Pod vs Steamer — HR Upside

Every year, I pit my Pod Projections against the Steamer projections in various categories. Today I’m going to continue the annual smackdowns by calculating AB/HR rates and then extrapolating them over 600 at-bats. At that point, I’ll compare how many home runs each system is forecasting, given a 600 at-bat projection. I’ll start by sharing the names of hitters Pod is projecting for significantly more home runs than Steamer. Many of these players figure to be part-timers, so consider them sleepers in deeper leagues.

Before diving into the names, remember that I rely heavily on my xHR/FB rate equation, which utilizes Statcast’s barrels and average fly ball distance, as well as pull and opposite percentage on fly balls, to settle on my HR/FB rate forecast. Also remember that there are only three reasons a home run forecast could be different — disagreement on HR/FB rate, fly ball rate, and strikeout rate. Unfortunately, the only forecast of the three that is published here for Steamer is strikeout rate, so we’ll have to guess on the other two.

I guess I, and you as a reader of my recent articles, shouldn’t be shocked to see Mike Yastrzemski’s name on an island all by himself. It’s true that he’s already 29, so he would be the epitome of “late bloomer”, but he’s shown excellent power at times in the minors. Plus, his home run breakout kind of began at Triple-A in 2019 where he posted a 28.6% HR/FB rate, a new career high at any stop. Now granted, that was his fourth stint at the level, and again, he was 28/29 at the time. But his 17.2% xHR/FB rate validates that at least what he did in the Majors was legit. He also did that with a slightly below average fly ball pull rate, though that could have been on purpose due to his home park. Speaking of which, his park is going to become a bit less pitcher friendly, which should help him sustain that high teen HR/FB rate.

Paging Alex Chamberlain, Paging Alex Chamberlain. Who would have thought that getting out of Colorado was all Mike Tauchman needed to show the world he actually could hit? I’m struggling to figure out why I’m so much more optimistic than Steamer is, as my HR/FB rate forecast assumes some healthy regression down to 15%. Perhaps Steamer is even lower? xHR/FB rate says 14.2%, but Yankee hitters sometimes outperform dramatically, depending on how they utilize the park.

Sleeper alert! Sleeper alert! Sam Hilliard is possibly what Tauchman could have been if he had stayed in Colorado. With so many potential outfielders, it won’t be clear until perhaps Opening Day whether Hilliard will be on the strong side of a platoon, open the year as a reserve outfielder, or even in the minors. But this guy broke out the power at Triple-A, and then carried it over during a cup of coffee with the Rockies. He even steals bases! He would be on all my teams if I could count on the Rockies to give him 500+ at-bats.

I’m quite surprised to find Tom Murphy’s name on this list, though now it seems pretty clear why — it’s the strikeout rate. I’m all the way down at 29.4%, while Steamer is at 34.1% (the rest are in the low-to-mid 30% range). So am I crazy? I have been using a new hitter xK% metric that I never shared, and it’s just as strong as my pitcher xK% equation…as it should be since it uses exactly the same components! Murphy’s xK% was only 27.6% in 2019, so he seems to have been quite a bit unlucky striking out over 30% of the time. We’ll see if he could maintain his strike type rates and push his strikeout rate below 30% like I’m forecasting.

Jacob Stallings is a nice cheap catcher sleeper, and we all like cheap catchers who might not kill you, right? His power has been MIA most of his minor league career, but jumped in a tiny Triple-A sample in 2019, before he maintained that home run power with the Pirates. And guess what? xHR/FB rate backs it up, spitting out a 15.2% mark, thanks to a strong pulled fly ball tendency.

It’s about time those gargantuan arms paid dividends for Yandy Diaz. Not only did he push his HR/FB rate into the high teens, he finally got his fly ball rate above 30%. There’s a lot for a projection system to regress here, so it’s no surprise that a computer doesn’t believe Diaz could be a transformed man. By the way, Diaz’s xHR/FB rate was…20.5%, suggesting he was actually unlucky. I know the Rays make us nervous with their playing time merry-go-round, but that just gives us some serious profit opportunities.

I loved Franchy Cordero heading into last season, but with so little playing time the last couple of years, this is really just a bunch of guesses. He’s worth a gamble if he wins a job though.

Another Ray?! This time, I’m actually two points higher on Brandon Lowe’s strikeout rate than Steamer, so that’s not the explanation. It must be the HR/FB rate, but again, my xHR/FB rate suggests Lowe underperformed last season. With a huge barrel rate and above average distance, he actually has additional upside if he chose to pull more of his flies.

LOL to see Christian Yelich’s name here. When do the projection systems finally buy in?

Scott Kingery has shown this kind of power before, as back in Double-A in 2017, he posted a similar HR/FB rate, and a robust .295 ISO. His xHR/FB rate completely validates his 2019 mark, though it’s not saying a whole lot since he was essentially league average in all components. Remember though, league average HR/FB rate was 15.3%!

FREE JOSH ROJAS!