It was a good first quarter for the Rockies, Yankees, Nationals, and Diamondbacks.
In this space yesterday, I examined the four struggling teams that have seen their BP Playoff Odds drop the most through one-quarter of the season. Let’s flip things around now and look at the four teams that have seen their odds rise the most since Opening Day.
The first quarter of the season has not been kind to the Giants, Mets, Pirates, and Mariners.
To slightly tweak a well-worn saying, you can't win a playoff spot in the first quarter of the season, but you can lose it.
The following four teams have seen their BP Playoff Odds decline the most since Opening Day, through slow starts, crowded disabled lists, and various other calamities. Let's take a closer look at how each team fell so far so fast, as well as how they might climb out of the early hole with three-quarters of the season left to play.
The more things change, the more they stay the same, except for when they change.
We’re basically a quarter of the way through the season. About 60 percent of the league will have played at least 40 games by the time you read this. This early landmark of the season has a funny way of sneaking up on us, because of the disruptions in the early-season schedule—extra off days, rainouts, and so on—and because of the distractions that keep baseball off the front page of the sports section until summer: the NFL Draft, the NBA and NHL playoffs, etc. We spend so much time (rightfully, by the way) reminding ourselves that it’s early that we eventually risk doing so even when it’s no longer so.
I’m not sure we’re there yet. I’m not sure it’s not still early. Rather than revisit this in two weeks and find I missed the crossing of the Rubicon, though, I figure it’s worth taking stock of what’s changed so far. To do so, let’s examine the 10 teams whose Playoff Odds have moved 12 percentage points or more since the season began. This is an imperfect way of deciding how much has changed, of course. It embraces both PECOTA’s initial estimation of each team’s true talent level, and the system’s rate of change—the way it incorporates new information without giving up the value added by maintaining a long memory and healthy skepticism about relatively small samples. Still, it’s something, so let’s test out the relationship between our intuitions and PECOTA’s projections.
Painting a table of how the season's expectations have changed.
Our lives are ruled by probabilities. All things are possible, and the varying degrees of possibility of various things govern everything from our decisions to our dispositions. Often, we’re too preoccupied by our preoccupations to look forward very far, but the truth is that few events in our lives sneak up on us. Conscious or subconscious, perceptions of the likelihood of important events inform our mood, our priorities and our choices.
Sports fandom is a unique sliver of life, though, in which those probabilities aren’t floating whispers in the background. We’re constantly reevaluating them, recalculating and recalibrating them. Even in baseball, the sport of the long season, we look for significance in every win and every loss. We try to gauge the impact of everything we see, not only in the context of the game or the series at hand, but in the big picture. That’s why spirited fans so often seem to agonize over every pitch: it affects our perception of our team’s chances in the long run, and that affects our sense of well-being about our entire investment in the team. The effect of those small things is minute, compared to what we perceive it to be, but baseball is bedeviling. It lures us into the sense of constant cataclysm that characterizes the NFL, even though the moments that really matter as much as the outcome of any given NFL game happen perhaps once a month.
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We likely already know who is going to make the playoffs. Is there still reason to watch?
This will be painful for some of you, but cast your mind back, if you can, to the baseball standings as they looked a year ago today. Behold: a wondrous world where the White Sox are in first place, the Giants are 16 games over .500, the Nationals are the best team in baseball, and the Orioles are a half-game up on the Rays for the second AL Wild Card spot (like that will last). The names of some of the teams at the top look strange, in light of what’s transpired this season, but I spy something even stranger: pennant races. Pennant races, as far as the eye can see.
On the morning of August 30, 2012, five of the six divisions had separations of five games or fewer between first and second place. Only in the NL Central, where the Reds had an eight-game lead over St. Louis and a nine-game cushion over the collapsing Pirates, was the division title all but awarded. According to our Playoff Odds Report for that day, there were four teams with playoff percentages of over 95 percent: the Reds, the Nats, the Rangers, and the Yankees. But there were a few tiers of lesser, but still strong contenders below that: the Braves and White Sox (oops) over 80 percent; the Cardinals, at just over 60 percent; the Tigers, Rays, and A’s between 50 and 60; the Angels, Pirates, and Dodgers clustered right around 30. And the odds weren’t buying the run differential-defying Orioles, whom PECOTA gave a 20 percent chance to claim the Wild Card they eventually won. In other words, there was an awful lot still at stake.
Have we been underrating big-market, high-payroll teams?
A couple of weeks ago, I wrote about the distribution of team wins, and the discovery that the distribution may in fact be bimodal, not normal as one might expect.
One of the predictions that came from this theory was that teams right at .500 would, counterintuitively, tend to regress away from the mean. So one thing we can do is actually check to see if the real world behaves the way we expect it to. I took all teams from 1969 on with even numbers of games and split them into “halves” of even-number games. I use scare-quotes for halves since in order to boost the sample size, I split into increments of two and kept any pair where both “halves” were within 20 games of each other. Then I looked at teams that were exactly .500 in the “before” sample— 716 teams total—and saw what they did afterward:
Before we get underway, some notes. PECOTA does not hate your favorite team. PECOTA is a collection of algorithms, written in computer code and run by an unfeeling machine. It cannot hate, or love. It can do only what it is told to do, nothing more or less.