A WAR for Triple Crowns

The Triple Crown is rarely bestowed upon any hitter in Major League Baseball. It is also a title that generates a great deal of discussion about its value.  Traditionalists, and perhaps mainstream fans, see the achievement as reaching a pinnacle feat of greatness.  You will at times hear about Frank Robinson's Triple Crown if you stick around at Camden Yards during a rain delay.  The beauty of the recognition of this feat is largely a product of cricket. 

Henry Chadwick, who was quite familiar and fond of cricket, was looking for a way back in the 1800s to easily communicate the events that transpired during a game.  He leaned on the simple metrics used in cricket to credit the players.  Simply put, the forefather of traditional statistics is cricket.  In that way, you can imagine that perhaps these metrics are better at describing that sport as opposed to baseball. 

Regardless, one would imagine that over the following 150 years that better metrics would be created.  Many would argue there are better metrics.  However, the simplicity in communicating the game that Chadwick devised has stuck around and has largely impacted our perception of this game.  This traditionalism vs. modernism fight has been largely on display on issues surrounding these metrics and the Triple Crown is not foreign to those discussions.

For example, this past winter I encouraged an aspiring writer who sent me a column on Triple Crowns to seek out writing opportunities at other sites.  I was simply not interested in how he was trying to place different types of importance on those feats.  The problem I really had with the article was that it was not really trying to bridge a gap between the metrics struggle.  For instance, why would home runs and runs batted in be equivalent in value?  That would shift importance towards that component and suggest that the three variables are not equal.  I think that runs opposed to the core belief in the award as well as abuses the concept of combining data to say more about a set of data.

That column has stuck in my mind though.  Although we tend to write about talent and future value, there is a place for describing what really happened.  Life is not always what will happen or how past events inform us about what will happen.  Sometimes, life is simply about what occurred and sometimes what occurred in a subset of data.  With that in mind, I can appreciate the Triple Crown.  No, it does not say this individual or that individual is the best player in history, but it is a rough award that notes players who were exceptional.  Of the 14 players who won the Triple Crown, maybe Tip O'Neill was the worst and he played in those weird days of baseball in the 1880s.

Anyway, I decided to tinker around and put the Triple Crown on the same scale as fWAR.  Based on that distribution, I devised formulas that would convert batting average, home runs, and RBIs on a similar scale.  One aspect we can hem and haw on, I took qualified players and then treated home runs and RBIs as a function of play appearances.  That felt right to me, but it certainly is another level of data manipulation for purists of cricket-derived statistics to rail against. 

avgWAR = 61.021 * AVG - 14.015
hr%WAR = -1.778 * LN(PA/HR) + 8.7967
rbi%WAR = -4.905 * LN(PA/RBI) + 12.965

Anyway, I then averaged the three WAR scores to devise something I called tcWAR.

Below are the top ten players from 2010 through 2013, career numbers:

Name	Team	tcWAR	PA	HR	RBI	AVG
Miguel Cabrera	Tigers	5.0	2685	156	507	.337
Ryan Braun	Brewers	4.2	2244	108	364	.316
Adrian Beltre	- - -	4.2	2510	126	401	.314
Carlos Gonzalez	Rockies	4.2	2193	108	364	.311
Troy Tulowitzki	Rockies	4.1	1850	90	309	.307
Robinson Cano	Yankees	4.0	2755	117	428	.312
David Ortiz	Red Sox	4.0	2194	114	361	.300
Allen Craig	Cardinals	4.0	1420	50	247	.306
Josh Hamilton	- - -	4.0	2381	121	401	.296
Joey Votto	Reds	3.8	2568	104	345	.317

How is this year's group of batters projected to do (statistics through May 21st)?

Name	Team	tcWAR	PA	HR	RBI	AVG
Troy Tulowitzki	Rockies	6.0	183	13	35	.378
Yasiel Puig	Dodgers	5.0	187	10	37	.333
Charlie Blackmon	Rockies	4.7	185	9	32	.335
Miguel Cabrera	Tigers	4.7	183	7	40	.321
Victor Martinez	Tigers	4.6	180	12	28	.329
Giancarlo Stanton	Marlins	4.6	205	12	44	.305
Justin Morneau	Rockies	4.6	174	9	32	.321
Brandon Moss	Athletics	4.6	178	10	40	.301
Nelson Cruz	Orioles	4.3	187	14	41	.282
Michael Brantley	Indians	4.2	192	9	36	.302

What should we take from this?  Well, very good players tend to do very well when it comes to these categories.  The absence of Jose Abreu also shows the uniqueness of MLB's current home run leader.  Also, Nelson Cruz is proving to be one of the most meaningful free agents of the past year, showing that having a haphazard recruitment process sometimes actually can work though it probably does not speak highly for the process itself.

I think that might confuse some into thinking that doing well in these categories means that these metrics are incredibly useful in determining which will do well as opposed to those who performed in the opportunities that were given to them.  For instance, you may be able to perform insanely well at a Wall Street Firm, but your online law degree probably will not provide you much of an opportunity to test yourself in that venue.  In other words, equally able players may not be given the same chances to perform.  Second, these metrics do not truly define baseball.  It is a much more varied game that cannot be reduced to only three considered counting statistics.  In other words, you may be great at sprinting while being pretty awful at hurdles.  Both have value, but if you only look at sprinters then you are missing a lot of what it means to be good at track events.