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.

2017 Pod Projections Index:
Lance McCullers
David Dahl

Who would make for the perfect hitter to be Pod Projected? The one with the biggest difference between the Fans and Depth Chart projections, of course!

Biggest diff between fans & depth charts:
1) Broxton
2) CSeager
3) TimA
4) Drury
5) CHernandez
6) Yoan
7) Eaton
8) GaryS
9) Bryant
10) Votto

— Eno Sarris (@enosarris) February 28, 2017

The Fans projections are notoriously bullish, but sometimes they rightly believe in a breakout, whereas the projection systems are programmed to forecast severe regression. Keon Broxton is no Spring chicken and is already 26 heading into the 2017 season. But he got his first chance to play regularly last season and made the most of it by posting a .343 wOBA, displaying both power and speed, excellent plate patience, and playing fabulous defense. Naturally, everyone is skeptical, though the Fans are far less so than Steamer and ZiPS. What about the Pod Projections, you ask? Let’s find out!

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Today, I continue the comparison of my Pod Projections to Steamer in various fantasy categories, this time identifying players I believe have stolen base upside. My stolen base projections are calculated using a proprietary metric I developed that is revealed in Projecting X 2.0. Essentially, it’s a stolen base attempts per opportunities ratio and I use historical rates to guide my projected rate.

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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.

2017 Pod Projections Index:
Lance McCullers

Today, I’ll dive into the first hitter to receive the exciting 2017 Pod Projection treatment. David Dahl thrilled us during his debut last year, showing power (.185 ISO), speed (7.7 Spd score, five steals), and batting average ability (.315). That’s literally everything we want as fantasy owners. Of course, let’s not ignore the fact that he required an absurd .404 BABIP to reach that impressive batting average mark. That said, he plays half his games at Coors Field, so perhaps his average has some staying power. Early 2017 NFBC drafters are already falling over each other to roster him, selecting him as the 22nd outfielder off the board (just before Matt Kemp, Khris Davis, and Adam Jones), and 91st overall. WOWZERS! That’s some serious love.

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I love comparing my Pod Projections to Steamer, since mine are all done in a massively time consuming manner by hand, while Steamer is spit out by the almighty computer in mere seconds. It works as a sort of checks and balances system, as I am likely aware of various issues the computer doesn’t know about, while I might have some inherent biases I don’t even realize that the computer won’t suffer from.

So today, I continue my new series pitting my projections against Steamer in a specific fantasy relevant stat category. Last Thursday, I listed the hitters that I was most bullish on for home runs compared to Steamer, so today, I’ll look into the hitters Steamer is most bullish on compared to my projections.

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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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