With trade deadlines coming up at the end end of the month, we are are going to publish some 2015 hitter projections to help owners make more informed decisions.  (Pitchers maybe later in the weak – I hate dealing with Saves and Wins so it may just be ERA, K, and WHIP). These are projections, just projections … an estimate of how a hitter will perform in 2015. The list should give owners a decent starting point when setting keepers or last minute trades for the next year.

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Last week I took a look at the three hitters who were not included in the initial Steamer preseason projections who are now projected to be above average fantasy players for the rest of the year. Today I want to look at the hitters who were included in the preseason projections who have seen their projected value increase the most one month into the season. I explained the methodology in the last post, but the short version is that each player is assigned a standardized score for each roto category (using z-scores) and when those are added up and an adjustment is made for positional scarcity we get a number called fantasy value above replacement (FVARz). Full disclosure: I’m using the numbers I calculated using the rest-of-season projections on April 29. I didn’t have time to re-run the numbers for this post, but that shouldn’t have a huge effect. Read the rest of this entry »

Yesterday, I ran out of time while writing my MASH Report to look at how the possible effects of diminished velocity could have on Clayton Kershaw. Well, using a couple of untested, but promising ideas, it seems he will be may not struggle with less fastball speed.

The worries with Kershaw stem from this tweet.

89-91, touched 92 a few times. RT @gq2scoops: Anybody know how Kershaw’s velocity was tonight?

— Dustin Nosler (@DustinNosler) May 1, 2014

He could be getting some of his strength back, but a possible 2+ mph drop could mean trouble for him. Kershaw’s fastball has at least averaged 92.5 mph in each of his six previous season. By looking at how he has produced previously at times with a lower velocities my indicate how he will do in the future.

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In the preseason I used Zach Sanders’ method for deriving fantasy value from roto category statistics to see how the Steamer projections valued players from a fantasy perspective. The system essentially compares each payer’s production in each category and assigns standardized values for each player in each category. When you add those numbers up, you get a player’s fantasy value above average. After a quick adjustment for positional scarcity, you’ve got fantasy value above replacement (FVARz). In the preseason this was helpful to get an idea about who might be over or undervalued. Now I’ve taken the Steamer rest of season projections both to see whose value has changed the most in the month or so since the season started and to potentially help with making trades.

Today I want to highlight a few players that were not included in the original Steamer projections. Next week I’ll take a look at the players whose value has increased the most since the start of the season. Read the rest of this entry »

We always hear our not-so-favorite broadcasters mentioning a player’s stats against a certain pitcher. Well, I think we are all hopefully smart enough to not take the results of 15 meetings between a pitcher and hitter seriously. Instead, we split samples into larger groups like right-handed hitter vs. left-handed pitcher. I have decided to cut the difference and create a spreadsheet which takes a middle ground. I grouped pitchers by handedness, velocity and groundball tendencies and found how hitters performed against the different pitcher groups.

First off, I wanted to have this Excel-only spreadsheet available online before the season started. Well, I got it done and working in time. Since Visual Basic macros were used in the final view, it doesn’t have a online option which I wanted. So today, I am going to make it publicly available, but at some point I hope to have it working in all spreadsheet formats and/or online at a place like Google.docs.

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On Tuesday, I wrote about wrinkles that I tried to add to the so-called Dewan Rule, hoping to leverage spring training statistics to help predict breakouts. It didn’t work, as was somewhat expected. In fact, Dewan himself admitted on Wednesday that the rule no longer seems to work.

However, a suggestion in the comments section led me to study the same data from a different angle, and it now seems a bit more promising.
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So, you may have heard that ZiPS projections are now available for 2014. You may also be wondering if said projections reveal information pertinent to your fantasy drafts. Well, let me tell you.

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Bender wrote about three players he would not draft yesterday, and I thought I’d pitch in with three of my own. These kinds of posts convey a lot of information about where the writer thinks the marketplace really diverges from reality, so they can be among the most useful when preparing for a draft. I’m not saying that you should take what we say as gospel, but if your own expectations are substantially different than ours, it might be worth taking a second look.

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I am going to finish my fantasy ranking series today (Part 1 and Part 2). Today, I am going to look at how I set up my draft ranking.  It is a little unique, but indispensable for finding draft day values, but I first need to clear up one issue from yesterday.

I am going to go over one problem people are noticing which is how high catchers are in my rankings and the lack of Robinson Cano. Well here are my projections for each. If you disagree, that is a different discussion, I am just looking at the difference in replacement level values:

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In my last article, I went over the initial work for valuing players in a basic fantasy league (12 5×5 teams with 23 roster positions).  Each league has its own unique rules so the procedure may need to be adjusted accordingly. Today, I am going to finish the positional rankings and begin to come up with an overall ranking.

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