The aftermath of The Great Valuation System Test continues! Before reading further, be sure you know what was being tested and our process, along with the results:

The Process
The Results

At the end of the results article, I mentioned that although we now have a good idea of which valuation system proved best at converting a player’s statistical line into a dollar value, that doesn’t necessarily mean that the system does the best job for every individual player or player type. So today I’ll look into different player groups and individual players and see if we could find any patterns.

I will be excluding ESPN because their rating number is on a different scale and only using the Razzball – 0% Pos Adjustment & 100% versions. I also don’t have room to fit all the systems in so had to cut down in some manner.

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Yesterday, I shared the exciting news that my project partner Jason Bulay and I have completed The Great Valuation System Test, which involved a whopping 13 fantasy baseball player valuation systems. As usual, I feel like I could have done a slightly better job of explaining our process and goal. Essentially, we wanted to determine which valuation system most accurately converts a player’s statistical line (accounting for his position or ignoring it) into a dollar value. I eagerly awaited all the data so I could run the correlations and had my fingers crossed that the system I use, the REP method, performed well, if not the best. So it’s time to unveil the results.

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It all began with a comment by Jason Bulay, aka The Stranger, on a post I published in January pitting two popular snake draft strategies against each other — best player available and position scarcity:

I posted this as a comment to Cwik’s article yesterday, but I really want to see everybody put their money where their mouth is with all the draft strategy/player valuation theory. Do a draft (or multiple drafts, because small sample size) where everybody will be scored using 2014 stats (or 2015 projections if you prefer). After the draft, add up everybody’s roster using standard 5×5 scoring. See who wins, and what kind of draft strategy really gets the best roster. See who loses, and mock them without mercy.

Not that I disagree with you – your points make sense. But I think this is something we can actually test and I’d love to read about the results, so why not give it a shot?

His idea was intriguing. We’re all very familiar with the various projection systems and know that the masterminds behind them continually strive to improve them. They are also tested every year and we learn which performed best. But valuation systems get none of this treatment, as there has seemingly been little to no progress made on properly valuing players since the original systems were developed and shared.

Jason eventually followed up with an email and after many back and forth messages, we finally settled on exactly what we wanted to test and how we would accomplish our goal.

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The Steamer and I series concludes as I finish with the last starting pitcher comparisons. Today, I check in on two pitchers of whom the Steamer projections are significantly more optimistic than my Pod Projections.

As per SIERA, Zack Greinke is coming off the second best skills of his career, driven in part by a rebound in his slider usage. He’s managed to post sub-3.00 ERAs for two straight seasons now, which has made him the 10th pitcher off the board on average in NFBC drafts. James Shields hit the free agent jackpot by signing with a National League team and remaining in a pitcher friendly home park. He, too, is loved by drafters, who are nabbing him 22nd among starters in NFBC. Let’s see why Steamer and I disagree on these two fine lads.

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The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X, and the process continues to evolve and improve.

After winning both the American League MVP and Cy Young awards back in 2011, Justin Verlander followed up strongly the next season, finishing second in the Cy Young voting. But in 2013, his fastball velocity slipped for a third straight year, which drove a decline in his peripherals and resulted in his highest SIERA mark since 2008. It got even worse last season, as his velocity dipped another mile per hour, his strikeout rate fell to its lowest mark since 2006, and he couldn’t strand runners at the rate he used to, while poor defense behind him added more fuel to the fire. All told, his ERA jumped above 4.00 for just the second time of his career.

At age 32 and with a seemingly clear explanation for his recent struggles in the form of the velocity loss, it’s no surprise that fantasy owners aren’t sure what to expect from Verlander this season. On average, he’s just the 46th starting pitcher off the board in NFBC leagues at pick 186, and his pick range sits between 93 and 253. That’s quite the discount for someone with his track record who may have had just one poor season. So let’s get to the projecting.

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When injury strikes, opportunity arises. This time, Michael Taylor is the beneficiary. Initially expected to step in for Jayson Werth as he recovers from right shoulder surgery, Taylor is suddenly set to enjoy more guaranteed playing time in the wake of Denard Span’s expected absence. Yesterday, Span underwent core muscle surgery, which figures to sideline him for at least four to six weeks. That means that Taylor will now fill in at center field, possibly for the entire first month of the season.

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The Steamer and I series continues this week as I move onto starting pitcher comparisons. Today, I check in on two pitchers of whom the Steamer projections are significantly more bearish than my Pod Projections.

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The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X, and the process continues to evolve and improve.

Interestingly, I have seen many commenters ask for advice when choosing between this Monday’s Pod Projectionee, Carlos Carrasco, and today’s choice, Jacob deGrom. You’ll see when I unveil my full deGrom projection below, but it’s a rather close call, as they have very similar forecasts.

With that said, deGrom essentially came out of nowhere last year to post a sub-3.00 ERA in 22 starts and earn NL Rookie of the Year honors. He generally posted ho-hum minor league peripherals, but perhaps fueled by a faster slider, his coming out party occurred in the Majors. Before beginning my projection, I shared four reasons why deGrom was for real. Since I gave it away above by comparing the projection to Carrasco’s, I’ll tell you that I still feel the same way.

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This post continues our Depth Chart Discussions. In an effort to suss out every team, we’ve divided them into four parts (infield, outfield, rotation, and bullpen) and will continue to break them down for you over the next few weeks. You can find the Depth Chart Discussion posts gathered here.

By our projections, the Dodgers have the second best starting pitching staff in baseball. That makes for quite an attractive rotation. Let’s discuss these lads, shall we?

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Last week, I posted the first comparison in this new series discussing discrepancies between the Steamer and Pod Projections. I began by looking at Corey Dickerson and A.J. Pollock, two players I was far more optimistic about this season than Steamer is. Today, I’ll look into a pair of sluggers who Steamer likes better than I.

Steamer doesn’t like many hitters better than I do. Of the 328 hitters we both project, Steamer projected at least .001 wOBA points higher than I did for just 83 of them (25.3%). On the other hand, I am more bullish on 232 hitters (70.7%), while we project identical wOBA marks for 13 hitters (4.0%).

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