Sabermetrics

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Sabermetrics 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]

Early history[edit]

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

Sabermetrics research began in the middle of the 20th century. Earnshaw Cook was one of the earliest researchers that contributed to this idea. Cook gathered the majority of his research into his 1964 book, Percentage Baseball. The book was the first of its kind to gain national media attention,[4] although it was widely criticized and not accepted by most baseball organizations. The idea of advanced baseball statistics did not become prominent in the baseball community until Bill James began writing his annual Baseball Abstracts in 1977.[5][6]

Bill James believed that people misunderstood how the game of baseball was played, claiming that it is actually defined by the conditions under which the sport is played.[2] Sabermetricians, sometimes considered baseball statisticians, began 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.

Before Bill James was able to bring the concept of sabermetrics to known topic, 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 in the early 1970s. He unsuccessfully used his results in an attempt to propose the idea that he should bat second in the lineup to his manager Earl Weaver. 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 Major League Baseball, 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]

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 former 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] 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 to further provide insight into the techniques use in the Oakland Athletic's front office.

Measure of Sabermetrics[edit]

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[edit]

The traditional measure for batting performance is considered to be the batting average. Bill James, along with other fathers of sabermetrics, proved this measure to be flawed as it ignores any other way a batter can reach base besides a hit.[12] This lead to the creation of the On-base percentage, which takes walks and hit-by-pitches into consideration.

Another flaw with the traditional measure of the batting average is that it will not take doubles, triples and home runs into consideration and will give each hit the same value.[12] Thus, a measure that will distinguish between these different hit outcomes, the slugging percentage, was created. Stephen Jay Gould proposed that the disappearance of .400 batting average is actually a sign of general improvement in batting.[13][14] This is because in the modern era, players are becoming more focused on hitting for power than for average.[14] Therefore, it has become more valuable to compare players using the slugging percentage and on-base percentage over the batting average.[13]

These two improved sabermetric measures are important skills to measure in a batter and have been combined to create the modern statistic OPS. On-base plus slugging 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.[15]

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[edit]

The traditional measure for pitching performance is considered to be the earned run average. This statistic provides the number of runs that a pitcher allows per game. It has proven to be flawed as it does not separate the ability of the pitcher from the abilities of the fielders that he plays with.[16] Another classic measure for pitching is a pitcher's winning percentage. This statistic can also be flawed as it is dependent on the pitcher's teammates' performances at the plate and in the field.

Sabermetricians have attempted to find different measures of pitching performance that does not include the performances of the fielders involved. This lead to the creation of defense independent pitching statistics (DIPS) system. Voros McCracken has been credited with the development of this system in 1999.[17] Through his research, McCracken was able to show that there is little to no difference between pitchers in the amount of hits a they allow, regardless of their skill level.[18] 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 hit, walks, home runs allowed, and strikeouts while adjusting for ballpark factors.[16] 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.[19]

Batting average on balls in play (BABIP) is another useful measurement for determining pitcher's performance.[18] 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.[18]

Fielding Measurements[edit]

The traditional measure for fielding performance is considered to be the fielding percentage. Though this statistics is able to measure a fielder's success rate when they field a ball, but it does not take into account the balls that may be out of the player's reach.[19] This has led sabermetricians to develop other measures for evaluating defense. One of these measurements is known as Defensive Average, which divides the field into zones to determine the responsibilities for each fielder.[20] Every ball hit within a fielder's zone is considered an opportunity for that fielder and if the fielder is able to make a play, he will be rewarded a credit for the play made.

Another measurement for fielding performance is the range factor. This statistic can be determined by dividing putouts and assists by the number of innings or games played at a given defense position.[21] Players are evaluated on the total amount of outs they can produce for their team, and if they are able to cleanly handle the balls that are hit into their zone.

Some of the other statistics that sabermetricians use to evaluate fielding performance are defensive runs saved and ultimate zone rating.

Other Measurements[edit]

Value over replacement player (VORP) is considered a popular sabermetric statistic. This statistic demonstrates how much a player contributes to his team in comparison to a fake replacement player that performs below average.[6][7] This measurement was founded by Keith Woolner, a former writer for the sabermetric group/website Baseball Prospectus.

Wins above replacement (WAR) is another popular sabermetric statistic that will evaluate a player's contributions to his team.[22] Similar to VORP, WAR compares a certain 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 their amount of playing time.[23]

Functions[edit]

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.[15] 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 problems. Sabermetricians have been able to clear this problem by adjusting the player's minor league statistics, also known as the Minor-League Equivalency (MLE).[15] 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.

