Predicting who will win baseball games is a hard task. Baseball is notorious for its high degree of luck, regression to the mean, and the inability for anyone to judge a player’s “true” talent based off of only a few games.
For examples of the small sample size issue, here’s some extra content from Fangraphs, BP, and myself. First, The Meaning of Small Sample Data, by Dave Cameron. Next, here is
Predicting MLB Records from a “Small” Sample Size written by yours truly. Finally here is Baseball Therapy: It’s a Small Sample Size After All by Russell Carleton of Baseball Prospectus.
Now, on August 21, 2019, the Houston Astros played the Detroit Tigers, in Houston. Here's the historic gamecast link.
With the so-called “hard” trade deadline approaching fast for MLB Teams, (now in a matter of hours!), we decided to once again fire up our servers and use our Bayesian model to predict each team’s end of season record, and consequently their shot of making the playoffs.
This season eliminated August waiver trades, a past opportunity to grab a player once a team’s stance has been made clearer. The most famous waiver trade perhaps was Justin Verlander moving from Detroit to Houston for the Astros’ historic World Series run in 2017. July 31 now represents a true, hard trade deadline for the first time in Major League Baseball history. If teams miss the opportunity to add to their clubs via trade by that date, there is no backup plan.
Now that most of the NBA teams have passed the halfway point of the season, we recalculated our end-of-season win total predictions and playoff probabilities. In truth, we don’t think that the second half of the season matters that much, in terms of playoff probability.
Since the top eight teams from each conference make the playoffs, the likelihood that even the top four teams in wins per conference at mid-season would fall out of the top eight at the end of the regular season is astronomically small. However, the second half does matter in terms of the teams fighting for the last couple of spots, as well as, of course, playoff seeding.
Last fall, we generated win probabilities for all 33 games of the MLB postseason, including the 2 wild-card games, 26 divisional and championship round games, and the 5 World Series games. We think it is finally time to declare how we did.
For each game, we compared win probabilities from 6 sources, two “baselines” (50/50 odds for each game, and the home team winning each game), two for-profit industries (Vegas betting lines and FiveThirtyEight’s Elo), and our two win probability metrics, Runs Scored/Runs Allowed wp%, created in 2017, and our Bayesian SaberSmart Simulator, created in 2018.
Fall brings joy to a lot of people, what with the break from the heat of summer, the annual arrival of Pumpkin Spiced Lattes and shoes, apple picking, and of course, the Fall Classic. This year, the World Series features the regular season juggernaut Boston Red Sox, and the perennial playoff participant, but never the winner, Los Angeles Dodgers.
The Red Sox have only lost two games this postseason, cruising past the Yankees in the ALDS and crushing the Astros and their co-co-co aces in the ALCS. Meanwhile, the Dodgers were on auto-pilot in the NLDS where they destroyed the Braves, before winning an epic battle over Milwaukee in seven games in the NLCS. The Dodgers were one win from winning the World Series last year, while the Red Sox last won the championship half a decade ago in 2013.