Over the last couple of years, I have run the “Steamer and I” series, pitting our hitter wOBA and pitcher ERA projections against each other and discussing the players our forecasts differ the most for. I’m going to do things a little bit differently this year by focusing on individual stat categories, identifying a group of players I’m significantly more bullish on compared to Steamer, and vice versa, in that metric.

We’ll start with home runs. I will be comparing my home run Pod Projections to Steamer, which have been extrapolated to the same number of at-bats I’m forecasting. Today, we’ll look at the hitters I’m most bullish on versus Steamer.

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The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve.

A couple of months ago, I received my first Pod Projection request from a commenter, and that request was for Astros starting pitcher Lance McCullers. The 23-year-old made his Houston debut in 2015, as he made 22 starts and posted an impressive 3.22 ERA with excellent underlying skills. Unfortunately, he followed up that freshman effort by finding himself on the disabled list for what amounted to about half the season. He dealt with both shoulder and elbow issues, which limited him to just 14 starts. Although his control deserted him, he still posted strong skills, en route to an identical ERA as 2015. Now, he’s the newest member of my 2017 LABR Mixed Draft squad, so let’s find out what I projected his 2017 results to look like.

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The section below before I reveal my team is going to be similar to previous LABR recaps since little has changed and there’s no sense in rewording things.

It’s mid-Feburary, so you know what that means…another super eeeeeeaaaaaaarrrrlllllllyyyyyyy LABR Mixed draft has been completed! Tout Wars auctions don’t take place for another month, my local league’s auction is in the same boat, and opening day is still six weeks away! The early timing of LABR Mixed presents some interesting challenges in that there are many position battles yet to have even begun and poor Pedro Alvarez still finds himself teamless. So on one hand, it requires us to perform serious research and really know the depth charts, but on the other, we’re all just speculating, crossing our fingers, and hoping for the best.

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Nearly a month and a half ago, I shared the names of six starting pitchers who my old xK% metric suggested had the most strikeout rate upside this season, assuming their equation components remained unchanged. I then got sidetracked, introduced an updated version of the equation with new component coefficients and then even played around with incorporating CH% (changeup percentage) into an even newer version of the equation. So I never actually got around to the list of starting pitchers with strikeout rate downside. It’s now time to share those names with you very patient people.

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So it’s been an xBABIP two weeks and we’re just about through analyzing every aspect of my new equation. Over the last couple of days, I’ve looked at the 2017 BABIP surgers and BABIP decliners, but the majority of the names were fairly obvious. If you posted a .230 BABIP in 2016, you’re probably going to find yourself on a potential surger list, while a .380 BABIP is likely going to get you onto the decliner list. Commenter Tom Cranker suggested cherry-picking a list of fantasy relevant hitters who posted 2016 BABIP marks around the league average (.300) who xBABIP actually believes should have performed significantly better or worse. These guys you wouldn’t think twice about believing their BABIP marks since they aren’t out of the ordinary, but their underlying skills suggest otherwise. Let’s take a look at some of those names.

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Let’s now follow up yesterday’s 2017 BABIP decliners list by looking back at who the new xBABIP would have convinced us to avoid heading into the 2016 season. Like I did when validating xBABIP using the surgers, I’ll compare how the would-have-been 2016 list performed versus their 2015 xBABIP and 2016 Steamer projections.

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Last Thursday, I used my new xBABIP equation to identify 10 fantasy relevant hitters whose xBABIP marks were significantly above their actual BABIP marks, suggesting serious BABIP upside in 2017. Today, I’ll make many of you sad with a list of names who are at risk of major BABIP regression this season, if they don’t improve their underlying skills by a massive degree. By no means do you want to avoid these names, you just simply don’t want to value them assuming their 2016 BABIP marks are actually sustainable. But since someone in your league probably does believe the 2016 BABIP is real, you probably won’t end up rostering them at a fair price.

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A week ago, I introduced the newest version of our ever evolving xBABIP equation, this time incorporating the much-needed shift data. Last Thursday, I identified the 10 fantasy relevant hitters with the greatest BABIP upside in 2017, given the gap between their 2016 BABIP and xBABIP. In the comments, I was asked if I could perform a retrospective analysis to see how the new equation would have done if I ran it heading into the 2016 season.

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Finally, after unmasking the newest version of xBABIP that accounts for shifts, it’s time to get to the names…you know, the kind of list you could actually use for your fantasy leagues this year! So let’s identify and discuss the fantasy relevant hitters whose xBABIP marks were significantly above their actual BABIP marks. These ten hitters should enjoy a BABIP rebound in 2017, assuming their BABIP-related skills remain stable.

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It’s xBABIP week and on Monday, I unveiled the latest incarnation of my equation, this time incorporating shift data. Then yesterday, I analyzed leaguewide shift data trends and unearthed some interesting tidbits. Today, it’s finally time to talk some names. We’ll begin by looking at the players that enjoyed the biggest gains using the new xBABIP equation versus Alex Chamberlain’s 2015 version that I had been using as my primary go-to, and also the biggest losers.

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