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Giving Some Meaning to RBI (As Much as Humanly Possible, That Is)

November 13, 2009

Ryan Howard and Prince Fielder had the most RBI this year, but were they the best at driving runners in?

“RBI” is a three-letter acronym that I’ve grown to detest over the years.  It’s simple, it’s a counting statistic, and it’s been cited for decades as a means of evaluating hitters.  It comes to no surprise that the casual fan still uses it in comparative debates or player evaluation, and despite the fact that a strong portion of fans are beginning to deprecate the use of RBI, it’s still being force-fed into the brains of the casual fan through the official websites of Major League Baseball.  And while I understand that it’s better to use simple statistics to give an idea of a player’s skillset to the general public, they’re sending out terribly misleading information.  I’d much rather they try and introduce Runs Created, as horribly flawed as it is, than continue to use RBI.  At least it gives us a better estimate of a hitter’s contributions.  RBI doesn’t.

RBI mean absolutely nothing without context.  Otherwise it is nothing more than a random number that seems to correlate well with good hitters.  If you’re a good hitter, you tend to have good RBI totals- and this is a perceived universal truth.  This does NOT, however, give us any semblance of accuracy. First of all, we have to take HR off of the RBI total.  Since RBI is meant to tell us about runs that the individual player knocked in, it makes no sense to include HR- it will artificially inflate the RBI totals of guys that hit a lot of home runs and underrate the players that have lower HR totals but are still consistent at driving runners in.  So, let’s say that Player A has 45 HR and 141 RBI, and Player B has 15 HR and 103 RBI.  Initially, there’s a difference of 38 RBI.  Once we make our small adjustment, the difference goes from 38 to 8. Now, let’s give it some actual context- since RBI are supposed to measure a player’s ability to drive in baserunners, we have to look at the opportunities they were given.  Player A knocked in 96 of 500 runners on base, good for 19.2%.  Player B, on the other hand, knocked in 88 of 445, which is 19.8%.  Player B was actually more effective than Player A at driving in baserunners, albeit by a very small amount.  And we would never know this unless we put it into context.  Player A, by the way, is Ryan Howard.  Player B?  Bobby Abreu.

I don’t need to go into a long-winded essay to further my argument- I think this is sufficient enough to make my point and the amount of articles written on the uselessness of RBI is plentiful.  RE24 (which uses a baseline of “average,” the absolute version of this is the “Value-Added Batting Runs” statistic done by Tom Ruane and Gary Skoog) tells us how much a player has increased the team’s run expectancy overall, which is more valuable than knowing how many runners he drove in.  It provides us with a situational context.  Win Probability Added is similar.  If we want a context-neutral overall evaluation of a hitter, all we need are linear weights.  It gives us all we need to know about how many runs the player contributed to his team.

But if you’re familiar with this site, you know how much I love to tinker around with numbers- so, naturally, I decided to make “contextually-adjusted RBI” figures and compare it to a baseline of average.  Even if the casual fan doesn’t believe in linear weights or other run estimators, this should be easy enough to understand- this is a simplistic way in which we can identify which hitters were the best “RBI-men.”  So I found the average everyday player’s OBI% (500 PA and above), looked at the player’s ROB opportunities, and compared the expected OBI to the actual OBI.  Here are your leaders and trailers for 2009:

BIAA Leaders:

1. Bobby Abreu, +21

2. Ryan Howard, +21

3. Prince Fielder, +19

4. Hanley Ramirez, +18

5. Albert Pujols, +17

BIAA Trailers:

1. Mark Teahen, -16

2. Chris Young, -16

3. Josh Willingham, -17

4. Vernon Wells, -17

5. Mike Cameron, -19

A lot of the names you’d expect to see are at the top of the list, but Abreu at the very top (tied with Howard) is something of a surprise.  There are a few surprises on the list- who would have thought that Pedro Feliz (+10) was more effective than Justin Morneau (+8) at driving in runners this year?  Asdrubal Cabrera (+8) over Mark Teixeira (+7)?  And some of the players that rate below average are quite surprising as well- Adam Dunn (-4), Adrian Gonzalez (-5), Mark Reynolds (-6), and Derek Jeter (-8) headline the “omg srsly?” section, while a lot of the players we’d expect to have low OBI conversion rates (i.e. players that aren’t known for their power) reside in the bottom depths of Major League regulars.

