Who Should Finish Second for AL Cy Young?
Even though he’s still got one start to go and several other pitchers will also see playing time over the next few days, the American League Cy Young race is all but over. Last year, it was a two-horse race between Gerrit Cole and Justin Verlander. This year, Shane Bieber has been so dominant that no other AL pitcher can come close to his accomplishments with less than a week remaining. He leads the league in strikeouts by 25 through Monday’s games, with the distance between first and second the same as the distance between second and 18th. His 41% strikeout rate is the best in baseball, and his 2.13 FIP and 1.74 ERA pace the league as well. There isn’t a credible argument against Bieber winning the award and he should even garner support for MVP. As for second place, there are a ton of candidates.
To try to wade through the potential two-through-five slots on voters’ ballots, let’s take a quick look at pitcher WAR through Tuesday night’s games:
| Name | IP | K/9 | BB/9 | HR/9 | BABIP | ERA | FIP | WAR |
|---|---|---|---|---|---|---|---|---|
| Shane Bieber | 72.1 | 13.9 | 2.2 | 0.9 | .268 | 1.74 | 2.13 | 2.9 |
| Dylan Bundy | 65.2 | 9.9 | 2.3 | 0.7 | .272 | 3.29 | 2.93 | 2.0 |
| Framber Valdez | 70.2 | 9.7 | 2.0 | 0.6 | .312 | 3.57 | 2.84 | 2.0 |
| Zack Greinke | 62.1 | 9.0 | 1.2 | 0.9 | .306 | 3.90 | 2.87 | 1.9 |
| Kenta Maeda | 60.2 | 10.5 | 1.5 | 1.2 | .206 | 2.52 | 3.04 | 1.9 |
| Lucas Giolito | 66.1 | 11.7 | 3.4 | 1.0 | .250 | 3.53 | 3.18 | 1.9 |
| Lance Lynn | 78.1 | 9.7 | 2.6 | 1.2 | .221 | 2.53 | 3.80 | 1.8 |
| Andrew Heaney | 62.2 | 9.6 | 2.4 | 0.9 | .297 | 4.02 | 3.19 | 1.7 |
| Marco Gonzales | 64.2 | 8.2 | 0.8 | 1.1 | .253 | 3.06 | 3.42 | 1.7 |
| Hyun Jin Ryu | 60.0 | 10.2 | 2.3 | 0.9 | .312 | 3.00 | 3.01 | 1.7 |
| Dallas Keuchel | 57.1 | 6.1 | 2.4 | 0.3 | .258 | 2.04 | 3.05 | 1.6 |
| Gerrit Cole | 73.0 | 11.6 | 2.1 | 1.7 | .242 | 2.84 | 3.87 | 1.5 |
There are 11 players with between 1.5 and two wins on the season. Any of them would make a fine choice for inclusion on a Cy Young ballot, but we should probably dig a bit deeper. We have to set a cutoff somewhere, so we’ll consider the players on the list above. Here’s where those candidates stand against each other in a few key categories:
| Name | IP | K% | BB% | ERA | ERA- | FIP | FIP- | WAR |
|---|---|---|---|---|---|---|---|---|
| Shane Bieber | 72.1 | 41% | 7% | 1.74 | 38 | 2.13 | 48 | 2.9 |
| Dylan Bundy | 65.2 | 27% | 6% | 3.29 | 76 | 2.94 | 66 | 2.0 |
| Framber Valdez | 70.2 | 26% | 6% | 3.57 | 84 | 2.84 | 65 | 2.0 |
| Zack Greinke | 62.1 | 25% | 3% | 3.90 | 91 | 2.88 | 65 | 1.9 |
| Kenta Maeda | 60.2 | 32% | 4% | 2.52 | 56 | 3.05 | 68 | 1.9 |
| Lucas Giolito | 66.1 | 33% | 10% | 3.53 | 81 | 3.19 | 70 | 1.9 |
| Lance Lynn | 78.1 | 27% | 7% | 2.53 | 52 | 3.81 | 82 | 1.8 |
| Andrew Heaney | 62.2 | 26% | 7% | 4.02 | 93 | 3.20 | 72 | 1.7 |
| Hyun Jin Ryu | 60 | 28% | 6% | 3.00 | 68 | 3.02 | 67 | 1.7 |
| Marco Gonzales | 64.2 | 23% | 2% | 3.06 | 72 | 3.43 | 79 | 1.7 |
| Dallas Keuchel | 57.1 | 17% | 6% | 2.04 | 47 | 3.06 | 68 | 1.6 |
| Gerrit Cole | 73 | 33% | 6% | 2.84 | 64 | 3.88 | 85 | 1.5 |
Bieber’s dominance is still clear. After Bieber, though, things get murky. Nearly every pitcher on the list above is among the leaders in one or more important statistical categories. Dylan Bundy shows up high in WAR thanks to solid innings totals to go along with his good FIP. Zack Greinke and Marco Gonzales have great walk numbers. Lance Lynn has pitched a ton of innings without allowing many runs. Lucas Giolito and Gerrit Cole have a ton of strikeouts. Dallas Kuechel, Kenta Maeda, and Hyun Jin Ryu are a bit behind in innings, but other aspects of their games stick out.
