Sabermetrics

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Bill James, who coined the term "sabermetrics" Bill James 2010.jpg
Bill James, who coined the term "sabermetrics"

In sports analytics, sabermetrics (originally SABRmetrics) is the empirical analysis of baseball, especially baseball statistics that measure in-game activity. Sabermetricians collect and summarize the relevant data from this in-game activity to answer specific questions. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research, founded in 1971. The term "sabermetrics" was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face. [1]

Contents

Early history

Henry Chadwick Henry Chadwick (NYPL b13537024-56451) (cropped).jpg
Henry Chadwick

Henry Chadwick, a sportswriter in New York, developed the box score in 1858. This was the first way statisticians were able to describe the sport of baseball by numerically tracking various aspects of game play. [2] The creation of the box score has given baseball statisticians a summary of the individual and team performances for a given game. [3]

Sabermetrics research began in the middle of the 20th century with the writings of Earnshaw Cook, one of the earliest sabermetricians. Cook's 1964 book Percentage Baseball was one of the first of its kind. [4] At first, most organized baseball teams and professionals dismissed Cook's work as meaningless. The idea of a science of baseball statistics began to achieve legitimacy in 1977 when Bill James began releasing Baseball Abstracts, his annual compendium of baseball data. [5] [6] However, James's ideas were slow to find widespread acceptance. [1]

Bill James believed there was a widespread misunderstanding about how the game of baseball was played, claiming the sport was not defined by its rules but actually, as summarized by engineering professor Richard J. Puerzer, "defined by the conditions under which the game is played--specifically, the ballparks but also the players, the ethics, the strategies, the equipment, and the expectations of the public." [2] Sabermetricianssometimes considered baseball statisticiansbegan trying to replace the longtime favorite statistic known as the batting average. [7] [8] It has been claimed that team batting average provides a relatively poor fit for team runs scored. [7] Sabermetric reasoning would say that runs win ballgames, and that a good measure of a player's worth is his ability to help his team score more runs than the opposing team.

Davey Johnson in 1986 Davey Johnson 1986.jpg
Davey Johnson in 1986

Before Bill James popularized sabermetrics, Davey Johnson used an IBM System/360 at team owner Jerold Hoffberger's brewery to write a FORTRAN baseball computer simulation while playing for the Baltimore Orioles of Major League Baseball (MLB) in the early 1970s. He used his results in an unsuccessful attempt to promote to his manager Earl Weaver the idea that he should bat second in the lineup. He wrote IBM BASIC programs to help him manage the Tidewater Tides, and after becoming manager of the New York Mets in 1984, he arranged for a team employee to write a dBASE II application to compile and store advanced metrics on team statistics. [9] Craig R. Wright was another employee in MLB, working with the Texas Rangers in the early 1980s. During his time with the Rangers, he became known as the first front office employee in MLB history to work under the title "sabermetrician". [10] [11]

David Smith founded Retrosheet in 1989, with the objective of computerizing the box score of every major league baseball game ever played, in order to more accurately collect and compare the statistics of the game.

Billy Beane as a player in 1989 Billy Beane 1989.jpg
Billy Beane as a player in 1989

The Oakland Athletics began to use a more quantitative approach to baseball by focusing on sabermetric principles in the 1990s. This initially began with Sandy Alderson as the general manager of the team when he used the principles toward obtaining relatively undervalued players. [1] His ideas were continued when Billy Beane took over as general manager in 1997, a job he held until 2015, and hired his assistant Paul DePodesta. [8] Through the statistical analysis done by Beane and DePodesta in the 2002 season, the Oakland A's went on to win 20 games in a row. This was a historic moment for the franchise, in which the 20th game was played at the Oakland–Alameda County Coliseum. [12] His approaches to baseball soon gained national recognition when Michael Lewis published Moneyball: The Art of Winning an Unfair Game in 2003 to detail Beane's use of sabermetrics. In 2011, a film based on Lewis' book—also called Moneyball —was released and gave broad exposure to the techniques used in the Oakland Athletics' front office.

