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10 Hitters Statcast Doubts (Fantasy Baseball)

10 Hitters Statcast Doubts (Fantasy Baseball)

A few days ago, I attempted to summarize the state of internet use of Statcast data for fantasy baseball analysis. By examining players’ 2017 projected isolated slugging percentage (ISO), 2016 ISO, as well as two versions of 2016 expected isolated slugging (xISO) based on Statcast data, I identified 10 hitters that Statcast trusts going into 2017. Today, I will flip the problem and look for players on whom the data casts more doubt.

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Background and Resources

Rather than repeat a long explanation of Statcast analysis, I will refer again to the original summary, and provide a condensed version. The detailed quantitative information provided by MLB’s Statcast system is undoubtedly a boon for analytically-inclined baseball enthusiasts and fantasy players alike, but it is very new and still improving. Thus, any empirical models and conclusions based thereon should be treated as experimental until the quality of data stabilizes and our analyses can be validated over time.

That said, I will be referring to a few sources of information that are helpful for the sharp fantasy player to know. Again, my first article provides a little more explanation for each.

Baseball Savant is the source of all raw Statcast data, and also provides some nice tools for visualizing all kind of batted balls. It truly is one of my favorite corners of the internet.

xStats.org houses an excellent suite of tools developed and maintained by Andrew Perpetua, which takes raw Statcast data and seeks to classify each batted-ball based on the results of those which were historically similar. Much more happens under the hood, but the result is an expected batting line for each player.

I scratched together a simple xISO tool that uses average quantities from the Baseball Savant leaderboard as well as more traditional batted-ball breakdowns in FB%, GB%, and Pull%.

Casting Doubt

As in my original article, I will center my analysis on isolated slugging. While ISO is not typically a fantasy category itself, many good things happen when a player hits for power. Breakouts and busts are often predicated on power spikes or slumps and, as the tools above show, the new information we get from Statcast can be made to correlate very strongly with ISO.

I will compare a few data points: 2016 ISO, 2017 Zeile Consensus Projected ISO, my 2016 xISO, and 2016 xISO calculated from Andrew Perpetua’s xStats.org. A “doubt” designation will be given when a hitter’s projected ISO is much higher than his 2016 ISO or 2016 xISO. Unlike the hitters that Statcast trusts, I feel compelled to split the doubted into a few categories.

The Rockies

Player 2017 Proj. ISO 2016 ISO 2016 xISO (AD) 2016 xISO (AP)
Nolan Arenado .269 .275 .241 .261
Carlos Gonzalez .227 .207 .196 .185
Ian Desmond .189 .162 .168 .165

Well, Ian Desmond just had surgery to repair a broken bone in his left hand. Reports suggest he will be back in April, but there is a degree of uncertainty about his 2017 season. Projection systems include a significant adjustment for his new home park, but the .189 ISO mark would be his highest since 2012, and over 25 points higher than 2016.

Nolan Arenado and Carlos Gonzalez are both projected for ISO marks that they have achieved in the more recent past; Arenado each of the last two years and Gonzalez in 2015, both in the same park they still call home. While the xISO numbers are cautious, Coors Field park factors are so extreme that it is difficult to truly doubt any of these Rockies.

The Rest

Player 2017 Proj. ISO 2016 ISO 2016 xISO (AD) 2016 xISO (AP)
Bryce Harper .245 .198 .204 .197
Josh Reddick .166 .123 .149 .114
Giancarlo Stanton .277 .249 .255 .227
Brett Gardner  .128  .101 .110 .092
Adrian Gonzalez .173 .150  .141  .150
Paul Goldschmidt  .221  .192 .174  .185
Jose Bautista  .237  .217  .218 .191

Bryce Harper (OF – WSH)
As documented by Jeff Sullivan, Bryce Harper had a monster 2015, followed by a surprisingly mediocre 2016. Based on Sullivan’s survey of the Statcast data, Harper’s 2015 slugging percentage was seemingly out of proportion with his average line drive and fly ball exit velocity. The 2016 xISO models, which are more sophisticated, but in the same spirit as Sullivan’s inquiry, suggest that his .198 actual ISO was quite fair.

Projections for 2017 naturally factor in his 2015 performance, but unless he makes additional improvements, an ISO over .240 may not be in the cards. Given Harper’s age and pedigree, real skill growth is certainly possible.

Josh Reddick (OF – HOU)
The oft-injured Reddick is projected to achieve an ISO above .160, which he did in both 2014 and 2015. The Statcast-based metrics, though, believe that his .123 2016 ISO was fully deserved.

Giancarlo Stanton (OF – MIA)
Sporting an America-themed compression sleeve, Stanton destroyed a pitch in Team USA’s decisive World Baseball Classic game against the Dominican Republic. His raw power is undeniable, and it came to the forefront in 2015 when he notched a .341 ISO mark.

His power was down last year, and the batted-ball data supports it. He will need to recover some of the line drives that became ground balls in 2016 to reach his lofty 2017 ISO projection.

Brett Gardner (OF – NYY)
At 237 in the Expert Consensus Rankings, Brett Gardner is not expected to be a star. After posting ISO marks around .150 for three straight years, he barely broke .100 in 2016, with a measly 89.8 mph exit velocity on liners and fly balls and a major drop in fly ball percentage. Entering his age-33 season, even in hitter-friendly Yankee Stadium, this may be the beginning of the end for Gardner’s fantasy utility.

Adrian Gonzalez (1B – LAD)
Following a theme among players in this article, Gonzalez earned a career low in ISO in 2016, apart from a cup of coffee in 2004. While the projection systems expect some return to form in 2017, Gonzalez will need to affect a significant restoration of his previously stable fly ball/line drive mix.

Paul Goldschmidt (1B – ARI)
A strikingly similar story can be told for Goldschmidt: fewer fly balls and career-low ISO fully supported by the Statcast-based models. Goldschmidt, though, is five years younger than Gonzalez, so a 2017 power rebound seems a better bet.

Jose Bautista (OF – TOR)
The difference between Bautista’s 2016 ISO and his projected 2017 ISO is the smallest of any player on this list. Well-documented injuries broke up a season in which Bautista’s strikeout rate spiked four percentage points, while his ISO dropped 68 points. Entering his age-36 season, Bautista may bounce back to some degree, but expectations of a 30 home run season may be optimistic, let alone a return to 40.

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Andrew Dominijanni is a correspondent at FantasyPros. For more from Andrew, check out his archive and follow him @ADominijanni.

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