Yesterday, I discussed six fantasy relevant starting pitchers who have most underperformed their SIERA marks. Now let’s flip over to the overperformers.

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Two months into the season is a good time to evaluate your team, its strengths and weaknesses. You usually can never have enough pitching, as there’s always someone who gets injured, suddenly loses velocity or effectiveness, and then you’re scrambling. So let’s review the starting pitchers that have underperformed their SIERA marks the most so far. This could be a good target list to trade for that includes pitchers that shouldn’t cost much to acquire.

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After rethinking what my Friday column looks like a few weeks ago, I wrote up some under-rostered relievers as the first step in reimagining this Tuesday column. This week, I’ll be looking at a few under-rostered starters who have been performing particularly well the past few weeks. I’ve split the article into pitchers rostered in more than and less than 60% of all Ottoneu leagues to give a good spread of shallow and deep options.

Roster > 60%

You’ve probably heard that Michael Kopech has finally figured things out after really struggling to start off the year. Through his first eight outings, he had a 5.74 ERA that paled in comparison to his ghastly 7.30 FIP. He had allowed a whopping 12 home runs during that stretch, though his xFIP wasn’t much better at 5.78. His strikeout and walk rates were trending the wrong direction and he looked thoroughly cooked. Then, on May 19, he held the Royals scoreless across eight innings, striking out 10 and walking no one. Granted, it doesn’t take an ace to keep Kansas City off the scoreboard but Kopech has proven that it wasn’t just a fluke against a weak opponent. Across his last four starts, including the one against the Royals, he’s posted a 2.05 ERA backed by a 2.56 FIP and it looks like all his command woes have been put behind him; he’s running an outstanding 9.5 strikeout-to-walk ratio during this hot stretch. This stretch of success seemingly stems from a mechanical adjustment to reassert his talent.

Miles Mikolas has also put a rough start to the season behind him. Through his first five starts, his ERA and FIP stood at 7.46 and 5.49, respectively. Since then, they’re down to 1.82 and 2.98 in eight starts and he’s been particularly effective over his last three outings. I don’t think there’s any one thing driving his recent success, it’s simply a return to his ultra-efficient profile after a rough five start stretch in April.

Over his last four starts, Jack Flaherty has posted a 1.88 ERA and a 2.45 FIP with a decent 3.13 strikeout-to-walk ratio. That’s an improvement over his early season work that suffered from far too many free passes. The biggest difference has been a greater reliance on his fastball; he threw his heater around 37% of the time through the first eight starts of the season and that’s jumped up ten points over the last four. Tangibly, that’s resulted in a nearly five point increase in his zone rate and just eight walks during this stretch.

Clarke Schmidt just tossed his best start of the season against the Mariners last week, holding them scoreless over 5.2 innings with seven strikeouts. Across his last three starts, he holds a 2.07 FIP with a 3.40 strikeout-to-walk ratio. To me, the perception of Schmidt’s struggles this year are out of step with his peripherals — his strikeout and walk rates during this streak of strong starts are right in line with his seasonal averages — but two ugly starts against the Rays and Rangers where he allowed 12 runs marr his overall line. I think his improvement is linked to how he’s using his sweeper. In his first nine starts of the year, he located his big breaking ball in the zone a little over 50% of the time. That rate has fallen three points over his last three starts and his whiff rate with the pitch has seen a five point increase up to 32.5%.

Roster < 60%

Kyle Gibson has been a solid, if unexciting contributor for years. This season, his strikeout rate is down a bit, though it’s been offset by a drop in home runs allowed. A weird seven inning shutout against the Yankees a few weeks ago where he allowed two hits and four walks to go along with three strikeouts is throwing off his strikeout-minus-walk rate you see above. He’s actually been pretty good over his last four outings, with a 2.92 ERA and a 3.20 FIP.

Gibson’s teammate Dean Kremer has also been on a hot streak and it stretches all the way back to the beginning of May. Across his last six starts, he’s posted a 2.55 ERA and a 3.60 FIP with a pretty good 2.90 strikeout-to-walk ratio to back it up. He’s also done this against some of the best offenses in the league — the Braves, Rays, Angels, Blue Jays, Rangers, and Giants — which is a great sign for when he starts facing some weaker teams. His improvement likely stems from his fastball velocity which has now reached a career high of 94.9 mph on average.

