Author Archive

Yasmani Grandal Will Be Alright

Jay Biggerstaff-USA TODAY Sports

If you drafted Yasmani Grandal based on Steamer’s 2022 pre-season projections, you were likely preparing to play in an OBP league. Grandal was projected to finish the season with the tenth best (tied with Max Muncy) OBP at .373. The 2021 league average OBP was .317. If you were to now head over to our 2022 leaderboards, you would see Grandal is holding a disappointing .279. But, narrow down that leaderboard to only viewing qualified catchers. The first thing that you may notice is that there are only seven catchers on the list and that Grandal is one of them.

You’ll also notice that Grandal’s .279 OBP is third from the bottom, yet his 12.2% BB% ranks first (high), his 18.4% K% ranks second, and his 7.6% SwStr% (low) ranks first. He’s walking and he isn’t striking out. That marks off two of the three true outcomes. Homeruns, being the third true outcome, have not come more than twice for Grandal, and that coupled with a .210 BABIP and a .180 AVG have probably made those rostering Grandal feel a little uneasy. But, if those same fantasy managers are believers in regresión a la media, then they are sitting pretty.

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Bullpen Report: May 24, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

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Bullpen Report: May 22, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

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J.D. Davis is Getting Robbed

Vincent Carchietta-USA TODAY Sports

Mike Trout, Yordan Alvarez, Aaron Judge, and… J.D. Davis? As of this writing (5/14/22), Davis is fourth on the Statcast expected stats leaderboard behind three of the best sluggers in baseball. Sure, he has about less than half of the plate appearances (62) as those other three (average of 124), but his .454 xwOBA is bright red nonetheless. Sadly, Davis is only slugging .300. Compare that with Yordan Alvarez’s .697, and you wonder why I’m mentioning Davis and Alvarez in the same paragraph. Somehow, Alvarez is actually expected to be slugging even higher, .082 points higher to be exact. Davis? He’s expected to be slugging .313 points higher, or a total of .613. Davis holds the largest difference between his wOBA (.301) and his xwOBA (.454) among hitters with enough balls in play to qualify for the leaderboard. Ladies and gentlemen, the man has been getting robbed and I give you the first example:

That ball was struck at 102 mph at an angle of 14 degrees. The estimated batting average by Statcast’s combination of hit speed and angle was 0.714. While there was an infield shift on, the outfield alignment is listed as “Standard” in the data. But you don’t have to drill into any data at all after watching the video to realize the ball was smoked, it was just smoked right at an outfielder.

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Bullpen Report: May 17, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

Read the rest of this entry »


Bullpen Report: May 15, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

Read the rest of this entry »


Let’s Go Oppo!

Let’s begin with a nice oppo example from this past Sunday’s game in Philadelphia, where the Phillies took on Max Scherzer and the Mets:

A young Bryson Stott stays through the ball and knocks in an RBI by going oppo. In last week’s post, I built a model that combined data from our batted ball, statcast, and plate discipline leaderboards for a single point in time in the 2021 season, and used those metrics to target whether or not (a 0/1 binary target variable) a batter recorded a hit the following day. While I pointed out that there was just too little data training the model I was using, I did think it interesting that Oppo% was the most important variable when predicting a hit. Was I on to something? Is predicting a hit as simple as looking at who goes oppo the most?

You and I both know there’s nothing simple about getting a hit, but Oppo% seems like an important statistic when we’re talking about singles. In one of my favorite offbeat fantasy baseball games, Beat The Streak, players must choose one player each day to get a hit and do that successfully for 56 days in order to win a Scrooge McDuck fortune ($5.6 mill). So, this week’s post is all about Oppo%; what it means, what it tells us about a player’s ability to record a hit, and if we can really use it to build out our own swimming pool of gold coins. So let’s take a good look at Oppo% and what it might mean for predicting a hit. Here are your current oppo leaders (qualified hitters) along with their batting average, BABIP, and slugging so far this season:

