Today, we’ve made some changes to Wins Above Replacement that completes the move from UZR to the full suite of Statcast equivalent metrics in FanGraphs WAR. This process began in 2022, when we replaced UZR’s range component with Statcast’s Fielding Runs Prevented, which is Outs Above Average (OAA) converted to runs above average. UZR will continue to be calculated on FanGraphs through the end of the 2025 season. Today’s changes are retroactive to the 2016 season. Read the rest of this entry »

This month at FanGraphs, we’ve been highlighting a number of site features and showing you how we use them. The goal is to make your visit to the website more useful, and to get the most out of the features we’ve added over the years. Today, I’m going to walk you through the data we keep on individual pitch types: how you can look at what’s in your favorite pitcher’s arsenal. I’ll also show you how to do this for every member of your favorite team’s pitching staff, as well as for all the pitchers in the majors.

One quick note here before we get started: All of this data can get chopped up any way you’d like using our custom leaderboards, which Dan Szymborski explained earlier this month. If you’re already a power user, this is just more data to pour into the soup. I’ll be looking at our standard-issue pages today for ease of use, but please feel free to mix and match these site tutorials in any way you prefer.

One of the greatest advancements in baseball data collection came in 2008. That year, Major League Baseball started publishing data produced by a system called Pitchf/x. Since then, we have location, speed, and movement data for every pitch thrown in the majors, give or take a few one-off stadiums that at the time didn’t have the correct camera system installed. Read the rest of this entry »

If you’ve been reading me with any frequency for the past 20-some years — the last six of them here at FanGraphs — you may have noticed that I’m prone to dropping the occasional number into my prose. In fact, Statcast says I do so in 57.6% of my sentences, which ranks in the 93rd percentile even among my FanGraphs colleagues. Admittedly, I just made that part up, but the point is that I’m someone who tends to present a fair bit of data to the reader in support of my analysis.

At this site, we feature a lot of data, and as a consequence, not all of it is easy to find, but we do our best to organize it logically so that users can do so. Once again, I’d like to highlight a particular area as part of our series on the useful site features you’ll find at FanGraphs.

Back in 2007, for the Baseball Prospectus book It Ain’t Over ‘Til It’s Over, I compiled a historical All-Star squad of ignominy, identifying players at each position whose performances had dragged their teams down in tight races: the Replacement-Level Killers. I’ve revisited the concept numerous times at multiple outlets and have adapted an expanded form of it into a midsummer series that serves as a trade deadline preview, highlighting the particular trouble spots on each contender. Read the rest of this entry »

The FanGraphs split tool is so powerful that its functions have to be… (rubs hands together)… (waits for applause)… split into multiple spotlight posts. I’ll admit right away that the feature I’m about to highlight is a little bit out there. I don’t use it every day, or even every week. But it allowed me to research what ended up being my favorite data-driven article that I’ve written in my time at this company.

The post in question, from last January, is titled “Yandy Díaz, Artificial Turf, and Earl [Expletive] Weaver.” As you can guess from the headline, it was born from a desire to talk about my favorite manager in baseball history, and his rhetorical gift for dense and florid obscenity. In order to get there, I had to dig around looking for hitters like Díaz: big, strong guys who hit the ball hard enough to put it over the fence, but who suffered from high groundball rates.

After some clicking and sorting, I was tickled to discover that there were a lot of Rays and Blue Jays at the top of the leaderboard. The Rays and Blue Jays — in addition to playing in the same division and having rhyming names — both play on artificial turf. Only five teams in the league do. Could they be targeting groundball hitters on purpose, on the pretense that fake grass is friendlier to such hitters than the real stuff? (I didn’t know it at the time, but the Marlins and Diamondbacks would make surprise runs to the playoffs in 2023 after finishing first and fourth in groundball rate. Both teams play on turf.)

Actually investigating that premise — that groundball hitters fare better on turf — required refining the whole set of offensive data down by batted ball type. Then again by stadium. There’s no split tool for grass vs. turf, nor for the two different brands of artificial turf. So that involved filtering for the stats at the five ballparks in question and consolidating them. Surely no tool can slice the apple that thin.

Poppycock. The splits tool did it with ease. By changing the filter from MLB to team-by-team, I then could split these groundball stats out into each individual team’s home ballpark. You could even change the date parameters to expand the sample to two seasons instead of one, or look at away teams’ stats in those environments.

And from there, the possibilities are… maybe not literally endless, but close enough you’d never be able to tell. These stats are available on a player-by-player basis, either as a leaguewide leaderboard or narrowed to one or a few specific hitters of interest via the Custom Players function.

