No matter how complete an article feels at the time of publication, there are always a handful of interesting details that slip through the cracks or don’t fit under the word limit. On top of that, I tend to receive a ton of feedback post-publication, some of which is even worth addressing.
Twitter isn’t the ideal medium to respond or provide those additional details. So I wanted to experiment with a kind of weekly, link roundup-style blog post, summarizing the articles I’ve done in the past week and highlighting a few pieces from other authors that are worth reading as well. As mentioned, this will be a trial run for now; your comments and criticisms are welcome.
At FiveThirtyEight, I wrote a followup to last week’s piece on optimal bullpen management with Rian Watt. We extended our metric, which measured the extent to which managers used their best relievers in the highest-leverage spots, to grade individual skippers. Better still, we established a run value for the skill, allowing us to say how many additional wins optimal bullpen management was worth.
The metric itself, which we called weighted Reliever Management+ (wRM+) is best thought of as a retrospective yardstick of a manager’s decisions. It is limited in that it does not factor in fatigue (both day-to-day and cumulative effects), matchups, or how bullpens can change over the year. Much of the criticism toward the piece focused on the fact that we didn’t account for these issues.
All of that criticism is, of course, fair. But insofar as it’s incredibly difficult to judge bullpen management in any sort of rigorous, quantitative way, I think this piece was a significant step forward.
The optimal metric would probably appraise bullpen decisions in a dynamic way, that is to say, on an inning-by-inning basis according to what the manager knows at the time of the decision. (The distinction between retrospective and dynamic measurements was suggested to me by BP writer and all-around good guy Rob Mains.)
So, for example, rather than aggregating season-level statistics as we did, you could build a system to grade every individual call to the bullpen according to which relievers were available in that game, their statistics to date in the season, their projections, the matchup (who they’d be facing), and so on. In this way, you could say whether a manager made the optimal decision based on the information he had at the time, and price in the effects of fatigue and availability.
Such a system would be exceedingly difficult to create, however. You’d need game-by-game information, and you’d have to make a lot of assumptions about when relievers were tired and how much to consider matchups. With that said, I have full faith that eventually, someone is going to make this kind of dynamic scoring system. It’s going to be awesome, and probably more accurate and insightful than wRM+ (although by how much, I do not know). In the mean time, I think of Rian and I’s metric as a step in the right direction, an approximation that works better over longer managerial careers, where factors like bullpen quality tend to even out.
For The Athletic, I wrote about some of the ways October baseball is different from the regular season, and how those factors may affect the overwhelming postseason-favorite Cubs.
It’s striking how distinct playoff baseball is from the rest of the year. On top of the weather and better caliber of opponent, you have very different patterns of pitching usage. As managers get more sabermetrically savvy, I think that October is going to get even weirder and more tactically separated from the rest of the year. Ned Yost pioneered a new style of employing his relievers to more full effect in the postseason, and that increased usage will only grow more pronounced. The increase in pitching quality–both in terms of higher-caliber starting pitchers, and more bullpen action–is probably the single biggest factor which separates October from the rest of the year.
Long-term, I think that means there will be a premium on hitters who can maintain their performance against the highest-quality opposition. That is, if those hitters really exist; so far, sabermetrics hasn’t found much evidence for there being a kind of hitter who is less susceptible to the quality of the opposing pitcher. (Of course, that doesn’t mean that front offices can’t find those hitters better than public analysts.)
Looking at some of the team-level records being broken this year. More on the Cubs BABIP here: http://cybermetric.blogspot.com/2016/09/cubs-have-allowed-historically-low-babip.html
It’s probably the biggest deviation from the league average of all time (at least for BABIP). So what is it? Defense? A new kind of positioning or shifting? Pitchers who can suppress batted ball velocity?
You’ll never guess the luckiest team in baseball this year.
3% of American adults own half of the guns in the United States. Think about that for a minute. The article is worth a full read.
From R.J. Anderson, on how the Oakland front office has failed to navigate the modern age of sabermetric equality.
A distillation of the righteous anger many feel when thinking about a Drumpf voter. I think I’m more insulated from Drumpf voters than most people; only one person on my Facebook feed ever tweets pro-Drumpf propaganda. As a result, I’m more bewildered and confused than angry.