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.
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.
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.
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.
Let’s continue our recaps of my Pod vs Steamer projections series, this time with stolen bases. As a reminder, I compared my 2017 Pod Projection stolen base forecast to the Steamer projected, extrapolated over the same number of plate appearances I had projected. This group is composed of those whose Pod Projected stolen base total most exceeded the Steamer projection. Let’s see how they did.
Before taking a short vacation, I reviewed the first preseason Pod vs Steamer Projections series posts, focused on home run upside. That article discussed the hitters whose home run Pod Projection was significantly greater than his Steamer projection. Today, I’ll recap the players I identified as possessing significant home run downside compared with Steamer. With the record setting home run total, this shall be interesting.
Before the 2017 season, I decided to switch up my typical “Steamer and I” series posts where I discuss one player in which my Pod Projections differ from Steamer. Instead, I compared my projections in specific fantasy categories to identify upside and downside guys my forecasts hinted at versus Steamer, representing the crowd. Let’s begin our recaps of the new series with the home run upside group, which are those hitters I projected for significantly more home runs than Steamer. Note that I extrapolated the actual Steamer home run projections to match the same number of at-bats I projected, so playing time differences wasn’t a factor.
Yesterday, I reviewed my list of 2017 HR/FB rate surgers, utilizing my Statcast-fueled xHR/FB rate to identify the guys with significant upside. Today, I’ll recap the list of HR/FB rate decliners. Having not yet looked at my list, I’m nervous the leaguewide spike to record-setting home run numbers is going to make me look silly. Let’s find out!
Geez, I could have blindly selected a handful of hitters whose HR/FB rates were due to rise in 2017 and probably would have hit on the majority! As I continue to recap my preseason lists, let’s move on to my 2017 HR/FB rate surgers. I compared my 2016 Statcast-fueled xHR/FB rate to the hitter’s actual HR/FB rate and identified six hitters whose xHR/FB rates were significantly above their actual marks, suggesting serious upside. Let’s see how these hitters performed.
Last Thursday, I discussed the 10 hitters I identified in the preseason as potential 2017 BABIP surgers, due to xBABIP marks well above actual marks. Eight of the nine hitters that actually recorded an at-bat enjoyed a BABIP increase. Let’s see how the nine hitters I identified in the potential BABIP decliners list fared.
