Last year, I wrote a piece about Luis Castillo. Even though I liked him, the draft helium priced me out of the room. In the process of drooling about his upside, everybody forgot the myriad plausible scenarios in which he could disappoint us. So I wrote about how it could go wrong.

Here we are in 2019, and it’s as if nothing has changed. A painful first half chilled owners, many of whom cut bait. Those with the patience to hold or the perspicacity to buy low were rewarded with a wonderful second half. Castillo is once again among the most heavily hyped non-ace pitchers in the league.

Today, we’re going to revisit that post, using the classic internet technique of quote – respond. You’ll see what I mean.

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For me, the end of the Super Bowl is the official start of the fantasy baseball season. Obviously, I never really take my attention away from baseball even after the World Series, but I’m definitely an outlier. There are plenty of big time baseball and football fans who close the book on the diamond for the pigskin come October (or even September if their fantasy team falls out and their favorite team doesn’t make the playoffs) only to return once football is done.

Well, it’s done!

With that, it’s time for a new SP ranking update. I’d be hinting at an update coming sooner than later, so I appreciate your patience. I’ve got a list running 120 deep with colored bars denoting some talent breaks. There is still a substantial Glob™ where the distinctions between pitchers become thinner. I don’t have an ironclad case for #80 over #106 the way I do #16 over #42. These are my preferences, though. I’m not leaning on The Glob™ to shirk accountability for my rankings, but it’d be foolish not to acknowledge how wide-open SP ranks become around 70 or so. In fact, there’s an upper tier Glob™ from around 35 to 79 and then the standard Glob™ from 80 until maybe even 150 or so, but I decided to cut it at 120.

I’ll have plenty more on pitcher rankings in the coming months, including lists with commentary on most (if not all) pitchers, lists for attacking The Glob™, my biggest buys, my biggest fades, and more! Justin and I will have a two-part positional preview pod on starting pitchers, each likely approaching two hours if I had to guess. But for now, enjoy this list and let me know what you think in the comments below.

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Alas, it’s Pod Projections time, as the 2019 forecasts are now available! As usual, I’ll dive into my projection methodology (detailed in Projecting X 2.0) by sharing my process on several hitters and pitchers.

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Yesterday, I examined some hitters with the largest plate appearance projection discrepancies using five separate sources. Today, pitchers take center stage.

I’m using the projected playing times from FanGraphs Depth charts and four other sources. Again, I won’t name them as I don’t want to debate the merits of each. My goal is to just find and evaluate different takes on the same players.

The differences aren’t nearly as drastic as the hitters, especially for the top arms. Most of the major differences involve around unknown roles and injury risks. I listed the top-200 at the end while the values for free agents and foreign signings may be off or missing. I’m going to focus on the biggest differences in some top-ranked pitchers.

Ross Stripling
Range (Max-Min): 67
Average: 112
Standard Deviation: 33

I’m not surprised one bit on Stripling. Unless the Dodgers get hit with a ton of injuries to their starters, he’s going to begin the season as a reliever or in the minors. He’s got the talent to be a top-20 starter but the number of starts he’ll get is unknown. Owners can draft him and hope his talent forces the Dodgers hand. The other issue is that he’s on the Dodgers who manipulate their roster to give pitchers scheduled days off via demotions or “injuries”. Good luck guessing right with him.

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The amount of stats available to analysts today is overwhelming. At least it’s getting that way with me. I’d prefer everything to be available to investigate an idea. But no one has the time to go over every single stat to see if a player has changed for the better or worse. I’m going to eliminate all but 10 stats to focus on those few that matter the most.

The key behind my analysis is to find if a pitcher or hitter has changed. A few dozen projection sets exist to set a talent baseline but once the season starts, most people want to throw them out (some even before the season) if a hitter is batting .150 or a pitcher has a 6.00 ERA. Players are human and creatures of habit so most won’t change. But some do and being able to focus on these few can help to find values.

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I love the idea, almost to a fault, of taking one or two of the top 5 SPs in the first and/or second round. The reason I like getting these top arms is that they provide a ton of strikeouts with great ratios. This base in ratios allows me to ignore pitching for almost 10 rounds and then bottom feed. One problem I’ve run into with this strategy is that I won’t have this option available if I’m picking in a draft’s first few spots. I’m not passing on the five-category hitters and according to the current NFBC ADP (average draft position), the top Aces will be gone by the time my second pick comes around. If I’m forced into this situation, I’m considering going with the what I’ll call the “Streaming WHIP” plan.

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How different are these two pitchers?

• Pitcher A: 3.67 ERA, 1.30 WHIP, 24% K, 7% BB, 3.18 FIP
• Pitcher B: 3.77 ERA, 1.20 WHIP, 28% K, 7% BB, 3.41 FIP

I’d probably lean toward B as I’m a strikeout slut, but the idea that they’re markedly different wouldn’t really hold up. Even if you look at their pitches, I’m not sure there’s a clear difference:

• Pitcher A: -4.2 FB, 10.0 SL, 1.4 CB, -1.3 CH
• Pitcher B: -4.8 FB, 11.2 SL, 4.8 CB, -3.2 CH

Pitcher B has a stronger second-best pitch with that curve, but Pitcher A’s fastball and changeup were both better while the pair shared similarly strong sliders. After his campaign, Pitcher A was taken as a top 40 SP in most drafts. Currently, Pitcher B is going among the top 25 SPs, which means yes, it’s two different seasons for these stat lines. Both also happen to pitch in the most hitter-friendly environment the game has ever seen.

By now you’ve likely guessed that both are Colorado Rockies.

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We all knew that Sonny Gray’s days as a New York Yankee had come to an end, and finally, the Reds acquired him and immediately signed him to a three-year extension. Moving to the National League is a good thing. Will the park switch improve his chances to rebound as well? Let’s check the 2017 park factors.

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It’s time to start discussing pitcher rankings and fantasy managers need to know it’s a new landscape for two reasons. First, the idea of every team having one or two 200-inning starters is *over*. The top arms are putting up similar stats to the past. The change now is with the floor. It has just fallen. Starters are just not going as long and the Wins and Strikeouts they accumulate are gone. Second, many bullpens are now going to more of a committee approach where there aren’t 30 set closers but more like 20. The lack of Saves in a concentrated few closers boost their value and the overall value of every Save.

It’s time to get to the rankings. I used the 15-team Standings Gain Points (SGP) Formula from The Process to create these rankings. I used FanGraphs Depth Chart projections (stats in the table) along with three other sources (not to be named). I ranked them by the average SGP value and also included the standard deviation in all the values.

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It seems as though each year, fantasy baseball analysts, “professional” and amateur alike, hone in on a new — or, if not new, then relatively untouched — metric or data set for their endlessly eager consumption. In 2015, FanGraphs introduced batted ball data to its leaderboards. In 2016, Statcast data was unveiled, although it arguably didn’t become popular until 2017, and before the 2017 season FanGraphs changed the game with its splits leaderboard. Baseball Prospectus has introduced myriad new metrics, too — DRA in 2015, DRC+ last year, etc. — and we began to lean into pitch-specific performance analysis last year. (The latter-most topic is relevant to what follows here.)

I recently joined Christopher Welsh and Scott Bogman of In This League on their podcast. I thought one of the evening’s questions was particularly topical and prescient (and I paraphrase): What will 2019’s it metric be? The question was asked with pitch values, something I’ve seen garner increasing attention on Twitter, in mind.

You can acquaint yourself with pitch values directly from the man who created them:

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