We can break this down by runners on base, as well.  Naturally, the conversion rates increase depending on the base state.  Overall OBI% is around 15%.  A runner on first is expected to be knocked in 5.7% of the time; 16.6% of the time on second, and 38% of the time on third base.  That’s about an increase of 10.9% from first to second and an increase of 21.4% from second to third.

1B BIAA Leaders:

1. Ryan Howard, +18

2. Prince Fielder, +11

3. Albert Pujols, +11

4. Pablo Sandoval, +10

5. Adam Lind, +9

1B BIAA Trailers:

1. Derek Jeter, -6

2. Yadier Molina, -6

3. A.J. Pierzynski, -6

4. Mark Teahen, -7

5. Chone Figgins, -8

Not much of a surprise here, to be honest- all five leaders hit for a considerable amount of power, while the bottom five don’t.  Now let’s see who fared the best and worst at driving in runners from second:

2B BIAA Leaders:

1. Carlos Lee, +13

2. Ryan Ludwick, +11

3. Yunel Escobar, +11

4. Derrek Lee, +10

5. Jason Bay, +9

2B BIAA Trailers:

1. Mike Cameron, -8

2. Emilio Bonifacio, -8

3. Casey Blake, -8

4. Jason Kendall, -11

5. Dan Uggla, -14

Some interesting names are at the top- I didn’t expect Ludwick or Escobar to be there, but they both performed exceptionally with runners on second.  As for the trailers, I’m shocked to see Uggla do so terribly here.  I guess since Bruce Bochy wants the Giants to be better at “situational hitting,” they shouldn’t bother with Uggla (I hope you can detect the sarcasm; if not, you need to get your sarcasm meter checked).  Kendall’s not much of a surprise.  Cameron just had a bad year when it came to knocking guys in.  I’m not sure if this is an outlier for him or not; I haven’t looked at his career numbers.  By the way, David Ortiz was a -7 in this field.  Talk about a major let-down.

3B BIAA Leaders:

1. Miguel Tejada, +11

2. Todd Helton, +10

3. Kurt Suzuki, +9

4. David Ortiz, +8

5. Pedro Feliz, +8

3B BIAA Trailers:

1. Lyle Overbay, -8

2. Russell Martin, -9

3. Carlos Pena, -9

4. Alfonso Soriano, -10

5. Curtis Granderson, -11

Some surprises at the top and at the bottom.  It looks like both Suzuki and Feliz, who aren’t known for being run producers, excelled at bringing in the runner from third.  It is a bit disconcerting to see Pena and Soriano among the trailers, since both are reputed to be middle of the order run producers.  Soriano had a bad year in general, so perhaps that has something to do with it.

So what do all of these numbers mean?  To be honest, not very much.  While we can turn RBI into a statistic that tells us how productive a hitter was at knocking in runners (which is what it was supposed to do in the first place!) it doesn’t effectively tell us anything about a player’s overall skill set.  Traditional RBI are largely a junk stat, and even this corrected form of it is still something of a junk statistic.  Despite fixing the inherent flaws of RBI- subtracting home runs; giving it context and comparing to league average- it’s still far from an effective statistic and is rather limited in its use.  But I’d rather the official MLB sites adopt this method than continue to say something like Jason Bay was a better RBI man than Bobby Abreu this year.  Better yet, MLB could adopt RE24…but I’m dreaming.

Here’s a spreadsheet containing all of the data.

OBI% and runners on base data from Baseball Prospectus.  Why they haven’t done this yet is beyond me.

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