Is sabermetrics effective in the postseason?

Two words: sabermetrics and postseason. Putting them together I bet more than 95% of you instantly go back to Game 6 of the 2020 World Series when Tampa Bay Rays manager Kevin Cash, leading 1-0 in the sixth inning, walked to the mound with the decision made to pull his starter Blake Snell, a Cy Young Award winner, winning the game 1-0, with only two hits allowed in 5 and one-third innings.

Snell had allowed just his second hit, had 9 strikeouts and looked giant on the mound. It was time to pitch with a runner on first base, a common situation for a pitcher of his stature.

Cash took him out of the game before the eyes of the world. He brought in reliever Nick Anderson to face Mookie Betts, whom Snell had already struck out a couple of times. The result? Betts’ double, the Dodgers tied the game. Anderson throws a wild pitch, Betts advances, and Corey Seager connects on a sacrifice fly for Betts to score. That’s how quickly the Dodgers turn the score 2-1. The Rays could not come back and after the 27th out, the Dodgers are the World Series champions.

How on earth could this happen? How do you pull your best pitcher at the best time? Where has baseball gone? The answer is in the numbers and the probabilities. Analytics has determined that when a starter has already turned the opposing lineup over twice, there is a high probability that hitters will make the necessary adjustment to strike out in their respective third innings. Remember how Dave Roberts did the exact same thing in the 2017 World Series with Rich Hill against the Astros in games 2 and 6? In both cases, Hill had the game under control, but in the fifth inning, he was simply sent to the showers. Both games were lost by the Dodgers. In 2018 Roberts went through the same motions with Hill and with Korea’s Hyun-Jin Ryu.

However the treatment with Clayton Kershaw and Walker Buehler was different.Why? They have a proven record of depth and effectiveness against a third or fourth rounder in the opposing lineup.

How do we understand modern baseball? How do we understand managerial decisions in the postseason?

The first thing we must be clear about in this baseball is that the manager does not make all the decisions. There is currently a so-called “Pitcher’s Plan” or “Game Plan” applied by all teams, where the group of analysts and researchers from the baseball operations and analytics department explore different scenarios in a hypothetical game based on the statistics they carry over, the tendencies of the hitters and pitchers, and their situational performances. This group attempts to put their hypotheses and possible outcomes on paper and it is the manager’s responsibility to follow through with this plan. Gone are the days when the manager’s intuition and his knowledge of the game and of each player, his own and the opposing players, was the basis for making decisions in the game. They would place their best pieces and then sit back and wait for luck to have its way based on who could dominate whom turn by turn.

It is true, it was a time when the game situation and the mood and condition of the pitcher and batter made the difference. Today we add to this human factor the analytical plan.

But Major League Baseball is a field in which historically teams and their players try by any means to find leverage points in order to dominate on the field. From spit, glues, props, sign stealing, stimulants, energizers, steroids and even superstitions like not stepping on the line, or wearing dirty underwear, or putting on any amulet, everything is tried to find an edge.

That is sabermetrics, the advanced analysis of statistics to visualize a possible outcome on the field. It is up to the manager and each player to use this information, process it and somehow try to adapt it to their performance on the field. Today all 30 Major League organizations use these resources to minimize chance and luck in a game, a factor that will always be present, but since the amount of investment of each team is exorbitant, the best corporate strategy is to minimize risk based on a science. It’s a way to justify decisions in a $10+ billion dollar industry.

You wouldn’t put your investment in the hands of chance and luck, would you? Neither would they.