Archive for Daily Graphings

The Rockies are Hot. Is it Time to Re-evaluate?

Heading into this season, the NL West looked like a three-team race. That’s not completely fair — it looked like a one-team race for first with two other solid teams — but with a 16-team playoff field, somewhere between two and three teams from each division are headed to the playoffs, leaving it a three-team race for either two or three playoff spots.

Fifteen-ish games later, there are indeed three NL West teams in playoff position. The Dodgers are there, of course, and the Padres — no surprises here. But then there are the Colorado Rockies, 11-4 and leading the National League. It’s early — although with a quarter of the season already in the books for many teams, how early is up for debate. But regardless of the time of year, the Rockies are in first place, and I wanted to learn more.

One thing I could do to learn more is look at the Rockies’ individual performances, particularly on the pitching side. Charlie Blackmon is off to a hot start, though looking at a player with a .500 BABIP is rarely compelling 15 games into his season. For whatever reason, neither of those paths grabbed me. I thought I’d take a look at whether we could have expected this, and how surprised we should be. Read the rest of this entry »


Despite Outbreak, Marlins Skate to the Top of the NL East

“They already have their own helmets.” — NASA recruiter, The Right Stuff

When word arose that the Marlins were so desperate for players in the wake of a coronavirus outbreak that sidelined more than half of their Opening Day roster — and threatened the viability of the remainder of the 2020 season — that they were calling up an Olympic speed skater, it felt like the scene in The Right Stuff where Jeff Goldbum and Harry Shearer pitch President Dwight Eisenhower, Senator Lyndon B. Johnson, and NASA bigwigs on the possibility of using race car drivers, circus acrobats, and other daredevils as astronauts. “Besides turning left, I don’t think there’s much similarity,” said 30-year-old second baseman Eddy Alvarez of the similarity between baseball and short track speed skating, the sport in which he won a silver medal at the 2014 Winter Olympics as part of Team USA’s 5,000 meter relay team.

One of 17 players added to the Marlins’ active roster at various points last week as the team returned to play following the postponement of seven games due to the outbreak, Alvarez debuted on Wednesday against the Orioles, becoming the first Winter Olympian ever to reach the majors, and the first non-baseball Olympian to play in the majors since Jim Thorpe (1913-19). He entered Sunday having gone 0-for-9 with five strikeouts, but collected his first big league hit off Met ace Jacob deGrom, a hot smash that third baseman J.D. Davis could only stop. It was one of his three hits in the game, accompanied by another infield single off deGrom, and a double off Edwin Díaz; Alvarez reached on an error in his other plate appearance, and also added a stolen base and a great diving play at second base. Have a day, Eddy.

Despite Alvarez’s banner day, the Marlins lost, 4-2, but even so, a team that went 57-105 last year finished the weekend with a 7-3 record, putting them into a tie with the Braves atop the NL East. Just what in the name of Don Mattingly’s sideburns is going on?

By now, the contours of the Marlins’ mess, the largest outbreak on any team to date, are at least somewhat familiar. Just before their Opening Day game against the Phillies on July 24, they placed catcher Jorge Alfaro on the Injured List for undisclosed reasons. Then, just before playing the Phillies two days later, MLB Network’s Jon Heyman reported that starting pitcher José Ureña was scratched due to a positive test, and soon afterwards, he added first baseman/designated hitter Garret Cooper and right fielder Harold Ramirez to the list of positives. Even so, the team went ahead with the game; it was initially reported that they did so after deciding to play via a group text centered around shortstop Miguel Rojas (Phillies general manager Matt Klentak clarified that the decision came from MLB). A day later, ESPN’s Jeff Passan reported that eight more players and two coaches had tested positive, and the hits kept coming; by July 31, the count included a staggering 18 total players — more than half the active roster. Read the rest of this entry »


Sunday Notes: Kyle Higashioka is a Yankee Who Supports Liverpool FC

Kyle Higashioka never walks alone. The 30-year-old New York Yankees catcher is an ardent Liverpool FC supporter, having adopted the English Premier League team in 2007. A California prep at the time, Higashioka “stumbled across some Steven Gerrard highlight videos on YouTube” — this shortly after Liverpool had lost a Champions League final — and the die was cast. He’s been hooked ever since.

