• 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.

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, Drew Rasmussen is a good example.

I recently joined a men’s 30+ hardball league because, apparently, I love the bitter taste of failure. I felt like a superstar when I left my local sporting goods store with a scroll of a receipt and some fresh gear that would certainly make me, at least, look like I know what I’m doing out there. In my first at-bat, I struck out swinging, missing on a changeup by a country mile. This pitcher knew what he was doing.

He saw me whiff on a heater, threw it again and again as I timed it up and fouled off a few, changed pace and sent me back to the dugout, head down and red-faced. It was hard to time up. I’m serious. Now, replace that 75 MPH heater coming from a former D3 college pitcher with a 102 MPH heater coming from a man they call “The Mountain” and I would have certainly been found in the fetal position on the right side of the batter’s box.

Professional hitters, however, are used to this kind of thing. But, even they struggle. It’s all relative I suppose. Let’s take a look at a hitter, White Sox rookie Oscar Colás, trying to time up Félix Bautista on April 16th:

Colás quickly fouled one off and got the bat on the ball. But, prior to that, he took a ball up and in. The foul ball was his second look at Bautista’s four-seamer and waiting for pitch number three, he sat at 1-1. At this point, Colás saw two fastballs and it couldn’t have hurt to see one more. He took another ball, again the four-seamer, and got ahead in the count, 2-1. Three four-seamers down, Colás must have been feeling like he had Bautista timed. But, wait, doesn’t Bautista have a devastating splitter? That’s what the scouting reports said at least. Maybe that’s coming next? Nope:

Another heater and Colas barely got a hold it, but he was given another opportunity to time it up. Now at 2-2, he was thrown yet another heater and put it in play:

So when oh when does Bautista throw his splitter? At this point in the inning, Bautista threw six straight four-seam fastballs. He had his splitter ready and waiting, but the next batter, Seby Zavala didn’t get to see one. Instead, he was thrown one four-seamer and whiffed, then another that he put in play for a base hit. That means the four-seam count now came to eight in a row and hitters were catching on.

Early this season Orioles broadcasters have continually mentioned that Bautista, who got a late start to spring training due to trouble with his knee and shoulder, just hasn’t yet found the splitter. Stuff+ has given us a new way to look at whether a pitcher has or does not have a certain pitch. Let’s take a look at Bautista’s game-by-game splitter Stuff+ prior to this April 16th outing:

He may not have fully had it in his first few appearances, but the pitch was trending up. For context, the league average Stuff+ on a splitter among all relievers in 2023 currently sits at 103. There were only two games in this early time span where Bautista was below that mark. Prior to this April 16th appearance “The Mountain” started to find his groove with back-to-back appearances above 140. Coming off of two appearances with the splitter working and he hadn’t yet thrown it to a single batter in this game in question. But, just like a brilliant closer does, he waited for the perfect time.

Lenyn Sosa came to bat with two outs, having seen his teammates time up fastballs up in the zone, ready to attack. After a first pitch called strike on a four-seamer, perhaps Sosa was lulled into thinking it was just a fastball kind of day for Bautista. Wrong. The next pitch thrown to Sosa was a totally spiked splitter. In all honesty, it was spiked so hard that Sosa may have not have even identified it as a splitter. The next one, however, was gold:

Bautista then capped off his performance with a swinging strike on an unhittable splitter:

Bringing in the rest of Bautista’s appearances this season (last night’s (5/4) data hasn’t come in yet), we can see that he reached a peak in this April 16th game and in his next appearance on the 18th, but then came back down to earth a bit. What happened on the 29th? Four splitters that looked good, but certainly don’t look 322 Stuff+ good:

Splitter 1
Splitter 2
Splitter 3
Splitter 4

Splitter #1 was a non-competitive pitch. Splitter #2 earned a swinging strike, but it was left up in the zone and seems like it could have been sent for a ride. Splitter #3 was a big miss. Splitter #4 was a really good pitch and an even better take. All together it is unclear why these four splitters read at obscure/outlier levels, but perhaps there’s something going wrong in the data. Regardless, and what does seem clear, is there’s some potential for monitoring individual, put away pitches prior to matchups for both fantasy and real-life players. There’s a lot here that needs to be worked out, mostly creating a rolling average chart, quality checking game-by-game Stuff+ measures, and monitoring game-by-game Stuff+ to see if there’s any connection, not from a performance standpoint, but from a usage standpoint. I would like to answer the question, does an individual pitch’s Stuff+ measurement in the game prior, lead to increased usage in the following? For now, Bautista seems to be finding a devastating pitch and we’ll have to see how he utilizes it going forward.

