Starting Pitcher xERA Underperformers — Jun 23, 2022
I haven’t done a lot of research on Statcast’s xERA metric, but it’s similar to batter xwOBA in that it uses a pitcher’s actual batted balls against to compute what a pitcher’s ERA “should” be. That means for all those who love justifying a pitcher’s low BABIP being the result of allowing soft contact, xERA should theoretically account for this. Now, this doesn’t mean the pitcher will continue to allow the types of batted balls that have resulted in a suppressed or inflated xERA, but it does suggest that what they have already allowed should yield the calculated xERA. So let’s review the pitchers who have most underperformed their xERA marks.
| Name | K% | BB% | BABIP | LOB% | HR/FB | ERA | xERA | Diff |
|---|---|---|---|---|---|---|---|---|
| Alex Cobb | 27.2% | 7.2% | 0.381 | 55.6% | 19.2% | 5.62 | 2.23 | 3.39 |
| Elieser Hernandez | 21.6% | 6.9% | 0.269 | 69.0% | 21.2% | 6.75 | 5.06 | 1.69 |
| Hunter Greene | 30.1% | 9.9% | 0.260 | 75.6% | 18.3% | 5.26 | 3.67 | 1.59 |
| Zach Eflin | 20.2% | 4.9% | 0.290 | 65.9% | 11.1% | 4.43 | 2.99 | 1.44 |
| Dylan Bundy | 18.8% | 4.3% | 0.302 | 69.0% | 13.7% | 5.17 | 3.80 | 1.37 |
| Tyler Mahle | 25.9% | 8.9% | 0.309 | 66.8% | 8.0% | 4.57 | 3.23 | 1.34 |
| Austin Gomber | 18.0% | 7.4% | 0.332 | 57.7% | 12.7% | 6.43 | 5.13 | 1.30 |
| German Marquez | 20.1% | 7.3% | 0.338 | 61.8% | 20.0% | 6.16 | 4.87 | 1.29 |
| Aaron Ashby | 27.5% | 10.7% | 0.336 | 70.7% | 18.8% | 4.25 | 3.01 | 1.24 |
My gosh, Alex Cobb is far and away the xERA underperformance king so far, though it’s come in just over the minimum innings I set of 40. With a career best strikeout rate and GB%, it’s shocking to see how inflated his ERA is. You can thank the trio of inflated BABIP and HR/FB rate, along with a suppressed LOB% for the underperformance. Cobb is not a perennial underperformer either, in fact, he has overperformed every year of his career. Oh, and his sinker has gained nearly two miles per hour of velocity. You might be lucky enough to find him sitting in your free agent pool. He’s a screaming buy.
With a high 90s fastball, Hunter Greene got a lot of sleeper love when he was competing for a rotation spot out of spring training. So far, the skills have been there, including a 30.1% strikeout rate. But an inflated HR/FB rate, combined with an insane 56% FB%, have wreaked havoc on his ERA. Great American Ballpark isn’t exactly the best park to be an extreme fly ball pitcher. That HR/FB rate figures to decline, but the FB% remains scary. He makes for a good buy in keeper leagues, assuming he’s cheap, but I’m a bit hesitant in single season shallow mixed leagues.
It’s hard to believe in Zach Eflin’s xERA, given his mediocre strikeout rate and overall skill set. Plus, while his LOB% is a bit low, his BABIP and HR/FB are fairly normal. It’s clear that based on his batted balls against, Statcast thinks he should have enjoyed better luck, but I wouldn’t expect it to last given his history. However, he has changed up his pitch mix, throwing a cutter now and his curveball significantly more, at the expense of his changeup and slider. That hasn’t made a lick of difference in the underlying skills, but perhaps has led to worse quality contact by opposing batters that should have yielded better results. Still, I’m not buying here.
Dylan Bundy has been an xERA underperformer for the majority of his career, but much of that was because he pitched half his games in a hitter’s paradise in Baltimore. With his fastball velocity down below 90 MPH for the first time, his strikeout rate has plummeted, while his BABIP has jumped to the second highest mark of his career. He could probably do better than a 5.17 ERA, but I have no interest here given the velocity loss leading to fewer strikeouts.
The second highest BABIP and second lowest LOB% of Tyler Mahle’s career has driven his ERA higher, but his xERA is actually the lowest of his career. I’m guessing that HR/FB rate is going to rise, but it should be offset by a drop in BABIP and increase in LOB%. I’m a bit concerned that his FB% has risen, so an increase in HR/FB rate could really up the homers allowed.
