Statistical Saturday: AVG, OBP and SLG

Welcome readers of Baseball Essential, this is the start of a brand new segment we call “Statistical Saturdays”, in which we will discuss one or multiple Sabermetric statistics every Saturday in an attempt to convey their usefulness or, in some cases, even their worthlessness. This week Shawn Brody breaks down batting average and on base percentage, while Jon Becker takes on slugging percentage. 

As far as baseball statistics go, Batting Average (AVG), On-Base Percentage (OBP) and Slugging Percentage (SLG) are likely the most widely known and simple offensive statistics in baseball. The three also make up a players ‘slash line’ or ‘clip’, which is represented as AVG/OBP/SLG. However, due to their simplicity they can occasionally be some of the more misunderstood methods used when arguing for or against the effectiveness of a player.

Batting Average (AVG)—                                            Hits/At Bats

While it is one of the simplest statistics in all of baseball, the rationale behind a batting average is that the resulting number is reflective of how often a player gets a hit. The batting average is the only mathematically calculated statistic in the batting Triple Crown, which is also composed of Home Runs (HR) and Runs Batted In (RBI).

The batting average for all of Major League Baseball in 2014 was .251, although it has been declining since 2006. A good AVG is usually above .280, while a poor AVG is typically below .230. The ‘Mendoza Line’—named after shortstop Mario Mendoza—sits at .200 and is typically a good benchmark for as low as a players batting average can go and still be in the Major Leagues.

While a batting average—on occasion—is decent indicator of current success, it is not a good indicator of future success, how a player contributes to their individual team, or how a player can contribute in the future to a team. For this reason, this statistic is one dimensional. It can really only convey how often a player got a hit over the course of a season or career, but cannot convey what type of hit the player got, like slugging percentage or various other statistics can. As a result, it’s difficult to understand just how effective a player was in relation to his team by using just his base amount hits and not caring where they went.

For example, in 2014 Philadelphia Phillies outfielder Ben Revere posted a .306 AVG which, from the outside looking in, is a very respectable average to have. However, the misleading portion of Revere’s average is that only 22 of the 184 hits he had—or 12%—were for more than a single. While singles can be better than walks—as they have the ability to advance a runner more than just one base—they are still nowhere near as effective as doubles, triples, and homeruns—which can be grouped together as extra base hits, or XBH—in relation to advancing runners. Therefore although Revere hit for a high average, it is unlikely that anyone can say he had a more successful offensive season than guys like Jose Bautista (39.2% XBH), Adam Jones (33.7% XBH), Mike Trout (48.6% XBH), Carlos Gomez (37.4% XBH) or Giancarlo Stanton (44.5% XBH) who all had batting averages in the .280-.290 range, and extra base hit percentages triple, and some quadruple, Revere’s 12% XBH total.

Average is not a terrible statistic, it’s just not as transparent to success as others like OBP or Slugging percentage. For this reason, when average stands alone it is an ineffective stat. However, when paired with the two statistics previously mentioned, an average can better assist an onlooker as both OBP and SLG have an average in it. When you subtract AVG from OBP, the raw walk (including hit by pitch) percentage is found in decimal form and when you subtract AVG from SLG, the power a hitter displayed can be found in the form of a statistic called ISO—which stands for isolated power, and will be covered sometime in the near future.


On Base Percentage (OBP) —                        (H + BB + HBP)/(AB+BB+HBP+SF)


In English, the formula for OBP is ‘Hits + Walks + Hit by Pitch divided by At Bats + Walks + Hit By Pitches + Sacrifice Flies’. What sets this statistic apart from AVG is that it describes how often a player gets on base not just via a hit, but via walk and hit by pitch as well. Although OBP does not elicit how exactly a player got on base, it is still a useful stat because it is more reflective of how often a player does not get out.

The reasoning for the effectiveness of On Base Percentage is this: The more a player gets on base, the less outs the player has made. The less outs a player has made, the greater the likelihood the team will score. And, obviously, the more runs a team scores the greater chance they win.

A good OBP is usually above .340, while a poor OBP is typically below .300. For 2014, the league average OBP was .314 and has consistently decreased since 2006.

Fangraphs also does a good job of explaining the concept here.

As they note, On Base Percentage was popularized among the public by the book-turned-movie ‘Moneyball’, which discussed the realization by the Oakland Athletics front office of the importance of the stat in the early 2000’s. As teams were misusing and undervaluing players that got on base at high percentages, the OBP-aware A’s were able to obtain such players for cheap. However, it’d be difficult to find a contemporary team that doesn’t understand the importance of OBP or the various stats that accompany it, meaning that teams likely now look to a conglomerate of other sabermetric statistics to find the same apparent flaw in the market the A’s found a decade and a half ago.

While OBP is still a better statistic to look at when comparing players or attempting to decipher the value a player might have had to their respective team compared to AVG, it is mildly outdated today thanks to the use of WAR, wOBA, wRC+, and even BB% which can be better Sabermetric methods of arguing for or against the worth a player might have displayed in previous years and even in predicting how a player will project to play in years to come.


Slugging Percentage (SLG)  —   Total Bases/At Bats


Simply put, slugging percentage describes what brings fans to the ballpark on a daily basis: power. Obviously, players need hits to accrue total bases, which would increase their slugging percentage, but going four-for-ten with four singles is just as good for slugging percentage as going two-for-ten with two doubles: four total bases in ten at-bats.  While it’s not the best indicator of how much power a batter has (someone with a .400 average, all singles, would still produce a .400 SLG), it’s definitely the most straightforward and easy to understand, and it’s effective enough for casual baseball fans.

There’s no such thing as a “good” slugging percentage based on the raw number (more on that when we get to ISO in a future Statistical Saturday), because it completely depends on the player’s batting average. That being said, having a slugging percentage about 125 points above one’s batting average is considered quite good, and 2014 leader Jose Abreu’s was more than twice that differential, as his was buoyed by both a high batting average and plenty of extra base hits. There’s not a great correlation, but here’s a look at how the amount of extra-base hits influences slugging percentage.

Because the steroid era has come to an end due to the stringent policies put in place by MLB regarding steroid use, slugging percentage as a whole has decreased across the league.

It’s nothing ridiculous, but it’s definitely trending downward, which is why power is at such a premium, and having a player that can hit even 25 home runs is very beneficial to a team in this age so dominated by pitchers. When we look at other statistics in future Statistical Saturdays, we’ll show why power is so important, using stats even more telling than slugging percentage.

As said ad nauseam during this piece, these stats don’t even scratch the surface of what baseball stats can tell. They can all be taken differently based on your knowledge of the game, but together they offer a good indicator of how well a player did during his previous season. Looking at just one piece of the puzzle doesn’t help, but looking at them all as a whole (we call that OPS) is quite helpful when evaluating a player.

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