Poll 2025: Which Group of Pitchers Performs Better?

The All-Star break is here! That means it’s time to get polling. As has become an annual tradition, I’m going to start by comparing starting pitchers’ ERA to SIERA, pitting the SIERA overperformers against the underperformers during the pre-all-star break period. This is the poll I began with back in 2013.
I came up with this idea given my faith in using SIERA, rather than ERA, over smaller samples as I essentially ignore ERA completely as late as the middle of the season, and it’s interesting to see how everyone else thinks. Will the SIERA overperformers continue to outperform, perhaps due to continued strong defensive support and/or more pitcher friendly ballparks, or will the magic disappear? Is it just bad luck that is due to reverse course for the SIERA underperformers or are they being hampered by one of the aforementioned factors that should continue to play a role the rest of the way?
My initial population group consisted of 116 pitchers who have thrown at least 70 innings. Group A is composed of the 10 largest SIERA overperformers, while Group B is composed of the 10 largest SIERA underperformers. Let’s compare.
Name | LD% | GB% | FB% | IFFB% | HR/FB | BABIP | LOB% | K% | BB% | ERA | SIERA | Diff |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Kodai Senga | 13.4% | 47.5% | 39.1% | 8.9% | 5.1% | 0.256 | 88.7% | 23.8% | 10.6% | 1.39 | 4.16 | -2.77 |
Tyler Mahle | 20.5% | 40.6% | 38.8% | 9.2% | 4.6% | 0.253 | 82.3% | 18.2% | 8.8% | 2.34 | 4.63 | -2.29 |
Randy Vásquez | 15.2% | 38.5% | 46.3% | 14.7% | 8.4% | 0.248 | 80.0% | 12.1% | 11.2% | 3.80 | 5.84 | -2.04 |
Andrew Abbott | 20.6% | 30.7% | 48.6% | 12.0% | 8.0% | 0.259 | 86.0% | 22.5% | 6.5% | 2.07 | 4.04 | -1.97 |
Noah Cameron | 16.6% | 45.1% | 38.3% | 10.8% | 9.5% | 0.218 | 86.4% | 21.1% | 8.0% | 2.31 | 4.15 | -1.83 |
Jose Quintana | 17.6% | 45.2% | 37.1% | 8.5% | 8.5% | 0.273 | 77.1% | 15.8% | 10.2% | 3.28 | 5.05 | -1.77 |
Ranger Suárez | 15.3% | 50.2% | 34.5% | 13.9% | 7.6% | 0.267 | 84.4% | 23.5% | 6.6% | 1.94 | 3.61 | -1.68 |
Seth Lugo | 19.2% | 38.8% | 42.0% | 9.5% | 12.9% | 0.239 | 87.9% | 21.9% | 7.7% | 2.67 | 4.08 | -1.41 |
Matthew Boyd | 18.5% | 37.0% | 44.5% | 12.4% | 7.3% | 0.273 | 81.1% | 23.2% | 5.2% | 2.34 | 3.70 | -1.36 |
Bailey Falter | 19.9% | 37.0% | 43.1% | 8.6% | 10.9% | 0.240 | 72.2% | 14.9% | 8.6% | 3.79 | 5.10 | -1.31 |
Group Average | 17.8% | 40.5% | 41.7% | 11.0% | 8.5% | 0.253 | 82.2% | 19.6% | 8.3% | 2.62 | 4.43 | -1.81 |
League Average* | 19.9% | 41.3% | 38.8% | 9.8% | 12.0% | 0.288 | 73.5% | 21.6% | 7.9% | 4.11 | 4.11 | 0.00 |
Name | LD% | GB% | FB% | IFFB% | HR/FB | BABIP | LOB% | K% | BB% | ERA | SIERA | Diff |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Sandy Alcantara | 21.5% | 45.3% | 33.2% | 5.1% | 12.1% | 0.300 | 53.2% | 17.3% | 9.0% | 7.22 | 4.66 | 2.56 |
Ben Brown | 18.8% | 41.9% | 39.3% | 9.8% | 14.1% | 0.362 | 65.5% | 25.3% | 7.5% | 6.13 | 3.60 | 2.53 |
Eduardo Rodriguez | 22.5% | 34.5% | 43.0% | 18.7% | 15.0% | 0.371 | 65.7% | 23.9% | 7.7% | 5.94 | 3.88 | 2.05 |
Trevor Williams | 25.4% | 33.0% | 41.6% | 6.0% | 9.5% | 0.347 | 61.6% | 17.4% | 5.6% | 6.21 | 4.47 | 1.73 |
Bryce Elder | 21.3% | 51.0% | 27.7% | 1.4% | 22.9% | 0.318 | 71.9% | 19.4% | 7.9% | 5.65 | 4.10 | 1.55 |
Antonio Senzatela | 20.5% | 47.9% | 31.6% | 4.5% | 14.4% | 0.367 | 66.6% | 11.1% | 7.5% | 6.60 | 5.14 | 1.46 |
Dylan Cease | 22.9% | 35.4% | 41.7% | 11.5% | 13.3% | 0.320 | 68.1% | 29.0% | 8.8% | 4.88 | 3.42 | 1.46 |