There is irony to his infatuation. Higashioka was drafted and signed by the Yankees in 2008, and two years later, Liverpool FC was purchased by the John Henry-led Fenway Sports Group. Yes, Higashioka lives and dies with a soccer club that operates within the Red Sox umbrella.

He’s not apologizing. Pointing out that Henry was once a minority owner of the Yankees, Higashioka stated that supporting a baseball team and supporting Liverpool are two completely different things. Moreover, he “started liking [Liverpool] before the Red Sox owners bought them; it’s kind of the luck of the draw who owns a team.”

A fair-weather fan he’s not. Along with staying true during the downtimes — “the Roy Hodgson days wren’t great” — Higashioka has gone out of his way to watch matches. Greenwich Mean Time and the Pacific Time Zone differ by eight hours.

“Living in California, I would meet up with the Orange County Liverpool Supporters Club,” explained the Huntington Beach native. “I remember an opening-week match where I met them at the pub at 4 a.m. to watch a game against Stoke.” Read the rest of this entry »


COVID-19 Schedule Adjustments Do Phillies No Favors

Due to the COVID-19 outbreaks on both the Marlins and Cardinals over the past few weeks, 15 games have been postponed so far this season that have yet to be made up. The postponements principally affect those two clubs due to their positive tests, but also the Phillies, who played against the Marlins as the outbreak happened, and several of those teams’ other scheduled opponents, including the Brewers, Tigers, Blue Jays, Orioles, and Yankees. With the Phillies resuming play on Monday, the Marlins playing on Tuesday, and the Cardinals set to play tonight against the Cubs, the league sent out a revised schedule with plans to make up all of the missed games.

Unfortunately, that new schedule has already hit a snag, as earlier today, Mark Saxon reported (and MLB confirmed) that tonight’s Cardinals game against the Cubs will be postponed due to an additional positive COVID-19 test result. Jesse Rogers added that there was at least one positive new test. It’s possible the Cardinals schedule will require further tinkering, which would likely come in the form of more doubleheaders. With that said, the current new plan looks like this:

Read the rest of this entry »


FanGraphs Prep: How Many Runs Should Have Scored?

This is the ninth in a series of baseball-themed lessons we’re calling FanGraphs Prep. In light of so many parents suddenly having their school-aged kids learning from home, we hope that these units offer a thoughtfully designed, baseball-themed supplement to the schoolwork your student might already be doing. The previous units can be found here.

Overview: A short unit centered on understanding the concept of expected runs and sequencing. In one of our earlier lessons, we learned about the relationship between runs and wins. Now, we’ll take that concept a step further and learn about expected runs and how they can tell us more about a team’s true talent.

Learning Objectives:

  • Use logic to determine all possible sequences of given events.
  • Use algebra to solve multiple equations.
  • Identify the effects of event sequencing in baseball.
  • Identify and apply the Pythagorean Expectation.
  • Explain the relationship between expected runs and wins.
  • Explain the uses of the Pythagorean Expectation using different inputs.

Target Grade-Level: 9-10

Daily Activities:

Day 1
In baseball, sequencing is the concept that the order of events on the field have an effect on run scoring results. Sometimes this concept is referred to as cluster luck because teams that cluster hits together appear more “lucky” than teams who don’t. This concept is pretty easy to demonstrate. Say a team collects three singles and one home run in a given inning. The order of those events will lead to very different outcomes. If the team hits the three singles before the home run, it will likely result in four runs. But if the home run is hit first with the three singles following, the likely result is fewer runs, perhaps as few as one. Read the rest of this entry »


Starting Pitcher Workloads Have Been Significantly Reduced in 2020

We’re two weeks into the long-delayed 2020 season, and one thing that sticks out thus far, beyond the schedule mayhem caused by COVID-19 outbreaks and the rule changes regarding extra innings and doubleheaders, is the plight of starting pitchers. Between the lengthy shutdown due to the coronavirus pandemic, during which players had no direct supervision, the abbreviated summer camp buildup, a flood of injuries, and expanded rosters, starting pitchers are pitching less than ever. Whether this is simply a continuation of a more long-term trend, an aberration founded in the unique circumstances of this season, or the start of a bigger paradigm shift, the numbers are worth tracking.

