A (Re)Introduction to the FanGraphs Library

Entering play on Thursday night, Kyle Seager owned a .274 batting average. Chris Johnson’s average was a nearly identical .273. The two third basemen have played in a similar number of games and have come to the plate close to the same number of times. If you use batting average to evaluate these players’ seasons, you’d come to the conclusion that Seager and Johnson are essentially equivalent players this year.

They’re not. In fact, it’s very clear Seager is substantially better than Johnson. Let me rephrase that: It’s very clear Seager is better than Johnson — but only if you’re well-versed in the language of baseball statistics. If you know how to properly value walks, extra base power, baserunning and defense, the difference between Seager and Johnson is impossible to miss.

At FanGraphs, our writers use statistics and metrics like wOBA, wRC+, FIP and WAR to evaluate baseball players and teams. We provide those tools, and more, so others might conduct evaluations on their own. Want to know Miguel Cabrera’s wOBA against lefties? You can find that on FanGraphs. But what if you don’t know what wOBA means, how it’s calculated or why you should care about it more than batting average?

You can find some of that information on FanGraphs. A well-motivated, self-starter could show up at the site, notice something called wOBA on the leaderboards, go to the glossary and figure out what it means and why it’s important. But it can be intimidating and challenging for people who are just starting out to make sense of everything we offer.

In an effort to make advanced statistics easier, and to understand and to better use the data and features available at FanGraphs, we’re relaunching and promoting the FanGraphs Library. There’s a lot of great information there already, but this revamped library is even better. There’s a steep learning curve, though, so I’ve been tasked with making things a bit simpler.

You Aren't a FanGraphs Member
It looks like you aren't yet a FanGraphs Member (or aren't logged in). We aren't mad, just disappointed.
We get it. You want to read this article. But before we let you get back to it, we'd like to point out a few of the good reasons why you should become a Member.
1. Ad Free viewing! We won't bug you with this ad, or any other.
2. Unlimited articles! Non-Members only get to read 10 free articles a month. Members never get cut off.
3. Dark mode and Classic mode!
4. Custom player page dashboards! Choose the player cards you want, in the order you want them.
5. One-click data exports! Export our projections and leaderboards for your personal projects.
6. Remove the photos on the home page! (Honestly, this doesn't sound so great to us, but some people wanted it, and we like to give our Members what they want.)
7. Even more Steamer projections! We have handedness, percentile, and context neutral projections available for Members only.
8. Get FanGraphs Walk-Off, a customized year end review! Find out exactly how you used FanGraphs this year, and how that compares to other Members. Don't be a victim of FOMO.
9. A weekly mailbag column, exclusively for Members.
10. Help support FanGraphs and our entire staff! Our Members provide us with critical resources to improve the site and deliver new features!
We hope you'll consider a Membership today, for yourself or as a gift! And we realize this has been an awfully long sales pitch, so we've also removed all the other ads in this article. We didn't want to overdo it.

This is going to be a comprehensive and ongoing project that will feature updates to the glossary entries, blog posts about how to use various stats and the site’s many features, and weekly chats — each Wednesday at 3 pm eastern, starting next week — to answer reader questions. You probably know FanGraphs is a sabermetrically-themed blog, but FanGraphs is also about the dissemination of quality information. The information is already here, but not everyone is up to speed on how to use it.

I’ll be doing everything I can to make learning and using sabermetrics easy. You can comment on posts in the library, ask questions in chats or find me on Twitter (@NeilWeinberg44). If there are things that don’t make sense, or you don’t know how to get your hands on the stats you want, I’d like to help.

If you want to kick back on your sofa and simply enjoy world-class athletes competing against each other, that’s perfectly fine too. No one’s pressuring you to become a stat-person. But if you want to evaluate players, engage in debates with friends, play armchair general manager or squash your fantasy baseball buddies, learning to speak saber is going to help. It doesn’t mean spending your life looking at spreadsheets instead of watching games but it does mean knowing how much a walk is worth compared to a double and why using runs allowed alone to judge a pitcher can be misleading.

There’s a lot of great information available to the public for free. If you want to get the most out of that information, we’re going to be here to help you do that. You probably knew Kyle Seager was having a better year than Chris Johnson without sabermetrics. That doesn’t require a lot of extra information. But not every comparison or analysis is so simple or so clear. Sometimes you need to park-adjust, know exactly how much a triple is worth or whether a defensive play was routine or unlikely.

