Merrill Kelly

The Diamondbacks signed Merrill Kelly after Kelly spent four years in the Korea Baseball Organization. I never heard of Kelly until the signing some it’s time to put together a profile for him.

First, here’s a tweet from Homin on Kelly’s profile:

KBO season ended. Merrill Kelly, former #rays prospect will play MLB next year. 92-94 mph FB, cutter, two-seam, CH, CV. Various pitches. No plus pitch, but reliable pitcher. Could be good long RP at mlb level. #rays are scouting him heavily.

— Homin Lee (@Homein22) November 13, 2018

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Introduction:

Today, I will introduce a game theory approach for comparing baseball projection systems. The day’s venture will not be a typical statistical analysis. I won’t be using any Chi-squared tests, nor will I calculate Type I or Type II errors. I won’t be evaluating MSEs or the like.

Instead, I will look to determine the profitability potential of each projection system by simulating what would have happened in a fantasy auction draft. Instead, I’ll play a game.

What do I mean by this?

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I heard in passing from a credible source:

“The effectiveness of a pitcher’s slider relies on it having the same spin as his fastball.”

I figured it would be an easy test and could help to immediately identify top-rated sliders. After looking at the data every conceivable way and came up with the following conclusion: publicly available spin information has near ZERO correlation to a slider’s effectiveness. But while rooting around, I did find two factors which do matter, fastball velocity and the difference in slider and fastball velocity.

The theory behind the quote is that a hitter has a tougher time differentiating a fastball and slider if they are spinning at the same rate. So, the closer the difference, a higher chance for a swing-and-miss.

I compared 2018 pitchers with at least 200 sliders and 200 four-seamers thrown. Then, I compared just the difference, the absolute value of the difference, square of difference. Nothing tangible. Nothing matched.

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One of the keys to fantasy success involves finding when projections can be systematically off. The hard part for fantasy owners is that most of these findings, like pitch velocity, get quickly incorporated into projections. Since it’s difficult to find these discrepancies, I was intrigued when I saw this quote by Mitchel Lichtman (MGL) in an article he wrote:

So, the substantial under-projections seem to occur when a player gains speed but his wOBA remains about the same.

And by substantial, it was a 22 point difference is wOBA. This is a major difference and could point owners to some nice upside plays. I decided to go ahead and dive in.

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Fantasy analysts and enthusiasts alike are still searching for ways to use Statcast’s expected wOBA (xwOBA) metric meaningfully to gain an edge. Unfortunately, beyond leveraging the difference between xwOBA and actual wOBA (what I, and probably countless others, refer to as the “wOBA minus xwOBA differential”), I don’t know yet how else you can use xwOBA effectively. Given already-widespread use of the metric, the minimal edge you can glean will come from interpretation.

I discussed the interpretation of xwOBA multiple times in 2018. In May, I highlighted hitters on whom to buy low because of their extreme/outlier wOBA–xwOBA differentials. In July, I called out xwOBA’s inability to account for what appeared to be the ball becoming un-juiced, thereby overestimating xwOBA across the league. In September, I investigated the predictiveness of xwOBA in-season (that is, the predictiveness of first-half xwOBA on second-half wOBA).

I discussed all of these topics during my presentation at BaseballHQ’s annual First Pitch Arizona forum, especially the former-most. Basically all of the hitters I tabbed as buy-lows outgained their prior performance by substantial margins — all of them, that is, except for Victor Martinez. Could he be considered a miss? Sure, except he was different from the rest of his fellow underachievers: he perennially underperforms his xwOBA. Perhaps the better question, then, is: Why was he a miss?

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A diverse pitching arsenal can help a starter successfully navigate a lineup several times since hitters have a harder time sitting on a single pitch. I went through the 2018 starters and found four pitcher groups who are the two ends of the spectrum. Either they rely on two pitches or have a diverse arsenal.

Many articles have been written about times through the order but the Holy Grail of research articles is the one MGL wrote a few years back. In it, he quantified how much having a third pitch helps. The research holds up even now. I took the 206 starters who threw at least 30 innings and found the percentage of pitches which were fastballs and next highest thrown. Normally, the average was around 75%. Then, I divided up the pitchers into 5% increments. Next, I subtracted the ERA from an average of their ERA estimators (FIP, xFIP, kwERA, SIERA) and here the average values. Read the rest of this entry »

I try not to miss examining players who had great, short seasons. An injury or time in the minors kept them off the end-of-season rankings. They flew under the radar but given a full season of playing time they stick out and could provide hidden value. Today, I’m going to start by examing the top prorated hitters.

I needed a way to value the hitters and decided to create an overall Standing Gain Points (SGP) formula from The Great Fantasy Baseball Invitational leagues. The 13 15-team leagues were set up with  14 hitters (1 C, 2 Util), 9 pitchers, and used AVG. Tanner Bell and I will be providing this formula, along with several others, in our new book, The Process, available within weeks (shameless plug).

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Let’s wrap up my 2018 Pod Projection reviews, ending with Tommy Pham. A surprise breakout in 2017, we didn’t truly know what we were going to get in 2018. A move to Tampa mid-season didn’t exactly benefit his offense as he merely went from one pitcher friendly park to another. Let’s find out how he ended up performing compared to my projection.

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Last week, I started digging through the free agent pitchers and found those arms who could improve on their pitch mix. Three prime candidates, Jeremy Hellickson, Matt Harvey, and Derek Holland, stood out. This installment includes the older pitchers from MLBtraderumors free-agent starter list while still ignoring those who may or may not become free agents. I’ll look into them once it’s official they are a free agent.

As I said in the previous article:

I’m just going to focus on the each of the pitcher’s 2018 pitch mix. I can’t assume they’ll develop a new pitch, so I need to work with what they showed last year. The two most common ways for pitcher to improve is to drop a horrible pitch or drop their fastball usage. These changes don’t guarantee an improvement but for now, the focus is on pitchers with upside beyond their projection.
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After going through the pitchers, I found they fit into three main groups depending on if changing their mix could help. This ranking is in no way a ranking of pitcher talent but I’m sure someone will bring it up in the comments. These are just pitchers who I believe can improve by adjusting their current pitch mix.

Major Improvement Candidates

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Shohei Ohtani was one of the most hyped rookies in recent memory. Fueling the excitement was the fact that he came over from Japan and he was a two-way player, both pitching and hitting, and doing each well…very well. Obviously, attempting to translate performance from a foreign league to MLB is difficult, and then you have to actually forecast the upcoming season, which is far tougher than a regular run of the mill projection for an MLB veteran.

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