Yesterday, I used my new xHR/FB rate to identify and discuss 15 hitters whose xHR/FB rates actually validate their HR/FB rate spikes in 2017. Today, I’m going to check in on the opposite end of the validations — those hitters who suffered severe declines in HR/FB rate that was confirmed by xHR/FB rate. Without xHR/FB rate, we cannot be sure if it’s luck or just skill changes driving the swings in HR/FB, so the metric assists in making that determination.

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As suggested by commenter Konoldo in yesterday’s post discussing 10 2018 HR/FB rate decliners, today I am going to use my new xHR/FB rate to identify surprise 2017 power sources validated by the metric. These are the hitters that either came out of nowhere to post big HR/FB rates, or really upped their games, blowing past even the most optimistic of projections. The knee-jerk reaction is always to expect severe regression, but xHR/FB rates might make you think twice. Perhaps a repeat is more likely than you think for these hitters.

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Yesterday, I used my new and improved xHR/FB rate equation to discuss 10 hitters whose xHR/FB rates sat significantly above their actual marks in 2017, suggesting serious 2018 upside. Today, I’ll talk about the other end of the spectrum, hitters whose xHR/FB rates were well below their actual marks, hinting at real downside risk in 2018, assuming the same underlying skills.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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