As the man who inspired Brad Pitt’s unforgettable role once said, “My shit doesn’t work in the playoffs.” Assuming Billy Beane wasn’t explaining his October Metamucil purchase to a grocery store manager who just happened to ask how his day was going, Beane might have meant that the statistics used to construct his major league rosters don’t collect large enough samples for late-season series. in order to finally make his grace work. Over the course of 162 games, the team’s production becomes a reasonable representation of the team’s true talent. But zoom in on any random seven-game stretch and the team on the field might look like a bunch of dudes in baseball player cosplay.
What applies to team results also applies to player results. A player with a respectable stat line in the regular season may turn into a pumpkin as the calendar turns to fall, or on the flip side, an unexpected hero may emerge from the ashes of a brutal summer and put the entire team on his back. .
Thinking about the law of averages, I always thought that consistent hitters would be in a better position to do well in the playoffs. My reasoning went like this: The inherent variance in these hitters’ performances wouldn’t stray too far from their season average, making them safer, more predictable options. Whereas streaky hitters — those with high peaks, low drops, and a steep transition between the two — can rely too much on “hitting at the right time” to be the type of hitters a front office should lean on during the offseason.
Student, I was wrong.
As it turns out, the postseason loves its hitters as much as it loves its microwave burritos: piping hot one bite, ice cold the next. That doesn’t mean the postseason turns its nose up at other microwave offerings, but instead of sticking to foods like mac and cheese that are brought to the same heat with the simple act of stirring, October baseball insists on indulging the taste buds in pizza rolls. and Hot Pockets or any other dough-and-cheese combination found in the frozen food aisle. You know, the kind of food where each bite spits out lava straight from the depths of Hell or the damned flavor-making thing from the Dippin’ Dots test kitchen.
In order to find the microwaveable entree most likely to satiate the monster that is postseason baseball, I had to first group the batters by category. To differentiate between consistent hitters (which I may refer to later using burrito nomenclature) and consistent hitters (which is the group I refer to whenever you see a reference to mac and cheese, or MAC for short), I borrowed. a specific method from Justin Choi, where he compared the amount of variation in all the weekly segments of offensive output. The most variable are the streakiest, and the least variable are the most consistent.
Although I kept that general outline, I made a few tweaks. Instead of using calendar weeks, which give inaccurate results that may not fully represent the extent of a hot streak or a cold spell, I used a rolling, seven-day average (at least 20 plate appearances), and then I sorted the samples better and alternated by picking from the top and bottom of the pile to get the weeks the best and worst of each player. If the selected seven-day sample had more than four days of overlap with any previously selected samples, it was excluded.
And because I was doing the weekly averages myself, I used wOBA instead of wRC+ to simplify the process even though it meant sacrificing park factor correction. (Don’t worry though, the top of Team Burrito’s leaderboard isn’t filled with Rockies swinging between homestands and road trips.)
Weekly variation was measured using the standard deviation. Scorers with values in the top 25% of the standard deviation went into the dashed category and scorers in the bottom 25% came under the constant label. From here, I took hitters from both teams and compared each individual’s regular season wOBA to their postseason wOBA (including only players with a PA of at least 20 in the postseason), then averaged the difference across the team. To get to the players that teams rely on the most in the postseason, I filtered the data for a set of hitters with a .330 wOBA or higher. Because if a team’s plan to win a World Series depends on a player with a .290 wOBA getting hot, it probably has other programmatic issues to address before worrying about the short-term distribution of offensive production. Like maybe work on getting some annoying productivity time.
Finally before we get to the results, I’ve gathered two ways of producing each player when comparing regular season performance to playoff performance. One version compares each player’s regular season wOBA to postseason wOBA within a one season before rating the entire team, while the other compares that of each player work numbers (although I only extracted data from the last 10 years, so the full careers of other players did not make up the data set). In the single-season version, players are classified as Burritos or MACs based on that individual season, while the career version makes that determination based on a player’s entire career.
If you use one season of data, both Burritos and MACs are equally likely to post the same numbers as they did in the regular season. A player with a .350 wOBA through September has the same chance of swinging his way to a .350 wOBA in October whether that .350 wOBA came together while nursing a mountain and valley season or diving across the field in the hills. This tells me one of two things, either one season is not enough to determine a hitter’s archetype, or the archetype has no effect on a player’s ability to perform at his level in the playoffs.
