Patrick Corbin is having a very weird season, and different stats tell very different stories about his season. To figure out what’s really happening, we’ll stroll through basic and advanced stats to show how his numbers change and, hopefully, why. For those of you acquainted with advanced statistics, feel free to just skip to the analysis part. If you don’t have a deep knowledge of sabermetrics, I hope I can give you some insight into what all those bizarre acronyms mean. Let’s start with not the what or how about advanced stats but rather why they exist.
Why Sabermetrics Exist
Measuring pitchers is hard. Sure, generally, good pitching gets good outcomes, but not always; last week, Juan Soto homered on a 101 MPH fastball above the letters, a nearly unhittable pitch. On the other hand, bad pitching doesn’t always get bad results; Albert Pujols got three outs on sub 60 MPH pitches! Let’s hone on this more, and to do this, I want to look at two specific plays which exemplify this.
In-game 7 of the 2001 World Series, with the bases loaded, a tie game, and the World Series on the line, the best reliever in the history of baseball stood on the mound in the highest pressure situation of his career. He threw a perfect pitch, a textbook Marino Rivera cutter right on the hands of Diamondbacks star LF Luis Gonzalez. The result was just as good as the pitch; Gonzalez was jammed and hit a little flare coming off the bat at a mere 58 MPH. Balls hit that hard and with a launch angle of 23º generate an average of .111 and an expected slugging % equaling that. This was not a well-hit baseball. Unfortunately for Mo, it dropped into shallow center field, just over the head of Derek Jeter. Mariano Rivera lost the World Series on a bloop single off of a perfect pitch.
Game 5 of the 2019 NLDS, 3-3 game in the bottom of the 9th. On the mound: RHP Daniel Hudson. In the box: C Will Smith. Hudson made a mistake, an 87 MPH cement mixer slider right over the heart of the plate. Smith crushed it. Smith hit the ball at 100 MPH and at a 26º launch angle. Balls hit like that land for a hit 62% of the time and left the park 41% of the time. For some reason, whether it be the cold October air, wind, or a different baseball, that ball mercifully landed in the glove of Adam Eaton just shy of the wall. I’m sure I don’t need to tell you what happens next.
The point is that outcomes don’t always show the true performance of a pitcher, especially in small sample sizes. Sabermetricians have tried to isolate just the pitcher in stats to solve this. Let’s follow that journey and see how what types of stats you look at can change what kind of season Patrick Corbin is having.
Wins, Losses, Strikeouts
Level I is wins, losses, and strikeouts. These are some of the oldest known stats and aren’t really used by
people with brains in front offices anymore. So what do they measure? Well, wins and losses only measure how good the rest of your team is and how long a manager will leave a pitcher in. Sure, better pitchers will generally have more wins, but the stat doesn’t isolate the pitcher’s performance at all. Strikeouts are better, and the problem is that in order to contextualize that number, you need to know innings pitched or batters faced. Otherwise, it’s kinda meaningless.
Patrick Corbin has 0 wins, 6 losses, and 46 strikeouts in 8 starts. This says that Corbin is well, pitching poorly, and isn’t getting bailed out by his team. As for the 46 Ks, it’s still a meaningless number, but maybe he has a decent strikeout rate? We need more information.
Related Article: Where has the 2019 Patrick Corbin gone? Or was it ever there?
ERA WHIP BAA
6.28 ERA 1.68 WHIP .286 BAA
ERA, WHIP, and BAA all take a step forward from the last three stats by removing team offense from the equation. For those of you who don’t know, ERA is (Earned Runs/Innings Pitched )*9. This measures how many runs pitchers give up on a rate basis. WHIP is (BB+H)/IP and measures how many baserunners a pitcher allows. BAA is just the batting average of hitters against the pitcher. An ERA is actually a pretty decent stat in large sample sizes but can sometimes fail because it doesn’t take batted ball data into account. WHIP doesn’t really matter that much because with pitching at the end of the day, all that matters is how many runs you give up. WHIP is useful for quantifying efficiency but not much else; as for BAA, it suffers the same pitfalls as WHIP but doesn’t even include walks. It really serves no purpose. I will say that these stats do something well, even if they have flaws or are redundant. I use all of them for some purpose from time to time.
