Welcome to our second weekly foray into the wide world of advanced analysis! For the next couple of weeks we’re going to talk about a selection of offensive statistics. Thrilling!

Truthfully, I agonized for a while over how to split up these posts in a way that made sense. The title should tell you how well that worked out for me. Though, in the end, it’s probably a reasonable distinction to make. The numbers we’re going to talk about first are all rate stats, and are either based on, or can be interpreted on a similar scale to, batting average.

A rate statistic is essentially a number that measures how often something happens – typically a percentage or average of some kind. Rate stats benefit from more data, and (provided there aren’t too many external influences) will normalize over time. Counting stats, on the other hand, are numbers a player racks up – home runs, stolen bases, Wins Above Replacement, the usual. Those numbers will usually go up with sheer playing time.

Batting average is the most commonly used yardstick for measuring a player’s offensive abilities. Unfortunately, it sucks. Quick: who was the better hitter in 2011? Curtis Granderson (.262) or Casey Kotchman (.306)? There’s only one right answer, and there’s also only one player listed here with a shot at next week’s AL MVP.

So what does batting average really measure, that it has room to be so misleading? It’s just the ratio of hits to at-bats. Unfortunately, those have both become terms of art, with fiddly definitions. A hit is awarded when a player smacks the baseball into fair territory and reaches base, but without help from an error or a fielder’s choice.

Additionally, an at-bat is not what you think it is – that thing you’re thinking of is a plate appearance. An at-bat is a plate appearance that doesn’t result in a sacrifice, walk, interference call, or the end of an inning. (Reaching on an error counts. And therefore actually detracts from a player’s batting average.)

So already, you can see that we’re looking at a pretty contrived statistic that a) doesn’t account for the totality of a player’s offensive contributions, b) is dependent on the opposition’s defense, and c) treats a home run and a bloop single exactly the same. Surely, I say to you, there must be a better way.

If you find yourself in a situation where you might normally use batting average, consider using one – or, better yet, a combination – of these statistics instead.

On-Base Percentage. Let’s start with the Stat That Moneyball Made Famous. This is the most basic, binary way to assess a player’s offensive value – it just asks whether or not he made an out. (Of course, in baseball, nothing is quite that simple – OBP excludes obstruction/interference and dropped third strikes, and the debate still rages as to whether it should include errors.)

Outs have a certain amount of value, which we’ll look at more when we talk about win percentage. Suffice to say – and you know this already – it’s easier for the defense to keep you from scoring runs if there is one out as opposed to none, or two outs rather than one. And really, the simplest distillation of a batter’s job when he stands in is just to get to first base safely, so that someone behind him can try to do the same. Do that enough times, and someone will cross the plate.

League-average OBP was .321 in 2011, so you can see that – as expected – it runs higher than batting average, due mostly to the inclusion of walks. OBP is particularly useful when you’re evaluating top-of-the-order hitters – the “table setters,” in the parlance of our times. These are the guys that you just want to get on base, so that your power hitters can drive them in.

Speaking of which…

Slugging Percentage. Not actually a percentage. It’s also based on at-bats, but that’s not a problem here, since we’re looking specifically at the power aspect of hits. If the guy doesn’t reach base safely, you can’t really credit him with power – at least, not in any concrete fashion, aside from the nebulously pejorative term “warning track power.”

SLG is the total number of bases a player collects divided by his at-bats. So essentially, the number that you’re looking at represents the average number of bases a guy gets per at-bat. Unlike the percentage-based stats, SLG has a perfect score of 4.000 – meaning four bases, or a home run, for every at-bat.

League-average SLG in 2011 was .399. Jose Bautista’s SLG in 2011 was .608. “Excellent” can reasonably be considered to be around .500. Jose Bautista hits baseballs far.

If you add OBP and SLG together, you get a fairly commonly used all-around measure of a player’s offensive production, called On-base Plus Slugging, or OPS. Joey Bats had an OPS of 1.056 in 2011. That is extremely good. By contrast, the league’s lowest OPS of the season goes to Alex Rios, weighing in at .613, which is just awful, y’all.

Both of these statistics have their drawbacks. OBP measures, essentially, a very narrow binary outcome: on base or not? That’s part of its beauty, but means that it’s only useful in very specific contexts. SLG is a simple way to apply weights to extra-base hits, because they really are more valuable than singles – but is a triple really just three times as valuable as a single? We’ll talk about different ways to look at power and weights in next week’s installment, when we cover isolated power and weighted on-base average. Stay tuned!

Questions/complaints/corrections? Take it to the comments. I’ll see you there.