I’ve been playing in auction leagues since about 2001 and believe it to be far superior to snake drafts. Why choose a draft format that immediately prevents you from acquiring players as soon as you know your draft slot isn’t number one? I want the opportunity to buy Mike Trout for $48 damn it! Okay, enough standing on my pedestal and rehashing why I think auctions are best. Let’s just talk about some random things that have popped into my head since my Tout Wars auction on Saturday.

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A few weeks back, I dropped some ice-cold water on some of the spring’s favorites just to give us a reality check about their downside. Interestingly enough, the guy I was struggling most to wet blanket is the one who is now dealing with an ailment: Anthony Rendon with his MCL. For me, his checkered health record was the only thing really holding him back as it could cut into his base-stealing production if it was something nagging and obviously something more severe could really take a chunk out of his numbers. Today, I’ll do the same from fast-rising pitchers and ideally, I’ll go beyond health concerns for all three picks as those loom overhead for every single pitcher every single time they throw the ball.

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Weekly update:

• Add a bunch of times to first.
• On batted ball, I am trying to correctly combine categories batted ball categories. With categories combined, it will take less time for a hitter’s batted ball profile to stabilize. I hope to have a major update on this area in the next week or two. After that, I can start getting some real values for the stats begin to stabilize.
• Here is a link to the data in an Excel format. For some reason I can only embed OpenOffice files.

Pitchers’ Approach Attacking Hitters

Robert Arthur at Baseball Prospectus has shown pitchers will change their approach depending on the hitter’s talent level. Here is a complete list of the number of fastballs (including sinkers) thrown to each hitter of the past two years divided into half seasons. Also the number of pitches in the strike by half season is included along with the fastball percentage in the strike zone. I will begin adding 2015 information as it becomes available.

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My Tout Wars evening almost went a very different way on Tuesday night. We had 15 of us gathered for the Tout Wars Mixed Draft and I had the 11^th overall pick. This is an OBP league which severely changes the value of some players, so keep that in mind when you’re looking at the draft board. We had to run the draft on RTSports through one of their mock drafts even though the league will be hosted on OnRoto in-season. This caused some issues right out of the gate and nearly set my night down a vastly different path.

On my end, the draft didn’t start at 7:00 PM central as scheduled. There were no sounders and nothing was moving. At about 7:04, it jumped live to the 14^th pick and I had been auto’d with Adam Jones. He is an unquestionably great player, but I wouldn’t necessarily take him there in a standard league with AVG and I certainly wouldn’t take him there in an OBP league. He experiences one of the biggest value shifts going from AVG to OBP. He has hit a composite .284 over the last five seasons, ranging from .280 to .287, but an unspectacular 3.9% walk rate leaves him with just a .321 OBP in that same span (.334 high, .311 low). I was pretty livid.

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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.

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Friend Eno explored the world of punted statistics yesterday. For those of you not in the know, “punting” occurs when a fantasy owner does not attempt to score in a specific stat. It’s most commonly seen with stolen bases and saves. Eno’s findings confirm that those are the optimal categories to punt.

Eno also discusses when to punt, noting that it’s a much more viable strategy in an H2H league than Roto. He explains the details, so check it out. If you’d like to discuss why H2H and Roto leagues are treated differently, let’s chat in the comments.

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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?

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Last Sunday, the FanGraphs Ottoneu League #2 did our auction. Chad Young, Brad Johnson and Scott Spratt have each given their thoughts on it. It was a unique auction (most are in some way) and by making a few early adjustments I was able to come away from it better than I expected.

To begin with, I hate to start any fantasy season in complete rebuild mode. I want to have a chance to win if everything goes right. Before last season was half way over I had about zero chance of winning so then I started a rebuild. I had the most free agent dollars, I picked up some $1 players (Harrison, Petit, Boxburger, House) and waited for a team to drop a high dollar player to free up some cash. The plan worked great by getting Joey Votto and Brian McCann. Also, I like prospects, even if they have limited upside, near the majors and picked up players like Matt Wisler, Carlos Rodon and Ty Kelly.

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I have never thought much about, or given much attention to, FanGraphs’ fan projections. It’s primarily a matter of stubbornness: I run my own projections, and I develop my own strategy, so why should I listen to you? At least there’s a trace of rationale behind it: I know how I created my projections (whether or not they’re any good is a topic for another day), but I have no idea how you created yours. Thus, I am more likely to blindly trust a computer-generated projection system such as Steamer instead of random fan projections.

Still, there is a sort of bizarre, secondhand wisdom to fan projections. For every person who is high on a particular player, there could be another person who is equally-and-oppositely down on him. Solicit and aggregate enough fan projections and you could produce a very reasonable prediction of a player’s performance by sheer chance.

Which is why fan projections intrigue me. If, for example, Steamer predicts the most likely outcome from a wide range of possible outcomes for a player, then the fans convey the anticipated outcome for a player. The difference between them, you could say, is what amounts to a market inefficiency (aka a price distortion). The larger the difference, the greater the inefficiency. We see these inefficiencies arise every year — 2014’s most prevalent example is probably Corey Kluber — and they typically manifest because of a lack of information about certain players.

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Last week, we came out with our Top 300. The outcomes looked excellent and I would not hesitate simply using the presented composites for your drafts.

CoolWinnebago asked if we would present our approaches. I provided a high level summary under bago’s comment, but I’ll summarize and then embed my personal rankings (without all the highlighting of my targets of course).

Feel free to skip toward the bottom for my embedded rankings, but here is the context/approach:

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