I think Ryan Schimpf is my favorite player. He takes the word extreme to an entirely new level, ranking at or near both the top and bottom of various statistical categories, for the better and for the worse. That’s what makes him such a fascinating hitter. He debuted with the Padres in 2016 to excellent results over about a half a season’s worth of plate appearances. He was a new breed of hitter – a five true outcomes type, as his plate appearances generally ended with either a walk, strikeout, fly out, pop-up, or home run. The approach worked that season, but failed miserably in 2017. His performance earned him a demotion to the minors, and ultimately a ticket out of San Diego.

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The best inspiration for an article is one in which you find a meaningful leaderboard, sort away, and identify who doesn’t belong. The surprise of the group, if you will. That player is most certainly going to be fun to discuss! That brings me to Eddie Rosario. If you perform a Statcast search and select only “Barrel” for “Quality of Contact” from August through the end of the season, you will be presented with a leaderboard of top sluggers ranked by number of barreled balls they hit during that time period. The top 10 is littered with your standard who’s who of the game’s best power hitters. Then you get down to #14 and who do you find, none other than Eddie Rosario.

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Last week, the Cubs signed Tyler Chatwood, who has had the unfortunate luck of spending the majority of his Major League career pitching half his games in the most offense friendly home park. He has still managed to perform respectably given the circumstances, posting a 4.31 ERA and 95 ERA- (5% better than league average where lower is better) over his career, which includes 142 innings with the Angels in his 2011 debut. Now heading into his age 28 season, let’s see how the park factors compare between Wrigley Field and Coors Field and why the move makes him a prime sleeper.

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Alas, we have finally reached our final 2017 preseason article recap! Welllll, this one shouldn’t have been the last one, but no one wants to read a recap of my David Dahl Pod Projection, right? So we wrap things up by reviewing my Pod Projection for curveball aficionado Lance McCullers, who was coming off around 200 innings of 3.22 ERA ball supported by strong skills over his first two seasons. Health was a question mark, but there was no doubting his talent. Let’s remind ourselves what I forecasted for his 2017 performance and how he actually performed.

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Today let’s continue recapping one of my 2017 Pod Projections, this time heading to Milwaukee to discuss Keon Broxton. Coming off an intriguing half-season in 2016 that featured an exciting blend of power and speed, along with some clear flaws, he was a popular sleeper for 2017 and one whose projections people couldn’t really settle on. So what was I projecting and how did that compare to his actual results? Let’s find out.

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Moving along on our recaps of my 2017 Pod Projections, we stumble upon Trea Turner, who delivered a fantasy half-season back in 2016 that made him the talk of the town heading into 2017 drafts. He was so darn good, he was generally a first round pick. How much, if any, regression was I projecting and how did that compare to his actual results? Let’s find out.

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It’s time to recap some of my 2017 Pod Projections! This preseason, I begun the series with one of 2016’s most surprising pitchers, Kyle Hendricks. We all figured that even backed by the historically strong Cubs defense, he was quite a bit fortunate en route to a sub-3.00 ERA. But how much regression was I projecting and how did that compare to his actual results? Let’s find out.

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Yesterday, I recapped my comparison of the starting pitcher ERA Pod Projections vs Steamer projections in which I was more bullish. Today I finish reviwing the Pod Projections vs Steamer projections series by looking at the group of starters I projected for worse ERA marks. Since I mentioned in yesterday’s article that I projected a lower ERA than Steamer for the vast majority of starters (which is one of the reasons I performed so poorly in the results comparison), I only had 21 pitchers whose ERA I was projecting a higher mark for. So this group to review is much smaller and the gap in ERA between the two projections is as well.

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We’re winding down the recaps comparing my Pod Projections to Steamer projections and will finish things off by moving on over to starting pitchers. We’ll begin by checking in on the group of hurlers in which I had forecasted a significantly better ERA than Steamer. Let’s see how these pitchers actually performed.

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Yesterday, I reviewed my Pod vs Steamer projections series with the stolen base upside guys, those hitters whose Pod Projection in stolen bases was well above the Steamer extrapolated projection. Today, I’ll finish the series on the offensive side with the stolen base downside list, the guys I projected to steal far fewer bases than Steamer. Let’s see how they performed.

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