Using baseball-savant data and some Python code, I have written a script that will loop through a pitcher’s three most recent appearances and flag any pitcher who has shown an increase in their fastball velocity. In raw form, it looks something like this:

Looking at the table above we can see that each of these three pitchers increased their fastball (“FF” in savant data) consistently over their last three appearances. Don’t believe me? You can check my work with Savant visualizations:

While I wrote more specifically about the merits of paying close attention to game-by-game fastball increases, quoting many other studies and great pieces along the way, I won’t be writing about it again here. Instead, I’ll simply show you a list of the starters and relievers who have increased game-by-game average velocity on their four-seamers and hope that you can take it from there. Sure, you could scroll through stacks of player pages to find players who have increased velocity until the cows come home, or you could write some code that will detect those increases and flag those players for you. I chose the second way. If you find it useful, I’ll do it on a more regular basis. That’s it. This post is more about the data than the words:

In deeper leagues, strong non-closer relievers can earn positive fantasy value. Every year, a slew of relievers seemingly pop up out of nowhere or take a giant step forward and become elite. Some of them eventually steal the closer role or record a couple of saves. So it pays to monitor their velocity readings as well. Today, I’ll share five relievers whose four-seam fastball velocity is up most compared to last year. Since we’re dealing with tiny samples here, I limited the search to just four-seamers and 10 pitches thrown during both 2022 and 2023.

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Here’s a list of relief pitchers, provided by Roster Resource, who could potentially earn saves and fill the closer role for the White Sox in 2023:

Reynaldo López
Kendall Graveman
Aaron Bummer
Joe Kelly
Jake Diekman

Which did you take for your fantasy team? López and Graveman are the relievers on this list who currently have the black border around their names that signifies shared closer duties on the Bullpen Report (now streaming). Those who chose Reynaldo López were victory-dancing all around the living room on opening day as the 29-year-old Southside reliever recorded his first career save. It wasn’t a dominant performance by any stretch as the big righty gave up a monster home run, but to be fair, it was a Yordan Alvarez home run:

At the end of last season, I wrote about López’s incredibly low FIP and argued that it was unsustainably low due to an unrealistic HR/FB rate. His 2022 HR/9 in 63.1 innings of relief was 0.1, he only gave up one homerun all season. In his first appearance as a reliever in 2023, López made me seem like a smart guy. So that’s it, right? López is the same reliever he was last year, except now he’ll be eaten up by the regression monster. Not so fast. Check out his increased velocity so far in 2023:

That much of a velocity increase really stands out and it comes on top of the increased velocity he displayed last year as he transitioned more into a full-time reliever. López has always been a hard thrower relying on his fastball and while he throws a curveball and a changeup, it’s the changeup that has been his best secondary offering. He has never really leaned on the pitch too heavily, throwing it 3.7% of the time in 2022, but the pitch earned a 15.2% swinging-strike rate (PitcherList) last season. That’s better than the league average swinging-strike rate on changeups among relievers, 13.9%. Even it has seen increased velocity so far in 2023:

The last time I wrote about López I noted the increased velocity on each of these pitches and how that led to increased whiff rates. Now, López has added even more velocity and a big question is, can he continue to add velocity without sacrificing control? His strikeout rates have been on the rise and so has his command (K/BB), but how will the added velo and increased appearances in high-leverage situations affect his ability to command the strike zone?