Now let’s look at Corbin. Corbin has a 6.28 ERA, 1.68 WHIP, and a .286 BAA. This backs up the first level of stats’ assessment that Corbin has been downright terrible. His 6.28 ERA is one of the worst in the league, and the WHIP is just as awful. These numbers quantify his results on the field, but not necessarily how well he’s pitching. Let’s see how things change when we get into sabermetrics.
FIP wOBAA K%
4.20 FIP .361 wOBAA 19.8 K%
These are the first ‘advanced stats’ we’ll see on the list. FIP (Fielding Independent Pitching) tries to separate a pitcher from the quality of their defense by only using HRs, Ks, and BBs and is an ERA estimator (treat the values like you would ERA). wOBA (weighted On Base Average) is like OPS but uses run expectancy to properly weight walks, 1B, 2B, 3B, and HRs, and is scaled like OBP. K% is simply Strikeouts/ Batters Faced and does a much better job than just Ks to find strikeout rate.
We see an interesting discrepancy here for Corbin; while Corbin’s 4.20 FIP and 19.8 K% are about league average, his .361 wOBA, well above the league average of about .310, shows how poor of a job he does limiting baserunners. It seems like Corbin has gotten unlucky.
SIERA xFIP K%-BB%
4.43 SIERA 4.39 xFIP 9.3 K%-BB%
SIERA (Skill-Interactive Earned Run Average) and expected FIP try to improve upon what FIP does by eliminating park factors and defense. The difference is that SIERA uses groundball rate in lieu of homers, and xFIP replaces homers with HR/FB rate. K%-BB% is pretty simple, but it contextualizes K% and can show the true value of a low K, low BB guy, as well as high K, high BB guys.
Corbin’s 4.43 SIERA and 4.39 xFIP seem to back up FIP’s diagnosis. Corbin has been pretty unlucky this year. We’re also shown this through his 9.3 K%-BB% which is significantly better than the league average. Clearly, we need to re-evaluate Corbin if he’s pitching this much better than his ERA suggests. But let’s see what the last layer shows.
pCRA dERA CSW
5.14 pCRA 5.22 dCRA 27.9% C
These are some of the most cutting-edge, newest numbers in baseball. Few people use them, and fewer still understand them. Let’s take them one by one and start with the predicted Classified Run Average. pCRA uses K% and BB%, like SIERA, but instead of ground ball rate, it uses barrel%. A barrel is a ball hit over 98 MPH within a specific range of launch angles. It was measured to be the best ERA estimator in baseball by Six-Man Rotation using margin for error. . If that’s not enough for you, and you want to remove literally every single variable, try deserved ERA. dERA is an ERA estimator that includes peripherals like the quality of opposing batters, park factors, and even weather. Finally, we have CSW or called strike% + swinging strike%. It’s deceptively simple but showcases a pitcher’s ability to be in the zone and get whiffs.
As the stats have gotten more advanced, Corbin’s numbers have gotten better. This will not last. Corbin’s 5.14 pCRA, and 5.22 dERA are far better than his 6.28 ERA but still atrocious. Weirdly his CSW still hovers right at league average at 27.9%. With all this information, let’s try and figure out exactly what’s going on.
Three facts expose themselves through this analysis, and they paint an interesting picture.
- Patrick Corbin has been very unlucky this season.
- Patrick Corbin has done a pretty good job throwing strikes and striking hitters out.
- Despite all the mitigating factors, Patrick Corbin has been terrible this season, and there is one fundamental reason why.
It’s truly bizarre; all of his expected stats are 1-2 runs lower than his ERA. This normally means a pitcher is giving up bloop hits or has bad defense. But Corbin’s ERA estimators range from 4.2 (just below average) to 5.22, which is well below average. He’s not walking a ton of guys and is getting a ton of strikes which is normally a big reason pitchers can’t perform, so we get to the crux of the problem. Patrick Corbin is getting crushed. pCRA, which has a huge weight on barrels, showcases, well, quite frankly, how often he makes mistakes, and he can’t catch a break on any of them. When he hangs a slider, it gets crushed.
On pitches over the heart of the plate, he’s given up 5 below average, which is in the bottom 10% of all pitchers. It’s really a shame, we all look for that one thing to fix Corbin, to bring him back to 2019, but that feels impossible now. There is no good explanation for why all of a sudden, hitters punish their mistakes so much worse now, and that is incredibly disheartening. I wish Patrick the best of luck, and I have faith in his work ethic and Jim Hickey’s abilities, but it’s time to close the door on this conversation.