Explaining Stats: Slugging Percentage
By Jeff Ellis
January 17, 2012
My earliest memory of baseball stats was as a child going over to my grandmother's house and after everyone was done with the Sunday paper I would cut out the giant section of stats in the Sunday Akron Beacon Journal.
For those who don't remember or did not get the paper every Sunday they had just about every player listed in order of batting average with Indians players bolded, and then pitchers listed the same way in order of ERA.
Also, depending on space allotted, they would have small boxes of less than ten names for other category leaders such as home runs, runs, RBI, doubles, strikeouts, etc. I would keep the list and look at it randomly as a source of information, and in time this would lead to me making games using dice or whatever I had on hand to play baseball games and keep my own stats of my own games. This practice faded as I grew older, but then when I got to college we had the internet and stats were at my finger tips at all times.
Yet, I still only really knew about the basic old school stats, but then about five years ago I started playing OOTP 5. It is a free baseball game that you play and everyone manages one team. This game had stats I didn't know and thus I had no way to know how to completely and correctly judge my players.
So in addition of looking to see what the abbreviations stood for, I started to examine and learn what they meant stat-wise and what would be a good score for each stat. I often refer to that baseline as the 300 level, because growing up 300 was the baseline for what a good hitter should break.
Sadly, as I learned about these stats I began to realize that many of what I had relied on for years were half stats and did not tell a true story. This was about the same time Major League Baseball started figuring this out and hiring stat guys who were famous for advanced stats and different ways of judging players.
Last year I started I started examining some of the newer stats with a piece on base percentage, but this time around I wanted to focus in on slugging percentage. I plan to write on a variety of stats, so feel free to ask about some you don't know or anything you would like to see profiled. I know some dislike the new stats, but they are now a part of baseball and are not going away. If anything they are getting even more complex.
So what is slugging percentage?
There is a basic and easy way to understand the formula for it. Slugging percentage is singles + (doubles x 2) + (triples x 3) + (home runs x 4) all divided by the players' total number of at bats. The easier way is to say it is the total bases a player accumulates divided by the players' at bats.
The league average for slugging percentage is often considered to be .400 to .415. For a player to have been exceptional last season and make the top 30 in both leagues he would have had to post a .495 SLG.
As a comparion, last year the highest slugging percentage for the Indians was Asdrubal Cabrera's .460 SLG, though Carlos Santana was close with a .457 SLG. They were 62nd and 66th in the league respectively, which shows how the Indians really did lack a credible consistent power threat.
For those wondering about the Indians targets for the hole at first base, Carlos Pena posted a .462 SLG and Casey Kotchman a .422 SLG, and both players were in the bottom half of all qualifying first baseman last year.
The old school method used before was typically that power hitters were judged by how many home runs they hit and the ability to hit for doubles did not represent power. This new approach with calculating slugging percentage allows for all extra base hits to be a part of the evaluation. This allows evaluators to take advantage of the full concept of power as maybe a player only has doubles power, which is still better than no power at all.
Bottom line, slugging percentage is a way to judge how effectively a player hits for power and it allows for better evaluation of the teams we follow.
Follow Jeff on Twitter @jeffmlbdraft, or email him at firstname.lastname@example.org