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Using Sabermetrics for Fantasy Baseball: HR/FB

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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How to Interpret HR/FB

HR/FB measures the percentage of fly balls that leave the park. Last year, a power-friendly baseball contributed to 15.3% of all fly balls ending up in the seats. 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, Cody Bellinger is generally regarded as one of the top sluggers in the game today. His HR/FB was 24.6% in 2019, significantly higher than the league-average rate. If this number regressed to the league average, Bellinger wouldn't be very good. However, he has a career rate of 21.8%. Clearly, above-average power is something Bellinger just does. He should continue to crush bombs with regularity.

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. There are limits here, as Billy Hamilton is never helping a fantasy team with his power no matter how many fly balls he hits. Still, FB% is generally the stat you want to look at for power potential.


What Is a Good FB%?

Elite sluggers generally post a fly ball percentage of around 40%. Subjected to this test, Bellinger had a 42.4% fly ball rate in 2019 and a career mark of 42.9%. These rate stats, combined with a consistently above average HR/FB, make Bellinger the consensus top-round pick he is.

Bellinger doesn't really illustrate the distinction between HR/FB and FB% because he excels at both. For a predictive illustration, consider Aaron Judge of the New York Yankees. His HR/FB last season was an unbelievable 35.1%, powering fantasy rosters with a total of 27 long balls despite being limited to 447 PAs. Of course, you know that Judge has the potential for more if you remember his 2017 total of 52 homers.

Judge posted a 35.6% HR/FB in his stunning rookie campaign, virtually unchanged from his rate last year. The difference lies in his FB%, which passed the 40% test described above in 2017 (43.2%) but fell well short last year (32.4%). If his FB% remains low, he could disappoint owners expecting 40+ home runs in a full healthy season. Of course, you could also make the argument that Judge's FB% has fallen because of his injuries, in which case it will rebound as soon as he's truly healthy. Do you want to roll the dice?

Some of the other players who look primed for significant power regression in 2020 include Fernando Tatis Jr. (31.9% HR/FB, 30.9 FB%), Alex Avila (37.5% HR/FB, 25 FB%), and Shohei Ohtani (26.5% HR/FB, 27.9 FB%). Two of the three players listed here last year (Ian Desmond and Eric Hosmer) were clear fantasy busts, while Ohtani returns to the list after a second successful season with limited PAs. You can bank on a repeat if you want to, but consider yourself warned.



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. A player with a large spike or decline in HR/FB should generally be expected to return to his established baseline moving forward. Ballpark factors may alter HR/FB, but in general raw fly ball percentage is a better tool to identify potential power breakouts.

Of course, it is possible for a batter to legitimately change his approach and permanently boost his HR/FB. Statcast allows us to measure precisely how hard a player is hitting the ball, potentially validating a performance that would otherwise be labeled a fluke. Check out some of our other introductory sabermetric articles by clicking on this link!

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