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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This past offseason, I found an xBABIP equation which correlated better than just BABIP when looking at season 1 to season 2 values . By using the the new Inside Edge data and player speed score, I kept the process  simple yet accurate. I have tweeted out the results a few times during the season, but it is time for another  full updated list.

The Inside Edge data tracks the normal bunts, grounders, fly balls and line drives. In addition to the four groups, they classify the batted ball into weak, medium and hard contract. For the xBABIP equation, I looked at all the line drives and all the hard hit fly balls and grounders. Additionally, speed is a component of getting on base so Bill James’s Speed Score is also added into the calculation.

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Yesterday, I identified and discussed the five players most added in CBS Sports leagues. So today of course, I’ll check in on those players being dropped. Often I find the dropped players are better than the added players as fantasy owners love to weight the last two weeks of performance infinitely more than the player’s entire body of work. So let’s see if owners are making the right moves when dropping these guys.

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I’m back with a second edition of roster trending, checking out some of the players who have experienced the biggest ownership spikes in CBS leagues over the last week. These lists are always interesting and offers an insightful glimpse into the mind of the average fantasy owner. So let’s take a gander at who is being added in leagues and determine whether fantasy owners have the right idea.

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Starting pitchers need to be treated like stocks. Perceived value is more important than inherent value. When a stock becomes overvalued compared with your valuation estimate, you sell it, even if the company is a good one. The same goes for pitchers. I’m a fan of Scott Kazmir, think he will remain a good pitcher and solid fantasy option and I continue to be in awe at his career revival. But, it’s time to sell. And that’s precisely what I did yesterday in my local 12-team mixed league.

**Keep in mind that I am typing this before his start last night.

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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 »

A year ago, I developed a regression equation to estimate what a pitcher’s strikeout rate (K%) should be. That formula used a trio of strike type rates found at Baseball Reference, including a pitcher’s looking, swinging and foul strike percentages. While the original formula was a strong estimator, I have since tweaked it slightly.

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There’s nothing I love more than a cliche for the title of a post.

Today I want to take a look at a few of the players who have seen some of the biggest drops in ownership percentage on ESPN.com so far this season. Because we’ve only played a few games this year, determining whether I think these guys should be snatched off the wire comes down to whether I liked them in the preseason. I put hundreds of hours into preseason prep work, so I might as well milk it for all it’s worth while I can.

Dillon Gee — 7-Day % Change: -27.6%

There was a point where four of the five most recent articles that showed up on Gee’s player page were written by yours truly. I loved what he did in 2012 when he saw a big spike in swinging strike rate which pushed his strikeout rate comfortably above league average. He also had a solid ground ball rate just over 50%, and he limited walks. But his ERA was north of 4.00 thanks to a strand rate that was in the lowest quantile among pitchers with at least as many innings as Gee. I was all over the guy with solid strikeout, walk and groundball rates going into 2013.

Gee delivered in a way with a 3.62 ERA last year. But he didn’t do it like I wanted him to. His swinging strike rate and strikeout rate fell back below league average to where they had been prior to 2012. His groundball rate also fell significantly as well, but his walk rate did hold. The main reason he was able to post a sub-4.00 ERA was a reversal of strand rate fortune. His strand rate went from 68.9% to 77.9%. To repeat his 2013 ERA he’ll either have to regain the above average strikeout and groundball rates or get lucky again. The good rates of 2012 seem to be the exception and not the rule, and you can’t own a guy banking on strand rate. Leave him on the wire, and use him as a streamer if the right matchup comes along. Read the rest of this entry »

Yesterday, I analyzed the five players most added in CBS leagues. Was the juice worth the squeeze? For the most part, no. Are fantasy owners also dropping players too hastily? It follows that if fantasy owners love to chase the hot player du jour, they also get too trigger happy when jettisoning players from their rosters. Let’s discuss the five most dropped non-injured players in CBS leagues. Are fantasy owners justified for their decisions and if these players are now available in your league, should you pounce?

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While we’re generally quick to throw out early-season performance as a matter of small sample size, doing so universally risks throwing the baby out with the bath water, to shoehorn an expression into a place it doesn’t really fit.

While small samples generally aren’t very predictive or revealing of true talent – the quickest metric to stabilize is strikeout rate, which requires about 60 plate appearances to cross the 70 percent reliability threshold – they do matter. An 0-for-20 stretch can doom a player, a 12-for-20 stretch earn him a great deal of leash with a manager. Small sample sizes have meaning for many players.

A week into the season, a handful of players are seeing far more playing time than was expected. How they are performing in these small samples could very well determine the fate of the rest of their seasons.
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