For those of you old enough to remember a time before Survivor and American Idol, you might recall the era of Kaizen that permeated the economies of the 1980s and 90s. In Japanese, kaizen means something like “continuous improvement,” and it was one of those old pre-capitalist ideas that got co-opted by industrial society. So instead of like, running a bit farther every day or being 10% happier, the concept of kaizen turned into this phantasm of continual product improvement and personal productivity maelstroms. Maybe you’re running faster, but it’s because your job needs you to finish your work and somebody else’s work at the same time. Product sprints. Agility. Synchronicity (and not the album by The Police). But “continual improvement” done in the name of producing things faster, doesn’t necessarily mean that the actual product is any better.
It’s really not a surprise that the fantasy sports world also adopted this kaizen mentality — more products, somehow “improving,” but ultimately making fantasy players work harder. How many people are old enough to remember when a copy of Baseball America and a printer was the complete setup to play fantasy sports? Now we’ve got data providers everywhere. How many accounts do you have with a data provider? I’ve got [thinks for a while] six? I’m still learning about fantasy analysis sites that I’ve never heard of before, and I’ve consumed fantasy content on the regular since Firefly was on actual broadcast TV. And which provider is better? Is it the one that outputs data the quickest? Is it the one that makes you laugh? Is it the one that uses the least amount of preface to their articles?
All this to say: I’ve “improved” my system a bit this week. Is it actually better? Who knows. I worked on it, I’ll tell you that much. I used best practices and data-backed principles learned from years of study. I had a “Hypeonator” that said if a player was “Hype” or “Whack” and then I deleted it. I merely open doors — it’s up to y’all if you take the hype. That said, let me share a bit of the terminology that I’ll be bringing to the fore for the upcoming articles.
Example Table:
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Carlos Rodon | 43.4 | 21.26% | 1.55% | 62.39% |
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Patrick Corbin | -45.6 | -24.08% | -6.55% | 14.57% |
Name: As names have power, words have power.
L30$/G: This is the $/G over the Last 30 days, as calculated by Rudy over on this side of the Razzball site. This is the actual fantasy value for the player, regardless of how the player should be playing. Remember when I pointed out last week that Tyler Mahle and Alek Manoah had basically the same advanced stats but were 200 spots apart on the Player Rater? This $/G is showing you precisely how useful this player is for your fantasy team. Note: I did not say this value means the player is good. There are plenty of players who are useful for your fantasy team who are not good. In the above example, we see Carlos Rodon is extremely useful for your team with his positive value, and Patrick Corbin is not useful at all for your fantasy team.
wK/9: Weighted K/9, calculated to show how many more or less strikeouts the pitcher is throwing compared to the field. 9 K/9 sounds great, right? Except it’s actually below average for your top pitchers right now. Rodon above has a 21.26% higher K/9 rate than the top 50% of MLB pitchers right now. Meanwhile, Patrick Corbin has a K/9 rate 25% lower than the top 50% of MLB pitchers right now. I calculate this on a total season basis; there is little recency bias here.
wPABIB: PABIB sounds like Mr. Pibb, right? So, BABIP is Batting Average on Balls in Play, and we all know it from the movie Moneyball, right up there with Brad Pitt. Problem is, at least in my world, is that BABIP tells us the batting average on balls that are hit into the field. I’m a bit more interested in how many outs are generated by balls hit in play. This is simply the inverse of BABIP. I do this because the quality of hits are a significant generator of BABIP; it’s not simply “hit it where they ain’t,” but “can’t catch what speeds by you at 110MPH.” I then weight PABIB, taking the top 50% of the field into account, and express the output as a percent. In the above example, Carlos Rodon is 1.55% better at generating outs than other pitchers, and Patrick Corbin is 6.55% worse than the field. I calculate this over the last 30 days so there is a fair amount of recency bias, but it’s also responsive to things like warmer weather and if MLB changed the balls again.
wL30FIP: This is the weighted Fielding Independent Pitching stat over the last 30 days. FIP isn’t really predictive over this sample, but it gives us a reasonable approximation if a player should be doing better than their usual fantasy stats indicate. For the weighting in this sample size, I only use the top 60 pitchers (a standard 12-team fantasy league deployment of 5 starters per team). In the example, Carlos Rodon’s FIP over the last month has been 62% better than the field. Patrick Corbin’s FIP is 14% better than the field — he should be doing better than we’re seeing. In fact, he’s 14% better than the top 60 pitchers — that’s gotta be worth something down the line, right? Maybe let’s talk about that in the meat of the article, shall we?
News and Notes
Patrick Corbin: My system really likes Patrick Corbin and keeps throwing him into Tier 2, despite the fact that Corbin is basically at the bottom of the Player Rater (indeed, he’s ranked at nearly 1100). What gives? He’s 0-5 with a 6+ ERA. That’s fantasy trash. Thing is, we can’t play fantasy based on what’s already happened. His season-to-date true skill stats are plenty fair: his FIP is 3.38, SIERA is 4.42, and he’s allowed 1 homer on the year over 30 innings. Over the last 20IP, he’s got a 2.37 ERA and, 2.56 FIP — nothing wrong with that. He’s allowing barrels but most of them are going at the ground. For most fantasy managers, you still don’t want to use this particular Corbin (try the Burnes flavor), but there’s going to be a big DFS winner soon who has a $5000 Patrick Corbin that gets the regression coming his way.