This is where grouping by job numbers comes in. As I looked at the data points for one season, I noticed a few players who showed up multiple times in both categories, depending on the season. Ronald Acuña Jr. classified as streaky in 2018 and ’19, but consistent in ’22 and ’23. In all four seasons he flies too close to the border to get any label. In 2021, he does not fall into the camp. Similarly, Kyle Schwarber hangs out at the other end of the spectrum in 2017 and ’18, before taking up permanent residence on that side of things from ’19 onward. If you look at Schwarber’s seven-game wOBA over his entire career (see below), the numbers are tightly clustered in the middle in ’17 and ’18, but have spread out significantly since ’19. This suggests that players change over time and that one season of consistency or consistency does not define everyone’s personality at the plate.
When comparing players’ regular season and playoff wOBA at a career level, MAC batters lose nearly 47 points of wOBA when faced with bright lights, cool temperatures, and strong postseason pitching. During that time, Team Burrito batters, on average, dropped just 25 wOBA points. But as we know, averages can speed up many extremes, and given the nature of these two groups, one can expect a difference in volatility. However, both averages have standard deviations around 0.07, which means that the actual results are highly-but-equally variable for both groups of hitters.
The MAC’s most surprising hitter in the playoffs is Nick Markakis, who leads the leaderboard in consensus, while holding a career regular season wOBA of .340 and a postseason wOBA of .235. Markakis shows that even reliable hitters are liable to underperform in the playoffs. It’s the same for its sequel counterparts, but the Burrito team is weighing that risk with greater upside.
Perhaps the king of the Burrito team is Hanley Ramirez, who posted a career regular season wOBA of .364 and a postseason wOBA of .434. Behind him on the leaderboard is Bryce Harper, who has a regular season wOBA of .385 and a postseason mark of .415. Harper, alongside his burrito buddy Schwarber (regular season wOBA .355, postseason wOBA .389), helped the Phillies make deep playoff runs from the wild card spot the past two seasons.
With this season’s playoffs fast approaching, which players are currently atop the frozen food leaderboards?
Both leaderboards boast players on contending teams, but given what we know now about the potential rise of many burrito-esque players, let’s take a look at a list of postseason hopefuls who draw heavily on this archetype. A few competitors have two burritos on the menu:
Atlanta Braves: Marcell Ozuna, Austin Riley
Baltimore Orioles: Colton Cowser, Anthony Santander
Boston Red Sox: Tyler O’Neill, Jarren Duran
Cleveland guards: José Ramírez, Josh Naylor
Kansas City Royals: Vinnie Pasquantino, Bobby Witt Jr.
Minnesota Twins: Byron Buxton, Jose Miranda
New York Mets: JD Martinez, Jesse Winker
New York Yankees: Aaron Judge, Juan Soto
Philadelphia Phillies: Bryce Harper, Kyle Schwarber
And there were two teams tied for the lead with three burritos on their roster, going one step further to tip the odds in their favor in October.
Arizona Diamondbacks: Joc Pederson, Ketel Marte, Christian Walker
Los Angeles Dodgers: Shohei Ohtani, Mookie Betts, Teoscar Hernández
Admittedly, Walker is injured, so the added benefit of an extra burrito may diminish depending on how he looks when he returns. And I want to be careful not to overemphasize the real impact of any profit that might be at play here. Not all burritos are of equal quality, and because we’re talking about a 20-point wOBA average applied to a small number of postseason plate appearances, there’s only so much that can be achieved in such a short period of time. All in all, it’s still better to be good than to hope for luck during a hitter’s hot streak. This is the kind of analysis that is very interesting to see, unlike anything that should be included in decision making. That said, the more opportunities teams give themselves to catch lightning in a bottle, the more likely they are to catch it.
Which raises bigger questions about the structure of the system and the hitter’s order. In an upcoming piece, we’ll do a little simulation in an attempt to determine the right ratio of burritos to mac and cheese, and what order you should eat them in. Until then, stay hungry.
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