Archive for fantasy baseball

I’m really not privy to the whole daily fantasy baseball thing, as proctored by FanDuel or DraftKings. It’s probably good that I’m not because I’m 98 percent certain I would immediately fall in love with it.

Still, I’m intrigued, mostly because it takes streaming to the extreme. And I love streaming. It’s a tedious, somewhat painstaking process, what with combing through splits, looking for the juiciest matchups that are also cost-effective.
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Did you draft Dustin Pedroia, who is on pace for almost 300 home runs? Mookie Betts? In a fit of extreme homerism, the entire Red Sox lineup, which will surely score 1,296 runs? That must feel pretty good. Good for you, Pete. Give yourself a pat on the back.

Or, wait — you were the one who drafted Kyle Lohse, weren’t you? Threw a mid-round pick at Mat Latos? Wrote “stream Nate Karns” on your list of good Tuesday decisions? Do you regret it?

Man, there have been some truly brutal starts to kick off the season. It’s really easy to make a knee-jerk decision in reaction to such preposterous, ego-damaging, season-dooming starts, but you have to remember — and I think it goes without saying — that these guys will (probably) never be worse this year than they were today.

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I participated in two drafts this past weekend. Both were 10-team auctions, one a season-long rotisserie keeper league (“LOWV,” henceforth), the other a head-to-head points redraft league (“Sandlot”). They are just home leagues, not renowned leagues such as Tout Wars or LABR or anything like that, but hey! Breaking down any draft can make for good insight, and if it helps just one person clarify his or her strategy, perhaps it did some good.

“So, Alex, how did you in your drafts?” Great, thanks for asking! I love both my teams. Love them. Except I made the same mistake in each draft: I left some money on the table. Like, $20 in one instance. It became a running gag: “Don’t question Alex — it’s all part of his master plan!” But here’s the catch: I arguably have the best team, per the projections, even after managing my budget so poorly.

So where did my strategy go wrong? Honestly, I’m not sure it did. (Or maybe I’m just trying to make myself feel better.)
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Depth chart discussions are in full swing. We are analyzing each team’s infield, outfield, rotation and bullpen components in separate segments. Catch up on the discussions here.

I don’t know how analyze the Cardinals’ outfield in a way that properly acknowledges the significant role the Cardinals’ carved out for Oscar Taveras without marginalizing or trivializing his life and talent nor condoning the cause of his passing. His sudden death shocked the baseball community and left a gaping hole in the St. Louis outfield. Unfortunately, there’s a lot we’ll never know about Taveras, the budding superstar who never was — or, perhaps more accurately, never got to be.

* * *

With the departures of Carlos Beltran and Allen Craig, and with Matt Adams employed full-time at first base, the St. Louis outfield looks thin. But the Cards have a pair of prospects ready to contribute at the Major League level (or close to it), both of whom will likely assume full-time roles in the next couple of years. Meanwhile, the Cardinals’ regulars, barring injury, will assume the lion’s share of the starting duties and produce enough offensive and defensive value to warrant their lack of depth — if they stay healthy, that is, and that’s a big “if.”

Left Field: Matt Holliday (Age 35)
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Depth chart discussions are in full swing. We are analyzing each team’s infield, outfield, rotation and bullpen components in separate segments. Catch up on the discussions here.

A couple of weeks ago, I highlighted the 10 most “MLB-ready” AAA outfield prospects based on a variety of requirements about which you can read if you click through. The idea was to ignore any kind of prospect labels and strictly let the statistics and hitters’ ages tell the story.

The list is by no means definitive, but Pirates outfielders assumed four of the 10 spots. Their projections weren’t necessarily rosy — they may all end up being bench pieces at best, for all we know — but it doesn’t negate the fact that they may be ready to positively contribute at the Major League level in some capacity. Toss into the mix top prospect Austin Meadows farther down the organizational ladder and it becomes clear that Pittsburgh has enough outfield depth throughout its system to support an ensemble cast that should be together for years to come.

