8 Hitters With Major HR/FB Upside

How does one project a power breakout? It is difficult, perhaps impossible, to develop a system that more often than not uncovers a player due for a power spike. So rather than sift through an array of underlying metrics searching for clues, there’s an easier way. It’s the same thing we do when we look at a hitter’s BABIP and compare it to his xBABIP or check a pitcher’s BABIP and assume better/worse fortune the following year will lead to improved/decreased performance.

For hitter HR/FB rate, we can use my xHR/FB equation I developed and compare what the hitter actually did (HR/FB rate) versus what the hitter perhaps should have done (xHR/FB rate). It’s not necessarily a case of projecting a power breakout, but a simple increase, which certainly might represent a surge to new heights, or simply a rebound off a disappointing previous season result.

I looked at all hitters who hit at least 50 fly balls (about a month and a half’s worth of data for a typical hitter) and compared their actual HR/FB rate to their xHR/FB, then sorted by the difference. These eight players were hand-picked based on fantasy attractiveness and all have major upside, which is likely not incorporated into any computer system’s projections (though, they are baked into my Pod Projections!).

8 Hitters With Major HR/FB Upside
Name Avg Distance Avg Abs Angle (AAA) SD Dist (SDD) xHR/FB Actual HR/FB Difference
Jonathan Lucroy 283.8 20.2 66.2 17.3% 7.6% -9.7%
Stephen Piscotty 301.0 28.2 53.5 20.6% 11.7% -8.9%
Matt Wieters 302.2 20.8 63.8 21.3% 12.9% -8.4%
Wil Myers 297.9 21.6 67.1 21.9% 13.6% -8.3%
Giovanny Urshela 273.9 22.0 66.3 15.7% 8.5% -7.2%
Gregory Polanco 275.1 20.8 58.9 12.6% 5.5% -7.1%
Marcell Ozuna 282.3 25.3 57.4 16.0% 9.3% -6.7%
Mark Trumbo 291.7 22.7 66.3 20.5% 14.5% -6.0%
Unweighted Lg Avg (50 FB min) 279.4 20.6 58.2 10.0% 11.5%

Jonathan Lucroy is coming off an injury plagued season that also saw him post his worst wOBA since 2011. All the important metrics moved in the wrong direction — a surging K%, coupled with a plummeting ISO and FB%. But lo and behold, his batted ball distance is right in line with where it’s sat the previous two seasons, while his SDD hit a new career high. A stable Hard% also supports the notion that he didn’t lose any power at all. For whatever reason, the results just weren’t there. He represents a great opportunity to grab a pretty clear rebound candidate for cheaper than he’ll likely cost in years.

One caveat, and it’s pretty major, is that he has underperformed his xHR/FB in five of his six seasons. And it has been a pretty severe underperformance, which is odd considering he calls a top HR park home. Still, he’ll be better in 2016, though I wouldn’t look for a high teens HR/FB rate!

Stephen Piscotty! This is what I was looking at that inspired me to ask the silly question of whether he was “the Superest of the Stars“. I won’t rehash what I discussed just last week, but if he does indeed hit second and have right field all to himself, he could be a bargain and the breakout we actually did see coming.

I haven’t calculated my dollar values yet so my initial rankings that were posted along with the rest of the gang last week don’t mean a whole lot. But, I was the most optimistic ranker of Matt Wieters, and his appearance above is precisely why. With math involved, perhaps he doesn’t come in 8th among catchers, but I’m rather confident I’ll remain the most, or one of the most, bullish. The recovery from TJ surgery dragged on longer than expected last year, but that should be over with now and he should be good to go. Even without the injury concerns, many are going to be concerned about the performance — a .155 ISO is his lowest since 2010. But, his 300+ distance was the highest of his career and the first time he even breached the 290 level. Don’t worry about the performance.