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Patrick Corbin | -45.6 | -24.08% | -6.55% | 14.57% |
Jesus Luzardo: [post-submission edit: he’s off to the IL!] How about we do that same “last 20 IP” comparison with Luzardo as we did with Corbin? Over Luzardo’s last 20IP, he’s got a 3.66 ERA, 5.12 FIP, 6 BB/9 and has allowed 4 homers. This is the thing about public perception: people kept asking me why Corbin was so high on my list, but nobody asked me why Luzardo was also high — in fact, chasing that tier 1. Asking isn’t a bad thing; as humans, we’re somewhat predisposed to question certain beliefs and let other beliefs go unquestioned (Hey Siri, define “confirmation bias.”). To start the season, all of us analysts were in awe of Luzardo’s re-invention in Miami, and now I’m starting to wonder if it was a Miami Miracle or just a David Blaine stunt. My system loves Luzardo’s K/9 rate — and we all should love a great K/9 rate. Strikeouts are the biggest predictor of future success for pitchers. Full stop. But pitchers can’t walk 6 batters per nine and allow nearly 2 HR/9 and expect to survive. You know who did that in 2020? Robbie Ray. Hmm…maybe there is room for resurrection. There’s room for a Luzardo re-awakening, but don’t be surprised if he turns into a pumpkin quickly.
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Jesus Luzardo | -15.7 | 13.21% | 6.45% | -24.91% |
Reid Detmers: No, hitter! Detmers came this close to a perfect game. Still, it was, as the record books go, pretty ugly from a boxscore standpoint. 9IP, 2K, 25 batted ball events. In baseball, you’re either safe or out. One of two choices, right? Imagine flipping a coin 25 times and each time it comes up heads. Out! Now do that 25 times in a row, except every time you flip the coin, your friend has to catch it and still land heads. No-hitters tend to be filled with strikeouts because it’s so difficult for zero batted balls to end up as a hit. FanGraphs reports that Detmers’ no-no featured the fewest strikeouts in a no-hitter since 2011. On the season, Detmers’ K rate is waaaaaaaay (manage that, spell check!) down compared to the field, and his FIP — even after the no-no — stands at 4.07. Elephant-minded readers recall that Alec Mills and his 86 MPH fastball threw a no-hitter in 2020, and Detmers’ no-no has that kind of feel to it. Even Mills managed to K 5 batters, though. Detmers is an OK try for 12-team leagues, but his fantasy value is mostly tied to his prospect status. He’s a top 50 prospect and only 22 years old, so the best is yet to come — it just likely won’t come in 2022.
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Reid Detmers | 1.7 | -48.15% | 13.12% | 15.55% |
Paul Blackburn: The top of my Confidence ranking is filled with the top strikeout artists in the league. After Pablo Lopez, we see the “median” pitchers for K-rate. And then comes Paul Blackburn, who has a precipitous lack of strikeouts but is somehow toward the top of the rankings. Why? His impressive ability to limit batted ball damage and walks. All of his true skill stats are below 3.0 runs allowed, he’s got 4 wins and 37 IP, and a WHIP below 1.00 thanks to that. A lot of fantasy-relevant pitchers have done this kind of performance for a year and had great success — Marco Gonzales, Hyun-Jin Ryu, and Zack Greinke have all had top 20 fantasy years with this kind of profile (and all have finished in the top 10 SP, with Grienke doing it multiple times). Blackburn’s 7.0 K/9 won’t matter much if he approaches 200 IP, because his total strikeouts will be equivalent to a 9+ K/9 pitcher who throws less IP. Keep starting.
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Paul Blackburn | 15.6 | -38.18% | 4.12% | 34.11% |
Luis Castillo: Small sample size (9IP) but he’s looking rough so far. Don’t start until he figures things out. Last year, it took him until the All-Star break to feel comfortable, and thereafter he was brilliant for fantasy. I’m not saying drop, but definitely don’t trot him out there every 5 days right now.
Glenn Otto: Otto had a nice showing last year but is approaching 20IP with a 6+ FIP this year. He’s walking nearly as many batters as he’s K-ing, so let him sit even in deep leagues.
Mike Clevinger: Gonna be in the “you do you” category for a while. He’s failed to top 5 IP in each of his starts (expected), has a BB/9 above 5 (unexpected), and a 5/4 ERA/FIP (what is this, Dave Brubeck?). You figure out if you want to start him or sit him — I didn’t draft him anywhere in the first place.
Michael Lorenzen: He’s been pretty blah so far after a hot season opener. I’m not a big strength of schedule guy, but Lorenzen’s good starts recently came against the injury-decimated White Sox and the Athletics (who are just decimated regardless of injuries). He’s a fine DFS play for those “on” days but don’t come yelling at me if you start him in a daily league and he has an “off” day.
