You might recall that just three weeks ago, I shared 10 HR/FB rate surgers for 2018. At the time, I was still using my original Statcast-driven xHR/FB rate. Since then, I have developed a new and improved version of the metric, dubbed xHR/FB 2.0. So it’s time to redo the HR/FB rate surgers. A couple of the names are the same as on the original list, but there are some new faces as well.
Yesterday, I shared and discussed nine fantasy relevant hitters whose Statcast Average Fly Ball Distance (Avg FB Dist) marks surged the most versus 2016. Not surprisingly, every single one of them enjoyed HR/FB rate gains, most of them significant jumps. Now let’s dive into the batters on the opposite end of the spectrum, those fantasy relevant hitters whose Avg FB Dist marks dropped most versus 2016.
It’s been Statcast’s average fly ball distance (Avg FB Dist) week, as I introduced the metric on Monday and then listed and discussed names whose Avg FB Dist marks suggest there is either extra stuff going on or some missing ingredients in their batted balls. Today, let’s dive into fantasy relevant players whose Avg FB Dist marks surged the most versus 2016.
Yesterday, I introduced you to Statcast’s batter average fly ball distance (Avg FB Dist), which is one of the new components of my recently updated and improved xHR/FB rate. Today, I’ll continue to swim in the Avg FB Dist pool, this time listing and discussing specific players.
Last week, I unveiled the newest version of my xHR/FB rate, which incorporates two Statcast metrics. The first of those components was Barrels per True Fly Ball Rate (Brls/True FB), which I introduced last Wednesday, and then discussed further on Thursday. Today, I’m going to dive into the other Statcast metric, Average Fly Ball Distance (Avg FB Dist), which is found on the Statcast Search page.
On Tuesday, I unveiled the latest version of my xHR/FB rate, and introduced a new metric that replaced the Brls/BBE equation component. Technically it’s new, but it’s not unfamiliar, as I simply swapped out the BBE denominator for true fly balls, which is just the fly ball total found here, minus pop-ups (IFFB). Yesterday, I dove deeper into the new Brls/TFB metric, sharing some data on my player population and then listing and discussing some names affected by the switch. Today I will continue on that Brls/TFB course with more fun stuff.
Since it was first introduced about a year and a half ago and published on the Statcast Leaderboard, Barrels quickly became one of my favorite metrics. Combining exit velocity with launch angle made it the perfect statistic to reference when investigating a hitter’s power potential. Since we like ratios better than counting stats for projection purposes, Barrels per Batted Ball Event (Brls/BBE) was my metric of choice. But as informative as it remains, I discovered that it actually wasn’t the best ratio when it came to forecasting HR/FB rates.
Nearly three years ago, I unveiled my original xHR/FB rate. Back then, Statcast was in its infancy, and wasn’t installed in all 30 stadiums until the upcoming season. As such, my original equation used metrics that Jeff Zimmerman provided me from scraped Gameday data, I believe. The equation was solid enough, producing a 0.649 adjusted R-squared. Clearly, there was more work to be done, but sadly, the data required to make improvements simply wasn’t available.
Nearly a year ago, I introduced the newest version of my xHR/FB rate, this time using the new Statcast metric, Barrels per Batted Ball Event (Brls/BBE). Along with Brls/BBE, I included two additional components — pulled and opposite field fly ball percentage, which I just lumped together for the second factor in the equation (oh, and also a park factor adjustment).
With three seasons in the Statcast Leaderboard books, it’s time to dive in to its short digital history. While the various metrics published on the site are sure to provide a better understanding of what drives a handful of statistics, I’m most interested in what fuels home runs. The leaderboard shares a number of interesting metrics, several of which would intuitively correlate with HR/FB rates. Given the leaguewide home run surge — for the second straight year, HR/FB rate hit a new high since 2002, the first season FanGraphs has batted ball data — we might find some answers on the virtual pages of Statcast’s records.
