If you’ve ever looked at a box score for a basketball game, one interesting statistic that is recorded is the plus / minus. Plus / minus denotes a team’s net points while the player is on the court.
As an example, if a player enters the game with the scored tied, and leaves with his or her team leading by 5, the player would have a plus / minus of +5. If that player re-entered the game when his or her team was up by 10 and subbed out with the team down by 2, his or her net plus / minus would be -7 (+5 + (-12) ). One small caveat is that minor adjustments are made so players don’t “receive” or “lose” points from being subbed in or out part way through free throw attempts.
Below you can see examples of the plus / minus from Game 1 of the Eastern Conference semifinals between the Philadelphia 76ers and the Boston Celtics, which the 76ers won 119 – 115.
The plus / minus data is pretty interesting, especially when combined with data about how many minutes each player played. For Philadelphia, in the 42 minutes (out of 48 total for the game) that Tobias Harris played, the 76ers had a net even margin with the Boston Celtics. On the other hand, in the 36 minutes that Tyrese Maxey played, the 76ers outscored the Celtics by 12 points. Lastly, in the 25 minutes De’Anthony Melton played, the 76ers were outscored by 8 points.
Clearly there were some minutes in which Harris was out of the game and Maxey was playing where the 76ers did very well and a good chunk of minutes where the 76ers played quite poorly when Melton was in, when Harris and Maxey were in the game.
The Celtics’ boxscore is arguably more interesting with Malcolm Brogdon logging a +14 in his 34 minutes and Al Hereford logging -17 in his 30 minutes. In a game the Celtics lost by only 4 points, that’s a large differential.
In order to better visualize how this discrepancies exist, I put together a visualization of plus / minus data for the entire game using play-by-play and score data from ESPN and then Python and the matplotlib library for analysis.
With the visualization, you can better see how all the plus / minus extremes for each team played out. For example, Maxey picked up points relative to Harris from subbing out a bit earlier in the 1st quarter and playing in the late second quarter. Comparing across teams also allows you to guess some of the matchups at play, with Maxey appearing to take advantage of the time Brogdon sat around halftime.
Here’s Game 4 of the Warriors – Lakers as a comparison:
If you’re interested in visualizing other games or seeing the code to generate the graphics, let me know!