If you’re like most baseball fans, you enjoy following a major league team, going to a few games now and then, paying attention to the standings, and you’re thrilled when your team makes a smart trade. Of course, you are also thrilled if your team has a good season and makes a deep run into the playoffs.
The typical fan enjoys the game of baseball season to season—in spite of the sideshows that sometimes get in the way, like contract disputes, steroid use and suspensions.
But for some ardent fans—and certainly for many general managers, scouts, fantasy baseball participants and sports talk-show hosts—there’s a whole other game inside the game they pay attention to, where statistics of every kind are created and sliced and diced in so many ways by analysts that it reduces the game to formulas and spreadsheets.
At its most serious level, all the number crunching of stats is called advanced analytics or, more commonly, sabermetrics.
Stats and labels have always been around. This is different.
To many fans, that term brings to mind the book and movie Moneyball, which is about the Oakland Athletics, General Manager Billy Beane and his use of analytics and statistics. (Haven’t seen it? You should…it’s a fun baseball movie, although much of it is exaggerated, Hollywood-style.)
Since the arrival of sabermetrics, new categories of statistics have arisen, well beyond batting average and earned run average. The new brand of statistics is meant to determine if a player is really as productive or valuable to a team as he is perceived to be.
If you’re an old-school baseball fan, you probably don’t know too much about sabermetrics…and you might not even care to know. But because these sabermetric-type terms are becoming more commonplace, it might be worthwhile to learn just a few of them. Let’s start right at the beginning.
What is sabermetrics?
Don’t think “light saber” or any other sharp tool. “Saber” comes from the acronym SABR, which stands for Society for American Baseball Research. SABR is an organization dedicated to the study of baseball in a variety of categories—and advanced analytics is only one of those categories.
Sabermetrics is the intense study and analysis of baseball performance, using player statistics and compiled mathematical formulas and equations. It’s complicated stuff, not for the fainthearted or math-challenged.
A man named Bill James is credited with coining the phrase sabermetrics. James and two other gentlemen—members of SABR—created its Statistical Analysis Committee in 1974.
Here are a few of the most common sabermetrics terms:
• OPS—On-base Plus Slugging. OPS is calculated as the sum of a player’s on-base percentage and slugging average. It essentially looks at two factors that are important to managers: the ability for a player to get on base and to hit for power. The great ones will have an OPS of .900 or more. The league leader in OPS is right around the 1.000 mark. The highest OPS numbers of all time belong to Babe Ruth, Ted Williams, Lou Gehrig and Barry Bonds.
• OBP—On-Base Percentage. OPB measures how often a batter reaches base (not counting an error, fielder’s choice, etc.). It’s the “on-base” factor used in OPS.
• WAR—Wins Above Replacement. You’ve got a solid player in your lineup. He’s exciting, fans love him and he gets clutch hits now and then—but just how valuable is he? Fans don’t care, but statisticians ask those kinds of questions. The WAR value comes from figuring out (using complicated formulas) how many “extra” wins that player is worth to the team if, let’s say, he weren’t on the team and in his place you had an average replacement. Yes…there are calculations for that sort of category now.
• WHIP—Walks plus Hits-per-Innings Pitched. WHIP gives analysts an idea of how a pitcher performs when it comes to allowing batters to reach base, either through hits or walks. WHIP is calculated by adding up the number of walks and hits the pitcher gives up, and then dividing it by the number of innings pitched. It focuses not on runs given up, as in earned run average (ERA), but the number of runners the pitcher allows on (or keeps off) the bases. Pedro Martinez has the lowest single-season WHIP in MLB history, with a figure of 0.7373, from when he pitched for the Boston Red Sox in 2000.
There are dozens more stats that sabermaticians have devised to analyze, categorize and rank today’s baseball players, as well as players from eras long past.
Baseball analytics has been around a long time. In the book The Sabermetric Revolution by Benjamin Braumer and Andrew Zimbalist, it’s noted that a sportswriter named Henry Chadwick proposed a way to examine an outfielder’s fielding ability. He also wrote on the importance of not making an out, which is different from simply getting a hit. Both of those notions would later become part of the sabermetric way of looking at things.
Henry Chadwick was one of America’s first well-known baseball reporters, writing about the sport in the 1860s and beyond. Born in England in 1824, he became a journalist in 1850 and died in 1908. He created the modern “box score” and the abbreviation “K” for a strikeout. Henry Chadwick also happens to be the only journalist in the National Baseball Hall of Fame, and SABR gives a Henry Chadwick Award annually.
What does it all mean?
Sabermetrics digs for answers to questions that try to get at the heart of a player’s performance and worth to a team: How did he REALLY do? Did he REALLY help our team, or is he getting paid more than he’s worth…according to sabermetrics?
Can sabermetrics measure the heart of a player, what he means to the dugout or to the fans? Those are some of the issues that bother fans who don’t want to see their team’s roster change faster than the menu at the local coffee shop.
One thing is for sure: As teams pay more for players, and as players switch teams every few years through free agency, sabermetrics will continue to be part of the player evaluation process.
That’s why virtually every major league team has someone on staff devoted to statistical research. It’s just part of the game of baseball in the 21st century