Traditional measurements

Sabermetrics was created in an attempt for baseball fans to learn about the sport through objective evidence. This is performed by evaluating players in every aspect of the game, specifically batting, pitching, and fielding. These evaluation measures are usually phrased in terms of either runs or team wins as older statistics were deemed ineffective.

Batting measurements

Ted Williams, the most recent MLB player to bat .400 for a season Ted Williams 1940 Play Ball.jpeg
Ted Williams, the most recent MLB player to bat .400 for a season

The traditional measure of batting performance is considered to be hits divided by the total number of at bats. Bill James, along with other fathers of sabermetrics, found this measure to be flawed, as it ignores any other way a batter can reach base besides a hit. [13] Conversely, on-base percentage (OBP), takes base on balls ("walks") and hit-by-pitches into consideration. [lower-alpha 1] Another issue with the traditional measure of the batting average is that it does not distinguish between hits (i.e., singles, doubles, triples, and home runs) and gives each hit equal value. [13] A measure that differentiates among these outcomes is the slugging percentage (SLG). [lower-alpha 1] To calculate the slugging percentage, the number of total bases of all hits is divided by the total number of times at bat.

Stephen Jay Gould proposed that the disappearance of .400 batting average (last achieved in MLB by Ted Williams in 1941) is actually a sign of general improvement in batting. [15] [16] This is because, in the modern era, players are becoming more focused on hitting for power than for average. [16] Therefore, it has become more valuable to compare players using the slugging percentage and on-base percentage over the batting average. [15]

These two improved sabermetric measures are important skills to measure in a batter and have been combined to create the modern statistic on-base plus slugging (OPS). OPS is the sum of the on-base percentage and the slugging percentage. This modern statistic has become useful in comparing players and is a powerful method of predicting runs scored from a certain player. [17]

Some of the other statistics that sabermetricians use to evaluate batting performance are weighted on-base average, secondary average, runs created, and equivalent average.

Pitching measurements

Ed Walsh, whose career 1.82 ERA is the lowest in MLB history Ed Walsh portrait 1911.jpg
Ed Walsh, whose career 1.82 ERA is the lowest in MLB history

The traditional measure of pitching performance is the earned run average (ERA). It is calculated as earned runs allowed per nine innings. Earned run average does not separate the ability of the pitcher from the abilities of the fielders that he plays with. [18] Another classic measure for pitching is a pitcher's winning percentage. Winning percentage is calculated by dividing wins by the total number of decisions (wins plus losses). Winning percentage is also heavily dependent on the pitcher's team, particularly on the number of runs it scores.

Sabermetricians have attempted to find different measures of pitching performance that exclude the performances of the fielders involved. One of the earliest developed, and one of the most popular in use, is walks plus hits per inning pitched (WHIP), which while not completely defense-independent, tends to indicate how many times a pitcher is likely to put a player on base (either via walk, hit-by-pitch, or base hit) and thus how effective batters are against a particular pitcher in reaching base.

A later development was the creation of defense independent pitching statistics (DIPS) system. Voros McCracken has been credited with the development of this system in 1999. [19] Through his research, McCracken was able to show that there is little to no difference between pitchers in the number of hits they allow on balls put into play—regardless of their skill level. [20] Some examples of these statistics are defense-independent ERA, fielding independent pitching, and defense-independent component ERA. Other sabermetricians have furthered the work in DIPS, such as Tom Tango who runs the Tango on Baseball sabermetrics website.

Baseball Prospectus created another statistics called the peripheral ERA. This measure of a pitcher's performance takes hits, walks, home runs allowed, and strikeouts while adjusting for ballpark factors. [18] Each ballpark has different dimensions when it comes to the outfield wall so a pitcher should not be measured the same for each of these parks. [21]

Batting average on balls in play (BABIP) is another useful measurement for determining pitchers’ performance. [20] When a pitcher has a high BABIP, they will often show improvements in the following season, while a pitcher with low BABIP will often show a decline in the following season. [20] This is based on the statistical concept of regression to the mean. Others have created various means of attempting to quantify individual pitches based on characteristics of the pitch, as opposed to runs earned or balls hit.

