## A Simple Intro to Sabermetrics: Offense

Puig, master of the Bat Flip - Christian Petersen

With the Royals in the midst of their second straight winning season, new fans and readers have arrived and are arriving, many of whom aren't familiar with advance stats. Here's a short primer on some things we use all the time.

For all the use of advanced stats by industry analysts, front offices, and fans, the media has, for the most part, not attached to them.  We still see batting average, runs batted in, and home runs on a stat line for a player on TV when he comes to bat.  For pitchers, ERA, win-loss record, and strikeout totals are paramount.  This results in a large amount of fans who follow baseball, some even very closely, but are unaware of the more recent stats.

There are a lot of misconceptions about advanced statistics in baseball.  Many see them as making the game too numbers-oriented and would rather stick to the 'traditional' stats that they grew up with.  This is a fallacy, though, because all stats are numbers and baseball, in particular, is a very numbers-oriented game.  Sabermetrics, which Bill James referred to as "the search for objective knowledge about baseball," merely attempts to find the best numbers for describing a player's performance.

With winning comes additional fans, and many of these fans don't have a working knowledge of baseball statistics.  No doubt that many new readers, lurkers, and commenters here have been intimidated by the statistics that are casually thrown about like Jeff Francoeur's bat in one of his strikeouts.

Thankfully, we are here to help.  I will set out and explain some ways of evaluation that we, and other baseball blogs, often use.  Since this website is about the Kansas City Royals (no, not the Lorde Royals, shocker), I will tie in some Royals examples as perspective.  I welcome any new or new-ish commenters to say hello and ask questions.  Many of the members of our community, notably Gopherballs, Jeff Zimmerman, and Scott McKinney, are number wizards and can answer specific questions very easily, though your argument may or may not be deconstructed in a blocked format should you choose to go that route.  So, here we go!

#### Batting Statistics

Offensive statistics are the easiest to quantify and are, therefore, the most accurate.  The core part of offensive stats is not batting average, as you might think, but on base percentage, or OBP, which is simply the percentage of times that a player gets on base.  Think of it this way:  you have 27 outs per game, and the only way to score is by not making outs.  Batting average does not take into account every time an out is or is not made and thus isn't very accurate.  A walk is worth just as much as a single because it does not make an out and places a runner on first base.  Of course, average and OBP are related, and are often correlated in a three-statistic line called a triple slash along with slugging percentage.  Slugging percentage shows how many extra base hits a player gets; the more extra base hits (XBH), the higher a slugging percentage.  Triple slashes look like this:

average/OBP/slugging

and are a simple and effective way of showing how well a hitter is hitting; I use it all the time.  For instance, Alex Gordon's current triple slash is .268/.348/.425 and Salvador Perez's triple slash is .285/.329/.444.  This tells you that Perez gets more hits than Gordon but gets on base less; however, the difference in slugging percentage is only due to the difference in averages.  This is not always the case; ISO, or isolated power, is the difference between slugging percentage and average.  A player with a .200 ISO hits more XBH than a player with a .150 ISO, even if their slugging percentages are the same.  Lorenzo Cain's triple slash is .324/.360/.449, and though his slugging percentage is similar to Perez's, nobody would say he hits for more power--that's what ISO quantifies.

Sometimes, triple slashes have a fourth slash with a higher number.  This is called OPS, or on base plus slugging.  OPS is a good statistic and better than average, OBP, or slugging in seeing the full productivity of a hitter. An OPS very simply is the addition of OBP and slugging.  A .600 OPS is bad, a .700 OPS is decent, a .800 OPS is very good, and a .900 OPS is awesome.  OPS+ is even better--it normalizes OPS to 100, which is league average, and each point above or below 100 is a percentage point above or below average.  It also adjusts for league and park factors, pretending everybody hits in the same league and ballpark.  Normalized stats like OPS are best for examining players across years, as Billy Butler's 2010 saw him hit a .857 OPS while Mike Sweney's 2003 was an .858 OPS.  However, Butler's OPS+ was 134 and Sweeney's was 120, meaning that Butler was actually better than Sweeney considering the offensive environment around him.

Walks and strikeouts are less important than walk and strikeout rate, or BB% and K%.  The league walks 7.8% of the time and strikes out 20.3% of the time; these numbers fluctuate yearly.  The Royals, as a team, strike out the fewest times in baseball at 15.8%.  Unfortunately, they don't walk much, and are tied for worst at walking at 6.4%.

Another pair of offensive statistics is wOBA and wRC+.  While OPS values slugging and OBP the same, wOBA does not, weighing OBP more heavily than slugging because it is more important.  Slugging values a home run four times as much as a walk, while, realistically, it is only about twice as good.  wRC+ is just like OPS+, except that it uses wOBA instead of OPS.  If you want a single stat that is maximum accuracy, this is the one.

There is one final thing to discuss.  Sometimes you will hear about 'BABIP', which is 'batting average on balls in play', often referred to as the 'BABIP Fairy'.  The idea behind BABIP is that a hitter has little control over where he hits the ball.  Sure, a hitter can pull a ball or hit it the other way or try to hit it in the air, but he has little control over where the ball goes.  Since defenders are not always positioned in the same position all the time, BABIP is mostly reliant on luck and the types of balls that are hit. The league average is right around .300, and if you see something particularly greater or lower than that, you know they have been blessed or curse by the BABIP Fairy.  Example:  Escobar's awful 2013 was fueled mostly by an extremely low BABIP of .264, and since Escobar doesn't hit for much power or walk much, he is more reliant on BABIP than most (as is the whole Royals team for that matter).

I will write up another one to help explain defense and one for pitching.  But, for now, that's enough about statistics.

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