Each play in the playoffs holds extra weight compared to the regular season. An error can change a game, and a loss can doom a series. In close games and series, it is often the team that executes the small plays that comes out on top.

A particular play in Game 2 of the NLDS between Washington and Los Angeles stood out in this context: Asdrúbal Cabrera singled to right field, driving in Ryan Zimmerman. However, the throw from the outfield held up Kurt Suzuki at third base, and Cabrera was thrown out trying to advance to second base on the throw. Although the Nationals still won the game, the baserunning error was not inconsequential in the series.

Evaluating the Result with WE and RE24

Two statistics – Win Expectancy and RE24 – can be used to show why trying to advance was a bad decision.

Win expectancy (WE) is the probability a team will win given the specific circumstances. Greg Stoll’s Win Expectancy Calculator [1] shows how potential baserunning outcomes by Cabrera change Washington’s win expectancy in Table 1 below.

The Nationals’ win expectancy before Cabrera’s single was 82.7%. The highest WE is 93.4% and results when Cabrera gets to second base, however, staying at first only decreases Washington’s win expectancy by 0.9%. In comparison, getting thrown out decreases their chances by 6.7% compared to staying at first. A 0.9% increase in WE is probably not worth risking 6.7%, especially in a playoff game where you have the lead. Read the rest of this entry »

I love good defense. Watching a center fielder chase down what should have been a blooped-in single, instead creating a shocked reaction from the baserunner as he turns and realizes he’s out is priceless. That classic, one hand in the dirt, rest of the shortstop’s body flying through the air snag, is truly my favorite. I know what people say about the excitement of a home run and I get it. The rifle-like, cracking sound of bat on ball, closely followed by fans standing and cheering and spilling and spitting! God, I’m going to miss baseball this winter!

As the season comes to a close, we celebrate more than just home runs. We celebrate and award players for all their actions on and off the field. With that, it’s nearly time to award the best defensive players of the year with the Rawlings Gold Glove Award. There’s nothing like having a gold glover on your team and being able to watch them hold it down in the field all season long.

​Like many awards, managers and team coaches get to vote on the Gold Glove. Managers can’t vote for players on their own team and they have to stay in their own league. In addition, they have to vote for players who qualify (mostly needing at least 713 total innings) as laid out by Rawlings. It’s nice to have the men who are closest to the game voting and giving out these awards, but there must also be some quantifiable way to determine who is deserving. According to Rawlings, 25% of the vote is left up to metrics. Using the SABR Defensive Index, advanced analytics are now built into the award. This index includes:

– Defensive runs saved (DRS)
– Ultimate Zone Rating (UZR)
– Runs Effectively Defended
– Defensive Regression Analysis
– Total Zone Rating Read the rest of this entry »

When your favorite baseball team misses out on the playoffs, October offers a brief free-agency in fandom. Do you temporarily switch to root for a loved one’s team, or choose to root against a rival?

For me personally, I want former Rockies players to do well. It would be fantastic to see DJ LeMahieu lift the Commissioner’s Trophy, even if he’s now wearing the wrong color of pinstripes.

But do I really have to root for the Yankees? I wanted to see if I had any other option — to see if there was any other playoff team with more former Rockies.

I started with FanGraphs data showing player totals from every season going back to 2001 (CC Sabathia is the player on a 2019 playoff roster with the earliest debut, having come on April 8, 2001 for Cleveland). I also defined “playoff roster” as only including players who made an appearance for a playoff-bound team in September of 2019, so if someone hasn’t seen the field in the last month, they’re not counted here.

I didn’t want a player with only 15 ABs to have the same weight as a player with 1,000 at-bats, so I used each player’s “appearances” for their former clubs (plate appearances as a batter plus total batters faced for pitchers, including both regular season and playoffs). Read the rest of this entry »

Michael Lorenzen is one of a kind. We’ve heard plenty of his multi-faceted accomplishments as of late. As far as pitchers go, the guy can mash. He was a two-way star at Cal State Fullerton, slashing .335/.412/.515 in his draft year, while posting 19 saves and a 1.99 ERA out of the bullpen. In the big leagues, he’s a career .267/.306/.514 hitter with seven home runs in 116 plate appearances. The hits haven’t come cheap, either. His 14 batted balls this season have had a remarkable 98.70-mph average exit velocity, despite him only barreling one of them.

Lorenzen can also move better than most. His top sprint speed of 28.2 mph in 2019 places him in a tie with Bryce Harper, Shohei Ohtani, George Springer, and Jorge Polanco, among others. His general athletic prowess means he’s been serviceable enough to play in the field with some level of frequency, converting all eight of his chances in 34.2 innings split over three outfield positions. On September 5th, the day after his historic performance, he even earned himself a start in center field for the out-of-contention Reds.

