We've spent a lot of time this pre-season parsing hard hit rate and all of its various components. One of the most fascinating aspects of this metric is almost certainly how each type of batted ball can be hit hard, yet the exit velocity threshold for each batted ball type is different. In other words, the threshold for a "hard hit" groundball is lower than the exit velocity for a "hard hit" flyball. As I introduced in my article last week, I questioned why we still analyzed the quality of a power hitter with the standard hard% metric when that number encompasses all batted ball types, yet 96% of all home runs last season were flyballs. Enter hard hit rate on flyballs....
If the ultimate goal is to identify players who "earned" their home run numbers, why wouldn't we want to look at the hard hit rate metric on a more granular level, specifically the hard hit rate on flyballs? Sure enough, as you can see from the table below, most of the leaders in HR/Hard-Hit FB Rate are also among the leaders in total homeruns.
Additionally, you can use the information below to help you make smarter decisions as it relates to evaluating repeatability or continuation of trends. Players with a low "HR/Hard% Flyballs" total could be in line for more power as natural regression swings the other way. Conversely, players with a high "HR/Hard% Flyball" could also see a swing the negative way as things like ball placement in stadium, trajectory, and others factors cause his rates to drop.
So what's the magical point that helps us determine what's high and what's low? Like any metric, this one is also going to be largely skill-dependent, making a player's average rate a nice baseline to use, but it's also possible to simply compare players against the league average "HR/Hard% FB" rate, which I found to be about 34% in 2018.
Another fascinating piece of this puzzle is finding the players with large discrepancies between their normal hard% and their hard% on flyballs. Unlocking this information will help you get an edge over others who simply use the generalized metric rather than the one that measures solely flyballs. More accurate data = more successful power identification.
Craving more analysis? Lou Blasi and myself will dive deep into this topic and discuss the list of players below this morning (Saturday April 6th) on the Fantistics show on SiriusXM Fantasy Sports Radio (XM 87/Sirius 210). Check it out live or listen on-demand!
