At the beginning of last season, I contextualized the swinging strike rate (SwStr%) (and refreshed those numbers after the season concluded). I had seen other analysts call certain pitches “above-average,” “below-average,” “elite,” etc. using the league-average whiff rate as a baseline. This is neither a criticism nor a judgment, as I absolutely did this before I had my statistically-driven epiphany. But understanding the average four-seamer’s or slider’s or cutter’s whiff rate lends additional context to any assertion one might make about the “elite-ness” of a pitch.

More recently, I wanted to convert discrete outcomes by pitch type into fielding independent pitching (FIP) statistics — namely, FIP and xFIP (expected FIP, which substitutes a pitcher’s rate of home runs per fly ball for the league-average rate). Let me warn you now: the results are very imperfect. It took some brute force on my part to get there, but I got there. I would wager that the the extreme (lowest and highest) values are probably a bit exaggerated. Regardless, it’s an interesting table to ingest:

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You should buy an ace.

The fantasy landscape has changed dramatically over the past few years. Just a half decade ago, a mid-$20s bid at a mixed league auction would buy you a top pitcher. $30 was unheard of … for any pitcher. A non-hitter in the first round was blasphemous. Pitching was thought of to be too volatile, and far too risky to roster at such a considerable cost.

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Injuries analysis is becoming a pain in the butt. First, MLB goes and changes the days missed from 15 to 10 thereby nullifying several projection models. And now they’ve gone and renamed the Disabled List the Injury List. I think of naming it the BDL (Broke D__k List). I’ve been waiting for a few more seasons of DL data to create a new formula which will become obsolete with the 12-day DL but why wait. I have two seasons of 10-day IL information to create a few comparisons, especially for pitchers.

While I’ve historically collected the data, Ryan Brock jumped in and completed the 2018 season. I’m not sure if I would have gotten to pulling it together because when I normally do it (post-season), I was finishing my book. I can’t thank Ryan enough.

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2/9/19

The latest episode of “The Sleeper and the Bust” is brought to you by Out of the Park Baseball 19, the best baseball strategy game ever made – available NOW on PC, Mac, and Linux platforms! Go to ootpdevelopments.com to order now and save 10% with the code SLEEPER19!

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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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