It’s my hope this project will accomplish two primary goals: First, I want to streamline the process by which a person learns about advanced stats so you can pick up the basic skills in an afternoon and be fluent in a couple of weeks. Second, I want people who are well-versed in sabermetrics to be able to make the most out of the FanGraphs’ features.

Did you know you can create and save a custom leaderboard with any players you want? Did you know that you can look up Alex Gordon’s on base percentage from June 7 to June 28? If there are specific things you want to learn, let me know.

If you want to learn more about the stats we use or the features we offer, stick around. If you have friends who might be interested, send them our way. There’s a lot to learn and plenty of questions to ask, regardless of how much time you spend on the site. All of you — and all of us — are here because we enjoy baseball and we want to uncover more about the game we love. I hope our library is just one more step toward reaching that goal.





Neil Weinberg is the Site Educator at FanGraphs and can be found writing enthusiastically about the Detroit Tigers at New English D. Follow and interact with him on Twitter @NeilWeinberg44.

46 Comments
Oldest
Newest Most Voted
Rian
12 years ago

Great post, though I’m guessing Fangraphs is more interested in the “dissemination” of quality information than the “decimation” of it 😉 Looking forward to these updates!

Blake
12 years ago

This is exciting stuff. I’ve tried to educate myself when I don’t understand certain statistics and methods for evaluation; excited to learn more!

Blake
12 years ago
Reply to  Blake

Also….long live Seager Boss

Pale Hose
12 years ago

This is going to be awesome!

Gabes
12 years ago

I’m not sure how deep this is planning to go, but I’d like to see a better discussion on how to calculate FIP-based WAR for pitchers. I’ve tried to follow the articles in the glossary to calculate pitcher WAR from scratch and it never seems to turn out right. I’m not sure how much of that curtain can be pulled back, but some more information would be welcomed. Thanks in advance for what already sounds like a good series.

Pale Hose
12 years ago
Reply to  Gabes

Second

Brian
12 years ago
Reply to  Gabes

I think it was in 2012 or 2013 when Dave started to use pop-outs in the WAR calculation, because an IFFB is pretty much as sure to be an out as a strikeout. So the FIP on the leaderboards is not the same as FIP used for WAR. The adjusted FIP for WAR purposes is.

FIP = ((13*HR)+3*(BB+HBP)-2*(IFFB+K))/IP + constant

This should close most of (if not all of) the gap between WAR you calculated and the WAR from the leaderbards.

I’m glad that the library is being updated because it was very confusing as it was.

Matt Perez
12 years ago

I’d like to see an update to the documentation about how WAR is determined?

The pitching documentation hasn’t been updated since 2009 (just looking at the glossary) and I’m pretty sure it’s missing things like how pitching leverage is used to determine reliever WAR (implemented I believe in 2010).

I’m sure there have been more changes since 2009 that I’m not aware of.

frivoflava29
12 years ago

Is there way to add a pitcher’s RA9 wins to your custom leaderboards/dashboard? Can there be? I know it’s relatively easy to calculate, but we don’t have access to FDP or BIP wins either, which also would be cool. Looking through the library makes me want to be able to make use of all these stats.

Tim L
12 years ago

Just wanted to mention too that there is a baseball analytics course (Sabermetrics 101) offered through edX, by Andy Andres at BU. The realtime course is almost over, but you can still access the course materials and it will be archived as well for continual access. The course offers five segments each week over six weeks covering topics in sabermetrics, statistics, tech (basic SQL and R), history, and interviews with contemporaries in the field.

They also anticipate offering a Sabermetrics 201 course at some point soon, so keep your eyes open for that if interested.

joser
12 years ago

About four years ago Graham MacAree at LookoutLanding did an excellent Sabermetrics 101 series. Fangraphs would do well to try to match that (with updated info for things that have changed and improved since then, particularly with respect to how Fangraphs specifically calculates certain results).

Since I’m linking LL anyway, I’ll also point out this post that compiles a variety of useful introductory material from sites all over the web (including FG, of course, but also THT, Tango’s blog, etc).

Gabes
12 years ago
Reply to  joser

This may be a level above the LL links you posted, but the Saber Archive (http://saberarchive.com/) started up by Matt Dennewitz has started accumulating articles that range from the ‘101’ level on up.

urchman
12 years ago

For stats like wOBA, FIP, etc., in addition to an explanation of what the stat is measuring and how it’s calculated, could FG also include the mean and z-score for each stat, preferably by year?

jadam7Member since 2018
12 years ago

I think a good statistic for the library/for people’s custom boards would be some sort of BABIP vs. Career BABIP ratio–a good measure of possible outlier performance. Of course pitch FX data can always indicate the hitter has improved in some area, but I think this would be a good road sign.

peterevang
12 years ago
Reply to  jadam7

Also, an xBABIP based on batted ball profile would be super! Thanks!

