Archive for Roto

Even though the World Series has just started, sleeper season has arrived for we who laugh haughtily at the idea of an offseason. So, like any good tout, I’m busy preparing for the winter by searching for the players that you’ll wish you would’ve drafted this time next year.

But first, the asterisk. Let’s just skip any philosophical debates about what does or does not constitute a sleeper, as its definition is very user-dependent and can range from very broad (any player, regardless of round/price that you think will return a substantial ROI) to very narrow (the out-of-nowhere player that returns Mullins-esque value).

Let’s just say that I keep my definition pretty loose, looking for players that I think will return big value relative to their price but also ones who I’m confident will, for whatever reason (boring vet, bad team, etc), be easier to acquire. Low Q-rating guys, if you will. Read the rest of this entry »

What’s the first thing you do when you get a new spreadsheet? My answer; sort ascending, sort descending. That’s what I did on the 2021 pitching leaderboards. I looked at the plate discipline metrics for qualified pitchers and sorted the sheet by descending swinging-strike rate (SwStr%). The names I saw were not surprising. Corbin Burnes leads the group at 16.6%. He’s followed by Max Scherzer (15.9%) and Robbie Ray (15.5%). José Berríos is not in the top 30. In fact, when you sort the same list by ascending swinging-strike rate, he’s in the top 10, meaning he had one of the lowest swinging strike rates in the league (9.9% to be specific). The lowest swinging strike getters in the league this year were Adam Wainwright (8.1%), Chris Flexen 플렉센 (8.6%), and Dallas Keuchel (8.7%).

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You remember sorting baseball cards, right? You sorted them on anything; career stats, teams, season, jersey color. You got your sticky fingers all over those glossy, fresh pieces of thin cardboard and you just sorted away. Let’s think of a clustering algorithm called k-means clustering as that 8-year-old card sorter, only with a set of instructions. “Hey kid, here’s a bunch of cards from the last month of the season, back in 2020. Rather than your typical stat-lines, these cards show each player’s change in batted-ball and plate discipline from the first half of the month to the second half of the month. Here, take a look at Randy Arozarena”:

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Stealing bases continue to be less and less of a priority as baseball evolves in its current iteration but regardless, they remain an equal part of the equation in most rotisserie setups. This makes it more important than ever to find extra ways to find speed in the margins.

With 2021 in the books, I wanted to spend some time on stolen bases, so I’ll start with speed trends, both overall and team-by-team. And then finish up today looking at how some of the 2022 free-agent class might be affected by where they end up signing. In the next piece, I’ll move on to if the value of stolen bases in fantasy has changed and whether we should adjust how we draft for them going forward.

Before we get started, though, will everyone please bow their heads in a moment of silence for baseball thievery, as we’ll begin with a reading of the obituary. Read the rest of this entry »

With the fantasy season almost wrapped up, we might as well kick off the gossip about one of the offseason’s most salacious topics. Velo, baby. Who found some, who lost some, and everything in between.

This will all be heavily parsed before the next Opening Day, as changes in fastball velocity can often be reliable indicators for which pitchers are heading in which directions. And for those who like to draft early, velocity changes can serve as an early flag for possible targets or to identify the players that might first need a closer look.

With that in mind, here are the 32 starting pitchers who have increased their average fastball velocity by at least 0.5 mph since 2020 (minimum 200 fastballs in each season). Four-seamers and sinkers are grouped together and numbers are from pitches only thrown as a starting pitcher. Also included are 2019 velocities, as well as the percentile ranks from 2019-2021. Read the rest of this entry »

If you go to our 2021 Leaderboards, look at team relief pitcher stats, and sort by wins, you’ll see an interesting top five. The Rays, as you might have guessed, are holding the one spot by 10 wins at 56. They are followed by the Giants (46 wins), the Yankees (45 wins), and the Mets and Brewers (tied with 44 wins). If you’re like me and you’ve given up on your pitching ratios long, long ago, but are still fighting to win your league, you need wins and saves. Strikeouts are also welcome, too.

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Back in April, I conducted an analysis that looked at which category made the most sense to punt in roto-category scoring leagues. The results proved (somewhat) the offensive category most conducive to that strategy is stolen bases. That’s easy.