Advanced methods

Value over replacement player (VORP) was once considered a popular sabermetric statistic. This statistic demonstrates how much a player contributes to his team in comparison to a hypothetical player that performs at the minimum level needed to hold a roster position on a major league team. This measurement was invented by Keith Woolner, a former writer for the sabermetric group/website Baseball Prospectus.

Wins above replacement (WAR) is another popular sabermetric statistic for evaluating a player's contributions to his team. [22] Similar to VORP, WAR compares a given player to a replacement-level player in order to determine the number of additional wins the player has provided to his team. [23] WAR values vary with hitting positions and are largely determined by a player's successful performance and amount of playing time. [23]

Quantitative analysis in baseball

Many traditional and modern statistics, such as ERA and Wins Shared, don't give a full understanding of what is taking place on the field. [24] :189–198 Simple ratios are not sufficient to understand the statistical data of baseball. Structured quantitative analysis is capable of explaining many aspects of the game, for example, to examine how often a team should attempt to steal. [25]

Applications

Sabermetrics can be used for multiple purposes, but the most common are evaluating past performance and predicting future performance to determine a player's contributions to his team. [17] These may be useful when determining who should win end-of-the-season awards such as MVP and when determining the value of making a certain trade.

Most baseball players tend to play a few years in the minor leagues before they are called up to the major league. The competitive differences coupled with ballpark effects make the exact comparison of a player's statistics a problem. Sabermetricians have been able to clear this problem by adjusting the player's minor league statistics, also known as the Minor-League Equivalency. [17] Through these adjustments, teams are able to look at a player's performance in both AA and AAA to determine if he is fit to be called up to the majors.

Applied statistics

Sabermetrics methods are generally used for three purposes:

  1. To compare key performances among certain specific players under realistic data conditions. The evaluation of past performance of a player enables an analytic overview. The comparison of this data between players can help one understand key points such as their market values. In that way, the role and the salary that should be given to that player can be defined.
  2. To provide prediction of future performance of a given player or a team. When past data is available about the performance of a team or a specific player, Sabermetrics can be used to predict the average future performances for the next season. Thus, a prediction can be made with a certain probability about the number of wins and losses.
  3. To provide a useful function of the player's contributions to his team. When analyzing data, one is able to understand the contributions a player makes to the success/failure of his team. Given that correlation, one can objectively sign or release players with certain characteristics.

Machine learning model

A machine learning model can be built using data sets available at sources such as baseball-reference. This model will give probability estimates for the outcome of specific games or the performance of particular players. These estimates are increasingly accurate when applied to a large number of events over a long term. The game outcome (win/lose) is treated as having a binomial distribution.

Predictions can be made using a logistic regression model with explanatory variables including: opponents' runs scored, runs scored, shutouts, time at bat, winning rate, and pitcher whip.

Advancements from 1985 - present

Bill James' two books, The Bill James Historical Baseball Abstract (1985) and Win Shares (2002) have continued to advance the field of sabermetrics. [26] His former assistant Rob Neyer, who later became a senior writer at ESPN.com and national baseball editor of SBNation, also worked on popularizing sabermetrics since the mid-1980s. [27]

Nate Silver, a former writer and managing partner of Baseball Prospectus, invented PECOTA in 2002–2003, introducing it to the public in the book Baseball Prospectus in 2003. [28] The acronym stands for Player Empirical Comparison and Optimization Test Algorithm, [29] and is a sabermetric system for forecasting Major League Baseball player performance. Simply put, it assumes that the careers of similar players will follow a similar trajectory. This system has been owned by Baseball Prospectus since 2003 and helps the website's authors invent or improve widely relied-upon sabermetric measures and techniques. [30]

Beginning in the 2007 baseball season, MLB started looking at technology to record detailed information regarding each pitch that is thrown in a game. This became known as the PITCHf/x system which is able to record the speed of the pitch, at its release point and as it crossed the plate, as well as the location and angle of the break of certain pitches through video cameras. [13] FanGraphs is a website that favors this system as well as the analysis of play-by-play data. The website also specializes in publishing advanced baseball statistics as well as graphics that evaluate and track the performance of players and teams.[ citation needed ]

See also

Notes

  1. 1 2 On-base percentage and slugging percentage date to at least 1941, [14] pre-dating both Bill James (born 1949) and SABR (formed 1971).

