While the NFBC Main Event garners most of the attention, there are a handful of leagues with even a larger entry fee ($2.5K to $15K). They get originally named “High Stakes Leagues” and this year there are nine of them. With so much money on the line, these fantasy managers are going to try to gain any advantage. Most of the time, these managers will be a week or two ahead of everyone else on their adds. Here are the players and some information on the ones added in four or more of these leagues. Read the rest of this entry »

One issue during the season is that the news cycle, even for projection-altering details, moves at such a fast clip. Or it’s a repeat of the box score. Or player movement news. Or a preview of the next game. I just don’t find many details during the season but here are a few times that some might find useful. Instead, I plan on putting out smaller and more timely news blurbs.

American League

Astros

• The Astros aren’t looking to replace José Abreu while they are still winning.

Baker receives Abreu-related questions routinely. His answers do not change. One of his responses in Milwaukee did, perhaps, illustrate the manager’s outlook on Abreu’s anemia.

“We’re still winning,” he said.

Until they aren’t, changes may be few. Abreu did inspire more confidence during a 1-for-4 showing on Monday, mashing two balls with 109 mph exit velocities or harder. He turned on Twins closer Jhoan Duran’s 103.6 mph fastball for a ninth-inning single, too. Games like this will only extend his runway further.

Read the rest of this entry »

7:32	Jeff Zimmerman:

Read the rest of this entry »

Last week, I examined if throwing too many four-seam fastballs led to a pitcher being predictable and getting hit around. What I noticed was that I needed to expand out past just four-seamers and include sinkers. Again, I failed to find a connection between fastball quality-and-quantity and weakly hit batted balls. Instead, I was able to determine some benchmarks to find good fastballs.

Through some observations, I believed that throwing too many fastballs, especially if they were of poor quality (e.g. slow, average spin), would get hit harder. I dug through the numbers just hoping for my thoughts to be verified but I found jack squat. Nothing. Read the rest of this entry »

In the article, I cover the players using CBS’s (about 40% or less initial roster rate) and Yahoo’s ADD/DROP rates. Both hosting sites have the option for daily and weekly waiver wire adds. CBS uses a weekly change while Yahoo looks at the last 24 hours. Yahoo is a great snapshot of right now while CBS ensures hot targets from early in the week aren’t missed. The players are ordered for redraft leagues by my rest-of-season preference grouped by starters, relievers, and hitters. Read the rest of this entry »

American League

Angels

• Hunter Renfroe has sat in two of the last five games. He might have joined Taylor Ward and Mickey Moniak in an timeshare for two outfield spots.

• Jared Walsh (vs RHP) and Luis Rengifo (vs LHP) are in a platoon.

Astros

• Jake Meyers (.730 OPS), Chas McCormick (.710 OPS), and Corey Julks (.673 OPS) are sharing two outfield spots. Read the rest of this entry »

While the NFBC Main Event garners most of the attention, there are a handful of leagues with even a larger entry fee ($2.5K to $15K). They get originally named “High Stakes Leagues” and this year there are nine of them. With so much money on the line, these fantasy managers are going to try to gain any advantage. Most of the time, these managers will be a week or two ahead of everyone else on their adds. Here are the players and some information on the ones added in four or more of these leagues. Read the rest of this entry »

American League

Angels

• Taylor Ward and Mickey Moniak are splitting time in left field.

• Luis Rengifo, Gio Urshela, Brandon Drury, and Jared Walsh are sharing three infield spots. Read the rest of this entry »

Updated on Sunday morning. Added a few players and moved a few players around.

Note: Starting today (Friday), my Memorial Day weekend is planned out for me and I’m just along for the ride. Here are my weekly waiver wire ranks and I’ll update them when I have time. I’ll post the updates here at the top and in the excerpt to let people know if/when there have been any changes. I’m going to be very bare-bones with no blurbs, but I’ll add more info as I find time.

In the article, I cover the players using CBS’s (about 40% or less initial roster rate) and Yahoo’s ADD/DROP rates. Both hosting sites have the option for daily and weekly waiver wire adds. CBS uses a weekly change while Yahoo looks at the last 24 hours. Yahoo is a great snapshot of right now while CBS ensures hot targets from early in the week aren’t missed. The players are ordered for redraft leagues by my rest-of-season preference grouped by starters, relievers, and hitters. Read the rest of this entry »

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.