A couple of months ago I read an article on a lesser known fantasy sports site where the author explained why he was so against the BABIP metric. This article was brought to my attention again recently and I wanted to comment on several points made. As I had said during the now famous sabermetrics vs. gut/scouting debate on the True Gurus Radio Show several weeks ago, the primary reason saber-stats such as BABIP are so hated is really because of a lack of understanding and complete misuse of the metric. So without further ado, let’s take a look at what this article said, with my comments following.

Probably the biggest concern is that there is no direct correlation between a pitcher’s fantasy-relevant stats (ERA/WHIP) and their BABIP, so it serves no purpose unless fantasy leagues use BABIP as a scoring category.

This was the author’s 1st concern about the application of BABIP for fantasy purposes. He is completely misunderstanding the use of the metric if this is truly how he feels. This is very strange since right above he actually defined the term, explained the theory, and even discussed Voros McCracken’s famous work on DIPS. As we’re all well aware, the use of BABIP is to determine which players are most likely to see their ERAs and WHIPs rise or fall depending on whether their BABIP is lower or higher than the league average. And of course there is a correlation between a pitcher’s BABIP and their ERA/WHIP! A pitcher with a low BABIP is obviously more likely to have a lower ERA and WHIP than they “should”, while a high BABIP would signify a higher ERA and WHIP than they “should”. It’s equivalent to saying that GB% serves no purpose to analyze unless fantasy leagues use it as a scoring category.

Pitchers who give up more home runs will also have lower BABIPs, and thus higher ERA’s, just like the effect of walks.

This is just plain wrong. Rather than simply looking at home runs, we’re betting off looking at a pitcher’s FB%. The higher that is, the lower the BABIP since a fly ball falls for a hit less often than a ground ball or a line drive. More HRs allowed by a pitcher doesn’t necessarily mean a higher FB%, and thus lower BABIP, because a low K pitcher will also allow lots of HRs since he allows more raw fly balls. And last, I have no idea where he came up with the notion that more walks lead to a lower BABIP. Was this concluded in some study I’m unaware of? How should a walk affect the frequency a ball falls for a hit when a batter puts the ball in play?

In examining Andruw Jones…

Perhaps Jones is an odd-ball example, but it is clear from major league average stats over the last three years that a rise/fall in BABIP does not have a synergistic relationship with BA, HR or any other fantasy-relevant stats. If one falls, the other could rise, fall, or stay the same. Fantasy analysts need to look at all of the relevant stats, and BABIP alone is probably the least relevant stat to try to gain any insight, or that may be indicative of future performance.

Well of course, no fantasy analyst has ever said that a rise/fall in BABIP alone would be synergistic with batting average, HRs, etc. This is a perfect example of the straw man fallacy as the author argues a point no one is arguing against. A rise in BABIP signifying a rise in batting average would only occur if the hitter’s contact rate and HR/F ratio remained the exact same.

Last year I read a column entitled “Deconstructing Upton” published on ESPN from renowned sabermetrician Ron Shandler of BaseballHQ…In that article, Shandler argued that Justin Upton’s BABIP was abnormally high, meaning “a crash is coming” and he recommended trading him away….At the time of his article, Upton was hitting .339 with 12 HR’s and 13 SB’s (through July 25, 2007, more than half of the season). However, Upton finished the season at .300, 24 HR and 22 SB’s, doubling his HR total in less at-bats for the remainder of the season. Finishing at .300 surely meant that he hit below .300 for the remainder of the year, but nothing near a “crash,” especially in the HR department.

The author obviously meant B.J. Upton, not Justin. I find this quite comical that the author cherry-picked an example of a player that Shandler, and every other fantasy analyst, said would regress in batting average and was actually right about, yet is using this as an example of how the “BABIP theory doesn’t work”. Upton ended up finishing the year with a ridiculous .399 BABIP. Guess what happened this year…Upton is now hitting .263 as his BABIP has regressed to .333, and that has come even with a much improved contact rate. So maybe us BABIP-users were right after all? And just a hint, you’re not going to get anywhere by choosing Ron Shandler as the expert to bash.