Oh, Wil Myers, have you disappointed us again?! Yes, yes you have. The poor guy cannot stay off the disabled list. But injury concerns aside, Myers showed serious pop last year and the ability to absolutely clobber it every once in a while (check out that SDD). This was Myers’ highest distance in his three seasons. It’s true that Petco is likely going to hurt his HR/FB rate given its right-handed HR park factor that ranks tied for third lowest in baseball. But no park is extreme enough to explain the entire discrepancy between his actual HR/FB rate and xHR/FB rate. With his missed time and overall disappointingness, there is probably going to be some real profit potential.

Hmmm, Giovanny Urshela’s name was a surprise to find here. He did post an ISO of nearly .200 during his time at Triple-A in 2014, but Kiley McDaniel called his power just average before the 2015 season. Now here’s the issue — his inflated xHR/FB rate is primarily driven by an above average AAA and well above average SDD, both of which are less sustainable year-to-year than distance. And his distance is actually below average. BUT! The AAA and SDD don’t have zero correlation of course and the SDD is actually not too much lower than distance. So his marks still hold some predictive value. I just wouldn’t consider a 15.7% HR/FB rate mark reasonable upside to hope for. That said, he could surprise with a low teens mark, perhaps 11% or 12%, which might still be well above what anyone else is expecting.

One might want to point to PNC Park as to why Gregory Polanco so underperformed his xHR/FB rate. Since it sports the seventh lowest left-handed home run park factor in baseball, it’s a reasonable explanation. Surprisingly though, his home HR/FB rate is actually double his away mark through his short career! It’s true that his distance, like Urshela’s, is also below league average and he makes up for it with slightly higher marks in the other two components, which is not what I typically like to see. But surely he could manage better than a weak 5.5% HR/FB rate this season, right?! If he improves, it will be looked upon as simply a young hitter improving. But really, he just wasn’t as bad from a power perspective last year as his results indicated. Also, might I add that his ISO actually increased from 2014 to 2015, so it may have just been a rearrangement of his extra-base hits that led to the HR/FB rate decline.

I was rooting hard for Marcell Ozuna to be traded when rumors were heating up. I was getting all giddy when the Rangers were mentioned and the thought of scooping him up in AL-Only Tout Wars. Even if he remains a Marlin heading into the season, do not forget that the fences are being moved in (as if Giancarlo Stanton needed any more help!). At home, Ozuna’s HR/FB rate sits at just 8.6% for his career, versus a 14.3% mark in away games. He should enjoy a double boost this season — from the friendlier home confines and the bounce back in results to more closely match his xHR/FB rate.

After swatting 30+ homers in 2012 and 2013, Mark Trumbo has launched just 36 home runs in the last two seasons combined. Hit ISO has dropped below .200 and HR/FB rate fallen from around 21% to 14% and change. But his distance is right around where he has sat every single year, while both his AAA and SDD marked new career bests. In fact, that xHR/FB rate was also a career high. You know what’s cool? He takes a power profile that likely would have yielded better results regardless of park to an Orioles home field that boosts right-handed home runs. A return to a 20% HR/FB rate isn’t so far-fetched.

And now, due to popular request, and because I’m a slave to you readers, I present to you the entire list of hitters who had a negative difference between their HR/FB rates and xHR/FB rates (patience, the downsiders are coming tomorrow):

