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.

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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.

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Let’s stick with my xBABIP equation and discuss the group of 10 hitters I identified as potential 2017 BABIP surgers. These were the guys whose xBABIP marks were significantly above their actual BABIP marks.

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Sometimes it’s obvious when a hitter’s BABIP is due for a rebound or regression, but that isn’t always the case. For the first time before this season, I decided to discuss some of the hitters whose BABIP marks looked relatively sustainable, but my new xBABIP equation disagreed. Let’s see how this group ended up doing.

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Yesterday, I reviewed the 2017 starting pitcher walk rate improvers using my updated xBB% equation. Today, I’ll recap my walk rate regressers, which includes those starting pitchers whose actual walk rates were significantly better than their xBB% marks.

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In late January, I updated my pitcher xBB% was include and additional variable, 3-0%, which is the percentage of a pitcher’s plate appearances in which a 3-0 count is seen. Since Alex Chamberlain had already published such a formula, which built upon my original equation, I simply updated the variables of his. I then used the new formula to highlight a group of starting pitchers with an xBB% significantly lower their actual 2016 marks. This group was then discussed as potential walk rate improvers in 2017. Let’s see how they did.

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Yesterday, I reviewed my 2017 starting pitcher strikeout rate upsider list, which produced embarrassing results. Let’s hope the downsider results look much improved. Once again, this list was compiled by using my pitcher xK% equation to identify starters whose 2016 xK% marks were significantly above their actual K% marks.

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At the beginning of January, I used my xK% equation to identify six starting pitchers with significant strikeout rate upside in 2017. Let’s see how these pitchers actually performed.

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Alas, we reach the final position to dive into for this year’s recap of Pod’s Picks & Pans. We finish with the starting pitchers, a group that always garners varying opinions. Let’s see how the players I was most bullish and bearish on versus the RotoGraphs consensus actually performed.

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Today we complete the hitter side of the 2017 Pod’s Picks & Pans with the outfielders. Let’s see how my rankings on the players I disagree with the RG consensus performed.

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