If you buy into the fact that hitters (or pitchers) will eventual regress (or increase) towards the mean of a .300 BABIP (as written by Ron Shandler), whereas a .300 BABIP has been stated as the average benchmark to which all players will gravitate towards (with the law of averages), then I guess the carrer BABIP’s of Wade Boggs (.344), Rod Carew (.359) and Ichiro Suzuki (.357) are just abhorations…

More misrepesenting what the studies have shown. Once again, choosing to call out Shandler, the author suggests that we believe a hitter should also regress toward the .300 BABIP league average, just like pitchers. This is totally false as Shandler has actually written that a hitter will establish his own personal level in which his BABIP should revert toward, and typically one should look at the hitter’s previous 3 years to determine this level.

Interestingly, last April of 2007, Bannister posted a similar .243 BABIP, but had an ERA of 4.91. Also, in September/October, he had a “low” BABIP of .253 but had an ERA of 7.30. In fact, the month (August) with his second worse BABIP (.290), he had his second best ERA (2.90). What gives?

Seriously? This is akin to saying that park factors are meaningless because Barry Bonds posted a higher home OPS in every season since 2002. Obviously the above simply tells you that if Bannister had a higher than .253 BABIP when his ERA was 7.30 in Sept/Oct, his ERA would be even higher, all else equal. The author implies that because Bannister had a high ERA with a low BABIP, then that renders BABIP useless as a metric. The author also makes the mistake of assuming we think BABIP is the only metric worth looking at, as if we simply ignore K/9, BB/9, LOB%, HR/F, and GB%. As a reminder: Bannister’s 2008 ERA = 5.37 and BABIP = .320.

In fact, I would be more concerned if a pitcher had a high BABIP (say, higher than the league average of .300), because by THAT thinking, his BABIP should eventually lower (if you trust the law of averages), and that could mean more walks and more home runs along with less singles.

Whaaaaaaaaaat? Where did this idea come from that a high BABIP that regresses toward league average could mean more walks and home runs? One has no affect on the other! A drop in BABIP simply means fewer balls falling for hits, because well, that’s what BABIP tells you (the frequency at which balls in play fall for hits).  

If the statement “one of the core elements is a pitcher dominance over hitters, which we measure using his rate of strikeouts per nine innings (K/9),” is true, then someone please tell me why Chien-Ming Wang managed to post a three-year average ERA of 3.84 and ranked 9th best overall in quality start percentage when he had the 9th worse (lowest) three-year average K/9 rate of 3.84? Okay, he’s the exception, not the rule.

A 61% ground ball rate is your answer, are you happy now?

However, some basic research of the previous three year averages among all pitchers do not necessarily show that groundball pitchers give up less hits either.

You are correct, but once again, no one was arguing with you. Ground balls have been proven to fall for hits less often than line drives, but more often than fly balls, so on average, a ground ball pitcher will have a higher BABIP than a fly ball pitcher.

The other interesting comparison is between ERA and BABIP alone, where pitchers with the lower BABIP have had higher ERA’s. Therefore, if a current pitcher has an abnormally low BABIP, if his BABIP actually does concede to the law of averages over time during a season (which I don’t believe in all the time), it doesn’t necessarily mean that a rising BABIP corresponds with rising ERA or QS%, in fact, the reverse may be true!

I have no idea where he gets this conclusion that pitchers with the lower BABIP have had higher ERAs. And then the author follows that up by making the preposterous claim that a rising BABIP might actually mean a declining ERA. As I said earlier, there are many other metrics that need to be examined, so a rising BABIP could certainly result in a lower ERA, but all else equal, this is just wrong.

Well that wraps up my deconstruction of an article I feel was poorly researched, not backed up by any statistical support, and proved once again that the real reason BABIP and other saber-stats are so criticized is due to a complete lack of understanding and misconceptions about its use. I quoted far more than I expected to, but I just couldn’t possibly pick only a couple of lines to comment on.

Questions, comments, criticisms, praise, expert league invitations? Email me at FBGeneralsMike@gmail.com.