Archive for buy low

Yesterday, I devised a new expected strikeout rate for pitchers and used it to identify qualified starting pitchers who over- or under-performed in 2018. I’m reluctant to make out the exercise to be more than it is. I simply wanted to take the most intuitive approach to describing a pitcher’s strikeout rate (K%): by using the plate discipline exhibited by opposing hitters. Today, I seek to do the same for hitters. I can tell you now the discussion will be much more qualitative than quantitative.

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Mike Foltynewicz, a first-ballot Hall of Namer, immediately strikes me as someone who outperformed his strikeout rate (K%) in 2018. I don’t have to look far for confirmation: his 27.2% strikeout rate outstripped his 10.3% swinging strike rate (SwStr%) by a mile. Because whiff rate correlates so strongly with strikeout rate, it serves as a useful proxy for what one could expect of a pitcher’s strikeout ability.

I generally follow this rule of thumb when I’m reluctant to get too into the weeds when assessing peripherals: SwStr% * 2 = K%. It’s imperfect but useful in a pinch. Folty violates this rule of thumb pretty dramatically. Of 13 qualified pitchers who struck out at least 27% of hitters, his 10.3% swinging strike rate falls well short of the shortlist’s 2nd-lowest mark (Charlie Morton, 11.9%). Foltynewicz’s 2018 performance has already wilted under what amounts to very little duress.

Still, I wanted to allow Foltynewicz the opportunity to redeem himself. Whiff rate does not a pitcher make; there are other components to plate discipline allowed such as chase rate (O-Swing%) and zone rate (Zone%), among others, that describe each pitcher in much finer detail. I broke down a pitcher’s plate discipline allowed into its component pitch outcomes:

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Fantasy owners tend to give good hitters on bad teams short shrift, and that was certainly the case for Justin Bour this spring. Even though he was coming off a breakout season in which he batted .289 with 25 home runs and 83 RBI in 429 plate appearances, Bour fell to the late rounds in many leagues, lagging behind the less accomplished Greg Bird and Josh Bell in ADP.

Two-and-a-half months into the season, the Marlins first baseman seems to be validating owners’ fears. He ranks 29th in a largely-disappointing pool of first basemen in terms of Roto value (per ESPN’s Player Rater). Bour is batting just .242, and despite posting a .375 OBP, he has scored just 24 runs. With 10 home runs and 27 RBI in 253 plate appearances, he is well behind last season’s pace for both stats. It’s little wonder he is widely available in 12-team mixed leagues.
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There are, like, a dozen articles of this nature written daily — that is, “buy-low” candidates using some kind of xMetric, likely derived from Statcast. That’s fine. I’m not hating on it. This was my modus operandi when I first started writing at RotoGraphs, and it’s how I really started to understand the cyclicality of player performance and the differences between descriptive and predictive metrics.

Speaking of which, I have no desire to rehash the “what xwOBA should really represent” discussion that consumed the sabermetric sphere a week or two ago. (Although, for reference, I’ll link you to Baseball Prospectus, MLBAM’s Tom Tango, and FanGraphs’ Craig Edwards.) Primarily, I want to provide some facts about xwOBA followed by some non-facts about how I use xwOBA to keep my biases in check.

There are two important tenets to xwOBAism. At the player level, wOBA does not always converge on xwOBA…

1. in a given season.
2. over the course of a career.

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I committed Matt Holliday to my disabled list Monday, marking the 14th(!!!!) DL move I’ve made for my primary team this season. Perhaps the state of my team is implied by the length of its disabled list. If not, I’ll make it clear: my team has been bad. Pretty darn bad.

All of my drafts were especially poor. I drafted the same terrible, injured, underachieving players in every league, so it has been generally a nightmare all around. The hole I dug for myself is deep. Kyle Lohse broke ground on said hole with an 8-run Opening Day outing that lasted all of 3-1/3 innings, and we never looked back. Woe is me. Alas, it’s barely the second week of June, and I have already resorted to my Hail Mary play: buy low on everyone in sight.

Calling it “buying low,” however, is a bit misleading. It’s a shallow league, so there is arguably a stronger incentive for owners to cut bait on underachieving name-brand players in order to ride the hot streaks of unknown quantities, given they crop up more abundantly. What I’m actually doing, then, is loading up on underachievers from waivers. My team is already underachieving. These guys are already underachieving. How much worse could it get?

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Man, I am having a blast with the Baseball Info Solutions batted ball data that was recently added to the batted ball leaderboards. Sure, there are reasons to complain: the batted ball spray and contact quality statistics lack context, leaving you in the dark about how spray and contact intersect. For example, there’s Hard%, and there’s LD%, but how many of a hitter’s balls in play are hard line drives? (You can actually find this data on individual player pages under the “Splits” tab — just not on the leaderboards.)

Just because the available data aren’t as granular as one might wish they were doesn’t make them worthless or unusable. Yesterday, I demonstrated that we can still achieve small gains in our understanding of batting average on balls in play (BABIP) using the new data.

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Chris Carter is off to a bad start. This is an unambiguously true fact. Jeff Sullivan, among other Twitterers (Tweeters?), have succinctly illuminated this unambiguously true fact:

selection of players with ISO of .000 Curtis Granderson Brandon Phillips Desmond Jennings Logan Morrison Chris Carter

— Jeff Sullivan (@based_ball) April 21, 2015

Carter has supplemented the zero extra-base hits with four singles, 21 strikeouts and nary a run batted in to speak of through 51 plate appearances. (FYI, that’s a 41.2-percent strikeout rate.) His atrociously bad start is the talk of the Twitter town, and it has Astros Manager A.J. Hinch dropping him in the batting order. As of last night, Carter’s ownership had dropped to 67.7 and 73 percent in ESPN and Yahoo! leagues, respectively, as owners have jumped ship.
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If fantasy baseball were a marathon, we’d all have run about a mile and a half. Most races don’t even have their volunteers stand with trays of water cups this early on, so you’d better pace yourself if you’re already tired. I think I forgot to stretch.

Here’s an obligatory sentence reminding you about the caveats about small samples while attributing a shred of validity to them. OK, now that the formalities are out of the way, let’s talk ownership trends. National League outfielders are a promising bunch, especially in regard to the youth movement. I’ve been sold on a handful of them prior to the start of the season, and I’m surprised by their meager ownership numbers. They aren’t completely unowned, as my misleading title alleges, but they’re close enough.

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An unambiguously true fact: Matt Holliday is an old man in baseball years and in dog years. Another unambiguously true fact: Holliday has been remarkably consistent throughout his career. Hear ye:

• He has hit at least 20 home runs in nine straight years, a streak currently matched only by David Ortiz and Miguel Cabrera;
• His walk rate has hovered between 10 and 12 percent for the better part of a decade, and his strikeout rate has always resided in the mid-teens;
• He has averaged 647 plate appearances per season dating back to 2006;
• And honestly, I don’t know if I’ve ever seen a batted ball profile so absurdly consistent.

Yet a slight dip in power and a career-worst batting average (.272, aka what some players can only dream of hitting) in 2014 couldn’t have come at a worse age, and it all has fans and projection systems alike running for the hills, as shown below.
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