HR/FB Upsiders
Name Flyballs + HRs (won’t match FG!) Avg Distance Avg Abs Angle (AAA) SD Dist (SDD) xHR/FB Actual HR/FB Difference
Josh Phegley 39 304.0 21.8 65.5 22.9% 12.0% -10.9%
Nick Hundley 53 289.1 24.8 66.2 20.9% 10.1% -10.8%
Scott Van Slyke 38 302.2 17.0 60.9 18.4% 8.7% -9.7%
Jonathan Lucroy 56 283.8 20.2 66.2 17.3% 7.6% -9.7%
Stephen Piscotty 44 301.0 28.2 53.5 20.6% 11.7% -8.9%
DJ LeMahieu 56 287.7 22.4 55.5 15.2% 6.7% -8.5%
Alberto Callaspo 45 264.5 18.7 61.4 9.9% 1.4% -8.5%
Matt Wieters 39 302.2 20.8 63.8 21.3% 12.9% -8.4%
Wil Myers 31 297.9 21.6 67.1 21.9% 13.6% -8.3%
Jean Segura 68 269.2 28.6 53.2 12.7% 5.3% -7.4%
Giovanny Urshela 39 273.9 22.0 66.3 15.7% 8.5% -7.2%
Gregory Polanco 90 275.1 20.8 58.9 12.6% 5.5% -7.1%
Hernan Perez 37 263.4 20.3 56.0 8.4% 1.4% -7.0%
Tyler Flowers 45 270.9 22.0 73.7 17.9% 11.0% -6.9%
Rajai Davis 51 286.2 21.7 58.8 15.8% 9.1% -6.7%
Marcell Ozuna 54 282.3 25.3 57.4 16.0% 9.3% -6.7%
Cameron Rupp 42 286.5 20.9 66.4 18.4% 11.8% -6.6%
Scooter Gennett 48 267.8 27.0 56.9 13.0% 6.7% -6.3%
Yangervis Solarte 105 275.4 22.6 60.9 14.3% 8.0% -6.3%
Cameron Maybin 47 279.6 26.5 64.4 18.6% 12.3% -6.3%
Brandon Barnes 34 264.2 24.1 54.1 9.6% 3.4% -6.2%
Christian Yelich 34 297.0 23.5 56.7 18.6% 12.5% -6.1%
Mark Trumbo 82 291.7 22.7 66.3 20.5% 14.5% -6.0%
Chris Johnson 40 270.0 23.1 56.8 11.7% 5.7% -6.0%
Clint Robinson 56 286.9 20.4 63.4 17.1% 11.2% -5.9%
Brad Miller 75 280.2 22.5 62.5 16.1% 10.3% -5.8%
Ben Paulsen 37 291.6 20.9 67.5 20.1% 14.3% -5.8%
Cliff Pennington 36 266.2 22.2 60.7 11.8% 6.0% -5.8%
Matt Duffy 86 286.5 21.0 57.7 15.1% 9.4% -5.7%
Jordy Mercer 61 276.1 19.6 49.5 8.7% 3.0% -5.7%
Aaron Hill 61 275.5 21.5 54.9 11.5% 5.9% -5.6%
Starling Marte 72 303.7 20.5 70.4 24.1% 18.6% -5.5%
Chris Coghlan 77 287.4 22.5 65.9 19.2% 13.7% -5.5%
Yasiel Puig 51 283.4 20.8 68.5 18.4% 13.1% -5.3%
Josh Harrison 82 273.4 21.0 49.4 8.7% 3.4% -5.3%
Miguel Cabrera 81 296.7 23.8 62.9 21.0% 15.8% -5.2%
Eddie Rosario 94 275.3 22.4 62.3 14.8% 9.6% -5.2%
Paulo Orlando 33 284.6 20.9 62.0 16.3% 11.1% -5.2%
Adam Jones 94 298.5 19.9 69.0 21.9% 16.8% -5.1%
Troy Tulowitzki 96 281.9 22.6 64.2 17.3% 12.2% -5.1%
