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WAR: What is it good for?

An in-depth look at advanced stats in baseball and how its changed fans' views

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Posted: Saturday, March 2, 2013 12:00 am | Updated: 8:06 pm, Sun Apr 21, 2013.

For Miguel Cabrera, the 2012 baseball season was a historic one. He completed the first major league Triple Crown since Carl Yastrzemski in 1967. It was an accomplishment many thought would not be achieved since Yaz’s historic 1967 season.

Cabrera, widely considered the best hitter in baseball, was always the player people close to the game hypothesized would be the one to do so, if ever. Known as a player who would hit for average and drive in as many runs as he humanly could, Cabrera would go on a tear in September, hitting 10 home runs and knocking in 27 RBIs to lock up the first Triple Crown in 45 years.

This historic feat would further Cabrera’s case as a future hall of fame player, while also easily locking up the first MVP award the illustrious slugger always had come so close to, but never achieved. The Most Valuable Player award is typically handed out to the best player in each league (American League and National League) annually, so with the Triple Crown in hand, it would seem that Cabrera winning the award would merely be a formality.

The only problem is that, according to the principals of sabermetrics and the Wins Above Replacement (WAR) statistic, Cabrera wasn’t the best player in the American League. That distinction belonged to rookie centerfielder Mike Trout of the Angels. This is the point at which sabermetrics finally came to the forefront of all the minds of baseball fans.

The history of sabermetrics is murky, but its humble origins are not. Sabermetrics namesake is the Society for American Baseball Research (SABR). An organization founded in Cooperstown, NY in 1971 as 15 researchers came together outside of the National Baseball Hall of Fame to form the organization. SABR’s membership has grown from 15 baseball fans in 1971 to over 6,000 members worldwide today. Statistical analysis is just one facet of SABR, however, they also have groups dedicated to Baseball and the Arts,

The Deadball Era, Women in Baseball, etc. SABR’s influence is so great, it once prompted Ernie Harwell to say, “SABR is the Phi Beta Kappa of baseball, providing scholarship which the sport has long needed… an excellent way for all of us to add to our enjoyment of the greatest game."

SABR’s principles of advanced statistical analysis would not begin to enter the baseball mainstream until a night security guard in Lawrence, Kan., decided in 1977 to publish one of the most historically important pieces of baseball literature the game would ever see.

In that year, Bill James published the “1977 Baseball Abstract: Featuring 18 categories of Statistical Information You Just Can’t Find Anywhere Else”. It was James’ rabid fandom combined with his studies in economics and literature at the University of Kansas that drove him to pore over baseball statistics on a nightly basis at his watch desk and ask himself questions such as, “baseball keeps copious records, and people talk about them and argue about them and think about them a great deal. Why doesn't anybody use them? Why doesn’t anybody say, in the face of this contention or that one, ‘Prove it'?”

James enjoyed gathering stats and examining them in such an unconventional way that even though he only sold 75 copies of his initial book, he would go on to publish a second edition in 1978, this time selling 250 copies. This gradual success led to James’ works being published by Ballantine Books in 1982 and releasing his unique take on statistical analysis in a yearly report now known simply as “The Bill James Handbook.” Eventually, James would become partnered with STATS, Inc. and coin the term sabermetrics, expressing his fondness for SABR.

Eventually, it wasn’t just the fans taking notice of James’ talents for analyzing the game in such a unique way. People on the inside of clubhouses across the country began to take notice as well. In the current day, James’ expertise has earned him a spot in the front office of the Boston Red Sox.

The aforementioned quote from James above is provided by author Michael Lewis and used in his book, “Moneyball.” “Moneyball” is the story of Oakland Athletics General Manager Billy Beane and his quest to conquer the free-spending teams in MLB with his own band of players mostly being paid the league minimum. To do this, Beane studied the moves of his predecessor, former Athletics GM Sandy Alderson (a long time reader of Bill James), and teamed up with Paul DePodesta, a Harvard graduate with his degree in economics, to find a new way to evaluate players outside of traditional statistics, thus being able to find talent that could contribute and be paid near the league minimum. Beane’s Athletics teams have never won a World Series, but they annually are in the conversation of the best clubs in baseball while maintaining one of the lowest payrolls in MLB.

History lessons aside, what is the real world application of sabermetrics to the game of baseball? Why should anyone care? The answer is simple. Sabermetrics offers scouts a way to analyze the individual contributions of each player on the field, in the batter’s box and on the pitcher’s mound regardless of how well their teammates perform. Sabermetrics also provide scouts with more effective methods of forecasting future performance of players.

One of the singular, most important ways to judge a hitters contribution offensively is the weighted on base average, or wOBA. Fangraphs cites wOBA as “the most important and popular catch-all offensive statistics.”

The difference between wOBA and traditional batting statistics like on-base percentage, batting average and slugging percentage are how hits and walks are weighed against each other. OBP (with the walk statistic), like batting average (with the hit statistic), counts each method of reaching base as equal.

