The Oddibe Awards

This is a slightly modified excerpt from my upcoming book, Bridging the Statistical Gap, to be released towards the end of April/beginning of May.
A friend of mine, RJ Anderson of Beyond the Box Score, recently sent me the introduction to a book he is currently writing to look over.  While reading I could not help but notice an extremely fascinating statistical tidbit and RJ graciously allowed me to conduct further research regarding his findings.  Using the Lahman Database he had taken all of the offensive seasons from 1960-2006 and, after tallying the counting stats (H, AB, 2B, etc.), calculated the average slash statistics (BA/OBP/SLG) of major league hitters in that span.  The average major league hitter from 1960-2006 put up a slash line of .259/.326/.395.
He then set parameters in the spreadsheet and was able to find the player with career numbers that most closely matched these slash statistics.  The player?  Oddibe McDowell.  McDowell’s career .253/.323/.395 was closer to the average than anyone else in that timespan.
While RJ then went onto discuss the collegiate and major league career of Sir Oddibe I decided to apply this theory to individual seasons.  I found the average slash lines for each year from 1981-2007 and found the players most closely resembling those lines.  Since Oddibe’s career line came the closest I have named my yearly award after him.  Therefore, the award for the most average offensive player, via slash stats, in a given year, will be hereby known as “The Oddibe Award of Excellence in Average Performance.”
This way anybody with a small sample size of statistics would be disqualified from inclusion; the slash parameters were originally smaller but widening them became a necessity when it was determined that so few people came within 5-7 points of each.  Some players would be within 1-2 points in BA and OBP but were 10-15 points off in SLG, and other variations of the same type of discrepancy.  If multiple players were essentially equivalent I went for those with the higher number of AB’s.  If multiple players were close and no clear-cut winner emerged I simply measured how far off they were in each of the three stats; I went for consistency meaning that a player within four points of all three would be more average than one who was equal in two stats but twelve points off in the third.
With that being said, here are the winners of the annual Oddibe Awards from 1981-2007:

 YEAR PLAYER TEAM BA/OBP/SLG 1981 Rich Dauer BAL .263/.317/.369 1982 Alan Trammell DET .258/.325/.395 1983 Alan Bannister CLE .265/.323/.393 1984 Ben Ogilvie MIL .262/.327/.384 1985 Bill Madlock PIT .251/.323/.388 1986 Rudy Law KC .261/.327/.388 1987 Robby Thompson SF .262/.328/.415 1988 Ozzie Virgil ATL .256/.313/.372 1989 Ken Caminiti HOU .255/.316/.369 1990 Gary Ward DET .256/.322/.392 1991 Luis Rivera BOS .258/.318/.84 1992 Jay Bell PIT .264/.326/.383 1993 Cory Snyder LAD .266/.331/.397 1994 Orlando Merced PIT .272/.343/.412 1995 Bret Boone CIN .267/.326/.429 1996 Travis Fryman DET .268/.329/.437 1997 Dan Wilson SEA .270/.326/.423 1998 Mike Bordick BAL .260/.328/.411 1999 Damion Easley DET .266/.346/.434 2000 Chad Curtis TEX .272/.343/.427 2001 Steve Cox TB .257/.323/.427 2002 Michael Barrett MON .263/.323/.418 2003 Robert Fick ATL .269/.335/.418 2004 Orlando Hudson TOR .270/.341/.438 2005 Brandon Inge DET .261/.330/.419 2006 Curtis Granderson DET .260/.335/.438 2007 Jhonny Peralta CLE .270/.341/.430

2008 ODDIBE GOES TO…?
With so many projection systems out there it just seemed natural to check who might qualify for the prestigious average award this season. And, as opening day really gets underway today (triple-rhyme) let’s examine this year’s Oddibe candidates, using StatSpeak alum Sean Smith’s CHONE projections.
1) Chris Burke – .256/.330/.392
2) Franklin Gutierrez – .259/.317/.404
3) Jacque Jones – .260/.318/.402
5) Brandon Inge – .249/.325/.405
We’ll all have to keep our Oddibe-eyes out for this one!

10 Responses to The Oddibe Awards

1. Minda says:

Very average post.
(Get it? Average?

2. I don’t get it. Explain.

3. Minda says:

Booooooooo!

4. Pizza Cutter says:

How is it that Oddibe “Young Again” McDowell himself doesn’t make the list?

5. It’s odd – it ends up being basically the same as the Cy Young Award article I wrote wherein the recipient of the award had a career worthy of the title but not really any individual seasons. Oddibe himself never had a season extremely close to the .259/.326/.395 but his career as a whole was ridiculously close.

6. tangotiger says:

Wouldn’t you want to base it on the league average of the year in question? Having the same baseline for 1968 and 1998 doesn’t seem correct.

7. Yeah that’s a good idea. I’ll go back in and look that up.

8. Josh says:

Shouldn’t you crunch the numbers of each individual season to find the most average hitter for that season?
To find who was most average in a particular year, you’d have to know what was average for that year.
I love the concept, though.

9. Josh, yep, I actually just did that tonight. I’m re-posting that right now. About 60% of the guys stayed the same. Check it now.

10. […] Score, sent me the introduction to a book he plans on writing, way back in March, and graciously allowed me to expound upon what he had been discussing. Essentially, RJ had, using the Lahman Database, found that the average […]