Now, all of the parks with artificial turf are indoors, which makes splits by weather irrelevant. But that’s available too. Not too long before I wrote the groundballs-on-turf article, I was in the auxiliary press box in Philadelphia, watching Seranthony Domínguez trying and failing to grip his changeup in driving rain and freezing cold conditions in Game 5 of the NLCS. Surely it must be difficult to pitch in the cold and the wet.

Good news: We can tell exactly how difficult by filtering for temperature and precipitation.

Temperature is just the tip of the proverbial iceberg: The splits tool also supports searches by custom range for elevation, wind speed, barometric pressure, and air density. I didn’t even know “air density” was something you could measure. Either way, there’s no need to use the time of year as a proxy for atmospheric conditions. The dog days of summer aren’t the same in Atlanta as they are in Boston, after all, so the splits tool allows you to be more precise.

These splits are useful both for rigorous empirical study — determining the effects of ballpark construction or weather on offensive environment — and for trivia — “leading the league in RBI when the temperature is over 80 degrees and the wind is blowing at least 10 mph,” or something equally esoteric and frivolous. That’s both sides of the coin for the numerically literate sports fan.

On the very first day of my freshman year of college, my Journalism 101 professor quoted a line from All the President’s Men: “Follow the money.” Over four years as an undergrad, I’d hear that maxim more times than I could count. Enough that after more than 10 years in the business, it’s been incorporated into my subconscious so thoroughly that I can hear my old professors and mentors (and sometimes Hal Holbrook) repeating it without needing them to be physically present.

Obviously, we at FanGraphs would like nothing better than for some of your money to be spent on a Membership. Your support funds valuable tools like the RosterResource payroll pages, my favorite way to follow that famous principle of journalism. Read the rest of this entry »

Over the next month, we at FanGraphs will be highlighting a number of site features and showing you how we use them. The goal is to make your visit to the website more enjoyable, and to help you get the most out of the features we’ve added over the years. Today, I’m going to walk through the various ways we deploy projections to make predictions about the future. Let’s explore our projected standings and playoff odds pages.

Before I ever worked at FanGraphs, I spent countless hours messing around with the playoff odds page. I like learning about the future, or at least learning about many possible futures, and I always found the slow-changing nature of projections early in the season to be soothing as a Cardinals fan. Stressed about last night’s crushing loss? On May 15? I could always look to the odds page, see that the team’s chances had barely budged, and calm myself down.

Five years into working here, I still use many of the same pages I did then, but they’ve been upgraded a good deal in the meantime. Let’s start with the nerve center of our predictions, the page that shows everything that feeds into our much-discussed playoff odds: the Projected Standings. You can find them using the navigation bar at the top of the site:

Read the rest of this entry »

Writing a book is a Herculean task to begin with, and in my inimitable way, I made it even harder when writing my 2017 book on the Hall of Fame, The Cooperstown Casebook, by challenging myself to compose concise 200–250 word summaries of the 220 major league players who were enshrined at that point as well as a few dozen past, present, and future candidates. My goal in doing so was to give the reader a thumbnail guide to these players’ careers while shining some fresh light on even the most familiar ones using advanced statistics. I had no shortage of options, but even so, I wish I had all the tools then that I do now. Here I’d like to highlight one of them as part of our series on useful site features you’ll find at FanGraphs.

Consider the case of Dazzy Vance, a colorful and dominant right-hander who made his name with the Brooklyn Dodgers in the 1920s and ’30s. Vance was 24 years old when he debuted with the Pirates in 1915, but a variety of arm troubles limited him to just 33 major innings through his age-30 season. Finally pain free after elbow surgery (probably to remove bone chips), he resurfaced with Brooklyn in 1922, and on the strength of his combination of a blazing fastball and a sharp overhand curve “with a sweep that would shame a windmill,” as one writer described it, he led the NL with 134 strikeouts that season, and proceeded to repeat the feat in each of the next six seasons as well. His 262 strikeouts in 1924 was the highest total by any NL pitcher besides Christy Mathewson in the 1901–1960 span, and the highest by any pitcher in either league between the start of the Live Ball era (1920) and the United States’ entry into World War II (1941).

While I had enough confidence in my research to lead Vance’s Casebook capsule with, “Relative to his league, Vance struck out batters at a higher rate than [Nolan] Ryan, [Roger] Clemens, [Pedro] Martinez — any of them…” I worried that by explicitly quantifying his skill in this area that I’d either open myself to error or make even more work for myself, since the temptation was to go into further detail on the subject and perhaps calculate such data for every enshrined pitcher. Little did I know that within a year of the book’s publication that I would not only join the staff of FanGraphs but propose the creation of a leaderboard to tackle such questions with a few easy clicks. Read the rest of this entry »

As David Appelman mentioned in yesterday’s State of the Union, over the next month we’re going to be highlighting some of FanGraphs’ features, sometimes off the beaten path, that can help you have a more productive, entertaining visit to our fair website. Today, I want to highlight some of our custom data options.