During the 2019 postseason, I noted that the period from 1998 to 2015 was fairly stable when it came to starting pitcher usage, even given a wide range in scoring environments and a whole lot of change within the game — expansion, the height of the PED scandal, the advent of PED testing, and the adoption of loose pitch count standards and innings limits on young pitchers. Since that time, we’ve seen starting pitchers throw fewer innings with each passing season, while at the same time generally improving their performance relative to the league.

Starting Pitcher Performance 2015-20
Season IP/GS Change K% BB% HR/9 ERA ERA- FIP FIP-
2015 5.81 -2.61% 19.5% 7.1% 1.06 4.10 103 4.03 102
2016 5.65 -2.8% 20.2% 7.7% 1.24 4.34 104 4.30 103
2017 5.51 -2.4% 20.6% 8.1% 1.34 4.49 103 4.48 103
2018 5.36 -2.8% 21.6% 8.0% 1.21 4.19 101 4.21 101
2019 5.18 -3.4% 22.3% 7.7% 1.44 4.54 101 4.51 100
2020 4.73 -8.7% 23.2% 8.6% 1.28 4.13 101 4.13 101
2020 data through August 5.

Bang! Already what sticks out is that this year, for the first time, starters are averaging fewer than five innings per turn, and their per-start average is down more than one full inning since 2015. What’s more, if this trend continues, it would be the biggest year-to-year drop in innings per start in the span, more than double the drop from 2018-19, and more than triple the other year-to-year drops within that span.

Over the years, a number of factors have driven that decrease, starting with deeper pitch counts, which are a byproduct of higher strikeout rates, as you can see in the table. There’s also the increased understanding of a few sabermetric concepts: starters are generally less effective facing batters for the third time in the game than prior; relievers are generally more effective facing batters for the first time than starters are in any of those appearances; and batters are less effective when they lack the platoon advantage. As starters’ workloads have decreased to account for those factors, their run prevention relative to the league has improved ever so slightly.

The drop-off from 2019 to ’20 is even steeper by a couple other measures:

Starting Pitcher Workloads 2015-20
Season IP/GS Change TBF/GS Change Pitches/GS Change
2015 5.81 -2.6% 24.5 -2.3% 93.1 -2.6%
2016 5.65 -2.8% 24.1 -2.0% 92.6 -0.6%
2017 5.51 -2.4% 23.6 -1.8% 91.5 -1.1%
2018 5.36 -2.8% 22.7 -3.9% 88.1 -3.8%
2019 5.18 -3.4% 22.1 -2.6% 86.4 -1.9%
2020 4.73 -8.7% 19.8 -10.6% 77.8 -9.9%
2020 data through August 5.

Read the rest of this entry »


Tyler Duffey as Object Lesson

As Pablo Picasso once said, “Good artists copy. Great artists steal.” Why start the article with that quote? To paraphrase my junior year English teacher Ms. Woods, “Ben, Advanced Placement readers expect essays that start with a quote, so it’s a safe way to start even if you think it’s trite.” Now, this isn’t an AP essay, but it is an article about how to write an article, so I feel comfortable getting a little bit more meta than usual.

It’s also, to be clear, still an article about baseball! More specifically, it’s about Tyler Duffey. He’s “breaking out” this year, in that he’s faced 16 batters and struck out 10 of them. That sample size? It’s too small to really say anything. Take a look at our handy sample size tool, and you’ll realize it in no time. And yet, we write these articles. Maybe it’s this piece on Chaz Roe, or this one on Tommy Kahnle getting good, or this one on Nick Anderson striking everybody out — over the years, they’ve become FanGraphs staples. How?

Here’s the secret: we’re not confining ourselves to that one sample. Sometimes, the pitcher was already good. Sometimes they had some good points and some bad points, and it looks like they changed the bad points. The idea, though, is that they had something going for them already, and the article is just catching the audience up to the reality on the ground.

