“A box score is more than a capsule archive. It is a precisely etched miniature of the sport itself, for baseball, in spite of its grassy spaciousness and apparent unpredictability, is the most intensely and satisfyingly mathematical of all our outdoor sports.”
—
Roger Angell, The New Yorker
Angell penned those lines for The New Yorker in the 1960s, when the promise of a new spring made him increasingly eager for his morning paper.
There, over a half a cup of coffee, he could review the stat lines of Ferguson Jenkins, Al Kaline, Juan Marichal, Tony Oliva and “other ballplayers — favorites and knaves — whose fortunes I follow from April to October.”
Reconstructing a ballgame took some imagination in those days, even for someone adept at interpreting a hitter’s stat line like 4-1-2-2.
In contrast, anyone currently gearing up to follow the exploits of Mike Trout, Bryce Harper or Clayton Kershaw will find that the “precisely etched miniature” of yore has exploded into a sweeping, 3-D panorama.
It’s like opening Pandora’s batter’s box.
The double play might go 6-4-3 if you’re scoring at home, but MLB’s Statcast is capturing that same play with radar technology that also has been used to track space shuttles — seriously — and recording each pitch at 40,000 frames per second.
Statcast will use optical tracking technology to follow base runners up the line at 25 frames per second, while also capturing the distance a fielder ran to make a catch and the velocity of the relay throw to first.
The modern-day box score might require trips to websites such as FanGraphs, The Hardball Times, Baseball Prospectus and BrooksBaseball, but it is possible to now know, for example, that A’s ace Sonny Gray was throwing curveballs that swerved with a 9.10-inch horizontal break.
And that Giancarlo Stanton of the Miami Marlins bashed a ball that left his bat at 120.3 mph.
And that a curveball from Collin McHugh of the Houston Astros twirled in with a spin rate of 2,538, far better than the league average of 2,307.
You might not be ready to embrace all those numbers, but start brushing up. Advanced metrics — the source of tired jokes about nerds in their mothers’ basements — are a now regular part of major league clubhouses, as common as sunflower seeds and pine tar.
“The information that we have available to us is ‘everything,’ ” Giants reliever George Kontos said. “Every pitch is documented: That’s any pitcher throwing to any hitter of any game in the major leagues. If there is something that’s not available to us in the packets, we can ask for it, and we can have it in 10 minutes.”
The silly debate over Scouting vs. Stats is over. The answer is unequivocally both. Almost every major league team has some sort of analytics department; no team is shuttering its traditional scouting department.
Consider the example of the Giants’ three World Series championship teams. In advance of every series, coaches provided players with a scouting report that blended the comprehensive observations of a real human with selected statistical data that goes as deep as a player needs.
“Yeah, whew,” second baseman Joe Panik said, smiling wide.
“Let’s say we enter a series with the Dodgers: We have a book of all the pitchers and their stats that show the percentages of what they throw in what counts. It really is amazing. Location charts. Velocity charts.
“There is so much available to us that you kind of have to pick and choose. What’s your game plan against certain guys?”
And to think: As baseball blossoms anew in 2016, the game is on the cusp of breakthroughs that could change our understanding of it.
* * *
“This encompassing neatness permits the baseball fan, aided by experience and memory, to extract from a box score the same joy, the same hallucinatory reality, that prickles the scalp of a musician when he glances at a page of his score of ‘Don Giovanni’ and actually hears bassos and sopranos, woodwinds and violins.”
Dave Cameron, 35, grew up without a television in his Seattle-area home. He listened to Mariners games on the radio as a kid but eventually wanted to know what the players looked like. So Cameron bought pack after pack of baseball cards at his local 7-Eleven.
Putting faces with the names had a flip side: The backs of the baseball cards were chock-full of numbers — averages, home runs, steals and RBIs.
“I just kind of fell in love with the statistics of baseball that way,” Cameron said.
He grew up to become an influential writer for FanGraphs.com. A’s executives Billy Beane and David Forst are among his fans.
FanGraphs, launched in 2005, found its niche by featuring advanced info — fly ball rates, line drive percentages, strikeout rates, etc. — that provided data that made it easier to understand and predict performance. It also created its own version of wins above replacement (WAR) and fielding independent pitching (FIP).
The site was an immediate boon to fantasy players and MLB front offices alike. The Washington Post, which recently detailed FanGraphs’ evolution, reported that in 2015, the site had roughly 1 million unique users per month — including regular visits from front office members of nearly every major league club.
“I like to think of FanGraphs as kind of the pinnacle of the online sabermetric community,” Josh Weinstock, an analyst in the Nationals’ baseball research and development department, told Post writer Barry Svrluga. “I really view it as the focal point through which people can more rigorously study baseball in a more quantitative way.”
Now, technology is making it possible to dive deeper. The radar-tracking data from MLB’s Statcast and Baseball Info Solutions make the info on the back of Cameron’s old baseball cards look like cave dwellings.
They just need to figure out what it means.
“I don’t think there’s any question that this new tracking data has the potential to revolutionize how we understand and how we see baseball,” Cameron said by phone from his home in North Carolina. “But we’re probably five or 10 years away from making really big sweeping conclusions.”