While slugging percentage does try to weight singles, double, triples and home runs to varying degrees it fails in this attempt by weighing doubles twice as important as singles, triples three times as important and home runs being quadruple the value of a single. The simple truth is the value of each method of reaching base is not that simple to calculate. The wOBA stat uses linear weights to value each method of reaching base, from the hit by pitch to the long ball.

What are linear weights? In short, they are the effectiveness of a specific method of reaching base averaged over seasons and specific situations. For example, with a runner on second and two outs--working a walk is fine, as the final out was not created, but it is not as important as a single that may score the run or a double into the gap that would assuredly score the run on second. However, with the bases empty, we could weigh a walk with two outs to be just as effective as the single as one base was achieved and the final out was not made. Over the course of the season, all of these scenarios are taken into account and averaged, creating their weights.

With these weights, the wOBA statistics accounts for every offensive contribution by a specific player over the course of a season and packages them into one tidy number that can more accurately be presented into a metric clearly defining the capabilities each player brings to their respective team and lineup. The statistic is expressed as a percentage much like BA and OBP. Typically a wOBA above .400 is considered outstanding, .300-.400 is considered average to great and anything under .300 is considered below average.

The game of baseball goes far beyond the contributions of the players who hit, however. What about the pitcher tasked with getting hitters out and protecting the leads given to them by their offense? How does sabermetrics affect them? One major statistic sabermetrics uses in the evaluation of the pitcher is known as Fielding Independent Pitching, or FIP. FIP attempts to measure the individual contributions of pitchers to their team by removing factors like the defensive capabilities of their teammates behind them.

Instead, the focus in calculating FIP is on the factors completely in the pitchers control, such as strikeouts, walks, hit batters and home runs. FIP attempts to deemphasize balls batted into play and focus on the aforementioned factors, using the previously mentioned linear weights to assign value to each of these occurrences.

FIP has grown to become one of the most useful metrics to measure the value of a pitcher over the course of a season, however, many do not use it for evaluation on a single game basis. It is also expressed in the same terms as ERA. In real numbers, an FIP below 3.2 is considered outstanding, between 3.2 and four is great to average and above four is typically subpar.

A final sabermetric stat is one that everybody in Detroit and Anaheim is at least somewhat aware of, WAR. WAR is the attempt of sabermetricians to take individual major league players and assign them a specific value to their team relative to a singular constant--the replacement player.

The replacement player, in the eyes of sabermetricians, is the player who takes the spot in the field of the starter who cannot play due to injury or other various reasons (in today’s game, one could easily speculate a team needing the replacement-level player for suspensions handed down for various drug-related suspensions). The replacement player is the player who comes off the bench or receives the call from the minor leagues and provides the bare minimum production required to be considered a viable major leaguer.

This is where the debate last fall reared its ugly head. Cabrera’s historic season at the dish opened the eyes of many as to how feared and great he was as a hitter, but what about the other aspects of the game he was playing? Cabrera typically is a slow baserunner, isn’t a very good defensive third baseman – he was very lacking in range, a stat that can be quantified with the Ultimate Zone Rating sabermetric statistic – and he did not run the bases on balls in play very well.

Trout, on the other hand, had himself a very great year at the plate, hitting for average and power (obviously not as well as Cabrera in this regard), but he also was the best defensive centerfielder in baseball – centerfield is widely considered one of the toughest defensive positions to play – and when he was on the basepaths--he was a terror, a sheer force to be reckoned with.

They each played different positions, had two different spots in their respective lineups, and approached the game in completely different ways. So how do you truly rate their individual contributions with such inherent differences between them? It came down to WAR.

The problem the MVP voters faced was to either give Cabrera the MVP for making history or to use the sabermetric approach that favored Trout? Historically, Trout’s season – according to WAR -- was not just amazing due to him being a rookie, it was one of the greatest season’s ever. Trouts’ score of 10 WAR was first in the AL compared to Cabrera’s 7.1 (still an outstanding tally, although it was third in the AL behind Trout and the Yankees Robinson Cano). In the end, the voters gave Cabrera a deserved MVP and Trouts day will have to come some other time.

The unfortunate circumstances that surround WAR are that the two leading baseball research websites – Fangraphs and Baseball-Reference -- calculate the statistic differently. Sometimes, but not often, this will lead to discrepancies of up to 2 WAR or more. This is one reason why many appreciate the reasoning behind the statistic but still have not fully come to embrace it.

WAR has already begun to become a topic in contract negotiations, as teams and players find it an interesting negotiating tool to use. Fangraphs even has a table listing the average dollar amounts, by position, that each WAR typically nets a player. However, free agency is typically a bonanza of millions of dollars being spent recklessly, so most players are still vastly overpaid due to the salary structure (or lack thereof) of MLB.

These three statistics are merely a starting point for someone interested in sabermetrics and all of the formulas for calculating these stats and their explanations and applications can be found at Fangraphs and Baseball-Reference.

Heed this final thought as you ponder advanced stats, Tigers fans: If you thought WAR was the tool of “nerds” and those outside the game, if you scoffed at sabermetrics and knew Cabrera was the easy winner in the MVP vote, then you must be happy Justin Verlander didn’t win the AL Cy Young last season. He did lead all MLB pitchers in WAR, after all.

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