Tyler Duffey is a great example of this. By pretty much any conceivable measure, he’s the best reliever in baseball so far this year. FIP? Tied for first with three guys who have only thrown an inning. xFIP? Second behind Colin Rea, one of the aforementioned one-inning wonders. Strikeout rate? First? Walk rate? Well, he hasn’t walked anybody, so that’s a yes.
Read the rest of this entry »


Luis Robert Is Doing a Lot of Things

Heading into 2019, opinions differed about how much of Luis Robert’s potential would manifest in games. Those opinions got considerably more uniform after a breakout season that saw Robert tap into his power. One of the top prospects heading into 2020 (he ranked seventh overall on our Top 100), Robert has helped a surging White Sox club filled with young talent get a good jump on the season. His .354/.415/.542 batting line has been good for a 177 wRC+, and he’s checking off every box on his scouting report for better or worse.

While defensive metrics don’t hold a lot of water this early in the year, the scouting reports on Robert are great. Eric Longenhagen has said Robert is a “plus-plus runner, and his instincts in center field are terrific.” Here’s a seemingly easy play Robert made early in the season:

The ball left the bat at more than 100 mph. Unless balls like that are hit right at a fielder, they’re usually a hit. Instead, Robert covered over 50 feet in under three seconds (the GIF above is 2.8 seconds long). Statcast tracks each batted ball’s hang time and the distance a player has to travel to get it. This is what Robert’s profile looks like:

The only balls Robert didn’t catch either hit the wall, or came with a 0% probability of making the play. Robert has been as advertised in the field. The same is true as a baserunner. Robert’s 29.4 feet per second sprint speed is near the top of the league, and he has four steals in five tries, finally getting caught last night. He also has three infield singles. Here’s one of those singles, where a slight hesitation on a routine ground ball allowed Robert to make it to first in under four seconds, essentially a Byron Buxton-level time:

Read the rest of this entry »


You Can’t Fit Yu Darvish Into a Pitch-Type Box

Yu Darvish’s calling card has always been his dizzying array of pitches. Hard cutter, slow cutter, curve, knuckle curve, slow curve, shuuto — if you can name it, he can probably throw it in a major league game. That’s not an obviously great skill, in the same way as Gerrit Cole’s overpowering fastball or Jacob deGrom’s ability to throw sliders in the mid 90’s with command, but the results speak for themselves: Darvish has the third-highest career strikeout rate of any starter, active or otherwise, and impressive run prevention numbers to boot: his career ERA- and FIP- both check in at a sterling 82.

So okay, fine, Yu Darvish has two calling cards: tons of pitches and the ability to use those pitches effectively. Let’s talk about the tons of pitches today, though, because they’re way more fun. Consider, if you will, the two systems we use to classify pitches. Darvish’s career looks like a bingo board on both, but they’re two very different bingo boards. First, our standard pitch types:

It’s a little bit of everything, with a heavy emphasis on cutters in the last two years. Meanwhile, the sliders have gotten slow — a near-career-low 79.9 mph, nearly as slow as his curveball, which has gotten fast. It’s a confusing mess. Next, take a look at pitch types per Pitch Info:

Rafts of sliders! More curveballs! The only thing the two systems seem to agree on is the 3.6% splitters, thrown at a dizzying 90 mph. You can’t see Pitch Info’s velocity numbers on here, but they’re divergent as well: these cutters are blazing, checking in at 92.3 mph, and the sliders are much faster than the first classification set, checking in at 86 mph.

What’s happening here is that the two systems don’t know what to do with Darvish’s array of breaking balls. Say, for the sake of argument, that Darvish throws seven different breaking balls, each with a different velocity and movement profile. Try to classify those using three buckets: cutter, slider, and curveball. Good luck! Here’s a pitch that Baseball Info Solutions, which doubles as our generic “Pitch Types” data source, classified as a cutter last night:

Looks like a cutter to me, or maybe a four-seamer that he over-cut inadvertently. It has a hair of glove-side break, which moves it from where O’Hearn thinks he’s swinging — middle-in fastball, a juicy first pitch target — to where he’s actually swinging, directly over the inside corner. At 93 mph, that’s a nasty pitch, no doubt, and it’s also pretty clearly a cut fastball. Darvish, who throws his four-seam fastball in the 95-96 mph range, is hardly throwing a 93 mph slider.