Rene Rivera 61 275.8 19.5 53.8 10.2% 5.2% -5.0%
Adeiny Hechavarria 61 268.0 23.5 52.1 9.5% 4.5% -5.0%
Travis Snider 32 273.1 19.8 60.9 12.4% 7.4% -5.0%
Kolten Wong 91 267.5 22.6 60.5 12.2% 7.2% -5.0%
Leonys Martin 33 275.2 18.6 60.4 12.2% 7.2% -5.0%
Seth Smith 79 287.6 22.1 56.4 15.4% 10.5% -4.9%
Jhonny Peralta 107 279.0 21.5 65.0 16.3% 11.5% -4.8%
Grady Sizemore 51 272.9 18.9 63.6 13.0% 8.2% -4.8%
Alex Rios 94 273.3 17.3 52.4 8.0% 3.3% -4.7%
Asdrubal Cabrera 116 271.1 22.9 61.0 13.4% 8.7% -4.7%
Brett Lawrie 82 290.5 20.4 58.9 16.3% 11.6% -4.7%
Abraham Almonte 30 274.8 19.0 65.6 14.3% 9.6% -4.7%
Lonnie Chisenhall 58 268.9 19.7 60.8 11.3% 6.6% -4.7%
Nick Ahmed 76 272.3 19.8 60.1 11.9% 7.3% -4.6%
Robinson Chirinos 40 291.4 19.8 61.9 17.4% 12.8% -4.6%
Carlos Gomez 77 283.0 19.7 59.5 14.3% 9.7% -4.6%
Michael Bourn 58 263.2 16.5 51.1 4.6% 0.0% -4.6%
Jimmy Rollins 113 273.4 21.7 56.8 11.8% 7.3% -4.5%
C.J. Cron 60 296.2 17.7 65.1 18.9% 14.4% -4.5%
Jace Peterson 88 277.7 17.6 52.2 9.2% 4.7% -4.5%
Jayson Werth 63 277.0 23.8 60.6 15.2% 10.8% -4.4%
Ruben Tejada 61 275.6 17.0 50.2 7.6% 3.2% -4.4%
Wilson Ramos 56 285.7 29.2 61.3 20.2% 15.8% -4.4%
Aaron Hicks 72 278.0 20.1 65.3 15.5% 11.1% -4.4%
Francisco Cervelli 60 279.0 20.0 54.9 11.7% 7.3% -4.4%
Joc Pederson 80 300.0 19.7 73.6 24.0% 19.7% -4.3%
Mark Canha 86 278.8 21.4 63.6 15.6% 11.4% -4.2%
Gregor Blanco 49 275.4 19.2 55.2 10.5% 6.3% -4.2%
Michael Taylor 58 281.0 25.4 65.4 18.8% 14.6% -4.2%
Chase Headley 94 273.8 19.2 60.7 12.2% 8.1% -4.1%
Kevin Pillar 99 253.2 22.8 65.8 10.7% 6.6% -4.1%
Cesar Hernandez 42 251.1 20.2 57.0 5.6% 1.5% -4.1%
Brian Dozier 142 284.4 24.0 60.8 17.2% 13.1% -4.1%
Daniel Murphy 124 279.2 18.8 58.0 12.3% 8.3% -4.0%
Eduardo Escobar 92 274.8 21.7 60.3 13.5% 9.5% -4.0%
James McCann 53 276.7 21.0 57.0 12.4% 8.4% -4.0%
Andre Ethier 67 288.6 21.8 58.3 16.3% 12.3% -4.0%
Yunel Escobar 61 278.7 18.7 58.2 12.3% 8.3% -4.0%
Aramis Ramirez 106 280.7 21.2 57.2 13.5% 9.6% -3.9%
Billy Butler 86 286.5 20.6 57.2 14.7% 10.8% -3.9%
Prince Fielder 124 279.1 19.0 67.6 16.1% 12.2% -3.9%
Anthony Gose 54 268.1 21.5 56.0 10.1% 6.2% -3.9%
Caleb Joseph 67 280.1 22.1 57.9 14.1% 10.3% -3.8%
