It’s time for an updated list of potential HR/FB rate surgers! As usual, I scanned the batted ball distance leaderboard, matched each hitter with his HR/FB rate, and identified those hitters whose distance suggests major HR/FB rate upside.

Please be aware that the other two components of my xHR/FB rate equation are missing from this analysis. So to avoid giving wrong advice, it’s why I have stayed away from discussing the hitters in the middle of the distance ranking. Also remember that this ignores park effects, which certainly plays a role.

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I have nothing clever to say. Let’s get right to it.

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Early last season, I introduced an equation that calculates a hitter’s expected isolated power, or xISO. Since I haven’t discussed it all so far this season, and we’re halfway through June, I figured now is better than never.

Before I proceed: Andrew Dominijanni expanded on my research about a month ago. He incorporated exit velocity, sourced from the new Statcast data hosted at Baseball Savant. The model better explains the variance in the data and has slightly better predictive (year-to-year) qualities, making it the optimal choice.

Andrew’s version of xISO generates a pretty simple calculation, but I’m feeling especially lazy today, and I can find hard-hit rate (Hard%), pull rate (Pull%) and fly ball rate (FB%) all on FanGraphs’ batted ball leaderboards.

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Last week, I discussed a multitude of players who have hit a shocking number of home runs so far this season. So today let’s check in on those on the opposite end of the spectrum, the players that beg the question…what the heck happened to your home run power?!?!?!

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The two players I’m recommending this week share almost nothing in common. One is young, powerful, and crushingly enticing. The other is nearing the end of a magnificent career with the same fleetness of foot he enthralled us with 15 years ago. Endless potential versus a potential storybook ending. And if you own either of them right now, you’re likely playing in a very, very deep league.
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Yesterday, I discussed five players whose early season home run totals have like totally shocked the world. Clearly, I missed a couple of obvious names and some of you commented reminding me of such. So let’s get to the rest of those shocking hitters sitting on home run totals we never expected at this point in the season.

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Contrary to what you might assume given my status as a veteran RotoGraphs writer and member of the Tout Wars and LABR leagues, I don’t pay a whole lot of attention to players on none of my fantasy teams. So every so often, I express surprise, or perhaps even shock, when I peruse the day’s box scores and notice a batting average or counting stat from a player at a level far off from our expectations. “Player X has 15 homers already?!?!” is how I will frequently react. Let’s discuss some of these players.

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Let’s be honest, most sleepers don’t come through in fantasy baseball. At least not the true sleepers, guys picked beyond the 250 mark. There have definitely been some big hits beyond 250 this year: Trevor Story (252), Marco Estrada (273), Rich Hill (288) – although he did just hit the DL, Jackie Bradley Jr. (320), and Carlos Beltran (326) to name a few.

I was reminded of the failure of late sleepers when news of the Chris Coghlan trade came across the wire yesterday during my chat. He was someone I really liked to keep up what he did last year (16 HR, 11 SB) with plenty of playing time available in Oakland. Let’s see what’s going on with him and two other deep sleepers (pick 250 or later) I liked. They’re still asleep, but let’s see if there is hope.

Chris Coghlan

He’s hitting .146/.215/.272 in 172 PA so far. It’s been really rough. Sure, a .170 BABIP is unfavorable and probably due for some regression, but it didn’t just happen to him. His strikeout rate has surged from 19% to 27% with his walk rate dipping from 12% to 8% at the same time. Last year, he made a concerted effort to pull more and untap his power, but his 32% pull rate is his lowest since 2010 (30%) and well below last year’s 42%. He’s also reaching a lot more. His O-swing% is way up at 30% after a 23% rate last year that was 11th-lowest in baseball. He’s also seeing the fewest fastballs of his career at 54%, down from a consistent 57-58% from 2012-15.

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Last week, I took Alex Chamberlain’s xBABIP equation for the first drive of the 2016 season, identifying those hitters whose xBABIPs most exceeded their actual BABIP marks. That was your potential BABIP surger list. Today I’ll check in on the flip side, those hitters whose BABIP marks greatly exceed their xBABIP marks. These hitters are at serious risk for BABIP, and resulting batting average, regression.

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It’s hard to believe that we’re now about two months into the season and this has been my first post on xBABIP all year. Well, here it is. While I developed my own xBABIP equation back in early 2015, the availability of new data since my formula was published allowed Alex Chamberlain to create an equation I prefer and use instead. Not only is the r-squared slightly better, but all the metrics are available here on FanGraphs. When I’m looking to buy low, the most attractive targets are hitters whose power is fine, but are simply suffering from an unfortunate BABIP. Below is that list of hitters.

For the first time, I have included all the components of the xBABIP equation so we can get a better sense of which component(s) each hitter is excelling in and where he could improve.

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