Episode 202
The latest episode of “The Sleeper and the Bust” is live!
In this episode, Paul Sporer and Jason Collette discuss some Spring Training injuries and then deep-dive into the AL and NL LABR auctions that took place this weekend in Phoenix:
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The following is what happens when I go a full week without a report. The injuries are rolling in and I have quite a few updates on spring training velocities.
• I guessing most people have heard that Yu Darvish has a tear in his ulnar collateral ligament. Here is Jon Daniels going through Darvish’s options:
“We got the MRI results yesterday evening. Dr. Meister met with Yu at that time and we just all got together this morning and talked through the options, effectively, that there are three options for Yu at this point,” Rangers general manager Jon Daniels said. “One is to attempt to pitch through it, which is not a great option. Two, would be an effort for rest and rehab. I think the sentiment is that is effectively what we did in the fall and in the winter and up until two days ago, we had very good results with it. He looked very good but obviously that did not pan out as desired. The third option would be Tommy John surgery.”
I don’t think he will immediately pitch though the pain. Instead, he will rest for few months with rehab which is what Tananka did. He may be able to pitch the last couple months of the season. If he decides to get Tommy John surgery, he will likely not be competing in the majors until May 2016. He may be a late round DL stash for this season, but nothing more.
• Hunter Pence will be out six to eight weeks with a fractured forearm. Arm related injuries for hitters seem to have the most lingering effects. His power could be down quite a bit once he returns.
The Steamer and I series continues this week as I move onto starting pitcher comparisons. Today, I check in on two pitchers of whom the Steamer projections are significantly more bearish than my Pod Projections.
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.
The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X, and the process continues to evolve and improve.
Interestingly, I have seen many commenters ask for advice when choosing between this Monday’s Pod Projectionee, Carlos Carrasco, and today’s choice, Jacob deGrom. You’ll see when I unveil my full deGrom projection below, but it’s a rather close call, as they have very similar forecasts.
With that said, deGrom essentially came out of nowhere last year to post a sub-3.00 ERA in 22 starts and earn NL Rookie of the Year honors. He generally posted ho-hum minor league peripherals, but perhaps fueled by a faster slider, his coming out party occurred in the Majors. Before beginning my projection, I shared four reasons why deGrom was for real. Since I gave it away above by comparing the projection to Carrasco’s, I’ll tell you that I still feel the same way.
It is much easier to get excited about a player than it is to see the negative. Sure, if a guy has a rotten injury record, it is pretty easy to knock him down. But most fantasy players are eager to identify to the next set of sleepers or breakouts or whatever term you feel is adequate to describe middle-round guys who will explode into early-round assets. What about looking at some of the flaws of those early-to-mid round guys we’re all so certain will explode this year? There are certainly reasons to love these guys (and several of them are guys I’m quite high on coming into the season), but let’s at least be aware of the shortcomings and what could possibly hold them back from that big time season we’re banking on.
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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Episode 201
The latest episode of “The Sleeper and the Bust” is live!
In this episode, Paul Sporer and Eno Sarris start their positional previews with catchers. Behind the dish they discuss:
And then it cutoff randomly!! My computer deleted Skype in the middle of the podcast. We didn’t get a chance to rejoin because we were on a tight schedule as it was, so we just cut it there.
As usual, don’t hesitate to tweet us or comment with fantasy questions.
You can subscribe to the podcast on iTunes or via the feed. Please rate & review the show in iTunes letting us know what you think!
Thanks to Ian Miller, aka Teen Archer, for the intro music. Approximately 44 minutes of joyous analysis.
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It’s a tale as old as fantasy sports: pay attention to nine of the ten categories on draft day and you can dominate those categories and win. There are some accepted tenets to this strategy, called ‘punting,’ but as it is with all these things we hold for granted, it’s useful to look at what the numbers think of our Conventional Wisdom.
For one, which stats to punt?
This post continues our Depth Chart Discussions. In an effort to suss out every team, we’ve divided them into four parts (infield, outfield, rotation, and bullpen) and will continue to break them down for you over the next few weeks. You can find the Depth Chart Discussion posts gathered here.
The world champs might be without their longtime hot-cornerman, but they have enough impact players to keep them competitive in real life and relevant so far as fantasy owners are concerned. Up the middle the team flashes the game’s best catcher and an emerging double-play duo, while first base belongs to a solid sleeper candidate.
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