A journeyman who has pitched in Korea in two separate stints, Ben Lively is making the most of his time in the majors with the Reds this year. Across four starts, he’s posted a 3.38 strikeout-to-walk ratio with a 3.33 ERA. The problem has been the home runs, particularly at home in the bandbox in Cincinnati; he’s allowed all five of his home runs at home which has caused his FIP to spike to 4.72. He’s a kitchen-sink righty with a fantastic slider fueling his high strikeout rate right now.

I had planned on writing up Alex Faedo in this space, but the Tigers just placed him on the Injured List with a finger injury. He suffers from the same problem as Lively: a fantastic strikeout-to-walk ratio is marred by far too many home runs allowed. Instead, I’ll highlight the prospect Detroit called up in Faedo’s place: Reese Olson. Command issues capped the potential ceiling of Olson despite possessing a wipeout slider. He threw that pitch a third of the time in his first major league start and it returned a 33.3% whiff rate. The thing to monitor for him will be his ability to locate his fastball. If he’s able to figure out his command issues, he’s got the deep repertoire to be able to produce in the Tigers rotation.

Yesterday, I shared and discussed six starting pitchers who have improved their average exit velocity (EV) against the most compared to 2022. While the correlation isn’t strong, there definitely is a positive correlation between EV and BABIP, whereby the higher the EV allowed, the higher the BABIP, and vice versa. Let’s now flip to the pitchers who have allowed a higher average EV this year.

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Since 2015, there’s been a small, but positive correlation (about 0.19) between average exit velocity (EV) against and BABIP. In other words, the higher the EV allowed, the higher the BABIP. Of course, there are many other factors involved, as the correlation isn’t very high, but it’s there. And all else equal, a pitcher does desire to induce soft contact versus hard. So let’s find out which starting pitchers have reduced their average EV marks the most compared to last season.

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Welcome back to the Ottoneu Starting Pitching Planner. Based on the Roster Resource Probables Grid, I’ve organized every starter slated to start next week into four categories: start, maybe, risky, and sit. The first and last category are pretty self-explanatory. Starters who fall into the “maybe” category are guys you could start if you need to keep up with the innings pitched pace in points leagues or need to hit your games started cap in head-to-head leagues; they’re good bets to turn in a decent start, but you shouldn’t automatically insert them into your lineup. If you’ve fallen behind on the innings pitched pace or you’re really starving for starts in a head-to-head matchup, you could turn to a “risky” starter or two.

I’ve also calculated a “Matchup Score” for each series using a straight combination of opponent’s home/away wOBA, opponent wOBA over the last 14 days, and the park factor for the ballpark the teams are playing in. It’s indexed so that 100 is average and anything above that is a favorable matchup and anything below is unfavorable. That matchup rating informs some of the sit/start recommendations I’m making, though the quality of the pitcher definitely takes precedence.

A few general schedule notes first:

• The Twins head out on a tough road trip next week with two tough AL East stops. Tropicana Field is pretty pitcher friendly which is why the matchup rating is so high against the best offense in the majors. Rogers Field is definitely not pitcher friendly and it’s only gotten more dangerous after the fences were moved this year. Start your Twins pitchers if you really need to but they’re all at risk of a blowup next week.
• The Orioles and Yankees get pretty easy schedules next week. Kyle Gibson has a two-start week that you should probably take advantage of and the rest of their rotation is a pretty good bet to produce against the Brewers and Royals. The Yankees host the White Sox and Red Sox next week and both of those opponents are hitting far worse on the road than in their hitter friendly home parks.
• The Rockies return home next week to host the Giants and Padres. That makes it pretty risky to start half the rotations from those two teams, though they do have nice matchups in their non-Coors series.
• The Cubs-Padres and Brewers-Reds series over the weekend will wrap around into Monday. They’re not reflected in the table above but the starters for those teams are listed in their proper categories.