Hunter Greene: Making me work overtime, eh? This blurb’s coming in well after I submitted the rest, so I suppose I shoulda made more no-hitter jokes. Wait — the joke is that Greene threw a no-hitter and lost! His strike ratio was way off and he allowed 5 walks. Dude was up near 120 pitches, which we all know is certain arm death in the current world of pitchers. Whateva. Totally Reds thing to do to lose to the [checks notes] Pirates while no-hitting them. Meanwhile, JKJ’s gonna update you on David Bednar’s value as an RP after he notches a [checks notes] save for his no-hit team. What is this — the darkest Moneyball timeline where every player is Youk? Before you get really scared, the box below was generated based on data up through Saturday and does not include Greene’s Sunday gem. So, when DFS players say that they need contrarian pitchers to win the big cash out — this is what they mean:
Name | L30$/G | wK/9 | wPABIB | wL30FIP |
---|---|---|---|---|
Hunter Greene | -75.5 | 8.19% | -1.78% | -113.54% |
The Rankings
A horizontal, visual interpretation of the top pitchers, featuring: Shane! Thanks, Google Sheets, real helpful there. It’s McClanahan, bee-tee-dubya.
Always do a sanity check. I’m providing free data that quite literally has a better or higher correlation to fantasy efficacy than many sites that charge an arm and a leg and don’t answer your questions. That said, I’m human and make mistakes; I also submit the article on Sunday so there’s a bit of lag. The source of this data is none other than Razzball itself. So, if you are winning money or having a great time reading the articles, please consider a subscription to the site or drop me a line in the comments and let me know I’m not wasting my life away for naught.
Here’s how to use the list:
- Tier: 1=best, 2=everybody else for 12 team consideration, 3=deep league/dynasty/best ball/tournaments/DFS.
- Name: Player name
- Confidence: The overall score my system outputs. The higher the score, the more confident I am in using the player in the near term. As always, we’re in small sample size territory, so this ranking will get better as the season goes on.
- Own%: This is the rostership % of the player in Razzball Commenter Leagues, run on Fantrax. This % may vary depending on site and format for readers.
- L30$/G: This is how valuable the player has been over the past month. Players with high confidence who have low or negative $/G are “buy low” candidates. Spot starters/Roleless Robs will have a lower $/G because they play in more games.
Tier | Name | Confidence | Own% | L30$/G |
---|---|---|---|---|
1 | Carlos Rodon | 4.268 | 100 | 46.3 |
1 | Shohei Ohtani | 4.065 | 100 | 24.3 |
1 | Dylan Cease | 4.045 | 100 | 0.8 |
1 | Shane McClanahan | 3.985 | 100 | 28.7 |
1 | Michael King | 3.961 | 5.3 | |
1 | Max Scherzer | 3.776 | 100 | 27.4 |
1 | Nestor Cortes | 3.728 | 100 | 16.5 |
1 | Corbin Burnes | 3.718 | 100 | 35.2 |
1 | Garrett Whitlock | 3.622 | 100 | -13.6 |
1 | Eric Lauer | 3.517 | 100 | 34.4 |
1 | Kevin Gausman | 3.505 | 100 | 32.5 |
1 | Freddy Peralta | 3.498 | 100 | -4.6 |
1 | Gerrit Cole | 3.417 | 100 | 22.4 |
1 | Jesus Luzardo | 3.414 | 100 | -15.1 |
1 | Lucas Giolito | 3.199 | 100 | 8.7 |
1 | Brandon Woodruff | 3.153 | 100 | 1.7 |
1 | Pablo Lopez | 3.065 | 100 | 45.3 |
1 | Joe Musgrove | 3.053 | 100 | 40.2 |
1 | Clayton Kershaw | 3.022 | 100 | 24.6 |
1 | Kyle Wright | 2.981 | 100 | -6.8 |
1 | Max Fried | 2.959 | 100 | 40.6 |