Modern Advancements[edit]

Many sabermetricians are still working hard to contribute to the field through creating new measures and asking new questions. Bill James' two Historical Baseball Abstract editions and Win Shares book have continued to advance the field of sabermetrics, 25 years after he helped start the movement.[24] His former assistance Rob Neyer, who is now a senior writer at ESPN.com and national baseball editor of SBNation, also worked on popularizing sabermetrics since the mid-1980s.[25]

Nate Silver, a former writer and managing partner of Baseball Prospectus, invented PECOTA. This acronym stands for Player Empirical Comparison and Optimization Test Algorithm,[26] and is a sabermetric system for forecasting Major League Baseball player performance. 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.[27]

Beginning in the 2007 baseball season, the MLB started looking at technology to record detailed information regarding each pitch that is thrown in a game.[28] 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 though video cameras.[28] 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.

Popular culture[edit]

See also[edit]

References[edit]

Notes
  1. ^ a b Lewis, Michael M. (2003). Moneyball: The Art of Winning an Unfair Game. New York: W. W. Norton. ISBN 0-393-05765-8. 
  2. ^ a b c Puerzer, Richard J. (Fall 2002). "From Scientific Baseball to Sabermetrics: Professional Baseball as a Reflection of Engineering and Management in Society". NINE: A Journal of Baseball History and Culture. 11: 34–48 – via Project Muse. 
  3. ^ "BaseballHallofFame.org". 
  4. ^ Albert, James; Jay M. Bennett (2001). Curve Ball: Baseball, Statistics, and the Role of Chance in the Game. Springer. pp. 170–171. ISBN 0-387-98816-5. 
  5. ^ "Bill James, Beyond Baseball". Think Tank with Ben Wattenberg. PBS. June 28, 2005. Retrieved November 2, 2007. 
  6. ^ Ackman, D. (May 20, 2007). "Sultan of Stats". The Wall Street Journal. Retrieved November 2, 2007. 
  7. ^ a b Jarvis, J. (2003-09-29). "A Survey of Baseball Player Performance Evaluation Measures". Retrieved 2007-11-02. 
  8. ^ a b Kipen, D. (June 1, 2003). "Billy Beane's brand-new ballgame". San Francisco Chronicle. Retrieved November 2, 2007. 
  9. ^ Porter, Martin (1984-05-29). "The PC Goes to Bat". PC Magazine. p. 209. Retrieved 24 October 2013. 
  10. ^ RotoJunkie - Roto 101 - Sabermetric Glossary (powered by evoArticles)
  11. ^ BaseballsPast.com
  12. ^ a b Albert, Jim (2010). Sabermetrics: The Past, the Present, and the Future (PDF). 
  13. ^ a b Gould, Stephen Jay (2003). "Why No One Hits .400 Anymore". Triumph and Tragedy in Mudville: A Lifelong Passion for Baseball. W. W. Norton & Company. pp. 151–172. ISBN 0-393-05755-0. 
  14. ^ a b Agonistas, Dan (4 August 2004). "Where have the .400 hitters gone?". Retrieved 30 August 2016. ... The discussion revolved around an essay that Gould wrote for Discover magazine in 1986 and that was reprinted both in his 1996 book Full House and in Triumph and Tragedy under the title "Why No One Hits .400 Anymore" ... 
  15. ^ a b c Grabiner, David J. "The Sabermetric Manifesto". The Baseball Archive. 
  16. ^ a b McCracken, Voros (January 23, 2001). "Pitching and Defense: How Much Control Do Hurlers Have?". Baseball Prospectus. 
  17. ^ Basco, Dan; Davies, Michael (Fall 2010). "The Many Flavors of DIPS: A History and an Overview". Baseball Research Journal. 32 (2). 
  18. ^ a b c Ball, Andrew (January 17, 2014). "How has sabermetrics changes baseball?". Beyond the Box Score. 
  19. ^ a b Baumer, Benjamin; Zimbalist, Andrew (2014). The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball. University of Pennsylvania Press – via JSTOR. 
  20. ^ Albert, Jim (2010). Sabermetrics: The Past, the Present, and the Future (PDF). 
  21. ^ Baseball-Reference.com (Fielding Stats Glossary)
  22. ^ Fangraphs: WAR
  23. ^ a b Schoenfield, David (July 19, 2012). "What we talk about when we talk about WAR". ESPN.com. 
  24. ^ Neyer, Rob (November 5, 2002). "Red Sox hire James in advisory capacity". ESPN.com. Retrieved March 7, 2009. 
  25. ^ Jaffe, C. (October 22, 2007). "Rob Neyer Interview". The Hardball Times. Retrieved November 2, 2007. 
  26. ^ "Baseball Prospectus | Glossary". www.baseballprospectus.com. Retrieved 2016-05-05. 
  27. ^ "Baseball Prospectus". Retrieved 2012-03-04. 
  28. ^ a b Albert, Jim (2010). Sabermetrics: The Past, the Present, and the Future (PDF). 

External links[edit]