Triston McKenzie and Aaron Civale are both on track to be activated from the IL over the weekend. Cal Quantrill was sent to the IL with a shoulder injury, though he probably would have been pushed out of a rotation spot anyway with both Tanner Bibee and Logan Allen thriving in the majors. Monitor McKenzie’s and Civale’s starts over the weekend to see how their stuff is holding up after their injuries. Both should be solid options going forward, though neither has a particularly easy matchup next week.

Notable two-start pitchers:

• Shane McClanahan
• Nestor Cortes
• Shane Bieber
• Framber Valdez
• Kyle Gibson
• Braxton Garrett
• Tony Gonsolin</li
• Lucas Giolito
• JP Sears

• Using Game-By-Game Fastball Velocity to Influence SP Sit/Start Decisions by Lucas Kelly
• MLB pitching models should incorporate recency, giving us an intriguing ranks update by Eno Sarris
• Baseball’s ‘Hot Hand’ Is Real by Rob Arthur and Greg Matthews

This article won’t take the place of my weekly RotoGraphs article and will not have much analysis. Instead, it will only provide data tables for your own analysis.

Quick Note: The data for this article is through games played on May 30th.

Relievers

Relievers only qualify to be placed in the table below if they have three appearances in the last 25 days. Though the time range is 25 days, the calculation only includes the three most recent appearances. In addition, I have isolated the table to relievers who have displayed an average change of .60 or greater in either direction (increase vs. decrease).

Starters

Starters only qualify to be placed in the table below if they have three appearances in the last 25 days and threw in at least the first inning in each of those appearances. The 25-day range should be wide enough to include three consecutive starts, but I may alter that time period in the future. Like in the above relievers table, I have isolated the table to starters who have displayed an average change of .60 or greater in either direction (increase vs. decrease). One final note, I do not remove pitchers who were recently injured. I think it’s advantageous to see how a pitcher’s velocity changed prior to injury. In today’s post, Julio Urías is a good example.

Welcome back to the Ottoneu Starting Pitching Planner. Based on the Roster Resource Probables Grid, I’ve organized every starter slated to start next week into four categories: start, maybe, risky, and sit. The first and last category are pretty self-explanatory. Starters who fall into the “maybe” category are guys you could start if you need to keep up with the innings pitched pace in points leagues or need to hit your games started cap in head-to-head leagues; they’re good bets to turn in a decent start, but you shouldn’t automatically insert them into your lineup. If you’ve fallen behind on the innings pitched pace or you’re really starving for starts in a head-to-head matchup, you could turn to a “risky” starter or two.

I’ve also calculated a “Matchup Score” for each series using a straight combination of opponent’s home/away wOBA, opponent wOBA over the last 14 days, and the park factor for the ballpark the teams are playing in. It’s indexed so that 100 is average and anything above that is a favorable matchup and anything below is unfavorable. That matchup rating informs some of the sit/start recommendations I’m making, though the quality of the pitcher definitely takes precedence.

A few general schedule notes first:

• The Brewers embark on a pretty tough road trip next week with stops in Toronto and Cincinnati. Both of those ballparks are incredibly conducive to home runs and both opponents play extremely well at home. Half of their rotation wouldn’t be recommended even if the matchup was good, but it’s probably a week where you’re more likely to sit Corbin Burnes and Freddy Peralta.
• After a tough pair of matchups on the road this week, the Marlins return home next week to host a couple of pretty weak lineups in their cavernous ballpark. The Orioles also have two easier matchups on the schedule which should help with some of your decision-making if you’re rostering any of their starters.
• The Royals and Cardinals have a weird two-game series next week followed by two off days in a row. It’s a scheduling quirk that’s a result of the holiday on Monday. St. Louis will get a chance for some extra rest during a week where they’re facing two weak teams.
• The Rockies are on the road next week and have a particularly enticing matchup in Kansas City next weekend giving you an opportunity to start Kyle Freeland or Austin Gomber — if you’re rostering them, you’ve been waiting for exactly this situation!

The Nationals offense has been hitting really well over the last two weeks and they’ve been pretty productive on the road this year making that matchup in Los Angeles particularly tough for the Dodgers. It doesn’t help that Dodger Stadium is pretty home run friendly either. After the Nats, the Yankees come to town which looks like an equally challenging series. Due to all the injuries sustained in their starting rotation, rookies Bobby Miller and Gavin Stone are lined up to take the ball in three games next week; all three look like pretty risky propositions even if the matchup against Washington seems enticing on paper.

