# Advanced Statistics: Offense

**Advanced Statistics – Offense**

**Colby Garrapy**

Baseball statistics say many things about players. People view those with a high batting average as being the best hitters and the pitchers with the most wins as being the best pitchers. While these stats say something about a player, they don’t show you everything. What if a batter goes 0-2 with three walks and another goes 2-4? While the second batter has a .500 average, the first player managed to get on one more time during the game. If a pitcher goes five innings and gives up four earned runs and records the win, while the other goes seven giving up three earned, five runs total and takes the loss, which is better?

The information I have provided doesn’t give us enough to quantify someone as being the better player, but it puts stats in a different perspective as to how they are viewed. I’m going to take a different look at baseball statistics and apply some theories and formulas to your current Lowell Spinners. I’m not trying to downplay the importance of common baseball stats, just explore different angles that are offered. At the conclusion, the view of normal statistics will be shadowed by what lies behind their current stat lines.

I’ll start simply with BA (Batting Average) and OBP (On-Base Percentage). A player’s BA shows us how well they have got a hit over the course of their at-bats. OBP shows us how often the player reaches base (hits, walks, hit by pitch, sacrifice flies). While a player’s BA only accounts for their hits, OBP accounts for the player’s ability to get on base and contribute.

OBP is a much more effective statistic to evaluate a players performance offensively. For instance, if a player bats .300 and has an OBP of .330, while another player bats .275 and has an OBP of .375, it is an indication that the second player reaches base .045 better than the first, which is a significant amount when discussing the two stats. Here is a list of the top five Spinners in each category.

BA (min. 30 AB) OBP (min.30 AB)

Jose Garcia .355 Jose Garcia .420

James Kang .324 Kolbrin Vitek .411

Felix Sanchez .321 Felix Sanchez .384

Kolbrin Vitek .297 Miles Head .381

Brandon Jacobs .276 James Kang .378

Now that we have cleared up how OBP is more important than BA, how do you distinguish those like Ichiro who hit lots of singles from those like Adam Dunn who hits homeruns? Another stat that is commonly referred is called is Slugging Percentage, or SLG. How slugging percentage works is you take the player’s total bases (single is one, double is two, etc) and divide it by his at-bats. This number gives you their SLG and quantifies how they batter “slugs.” Someone like Ichiro typically has a high BA and a low SLG. On the other hand Adam Dunn typically carries a low BA and a high SLG because of the amount of homeruns he hits.

To make life a little easier for baseball gurus like myself, a simple stat that quantified a player’s ability to get on base and ability to hit for power was developed called OPS, or On-Base plus SLG. All this does is take a player’s OBP and adds it to their SLG to give you one number to evaluate their hitting ability. We’ll take a look at how your Spinners stack up with these statistics.

SLG OPS

Sean Killeen .533 Jose Garcia .888

Jose Garcia .468 Sean Killeen .854

James Kang .442 James Kang .820

Kolbrin Vitek .407 Kolbrin Vitek .817

Brandon Jacobs .402 Miles Head .758

Now that I have covered some fundamentals to look for in offense statistics, I’ll take it a step further and examine some more in depth stats that allow us to see how productive some players actually are. ISO, or Isolated Power, is a statistic that shows us how much “power” a player has or produces. What this stat does is eliminate singles because they don’t determine a player’s power. There are two formulas that allow us to get their ISO. The simplest is:

SLG – BA = ISO

This can get you a player’s ISO quickly, another way that will get you the same ISO is:

TB (Total Bases) – H / AB = ISO

For the sake of this article we will use the second formula as it allows us to take a look at how many hits the player currently has. Here are the Spinners top ISO producers thus far this season:

ISO

Sean Killeen .333

Brandon Jacobs .126

James Kang .118

Jose Garcia .113

Kolbrin Vitek .110

Other than Sean Killeen the Spinners have not produced much power this season. None of the players listed above have more than one homerun other than Killeen (5). A lot of the players with over 30 at-bats had less than .100 for their ISO. This is an indication that the Spinners have had troubles with their power production.

We’ll now take a look at a statistic called Runs Created, RC. Red Sox Advisor, Bill James, developed this stat and what it does is measure the number of runs a particular player has contributed to his team. Throughout the years a number of different formulas has been developed to get the number of runs created by each player. The most basic of formulas looks like this:

(H + BB) x TB = RC

AB + BB

Since then, new formulas were developed that took into account factors like hit by pitch, grounded into DP, sacrifice hits and more. One formula was created that took into account a player’s contributions on the base path with stolen bases. This is the formula I will be using today to come up with the RC for the Spinners.

(H + BB – CS) x (TB + (.55 x SB)) = RC

AB + BB

This formula expands on the basic formula and accounts for their base running abilities and failures (CS). Here is a look at the Spinners top five run creators.

RC

Kolbrin Vitek 16

Felix Sanchez 13

Brandon Jacobs 12

Jose Garcia 11

Miles Head 10

These are the Spinners top five players for runs created. If you have been paying close attention throughout the article, you can see these names are starting to appear over and over again. This is an indication of who the Spinners top offensive players are.

I will now take a look at one last stat. With this stat we will be leaving one piece of information out due to the fact I have limited resources in acquiring my statistics. Because it is left out for everyone we will still get a good idea of who performs well for the stat. What I want to look at is wOBA, or weighted on-base average. This is where it can get a little confusing.

What wOBA does is account for a player’s contributions in the correct value. OPS is a good number to look at quickly when it comes to a player’s ability to get on base and their slugging. But it weighs it together when OBP is much more valuable than slugging. In SLG a double is weighed as twice as much as a single, and a triple as three times. But is a triple really 3x as valuable as a single? wOBA weighs each situation according to their correct value. In the end you end up with a number that looks like a BA. Typically someone with a .330 wOBA is average, but varies every year. Here is the formula to get wOBA:

wOBA=((0.72*NIBB)+(0.75*HBP)+(0.9*1B)+(0.92*RBOE)+(1.24*2B)+(1.56*3B)+(1.95*HR))/PA

It looks confusing, but for the two stats that you may not be familiar with, NIBB is Non-Intentional walks and RBOE is reached base on error. With the data I have available I do not have RBOE, so we will be leaving that stat out when coming up with wOBA. Here are your Spinners top contributors with wOBA:

wOBA

Jose Garcia .396

Kolbrin Vitek .370

Sean Killeen .361

James Kang .344

Miles Head .343

These are the top players on the Spinners for wOBA, all of which are above the average mark. These numbers show these players have the ability to get on and get the extra base hits.

Baseball stats say a lot about a particular player. While they may hide in the shadows of those who are getting the high averages, it doesn’t mean they are going unnoticed. These stats are just the beginning and there is much more out there that can be done to critique a player and his abilities. My next segment will cover pitching and how the Spinners match up against each other on the mound.