Here at FanGraphs, we use a FIP-based WAR, but it is not the only version out there. When I looked at this award last season, I discussed why voters might choose different versions of WAR based on their own preferences:
In many ways, the versions of WAR are all trying to do the same thing, which is to credit a pitcher for certain outcomes based on the pitcher’s work. This isn’t new. It’s why earned run average tries to strip away the unearned runs. ERA, Baseball-Reference’s WAR and RA/9 WAR both look at the number of runs and then work backwards to try to arrive at a deserved result. FIP-based WAR looks at the outcomes most controlled by the pitcher (walks and strikeouts) and then adds or subtracts credit for some batted balls via the home run and infield flies, and gives credit for all outs made. Baseball Prospectus looks at the most likely outcomes given the circumstances and assigns a value.
To provide additional context to this year’s race, the table below shows how various sites have calculated WAR for the pitchers above, along with a weighted average (with Baseball-Reference and RA/9 WAR averaged along with WAR here and Baseball Prospectus’s WARP):
| Name | WAR | RA9-WAR | B-Ref | BPro | wAVG |
|---|---|---|---|---|---|
| Shane Bieber | 2.9 | 3.8 | 3 | 2.5 | 2.9 |
| Lance Lynn | 1.8 | 3.1 | 2.9 | 1.6 | 2.1 |
| Kenta Maeda | 1.9 | 2.4 | 1.7 | 1.6 | 1.9 |
| Dylan Bundy | 2.0 | 1.5 | 1.7 | 1.6 | 1.7 |
| Gerrit Cole* | 1.5 | 2.1 | 1.6 | 1.8 | 1.7 |
| Hyun Jin Ryu | 1.7 | 1.7 | 2.3 | 1.4 | 1.7 |
| Framber Valdez* | 2.0 | 1.2 | 0.9 | 1.7 | 1.6 |
| Zack Greinke | 1.9 | 1.3 | 1.1 | 1.5 | 1.5 |
| Dallas Keuchel | 1.6 | 2.5 | 1.9 | 0.8 | 1.5 |
| Lucas Giolito | 1.9 | 1.3 | 0.7 | 1.6 | 1.5 |
| Marco Gonzales | 1.7 | 1.6 | 1.3 | 1.2 | 1.5 |
| Andrew Heaney | 1.7 | 1 | 1.4 | 1.1 | 1.3 |
When we take a higher-level view based on WAR, Lynn’s strength in run-prevention combined with good numbers here and at Baseball Prospectus put him into the second spot. Maeda’s solid numbers across the board put him in third, with Bundy, Ryu, and Cole in a virtual tie for fourth. We haven’t incorporated any Statcast numbers into the analysis thus far, so let’s take a look at the candidates via xwOBA, which includes strikeouts, walks and expected wOBA from batted balls:
| Player | wOBA | xwOBA | Difference |
|---|---|---|---|
| Shane Bieber | .220 | .258 | -.038 |
| Kenta Maeda | .217 | .263 | -.046 |
| Lucas Giolito | .250 | .277 | -.027 |
| Lance Lynn | .258 | .280 | -.022 |
| Dylan Bundy | .263 | .282 | -.019 |
| Hyun Jin Ryu | .281 | .287 | -.006 |