Matt Holliday 31 266.4 25.8 54.9 11.3% 7.5% -3.8%
Jake Lamb 56 280.1 18.9 53.6 10.9% 7.2% -3.7%
Adrian Beltre 104 285.5 19.5 56.3 13.6% 9.9% -3.7%
Marcus Semien 95 279.3 21.2 56.0 12.7% 9.1% -3.6%
Carlos Santana 99 276.3 22.0 64.3 15.5% 11.9% -3.6%
Starlin Castro 85 277.9 17.7 58.9 11.9% 8.3% -3.6%
Brandon Belt 83 288.5 19.7 63.2 17.1% 13.6% -3.5%
Elian Herrera 40 277.0 23.8 56.3 13.5% 10.0% -3.5%
Jacoby Ellsbury 76 268.5 19.9 56.8 9.7% 6.2% -3.5%
Cody Asche 70 273.5 19.5 63.5 13.4% 9.9% -3.5%
Ian Kinsler 140 265.5 20.9 54.3 8.5% 5.0% -3.5%
Brandon Crawford 80 303.1 19.6 60.4 19.7% 16.2% -3.5%
Randal Grichuk 61 296.9 22.5 68.4 22.6% 19.1% -3.5%
Yonder Alonso 54 271.4 18.6 55.2 9.3% 5.8% -3.5%
Jake Smolinski 26 292.4 23.9 49.8 14.9% 11.5% -3.4%
Logan Morrison 101 284.0 17.5 63.5 15.0% 11.6% -3.4%
Yadier Molina 91 267.7 22.2 45.6 6.3% 2.9% -3.4%
Ben Zobrist 102 276.6 22.0 57.7 13.1% 9.7% -3.4%
Matt Joyce 41 272.6 16.3 59.3 10.0% 6.6% -3.4%
David Freese 51 284.4 25.2 63.8 19.0% 15.6% -3.4%
Charlie Blackmon 104 276.0 17.8 62.1 12.7% 9.3% -3.4%
Anthony Rendon 52 281.8 17.5 50.5 9.5% 6.2% -3.3%
Howie Kendrick 45 302.0 20.9 53.6 17.4% 14.1% -3.3%
Jung-ho Kang 53 298.8 16.5 68.4 20.2% 16.9% -3.3%
Brock Holt 56 265.9 18.5 49.6 5.7% 2.4% -3.3%
Lorenzo Cain 120 279.4 21.1 60.4 14.4% 11.2% -3.2%
Yasmani Grandal 66 293.9 20.4 65.2 19.5% 16.3% -3.2%
Ian Desmond 76 296.6 20.1 61.2 18.6% 15.4% -3.2%
Adam LaRoche 78 286.4 17.8 57.5 13.5% 10.3% -3.2%
Pablo Sandoval 86 275.3 18.9 56.7 10.9% 7.8% -3.1%
Jarrod Saltalamacchia 40 287.4 18.1 66.7 17.4% 14.3% -3.1%
Adrian Gonzalez 107 302.3 19.2 61.0 19.5% 16.4% -3.1%
Robinson Cano 89 290.3 19.6 67.0 19.0% 15.9% -3.1%
Anthony Rizzo 141 287.9 18.4 66.4 17.6% 14.6% -3.0%
Brandon Moss 103 284.4 18.1 63.6 15.5% 12.5% -3.0%
Melky Cabrera 92 266.1 22.6 56.5 10.3% 7.3% -3.0%
Sean Rodriguez 32 280.0 13.5 60.4 11.0% 8.0% -3.0%
Kevin Kiermaier 67 266.5 22.9 58.6 11.4% 8.4% -3.0%
Brayan Pena 38 255.9 16.1 52.2 3.0% 0.0% -3.0%
Justin Turner 79 285.7 22.8 60.4 16.8% 13.9% -2.9%
Freddy Galvis 100 263.7 21.1 51.9 7.2% 4.3% -2.9%
Corey Dickerson 27 308.2 19.8 61.3 21.4% 18.5% -2.9%