1 | Sean Manaea | 2.955 | 100 | -28.7 |
1 | Zac Gallen | 2.948 | 100 | 33.5 |
1 | Tarik Skubal | 2.941 | 100 | 22 |
1 | Aaron Nola | 2.928 | 100 | -4.2 |
1 | Chris Paddack | 2.892 | 7 | -14.3 |
1 | Tylor Megill | 2.867 | 100 | -33.8 |
1 | Triston McKenzie | 2.848 | 100 | 9.6 |
2 | Carlos Carrasco | 2.794 | 100 | 7.6 |
2 | A.J. Minter | 2.773 | 2 | -1.8 |
2 | Paul Blackburn | 2.771 | 100 | 15.6 |
2 | Merrill Kelly | 2.755 | 100 | 14.7 |
2 | Tyler Mahle | 2.747 | 98 | -49 |
2 | Zack Wheeler | 2.747 | 100 | -30.6 |
2 | Cristian Javier | 2.745 | 100 | -11.4 |
2 | Kenley Jansen | 2.743 | 100 | 10.5 |
2 | Patrick Corbin | 2.740 | 11 | -46.5 |
2 | Logan Gilbert | 2.739 | 100 | 18 |
2 | Chris Bassitt | 2.733 | 100 | 10.6 |
2 | Dane Dunning | 2.731 | 27 | -18.8 |
2 | Frankie Montas | 2.711 | 100 | -5.9 |
2 | Michael Kopech | 2.705 | 100 | 6.9 |
2 | MacKenzie Gore | 2.702 | 100 | 1 |
2 | Justin Verlander | 2.674 | 100 | 60.4 |
2 | Martin Perez | 2.667 | 32 | 13.1 |
2 | Patrick Sandoval | 2.651 | 100 | -6 |
2 | Ryan Helsley | 2.644 | 100 | 8.9 |
2 | Alek Manoah | 2.630 | 100 | 26.1 |
2 | Luis Garcia | 2.628 | 100 | 19.9 |
2 | Luis Garcia | 2.628 | 100 | 19.9 |
2 | Drew Rasmussen | 2.624 | 100 | 12.8 |
2 | Victor Arano | 2.603 | -6 | |
2 | Spencer Strider | 2.594 | 50 | -4 |
2 | Justin Wilson | 2.586 | -5.9 | |
2 | Sam Hentges | 2.562 | -0.7 | |
2 | Walker Buehler | 2.553 | 100 | -4.2 |
2 | Joe Ryan | 2.549 | 100 | 22.5 |
2 | Wil Crowe | 2.524 | 14 | -4.4 |
2 | Miles Mikolas | 2.522 | 100 | 32.9 |
2 | Keegan Akin | 2.514 | -13.2 | |
2 | Logan Webb | 2.514 | 100 | -25.2 |
2 | Steven Matz | 2.502 | 32 | -18 |
2 | Shane Bieber | 2.502 | 100 | -31.9 |
2 | Yu Darvish | 2.498 | 100 | 9.8 |
2 | Jason Adam | 2.496 | -1.4 | |
2 | Zach Eflin | 2.496 | 9 | -47.1 |
2 | Tyler Anderson | 2.495 | 20 | -9.5 |
2 | Tanner Houck | 2.492 | 45 | -22.2 |
2 | Yency Almonte | 2.491 | 12.9 | |
2 | Brock Burke | 2.485 | 18 | 4.2 |
2 | Seranthony Dominguez | 2.485 | 2 | -2.6 |
2 | Bruce Zimmermann | 2.477 | -0.8 | |
2 | Jovani Moran | 2.472 | 4.9 | |
2 | Chad Kuhl | 2.472 | 39 | 13.2 |
2 | Scott Effross | 2.472 | -4.1 | |
2 | Chasen Shreve | 2.457 | 5 | 0.4 |
2 | Robbie Ray | 2.455 | 100 | -3.4 |
2 | Luis Severino | 2.452 | 100 | -12.6 |
2 | Evan Phillips | 2.447 | -1.7 | |
2 | Jameson Taillon | 2.444 | 98 | -6.5 |
2 | Jimmy Herget | 2.433 | 2 | -3 |
2 | Framber Valdez | 2.420 | 100 | -28.2 |
2 | Bryse Wilson | 2.419 | -46.1 | |
2 | David Bednar | 2.418 | 100 | 3.8 |
2 | Ross Stripling | 2.417 | -30.7 | |
2 | Alex Cobb | 2.413 | 98 | -24.8 |
2 | Austin Gomber | 2.409 | 11 | -16.8 |
2 | Jordan Montgomery | 2.409 | 100 | -13.8 |
2 | Corey Kluber | 2.407 | 57 | -35.6 |
2 | Eduardo Rodriguez | 2.407 | 100 | -7 |
2 | Mauricio Llovera | 2.403 | -3.6 | |
2 | Will Vest | 2.398 | 9 | 1.4 |
2 | Trevor Stephan | 2.390 | 5 | 0.7 |
2 | Nick Pivetta | 2.390 | 7 | -35 |
2 | Alex Vesia | 2.387 | -5.1 | |
2 | Brooks Raley | 2.383 | 73 | -3.8 |
2 | Adam Wainwright | 2.383 | 100 | -22.3 |
2 | JT Brubaker | 2.382 | 5 | -34.2 |
2 | Erik Swanson | 2.374 | 2 | -2.1 |
2 | Trevor Gott | 2.371 | -3.5 | |
2 | Andrew Chafin | 2.368 | -5.7 | |
2 | Parker Mushinski | 2.363 | -7.8 | |
2 | Adrian Houser | 2.355 | 16 | -9.1 |
2 | Kyle Freeland | 2.348 | -43.8 | |
2 | German Marquez | 2.341 | 64 | -71.4 |
2 | Jeffrey Springs | 2.340 | -2.7 | |
2 | Kyle Gibson | 2.340 | 82 | -37.4 |
2 | Trevor Rogers | 2.339 | 100 | -27 |
2 | Josh Hader | 2.337 | 100 | 7.9 |