2022 Oppo% Leaders
Name PA Oppo% AVG BABIP SLG
Yoshi Tsutsugo 92 42.1% 0.203 0.250 0.270
Myles Straw 127 38.9% 0.255 0.311 0.327
Willson Contreras 100 38.8% 0.279 0.328 0.477
Sheldon Neuse 104 38.8% 0.305 0.415 0.411
Seiya Suzuki 111 37.1% 0.247 0.328 0.473
Nicky Lopez 91 36.9% 0.221 0.266 0.260
J.D. Martinez 92 36.5% 0.294 0.367 0.518
Randal Grichuk 96 36.5% 0.281 0.356 0.449
Aaron Hicks 87 35.3% 0.250 0.327 0.294
Freddie Freeman 119 34.9% 0.317 0.349 0.515
MLB Average 24.6% 0.233 0.282 0.371
Among qualified hitters as of 5/10/22.

Each one of these hitters, besides Tsutsugo and Lopez, is hitting above league average according to batting average and BABIP. Remove the two hitters already mentioned, remove Hicks and Straw, and everyone left is slugging above average. This is a good group of hitters. But, I don’t know that beyond Freeman and J.D. Martinez I would be trusting anyone from this group with all my gold coins. In other words, I wouldn’t feel confident in making my daily hit prediction by sorting descending on Oppo%…yet.

As always, people will shout, it’s not enough data! They’re right, but they don’t need to shout. This issue was present in my model from last week’s post. Just a snapshot of one day in baseball doesn’t do the full game justice. I went back and added more data to the model I built previously (still not enough, but we’ll call it “improved”) and Oppo% decreased in importance, but stayed in the mix as an important variable to consider when predicting a hit.

With a larger dataset, the higher feature importances were taken over by things like HardHit%, Barrel%, maxEV, and LD%, which we should expect. In fact, for those who read last week’s post, here is an updated feature importance chart for the same model with more data to train on:

model var importance 2

This isn’t as interpretable as a regression model. A random forest creates lots of little decision trees that act as voters to make predictions. Therefore, the model can be difficult to interpret, because you would have to go look at all the little trees being built to get a full picture of how the predictions are being made. In this example, you can see that HardHit% is the first most important feature and IFFB% is the second most. But good hitters should look to hit the ball harder and pop up in the infield less, yet their importances are measured almost equally? That’s because hitting in-field fly balls is just as bad for your hit-ability as hitting the ball hard is good for your hit ability. The 0.06 feature importance isn’t all that interpretable without that background knowledge. We know it’s important, but what does important mean? Furthermore, if we’re trying to figure out how important Oppo% is to a batter getting a hit, more data tells us that it is less important. What the heck does that mean?! Whoaaa! Relax. Take a breath. Watch this video:

While going oppo is no longer as important in a model with a larger dataset, I still see its importance, don’t you? Instead of worrying about fancy models and sample sizes, let’s just take a moment to look at Oppo% in the context of the 2021 season. Here’s a breakdown of batted ball data from the 2021 full season with a 170 PA threshold and how hard, medium, or soft the balls were hit:

Batted Ball Break Downs 2021
Soft Med Hard BABIP
Oppo 24.4 52.8 22.8 0.300
Pull 12.6 50.3 37.1 0.282
Cent 15.2 51.7 33.1 0.296
Among hitters with at least 170 PAs

Opposite hit balls in play were hit softly more often, hit hard less often, but had a higher BABIP than both pulled and centered balls in play. Wild! Want more? How about adding in a little contact type data:

Batted Ball Break Downs with Contact Type 2021
LD GB FB
Oppo 21.6 21.5 56.9
Pull 20.5 57.7 21.8
Cent 20.2 41 38.8
Among hitters with at least 170 PAs
Now, opposite-field batted balls had higher fly ball rates than pulled balls? That’s interesting. My guess is that those are the jam shots that result in fly ball, easy outs. Take a look at an example from the 2021 leader in opposite hit fly balls, Ozzie Albies:

…but sometimes, this happens:

What is most highly correlated with Oppo%? BABIP for the win! A correlation of 0.4 doesn’t make you want to run to pick Yoshi Tsutsugo every day, but it is interesting nonetheless. A small negative correlation with SLG seems strange, but perhaps that’s because unless you drill the ball down the line, chances are your opposite-field hit won’t get you a ton of extra bases.

