Below are the latest playing time changes for pitchers in the past week, with a couple of brutal pieces of news — Tommy John surgery for both Corbin Burnes and Jackson Jobe — the unfortunate headliners this week.

I started writing this week’s Big Kid Adds, and the article morphed into how to evaluate starters who have thrown just a few games (normal list of added players at the end of the article). With little information to go off besides prospect reports, it’s key to find the best talent before others.

For the four starters, I’ll use a simple FanGraphs query to collect the information I use when there is just a few games worth of data. Read the rest of this entry »

Below are the latest playing time changes for pitchers in the past week, highlighted by AJ Smith-Shawver’s season-ending injury that increases the importance of Grant Holmes and Bryce Elder in Atlanta’s rotation.

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. I should also note that I’ve updated the way I’m calculating the park factors for the two new minor league stadiums that the Athletics and Rays are playing in this year; I’m taking the one-year park factors from Statcast and regressing them towards neutral, with the one-year factors increasing in weight as more games are played in those stadiums (those series are still marked in yellow below).

Every week, I look through my rostered pitchers noting the worst ones and churn them out next week. This week, the Yusei Kikuchi stood out. Someone with a 3.06 ERA and his ERA estimators around 4.50. It was his ERA estimators throwing red flags, but I have other pitchers worse. It was his 1.52 WHIP, third worst among qualified starters behind Kyle Freeland (1.63) and Jack Kochanowicz (1.56). With WHIP being its own Roto category, it has as much weight as ERA but ERA is the mentioned multiple times more often than WHIP. I’m just going to create a simple WHIP to ERA conversion to put both on the same scale.

To get the conversion equation, I used the overall rankings for the NFBC’s Main Event (15 team) and Online Championship (12 team). With them, I ranked the WHIP and ERA values separately. I removed the the first and last 10% of values because the change for them isn’t linear.

With the tails removed and plotted the best remaining WHIP with the best remaining ERA. I did that for each one. Here are the plotted results.

The correlation is nearly perfect, so the correlation equations can be used to convert a WHIP to an ERA equivalent. Here is conversion table.

The results for the two league types are close so I’ll only use the Main Event information going forward. Besides the above table, I have created a public Google Sheet (copy by going to File -> Make a Copy) where a WHIP can be entered and an equivalent ERA is spit out.

Kikuchi’s 1.52 WHIP would be equivalent to a ~5.50 ERA. No one is starting/rostering a pitcher with a 5.50 ERA this deep into the season. The high WHIP can’t be ignored and I’m likely to move on where I can find decent options.

Besides Kikuchi, Here are the qualified pitchers who have a WHIP that does as much ratio damage as a 4.50 or worse ERA.

Gavin Williams and José Soriano have been devastating managers’ in the WHIP category but it doesn’t seem as bad with sub-4.00 ERA.

WHIP is probably one of the most misunderstood categories and hopefully I made it easier to understand an expectable value.

The search for pitching help is never ending. Between injuries and ineffectiveness, fantasy players are always on the lookout for pitchers who are performing well who can provide some reinforcements. There have been a bunch of unheralded starters compiling strong starts since the calendar rolled over to May. Here are eight who are rostered in less than 60% of all Ottoneu leagues.

I covered a couple of guys listed above the last time I ran this column: Chad Patrick and Chris Paddack. They’ve both continued to pitch excellently and what might have been a hot streak has now turned into a solid two months of production. Patrick’s fastball velocity has ticked up as the season has progressed and he’s seen his strikeout rate rise as a knock-on effect. Paddack hasn’t been as good as Patrick but he’s extended his stretch of starts with two or fewer runs allowed to five games now.

Ryne Nelson has gotten an opportunity to start recently as the Diamondbacks have dealt with a number of injuries to their roster. He was probably ticketed for a return to the bullpen with the impending return of Eduardo Rodriguez but Corbin Burnes’s elbow injury should give Nelson an extended look in the rotation. He had a nice stretch of starts during the second half of the season last year — a 3.05 ERA and a 3.14 FIP from the beginning of July through the end of the season — and the hope is that he can replicate that mini-breakout this year. He won’t strikeout that many leaving him at the whim of batted ball luck, but he’s proven he can find success with that profile in the past.

Sean Burke entered the season with a bit of helium thanks to an intriguing cup of coffee last year. He was the White Sox Opening Day starter and he tossed a six-inning scoreless gem in the first game of the year. Things went downhill from there; he allowed 22 runs over his next five starts and both his ERA and FIP were up over six. His next six appearances have been much better to the tune of a 2.73 ERA and a 4.26 FIP. He’s still struggling with his command but he’s managed to navigate the extra traffic. The other thing to note is that the White Sox used an opener in front of Burke in his last appearance. If they continue that trend, you should be aware of the Ottoneu rules surrounding openers/followers: bulk pitchers who come in after an opener only get points if they’re slotted into a RP slot since they’re making a relief appearance.

Bailey Falter has been on an impressive run of starts since the beginning of May; over his last six starts he’s allowed a total of four runs! The underlying peripherals look pretty ugly however as he’s struck out just 19 in 35.2 innings while walking 13. He’s surviving by suppressing every batted ball put in play against him. I wouldn’t trust that he’s going to continue this hot streak.

Ryan Yarbrough has been fantastic since the Yankees moved him to their starting rotation at the start of May. He’s allowed no more than two runs in any of his five starts and has produced a fantastic 4.8 strikeout-to-walk ratio. His changeup and sweeper are both returning whiff rates north of 40% and he’s emphasized his cutter in his pitch mix to keep right-handed batters at bay. One thing to note for Ottoneu players: he’s allowed a home run in four of his five starts which has held him back from truly racking up the points in this format.

If you’re really desperate for some innings, Germán Márquez has looked decent-ish over his last few starts after a particularly ugly start to the season. Even at his peak, his points per innings pitched never crossed over five since his home ballpark is so tough to pitch in. I will note that he’s allowed just four home runs this year and none since May 4.

After bouncing around four teams over the past year, Adrian Houser has caught on with the White Sox this May. His first three starts for Chicago have gone as well as could be expected; he’s allowed a total of three runs while running a decent 2.8 strikeout-to-walk ratio. He’s had spurts of effectiveness in the past while he was with Milwaukee and it’s possible he’s found something that works this year. He’s added a ton of horizontal movement to his changeup and is currently running a 52.9% whiff rate with that pitch. Monitor his performance over the next few weeks and see if that pitch is still as effective once batters have a better scouting report on it.

Studying the balance of plate discipline metrics on individual pitches can be fascinating. They tell a story, if you look closely enough. Read the rest of this entry »

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. I should also note that I’ve updated the way I’m calculating the park factors for the two new minor league stadiums that the Athletics and Rays are playing in this year; I’m taking the one-year park factors from Statcast and regressing them towards neutral, with the one-year factors increasing in weight as more games are played in those stadiums (those series are still marked in yellow below).

Below are the most significant playing time projection changes for pitchers for the past week, led by Jared Jones‘ season-ending elbow surgery that could keep him out for most or all of 2026, too.

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. I should also note that I’ve updated the way I’m calculating the park factors for the two new minor league stadiums that the Athletics and Rays are playing in this year; I’m taking the one-year park factors from Statcast and regressing them towards neutral, with the one-year factors increasing in weight as more games are played in those stadiums (those series are still marked in yellow below).