I wanted to use my space this week to write up a limited history of sabermetrics – the objective analysis of baseball through statistics – but first, I have to clear up something which got me a lot of feedback from readers.

Last week, I wrote that on-base percentage (OBP) is the most valuable statistic when trying to determine how valuable a particular player is to an offense.

I’ll admit I made a mistake there.

I should have written that OBP is the most important one-dimensional statistic to valuing offensive performance.

There is a combination statistic called OPS – on-base percentage plus slugging percentage (SLG) – that more accurately defines a player’s total contribution to an offense.

This is because OPS takes into account a hitter’s ability to reach base at a high rate while measuring a player’s ability to hit for power. This allows for different types of players to be evaluated on the same scale.

A patient hitter with a very high OBP and a lower SLG can be valued just as highly as a hitter who hits for a ton of power but has a little trouble being patient at the plate.

Obviously the best players are the ones who can do both very effectively, but that isn’t always the case.

I’ll use an example from my hometown Chicago Cubs to make this point even clearer.

Derrek Lee (.913 OPS) and Alfonso Soriano (.897 OPS) had similar offensive years in 2007 and had OPS numbers that reflected this. But Lee and Soriano couldn’t be more different in their approaches to hitting.

Lee (.400 OBP/.513 SLG) is a patient hitter who takes a fair amount of walks and gets on-base at a high rate, but he struggled to hit for power last season.

Soriano, on the other hand, reaches base at a much lower rate (.337 OBP) and hit for better power numbers (.560 SLG).

Both players are valuable to an offense, but in profoundly different ways. OPS is a statistic that attempts to quantify offensive performance without discriminating against either type of player.

While OPS is a very good statistic that is becoming more and more mainstream, it should be noted that there are baseball analysts who have problems with OPS because of its crude nature.

This argument was highlighted in Michael Lewis’ Moneyball, a book that I’ll talk more about next week.

By taking on-base percentage and slugging and simply adding them together to get OPS, it implies that the two statistics are of equal weight when it comes to a team’s ability to score runs.

This is where many “stats guys” have trouble accepting OPS at face value as the best possible way to evaluate offensive performance. Many believe that one extra point of OBP is more valuable than one extra point of SLG.

This is often based upon the fact that OBP and SLG are calculated on two separate scales. What I mean by this is that a perfect OBP would be 1.000, while a perfect SLG would be 4.000.

For OBP and SLG to carry equal weight, a team with an OBP of 1.000 would score just as many runs as a team with a SLG of 1.000, and that simply isn’t true.

Theoretically, a team with an OBP of 1.000 would score an infinite number of runs. A team with a SLG of 1.000 would score a very large number of runs, but it would certainly be far less than an infinite number.

For this reason, Bill James – considered the father of sabermetrics – and others have argued that an extra point of OBP is worth as much as one and a half times as much as an extra point of SLG.

Now, this doesn’t discount OPS altogether. OPS, while debated, still provides a much better look at offensive performance than the traditional triple crown statistics (AVG/HR/RBI) that have ruled baseball for decades.

Learning the importance of “new” statistics like OPS, and what they actually mean for statistical analysis, is just one more step in the process of thinking about baseball in a more intelligent way.

Next week, I’ll try to apply what I’ve discussed so far to real-life scenarios before the season gets underway.

Until then, I hope you’re enjoying spring training as much as I am.

Dave Fultz is a junior in Communications. He can be reached at [email protected].