Elan
12 years ago

Do you guys have stadium-specific stats? I’m curious about HR/FB ratios across the league.

Bob
12 years ago

Might be a little overdue, but it’s definitely a great idea and I look forward to it

Joe Durant
12 years ago

What I’d really like is for, when I hover my mouse over the top of a column, to see what the abbreviations stand for, and a small description of the stat. It does it on the player pages, but not on the leader boards (for me, anyway)

peterevang
12 years ago
Reply to  Joe Durant

Seconded!

scooter262
12 years ago

Trying to find Basruns on the site. I have read about them in several articles, but have not been able to find them in any leaderboards or list pages.

scooter262
12 years ago
Reply to  scooter262

Baseruns.

Brian
12 years ago
Reply to  scooter262

Baseruns only make sense to use for teams. This is because Baseruns values depend on the rate at which a team’s runners score when they reach a specific base. So you shouldn’t use it to evaluate a player because he has nothing to do with which base his teammate reached or how often he will score once he gets there.

You could use some league average numbers for the scoring rate part of BaseRuns, but at that point you’re pretty much creating your own linear weights and you might as well use the ones that Fangraphs already calculated for you.

So in short, wRC (not wRC+) is a good enough measure of how many runs each player contributed to his team.

The effect that all those wRCs have on each other, when added up, is the team BaseRuns result at the link that Neil posted.

Bradsbeard
12 years ago

One thing that is very difficult to wrap my head around, much less explain to other people, is the WAR positional adjustment. The current glossary entry does a decent job of explaining how it operates, but it’s hard to get a sense of how the adjustments are derived or what they say about a particular player. For instance, when we say Miguel Cabrera gets a credit of +2.5 runs for standing in at 3B for a 162 games, are we saying anything in particular about his defensive skill? There is some form of accounting going on there, but it is unclear what is being accounted for. I’d really appreciate seeing a piece explaining how the precise adjustments were calculated and assigned. There is a link in the glossary to an old Tango blog post which sort of lays out in a stream of consciousness manner how they were derived from UZR, but it’s hard to follow and I have a hard time drawing conclusions from it. It would definitely be a project, but I really think if would be worth your while.

Looking forward to what’s in store!

scb
12 years ago

Thanks for the heads up about the custom leaderboards. Those are awesome.

Now is there a tool that makes you stop poking around on Fangraphs after a certain amount of time so you can actually finish the work you need to get done by the end of the day?

mgoetze
12 years ago

“FanGraphs is also about the dissemination of quality information.”

It is? Explain the presence of Inside Edge fielding “data” on your site then.

OkraMember since 2016
12 years ago

why is it that two pitchers with very similar BB, SO, and HR rates can have two very different FIP numbers? aren’t those the only three things that FIP looks at? thanks for answering

OkraMember since 2016
12 years ago
Reply to  Okra

for example, here are colby lewis and yordano ventura’s stats for this year. very similar with lewis actually having a better SO rate and HR/FB rate, yet a much worse FIP. why is that?

k/9 BB/9 HR/FB FIP
7.82 2.79 8.9 4.16 colby lewis
7.52 2.74 10.1 3.57 yordano ventura

just one problem...
12 years ago
Reply to  Okra

HR/FB rate is not directly part of FIP. In your example we need to look at HR/9. Evidently Colby Lewis has a high FB% which means his HR/9 is big. The coefficient for HR in the FIP core is 13 versus 3 and 2 for K & BB so even small variation in HR has a huge effect.

Jordan
12 years ago
Reply to  Neil Weinberg

Are the FIP coefficients determined from linear weights?

NotFoul
12 years ago

I’ve stuggled to find the time to dive into saber stuff, but I’m ready to learn. Guess I picked the right time to stop being lazy. Looking forward to the (Re)Introduction.

Hunter Satterthwaite
12 years ago

Hey Neil, you mind following me on twitter at @huntman234 so I can learn more about sabermetrics?

peterevang
12 years ago

Is there a way to look at just righties or lefties (for either pitchers or batters)? It seems like a natural option, but I haven’t found it. Thanks!