Related Research Articles

Baseball statistics play an important role in evaluating the progress of a player or team.

<span class="mw-page-title-main">On-base percentage</span> Hitting statistic in baseball

In baseball statistics, on-base percentage (OBP) measures how frequently a batter reaches base. An official Major League Baseball (MLB) statistic since 1984, it is sometimes referred to as on-base average (OBA), as it is rarely presented as a true percentage.

On-base plus slugging (OPS) is a sabermetric baseball statistic calculated as the sum of a player's on-base percentage and slugging percentage. The ability of a player both to get on base and to hit for power, two important offensive skills, are represented. An OPS of .800 or higher in Major League Baseball puts the player in the upper echelon of hitters. Typically, the league leader in OPS will score near, and sometimes above, the 1.000 mark.

<span class="mw-page-title-main">Slugging percentage</span> Hitting statistic in baseball

In baseball statistics, slugging percentage (SLG) is a measure of the batting productivity of a hitter. It is calculated as total bases divided by at-bats, through the following formula, where AB is the number of at-bats for a given player, and 1B, 2B, 3B, and HR are the number of singles, doubles, triples, and home runs, respectively:

<span class="mw-page-title-main">Bill James</span> American baseball writer and statistician

George William James is an American baseball writer, historian, and statistician whose work has been widely influential. Since 1977, James has written more than two dozen books about baseball history and statistics. His approach, which he named sabermetrics after the Society for American Baseball Research (SABR), scientifically analyzes and studies baseball, often through the use of statistical data, in an attempt to determine why teams win and lose.

In baseball, a sacrifice bunt is a batter's act of deliberately bunting the ball, before there are two outs, in a manner that allows a baserunner to advance to another base. The batter is almost always put out, and hence sacrificed, but sometimes reaches base on an error or fielder's choice. In that situation, if runners still advance bases, it is still scored a sacrifice bunt instead of the error or the fielder's choice. Sometimes the batter may safely reach base by simply outrunning the throw to first; this is not scored as a sacrifice bunt but rather a single.

<span class="mw-page-title-main">Billy Beane</span> American baseball player and executive (born 1962)

William Lamar Beane III is an American former professional baseball player and current front office executive. He is currently senior advisor to owner John Fisher and minority owner of the Oakland Athletics of Major League Baseball (MLB) and formerly the executive vice president of baseball operations. He is also minority owner of soccer clubs Barnsley of the EFL League One in England and AZ Alkmaar of the Eredivisie in the Netherlands. From 1984 to 1989 he played in MLB as an outfielder for the New York Mets, Minnesota Twins, Detroit Tigers, and Oakland Athletics. He joined the Athletics' front office as a scout in 1990, was named general manager after the 1997 season, and was promoted to executive vice president after the 2015 season.

In baseball, value over replacement player is a statistic popularized by Keith Woolner that demonstrates how much a hitter or pitcher contributes to their team in comparison to a replacement-level player who is an average fielder at that position and a below average hitter. A replacement player performs at "replacement level," which is the level of performance an average team can expect when trying to replace a player at minimal cost, also known as "freely available talent."

<i>Moneyball</i> 2003 book by Michael Lewis

Moneyball: The Art of Winning an Unfair Game is a book by Michael Lewis, published in 2003, about the Oakland Athletics baseball team and its general manager Billy Beane. It describes the team's sabermetric approach to assembling a competitive baseball team on a small budget. It led to the 2011 film Moneyball, starring Brad Pitt and Jonah Hill.

In baseball, fielding independent pitching (FIP) is intended to measure a pitcher's effectiveness based only on statistics that do not involve fielders. These include home runs allowed, strikeouts, hit batters, walks, and, more recently, fly ball percentage, ground ball percentage, and line drive percentage. By focusing on these statistics and ignoring what happens once a ball is put in play, which – on most plays – the pitcher has little control over, DIPS claims to offer a clearer picture of the pitcher's true ability.