Walker Buehler | 22.0% | 44.3% | 33.7% | 8.4% | 20.5% | 0.302 | 69.7% | 17.7% | 9.9% | 6.12 | 4.74 | 1.37 |
Cal Quantrill | 24.6% | 34.4% | 41.0% | 10.5% | 11.4% | 0.335 | 65.6% | 19.0% | 6.8% | 5.62 | 4.37 | 1.25 |
Zac Gallen | 19.9% | 41.4% | 38.7% | 2.3% | 16.2% | 0.290 | 66.1% | 22.2% | 9.1% | 5.40 | 4.18 | 1.22 |
Group Average | 21.9% | 41.1% | 37.0% | 7.9% | 14.5% | 0.331 | 65.3% | 20.3% | 8.0% | 5.95 | 4.25 | 1.70 |
League Average* | 19.9% | 41.3% | 38.8% | 9.8% | 12.0% | 0.288 | 73.5% | 21.6% | 7.9% | 4.11 | 4.11 | 0.00 |
Group | LD% | GB% | FB% | IFFB% | HR/FB | BABIP | LOB% | K% | BB% | ERA | SIERA | Diff |
---|---|---|---|---|---|---|---|---|---|---|---|---|
A | 17.8% | 40.5% | 41.7% | 11.0% | 8.5% | 0.253 | 82.2% | 19.6% | 8.3% | 2.62 | 4.43 | -1.81 |
B | 21.9% | 41.1% | 37.0% | 7.9% | 14.5% | 0.331 | 65.3% | 20.3% | 8.0% | 5.95 | 4.25 | 1.70 |
League Average* | 19.9% | 41.3% | 38.8% | 9.8% | 12.0% | 0.288 | 73.5% | 21.6% | 7.9% | 4.11 | 4.11 | 0.00 |
Wow, these two groups have significantly wider gaps than last year! Group A, the overperformers, are overperforming by more, while Group B, the underperformers, are underperforming by more. That’s pretty crazy. What I love seeing is that while the margin is relatively small, Group B’s underlying skills have actually been a bit better, driving a slightly lower SIERA. And yet, their ERA is approaching 6.00!
Let’s dive into the underlying drivers of the differences in ERA-SIERA gap. Group A’s batted ball profile certainly appears better than Group B’s. The group has allowed a lower LD%, while generating a higher FB%, and inducing a higher IFFB%. That’s a perfect recipe for a lower BABIP, though the higher FB% could potentially result in more home runs allowed. Sure enough, the group has posted a lower BABIP. But is that batted ball profile difference really significant enough to justify the massive gap in BABIP marks between the groups?! I’d say almost certainly no.
Next we move onto one of the other members of the luck trio, HR/FB rate. Unsurprisingly, we see a dramatic difference here as well. There definitely is some skill involved here (just like BABIP), but there’s so much noise, that over a small sample size of half a season of fly balls, there’s just not very much predictive value in what has already been recorded in the books. So we don’t necessarily know Group A is inherently better at keeping fly balls in the park than Group B is, even though that’s what has happened so far.
The final member of the luck trio is LOB% and once again, we see a huge gap between the rates of the two groups. There are a number of factors that influence this rate and like BABIP and HR/FB rate, a pitcher’s skill definitely plays a role. But so does fortune, good or bad. There’s almost no chance Group A owns 80%+ LOB% skills, while Group B sits at just 65%. The best pitchers are generally going to average out in the high 70% range over their careers, while the worst in the mid-to-high 60% range (though these pitchers aren’t going to get to pitch for very long with an LOB% that consistently low). So there’s no way Group A is going to continue with a 10-pitcher average over 80%.
Last, we end up on strikeout and walk rates. The rates here are pretty close, but Group A has actually posted slightly worse marks, with a lower strikeout rate and higher walk rate. That mostly explains why its aggregate SIERA is slightly higher than Group B.