His Swiss Army knife capabilities aren’t the only reason he’s unique. Lorenzen is an outlier on the mound as well. Lorenzen has spent the last four years as a solid reliever, working to a cumulative 3.48 ERA over 290 innings out of the Cincinnati bullpen. After a failed run as a starter in his rookie season, he seems to have found his niche working in the later innings.

This is far from out of the ordinary. But while failed starters tend to simplify their pitch mix upon shifting to the bullpen, Lorenzen has doubled down on his six-pitch arsenal, throwing each of his four-seamer, sinker, cutter, changeup, cutter, slider, and curveball between 7% and 28% of the time. It’s rare enough for any pitcher to have a true six-pitch mix, much less a reliever. I ran a Statcast search to find every pitcher since 2017 (when Statcast arsenal data begins) to have thrown at least six pitches between 5% and 40% of the time, minimum 250 pitches per season. Lorenzen still stands out: Read the rest of this entry »

There are still a lot of teams that are fighting for a postseason spot while we wind down the season. As I watch a lot of games down the stretch, I hear many different announcers bring up the same thing. If you want to win championships, then you need to follow a key ideology that the Astros and Red Sox have both preached in their title-winning seasons: You need to be able to take your walks, and you need to be able to put the ball in play instead of striking out.

In 2017, the Houston Astros had the lowest strikeout rate as a team. They were able to do that while also having the league’s highest team isolated power. Last season, the Red Sox had the third-lowest strikeout rate in the league while having the ninth-best walk rate and fourth-best ISO. This got me to thinking about teams’ walk and strikeout rates. But I did not want to just look at it from the full season perspective. I wanted to compare teams’ rates from before the All-Star game to post-All-Star game (more specifically August 26th, because that is when I am writing this).

Thanks to FanGraphs, I was able to pull the data for the two date ranges and compare the numbers. Let us take a look: Read the rest of this entry »

As the Statcast era continues to age, we baseball obsessives are collecting more and more pitches to analyze in countless different ways. MLB Advanced Media releases 90 different metrics for every pitch thrown, including a pitch’s classification, where all the defenders are standing upon the pitch being thrown, exit speed, launch and spray angle, etc. Analysts across the web, armed with this exhaustive data set, have been able to unearth previously unknowable mysteries regarding team and player performance and league-wide trends.

One area of pitching analysis that has been largely untouched by the public is pitch sequencing. Baseball Savant has done some work with visualizing how a pitcher sequences his pitches, but to my knowledge there is no way to look at pitch sequencing for the league as a whole and see which sequences are most used and most effective. I was curious how pitchers have attacked hitters since 2015 (the beginning of the aforementioned Statcast era), so I parsed through every pitch thrown in the regular season starting from the beginning of the 2015 campaign up until August 11th of this year. I looked at how pitchers have paired pitches during every plate appearance. I discarded pitches that were not thrown to the same batter or the same inning; a pitch that is thrown to end an inning followed by a pitch to start an inning should not be considered a sequence (same can be said for two different plate appearances). The sequences should be read as the pitch on the right precedes the pitch on the left. Now, let us look at the trends:

Read the rest of this entry »

I make pitching gifs on a regular basis. In fact, there are dozens of other accounts on Twitter that do it as well. We participate in trying to help other fans understand what happens during plate appearances that go beyond what meets the eye. They can be great for seeing pitch shapes and how they contrast each other, but it’s important to know that there are some factors that can make them a bit deceptive (I myself have been guilty of making more out of an overlay that there actually is).

Overlays can be good for viewing how pitches move in relation to each other or noticing how different spin and axis affect the shape of a pitch. The Athletic’s Joe Schwarz is great at writing about and breaking that stuff down with the help of another gif-creating giant, ‘cardinalsgifs‘.

These two use gifs to demonstrate how a pitcher has made adjustments, for better or worse, and compare how it impacted the shape of their respective pitch. Having a good camera angle for that practice matters as we are less concerned about how the hitter sees the pitch and more about how certain tweaks can alter its personality.

