Last week, I began looking at which players my ranking differed most from compared to the staff consensus. Shortstop is a much better position this year when digging for sleepers than its middle infield counterpart, second base. That gives you the opportunity to bypass the top options and grab when of the late rounders with nice upside. For the shortstop bullish and bearish picks, I will once again only look at my top 18 for bullish and the consensus top 18 for the bearish group.

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All this week I have been checking in on the players I have ranked most differently from the other RotoGraphers in our recently published consensus. Today are the second basemen, a group that doesn’t have a whole lot of good late round sleepers like the shortstop position does. So maybe instead you pick an undervalued guy in the middle rounds that I identify in the bullish section. That section will include guys I ranked in the top 18, while the bearish will look at those ranked in the top 18 by the consensus.

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On Monday, I started identifying which players at each position my ranking differed most from the RotoGraphs consensus. I began with catchers, and now it’s time to move around the diamond to first base. Once again, I will only look at those expected to earn value in standard 12-team mixed leagues. With the first base, corner and utility slots, I will assume 20 first base will earn at least a buck of value. The bullish picks will only include players I ranked in the top 20, while the bearish will include only those included in the top 20 by the consensus.

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Last night, I participated in the other division of expert drafts, Tout Wars. If you recall, in mid-February I partook in the LABR mixed online draft league for the second year after its inaugural 2012 season. Not surprisingly, Tout Wars wanted a piece of the online snake draft action as well and started up their own version this year. When I received the invite to take part in Tout Wars, I was super excited, as it was my goal since I started my fantasy baseball writing career. The format is essentially the same as LABR, with one big difference — it counts OBP instead of AVG. It is a 15-team league with the standard 23-man rosters and a 4 man bench. The reserve roster is smaller than the six allowed in LABR. Interestingly, and strangely, Eno Sarris is also a member of the league. Without further ado, let’s see how I did.

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This week, I will be identifying the players at each position in which my rankings differ most from the consensus that was unveiled last week. The funny thing about comparing my rankings to the other three RotoGraphers is how many times I am surprised at who I value much more or less than them. Most of the time, I could guess who I am more or less bullish on even before I see everyone else’s rankings as it simply comes down to a difference in projections. However, that’s not always the case. Sometimes I am bewildered as to why my rankings differ so drastically because my projections seems right in line with general expectations. So I will attempt to figure out and explain why I am higher or lower on each player.

Since I don’t know what the other RotoGraphers’ projections are, I will be referencing the projections systems frequently and using those as a proxy. To make this more useful, the bullish section will only include players who I project to earn positive value in a 12-team mixed league, while the bearish one will only include players the consensus expects to earn positive value.

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In what is likely my last Pod Projection post of the year (my eBook teaches you how to forecast players yourself!), Johnny Cueto wins the honor of finishing up the series. Cueto has posted sub-3.00 ERAs two years running now, despite all ERA estimators sitting significantly above those marks. Great fortune (skill?) in the three “luck” metrics we analyze is the explanation for his ERA estimator beating ways. Can it continue?

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As a FanGraphs reader, you are no doubt familiar with the many projection systems we display statistical lines from on the player pages of the site. These are fantastic models and I have mentioned many times how big a fan of the Steamer pitcher forecasts I am. Unfortunately, it is thought that these systems only have around a 70% accuracy rate, which may or may not seem high to you. The belief is that any additional factors added to the computer models will barely move the needle, so hope for an 80%+ success rate should probably be given up. That said, there are many reasons why these models cannot become better at projecting players, and it doesn’t have anything to do with the fact that we are dealing with human beings and no matter how much data we have, sometimes that .001% event happens. Projection systems have weaknesses and they are pretty easy to identify. Let’s discuss them, shall we?

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Next stop on the Pod Projections train is last year’s breakout starter Chris Sale, who spent his first season in the White Sox rotation. While I cannot claim credit for expecting him to be that good, I was a huge fan heading into the season. But after a more human second half that included a 4.03 ERA and a significant innings increase, what should we expect as a follow up?

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Before I begin, I wanted to get something out of the way first. I have never played in a keeper league for more than a season (therefore never having the opportunity to make keeper selections), and so I might be wrong about my feelings on this strategy. But, I don’t think I am. On Saturday, I was asked to participate in an online auction for a FanGraphs reader who was unable to attend. Being the awesome person that I am and unwilling to pass on a chance to participate in another auction, the player selection format I enjoy significantly more than the snake draft, I said yes with little convincing necessary.

This was a 12-team 5×5 mixed rotisserie keeper league, where if an owner chooses to keep a player, his salary would increase $3. Standard roster size, except the league uses just one catcher instead of two. Oh, and you also use your auction budget ($270, instead of $260) to bid on your 5 reserves. Anyway, having had little experience in a keeper league auction to compare, this one seemed insane. Let me tell you how.

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It’s been over a week since I shared my last Pod Projection, so let’s get back on the saddle. Easily tallying the second highest number of votes was Max Scherzer. Clearly, Scherzer set your heart aflutter when he posted that 2.69 ERA in the second half. Funny, it was just the luck pendulum swinging the other way, rather than any change in skills, as his xFIP was very similar in each half. On to the projection we go.

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