Oppo Correlation Heatmap

Don’t stare at the correlation chart for too long or you may never get up from your desk chair. Let me instead steer your focus to another table, showing production by contact type:

2022 Production by Batted Ball Direction
SLG ISO wRC+
Cent 0.423 0.125 107
Oppo 0.452 0.135 120
Pull 0.588 0.267 163
Among hitters with at least 70 PAs

Contradictory to what the correlation chart makes us believe when looking at the negative correlation between Oppo% and SLG, it looks like so far this season Oppo% are better for slugging than center struck balls in play. My hypothesis about balls knocked down the line driving those extra-base hits stands. Here’s an example:

As opposed to this ball hit right up the middle into a strategic defensive alignment:

Somehow, we’ve made it this far without talking about the shift, but I won’t dive into that today. Clearly, it must have an impact. If a pull shift is on and a hitter goes oppo, that’s great. But it’s not necessarily the norm. Wander Franco leads the league in hits when going oppo against a traditional shift with 12. He has 38 hits in total.

So does anything that I’ve laid out here today help us understand if going oppo more often brings in more hits? Not really. One of the biggest reasons for that, I believe, is that the league adjusts. If you beat the shift too many times, you stop getting shifted on and it’s harder to get a soft, oppo hit. To drive this point home, I used the same data that built out my feature importances on a more standard logistic regression model. I controlled for multicollinearity (which I know FanGraphs readers love) and passed in the resultant variables, again, targeting a binary hit or not hit variable and Oppo% was found to have a p-value of 0.485 making it above a 0.05 threshold and therefore an insignificant predictor. The variables that were found to be significant? Zone% and EV.

So, today (or maybe tomorrow), when you go to make your Beat The Streak picks, don’t bank on hitters who go oppo. Just try to enjoy the visual that comes from a hitter going oppo. Instead, look for players who barrel and hit the snot out of the ball, and who get pitches in the zone. But, then again, doing something like this will play:


Bullpen Report: May 10, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

Read the rest of this entry »


Bullpen Report: May 8, 2022

The 2022 version of Bullpen Report includes five different sections, as well as the closer chart, which can be found at the bottom of the page.

We will always include a link to the full Closer Depth Chart at the bottom of the Bullpen Report each day. It’s also accessible from the RosterResource drop-down menu and from any RosterResource page. Please let us know what you think.

  1. Notable Workloads: Primary closers or valuable members of a closer committee who have been deemed unavailable or likely unavailable for the current day due to recent workload.
  2. Injury News
  3. Outlier Saves: Explanation for a non-closer earning a save during the previous day.
  4. Committee Clarity: Notes on a closer committee that clarify a pitcher’s standing in the group.
  5. Losing A Grip: Struggling closers who could be on the hot seat.

The “RosterResource” link will take you to the corresponding team’s RosterResource depth chart, which will give you a better picture of the full bullpen and results of the previous six days (pitch count, save, hold, win, loss, blown save).

Click HERE to view the full Closer Depth Chart.

Read the rest of this entry »


Hit Model Experimentation

Choose one batter to get a hit in tomorrow’s games. You can choose any batter you’d like. This game is simple. This game is called Beat the Streak. This game is hard. The trick is that you need to do it 56 times in a row. As of this writing, there have been 743 games played and 27,440 at-bats recorded in 2022. You can only choose one per day, however, and currently, the leader of the Beat the Streak challenge has chosen 29 consecutive hitters to hit. They are just over halfway there. I enjoy playing this game, but it can be really demoralizing, and I’m just doing it from my couch, relying on other people to get a hit. I can’t imagine what it’s like to have a stadium full of people yelling at you and then actually trying to get a real hit. I’ve written a few times about a model I’m using to aid in the choosing of my daily picks, but I’m starting to wonder if there’s a better way. It would be nice to just look at one or two metrics that help decide, rather than running a daily model, merging matchups, and splicing in park factors. In this post, I’ll walk through an experimental process that simply asks the question, what 2022 season statistics from the leaderboards here at FanGraphs can help us choose likely hitters.

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