Let’s now talk some specific names, beginning with the overperformers. Kodai Senga leads baseball as the largest SIERA overachiever. Some might wave that title away thanks to his “ghost fork”, but that would be silly. First, any particular reason someone can come up with doesn’t automatically justify any result. If he had a 0.00 ERA, would we hear the same argument about the ghost fork? How about a 0.50 ERA? At what ERA are we willing to acknowledge he’s been lucky and it’s not just some magical pitch? Second, Statcast’s xERA accounts for batted ball quality against. That metric sits at 3.17. Yes, that’s nearly a run lower than his SIERA, but also almost two runs higher than his actual ERA. No matter what metric you use, he’s benefited from gobs of good fortune. Since his strikeout rate has also collapsed with his 2023 mark, he seems like the ultimate sell high.
Every time Randy Vásquez starts, I expect like a 10-run, 0.2 inning outing. But instead, it’s a consistent four and change innings with one to two runs allowed and poor strikeout and walk rates. It’s incredible! I don’t think I’ve ever seen a pitcher with skills as weak as his appear on these leaderboards. Even his xERA is 5.80, so it’s been a true smoke and mirrors act, but the clock has gotta strike midnight soon.
I was intrigued by Noah Cameron when he was up in velocity during spring training, but that hasn’t materialized in the Majors. The .199 BABIP won’t last, of course, but his 3.36 xERA does suggest he has done a great job limiting high quality contact. Will that last though? With a strikeout rate barely over 20%, I wouldn’t really be interested in risking my ratios to find out.
There’s Seth Lugo again! He handily overperformed his SIERA last year, making him seem like an easy bust call this year. Instead, his skills have slipped and SIERA has risen, but he has overperformed even more. Even his xERA isn’t buying it, and it’s actually higher than his SIERA, making it even more of a head-scratching first half. With a below average strikeout rate, he’s just not the type of pitcher I would feel comfortably starting each week.
Now we’ll flip over the underperformers. Yikes, this has not been the return from TJ surgery anyone wanted to see for Sandy Alcantara. It’s true, the skills here have really deteriorated, as his strikeout rate is down to just 17.3% and his walk rate has spiked to its highest since 2019. He has lost a bit of velocity, but not an alarming amount and his Stuff+ is still well above the league average. We know it could take a while for a pitcher returning from such surgery to regain their command, and sure enough, his Location+ has dropped. Depending on how he finishes the season, he could make for a nice rebound candidate next year, but I’m not particularly interested in speculating on one over the remainder of this season.
Eduardo Rodriguez has posted the highest BABIP in baseball. No wonder he’s one of just three starters with an ERA over two runs higher than his SIERA! His SIERA also sits sub-4.00, so he actually should actually be helping fantasy teams. Instead, he has been torpedoing their ratios. I don’t think the upside here is enough to bother hoping for better results, but he should generate some positive value in NL-Only leagues over the rest of the season.
What on Earth has happened to Dylan Cease?! His underlying skills are almost identical to last year, as is his SIERA. Granted, his xERA is up a bit, but it’s still just 3.66, which is more than a full run lower than his actual ERA. The velocity is good and his SwStk% is at a career best and ranks second in baseball. It all sounds great, except for the luck metrics conspiring against him to elevate his ERA to the highest since his 2019 debut. To add insult to injury, the inflated ERA has led to just three measly wins! I keep meaning to throw out more offers for him in my league, and then he ends up having another poor outing to give me an extended window to make an offer. I don’t know about you, but I would prefer Cease to any of the ten names in Group A for the rest of the season.
I was never a big fan of Walker Buehler as an ace as his high strikeout rates weren’t driven by a high SwStk% as much as other names, which always worried me. But I thought perhaps he would make for a solid dart throw this season given a likely cheap price. Glad I didn’t end up rostering him! Even though he has underperformed, he has still posted poor skills, even worse than last year. Injuries may have permanently taken their toll here.
Zac Gallen has always been in a similar boat as Buehler to me, with middling SwStk% marks not really justifying the high strikeout rates. Eventually, the bottom fell out and his strikeout rate has cratered, though it had more to do with his SwStk% declining, rather than remaining stable with his strikeout rate dropping to match it. Both pitch models agree that his stuff hasn’t been above average since 2022, and his above average command in location just haven’t been enough to make up for it. He’ll no doubt record better results the rest of the way, but I wouldn’t be comfortable starting him in a shallow mixed league. His Jekyll and Hyde act this year also makes it very difficult to choose when to start and bench him.
So which group performs better over the rest of the season? Let’s get to the poll questions. Feel free to share your poll answers and why you voted the way you did.
Mike Podhorzer 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.
About half of that second bucket I expect to put up very little in the way of innings the rest of the year either do to injury or lack of opportunity. Some good guys in the remainder but some dreadful guys like Sentazela that are going to skew the score