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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When I’m reviewing a breakout starting pitcher, especially one who has raised his strikeout rate, I want to see a SwStk% surge. I get skeptical of pitchers who increase their strikeout rate without a corresponding increase in SwStk%. The higher strikeout rate is therefore usually due to some combination of an increased called strike and/or foul strike rate, both of which aren’t as skills-driven as SwStk% is. So let’s review the pitchers who have increased their SwStk% the most compared to 2022. Have they also enjoyed an increased strikeout rate?

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Welcome back to the SP Drip— *record scratch* Wait, that headline doesn’t say “Drip.” After gathering feedback from across the Ottoneu universe, I’ve heard loud and clear that streaming recommendations — even in their adjusted form I presented in this biweekly column — just weren’t providing enough value for owners. Instead, they’re looking for sit/start recommendations further up the SP chain. Personally, I found that the same handful of pitchers ended up being recommended over and over again in the Drip — it turns out that the deep rosters of the format mean there are very few viable starters who are owned in less than half the leagues across Ottoneu. I’m still not sure what Tuesday’s article will look like moving forward, but on Fridays, you’ll get the full picture of the week ahead. Introducing the Ottoneu Starting Pitching Planner!

What I’ve done below is organize every starter on all 30 teams based on the Roster Resource Probables Grid and sorted them 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. As this is the first run of this new format, please let me know if there’s any feedback or questions.

A few general schedule notes first:

• The Red Sox have a couple of tough matchups on the West Coast in Los Angeles and Arizona. Angel Stadium is a home run heaven and the Angels are always dangerous with Mike Trout and Shohei Ohtani swinging big sticks, and the Diamondbacks have been one of the hottest teams in baseball recently.
• The Marlins also get to visit Angel Stadium but they have a date in Coors Field first. That means there are a bunch of solid Miami starters who have really poor recommendations this week and it’s a rough stretch for the rookie Eury Pérez.
• The White Sox will face the two worst offenses in baseball next week which means guys like Mike Clevinger and Michael Kopech are viable starters.
• The Rangers also have a pair of favorable matchups next week in Pittsburgh and Baltimore. Dane Dunning has been brilliant since joining the rotation and he gets a pair of starts in some cavernous ballparks.

Despite their fantastic record recently, the Dodgers offense has been particularly bad on the road this year and hasn’t been hitting all that well over the last two weeks either. That makes the matchup against the Rays next weekend particularly enticing for Tampa Bay starters. Tyler Glasnow is scheduled to come off the Injured List during that series and I want to rank him higher with the nice matchup to cushion his activation, but it’s so hard to predict what we’ll see from him after his spring injury.

The Mets travel to Coors Field next weekend and Max Scherzer and Justin Verlander are lined up to start two of those games. Neither one has been an automatic start this year anyway — both have dealt with injuries and Scherzer has been inconsistent when he’s been healthy. It’s tough to sit the pitchers you’ve invested a ton of your salary cap into, but I wouldn’t trust either of them in the thin air in Denver.

Notable two-start pitchers:

• Eduardo Rodriguez (@KCR, vCHW)
• Gerrit Cole (vBAL, vSDP)
• Dylan Cease (@CLE, @DET)
• Spencer Strider (vLAD, vPHI)
• Cristian Javier (@MIL, @OAK)
• Alex Cobb (@MIN, @MIL)
• Corbin Burnes (vHOU, vSFG)
• Luis Castillo (vOAK, vPIT)
• Dane Dunning (@PIT, @BAL)
• MacKenzie Gore (vSDP, @KCR)
• Brady Singer (vDET, vWSN)

I’m still in disbelief from a recent finding I made. It started with this comment in a recent article I wrote about STUFF:

How much WHIP changed in the two “Stuff” models was almost too good to be true. In both cases, the walk rate increased as a pitcher’s stuff got better, but the hit suppression was so large that the WHIP declined.

Well I was wrong about the hit suppression. I went back and found no link to BABIP. The difference was because WHIP is on an innings denominator and a strikeout removes the chance for a Hit and Walk. An out comes down to the random chance of a batted ball. I know it’s confusing so here is an example assuming a pitcher with a 9 K/9, 3 BB/9, and .300 BABIP and throws 6 IP/GS. Read the rest of this entry »