I’m never sure how to treat Rockies players when it comes to Statcast metrics, but German Marquez’s SwStk% has plummeted and strikeout rate is at a career low. So unlucky or not with his 6.16 ERA, I’m not interested, even if he does see better results the rest of the way.
Hopefully Aaron Ashby’s injury doesn’t knock him out too long, as I’m really intrigued by his combination of strikeouts and groundballs. A combination of inflated BABIP and HR/FB rate has driven up his ERA and overshadowed an exciting skill set. This is a good opportunity for keeper leaguers to try buying here.
Mike Podhorzer is the founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
Sometimes this stat can also be “pitching in front of a bad defense” or “pitchers who have struggled executing their pitches out of the stretch.” The former results in poor outs conversion, and the latter can result in low LOB% and what could look like unlucky sequencing of hits.
For Alex Cobb, it is certainly the former (so far).
Why do you say certainly? Looking at the xWOBA for pitchers on the Giants, there don’t seem to be any particularly obvious trends there.
Wouldn’t bad defense reflect across all of their pitchers?
I believe hmmph3 is referring to a memorable bad outing this year where the Giants defense just ruined him. (But I’m apparently too old to remember it well.)
Alex Cobb is going to end up being on a lot of teams that miss the playoffs this year…
Is baseball really more watchable with analytics?
05-30-2022, 03:56 PM
I’m being honest, I like talking baseball and stats online, but I can’t stand watching the game as I quit watching it completely because of the overall run environment of the game is not worth any amount of time to invest in the game.
Do I believe analytics can have value to a large sample size of a season to whether a team wins or loses? Of course I do.
Do I understand advanced stats and what they mean? Do I understand their overall purpose, which is what wins game? Of course I do.
Do I understand the cat and mouse between pitcher and hitter? Do I understand the nuances of how baseball is supposed to be enjoyed with the idea of “anticipation” in mind? Of course I do.
I bring these questions up, because I’ve found people get a lot of backlash for not enjoying the game, because they assume people don’t know anything about baseball in terms of advanced stat or they are unknowledgeable about the cat and mouse that goes on between pitcher and hitter. While that may apply to most people, that certainly does not apply to me.
No matter how much I understand advanced stats or the cat and mouse between pitcher and hitter or how baseball is supposed to be enjoyed, I still do not accept it or enjoy it.
I grew up in an age of baseball in the 90s and 2000s where baseball to me was at it’s very best. Yes advanced stats were present, but as just about all of us know, they were not used as prevalently now and there was a lot more randomness in the game. To me, the fact that there was more in the way of randomness made the game better.
To illustrate my point of randomness using an example, I compare baseball during the steroid era to the company World Wrestling Entertainment during the late 90s and 2000s. During that time, both companies did not follow to a tee a script. They improvised in terms of what they went about doing things using their imagination and creativity to entertain fans. It seemed like both companies could do no wrong as there was something for everyone. Even the die hards who preferred more pitching duals were very into the MLB product. The ratings proved it.
Nowadays EVERYTHING follows a script to a tee in both Major League Baseball and World Wresting Entertainment. It’s a big reason to explain why BOTH have become unwatchable for me.
We saw teams come back from 12 run deficits and the larger number of lead changes occurring in the games kept the product fresh. You never felt in a game back in 2000 (even if you got down 8 runs) that the game was over like it is now. That’s what made the 8-10 run inning fun to watch, because it was more common then with less use of advanced stats then it is now. You saw a variety of different things happen when a team scored 8 runs in an inning and teams strung hit after hit together. Now a 4 run inning is primarily considered the big inning in baseball. Big innings allowed for more comebacks, because it gave more to the game in terms of the “unexpected.”
In most at bats you watch in baseball today you mostly only see 1 of 3 outcomes, which is strikeout, walk, or homerun. No matter how much I know about baseball and the facts about what it’s supposed to be like, I simply don’t care about the nuances that exist in the game.
Sure pitching being a lot better with the overall velocity of pitchers being up explains why offense is down (along with shift, etc.), but there are people like David Cone who fail to realize that advanced stats explains why pitchers are a lot better. Advanced stats said throwing in the high 90s with movement (and high spin rate) to go along with locations gives you a better chance than a guy throwing in the low 90s with movement and location.
For me advanced stats not only changed the game, but changed the game for the worst by making pitchers better.