Sunday, October 31, 2010

What is Sabermetrics?

Now that Sandy Alderson is the Mets GM, he will using Sabermetrics as a measurement in our team performance.

Sandy Alderson as general manager of the Oakland Athletics began focusing on sabermetric principles toward obtaining relatively undervalued players as a result of directives from new owners Stephen Schott and Ken Hofmann to slash payroll in 1995.

Alderson's successor and protégé Billy Beane has been the Athletics' general manager since 1997. Although not a public proponent of sabermetrics, it has been widely noted that Beane has steered the team during his tenure according to sabermetric principles. Since the Athletics have lower revenues and are considered a small market team, Beane's use of sabermetrics to capitalize on what are perceived to be undervalued talents is sometimes credited with keeping the A's competitive with larger market teams like the Yankees and Red Sox.

Alderson who is looking to hire Paul Depodesta as a statistical analysis for the Mets.

Paul DePodesta was a key figure in Michael Lewis' book Moneyball: The Art of Winning an Unfair Game. It was in this book that sabermetric baseball analysis was thrust into the mainstream.

At the age of 31, he was named general manager of the Los Angeles Dodgers on February 16, 2004 making him the fourth-youngest person to be named general manager in baseball history. On June 30, 2006, DePodesta was hired as the special assistant of baseball operations for the San Diego Padres.

What is Sabermetrics?

Sabermetrics is the analysis of baseball through objective evidence, especially baseball statistics that measure in-game activity rather than industry activity such as attendance. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research. It was coined by Bill James, who was one of its pioneers and has long been its most prominent advocate and public face.

Examples of sabermetric measurements and their definitions:

Base Runs (BsR)

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/pitcher creates/allows.

It measures essentially the same thing as Bill James' Runs Created, but as sabermetrician Tom M. Tango points out, BaseRuns models the reality of the run-scoring process significantly better than any other "run estimator".

Defense Independent Pitching Statistics (DIPS)

In baseball, defense-independent pitching statistics (DIPS) measure a pitcher's effectiveness based only on plays that do not involve fielders: home runs allowed, strikeouts, hit batters, walks, and, more recently, fly ball percentage, ground ball percentage, and (to much a lesser extent) line drive percentage. Those plays are under only the pitcher's control in the sense that fielders (not including the catcher) have no effect on their outcome.

Equivalent average (EQA)

Equivalent Average (EqA) is a baseball metric invented by Clay Davenport and intended to express the production of hitters in a context independent of park and league effects.[1] It represents a hitter's productivity using the same scale as batting average. Thus, a hitter with an EqA over .300 is a very good hitter, while a hitter with an EqA of .220 or below is poor. An EqA of .260 is defined as league average.

When EqA was invented cannot readily be documented, but references to it were being offered on the usenet as early as January 14, 1996.

Fantasy Batter Value (FBV)

Late-inning pressure situations (LIPS)

A late-inning pressure situation is a baseball statistic developed by the Elias Sports Bureau in their annual book The 1985 Elias Baseball Analyst to determine if "clutch" hitters exist. This question was first posed by Richard D. Cramer in his article "Do Clutch Hitters Exist?" published in the 1977 edition of The Baseball Research Journal. According to the Elias Sports Bureau, a Late Inning Pressure Situation is "any at-bat in the seventh inning or later, with the batter's team trailing by three runs or less (or four runs if the bases were loaded)." Development of the late inning pressure situation coincides with an increased attempt to reflect an individual's accomplishments in baseball statistics. In the case of the late inning pressure situation, it attempts to quantify the subjective term "clutch".

On-base plus slugging (OPS)

On-base plus slugging (OPS) is a sabermetric baseball statistic calculated as the sum of a player's on-base percentage and slugging percentage.[1] The ability of a player to both get on base and to hit for power, two important hitting skills, are represented. An OPS of .900 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.

PECOTA (Player Empirical Comparison and Optimization Test Algorithm)

PECOTA, a backronym for Player Empirical Comparison and Optimization Test Algorithm, is a sabermetric system for forecasting Major League Baseball player performance. The acronym was actually based on the name of journeyman major league player Bill Pecota, who with a lifetime batting average of .249 is perhaps representative of the typical PECOTA entry. PECOTA was developed by Nate Silver in 2002-2003 and introduced to the public in the book Baseball Prospectus 2003.[1] Baseball Prospectus (BP) has owned PECOTA since 2003; Silver managed PECOTA from 2003 to 2009. Beginning in Spring 2009, BP assumed responsibility for producing the annual forecasts.

Peripheral ERA (PERA)

Peripheral ERA (PERA) is a pitching statistic created by the Baseball Prospectus team. It is the expected earned run average taking into account park-adjusted hits, walks, strikeouts, and home runs allowed. Unlike Voros McCracken's DIPS, hits allowed are included. PERA doesn't attempt to eliminate the effect of luck on batted balls away from ERA, instead attempting to account for good (or bad) luck in the combinations of hits, walks, home runs, and strikeouts. A lower PERA than EqERA (adjusted ERA) may indicate poor luck which may even itself out in the future, leading to a lower EqERA despite no change in quality of pitching.

