So Much For an Evan Longoria Home Run Rebound
Yesterday, the Giants decided that Pablo Sandoval wasn’t actually the answer at third base for them in 2018 and traded for Rays-lifer Evan Longoria. Now, Longoria’s chances of rebounding in the home run category have just gone splat. While he has posted HR/FB rates in the mid-to-high teens for most of his career, that mark dipped just below 11% in 2014 and 2015, before rebounding back into the mid-teens in 2016, en route to a career high homer total. The rebound was short-lived though, as his HR/FB rate fell back down to just 10.5% — a career low — this season. Given that he’s not so totally over the hill and he has shown strong power skills as recently as that 2016 season, you had to have figured some sort of dead cat bounce. But now, that bounce is far less likely to occur.
Let’s compare park factors. Since one year factors could be fickle and don’t necessarily tell us the true affect a ballpark has on a specific metric, I decided to use a weighted three season factor for Longoria’s destination, AT&T Park. That acts as a projection for the park’s 2018 factor. On the other hand, I will simply present the 2017 park factors for Tropicana Field, as all we care about is how it actually played this season to compare to how AT&T is likely to play next year.
| Park Name | R | 1B | 2B | 3B | HR | GB | FB | LD | K | BB |
|---|---|---|---|---|---|---|---|---|---|---|
| Tropicana Field | 91 | 102 | 90 | 118 | 96 | 91 | 102 | 94 | 113 | 103 |
| AT&T Park | 95 | 106 | 99 | 118 | 76 | 101 | 98 | 98 | 103 | 105 |
Well, isn’t this interesting. Though I probably wouldn’t have guessed it, AT&T appears to be slightly less pitcher friendly than Tropicana overall! It’s a bit better for singles and doubles, while the triples factors are identical. But check out that huge disparity in home run factors.
Given that gap, it’s hard to believe that AT&T is less pitcher friendly, but that’s what the data says. And since home runs are a category, while singles and doubles are not, this move takes a massive bite out of Longoria’s already deflated value.
The good news is that his BABIP should benefit from the additional singles and doubles, which he could certainly use coming off the second lowest BABIP of his career. But that wouldn’t necessarily boost his batting average if his home run total takes a hit.
The other concern relates to his strikeout rate. He just posted the best Contact% and lowest strikeout rate of his career, which doesn’t normally happen during a player’s age 31 season. So park switch or not, you would have to assume the strikeout rate is headed back toward his career average. The good news though is that Tropicana actually significantly inflated strikeouts in 2017, while AT&T figures to only marginal boost them.
The park switch shouldn’t actually kill Longoria’s offensive output, but instead just rejigger it toward a different path of production. As a fantasy owner, though, a similar wOBA alone doesn’t guarantee he’s going to hold his value given that home runs plays such a vital role in a hitter’s fantasy value.
The switch in teams shouldn’t affect his runs batted in or runs scored totals much as both offense were expected to be below average and he was going to hit in the middle of either lineup. The one way he could surprise is to push his FB% back into the 40% range, as it dropped below that level for the first time this season. He’ll actually need to do that to ensure his home run total remains at least 20, as the new park puts his HR/FB rate at serious risk of dropping into the single digits.
Overall, this trade seemed to do nothing positive for any players’ fantasy values, as Longoria loses value, Ryan Schimpf still remains without an obvious starting gig, and Christian Arroyo’s lack of power and speed means that even if he now might actually have a job, it barely matters.
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.
Kiermeir is likely largely responsible for depressing the singles/doubles at the trop! He cant help out on the ones that leave the park…
That’s not how park factors work. Teams are measured against their performances at their away park to compensate for their own relative strengths and weaknesses.
Link with some more detailed explanation about why Kiermaier’s defense doesn’t skew park factors: http://www.statcorner.com/exp_HandedParkFactors.php (that’s the source of the factors Mike used here).
The trade may tough for Longoria owners, as Mike said.
But anybody who owns Machado—there were rumors he might be traded to the Giants—is thrilled.
OTOH: I’m an Orioles fan and I sure hope Duquette and Angelos don’t blow it again. They lost a chance to trade Britton for prospects last year and I’m betting that they’ll miss a chance to trade Machado for a good young prospect arm.
Off topic, I know. But it sure is frustrating to be a fan of a poorly run organization.
Thanks for using multi-year park factors Mike! This analysis is much stronger for it.
It was pretty crazy to see the volatility in the AT&T Park triples factors. Something like 165 to 135 to 105 over 3 years. I would guess part of that is due to the scarcity of triples themselves, so a small absolute change in triples will be a much higher percentage change than in other metrics and therefore have out an outsized effect on the factor.
I think you need to split this out by RHH and LHH. AT&T, if my memory serves me correctly, has a huge split as the RF area is huge, but the LF area is more forgiving and average. In short, some RHH like cody ross or pat burrell havent’ actually done bad in AT&T, whereas Brandon Belt and others not named bonds have struggled.
StatCorner’s park factors are by handedness, so unless Mike aggregated left- and right-handed numbers those should already be taken into account:
Here’s the source data (from the chart)
http://www.statcorner.com/ParkReport.php
Correct, I only used the right-hand park factors. It’s true that park factors will affect everyone differently given their individual spray charts, but AT&T will never be a hitter’s park no matter who you put at the plate.
I would love to see one of these articles/breakdowns for Yonder Alonso.
I won’t be back until after New Years, but the summary = Progressive Field excellent for left-handed homers, was a bit more favorable than Safeco and significantly more so than Oakland. Solid landing spot, and with second half decline, he should come at a reasonable price.
Can someone explain to me how a park itself could affect strikeout totals (outside of perhaps the batter’s eye) in any significant way?
It’s obvious that there would be observable patterns in K rate per park, but I would tend to consider that a factor of both pitching staff (home and division, primarily, as that’s where most of the data would generate) and potentially even the hitting coach’s approach. Nothing about the dimensions of the park, altitude, etc. should have any impact.
Foul territory – more of it = fewer walks and strikeouts because of the increased chances of fouling off and ending the plate appearance
Batter’s eye – any distraction could increase strikeouts
Atmosphere – Coors Field, the air reduces movement, making it easier to put bat on ball and avoid striking out
Coors Field notwithstanding, I wouldn’t imagine statistical significance in almost any other field’s atmospheric conditions, though it’s a valid variable to consider (however limited).
Foul territory does make sense in terms of increased chances of a foul out ending the PA, but that reasoning actually contradicts the data in this case. The Trop has some prodigious foul ground, which should lead to more foul outs, and thus fewer strikeouts, but the analysis indicates the opposite. AT&T as well. Much smaller foul area by comparison, but fewer strikeouts by park factor (even more interesting given the NL/AL difference).