Every pre-season, I compare my rankings to the RotoGraphs consensus (which excludes my ranking of course) to discover which players I’m apparently more bullish or bearish on than the others. I was strapped for time this year and so only published a bullish piece for hitters, dubbed Pod’s Picks. Let’s see how these hitters ended up performing and ultimately ranking. Remember that the rankings are positional and not overall, which makes this exercise a bit more difficult. I’ll be using the FanGraphs auction calculator to compare values.

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Yesterday, I reviewed my preseason list of starting pitchers composed of guys my Pod Projected ERA was significantly better than Steamer’s forecast. They were my upside guys. Today, I’ll recap how the guys my projections considered as having ERA downside ended up performing. You might notice that this is half the size of the upside list, which likely owes to my projections being more optimistic on ERA on the whole.

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Let’s flip back to evaluating my preseason pitcher projections. I compared my Pod Projected ERA with Steamer’s ERA projections and discussed 11 I was most bullish on. Let’s see how they performed. Hopefully I didn’t embarrass myself. Also, be aware that these were the projections as of the date my post was published, which was March 6. It’s very possible that my or Steamer’s ERA projection changed from then through the beginning of the season.

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Piggy backing on my research into previous season breakouts published on The Hardball Times, I identified and discussed 12 such men from 2017 as we pondered 2018 performance. Not surprisingly, I discovered that last season’s breakouts made for terrible investments. Of course, this was as a group in aggregate. It doesn’t necessarily mean that every prior season breakout will bust. But as a group, they don’t make for good draft day targets.

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In addition to sharing my standard lists of potential BABIP surgers and decliners heading into the 2018 season based on my xBABIP equation, I also discussed hitters who seemingly posted repeatable BABIP marks at first glance, but a deeper dive revealed the potential for dramatic upside or downside. These were the guys whose BABIP marks were around the league average (appearing rather normal), but with xBABIP marks at least 0.030 points above or below. Let’s see how they ended up performing.

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Yesterday, I reviewed the list of 11 potential BABIP surgers for 2018 I published in mid-February. Today, let’s look at my BABIP decliner list. Given my past successes with decliners vs surgers list, I’m betting this list is going to look good. Let’s see if that turns out true.

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In mid-February, I identified and discussed 11 hitters whose xBABIP marks stood significantly above their actual BABIP marks. I dubbed the group the potential BABIP surgers for 2018. There are two important caveats to remember:

1) This equation, while the best currently out there for estimating what BABIP should have been given underlying skills, is still not great, leaving lots of room for batters skills not captured in the equation, and of course, lady luck
2) xBABIP is not predictive/forward looking/a projection. It’s backwards looking like SIERA, but it correlates with next year BABIP better than BABIP itself, which is quite meaningful.

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Yesterday, I reviewed the list of hitters who might benefit from an increased rate of pulled flied balls heading into the season. Today, I’ll recap the hitters who already hit a ton of fly balls in 2017, but posted below average Brls/True FB and Avg FB Dist marks. The thinking here is they needed every bit of that FB Pull% to knock balls over the fence, considering they were below average in the other two metrics. Let’s see how they performed.

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In early February, I essentially listed hitters who have posted low fly ball pull percentages. However, I added two important additional filters to finalize the list — above average Brls/True FB and Avg FB Dist. The idea here is that they already have the raw power to hit their balls out of the park, but they just need to hit those balls more to the pull side where the fences are closer. These are the guys I considered potentially benefiting most from more pulled flies. Let’s find out whether they did indeed increase their FB Pull% and if that jump also fueled a spike in HR/FB rate.

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Yesterday, I reviewed my preseason list of nine potential strikeout rate surgers. Today, let’s find out how the 10 pitchers I identified as potential strikeout rate decliners actually performed.

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