But you punted already. The punting is done. That ball ain’t coming back. Now you need to win, win, win! Therefore, you need home runs. When taking the last 15 games of the season from qualified hitters from 2015 to 2019, and limiting the dataset to just the three categories: home runs, runs, and RBI, I get the following correlations:

Homeruns, late in the season, have the highest sum of correlation. When batters hit home runs in small samples, they’re bringing runners in and scoring runs themselves. No duh. Here are three players that are projected (as of 9/20/21) to hit three more home runs according to our Depth Charts Rest of Season Projections. Now, I know you deep-league players are going to scoff and turn your nose up at these players who have not been available since your draft, but let’s give some love to the churn and burn, shallow leaguers, trying to squeeze out a few more category tens. 

C.J. Cron, Depth Charts ROS: 3 HR, 8 RBI, 6 R. ESPN Roster %: 70.9. 

Mike Podhorzer’s recent article encourages you to stack up on Rockies hitters for good reason. Pod did not include Cron because he assumed he would be gobbled up by your league mates already. But he recently went 0-for-11 before a two-hit night in Washington followed by another 0-for-3 night. There are surely managers out there that have dropped Cron and are unaware of the fact that he will be hitting in Colorado for nine games, as pointed out by Podhorzer. At home, Cron has batted .315 and on the road, has batted .226. While he is slumping as of late, his second-half .283 average is improved from his first-half .254 and his ROS projections could add a few more needed digits to your totals. 

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Miguel Sanó, Depth Charts ROS: 3 HR, 7 RBI, 6 R. ESPN Roster %: 50.2.

Sano is one of those players, like Cron, that you may just be able to pick up on the wire because other managers have lost faith. But, recently Sano has been on a tear going 6-for-21 with two home runs, four RBI, and five runs. What is there left to say about Sano? He ranks 11th in savant’s Brls/PA% and fourth in average exit velocity. He’s going to hit the ball hard and hopefully, he puts it over the fence three more times as projected. Luckily, you can grab him on a hot streak and, hopefully, won’t have to suffer through too many hitless games the rest of the way. 

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Tyler O’Neill, Depth Charts ROS: 3 HR, 7 RBI, 7 R. ESPN Roster %: 71.8.

This season I have fallen in love with xwOBA and its in-season predictive power. Tyler O’Neill ranks 16th in xwOBA among minimum balls in play qualified hitters. His teammate Paul Goldschmidt is just above him at 15th and since August 15th the Cardinals rank 9th in wOBA. With an offense clicking, a man that looks like he could hit a ball to Greenland, and projections to further the narrative, O’Neill should be rostered on your team the rest of the way.

Here’s how Justin Mason put it in last Friday’s edition of The Sleeper and the Bust:

 “This is one of the things people should really be thinking about, strategy-wise, the rest of the way…look for these opportunities where you can grab the follower in good matchups because as teams start to limit their guys…this is a time where you can really get some guys without going over any kind of starts limits.”

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Falling into a rut with your decisions can be deadly as the fantasy season comes to a close, particularly with pitchers and when you choose to start them. Depending on the starter and the team they’re facing, as well as your own categorical needs, matchups that might have been must-starts in July could sit in a gray area in September.

With that in mind, we’re going to take a look at starting pitchers who were in the top-50 for the first half but have fallen out since the break. And instead of just looking at drops in just fantasy categories, we’ll use total value and see where the drops have come and whether you should trust them as we come down the final championship stretch.

A few notes about calculated values:

• As you can’t use date ranges with our auction calculator, I calculated my own values using a standard z-score methodology. One difference is that values were made using only starting pitchers, scored using wins, strikeouts, ERA, and WHIP.
• In addition to ERA and WHIP, I’ve also included “xERA” and “xWHIP” but these are not expected values, rather they are the ratios weighted to the number of innings pitched.  A 3.50 ERA over 200 IP is better than a 3.50 ERA over 100 IP and a 2.25 ERA over 120 IP is better than a 2.00 ERA over 90 IP. Basically, xERA and xWHIP put these values on the same scale, allowing us to judge ratios on a 1-to-1 basis, regardless of innings pitched.

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Do the top starting pitchers on contending teams pitch more innings as the season goes on and their team fights for a playoff spot? Do the top starting pitchers on teams that are likely to clinch a playoff spot pitch less innings as the season goes on, to save their arms for the playoffs? Unfortunately, these questions arose in my mind after I traded a big bat for a front-line starter on a team that is sure to make the playoffs right at my league’s trade deadline. Was that a mistake? Should we value hitters more than top starters on teams likely to clinch early? Is that too many questions for an opening paragraph?

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