He was put to an early test on Sunday (4/2) afternoon when he entered the bottom of the ninth with a five-run lead and things got shaky. After walking the lead-off man, César Salazar, López threw a wild one that let him take second:

After another walk to Jeremy Peña, López got Alex Bregman swinging on a 100 mph fastball:

Even though López got out number two on a Kyle Tucker fly ball, he gave up two rbi singles thereafter, balked a runner over to the third base, and made his manager bite his nails. Things finally came to a close with another fly ball, this time without leaving the infield. So, while increased velocity is great, López’s command doesn’t look locked in just yet and he has a history of high walk rates. In 2020, his BB% crept up to 12.4% in his 26.1 innings as a starter. The 2022 league average BB% among starters was 7.5%. That seems to always be the “Strange Case of Dr Jekyll and Mr Hyde” for López; good, hard stuff, but touchy control. But, Reynaldo López is no longer a starter. Now, he has the freedom to focus his efforts on short, high-leverage stints, letting his velocity and stuff challenge hitters. For those of you who have fully converted to the ways of Stuff+, here are López’s early 2023 numbers:

stf+ FA – 148
stf+ SL – 133
stf+ CH – 108

While I don’t really know what those numbers mean after two full innings, they are all pretty high. I assume that’s good. As with all things, we’ll just have to wait and see what happens. I’m rooting for López and if he’s available in any of my leagues, I’m adding him. White Sox manager Pedro Grifol has been impressed with Reynaldo López calling him a “special talent”, but he hasn’t named any reliever as the team’s closer in Liam Hendrik’s absence and that will likely be the case all season. Reynaldo López’s potential has always been there and if fantasy managers have the roster spot available and can keep close tabs on him, I believe he has a lot of strikeout and save/hold/win upside for 2023.

Let’s shift now from Lucky/Unlucky, where we’ve been for the last three installments, to another gimmicky approach that has proven surprisingly useful over the seasons. We refer to the Quadrinity. Brief history lesson: long ago, Bret Sayre, then of Baseball Prospectus, posited that “the three skills that are most important to the art of pitching [are] getting strikeouts, reducing walks, and keeping the ball on the ground,” and that pitchers who can do those three things, as betokened by their above-average numbers in those categories, are worth the attention of those of us who care about such matters. He called this approach The Holy Trinity. And it made sense to us.

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I’ll wrap up my 2023 positional rankings with a look at the relief pitching market. You can find links to the rest of my rankings as well as Chad’s below. And a reminder, if you want a big picture view, you can see our ordinal Ottoneu rankings on the FanGraphs Fantasy Rankings Board.

Jake Mailhot’s Ottoneu Position Rankings: C | 1B | 2B | SS | 3B | OF | SP | RP
Chad Young’s Ottoneu Position Rankings: C | 1B | 2B | SS | 3B | OF | SP | RP

I really like the format of Chad’s ranking so I’ll try and emulate them a bit here. Here are few more notes about my process:

1. Tiers > Ranks. While these players will all be technically ranked ordinally, the tier they’re placed in really matters. The order within the tiers doesn’t matter as much, though that isn’t to imply that the players within each tier are interchangeable either.
2. Projected points. I’ve been building my own homebrewed projections for the past decade plus, ever since I started playing Ottoneu, and they form the basis for the rankings below. They’re nothing overly complicated; essentially just a MARCEL-esque projection using three years of historical data filtered through a rough aging curve and adjusted for the current run environment. I also include a collection of three public projection systems (ZiPS, Steamer, and PECOTA) to provide some additional context. That gives each player six data sources that form their projection.
3. P/IP is the basis. Points per innings pitched is the gold standard by which you should be evaluating pitchers in Ottoneu but there are plenty of factors that will affect a player’s ranking outside of their raw projection. Injury risk, projected playing time and role, age, and future value are all things that need to be taken into account when evaluating pitchers.
4. Dollar amounts are pre-inflation. The dollar amounts assigned to each tier are pre-inflation but are easily adjusted for your league context.

Rather than give notes on every player like Chad, I’ll give my general thoughts on the position below and discuss a handful of players I like more or less than his rankings. Let’s get into it.

NOTE: For the P/IP projection you see below, I’ve subtracted out points for saves and holds. Those two categories are notoriously fickle and extremely difficult to project. Evaluating relief pitchers based on their raw skills alone has usually worked out for me; teams generally give their highest leverage opportunities to their best bullpen arms, so the saves and holds should flow from those pitchers with the best skills. I’ve also included a column for each pitcher’s projected role based on the Roster Resource Depth Charts. Between those two factors, you should have a pretty solid grasp of how any given reliever should be valued.