That was a gimme. How about this one?

Victor Caratini’s overzealous framing aside, that looks like a pretty different pitch to me. It’s slower, and bendier; if the last pitch had a hair of break, this one has an entire bearskin rug. It doesn’t have that cutter-esque ride, either. Just one problem: Darvish, by his own admission, throws two types of cutters. So maybe that’s a cutter too.

And what about this one?

Aside from Caratini’s framing paying off, that looks like a completely different pitch. It has as much vertical break as horizontal, and it’s 10 mph slower than the first cutter we looked at. Maybe this one’s a slider, then.

But what about this one, literally the previous pitch?

That’s even slower, but it has less drop; that looks more like a textbook slider, mostly glove-side break, though not a ton of break at that. East-West movement in the low 80s? Sounds like a slider to me. Before you go calling that a slider, though, consider this pitch, which was classified as a slider:

Gravity took this one far more than the last one, despite almost identical velocity. How can those two be the same pitch? And don’t go calling it a curve, either, because I’ve got one of those to show you, and it’s more North-South despite similar velocity:

And of course, Darvish throws two different types of curves — three, really, though we haven’t seen the extremely slow curve/eephus yet this year. Take a look at this majestic lollipop:

I just showed you seven different pitches. None of them were obviously the same if you look at the three critical elements of a pitch: velocity, vertical break, and horizontal break. Try fitting them into three buckets — cutter, slider, and curve — and you start to see the problems inherent in classifying Darvish’s pitches.

Still, even if you don’t have the right names for things, there’s often some internal logic. Take Shane Bieber’s new arsenal, for example. He calls his pitches a cutter, slider, and curve. I looked at them and saw two curves and a slider. We’ve since reclassified the “hard slider” to a cutter and the “hard curve” to a slider, which gives you this graph for all of his pitches in 2020:

If you ignore the colors and shapes, there are five distinct spots. Quibble all day about what to call them — and we here at FanGraphs love to quibble, don’t get me wrong — but Bieber does five distinct things to the ball when he throws it, and that moves it into five distinct areas. Here’s Darvish’s 2020 chart:

This uses the Pitch Info classifications from above, which is why there are more “sliders” than “cutters,” but c’mon. These dots overlap. The edges bleed together, and there’s less center of mass. Some of the splitters are in the sinker quadrant, some in the slider quadrant. The cutters are everywhere, with some rising and some falling. The curveballs could easily be two pitches, and some could be sliders. Some of the curveballs have vertical movement if you don’t account for gravity!

When I set out to write this article, I wanted to talk about how Darvish was willing to throw any pitch in any count. The league as a whole decreases its fastball usage (excluding cutters) by five percentage points on two-strike counts. Darvish has thrown his more often with two strikes this year, 32.3% against 31% in all other counts. Take 0-0 out of the equation, and it’s even stranger: Darvish throws 43% fastballs to start an at-bat, then 24.5% fastballs until he hits two strikes, then 32.3% fastballs.

As I mulled over what to call each pitch and where to draw bright lines in describing his pitch usage, however, I changed my mind. Darvish isn’t exactly going against the grain, using his curveball when others would use their fastball and his slider when others would use their changeup. He changes each of his pitches so much, more run here or drop there, that while he does sometimes pitch against the grain, he sometimes throws a slider in a slider count and is still bucking convention, easier to do when you have fifteen sliders or whatever.

So in the end, forget all that noise. This isn’t an article about why Yu Darvish is great, at least not one of those nuts-and-bolts analytical articles where I show you the new pitch, show you how he’s using it in an interesting way, and then show you how that reduces hitters to a quivering mess in the batter’s box while unlocking fame and fortune for the pitcher.