| Gerrit Cole | .275 | .290 | -.015 |
| Zack Greinke | .282 | .310 | -.028 |
| Marco Gonzales | .257 | .313 | -.056 |
| Framber Valdez | .275 | .320 | -.045 |
| Andrew Heaney | .281 | .322 | -.041 |
| Dallas Keuchel | .244 | .330 | -.086 |
Bieber leads, as expected, with Maeda a close behind. There’s a pretty close group from Giolito to Cole, with another tier from Greinke to Heaney, and Keuchel taking up the last spot. All players are above the league average of .333, though Keuchel is pretty close. Keuchel’s extreme groundball tendencies and a solid defense mean that his actual results are much better than expected. While every player has an xwOBA higher than their wOBA, the average difference for all pitchers is about 20 points, so Giolito, Lynn, Bundy, Cole and Greinke have all received pretty close to what might be expected based on xwOBA. Bieber, Maeda, Gonzales, and Framber Valdez have been somewhat fortunate, with Keuchel the extreme outlier. Ryu is the only pitcher who looks like he might have been on the receiving end of some bad luck.
We can actually take the xwOBA from above and create a rough version of WAR based on those numbers. Below you’ll find that version of WAR added to the previous table of WAR above:
| Name | WAR | RA9-WAR | B-Ref | BPro | xWAR | wAVG |
|---|---|---|---|---|---|---|
| Shane Bieber | 2.9 | 3.8 | 3.0 | 2.5 | 2.7 | 2.9 |
| Lance Lynn | 1.8 | 3.1 | 2.9 | 1.6 | 2.5 | 2.2 |
| Kenta Maeda | 1.9 | 2.4 | 1.7 | 1.6 | 2.1 | 1.9 |
| Dylan Bundy | 2.0 | 1.5 | 1.7 | 1.6 | 2.0 | 1.8 |
| Gerrit Cole | 1.5 | 2.1 | 1.6 | 1.8 | 2.0 | 1.8 |
| Hyun Jin Ryu | 1.7 | 1.7 | 2.3 | 1.4 | 1.8 | 1.7 |
| Lucas Giolito | 1.9 | 1.3 | 0.7 | 1.6 | 2.1 | 1.7 |
| Framber Valdez | 2.0 | 1.2 | 0.9 | 1.7 | 1.3 | 1.5 |
| Zack Greinke | 1.9 | 1.3 | 1.1 | 1.5 | 1.3 | 1.5 |
| Marco Gonzales | 1.7 | 1.6 | 1.3 | 1.2 | 1.3 | 1.4 |
| Dallas Keuchel | 1.6 | 2.5 | 1.9 | 0.8 | 0.9 | 1.4 |
| Andrew Heaney | 1.7 | 1.0 | 1.4 | 1.1 | 1.1 | 1.3 |
Voters have different options when relying on WAR. They can choose the metric that best fits their preference for how to value pitchers and provide credit for different outcomes. If voters want to take the easy way out and average them, Bieber is still obviously first, followed by Lynn and Maeda, with Bundy and Cole rounding out the top five. Ryu and Giolito are close enough to make very solid claims as well. The rest of the group all have significant drawbacks in one metric or another, or simply are a cut below in nearly all of them. The bottom five have had good seasons, just not quite good enough to make most Cy Young ballots.