Domonic Brown 29 282.5 16.2 56.1 11.2% 8.3% -2.9%
Martin Prado 67 266.7 21.7 55.5 9.7% 6.8% -2.9%
Matt Kemp 119 291.6 21.1 59.4 17.1% 14.3% -2.8%
Buster Posey 111 285.3 20.3 55.9 13.8% 11.0% -2.8%
Kendrys Morales 139 286.5 20.7 61.1 16.3% 13.5% -2.8%
Chris Owings 79 270.6 19.7 46.0 6.0% 3.2% -2.8%
Jonathan Schoop 48 302.7 21.1 60.1 20.2% 17.4% -2.8%
Will Middlebrooks 63 286.0 16.3 59.5 13.5% 10.7% -2.8%
J.J. Hardy 65 271.5 21.5 53.9 10.1% 7.4% -2.7%
Mitch Moreland 87 296.7 19.6 68.1 21.0% 18.3% -2.7%
Jason Heyward 65 277.3 20.8 62.8 14.7% 12.0% -2.7%
Sam Fuld 29 252.9 19.2 59.4 6.5% 3.8% -2.7%
Will Venable 32 276.2 22.1 59.5 13.8% 11.1% -2.7%
A.J. Pierzynski 70 261.2 22.3 62.1 11.0% 8.4% -2.6%
Elvis Andrus 99 260.0 23.9 50.1 6.9% 4.3% -2.6%
Nolan Arenado 139 295.2 21.7 66.7 21.1% 18.5% -2.6%
Carlos Beltran 113 279.9 20.9 58.4 13.7% 11.1% -2.6%
Trevor Plouffe 123 283.0 21.3 58.2 14.6% 12.0% -2.6%
Salvador Perez 105 286.0 20.3 58.4 15.0% 12.4% -2.6%
Chris Iannetta 61 274.3 19.1 63.7 13.5% 10.9% -2.6%
Cory Spangenberg 32 277.4 22.0 49.2 10.1% 7.5% -2.6%
Freddie Freeman 89 294.4 21.6 60.1 18.3% 15.8% -2.5%
Rusney Castillo 39 279.5 24.6 50.5 12.3% 9.8% -2.5%
Marlon Byrd 87 291.0 22.6 64.9 19.8% 17.3% -2.5%
Steve Pearce 68 280.0 23.4 63.3 16.8% 14.3% -2.5%
Andres Blanco 35 275.8 16.5 65.6 13.3% 10.9% -2.4%
Dustin Ackley 45 294.1 22.0 51.6 15.1% 12.7% -2.4%
Adam Eaton 79 275.0 20.6 61.1 13.3% 10.9% -2.4%
Justin Upton 114 282.7 21.0 66.7 17.6% 15.2% -2.4%
Joe Panik 73 262.7 23.0 55.7 9.3% 6.9% -2.4%
Todd Frazier 139 287.3 18.3 66.6 17.5% 15.1% -2.4%
Juan Lagares 66 265.0 22.0 51.6 7.9% 5.5% -2.4%
Stephen Vogt 97 274.2 21.8 64.2 14.9% 12.5% -2.4%
Kyle Seager 142 276.7 20.9 62.4 14.4% 12.1% -2.3%
Ender Inciarte 64 262.5 19.9 54.7 7.4% 5.1% -2.3%
Derek Dietrich 44 297.9 21.1 48.8 14.6% 12.3% -2.3%
Austin Jackson 67 273.2 24.3 55.2 12.4% 10.1% -2.3%
Andrew McCutchen 115 299.7 17.1 55.8 15.9% 13.6% -2.3%
Blake Swihart 39 272.9 22.8 53.1 10.8% 8.6% -2.2%
A.J. Pollock 83 291.1 21.7 54.5 15.4% 13.2% -2.2%
Nick Markakis 76 257.8 20.3 49.1 4.3% 2.1% -2.2%
Justin Maxwell 41 287.6 23.5 51.2 14.1% 11.9% -2.2%
Derek Norris 83 274.6 19.4 56.9 11.1% 8.9% -2.2%