Left Field: Starling Marte (Age 26)
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RotoGraphs has graciously (and, as we’ll soon learn, erroneously) allowed me to make bold predictions for the 2015 season. Last year, in the privacy of my own blog, I predicted Dan Haren would strike out fewer than seven batters-per-nine after notching an 8.0 K/9 in 2013. He finished the 2014 season with a 7.02 K/9. Needless to say, I’m looking for vengeance. So let’s do this! Right now!!!!

1. Giancarlo Stanton finishes outside the top 10… outfielders.

FanGraphs’ auction calculator, in its default settings, depicts Stanton as the third most expensive player behind Mike Trout and Joe Blanton Clayton Kershaw. He ranks second in average auction value in ESPN drafts. He’ll find his way to the disabled list again, and the BABIP gods will punish him en route, leaving him outside not only the top 10 overall but also the top 10 outfielders outright.

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Average Draft Position or ADP is very valuable. I weighed NFBC’s ADP into my personal NFBC Draft Champion rankings equally to my position-adjusted composite projections (Baseball HQ combined with RotoChamp composites (Steamer, ZIP’s, etc.)) and the results were great. I used this, our pitcher arsenal scores and these hitter analytics  as my three main draft tools.

I wanted to take evaluating draft position one step further. I want to understand how consistent each player is drafted near their ADP.

Howard Bender, who manages Mock Draft Army provided me with the raw draft results of 19 expert drafts (NFBC format: 2c-1b-2b-3b-ss-ci-mi-5of-9p). It’s not the largest sample, but they are expert drafts, and the drafts that I have taken part in definitely provided great references.

The Approach:

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… if this nonsense with his agent(s?) ever clears up.

I feel like Debbie Downer from the classic Saturday Night Live sketch. I found reasons to dislike Yasmany Tomas, and now I’m here trying to find reasons to dislike Hector Olivera. It’s largely because I’m stubborn and would rather die by own fantasy baseball sword than someone else’s. But I haven’t seen any assessment of Olivera’s Cuban National Series (CNS) statistics beyond he hit an impressive .323/.407/.505 in his 10 years in Cuba, so I’ll attempt to expand on this.

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Two weeks ago, I wrote about the importance of evaluating expected strikeout rate (xK%) in the context of each pitcher’s respective histories. In other words, xK% on its own can only tell you so much about a pitcher’s chance and magnitude of regression toward the mean.

And last week, I refined the expected walk rate (xBB%) metric for pitchers by adding a proxy for pitch sequencing in the form of percentage of counts that reach 3-0 (“3-0%”). This helped better explain the model’s fit with respect to the data, as pitchers who worked into more 3-0 counts tended to walk more batters. (Who knew?)

The logical next step is to combine the two aforementioned analyses: 1) comparing xBB% to BB% 2) for each pitcher over time. I’ll reiterate a couple of key points. Calculating a pitcher’s xBB% can give us a decent idea of how lucky or unlucky he may have been during a given season. Calculating his xBB% and comparing it to his actual BB% on an annual basis can give us a better idea of truly how he typically performs against his xBB% — that is, if he consistently outperforms his xBB%, perhaps the difference between his xBB% and BB% is not a matter of luck at all but a skill or characteristic not captured by the variables specified in the xBB% equation.
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I expected to follow up my xK% differential post from last week with a complementary xBB% differential post. For those who don’t enjoy surprises, I’ll let you know now that that didn’t happen. In its stead, I bring what I hope is good news — news that will not only influence a future xBB% differential post but also may impact general pitcher analysis henceforth and possibly international diplomacy.

The title of this post, however, is a tad misleading. I think I can say, with some degree of certainty — and I hope to demonstrate, with some degree of competency — that pitch sequencing indeed plays a role in a pitcher’s walk rate, as the devilishly handsome Mike Podhorzer has postulated. What I can’t describe, with any degree of certainty, is the magnitude of the role it plays. In truth, I desperately want to prove Mike wrong: there must be other factors, outside of pitch sequencing (and pitch framing, perhaps), that help explain a pitcher’s walk rate. For example, I have tried incorporating O-Swing% and Zone%, two PITCHf/x metrics provided by FanGraphs that I swore would fill in the cracks, but they offer little in the way of additional explanatory power.

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