Welcome to the return of the Steamer and I series. I debuted Steamer and I last year and have decided to bring it back for an encore performance. In the series, I pit my Pod Projection against Steamer, comparing wOBA forecasts for hitters and ERA for pitchers. I’ll choose several fantasy relevant players to discuss on each end of the spectrum – those I am far more optimistic on and those I am more bearish on.
2/28/16
The latest episode of “The Sleeper and the Bust” is live!
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We have a new email address for questions: sleeperpod@gmail.com. Send your fantasy-relevant questions. You can send keeper questions, but those are much better for Twitter. Questions most likely to get selected are those that apply more broadly, as opposed to specific trade or keeper queries. However, if you do ask a league-specific question, please include the league size and categories.
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A couple of months ago, I wrote an article about platoon options, and astute reader Tacocat pointed out that platoon hitters never actually realize their versus left-handed pitcher or versus right-handed pitcher splits that we frequently cite. Instead, platoon hitters start games with a platoon advantage, and then sometimes managers have to leave them in to face same-handed pitchers out of the bullpen.
Daily players use the same decision-making as actual managers. You can choose to start a platoon player because he is facing an opposite-handed starter, but that creates a chance that he could see a plate appearance versus a same-handed reliever later in the game. If you are relying on a split stat versus left-handed or right-handed pitchers to make that start/sit decision, then your platoon hitters will underperform your expectations on average.
Two years ago, I shared with you an updated version of my xK% equation. The formula uses a trio of strike type rates found at Baseball-Reference.com, including a pitcher’s looking, swinging, and foul strike percentages, along with his overall rate of strikes thrown. With an adjusted R-squared of 0.913, it explains a very higher percentage of a pitcher’s strikeout rate. Its best use is early in the season when the plate appearance (the K% denominator) sample size is still small, as xK% uses total pitches as the denominator, so we can reach a reasonable sample size to analyze much more quickly.
You’ve just signed up to play Ottoneu – now what?
Ottoneu is growing, and while you’re going to see a lot of ink spilled here on RotoGraphs about this premier fantasy game, the learning curve for rookies can be a little steep. Below are ten critical tips you should consider when embarking on your first Ottoneu fantasy baseball season. What follows is based on the assumption that you’ve either joined an existing Ottoneu league or are creating a new league and are now preparing to draft in your first spring auction.
1) Join the Ottoneu Community
One of the best aspects of Ottoneu is the massive contingent of game players discussing all things baseball (and football) 24/7/365. You can find the most active Ottoneu gamers on the official community site and on Slack. Complementing the already feature-rich platform, the Ottoneu community brings all owners together in one place to crowdsource player information, trade feedback, auction tips, keep/cut decisions, enhanced league communications, and a forum for recruiting new league owners. Even if you don’t play Ottoneu (yet), the community is a goldmine of daily baseball dialogue, strategy, and advice, and it also the perfect place to dip your toe in if you have any interest in learning more about playing and joining Ottoneu. When you do play Ottoneu, you’ll want to get acquainted with the community as soon as possible, as it is an excellent resource for new Ottoneu players.
The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve.
Yesterday, I published my first Pod Projection of the year, and the honor was bestowed upon the Dodgers’ hyped young shortstop, Corey Seager. Several commenters asked me to clarify my feelings on Seager’s ADP in relation to Xander Bogaerts, so I figured I might as well expand upon my thoughts on the latter by giving him the full Pod Projection treatment.
Bogaerts, a former top prospect with the Red Sox, completely transformed into a new type of hitter in 2015. It’s odd because this is something you might expect from an established veteran who is compensating for deteriorating skills. Established veteran Bogaerts is not, but the finished product delivered significantly more offensive value than the 2014 version. He struck out far less, though his SwStk% only declined marginally, the respectable minor league power he had displayed in the past declined even further, he became an extreme ground ball hitter, at the expense of fly balls, he went to the opposite field with dramatically greater frequency, and his BABIP skyrocketed. Phew! Is there anything in Bogaerts’ statistical profile that didn’t change drastically?! His line drive and pop-up rates were virtually unchanged, so there’s that!
With all these changes, it makes projecting his 2016 performance that much more difficult. It’s hard enough forecasting a player with just two Major League seasons to his name, so when we cannot even determine a true baseline for his skills, we’re essentially just taking a wild guess. So here goes…
The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve.
The honor for first 2016 Pod Projectionee goes to Dodgers shortstop Corey Seager. He came to the plate just 113 times in his Major League cup of coffee, but man did he impress. He posted a robust .421 wOBA and displayed elite underlying skills across the board. I wrote him up in mid-November, concluding with the following:
With all the other exciting sophomores getting more attention, it’s possible Seager slips under the radar, even with his excellent September performance. Normally, he’s the type of player who would be a near lock to be overvalued. But I’m not so sure about it. In fact, I’m rather curious where fantasy owners will peg his value. I don’t expect a big breakout, but he could very well be a solid across the board contributor.
“…it’s possible Seager slips under the radar”, ha! He’s currently the 55th player off the board and third shortstop selected according to NFBC ADP. Surely fantasy owners haven’t forgotten about him and are putting an awful lot of stock into his prospect pedigree and a tiny sample of MLB performance. Are they justified in their optimism?
You smell that? That’s the smell of spring in the air. Baseball is around the corner and draft season will be in high gear before we know it. We already ran our first set of rankings that you hopefully got a chance to check out as they were rolled out. You can either bookmark the Rankings filter which will show you all posts dealing with rankings or you can access them by position in the sidebar:
In a post later today, I’ll be covering all of our draft tools in more depth, but let’s get to what you came here for, the spreadsheet!
Not only does it contain all of the rankings from the seven of us, but we’ve also added Steamer Projections and a cross-off capability that allows you to assign each player to the team that drafted him while putting a line through his name and numbers. Thanks to Jeff Zimmermann, Tanner Bell, and Danielle Mason (Justin’s wife) for their work on this. As with our rankings, this is our first run, so we will be making enhancements where necessary. In fact, if there is anything you’d really like to see on future updates, please let us know. If it’s feasible, we’ll try to get it on there. The next update of this spreadsheet won’t come until March when we update the rankings.
Without further ado:
There was a misalignment in OF and RP in the first upload here which skewed some Steamer Projections. It has been fixed. If you downloaded before 12:58 PM Central on 2/19, please re-download.
Three years ago, I conducted an exhaustive study of ESPN Home Run Tracker data. At that time, it was the primary tool I used to validate a batter’s power, before we got into the sexy new batted ball distance, and then combined that with standard deviation of distance and average absolute angle. The short story is I found that hitters with an unusually high percentage of “Just Enough” (JE) homers saw their HR/FB rates decline the following year, significantly more than the rest of the player population. On the other hand, those who hit a high percentage of “No Doubt” (ND) homers maintained their HR/FB rate much better than the rest of the group.
Three years ago, I conducted an exhaustive study of ESPN Home Run Tracker data. At that time, it was the primary tool I used to validate a batter’s power, before we got into the sexy new batted ball distance, and then combined that with standard deviation of distance and average absolute angle. The short story is I found that hitters with an unusually high percentage of “Just Enough” (JE) homers saw their HR/FB rates decline the following year, significantly more than the rest of the player population. On the other hand, those who hit a high percentage of “No Doubt” (ND) homers maintained their HR/FB rate much better than the rest of the group.
