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The Joy of wOBA
Posted By Dave Cameron On November 25, 2008 @ 12:00 pm In Daily Graphings | 29 Comments
Last night, David announced that FanGraphs is officially carrying wOBA as our newest statistical addition. For those of you who have read The Book, you’ll be familiar with wOBA, but for those of you who aren’t, here’s a brief introduction and some reasons why you should give this new, funny sounding stat a try.
First off, wOBA is a linear weight formula presented as a rate statistic scaled to On Base Percentage. Essentially, what that means is that average wOBA will always equal average OBP for any given year. If you know what the league’s OBP is, you know what the league’s wOBA is. Usually, league average falls in the .335 range – it was .332 last year, but offense was down around the game in 2008, which may or may not continue.
So, why should you care about wOBA? What makes it better than OPS or any of the more famous rate statistics that measure offensive value? The beauty of wOBA lies in linear weights. Essentially, every outcome has a specific run value that is proportional to other outcomes – a home run is worth a little more than twice as much a single, for instance. What wOBA does, as all linear weights formulas do, is value these outcomes relative to each other so that they are properly valued.
OPS, as you probably know, significantly undervalues the ability of a hitter to get on base. It treats a .330 OBP/.470 slug as equal to a .400 OBP/.400 slug, when the latter is more conducive to scoring runs. wOBA gives proper weight to all the things a hitter can do to produce value, and is a more accurate reflection of a hitter’s value.
For a practical example, let’s look at Ryan Ludwick versus Hanley Ramirez. Ludwick had a .966 OPS versus a .940 OPS for Ramirez – not a huge difference, but one most people would consider significant. If you put a lot of stock in OPS, you’d probably argue that Ludwick had a better offensive season.
However, Ramirez actually had a slightly higher wOBA, .403 to .401. This is due to the fact that Ramirez posted a .400/.540 line compared to Ludwick’s .375/.591 mark. Ramirez’s 25 point advantage in OBP was slightly more valuable than Ludwick’s 51 point advantage in SLG, and wOBA reflects this.
The other great advantage wOBA has is that it’s extremely easy to convert into run values. Simply take a player’s wOBA difference from the league average, divide by 1.15, and multiply that by how many plate appearances he got, and you have a run value above or below average for that player.
For instance, using Ramirez, who we already said had a .403 wOBA, which is 72 points higher than the 2008 NL average of .331. 0.072 / 1.15 = 0.063. 0.063 * 700 = 43.82 runs above average.
wOBA – league average wOBA divided by 1.15 times plate appearances = runs above average by linear weights. Simple, easy, and accurate. This is the joy of wOBA.
If you want a solid, context-neutral statistic that values hitting properly, wOBA is a great place to start. Some of the other great stats here on FanGraphs, such as WPA/LI and WPA, take context into account to add or subtract value based on how a hitter did in certain situations, but there are times when you just want to know how a batter did at the plate, regardless of who was on base or what the score was at the time. For those, wOBA is the perfect answer.
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