***Now featuring an attempted answer by me***
What would your response be if I told you that in 2009, there was only one team that was more efficient in MLB than the Astros? Since that was rhetorical, I'll answer what I assume: WTF?!
But it's true. Kind of. More like, sort of—actually.
According to the Bill James Handbook—which the kind folks at Acta Sports sent my way—I've had the opportunity to mull over the surplus of entertaining stats, charts, tables, and graphs that pack that pages of the Handbook (they'll likely be the fodder for about three months worth of posting...just warning you). While I've come across a couple of truly interesting things, the team efficiency scores have had me scratching my head for a few days now.
James' Team Efficiency measure is a combination of a couple different scaled scores based on hitting efficiency (basically our RC's created compared to RS), pitching efficiency (basically our PRC compared to RA), and our Pythag-differential. To quote James himself on this measure:
Teams bounce up and down these rankings, and there is a lot of pure luck which is included under the heading "efficiency" (10).
So basically it's this massive aggregator of macro-data that requires sifting through. This works well for us because we're just the people do that for the Astros.
Here's how the separate efficiency scores that comprise team efficiency played out (100 is average):
- Hitting Efficiency: 96
- Pitching Efficiency: 101
- Runs Efficiency: 111
- Overall Efficiency: 106
What's crazy to note, and James actually notes it, is that given our various efficiencies, the Astros were expected to garner 70 wins. That
Nationals, were also expected to garner 70 wins by this measure. The difference between those two teams? Their run efficiency. The Nats out paced us by a ton in Hitting Efficiency, and were just behind us in Pitching Efficiency (I'm cursing myself for capitalizing the efficiencies to start with).
Before we go any further, I understand that the aggregate efficiency stat likely suffers from a lack of attention to too wide of margins of error and lack of attention to significant figures. But what's fascinating is that somehow the Astros have managed to outpace what they should have accomplished. Yes, 2009 wasn't a great finish like 2008, but the Astros still managed to keep their heads well above water.
My first guess at how we managed to this is that there are probably some subtle loopholes in these measures because it's difficult to measure the interactions between events like hits, doubles, triples, home runs, strikeouts, walks, GIDP, SF, etc. Further, base running is difficult to measure, too. Using BPro EqBR, the Astros were 13th in base running and pretty much broke even on the base-paths, which is an accomplishment in and of itself.
Obviously, as we've hashed out many times before, prevailing in close games helps a team outpace their Pythag record, but I don't think we were as stellar of a close game team as were in 2008. Yet, only the Mariners had a better Run Efficiency than we did in 2009.
So what was it about this team in 2009 that mad them the most efficient team in the National League and the second most efficient team in baseball (the Angels were first)? Do we give credit to the small ball tactics of Cooper? The speed of Bourn? Or is it some combination of factors that doesn't immediately jump out at us? Or do we just chock it up blind luck?
We've got all day. Let's see what we can come up with.
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Since I left the questions open-eneded and unanswered, I'll start.
The Astros seemed to be a team that once in a favorable position, they capitalized. Looking at their BR batting splits, there's a big trend in both the positioning of runners, and the counts the Astros reached, that allowed them to make the most of their meager offensive output overall. Their best OPS in terms of bases occupied came with a man on second (.879) and their best count OPS was the 3-0 count and the 3-1 count at 2.184 and 1.364 respectively (yes, those should probably always be the best counts, but 2.184—that's impressive).
Do we call it clutch, or luck? Or do we just call it statistical probabilities, since they seemed to perform favorable with the odds were stacked for them?
