Archive for Daily Graphings

Mariano Rivera turned 43 last November. There was wide speculation that he would retire at the end of the 2012 season, until his 2012 season ended with an untimely season-ending injury, and Rivera decided to try to make a comeback so that his last season could occur on his terms.

But even though Mariano Rivera’s career is full of unprecedented moments, that does not mean that it will be trivial for him to come up with another. Baseball has been played in America for the better part of two centuries, and unprecedented things are generally unprecedented for a reason: they are extraordinarily unlikely. So how many players have been able to play effectively after losing a full season in their 40s?
Read the rest of this entry »

This morning, we announced that we’d come to an agreement with Sean Forman of Baseball-Reference on a unified replacement level, allowing both WAR calculations to measure players on the same scale. In that post, though, I didn’t spend much time talking about why replacement level is the baseline to begin with, so I thought it was worth taking a little bit more time to talk about why replacement level is a necessary concept.

After all, we’re all used to metrics that use average as a baseline, and average is easily defined and measured. Why not just measure everyone against league average, and use WAA instead of WAR?

There are two answers to that question, really. Let’s tackle them in order of importance, beginning with the playing time issue.

Read the rest of this entry »

Prospect lists are one of the best parts of the off-season. Marc Hulet published his top 100 yesterday as the culmination of several months of work, and Baseball America, Baseball Prospectus, Keith Law, John Sickels and a plethora of websites have published others. Each group puts myriad hours into analyzing, calling, writing, editing, re-analyzing and finally publishing their work. But even after all that, they usually come to several different conclusions. I decided — instead of focusing on a specific list — to generate a list that combined each of these lists into one.

The idea of community or consensus lists isn’t new. Sites have done it before, but I’ve added some wrinkles:

Read the rest of this entry »

Two stories for you, one shorter than the other: Not long ago, much of the FanGraphs staff was down in Arizona, and on one particular Friday night a lot of us went over to Peoria to watch the Mariners play an exhibition game against the Kingdom of the Netherlands. There was absolutely nothing at stake, although I suppose you could argue Jon Garland was sort of pitching for a job. Anyhow, it was a friendly, but somewhere in the early innings the Dutch dugout started to chirp about a questionable call. The first-base umpire basically paused the game so that he could shout at the dugout and tell them to shut up. This was a quiet exhibition and the ballpark was otherwise pretty silent, so, yeah, that was weird and audible. Tempers flared in a nothing baseball game.

Wednesday afternoon, the Mariners played a Cactus League game against I don’t remember who. It doesn’t matter. What matters, for our purposes, is that Eric Wedge got ejected. The Mariners’ manager was ejected from a pointless competition. Maybe the umpire was a little too hasty or aggressive, but there was some sort of provocation. Again, tempers flared in a nothing baseball game.

Read the rest of this entry »

On Christmas Eve of 2008, David Appelman gave the world a present – “win values” on the pages of FanGraphs. It wasn’t labeled WAR for a little while longer, though it was an implementation of the model Tom Tango laid out at The Book Blog a few months prior. Over these last four years, the model has become quite popular, and even those who are not fans of analytics know what WAR stands for. Over time, the model grew in popularity, and in 2010, Baseball Reference added it to their collection of statistics. Because WAR is essentially a model of player value, there are decisions that have to be made about the way it is constructed that don’t have an obviously correct answer. In places where we had made one decision, Sean Forman (and Sean Smith, who assisted with their original implementation) made some other decisions, and the calculations differ in some significant ways.

We know that this is a source of frustration for some folks, having two sites both publicly display different calculations for a statistic of the same name. Often, the differences between the two have been used to discredit the entire model. For instance, Jim Caple wrote this on ESPN.com a few months back:

Actually, we know it isn’t always accurate because depending on your source — FanGraphs or Baseball-reference.com — you can get wildly different WAR scores… For example:

Does (Jack) Morris, in fact, belong in the Hall of Fame? No, he doesn’t, according to baseball-reference.com, which gives him a WAR score of 39.3, tied for 145th all time among pitchers. Maybe he does, according to FanGraphs, which gives him a 56.9 WAR, 75th all time.

When Caple wrote it, I wasn’t exactly sure why Morris’ value differed so much, but since we measure pitching in very different ways, I assumed that the 17.6 win gap was due to some differences between Morris’ FIP and his runs allowed. But, then, I looked it up, and Morris’ career ERA (3.90) was almost an exact match for his FIP (3.94). Adjusted for park, Morris’ career FIP- was 97, while his ratio of RA9 to league average on Baseball-Reference is 96. Even with very different inputs, both models came to the same conclusion about Morris – he was a slightly above average pitcher who had a very long career. So, why did we give him credit for an additional 17.6 wins?

The answer, quite simply, lies with replacement level. Our model used a lower baseline than Baseball-Reference did, so the same performance would result in a higher WAR in our model than in theirs. Over very long careers — like Morris’, for instance, or many of the old time pitchers who threw forever — this could really begin to add up, and give the appearance of large disagreements when the two systems didn’t actually see things all that differently. In the case of guys with substantial careers, many of the large discrepancies were simply driven by the fact that the two sites had a different definition of replacement level.

Read the rest of this entry »

A few weeks ago, you may have seen this tweet:

In today’s Crazy Big Nerd News, FanGraphs and Baseball-Reference.com have agreed to standardize Replacement Level. #SABRanalytics

— robneyer (@robneyer) March 8, 2013

Today, we’ve rolled out those changes, and some other ones!