Pythagorean expectation

Pythagorean expectation is a formula invented by Bill James to estimate how many games a baseball team "should" have won based on the number of runs they scored and allowed. Comparing a team's actual and Pythagorean winning percentage can be used to evaluate how lucky that team was (by examining the variation between the two winning percentages). The term is derived from the formula's resemblance to the Pythagorean theorem.

Range Factor

Range Factor (commonly abbreviated RF) is a baseball statistic developed by Bill James. It is calculated by dividing putouts and assists by number of innings or games played at a given defense position.[1] The statistic is premised on the notion that the total number of outs that a player participates in is more relevant in evaluating his defensive play than the percentage of cleanly handled chances as calculated by the conventional statistic fielding percentage.

Runs created

Runs created (RC) is a baseball statistic invented by Bill James to estimate the number of runs a hitter contributes to his team.

Secondary average

Secondary average, or SecA, is a baseball statistic - more precisely, a sabermetric measurement of hitting performance. It is a complement to batting average, which is a simple ratio of base hits to at bats. Secondary average is a ratio of bases gained from other sources (extra base hits, walks and net bases gained through stolen bases) to at bats. Secondary averages have a higher variance than batting averages.

Similarity score

In Sabermetrics and APBRmetrics, similarity scores are a method of comparing baseball and basketball players (usually in MLB or the NBA) to other players, with the intent of discovering who the most similar historical players are to a certain player.

Speed Score

Speed Score is a statistic used in Sabermetric studies to evaluate a baseball player's speed. It was invented by Bill James, and first appeared in the 1987 edition of the Bill James Baseball Abstract.[1]

Speed Score includes five factors: stolen base percentage, stolen base attempts as a percentage of opportunities, triples, double plays grounded into as a percentage of opportunities, and runs scored as a percentage of times on base.[2] Baseball Prospectus has developed a modified version of Speed Score that equally weights each component.

Super linear weights

Super Linear Weights is a method for evaluating the contributions of a baseball player towards his team. It was designed by Mitchel Lichtman and it calculates the total value that a baseball player contributes towards his team in terms of runs, where 0 represents the number of runs the average player adds. It uses linear weights to determine how many runs a player contributes on offense and Ultimate zone rating (UZR) to determine how many runs he saves on defense.

Super Linear Weights measures value, or how much a player actually contributes to his team, as opposed to ability, or how good the player is independent of the context in which he plays (park, team, league, etc.) An example of another measure of value is Bill James' Win Shares. Some examples of measures of ability are Pete Palmer's Total player rating and Keith Woolner's Value over replacement player. Measures of value are often used to compose lists of the best players in a certain season or of all-time, whereas measures of ability are often used to predict a player's performance in future seasons.

Total player rating (aka PW/BFW)

Total player rating (TPR), also known as Batter-Fielder/Pitcher Wins (BFW/PW) is a metric for measuring the value of baseball players, and to enable players to be compared against each other even when they played for different teams, at different positions, and in different eras. It was developed by sabermetrician Pete Palmer and was popularized in the Total Baseball series of encyclopedias during the 1980s.

Ultimate zone rating (UZR)

Ultimate zone rating (UZR) is a sabermetric statistic used to measure fielding.

UZR calculations are provided at Fangraphs by Mitchel Lichtman.

Value over replacement player (VORP)

In baseball, value over replacement player (or VORP) is a statistic popularized by Keith Woolner that demonstrates how much a hitter contributes offensively or how much a pitcher contributes to his team in comparison to a fictitious "replacement player," who is an average fielder at his position and a below average hitter[1][2]. 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."

Win shares

Win shares is the name of the metric Bill James describes in his 2002 book Win Shares.

It considers statistics for baseball players, in the context of their team and in a sabermetric way, and assigns a single number to each player for his contributions for the year. All pitching, hitting and defensive contributions by the player are taken into account. Statistics are adjusted for park, league and era.


In baseball, wOBA (or weighted on-base average) is a statistic, based on linear weights, designed to measure a player's overall offensive contributions per plate appearance. It is formed from taking the observed run values of various offensive events, dividing by a player's plate appearances, and scaling the result to be on the same scale as on-base percentage. Unlike statistics like OPS, wOBA attempts to assign the proper value for each type of hitting event. It was created by Tom Tango and his coauthors for The Book: Playing the Percentages in Baseball.

Wins above replacement (WAR)

Wins Above Replacement, commonly known as WAR, is a sabermetric baseball statistic that is used to show how many more wins a player would give a team as opposed to a below-average player at that position. This statistic is commonly used in Baseball Prospectus.

I would like to thank Wikipedia for all the definitions and references for making this post. If you would like to read more about Sabermetrics, Click Here!
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