Cameron used the example of pitch framing. PITCHf/x began compiling precise pitch location in 2006. But it wasn’t until 2011 that Mike Fast, then an analyst for Baseball Prospectus, was able to isolate the value of a savvy catcher working his glove behind the plate.
He concluded that a receiver adept at framing pitches — catching a ball in a way that makes it look like a strike — could have a major effect on the game. Jose Molina, who was good at it, was worth 35 runs above average over 120 games; Ryan Doumit, who wasn’t, was worth 26 runs below average.
“That took five years before we got a real tangible metric that changed the way we saw the game,” Cameron said. “I wouldn’t be surprised if there was something similar with Statcast, where we have a treasure trove of data and really no idea how to use it.
“People are quoting exit velocity all the time” — that is, how fast a ball leaves a hitter’s bat — “but we don’t really know how well that ages. We have one year of data.
“If you hit the ball 97 mph when you’re 24, what does that mean when you’re 27? We have no idea.”
* * *
“Every player in every game is subjected to a cold and ceaseless accounting; no ball is thrown and no base is gained without an instant responding judgment — ball or strike, hit or error, yea or nay — and an ensuing statistic.”
A handful of notable players, such as Zack Greinke of the Diamondbacks, Brandon McCarthy of the Dodgers and Glen Perkins of the Twins, are outspoken advocates of the new wave of statistics.
Others are still finding their way.
Giants first baseman Brandon Belt is well aware of his BABIP — batting average on balls put in play — as well he should be. Belt’s .363 mark last season ranked 11th in the majors last season, just a few ticks below MVP Bryce Harper (.369).
FanGraphs.com also notes that Belt’s 39.5 percent hard hit rate was barely behind Miguel Cabrera and Mike Trout, good for ninth in the league. Belt also is coming off a career-high line drive rate of almost 29 percent. But as someone open to looking at the stats in the scouting report, Belt said it’s tricky to balance the benefits of information with the perils of overthinking.
“I had a tough time with it early on in my career,” he said. “It’s taken a while to get that out of my head and just go play baseball.”
Panik, who made the All-Star team last year in his first full season, said his daily ritual includes studying some stats — then pushing them to the back of his mind. He will study the percentages of an opposing pitcher’s pitch sequencing (“What do they throw in what counts? What pitch does he go to when he’s in trouble?” Panik said). He does this work before batting practice, then slowly makes his transformation back from scholar to ballplayer.
“Once you get in the batter’s box, you clear your mind, and you go to work,” he said. “When you’re in the box, you don’t want to be thinking those things. You just want to see the ball, hit the ball.”
But no one, teammates say, handles the balance better than catcher Buster Posey. The three-time All-Star prepares meticulously before the game, inhaling massive quantities of video and statistical information.
Then he will spit it all out like a bad wad of gum if the situation dictates.
“You have to pick and choose what stats you are going to look at,” Posey said. “I think it’s great. I think it’s very beneficial. But at the same time, you have to use your instincts.”
* * *
This is a statistical evolution, not a revolution. Stats are as interwoven with the game as the stitches on a baseball. The writer Alan Schwarz opens his book “The Numbers Game” about the history of baseball stats with a box score from 1858.
He also recounts the story of Allan Roth, the first full-time statistician ever hired by a major league club. Branch Rickey hired Roth after the 1947 season. And it was Roth who helped persuade the Brooklyn Dodgers to trade Dixie Walker, even though the right fielder hit .306.
Why? Roth had kept diagrams of where each batter’s hits went — the first “spray chart” — and noticed that Walker was no longer pulling the ball, a sign that his bat speed was trending downward. (Yep: Walker was out of the league two years later.) “Baseball is a game of percentages,” Roth once explained. “I try to find the actual percentage.”
The timeline is filled with luminaries from Bill James to John Dewan to Rob Neyer and Brian Kenny.
And, for the younger generation, there is Brad Pitt.
—’Moneyball’ was the moment,” said Sam Miller, the editor-in-chief of Baseball Prospectus. “Before that, there were smart guys who knew each other on the Internet. But that was about it. And they clearly felt like an outsider culture.”
In his book “Moneyball,” writer Michael Lewis chronicled how Beane used statistical analysis to help make the small-payroll A’s a regular-season powerhouse. The book came out in 2003 and the movie, starring Pitt, in 2011.
“After ‘Moneyball,’ there was a huge boom in business at Baseball Prospectus, and there was a huge change in the prestige and in the number of people who identified as fans of sabermetrics,” said Miller, who lives in San Carlos.
It was a movement that launched a thousand WHIPs (walks plus hits per innings pitched). After “Moneyball,” more and more fans started to look at stats to win their fantasy leagues, realizing that traditional stats such as RBIs were often deceptive measures of a player’s value.
But as a measure of how rapidly things are changing, Miller points to how quaint even “Moneyball” looks by comparison. Beane’s most memorable coup in those days? He recognized the under-market value of on-base percentage.
“What Billy Beane was doing was supposedly radical and revolutionary,” Miller said. “And he had access to probably less data than you can pull up on your cellphone in the next 30 seconds.”