Here are the details:

– Replacement level is now set at an even 1,000 WAR per 2,430 game season. Batters are given 57% of all total WAR with pitchers receiving the remaining 43%. This will cause players to drop in WAR by about 0.3 WAR per recent season.

– The leagues for batters are now zeroed out in terms of runs above average. Most of this adjustment is done in Batting, while the final league adjustment is done behind the scenes. We will soon have a “League Adjustment” stat which shows exactly what the league adjustment is for each player. On a seasonal level, AL position players will see about a 0.2 decrease, with NL position players receiving about a 0.4 decrease in WAR.

– Infield fly balls are now part of our pitcher WAR calculation. They are counted the same as a strikeout in the FIP calculation (though generic FIP on the site has not changed). You can see Dave Cameron’s original post to find out more about this change.

– UZR has been given a minor update. There was a small issue with calculating the foul line and this has now been corrected. Also, the 2012 park factors were updated. Players may have had their UZR values changed by a run or two at most.

Dave Cameron will have another post up in about 15 minutes going into more detail on the replacement level changes.

On an individual-player basis, I think we can all agree that spring-training statistics suck. If you’re a reader of FanGraphs, or if you’ve even just heard of FanGraphs, you probably understand that these numbers aren’t predictive. Oh, we’ll always allow ourselves to trick ourselves. Giants fans will allow themselves to believe in Brandon Belt, and Mariners fans will allow themselves to believe in Justin Smoak. We can always trick ourselves to believe in the positive while dismissing the negative. But, guns to our heads, we’d all say “Ahh! Put that gun down!” And then we’d acknowledge that, truthfully, even the positive numbers probably don’t mean much.

But now consider spring-training statistics as a group, as a whole. What is spring training but a whole bunch of baseball games between high-level professionals? What are the numbers but reflections of what took place on the field during ordinary baseball games? Just because the numbers probably won’t tell you much about what will happen doesn’t mean they don’t tell you what has happened. That is precisely what they do. And for our purposes here, we can make use of overall, league-wide spring-training statistics.

Read the rest of this entry »

Some of you may recall that before being promoted from a FanGraphs Community Research writer to an actual FanGraphs writer, my primary focus was on the relationship between batted ball types (infield fly balls, in particular) and BABIP for pitchers.  At the time, I’d been leaving park factors out of the equation in a [vain] attempt to keep things simple, but now I want to give them a bit of attention.

Read the rest of this entry »

Not all that long ago, I wrote about Gio Gonzalez striking out a ton of opposing pitchers. Though Gonzalez set a modern-day record, the achievement itself was not entirely surprising: Gonzalez is a durable pitcher who gets a lot of strikeouts, and pitchers strike out a lot as batters. This is because pitchers are by and large terrible batters, dragging down the offensive numbers of the National League. What was more surprising, to me, was something I noticed about R.A. Dickey, which I included in the post as a note.

Dickey is a knuckleballer, and the league’s only knuckleballer worth a damn. He became a regular with the Mets in 2010, and as a Met, he threw more than 600 innings. Over that span, Dickey faced 2,344 non-pitchers, and he struck out 19% of them, or at least 19% of the guys who didn’t sac bunt. Over the same span, Dickey faced 172 pitchers, and he struck out 17% of them, or at least 17% of the guys who didn’t sac bunt. In other words: with the Mets, R.A. Dickey struck out a lower rate of pitchers than position players.

Read the rest of this entry »

Bronson Arroyo has won 115 games in the past nine seasons. He’s also come up big in the postseason. But none of his success has come thanks to overpowering stuff.

The Cincinnati Reds’ right-hander is a craftsman. His fastball rarely reaches 90 mph, and his breaking pitches are more varied than they are exceptional. His strengths are deception and guile. Featuring a high leg kick and multiple arm angles, he delivers a cornucopia of offerings that more than make up for his lack of velocity.

Arroyo talked about his cerebral approach to pitching — and his ability to mix and match with the best of them — last week in Goodyear, Arizona.

——

David Laurila: How do you get guys out?

Bronson Arroyo: It’s never simple, but that’s just the nature of the game. There’s such a fine line between a pop-up to center field and a home run 40 feet over the wall. It’s all about the precision of the bat on the ball, and because of that, there’s nothing concrete about the game. You can never say, “If I throw this breaking ball at 78 mph, on the outside corner at the knees, it won’t get hit hard. “ It might get hit out of the park.

Pitching is kind of like making educated guesses. Where are the places I can go in the strike zone to beat this guy? Where can I go where he’ll do the least amount of damage? And sometimes that changes. You can have the bases loaded in the bottom of the last inning and not be able to afford to give up one run. Sometimes it doesn’t matter if you go to his weak spot, because he ends up hitting a blooper over second base and you still lose. It’s a very tough game, because it never stays the same. There are so many variables.

I’ve been successful over a long period of time by mixing and matching pitches a little differently than most guys. I pitch backwards a lot. I throw a lot of off-speed stuff in fastball counts. I’m also aware of my surroundings. I’m pitching, sometimes — not on a hunch, but on calculations based on a guy’s body language, his eyes, what he did to me last time. He’s watching a videotape of the last time I faced him, and I’m watching the same videotape. I know he’s making adjustments and I have to make them too. Who is going to beat the other to the punch?

It’s this whole mental game for me. I’m not physically dominating. I can’t go out there like Homer Bailey and Johnny Cueto and throw 94-95. I’m throwing 87. It’s harder for me to beat people with brute physical ability, and for that reason I have to spin the ball a little different. Read the rest of this entry »