Because I already went through the effort of determining an xWAR this season, and you might find it interesting, here’s a rough xWAR based on xwOBA for all AL pitchers who have faced at least 150 batters this season:
| Name | Team | IP | WAR | woba | xwoba | xWAR |
|---|---|---|---|---|---|---|
| Shane Bieber | Indians | 72.1 | 2.9 | .220 | .258 | 2.7 |
| Lance Lynn | Rangers | 78.1 | 1.8 | .258 | .280 | 2.5 |
| Lucas Giolito | White Sox | 66.1 | 1.9 | .250 | .277 | 2.1 |
| Kenta Maeda | Twins | 60.2 | 1.9 | .217 | .263 | 2.1 |
| Gerrit Cole | Yankees | 73 | 1.5 | .275 | .290 | 2.0 |
| Dylan Bundy | Angels | 65.2 | 2.0 | .263 | .282 | 2.0 |
| Hyun Jin Ryu | Blue Jays | 60 | 1.7 | .281 | .287 | 1.8 |
| Tyler Glasnow | Rays | 51.1 | 1.2 | .289 | .276 | 1.7 |
| Cristian Javier | Astros | 48.2 | 0.4 | .273 | .287 | 1.4 |
| Zack Greinke | Astros | 62.1 | 1.9 | .282 | .310 | 1.3 |
| Marco Gonzales | Mariners | 64.2 | 1.7 | .257 | .313 | 1.3 |
| Zach Plesac | Indians | 48.2 | 1.4 | .232 | .290 | 1.3 |
| Framber Valdez | Astros | 70.2 | 2.0 | .275 | .320 | 1.3 |
| Aaron Civale | Indians | 70 | 1.4 | .316 | .321 | 1.3 |
| Carlos Carrasco | Indians | 62 | 1.4 | .291 | .318 | 1.2 |
| Andrew Heaney | Angels | 62.2 | 1.7 | .281 | .322 | 1.1 |
| J.A. Happ | Yankees | 44.1 | 0.7 | .279 | .300 | 1.1 |
| Yusei Kikuchi | Mariners | 41 | 0.9 | .296 | .297 | 1.1 |
| Blake Snell | Rays | 50 | 0.6 | .292 | .313 | 1.0 |
| Jesus Luzardo | Athletics | 56 | 0.8 | .312 | .321 | 1.0 |
| Sean Manaea | Athletics | 48 | 1.2 | .302 | .313 | 1.0 |
| John Means | Orioles | 37.2 | 0.0 | .320 | .296 | 1.0 |
| Jose Berrios | Twins | 58 | 1.1 | .296 | .325 | 1.0 |
| Brady Singer | Royals | 57.1 | 0.7 | .295 | .325 | 1.0 |
| Jordan Montgomery | Yankees | 38.2 | 0.7 | .316 | .305 | 0.9 |
| Chris Bassitt | Athletics | 56 | 1.0 | .294 | .326 | 0.9 |
| Griffin Canning | Angels | 56.1 | 0.8 | .325 | .327 | 0.9 |
| Justus Sheffield | Mariners | 50.1 | 1.4 | .277 | .324 | 0.9 |
| Dallas Keuchel | White Sox | 57.1 | 1.6 | .244 | .330 | 0.9 |
| Masahiro Tanaka | Yankees | 44 | 0.8 | .293 | .319 | 0.8 |
| Martin Perez | Red Sox | 58 | 0.5 | .301 | .334 | 0.8 |
| Ryan Yarbrough | Rays | 52.1 | 0.8 | .299 | .332 | 0.8 |
| Randy Dobnak | Twins | 46.2 | 0.8 | .308 | .334 | 0.6 |
| Danny Duffy | Royals | 50.1 | 0.3 | .319 | .338 | 0.6 |
| Nathan Eovaldi | Red Sox | 42.1 | 0.6 | .335 | .334 | 0.6 |
| Mike Minor | – – – | 51.2 | 0.6 | .311 | .341 | 0.6 |
| Brad Keller | Royals | 48.2 | 1.0 | .239 | .341 | 0.6 |
| Mike Fiers | Athletics | 54 | 0.7 | .326 | .344 | 0.5 |
| Lance McCullers Jr. | Astros | 51 | 0.9 | .310 | .348 | 0.5 |
| Taijuan Walker | – – – | 50.1 | 0.4 | .298 | .352 | 0.4 |
| Matthew Boyd | Tigers | 54.1 | 0.0 | .379 | .356 | 0.3 |
| Frankie Montas | Athletics | 47 | 0.1 | .358 | .354 | 0.3 |
| Kris Bubic | Royals | 45.1 | 0.6 | .315 | .354 | 0.3 |
| Trevor Richards | Rays | 32 | 0.1 | .370 | .347 | 0.3 |
| Spencer Turnbull | Tigers | 51.2 | 1.2 | .287 | .368 | 0.1 |
| Ryan Weber | Red Sox | 40 | -0.1 | .342 | .371 | 0.0 |
| Asher Wojciechowski | Orioles | 37 | -0.2 | .392 | .370 | 0.0 |
| Jordan Lyles | Rangers | 54.2 | -0.1 | .348 | .370 | 0.0 |
