A few years ago, I added postseason series win probability graphs and data. Most people are familiar with win probability graphs, which show each team’s win expectancy based on the inning, score, outs, & bases occupied. For series win probability, I took it one step further and put it in the context of a postseason series.
I feel that these new graphs are a big step forward in following the play by play of each postseason series and I hope you feel the same.
Individual Player’s Series Win Probability Added (sWPA)
When I originally added the postseason data, I included a page for the top plays in postseason history. This shows which plays had the biggest difference in sWPA from before and after the play. In the new update, each player is credited/debited sWPA based on their involvement in the play. I decided to use the same method for allocating WPA that is used at Baseball-Reference.
sWPA vs wsWPA
wsWPA is World Series Win Probability Added. This is not just the win probability of winning the series, but winning the World Series. This is calculated as sWPA divided by (# of series before the World Series * 2). Obviously, the sWPA in the World Series would be equal to the wsWPA.
Example: Francisco Cabrera’s walk-off 2-run single in the 1992 NLCS increased the Braves chances of winning the series by 74% (26% -> 100%). Since the NLCS is one series away from the World Series, this is how we calculate wsWPA:
74% / (1 * 2) = 37%
This tells us that Cabrera increased his team’s chances of winning the World Series by 37%.
A 20% sWPA play in the Wild Card game would be divided by six since it is three series away from the World Series:
(20% / (3 * 2)) = 3.33%
wsWPA is a good way to compare the importance of plays from different types of series
I have included regular season tiebreakers in the postseason data. While they are not technically postseason games, they are pivotal in World Series win probability.