Alas, we made it to the last Pod’s Picks & Pans recap, as we conclude with the starting pitchers. Since I pride myself on my pitcher projections, I always feel pressure to deliver more accurate forecasts, and ultimately, rankings. Let’s see how things turned out this year.
Matt Moore didn’t post jaw-dropping numbers in 2016, but the year should be viewed as a success. He had a rocky 2015 season coming back from Tommy John surgery, and he set a new career high with 198.1 innings split between the Rays (130.0 innings) and Giants (68.1 innings) in 2016. Staying healthy enough to knock on the door of 200 innings is a success in its own right. The surface stats and ERA estimators weren’t great, and he finished 60th among starting pitchers, but I’ll once again be firing up the hype machine for the once highly-touted prospect. Read the rest of this entry »
On Wednesday, I released my Way Too Early Rankings for starting pitchers. It’s by far the hardest position to rank this early in the offseason because there’s just soooo much information to incorporate. Part of this exercise was designed to have you call me out when I made a glaring mistake. I may have done so with Danny Duffy.
Baseball’s supposed to be a simple game and it is in theory. But the deeper a person digs, the more complex it gets. ERA estimators like FIP, xFIP, kwERA, and SIERA came along to help explain the limits of ERA. The main issue with each metric is how to deal with batted ball data. More specifically, they fail at it. I tried to answer the batted data question with pERA but it only explained some of the differences. Even with all those attempts to fill in the missing data, some differences haven’t been explained. Today, I am going to fill in on missing gap while examining a pitcher’s breaking ball zone rate.
Today’s study will be sponsored by Michael Pineda and Robbie Ray. Each pitcher has posted good strikeout and walk numbers which historically has pointed to good ERA’s. Instead, they get hit around and their ERA’s are quite a bit higher than their estimators. Here are the career stats for the pair.
In his first plate appearance he knocked a two run double that short hopped the deepest part of the ballpark on his way to a three hit, four RBI major league debut. He registered Division, Championship, and World Series starts during his rookie season. He has a career 3.16 ERA after his sophomore season, a talent for spinning various household objects on his finger, and his grandfather is a baseball meme. Of course I am talking about Steven Matz, the 25 year old Metropolitan South Paw.
A few weeks ago I claimed Steven Matz ranked 7th among the top starting pitchers using xStats (xOBA, VH%, scFIP, etc). This may have been a little controversial to some, and I know it brought a smile on a few others. While that ranking was, more or less, algorithmic, I do stand by the assessment of Matz. He is good. He is very good. He may be one of the most underrated starters right now, and that needs to change.
The fun continues as the fantasy-like trades are piling up! Yesterday, the White Sox continued their fire sale by making a four-player trade, with Lucas Giolito being the centerpiece of their return. Heading into the 2016 season, Giolito was an elite prospect, ranking as the best in the Nationals system, thanks to a lethal fastball-curve ball combo. But a poor showing over a small sample in the Majors has dimmed his star a bit. Now rather than trying to rebound in the more pitcher friendly National League and a neutral Nationals Park, he’s going to have to regain his status in the American League in one of the most home run friendly parks in baseball.
With the calendar turned to December, the “Way Too” portion of the title feels incorrect. Still, we have a series to finish so let’s get down to business. This is the seventh of eight volumes in the Way Too Early Rankings collection. Pre-Order the complete edition now – it makes a great stocking stuffer! You can find outfielders and links to the rest by following a link.
As a reminder, these rankings represent my first reactions rather than a truly rigorous approach. I’ve used an absolutely objective technique called mental math to compile the lists. I’m assuming a standard 5×5 format.
The purpose of this exercise is two-fold: to get an early start on 2017 rankings and to crowdsource missing or misranked players. That’s where you come in. Let your thoughts and feelings be known in the comments. As we’ve done in previous editions, we’ll break this into digestible chunks.
Starting pitcher is the deepest and most difficult position to rank. I’ll be focusing written analysis on the players who most interest me. There’s a very high likelihood some players have slipped through the cracks. I think we’ll have a lot to talk about in the comments.
Yesterday, we were treated to a thrilling blockbuster of a trade, the type that has probably become all too common in keeper leagues, in which a contending team gives up their top prospects, and a rebuilding team “dumps” their star(s) in return. You know by now that Chris Sale is heading to Beantown and will don a Red Sox uniform. Or perhaps you just heard that his socks have changed color, ya know, from white to red. Paul Sporer gave you a quick rundown on how the move is likely to affect Sale’s fantasy value, but I wanted to go through the park factors and get more specific. So let’s compare the relevant park factors and discuss how the park switch may impact his performance.
Clayton Kershaw missed a big chunk of the season yet he was still a fantasy MVP. The real world NL Cy Young award debate was duplicated in fantasy land with Max Scherzer and Kershaw comfortably leading Jon Lester, Kyle Hendricks, and Madison Bumgarner. What’s more valuable, Scherzer’s quantity or Kershaw’s quality? Our auction calculator says quantity by $1.50.
Hyun Soo Kim signed with the Orioles before last season on a two-year deal. He struggled mightily in spring training and because of the nature of his contract, the major league team was forced to roster him. After just 17 plate appearances in April, he became a decent semi-regular in the lineup. The left-handed hitter got on the strong side of a platoon with Joey Rickard or Nolan Reimold being the other half.
He became a decent fantasy option in daily transaction leagues by posting a .329/.410/.454 in until July 10th when he went on the DL with a hamstring injury. After the injury, he hit only .275/.353/.386. The second half numbers are decent numbers, but not as good as before the injury.
With the new StatCast data, I examined it to determine if there was a drop in Kim’s exit velocity around the time of the injury. Using a 10-day rolling average, the available data may not look like it but the rolling average generally stays around 7 mph of the overall average. Additionally, there was no huge pattern change around the time of the injury.
The problem is that StatCast is not able to collect all the available data as documented at FanGraphs and The Hardball Times. The missing data is normal weak groundballs or high infield popups. I am not going to regurgitate the reasons and the exact details from the previous articles but I am going to take a step forward in accounting for the missing data.