| Jorge Lopez | – – – | 37 | 0.4 | .312 | .376 | 0.0 |
| Dylan Cease | White Sox | 53.2 | -0.1 | .339 | .375 | -0.1 |
| Justin Dunn | Mariners | 40.2 | -0.2 | .302 | .381 | -0.1 |
| Kyle Gibson | Rangers | 61.1 | 0.1 | .359 | .384 | -0.3 |
| Alex Cobb | Orioles | 45.1 | 0.4 | .319 | .396 | -0.4 |
| Tanner Roark | Blue Jays | 43.2 | -0.5 | .418 | .399 | -0.5 |
Craig Edwards can be found on twitter @craigjedwards.
Liam Hendriks
This actually seems like the year for a reliever, right? The top relievers have between 22 and 29 innings. The top starters have been 60 and 75 innings.
In the NL, he wouldn’t have a chance, but Devin Williams currently has 1.4 wins in 25 innings. How crazy is that?
I’d say it’s even worse to pick a reliever this year. You want to give a pitcher an award for what amounts to 4 good starts worth of innings? No effing thank you. Made worse because, you know, Bieber exists.
My vote is for Kenta Maeda. Among SP with at least 40 innings this year, he is 4th in the AL in ERA, 6th in FIP, 2nd in xFIP, 7th in K/9, 7th in BB/9, 6th in K/BB rate, the lowest opponents BA, lowest WHIP, 2nd in SIERA…He’s a worthy runner-up.
Also the lowest average exit velocity, which helps to back up some of the other stats.
Maybe I’m misunderstanding, or maybe it’s a one short year fluke, but how can every pitcher’s xwOBA be higher than their wOBA? I thought it was calculated based on batted ball profiles and was meant to remove luck to show the expected outcome. By definition, everyone cannot have better than average luck (or worse than average in the case of hitters.) If it consistently shows the average outcome to be better (for a hitter) than it is in reality, shouldn’t the calculation methodology be adjusted?
It looks like the overall distribution shifted and was not updated.
Looks like the average xWOBA is 335 and average wOBA is 315 https://baseballsavant.mlb.com/expected_statistics
In other words, expected statistics are based off of regression of underlying data to actual achieved statistics over a several year span. Changes, such as the baseball being slightly less aerodynamic this year after being at its most aerodyamic last year can’t be immediately incorporated; using too short of a timeframe for the regression will just result in an outcome that reflects too much noise.
Also, it’s not always accurate to call all deviations from an expected statistic luck, it is “unexplained variance” and in some cases we might know exactly what is behind some of the variance (such as the hitter’s speed), but still purposefully exclude that variable as it’s not relevant to what the expected statistic is meant to measure.
This is a good longer version of what I was trying to say. Thanks.
I’m pretty sure xWOBA now uses hitter sprint speed as part of it
I am absolutely not buying that Lance Lynn should get credit for park factors for a stadium he isn’t even effing playing in. No. Way.
I already have enough problems with the defensive adjustments that are being used for bWAR, I don’t need this on top of it to screw it all up. Give me Maeda or Valdez or Bundy in the #2 slot.