Johnny Giavotella 65 256.3 21.6 51.6 5.5% 3.3% -2.2%
Travis d’Arnaud 64 278.1 21.6 67.8 17.2% 15.0% -2.2%
Kurt Suzuki 97 261.8 21.0 49.2 5.7% 3.5% -2.2%
Kris Bryant 121 292.3 20.4 61.9 17.9% 15.8% -2.1%
Marwin Gonzalez 52 285.9 19.0 62.6 15.9% 13.8% -2.1%
Jason Kipnis 83 266.2 20.8 55.2 9.0% 6.9% -2.1%
Ryan Flaherty 46 294.3 19.7 54.9 15.4% 13.4% -2.0%
Carlos Sanchez 48 257.1 24.3 56.8 9.0% 7.0% -2.0%
Denard Span 30 274.0 17.3 59.1 10.8% 8.8% -2.0%
Odubel Herrera 55 259.6 20.4 61.5 9.6% 7.6% -2.0%
Ryan Zimmerman 61 280.1 21.7 69.6 18.4% 16.5% -1.9%
Manny Machado 124 293.7 23.2 61.8 19.5% 17.6% -1.9%
Erick Aybar 90 254.1 17.2 55.2 4.2% 2.3% -1.9%
Xander Bogaerts 89 266.0 23.9 46.9 7.2% 5.3% -1.9%
Addison Russell 82 278.0 19.3 56.5 11.7% 9.8% -1.9%
Gerardo Parra 96 280.6 22.0 53.3 12.4% 10.6% -1.8%
Brandon Guyer 60 275.5 21.1 52.6 10.4% 8.6% -1.8%
Jonny Gomes 37 274.2 20.3 60.1 12.6% 10.8% -1.8%
Ryan Goins 56 262.8 20.0 55.7 7.9% 6.1% -1.8%
Evan Longoria 134 280.6 21.3 54.6 12.6% 10.8% -1.8%
Jedd Gyorko 85 288.9 19.1 59.4 15.5% 13.7% -1.8%
Victor Martinez 101 278.0 19.2 49.2 8.9% 7.2% -1.7%
Mike Moustakas 134 276.2 18.3 61.9 12.9% 11.2% -1.7%
Chase Utley 72 270.1 18.5 54.7 8.7% 7.0% -1.7%
Danny Espinosa 50 285.6 21.0 59.9 15.8% 14.1% -1.7%
Michael Brantley 96 266.5 21.0 61.5 11.6% 9.9% -1.7%
Jose Iglesias 45 256.9 21.7 47.1 4.0% 2.4% -1.6%
Jose Reyes 72 252.3 14.8 64.5 6.2% 4.7% -1.5%
Curtis Granderson 143 289.9 21.3 56.7 15.8% 14.3% -1.5%
Mike Zunino 66 282.0 18.9 53.9 11.6% 10.1% -1.5%
Jay Bruce 127 281.1 19.0 62.7 14.7% 13.3% -1.4%
Eugenio Suarez 71 274.2 22.2 59.9 13.5% 12.1% -1.4%
Dexter Fowler 114 267.5 22.9 59.4 11.9% 10.6% -1.3%
Darin Ruf 49 281.4 23.2 66.3 18.2% 16.9% -1.3%
Jimmy Paredes 47 285.1 21.6 59.2 15.6% 14.3% -1.3%
Conor Gillaspie 36 262.4 19.2 55.6 7.4% 6.1% -1.3%
Mark Reynolds 71 278.8 20.6 59.7 13.8% 12.5% -1.3%
Joe Mauer 69 285.9 20.3 49.7 11.6% 10.3% -1.3%
Tyler Collins 40 271.9 20.9 49.7 8.3% 7.1% -1.2%
Avisail Garcia 77 276.8 19.3 60.3 12.9% 11.7% -1.2%
Kevin Plawecki 34 266.6 18.5 50.8 6.3% 5.1% -1.2%
Jake Marisnick 58 270.9 21.8 57.3 11.4% 10.2% -1.2%
Colby Rasmus 102 280.4 25.8 65.1 18.7% 17.6% -1.1%
