Archive for baseball

Here’s the original post. No dilly-dallying, let’s dive in.

1) Steven Kwan is a top-30 outfielder.

Kwan walk more than he stuck out, and while he only hit six home runs, he stole 19 bases and slashed .298/.373/.400 (124 wRC+). Only five qualified hitters had a better strikeout-to-walk ratio (K/BB), and only Luis Arraez had a lower swinging strike rate (SwStr%). Ultimately, Kwan finished the season 19th among outfielders on Razzball’s Player Rater. The haters will point to volume (he accumulated 622 plate appearances) but Kwan finished 20th among qualified outfielders on a per-game basis—that is, ignoring volume.

You may remember Kwan started the season scorching hot, then predictably fell back to earth, which entailed a somewhat grueling slump. Da Haters pointed to this slump as an indication of Kwan’s lack of viability as a Major Leaguer rather than simple gravity. The slump actually cost Kwan some starting time—he could’ve notched 700 PA if the Guardians didn’t lose faith in him in May, like everyone else did—but he rebounded by showcasing his tools. More excitingly, his counting stats increased as the season wore on, and he compiled three home runs, seven steals, and a .309 average in September alone.

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A little more than a year ago, Al Melchior had the brilliant and beautifully straightforward idea of investigating how strongly pretty much ever Statcast metric correlated with various traditional power metrics and compiling them in one post. He asked me to help out, which I was more than glad to do.

Recently, I saw folks talking about this again, and someone asked specifically about the 2019 season. I figured I could refresh the values from the original post quickly enough (certainly a lot more quickly than I did last time), and it would also help bring pertinent information to the fore for folks neck-deep in draft prep.

Spoiler alert: the results barely changed. But! I do feel more confident in this particular set of values, as I nerded out with programming instead of pulling dozens of different queries from the Baseball Savant search function and constantly getting frazzled.

OK, here’s the goods. For 2019 hitters:

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As part of some midseason RotoGraphs shenanigans organized by Brad Johnson, the Birchwood Brothers (aka Michael and Dan Smirlock) invited me into the Birchwood Derby, a midseason re-draft league. A post-draft recap seems appropriate, mostly because this was my first midseason re-draft ever.

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It took a dominant 11-strikeout, zero-walk performance from Taijuan Walker for the fantasy world to finally take notice of him. I don’t have ownership trend data to exemplify this, but I do have an anecdote: he was available in every league I’m in before the start, and he was owned in every league I’m in shortly after it.

The truth is Walker had demonstrated progress, described here by Eno Sarris, in his prior four starts, notching 27 strikeouts to three walks in 29 innings. Someone who hadn’t been paying attention to Walker probably wouldn’t have noticed: his ERA prior to the recent five-game surge stood at 7.33, and he had completed the sixth inning only twice in nine games. Once a hyped prospect, he looked like a 22-year-old who still needed seasoning to reach his potential.

No longer, as you will probably have to give up an asset of value to acquire Walker from a fellow owner now. The price may not be too steep given his poor ratios (4.94 ERA, 1.39 WHIP), but this is likely the highest they’ll be for the rest of the season.

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Every year, we here at RotoGraphs publish tiered rankings for every position and update them throughout the year. What you will read below are, more or less, my end-of-season projections for National League outfielders, since the season hasn’t started yet. However, these rankings will change as the year progresses, and I would be a fool to tell you the tiers below will look the same in September.

No doubt, this is a contentious matter, and you can tell me how much of a moron I am in the comments.

Without further ado, here is the 2015 season’s first installment of tiered rankings for NL outfielders.

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This is meant to be less of an overly serious analysis as it is an exercise in projecting minor league players in a new and different way. Unfortunately, Chris Mitchell has largely done what I’m about to present, and with more sophistication at that, so I’ll have to strike out the new part. But different? Sure, to an extent.

While Chris’ KATOH predicts a hitter’s probability of major league success by projecting career wins above replacement (WAR) thresholds, my model predicts probability of future success in the context of various career accomplishments: Will he be a better-than-replacement level starter? An All-Star? A future MVP? Ultimately, the exercise is simpler and more qualitative, evaluating strictly AAA stats (rather than all minor league levels, as KATOH does) and making predictions according to various marginal changes in common statistics such as isolated power (ISO), stolen base rate (SB/PA) and age. Think of the model as a series of player comparisons. Also, please think of the model as not a replacement or substitute for KATOH but a complement to it, albeit a less intense one. I will use this tool for analysis, but only infrequently; I recommend you keep up with all of Chris’ KATOH posts (as well as Kiley McDaniels‘ prospect coverage) to fulfill your prospect consumption needs.

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I’d like to talk to you about Dellin Betances.

Wait! Wait. No. No, I wouldn’t. I’d like to talk about Mike Podhorzer first. Mike has published a lot of great work covering the fundamentals of the xK% (and xBB%) metric for pitchers (and hitters), so if you are unfamiliar with or falling behind on his work, I recommend you first click here, here or here. But if you’re lazy, the short of it is: xK%, or expected strikeout rate, is an equation birthed from a linear regression that measures how a pitcher’s looking, swinging and foul-ball strike rates as well as overall strike percentage correlates with his strikeout rate. It doesn’t predict future strikeout rates as much as it retrospectively adjusts past strikeout rates; thus, it is a good tool for identifying pitchers who potentially benefited (or suffered) from good (bad) luck in a previous season – say, 2014.

Like many other metrics completely unrelated to xK%, however, there is evidence that certain players consistently out-perform (or under-perform) what their xK% rates predict their actual K% rates should be. (Mike alludes to this trend in his quip about Jeremy Hellickson, a xK% underachiever, in one of the articles linked above.) Similarly to how a power hitter will post consistently higher ratios of home runs to fly balls (HR/FB) than a non-power hitter, or how Mike Trout will probably post some of the highest batting averages on balls in play (babip) in the league for years to come, it appears there is some skill, or perhaps a particular characteristic, inherent to pitchers who consistently best, or fall short of, their xK% rates.

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Episode 106

The latest episode of The Sleeper and the Bust is now live! Jason Collette and Eno Sarris re-visit the Billy Hamilton concern-o-meter, discuss Anthony Rizzo, Mike Morse, deep sleeper bats, the crazy closer situations, and even more injuries.

As usual, don’t hesitate to tweet us any fantasy questions you have that we may answer on our next episode.

You can subscribe to the podcast on iTunes or via the feed.

Thanks to Ian Miller aka Teen Archer, for the new intro music Approximately46 min of joyous analysis.

Let’s a give a big round of applause to the idiots at the IOC, shall we? The need to draw more attention and revenue to the Olympics led these buffoons to killing the Games’ integrity by removing the amateur status requirements to participate so they could draw in more professional and marketable athletes. While that may have been fine and dandy for the basketball world, as the NBA season ends in June and the summer Olympics don’t start up until late July, it was an epic fail for baseball as players were asked to leave their MLB teams in the middle of the season to go and compete. MLB complied and allowed players to play, but there were no marquee names headed for the games and in the 2004, the United States didn’t even field a team. Read the rest of this entry »