Sunday Stats! (OBP, SLG, OPS, OPS+)

Reminder:   The one thing I love about twitter is meeting other Cubs fans, talking baseball, and getting to know them.  There is never anything wrong with talking baseball, and I want to give fans an opportunity to share their thoughts on the Cubs here on the blog.  So our first new feature will be all about stats, the advanced kind, so you know what I’m talking about if I throw some sort of weird numbers at you.  Brandon has volunteered to introduce readers to some of these stats every Sunday, I hope you enjoy the feature, and give Brandon a follow on twitter to talk some baseball.

  Welcome back to the second Stats Sunday (which is tentative to change). Sorry I couldn’t get one in last weekend as I was on vacation. Today we are going to talk about 3 stats that are the foundation of your understanding of batting stats. These 3 are the Adam and Eve of Baseball sabermetrics. We are talking about OBP, or On Base Percentage, SLG, or slugging percentage, and finally OPS, or On Base plus Slugging.

  To have a solid understanding of OBP, is the first step to understanding every other stat that’s ever been created. Let’s talk about what goes into OBP. The formula is as follows: OBP=    The purpose of OBP is to account for all the ways a hitter can get on base or influence baserunners. Critical fact: It was the first sabermetric to incorporate getting on base via a walk. Back twenty or thirty years ago, this was like landing on the moon for baseball nerds. However, nothing is perfect. It doesn’t account for the value of say a homer or a triple, which is where slugging percentage comes in.  SLG = (1B + 2 × 2B + 3 × 3B + 4 × HR) / AB. The genius of slugging percentage is just the problems of OBP. A double is given more value than a single but less than a triple. Here comes the most inclusive stat thus far, OPS (On Base plus Slugging). Actually, that is the formula, super simple. All of the problems of OBP and the problems of SLG are fixed by this one stat. It represents all of the ways a hitter can get on base and represents the value of hits.

  Let’s get into why you should be using these stats and how to use them. Why should you use OBP? Very simply, to determine how often a hitter is getting on base. Joey Votto led the league in 2012 with an OBP of .474, that is absolutely ridiculous. The OBP average from 1901-2014 was .329, and last year the league average was .321.  A VERY good OBP is normally around .390. The league average from 1901-2014 for SLG is .382. The average from 1980-2014 was 406. Let’s say anything below .390 is below league average and anything above .390 is above league average. Finally, league average OPS is around 740, 800 is good, 1000 is less than what Kris Bryant had in his minor league career. This is not a joke.

  SURPRISE! ONE MORE STAT TODAY! We call it OPS+. This is by far the easiest stat of the bunch to understand.  League average is set at 100 and for every point you are above, you are 1 percentage point better than league average. The same goes for an OPS+ under 100.  Another cool thing about OPS+ is that it is adjusted to park factors. So a hitter’s park like Coors field would inflate an OPS+. With a pitcher’s park, you would normally have lower numbers. The single season leader for OPS+ EVER is 266 from Barry Bonds. He was kind of good at the baseballs. On average, I like a known hitter to have an OPS in the 130-150 range. That’s where Rizzo falls in. Let’s take a look at the OPS+ from the 1984 Cubs who were known as being a really, really good hitting team. The following chart is sorted by OPS+ from largest to smallest using Excel. Which reminds me, if you ever want any data I use in the articles, send me an email, and within the hour you will have more Cubs stats than you can possibly imagine.

  Unfortunately, I am having a little trouble with Tableau and how to make the data consolidated, so that it is easy to read. There is a way to make the data more interactive and fun to play but am not sure how. And because of this, I can’t get the data into a picture that everyone can see. Just for a little taste of the action, Rogers Hornsby is the career leader for the Cubs with an OPS over 1000. Let me know if you can help out. Send me an email if you want to mess around with the picture. It’s just way too much data to put in a graph that will fit in the articles.  Looking at the chart, we see number 1, Hall of Famer, Ryne Sandberg. He consistently came through with good seasons and by the way, THE NUMBER OF PLATE APPEARANCES. HOLY COW! I left the pitchers in because it’s fun to see how bad pitchers are at batting.

  So that’ll wrap it up for this week. Next week we will look at a stat that is simple, yet tells a lot about a player’s power. Go Cubs!  

