Miguel Cabrera hasn’t just been one of baseball’s best hitters over the last ten years, he has also remained amazingly consistent. As fantasy owners, we’re used to our top picks disappointing us, but Cabrera has never posted a wOBA below .374 in a full season. And yet, this was a season of firsts for Cabrera, which despite an above his career average .413 wOBA, resulted in a loss for all those who paid top dollar for his services on draft day.

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Yesterday, I recapped my preseason starting pitcher strikeout rate upside target list using my xK% equation. So naturally today I’ll review the other side of that list, those pitchers who posted strikeout rates well below their xK% marks, which suggested potential downside for the 2015 season.

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Review season continues this week and I begin by analyzing how well my xK% equation performed at identifying starting pitchers with strikeout rate upside in 2015. When I originally created my upside target group, it wasn’t a straight list of the starters whose xK% marks most exceeded their actual K% marks, but rather the more interesting names that were fantasy relevant that appeared at or near the top.

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In the majority of fantasy leagues, Jonathan Lucroy was likely valued as a top five catcher. His strong batting average, respectable power, and best of all, consistently high plate appearance totals, made him a top option at the position. But as the books closed on the 2015 season, Lucroy finished just 12th, the last man to accrue any value in 12-team mixed leagues that start just one backstop. We’re used to catchers disappointing, which is why many fantasy owners choose to “punt” the position and just go cheap, refusing to pay the market rates for the elite. So let’s find out what went wrong.

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It’s highly unlikely that Welington Castillo was drafted in your shallow mixed league this season. And heck, he was the last pick in the 15 team LABR mixed draft. He wasn’t even the starting catcher for the team he started the year with and he ended up being a member of three different organizations by season’s end. And yet after all this, he still managed to earn the 11th highest value among catchers.

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Remember this site? Of course you do. This was one of the many “facts” we learned about Matt Wieters:

Before reporting to Camden Yards, Matt Wieters traveled through the time-space continuum and righted all the wrongs in Orioles history: He wiped Cleon Jones’ shoe polish off the ball, settled the 1981 baseball strike so they could win the division, straight-jacketed Jeffrey Maier, and intercepted Roberto Alomar’s loogie before it hit its mark.

After crushing minor league pitching in 2008, Wieters was all the rage. And that hype train was what spawned this hilarious-at-the-time page. Now, it looks silly in hindsight.

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Review season continues and today I’ll recap the starting pitchers whose spring training strikeout rates were significantly above their Steamer projected K% marks. As a reminder, with the help of Matt Swartz, I found that spring strikeout rates do provide meaning with regards to regular season performance, something that Dan Rosenheck validated as true more recently.

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So yesterday, I reviewed the results of my other HR/FB rate analysis based on ESPN Home Run Tracker data and recapped the players identified as having significant upside in 2015. My list didn’t perform too well, so let’s hope today’s goes better. I’ll be checking in on the guys who hit the most Just Enough home runs in 2014, which I deemed as having serious HR/FB rate downside in 2015.

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Today I’ll review another article focused on identifying hitters with home run upside. On Monday, I recapped the names based on my xHR/FB rate equation, while today I will discuss the list I cobbled together using ESPN Home Run Tracker. What’s always interesting is when both methods disagree and I’m not always sure which to believe. I tend to side with the xHR/FB rate equation though just because the formula uses significantly more data points.

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Yesterday, I reviewed my preseason target list of hitters whose xHR/FB rates suggested significant HR/FB rate upside in 2015. Today I’ll recap the opposite end, those hitters who my xHR/FB rate equation suggested had significant HR/FB rate downside. These were the guys who most outperformed their xHR/FB rates in 2014 and were at risk of a decline.

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