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!).
| 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.
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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):
| 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 founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
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.
Of course! It’s just like any metric in which the larger the sample, the more value it provides. I imagine you have Piscotty cheap, so it depends on how price of course.
Have you looked at what the typical year to year variance for this stat usually is? Would +/= 5% be considered normal year to year variance where anything above that considered an outlier?
I’m really intrigued by DJ LeMahieu with this. His ADP has him right around 14th 2B taken and if he could improve his 6HR total up to ~10HR and keep some of the inflated SB/AVG he had at say 15/280 he could provide real nice value later on. If he can put up that stat line he would be a poor man’s kipnis at a much lower cost.
The xHR/FB can jump around because there are 3 different components and AAA has a rather low YoY correlation. It does seem like DJ could flirt with double digit homers, but going from 6 to 10 isn’t going to boost his value all that much!
Keep in mind LeMahieu hit <20% fly balls last year, so even if he regresses to his xHR/FB he still won't hit many HRs. He's a slap hitter. And it may not regress at all, since his career HR/FB is only 5% and that is in over 500 games. Last year's 6.7% was a career high.
Mike, what does this mean for Starling Marte?
Most believe his HR spike last year was a fluke, but this list shows he under performed a bit.
Yup, he’s been underperforming through his short career, but his excellent distance led to my 2015 bold prediction that he’d hit 20 homers, which he just missed. The park is holding him back and I think he has probably peaked. I don’t see much additional upside though what he did in 2015 was no fluke.
Sorry guys, I disabled my adblocker for this site at the request of a previous article and for the last few months I’ve been struggling to read anything on this site because the automatically loading videos were constantly screwing up FireFox. Back to adblock.
Seconded. If it were static ads, I could handle those, but the auto-load videos are just awful. They bog my machine down if not crashing it entirely.
Yeah, I have a brand new chromebook and a laptop with a brand new SSD and they can’t even bull through this site. Worst on the Internet for slowdowns.
The flash process that runs ads on the site are taking up more of my PCs resources than Firefox itself. Sorry guys, but these ads make the site unusable and make a strong case for adblock
You can disable the flash player under settings in any browser…
This makes Segura a little more interesting as a bench option, given that he may pick up additional positional eligibility at 2B.
Segura’s high appearance here is a fluke thanks to an aberrant AAA. He won’t come close to that again which is inflating his xHR/FB rate.
It always fun to think you can get an edge on your league mates by reading columns like this. But Mike: wasn’t Justin Smoak on this list a year ago? I think we know how that turned out. And Christian Yelich?
I’m going to hold your feet to the fire this time Mike. I’m writing down everyone on the top of your list.
JK. It’s entertaining stuff. Can’t get enough of it. All projection systems have flaws, even if they have a reasonable basis for their projections.
Does anybody remember who were some of the other names on the 2015 list?
He was right about Smoak! Tripled his HR/FB
Umm, both those hitters increased their HR/FB rates as predicted!
Fair enough. But I think we know what a boost in HR/FB rates implies: a breakout season.
So, I typed in Smoak’s name in the search box and found the original article from Jan. 27 2015. In that article you said that if Yelich would stop hitting so many GBs and more FBs he could become a 20/25 player and thus a “top fantasy outfielder.” The GB% didn’t go down, it went up, and the FB% went down, not up; thus he failed to achieve what you thought he might achieve. Besides, in Yelich’s case his HR/FB rate went from 11.5% to 12.5%, a very modest gain of less than 9%.
I then googled your name and bold predictions: using your formula you suggested that Smoak could hit 25 HRs and bat .260.
I don’t know that I bought into the batting average but I certainly bought into the HR projection (or something very close to it) for the reasons you stated. And Smoak almost certainly would have hit 20+ HRs had he not been put into a platoon with Colabello. Of course, he didn’t sniff .260.
I apologize for not making myself more clear: I wasn’t attacking the formula, I was just saying what we all know. Outcomes depend on too many variables, some of which are simply unpredictable.
And to repeat: I do enjoy your insights and hope to capitalize on them, knowing full well that again multiple factors may spoil the outcomes that we’re hoping for.
Never buy into “Bold Predictions” they are intended to be, at pretty much a minimum, like a 90% projection for the player. They aren’t things that should happen, they are things that might happen.
As for Yelich, the statement that if he were to turn a bunch of GBs into FBs, he may hit 20 homers was true last year just as it is still true today.
I think your issue is that you are reading in conclusions that simply aren’t there as stated. This list simply shows one methodology (a self-admittedly highly variable one) that is better at predicting changes in HR/FB% than the average human weighing arbitrary factors inside her own head.
The correct response to the author of this article is not “I am tired of predictions ever being wrong, I am putting you on notice right now that I intend to remind you of every instance in which you were wrong once enough time has passed for me to easily prove it”… Instead, we should say “this methodology is fairly simple, but inarguably better than nothing, thank you for doing this work and providing me with an easily understandable graphic that quickly shows deviations in a particular skill”
To summarize…
What the author said:
“If I apply one methodology to everyone, we seem to get a result that is more valuable than random guessing, here are the results, and the methodology, do with it as you like”
What you apparently heard:
“The players at the top of this are all guaranteed to have significantly more productive offensive seasons than they have in the past, specifically, Smoak will hit at least 25 home runs in 2015, and Yelich will hit at least 20 home runs in 2015′
Not really. And again, I guess I didn’t make myself clear.
I completely buy into your statement summarizing what Mike said. His methodology is absolutely “more valuable than random guessing.”
Second of all, I wasn’t really being serious, that’s why I said JK (just kidding). I really do enjoy Mike’s columns and I honestly do hope to use them to my advantage—as I do with so many other columnists in FG and RG—-when playing fantasy.
I can’t get “tired” of predictions that have a reasonable basis, e.g., Smoak’s FB distance increases coupled with a move to Rogers Center (one of the best hitter’s parks by park factors in baseball) should equal a significant number of HRs.
And sure, Yelich could have a surge in HRs if he hit more fly balls. But I ask: why should a hitter who plays half his games on turf and hits hard ground balls (or at least not soft ones) to all fields stop doing what has made him successful? I’m not a Marlins fan and therefore I don’t see them play very often, but my guess is that Yelich has no interest in trying to hit more FBs. Maybe now that the fences have been moved in, he may try a different approach to hitting, IDK.
I think the best way to summarize my remarks is this: if you don’t have something constructive to add, maybe you should button it. I’m an inveterate contrarian and I like to joke around—maybe too much. (Certainly some of my employers have felt this way.)
Have you considered trying to build a more predictive xHR/FB? E.g. re-running the regression to predict Year 2 HR/FB versus Year 1?
Nope because it’s missing park factors which play a major role. There’s no easy way to incorporate those.
Good stuff as usual, Mike. Would be cool to see a FB% column in the table too, just for reference. eg, LeMahieau and Wieters both had a differential of about 9.5 percentage points, but Wieters hits twice as many flyballs so by extension could see a spike of twice as many HRs.
I thought of this when I went to bed last night. Is also helpful for anyone wanting to analyze the data further. Will add tonight.
Added!
Gonna need this Polanco hype train to slow down, I’m looking forward to getting good value on draft day for him.