Hmmm…looking over how BR explains their park factors, sounds like they use the factor for the park that’s being played in. So unless I’m completely missing something, I’m not sure what the issue is.
https://www.baseball-reference.com/about/parkadjust.shtml
Beyond that, the park factor adds 0.1 WAR to Lynn’s total relative to a 100% neutral park.
Are they using last year’s park factors, or this year’s? How about Fangraphs? How about BP? How about xwOBA? Any of them using last year’s park factors shouldn’t be used at all to assess Lynn. Their previous park was fairly extreme, and this one almost certainly is not to the same degree.
The article that I linked to above shows how BR uses park factors in a situation like this. And on the Rangers team page, they show a 106 one-year pitching factor vs 108 last year. But the bigger point is that the impact of park factors is fairly negligible. And more so in a 60 game season.
You pitch in the scenario given, park factors shouldn’t matter. Actual results matter.
Agree completely. Just like all other numbers, park factor is flawed. Does the system give credit to a hitter if every one of his HR’s is a 420+ rocket if he is playing in a bandbox like Yankee Stadium or is he simply penalized because he had the misfortune to hit them in an extreme hitter’s park?
I would say Lynn is the second best pitcher on the list, so no qualms letting him get second. Fangraphs list seems Al west heavy, no?
Are there differences in the quality of hitters given the extreme unbalanced schedules this year? And is that reflected in the stats above?
What’s the source of the differences between the RA9-WAR and bWAR? Pitcher DRS?
I’m a little unsure about using xwOBA this confidently for pitchers, especially given that it’s higher than wOBA allowed for EVERY one of these top pitchers. xwOBA was developed to measure hitters’ ‘deserved’ outcomes, and it seems to clearly be missing something with top pitchers. My best guess is that it’s because xwOBA ignores defensive shifts. The best starters execute the gameplan set by scouting/analyzing the opposing hitter, which usually results in batters hitting the ball where the analytics predicts they will, i.e. at least slightly more likely to be caught by a fielder than usual. That doesn’t necessarily mean a hard shift, per se— the need for/potential benefit of a shift is inversely proportional to the range of the fielders, so it’s really
This effect should, in general, be most pronounced for pitchers with extreme ground ball rates with good infield defenses behind them. Valdez, Keuchel, and Ryu are #2, 4, and 5 respectively in ground ball rate among AL starters with at least 40IP this year, unsurprisingly. Gonzales, meanwhile, is an extreme fly-ball pitcher whose home park’s marine layer depresses fly balls by a lot.
Verifying/disproving this hypothesis with defensive data from this year is a impossible given the tiny sample size, but I’d very much like to see an article on this subject from someone with more expertise.
Lynn, Cole, and Maeda are all right there. A good start to end the season or a poor one could switch that order around.
Lance Lynn or Devin Williams.
Obviously Eric Kratz. I mean, have you seen that knuckleball?
Thanks for the post, Craig. BTW, I wonder how the park factor is applied this year in stats sites.
I find it funny that the Angels have two of the top AL pitchers in WAR (Bundy/Heaney) and two of the top AL MVP Candidates (Trout/Rendon) and are still missing the playoffs.
Angels are 10th in position player WAR and 13th in pitching WAR for all of MLB. People will respond with Julio Teheran and Patrick Sandoval being miserable or Albert Pujols or Shohei Ohtani or Jo Adell or Rengifo being bad or players missing time but this is, overall, at least not a “bad” team. But it is a top-heavy team, where the big problem is that there are just too many black holes in the lineup. If you decide to cut Pujols so you can play Walsh, and find a way to get Taylor Ward in the lineup regularly at the expense of Adell/Upton you’ve already dramatically improved the team.
The other issue is that their bullpen has been pretty unfortunate. This, to me, is the absolute craziest part of the rumors about them bringing in Dombrowski. I get that is what you do when you want to blow up your future and win now but they couldn’t have picked a worse GM for developing a bullpen. If I’m the Angels I’m looking for a guy from the Twins or another team like that who can bring some of that bullpen magic with them.
