courtesy of FanGraphs as of May 17th and graphs by my daughter, Donna.
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