          — Brandon

Hope everyone enjoyed the first “Sunday Stats,” if you are interested in sharing something about baseball just give me a shout on twitter.

Sunday Stats (NEW Feature)

The one thing I love about twitter is meeting other Cubs fans, talking baseball, and getting to know them.  There is never anything wrong with talking baseball, and I want to give fans an opportunity to share their thoughts on the Cubs here on the blog.  So our first new feature will be all about stats, the advanced kind, so you know what I’m talking about if I throw some sort of weird numbers at you.  Brandon has volunteered to introduce readers to some of these stats every Sunday, I hope you enjoy the feature, and give Brandon a follow on twitter to talk some baseball.

—  Hello all. My name is Brandon. Welcome to a new series on advanced sabermetrics. (I need a name for it. Help me out.) Some background for you. George asked me to come on and do a series introducing the blog to advanced sabermetrics. I was happy to oblige. What is my goal in writing this column?  Well it’s quite simple, I want to make you a better baseball fan. I feel as though there are two types of fans. Type 1 are the kinds of people who watch games and analyze from memory. The brain doesn’t have the capacity to remember 162 games every year which is why statistics are so important. The other kind is the type of fan that is type one but also uses sabermetrics to back up arguments and to judge players. I am hoping to convert you from type 1 to type 2 by the end of this series and if you already qualify yourself as #2, I hope you just learn a little something.

Each week, we will dive deep into one or more statistics. Each article will explain what the stat is, how it is calculated, why you should use it, and then also some context with Cubs players. All data for the series has been acquired from FanGraphs. If you have never been to FanGraphs, you have done life wrong and you need to check it out. They provide player specific stats but also have a great blog. Check out Jeff Sullivan; he is absolutely fantastic. Anyways, we will go in depth on the stats I feel are the ones that you should judge players off of. For example, wOBA or wRC+, but more on that later.

We are going to dive deep into BB% and K% today, or walk rate and strikeout rate. The reason I am doing them together is because they are so similar. They are talking about different topics, but other than that they are really similar. BB% and K% talk about how much an individual player walks or strikes out. It’s that simple. One of the things to understand is that this is measured based off of plate appearances and not at-bats. Walks don’t count as at-bats, which is why when you see a player’s line for a single game, walks are not included.

How is the stat calculated? Very simply. BB%= BB/PA*100. K%=K/PA*100. Everyone should understand what goes into a stat to calculate it. Sure, math might not be fun, but it is good to know. The multiplication by 100 is to make the stat into a percent.

Let’s get into the context of the stat. The higher the walk rate, the better. Walking is good. It means they have plate discipline and also get on base. (If you want to read more on plate discipline stats, go check out Michael Cerami’s article on Bleacher Nation. He broke down all of those stats and what they mean. I won’t be talking about them because he already has, and it’s a fantastic article.) High strikeout rates are not good. It means they strike out a butt load. Someone you may think of when it comes to high K% is Javier Baez. We are all familiar with his strike out problems. It is the reason he is not with the major league team right now. Strikeouts make fans mad, they make players mad, but it is detrimental to daily games that no team excessively strikes out. When you read the graphs below remember the next few sentences. Use the following numbers to mess around with the graphs. The league average in 2014 for K% was 18.6%. League average BB% was 8.1%. Same context goes for BB% as it does K%.

Have fun interpreting those charts. Be careful to remember sample size. I did leave pitcher stats in, because those are really fun to look at. I am going to play around with tableau more and try and figure out how export better. Scott Lindholm of Beyond the Box Score and Wrigleyville BP uses Tableau a lot and it’s thanks to him that we have these graphs. One person to look at is Anthony Rizzo. We know this guy is a monster already but look at how much he walks, and how little he strikes out. It made me have an even greater appreciation for him.

If you have any questions at all, reach out to me on Twitter: @bagman928 or feel free to email me: bagman91999@gmail.com. I will be happy to help you out. Also, let me know if you want me to mix up whether I do all batting stats or mix it in with some pitching and fielding stats. See you next week! —

Hope everyone enjoyed the first “Sunday Stats,” if you are interested in sharing something about baseball just give me a shout on twitter.