Skip to content

Creating a live win probability model based off of 4th quarter data from the 15-16 and 16-17 seasons

Notifications You must be signed in to change notification settings

tannermckean23/nba-predictions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 

Repository files navigation

nba-predictions

Creating a live win probability model based off of 4th quarter data from the 15-16 and 16-17 seasons

All cleaning of the data, making of the model, and looking at predictions is located in 'the-model'

Visualizations were created looking at the Oklahoma City Thunder vs Sacramento Kings game from December 6th, 2015.

In 'late-game' two different situations are examined.

First we look at situations where a team is down 1 with between 28 and 30 seconds left, and the opposing team has just gained possession of the ball. We analyze whether that team should foul or not. The data leads us to conclude that we should not foul.

Next we consider when we can rest players in the fourth quarter while having a small effect as possible on the outcome of the game. First we look at the beginning of the fourth. The data shows that if the team has a 15 point lead/deficit or more, then key players do not need to start the fourth quarter and likely do not need to go back into the game. Then we look at the 4-5 minute mark. If a team has about a 12 point lead/deficit, then their key players can be taken out of the game and the result of the game should be affected as little as possible.

About

Creating a live win probability model based off of 4th quarter data from the 15-16 and 16-17 seasons

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published