2 | Zack Greinke | 2.318 | 36 | -37.5 |
2 | Tommy Nance | 2.314 | 4.9 | |
2 | Penn Murfee | 2.314 | 1 | |
2 | Kyle Nelson | 2.314 | -1.5 | |
2 | Andrew Heaney | 2.309 | 86 | 90.7 |
2 | Mitch Keller | 2.306 | 7 | -57.9 |
2 | JT Chargois | 2.304 | ||
2 | Rich Hill | 2.302 | 5 | -6.4 |
2 | Matt Strahm | 2.299 | -2.6 | |
2 | John Brebbia | 2.297 | -4.9 | |
2 | Collin McHugh | 2.296 | 2 | -10.6 |
2 | Nathan Eovaldi | 2.295 | 100 | -11.1 |
2 | Alex Wood | 2.292 | 100 | -6 |
2 | Humberto Castellanos | 2.291 | -14.2 | |
2 | Dylan Bundy | 2.288 | 25 | -44.6 |
2 | Taylor Hearn | 2.283 | -31.5 | |
2 | Daulton Jefferies | 2.282 | 5 | -51.5 |
2 | Alex Lange | 2.272 | -1.6 | |
2 | Jake Walsh | 2.265 | 2.8 | |
2 | Sam Selman | 2.265 | 12.6 | |
2 | Noah Syndergaard | 2.265 | 100 | 1.9 |
2 | Bryan Baker | 2.264 | 2 | -5.3 |
2 | Adam Ottavino | 2.257 | -4.8 | |
2 | Zach Davies | 2.256 | -12.3 | |
2 | Julian Merryweather | 2.252 | -10.6 | |
2 | Marcus Stroman | 2.241 | 84 | -36.5 |
2 | Reid Detmers | 2.240 | 23 | 1.7 |
2 | Charlie Morton | 2.238 | 100 | -46.3 |
2 | Josh Winder | 2.235 | 52 | 10.3 |
2 | Tanner Rainey | 2.233 | 98 | -5.9 |
2 | Drew Smith | 2.226 | -3.2 | |
2 | Edwin Diaz | 2.219 | 100 | 5.4 |
2 | Hector Neris | 2.215 | 18 | -1.8 |
2 | Clay Holmes | 2.214 | 93 | 4.5 |
2 | Tony Gonsolin | 2.201 | 100 | 23.9 |
2 | Taylor Rogers | 2.200 | 100 | 5.5 |
2 | Jose Quintana | 2.194 | 14 | -12.1 |
2 | Zach Jackson | 2.184 | -6.1 | |
2 | Cole Sands | 2.181 | -8 | |
2 | Konnor Pilkington | 2.178 | -0.8 | |
2 | Daniel Norris | 2.176 | -4.9 | |
2 | Sandy Alcantara | 2.175 | 100 | -1.7 |
2 | Cody Stashak | 2.172 | 1.9 | |
2 | Rafael Montero | 2.167 | 73 | -0.7 |
2 | Justin Steele | 2.166 | -68.8 | |
2 | Enyel De Los Santos | 2.163 | -6.9 | |
2 | Eli Morgan | 2.163 | -24.6 | |
2 | Bryan Abreu | 2.161 | -2.3 | |
2 | Camilo Doval | 2.161 | 100 | 1 |
2 | Pierce Johnson | 2.160 | 2 | -12.2 |
2 | A.J. Puk | 2.158 | 9 | 2.7 |
2 | Sean Doolittle | 2.152 | -3.3 | |
2 | Anthony Bass | 2.152 | 9 | -0.2 |
2 | James Norwood | 2.150 | -7.5 | |
2 | Kendall Graveman | 2.145 | 25 | -5.2 |
2 | Devin Williams | 2.145 | 55 | -2.2 |
2 | Brad Boxberger | 2.141 | -4.3 | |
2 | Joely Rodriguez | 2.132 | -3.4 | |
2 | Jordan Hicks | 2.128 | 20 | -32.1 |
2 | Daniel Bard | 2.126 | 100 | 1 |
2 | Daniel Hudson | 2.118 | 5 | -6.6 |
2 | David Robertson | 2.113 | 100 | 4.1 |
2 | Caleb Thielbar | 2.108 | 2 | -6.5 |
2 | Julio Urias | 2.106 | 100 | 20.7 |
2 | Joan Adon | 2.103 | -59.5 | |
2 | Lucas Luetge | 2.096 | -9.8 | |
2 | Raisel Iglesias | 2.092 | 100 | -1.8 |
2 | Jake Odorizzi | 2.091 | 18 | -1.8 |
2 | Joel Kuhnel | 2.091 | -6.5 | |
2 | Seth Martinez | 2.090 | 1.8 | |
2 | Tyler Wells | 2.085 | 14 | -7.8 |
2 | Jhoan Duran | 2.083 | 100 | -1.3 |
2 | Corey Knebel | 2.081 | 100 | -2.4 |
2 | Erick Fedde | 2.080 | -29.9 | |
2 | Josh Staumont | 2.079 | 30 | -4.1 |
2 | Antonio Senzatela | 2.077 | -55.5 | |
2 | Phillips Valdez | 2.077 | -10.1 | |
2 | Brad Keller | 2.076 | 34 | -15.6 |
2 | Daniel Lynch | 2.074 | 9 | 8 |
2 | Aaron Loup | 2.071 | -3.8 | |
2 | Aaron Civale | 2.067 | 27 | -78.7 |
2 | Brett Martin | 2.059 | -7 | |
2 | Chris Stratton | 2.053 | 5 | -9.3 |
2 | Rowan Wick | 2.049 | 57 | 1 |
2 | Josiah Gray | 2.049 | 82 | -8.1 |
2 | Corbin Martin | 2.042 | -15.3 | |
2 | J.P. Feyereisen | 2.038 | 2 | 9.9 |
2 | Aaron Ashby | 2.033 | 48 | -46.7 |
2 | Cal Quantrill | 2.030 | 34 | -42.2 |
2 | Jordan Lyles | 2.029 | -24.1 | |
2 | Matt Foster | 2.028 | -6.6 | |