Most MLB cameras do not lend themselves to a good visual representation of an event. You’re not getting the actual pitch shape nor are you getting the real trajectories from the hitter’s perspective. Even direct-level views (via the Braves, Marlins, or Orioles, to name a few) aren’t always beneficial, especially if you’re trying to make a point of how “filthy” or “nasty” pitches are to hitters. Read the rest of this entry »

*Note: All numbers updated to August 12th, 2019*

Introduction

Consider the following comparison between Freddie Freeman (29) and Carlos Santana (33). Both players were starters for the 2019 All-Star teams of their respective leagues, and both are enjoying breakout seasons beyond their usual high production level, with nearly identical statistics across the board.

However, I argue that there is an underlying statistic that makes Santana’s success less impressive and Freeman’s worth MVP consideration. Recall the quality of competition of pitchers faced. The Atlanta Braves’ division, the NL East, contains the respectable pitching competition of the Mets (13th in league-wide in ERA), Nationals (15th), Marlins (16th), and Phillies (19th). Contrast this with the competition of the Cleveland Indians in the AL Central: The Twins (ninth), White Sox (22nd), Royals (24th), and Tigers (28th). Over 503 plate appearances, Santana has faced a top-15 pitcher (ranked by FIP) just 15 times, compared to 46 times by Freeman over 533 plate appearances. wRC+ controls for park effects and the current run environment, while xwOBA takes into account quality of contact, but all modern sabermetrics fail to address the problem of Freeman and Santana’s near-equal statistics despite widely different qualities of competition. Thus, I present the modeling system of playerElo. Read the rest of this entry »

The trade and struggles of Chris Archer have been well-documented by the baseball community. As many patrons of this very website know, Archer was sent from the Rays to the Pirates at the 2018 trade deadline for Austin Meadows, Tyler Glasnow, and a player to be named later, who was revealed as Shane Baz. Both Meadows and Glasnow have been very productive at the major league level for the Rays, while Baz is FanGraph’s 63rd-rated prospect on THE BOARD, carrying a future value of 50.

Archer, on the other hand, has been an unmitigated disaster. The once-tantalizing strikeout artist has delivered a 5.01 ERA paired with a 5.05 FIP. He has still struck out batters at a 26.0% rate, but his walk rate with the Bucs has surged to 10.1%. The main culprit for Archer’s spell of bad performance has been home runs; Archer has always tended to give up more fly balls than the average hurler, but since his move to Pittsburgh, 19.6% of his fly balls have gone over the fence, about 6% more than league average over that time span. Naturally, this leaves all of us baseball fans wondering, what happened to the pitcher who just four years ago was deemed by Dave Cameron as one of the 10 most valuable assets in MLB?

The Pirates were once thought of as one of the savviest organizations in baseball, a team that could spin washed-up pitchers into innings-eating workhorses. Detailed in Travis Sawchik’s book Big Data Baseball, the Pirates were one of the first teams to weaponize the infield shift. Pirates pitchers under the tutelage of pitching coach Ray Searage have been taught to rely on sinkers and two-seamers and to induce ground balls that can be gobbled up by the shift. As hitters have adjusted to the shift and focused on putting balls in the air, the Pirates’ approach of tailing fastballs low in the strike zone has become outdated. What was once the fountain of youth for veteran pitchers has become the focus of ridicule from the more analytically inclined. Read the rest of this entry »

A look at the relief pitcher ERA leaderboard yields names many baseball fans are now familiar with. Felipe Vazquez, Adam Ottavino, and Ken Giles have been in the spotlight before. The breakout seasons for All-Star trio Kirby Yates, Shane Greene, and Liam Hendriks have been well documented. Will Harris has been quietly dominant for multiple years. Even Scott Oberg had 200 innings of respectable relief pitching under his belt entering this year.

And then there is Aaron Bummer. Like most of his teammates on the White Sox who don’t routinely flip their bats into near-earth orbit, Bummer is fairly anonymous to the baseball world at large. Yet he has been without question the best arm in a surprisingly respectable White Sox bullpen, notching 49 innings across 41 appearances in 2019, posting a 1.65 ERA that is good for third amongst qualified relief pitchers.

Bummer is an outlier on this leaderboard in more than name recognition. The names ahead of him are racking up the strikeouts, with Yates posting a 14.58 K/9 to go with his 1.08 ERA while Hendriks holds 12.42 and 1.30 marks, respectively. Bummer averages a measly 7.88 K/9 by comparison. Few other relievers with such stellar ERAs have struck out batters at the low rate that Bummer has.

Bummer has largely accomplished this through an astronomical 68% ground-ball rate, surpassed by only worm-burner sensei Zack Britton. So how did this 19th-round relief-only prospect who topped out at 23rd on any White Sox prospect list turn into a ground-ball machine with one of baseball’s most effective fastballs? Let’s take a look. Read the rest of this entry »