This article originally appeared on RotoBaller.com and was co-authored by Rick Lucks.
Using BABIP to predict a player's batting average is great. Average is a category in many league formats, and every hit is an opportunity to steal a base or score a run. But most owners find the long ball sexier.
Every HR comes with a guaranteed run scored and at least one RBI. Many owners build their teams around power for this reason. Yet fluky HR campaigns can happen just as easily as fluky batting average ones. How do we tell the difference between a legitimate breakout and a fluke?
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HR/FB% measures the percentage of fly balls that leave the park. Like BABIP, the typical league baseline is easy to remember at around 10%. Also like BABIP, an experienced player's personal benchmark in the stat is a better indicator of his future performance than the league average. For example, Giancarlo Stanton is generally regarded as one of the top sluggers in the game today. His HR/FB% was 22.7% in 2016, nearly double the league average rate. If this number regressed to the league average, Stanton wouldn't be very good. However, he has a career rate of 25.4%. Clearly, above average power is something Stanton just does. Last year was actually a down year for him.
Large spikes or dropoffs in HR/FB% are generally temporary, meaning that the stat is usually not predictive of a power breakout. Fantasy owners want to know the next power breakout, so this may be somewhat disappointing. Future power production may be predicted, however, by an increase in fly ball rate, or the percentage of a batter's flies as opposed to liners or grounders. Elite sluggers generally post a fly ball percentage of 40% or higher. Subjected to this test, Stanton had a 43.3% rate in 2016 and a career mark of 40.6%. These rate stats, combined with a consistently above average HR/FB%, make Stanton the player he is.
Stanton doesn't really illustrate the distinction between HR/FB% and FB% because he excels at both. For a predictive illustration, consider Minnesota's Joe Mauer. His HR/FB% last season was a solid 12.8%, suggesting that he should have hit a few bombs for fantasy owners. Yet he managed only 11 big flies in 576 PAs last season. The reason is a tiny 21.3% fly ball rate, a rate too low to do anything with even Stanton's power.
No one thinks Mauer is going to hit for power in 2017, but plenty of people fell for it back in 2010. The year prior, Mauer went bonkers with a .365/.444/.587 line and 28 bombs. His HR/FB% spiked to 20.4% in 2009, but nothing in his history indicated he could maintain a level that high as his previous career best was 10.8% in 2006. Meanwhile, his 29.5 FB% was far too low to expect any real power production moving forward. He received first round attention from fantasy owners, and the Twins gave him an extension they could not really afford. Mauer morphed back into the singles hitter we know today, ruining many 2010 fantasy seasons and saddling the Twins with one of the worst contracts in MLB.
If you're looking for the 2017 version of 2010 Mauer, Christian Yelich (23.6% HR/FB%, 20 FB%), Eric Hosmer (21.4% HR/FB%, 24.7 FB%), and Ryan Braun (28.8 HR/FB%, 25.1 FB%) all seem like strong candidates for power regression. It is also worth noting that the league as a whole managed a 12.8 HR/FB% last season, an elevated figure that could mean significantly fewer dingers in the 2017 season if it regresses to normal.
HR/FB% is considered the BABIP of power because it can be used to evaluate whether a given player is outperforming his true talent level. The league average usually hovers around 10%, and a given player's past performance is a better indicator of future performance than the generic league baseline. A player with a large spike or drop off in HR/FB should be expected to return to his established baseline moving forward. Ballpark factors or a major change in offensive approach may permanently alter HR/FB%, but in general raw fly ball percentage is a better tool to identify potential power breakouts. This may seem to indicate that batters want to hit nothing but flies, but that is not always the case. We'll look at why in Part 3 of this series, batted ball distribution.