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.

2017 Pod Projections Index:
Lance McCullers

Today, I’ll dive into the first hitter to receive the exciting 2017 Pod Projection treatment. David Dahl thrilled us during his debut last year, showing power (.185 ISO), speed (7.7 Spd score, five steals), and batting average ability (.315). That’s literally everything we want as fantasy owners. Of course, let’s not ignore the fact that he required an absurd .404 BABIP to reach that impressive batting average mark. That said, he plays half his games at Coors Field, so perhaps his average has some staying power. Early 2017 NFBC drafters are already falling over each other to roster him, selecting him as the 22nd outfielder off the board (just before Matt Kemp, Khris Davis, and Adam Jones), and 91st overall. WOWZERS! That’s some serious love.

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Over the last couple of years, I have run the “Steamer and I” series, pitting our hitter wOBA and pitcher ERA projections against each other and discussing the players our forecasts differ the most for. I’m going to do things a little bit differently this year by focusing on individual stat categories, identifying a group of players I’m significantly more bullish on compared to Steamer, and vice versa, in that metric.

We’ll start with home runs. I will be comparing my home run Pod Projections to Steamer, which have been extrapolated to the same number of at-bats I’m forecasting. Today, we’ll look at the hitters I’m most bullish on versus Steamer.

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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.

A couple of months ago, I received my first Pod Projection request from a commenter, and that request was for Astros starting pitcher Lance McCullers. The 23-year-old made his Houston debut in 2015, as he made 22 starts and posted an impressive 3.22 ERA with excellent underlying skills. Unfortunately, he followed up that freshman effort by finding himself on the disabled list for what amounted to about half the season. He dealt with both shoulder and elbow issues, which limited him to just 14 starts. Although his control deserted him, he still posted strong skills, en route to an identical ERA as 2015. Now, he’s the newest member of my 2017 LABR Mixed Draft squad, so let’s find out what I projected his 2017 results to look like.

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Some fans call him Superman, and for good reason. He hits for average and for power; he draws walks and barely strikes out; he plays premier defense at a premium position. He’s won Rookie of the Year, Most Valuable Player, three Silver Sluggers, a batting title, a Gold Glove, and oh by the way, three World Series rings. Read the rest of this entry »

Projection Analysis: Yoan Moncada

Many prospect experts project Yoan Moncada to be one of the game’s few top prospects. Some have him as the top guy but his MLB playing time and production varied substantially. I found I needed a projection I felt comfortable using.  I’ll start with his playing time.

I believe he’ll be promoted between the Super Two deadline (so the White Sox can save money) and early September (rosters expand). I thought about using July 15th (All-Star Game) as my cut off.

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My Tout Wars prep continues. I have already examined the league’s historical aspects which I have used to create initial auction values and a draft outline. With the initial projections out of the way, I am refining them. One step in this process is to find the replacement level player and adjust players who will miss time accordingly.

The concept behind the replacement level player is fairly simple. If a good player is expected to miss significant time, his fantasy value is based on just the games he is expected to play. For the games he misses, some lesser player (replacement level player) will fill. The better player’s total value will be both his and the replacement player’s contribution.

For example, I don’t expect Yoan Moncada to get called any earlier than the Super Two deadline around June 1st. For the months he’s in the minors, a less talent replacement level player will be subbing in for him. The same idea works with pitchers. Tyson Ross is expected to miss at least a couple of months so a replacement is needed until he gets healthy.

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My fellow RotoGraph writers and I have started compiling our preseason position rankings. My initial rankings are projection based and then I adjust them as I see fit. I found several rankings/projections where the industry and I disagree. I am going to dig into three of those players today with more to come.

Freddie Freeman: Disputed Projection

Tenth? Really? I didn’t expect Freeman that low. Depth Chart based SGP values place him out as the tenth first baseman. At NFBC, he is the 6th first baseman which is near my gut based ranking. Additionally, he just went 24th overall in MLB.com’s Fantasy411 slow industry draft.

I am fine with the six players ahead of him (Goldy, Rizzo, Cabrera, Votto, E5, and Bryant). Then my gut disagrees and I am pretty sure some of our readers will also.

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Last week, our own Brad Johnson discussed unpredictable auction values in “Rationality Will Ruin You”. I 100% agree with his premise. Unexpected inflation exists but so does a solution. By charting out the desired and the potential outcomes before an auction, an owner can remove a ton of auction frustration.

Brad examined the elite player section of the draft where the actual auction values are higher than most people’s predicted values. Owners refuse to pay these high values but instead end up spending their resources on near replacement level talent. The following simple chart helps an owner deal with the problem along with uneven hitter/pitcher mix and outlining a personal auction strategy. The process is similar to the one used in Winning Fantasy Baseball by Larry Schechter but with a few more additions. Here’s the procedure.

Step 1. Get auction values

This step could be as simple as using our auction calculator or creating your own projections like our own Mike Podhozer does. To set the pitcher/hitter mix, use the league’s historic mix or just go with standard 70/30 split.

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Prospect list season is in full swing. Our Eric Longenhagen is knocking out his team lists. Keith Law has just finished his top 100 and team lists. Baseball America is done with their team rankings and is working on their prospect annual. And MLB.com just released their position rankings and top 100. The MLB.com’s top 100 list intrigues me the most. Since it provides scouting grades, it can be used to project a hitter’s fantasy value.

Earlier this offseason, I had a series on using prospect grades to project MLB talent.  While Field and Arm grades help to keep some players playing, defense doesn’t count in fantasy leagues. By comparing a hitter’s Bat, Power, and Speed grades I was able to come up with an overall 20-80 fantasy grade and projected full season stats. These values aren’t close to the final say in player values. They are just an input to be used with scouting reports, normal projections, and other systems like KATOH. Read the rest of this entry »

So far in my Tout Wars preparation series, I’ve documented the league’s draft tendencies and the stats needed to win. Today, I’ll create the framework for player pricing. Along the way, I will show how there is no position scarcity except with catcher. At least for this league

Completing this step brings the preparation is laborious, but necessary. Once it’s done, I can spend most of my time evaluating players and their projected playing time.

For evaluating players, I utilize the Standings Gain Points (SGP) method. I previously outlined the procedure and it‘s the same method Larry Schechter recommends in his book, Winning Fantasy Baseball. Normally, this procedure is fairly straight forward since I’ve historically used three-year average values. Last year’s offensive explosion complicates the math. With more offense available, home runs, Runs, and RBIs become less important. Predicting 2017’s run scoring environment is impossible so I won’t for now. I feel I need to use a weighted average system with 2016 getting the most weight but I am just not sure how much to weight them. To get the process started, I will use the average standings from 2014 to 2016 for this work.

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