I think the results in the last table are likely to reflect the voting, except with Maeda switching with Lynn. As good as Lynn has been the more successful team narrative will likely favour Maeda. I also expect Hendriks to be up there. Bundy has had too many klunkers to get more votes than Cole who is still the second most dominant pitcher in the AL.
Two guys not good enough to warrant investment/rotation spots with the Dodgers are now down-ballot AL Cy Young candidates… And I think that says more about how loaded the Dodgers were/are than anything negative about their player evaluation abilities.
Lynn’s innings and ERA (two of the three factors, along with Ks, that seem to be carrying the day now that wins are better understood), will easily make him the #2 pick.
Also, it’s not a bad pick. Innings are an even bigger deal this year and Lynn’s total is very impressive.
Innings, ERA, WHIP, and W/L are probably the most important to look at. So yes, Lynn would be a solid #2.
Question about the xWAR table: how is it that several pitchers who have a higher xwOBA than their wOBA also have a higher xWAR than WAR? For example, Kenta Maeda has a .217 wOBA/.263 xwOBA, but a 1.9 WAR/2.1 xWAR. Wouldn’t a 46 point jump in wOBA drastically decrease his WAR?
There’s definitely something funky there. Jose Berrios and Brady Singer have nearly the exact same statistics (IP/wOBA/xwOBA), but Berrios goes from 1.1 WAR to 1.0 xWAR, while Singer goes from 0.7 WAR to 1.0 xWAR.
Keuchel is #2. That ERA is a half run better than everyone else.
Personally I’ve always been a fan of fangraphs WAR for hitting, and predicting what will happen in the future. It is a better indicator of what should of happened as well. The one time I prefer bref is pitching war when it used for votes. In my opinion votes should be based on what did actually happen, regardless of luck, etc.
Strongly agree with this
This argument would be a lot stronger if it weren’t for the big problems with bWAR’s defensive adjustments. DRS is extremely twitchy, and you can get some totally crazy results with bWAR based on that.
To be fair, what bWAR is trying to do is nearly impossible. Which the reason why fWAR–while it doesn’t make sense philosophically here–is a far superior choice. Frankly, Craig’s xwOBA-WAR makes more sense here too. As does RA9-WAR, if you really want to base it on “what happened.”
WARP is a little different. FIP is literally based on “what happened”–there is no adjusting based on expected outcomes. It takes measurable indicators of pitcher performance that are uncontaminated by anything else and uses it to calculate value. WARP is literally based on expected outcomes–the probability of an event being due to chance.
I’d say that an average of fWAR, xwOBA-WAR, and RA9-WAR would probably be your best bet, with bWAR and WARP being left out.
Well said. FIP doesn’t necessarily have anything at all to do with how well you pitched, so I find it odd to use it for awards.
“This year, Shane Bieber has been so dominant that no other AL pitcher can come close to his accomplishments with less than a week remaining.”
Yeah… he’s certainly dominant in allowing loud contact.
Bieber
18: 89.6 (Exit Velocity) & .404 (XWOBACON)
19: 90.5 & .414
20: 88.9 & .405
Maeda
16: 85.7 & .357
17: 86.2 & .366
18: 87.3 & .378
19: 86.1 & .343
20: 85.3 & .364
Over the last 3 years, among the 45 pitchers with at least 1000 batted balls yielded, Bieber has allowed the 3rd-highest overall average exit speed and THE highest overall projected production (of 85 pitchers with 750 BBE, he has allowed the 4th-highest EV and projected BB production), which means that FIP, a metric that assumes league average results on balls in play for all pitchers, substantially overrates Bieber’s performance. And, indeed, his xERA is currently only 2.55, which is great but not otherworldly.
There is a reason why Tony Blengino, the erstwhile Fangraphs writer and former baseball executive, never used FIP in his pieces when evaluating pitchers (and wRC+ when evaluating hitters), instead opting for Tru ERA-, which is basically xwOBA on a scale where 100 equals league average.
Edwards, do you think it is fluke that the Dodgers’ pitching staff is now leading the Majors in Hard-Hit% for 7 years in a row, even with their best contact managers (Ryu and Maeda) no longer on the team?