This is an article about how fun it is to watch Darvish pitch and try to name the pitch he’s throwing. It’s wild. When he’s on, he can command them all at will — and as his 3.1% walk rate will tell you, he’s on right now. This form of Darvish is both dominant and delightful. Through three starts, he has a 2.12 ERA and a 1.63 FIP (2.99 xFIP). He has the second-most WAR among all pitchers this year, behind only Bieber. And yet, that’s not the fun part. The fun part is when he does this:

Which is a nasty enough pitch on its own, 97 on the black with some arm-side run to paint the corner, even if he missed Caratini’s target. But it’s not just that; it’s that in the same outing, he’s liable to do this:

And batters are so geared up for so many things that they just sometimes let it go by. Anyone can throw a 90 mph cutter that backs up and spins instead of breaking. When Darvish does it, though, you think hey, wait, maybe that was on purpose. Baseball is fun when you can analyze it, but it’s also fun when you’re left wondering, and no pitcher in baseball leaves me gleefully wondering more than Darvish right now.


2020’s Most Irreplaceable Players

The 2020 major league season is about 20% done, which might feel strange given that the season isn’t quite two weeks old, but it’s just one of the many odds things about this year. We’re just three weeks from the trade deadline and the basic contours of who the contenders and the also-rans are has become clear in a shockingly small number of games. That shortened slate has also seen a number of key players go down with significant injuries. The threat of COVID-19 looms large over any discussion of missed time this season, but sadly, more familiar maladies will also take their toll — Justin Verlander is still weeks from a potential return from a right forearm strain, Shohei Ohtani likely won’t pitch again this season after leaving Sunday’s game with a forearm strain of his own, and Mike Soroka joined the list with a painful tear to his Achilles tendon Monday evening, ending his 2020 season before it had really begun. Even Max Scherzer exited Wednesday night’s action with a sore hamstring, though thankfully it appears minor.

How big a loss for the Braves was Soroka? With him still in the rotation, the ZiPS projection system had the Atlanta Braves with an 89.5% chance of making baseball’s expanded 16-team playoffs. Without Soroka, that number drops to 81.5%, nearly doubling the probability that Atlanta watches the playoffs from home. How does that eight percentage points rank among baseball’s stars? As I do every season, I asked ZiPS to re-project league standings with individual star players removed from their team’s rosters.

This isn’t a WAR ranking, which would be kind of boring. Teams whose playoff fortunes are most up in the air, especially those without sufficient depth, tend to be the ones that get in the most trouble when they lose a key player due to injury. The combination of good early results and deep rosters has left a few teams at the top of the food chain — the Braves, Dodgers, Athletics, Twins, and Yankees — without a single player in the top 25 in playoff leverage. That’s not to say that losing Mookie Betts or Cody Bellinger wouldn’t be a huge loss for the Dodgers, but the team has good backup options and it would take losing both to seriously change the team’s playoff odds.

With Wednesday night’s games in the books, here are the ZiPS-projected playoff probabilities for every team:

ZiPS Playoff Probability – 8/6/20
Team Playoff Probability
Los Angeles Dodgers 97.4%
New York Yankees 94.3%
Minnesota Twins 90.7%
Chicago Cubs 85.4%
Oakland Athletics 81.9%
Atlanta Braves 81.5%
Houston Astros 77.5%
Cleveland Indians 76.6%
San Diego Padres 74.3%
Tampa Bay Rays 72.4%
Chicago White Sox 69.1%
Washington Nationals 69.1%
Philadelphia Phillies 56.0%
Cincinnati Reds 53.1%
Milwaukee Brewers 52.6%
St. Louis Cardinals 52.2%
Los Angeles Angels 49.6%
Colorado Rockies 45.6%
New York Mets 45.0%
Toronto Blue Jays 44.2%
Boston Red Sox 42.4%
Arizona Diamondbacks 31.8%
Texas Rangers 27.2%
Miami Marlins 24.1%
Detroit Tigers 23.2%
San Francisco Giants 22.9%
Kansas City Royals 18.6%
Seattle Mariners 17.1%
Baltimore Orioles 15.1%
Pittsburgh Pirates 8.9%

Read the rest of this entry »