2 | Liam Hendriks | 2.027 | 100 | 0.9 |
2 | Dany Jimenez | 2.026 | 100 | 4.2 |
2 | Luis Cessa | 2.025 | -5.3 | |
2 | Felix Bautista | 2.025 | -2.7 | |
2 | Dillon Tate | 2.022 | 7 | -3.2 |
2 | Kyle Hendricks | 2.015 | 80 | -8.3 |
2 | Paul Sewald | 2.013 | 64 | 2.8 |
2 | Jared Solomon | 2.010 | -2.5 | |
2 | Jesse Chavez | 2.008 | -5.8 | |
2 | Steven Okert | 2.007 | -4.2 | |
2 | Michael Wacha | 2.006 | 59 | 33.9 |
3 | Keegan Thompson | 1.997 | 5 | 4.2 |
3 | Jose Urquidy | 1.996 | -39.3 | |
3 | Giovanny Gallegos | 1.990 | 100 | -4.2 |
3 | Carlos Hernandez | 1.989 | 5 | -102.9 |
3 | Tim Mayza | 1.987 | -2.4 | |
3 | Rony Garcia | 1.973 | -2.3 | |
3 | Luis Gil | 1.971 | -73.8 | |
3 | Elieser Hernandez | 1.970 | 14 | -35.6 |
3 | Jose Álvarez | 1.970 | -5.6 | |
3 | Jeff Hoffman | 1.953 | -3.4 | |
3 | Chris Martin | 1.947 | -8.5 | |
3 | Michael Lorenzen | 1.941 | 59 | -14.6 |
3 | Adonis Medina | 1.939 | 22 | |
3 | Sergio Romo | 1.937 | -1 | |
3 | Andrew Bellatti | 1.934 | -4.4 | |
3 | Emmanuel Clase | 1.932 | 100 | 2.8 |
3 | Tanner Scott | 1.931 | -6.4 | |
3 | Yusei Kikuchi | 1.929 | 23 | -21.8 |
3 | Chad Green | 1.929 | 14 | -5 |
3 | Jhon Romero | 1.912 | -1.3 | |
3 | Alexis Diaz | 1.910 | 2 | -1 |
3 | Jorge Lopez | 1.909 | 100 | 7.5 |
3 | Kyle Barraclough | 1.908 | -2.6 | |
3 | Dusten Knight | 1.907 | ||
3 | Chris Flexen | 1.904 | 14 | -24.6 |
3 | Jalen Beeks | 1.903 | 5 | 1.6 |
3 | Tyler Rogers | 1.902 | -5.2 | |
3 | Andres Munoz | 1.900 | 48 | -6 |
3 | Dillon Peters | 1.897 | 2 | 4 |
3 | Dallas Keuchel | 1.884 | -71.6 | |
3 | Anderson Severino | 1.881 | -10.9 | |
3 | Nick Martinez | 1.881 | 5 | -29.7 |
3 | Roansy Contreras | 1.879 | 7 | 28.7 |
3 | Hoby Milner | 1.877 | -6.3 | |
3 | Zach Thompson | 1.874 | -36.7 | |
3 | Austin Voth | 1.873 | -3 | |
3 | Jose Alvarado | 1.870 | -11.4 | |
3 | Ross Detwiler | 1.865 | -1.3 | |
3 | Jordan Romano | 1.864 | 100 | -0.2 |
3 | Tyler Kinley | 1.854 | -4.5 | |
3 | Joe Jimenez | 1.852 | -6 | |
3 | Jhoulys Chacin | 1.850 | -12.3 | |
3 | Jose Berrios | 1.845 | 100 | -29.9 |
3 | Seth Lugo | 1.844 | 2 | -6.2 |
3 | George Kirby | 1.836 | 100 | 6.8 |
3 | Jackson Stephens | 1.831 | -2.7 | |
3 | Darren O’Day | 1.830 | -5.1 | |
3 | Hunter Harvey | 1.827 | -4.7 | |
3 | Vince Velasquez | 1.826 | -39.4 | |
3 | Zach Plesac | 1.819 | 36 | -53.1 |
3 | Craig Kimbrel | 1.818 | 100 | 0.7 |
3 | Joe Mantiply | 1.815 | 2 | -2.5 |
3 | Ty Blach | 1.812 | -8.9 | |
3 | Nabil Crismatt | 1.811 | -1 | |
3 | Drew Smyly | 1.807 | 5 | -45 |
3 | Jose Ruiz | 1.807 | -7.1 | |
3 | Griffin Jax | 1.802 | 7 | 3.8 |
3 | Michael Rucker | 1.801 | -11.4 | |
3 | Cody Poteet | 1.799 | 0 | |
3 | Joel Payamps | 1.792 | -2.3 | |
3 | Robert Gsellman | 1.791 | -16.4 | |
3 | Anthony Kay | 1.786 | ||
3 | Kyle Bradish | 1.785 | 9 | -11 |
3 | Scott Barlow | 1.777 | 100 | 1.3 |
3 | Jakob Junis | 1.776 | 16 | 7.5 |
3 | John Schreiber | 1.775 | 7 | 1.3 |
3 | Duane Underwood Jr. | 1.775 | -17.8 | |
3 | Sam Moll | 1.772 | -4.9 | |
3 | Blake Treinen | 1.769 | 18 | 24.5 |
3 | Vladimir Gutierrez | 1.764 | -96.1 | |
3 | Jon Gray | 1.760 | 36 | -39.2 |
3 | Ian Anderson | 1.756 | 100 | -1.5 |
3 | Carl Edwards Jr. | 1.755 | -11.3 | |
3 | Mitch White | 1.753 | -11.4 | |
3 | Trevor Williams | 1.748 | -16.1 | |
3 | Jackson Kowar | 1.742 | ||
3 | Jake Cousins | 1.740 | -6.5 | |
3 | Cole Irvin | 1.740 | 14 | 6.4 |
3 | Tyler Thornburg | 1.739 | -13.8 | |
3 | Steve Cishek | 1.736 | -10.3 | |
3 | Amir Garrett | 1.735 | -3.9 | |
