We all know and agree not all hits are created equal. We can take this a step further and agree not all ways of getting on base are created equal. Since we all agree on this we can now agree while possessing value, batting average, on-base percentage, slugging, and OPS are not ideal for assessing the overall offensive value of a hitter.
The question is if those aren’t ideal, do we have anything better? Yes, we do. Weighted on-base average or wOBA as its most commonly called. The two biggest shortcomings of the aforementioned four are: 1) only one factors in every possibility and 2) they all improperly weigh the outcomes. wOBA was created to both factor in all possible outcomes of each plate appearance and properly weigh them.
Note: I love OBP. I think it is an incredibly valuable stat. Essentially, it tells you who is good at getting on base. wOBA attempts to measure the quality of the way in which players get on base; getting on base by singling is better than a walk because a single had the possibility of moving runners up by more than one base.
Calculating wOBA is relatively easy. There are several pieces of data and you have to have a reference for the linear weights but the math itself is simple. Basic addition, multiplication, and division. The linear weights are just the values given to each outcome. Here is a table from Fangraphs that contains the linear weights necessary for wOBA calculations dating back to 1871. As an example let’s calculate the wOBA from Aaron Judge’s 2017 rookie season. Here is the formula for calculating wOBA for 2017.
Judge’s stats necessary for calculation are 116 unintentional walks, 5 hit by pitch, 75 singles, 24 doubles, 3 triples, 52 home runs, 542 at bats, 127 walks, 11 intentional walks, and 4 sacrifice flies. Here is the formula with his numbers plugged in.
Not only is this a well above average wOBA Judge’s wOBA of .430 is second in all of baseball trailing only Mike Trout.
What Does This Tell Me & How Can I Use It?
One important thing to remember about wOBA is that it is always scaled to league average OBP. The only reason this is done is to provide us a metric on a scale we are already comfortable with. Above .400 is superior, below .300 is bad, and .320 to .340 is league average.
Two other important things to remember is that it is context-neutral, meaning it doesn’t factor in runners on base or inning or any other game specific factor. And finally, remember it’s not park or position adjusted, meaning an outfielder playing half his games at Coors Field will probably have a slightly inflated wOBA compared to a catcher playing half his games in Safeco Field.
The best part about wOBA is, as Neil Weinberg states in this article over at Fangraphs, it is the gateway stat for sabermetrics. If you want to understand other advanced offensive sabermetrics get a solid grasp of wOBA.
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