Saturday, March 16, 2013
I mean, 29-9 in one-run games? C’mon son. You can’t expect us to believe that happened any way other than dumb luck, right? There’s absolutely no chance that skill is repeatable, at least to that degree. This is common knowledge, and there’s no point trying to argue against it. But I will argue for it, anyway, because it’s fun to quantify things.
How unsustainable is that 29-9 record in one-run games? Well, for starters, it’s the highest winning percentage in one-run games in MLB history (dating back to 1901, which is 2332 individual team seasons). Anything that extreme is due for some serious regression to the mean. But do records in one-run games regress to .500, or to some other team-specific level, similar to how we now know that hitter BABIP regresses to an established hitter mean? ...
Do Elite Teams Still Regress?
The logic behind this question is that teams who do other-worldly in one-run games may have some underlying skill or profile that allows them to do so, so they may not regress quite as far. The opposite logic might be that they have much further to fall in regression.
This graph just took teams who won better than 60% of their one-run games in one year, which is a sample of 267 teams, or roughly teams in the 89th percentile for one-run game performance. Please note the change in scale on the x-axis, as we’re only looking at elite teams. ...
We see basically the same thing as before – almost no relationship, with an R2 of just 1.2% and just as weak a trendline. It does not appear that even elite teams in one-run games show a particular skill that repeats year over year. To examine further, though, I looked at the average one-run game winning percentage for several buckets of performance levels.
The only things I could think of that may predict one-run game success is a very strong bullpen or an excellent tactician on the bench. The latter is impossible to measure, though I’d guess Buck Showalter falls somewhere short of “master strategist.” As for the bullpen, well, I wasn’t going to pull reliever data for 2332 team seasons, but I DID pull it for the last three years (90 team seasons). Bullpen FIP had an 11.5% R2 with one-run game winning percentage, even stronger than the previous year’s Pythagorean winning percentage. It appears bullpen FIP, though not terribly predictive, is at least somewhat of a signal of one-run game capability. Unfortunately for the Orioles, their bullpen was merely average with a 3.68 FIP, so it doesn’t appear they have an edge there, either.
Tuesday, February 12, 2013
“Last year, we scored more runs than in the previous year. It’s not all how many runs you score. In 2011, we were very good and efficient at winning close ballgames. Last year, we weren’t. If you look at statistics, high-leverage situations we were not good. Late and close we were not good. Yet we improved ourselves with runners in scoring position. 2007 was the same way, we had a negative run differential (and still won 90 games). That’s what we’re looking for. We’re looking for the net effect.”
*Gibson on last season: “I can say that 81-81 does not sound good to me at all. I took it very personally. I take responsibility for it. You analyze why does that happen. Again, you analyze numbers and reality and in 2011 we overachieved. In 2012 we underachieved. We want to overachieve again regardless (of what people predict).”
Well, at least we know what the plan is now.
Posted: February 12, 2013 at 12:48 AM | 21 comment(s)
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