The Mariners head to Texas to face the red hot Rangers next weekend which opens up some tough choices for a couple of their starters. Marco Gonzales is an easy sit, but Bryce Miller and Luis Castillo are scheduled to take the mound in the other two games and they’ll face a really strong offense. I’ve listed them both as starts since Miller has been simply dominant across his first five starts in the majors and Castillo looked much better in his last start against the A’s. I’d understand if you chose to avoid that matchup though since it looks really poor on paper.

Notable two-start pitchers:

• Joe Ryan
• Shane McClanahan
• Sandy Alcantara
• Zac Gallen
• Nathan Eovaldi
• Sonny Gray
• Anthony DeSclafani
• Bryce Miller
• Tyler Wells
• Logan Allen

The question came up when I examined David Peterson. I wondered if he was getting hit around because he was throwing a ton of subpar fastballs. Today, I’m back-testing the theory.

I had no idea what I was going to find but the results, positive or negative, will help to shape future studies. I examined starters from 2021 and 2022 who threw at least 20 innings (n=201). I limited the time frame to include the STUFFF metrics that have only been around that long. Also, I limited this study to guys who threw their four-seamer more than their sinker. I started with just four-seamers and stayed away from sinkers. The STUFFF metrics are separated based on pitch type so I wanted to stay in one lane.

The narrative behind four-seamers (or any fastball) would be that batters would familiarize themselves with these fastballs. I know that bad fastballs won’t generate as many strikeouts but do they get hit around more, especially if that’s all batters see.

Additionally, I included my pERA values which is only based on if the pitch misses (SwStr%) and the direction it is hit (GB%). These values might seem high but I don’t scale the value based on pitch type and fastballs generate fewer swings-and-misses than non-fastballs. It’s time to start the journey.

First, I grouped the pitchers by how far their ERA estimator was from their actual ERA. Here are the results.

There is a lot to unpack, but the biggest takeaways for me are

• The pitchers with higher than expected ERA threw more fastballs on average.
• The pitchers with higher-than-expected ERA generally had worse STUFFF.
• The pitchers with lower-than-expected ERA mixed in more sinkers.
• Fastball velocity didn’t matter. It still remains linked to strikeouts.

Here are two more groupings by HR/9 and BABIP.

The results are a little messier but the conclusions are close to being the same.

• The batters who got hit around threw a few more fastballs on average.
• The pitchers who got hit around had worse STUFFF.
• Fastball velocity or sinker/four-seam mix didn’t matter to over-or-under-perform batted ball metric.

The two major factors seem to be the usage rate and the STUFFF metrics.

After eyeballing the above tables, it seems like a usage under 40% along with a Stuff+ value under 90 and a Bot Stuff under 50. To see if these benchmarks work, I took the 2023 starters and grouped them.

The pitchers I expected to perform worse actually performed better. That’s suboptimal. I did find out what possibly didn’t work but it would be nice if the values were predictive. I ran one last comparison for future reference, here are the pitchers’ stats for if their ERA is above or below their ERA estimators so far this season.

The usage doesn’t matter this season but the STUFFF values show some signs worth continued investigation.

That’s enough failure for one article. Here is what I see needs to be done next.

• Sinkers will be included by weighting the results by usage. David Peterson mixes in some (bad) sinkers so maybe the combination brings more clarity.
• I’m going to attempt a fastball grade that takes into account the predictive values (STUFFF), pitch results (pERA), and batted ball results (pVAL). From some past work, I wasn’t a huge fan of pVALs but I think they might help show the possible disconnects between shape and results (e.g. ability to hide the ball).

While I didn’t come to any groundbreaking information, I found what not to believe and hopefully, I can improve the future results.

Yesterday, I reviewed and discussed the starting pitchers who have raised their SwStk% marks the most compared to 2022. Now let’s flip to the pitchers whose SwStk% marks have declined most. All else being equal, a lower rate of whiffs should result in a low strikeout rate and a higher ERA.

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