<span class="mw-page-title-main">Baseball Prospectus</span> Baseball analytics media company

Baseball Prospectus (BP) is an organization that publishes a website, BaseballProspectus.com, devoted to the sabermetric analysis of baseball. BP has a staff of regular columnists and provides advanced statistics as well as player and team performance projections on the site. Since 1996 the BP staff has also published a Baseball Prospectus annual as well as several other books devoted to baseball analysis and history.

<i>Whatever Happened to the Hall of Fame?</i>

Whatever Happened to the Hall of Fame?: Baseball, Cooperstown, and the Politics of Glory is a book by baseball sabermetrician and author Bill James. Originally published in 1994 as The Politics of Glory, the book covers the unique history of the Baseball Hall of Fame, the evolution of its standards, and arguments for individual players in a typically Jamesian, stat-driven manner. James drives home early on the heated and biased nature of Hall of Fame arguments between fans and writers alike. He states that his goal is not to serve individual players or candidates but to "reinforce the truth in what other people say" and to "serve the argument itself."

Robert "Voros" McCracken is an American baseball sabermetrician. "Voros" is a nickname from his partial Hungarian heritage. He is widely recognized for his pioneering work on Defense Independent Pitching Statistics (DIPS).

Catcher's ERA (CERA) in baseball statistics is the earned run average of the pitchers pitching when the catcher in question is catching. Its primary purpose is to measure a catcher's game-calling, rather than his effect on the opposing team's running game. Craig Wright first described the concept of CERA in his 1989 book The Diamond Appraised. With it, Wright developed a method of determining a catcher's effect on a team's pitching staff by comparing pitchers' performance when playing with different catchers.

Base runs (BsR) is a baseball statistic invented by sabermetrician David Smyth to estimate the number of runs a team "should have" scored given their component offensive statistics, as well as the number of runs a hitter or pitcher creates or allows. It measures essentially the same thing as Bill James' runs created, but as sabermetrician Tom M. Tango points out, base runs models the reality of the run-scoring process "significantly better than any other run estimator".

The 1989 Oakland Athletics season saw the A's finish in first place in the American League West, with a record of 99 wins and 63 losses, seven games in front of the Kansas City Royals. Oakland dominated the American League, earning their second consecutive AL West title, as well as marking the second straight year in which they finished with the best record in all of baseball. A's pitcher Dave Stewart recorded his third straight season of earning 20 or more wins while Rickey Henderson put on a dazzling offensive performance in the postseason as he approached the prospects of landing a three million dollar contract for the following season. The team defeated the Toronto Blue Jays in five games in the ALCS, then swept their cross-Bay rivals, the San Francisco Giants, in an earthquake-marred World Series. The Athletics looked to be a future dynasty by the close of the 1989 season.

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<span class="mw-page-title-main">Earned run average</span> Baseball statistic

In baseball statistics, earned run average (ERA) is the average of earned runs allowed by a pitcher per nine innings pitched. It is determined by dividing the number of earned runs allowed by the number of innings pitched and multiplying by nine. Thus, a lower ERA is better. Runs resulting from passed balls, defensive errors, and runners placed on base at the start of extra innings are recorded as unearned runs and omitted from ERA calculations.

Wins Above Replacement or Wins Above Replacement Player, commonly abbreviated to WAR or WARP, is a non-standardized sabermetric baseball statistic developed to sum up "a player's total contributions to his team". A player's WAR value is claimed to be the number of additional wins his team has achieved above the number of expected team wins if that player were substituted with a replacement-level player: a player who may be added to the team for minimal cost and effort.

Sports analytics are collections of relevant historical statistics that can provide a competitive advantage to a team or individual. Through the collection and analysis of these data, sports analytics inform players, coaches and other staff in order to facilitate decision making both during and prior to sporting events. The term "sports analytics" was popularized in mainstream sports culture following the release of the 2011 film, Moneyball, in which Oakland Athletics General Manager Billy Beane relies heavily on the use of baseball analytics, building upon and extending the established practice of Sabermetrics, to build a competitive team on a minimal budget.

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