Pod vs Steamer — Home Run Upside

Last year, I transformed my series pitting my Pod Projections against Steamer projections into a categorical comparison. I’m going to continue that this year, but instead of comparing counting stats extrapolated over my plate appearance projection, I’m going to go straight to ratios. As an ardent supporter of ratios over counting stats, I have no idea why I didn’t do this to begin with!

We’ll start with guys I’m projecting for better home run production than Steamer. I looked at players I’m projecting for at least 400 at-bats and 10 homers and compared the AB/HR forecasts from each system. I then calculated the percentage of the Steamer AB/HR mark the Pod Projection represented. That method evens out the lower and higher numbers for a more accurate comparison.

The difference in AB/HR can be driven by one or a combination of these three factors – strikeout rate, fly ball rate, and home run per fly ball rate. Since Steamer’s FB% projections aren’t available on FanGraphs, I can only determine whether a discrepancy between K% is the culprit.

So here are the seven fantasy relevant hitters in which the Pod AB/HR projection is less than 90% of Steamer. After running the calculation for all hitters, it’s clear that Steamer is much more bullish on homers overall than I am!

Pod vs Steamer — HR Upside
Player K% FB% HR/FB Pod AB/HR Steamer AB/HR Pod % of Steamer
Colin Moran 21.4% 38.0% 14.0% 24.4 33.7 72%
Chris Taylor 23.6% 36.0% 11.5% 32.5 41.9 78%
James McCann 22.3% 35.0% 13.5% 27.7 34.1 81%
Elvis Andrus 14.4% 31.0% 9.5% 39.7 48.3 82%
Jorge Bonifacio 25.4% 37.0% 16.0% 23.3 27.8 84%
Matt Carpenter 19.6% 45.0% 12.7% 22.6 26.2 86%
Whit Merrifield 15.8% 38.0% 7.5% 41.8 48.5 86%
Aaron Judge 31.1% 43.0% 30.0% 12.1 13.7 88%
Joey Gallo 35.3% 53.0% 28.5% 11.3 12.8 88%

You know what a computer system is wholly unaware of? Mechanical/swing changes. That clearly explains Colin Moran’s appearance at the top of the list, as he was one of the many beneficiaries of the fly ball revolution. The adjustments he made heading into 2017 led to a surge in both FB% and HR/FB rate at Triple-A. I believe it, whereas a computer system is going to be more skeptical given the mediocrity that came before. Prime NL-Only and deep mixed league sleeper.

Ha, one of last season’s out of nowhere breakouts, Chris Taylor, is sitting second on this list. Makes me look like a noob, huh? But here’s the thing — his xHR/FB rate was a solid 13.7%, not far below his actual mark, which suggests legit improvement, rather than a completely fluky performance. Even with dramatic HR/FB regression baked in, my projection is still far more bullish. That’s likely because Taylor had only posted a double digit HR/FB rate once in his minor league career, and that came back in 2013 at High-A. His next highest mark over a reasonable sample was just 6.9%. But guess what? He’s another swing changer, and learned from a fellow one, teammate Justin Turner.

Part of the discrepancy for James McCann is the strikeout rate — I’m projecting an improvement, whereas all the projections are forecasting it jumps back up near 24%. The reason for the bullish strikeout rate? A career high Contact%.

At the risk of sounding like a broken record, Elvis Andrus is yet another typically light-hitting middle infielder who broke out the power in 2017. Naturally, a computer projection system is going to bet on severe regression. But he truly is a new hitter. And about his first teen HR/FB rate and nearly double his previous best of 6.7%? Well, xHR/FB rate suggests it could have been better, calculating a 12.3% mark. It’s totally fine to question whether he could do it again, but make no mistake — this ain’t no low-to-mid-single digit HR/FB rate guy any more.

Jorge Bonifacio isn’t a fly ball revolution joiner or surprise 2017 breakout. Instead, he was just a rookie who posted the highest HR/FB rate of his professional career, almost doubling his previous career high set in the minors. No one expects him to repeat. But with an xHR/FB rate nearly as high as his actual mark, it’s hard to ignore the possibility that he is simply a better power hitter now, as he continued to develop in the Majors. Another potential difference could be in his fly ball rate projection, as I’m projecting a marginal increase, given 40%+ fly ball rates in the minors.

Matt Carpenter battled injury last year, plus his xHR/FB rate was slightly higher than his actual mark. I’m projecting a small rebound, plus a better strikeout rate than Steamer. I’m also expecting him to hold onto some of his FB% gains.

Whit Merrifield! He’s the third middle infielder on here who surprised with his power last year. But was it really so outrageous? He only posted a 9.4% HR/FB rate, but managed to knock 19 homers thanks to an excellent 14% strikeout rate. His xHR/FB rate was actually just above 10%, while even his 2016 mark was 7.6%, more than double his actual mark. Even regression to a 7.5% HR/FB rate has led to such a gap in AB/HR, which I think is crazy.

It’s quite funny to find Aaron Judge and Joey Gallo at the bottom of this list. Let’s figure out what brought the two of them here. Interestingly, I’m projecting a slightly worse strikeout rate for each of them, so that eliminates strikeout rate as the cause of the discrepancy. It could well be fly ball rate, as both are well above the league average and even though their history supports these levels, a computer system might still be regressing heavily. It could certainly also be HR/FB rate as these are two of my highest forecasts. If you’re curious, Judge’s xHR/FB was right on target at 36%, while Gallo’s sat at a robust 28.7%.

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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The less AB/HR, the more HR for equal total of ABs. So, someone with 20 AB/HR would hit 25 HRs in 500 ABs, While someone with 25 AB/HR would hit 20 HRs in 500 ABs. Thus, POD would be more bullish on HRs than Steamer. Also, the difference column of the chart is showing the % of Steamer that POD represents, not the difference. Example, Colin Moran’s difference would be 28%, not 72%. Or, am I lost?


Chicago Mark
Chicago Mark

Did he change it or am I reading it wrong? Pod’s picks all have lees AB/HR giving them home run upside.


Steamer overall projects more home runs, but this table is specifically those players for which Mike projects more home runs. These guys are the biggest exceptions to the trend.

The Real McNulty
The Real McNulty