Last week, I dug into the 2014 ESPN Home Run Tracker data and identified six hitters who applying the findings of my previous analysis are candidates for HR/FB rate downside this season. Today it’s time to take a look on the other side of the coin, those hitters who appear to have some serious upside. This time I’ll check in on the bottom of the “Just Enough” percentage (JE%) leaderboard. The thinking here is that an errant gust of wind here and there or a millimeter difference in where the bat meets the ball could push balls that had been fly outs to head just over the wall.

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Two years ago, I conducted an exhaustive study of ESPN Home Run Tracker data. At that time, it was the primary tool I used to validate a batter’s power, before we got into the sexy new batted ball distance, and then combined that with SDD and angle. The short story is I found that hitters with an unusually high percentage of “Just Enough” (JE) homers saw their HR/FB rates decline the following year, significantly more than the rest of the player population. On the other hand, those who hit a high percentage of “No Doubt” (ND) homers maintained their HR/FB rate much better than the rest of the group.

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On Monday, I unveiled the xHR/FB rate equation I devised a year ago. Yesterday, I began my look back at 2014, discussing a selection of hitters whose xHR/FB rates suggest serious HR/FB rate upside this year. Today, I finish my look back, this time at the overachievers. These are the bust candidates, at least when it comes to home runs, assuming of course they sustain similar batted ball distances, average absolute angles and standard deviation of distances (SDD). Since my formula ignores home ballpark which absolutely plays a major role, I will mention it as a possible explanation for such overperformance as warranted.

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Yesterday, I unveiled the xHR/FB rate equation I devised a year ago. So today I’ll begin my look back at 2014 and discuss a selection of hitters whose xHR/FB rates suggest serious HR/FB rate upside this year, assuming of course they sustain similar batted ball distances, average absolute angles and standard deviation of distances (SDD). Since my formula ignores home ballpark which absolutely plays a major role, I will mention it as a possible explanation for such underperformance as warranted.

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A year ago, I took our batted ball distance and HR/FB rate analysis to its final step. Armed with additional metrics from our in-house math ninja Jeff Zimmerman, I published an equation to predict a hitter’s home run per fly ball rate, which I cleverly dubbed xHR/FB. Unfortunately, the actual equation derived has been hidden behind the FG+ pay wall since. No longer.

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Draft season is fast approaching. That means that draft strategy will once again be a hot topic, as fantasy enthusiasts argue the merits of one philosophy versus another. But one particular debate threatens to make my head explode every single year. That is the notion of making your draft selection based on “best player available” (BPA) versus “position scarcity” (PS). The decision makes no sense to me. This is why.

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Yesterday, the Astros continued to alter their outfield, this time by signing Colby Rasmus to a one-year contract. I’m sure glad I’m not overseeing the Astros depth chart, because it has seemingly changed every day. Rasmus suddenly becomes the team’s starting center fielder, with the collection of Jake Marisnick, Robbie Grossman and Alex Presley likely fighting for reserve roles. Let’s begin with the park factors to determine whether this impacts Rasmus’ fantasy value at all.

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Yesterday, I dove into the three xHR/FB rate components to explain what fueled Todd Frazier’s home run surge. Today, I’ll dissect Miguel Cabrera, who set a new career low HR/FB rate, as it dipped from a career high of 25.4% in 2013 to just 14.0% in 2014.

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Over the last couple of weeks, I have talked a lot about a hitter’s batted ball distance and the additional components included in my xHR/FB rate formula. The cool thing about learning about these metrics is now it’s a bit easier to understand what drove a particular hitter’s power surge or what led to a decline in home run output. As I am in the middle of my hitter projections, I have stumbled upon players with some interesting trends.

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Yesterday, I shared with you the leaders and laggards of one of the components of my xHR/FB ratio, average absolute angle. Today, I check in on the leaders and laggards of the other non-distance variable of my equation, the standard deviation of distance (SDD). The SDD is much more stable year to year than the average absolute angle, coming in a bit below batted ball distance with a 0.50 correlation.

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