Rather than pick a handful of guys to write up like in my previous rankings articles, I’m just going to give some general thoughts about building a bullpen in Ottoneu. There are two competing considerations when building your strategy: relievers are the most volatile part of your roster and they’re the most fungible players in the format. That means even if you invest heavily to build an elite bullpen, a team who spends $10 total on 5 or 6 relievers could outperform your team if they find the right mix of breakouts and sleepers. Be ready to churn through a bunch of relievers throughout the season as pitchers get hurt or lose their effectiveness. That process is so much easier if you’re not invested into a bunch of high priced closers.

While I’m not as extreme as Chad in my devaluation of relief pitchers, I’ve rarely rostered any of the elite closers in my time playing Ottoneu. Generally, I’ll allocate around $25-$30 of my salary cap to fill out my bullpen and that’s usually accomplished by picking a couple of guys from the middle tiers and then a bunch of $1-$3 fliers that I can churn through during the season.

Like I said above, skills really matter because teams will generally use their most skilled relievers in the highest leverage situations. That means Ottoneu Points and 4×4 owners can ignore the closer carousel game that 5×5 players are tied to. A pitcher’s place in the bullpen pecking order matters, but it should be a secondary consideration when you’re looking for potential breakouts on the waiver wire.

Back to our search for players whose granular stats suggest that last season’s fantasy-relevant stats make it appear that they were having better (or worse) seasons than they actually had. In our search for unlucky pitchers, we look for guys who had high BABIPs and HR/FB percentages but low Hard-Hit percentages. To find lucky pitchers, we look for the opposite. The idea, as we explained last week, is that those stats are out of alignment with each other, that the misalignment is a consequence of luck, and that, luck good or bad tending as it does to disappear, the pitchers in question will do better (or worse) this season. Last week, we did starting pitchers; this week, relievers.

A word about luck and relievers generally before we get started: as usual, the list of luckies is far more interesting to us fantasy baseball owners than the list of unluckies. That’s because we’re unduly interested in saves, and it doesn’t do us that much good to know that, say, the 6^th best pitcher in a team’s bullpen is in reality the 4^th best. So, while the group of unlucky relievers always yields some astonishments, they’re not going to do you much good unless it looks like they’ve got a shot at saves, like Brooks Raley 레일리 last season, or they might wind up in somebody’s starting rotation, like Austin Voth last season. So we’ll just mention four relief pitchers who were certainly unlucky last season, and whom you can expect to do better this season, but who don’t look like candidates to close games for their respective teams. These are: Jake Diekman (although it’s not inconceivable he gets some saves), Tommy Nance, Joel Payamps, and Victor Arano. If your draft is deep enough, by all means go after one of them. Otherwise:
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A summarized version of this post was originally presented as part of PitcherList’s PitchCon online baseball conference for charity to support the ALS Association.

Pitch location, especially pitch height, enables pitchers to augment hitters’ launch angles. This is hugely important for pitchers given that hitters exert outsized influence on exit velocities (EVs), while pitchers exert little influence on EV. As such, EV is more predictive of hitter success than launch angles are. Yet EV remains at the mercy of its launch angle counterpart; a 115-mph blast isn’t half as valuable on the ground as it is in the air. A pitcher can improve his chances of inducing those suboptimal launch angles by weaponizing optimal pitch locations.

There’s a corollary to this for pitchers: capital-S ‘Stuff’ is more predictive of pitcher success, yet it’s pitch location that primarily dictates the outcome of a pitch or plate appearance. Max Bay, now of the Astros’ R&D department, once said Stuff makes a pitcher “resilient” to bad locations–it allows more room for mistakes. But mistakes are still made, and for the majority of pitchers, they are made (or avoided) largely through pitch location.

How sensitive, then, is launch angle to pitch height? If we raise or lower a pitch by an inch or a foot, how much can we expect the resultant launch angle to change? How much can we expect rates of ground balls (GB%), line drives (LD%), fly balls (FB%), and pop-ups (PU%) to change? Read the rest of this entry »

Last week I detailed how I am preparing for an upcoming Ottoneu re-draft and how I set my hitter targets. In this post, I finish the job and detail my approach to targeting pitchers. I should note that this is an iterative process. It is necessary to go back and forth to figure out a good balance between hitting and pitching and so much of that is dictated by who you have on the free-agent list. Regardless, I’m a planner and need to set my targets ahead of time. I need to see what happens if Plan A fails and what Plan B really looks like. Sadly, I was never the kid in school who could just roll out of bed, head to the exam in their pajamas, and get an A without studying.

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