3 | Steven Wilson | 1.731 | -3.6 | |
3 | Zach Pop | 1.728 | -26.5 | |
3 | Spenser Watkins | 1.728 | -58.2 | |
3 | Justin Grimm | 1.727 | -9.7 | |
3 | Reynaldo Lopez | 1.722 | 2 | 0.4 |
3 | Kodi Whitley | 1.720 | -6.1 | |
3 | Nick Lodolo | 1.715 | 52 | 6.8 |
I know we haven’t seen Snell yet, but where do you anticipate him falling on your tiers? Do you prefer him, Blackburn or P Sandoval? Thanks for this list and breakdown. It’s great to read and study.
Snell was sneaky high (the name of my upcoming anime series, btw) on my pre-season charts because he had a really nice finish to last year — 12.5 K/9, sub 3.00 ERA over his last 9ish starts. It’s always tough to recommend a guy coming back from injury, but that kind of K prowess is rare and a team chasing the championship is much more likely to win by trying for a Snell resurgence than continuing to hope Paul Blackburn doesn’t turn into a pumpkin. Give Snell a shot. Good luck!
Thank you! I share similar sentiments as you do on Snell. Keep up the great work!
Blair,
What’s the outlook on Syndergaard ROS? Thanks brother!
Generally positive but he’ll likely be inning capped due to the TJ return, which puts him in the top 60 SP in terms of “he’s done it before and can do it again,” but there’s really no reason to expect he gets much more than 150 IP, and he’s not efficient enough with his Ks to really be a fantasy asset right now. That said, he’ll likely get better in the next month or so as he’s back up to speed.
Hi Blair,
I so appreciate all your help, honesty and information.
1. Would you start the Padres Mike Clevinger at Philadelphia?
2. Would you start AZ’s Merrill Kelly at LAD?
3. Following your advice, I was going to start Cards Mikolas at the Mets and Tyler Anderson of LA at home against AZ. Do you still agree?
Thanks so much!!
Clev is up to you — he hasn’t topped 5 IP (so, no Wins) and has walked a ton of batters (so, high WHIP), so I don’t see a major reason to start him.
Yep, start Kelly, Mikolas, and Anderson. Good luck!
Thanks so very much!!!
I know that you have Freddy Peralta ranked much higher than Alek Manoah so maybe a silly question but in a dynasty format, which would you prefer.
Thanks
I prefer Peralta long-term, but they’re both roughly equivalent at this point — the best “predictor” right now is intuition based on their career sample sizes. :)
Hi Blair,
Sorry to bother you but my question (Martin Rostoker) was missed.
Thank you as always for your assistance!
Martin
1) My weekly question. How much are you factoring innings in your rating?
2) I’m embarased to mention this, but I use your list to identify cheap, effective pitchers. But occasionally, I see guys that I don’t know.
Would it be possible to provide a 3 character (say) team reference so I can
more easily pair them when I see a team using an opener.
Always happy for the weekly question!
Right now the cutline is 21 2/3 IP, which is automatically generated based on MLB pitcher workloads as a pretty low-entry point for players. Players who are above the cutline get a nice boost in their score because A) starting pitchers, B) more evidence for performance, and C) weak K-based players can be valuable with surplus IP.
Yeah, I might add in the team column next week. I had thought about adding it earlier this year but thought people might skip it. Thanks for the advice!
I’m still confused. John Shreiber (RedSox) is rated (Tier 3) with 7 (very effective) innings. Not consistent with above response.