Angel Pagan 95 257.5 18.4 48.8 3.2% 2.1% -1.1%
Nick Swisher 33 284.8 18.5 55.4 12.6% 11.5% -1.1%
Jorge Soler 56 291.0 18.2 56.8 14.6% 13.5% -1.1%
Mookie Betts 146 272.8 20.4 52.2 9.3% 8.2% -1.1%
Jed Lowrie 62 275.2 21.9 55.2 11.8% 10.8% -1.0%
Daniel Descalso 31 265.2 24.2 56.3 10.7% 9.8% -0.9%
Juan Uribe 68 278.8 16.7 66.8 14.6% 13.7% -0.9%
Didi Gregorius 103 261.2 20.8 53.1 6.9% 6.0% -0.9%
J.T. Realmuto 81 261.4 22.7 55.6 8.8% 7.9% -0.9%
Jose Ramirez 69 255.6 22.6 54.7 7.0% 6.1% -0.9%
Nick Castellanos 120 274.7 21.4 51.7 10.1% 9.2% -0.9%
Kelly Johnson 55 295.3 19.1 65.9 19.6% 18.7% -0.9%
David DeJesus 51 263.1 22.6 50.5 7.3% 6.4% -0.9%
Gregory Bird 37 305.3 19.7 62.9 21.2% 20.4% -0.8%
Luis Valbuena 96 291.6 22.3 59.0 17.5% 16.7% -0.8%
Adam Lind 93 286.2 21.5 56.2 14.7% 14.1% -0.6%
Alex Gordon 80 290.0 18.7 54.4 13.6% 13.0% -0.6%
Josh Reddick 105 270.8 20.2 58.7 11.2% 10.6% -0.6%
Rougned Odor 77 278.4 21.2 55.6 12.4% 11.8% -0.6%
Dioner Navarro 49 269.0 17.7 56.9 8.9% 8.3% -0.6%
Brett Gardner 105 271.2 22.2 56.9 11.6% 11.0% -0.6%
Neil Walker 114 275.8 17.7 56.4 10.4% 9.9% -0.5%
Yasmany Tomas 39 288.0 17.3 57.0 13.5% 13.0% -0.5%
A.J. Ellis 36 289.4 19.3 56.1 14.5% 14.0% -0.5%
Torii Hunter 101 286.4 24.5 55.3 15.8% 15.4% -0.4%
Martin Maldonado 35 279.1 18.0 47.4 7.9% 7.5% -0.4%
Omar Infante 91 252.9 17.9 48.7 1.8% 1.4% -0.4%
Alexi Amarista 54 260.4 17.4 50.0 3.9% 3.6% -0.3%
Maikel Franco 43 298.0 17.8 56.9 16.2% 15.9% -0.3%
Alex Rodriguez 114 299.3 21.6 67.3 22.3% 22.1% -0.2%
Jose Bautista 163 286.7 20.4 67.4 18.6% 18.4% -0.2%
Brandon Phillips 89 265.4 20.5 53.0 7.8% 7.6% -0.2%
Josh Donaldson 140 301.7 22.1 64.2 22.0% 21.8% -0.2%
Stephen Drew 92 271.6 22.4 56.9 11.8% 11.6% -0.2%
Preston Tucker 53 292.6 18.8 58.3 15.8% 15.7% -0.1%
Alcides Escobar 121 255.0 18.7 47.0 2.0% 1.9% -0.1%
Lucas Duda 127 285.7 19.4 62.4 16.0% 15.9% -0.1%





Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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Steve
8 years ago

Is this the kind of thing that can be skewed by a small sample size? As someone deciding whether to keep Piscotty, I want to believe…but I’m skeptical.