There are lots of ways to use FanGraphs, but as an individual of rather numerate inclination, I tend to get a lot of data from the site. I did that back when I was blogging at Baseball Think Factory and writing for ESPN, and I certainly haven’t curtailed that impulse as an employee of FanGraphs. Quite often, it’s simply easier for me to get things directly from the site than to go through my massive hoard of invariably unhelpfully named spreadsheets and databases. And one thing that I use a lot is the custom reports feature. We have so much data all over the site that it’s no simple matter to just get one massive export to rule them all, and in the Dark Mode, bind them. Read the rest of this entry »

Hi everyone!

It’s been almost two years since we talked about how FanGraphs is doing, and with Opening Day fast approaching, I thought it would be a good time to give you an update on where the site stands now. Read the rest of this entry »

Here’s your chance to vote for the 2024 SABR Analytics Conference Research Awards winners.

The SABR Analytics Conference Research Awards will recognize baseball researchers who have completed the best work of original analysis or commentary during the preceding calendar year. Nominations were solicited by representatives from SABR, Baseball Prospectus, FanGraphs, the Internet Baseball Writers Association of America, and Sports Info Solutions.

To read any of the finalists, click on the link below. Scroll down to cast your vote.

Contemporary Baseball Analysis

• R.J. Anderson, “Why Baseball’s Next Unionization Effort Could Come From MLB Front Offices,” CBS Sports, May 1, 2023
• David J. Gordon, “Balancing Starter and Bullpen Workloads in a Seven-Game Postseason Series,” SABR Baseball Research Journal, Fall 2023
• Hannah Keyser and Zach Crizer, “How the Not-So-Subtle Art of Chucking it Right Down the Middle is Helping MLB Pitchers Get Ahead,” Yahoo! Sports, April 4, 2023
• Eric Longenhagen, “Let’s Get Small: Hundreds of Minor Leaguers Have Shrunk,” FanGraphs, September 29, 2023
• Robert Orr, “Quantifying the Corey Seager Approach,” Baseball Prospectus, November 8, 2023

Contemporary Baseball Commentary

• Michael Baumann, “I Was Supposed to Write About Elly De La Cruz Today,” FanGraphs, June 16, 2023
• Michael Clair, “In the Mountains of the World’s Most Remote Country, Baseball Takes Hold,” MLB.com, August 3, 2023
• Evan Drellich, “MLB’s Billionaire Owners Leaning on Public for Wave of New Ballparks,” The Athletic, September 12, 2023
• Esteban Rivera, “Shohei Ohtani’s Deal With New Balance Has Immense Potential,” FanGraphs, March 13, 2023
• Ginny Searle, “The Wrong Lessons Learned,” Baseball Prospectus, June 16, 2023

Historical Baseball Analysis/Commentary

• Russell A. Carleton, “Is WAR Still Stuck in the 20th Century?” Baseball Prospectus, February 8, 2023
• Stephen Dame, “Softball and Swastikas: The Riot at Toronto’s Christie Pits,” SABR Baseball Research Journal, Fall 2023
• Patrick Dubuque, “The Other Aging Curve,” Baseball Prospectus, January 31, 2023
• Sam Miller, “Based On A True Story: The Game’s Most Preposterous Fun Fact,” Pebble Hunting, June 6, 2023
• Dayn Perry, “Old Yankee Stadium’s Rise And Fall: Complete Story of ‘The House That Ruth Built’ 100 Years After Its Opening,” CBS Sports, April 18, 2023

John Dewan Defensive Analytics Award

• Robert Arthur, “The End of the Shift Helped Left-Handed Line Drive Hitters the Most,” Baseball Prospectus, November 7, 2023
• Alex Eisert, “Breaking Down the Kansas Kids’ Gold Glove Snub,” FanGraphs, October 31, 2023
• Jonathan Judge, “Introducing RDA,” Baseball Prospectus, February 8, 2023
• Rob Mains, “Fielding, It Turns Out, Does Slump,” Baseball Prospectus, August 29, 2023
• Mark Simon, “What Has 20 Years of Defensive Runs Saved Data Meant to Baseball?” Sports Info Solutions, February 7, 2023

Voting will be open through 11:59 p.m. MST on Friday, February 9, 2024.

Mobile or Safari users, click here to access the survey

Results will be announced and presented at the SABR Analytics Conference, March 8-10, 2024, in Phoenix, Arizona. Learn more or register for the conference at SABR.org/analytics.