To be fair, the big board has every pitcher who has appeared in MLB this year. I just include like, the top 300 because that’s more than enough for fantasy players ? But stats don’t become predictive until 400 IP of data — most pitchers will never reach that threshold. K/9 can lock in towards short-term prediction pretty quick, but that usually takes 3+ starts to have any sort of coherence. That’s why I have a (pretty low) barrier of entry on my IP cutline — if we’re really trying to be predictive, we can only do that with pitchers like Max Scherzer, who have years of experience. Some guy with the Diamondbacks (Davidson?) threw a no-hitter in his MLB debut last year and basically hasn’t seen the mound again and has generated a 10+ ERA and 8+ FIP since ? So, one or a couple good performances hold no indication of future performance is the takeaway.
Thanks for giving me so much attention. I really appreciate your effort and how you support my need to find effective pitchers w/o clear roles (e.g., King after 2 weeks).
I’m now trying to figure out who gets on your list. I’m not really interested in Shreiber (who has been good in his limited MLB activation time), but I want to understand why he is on your list despite only 7 innings! I’m wondering if you’re extrapolating performance to the full (to date) team games.
And BTW, I would never suggest expanding your player pool. It is already overwhelming.
Thanks for spending so much time with me each week. I realize that performance predictions are ridiculously difficult until you have lots of data — but obviously meaningless if you wait until late August for confident results.
What I’m trying to understand is why some pitchers with very few innings (e.g., Shreiber) are on this list. He’s been up only briefly (perhaps less than 25% of team’s games), so I’m wondering if you may somehow be extrapolating his innings).
Becausej of you, I was able to find King, Strider, Burkes, and Keegan Thompson (I exchange one when he pitches). Now that Strider and Keegan have graduated to SP, looking for another.
I realize my above comment had all my laughing faces appear as ? so thanks commenting system for not allowing emojis.
But yeah, the game of “is this guy gonna be useful” is bound to allow low IP guys in — for example, what do we make of Clevinger, who should be good, but is waaay behind in IP. Truth is, nobody can actually predict him. Same with Shreiber or Rando McCupofCoffee. Harkening back to one of my pre-season posts, out of the 397 pitchers who made a start in 2021, only 20 made it a full season. and a total of 41 made it through 90% of their starts. So, we need a lot of Streamers, right? Every bit of data we get on any pitcher — whether it be 7 innings or 400 innings — adds up to giving us more and more reasons to either start or sit. So that’s why I’ve tried to set up my system to incorporate as much new blood as it does old blood (ew). It compliments but also stands apart from Rudy’s Streamonator, if that makes sense.
Dammit Blair! You’re gonna talk me into getting Corbin back onto my NL-only roster. I had him as a cheap keeper and endured waaay too much of his suckage the last couple years due to move restrictions and hope. I’m finally blissfully out in 2022 only to have 3 Ps go on the IL in the same week, and now I’m HOPING I bid enough to land Corbin and Quintana. WHO’S LAUGHING NOW, JOKER!?
Why so serious?
Hi Blair
Your pitching insight is always appreciated. I am very grateful for you providing the details on your reason.
1. I was going to start Mikolas and Freddy Peralta. Do you agree?
2.Would your start Tyler Anderson of the Dodgers at home against AZ and on the road at Washington?
3. Is it worth picking up Martin Perez ? If you agree, who would you drop from the following:
Cristian Javier
Paul Blackburn
Tyler Anderson
Mike Clevinger
Dane Dunning
Kyle Bradish
4.Would you pick up Chase Silseth? If yes, who would you waive from the following list.
THANKS so much!
Martin
Huh, I definitely wrote out an answer yesterday but it looks like the system didn’t take it. Anyway!
Yes, go with Mikolas and Peralta — Peralta is set it and forget it. Mikolas will blow up eventually but ride him while he’s useful.
Yes, start Anderson twice.
Perez always has one good month and then crashes — his skill set just isn’t formed around consistent success. I would avoid.
Silseth got another start added to his cup of coffee but he’s got zero minor league track record (30 IP), 1 MLB start, and is an 11th round draft pick at 21 years old — the list of modern-era starters who have thrived out of those conditions is basically: nobody. I would avoid in most fantasy formats unless you’re desperate.
Good luck!
Thanks so very much. I do appreciate these details and your help!!!
No Sonny Gray anywhere to be found? He can’t be that bad, can he?
Gray is currently 50 spots beyond where I cut/paste my leaderboard of a billion pitchers — mostly because he’s about 1 quality start away from getting past the IP cutline and getting a points boost. That said, a 5FIP ain’t great. Tread cautiously.
Thoughts on Ranger “Danger” Suarez? compared to the likes of Detmers, B. Keller, Ian “Tull” Anderson?
Ranger Danger got the “sit” vote from me last week but it looks like he’s righting the ship. He may not be as crazy good as last year, but it’s better than nothing.
Anderson is gonna need that Aqualung because he’s still drowning. He’s only 24, plenty of life left, but 6 K/9 and nearly 5 FIP ain’t gonna win any fantasy leagues.
You dropping Alex Wood for Martin Perez in a QS league?
Or Corbin
I personally love Wood (hehe!) when he’s healthy so let him keep going as long as he’s not on the IL
Tier 2 needs yet another Luis Garcia!
Yeah I wish I had a non-crazy way of fixing it. Rudy’s Luis Garcias are clear, but I know a fair amount of fantasy sites struggle with the starter/closer Garcias.
Kinda like when we used to be able to draft Ryan Braun, the relief pitcher.