Sabermetric Spring Training: wOBA

After reviewing FIP last week I thought we would take a look at a stat on the offensive side.  This stat attempts to incorporate all things a hitter does at the plate and give a value similar to OBP.  That raises the question “Why not use OBP, or OPS?”  I’ll attempt to answer that first.

Many thought the move to OBP and OPS would be the answer to finding how good a hitter was, but it was quickly apparent that those stats had some flaws that would lead to discrepancies.  OBP weights all hits equally as well as walks.  We know that is not true, but while SLG attempts to weight hits, it does a poor job.  A triple is not worth three times as much as a single for instance.  When you combine the two you are just adding two flawed stats and not removing the issues.

To solve this problem Tom Tango created wOBA, which attempts to value each potential situation in regards to its chance of resulting in a run scored.  This is called linear weights.  Any situation has a potential run value and can be increased or decreased by the outcome of an at bat.  To give an example:  When an inning starts the average team will score 0.56 runs.  If a hitter gets a single to lead off the inning the RE (Run Expectancy) increases to 0.85.  The hitter increased the chance to score by 0.29.

Those linear weights deal with context though and wOBA attempts to remove context by not accounting for runners on base and only what the player did in his plate appearance.  Also this data is all historical and needs to be updated based on the current run environment.  According to FanGraphs this is the current values and equation:

wOBA = (0.69×uBB + 0.72×HBP + 0.89×1B + 1.26×2B + 1.60×3B + 2.08×HR + 0.25×SB -0.50×CS) / PA

The values are slightly modified as well to make the resulting value model closely to OBP to help people understand what is good, average or poor.  So a .400 wOBA is great, .321 is average (in 2010) and anything below is below average.  It also includes steals as an overall player value instead of just hitting skill.

It’s not league or park adjusted, but wOBA can tell you a lot about a player.  It can also be used to account for runs created in the form of wRAA (Weighted Runs Above Average).  When comparing hitters you should remember the effect of league as well as park if using wOBA.

2011 Examples
Jose Bautista     .447 (best)
Jacoby Ellsbury   .402
League Average    .316
Carl Crawford     .304
Alex Rios         .266 (worst)

Categories: Boston Red Sox Sabermetric Spring Training

After taking an interest in sabermetrics and statistical analysis Troy began trying to use it to an advantage in fantasy baseball. He started the website and also spent time at and After a few years the interest in the Red Sox drew him to start a Red Sox-oriented site (Yawkey Way Academy) with fellow writer Lee Perrault. A short time later he joined Fire Brand. Writer from: December 14, 2009 – July 24, 2010, March 3, 2011 – May 10, 2012.

7 Responses to “Sabermetric Spring Training: wOBA” Subscribe

  1. rjs February 16, 2012 at 11:34 AM #

    There articles are great! Keep 'em coming.

    • Jim February 16, 2012 at 1:26 PM #

      Jim. Agreed!

  2. tonez February 16, 2012 at 2:24 PM #

    I might be missing something. Why are uBB and HBP given different values when the result is the same?

    • TroyPatterson February 16, 2012 at 3:02 PM #

      Good question.

      The difference is due to the effect of situation. An unintentional more often occurs in a situation when the pitcher is avoiding the hitter. They aren't always, but the pitcher will avoid them as best as possible when they really hurt. HBP on the other hand are extremely random and will have a higher tendency to hurt the pitcher and help the hitter score a run.

      It's a small effect, but enough to worth seperating the two.

  3. TOB$ February 16, 2012 at 6:10 PM #

    For AL East positional rankings, click here:

  4. Zach February 16, 2012 at 8:33 PM #

    So, there's no valuation included for an iBB?

  5. Ben March 1, 2012 at 5:54 PM #

    I was going to ask if you left out Adam Dunn, but was surprised to find that his wOBA was actually higher than Rios's – barely. Dunn had a wOBA of .268 to Rios's .266.