Here is Andrew Friedman on Tony Watson.
“Watson has been high on our radar for a while and we checked in periodically with the Pirates about him,” Friedman said. “He is a master of inducing weak contact and he’s a great competitor and teammate. He’s been a big part of our continued success and is going to help lengthen our bullpen in October.”
Lastly, as for Bieber’s fantastic K rate, this is not a fricking K contest. If anything, that should be a minus for Bieber because, in principle, we should give the award to a PITCHER, not a THROWER , who rely heavily on the velocity/stuff for his success and, once those are diminished, will be toast like most pitchers; Just try to compare Greinke and King Felix.
Blengino on Bieber
“#1 RHP Shane Bieber (Indians) – With 13.1 PRAA, Bieber’s current advantage in the Cy race is much more precarious than you might think. Bieber’s excellence is totally attributable to his K/BB excellence, driven by his stellar knuckle-curve. He’s just not a good contact manager. Talk about consistency – Bieber’s Adjusted Contact Score in both 2018 and 2019 was 111. Thus far in 2020……it’s 110. His Adjusted Fly Ball Contact Score is a worst-in-the-majors and historically catastrophic 205. 37.5% of the fly balls he has allowed have been hit at over 100 MPH, 21.9% over 105 MPH. Most of the damage is done against his four-seam fastball. He needs to get that pitch to at least league average to truly catapult himself into the elite category over the long haul. He ranked 8th in the AL in PRAA (20.8) in 2019.”
So are we giving it to a pitcher or a thrower? Because your second comment contradicts your first. If he has a “stellar knuckle-curve” and uses it properly, that would indicate he’s a good pitcher, yes? I think of players like Nolan Ryan as “throwers”, since he basically let rip all the time. Yeah, he had a good K%, but he also always had a high BB%. Bieber has a super elite (although almost certainly higher than it should be) K%, but his BB% is also a full 2 points below league average.
If contact management is king, then your the AL Cy Young top 5 is (among pitchers with >750 pitches): Lance Lynn, Cristian Javier, Dylan Bundy, Martin Perez, and Lucas Giolito. Look, Martin Perez is a fine fourth starter for a team, but he’s not the fourth best pitcher in the AL.
Pitching is about getting outs any way you can, every batter you get out is a batter that doesn’t score. To say that strikeouts are a “minus” is ridiculous on it’s face, since a strikeout is, for all intents and purposes, a guaranteed out.
Lastly, as for Bieber’s awful Adjusted Fly Ball Contact Score, this is not a fricking contact management contest.
(This sort of rhetoric cuts both ways, eh?)
Not sure which is worse, the idea that King Felix, the guy who literally had 5 above average pitches, was a “THROWER”, or the idea that Bieber, the guy with the ~2% Minor league walk rate, is a “THROWER”.
What’s the cutoff here? FB velo under 90 MPH? Overperforming FIP 3 years in a row? Last name of “Moyer”? Do you have to be left handed? Occasionally throw an Eephus? Or is this all about exit velo stripped of context of launch angle? Is Yu Darvish a pitcher or a thrower? Max Scherzer? Gerrit Cole? Corey Kluber?
What if you have above average walk rate, GB%, First Pitch Strike %, and OSwing%, and throw 5 pitches? does that make you a “PITCHER”?
I’d point out that we have like 4 years of this data, we still have relatively little idea what the predictive value of xwOBA based on BBE data is. Also, you have provided the evidence that its not very descriptive of actual run allowance over a short term (2-3 years).
Also, how are the Dodgers at all relevant to this conversation?
I’m going to go out on a limb and say he’s a Dodgers fan…
You make some good points here, but just in such a terrible way. I always loved Tony Blengino’s contact management pieces.
I’d like to congratulate Tanner Roark for making it onto a Fangraphs list that didn’t involve you searching for it by yourself.
I remember Wins. I remember when Don Drysdale was on the Brady Bunch, and I remember Wins.. Kids these days.