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.
You don’t need me to tell you that 2015 produced an outstanding group of Rookie Hitters. The question is which player rises to the top of this very stellar group?
In order to make this determination, we first needed to select criteria upon which to assess offensive performance. In my opinion, RC+ is a great tool because it is easy to use. Any two players can be compared because it establishes a league average rate for position players of 100. It also controls for league and park effects but does not control for position played which will enter the conversation latter. Since we are talking about hitting only, we are not factoring in the defensive wizardry or lack thereof of any of the players selected.
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.
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.
Episode 285
The latest episode of “The Sleeper and the Bust” is live!
In this episode, Paul Sporer and Eno Sarris are back to discuss more playoff standouts including Daniel Murphy, Stephen Piscotty, Kevin Pillar, and Jorge Soler. They finish with scouting reports on the game 1 starts of each LCS and how the teams facing them might find success.
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This is one of those fun awards where there is debate about what the award means. Roto and Hitter are clear, but what constitutes a comeback? Does the winner have to come back from injury or ineffectiveness or both? How good does he have to be to have “comeback?”
Well, since I get the only vote, I also define the parameters. I prefer unexpected comebacks, so I give more credit to coming back from ineffectiveness than injury. I think you need to make a BIG return to win this award – going from top 20 bat, to borderline useful player, to top 20 bat is more impressive than going from top 75 bat, to top 200 bat, to top 75 bat. With that in mind, my pick: Chris Davis.
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.
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.
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.
Reviewing one’s bold predictions is like opening that tupperware container that’s been forgotten at the back of your refrigerator for some time: you hope the contents might still be edible, but in actuality, you’re about to see something you wish you hadn’t, and the smell isn’t too good, either. Here we go.
As a heads up, the rankings below rely on ESPN’s Player Rater.
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