Ever since the release of Moneyball it seems that baseball has only gotten more complex. Baseball used to be as simple as measuring a player’s batting average to know their true talent level. With the advent of the Moneyball strategy, the focus turned from batting average to on base percentage. Over the years it has expanded further than that. Now a batter’s value is measure by WAR, wRC+, WOBA while a pitcher’s value is measured by FIP, WHIP, SIERA, xFIP and a defender is measured by UZR and so on and so forth. More so than ever before baseball has become more complex, and yet understanding of the ins and outs of the game has never been higher or more clear.
For many these new measurements of talent and performance read like a complex foreign language. With this article, I am hoping to explain some of this terminology in more depth and demystify some of these advanced sabermetric concepts for the casual baseball fan. Baseball has advanced quite a bit over the last ten to fifteen years in terms of statistics and has left many casual baseball fans behind.
Today’s topic in regards to advanced baseball metrics is defense. In terms of measurement using advanced sabermetrics, defense is perhaps the easiest and most simplified of the three main areas of statistical measurement, with pitching and hitting being the other two, more complex aspects of the game. For the sake of brevity and understanding, a discussion on the use of advanced sabermetrics to measure defensive value must be split between catcher specific defensive statistics and those of the average positional fielder.
Pitch framing has become one of the hottest topics in all of baseball over the last several years. More so than ever teams have attempted to field catchers with a strong acumen for “stealing” strikes, preventing passed balls, and providing the most positive value not only defensively but also positive value for the results of the pitcher on any given day.
The use of advanced sabermetrics to quantify overall catcher defense can be split into four separate categories: catcher’s affect on baserunning, on passed balls, on stealing strikes, more commonly known as pitch framing, and finally overall defensive value.
To begin with Fangraphs uses rSB and RPP to quantify a catcher’s contributions on both baserunning and passed balls in order to get an accurate measure of a catcher’s contribution defensively through the WAR statistic (which was discussed at length in part 1 of this series). At its basis rSB, Stolen Base Runs Saved, is a measurement of how many runs a catcher saves his team based on his performance throwing out baserunners or preventing baserunners from attempting steals. On the other hand, RPP, Passed Pitch Runs, measures the number of runs a catcher is above or below average at preventing passed balls. When added together these two numbers are used to calculate the defensive score of a catcher’s WAR. Anything above a score of 0 for both of these statistics is considered to be above average.
On the other hand, Statcorner goes a bit further than Fangraphs and quantifies both pitch framing and a catcher’s overall defensive value to his team (similar to the defensive WAR calculation of Fangraphs). The two main things to look at with regards to the Statcorner data is the Plus calls statistic and the RAA statistics. Plus calls basically are pitches that were actually balls that were called strikes because of that specific catcher’s framing ability. Currently the top performer in this category in 2015 is Francisco Cervelli who has 177 plus calls, or 177 strikes called on pitches that were considered outside of the strike zone.
To go one step further, RAA, or Runs Above Average, measures how many runs above average a catcher is on defense. This stat takes into account all of catcher’s defensive contributions, which includes their pitch framing, measured by plus calls, and quantifies it through a number. For some clarification, the best RAA in the league is 23.5 while the worst is -15.8. This basically means the best catcher saved his team 23 runs through defense alone while the worst catcher cost his team nearly 16 runs with poor defense.
Moving beyond catcher defense, Fangraphs uses several statistics to quantify a positional player’s defensive contributions which include DEF, UZR, DRS, as well as inside edge fielding. It is best to begin with DEF, an abbreviation for defensive runs above average, which quantifies a player’s defensive value relative to the league average. The important distinction to be made between DEF and UZR/DRS is that DEF is adjusted to allow for comparisons between players of different positions while UZR/DRS only measure performance at a certain position and can only be compared within that position. To allow for comparisons across separate positions, the DEF statistic measures “value relative to positional average (fielding runs) and positional value relative to other positions (positional adjustment).” In this way it allows a left fielder to be compared to a shortstop or other infielder despite vast differences among the positions. 0 is considered average with anything above that being considered above average with the best defensive players garnering scores in the 20s.
On the other hand, UZR and DRS measure defense at each specific position separately. UZR stands for Ultimate Zone Rating and tries to quantify how many runs an individual player saves/gives up based on his defense alone. This stat is separated into four separate categories, outfield arm runs, double play runs, range runs, and error runs, which are all added together to get an overall UZR score. Similarly to DEF, UZR is scaled to 0 as league average and any score above 0 is considered to be above average with the best gloves scoring 15 or higher. DRS stands for defensive runs saved and is a similar statistic to UZR, measuring total defensive value through runs saved by using a wide variety of smaller, individual defensive categories such as the range, throwing, and double play measures used in UZR.
One final defensive measurement that is used is called Inside Edge Fielding which splits batted balls into six categories: impossible, remote, unlikely, about even, likely, and almost certain. Basically this measures how often a player makes a play on a ball in each specific category and is thus used to quantify a player’s defensive value through his range and likelihood to commit errors.
In the final edition of Deciphering Advanced Statistics we have quantified the main advanced sabermetrics used to measure defense. With this series finished, hopefully the average fan can have a little better understanding of all the math that goes into the game of baseball on a daily basis.
Patrick Brewer is the Lead National League writer for Call to the Bullpen. You can find him on Twitter @PatrickBrewer93, or join in the conversation@CTBPod, in the comment section below or on our Facebook Page.